{"uuid": "04db93f9-fdb3-4b6a-b7ff-1ef6316af86c", "vulnerability_lookup_origin": "1a89b78e-f703-45f3-bb86-59eb712668bd", "author": "9f56dd64-161d-43a6-b9c3-555944290a09", "vulnerability": "CVE-2024-50623", "type": "seen", "source": "https://gist.github.com/marcuswhitney/388d616a47ad991666491b5f5b488b02", "content": "\n\n\n  Reader Import 4/5\n  https://read.readwise.io/\n  One-time migration of saved items from Readwise Reader.\n  \n    Announcing Protocol\n    https://blog.ethereum.org/2025/06/02/announcing-protocol\n    readwise:01jws6ydqm9g1wdx8qwksqed1p\n    Mon, 02 Jun 2025 20:57:18 +0000\n    Ethereum Foundation Blog\n    \n\nEthereum stands at the edge of major breakthroughs. zkEVMs have rapidly accelerated, enabling us to rearchitect L1 to simultaneously support scale, verifiability, security and censorship-resistance. L2s are hardening, meeting users where they are, and eager to double down on using Ethereum as their root of trust. In short, the world is ready for the world computer.\n\nThese significant innovations both unlock massive benefits for our users and will allow us to onboard many, many more. The stakes are high: This moment may be Ethereum\u2019s best shot at deploying not only our technology, but our values, at planetary scale.\n\nAs a response, we must rethink our current approach to designing, developing and stewarding the protocol. This process of \u201cshipping protocol\u201d is messy, asking us to respond proactively to demands that are hard to articulate and even harder to fulfill. It is our responsibility to use our skills to benefit the broader community.\n\nExecuting on this mandate will require a new level of focus and collaboration for our group, the Protocol Research & Development teams within the EF. This means doubling down on areas where the EF has unique domain knowledge and deep expertise unmatched in our ecosystem: from writing mission-critical code, to publishing breakthrough research and coordinating large initiatives.\n\nTo support this vision, we are making changes to the way that we operate, re-orienting towards our three strategic goals: scaling the L1, scaling the blobs, and improving UX. Practically, this means restructuring our teams and creating explicit coordination structures around these strategic goals.\n\nThis also means some members of PR&D won\u2019t be continuing with the Ethereum Foundation. We hope these individuals continue on in the Ethereum ecosystem and encourage others building out their teams to seek them out.\n\nThe changes we\u2019re announcing today are a departure from our previous ways of working, but we feel these set us on a more responsive and effective path. To mark the beginning of this new chapter and structure, we\u2019d like to reintroduce \u201cProtocol R&D\u201d to the world under a new name: Protocol.\n\nStrategic initiatives\n\nOver the last year, many of us concluded that we needed to do a better job articulating our priorities. In conversation with our community, our collective mind has produced three ambitious goals for us to achieve in short order: scale L1, scale blobs, improve UX. Doing so successfully is the most valuable work we could be doing on behalf of our community, and it is our responsibility to deliver on it.\n\nIt is time for us to ensure that these goals directly drive our attention and resource allocation. Each of these goals is now mapped to a strategic initiative for Protocol, a shared workspace to bring our complementary talents together. We encourage every team in Protocol to consider how their work is supporting our execution of these strategic initiatives.\n\nCritical to our execution is the presence of leaders in our group whom the community trusts. We are being more explicit in assigning leaders to accelerate our strategic initiatives in order to increase accountability.\n\nSpecifically, the following people are responsible for ensuring the EF executes on each of its strategic goals:\n\n\nScale L1: Tim Beiko & Ansgar Dietrichs\nScale L2: Alex Stokes & Francesco D\u2019Amato\nImprove UX: Barnab\u00e9 Monnot & Josh Rudolf\n\nThey will be supported by Dankrad Feist, who will act as a strategic advisor to all tracks, as well as the leads for the projects defined to move these goals forward.\n\nYou can find more details on our three strategic initiatives here.\n\nTeams\n\nMore than ever, we are required to solve problems bringing the abilities of all Protocol members at once. Rapidly transitioning research into prototypes and to production means that we need tighter collaboration and feedback loops. We have seen many more bridges form across our teams over the past years, bringing tangible results. With a shared vision, we must ensure that our shared home is incredible to work in.\n\nBeing open in our collaboration with every member of Protocol requires shared expectations and high trust that each of us is delivering at their highest level. Team leads will be responsible for ensuring that their members meet our bar for technical excellence and enjoy continuous growth, pushing themselves ever further.\n\nProtocol is now a more united and leaner organization with more focused teams. You can find our updated org chart here.\n\nOur community\n\nProtocol cannot accomplish everything on its own. Our ecosystem is made stronger from the work of many other core research and development teams, who amplify our own efforts and bring features to reality. Our role is not to replace these teams, but to set a high standard for ourselves in our work with them.\n\nProtocol is driving efforts towards reconfiguring our main governance forums and introducing new ones. It is critical to continue eliciting the right signals and translating them into action.\n\nWe are looking for new members to join us in this effort, and become a part of the larger Ethereum core development community. Two roles we believe are critical to help us solve real problems for Ethereum users are a UX Lead and Performance Engineering Lead. In addition to these, we welcome exceptional applicants who are excited about our mission to let us know in our General Application.\n\nSo let\u2019s do it together. Let\u2019s ship Protocol.]]>\n    \n\nEthereum stands at the edge of major breakthroughs. zkEVMs have rapidly accelerated, enabling us to rearchitect L1 to simultaneously support scale, verifiability, security and censorship-resistance. L2s are hardening, meeting users where they are, and eager to double down on using Ethereum as their root of trust. In short, the world is ready for the world computer.\n\nThese significant innovations both unlock massive benefits for our users and will allow us to onboard many, many more. The stakes are high: This moment may be Ethereum\u2019s best shot at deploying not only our technology, but our values, at planetary scale.\n\nAs a response, we must rethink our current approach to designing, developing and stewarding the protocol. This process of \u201cshipping protocol\u201d is messy, asking us to respond proactively to demands that are hard to articulate and even harder to fulfill. It is our responsibility to use our skills to benefit the broader community.\n\nExecuting on this mandate will require a new level of focus and collaboration for our group, the Protocol Research & Development teams within the EF. This means doubling down on areas where the EF has unique domain knowledge and deep expertise unmatched in our ecosystem: from writing mission-critical code, to publishing breakthrough research and coordinating large initiatives.\n\nTo support this vision, we are making changes to the way that we operate, re-orienting towards our three strategic goals: scaling the L1, scaling the blobs, and improving UX. Practically, this means restructuring our teams and creating explicit coordination structures around these strategic goals.\n\nThis also means some members of PR&D won\u2019t be continuing with the Ethereum Foundation. We hope these individuals continue on in the Ethereum ecosystem and encourage others building out their teams to seek them out.\n\nThe changes we\u2019re announcing today are a departure from our previous ways of working, but we feel these set us on a more responsive and effective path. To mark the beginning of this new chapter and structure, we\u2019d like to reintroduce \u201cProtocol R&D\u201d to the world under a new name: Protocol.\n\nStrategic initiatives\n\nOver the last year, many of us concluded that we needed to do a better job articulating our priorities. In conversation with our community, our collective mind has produced three ambitious goals for us to achieve in short order: scale L1, scale blobs, improve UX. Doing so successfully is the most valuable work we could be doing on behalf of our community, and it is our responsibility to deliver on it.\n\nIt is time for us to ensure that these goals directly drive our attention and resource allocation. Each of these goals is now mapped to a strategic initiative for Protocol, a shared workspace to bring our complementary talents together. We encourage every team in Protocol to consider how their work is supporting our execution of these strategic initiatives.\n\nCritical to our execution is the presence of leaders in our group whom the community trusts. We are being more explicit in assigning leaders to accelerate our strategic initiatives in order to increase accountability.\n\nSpecifically, the following people are responsible for ensuring the EF executes on each of its strategic goals:\n\n\nScale L1: Tim Beiko & Ansgar Dietrichs\nScale L2: Alex Stokes & Francesco D\u2019Amato\nImprove UX: Barnab\u00e9 Monnot & Josh Rudolf\n\nThey will be supported by Dankrad Feist, who will act as a strategic advisor to all tracks, as well as the leads for the projects defined to move these goals forward.\n\nYou can find more details on our three strategic initiatives here.\n\nTeams\n\nMore than ever, we are required to solve problems bringing the abilities of all Protocol members at once. Rapidly transitioning research into prototypes and to production means that we need tighter collaboration and feedback loops. We have seen many more bridges form across our teams over the past years, bringing tangible results. With a shared vision, we must ensure that our shared home is incredible to work in.\n\nBeing open in our collaboration with every member of Protocol requires shared expectations and high trust that each of us is delivering at their highest level. Team leads will be responsible for ensuring that their members meet our bar for technical excellence and enjoy continuous growth, pushing themselves ever further.\n\nProtocol is now a more united and leaner organization with more focused teams. You can find our updated org chart here.\n\nOur community\n\nProtocol cannot accomplish everything on its own. Our ecosystem is made stronger from the work of many other core research and development teams, who amplify our own efforts and bring features to reality. Our role is not to replace these teams, but to set a high standard for ourselves in our work with them.\n\nProtocol is driving efforts towards reconfiguring our main governance forums and introducing new ones. It is critical to continue eliciting the right signals and translating them into action.\n\nWe are looking for new members to join us in this effort, and become a part of the larger Ethereum core development community. Two roles we believe are critical to help us solve real problems for Ethereum users are a UX Lead and Performance Engineering Lead. In addition to these, we welcome exceptional applicants who are excited about our mission to let us know in our General Application.\n\nSo let\u2019s do it together. Let\u2019s ship Protocol.]]>\n  \n  \n    Satya Nadella, CEO of Microsoft, just made a bold prediction: "The application layer is collapsing into agents." Translation? Your apps are obsolete. \ud83e\uddf5\n    https://www.reddit.com/r/Hedera/comments/1kvxe02/satya_nadella_ceo_of_microsoft_just_made_a_bold/?share_id=5ZDVPY8HBlh5EBIsmuoBA&utm_content=2&utm_medium=ios_app&utm_name=iossmf&utm_source=share&utm_term=22\n    readwise:01jwkfw9qatspra0nm3g8e2f04\n    Sat, 31 May 2025 15:37:59 +0000\n    reddit.com\n     r/Hedera \n\n Cold_Custodian \n\n\n\nTop 1% Poster    \n\n    Discussion    \n\nFirst, let's decode what Nadella actually means:\n\nTraditional apps = databases + business logic\n\nBut now? The logic is moving to AI agents.\n\nInstead of opening 4 different apps to complete a task, you'll delegate everything to agents that pull data from everywhere.\n\nThe \"AI Tier\" is Microsoft's master plan:\n\nA new layer where AI agents live and orchestrate between all your tools.\n\nYour CRM, email, calendar, design tools - they all become data sources.\n\nThe agent becomes your universal interface.\n\nAnd Microsoft 365 is already transforming:\n\n\"Microsoft 365 is becoming an IDE with chat\"\n\nTranslation: Your Office suite is turning into a coding environment where you program with natural language instead of clicks.\n\nCopilot Studio lets you build custom agents without code.\n\nWhat does this mean for SaaS companies?\n\nThey're no longer selling complete solutions.\n\nThey're becoming \"curators of domain-specific data\" that agents access.\n\nYour favorite tools won't disappear - they'll become invisible infrastructure.\n\nThe user experience shift is massive\u2026\n\nBefore: Open Slack \u2192 check messages \u2192 open Notion \u2192 update project \u2192 open Calendar \u2192 schedule meeting\n\nAfter: \"Agent, update project status and schedule a team sync for tomorrow\"\n\nOne command. Multiple systems. Zero context switching.\n\nThe uncomfortable truth?\n\nWho controls the agents controls everything.\n\nSo Microsoft is extending their identity management and data protection to agents.\n\nIf you're building on their platform, they own the orchestration layer.\n\nAnd the economics are wild:\n\n\"The near-zero cost of intelligence will unlock significant productivity gains\"\n\nWhen AI agents cost pennies to run complex workflows, every business process gets reimagined.\n\nBut energy consumption still remains the hidden cost\u2026\n\nWhat does this mean for builders?\n\n \n \n Stop building standalone apps - build agent-compatible tools  \n \n Focus on data APIs, not user interfaces  \n \n Design for orchestration, not isolation  \n \n Think workflow automation, not feature sets   \n\nMicrosoft is betting this shift happens in the next 2-3 years.\n\nSaaS companies that don't adapt to the agent era risk becoming irrelevant.\n\nThe application layer as we know it is already collapsing.\n\nBut there's massive opportunity here:\n\nWhile big tech fights for the agent orchestration layer, builders can focus on:\n\n \n \n Specialized agent tools  \n \n Domain-specific training data  \n \n Agent workflow optimization  \n \n Privacy-preserving agent frameworks   \n\nThe key insight?\n\nThis isn't about better chatbots - it's about fundamentally rewiring how humans interact with technology.\n\nThe companies that understand this first will build the next generation of billion-dollar businesses.\n\n\"We're in the agent era\" - Satya Nadella\n\n\n\n\n\n\n\n\n\n\nanarchy.build\n@anarchy_build\n\n\n\n\n\n\n\n\n\n\n\n\n\nSatya Nadella, CEO of Microsoft, just made a bold prediction:\n\"The application layer is collapsing into agents.\"\nTranslation? Your apps are obsolete.\nIn a recent interview, he revealed the ONE shift that will redefine AI\u2019s future...\nHere's everything you need to know:\ud83e\uddf5\n\n\n\n\nPosted May 25, 2025 at 10:07AM\n\n\n\n\n\n\n\n\n\n\n\n\n\nanarchy.build\n@anarchy_build\n\n\n\n\n\n\n\n\n\n\n\n\n\nSatya Nadella, CEO of Microsoft, just made a bold prediction:\n\"The application layer is collapsing into agents.\"\nTranslation? Your apps are obsolete.\nIn a recent interview, he revealed the ONE shift that will redefine AI\u2019s future...\nHere's everything you need to know:\ud83e\uddf5\n\n\n\n\nPosted May 25, 2025 at 10:07AM\n\n\n\n\n   x.com    \n\n    116116        ]]>\n     r/Hedera \n\n Cold_Custodian \n\n\n\nTop 1% Poster    \n\n    Discussion    \n\nFirst, let's decode what Nadella actually means:\n\nTraditional apps = databases + business logic\n\nBut now? The logic is moving to AI agents.\n\nInstead of opening 4 different apps to complete a task, you'll delegate everything to agents that pull data from everywhere.\n\nThe \"AI Tier\" is Microsoft's master plan:\n\nA new layer where AI agents live and orchestrate between all your tools.\n\nYour CRM, email, calendar, design tools - they all become data sources.\n\nThe agent becomes your universal interface.\n\nAnd Microsoft 365 is already transforming:\n\n\"Microsoft 365 is becoming an IDE with chat\"\n\nTranslation: Your Office suite is turning into a coding environment where you program with natural language instead of clicks.\n\nCopilot Studio lets you build custom agents without code.\n\nWhat does this mean for SaaS companies?\n\nThey're no longer selling complete solutions.\n\nThey're becoming \"curators of domain-specific data\" that agents access.\n\nYour favorite tools won't disappear - they'll become invisible infrastructure.\n\nThe user experience shift is massive\u2026\n\nBefore: Open Slack \u2192 check messages \u2192 open Notion \u2192 update project \u2192 open Calendar \u2192 schedule meeting\n\nAfter: \"Agent, update project status and schedule a team sync for tomorrow\"\n\nOne command. Multiple systems. Zero context switching.\n\nThe uncomfortable truth?\n\nWho controls the agents controls everything.\n\nSo Microsoft is extending their identity management and data protection to agents.\n\nIf you're building on their platform, they own the orchestration layer.\n\nAnd the economics are wild:\n\n\"The near-zero cost of intelligence will unlock significant productivity gains\"\n\nWhen AI agents cost pennies to run complex workflows, every business process gets reimagined.\n\nBut energy consumption still remains the hidden cost\u2026\n\nWhat does this mean for builders?\n\n \n \n Stop building standalone apps - build agent-compatible tools  \n \n Focus on data APIs, not user interfaces  \n \n Design for orchestration, not isolation  \n \n Think workflow automation, not feature sets   \n\nMicrosoft is betting this shift happens in the next 2-3 years.\n\nSaaS companies that don't adapt to the agent era risk becoming irrelevant.\n\nThe application layer as we know it is already collapsing.\n\nBut there's massive opportunity here:\n\nWhile big tech fights for the agent orchestration layer, builders can focus on:\n\n \n \n Specialized agent tools  \n \n Domain-specific training data  \n \n Agent workflow optimization  \n \n Privacy-preserving agent frameworks   \n\nThe key insight?\n\nThis isn't about better chatbots - it's about fundamentally rewiring how humans interact with technology.\n\nThe companies that understand this first will build the next generation of billion-dollar businesses.\n\n\"We're in the agent era\" - Satya Nadella\n\n\n\n\n\n\n\n\n\n\nanarchy.build\n@anarchy_build\n\n\n\n\n\n\n\n\n\n\n\n\n\nSatya Nadella, CEO of Microsoft, just made a bold prediction:\n\"The application layer is collapsing into agents.\"\nTranslation? Your apps are obsolete.\nIn a recent interview, he revealed the ONE shift that will redefine AI\u2019s future...\nHere's everything you need to know:\ud83e\uddf5\n\n\n\n\nPosted May 25, 2025 at 10:07AM\n\n\n\n\n\n\n\n\n\n\n\n\n\nanarchy.build\n@anarchy_build\n\n\n\n\n\n\n\n\n\n\n\n\n\nSatya Nadella, CEO of Microsoft, just made a bold prediction:\n\"The application layer is collapsing into agents.\"\nTranslation? Your apps are obsolete.\nIn a recent interview, he revealed the ONE shift that will redefine AI\u2019s future...\nHere's everything you need to know:\ud83e\uddf5\n\n\n\n\nPosted May 25, 2025 at 10:07AM\n\n\n\n\n   x.com    \n\n    116116        ]]>\n  \n  \n    My workflow for going 0 to 1 on meaty app...\n    https://x.com/DanHightowerJr/status/1928515588231508218/?rw_tt_thread=True\n    readwise:01jwhapn44qq1fq40qf2jp5nd4\n    Fri, 30 May 2025 19:29:03 +0000\n    X (formerly Twitter)\n    \nMy workflow for going 0 to 1 on meaty app ideas:\n1. give @vercel's v0 the big idea. spare it the details of each feature\n2. iterate in v0 until you're happy enough with the foundation\n3. download the code and open it in @cursor_ai\n4. create a new https://t.co/MHwnV1b2BA file and drop in your full spec\n5. first prompt in Cursor agent: \"review the code and https://t.co/MHwnV1b2BA then write a new file called https://t.co/HJ3IIWv8Nz with all the detailed steps needed to complete the spec\"\n6. open a new agent chat per step. go step by step, iterating until you're done with that step. \n7. once you've got a good v0, toss your project into a new GitHub repo\n8. return to vercel to deploy it\n9. share your new app, get feedback, return to Cursor to update, Vercel auto-deploys them.]]>\n    \nMy workflow for going 0 to 1 on meaty app ideas:\n1. give @vercel's v0 the big idea. spare it the details of each feature\n2. iterate in v0 until you're happy enough with the foundation\n3. download the code and open it in @cursor_ai\n4. create a new https://t.co/MHwnV1b2BA file and drop in your full spec\n5. first prompt in Cursor agent: \"review the code and https://t.co/MHwnV1b2BA then write a new file called https://t.co/HJ3IIWv8Nz with all the detailed steps needed to complete the spec\"\n6. open a new agent chat per step. go step by step, iterating until you're done with that step. \n7. once you've got a good v0, toss your project into a new GitHub repo\n8. return to vercel to deploy it\n9. share your new app, get feedback, return to Cursor to update, Vercel auto-deploys them.]]>\n  \n  \n    All beginner writers face this problem:\n    https://x.com/dickiebush/status/1739678468168630333?s=12&t=ZflMTUWvt_7uY-E_46hJ6Q\n    readwise:01jv25hq5n4xnmdtaj0cc4psf1\n    Mon, 12 May 2025 11:54:40 +0000\n    X (formerly Twitter)\n    \nAll beginner writers face this problem:\n\"I'm not sure how to come up with ideas to write about.\"\nThe solution?\nThe Endless Idea Generator:\n\nThis is *by far* our most popular Ship 30 framework.\nEvery student comes in with that same feeling:\n\"What am I going to write about for 30 days?\"\n60 minutes later, they leave *overflowing* with ideas to write about.\n6 days left to hop aboard!\nShip30for30.com\n\nAnd if you're on the fence, wondering if Ship 30 is right for you, don't take our word for it.\nRead what our 10,000+ successful students had to say about their 30 days:\nship30for30.com/meet-our-alumni]]>\n    \nAll beginner writers face this problem:\n\"I'm not sure how to come up with ideas to write about.\"\nThe solution?\nThe Endless Idea Generator:\n\nThis is *by far* our most popular Ship 30 framework.\nEvery student comes in with that same feeling:\n\"What am I going to write about for 30 days?\"\n60 minutes later, they leave *overflowing* with ideas to write about.\n6 days left to hop aboard!\nShip30for30.com\n\nAnd if you're on the fence, wondering if Ship 30 is right for you, don't take our word for it.\nRead what our 10,000+ successful students had to say about their 30 days:\nship30for30.com/meet-our-alumni]]>\n  \n  \n    'Credit card companies with wings'\n    https://www.businessinsider.com/airlines-credit-cards-loyalty-miles-rewards-profits-delta-united-american-2025-5\n    readwise:01jv16wx43gg76yf3kzgt0h9vt\n    Mon, 12 May 2025 02:59:00 +0000\n    Business Insider\n    \n \n \n   Getty Images; Jenny Chang-Rodriguez/BI  \n\nWhile it's ubiquitous, air travel remains one of the wildest technical achievements in human history. Beyond the scientific feat that goes into achieving takeoff, airlines must coordinate tens of thousands of bags, employees, and travelers to make sure everyone gets to where they're going. Despite the sheer effort involved, moving people through the sky from point A to point B isn't what makes the bottom line soar in the airline business these days. Instead, the major players rake in billions of dollars thanks to a feat of financial engineering: loyalty and credit card spending.\n\nFirst developed in the 1980s, airline loyalty perks revolutionized the industry, creating a base of passionate customers eager to fly a specific carrier or use its credit card in exchange for things like free checked luggage, seat upgrades, early boarding, ever-popular airport lounge access, and \"free\" flights. A 2024 OAG analysis found that 82% of travelers worldwide were enrolled in at least one airline loyalty program. Delta SkyMiles is the world's largest, with over 120 million members. As of 2023, 31 million airline credit cards had been issued in the US, according to the trade association Airlines for America, and 57% of points were accumulated through cardholder spending.\n\nThe combination of people flying and swiping their credit cards has ballooned airline loyalty into a juggernaut and a primary source of airlines' income \u2014 so much so that carriers would struggle to profit without it. Federal airline filings show loyalty represents over $25 billion in yearly revenue. Among the Big Four in 2024, Southwest earned about $2.2 billion from its loyalty program, or about 8% of its total revenue, United $2.9 billion (5%), American $6.1 billion (11.3%), and Delta $7.4 billion (12%).\n\nAirlines enjoy myriad benefits beyond a loyal customer base, a strong brand, and free marketing whenever someone swipes their card around town. Frequent flyer programs increase a carrier's valuation and generate consistent revenue streams. Played correctly, these programs can also be good for customers looking to optimize their points for vacations. But there are some risks to loyalty from a customer perspective. Carriers can, and will, adjust the value of their points on a whim, boosting their bottom lines at the expense of customers.\n\nThe business has morphed airlines into miniature central banks, printing points as currency and often profiting more from selling them than from actually flying airplanes, or as TJ Dunn, a points guru and editor in chief at the Prince of Travel, told me: \"A lot of people call airlines credit card companies with wings.\"\n\nAmerican Airlines launched the first modern major airline loyalty program, AAdvantage, in 1981. United's MileagePlus and Delta Air Lines' SkyMiles programs followed that same year, while Southwest Airlines' Rapid Rewards program began in 1987. In the same decade, airlines decided to go beyond simply rewarding frequent flyers and began building what has become one of their biggest cash cows: co-branded credit cards. By partnering with banks, airlines can monetize these loyalty miles and points, creating a source of cash to supplement the basic flying business.\n\nAirline points are, in essence, an IOU created out of thin air. Carriers turn around and sell these points and miles to banks in exchange for US dollars to fund their operations, like buying planes and paying pilots. Banks then distribute those to holders of the co-branded cards when they make everyday purchases \u2014 including on nonflying items and activities. Customers then redeem those IOUs for airline services. Put another way, you're turning the money you spent on groceries, gas, clothes, and that $500 VR headset you barely use into jet fuel for your next flight.\n\nBanks like this agreement because it drives high spending and brand loyalty. Airlines love it because it generates repeat customers and a constant loop of revenue as people shop. The more a cardholder spends, the more points they earn, and the more a bank pays the airline. Consumers love it because it feels like they're getting free money when redeeming points. On paper, everyone wins.\n\nEven if everyone comes off happy, the setup is an especially good deal for the airlines. A March report from the travel company Point.me said each airline point is generally valued at about 1 cent, in terms of how much value customers receive when they redeem them, but banks buy them for anywhere from 1.5 to 2.5 cents before any bulk discounts. The margins for selling points range from 39% to 53%. Airlines regularly lure new cardholders with enticing sign-on bonuses and other built-in perks, like travel credits and free checked luggage. Southwest and United partner with JPMorgan Chase, American works with Citibank, and Delta partners with American Express. Each airline has different tiers, and the annual fees \u2014 from which airlines receive a kickback \u2014 can range from $0 to $695 a year.\n\nPlease help BI improve our Business, Tech, and Innovation coverage by sharing a bit about your role \u2014 it will help us tailor content that matters most to people like you.\n\nWhat is your job title?  (1 of 2) \n\n Entry level position\n\n Project manager\n\n Management\n\n Senior management\n\n Executive management\n\n Student\n\n Self-employed\n\n Retired\n\n Other\n\nWhat products or services can you approve for purchase in your role?  (2 of 2) \n\n Advertising / Marketing\n\n Client / Account Management\n\n Company strategy\n\n HR / Training / Office support\n\n Managing budgets\n\n IT / Telecoms / Tech\n\n Recruiting new employees\n\n Sales\n\n Software development\n\n Financial\n\n Other\n\n None of the above\n\nBy providing this information, you agree that Business Insider may use this data to improve your site experience and for targeted advertising. By continuing you agree that you accept the  Terms of Service  and  Privacy Policy  .\n\nThanks for sharing insights about your role.\n\nHaving an airline credit card tends to make you a stickier customer.\n\nThere are some ways savvy travelers can gain the upper hand. Customers can book reward itineraries via airline websites, paying only taxes and fees, often at steep discounts compared with the cash cost of the same flight. For example, a one-way United business class flight from Los Angeles to Sydney on June 4 costs 100,000 points (plus $33). The average redemption value of United points is 1.3 cents per point, meaning the points needed to book the flight equal roughly $1,300 \u2014 but the ticket paid for outside the loyalty program costs $4,988.\n\n\"I've gotten so many good redemptions,\" said Dunn, who largely flies business class using points instead of paying the multithousand-dollar cash price. \"One was a last-minute United Polaris from San Francisco to French Polynesia for 85,000 points. Another was American from Los Angeles to Sydney for 65,000 points.\"\n\nOffering cheaper or almost free flights, upgraded seats, or complimentary checked luggage seems like a self-own by the airlines \u2014 why give money away? But all the special offers are offset by several factors. One, the cost to airlines of letting you redeem points is often far lower than the money they earned up front from selling those points to the banks, especially during off-peak times. So you may feel like you're getting a deal, but the bank already covered your redemption for that \"free\" seat. Two, spending to earn enough points or status for a flight or upgrade means the airline has already secured thousands of dollars' worth of your business many times over, whether you booked a flight with them instead of a competitor (whose standard cost may have been lower) or used its credit card.\n\n\"Having an airline credit card tends to make you a stickier customer,\" Savanthi Syth, a Raymond James analyst, told me.\n\nThree, the complimentary or points-bought upgrades are typically business- or first-class seats that would go unoccupied anyway or be used for last-minute bumps on the day of travel.\n\nThe fourth and final way that airlines end up winning the points game is perhaps the biggest and simplest: They're relying on people never using those points. The McKinsey consulting group estimated in 2018 that 30 trillion airline points went unused globally. That's billions of dollars' worth of unredeemed flights. Unredeemed points are listed as a liability on an airline's balance sheet to account for potential redemptions, but the ones that go unused are essentially \"free money\" because airlines keep the revenue from issuing the points without having to offer any actual reward in return. And the cost to keep unredeemed points in the system is virtually zero. A 2024 federal filing said Southwest had $4.8 billion worth of unused points on its balance sheet; Delta has about $9 billion.\n\nMany people are so price-sensitive that they fly whichever airline has the lowest cost and never earn enough points from flying on a single carrier to redeem anything meaningful. Some people don't travel as much as they think they will when they sign up for a co-branded credit card \u2014 especially younger people like students. This same group may not have the cash funds to pay for a vacation beyond the points flight redemption. And even when people do end up using them, airlines can mitigate the hit by manipulating the number of seats available for redemptions and how many points they cost based on factors like demand and capacity. This type of price increase pushes frequent flyers away from using rewards to offset an expensive cash ticket.\n\nAny good loyalty program comes with the risk of people milking too much out of it, at least from the airline's point of view. This has prompted carriers to periodically \u2014 and unexpectedly \u2014 change the level of points, spending, or eligibility required to earn status, freebies, and benefits. The goal is to maximize loyalty revenue, reduce flight redemptions, and elevate brand exclusivity by making people pay more for what was previously offered at lower rates. But it also runs the risk of running people off.\n\nPlease help BI improve our Business, Tech, and Innovation coverage by sharing a bit about your role \u2014 it will help us tailor content that matters most to people like you.\n\nWhat is your job title?  (1 of 2) \n\n Entry level position\n\n Project manager\n\n Management\n\n Senior management\n\n Executive management\n\n Student\n\n Self-employed\n\n Retired\n\n Other\n\nWhat products or services can you approve for purchase in your role?  (2 of 2) \n\n Advertising / Marketing\n\n Client / Account Management\n\n Company strategy\n\n HR / Training / Office support\n\n Managing budgets\n\n IT / Telecoms / Tech\n\n Recruiting new employees\n\n Sales\n\n Software development\n\n Financial\n\n Other\n\n None of the above\n\nBy providing this information, you agree that Business Insider may use this data to improve your site experience and for targeted advertising. By continuing you agree that you accept the  Terms of Service  and  Privacy Policy  .\n\nThanks for sharing insights about your role.\n\nThe latest example of this switcheroo is when United increased virtually all of its co-branded credit card annual fees in March by between $55 and $245. Delta similarly upped the yearly cost for its Amex cards in 2024. The buck didn't stop there, with both airlines also overhauling parts of their loyalty programs. Delta added limitations on its Sky Club lounge access and made earning status more costly by basing it on spending rather than miles flown. Delta said the changes addressed a need to manage overcrowding at airport lounges and how many people earn elite status.\n\nMost consumers are using few to none of these benefits.\n\nUnited's loyalty changes were tamer, such as upping the price for its lounge access, though they still frustrated members. Even the new credit card \"perks\" \u2014 which the company said would enhance their value by targeting different consumer travel styles \u2014 have some noticeable drawbacks. Sally French, a NerdWallet analyst, told me that United's new benefits have \"coupon book energy to the max.\" Customers can use travel credits on things like hotels, ride-hailing services, rental cars, Instacart, and flights with the semiprivate charter company JSX. These may seem useful in theory, but the problem is that the $60 to $150 annual credit for Uber and Lyft is allotted at $5 to $18 a month, depending on the card. The same goes for Instacart. French said the up to $200 annual JSX credit may not put a huge dent in the company's pricier airfare, which starts at about $200 one way for short hops but can reach $1,000 or more on longer flights. And the up to $200 hotel credit? That has to be put toward bookings at Renowned Hotels and Resorts \u2014 it can't be used on your preferred brand, which might be Hyatt or Marriott. Given the limited value and scope, many customers are leaving these deals on the table \u2014 but the airline already cashed in on the sign-up with the bank.\n\n\"Most consumers are using few to none of these benefits,\" French told me.\n\nStill, French said there are some, albeit few, positives to airline loyalty changes, like less crowded lounges and more membership exclusivity. And many cardholders will likely stay loyal despite the changes. Delta's president, Glen Hauenstein, said in the airline's January earnings call that about 1 million people signed up for its Amex card in 2024. In its full-year earnings call, United also said it saw 1 million new credit card acquisitions last year \u2014 though it's unclear how its 2025 changes will affect sign-ups.\n\nAirlines are facing a grim outlook right now. Economic uncertainty and President Donald Trump's tariff war have sent airline stocks tumbling and threaten profit outlooks. Recession worries are testing travelers' willingness to fly, and a reduction in domestic government travel following federal layoffs hasn't helped. Still, loyalty may be a saving grace because, regardless of a recession, credit card spending and subsequent earnings aren't going away \u2014 a buffer that helped airlines' financials during the pandemic and could again if there's a downturn this year.\n\nDelta's April earnings showed loyalty revenue increased by 7% year over year, including the $2 billion made from its Amex partnership. This was down from the 12% loyalty revenue increase the airline posted between the first quarters of 2023 and 2024 but still high enough to keep overall growth in the green. Similarly, United's earnings revealed a 9.4% increase in loyalty revenue year over year, a slide from the 15% bump in the first quarter of 2024 but still a strong number.\n\nEven with the potential for regulatory and economic roadblocks, loyalty ecosystems are imperative to an airline's success.\n\nAmerican's 5% increase in loyalty revenue, driven by credit card swipes, was the lowest of the three mainline carriers. Southwest did not disclose its year-over-year loyalty performance. Neither airline reported a quarterly profit but said loyalty padded their bottom lines: \"We had a record first-quarter spend in our co-branded credit card,\" Southwest's chief operating officer, Andrew Watterson, said during the airlines' earnings call.\n\nThe golden goose, however, is under threat. The Department of Transportation in September began investigating the programs at American, Delta, Southwest, and United to determine whether they were engaging in \"unfair, deceptive, or anticompetitive practices.\" Then-Transportation Secretary Pete Buttigieg said the airlines' ability to devalue their points is hurting Americans and their families. It's unclear how the Trump administration will carry out the investigation.\n\nEven with the potential for regulatory and economic roadblocks, loyalty ecosystems are imperative to an airline's success. As the people-moving business has gotten more cutthroat and margins have been squeezed, the major carriers are relying more than ever on revenue from nonticket sources. While bag and seat-selection fees draw customers' ire, loyalty points and credit card tie-ins almost feel like a game. That's pushing airlines away from their core flying business and making them into mini financial institutions. In Gen Z talk, it's giving less Wright brothers and more JPMorgan.\n\nTaylor Rains is a senior aviation reporter on the transportation team focused on all things aircraft and airlines.\n\nBusiness Insider's Discourse stories provide perspectives on the day's most pressing issues, informed by analysis, reporting, and expertise.\n\nMost popular]]>\n    \n \n \n   Getty Images; Jenny Chang-Rodriguez/BI  \n\nWhile it's ubiquitous, air travel remains one of the wildest technical achievements in human history. Beyond the scientific feat that goes into achieving takeoff, airlines must coordinate tens of thousands of bags, employees, and travelers to make sure everyone gets to where they're going. Despite the sheer effort involved, moving people through the sky from point A to point B isn't what makes the bottom line soar in the airline business these days. Instead, the major players rake in billions of dollars thanks to a feat of financial engineering: loyalty and credit card spending.\n\nFirst developed in the 1980s, airline loyalty perks revolutionized the industry, creating a base of passionate customers eager to fly a specific carrier or use its credit card in exchange for things like free checked luggage, seat upgrades, early boarding, ever-popular airport lounge access, and \"free\" flights. A 2024 OAG analysis found that 82% of travelers worldwide were enrolled in at least one airline loyalty program. Delta SkyMiles is the world's largest, with over 120 million members. As of 2023, 31 million airline credit cards had been issued in the US, according to the trade association Airlines for America, and 57% of points were accumulated through cardholder spending.\n\nThe combination of people flying and swiping their credit cards has ballooned airline loyalty into a juggernaut and a primary source of airlines' income \u2014 so much so that carriers would struggle to profit without it. Federal airline filings show loyalty represents over $25 billion in yearly revenue. Among the Big Four in 2024, Southwest earned about $2.2 billion from its loyalty program, or about 8% of its total revenue, United $2.9 billion (5%), American $6.1 billion (11.3%), and Delta $7.4 billion (12%).\n\nAirlines enjoy myriad benefits beyond a loyal customer base, a strong brand, and free marketing whenever someone swipes their card around town. Frequent flyer programs increase a carrier's valuation and generate consistent revenue streams. Played correctly, these programs can also be good for customers looking to optimize their points for vacations. But there are some risks to loyalty from a customer perspective. Carriers can, and will, adjust the value of their points on a whim, boosting their bottom lines at the expense of customers.\n\nThe business has morphed airlines into miniature central banks, printing points as currency and often profiting more from selling them than from actually flying airplanes, or as TJ Dunn, a points guru and editor in chief at the Prince of Travel, told me: \"A lot of people call airlines credit card companies with wings.\"\n\nAmerican Airlines launched the first modern major airline loyalty program, AAdvantage, in 1981. United's MileagePlus and Delta Air Lines' SkyMiles programs followed that same year, while Southwest Airlines' Rapid Rewards program began in 1987. In the same decade, airlines decided to go beyond simply rewarding frequent flyers and began building what has become one of their biggest cash cows: co-branded credit cards. By partnering with banks, airlines can monetize these loyalty miles and points, creating a source of cash to supplement the basic flying business.\n\nAirline points are, in essence, an IOU created out of thin air. Carriers turn around and sell these points and miles to banks in exchange for US dollars to fund their operations, like buying planes and paying pilots. Banks then distribute those to holders of the co-branded cards when they make everyday purchases \u2014 including on nonflying items and activities. Customers then redeem those IOUs for airline services. Put another way, you're turning the money you spent on groceries, gas, clothes, and that $500 VR headset you barely use into jet fuel for your next flight.\n\nBanks like this agreement because it drives high spending and brand loyalty. Airlines love it because it generates repeat customers and a constant loop of revenue as people shop. The more a cardholder spends, the more points they earn, and the more a bank pays the airline. Consumers love it because it feels like they're getting free money when redeeming points. On paper, everyone wins.\n\nEven if everyone comes off happy, the setup is an especially good deal for the airlines. A March report from the travel company Point.me said each airline point is generally valued at about 1 cent, in terms of how much value customers receive when they redeem them, but banks buy them for anywhere from 1.5 to 2.5 cents before any bulk discounts. The margins for selling points range from 39% to 53%. Airlines regularly lure new cardholders with enticing sign-on bonuses and other built-in perks, like travel credits and free checked luggage. Southwest and United partner with JPMorgan Chase, American works with Citibank, and Delta partners with American Express. Each airline has different tiers, and the annual fees \u2014 from which airlines receive a kickback \u2014 can range from $0 to $695 a year.\n\nPlease help BI improve our Business, Tech, and Innovation coverage by sharing a bit about your role \u2014 it will help us tailor content that matters most to people like you.\n\nWhat is your job title?  (1 of 2) \n\n Entry level position\n\n Project manager\n\n Management\n\n Senior management\n\n Executive management\n\n Student\n\n Self-employed\n\n Retired\n\n Other\n\nWhat products or services can you approve for purchase in your role?  (2 of 2) \n\n Advertising / Marketing\n\n Client / Account Management\n\n Company strategy\n\n HR / Training / Office support\n\n Managing budgets\n\n IT / Telecoms / Tech\n\n Recruiting new employees\n\n Sales\n\n Software development\n\n Financial\n\n Other\n\n None of the above\n\nBy providing this information, you agree that Business Insider may use this data to improve your site experience and for targeted advertising. By continuing you agree that you accept the  Terms of Service  and  Privacy Policy  .\n\nThanks for sharing insights about your role.\n\nHaving an airline credit card tends to make you a stickier customer.\n\nThere are some ways savvy travelers can gain the upper hand. Customers can book reward itineraries via airline websites, paying only taxes and fees, often at steep discounts compared with the cash cost of the same flight. For example, a one-way United business class flight from Los Angeles to Sydney on June 4 costs 100,000 points (plus $33). The average redemption value of United points is 1.3 cents per point, meaning the points needed to book the flight equal roughly $1,300 \u2014 but the ticket paid for outside the loyalty program costs $4,988.\n\n\"I've gotten so many good redemptions,\" said Dunn, who largely flies business class using points instead of paying the multithousand-dollar cash price. \"One was a last-minute United Polaris from San Francisco to French Polynesia for 85,000 points. Another was American from Los Angeles to Sydney for 65,000 points.\"\n\nOffering cheaper or almost free flights, upgraded seats, or complimentary checked luggage seems like a self-own by the airlines \u2014 why give money away? But all the special offers are offset by several factors. One, the cost to airlines of letting you redeem points is often far lower than the money they earned up front from selling those points to the banks, especially during off-peak times. So you may feel like you're getting a deal, but the bank already covered your redemption for that \"free\" seat. Two, spending to earn enough points or status for a flight or upgrade means the airline has already secured thousands of dollars' worth of your business many times over, whether you booked a flight with them instead of a competitor (whose standard cost may have been lower) or used its credit card.\n\n\"Having an airline credit card tends to make you a stickier customer,\" Savanthi Syth, a Raymond James analyst, told me.\n\nThree, the complimentary or points-bought upgrades are typically business- or first-class seats that would go unoccupied anyway or be used for last-minute bumps on the day of travel.\n\nThe fourth and final way that airlines end up winning the points game is perhaps the biggest and simplest: They're relying on people never using those points. The McKinsey consulting group estimated in 2018 that 30 trillion airline points went unused globally. That's billions of dollars' worth of unredeemed flights. Unredeemed points are listed as a liability on an airline's balance sheet to account for potential redemptions, but the ones that go unused are essentially \"free money\" because airlines keep the revenue from issuing the points without having to offer any actual reward in return. And the cost to keep unredeemed points in the system is virtually zero. A 2024 federal filing said Southwest had $4.8 billion worth of unused points on its balance sheet; Delta has about $9 billion.\n\nMany people are so price-sensitive that they fly whichever airline has the lowest cost and never earn enough points from flying on a single carrier to redeem anything meaningful. Some people don't travel as much as they think they will when they sign up for a co-branded credit card \u2014 especially younger people like students. This same group may not have the cash funds to pay for a vacation beyond the points flight redemption. And even when people do end up using them, airlines can mitigate the hit by manipulating the number of seats available for redemptions and how many points they cost based on factors like demand and capacity. This type of price increase pushes frequent flyers away from using rewards to offset an expensive cash ticket.\n\nAny good loyalty program comes with the risk of people milking too much out of it, at least from the airline's point of view. This has prompted carriers to periodically \u2014 and unexpectedly \u2014 change the level of points, spending, or eligibility required to earn status, freebies, and benefits. The goal is to maximize loyalty revenue, reduce flight redemptions, and elevate brand exclusivity by making people pay more for what was previously offered at lower rates. But it also runs the risk of running people off.\n\nPlease help BI improve our Business, Tech, and Innovation coverage by sharing a bit about your role \u2014 it will help us tailor content that matters most to people like you.\n\nWhat is your job title?  (1 of 2) \n\n Entry level position\n\n Project manager\n\n Management\n\n Senior management\n\n Executive management\n\n Student\n\n Self-employed\n\n Retired\n\n Other\n\nWhat products or services can you approve for purchase in your role?  (2 of 2) \n\n Advertising / Marketing\n\n Client / Account Management\n\n Company strategy\n\n HR / Training / Office support\n\n Managing budgets\n\n IT / Telecoms / Tech\n\n Recruiting new employees\n\n Sales\n\n Software development\n\n Financial\n\n Other\n\n None of the above\n\nBy providing this information, you agree that Business Insider may use this data to improve your site experience and for targeted advertising. By continuing you agree that you accept the  Terms of Service  and  Privacy Policy  .\n\nThanks for sharing insights about your role.\n\nThe latest example of this switcheroo is when United increased virtually all of its co-branded credit card annual fees in March by between $55 and $245. Delta similarly upped the yearly cost for its Amex cards in 2024. The buck didn't stop there, with both airlines also overhauling parts of their loyalty programs. Delta added limitations on its Sky Club lounge access and made earning status more costly by basing it on spending rather than miles flown. Delta said the changes addressed a need to manage overcrowding at airport lounges and how many people earn elite status.\n\nMost consumers are using few to none of these benefits.\n\nUnited's loyalty changes were tamer, such as upping the price for its lounge access, though they still frustrated members. Even the new credit card \"perks\" \u2014 which the company said would enhance their value by targeting different consumer travel styles \u2014 have some noticeable drawbacks. Sally French, a NerdWallet analyst, told me that United's new benefits have \"coupon book energy to the max.\" Customers can use travel credits on things like hotels, ride-hailing services, rental cars, Instacart, and flights with the semiprivate charter company JSX. These may seem useful in theory, but the problem is that the $60 to $150 annual credit for Uber and Lyft is allotted at $5 to $18 a month, depending on the card. The same goes for Instacart. French said the up to $200 annual JSX credit may not put a huge dent in the company's pricier airfare, which starts at about $200 one way for short hops but can reach $1,000 or more on longer flights. And the up to $200 hotel credit? That has to be put toward bookings at Renowned Hotels and Resorts \u2014 it can't be used on your preferred brand, which might be Hyatt or Marriott. Given the limited value and scope, many customers are leaving these deals on the table \u2014 but the airline already cashed in on the sign-up with the bank.\n\n\"Most consumers are using few to none of these benefits,\" French told me.\n\nStill, French said there are some, albeit few, positives to airline loyalty changes, like less crowded lounges and more membership exclusivity. And many cardholders will likely stay loyal despite the changes. Delta's president, Glen Hauenstein, said in the airline's January earnings call that about 1 million people signed up for its Amex card in 2024. In its full-year earnings call, United also said it saw 1 million new credit card acquisitions last year \u2014 though it's unclear how its 2025 changes will affect sign-ups.\n\nAirlines are facing a grim outlook right now. Economic uncertainty and President Donald Trump's tariff war have sent airline stocks tumbling and threaten profit outlooks. Recession worries are testing travelers' willingness to fly, and a reduction in domestic government travel following federal layoffs hasn't helped. Still, loyalty may be a saving grace because, regardless of a recession, credit card spending and subsequent earnings aren't going away \u2014 a buffer that helped airlines' financials during the pandemic and could again if there's a downturn this year.\n\nDelta's April earnings showed loyalty revenue increased by 7% year over year, including the $2 billion made from its Amex partnership. This was down from the 12% loyalty revenue increase the airline posted between the first quarters of 2023 and 2024 but still high enough to keep overall growth in the green. Similarly, United's earnings revealed a 9.4% increase in loyalty revenue year over year, a slide from the 15% bump in the first quarter of 2024 but still a strong number.\n\nEven with the potential for regulatory and economic roadblocks, loyalty ecosystems are imperative to an airline's success.\n\nAmerican's 5% increase in loyalty revenue, driven by credit card swipes, was the lowest of the three mainline carriers. Southwest did not disclose its year-over-year loyalty performance. Neither airline reported a quarterly profit but said loyalty padded their bottom lines: \"We had a record first-quarter spend in our co-branded credit card,\" Southwest's chief operating officer, Andrew Watterson, said during the airlines' earnings call.\n\nThe golden goose, however, is under threat. The Department of Transportation in September began investigating the programs at American, Delta, Southwest, and United to determine whether they were engaging in \"unfair, deceptive, or anticompetitive practices.\" Then-Transportation Secretary Pete Buttigieg said the airlines' ability to devalue their points is hurting Americans and their families. It's unclear how the Trump administration will carry out the investigation.\n\nEven with the potential for regulatory and economic roadblocks, loyalty ecosystems are imperative to an airline's success. As the people-moving business has gotten more cutthroat and margins have been squeezed, the major carriers are relying more than ever on revenue from nonticket sources. While bag and seat-selection fees draw customers' ire, loyalty points and credit card tie-ins almost feel like a game. That's pushing airlines away from their core flying business and making them into mini financial institutions. In Gen Z talk, it's giving less Wright brothers and more JPMorgan.\n\nTaylor Rains is a senior aviation reporter on the transportation team focused on all things aircraft and airlines.\n\nBusiness Insider's Discourse stories provide perspectives on the day's most pressing issues, informed by analysis, reporting, and expertise.\n\nMost popular]]>\n  \n  \n    How Long Does it Take to Speak Spanish Fluently?\n    https://expanish.com/blog/how-long-take-speak-spanish-fluently/\n    readwise:01jv0cjyvxyhcewg86p69mka76\n    Sun, 11 May 2025 19:19:11 +0000\n    expanish.com\n    Contents\n\n\n\nWhat does being \u201cfluent\u201d in Spanish mean?\n\nSo how long does it take to learn Spanish?\n\nKey factors affecting how quickly you can master the Spanish language\n\nExample study timelines\n\nTips for improve your Spanish faster\n\nFAQs\n\n\n\nWhat does being \u201cfluent\u201d in Spanish mean?\n\nFluency in a language can be rather subjective as people have different goals and requirements. The Common European Framework of Reference for Languages (CEFR) defines six levels of language proficiency, ranging from complete beginner (A1) to a master of proficiency (C2). However, in practice most people are aiming for conversational fluency - that is, being able to easily interact with other Spanish speakers in a variety of real-life situations. By the time you reach the B2 level you should be in this position. If you want to use Spanish in a professional context you will likely need to reach level C1/C2.\n\nHow many hours are needed to learn Spanish?\n\nThe truth is that there is no simple and easy answer to this as everyone is different. As a starting reference point, the CEFR provides some estimates for the average time to learn Spanish for English speakers. However, we recommend you don\u2019t get too fixated on the numbers in the table below - your own language journey will be unique to you and the circumstance you are in.\n\n\nLevel\nDescription\nTime Required (Hours)\nA1 (Beginner)\nBasic phrases and everyday expressions.\n70\u2013100 hours\nA2 (Elementary)\nSimple conversations about familiar topics.\n150\u2013200 hours\nB1 (Intermediate)\nConversations about everyday life and personal interests.\n300\u2013400 hours\nB2 (Upper Intermediate)\nCan work or study in Spanish with limited support.\n500\u2013600 hours\nC1 (Advanced)\nExpress ideas fluently and spontaneously.\n700\u2013900 hours\nC2 (Proficient)\nNear-native fluency and comprehension.\n1,000+ hours\n\nThe US Foreign Service Institute offers another benchmark, based on over 75 years of teaching languages to diplomats. It estimates that the average student will take around 750 class hours to reach \u201cgeneral professional proficiency\u201d in Spanish.\n\nKey factors that affect how quickly you can master the Spanish language\n\nAs we\u2019ve said, everyone is different and will learn the language at different speeds. However, there are some important factors that will influence how quickly you advance your Spanish.\n\n\n\nYour starting point: If you are a complete beginner it will take a bit of time to build a solid base for understanding and using Spanish - after that your learning will likely accelerate. Those people with some previous exposure to the language, especially as a young child, may be able to pick up the basics more quickly. Also, if you already speak more than one language, particularly if that includes a romance language (e.g. French or Italian), this might help you learn Spanish more quickly.\n\nYour goals: Setting out clear objectives can help keep you motivated, which will support effective language learning. If you\u2019re just seeking to be able to communicate at a basic level, then 1-3 months of learning will likely be enough to reach your goal. Achieving conversational fluency is a longer journey that will require more dedication and patience, but with consistent practice it\u2019s possible in 6-12 months. For professional level Spanish you will probably need to complete at least 1-2 years of study and practice. Being realistic about your language goals will help you set out a study program that works for you.\n\nYour study method: It\u2019s fairly obvious, but the more hours per day you put into learning Spanish, the faster you will likely reach your desired level. Taking an intensive Spanish language course, with daily lessons and around 20-30 study hours per week, should lead to faster progress than part-time study. Even outside of lessons, daily practice will accelerate your learning. That\u2019s why immersion programs in Spanish-speaking countries are the best way to conquer the Spanish language as you will be forced to use it on a daily basis in different real-life situations.\n\nYour exposure to the language: As above, if you are in Spain or another Spanish-speaking country then you will be exposed to the language 24/7 in all kinds of everyday situations. Aside from Spanish lessons, you will have constant access to Spanish television and radio and be able to interact with locals whenever you wish. This will help you reach proficiency far more quickly than if you are taking a few lessons a week in your home country. \n\nExample study timelines\n\nBelow are some possible timelines for learning Spanish for a beginner, based on different approaches to study. Remember, these are just broad guidelines: the most important point is that immersive and intensive language learning is the best and fastest way to become fluent in Spanish.\n\nTime required to learn Spanish for beginners\n\n\nLanguage goal\nIntensive Spanish course (20+ hours p/week) in Spain or Latin America\nPart-time study (2-3 times p/week) in a non-Spanish speaking country\nSelf-learning (e.g. language apps, textbooks)\nBasic communication (A2-B1)\n1-2 months\n2-4 months\n3-6 months\nConversational fluency (B2-C1)\n6-9 months\n12-18 months\n1-2 years\nMastery (C2)\n1-2 years\n3+ years\n5+ years\n\nTips to improve your Spanish Faster\n\nImmerse yourself in the language\n\nWe\u2019ve talked about the benefits of language immersion, but to really take advantage of this requires some effort. If you\u2019re studying in Spain or another Spanish-speaking country, then make sure you interact with native speakers and try to learn about local culture and traditions. This will dramatically improve your range of vocabulary, listening skills and help you perfect your pronunciation.\n\nFocus on speaking\n\nThe best way to learn Spanish quickly is to use it as much as possible. Don\u2019t worry too much about making mistakes - no one will expect you to speak perfectly (many locals don\u2019t either!). It\u2019s more important to be able to communicate, to understand others and be able to make yourself understood. To get you going, it can be a good idea to join language exchange groups or take part in Spanish-speaking activities offered by many language schools like Expanish.\n\nPractice daily\n\nEven just 15-30 minutes of practice a day can make a big difference to your grammar and vocabulary. If you don\u2019t have any lessons in a day, try completing a task or game in Spanish, watching a Spanish tv program (with or without subtitles, depending on your level) or listening to Spanish radio/podcasts. It doesn\u2019t matter if you don\u2019t understand everything at first - just hearing the sounds and words will help you improve your own listening and speaking skills. You\u2019ll be amazed at how quickly you start to pick it up if you expose yourself regularly to the language!\n\nTake an intensive course\n\nSelf-study is very important, but there\u2019s no substitute for structured learning, especially for beginners and intermediate speakers. Schools like Expanish offer a range of intensive Spanish language courses that are tailored to individual needs/goals and include immersive learning techniques to really accelerate progress. Given the importance of immersion, we recommend in person courses in Spanish-speaking countries ahead of online courses.\n\nFAQS:\n\nCan I learn Spanish in 3 months?\n\nHow long does it take to master the Spanish language if I already speak another Romance language?\n\nDo I need to live in a Spanish-speaking country to become fluent?\n\nWhat\u2019s the fastest way to learn Spanish?]]>\n    Contents\n\n\n\nWhat does being \u201cfluent\u201d in Spanish mean?\n\nSo how long does it take to learn Spanish?\n\nKey factors affecting how quickly you can master the Spanish language\n\nExample study timelines\n\nTips for improve your Spanish faster\n\nFAQs\n\n\n\nWhat does being \u201cfluent\u201d in Spanish mean?\n\nFluency in a language can be rather subjective as people have different goals and requirements. The Common European Framework of Reference for Languages (CEFR) defines six levels of language proficiency, ranging from complete beginner (A1) to a master of proficiency (C2). However, in practice most people are aiming for conversational fluency - that is, being able to easily interact with other Spanish speakers in a variety of real-life situations. By the time you reach the B2 level you should be in this position. If you want to use Spanish in a professional context you will likely need to reach level C1/C2.\n\nHow many hours are needed to learn Spanish?\n\nThe truth is that there is no simple and easy answer to this as everyone is different. As a starting reference point, the CEFR provides some estimates for the average time to learn Spanish for English speakers. However, we recommend you don\u2019t get too fixated on the numbers in the table below - your own language journey will be unique to you and the circumstance you are in.\n\n\nLevel\nDescription\nTime Required (Hours)\nA1 (Beginner)\nBasic phrases and everyday expressions.\n70\u2013100 hours\nA2 (Elementary)\nSimple conversations about familiar topics.\n150\u2013200 hours\nB1 (Intermediate)\nConversations about everyday life and personal interests.\n300\u2013400 hours\nB2 (Upper Intermediate)\nCan work or study in Spanish with limited support.\n500\u2013600 hours\nC1 (Advanced)\nExpress ideas fluently and spontaneously.\n700\u2013900 hours\nC2 (Proficient)\nNear-native fluency and comprehension.\n1,000+ hours\n\nThe US Foreign Service Institute offers another benchmark, based on over 75 years of teaching languages to diplomats. It estimates that the average student will take around 750 class hours to reach \u201cgeneral professional proficiency\u201d in Spanish.\n\nKey factors that affect how quickly you can master the Spanish language\n\nAs we\u2019ve said, everyone is different and will learn the language at different speeds. However, there are some important factors that will influence how quickly you advance your Spanish.\n\n\n\nYour starting point: If you are a complete beginner it will take a bit of time to build a solid base for understanding and using Spanish - after that your learning will likely accelerate. Those people with some previous exposure to the language, especially as a young child, may be able to pick up the basics more quickly. Also, if you already speak more than one language, particularly if that includes a romance language (e.g. French or Italian), this might help you learn Spanish more quickly.\n\nYour goals: Setting out clear objectives can help keep you motivated, which will support effective language learning. If you\u2019re just seeking to be able to communicate at a basic level, then 1-3 months of learning will likely be enough to reach your goal. Achieving conversational fluency is a longer journey that will require more dedication and patience, but with consistent practice it\u2019s possible in 6-12 months. For professional level Spanish you will probably need to complete at least 1-2 years of study and practice. Being realistic about your language goals will help you set out a study program that works for you.\n\nYour study method: It\u2019s fairly obvious, but the more hours per day you put into learning Spanish, the faster you will likely reach your desired level. Taking an intensive Spanish language course, with daily lessons and around 20-30 study hours per week, should lead to faster progress than part-time study. Even outside of lessons, daily practice will accelerate your learning. That\u2019s why immersion programs in Spanish-speaking countries are the best way to conquer the Spanish language as you will be forced to use it on a daily basis in different real-life situations.\n\nYour exposure to the language: As above, if you are in Spain or another Spanish-speaking country then you will be exposed to the language 24/7 in all kinds of everyday situations. Aside from Spanish lessons, you will have constant access to Spanish television and radio and be able to interact with locals whenever you wish. This will help you reach proficiency far more quickly than if you are taking a few lessons a week in your home country. \n\nExample study timelines\n\nBelow are some possible timelines for learning Spanish for a beginner, based on different approaches to study. Remember, these are just broad guidelines: the most important point is that immersive and intensive language learning is the best and fastest way to become fluent in Spanish.\n\nTime required to learn Spanish for beginners\n\n\nLanguage goal\nIntensive Spanish course (20+ hours p/week) in Spain or Latin America\nPart-time study (2-3 times p/week) in a non-Spanish speaking country\nSelf-learning (e.g. language apps, textbooks)\nBasic communication (A2-B1)\n1-2 months\n2-4 months\n3-6 months\nConversational fluency (B2-C1)\n6-9 months\n12-18 months\n1-2 years\nMastery (C2)\n1-2 years\n3+ years\n5+ years\n\nTips to improve your Spanish Faster\n\nImmerse yourself in the language\n\nWe\u2019ve talked about the benefits of language immersion, but to really take advantage of this requires some effort. If you\u2019re studying in Spain or another Spanish-speaking country, then make sure you interact with native speakers and try to learn about local culture and traditions. This will dramatically improve your range of vocabulary, listening skills and help you perfect your pronunciation.\n\nFocus on speaking\n\nThe best way to learn Spanish quickly is to use it as much as possible. Don\u2019t worry too much about making mistakes - no one will expect you to speak perfectly (many locals don\u2019t either!). It\u2019s more important to be able to communicate, to understand others and be able to make yourself understood. To get you going, it can be a good idea to join language exchange groups or take part in Spanish-speaking activities offered by many language schools like Expanish.\n\nPractice daily\n\nEven just 15-30 minutes of practice a day can make a big difference to your grammar and vocabulary. If you don\u2019t have any lessons in a day, try completing a task or game in Spanish, watching a Spanish tv program (with or without subtitles, depending on your level) or listening to Spanish radio/podcasts. It doesn\u2019t matter if you don\u2019t understand everything at first - just hearing the sounds and words will help you improve your own listening and speaking skills. You\u2019ll be amazed at how quickly you start to pick it up if you expose yourself regularly to the language!\n\nTake an intensive course\n\nSelf-study is very important, but there\u2019s no substitute for structured learning, especially for beginners and intermediate speakers. Schools like Expanish offer a range of intensive Spanish language courses that are tailored to individual needs/goals and include immersive learning techniques to really accelerate progress. Given the importance of immersion, we recommend in person courses in Spanish-speaking countries ahead of online courses.\n\nFAQS:\n\nCan I learn Spanish in 3 months?\n\nHow long does it take to master the Spanish language if I already speak another Romance language?\n\nDo I need to live in a Spanish-speaking country to become fluent?\n\nWhat\u2019s the fastest way to learn Spanish?]]>\n  \n  \n    How much will an apartment in the Condesa cost in 2024?\n    https://search.app/?link=https%3A%2F%2Fnolab%2Emx%2Fblog%2Fen%2Fhow%2Dmuch%2Dan%2Dapartment%2Dcosts%2Din%2Dla%2Dcondesa%2F%23%3A%7E%3Atext%3DAccording%2520to%2520the%2520latest%2520analysis%2Cbetween%252055%252C000%2520and%252065%252C000%2520MXN%2E&utm_campaign=57165%2Dor%2Digacx%2Dweb%2Dshrbtn%2Diga%2Dsharing&utm_source=igadl%2Cigatpdl%2Csh%2Fx%2Fgs%2Fm2%2F5\n    readwise:01jtnsc991vs2gx5s04dmhf37x\n    Wed, 07 May 2025 16:31:06 +0000\n    Forbes\n    \n\u00bfCu\u00e1nto cuesta un departamento en la Condesa? - Nolab.\n\nAre you going to invest in La Condesa? You are not making a mistake! It is one of the most emblematic neighborhoods, with an unparalleled quality of life and a super privileged location in the whole CDMX. Thanks to its architecture, geographic attributes, avenues and parks, La Condesa is a reference of habitability in the city. Find out below how much an apartment in the Condesa will cost in 2024 and make your best investment.\n\nAccording to the latest analysis by Nolaband taking into account the internal portfolio and other property catalogs such as inmuebles24 and propiedades.com, the average cost of an apartment in Colonia Condesa ranges between $6,500,000 MXN and $6,700,000 MXN with average features such as 2 bedrooms, 1 and 2 bathrooms and 1 parking space.\n\nPrices per square meter in the Condesa may vary depending on the type of age of the property. In new properties you can find a cost per square meter ranging between 80,000 and 90,000 MXN, while in pre-owned properties prices can vary between 55,000 and 65,000 MXN.\n\nWhere does Colonia Condesa come from and where is it located?\n\nCurrently located in the Cuauht\u00e9moc district, to the west of the CDMX and next to Chapultepec Forest, La Condesa has its origins in colonial times, when the Hacienda Santa Mar\u00eda del Arenal occupied the area between Tacubaya and Romita. In 1704, Do\u00f1a Mar\u00eda Magdalena D\u00e1valos de Bracamonte y Orozco, Third Countess of Miravalle, acquired this land, which now comprises the Condesa, Hip\u00f3dromo Condesa and part of Roma Norte neighborhoods.\n\nThe aristocrat, born in 1701, played a crucial role in the development of the area, diligently managing her properties and transforming them into areas of high value, so you will find traces of colonial architecture, combined with modernist currents similar to the European trends of the nineteenth century, and yet you will also find innovative and contemporary projects that combine the best of a minimalist and functional style in a strident and multicultural environment.\n\nLearn more about the area!\n\nRoma Norte or Roma Sur: Where to invest in luxury properties \ud83d\udcb0\n\nWhat factors influence the prices of apartments in the Condesa?\n\n \nExcellent location in the CDMX: La Condesa enjoys a central location, with easy access to other key areas of Mexico City such as the west and south of the CDMX. La Condesa is adjacent to other neighborhoods with great style, quality of life and added value, such as San Miguel Chapultepec, Hip\u00f3dromo Condesa, Ju\u00e1rez and Roma Norte. \n\n \nQuality of new real estate projects and premium renovations: The area has a mix of modern and historic buildings, which can influence prices depending on the age and condition of the property. \n\n \nAmenities: Without a doubt, amenities play a key role in any real estate development, not only in the Condesa; the presence of features such as 24-hour security, common areas, coworking spaces, gyms and parking lots have a positive impact on the value of properties, especially new ones. Tip: In recent years it has registered a capital gain that fluctuates between 5% and 7%, so the best time to buy a property in this neighborhood is now, whether you want it to live in or as an investment. \n\n \nDemand and community: Wanting to live in La Condesa is a feeling that goes beyond the inhabitants of CDMX, the qualities of this neighborhood are known internationally, so its high demand for properties to buy or rent, due to its prestige and lifestyle, plays a very relevant role in the cost of apartments. Here you will find communities of people from all over the world, young and old, pet lovers, LGBT+ communities and tourists. \n\n \nQuality of life and lifestyle: The neighborhood\u2019s layout allows for bicycle-friendly mobility and its connection to public transportation allows for car-free living. With attractions such as Parque Mexico and Parque Espa\u00f1a providing green spaces ideal for outdoor activities, the neighborhood\u2019s Art Deco and modern architecture adds a unique charm, while its diverse and cosmopolitan community fosters an inclusive and dynamic environment that radiates the feeling of all its inhabitants. \n\nWhat do you think about this emblematic neighborhood in the heart of the CDMX? If it appeals to you as much as it does to us, now is the perfect time to invest! Contact us and discover the wide range of properties in La Condesa that fit your investor profile.]]>\n    \n\u00bfCu\u00e1nto cuesta un departamento en la Condesa? - Nolab.\n\nAre you going to invest in La Condesa? You are not making a mistake! It is one of the most emblematic neighborhoods, with an unparalleled quality of life and a super privileged location in the whole CDMX. Thanks to its architecture, geographic attributes, avenues and parks, La Condesa is a reference of habitability in the city. Find out below how much an apartment in the Condesa will cost in 2024 and make your best investment.\n\nAccording to the latest analysis by Nolaband taking into account the internal portfolio and other property catalogs such as inmuebles24 and propiedades.com, the average cost of an apartment in Colonia Condesa ranges between $6,500,000 MXN and $6,700,000 MXN with average features such as 2 bedrooms, 1 and 2 bathrooms and 1 parking space.\n\nPrices per square meter in the Condesa may vary depending on the type of age of the property. In new properties you can find a cost per square meter ranging between 80,000 and 90,000 MXN, while in pre-owned properties prices can vary between 55,000 and 65,000 MXN.\n\nWhere does Colonia Condesa come from and where is it located?\n\nCurrently located in the Cuauht\u00e9moc district, to the west of the CDMX and next to Chapultepec Forest, La Condesa has its origins in colonial times, when the Hacienda Santa Mar\u00eda del Arenal occupied the area between Tacubaya and Romita. In 1704, Do\u00f1a Mar\u00eda Magdalena D\u00e1valos de Bracamonte y Orozco, Third Countess of Miravalle, acquired this land, which now comprises the Condesa, Hip\u00f3dromo Condesa and part of Roma Norte neighborhoods.\n\nThe aristocrat, born in 1701, played a crucial role in the development of the area, diligently managing her properties and transforming them into areas of high value, so you will find traces of colonial architecture, combined with modernist currents similar to the European trends of the nineteenth century, and yet you will also find innovative and contemporary projects that combine the best of a minimalist and functional style in a strident and multicultural environment.\n\nLearn more about the area!\n\nRoma Norte or Roma Sur: Where to invest in luxury properties \ud83d\udcb0\n\nWhat factors influence the prices of apartments in the Condesa?\n\n \nExcellent location in the CDMX: La Condesa enjoys a central location, with easy access to other key areas of Mexico City such as the west and south of the CDMX. La Condesa is adjacent to other neighborhoods with great style, quality of life and added value, such as San Miguel Chapultepec, Hip\u00f3dromo Condesa, Ju\u00e1rez and Roma Norte. \n\n \nQuality of new real estate projects and premium renovations: The area has a mix of modern and historic buildings, which can influence prices depending on the age and condition of the property. \n\n \nAmenities: Without a doubt, amenities play a key role in any real estate development, not only in the Condesa; the presence of features such as 24-hour security, common areas, coworking spaces, gyms and parking lots have a positive impact on the value of properties, especially new ones. Tip: In recent years it has registered a capital gain that fluctuates between 5% and 7%, so the best time to buy a property in this neighborhood is now, whether you want it to live in or as an investment. \n\n \nDemand and community: Wanting to live in La Condesa is a feeling that goes beyond the inhabitants of CDMX, the qualities of this neighborhood are known internationally, so its high demand for properties to buy or rent, due to its prestige and lifestyle, plays a very relevant role in the cost of apartments. Here you will find communities of people from all over the world, young and old, pet lovers, LGBT+ communities and tourists. \n\n \nQuality of life and lifestyle: The neighborhood\u2019s layout allows for bicycle-friendly mobility and its connection to public transportation allows for car-free living. With attractions such as Parque Mexico and Parque Espa\u00f1a providing green spaces ideal for outdoor activities, the neighborhood\u2019s Art Deco and modern architecture adds a unique charm, while its diverse and cosmopolitan community fosters an inclusive and dynamic environment that radiates the feeling of all its inhabitants. \n\nWhat do you think about this emblematic neighborhood in the heart of the CDMX? If it appeals to you as much as it does to us, now is the perfect time to invest! Contact us and discover the wide range of properties in La Condesa that fit your investor profile.]]>\n  \n  \n    Vibe coders and new developers coding with AI should be...\n    https://x.com/iannuttall/status/1918598483180957912/?s=12&rw_tt_thread=True\n    readwise:01jtb9qnq5x3fg82haavdw66hc\n    Sat, 03 May 2025 14:45:17 +0000\n    X (formerly Twitter)\n    \nVibe coders and new developers coding with AI should be building MCP servers ASAP\nAn entire market is wide open and completely untapped right now. The opportunity is massive.\nHere's the simple 3-step playbook to get in on the goldrush:\n\n1) Find a painkiller problem to solve\nIt could be looking up/formatting data, scraping URLs, finding UI components, or connecting apps in useful ways\nIf you find a solution that fixes a painful problem, you can sell it\nExample: Magic MCP by @serafimcloud makes \u00a3400+ MRR\n\n2) Create a remote MCP with @Cloudflare\nCloudflare are ALL IN on MCPs. One-click deploy to get started with or without auth is a game changer and removes the pain of running an MCP locally for users\n@rickyrobinett built one in minutes to order pizza\nx.com/rickyrobinett/\u2026\n\n3) Monetise it with @stripe\n@jeff_weinstein announced Stripe MCP payments so you can charge for access in like 20 lines of code \ud83e\udd2f\nx.com/jeff_weinstein\u2026\n\nI expect to see dozens of examples in the next 1-2 months of indie hackers and solopreneurs spinning up profitable MCPs in a weekend hack\nThis is still so new that there is no real competition.\nBut what about distribution?\n\nCloudflare and @AnthropicAI are highly motivated to make MCP work\nAnthropic just launched \"Integrations\" which is really hosted and verified MCP servers and I predict an app store/marketplace = instant distribution!\n+ thanks to Epic hopefully no fees ;)\nx.com/AnthropicAI/st\u2026\n\nAnd that's just the start...\nPretty soon agents will have access to that app store/marketplace and will be able to choose the best server, purchase access to it, and start using it - all without human interaction\nMCP is kinda like the invention of the wheel, we just need cars!\n\nI don't usually do threads like this but it's easier to link out and and share a bunch of resources vs one long post\nIf you liked this, reply and let me know so I can do more and follow me @iannuttall if you want to see how I'm trying to keep up with AI and new tech like MCPs \ud83d\ude30]]>\n    \nVibe coders and new developers coding with AI should be building MCP servers ASAP\nAn entire market is wide open and completely untapped right now. The opportunity is massive.\nHere's the simple 3-step playbook to get in on the goldrush:\n\n1) Find a painkiller problem to solve\nIt could be looking up/formatting data, scraping URLs, finding UI components, or connecting apps in useful ways\nIf you find a solution that fixes a painful problem, you can sell it\nExample: Magic MCP by @serafimcloud makes \u00a3400+ MRR\n\n2) Create a remote MCP with @Cloudflare\nCloudflare are ALL IN on MCPs. One-click deploy to get started with or without auth is a game changer and removes the pain of running an MCP locally for users\n@rickyrobinett built one in minutes to order pizza\nx.com/rickyrobinett/\u2026\n\n3) Monetise it with @stripe\n@jeff_weinstein announced Stripe MCP payments so you can charge for access in like 20 lines of code \ud83e\udd2f\nx.com/jeff_weinstein\u2026\n\nI expect to see dozens of examples in the next 1-2 months of indie hackers and solopreneurs spinning up profitable MCPs in a weekend hack\nThis is still so new that there is no real competition.\nBut what about distribution?\n\nCloudflare and @AnthropicAI are highly motivated to make MCP work\nAnthropic just launched \"Integrations\" which is really hosted and verified MCP servers and I predict an app store/marketplace = instant distribution!\n+ thanks to Epic hopefully no fees ;)\nx.com/AnthropicAI/st\u2026\n\nAnd that's just the start...\nPretty soon agents will have access to that app store/marketplace and will be able to choose the best server, purchase access to it, and start using it - all without human interaction\nMCP is kinda like the invention of the wheel, we just need cars!\n\nI don't usually do threads like this but it's easier to link out and and share a bunch of resources vs one long post\nIf you liked this, reply and let me know so I can do more and follow me @iannuttall if you want to see how I'm trying to keep up with AI and new tech like MCPs \ud83d\ude30]]>\n  \n  \n    VC_Playbook_April2025\n    https://readwise.io/reader/document_raw_content/298624878\n    readwise:01jt97x7026n3px1esr6hea73p\n    Fri, 02 May 2025 19:34:53 +0000\n    \n\u200cCOFTO\n\n\nVC regulatory\nplaybok\nThe VC regulatory landscape is changing. Are you up to date?\n\n\n\nCOFTO\n\n\u200cVC regulatory playbook\nUpdated March 2025\n\nAs regulatory scrutiny increases on private funds\u2014and private markets more generally\u2014Carta has put together a playbook that lays out the regulatory landscape, compliance requirements, and additional considerations for fund managers to consider as they navigate the evolving private market regulatory landscape.\n\n\n\nI  Regulation of the private fund\n\n\n\n\n\nRegulation of the fundraising process\n\n\n\n\nRegulation of the fund manager\n\n\n\nERA compliance checklist\n\n\n\n\nAdditional regulatory considerations\n\nPrivate fund regulation: the basics\nThere are three categories of regulation all venture capital advisers should be aware of:\n\n\nRegulation of the fund (Investment Company Act)\n\nRegulation of the fund manager(Investment Advisers Act)\n\nRegulation of the fundraising process\nWe\u2019ll cover each of the three areas in depth, and provide answers to some of the frequently asked questions below.\n\n\n\nFund regulation\n\n\nDo I need to register my fund?\n\nWhat are Section 3(c)(l) and Section 3(c)(7)?\n\nWhat are the limits on registration\nexemptions?\n\nWho can invest in registration\u2014\nexempt funds?\nFundraising regulation\n\nWhat is Regulation D?\n\nWhat are Rule 506(b) and Rule 506(c)?\n\nCan I advertise my fund offering?\n\nWhat is Form D and when do I file it?\nFund manager regulation\n\n\tDo I need to register as an investment adviser?\n\nWhat is Form ADV and when do I file it?\n\nWhat regulatory obligations do exempt reporting advisers (ERAs) have?\n\n\nThis guide is not meant to cover every legal obligation or be a substitute for legal advice, but rather serve as an informational guide\nto legal and regulatory compliance requirements. You should discuss with your own legal counsel other factors that may apply to your specific circumstances to ensure compliance.\n\n\u200cRegulation of the  fund\u200c\nA fund must register with the SEC as an investment company unless it meets the criteria for an exemption. Venture capital funds rely\non two exemptions to avoid SEC registration:\n\n\nSection 3(c)(l)\n\nSection 3(c)(7)\n \n\nSection 3(c)(1)\nA 3(c)(l) fund involves a private placement by a fund that will have no more than 100 beneficial owners who are accredited investors.\n\nCounting beneficial owners: As a default, one individual or entity will count as one LP. But in certain instances,\nthe SEC will \u201clook through\u201d an investment vehicle or entity for purposes of counting its underlying beneficial owners. These include:\n\n\nLP entities created by their members for the specific purpose of investing in the fund\n\nLP entities investing 10% or more of the fund voting assets\n\nLP entities investing 40% or more of the LP's assets into a single fund\n\nQualifying \nventure capital funds\nCongress created a special category of 3(c)(1) funds known as a \u201cqualifying venture capital fund\u201d that can have up to 250 beneficial owners if the fund is under $12 million and meets the definition of a venture capital fund.\n\nA venture capital fund has its own special requirements:\n\n\n\n\tA venture capital fund must hold at least 80% of assets in \u201cqualifying investments\u201d \u2014 cash and equity securities acquired directly from portfolio companies. In other words, VC funds can invest in non\u2014qualifying investments\u2014fund\u2014of\u2014fund investments, digital assets, secondary transactions, etc.\u2014but they are limited\nto no more than 20% of capital.\n\nA venture capital fund cannot be substantially leveraged: To maintain their exemption, VC funds can't leverage more than 15% of their AUM and outstanding loans must be repaid in120 days of borrowing.\n\nA venture capital fund cannot provide redemption rights except in limited, extraordinary circumstances.\n\nA venture capital fund must pursue a venture investment strategy.\n\nA venture capital fund cannot be registered under the Investment Company Act. In other words, it must be a private fund and cannot be a business development company(BDC).\n\n\u200cSection 3(c)(7)\nA 3(c)(7) fund involves a private placement to qualified purchasers. While there is no explicit investor limit, a 3(c)(7) fund cannot have more than 1,999 investors to avoid being considered a reporting company under Section 12(g) of the Securities Exchange Act.\n\n\n\nQualified purchasers must meet a higher bar than accredited investors. Qualified purchasers are individuals or family investment units with $5 million or more in investments, or an entity with $25 million or more in investments.\n\n\nSome points to note:\n\n\nKnowledgeable employees of the fund are not counted as beneficial owners under 3(c)(1) and do not need to be qualified purchasers to invest in a 3(c)(7) fund.\n\nFor purposes of the 100 beneficial ownership limit under 3(c)(l), the SEC can integrate\u2014or view as a single fund\u2014similar funds, unless a reasonable investor would consider their interests to be materially different. Section 3(c)(l) funds are not integrated with 3(c)(7) funds, which means this parallel fund structure can be used to maximize the number of investors.\n\n\n\n\n\n\nAll investors are qualihed purchasers\n\n\n\n$5M individual investments,\n$25M entity investments\n\nUp to1,999 QPs permitted\n\nFund regulation (Investment Company Act)\n\n\u200cRegulation of the\u200c\n\nRule 506(b) vs. 506(c)\nCompare the different safe harbors set forth by Rule 506(b) and Rule 506(c) to determine which is right for your fund.\n\nRule 506(b)\n\n\nCan raise unlimited capital\n\n\tCan raise from accredited investors and up to 35 non\u2014 accredited, sophisticated investors with additional disclosures\n\nAccredited investors can self\u2014\ncertify\n\n\tCannot advertise outside network; must have pre\u2014existing, substantive relationship\n\nRule 506(c)\n\nCan raise unlimited capital\n\n\tCan raise from accredited investors only\n\n\tMust take steps to verify that all investors are accredited\n\n\tCan publicly market capital raise to prospective investors\n\nfundraising process\nGenerally, the federal securities laws require every ofTer and sale of a security, including interests in a fund, to be registered with the SEC unless an exemption applies.\nMost venture capital in the United States is raised in private placements through an exemption created under Rule 506 of Regulation D. Rule 506 supplies two pathways to an exempt private placement:\n\nRule 506(b)\nUnder 506(b), fund managers can raise an unlimited amount of capital from an unlimited number of accredited investors (and up to 35  non\u2014accredited, sophisticated investors with enhanced disclosure). Fund managers may not use general solicitation in this type of offering.\n\n\nNote:\n\n\nWhile it's technically possible to include non-accreditedinvestors in VC funds, fund managers almost universally avoid it due to the costs associated with additional disclosure requirements.\n\n\nRule 506(c)\nWith 506(c), fund managers can use general solicitation for offerings. Just like 506(b), fund managers can raise an unlimited amount of capital,\nbut they can only raise from accredited investors. The fund must also take \u201creasonable steps\u201d to verify that all fund investors are accredited\u2014a more burdensome undertaking that requires more than self\u2014certification.\n\n\u200cForm D\nFunds raising capital under 506(b) or 506(c) are required to file a Form D with the SEC no later than 15 days after the first close.\n\n\nNote:\n\n\n\tThe SEC is expected to consider changes to Regulation D that could impact timelines associated with Form D filings, as well as the information collected on the form. Follow Carta's Policy Desk and subscribe to the weekly policy newsletter to stay on top of any changes.\n\n\nBlue sky filings\nIn addition to filing a Form D with the SEC, funds that raise capital under Regulation D will likely have state blue sky filing requirements. Securities offered and sold under Regulation D are exempt from state registration, but most states require notice filings.\n\nRegulation S\nFunds can use Regulation S to raise capital outside of the U.S. Offerings under Regulation S are generally limited to non\u2014U.S. persons, and the fund and its affiliates are prohibited from undertaking directed selling efforts in the U.S.\n\n\nPolicy outlook:\n\n\n\tCongress and the SEC are expected to consider reforms to make it easier for funds to raise capital under Regulation D, including expanding accredited investor on\u2014ramps. Follow Carta's Policy Desk and subscribe to the weekly policy newsletter to stay on top of any changes.\n\n\u200cRegulation of\u200c\nthe fund manager\nUnder the Investment Advisers Act, any person who provides advice to others regarding securities in exchange for compensation is an investment adviser. Most VC fund managers meet this definition.\n\nPrivate fund advisers, including VC fund managers, must register with the SEC as an investment adviser unless they qualify as an exempt reporting adviser (ERA) or do not meet certain asset requirements.\n\nThe size of the adviser's assets under management (AUM) will determine whether the adviser will register with the SEC or a state securities regulator.\n\nSize of assets under management by the adviser\n\n\n\n\n\n\nSmall adviser (less than $25M) Mid\u2014size adviser ($25M\u2014ll0M) Large adviser (more than $ll0M)\nRegulated by\n\nState\n\nState or SEC\n\nSEC\n\n \n\n\u200cRegistered investment advisers\nRegistered investment advisers (RIAs) have heavier compliance burdens than exempt reporting advisers. On top of the the ERA compliance requirements, RIAs are subject to additional Advisers Act requirements, which include:\n\n\n\tEnhanced filing requirements: RIAs are required to he additional information on Form ADV (Part 2Afund brochure) and Form PF.\n\nCompliance: RIAs are required to adopt written policies and procedures designed to prevent violations of the Advisers Act. These policies and procedures must be reviewed annually, and the annual review must be documented in writing. RIAs must also have a dedicated chief compliance officer and compliance program tailored to the business.\n\nRecordkeeping rule: RIAs are required to maintain extensive books and records of their business, including records of all written communications and documentation to support other Adviser Act compliance requirements.\n\nCode of ethics: RIAs must establish and enforce a written code of ethics that outlines responsibilities and standards of conduct, including with respect to personal trading by employees and disclosure of conflicts of interest.\n\nCustody and annual audit requirements: RIAs are subject to the Adviser Act's custody rule obligations and audit requirements.\n\n\tMarketing rule: RIAs must disclose net performance metrics alongside gross performance metrics, whether they're reporting on single investments or a group of investments.\n\nLimitations around performance-basedcompensation: For RIAs to receive performance-based compensation, fund investors must be qualified clients.\n\nPolicy outlook: Under the previous administration, the SEC proposed a number of changes that could have significantly increased RIA compliance obligations, including limiting the privately offered securities exemption under the custody rule, heightened cybersecurity and vendor due diligence, and new ESG disclosures, among others. We do not expect the Trump administration to take the same approach, and could see efforts to provide clarity or streamline compliance obligations for RIAs. Subscribe to Carta's Policy Weekly newsletter for updates.\n\u200cExempt reporting advisers\nFund managers can avoid costly regulatory and compliance requirements associated with being an RIA if they meet certain requirements to be an exempt reporting adviser (ERA):\n\n\nPrivate fund adviser exemption: The fund manager solely advises private funds and the total AUM overseen by the fund manager is less than $150 million.\n\n\tVenture capital adviser exemption: This exemption is available to fund managers who solely advise venture capital funds. Unlike the private fund exemption, VC fund managers can raise an unlimited amount of capital without being required to register with the SEC.\n\n\nA venture capital fund has its own special requirements:\n\n\n\tA venture capital fund must hold at least 80% of assets in \u201cqualifying investments\u201d \u2014cash and equity securities acquired directly from portfolio companies. In other words, VC funds can invest in non\u2014qualifying investments (fund\u2014of-fund investments, digital assets, secondary transactions, etc.) but they are limited to no more than 20% of capital.\n\nA venture capital fund cannot be substantially leveraged: To maintain their exemption, VC funds can't leverage more\nthan 15% of their AUM and outstanding loans must be repaid within 120 days of borrowing.\n\nA venture capital fund cannot provide redemption rights except in limited, extraordinary circumstances.\n\nA venture capital fund must pursue a venture investment strategy.\n\nA venture capital fund cannot be registered under the Investment Company Act. In other words, it must be a private fund and cannot be a business development company(BDC).\n\n\nPer SEC guidance, a fund must be eligible to register with the SEC to be eligible to file with the SEC as an ERA. This means that private fund advisers who otherwise meet the venture capital or private fund adviser exemption will not be able to Ale with the SEC as an ERA unless they have over $25 million in AUM, generally speaking. They would instead be subject to state law requirements, and many states have adopted exemptions that mirror the federal private fund adviser exemptions. But even if a fund manager does not Ale as an ERA with the SEC, \u00f1duciary duties and Advisers Act obligations still apply.\n\n\n\u200cAm I an ERA?\nUse the flow chart below determine if you're an exempt reporting adviser (ERA).\n\n\n\nYes\nNo\nYou must register as\naninvestment adviser\nNo\n\nAcross all funds you manage, are assets under management <$150M?\n\n\nYou're an ERA under the private fund adviser exemption\n\nDo you manage only private funds?\n\nYou only advise venture capital funds\n\nNo\n\nYes\n\nYes\n\u200cCOFTO\u200c\n\n\n  compliance\nchecklist\nWhile ERAs are not subject to SEC registration, \u201cexempt\u201d is somewhat of a misnomer. In addition to filing basic information with the SEC, ERAs must comply with certain provisions of the Advisers\nAct and can be examined by the SEC.\n\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\n\nPay-to-play\n\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act CA diversity disclosure\n\nReporting\n\n\nrequlrements\n\n\nForm ADV\n\n\nERAs are not required to register with the SEC, but they are required to file certain information on Form ADV. Form ADV is the uniform document used by investment advisers to register with both the SEC and state securities authorities. This is the same form that RIAs use to register, but ERAs are only required to complete certain items in Part 1A and not the entire brochure.\n\nPART 1A INFORMATIO N INCLUDES :\n\n\n\nBasic identifying information, such as legal name, and principal ofhce and place of business\n\nFund size\n\nOther business interests\n\nDisciplinary history\n\n\nControl persons\n\n\nPROCESS:\n\n\nForm ADV is electronically filed and publicly available on FINRA's IARD system.\n\n\tThe initial Form ADV must be filed with the SEC within 60 days from when the advisory relationship with the first fund begins, which is typically the first close.\n\n\nForm ADV must be updated at least annually within 90 days after the end of the adviser's fiscal year. More frequent updates may be required in the event of material developments listed in form instructions.\n\n\nERAs who claim the private fund exemption (AUM < $150 million) must update their valuations annually to show the exemption is still valid.\n\nIf the AUM increases beyond $150 million, the adviser must register and become an RIA within six months.\n\n\nERAs claiming the venture capital exemption do not need to confirm AUM because the VC exemption has no threshold.\n\nState registration and blue sky filings\nStates generally require advisers whose principal place of business is in that state to make notice filings and pay fees. This can generally be done by selecting the relevant states on Form ADV so that the state automatically receives a copy. Most states have adopted state law exemptions that mirror the federal exemptions for venture capital advisers, though state\u2014specific rules vary. ERAs should check their state's laws to determine if any additional compliance requirements apply.\n\nThe compliance obligations that apply to federal ERAs will still apply to unregistered or state\u2014registered private fund advisers (including small private fund advisers who may not have any filing requirements).\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\nPay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\nPrivacy\nCorporate Transparency Act CA diversity disclosure\n\nFiduciary obligations\n\nand the Advisers Act\n\n\nAs investment advisers, fund managers owe fiduciary obligations to their clients, which means the fund manager is required to put\n\n\n\nclient interests (i.e., those of the private fund and its investors) above their own. As a fiduciary, the adviser must make full disclosure of all material facts relating to the advisory relationship, including full disclosure of all material conflicts of interest. These fiduciary obligations cannot be waived through disclosure or investor consent. The SEC recently reafhrmed these fiduciary obligations as part of its Private Fund Adviser rules.\n\nWhile a number of the provisions of the Advisers Act do not apply to ERAs, there are certain requirements that do apply to venture capital fund managers, in addition to broader fiduciary responsibilities.\n\n\n\nAnti-fraud requirements\n\nAll investment advisers\u2014ERAs and RlAs\u2014are subject to the Advisers Act's anti\u2014fraud prohibitions under Section 206 and Rule 206(4)\u20148. These rules prohibit advisers from making false or misleading statements, omitting material facts, or otherwise defrauding current or prospective investors in the funds they manage. Examples of conduct that have been found\n\nto violate the anti\u2014fraud rules includes: providing misleading performance metrics, promising guaranteed returns, making inaccurate management fee disclosures, and failing to disclose conflicts of interest.\n\n\n\nThe SEC has increasingly focused on conflicts and fees, and has interpreted its anti\u2014fraud enforcement broadly. To ensure compliance with the anti\u2014fraud provisions, a fund manager should:\n\n\nReview whether current operating practices align with requirements in fund documents, particularly around calculation of fees and valuation practices\n\nEnsure all material conflicts of interest are disclosed\n\nEnsure provisions in fund offering documents and other fund documents are aligned and there is no confusion or conflict.\n\nThe bottom line for anti\u2014fraud requirements: Do what you say you are going to do and disclose your conflicts.\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\n\nPay-to-play\n\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\nPay-to-play\n\n\n\nERAs are subject to Advisers Act requirements that prohibit investment advisers from engaging in pay\u2014to\u2014play(P2P). In other words, an adviser can't be compensated for services provided to a government entity or official after making political contributions to the same. Fund managers should take note if federal, state, or local government entities\u2014including pension plans and university endowments\u2014are investors or are being solicited as potential investors in the fund.\n\nHere is what you need to know:\n\n\n\n\n\n\nERAs and their associates are subject to a two\u2014year cooling off period after making a contribution to an official or government entity before the adviser can receive compensation for advisory services provided to that ofhcial or entity. In addition to direct contributions, ERAs cannot solicit or coordinate campaign contributions for government officials or entities to whom the adviser is providing\nor is seeking to provide services.\n\nP2P violations are strict liability, meaning no quid pro quo or other intent is necessary to be held liable for a violation.\n\n\n\n\tThe SEC is pursuing P2P violations and has brought several cases recently.\n\n\nMNPI policies\nAll investment advisers\u2014RlAs and ERAs\u2014are required to establish, maintain, and enforce written policies and procedures designed to prevent the misuse of material nonpublic information (MNPI)\n\n\n\n\nby the fund manager or associated persons.\n\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations\nRegistering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\n\n\u200cAdditional regulatory considerations\n\n\nSEC examinations and enforcement\n\n\nEven though they are not registered, ERAs are subject to regulatory review by the SEC's Division of Examinations. ERAs can be examined for cause or as part of the SEC's routine examination program.\nSEC examinations staff outline yearly exam priorities to highlight\n\nareas of focus and issue risk alerts to drive attention to specific matters.\n\n\nSEC staff has historically not conducted ERA exams on a regular basis, though that posture has shifted as more scrutiny is applied to the growing private fund industry.\n\nWhat Fund Managers need to know:\n\n\n\nThe SEC has been increasing its scrutiny of private fund managers, including venture capital fund managers, and this scrutiny will only increase as new regulatory requirements are implemented. Current and aspiring VC fund managers should understand their regulatory obligations, put policies and procedures in place to meet those compliance obligations, and ensure they are abiding by terms in LPAs and other fund agreements. This is particularly important in areas the SEC has flagged through a risk alert or exam priority, or where the Commission has focused recent rulemaking efforts.\n\n\n\nThe SEC's 2025 Exam Priorities, which were announced under former SEC Chair Gary Gensler, focus on a number of areas that will impact ERAs, including:\n\n\nPortfolio management risks in light of current market conditions, including the impact on valuation and how this may impact fee and expense calculation\n\nDue diligence practices around prospective portfolio companies\n\n\tCompliance with custody, audit, and reporting requirements under Form ADV and Form PF\n\nFiduciary obligations\n\nNew SEC leadership will likely shift focus away from private fund managers as compared to the prior administration, but we expect the agency to continue to pursue fraud and rigorously enforce compliance and fiduciary obligations. The SEC will also be responsible for examining private funds\u2014ERAs and RlAs\u2014for compliance with new AML requirements.\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations\n\nRegistering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act CA diversity disclosure\n\nRegistering as an RIA\n\n\n\n\nWith the additional regulatory requirements and added compliance costs and burdens, why would a VC fund manager consider registering as an investment adviser?\n\n\nAdditional flexibility\nVenture capital funds are fairly limited in the types\nof investments they can make, and VC ERAs can only advise venture funds. Private fund ERAs are limited to\n$150M AUM. SEC registration may make sense for venture firms looking to explore new business lines, different asset classes, or joint ventures.\n\n\n\nInvestor demand\nGiven the additional regulatory requirements, some investors may be more willing to invest in a fund that is advised by an RIAvs. an ERA.\n\n\n\n\n\n\n\n\nVC funds will have to decide whether to register by balancing regulatory requirements and costs with what works best for their respective business models. The SEC has adopted or proposed a number of new compliance obligations for private fund advisers that will significantly impact RIAs more than ERAs. The cumulative burden of these expected regulatory changes, in addition to heightened scrutiny, could be prohibitive for funds that may have been considering registration\n\n\n\n\nto pursue new business opportunities.\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\nOther compliance\n\nobligations\n\n\nKnow your customer / Anti-money laundering considerations\n\n\nMost funds incorporate know\u2014your\u2014customer/anti\u2014money laundering protocols in their operations, but beginning in January 2026, fund managers will have to comply with a formal regulatory regime.\n\n\n\n\nThe Financial Crimes Enforcement Network(FinCEN) finalized new rules to apply its anti\u2014money laundering/countering the financing of terrorism (AML/CFT) requirements to investment advisers, including private equity and venture capital fund advisers. This rule aims to address illicit financing threats involving investment advisers and raises concerns that VC funds, in particular, have been a haven for illicit proceeds and are used by foreign actors to access critical technologies.\n\n\nNew compliance obligations for private funds include:\n\n\n\n\nDevelop and implement \u201crisk\u2014based\u201d AML program, which includes internal controls and policies, designated AML officer, compliance stafhng and training, routine independent audits, and ongoing customer due diligence\n\nFile suspicious activity reports (SARs) with FinCEN to report suspicious transactions over $5,000\n\nRecordkeeping with respect to transmittal of funds\n\n\n\tComply with other Bank Secrecy Act (BSA) obligations that apply to financial institutions\n\n\nThe SEC will be responsible for examining private fund RIAs and ERAs for compliance with the new AML requirements.\n\n\n\nWhile many advisers have some AML protocols in place, this formal regulatory regime will shift the standard, imposing significant compliance obligations particularly for smaller private fund managers. Exempt reporting advisers (ERAs), who are currently not subject to these types of regulatory obligations and exam scrutiny, will bear the same compliance burden of larger, well\u2014resourced  SEC\u2014registered investment advisers (RIAs). This will create a disproportionate compliance cost and burden for smaller fund advisers.\n\nThese rules are set to become effective on January 1, 2026.\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\n\nPay-to-play\n\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\nCA diversity disclosure\n\nPrivacy\n\n\n\nWhile RIAs are subject to privacy requirements speci\u00f1ed under the Advisers Act (Regulation S\u2014P), ERAs must comply with data privacy and security requirements implemented by the Federal Trade Commission under the Gramm-Leach-BIiIey Act. The FTC requires ERAs to develop, implement, and maintain comprehensive information security programs that identify risks to security, con\u00f1dentiality, and customer information and contain safeguards for protecting nonpublic personal information. ERAs must send initial privacy notices to investors along with standard fund documents describing their privacy and procedures. ERAs should routinely monitor and test privacy safeguards and appoint an individual responsible for monitoring.\n\n\n\n\nCorporate Transparency Act reporting requirements\n\n\n\nBeginning January 1, 2024, new reporting requirements took effect under the Corporate Transparency Act . Unless an exemption applies, entities formed or registered after this date are required to disclose beneficial ownership information (BOI) to FinCEN within 90 days; existing entities have to he an initial report by January 1, 2025, though these deadlines have shifted due to court and administrative actions. As of this writing, CTA compliance is not being enforced against U.S. persons, though this issue remains fluid and could shift again.\n\n\nCTA exemptions\n\nSEC-registered investment advisers\n\nVenture capital fund advisers\n\nPooled investment vehicles operated or advised by RIAs or venture capital fund advisers\n\n\nLarge U.S. operating companies with 20+ full-time employees and $5 million in revenue\n\n\nEntities wholly owned or controlled by an exempt entity\n\n\n\nGenerally speaking, many private funds and private fund advisers who are registered with the SEC or meet the requirements of the venture capital adviser exemption will be exempt from CTA reporting. However, there remains uncertainty around the scope of these exemptions. Notably, ERAs that manage small private funds (<$150M) but do not meet the venture capital exemption must comply with CTA reporting requirements. Consequently, entities like management companies, special purpose vehicles, and co\u2014investment vehicles may still be subject to BOI reporting requirements. Early\u2014stage portfolio companies may also be subject to CTA reporting requirements. Fund managers should consult with counsel to determine if any CTA filing obligations exist with respect to their funds.\n\n\nPolicy update:\n\n\n\tOn March 2, 2025, the Treasury Department announced it will not enforce the beneficial ownership filing requirements for U.S. persons and companies at this time. FinCEN plans to provide new guidance on compliance for foreign entities. This situation remains fluid, and additional legal challenges may arise. Keep up to date with the latest actions here.\n\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\n\nCalifornia VC diversity disclosure requirements\n\n\n\nIn 2025, California enacted legislation aimed at increasing transparency around diversity in the venture capital ecosystem and promoting more inclusive investments through disclosures. Under the new requirements, which are set to take effect March 2026, VC funds with a nexus to California will need to collect and report demographic information about the portfolio company founders in which they invest as well as investment information to the California Department of Financial Protection and Innovation (DFPI) on an annual basis.\n\nCovered entities\n\n\n\nThe new law applies to VC investors, VC funds, or VC operating companies that are primarily engaged in the business of financing or investing in startup, early\u2014stage, or emerging growth companies over which California has some jurisdiction, as determined by one of the following factors:\n\n\n\nThe company is headquartered in CA.\n\nThe company has a significant presence or operations in CA.\n\n\tThe company invests in businesses that are located in or have significant operations in CA.\n\n\n\tThe company solicits or receives investments from CA residents. In other words, most VC funds will fall under this regime.\n\n\nReporting requirements\n\n\nDemographic data: VC funds must report demographic information for the founding teams of the portfolio companies in which the fund invested the prior calendar year. Such information includes race, gender identity, LGBTQ+ identity, and disability or veteran status,\nand must be reported on an aggregated and anonymized basis.\n\nFunds must collect this information through a standardized survey provided to founders post\u2014investment, though founders can decline to participate.\n\nInvestment data: VC funds must also report the total amount\n\n\ninvested in primarily diverse founding teams over the past calendar year, including as a percentage of the total venture capital investments they made.\n\n\nPublic reporting: The law requires DFPI to publish each report on its website, which means information related to investments that is not currently public will soon be made accessible.\n\nFailure to report: VC firms that fail to file timely reports will have 60 days after receiving notice from DFPI to file. After that time period, the state could pursue additional remedies, including stiff monetary penalties of up to $5,000 per day, for noncompliance.\n\nImplementation\nVenture capital firms will have to comply with the new diversity reporting requirements beginning in March 2026, which means VC funds will need to collect this information for investments made beginning in 2025. This law may still face legal challenges or be delayed further to address implementation issues, but fund managers should start assessing their compliance functions in preparation for these upcoming reporting obligations.\n\ncarta\n\n\nDISCLOSURE: This communication is on behalf of eshares Inc., d/b/a Carta Inc. (\"Carta\"). This communication is for informational purposes only, and contains general information only. Carta is not, by means of this communication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services.\nThis publication is not a substitute for such professional advice or services nor should it be used as a basis for any decision or action that may affect your business or interests. Before making any decision or taking any action that may affect your business or interests, you should consult a qualified professional advisor. This communication is not intended as a recommendation, offer or solicitation for the purchase or sale of any security. Carta does not assume any liability for reliance on the information provided herein.\n02025 eshares, Inc. dba Carta, Inc. (\"Carta\"). All rights reserved. Reproduction prohibited.]]>\n    \n\u200cCOFTO\n\n\nVC regulatory\nplaybok\nThe VC regulatory landscape is changing. Are you up to date?\n\n\n\nCOFTO\n\n\u200cVC regulatory playbook\nUpdated March 2025\n\nAs regulatory scrutiny increases on private funds\u2014and private markets more generally\u2014Carta has put together a playbook that lays out the regulatory landscape, compliance requirements, and additional considerations for fund managers to consider as they navigate the evolving private market regulatory landscape.\n\n\n\nI  Regulation of the private fund\n\n\n\n\n\nRegulation of the fundraising process\n\n\n\n\nRegulation of the fund manager\n\n\n\nERA compliance checklist\n\n\n\n\nAdditional regulatory considerations\n\nPrivate fund regulation: the basics\nThere are three categories of regulation all venture capital advisers should be aware of:\n\n\nRegulation of the fund (Investment Company Act)\n\nRegulation of the fund manager(Investment Advisers Act)\n\nRegulation of the fundraising process\nWe\u2019ll cover each of the three areas in depth, and provide answers to some of the frequently asked questions below.\n\n\n\nFund regulation\n\n\nDo I need to register my fund?\n\nWhat are Section 3(c)(l) and Section 3(c)(7)?\n\nWhat are the limits on registration\nexemptions?\n\nWho can invest in registration\u2014\nexempt funds?\nFundraising regulation\n\nWhat is Regulation D?\n\nWhat are Rule 506(b) and Rule 506(c)?\n\nCan I advertise my fund offering?\n\nWhat is Form D and when do I file it?\nFund manager regulation\n\n\tDo I need to register as an investment adviser?\n\nWhat is Form ADV and when do I file it?\n\nWhat regulatory obligations do exempt reporting advisers (ERAs) have?\n\n\nThis guide is not meant to cover every legal obligation or be a substitute for legal advice, but rather serve as an informational guide\nto legal and regulatory compliance requirements. You should discuss with your own legal counsel other factors that may apply to your specific circumstances to ensure compliance.\n\n\u200cRegulation of the  fund\u200c\nA fund must register with the SEC as an investment company unless it meets the criteria for an exemption. Venture capital funds rely\non two exemptions to avoid SEC registration:\n\n\nSection 3(c)(l)\n\nSection 3(c)(7)\n \n\nSection 3(c)(1)\nA 3(c)(l) fund involves a private placement by a fund that will have no more than 100 beneficial owners who are accredited investors.\n\nCounting beneficial owners: As a default, one individual or entity will count as one LP. But in certain instances,\nthe SEC will \u201clook through\u201d an investment vehicle or entity for purposes of counting its underlying beneficial owners. These include:\n\n\nLP entities created by their members for the specific purpose of investing in the fund\n\nLP entities investing 10% or more of the fund voting assets\n\nLP entities investing 40% or more of the LP's assets into a single fund\n\nQualifying \nventure capital funds\nCongress created a special category of 3(c)(1) funds known as a \u201cqualifying venture capital fund\u201d that can have up to 250 beneficial owners if the fund is under $12 million and meets the definition of a venture capital fund.\n\nA venture capital fund has its own special requirements:\n\n\n\n\tA venture capital fund must hold at least 80% of assets in \u201cqualifying investments\u201d \u2014 cash and equity securities acquired directly from portfolio companies. In other words, VC funds can invest in non\u2014qualifying investments\u2014fund\u2014of\u2014fund investments, digital assets, secondary transactions, etc.\u2014but they are limited\nto no more than 20% of capital.\n\nA venture capital fund cannot be substantially leveraged: To maintain their exemption, VC funds can't leverage more than 15% of their AUM and outstanding loans must be repaid in120 days of borrowing.\n\nA venture capital fund cannot provide redemption rights except in limited, extraordinary circumstances.\n\nA venture capital fund must pursue a venture investment strategy.\n\nA venture capital fund cannot be registered under the Investment Company Act. In other words, it must be a private fund and cannot be a business development company(BDC).\n\n\u200cSection 3(c)(7)\nA 3(c)(7) fund involves a private placement to qualified purchasers. While there is no explicit investor limit, a 3(c)(7) fund cannot have more than 1,999 investors to avoid being considered a reporting company under Section 12(g) of the Securities Exchange Act.\n\n\n\nQualified purchasers must meet a higher bar than accredited investors. Qualified purchasers are individuals or family investment units with $5 million or more in investments, or an entity with $25 million or more in investments.\n\n\nSome points to note:\n\n\nKnowledgeable employees of the fund are not counted as beneficial owners under 3(c)(1) and do not need to be qualified purchasers to invest in a 3(c)(7) fund.\n\nFor purposes of the 100 beneficial ownership limit under 3(c)(l), the SEC can integrate\u2014or view as a single fund\u2014similar funds, unless a reasonable investor would consider their interests to be materially different. Section 3(c)(l) funds are not integrated with 3(c)(7) funds, which means this parallel fund structure can be used to maximize the number of investors.\n\n\n\n\n\n\nAll investors are qualihed purchasers\n\n\n\n$5M individual investments,\n$25M entity investments\n\nUp to1,999 QPs permitted\n\nFund regulation (Investment Company Act)\n\n\u200cRegulation of the\u200c\n\nRule 506(b) vs. 506(c)\nCompare the different safe harbors set forth by Rule 506(b) and Rule 506(c) to determine which is right for your fund.\n\nRule 506(b)\n\n\nCan raise unlimited capital\n\n\tCan raise from accredited investors and up to 35 non\u2014 accredited, sophisticated investors with additional disclosures\n\nAccredited investors can self\u2014\ncertify\n\n\tCannot advertise outside network; must have pre\u2014existing, substantive relationship\n\nRule 506(c)\n\nCan raise unlimited capital\n\n\tCan raise from accredited investors only\n\n\tMust take steps to verify that all investors are accredited\n\n\tCan publicly market capital raise to prospective investors\n\nfundraising process\nGenerally, the federal securities laws require every ofTer and sale of a security, including interests in a fund, to be registered with the SEC unless an exemption applies.\nMost venture capital in the United States is raised in private placements through an exemption created under Rule 506 of Regulation D. Rule 506 supplies two pathways to an exempt private placement:\n\nRule 506(b)\nUnder 506(b), fund managers can raise an unlimited amount of capital from an unlimited number of accredited investors (and up to 35  non\u2014accredited, sophisticated investors with enhanced disclosure). Fund managers may not use general solicitation in this type of offering.\n\n\nNote:\n\n\nWhile it's technically possible to include non-accreditedinvestors in VC funds, fund managers almost universally avoid it due to the costs associated with additional disclosure requirements.\n\n\nRule 506(c)\nWith 506(c), fund managers can use general solicitation for offerings. Just like 506(b), fund managers can raise an unlimited amount of capital,\nbut they can only raise from accredited investors. The fund must also take \u201creasonable steps\u201d to verify that all fund investors are accredited\u2014a more burdensome undertaking that requires more than self\u2014certification.\n\n\u200cForm D\nFunds raising capital under 506(b) or 506(c) are required to file a Form D with the SEC no later than 15 days after the first close.\n\n\nNote:\n\n\n\tThe SEC is expected to consider changes to Regulation D that could impact timelines associated with Form D filings, as well as the information collected on the form. Follow Carta's Policy Desk and subscribe to the weekly policy newsletter to stay on top of any changes.\n\n\nBlue sky filings\nIn addition to filing a Form D with the SEC, funds that raise capital under Regulation D will likely have state blue sky filing requirements. Securities offered and sold under Regulation D are exempt from state registration, but most states require notice filings.\n\nRegulation S\nFunds can use Regulation S to raise capital outside of the U.S. Offerings under Regulation S are generally limited to non\u2014U.S. persons, and the fund and its affiliates are prohibited from undertaking directed selling efforts in the U.S.\n\n\nPolicy outlook:\n\n\n\tCongress and the SEC are expected to consider reforms to make it easier for funds to raise capital under Regulation D, including expanding accredited investor on\u2014ramps. Follow Carta's Policy Desk and subscribe to the weekly policy newsletter to stay on top of any changes.\n\n\u200cRegulation of\u200c\nthe fund manager\nUnder the Investment Advisers Act, any person who provides advice to others regarding securities in exchange for compensation is an investment adviser. Most VC fund managers meet this definition.\n\nPrivate fund advisers, including VC fund managers, must register with the SEC as an investment adviser unless they qualify as an exempt reporting adviser (ERA) or do not meet certain asset requirements.\n\nThe size of the adviser's assets under management (AUM) will determine whether the adviser will register with the SEC or a state securities regulator.\n\nSize of assets under management by the adviser\n\n\n\n\n\n\nSmall adviser (less than $25M) Mid\u2014size adviser ($25M\u2014ll0M) Large adviser (more than $ll0M)\nRegulated by\n\nState\n\nState or SEC\n\nSEC\n\n \n\n\u200cRegistered investment advisers\nRegistered investment advisers (RIAs) have heavier compliance burdens than exempt reporting advisers. On top of the the ERA compliance requirements, RIAs are subject to additional Advisers Act requirements, which include:\n\n\n\tEnhanced filing requirements: RIAs are required to he additional information on Form ADV (Part 2Afund brochure) and Form PF.\n\nCompliance: RIAs are required to adopt written policies and procedures designed to prevent violations of the Advisers Act. These policies and procedures must be reviewed annually, and the annual review must be documented in writing. RIAs must also have a dedicated chief compliance officer and compliance program tailored to the business.\n\nRecordkeeping rule: RIAs are required to maintain extensive books and records of their business, including records of all written communications and documentation to support other Adviser Act compliance requirements.\n\nCode of ethics: RIAs must establish and enforce a written code of ethics that outlines responsibilities and standards of conduct, including with respect to personal trading by employees and disclosure of conflicts of interest.\n\nCustody and annual audit requirements: RIAs are subject to the Adviser Act's custody rule obligations and audit requirements.\n\n\tMarketing rule: RIAs must disclose net performance metrics alongside gross performance metrics, whether they're reporting on single investments or a group of investments.\n\nLimitations around performance-basedcompensation: For RIAs to receive performance-based compensation, fund investors must be qualified clients.\n\nPolicy outlook: Under the previous administration, the SEC proposed a number of changes that could have significantly increased RIA compliance obligations, including limiting the privately offered securities exemption under the custody rule, heightened cybersecurity and vendor due diligence, and new ESG disclosures, among others. We do not expect the Trump administration to take the same approach, and could see efforts to provide clarity or streamline compliance obligations for RIAs. Subscribe to Carta's Policy Weekly newsletter for updates.\n\u200cExempt reporting advisers\nFund managers can avoid costly regulatory and compliance requirements associated with being an RIA if they meet certain requirements to be an exempt reporting adviser (ERA):\n\n\nPrivate fund adviser exemption: The fund manager solely advises private funds and the total AUM overseen by the fund manager is less than $150 million.\n\n\tVenture capital adviser exemption: This exemption is available to fund managers who solely advise venture capital funds. Unlike the private fund exemption, VC fund managers can raise an unlimited amount of capital without being required to register with the SEC.\n\n\nA venture capital fund has its own special requirements:\n\n\n\tA venture capital fund must hold at least 80% of assets in \u201cqualifying investments\u201d \u2014cash and equity securities acquired directly from portfolio companies. In other words, VC funds can invest in non\u2014qualifying investments (fund\u2014of-fund investments, digital assets, secondary transactions, etc.) but they are limited to no more than 20% of capital.\n\nA venture capital fund cannot be substantially leveraged: To maintain their exemption, VC funds can't leverage more\nthan 15% of their AUM and outstanding loans must be repaid within 120 days of borrowing.\n\nA venture capital fund cannot provide redemption rights except in limited, extraordinary circumstances.\n\nA venture capital fund must pursue a venture investment strategy.\n\nA venture capital fund cannot be registered under the Investment Company Act. In other words, it must be a private fund and cannot be a business development company(BDC).\n\n\nPer SEC guidance, a fund must be eligible to register with the SEC to be eligible to file with the SEC as an ERA. This means that private fund advisers who otherwise meet the venture capital or private fund adviser exemption will not be able to Ale with the SEC as an ERA unless they have over $25 million in AUM, generally speaking. They would instead be subject to state law requirements, and many states have adopted exemptions that mirror the federal private fund adviser exemptions. But even if a fund manager does not Ale as an ERA with the SEC, \u00f1duciary duties and Advisers Act obligations still apply.\n\n\n\u200cAm I an ERA?\nUse the flow chart below determine if you're an exempt reporting adviser (ERA).\n\n\n\nYes\nNo\nYou must register as\naninvestment adviser\nNo\n\nAcross all funds you manage, are assets under management <$150M?\n\n\nYou're an ERA under the private fund adviser exemption\n\nDo you manage only private funds?\n\nYou only advise venture capital funds\n\nNo\n\nYes\n\nYes\n\u200cCOFTO\u200c\n\n\n  compliance\nchecklist\nWhile ERAs are not subject to SEC registration, \u201cexempt\u201d is somewhat of a misnomer. In addition to filing basic information with the SEC, ERAs must comply with certain provisions of the Advisers\nAct and can be examined by the SEC.\n\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\n\nPay-to-play\n\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act CA diversity disclosure\n\nReporting\n\n\nrequlrements\n\n\nForm ADV\n\n\nERAs are not required to register with the SEC, but they are required to file certain information on Form ADV. Form ADV is the uniform document used by investment advisers to register with both the SEC and state securities authorities. This is the same form that RIAs use to register, but ERAs are only required to complete certain items in Part 1A and not the entire brochure.\n\nPART 1A INFORMATIO N INCLUDES :\n\n\n\nBasic identifying information, such as legal name, and principal ofhce and place of business\n\nFund size\n\nOther business interests\n\nDisciplinary history\n\n\nControl persons\n\n\nPROCESS:\n\n\nForm ADV is electronically filed and publicly available on FINRA's IARD system.\n\n\tThe initial Form ADV must be filed with the SEC within 60 days from when the advisory relationship with the first fund begins, which is typically the first close.\n\n\nForm ADV must be updated at least annually within 90 days after the end of the adviser's fiscal year. More frequent updates may be required in the event of material developments listed in form instructions.\n\n\nERAs who claim the private fund exemption (AUM < $150 million) must update their valuations annually to show the exemption is still valid.\n\nIf the AUM increases beyond $150 million, the adviser must register and become an RIA within six months.\n\n\nERAs claiming the venture capital exemption do not need to confirm AUM because the VC exemption has no threshold.\n\nState registration and blue sky filings\nStates generally require advisers whose principal place of business is in that state to make notice filings and pay fees. This can generally be done by selecting the relevant states on Form ADV so that the state automatically receives a copy. Most states have adopted state law exemptions that mirror the federal exemptions for venture capital advisers, though state\u2014specific rules vary. ERAs should check their state's laws to determine if any additional compliance requirements apply.\n\nThe compliance obligations that apply to federal ERAs will still apply to unregistered or state\u2014registered private fund advisers (including small private fund advisers who may not have any filing requirements).\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\nPay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\nPrivacy\nCorporate Transparency Act CA diversity disclosure\n\nFiduciary obligations\n\nand the Advisers Act\n\n\nAs investment advisers, fund managers owe fiduciary obligations to their clients, which means the fund manager is required to put\n\n\n\nclient interests (i.e., those of the private fund and its investors) above their own. As a fiduciary, the adviser must make full disclosure of all material facts relating to the advisory relationship, including full disclosure of all material conflicts of interest. These fiduciary obligations cannot be waived through disclosure or investor consent. The SEC recently reafhrmed these fiduciary obligations as part of its Private Fund Adviser rules.\n\nWhile a number of the provisions of the Advisers Act do not apply to ERAs, there are certain requirements that do apply to venture capital fund managers, in addition to broader fiduciary responsibilities.\n\n\n\nAnti-fraud requirements\n\nAll investment advisers\u2014ERAs and RlAs\u2014are subject to the Advisers Act's anti\u2014fraud prohibitions under Section 206 and Rule 206(4)\u20148. These rules prohibit advisers from making false or misleading statements, omitting material facts, or otherwise defrauding current or prospective investors in the funds they manage. Examples of conduct that have been found\n\nto violate the anti\u2014fraud rules includes: providing misleading performance metrics, promising guaranteed returns, making inaccurate management fee disclosures, and failing to disclose conflicts of interest.\n\n\n\nThe SEC has increasingly focused on conflicts and fees, and has interpreted its anti\u2014fraud enforcement broadly. To ensure compliance with the anti\u2014fraud provisions, a fund manager should:\n\n\nReview whether current operating practices align with requirements in fund documents, particularly around calculation of fees and valuation practices\n\nEnsure all material conflicts of interest are disclosed\n\nEnsure provisions in fund offering documents and other fund documents are aligned and there is no confusion or conflict.\n\nThe bottom line for anti\u2014fraud requirements: Do what you say you are going to do and disclose your conflicts.\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\n\nPay-to-play\n\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\nPay-to-play\n\n\n\nERAs are subject to Advisers Act requirements that prohibit investment advisers from engaging in pay\u2014to\u2014play(P2P). In other words, an adviser can't be compensated for services provided to a government entity or official after making political contributions to the same. Fund managers should take note if federal, state, or local government entities\u2014including pension plans and university endowments\u2014are investors or are being solicited as potential investors in the fund.\n\nHere is what you need to know:\n\n\n\n\n\n\nERAs and their associates are subject to a two\u2014year cooling off period after making a contribution to an official or government entity before the adviser can receive compensation for advisory services provided to that ofhcial or entity. In addition to direct contributions, ERAs cannot solicit or coordinate campaign contributions for government officials or entities to whom the adviser is providing\nor is seeking to provide services.\n\nP2P violations are strict liability, meaning no quid pro quo or other intent is necessary to be held liable for a violation.\n\n\n\n\tThe SEC is pursuing P2P violations and has brought several cases recently.\n\n\nMNPI policies\nAll investment advisers\u2014RlAs and ERAs\u2014are required to establish, maintain, and enforce written policies and procedures designed to prevent the misuse of material nonpublic information (MNPI)\n\n\n\n\nby the fund manager or associated persons.\n\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations\nRegistering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\n\n\u200cAdditional regulatory considerations\n\n\nSEC examinations and enforcement\n\n\nEven though they are not registered, ERAs are subject to regulatory review by the SEC's Division of Examinations. ERAs can be examined for cause or as part of the SEC's routine examination program.\nSEC examinations staff outline yearly exam priorities to highlight\n\nareas of focus and issue risk alerts to drive attention to specific matters.\n\n\nSEC staff has historically not conducted ERA exams on a regular basis, though that posture has shifted as more scrutiny is applied to the growing private fund industry.\n\nWhat Fund Managers need to know:\n\n\n\nThe SEC has been increasing its scrutiny of private fund managers, including venture capital fund managers, and this scrutiny will only increase as new regulatory requirements are implemented. Current and aspiring VC fund managers should understand their regulatory obligations, put policies and procedures in place to meet those compliance obligations, and ensure they are abiding by terms in LPAs and other fund agreements. This is particularly important in areas the SEC has flagged through a risk alert or exam priority, or where the Commission has focused recent rulemaking efforts.\n\n\n\nThe SEC's 2025 Exam Priorities, which were announced under former SEC Chair Gary Gensler, focus on a number of areas that will impact ERAs, including:\n\n\nPortfolio management risks in light of current market conditions, including the impact on valuation and how this may impact fee and expense calculation\n\nDue diligence practices around prospective portfolio companies\n\n\tCompliance with custody, audit, and reporting requirements under Form ADV and Form PF\n\nFiduciary obligations\n\nNew SEC leadership will likely shift focus away from private fund managers as compared to the prior administration, but we expect the agency to continue to pursue fraud and rigorously enforce compliance and fiduciary obligations. The SEC will also be responsible for examining private funds\u2014ERAs and RlAs\u2014for compliance with new AML requirements.\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations\n\nRegistering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act CA diversity disclosure\n\nRegistering as an RIA\n\n\n\n\nWith the additional regulatory requirements and added compliance costs and burdens, why would a VC fund manager consider registering as an investment adviser?\n\n\nAdditional flexibility\nVenture capital funds are fairly limited in the types\nof investments they can make, and VC ERAs can only advise venture funds. Private fund ERAs are limited to\n$150M AUM. SEC registration may make sense for venture firms looking to explore new business lines, different asset classes, or joint ventures.\n\n\n\nInvestor demand\nGiven the additional regulatory requirements, some investors may be more willing to invest in a fund that is advised by an RIAvs. an ERA.\n\n\n\n\n\n\n\n\nVC funds will have to decide whether to register by balancing regulatory requirements and costs with what works best for their respective business models. The SEC has adopted or proposed a number of new compliance obligations for private fund advisers that will significantly impact RIAs more than ERAs. The cumulative burden of these expected regulatory changes, in addition to heightened scrutiny, could be prohibitive for funds that may have been considering registration\n\n\n\n\nto pursue new business opportunities.\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\nOther compliance\n\nobligations\n\n\nKnow your customer / Anti-money laundering considerations\n\n\nMost funds incorporate know\u2014your\u2014customer/anti\u2014money laundering protocols in their operations, but beginning in January 2026, fund managers will have to comply with a formal regulatory regime.\n\n\n\n\nThe Financial Crimes Enforcement Network(FinCEN) finalized new rules to apply its anti\u2014money laundering/countering the financing of terrorism (AML/CFT) requirements to investment advisers, including private equity and venture capital fund advisers. This rule aims to address illicit financing threats involving investment advisers and raises concerns that VC funds, in particular, have been a haven for illicit proceeds and are used by foreign actors to access critical technologies.\n\n\nNew compliance obligations for private funds include:\n\n\n\n\nDevelop and implement \u201crisk\u2014based\u201d AML program, which includes internal controls and policies, designated AML officer, compliance stafhng and training, routine independent audits, and ongoing customer due diligence\n\nFile suspicious activity reports (SARs) with FinCEN to report suspicious transactions over $5,000\n\nRecordkeeping with respect to transmittal of funds\n\n\n\tComply with other Bank Secrecy Act (BSA) obligations that apply to financial institutions\n\n\nThe SEC will be responsible for examining private fund RIAs and ERAs for compliance with the new AML requirements.\n\n\n\nWhile many advisers have some AML protocols in place, this formal regulatory regime will shift the standard, imposing significant compliance obligations particularly for smaller private fund managers. Exempt reporting advisers (ERAs), who are currently not subject to these types of regulatory obligations and exam scrutiny, will bear the same compliance burden of larger, well\u2014resourced  SEC\u2014registered investment advisers (RIAs). This will create a disproportionate compliance cost and burden for smaller fund advisers.\n\nThese rules are set to become effective on January 1, 2026.\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements\n\nPay-to-play\n\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\nCA diversity disclosure\n\nPrivacy\n\n\n\nWhile RIAs are subject to privacy requirements speci\u00f1ed under the Advisers Act (Regulation S\u2014P), ERAs must comply with data privacy and security requirements implemented by the Federal Trade Commission under the Gramm-Leach-BIiIey Act. The FTC requires ERAs to develop, implement, and maintain comprehensive information security programs that identify risks to security, con\u00f1dentiality, and customer information and contain safeguards for protecting nonpublic personal information. ERAs must send initial privacy notices to investors along with standard fund documents describing their privacy and procedures. ERAs should routinely monitor and test privacy safeguards and appoint an individual responsible for monitoring.\n\n\n\n\nCorporate Transparency Act reporting requirements\n\n\n\nBeginning January 1, 2024, new reporting requirements took effect under the Corporate Transparency Act . Unless an exemption applies, entities formed or registered after this date are required to disclose beneficial ownership information (BOI) to FinCEN within 90 days; existing entities have to he an initial report by January 1, 2025, though these deadlines have shifted due to court and administrative actions. As of this writing, CTA compliance is not being enforced against U.S. persons, though this issue remains fluid and could shift again.\n\n\nCTA exemptions\n\nSEC-registered investment advisers\n\nVenture capital fund advisers\n\nPooled investment vehicles operated or advised by RIAs or venture capital fund advisers\n\n\nLarge U.S. operating companies with 20+ full-time employees and $5 million in revenue\n\n\nEntities wholly owned or controlled by an exempt entity\n\n\n\nGenerally speaking, many private funds and private fund advisers who are registered with the SEC or meet the requirements of the venture capital adviser exemption will be exempt from CTA reporting. However, there remains uncertainty around the scope of these exemptions. Notably, ERAs that manage small private funds (<$150M) but do not meet the venture capital exemption must comply with CTA reporting requirements. Consequently, entities like management companies, special purpose vehicles, and co\u2014investment vehicles may still be subject to BOI reporting requirements. Early\u2014stage portfolio companies may also be subject to CTA reporting requirements. Fund managers should consult with counsel to determine if any CTA filing obligations exist with respect to their funds.\n\n\nPolicy update:\n\n\n\tOn March 2, 2025, the Treasury Department announced it will not enforce the beneficial ownership filing requirements for U.S. persons and companies at this time. FinCEN plans to provide new guidance on compliance for foreign entities. This situation remains fluid, and additional legal challenges may arise. Keep up to date with the latest actions here.\n\n\n\n\nChecklist\nREPORTING REQUIREI IENTS\n\nForm ADV\n\nState registration\n\nFIDUCIARY OBLIGATIONS AND THE ADVISERS ACT\n\nAnti\u2014fraud requirements Pay-to-play\nMNPI policies\n\nADDITIONAL CONSIDERATIONS\n\nSEC examinations Registering as an RIA\n\nOTHER COMPLIANCE OBLIGATIONS\n\nKYC/AML\n\nPrivacy\n\nCorporate Transparency Act\n\nCA diversity disclosure\n\n\nCalifornia VC diversity disclosure requirements\n\n\n\nIn 2025, California enacted legislation aimed at increasing transparency around diversity in the venture capital ecosystem and promoting more inclusive investments through disclosures. Under the new requirements, which are set to take effect March 2026, VC funds with a nexus to California will need to collect and report demographic information about the portfolio company founders in which they invest as well as investment information to the California Department of Financial Protection and Innovation (DFPI) on an annual basis.\n\nCovered entities\n\n\n\nThe new law applies to VC investors, VC funds, or VC operating companies that are primarily engaged in the business of financing or investing in startup, early\u2014stage, or emerging growth companies over which California has some jurisdiction, as determined by one of the following factors:\n\n\n\nThe company is headquartered in CA.\n\nThe company has a significant presence or operations in CA.\n\n\tThe company invests in businesses that are located in or have significant operations in CA.\n\n\n\tThe company solicits or receives investments from CA residents. In other words, most VC funds will fall under this regime.\n\n\nReporting requirements\n\n\nDemographic data: VC funds must report demographic information for the founding teams of the portfolio companies in which the fund invested the prior calendar year. Such information includes race, gender identity, LGBTQ+ identity, and disability or veteran status,\nand must be reported on an aggregated and anonymized basis.\n\nFunds must collect this information through a standardized survey provided to founders post\u2014investment, though founders can decline to participate.\n\nInvestment data: VC funds must also report the total amount\n\n\ninvested in primarily diverse founding teams over the past calendar year, including as a percentage of the total venture capital investments they made.\n\n\nPublic reporting: The law requires DFPI to publish each report on its website, which means information related to investments that is not currently public will soon be made accessible.\n\nFailure to report: VC firms that fail to file timely reports will have 60 days after receiving notice from DFPI to file. After that time period, the state could pursue additional remedies, including stiff monetary penalties of up to $5,000 per day, for noncompliance.\n\nImplementation\nVenture capital firms will have to comply with the new diversity reporting requirements beginning in March 2026, which means VC funds will need to collect this information for investments made beginning in 2025. This law may still face legal challenges or be delayed further to address implementation issues, but fund managers should start assessing their compliance functions in preparation for these upcoming reporting obligations.\n\ncarta\n\n\nDISCLOSURE: This communication is on behalf of eshares Inc., d/b/a Carta Inc. (\"Carta\"). This communication is for informational purposes only, and contains general information only. Carta is not, by means of this communication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services.\nThis publication is not a substitute for such professional advice or services nor should it be used as a basis for any decision or action that may affect your business or interests. Before making any decision or taking any action that may affect your business or interests, you should consult a qualified professional advisor. This communication is not intended as a recommendation, offer or solicitation for the purchase or sale of any security. Carta does not assume any liability for reliance on the information provided herein.\n02025 eshares, Inc. dba Carta, Inc. (\"Carta\"). All rights reserved. Reproduction prohibited.]]>\n  \n  \n    Opinion | How to Survive the Trump Years With Your Spirit Intact - The New York Times\n    https://www.nytimes.com/2025/05/01/opinion/trump-faith-humanism.html?smid=nytcore-ios-share&referringSource=articleShare\n    readwise:01jt8ng7a83a4vjbtypn6cfacm\n    Fri, 02 May 2025 14:13:13 +0000\n    New York Times\n    David Brooks\n\n\nCredit: Photo illustration by Balarama Heller for The New York Times\n\n\n\n\n\nBy David Brooks\n\nOpinion Columnist\n\nI had forgotten how exhausting it is to live in Donald Trump\u2019s world. He\u2019s not only a political figure. He creates a psychological and social atmosphere that suffuses the whole culture \u2014 the airwaves, our conversations, our moods.\n\nIf there is one word to define Trump\u2019s atmosphere, it is \u201cpagan.\u201d The pagan values of ancient Rome celebrated power, manliness, conquest, ego, fame, competitiveness and prowess, and it is those values that have always been at the core of Trump\u2019s being \u2014 from his real estate grandiosity to his love of pro wrestling to his king-of-the-jungle version of American greatness.\n\nThe pagan ethos has always appealed to grandiose male narcissists because it gives them permission to grab whatever they want. This ethos encourages egotists to puff themselves up and boast in a way they find urgently satisfying; self-love is the only form of love they know.\n\nThe pagan culture is seductive because it lures you with images of heroism, might and glory. Think of Achilles slaughtering his enemies before the walls of Troy. For a certain sort of perpetual boy, what could be cooler than that? But there is little compassion in this worldview, no concept that humility might be a virtue. There is a callous tolerance of cruelty.\n\nTom Holland is a historian who wrote several fine books of classical history, like \u201cPersian Fire.\u201d Gradually he became more and more appalled by many of those ancient pagans \u2014 those Caesars who could slaughter innocent human beings by the hundreds of thousands while everyone thought this was totally fine.\n\n\u201cThis is a really terrifyingly alien world, and the more you look at it, the more you realize that it is built on systematic exploitation,\u201d Holland told the writer Justin Brierley. \u201cIn almost every way, this is a world that is unspeakably cruel to our way of thinking. And this worried me more and more.\u201d\n\nThe callous tolerance of cruelty is a river that runs through human history. It was dammed up, somewhat, only by millenniums of hard civilizational work. The pagan ethos \u2014 ancient or modern \u2014 always threatens to unleash brutality once again. The pagan ethos does not believe that every human was made in the image of God, does not believe in human equality, is not concerned about preserving the dignity of the poor. It does not care much about the universal feelings of benevolence, empathy and faithfulness toward one another, which, it turns out, are absolutely required for a democracy to function.\n\nWe seem to be entering a pagan century. It\u2019s not only Trump. It\u2019s the whole phalanx of authoritarians, all those greatness-obsessed macho men like Vladimir Putin and Xi Jinping. It\u2019s the tech bros. It\u2019s Christian nationalism, which is paganism with worship music. (If you ever doubt the seductive power of paganism, remember it has conquered many of the churches that were explicitly founded to reject it.)\n\nIf paganism is a grand but dehumanizing value system, I\u2019ve found it necessary, in this increasingly pagan age, to root myself in anything that feels rehumanizing, whether it\u2019s art or literature or learning. I\u2019ve found it incredibly replenishing to be spending time around selfless, humble people who are still doing the work of serving the homeless, mentoring a lost kid who\u2019s joined a gang. These days I need these moral antidotes to feel healthy, resilient and inspired.\n\nIn his book \u201cThe Year of Our Lord 1943,\u201d Alan Jacobs shows how many people during World War II felt the exact same impulse. With the bomb blasts of savagery growing greater in their ears, people like C.S. Lewis and the University of Chicago president Robert Maynard Hutchins recommitted themselves to humane education, to the task of raising generations that would never again fall for the strongman\u2019s seductive promise of domination. That era eventually produced a golden age of public theology \u2014 Reinhold Niebuhr, Abraham Joshua Heschel, Martin Luther King \u2014 and so much else.\n\nMany great moral traditions have always stood against paganism and rebutted it. If paganism stands for manly dominance, Judaism, for example, stands for piety, learning and strictness of conscience. Think of the words so highly valued in Jewish life: chesed (loving kindness), simcha (joy, especially communal joy), anavah (humility), tzedek (justice and charity), limud (study and learning) and kedushah (holiness). Those words lift us up to an entirely different moral realm.\n\nFor the Romans, the cross was a symbol of their power \u2014 their power to crucify. The early Christians took the cross as their symbol, too, but as a symbol for compassion, grace and self-sacrificial love. Christianity is built on a series of inversions that make paganism look pompous and soulless: Blessed are the meek. Blessed are the poor in spirit. The last shall be first. The poor are closer to God than the rich. Jesus was perpetually performing outrageous acts of radical generosity, without calculating the cost.\n\nThe Judeo-Christian ethos showed the world something loftier than paganism. As G.K. Chesterton put it in \u201cThe Everlasting Man,\u201d \u201cOne of the strange marks of the strength of Christianity is that, since it came, no pagan in our civilization has been able to be really human.\u201d\n\nJudaism and Christianity confront paganism with rival visions of the good. The contrast could not be starker. Paganism says: Make yourself the center of the universe. Serve yourself and force others to serve you. The biblical metaphysic says: Serve others, and you will find joy. Serve God, and you will delight in his love.\n\nYou may be a person of faith or a person of no faith, but which moral atmosphere do you want to live in? The cultural atmosphere you immerse yourself in will slowly form who you are. I don\u2019t fault those pagans for sucking down all those muscle-building diet supplements, but I know the kind of nourishment I need these days for the strength of my mind and the health of my soul.\n\nApparently, I\u2019m not alone. Something\u2019s going on in our culture. The decline of religious participation, which was so rapid between 2010 and 2020, seems to have stopped. There has been a relative surge in religious interest among young men. According to research by the evangelical Christian polling group Barna, 66 percent of Americans say they have made a personal commitment to Jesus \u2014 a 12-percentage-point jump since 2021.\n\nSimilar things may be happening in Europe. In France the Catholic Church saw a 45 percent increase in new catechumens this Easter compared with last year, and it has baptized more than 17,000 people, the highest yearly number of entrants in over 20 years. According to an April report by the Bible Institute, the percentage of British adults age 18 to 24 who attend church at least monthly increased from 4 percent in 2018 to 16 percent today, including a 21 percent gain among young men. I\u2019ve been predicting a revival among the religious left, but that seems not to be happening. The Christian resurgence in Britain is not among the progressive mainline denominations; it\u2019s primarily among Catholics and Pentecostals, with two million more people attending church than six years ago.\n\nIn his book \u201cThe Surprising Rebirth of Belief in God,\u201d Brierley notes that the New Atheists were all the rage several years ago, but now it\u2019s unlikely believers like Ayaan Hirsi Ali, Jordan Peterson and the rock star Nick Cave. Vanity Fair recently ran a story headlined \u201cChristianity Was \u2018Borderline Illegal\u2019 in Silicon Valley. Now It\u2019s the New Religion.\u201d\n\nThis movement was already underway before Trump was elected to a second term. It\u2019s a response to a series of gods that failed: The belief that science and tech could solve our quest for meaning. The belief that we can live like hyperindividualists and still experience a sense of communal belonging. The belief that the right B.M.I. could lead to purpose and peace.\n\nAre we on the cusp of a new religious revival? The evidence is still much too flimsy and fresh to justify that kind of sweeping assertion, so color me skeptical. I think it\u2019s more accurate to say that there is currently a great spiritual yearning in the populace, which the religious institutions have not yet risen to meet.\n\nBut I do think we\u2019re on the cusp of a great cultural transition. On the one hand, the eternal forces of dehumanization are blowing strong right now: concentrated power; authoritarianism; materialism; runaway technology; a presidential administration at war with the arts, universities and sciences; a president who guts Christianity while pretending to govern in its name.\n\nOn the other hand, there are millions of humanists \u2014 secular and religious \u2014 repulsed by what they see. History is often driven by those people who are quietly repulsed for a while and then find their voice. I suspect different kinds of humanists will gather and invent other cultural movements. They will ask the eternal humanistic questions: What does it mean to be human? What is the best way to live? What is the nature of the common humanity that binds us together? As these questions are answered in new ways, there will be new cultural movements and forms.\n\nAs the theologian Dallas Willard put it, there has been, over the past decades of neglect, a loss of moral knowledge. We came to a spot in 2024 in which 77 million Americans took a look at Trump\u2019s moral character and didn\u2019t have a problem with what they saw. But the consequences of those character failings are becoming evident in concrete ways.\n\nNew winds are going to blow.\n\nThe Times is committed to publishing a diversity of letters to the editor. We\u2019d like to hear what you think about this or any of our articles. Here are some tips. And here\u2019s our email: letters@nytimes.com.\n\nFollow The New York Times Opinion section on Facebook, Instagram, TikTok, Bluesky, WhatsApp and Threads.]]>\n    David Brooks\n\n\nCredit: Photo illustration by Balarama Heller for The New York Times\n\n\n\n\n\nBy David Brooks\n\nOpinion Columnist\n\nI had forgotten how exhausting it is to live in Donald Trump\u2019s world. He\u2019s not only a political figure. He creates a psychological and social atmosphere that suffuses the whole culture \u2014 the airwaves, our conversations, our moods.\n\nIf there is one word to define Trump\u2019s atmosphere, it is \u201cpagan.\u201d The pagan values of ancient Rome celebrated power, manliness, conquest, ego, fame, competitiveness and prowess, and it is those values that have always been at the core of Trump\u2019s being \u2014 from his real estate grandiosity to his love of pro wrestling to his king-of-the-jungle version of American greatness.\n\nThe pagan ethos has always appealed to grandiose male narcissists because it gives them permission to grab whatever they want. This ethos encourages egotists to puff themselves up and boast in a way they find urgently satisfying; self-love is the only form of love they know.\n\nThe pagan culture is seductive because it lures you with images of heroism, might and glory. Think of Achilles slaughtering his enemies before the walls of Troy. For a certain sort of perpetual boy, what could be cooler than that? But there is little compassion in this worldview, no concept that humility might be a virtue. There is a callous tolerance of cruelty.\n\nTom Holland is a historian who wrote several fine books of classical history, like \u201cPersian Fire.\u201d Gradually he became more and more appalled by many of those ancient pagans \u2014 those Caesars who could slaughter innocent human beings by the hundreds of thousands while everyone thought this was totally fine.\n\n\u201cThis is a really terrifyingly alien world, and the more you look at it, the more you realize that it is built on systematic exploitation,\u201d Holland told the writer Justin Brierley. \u201cIn almost every way, this is a world that is unspeakably cruel to our way of thinking. And this worried me more and more.\u201d\n\nThe callous tolerance of cruelty is a river that runs through human history. It was dammed up, somewhat, only by millenniums of hard civilizational work. The pagan ethos \u2014 ancient or modern \u2014 always threatens to unleash brutality once again. The pagan ethos does not believe that every human was made in the image of God, does not believe in human equality, is not concerned about preserving the dignity of the poor. It does not care much about the universal feelings of benevolence, empathy and faithfulness toward one another, which, it turns out, are absolutely required for a democracy to function.\n\nWe seem to be entering a pagan century. It\u2019s not only Trump. It\u2019s the whole phalanx of authoritarians, all those greatness-obsessed macho men like Vladimir Putin and Xi Jinping. It\u2019s the tech bros. It\u2019s Christian nationalism, which is paganism with worship music. (If you ever doubt the seductive power of paganism, remember it has conquered many of the churches that were explicitly founded to reject it.)\n\nIf paganism is a grand but dehumanizing value system, I\u2019ve found it necessary, in this increasingly pagan age, to root myself in anything that feels rehumanizing, whether it\u2019s art or literature or learning. I\u2019ve found it incredibly replenishing to be spending time around selfless, humble people who are still doing the work of serving the homeless, mentoring a lost kid who\u2019s joined a gang. These days I need these moral antidotes to feel healthy, resilient and inspired.\n\nIn his book \u201cThe Year of Our Lord 1943,\u201d Alan Jacobs shows how many people during World War II felt the exact same impulse. With the bomb blasts of savagery growing greater in their ears, people like C.S. Lewis and the University of Chicago president Robert Maynard Hutchins recommitted themselves to humane education, to the task of raising generations that would never again fall for the strongman\u2019s seductive promise of domination. That era eventually produced a golden age of public theology \u2014 Reinhold Niebuhr, Abraham Joshua Heschel, Martin Luther King \u2014 and so much else.\n\nMany great moral traditions have always stood against paganism and rebutted it. If paganism stands for manly dominance, Judaism, for example, stands for piety, learning and strictness of conscience. Think of the words so highly valued in Jewish life: chesed (loving kindness), simcha (joy, especially communal joy), anavah (humility), tzedek (justice and charity), limud (study and learning) and kedushah (holiness). Those words lift us up to an entirely different moral realm.\n\nFor the Romans, the cross was a symbol of their power \u2014 their power to crucify. The early Christians took the cross as their symbol, too, but as a symbol for compassion, grace and self-sacrificial love. Christianity is built on a series of inversions that make paganism look pompous and soulless: Blessed are the meek. Blessed are the poor in spirit. The last shall be first. The poor are closer to God than the rich. Jesus was perpetually performing outrageous acts of radical generosity, without calculating the cost.\n\nThe Judeo-Christian ethos showed the world something loftier than paganism. As G.K. Chesterton put it in \u201cThe Everlasting Man,\u201d \u201cOne of the strange marks of the strength of Christianity is that, since it came, no pagan in our civilization has been able to be really human.\u201d\n\nJudaism and Christianity confront paganism with rival visions of the good. The contrast could not be starker. Paganism says: Make yourself the center of the universe. Serve yourself and force others to serve you. The biblical metaphysic says: Serve others, and you will find joy. Serve God, and you will delight in his love.\n\nYou may be a person of faith or a person of no faith, but which moral atmosphere do you want to live in? The cultural atmosphere you immerse yourself in will slowly form who you are. I don\u2019t fault those pagans for sucking down all those muscle-building diet supplements, but I know the kind of nourishment I need these days for the strength of my mind and the health of my soul.\n\nApparently, I\u2019m not alone. Something\u2019s going on in our culture. The decline of religious participation, which was so rapid between 2010 and 2020, seems to have stopped. There has been a relative surge in religious interest among young men. According to research by the evangelical Christian polling group Barna, 66 percent of Americans say they have made a personal commitment to Jesus \u2014 a 12-percentage-point jump since 2021.\n\nSimilar things may be happening in Europe. In France the Catholic Church saw a 45 percent increase in new catechumens this Easter compared with last year, and it has baptized more than 17,000 people, the highest yearly number of entrants in over 20 years. According to an April report by the Bible Institute, the percentage of British adults age 18 to 24 who attend church at least monthly increased from 4 percent in 2018 to 16 percent today, including a 21 percent gain among young men. I\u2019ve been predicting a revival among the religious left, but that seems not to be happening. The Christian resurgence in Britain is not among the progressive mainline denominations; it\u2019s primarily among Catholics and Pentecostals, with two million more people attending church than six years ago.\n\nIn his book \u201cThe Surprising Rebirth of Belief in God,\u201d Brierley notes that the New Atheists were all the rage several years ago, but now it\u2019s unlikely believers like Ayaan Hirsi Ali, Jordan Peterson and the rock star Nick Cave. Vanity Fair recently ran a story headlined \u201cChristianity Was \u2018Borderline Illegal\u2019 in Silicon Valley. Now It\u2019s the New Religion.\u201d\n\nThis movement was already underway before Trump was elected to a second term. It\u2019s a response to a series of gods that failed: The belief that science and tech could solve our quest for meaning. The belief that we can live like hyperindividualists and still experience a sense of communal belonging. The belief that the right B.M.I. could lead to purpose and peace.\n\nAre we on the cusp of a new religious revival? The evidence is still much too flimsy and fresh to justify that kind of sweeping assertion, so color me skeptical. I think it\u2019s more accurate to say that there is currently a great spiritual yearning in the populace, which the religious institutions have not yet risen to meet.\n\nBut I do think we\u2019re on the cusp of a great cultural transition. On the one hand, the eternal forces of dehumanization are blowing strong right now: concentrated power; authoritarianism; materialism; runaway technology; a presidential administration at war with the arts, universities and sciences; a president who guts Christianity while pretending to govern in its name.\n\nOn the other hand, there are millions of humanists \u2014 secular and religious \u2014 repulsed by what they see. History is often driven by those people who are quietly repulsed for a while and then find their voice. I suspect different kinds of humanists will gather and invent other cultural movements. They will ask the eternal humanistic questions: What does it mean to be human? What is the best way to live? What is the nature of the common humanity that binds us together? As these questions are answered in new ways, there will be new cultural movements and forms.\n\nAs the theologian Dallas Willard put it, there has been, over the past decades of neglect, a loss of moral knowledge. We came to a spot in 2024 in which 77 million Americans took a look at Trump\u2019s moral character and didn\u2019t have a problem with what they saw. But the consequences of those character failings are becoming evident in concrete ways.\n\nNew winds are going to blow.\n\nThe Times is committed to publishing a diversity of letters to the editor. We\u2019d like to hear what you think about this or any of our articles. Here are some tips. And here\u2019s our email: letters@nytimes.com.\n\nFollow The New York Times Opinion section on Facebook, Instagram, TikTok, Bluesky, WhatsApp and Threads.]]>\n  \n  \n    Here\u2019s What Happened With Tennessee\u2019s Biggest Bills This Session\n    https://nashvillebanner.com/2025/04/24/tennessee-legislative-session-wrap-up/?utm_medium=email&utm_campaign=The%20Flyer%20--%20April%2024%2C%202025&utm_source=ae2961c671\n    readwise:01jt8mqynmbxve3gpbvsr8sx78\n    Fri, 02 May 2025 13:59:57 +0000\n    Nashville Banner\n    \nThe view from the gallery of the Tennessee House of Representatives. Credit: Martin B. Cherry / Nashville Banner \n\nTuesday night, the Tennessee General Assembly adjourned for the year, more or less marking the halfway point of a two-year legislative session.\n\nAt this juncture, some of the most controversial bills around issues like immigration and public safety are waiting to be reprised early next year, while other proposals have been irreversibly shot down or sent to the governor\u2019s desk to be signed into law.\n\nBelow is a summary of where bills previously covered by the Banner stand.\n\nImmigration\n\nPUBLIC SCHOOLS: There was more than one attempt to limit some children\u2019s access to public education based on their immigration status this year. The first related effort was part of Rep. Gino Bulso\u2019s so-called TRUMP Act (HB 145/SB 268), which would prevent those without legal status from \u201cbenefiting from taxpayer money,\u201d including use of banks and charging tuition for public schools. Bulso\u2019s bill failed in the House Banking and Consumer Affairs subcommittee back in March.\n\nA more advanced effort to challenge Supreme Court precedent and allow school districts to charge tuition to, or ultimately deny, undocumented students came from Rep. William Lamberth (R-Portland) and Sen. Bo Watson (R-Hixson) in the form of HB 793/SB 836. Unlike the Bulso bill, this version is permissive and would leave the decision up to each individual school district. After a month of widespread backlash and protests, the Senate narrowly passed this version in April but the bill stalled on the House side as Lamberth sought clarity on whether it would risk more than $1 billion in federal education funding. The bill will almost certainly be reintroduced next year and would not require any additional action from the Senate unless it is amended.\n\nLICENSES AND DMV: Among the flurry of immigration bills introduced this year were a handful targeting identification and driving privileges, which account for most interactions with law enforcement and can result in arrest or deportation. One of the first bills introduced this session was HB 11/SB 5, a proposal by Rep. Scott Cepicky (R-Culleoka) to redesign driver\u2019s licenses to denote a person\u2019s immigration status. While Cepicky withdrew his bill, another HB 749/SB 1086 by Rep. Lee Reeves (R-Franklin) and Sen. Jack Johnson (R-Franklin) invalidating driver\u2019s licenses issued to undocumented migrants by another state passed both chambers, and is awaiting the governor\u2019s signature. Another bill to limit access to licenses \u2014 HB 556/SB 1373 by Watson and Rep. Kip Capley (R-Summertown) \u2014 would have only allowed the state to offer road tests and other DMV services in English, but it failed in the House Transportation Committee.\n\nOTHER IMMIGRATION BILLS FAIL: Even with the appetite for immigration enforcement bills, several efforts failed to materialize, including HB 10/SB 6, an early bill by Rep. Todd Warner (R- Chapel Hill) and Sen. Joey Hensley (R-Hohenwald), that would have required law enforcement to seek federal detainers for those in custody without citizenship and would have required them to transport the individuals to \u201cnearby\u201d sanctuary cities like Chicago if the maximum detainer ran out before the federal government could take custody. It failed in subcommittee. Efforts to defend against increased immigration enforcement, like HB 1202/SB 17 a bill by Sen. Todd Gardenhire (R-Chattanooga) and Rep. Sabi \u201cDoc\u201d Kumar (R-Springfield) that would have limited the scope of a 2024 law requiring law enforcement to cooperate with federal officials in deportation efforts to only impact those charged with criminal offenses failed in the Senate Judiciary Subcommittee.\n\nPublic Safety and Criminal Justice\n\nCONSTITUTIONAL AMENDMENTS: Three proposed constitutional amendments passed their final votes in the legislature, sending them to voters to decide during the 2026 gubernatorial election. One, banning a potential state property tax, and two addressing bail and victims\u2019 rights are in the hands of voters. Another, known as Marsy\u2019s Law, enshrines a victim\u2019s bill of rights, and mirrors at least 12 other states that have adopted the policy since 2008. The final amendment would remove the right to bail for those accused of one of at least 70 different offenses, though that number could grow given the language of the amendment.\n\nDEM GUN BILLS: A pair of similar but unaligned Democratic gun bills were shelved for the year. The first such bill introduced late last year is HB 599/SB 34 by Sen. Heidi Campbell (D-Nashville) and Rep. Bob Freeman (D-Nashville). It would create a misdemeanor for knowingly selling, giving or otherwise transferring a firearm to someone who is prohibited by state or federal law from possessing it. A bill with a similar intent but broader application is HB 947/SB 1191, introduced by new Rep. Shaundelle Brooks (D-Nashville) and Sen. Raumesh Akbari (D-Memphis). Named Akilah\u2019s Law for her deceased son, Brooks\u2019 bill would make a similar charge for transferring a firearm to anyone who has been voluntarily or involuntarily admitted for mental health care in the last five years. Concerns about the scope of the bill and the alignment of the two bills led to both being shelved for the time being.\n\nAnother gun bill by Campbell, HB 2199/SB 1785 or MaKayla\u2019s Law, would have expanded the charge of reckless endangerment to include failure to safely store a firearm in instances where a child under 13 accessed the gun and injured or killed themselves or another child, but failed in the Senate Judiciary Committee.\n\nLETHAL FORCE (HB 856/SB 1407): A bill by Rep. Kip Capley (R-Summertown) and Sen. Joey Hensley (R-Hohenwald) would have expanded when the state allows civilians to use lethal force, making it justified if they believed it was \u201cimmediately necessary to prevent or terminate the other\u2019s actual or attempted trespass; arson; damage to property; burglary; theft; robbery; or aggravated cruelty to animals, serious bodily injury, or death to animals or livestock.\u201d The bill failed in the Senate Judiciary Committee.\n\nSlideshow: 2025 Legislative Session\n\n\n\n\nThe view from the gallery of the Tennessee House of Representatives. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Cameron Sexton is once again elected to be Speaker of the House. Credit: Martin B. Cherry / Nashville Banner\n\n\nActivists hold signs criticizing the State House\u2019s Republican supermajority. Credit: Martin B. Cherry / Nashville Banner\n\n\nAn overflow audience watches the House Education Committee debate on a TV in the hallways of Cordell Hull Building. Credit: Martin B. Cherry / Nashville Banner\n\n\nState Sen. Ferrell Haile (R-Gallatin) speaks during a Senate floor session. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Justin Pearson (D- Memphis) rallies the protesters after a House Education Committee meeting. Credit: Martin B. Cherry / Nashville Banner\n\n\nElla Brinen smiles after her \u201cfoster youth bill of rights\u201d passed a Senate committee.\n\n\nProtesters embrace during a march outside the state Capitol. Credit: Martin B. Cherry / Nashville Banner\n\n\nProtesters chant and pray after being escorted out of the gallery by state troopers. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Justin Pearson (D-Memphis) confronts Rep. Andrew Farmer (R-Sevierville) during a House Criminal Justice Committee meeting. Credit: Martin B. Cherry / Nashville Banner\n\n\nState Sen. Bo Watson (R-Hixson) is all smiles ahead of a Senate floor session. Credit: Martin B. Cherry / Nashville Banner\n\n\nActivists fill the Senate gallery to protest a bill that will allow school districts to ban undocumented immigrants from attending public schools. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. John Ray Clemmons (D-Nashville) argues against HB0793 on April 7, 2025. Credit: Martin B. Cherry / Nashville Banner\n\n\nA signs in protest of Rep. William Lamberth\u2019s HB0793, a controversial bill meant to challenge Supreme Court precedent. Credit: Martin B. Cherry / Nashville Banner\n\n\nProtesters become emotional after a Senate Education Committee meeting, Credit: Martin B. Cherry / Nashville Banner\n\n\nLisa Sherman Luna, executive director of TIRRC, rallies supporters at Speaker Beth Harwell Plaza on March 5, 2025. Credit: Martin B. Cherry / Nashville Banner\n\n\nMacy Fluharty is escorted out of the House gallery on March 17, 2025 after protesting bills limiting the rights of transgender people and immigrants. Credit: Martin B. Cherry / Nashville Banner\n\n\nPratik Dash shouts at state senators who voted in favor of a bill that would allow school districts to ban or charge undocumented children for public education. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Kip Capley (R-Summertown) speaks demonstrably on the House floor. Credit: Martin B. Cherry / Nashville Banner\n\n\nSpeaker of the House Cameron Sexton (R-Crossville). Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Justin Jones (D-Nashville) debates with Rep. Lamberth (R-Portland) on the House floor. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Shaundelle Brooks (D-Hermitage) talks with James Shaw Jr. after her bill, \u201cAkilah\u2019s Law,\u201d passed the House Criminal Justice Committee. Credit: Martin B. Cherry / Nashville Banner\n\n\nThe view from the gallery of the Tennessee House of Representatives. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Cameron Sexton is once again elected to be Speaker of the House. Credit: Martin B. Cherry / Nashville Banner\n\nRep. Cameron Sexton is once again elected to be Speaker of the House. Credit: Martin B. Cherry / Nashville Banner\n\nJAIL DEATHS: Driven by the death of a constituent\u2019s son and ongoing safety concerns in the Trousdale Turner Correctional Center, Sen. Mark Pody (R-Lebanon) introduced a pair of caption bills that he hoped could create new accountability for Tennessee\u2019s private prisons and potentially downgrade Trousdale Turner to a minimum security prison. A final amended version of one of those bills \u2014 HB 114/SB 1115 sponsored in the House by Rep. Clark Boyd (R-Lebanon) \u2014 passed both chambers unanimously. If signed by the governor, the bill will require reporting on deaths from Tennessee\u2019s private prisons. It would require a 10 percent inmate reduction at any facility with a death rate that doubles that of a comparable prison in the state.\n\nAPPEALING CONVICTIONS (HB 601/SB 0256): A bipartisan bill to remove barriers for people convicted of crimes to present new evidence in court to appeal their convictions passed easily in both chambers. The bill by Sen. Todd Gardenhire (R-Chattanooga) and Sen. Bob Freeman (D-Nashville) would make it easier for non-scientific evidence to be heard post-conviction while also allowing District Attorneys to prevent new evidence in cases prosecuted by their office. The bill is awaiting the governor\u2019s signature.\n\nJUVENILE BILLS: A bill (HB 77/SB 237) by Rep. Robert Stevens (R-Smyrna) and Sen. Brent Taylor (R-Memphis), would require juveniles 16 or older to be tried in adult court for their second offense, but had not been heard in subcommittee, meaning the bill could come back next year. An amended version of another Taylor bill \u2014 HB 34/SB 221 \u2014 allows courts to use information from typically sealed juvenile court records in future pretrial decisions for five years after the juvenile offense and requires magistrates to consider juvenile history in bond decisions. This bill has passed both chambers and is awaiting the governor\u2019s signature.\n\nVOYEURISM: After a group of women discovered a Nashville man had  recorded them during sex without their knowledge or consent, they banded together to find all of his victims and promote legislative changes to increase accountability for the crime of unlawful photography. The primary bill to come out of the group\u2019s effort \u2014 sponsored by Freeman and Sen. Jeff Yarbro (D-Nashville) \u2014 is known as the Voyeurism Victims Act and has been signed into law, changing criminal code to start the statute of limitations to prosecute an act of unlawful photography to begin when the victim learns about the crime rather than on the date of the crime. It also allows victims to obtain orders of protection. A related bill by Bulso and Sen. Dawn White (R-Murfreesboro) increases the offense to a felony. It requires offenders to be placed on the sex offender registry, passed both chambers and is awaiting the governor\u2019s signature.\n\nOther Bills\n\nANTI-DIVERSITY: A bill dissolving the state\u2019s Human Rights Commission and moving its related staff under the Attorney General\u2019s control passed and is awaiting the governor\u2019s signature. The bill, HB 910/SB 861 by Rep. Johnny Garrett (R-Goodlettsville) and Sen. John Stevens (R-Huntingdon) will give the HRC staff until July to transition their responsibilities to the AG\u2019s office. The appointed commission will cease to exist, despite concerns from staff about the bill\u2019s origin and impact on the more than 1,000 open discrimination cases. A pair of bills seeking to \u201cdismantle DEI\u201d by prohibiting diversity, equity and inclusion hiring provisions in state government, local governments and publicly funded colleges and universities also passed this session.\n\nCANNABIS CRACKDOWN: Multiple new restrictions on the sale of THCa passed this session, in an effort to close a loophole that effectively legalized most recreational pot sales in the state in 2023. The most significant regulatory bill \u2014 (HB1376/SB 1413) by Lamberth and Sen. Richard Briggs (R-Knoxville) \u2014 is awaiting a signature from the governor, and would prohibit the retail sale of products with a .3 percent or higher combined concentration of THCa and/or Delta 9, change the tax structure for cannabis products and move the regulation of their sales under the Alcoholic Beverage Commission.\n\nAnother bill, HB 1148/SB 1236 by Rep. Ed Butler (R-Rickman) and Sen. Ferrell Haile (R-Gallatin) that would ban THCa and THCp, was not funded in the budget but could be revived next year. An effort by Rep. Aftyn Behn (D-Nashville) and Campbell to further legalize recreational use and use the proceeds for road repairs \u2014 HB 703/SB 921 known as the \u201cpot for potholes\u201d bill \u2014 failed in the House Criminal Justice subcommittee.\n\nHOMELESS ENCAMPMENTS: A bill setting deadlines on the clearing of homeless encampments and disposal of personal belongings passed both chambers and is awaiting the governor\u2019s signature. Despite concerns from service providers who help people experiencing homelessness, HB 197/SB 217, sponsored by Taylor and Rep. Tom Leatherwood (R-Arlington), passed both the House and Senate, setting a 30-day deadline for local authorities and service providers to clear encampments in certain public areas, such as bridges and overpasses. It requires only a 10-day notice before disposing of personal belongings and requires localities to establish encampment clearing protocols with the Tennessee Department of Transportation.\n\nGROCERY TAX: Multiple efforts to repeal the state\u2019s 4 percent tax on groceries stalled again this session. The first version, HB 2/SB 2 brought by Behn and Sen. Charlene Oliver (D-Nashville), would have eliminated the tax to reduce the cost for consumers, replacing it with $250,000 in projected revenue from corporate grocery stores. The effort to revive Behn\u2019s 2024 grocery tax repeal bill stalled again this spring, but was sent to summer study, meaning it could be revived next year. A similar effort, HB 21/SB 1367 by Rep. Elaine Davis (R-Knoxville) and Watson, would repeal the tax but offered no alternative revenue and was placed behind the budget without funding, sending it to a comparable limbo.\n\nREPRODUCTIVE RIGHTS TBD: Lawmakers codified some reproductive rights in a Republican-led proposal protecting access to in vitro fertilization and birth control passed in the Tennessee House on Thursday, despite opposition from dozens of republicans. HB 533/SB 449 by Rep. Iris Rudder (R-Winchester) and Sen. Becky Massey (R-Knoxville) narrowly passed both chambers and is awaiting the governor\u2019s signature, while a group of 11 other Republicans implored the governor to use his first-ever veto to block the bill. A pair of Democratic bills to restore and codify different reproductive rights both predictably failed.\n\nFOSTER CARE BILLS: Lawmakers passed a \u201cfoster care bill of rights,\u201d led by former foster youth, enshrining rights to things like school, housing, medical care and reliable contact with a trusted adult. While it was sponsored by Haile and Rep. Mary Littleton, HB 1359/ SB1015 was written by 19-year-old former foster child Ella Brinen and passed both chambers unanimously. It\u2019s now awaiting the governor\u2019s signature. Another bill to require more transparency in how federal dollars intended for foster children are spent by the department failed in the House Judiciary Committee earlier this month. The bill, HB 1131 / SB 1331 by Yarbro and Rep. Antonio Parkinson (D-Memphis) was spurred by reports of the Department of Children\u2019s Services claiming million of dollars intended for individual foster children.\n\nSCHOOL PHONE BAN: In an effort to curb classroom distractions and cyberbullying, the legislature passed HB 932/SB. 897, a bill by Rep. Rebecca Alexander (R-Jonesborough) and Haile, requiring school boards to create cell phone ban policies, has been signed into law by the governor. The new law, which takes effect on July 1, requires each local education authority to develop a policy banning the use of personal devices in the classroom, including cell phones, tablets, and laptops. Each body can develop a specific policy defining whether devices are allowed on school grounds, whether they can be used during non-instructional times such as lunch breaks, and what the emergency contact protocol will be for students and parents.\n\nCorrection: An earlier version of this story contained an incorrect number for a foster care bill sponsored by Sen. Jeff Yarbro and Rep. Antonio Parkinson.]]>\n    \nThe view from the gallery of the Tennessee House of Representatives. Credit: Martin B. Cherry / Nashville Banner \n\nTuesday night, the Tennessee General Assembly adjourned for the year, more or less marking the halfway point of a two-year legislative session.\n\nAt this juncture, some of the most controversial bills around issues like immigration and public safety are waiting to be reprised early next year, while other proposals have been irreversibly shot down or sent to the governor\u2019s desk to be signed into law.\n\nBelow is a summary of where bills previously covered by the Banner stand.\n\nImmigration\n\nPUBLIC SCHOOLS: There was more than one attempt to limit some children\u2019s access to public education based on their immigration status this year. The first related effort was part of Rep. Gino Bulso\u2019s so-called TRUMP Act (HB 145/SB 268), which would prevent those without legal status from \u201cbenefiting from taxpayer money,\u201d including use of banks and charging tuition for public schools. Bulso\u2019s bill failed in the House Banking and Consumer Affairs subcommittee back in March.\n\nA more advanced effort to challenge Supreme Court precedent and allow school districts to charge tuition to, or ultimately deny, undocumented students came from Rep. William Lamberth (R-Portland) and Sen. Bo Watson (R-Hixson) in the form of HB 793/SB 836. Unlike the Bulso bill, this version is permissive and would leave the decision up to each individual school district. After a month of widespread backlash and protests, the Senate narrowly passed this version in April but the bill stalled on the House side as Lamberth sought clarity on whether it would risk more than $1 billion in federal education funding. The bill will almost certainly be reintroduced next year and would not require any additional action from the Senate unless it is amended.\n\nLICENSES AND DMV: Among the flurry of immigration bills introduced this year were a handful targeting identification and driving privileges, which account for most interactions with law enforcement and can result in arrest or deportation. One of the first bills introduced this session was HB 11/SB 5, a proposal by Rep. Scott Cepicky (R-Culleoka) to redesign driver\u2019s licenses to denote a person\u2019s immigration status. While Cepicky withdrew his bill, another HB 749/SB 1086 by Rep. Lee Reeves (R-Franklin) and Sen. Jack Johnson (R-Franklin) invalidating driver\u2019s licenses issued to undocumented migrants by another state passed both chambers, and is awaiting the governor\u2019s signature. Another bill to limit access to licenses \u2014 HB 556/SB 1373 by Watson and Rep. Kip Capley (R-Summertown) \u2014 would have only allowed the state to offer road tests and other DMV services in English, but it failed in the House Transportation Committee.\n\nOTHER IMMIGRATION BILLS FAIL: Even with the appetite for immigration enforcement bills, several efforts failed to materialize, including HB 10/SB 6, an early bill by Rep. Todd Warner (R- Chapel Hill) and Sen. Joey Hensley (R-Hohenwald), that would have required law enforcement to seek federal detainers for those in custody without citizenship and would have required them to transport the individuals to \u201cnearby\u201d sanctuary cities like Chicago if the maximum detainer ran out before the federal government could take custody. It failed in subcommittee. Efforts to defend against increased immigration enforcement, like HB 1202/SB 17 a bill by Sen. Todd Gardenhire (R-Chattanooga) and Rep. Sabi \u201cDoc\u201d Kumar (R-Springfield) that would have limited the scope of a 2024 law requiring law enforcement to cooperate with federal officials in deportation efforts to only impact those charged with criminal offenses failed in the Senate Judiciary Subcommittee.\n\nPublic Safety and Criminal Justice\n\nCONSTITUTIONAL AMENDMENTS: Three proposed constitutional amendments passed their final votes in the legislature, sending them to voters to decide during the 2026 gubernatorial election. One, banning a potential state property tax, and two addressing bail and victims\u2019 rights are in the hands of voters. Another, known as Marsy\u2019s Law, enshrines a victim\u2019s bill of rights, and mirrors at least 12 other states that have adopted the policy since 2008. The final amendment would remove the right to bail for those accused of one of at least 70 different offenses, though that number could grow given the language of the amendment.\n\nDEM GUN BILLS: A pair of similar but unaligned Democratic gun bills were shelved for the year. The first such bill introduced late last year is HB 599/SB 34 by Sen. Heidi Campbell (D-Nashville) and Rep. Bob Freeman (D-Nashville). It would create a misdemeanor for knowingly selling, giving or otherwise transferring a firearm to someone who is prohibited by state or federal law from possessing it. A bill with a similar intent but broader application is HB 947/SB 1191, introduced by new Rep. Shaundelle Brooks (D-Nashville) and Sen. Raumesh Akbari (D-Memphis). Named Akilah\u2019s Law for her deceased son, Brooks\u2019 bill would make a similar charge for transferring a firearm to anyone who has been voluntarily or involuntarily admitted for mental health care in the last five years. Concerns about the scope of the bill and the alignment of the two bills led to both being shelved for the time being.\n\nAnother gun bill by Campbell, HB 2199/SB 1785 or MaKayla\u2019s Law, would have expanded the charge of reckless endangerment to include failure to safely store a firearm in instances where a child under 13 accessed the gun and injured or killed themselves or another child, but failed in the Senate Judiciary Committee.\n\nLETHAL FORCE (HB 856/SB 1407): A bill by Rep. Kip Capley (R-Summertown) and Sen. Joey Hensley (R-Hohenwald) would have expanded when the state allows civilians to use lethal force, making it justified if they believed it was \u201cimmediately necessary to prevent or terminate the other\u2019s actual or attempted trespass; arson; damage to property; burglary; theft; robbery; or aggravated cruelty to animals, serious bodily injury, or death to animals or livestock.\u201d The bill failed in the Senate Judiciary Committee.\n\nSlideshow: 2025 Legislative Session\n\n\n\n\nThe view from the gallery of the Tennessee House of Representatives. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Cameron Sexton is once again elected to be Speaker of the House. Credit: Martin B. Cherry / Nashville Banner\n\n\nActivists hold signs criticizing the State House\u2019s Republican supermajority. Credit: Martin B. Cherry / Nashville Banner\n\n\nAn overflow audience watches the House Education Committee debate on a TV in the hallways of Cordell Hull Building. Credit: Martin B. Cherry / Nashville Banner\n\n\nState Sen. Ferrell Haile (R-Gallatin) speaks during a Senate floor session. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Justin Pearson (D- Memphis) rallies the protesters after a House Education Committee meeting. Credit: Martin B. Cherry / Nashville Banner\n\n\nElla Brinen smiles after her \u201cfoster youth bill of rights\u201d passed a Senate committee.\n\n\nProtesters embrace during a march outside the state Capitol. Credit: Martin B. Cherry / Nashville Banner\n\n\nProtesters chant and pray after being escorted out of the gallery by state troopers. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Justin Pearson (D-Memphis) confronts Rep. Andrew Farmer (R-Sevierville) during a House Criminal Justice Committee meeting. Credit: Martin B. Cherry / Nashville Banner\n\n\nState Sen. Bo Watson (R-Hixson) is all smiles ahead of a Senate floor session. Credit: Martin B. Cherry / Nashville Banner\n\n\nActivists fill the Senate gallery to protest a bill that will allow school districts to ban undocumented immigrants from attending public schools. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. John Ray Clemmons (D-Nashville) argues against HB0793 on April 7, 2025. Credit: Martin B. Cherry / Nashville Banner\n\n\nA signs in protest of Rep. William Lamberth\u2019s HB0793, a controversial bill meant to challenge Supreme Court precedent. Credit: Martin B. Cherry / Nashville Banner\n\n\nProtesters become emotional after a Senate Education Committee meeting, Credit: Martin B. Cherry / Nashville Banner\n\n\nLisa Sherman Luna, executive director of TIRRC, rallies supporters at Speaker Beth Harwell Plaza on March 5, 2025. Credit: Martin B. Cherry / Nashville Banner\n\n\nMacy Fluharty is escorted out of the House gallery on March 17, 2025 after protesting bills limiting the rights of transgender people and immigrants. Credit: Martin B. Cherry / Nashville Banner\n\n\nPratik Dash shouts at state senators who voted in favor of a bill that would allow school districts to ban or charge undocumented children for public education. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Kip Capley (R-Summertown) speaks demonstrably on the House floor. Credit: Martin B. Cherry / Nashville Banner\n\n\nSpeaker of the House Cameron Sexton (R-Crossville). Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Justin Jones (D-Nashville) debates with Rep. Lamberth (R-Portland) on the House floor. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Shaundelle Brooks (D-Hermitage) talks with James Shaw Jr. after her bill, \u201cAkilah\u2019s Law,\u201d passed the House Criminal Justice Committee. Credit: Martin B. Cherry / Nashville Banner\n\n\nThe view from the gallery of the Tennessee House of Representatives. Credit: Martin B. Cherry / Nashville Banner\n\n\nRep. Cameron Sexton is once again elected to be Speaker of the House. Credit: Martin B. Cherry / Nashville Banner\n\nRep. Cameron Sexton is once again elected to be Speaker of the House. Credit: Martin B. Cherry / Nashville Banner\n\nJAIL DEATHS: Driven by the death of a constituent\u2019s son and ongoing safety concerns in the Trousdale Turner Correctional Center, Sen. Mark Pody (R-Lebanon) introduced a pair of caption bills that he hoped could create new accountability for Tennessee\u2019s private prisons and potentially downgrade Trousdale Turner to a minimum security prison. A final amended version of one of those bills \u2014 HB 114/SB 1115 sponsored in the House by Rep. Clark Boyd (R-Lebanon) \u2014 passed both chambers unanimously. If signed by the governor, the bill will require reporting on deaths from Tennessee\u2019s private prisons. It would require a 10 percent inmate reduction at any facility with a death rate that doubles that of a comparable prison in the state.\n\nAPPEALING CONVICTIONS (HB 601/SB 0256): A bipartisan bill to remove barriers for people convicted of crimes to present new evidence in court to appeal their convictions passed easily in both chambers. The bill by Sen. Todd Gardenhire (R-Chattanooga) and Sen. Bob Freeman (D-Nashville) would make it easier for non-scientific evidence to be heard post-conviction while also allowing District Attorneys to prevent new evidence in cases prosecuted by their office. The bill is awaiting the governor\u2019s signature.\n\nJUVENILE BILLS: A bill (HB 77/SB 237) by Rep. Robert Stevens (R-Smyrna) and Sen. Brent Taylor (R-Memphis), would require juveniles 16 or older to be tried in adult court for their second offense, but had not been heard in subcommittee, meaning the bill could come back next year. An amended version of another Taylor bill \u2014 HB 34/SB 221 \u2014 allows courts to use information from typically sealed juvenile court records in future pretrial decisions for five years after the juvenile offense and requires magistrates to consider juvenile history in bond decisions. This bill has passed both chambers and is awaiting the governor\u2019s signature.\n\nVOYEURISM: After a group of women discovered a Nashville man had  recorded them during sex without their knowledge or consent, they banded together to find all of his victims and promote legislative changes to increase accountability for the crime of unlawful photography. The primary bill to come out of the group\u2019s effort \u2014 sponsored by Freeman and Sen. Jeff Yarbro (D-Nashville) \u2014 is known as the Voyeurism Victims Act and has been signed into law, changing criminal code to start the statute of limitations to prosecute an act of unlawful photography to begin when the victim learns about the crime rather than on the date of the crime. It also allows victims to obtain orders of protection. A related bill by Bulso and Sen. Dawn White (R-Murfreesboro) increases the offense to a felony. It requires offenders to be placed on the sex offender registry, passed both chambers and is awaiting the governor\u2019s signature.\n\nOther Bills\n\nANTI-DIVERSITY: A bill dissolving the state\u2019s Human Rights Commission and moving its related staff under the Attorney General\u2019s control passed and is awaiting the governor\u2019s signature. The bill, HB 910/SB 861 by Rep. Johnny Garrett (R-Goodlettsville) and Sen. John Stevens (R-Huntingdon) will give the HRC staff until July to transition their responsibilities to the AG\u2019s office. The appointed commission will cease to exist, despite concerns from staff about the bill\u2019s origin and impact on the more than 1,000 open discrimination cases. A pair of bills seeking to \u201cdismantle DEI\u201d by prohibiting diversity, equity and inclusion hiring provisions in state government, local governments and publicly funded colleges and universities also passed this session.\n\nCANNABIS CRACKDOWN: Multiple new restrictions on the sale of THCa passed this session, in an effort to close a loophole that effectively legalized most recreational pot sales in the state in 2023. The most significant regulatory bill \u2014 (HB1376/SB 1413) by Lamberth and Sen. Richard Briggs (R-Knoxville) \u2014 is awaiting a signature from the governor, and would prohibit the retail sale of products with a .3 percent or higher combined concentration of THCa and/or Delta 9, change the tax structure for cannabis products and move the regulation of their sales under the Alcoholic Beverage Commission.\n\nAnother bill, HB 1148/SB 1236 by Rep. Ed Butler (R-Rickman) and Sen. Ferrell Haile (R-Gallatin) that would ban THCa and THCp, was not funded in the budget but could be revived next year. An effort by Rep. Aftyn Behn (D-Nashville) and Campbell to further legalize recreational use and use the proceeds for road repairs \u2014 HB 703/SB 921 known as the \u201cpot for potholes\u201d bill \u2014 failed in the House Criminal Justice subcommittee.\n\nHOMELESS ENCAMPMENTS: A bill setting deadlines on the clearing of homeless encampments and disposal of personal belongings passed both chambers and is awaiting the governor\u2019s signature. Despite concerns from service providers who help people experiencing homelessness, HB 197/SB 217, sponsored by Taylor and Rep. Tom Leatherwood (R-Arlington), passed both the House and Senate, setting a 30-day deadline for local authorities and service providers to clear encampments in certain public areas, such as bridges and overpasses. It requires only a 10-day notice before disposing of personal belongings and requires localities to establish encampment clearing protocols with the Tennessee Department of Transportation.\n\nGROCERY TAX: Multiple efforts to repeal the state\u2019s 4 percent tax on groceries stalled again this session. The first version, HB 2/SB 2 brought by Behn and Sen. Charlene Oliver (D-Nashville), would have eliminated the tax to reduce the cost for consumers, replacing it with $250,000 in projected revenue from corporate grocery stores. The effort to revive Behn\u2019s 2024 grocery tax repeal bill stalled again this spring, but was sent to summer study, meaning it could be revived next year. A similar effort, HB 21/SB 1367 by Rep. Elaine Davis (R-Knoxville) and Watson, would repeal the tax but offered no alternative revenue and was placed behind the budget without funding, sending it to a comparable limbo.\n\nREPRODUCTIVE RIGHTS TBD: Lawmakers codified some reproductive rights in a Republican-led proposal protecting access to in vitro fertilization and birth control passed in the Tennessee House on Thursday, despite opposition from dozens of republicans. HB 533/SB 449 by Rep. Iris Rudder (R-Winchester) and Sen. Becky Massey (R-Knoxville) narrowly passed both chambers and is awaiting the governor\u2019s signature, while a group of 11 other Republicans implored the governor to use his first-ever veto to block the bill. A pair of Democratic bills to restore and codify different reproductive rights both predictably failed.\n\nFOSTER CARE BILLS: Lawmakers passed a \u201cfoster care bill of rights,\u201d led by former foster youth, enshrining rights to things like school, housing, medical care and reliable contact with a trusted adult. While it was sponsored by Haile and Rep. Mary Littleton, HB 1359/ SB1015 was written by 19-year-old former foster child Ella Brinen and passed both chambers unanimously. It\u2019s now awaiting the governor\u2019s signature. Another bill to require more transparency in how federal dollars intended for foster children are spent by the department failed in the House Judiciary Committee earlier this month. The bill, HB 1131 / SB 1331 by Yarbro and Rep. Antonio Parkinson (D-Memphis) was spurred by reports of the Department of Children\u2019s Services claiming million of dollars intended for individual foster children.\n\nSCHOOL PHONE BAN: In an effort to curb classroom distractions and cyberbullying, the legislature passed HB 932/SB. 897, a bill by Rep. Rebecca Alexander (R-Jonesborough) and Haile, requiring school boards to create cell phone ban policies, has been signed into law by the governor. The new law, which takes effect on July 1, requires each local education authority to develop a policy banning the use of personal devices in the classroom, including cell phones, tablets, and laptops. Each body can develop a specific policy defining whether devices are allowed on school grounds, whether they can be used during non-instructional times such as lunch breaks, and what the emergency contact protocol will be for students and parents.\n\nCorrection: An earlier version of this story contained an incorrect number for a foster care bill sponsored by Sen. Jeff Yarbro and Rep. Antonio Parkinson.]]>\n  \n  \n    A US-China Beautiful Rebalancing\n    https://www.linkedin.com/pulse/us-china-beautiful-rebalancing-ray-dalio-bms2e?utm_source=share&utm_medium=member_ios&utm_campaign=share_via\n    readwise:01jsm9vzagc1s21pf8vnyxkab3\n    Thu, 24 Apr 2025 16:25:06 +0000\n    linkedin.com\n    \n \n \n \n \n\n Ray Dalio \n\n Founder, CIO Mentor, and Member of the Bridgewater Board \n\nI was pleased and not surprised that the US and China will be having \u201ctariff negotiations,\u201d which will be negotiations on much more than trade. In my dreams, I can imagine the US and China working out a beautiful rebalancing\u2014one in which the unsustainable excesses are reduced to levels that are sustainable. \n\nThe Problems and the Solutions\n\nTo review, as a result of many factors that I won\u2019t digress into again, this is the dynamic I see:\n\n \nAmericans (and others) buy inexpensive manufactured goods from China that are financed by the United States borrowing from China (and others)\u2026 \nAnd in the process, the United States has lost its ability to manufacture effectively, which has contributed to the plight of the bottom 60%, while it has developed a geopolitically threatening dependence on manufactured goods from China (and other countries)\u2026 \nAt the same time, China (and other countries) has developed an unhealthy, excessive dependence on the returns of US debt assets (and other American capital market assets). \n\nThis is an unsustainable imbalance that one way or another\u2014i.e., in a coordinated, well-managed way or in a crash\u2014must come to an end.\n\nSaid differently, as a result of these excesses, the US has become the world\u2019s dominant consumer and borrower thus building foreigners\u2019 unhealthy dependencies on selling their goods to US consumers and on the returns of US bonds and other American investments, and China has become the world\u2019s dominant manufacturer and lender thus building unhealthy dependencies on selling and lending/investing in other markets, and all of these are threatening in a world in which mutual dependencies are threatening\u2014so, they must be rectified.\n\nWhat needs to be done about this situation? Said oversimply:\n\nThe US needs to:\n\n \nCut the deficit  \nRaise manufacturing \nCut consumption \nReduce its debt burden \n\nChina needs to:\n\n \nCut the surplus \nLower manufacturing  \nRaise consumption \nReduce its debt burden \n\nIn thinking about how to best engineer these changes, each country has a) its own domestic issues to consider, b) adequate tools to manage this situation well, and c) different approaches to managing their economies (e.g., production in the United States is primarily driven by free-market participants in pursuit of profits while what is produced in China is primarily driven by governments, especially local governments, pursuing volumes of output). That means that with cooperation and capable decision making, orderly big progress to greatly reduce these unsustainable imbalances can be made.\n\nBecause there are many ways that both sides working together can engineer a beautiful rebalancing, I won\u2019t explore the possibilities now. I will just emphasize my main point, which is that this rebalancing, which is especially important given what the new world order is like, can and needs to happen in an orderly way, and the most important three questions are 1) will the two sides work well together to engineer big reductions in these imbalances so they take place in the least disruptive way possible, 2) how will a deal be enforced, and 3) will this deal be adhered to?\n\nThe views expressed here are my own and not necessarily those of Bridgewater. ]]>\n    \n \n \n \n \n\n Ray Dalio \n\n Founder, CIO Mentor, and Member of the Bridgewater Board \n\nI was pleased and not surprised that the US and China will be having \u201ctariff negotiations,\u201d which will be negotiations on much more than trade. In my dreams, I can imagine the US and China working out a beautiful rebalancing\u2014one in which the unsustainable excesses are reduced to levels that are sustainable. \n\nThe Problems and the Solutions\n\nTo review, as a result of many factors that I won\u2019t digress into again, this is the dynamic I see:\n\n \nAmericans (and others) buy inexpensive manufactured goods from China that are financed by the United States borrowing from China (and others)\u2026 \nAnd in the process, the United States has lost its ability to manufacture effectively, which has contributed to the plight of the bottom 60%, while it has developed a geopolitically threatening dependence on manufactured goods from China (and other countries)\u2026 \nAt the same time, China (and other countries) has developed an unhealthy, excessive dependence on the returns of US debt assets (and other American capital market assets). \n\nThis is an unsustainable imbalance that one way or another\u2014i.e., in a coordinated, well-managed way or in a crash\u2014must come to an end.\n\nSaid differently, as a result of these excesses, the US has become the world\u2019s dominant consumer and borrower thus building foreigners\u2019 unhealthy dependencies on selling their goods to US consumers and on the returns of US bonds and other American investments, and China has become the world\u2019s dominant manufacturer and lender thus building unhealthy dependencies on selling and lending/investing in other markets, and all of these are threatening in a world in which mutual dependencies are threatening\u2014so, they must be rectified.\n\nWhat needs to be done about this situation? Said oversimply:\n\nThe US needs to:\n\n \nCut the deficit  \nRaise manufacturing \nCut consumption \nReduce its debt burden \n\nChina needs to:\n\n \nCut the surplus \nLower manufacturing  \nRaise consumption \nReduce its debt burden \n\nIn thinking about how to best engineer these changes, each country has a) its own domestic issues to consider, b) adequate tools to manage this situation well, and c) different approaches to managing their economies (e.g., production in the United States is primarily driven by free-market participants in pursuit of profits while what is produced in China is primarily driven by governments, especially local governments, pursuing volumes of output). That means that with cooperation and capable decision making, orderly big progress to greatly reduce these unsustainable imbalances can be made.\n\nBecause there are many ways that both sides working together can engineer a beautiful rebalancing, I won\u2019t explore the possibilities now. I will just emphasize my main point, which is that this rebalancing, which is especially important given what the new world order is like, can and needs to happen in an orderly way, and the most important three questions are 1) will the two sides work well together to engineer big reductions in these imbalances so they take place in the least disruptive way possible, 2) how will a deal be enforced, and 3) will this deal be adhered to?\n\nThe views expressed here are my own and not necessarily those of Bridgewater. ]]>\n  \n  \n    For Black Americans, Mexico offers little respite from racism\n    https://theweek.com/life/1012528/for-black-americans-mexico-offers-little-respite-from-racism\n    readwise:01jskwehjha6nc727873a0kj6b\n    Thu, 24 Apr 2025 12:30:35 +0000\n    theweek\n      \n \n\n(Image credit: Illustrated | iStock)\n\nWilliam Shakespeare's famous adage \"a rose by any other name would smell as sweet\" was once just a phrase I had stuck in my head from that '90s \"Romeo and Juliet\" remake in which the creators made the questionable choice to use the Shakespearean language nearly-word-for-word alongside shootouts and soul patches.\n\nBut while walking the streets of Mexico, I had finally found a personal connection. Albeit in a much less romantic and far more disturbing manner. Because here I was reminded that racism by any other name hurts just as much.\n\nI came to Mexico City (aka CDMX) in April for an extended vacation and language immersion. CDMX has become a popular tourist destination. And over the last couple of years, Black American ex-pats had been traveling to Mexico to seek refuge from racism.\n\nSign up for The Week's Free Newsletters\n\nFrom our morning news briefing to a weekly Good News Newsletter, get the best of The Week delivered directly to your inbox.\n\nFrom our morning news briefing to a weekly Good News Newsletter, get the best of The Week delivered directly to your inbox.\n\nI later learned that ex-pats have formed tight-knit communities in CDMX, with organized events and meetups, helping to foster connection and form roots. But if the only way I could find community was through spending time solely with other Americans, then why would I pay all this money to leave Florida?\n\nAnd the idea of \"refuge\" still seemed like a reach to me because I couldn't believe Black Americans could go from living in one country with well-documented systemic racial issues to another with its own racial inequality and somehow have a better experience.\n\nI'd been to Mexico before on vacation, in Canc\u00fan and Cozumel, where I'd spent just a couple of days and had a fine time. But after living in Italy in 2013, I learned that visiting a place for a couple of days is far different from what you experience over a long period of time. I was determined to never be caught off guard again.\n\nSo, I took the concept of \"racial refuge\" with a grain of salt and started my journey. I had a great time meeting people, touring the popular areas of Condessa and Centro Historico, blowing up my followers' Instagram feeds with vacation-envy photos, and having my fill of tacos, chillaquiles and pozole.\n\nBut within days, I realized that \"refuge\" is probably far too strong a word. From stares to unwanted touching, unsolicited photos, side comments and racial profiling in several popular central-Mexican destinations, I realized racism is just as present, no matter the culture.\n\nAnd I'd much rather face the devil I know.\n\nUp and down the streets of CDMX, a friend and I had been asked on multiple occasions for photos. On a visit to the National Museum of Anthropology, my mother and I were certain we caught kids from different parties pointing and sneaking photos of us while their parents knowingly allowed their rude behavior.\n\nDuring one trip to visit the historical area of Teotihuacan, as my Black female friend and I tried to take in the site of more than one dozen temples and two towering pyramids, an onlooker asked for pictures of us while we were in the presence of nearly 2,000-year-old structures with centuries of backstory far more photograph-worthy.\n\nAnd while in Guanajuato City, we could barely make it across the colorful streets without being asked for a dozen photos, as if we were Beyonce\u0301 and Kelly Rowland. (But even such celebrity status didn't stop us from being followed by an employee in a crowded shop.) And at one point, a young woman touched my friend's hair from behind before asking if she could do so. When my friend said \"no,\" she walked away giggling as if it were a game.\n\nI quickly shouted \"\u00a1No somos animales!\"\n\nWe are not animals and this is not a zoo.\n\nThe constant \"othering,\" the pointing, the staring, the side comments, the photos \u2014 all of these are reminiscent of how Black people (and other marginalized groups) had been treated like creatures in the years following colonization. Black people were looked at as anomalies for their features and placed on display so others can do just as they've done to my friend, my mother, and me throughout Mexico.\n\nWhen I tried to discuss how I felt with a few other Black travelers, they essentially said \"Oh they're just curious.\" But in such cosmopolitan areas, with free city WIFI in CDMX, and decades of American TV shows with Black actors, the \"curiosity\" seems unwarranted.\n\nAnd they can call it what they want, but I'll call it racism.\n\nAt one point during my stay, I saw someone in a Facebook group for Black people in Mexico City complain about similar issues and lamenting how they'd wished Black ex-pats had been more open about expressing the racism one might experience in Mexico, and while some commenters claimed they hadn't had any issues, others simply wrote it off as innocent or said they'd simply gotten used to the treatment.\n\nBut if we must \"get used to\" racism, as sad as that is, what's the point of moving to another country just to start all over with it?\n\nOne might argue what I've experienced is better than the systemic racism or police violence in the United States, but it might prove difficult to say just how deep the systemic issues are for ex-pats. That's especially true if many are working remotely, allowing them to avoid the need to climb the ladder through Mexican society.\n\nI wonder how many Black travelers are attempting to acquire jobs in CDMX, or have to deal directly with life's facets through which systemic racism can truly show its face.\n\nAnd when it comes to the police in Mexico, I had been warned about crooked cops early on in my stay. And while doing my own research, I learned that brutality was common, particularly against an increasing number of Black migrants.\n\nIf one is familiar with Mexico's history with its own Black residents, the discrimination, violence and inequality aren't too surprising. How can a country that only recently recognized its own Black population openly embrace Black outsiders?\n\nPerhaps I've already accepted that there is no \"racial refuge\" for Black people beyond spaces where we are the majority. And even then, if Brazil and South Africa were to serve as examples, it's still not guaranteed.\n\nDespite the abundant issues of prejudice, my experience here has been memorable and enjoyable. It helped that I was ready to address any sort of mistreatment. But I can't easily shake the discomfort and disgust I feel when being so blatantly \"othered,\" just as I felt years ago in the city of Florence, Italy.\n\nAnd as it did then, the long-term exposure to this in-your-face racism made me eager to head back to what I'm \"used to.\"\n\nSign up for Today's Best Articles in your inbox\n\nA free daily email with the biggest news stories of the day \u2013 and the best features from TheWeek.com\n\nContact me with news and offers from other Future brandsReceive email from us on behalf of our trusted partners or sponsorsBy submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.\n\n\n\nNicole Phillip is a New York University alumna and multimedia journalist who currently works in the social media space. Her writing spreads across beats with a particular focus on matters of race and intersectional feminism. You can find her work in The Week, The New York Times, The 1619 Project digital publication, The Daily Beast, ABC News, and NBC Universal Local. She considers herself to be a skilled shapeshifter between journalistic mediums, but often finds herself drawn to writing.]]>\n      \n \n\n(Image credit: Illustrated | iStock)\n\nWilliam Shakespeare's famous adage \"a rose by any other name would smell as sweet\" was once just a phrase I had stuck in my head from that '90s \"Romeo and Juliet\" remake in which the creators made the questionable choice to use the Shakespearean language nearly-word-for-word alongside shootouts and soul patches.\n\nBut while walking the streets of Mexico, I had finally found a personal connection. Albeit in a much less romantic and far more disturbing manner. Because here I was reminded that racism by any other name hurts just as much.\n\nI came to Mexico City (aka CDMX) in April for an extended vacation and language immersion. CDMX has become a popular tourist destination. And over the last couple of years, Black American ex-pats had been traveling to Mexico to seek refuge from racism.\n\nSign up for The Week's Free Newsletters\n\nFrom our morning news briefing to a weekly Good News Newsletter, get the best of The Week delivered directly to your inbox.\n\nFrom our morning news briefing to a weekly Good News Newsletter, get the best of The Week delivered directly to your inbox.\n\nI later learned that ex-pats have formed tight-knit communities in CDMX, with organized events and meetups, helping to foster connection and form roots. But if the only way I could find community was through spending time solely with other Americans, then why would I pay all this money to leave Florida?\n\nAnd the idea of \"refuge\" still seemed like a reach to me because I couldn't believe Black Americans could go from living in one country with well-documented systemic racial issues to another with its own racial inequality and somehow have a better experience.\n\nI'd been to Mexico before on vacation, in Canc\u00fan and Cozumel, where I'd spent just a couple of days and had a fine time. But after living in Italy in 2013, I learned that visiting a place for a couple of days is far different from what you experience over a long period of time. I was determined to never be caught off guard again.\n\nSo, I took the concept of \"racial refuge\" with a grain of salt and started my journey. I had a great time meeting people, touring the popular areas of Condessa and Centro Historico, blowing up my followers' Instagram feeds with vacation-envy photos, and having my fill of tacos, chillaquiles and pozole.\n\nBut within days, I realized that \"refuge\" is probably far too strong a word. From stares to unwanted touching, unsolicited photos, side comments and racial profiling in several popular central-Mexican destinations, I realized racism is just as present, no matter the culture.\n\nAnd I'd much rather face the devil I know.\n\nUp and down the streets of CDMX, a friend and I had been asked on multiple occasions for photos. On a visit to the National Museum of Anthropology, my mother and I were certain we caught kids from different parties pointing and sneaking photos of us while their parents knowingly allowed their rude behavior.\n\nDuring one trip to visit the historical area of Teotihuacan, as my Black female friend and I tried to take in the site of more than one dozen temples and two towering pyramids, an onlooker asked for pictures of us while we were in the presence of nearly 2,000-year-old structures with centuries of backstory far more photograph-worthy.\n\nAnd while in Guanajuato City, we could barely make it across the colorful streets without being asked for a dozen photos, as if we were Beyonce\u0301 and Kelly Rowland. (But even such celebrity status didn't stop us from being followed by an employee in a crowded shop.) And at one point, a young woman touched my friend's hair from behind before asking if she could do so. When my friend said \"no,\" she walked away giggling as if it were a game.\n\nI quickly shouted \"\u00a1No somos animales!\"\n\nWe are not animals and this is not a zoo.\n\nThe constant \"othering,\" the pointing, the staring, the side comments, the photos \u2014 all of these are reminiscent of how Black people (and other marginalized groups) had been treated like creatures in the years following colonization. Black people were looked at as anomalies for their features and placed on display so others can do just as they've done to my friend, my mother, and me throughout Mexico.\n\nWhen I tried to discuss how I felt with a few other Black travelers, they essentially said \"Oh they're just curious.\" But in such cosmopolitan areas, with free city WIFI in CDMX, and decades of American TV shows with Black actors, the \"curiosity\" seems unwarranted.\n\nAnd they can call it what they want, but I'll call it racism.\n\nAt one point during my stay, I saw someone in a Facebook group for Black people in Mexico City complain about similar issues and lamenting how they'd wished Black ex-pats had been more open about expressing the racism one might experience in Mexico, and while some commenters claimed they hadn't had any issues, others simply wrote it off as innocent or said they'd simply gotten used to the treatment.\n\nBut if we must \"get used to\" racism, as sad as that is, what's the point of moving to another country just to start all over with it?\n\nOne might argue what I've experienced is better than the systemic racism or police violence in the United States, but it might prove difficult to say just how deep the systemic issues are for ex-pats. That's especially true if many are working remotely, allowing them to avoid the need to climb the ladder through Mexican society.\n\nI wonder how many Black travelers are attempting to acquire jobs in CDMX, or have to deal directly with life's facets through which systemic racism can truly show its face.\n\nAnd when it comes to the police in Mexico, I had been warned about crooked cops early on in my stay. And while doing my own research, I learned that brutality was common, particularly against an increasing number of Black migrants.\n\nIf one is familiar with Mexico's history with its own Black residents, the discrimination, violence and inequality aren't too surprising. How can a country that only recently recognized its own Black population openly embrace Black outsiders?\n\nPerhaps I've already accepted that there is no \"racial refuge\" for Black people beyond spaces where we are the majority. And even then, if Brazil and South Africa were to serve as examples, it's still not guaranteed.\n\nDespite the abundant issues of prejudice, my experience here has been memorable and enjoyable. It helped that I was ready to address any sort of mistreatment. But I can't easily shake the discomfort and disgust I feel when being so blatantly \"othered,\" just as I felt years ago in the city of Florence, Italy.\n\nAnd as it did then, the long-term exposure to this in-your-face racism made me eager to head back to what I'm \"used to.\"\n\nSign up for Today's Best Articles in your inbox\n\nA free daily email with the biggest news stories of the day \u2013 and the best features from TheWeek.com\n\nContact me with news and offers from other Future brandsReceive email from us on behalf of our trusted partners or sponsorsBy submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.\n\n\n\nNicole Phillip is a New York University alumna and multimedia journalist who currently works in the social media space. Her writing spreads across beats with a particular focus on matters of race and intersectional feminism. You can find her work in The Week, The New York Times, The 1619 Project digital publication, The Daily Beast, ABC News, and NBC Universal Local. She considers herself to be a skilled shapeshifter between journalistic mediums, but often finds herself drawn to writing.]]>\n  \n  \n    Boardroom Tool: Questions for Directors to Ask About AI\n    https://www.nacdonline.org/all-governance/governance-resources/governance-research/director-handbooks/DH/2025/ai-in-cybersecurity/boardroom-tool-questions-for-directors-to-ask-about-ai/?ite=9045&ito=1355&itq=363b6e44-2541-4677-8e0d-167887203478&itx%5Bidio%5D=1358278\n    readwise:01jshafpz3my705vdfxzwb1t33\n    Wed, 23 Apr 2025 12:38:10 +0000\n    nacdonline.org\n    High-performing boards comprise a diverse set of directors who ask direct and insightful questions as they seek knowledge to make informed decisions. Here are sample questions boards ought to ask about AI and cybersecurity:\n\nGENERAL QUESTIONS\n\n \nHow are our competitors using AI? \nHow are we using AI? \nDo we feel obligated to do this? \nWhen we do \u201cthis\u201d what is happening to our risk? \nHow fast should we be, and/or do we need to be going? \nHow can we use AI to disrupt our business and our industry? \nWhat are the risks of investing in AI versus maintaining the status quo? \nWhat\u2019s our plan to acquire AI capabilities? \nWho can help us? \nHow much will AI cost, and what is the expected return on investment? \nWho will lead our AI effort, and what makes them qualified to do so? \nHow do we measure success? \nDo we need a Chief AI Officer? \nWhat is our risk exposure if malicious cyber actors use AI-enabled technology to attack our infrastructure? How do you know? \nHow can we use AI capabilities to reduce our cyber-risk exposure? \nIs the use of AI representing the shareholders\u2019 interests? \nDoes the board have a clear understanding of what our organization considers ethical use of AI to be? \nHas the organization clearly defined and communicated what ethical AI use means for us? \nDo we have internal processes in place to adequately communicate the ethical use of our AI systems? \nDo we have channels in place with entities outside our organization to adequately and appropriately communicate about the ethical use of our AI use cases? \n\nQUESTIONS REGARDING AI RISKS\n\n \nWhat are the risks for our expected uses of AI? Can they be quantified? \nHow will the use of AI disrupt the company\u2019s business and industry? \nWhat are the governance implications of the use of AI and related policies and controls? \nHave we segregated training data, so we know the provenance of the data used to train our models? \nHave we established an AI governance board or committee? \nHow can we review and approve governance policies for AI that include human review by management? \nWhat is our CDO\u2019s (Chief Data Officer) or Data Governance leader's strategy for handling data sharing requests at the scale the business is implementing AI? \nWhat is our third-party risk associated with AI? \nWho are our riskiest vendors, and how is our organization managing that risk? (Most vendors are basically writing off as much AI risk as possible on the licensee, especially because this market is largely unregulated at this point.) \n\nQUESTIONS REGARDING REGULATION OF AI\n\n \nHave we explored the operational and regulatory challenges related to the proposed use of AI? \nWhere does the proposed AI use case rank on the EU Artificial Intelligence Act scale of risk (unacceptable risk, high risk, limited risk, or minimal risk) for both the provider and user? \nAre we developing AI in accordance with putative legislative and regulatory expectations? \nHave we assigned responsibility for tracking AI regulatory matters to a chief legal officer or general counsel as regulations develop? \nAre our policies, processes, procedures, and practices related to the mapping, measuring, and managing of AI risk in place, transparent, and implemented effectively? How do we know? \nDo our accountability structures ensure appropriate teams and individuals are empowered, responsible, and trained for mapping, measuring, and managing AI risks? \nAre policies and procedures in place to address AI risks from third-party software and other supply-chain issues? \nAre we using protected data to train the model that can be subject to opt-out or removal requests? \nHave we reviewed our insurance policies for AI-related risks and use cases? \n\nQUESTIONS REGARDING THE BOARD\u2019S ABILITY TO OVERSEE AI\n\n \nDoes the current board possess adequate expertise to properly and effectively perform oversight over our use of AI? \nDoes the board need to institute its own AI board education program to enable it to properly carry out its fiduciary responsibility? \nShould the board hold periodic virtual sessions to consider/educate board members about AI as it pertains specifically to our business? \nDo we need to restructure the board to effectively manage our extended cyber risk due to our current and anticipated use of AI? \nDo we need a new committee to focus on AI? \nShould all the board committees be discussing AI? \nShould our AI/cyber risk be considered as a separate matter for board discussion and action, or should it be integrated as a part of our overall operations? Or both? \n\nQUESTIONS REGARDING OVERSIGHT AND MANAGEMENT OF AI\n\n \nDoes our corporate structure ensure management is balancing the potential benefits of AI with potential risk? \nIs the board considering AI risks simultaneously with economic benefits from AI use cases? \nDoes our budgeting process ensure adequate funding for continuous monitoring, testing, and auditing of AI risk? \nIs there appropriate and sufficient employee training, including budget, to assure that relevant portions of the organization\u2019s workforce are able to implement the AI-based use case? \nHave we engaged \u201cred teams\u201d to assess generative AI use cases, thus assuring that all necessary aspects of the organization have had proper input into the development and deployment of safe and resilient AI solutions? \nHave we considered the company\u2019s outsourcing plan with respect to AI and the risks outsourcing may entail? \nHow do we know that our AI supplier is using best practices? \nHas the management team conducted adequate due diligence to determine the degree of risk associated with a specific AI use case based on the pre-deployment testing process? \nAre our testing, monitoring, auditing, and mitigation efforts reflected in our logging and metadata emanating from the AI itself, or is a human in the loop? \nHas the management team adequately and empirically determined that the proposed AI use case risk can be mitigated or transferred in line with the organization\u2019s risk appetite? \nAre processes in place to maintain an acceptable risk profile over time and accounting for the potential for the AI to \u201cdrift\u201d? \n\n\n\n Explore the AI in Cybersecurity Report \n\n\n\nAI Friend and Foe\n\nElevate your board's AI oversight capabilities to balance cybersecurity benefits with emerging risks, while ensuring responsible governance for strategic advantage.\n\n\n\nDefining AI and Its Impact on Cybersecurity\n\nUnderstand essential AI types and their cybersecurity implications, from traditional systems to LLMs, while addressing key risks including skills gaps, model drift, and lack of model transparency.\n\n\n\nAI as a Cybersecurity Risk and Force Multiplier\n\nNavigate the dual impact of AI in cybersecurity as both a risk multiplier enabling sophisticated attacks and a force multiplier enhancing threat detection, analytics, and workforce capabilities.\n\n\n\nHow AI Will Impact Cybersecurity Regulatory and Disclosure Matters\n\nDiscover how organizations must navigate AI's regulatory challenges and fulfill their disclosure obligations to ensure responsible and transparent AI use and oversight.\n\n\n\nHow AI Impacts Board Readiness for Oversight of Cybersecurity and AI Risks\n\nEquip your board with essential AI governance knowledge to address cybersecurity vulnerabilities and implement risk assessment frameworks for responsible implementation and improve board readiness for AI governance.\n\n\n\nLeverage this question framework to guide board discussions on AI to ensure proper board governance and oversight of this critical technology.]]>\n    High-performing boards comprise a diverse set of directors who ask direct and insightful questions as they seek knowledge to make informed decisions. Here are sample questions boards ought to ask about AI and cybersecurity:\n\nGENERAL QUESTIONS\n\n \nHow are our competitors using AI? \nHow are we using AI? \nDo we feel obligated to do this? \nWhen we do \u201cthis\u201d what is happening to our risk? \nHow fast should we be, and/or do we need to be going? \nHow can we use AI to disrupt our business and our industry? \nWhat are the risks of investing in AI versus maintaining the status quo? \nWhat\u2019s our plan to acquire AI capabilities? \nWho can help us? \nHow much will AI cost, and what is the expected return on investment? \nWho will lead our AI effort, and what makes them qualified to do so? \nHow do we measure success? \nDo we need a Chief AI Officer? \nWhat is our risk exposure if malicious cyber actors use AI-enabled technology to attack our infrastructure? How do you know? \nHow can we use AI capabilities to reduce our cyber-risk exposure? \nIs the use of AI representing the shareholders\u2019 interests? \nDoes the board have a clear understanding of what our organization considers ethical use of AI to be? \nHas the organization clearly defined and communicated what ethical AI use means for us? \nDo we have internal processes in place to adequately communicate the ethical use of our AI systems? \nDo we have channels in place with entities outside our organization to adequately and appropriately communicate about the ethical use of our AI use cases? \n\nQUESTIONS REGARDING AI RISKS\n\n \nWhat are the risks for our expected uses of AI? Can they be quantified? \nHow will the use of AI disrupt the company\u2019s business and industry? \nWhat are the governance implications of the use of AI and related policies and controls? \nHave we segregated training data, so we know the provenance of the data used to train our models? \nHave we established an AI governance board or committee? \nHow can we review and approve governance policies for AI that include human review by management? \nWhat is our CDO\u2019s (Chief Data Officer) or Data Governance leader's strategy for handling data sharing requests at the scale the business is implementing AI? \nWhat is our third-party risk associated with AI? \nWho are our riskiest vendors, and how is our organization managing that risk? (Most vendors are basically writing off as much AI risk as possible on the licensee, especially because this market is largely unregulated at this point.) \n\nQUESTIONS REGARDING REGULATION OF AI\n\n \nHave we explored the operational and regulatory challenges related to the proposed use of AI? \nWhere does the proposed AI use case rank on the EU Artificial Intelligence Act scale of risk (unacceptable risk, high risk, limited risk, or minimal risk) for both the provider and user? \nAre we developing AI in accordance with putative legislative and regulatory expectations? \nHave we assigned responsibility for tracking AI regulatory matters to a chief legal officer or general counsel as regulations develop? \nAre our policies, processes, procedures, and practices related to the mapping, measuring, and managing of AI risk in place, transparent, and implemented effectively? How do we know? \nDo our accountability structures ensure appropriate teams and individuals are empowered, responsible, and trained for mapping, measuring, and managing AI risks? \nAre policies and procedures in place to address AI risks from third-party software and other supply-chain issues? \nAre we using protected data to train the model that can be subject to opt-out or removal requests? \nHave we reviewed our insurance policies for AI-related risks and use cases? \n\nQUESTIONS REGARDING THE BOARD\u2019S ABILITY TO OVERSEE AI\n\n \nDoes the current board possess adequate expertise to properly and effectively perform oversight over our use of AI? \nDoes the board need to institute its own AI board education program to enable it to properly carry out its fiduciary responsibility? \nShould the board hold periodic virtual sessions to consider/educate board members about AI as it pertains specifically to our business? \nDo we need to restructure the board to effectively manage our extended cyber risk due to our current and anticipated use of AI? \nDo we need a new committee to focus on AI? \nShould all the board committees be discussing AI? \nShould our AI/cyber risk be considered as a separate matter for board discussion and action, or should it be integrated as a part of our overall operations? Or both? \n\nQUESTIONS REGARDING OVERSIGHT AND MANAGEMENT OF AI\n\n \nDoes our corporate structure ensure management is balancing the potential benefits of AI with potential risk? \nIs the board considering AI risks simultaneously with economic benefits from AI use cases? \nDoes our budgeting process ensure adequate funding for continuous monitoring, testing, and auditing of AI risk? \nIs there appropriate and sufficient employee training, including budget, to assure that relevant portions of the organization\u2019s workforce are able to implement the AI-based use case? \nHave we engaged \u201cred teams\u201d to assess generative AI use cases, thus assuring that all necessary aspects of the organization have had proper input into the development and deployment of safe and resilient AI solutions? \nHave we considered the company\u2019s outsourcing plan with respect to AI and the risks outsourcing may entail? \nHow do we know that our AI supplier is using best practices? \nHas the management team conducted adequate due diligence to determine the degree of risk associated with a specific AI use case based on the pre-deployment testing process? \nAre our testing, monitoring, auditing, and mitigation efforts reflected in our logging and metadata emanating from the AI itself, or is a human in the loop? \nHas the management team adequately and empirically determined that the proposed AI use case risk can be mitigated or transferred in line with the organization\u2019s risk appetite? \nAre processes in place to maintain an acceptable risk profile over time and accounting for the potential for the AI to \u201cdrift\u201d? \n\n\n\n Explore the AI in Cybersecurity Report \n\n\n\nAI Friend and Foe\n\nElevate your board's AI oversight capabilities to balance cybersecurity benefits with emerging risks, while ensuring responsible governance for strategic advantage.\n\n\n\nDefining AI and Its Impact on Cybersecurity\n\nUnderstand essential AI types and their cybersecurity implications, from traditional systems to LLMs, while addressing key risks including skills gaps, model drift, and lack of model transparency.\n\n\n\nAI as a Cybersecurity Risk and Force Multiplier\n\nNavigate the dual impact of AI in cybersecurity as both a risk multiplier enabling sophisticated attacks and a force multiplier enhancing threat detection, analytics, and workforce capabilities.\n\n\n\nHow AI Will Impact Cybersecurity Regulatory and Disclosure Matters\n\nDiscover how organizations must navigate AI's regulatory challenges and fulfill their disclosure obligations to ensure responsible and transparent AI use and oversight.\n\n\n\nHow AI Impacts Board Readiness for Oversight of Cybersecurity and AI Risks\n\nEquip your board with essential AI governance knowledge to address cybersecurity vulnerabilities and implement risk assessment frameworks for responsible implementation and improve board readiness for AI governance.\n\n\n\nLeverage this question framework to guide board discussions on AI to ensure proper board governance and oversight of this critical technology.]]>\n  \n  \n    Directors Quarterly: April 2025 \n    https://readwise.io/reader/document_raw_content/296498273\n    readwise:01jsha812peayxm3dzeszt9wjh\n    Wed, 23 Apr 2025 12:33:58 +0000\n    readwise.io\n    \n\nCutting through the noise\nWith the post-election landscape still unfolding, navigating the policy and regulatory shifts underway\u2014and assessing the potential upsides and downsides\u2014requires boards and business leaders to be more agile, engaged, and aligned than ever. Cutting through the noise will be challenging. Proactive decision-making amid such uncertainty demands proactive leadership. Stakeholder expectations are also shifting\u2014and shareholders are watching to see how boards respond.\nAs generative AI (GenAI) tools quickly become ubiquitous, and boards seek to help companies balance the risks and opportunities that the technology poses, we look at the current state of GenAI oversight and offer questions for\nboards to consider, with insights from the recent KPMG Board Leadership Center (BLC) webcast and director survey.\nGeopolitics, tariffs, and political uncertainty remain top of mind for boards as we head into the second quarter. In this edition, we highlight five of the most pressing geopolitical risks facing companies in the near term and their potential impacts.\nThis quarter, we also explore how audit committee members and CFOs can maintain a strong working relationship as they each grapple with expanding workloads, increased complexity, and ongoing digital disruptions. And for audit committee members, we provide an update on financial reporting and auditing developments that may impact companies in the near term. Finally, we share observations on the M&A environment and the implications for board oversight.\n\n\nWhat\u2019s inside\n\n\n\n2\n\nFinancial reporting and auditing update\n\n\n\n\n4\n\nStrengthening the CFO\u2013 audit committee relationship\n\n\n\n\n7\n\nObservations on M&A oversight\n\n\n\n\n10\n\n9 Top geopolitical risks State of AI:\nA boardroom lens\n\n\n\n12 Mark your calendar\n\n\nJohn H. Rodi Co-Leader KPMG BLC\nAnne C. Zavarella\n\nCo-Leader KPMG BLC\n\n\u00a9 2025 KPMG LLP, a Delaware limited liability partnership and a member firm of the KPMG global organization of independent member firms affiliated with KPMG International Limited, a private English company limited by guarantee. All rights reserved. USCS027017-3A\n\nDirectors quarterly\nInsights from the Board Leadership Center\n\nApril 2025\n\n\n\nFinancial reporting and auditing update\n\u200c\n\nEffects of US tariffs on financial reporting*\nRecent US tariffs on imports from Mexico, Canada, and China, along with retaliatory tariffs, may cause supply chain disruptions, increased costs, price volatility, and market demand shifts, potentially affecting multiple areas of financial reporting. Rapidly changing tariff policies are creating significant uncertainty about\nthe applicability and duration of the tariffs, which can pose challenges in preparing estimates, assumptions, and projected financial information. Our handbook, Accounting for economic disruption, although not tariff-specific, is a useful tool for evaluating some of these potential impacts.\n\n\nRevenue. Revenue contracts may be revised to address tariff costs or may be affected by changes in customer demand. Companies should carefully consider various aspects of the revenue recognition guidance, including contract modifications, potential price concessions and collectability risk, and the need to revise estimates and judgments such as variable consideration and stand-alone selling prices.\n\nImpairment. Tariffs may result in changes in impairment assessments and conclusions for financial and nonfinancial assets.\n\n\nInventory: Tariffs capitalized as inventory without corresponding increases in selling prices may result in inventory costs exceeding their net realizable value, leading to inventory impairment. For inventories measured at lower of cost or market, determining the replacement cost may become challenging due to supply chain disruptions and fluctuating prices.\n\nGoodwill and long-lived assets: Increased costs, changes in customer demand, or supply chain disruptions due to tariffs could give rise to an impairment triggering event.\nIf a quantitative impairment test is required, it may be necessary to adjust previous\nassumptions used in financial projections, such as sales growth, supply costs, tariff costs, and capital spending.\n\u2013  Financial assets: Factoring in certain economically disruptive events likely results in an increase in the allowance for expected credit losses. Companies should consider the impact of tariffs on the information management used in developing its estimate and other factors influencing its estimate, including past events, current conditions, and reasonable and supportable forecasts about the future.\n\n\nGoing concern. Companies may face liquidity challenges if they are unable to sufficiently increase selling prices to offset tariffs or due to decreased customer demand. Management should evaluate how tariffs will affect the company\u2019s ability to meet obligations as they become due. Given uncertainty about the timing and amount of the tariffs, relying on past experiences to establish future expectations may not be appropriate. Overall, management\u2019s going concern assessment may be more complex and require additional judgment.\nIn addition, companies may need to address subsequent events, restructuring provisions, deferred tax asset valuations, and modifications to leases\nor debt. Companies should also evaluate financial statement disclosures, including risks and uncertainties and, if applicable, risk factors required by Regulation\nS-K Item 101, and management\u2019s discussion and analysis required by Regulation S-K Item 303.\nSEC rescinds SAB 121 \u2013 Digital assets\nOn January 23, 2025, the SEC staff issued Staff Accounting Bulletin No. 122 (SAB 122), which rescinds the interpretive guidance in SAB 121. With the rescission of SAB 121, companies that hold digital assets on behalf of others will no longer be required to automatically record a safeguarding obligation liability at the full fair value of those digital assets or make specific disclosures about those assets and related safeguarding obligations. Instead, an entity that has\nan obligation to safeguard digital assets for others should only recognize a liability related to the risk\n*As of March 2025. Find further developments on tariffs at kpmg.com.\n\nof loss under such an obligation, and if so, measure of such liability, by applying the recognition and measurement requirements for liabilities arising from loss contingencies.\nImportantly, SAB 122 does not change the requirement for entities holding or otherwise safeguarding digital assets for others to evaluate whether they \u201ccontrol,\u201d and should therefore recognize on their balance\nsheet, those digital assets. In such cases, the entity is deemed the \u201caccounting owner\u201d of the digital assets and would be required to recognize both the digital assets and a liability reflecting its obligation to return those digital assets to their legal owner.\nAfter adopting SAB 122, existing requirements to provide disclosures that allow investors to understand an entity\u2019s obligation to safeguard digital assets held for others still apply.\nEntities will apply SAB 122 on a fully retrospective basis in annual periods beginning after December 15, 2024. Additionally, entities have the option to apply SAB 122 in any earlier interim or annual financial statement period included in filings with the SEC after January\n30, 2025. On adoption, entities should include clear disclosure about the effects of the accounting changes.\n\nSustainability reporting \u2013 More flux\nA little more than a year after the rule\u2019s adoption, the SEC voted on March 27, 2025, to end its defense of the Climate Rule. This action was not unexpected. In February, SEC Acting Chairman Mark T. Uyeda issued a statement indicating he had asked the court not to schedule arguments related to the Climate Rule.\nAs to more substantive sustainability reporting news, there has been a flurry of state-level climate reporting proposals, the European Commission (EC) has issued major proposals to reduce the burden of sustainability reporting, and the International Sustainability Standards Board (ISSB) is set to propose practical amendments to ease application.\nState-level climate laws\nThe California Air Resources Board (CARB) public consultation period on the California climate laws ended on March 21. CARB has until July 1, 2025, to adopt the underlying regulations. Climate risk reporting following the recommendations of the Task Force on Climate-related Financial Disclosures (TCFD) remains due by January 1, 2026. Our recent webcast discussed what TCFD reporting looks like and how to prepare.\nIn January and February 2025, Illinois, New Jersey, and New York State proposed greenhouse gas (GHG) emissions reporting bills similar (although not identical) to California\u2019s; and Colorado introduced and then\npostponed proposals. New York State also proposed a climate risk reporting bill similar to California\u2019s.\nEU developments\nAt the end of February, the EC released an Omnibus package of proposals to reduce sustainability reporting and due diligence requirements. All of the proposals are subject to change as they progress through the European Parliament and the Council of the EU and are subsequently transposed into national law.\nUnder the proposals, only large (as defined) companies with more than 1,000 employees would be in scope of the Corporate Sustainability Reporting Directive (CSRD) and therefore required to report under European Sustainability Reporting Standards (ESRS). To allow\nthe EC more time to agree on substantive changes to reporting requirements, a two-year postponement in mandatory reporting under ESRS and EU Taxonomy for second- and third-wave companies (currently for fiscal years 2025 and 2026 with a two-year opt-out) has been agreed under a so-called \u201cStop the clock\u201d directive. The directive is pending final adoption to EU law, after which it will be transposed into national law.\nThe EC intends to amend ESRS to substantially reduce the volume of disclosures\u2014e.g., by prioritizing quantitative datapoints over narrative text and clearly distinguishing between mandatory and voluntary datapoints. The concept of double materiality\nwould remain, but the EC intends to provide clearer instructions on applying the materiality principle. The EC no longer plans to adopt sector-specific standards.\nRead our summary of the Omnibus proposals and listen to our podcast.\nISSB developments\nWith respect to measuring GHG emissions, the IFRS\u00ae Sustainability Disclosure Standards leverage the GHG Protocol\u2019s Corporate Standard (2004). As implementation and analysis has progressed, practical\nquestions about applying the requirements have arisen.\nIn January, the ISSB added a project to its agenda to propose targeted amendments to the climate standard, with an exposure draft expected in April 2025. The proposals, which respond to stakeholder concerns,\n\nFor more detail, see the\nKPMG Q1 2025 Quarterly Outlook.\n\nare intended to be pragmatic and will cover the following: alternative global warming potential values, jurisdictional relief to use a method other than the GHG Protocol to measure GHG emissions, disclosing GHG emissions that arise from a company\u2019s financial investments, and disaggregating financed emissions by industry.\n\nStrengthening the CFO\u2013\naudit committee relationship\n\u200c\n\nTheir common goals\u2014quality financial reporting and creating value for the business and its stakeholders\u2014 may be clear, but as CFOs and audit committees grapple with expanding workloads, increased complexity, and ongoing digital disruptions, staying in sync has never been more challenging.\nThe work of the CFO and the finance function has continued to expand beyond financial reporting. CFOs often have responsibility for a range of nonfinancial issues, including sustainability, cybersecurity, artificial intelligence (AI), and digital transformation, as\nwell as managing strategic risks\u2014all of which may require new skill sets on the finance team. Many CFOs today do not have a traditional accounting and financial reporting background. At the same time, the composition of many audit committees has changed to reflect expanded committee oversight responsibilities for a range of risks, many of which are nonfinancial, such as cybersecurity, GenAI, and climate and other environmental and social issues. The expanded role\nof the audit committee means that ongoing education for all members is vital, with some members requiring deeper dives in specific areas.\n\nThe evolving role\nThe traditional CFO focused primarily on financial reporting, which includes the integrity of numbers and the adequacy of internal controls over financial reporting, as well as the internal and external\naudit functions.\nWith a more complex business and risk environment generally, driven by factors including heightened geopolitical risks and uncertainty, emerging technologies, and demands for climate and sustainability reporting, CFOs have taken on more responsibility as strategic leaders, helping set and adjust strategy and key performance metrics and manage risk.\nCFOs now often lead\u2014not just support\u2014technology and innovation projects, and lead or play a key role in enterprise risk management.\nToday\u2019s CFOs lead a finance function that is expected to contribute more to developing and executing business strategy while continuing to effectively carry out its day-to-day financial reporting and control responsibilities. As the CFO\u2019s role has evolved, so has the skill set required for the position. For example, audit committee members tell us that talent management has become one of the most important skills for a CFO. Ensuring that the finance function has the right skills is a continuing challenge, given the talent shortage in accounting and the need for technology professionals with AI-related skills, as well as professionals with environmental, social, and governance expertise. CFOs need to be engaged and visible in establishing a culture and environment that attracts and retains talent.\nOther CFO capabilities emphasized by audit committee members include:\n\n\nUnderstanding the business, industry, market, and competition, and the ability to see \u201cwhat\u2019s coming next\u201d;\n\nCommunicating effectively internally with management and the board and externally with investors, rating agencies, regulators, and bankers; and\n\nUnderstanding and supporting the learning and development needs of the finance team and audit committee.\nGiven that many CFOs may not have traditional accounting backgrounds and deep financial reporting, accounting, and internal control skill sets, a strong accounting team, especially a strong controller, chief accountant, and chief audit executive (CAE), is needed.\n\nSigns of a healthy relationship\nThe relationship between the CFO and the audit committee chair is critical and trust and transparency are key. Developing that relationship takes time and it is the chair\u2019s responsibility, particularly when there is a new CFO, to let the CFO know that they have an ally. The relationship between the CFO and the audit committee can vary depending on the company. For example, at some companies, the audit committee\u2019s primary relationship is with the controller or CAE.\nHowever, even then, the CFO\u2019s personal relationship with the chair is critical and objectivity and skepticism remain essential.\nAudit committee members and CFOs we spoke with offered examples of potential red flags in the\nCFO\u2013audit committee relationship: an audit committee member asks a question and the controller or CAE hesitates before answering, or the audit committee chair learns of bad news from someone other than\nthe CFO. The CFO should deliver any bad news to the audit committee chair directly and in advance of audit committee meetings. The CFO may also find themself in a difficult position if they are not on the same page with the CEO or if the CEO wants to\ncontrol information going to the board. The committee chair can be a sounding board for the CFO in those situations.\nThe cadence of communications between the CFO and audit committee chair is important. Some audit committee chairs told us that they talk with the CFO monthly or even weekly, while others said they talk at least once quarterly to prepare for the audit committee meeting and reach agreement on the agenda and\nattendees. Special circumstances, such as an internal control deficiency or investigation, require additional discussions.\nA key area of audit committee focus is information quality, or getting the right information at the right time, in the right format. The CFO should put numbers and issues of importance to the business and its performance into context without overloading the audit committee with information. Ideally, premeeting materials should highlight issues and be available\nto committee members at least a week before the meeting.\nCFO turnover and bench strength\nAccording to Russell Reynolds Associates\u2019 Global CFO Turnover Index,1 CFO turnover remains high, and CFO tenure reached a five-year low of 5.6 years in 2024.\nThere are a number of reasons for the high CFO turnover rate, including more CFO retirements, more CFOs promoted to CEO positions, more willingness to change CFOs as economic uncertainty becomes the new norm, and high demand for experienced CFOs.\nGiven the CFO\u2019s strategic role, which touches on many critical areas of the business, CFO turnover, particularly when unexpected, poses a significant risk of disruption to a company. A robust CFO succession planning process is essential. A key question for audit committees is whether its CFO succession planning process is keeping pace and evolving to identify the CFO skills, traits, characteristics, and experiences\nnecessary to lead the finance function\u2019s transformation efforts and contributions to developing and executing the business strategy.\n\n\n\n1 Russell Reynolds Associates, Global CFO Turnover Index, August 9, 2024.\n\nCFO succession planning should be an ongoing process that involves developing a robust pipeline of talent and should include:\n\n\nSuccession planning for direct reports to the CFO;\n\nOpportunities for the audit committee to assess bench strength and identify potential CFO successors; and\n\nTraining and development of the members of the finance organization.\nInstitutional investors have been vocal about the importance of human capital and talent development\nprograms and their link to strategy.\nWe expect companies will face an increasingly difficult challenge in finding, developing, and retaining the talent required at all levels of the finance function.\nAudit committees should consider whether the finance function\u2019s talent plan aligns with its strategy and assess which types of talent are needed or are in short supply and how the company will successfully compete for this talent.\nAs their respective roles continue to evolve in response to the changing environment, the relationship between the CFO, the audit chair, and the audit committee must follow suit.\n\n\n\nClaudia H. Allen (left) and Patrick A. Lee\nare senior advisors with the KPMG BLC.\n\n\n\nThis article first appeared in NACD Directorship Magazine.\n\n\nObservations on M&A oversight\n\u200c\nAfter several years of reduced deal volume, companies are looking to revive their mergers and acquisition activity. According to a December survey by KPMG US, 85 percent\nof corporate deal makers said they were evaluating more deals than in the six months prior, primarily seeking to drive growth in the core business, and more than half of those surveyed anticipated a new deal in the first half of 2025. Although valuation continues to be the primary barrier for buyers, interest rates and securing financing remain important considerations, and a third of respondents indicated they are prioritizing organic growth over external acquisitions. Nearly 80 percent of respondents are already using GenAI\nin their M&A process, and even more say they plan to add it soon. These dynamics make board oversight of M&A critical, helping to ensure that deals are aligned with the company\u2019s strategy, that key risks are evaluated, and that integration and other post-deal challenges such as talent and culture are carefully considered.\nIn early March, the KPMG BLC interviewed Kevin Bogle, KPMG Global Lead Partner for Alphabet Inc. and former principal in charge of Deal Advisory and Strategy for the Technology, Media, & Telecommunications practice, for more insights on the deal environment and board challenges.\n\nBLC: How do you expect the M&A landscape to change in the coming year with a new administration in the US and several other jurisdictions?\n\nKevin Bogle (KB): The prevailing sentiment is that the administration will be more business-friendly, primarily due to less regulation, and that means greater certainty around the ability to get deals done. We had noticed an\nuptick in M&A activity with an increase in financial due diligence during the last quarter of 2024, suggesting there could be more deals in 2025 compared to 2024. That would have been consistent with a stronger economic environment, steady interest rates, and technological advancements. Uncertainty, however, has slowed actual activity in the first quarter, as companies try to predict the impact of escalating tariffs around\nthe world.\nThe amount of money in private equity (nearly $3 trillion globally in dry powder) also means that PE will be heavily involved on the buy side. They\u2019ll have to be creative to compete with public companies whose ability to cut deals is fueled by high stock prices (and high valuations). I believe private equity firms will become very innovative, entering into deals and transactions they might not have previously considered, while simultaneously needing to divest a substantial number of assets.\nBLC: What are you seeing as the greatest current barriers to M&A?\nKB: Persistent uncertainty, particularly in geopolitics and cross-border transactions, is always a risk.\nThis affects both buyers and sellers and can cause hesitation and a lack of confidence in making significant financial commitments. Regulatory complexities and potential changes in laws also\n\npose significant hurdles for M&A transactions, as well as the economic uncertainty embedded in tariffs, inflation, valuations, recession fears, and the persistence of higher interest rates. The need for comprehensive due diligence and the integration of\ndiverse company cultures are also challenges that must be navigated carefully to ensure successful mergers and acquisitions. Companies must assess the financial health, operational capabilities, and strategic fit of potential targets, which can be a lengthy and complex process. Lastly, the need to broaden the aperture for companies and talent globally\u2014you need to be looking everywhere\u2014makes pinpointing a deal or target that much harder.\nBLC: How is innovative technology, such as AI, enhancing or impacting the M&A process, both in due diligence and integration?\nWhat about how targets are identified and evaluated?\nKB: In the due diligence phase, AI can automate and streamline the analysis of vast amounts of data, allowing for more efficient and thorough evaluations of potential targets. This technology can identify patterns and insights that might be missed by traditional analysis, ensuring a more comprehensive\nunderstanding of the target company\u2019s financial health, operational efficiency, and potential risks. Additionally, AI can facilitate the integration process by analyzing and predicting the compatibility of different company cultures, operational systems, and strategic goals.\nIn terms of identifying and evaluating targets, AI can leverage data to pinpoint companies that align with the acquirer\u2019s strategic objectives. By analyzing financial metrics, market trends, and competitive landscapes,\nAI can help companies identify the most promising acquisition opportunities. An emerging challenge on the technology side, however, is ensuring that the target\nis compliant with regulations on technology use and data privacy, as well as how that target is using AI and whether the company has guidelines regarding its use.\nBLC: From your experience, where does governance and board oversight add the most value to M&A for acquirers and targets?\nKB: For both acquirers and targets, the board adds the most value by ensuring that the transaction aligns with the company\u2019s strategic objectives and that management is following its own \u201cdeal playbook.\u201d Having such a playbook helps to manage risk and\nfosters transparency and accountability. Boards also provide oversight during the due diligence process, helping to identify and mitigate potential risks and ensure that all legal and regulatory requirements are met. When needed, boards can facilitate communication and collaboration between the acquirer and target, bringing their experience from past deals in helping to integrate (or not integrate) their cultures and operations more effectively and ensuring that the combined entity is well positioned for long-term success.\nBLC: In light of technology and regulatory trends, as well as the competitive landscape, how are boards engaging differently in the M&A process than they have in the past?\nKB: With more data and information driving the M&A process, boards play a critical role in helping the company step back and evaluate whether the deal will genuinely provide shareholder value. The\nincreased access to data allows the board to ask more questions and exercise greater skepticism, ensuring\na thorough diligence process. This enhanced scrutiny not only helps to identify any potential issues but also contributes to a better overall understanding of the transaction, leading to more informed decision-making. Boards are now more focused on understanding the expertise and capacity of third-party advisors in the deal process. How have they been vetted? What\nis their experience? Boards should also be delving deeper into technological considerations, ensuring that management has adequately addressed these aspects to the board\u2019s satisfaction.\nBLC: How do boards assess culture and anticipate challenges that may arise in post- merger integration?\nKB: Culture is one of the hardest areas to get right. I think one of the good things that came out of COVID is that companies are conducting more thorough diligence on people, not just in terms of retention bonuses and compensation, but helping to ensure a strong cultural fit. The board should help the company\nmake that assessment early. Some acquisitions require fast integration to add processes and controls to grow and be successful. In other cases, the company may choose not to integrate at all. Regardless of which option the company takes, that decision can be determined up front, and the board (on both sides)\ncan help to limit surprises and deal-value erosion.\n\nTop geopolitical risks\n\u200c\n\nIn 2025, companies continue to navigate a number of geopolitical risks that are impacting operations and growth. In Top geopolitical risks 2025, KPMG International explores\nfive of the most pressing geopolitical risks companies face in the near term and their potential impacts.\n\n\nShifts in power, economic centers, and trade\nNew trade alliances and investment hubs are redefining global power dynamics. The US is imposing tariffs, eliciting retaliatory responses. New economic \u201cnodes\u201d are emerging outside of traditional investment centers, putting pressure on investment decisions, supply chains, and global footprints.\n\nA complex and fragmented regulatory and tax environment\nRegulations and tax are evolving at different speeds in different geographies. Many countries are adopting a minimum global tax, while others are withdrawing from multilateral tax policy. Global sourcing and supply chain economics are in flux, regulatory and tax compliance has become more complex and costly, and investment in the green transition is coming under question.\n\nA politicized technology landscape\nShifting alliances based on national security concerns and fragmented regulations add to the complexity, while the emergence of new GenAI players challenges US dominance. Regulators are struggling to keep\npace with new GenAI solutions, and a rolling back of\nregulations could leave AI models out of control. Geopolitical competition in AI and other technologies (i.e., quantum computing) is creating technological blocs around the US and China, thus jeopardizing international cooperation and access. Unregulated digital and GenAI solutions could harm ethical reputations.\n\nThreats to supply chains, assets, and infrastructure\nGeopolitical rivalries, trade protectionism, conflict, competition for resources, cyberattacks, and climate events are placing strains on globally exposed businesses. Wars and tensions pose rising threats to key shipping choke points. Countries are adopting protectionist measures to safeguard and diversify\ntheir supply chains, including energy, food, and critical minerals. Supply chains are under pressure, and it\u2019s increasingly tough to secure access to food supplies.\n\nPressures on workforces\n\n\nRead more at Top geopolitical risks 2025.\n\nDemographic shifts, technological advancements, and cultural changes are impacting talent. Workforce challenges are driven by aging populations, mass retirement, falling birth rates in developed markets, changing worker preferences, culture wars, AI integration, and the need for reskilling. Companies in mature economies face a growing talent shortage and must adapt to changing work preferences of younger generations. Evolving immigration policies could also create challenges for talent sourcing and global mobility.\n\nState of AI:\nA boardroom lens\n\u200c\n\u201cRight now, AI shouldn\u2019t just be the top focus for companies. It should be number one, two, and three,\u201d said Erik Brynjolfsson, professor and senior fellow at the Stanford Institute for Human-Centered AI, and director of the Stanford Digital Economy Lab. On our March 20 webcast, Brynjolfsson and Per Edin, Advisory leader for Generative AI, KPMG LLP, discussed the rapid ascent of GenAI, the roll-out of newer GenAI models (such as reasoning models and agentic AI), the economic benefits GenAI can offer\u2014including greater productivity, and board oversight, in a conversation moderated by Claudia Allen, senior advisor at the KPMG BLC.\n\nWatch the webcast replay\n\nEdin highlighted four questions for boards to consider:\n\nFollowing the public launch of ChatGPT in November 2022, many companies moved quickly to evaluate the impact that GenAI would have on strategy and\noperations by selectively testing new tools. According to Edin, about half of companies he\u2019s observed have exited the piloting phase for GenAI. \u201cSome with good results; some with mixed results,\u201d said Edin. \u201cAttention has shifted toward the value equation. The \u2018r\u2019 of ROI is in focus.\u201d\nBrynjolfsson cited a 14% productivity gain in a study he conducted of the call center for a large financial services company. \u201cNot only did resolutions per hour and calls handled per hour go up, but we also found significantly higher customer satisfaction. Employees were happier too,\u201d he said. The large language model the company used was learning from the best employees and using that to teach newer employees who saw productivity increases of 30% to 40%.\nEdin noted that employee adoption and use is one of the key barriers to realizing the benefits of GenAI, followed by data. \u201cAs we move into the scaling\nphase\u2014embedding AI into everyday work\u2014companies are quickly realizing that to make the models effective they need to effectively access the right data\u2014the sales pipeline, the call center records, etc.,\u201d said Edin. Directors should be asking, \u201cWhere is our proprietary data today? How much is in the cloud? How can we accelerate our data platform transition? What about the privacy, governance, and security of data?\u201d\n\n\nAs a board, do we dedicate enough time to strategy overall and specifically to AI?\n\nHow is each member of the management team contributing to the strategy, productivity, and safety of the AI rollout?\n\nHow are we helping our employees adopt these new powerful tools?\n\nFor the CFO, how has the five-year financial forecast changed as a result of AI adoption?\n\u201cToo few companies are taking AI as seriously as they should,\u201d said Brynjolfsson, \u201cand the leaders are going to be the ones that identify the tasks where AI can be most helpful and then use tools to implement AI in a way that creates real business value.\u201d\n\n\n\nWebcast survey results\nConsidering both the risks and opportunities, how would you describe the pace of your company\u2019s adoption of GenAI?*\n\n\nAssertive\n11%\nMeasured\n39%\nReserved\n34%\nUnsure\n16%\n\n* Among 865 self-identified corporate directors surveyed prior to the March 20, 2025, KPMG BLC webcast.\n\n\n\nHow would you describe the processes and controls put in place to monitor the development and use of GenAI at your company?**\n\n\nMature and robust\n6%\nAdequate and improving\n36%\nLimited\n38%\nUnsure\n20%\n\n**Among 859 self-identified corporate directors surveyed prior to the March 20, 2025, KPMG BLC webcast.\n\n\nFor more insights on board oversight of GenAI, see our\n2025 Survey: Boardroom Lens on Generative AI.\n\n\u200cMark your calendar\n\nBLC Quarterly Webcast\nJune 26, 11:00 a.m. ET\nJoin us for our quarterly KPMG BLC webcast as we discuss takeaways and trends from the 2025 proxy season.\nVisit watch.kpmg.us/BLCwebcast.\n\nPodcast: How to use independent directors effectively\nOn demand\nKPMG Private Enterprise Partner Erika Whitmore speaks with KPMG BLC Senior Advisor Claudia Allen about how CEOs can effectively utilize their board members, how private company independent directors can add value, and the importance of succession planning.\nTo register, visit kpmg.com.\n\nSelected reading\nPodcast: CEO succession planning\nOn demand\nKPMG BLC Senior Advisor Annalisa Barrett speaks with Diligent about the growing importance of CEO succession planning in 2025.\nTo listen, visit Diligent.com.\n\nRegulatory signals for \u201cderegulation\u201d KPMG Regulatory Insights\n\nWhere boards aren\u2019t seeing results Russell Reynolds\n\nEthical use of AI in cybersecurity KPMG LLP\n\nBoard disclosures on AI oversight ISS\n\nDelaware enacts amendments to DGCL Richards, Layton & Finger\n\nTo receive articles like these from Board Leadership Weekly, register at kpmg.com/blcregister.\nContact us\nkpmg.com/us/blc T: 800-808-5764\n\nE: us-kpmgmktblc@kpmg.com\n\n\nClaudia H. Allen Senior Advisor KPMG BLC\n\n\nStephen L. Brown Senior Advisor KPMG BLC\nSusan M. Angele Senior Advisor KPMG BLC\n\n\n\nPatrick A. Lee Senior Advisor KPMG BLC\nAnnalisa Barrett Senior Advisor KPMG BLC\n\nAbout the KPMG Board Leadership Center\nThe KPMG BLC champions outstanding corporate governance to drive long term value and enhance stakeholder confidence. Through an array of insights, perspectives, and programs, the BLC promotes continuous education and improvement of public and private company governance. BLC engages with directors and business leaders on the critical issues driving board agendas\u2014from strategy, risk, talent, and sustainability to data governance, artificial intelligence, audit quality, proxy trends, and more. Learn more at kpmg.com/us/blc.\n\nSome or all of the services described herein may not be permissible for KPMG audit clients and their affiliates or related entities.\n\n\n\nLearn about us:    kpmg.com\n\nThe views and opinions expressed herein are those of the authors, speakers, and interviewees and do not necessarily represent the views and opinions of KPMG LLP.\n\nThe information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future.\nNo one should act upon such information without appropriate professional advice after a thorough examination of the particular situation.\n\u00a9 2025 KPMG LLP, a Delaware limited liability partnership and a member firm of the KPMG global organization of independent member firms affiliated with KPMG International Limited, a private English company limited by guarantee. All rights reserved.The KPMG name and logo are trademarks used under license by the independent member firms of the KPMG global organization. USCS027017-3A]]>\n    \n\nCutting through the noise\nWith the post-election landscape still unfolding, navigating the policy and regulatory shifts underway\u2014and assessing the potential upsides and downsides\u2014requires boards and business leaders to be more agile, engaged, and aligned than ever. Cutting through the noise will be challenging. Proactive decision-making amid such uncertainty demands proactive leadership. Stakeholder expectations are also shifting\u2014and shareholders are watching to see how boards respond.\nAs generative AI (GenAI) tools quickly become ubiquitous, and boards seek to help companies balance the risks and opportunities that the technology poses, we look at the current state of GenAI oversight and offer questions for\nboards to consider, with insights from the recent KPMG Board Leadership Center (BLC) webcast and director survey.\nGeopolitics, tariffs, and political uncertainty remain top of mind for boards as we head into the second quarter. In this edition, we highlight five of the most pressing geopolitical risks facing companies in the near term and their potential impacts.\nThis quarter, we also explore how audit committee members and CFOs can maintain a strong working relationship as they each grapple with expanding workloads, increased complexity, and ongoing digital disruptions. And for audit committee members, we provide an update on financial reporting and auditing developments that may impact companies in the near term. Finally, we share observations on the M&A environment and the implications for board oversight.\n\n\nWhat\u2019s inside\n\n\n\n2\n\nFinancial reporting and auditing update\n\n\n\n\n4\n\nStrengthening the CFO\u2013 audit committee relationship\n\n\n\n\n7\n\nObservations on M&A oversight\n\n\n\n\n10\n\n9 Top geopolitical risks State of AI:\nA boardroom lens\n\n\n\n12 Mark your calendar\n\n\nJohn H. Rodi Co-Leader KPMG BLC\nAnne C. Zavarella\n\nCo-Leader KPMG BLC\n\n\u00a9 2025 KPMG LLP, a Delaware limited liability partnership and a member firm of the KPMG global organization of independent member firms affiliated with KPMG International Limited, a private English company limited by guarantee. All rights reserved. USCS027017-3A\n\nDirectors quarterly\nInsights from the Board Leadership Center\n\nApril 2025\n\n\n\nFinancial reporting and auditing update\n\u200c\n\nEffects of US tariffs on financial reporting*\nRecent US tariffs on imports from Mexico, Canada, and China, along with retaliatory tariffs, may cause supply chain disruptions, increased costs, price volatility, and market demand shifts, potentially affecting multiple areas of financial reporting. Rapidly changing tariff policies are creating significant uncertainty about\nthe applicability and duration of the tariffs, which can pose challenges in preparing estimates, assumptions, and projected financial information. Our handbook, Accounting for economic disruption, although not tariff-specific, is a useful tool for evaluating some of these potential impacts.\n\n\nRevenue. Revenue contracts may be revised to address tariff costs or may be affected by changes in customer demand. Companies should carefully consider various aspects of the revenue recognition guidance, including contract modifications, potential price concessions and collectability risk, and the need to revise estimates and judgments such as variable consideration and stand-alone selling prices.\n\nImpairment. Tariffs may result in changes in impairment assessments and conclusions for financial and nonfinancial assets.\n\n\nInventory: Tariffs capitalized as inventory without corresponding increases in selling prices may result in inventory costs exceeding their net realizable value, leading to inventory impairment. For inventories measured at lower of cost or market, determining the replacement cost may become challenging due to supply chain disruptions and fluctuating prices.\n\nGoodwill and long-lived assets: Increased costs, changes in customer demand, or supply chain disruptions due to tariffs could give rise to an impairment triggering event.\nIf a quantitative impairment test is required, it may be necessary to adjust previous\nassumptions used in financial projections, such as sales growth, supply costs, tariff costs, and capital spending.\n\u2013  Financial assets: Factoring in certain economically disruptive events likely results in an increase in the allowance for expected credit losses. Companies should consider the impact of tariffs on the information management used in developing its estimate and other factors influencing its estimate, including past events, current conditions, and reasonable and supportable forecasts about the future.\n\n\nGoing concern. Companies may face liquidity challenges if they are unable to sufficiently increase selling prices to offset tariffs or due to decreased customer demand. Management should evaluate how tariffs will affect the company\u2019s ability to meet obligations as they become due. Given uncertainty about the timing and amount of the tariffs, relying on past experiences to establish future expectations may not be appropriate. Overall, management\u2019s going concern assessment may be more complex and require additional judgment.\nIn addition, companies may need to address subsequent events, restructuring provisions, deferred tax asset valuations, and modifications to leases\nor debt. Companies should also evaluate financial statement disclosures, including risks and uncertainties and, if applicable, risk factors required by Regulation\nS-K Item 101, and management\u2019s discussion and analysis required by Regulation S-K Item 303.\nSEC rescinds SAB 121 \u2013 Digital assets\nOn January 23, 2025, the SEC staff issued Staff Accounting Bulletin No. 122 (SAB 122), which rescinds the interpretive guidance in SAB 121. With the rescission of SAB 121, companies that hold digital assets on behalf of others will no longer be required to automatically record a safeguarding obligation liability at the full fair value of those digital assets or make specific disclosures about those assets and related safeguarding obligations. Instead, an entity that has\nan obligation to safeguard digital assets for others should only recognize a liability related to the risk\n*As of March 2025. Find further developments on tariffs at kpmg.com.\n\nof loss under such an obligation, and if so, measure of such liability, by applying the recognition and measurement requirements for liabilities arising from loss contingencies.\nImportantly, SAB 122 does not change the requirement for entities holding or otherwise safeguarding digital assets for others to evaluate whether they \u201ccontrol,\u201d and should therefore recognize on their balance\nsheet, those digital assets. In such cases, the entity is deemed the \u201caccounting owner\u201d of the digital assets and would be required to recognize both the digital assets and a liability reflecting its obligation to return those digital assets to their legal owner.\nAfter adopting SAB 122, existing requirements to provide disclosures that allow investors to understand an entity\u2019s obligation to safeguard digital assets held for others still apply.\nEntities will apply SAB 122 on a fully retrospective basis in annual periods beginning after December 15, 2024. Additionally, entities have the option to apply SAB 122 in any earlier interim or annual financial statement period included in filings with the SEC after January\n30, 2025. On adoption, entities should include clear disclosure about the effects of the accounting changes.\n\nSustainability reporting \u2013 More flux\nA little more than a year after the rule\u2019s adoption, the SEC voted on March 27, 2025, to end its defense of the Climate Rule. This action was not unexpected. In February, SEC Acting Chairman Mark T. Uyeda issued a statement indicating he had asked the court not to schedule arguments related to the Climate Rule.\nAs to more substantive sustainability reporting news, there has been a flurry of state-level climate reporting proposals, the European Commission (EC) has issued major proposals to reduce the burden of sustainability reporting, and the International Sustainability Standards Board (ISSB) is set to propose practical amendments to ease application.\nState-level climate laws\nThe California Air Resources Board (CARB) public consultation period on the California climate laws ended on March 21. CARB has until July 1, 2025, to adopt the underlying regulations. Climate risk reporting following the recommendations of the Task Force on Climate-related Financial Disclosures (TCFD) remains due by January 1, 2026. Our recent webcast discussed what TCFD reporting looks like and how to prepare.\nIn January and February 2025, Illinois, New Jersey, and New York State proposed greenhouse gas (GHG) emissions reporting bills similar (although not identical) to California\u2019s; and Colorado introduced and then\npostponed proposals. New York State also proposed a climate risk reporting bill similar to California\u2019s.\nEU developments\nAt the end of February, the EC released an Omnibus package of proposals to reduce sustainability reporting and due diligence requirements. All of the proposals are subject to change as they progress through the European Parliament and the Council of the EU and are subsequently transposed into national law.\nUnder the proposals, only large (as defined) companies with more than 1,000 employees would be in scope of the Corporate Sustainability Reporting Directive (CSRD) and therefore required to report under European Sustainability Reporting Standards (ESRS). To allow\nthe EC more time to agree on substantive changes to reporting requirements, a two-year postponement in mandatory reporting under ESRS and EU Taxonomy for second- and third-wave companies (currently for fiscal years 2025 and 2026 with a two-year opt-out) has been agreed under a so-called \u201cStop the clock\u201d directive. The directive is pending final adoption to EU law, after which it will be transposed into national law.\nThe EC intends to amend ESRS to substantially reduce the volume of disclosures\u2014e.g., by prioritizing quantitative datapoints over narrative text and clearly distinguishing between mandatory and voluntary datapoints. The concept of double materiality\nwould remain, but the EC intends to provide clearer instructions on applying the materiality principle. The EC no longer plans to adopt sector-specific standards.\nRead our summary of the Omnibus proposals and listen to our podcast.\nISSB developments\nWith respect to measuring GHG emissions, the IFRS\u00ae Sustainability Disclosure Standards leverage the GHG Protocol\u2019s Corporate Standard (2004). As implementation and analysis has progressed, practical\nquestions about applying the requirements have arisen.\nIn January, the ISSB added a project to its agenda to propose targeted amendments to the climate standard, with an exposure draft expected in April 2025. The proposals, which respond to stakeholder concerns,\n\nFor more detail, see the\nKPMG Q1 2025 Quarterly Outlook.\n\nare intended to be pragmatic and will cover the following: alternative global warming potential values, jurisdictional relief to use a method other than the GHG Protocol to measure GHG emissions, disclosing GHG emissions that arise from a company\u2019s financial investments, and disaggregating financed emissions by industry.\n\nStrengthening the CFO\u2013\naudit committee relationship\n\u200c\n\nTheir common goals\u2014quality financial reporting and creating value for the business and its stakeholders\u2014 may be clear, but as CFOs and audit committees grapple with expanding workloads, increased complexity, and ongoing digital disruptions, staying in sync has never been more challenging.\nThe work of the CFO and the finance function has continued to expand beyond financial reporting. CFOs often have responsibility for a range of nonfinancial issues, including sustainability, cybersecurity, artificial intelligence (AI), and digital transformation, as\nwell as managing strategic risks\u2014all of which may require new skill sets on the finance team. Many CFOs today do not have a traditional accounting and financial reporting background. At the same time, the composition of many audit committees has changed to reflect expanded committee oversight responsibilities for a range of risks, many of which are nonfinancial, such as cybersecurity, GenAI, and climate and other environmental and social issues. The expanded role\nof the audit committee means that ongoing education for all members is vital, with some members requiring deeper dives in specific areas.\n\nThe evolving role\nThe traditional CFO focused primarily on financial reporting, which includes the integrity of numbers and the adequacy of internal controls over financial reporting, as well as the internal and external\naudit functions.\nWith a more complex business and risk environment generally, driven by factors including heightened geopolitical risks and uncertainty, emerging technologies, and demands for climate and sustainability reporting, CFOs have taken on more responsibility as strategic leaders, helping set and adjust strategy and key performance metrics and manage risk.\nCFOs now often lead\u2014not just support\u2014technology and innovation projects, and lead or play a key role in enterprise risk management.\nToday\u2019s CFOs lead a finance function that is expected to contribute more to developing and executing business strategy while continuing to effectively carry out its day-to-day financial reporting and control responsibilities. As the CFO\u2019s role has evolved, so has the skill set required for the position. For example, audit committee members tell us that talent management has become one of the most important skills for a CFO. Ensuring that the finance function has the right skills is a continuing challenge, given the talent shortage in accounting and the need for technology professionals with AI-related skills, as well as professionals with environmental, social, and governance expertise. CFOs need to be engaged and visible in establishing a culture and environment that attracts and retains talent.\nOther CFO capabilities emphasized by audit committee members include:\n\n\nUnderstanding the business, industry, market, and competition, and the ability to see \u201cwhat\u2019s coming next\u201d;\n\nCommunicating effectively internally with management and the board and externally with investors, rating agencies, regulators, and bankers; and\n\nUnderstanding and supporting the learning and development needs of the finance team and audit committee.\nGiven that many CFOs may not have traditional accounting backgrounds and deep financial reporting, accounting, and internal control skill sets, a strong accounting team, especially a strong controller, chief accountant, and chief audit executive (CAE), is needed.\n\nSigns of a healthy relationship\nThe relationship between the CFO and the audit committee chair is critical and trust and transparency are key. Developing that relationship takes time and it is the chair\u2019s responsibility, particularly when there is a new CFO, to let the CFO know that they have an ally. The relationship between the CFO and the audit committee can vary depending on the company. For example, at some companies, the audit committee\u2019s primary relationship is with the controller or CAE.\nHowever, even then, the CFO\u2019s personal relationship with the chair is critical and objectivity and skepticism remain essential.\nAudit committee members and CFOs we spoke with offered examples of potential red flags in the\nCFO\u2013audit committee relationship: an audit committee member asks a question and the controller or CAE hesitates before answering, or the audit committee chair learns of bad news from someone other than\nthe CFO. The CFO should deliver any bad news to the audit committee chair directly and in advance of audit committee meetings. The CFO may also find themself in a difficult position if they are not on the same page with the CEO or if the CEO wants to\ncontrol information going to the board. The committee chair can be a sounding board for the CFO in those situations.\nThe cadence of communications between the CFO and audit committee chair is important. Some audit committee chairs told us that they talk with the CFO monthly or even weekly, while others said they talk at least once quarterly to prepare for the audit committee meeting and reach agreement on the agenda and\nattendees. Special circumstances, such as an internal control deficiency or investigation, require additional discussions.\nA key area of audit committee focus is information quality, or getting the right information at the right time, in the right format. The CFO should put numbers and issues of importance to the business and its performance into context without overloading the audit committee with information. Ideally, premeeting materials should highlight issues and be available\nto committee members at least a week before the meeting.\nCFO turnover and bench strength\nAccording to Russell Reynolds Associates\u2019 Global CFO Turnover Index,1 CFO turnover remains high, and CFO tenure reached a five-year low of 5.6 years in 2024.\nThere are a number of reasons for the high CFO turnover rate, including more CFO retirements, more CFOs promoted to CEO positions, more willingness to change CFOs as economic uncertainty becomes the new norm, and high demand for experienced CFOs.\nGiven the CFO\u2019s strategic role, which touches on many critical areas of the business, CFO turnover, particularly when unexpected, poses a significant risk of disruption to a company. A robust CFO succession planning process is essential. A key question for audit committees is whether its CFO succession planning process is keeping pace and evolving to identify the CFO skills, traits, characteristics, and experiences\nnecessary to lead the finance function\u2019s transformation efforts and contributions to developing and executing the business strategy.\n\n\n\n1 Russell Reynolds Associates, Global CFO Turnover Index, August 9, 2024.\n\nCFO succession planning should be an ongoing process that involves developing a robust pipeline of talent and should include:\n\n\nSuccession planning for direct reports to the CFO;\n\nOpportunities for the audit committee to assess bench strength and identify potential CFO successors; and\n\nTraining and development of the members of the finance organization.\nInstitutional investors have been vocal about the importance of human capital and talent development\nprograms and their link to strategy.\nWe expect companies will face an increasingly difficult challenge in finding, developing, and retaining the talent required at all levels of the finance function.\nAudit committees should consider whether the finance function\u2019s talent plan aligns with its strategy and assess which types of talent are needed or are in short supply and how the company will successfully compete for this talent.\nAs their respective roles continue to evolve in response to the changing environment, the relationship between the CFO, the audit chair, and the audit committee must follow suit.\n\n\n\nClaudia H. Allen (left) and Patrick A. Lee\nare senior advisors with the KPMG BLC.\n\n\n\nThis article first appeared in NACD Directorship Magazine.\n\n\nObservations on M&A oversight\n\u200c\nAfter several years of reduced deal volume, companies are looking to revive their mergers and acquisition activity. According to a December survey by KPMG US, 85 percent\nof corporate deal makers said they were evaluating more deals than in the six months prior, primarily seeking to drive growth in the core business, and more than half of those surveyed anticipated a new deal in the first half of 2025. Although valuation continues to be the primary barrier for buyers, interest rates and securing financing remain important considerations, and a third of respondents indicated they are prioritizing organic growth over external acquisitions. Nearly 80 percent of respondents are already using GenAI\nin their M&A process, and even more say they plan to add it soon. These dynamics make board oversight of M&A critical, helping to ensure that deals are aligned with the company\u2019s strategy, that key risks are evaluated, and that integration and other post-deal challenges such as talent and culture are carefully considered.\nIn early March, the KPMG BLC interviewed Kevin Bogle, KPMG Global Lead Partner for Alphabet Inc. and former principal in charge of Deal Advisory and Strategy for the Technology, Media, & Telecommunications practice, for more insights on the deal environment and board challenges.\n\nBLC: How do you expect the M&A landscape to change in the coming year with a new administration in the US and several other jurisdictions?\n\nKevin Bogle (KB): The prevailing sentiment is that the administration will be more business-friendly, primarily due to less regulation, and that means greater certainty around the ability to get deals done. We had noticed an\nuptick in M&A activity with an increase in financial due diligence during the last quarter of 2024, suggesting there could be more deals in 2025 compared to 2024. That would have been consistent with a stronger economic environment, steady interest rates, and technological advancements. Uncertainty, however, has slowed actual activity in the first quarter, as companies try to predict the impact of escalating tariffs around\nthe world.\nThe amount of money in private equity (nearly $3 trillion globally in dry powder) also means that PE will be heavily involved on the buy side. They\u2019ll have to be creative to compete with public companies whose ability to cut deals is fueled by high stock prices (and high valuations). I believe private equity firms will become very innovative, entering into deals and transactions they might not have previously considered, while simultaneously needing to divest a substantial number of assets.\nBLC: What are you seeing as the greatest current barriers to M&A?\nKB: Persistent uncertainty, particularly in geopolitics and cross-border transactions, is always a risk.\nThis affects both buyers and sellers and can cause hesitation and a lack of confidence in making significant financial commitments. Regulatory complexities and potential changes in laws also\n\npose significant hurdles for M&A transactions, as well as the economic uncertainty embedded in tariffs, inflation, valuations, recession fears, and the persistence of higher interest rates. The need for comprehensive due diligence and the integration of\ndiverse company cultures are also challenges that must be navigated carefully to ensure successful mergers and acquisitions. Companies must assess the financial health, operational capabilities, and strategic fit of potential targets, which can be a lengthy and complex process. Lastly, the need to broaden the aperture for companies and talent globally\u2014you need to be looking everywhere\u2014makes pinpointing a deal or target that much harder.\nBLC: How is innovative technology, such as AI, enhancing or impacting the M&A process, both in due diligence and integration?\nWhat about how targets are identified and evaluated?\nKB: In the due diligence phase, AI can automate and streamline the analysis of vast amounts of data, allowing for more efficient and thorough evaluations of potential targets. This technology can identify patterns and insights that might be missed by traditional analysis, ensuring a more comprehensive\nunderstanding of the target company\u2019s financial health, operational efficiency, and potential risks. Additionally, AI can facilitate the integration process by analyzing and predicting the compatibility of different company cultures, operational systems, and strategic goals.\nIn terms of identifying and evaluating targets, AI can leverage data to pinpoint companies that align with the acquirer\u2019s strategic objectives. By analyzing financial metrics, market trends, and competitive landscapes,\nAI can help companies identify the most promising acquisition opportunities. An emerging challenge on the technology side, however, is ensuring that the target\nis compliant with regulations on technology use and data privacy, as well as how that target is using AI and whether the company has guidelines regarding its use.\nBLC: From your experience, where does governance and board oversight add the most value to M&A for acquirers and targets?\nKB: For both acquirers and targets, the board adds the most value by ensuring that the transaction aligns with the company\u2019s strategic objectives and that management is following its own \u201cdeal playbook.\u201d Having such a playbook helps to manage risk and\nfosters transparency and accountability. Boards also provide oversight during the due diligence process, helping to identify and mitigate potential risks and ensure that all legal and regulatory requirements are met. When needed, boards can facilitate communication and collaboration between the acquirer and target, bringing their experience from past deals in helping to integrate (or not integrate) their cultures and operations more effectively and ensuring that the combined entity is well positioned for long-term success.\nBLC: In light of technology and regulatory trends, as well as the competitive landscape, how are boards engaging differently in the M&A process than they have in the past?\nKB: With more data and information driving the M&A process, boards play a critical role in helping the company step back and evaluate whether the deal will genuinely provide shareholder value. The\nincreased access to data allows the board to ask more questions and exercise greater skepticism, ensuring\na thorough diligence process. This enhanced scrutiny not only helps to identify any potential issues but also contributes to a better overall understanding of the transaction, leading to more informed decision-making. Boards are now more focused on understanding the expertise and capacity of third-party advisors in the deal process. How have they been vetted? What\nis their experience? Boards should also be delving deeper into technological considerations, ensuring that management has adequately addressed these aspects to the board\u2019s satisfaction.\nBLC: How do boards assess culture and anticipate challenges that may arise in post- merger integration?\nKB: Culture is one of the hardest areas to get right. I think one of the good things that came out of COVID is that companies are conducting more thorough diligence on people, not just in terms of retention bonuses and compensation, but helping to ensure a strong cultural fit. The board should help the company\nmake that assessment early. Some acquisitions require fast integration to add processes and controls to grow and be successful. In other cases, the company may choose not to integrate at all. Regardless of which option the company takes, that decision can be determined up front, and the board (on both sides)\ncan help to limit surprises and deal-value erosion.\n\nTop geopolitical risks\n\u200c\n\nIn 2025, companies continue to navigate a number of geopolitical risks that are impacting operations and growth. In Top geopolitical risks 2025, KPMG International explores\nfive of the most pressing geopolitical risks companies face in the near term and their potential impacts.\n\n\nShifts in power, economic centers, and trade\nNew trade alliances and investment hubs are redefining global power dynamics. The US is imposing tariffs, eliciting retaliatory responses. New economic \u201cnodes\u201d are emerging outside of traditional investment centers, putting pressure on investment decisions, supply chains, and global footprints.\n\nA complex and fragmented regulatory and tax environment\nRegulations and tax are evolving at different speeds in different geographies. Many countries are adopting a minimum global tax, while others are withdrawing from multilateral tax policy. Global sourcing and supply chain economics are in flux, regulatory and tax compliance has become more complex and costly, and investment in the green transition is coming under question.\n\nA politicized technology landscape\nShifting alliances based on national security concerns and fragmented regulations add to the complexity, while the emergence of new GenAI players challenges US dominance. Regulators are struggling to keep\npace with new GenAI solutions, and a rolling back of\nregulations could leave AI models out of control. Geopolitical competition in AI and other technologies (i.e., quantum computing) is creating technological blocs around the US and China, thus jeopardizing international cooperation and access. Unregulated digital and GenAI solutions could harm ethical reputations.\n\nThreats to supply chains, assets, and infrastructure\nGeopolitical rivalries, trade protectionism, conflict, competition for resources, cyberattacks, and climate events are placing strains on globally exposed businesses. Wars and tensions pose rising threats to key shipping choke points. Countries are adopting protectionist measures to safeguard and diversify\ntheir supply chains, including energy, food, and critical minerals. Supply chains are under pressure, and it\u2019s increasingly tough to secure access to food supplies.\n\nPressures on workforces\n\n\nRead more at Top geopolitical risks 2025.\n\nDemographic shifts, technological advancements, and cultural changes are impacting talent. Workforce challenges are driven by aging populations, mass retirement, falling birth rates in developed markets, changing worker preferences, culture wars, AI integration, and the need for reskilling. Companies in mature economies face a growing talent shortage and must adapt to changing work preferences of younger generations. Evolving immigration policies could also create challenges for talent sourcing and global mobility.\n\nState of AI:\nA boardroom lens\n\u200c\n\u201cRight now, AI shouldn\u2019t just be the top focus for companies. It should be number one, two, and three,\u201d said Erik Brynjolfsson, professor and senior fellow at the Stanford Institute for Human-Centered AI, and director of the Stanford Digital Economy Lab. On our March 20 webcast, Brynjolfsson and Per Edin, Advisory leader for Generative AI, KPMG LLP, discussed the rapid ascent of GenAI, the roll-out of newer GenAI models (such as reasoning models and agentic AI), the economic benefits GenAI can offer\u2014including greater productivity, and board oversight, in a conversation moderated by Claudia Allen, senior advisor at the KPMG BLC.\n\nWatch the webcast replay\n\nEdin highlighted four questions for boards to consider:\n\nFollowing the public launch of ChatGPT in November 2022, many companies moved quickly to evaluate the impact that GenAI would have on strategy and\noperations by selectively testing new tools. According to Edin, about half of companies he\u2019s observed have exited the piloting phase for GenAI. \u201cSome with good results; some with mixed results,\u201d said Edin. \u201cAttention has shifted toward the value equation. The \u2018r\u2019 of ROI is in focus.\u201d\nBrynjolfsson cited a 14% productivity gain in a study he conducted of the call center for a large financial services company. \u201cNot only did resolutions per hour and calls handled per hour go up, but we also found significantly higher customer satisfaction. Employees were happier too,\u201d he said. The large language model the company used was learning from the best employees and using that to teach newer employees who saw productivity increases of 30% to 40%.\nEdin noted that employee adoption and use is one of the key barriers to realizing the benefits of GenAI, followed by data. \u201cAs we move into the scaling\nphase\u2014embedding AI into everyday work\u2014companies are quickly realizing that to make the models effective they need to effectively access the right data\u2014the sales pipeline, the call center records, etc.,\u201d said Edin. Directors should be asking, \u201cWhere is our proprietary data today? How much is in the cloud? How can we accelerate our data platform transition? What about the privacy, governance, and security of data?\u201d\n\n\nAs a board, do we dedicate enough time to strategy overall and specifically to AI?\n\nHow is each member of the management team contributing to the strategy, productivity, and safety of the AI rollout?\n\nHow are we helping our employees adopt these new powerful tools?\n\nFor the CFO, how has the five-year financial forecast changed as a result of AI adoption?\n\u201cToo few companies are taking AI as seriously as they should,\u201d said Brynjolfsson, \u201cand the leaders are going to be the ones that identify the tasks where AI can be most helpful and then use tools to implement AI in a way that creates real business value.\u201d\n\n\n\nWebcast survey results\nConsidering both the risks and opportunities, how would you describe the pace of your company\u2019s adoption of GenAI?*\n\n\nAssertive\n11%\nMeasured\n39%\nReserved\n34%\nUnsure\n16%\n\n* Among 865 self-identified corporate directors surveyed prior to the March 20, 2025, KPMG BLC webcast.\n\n\n\nHow would you describe the processes and controls put in place to monitor the development and use of GenAI at your company?**\n\n\nMature and robust\n6%\nAdequate and improving\n36%\nLimited\n38%\nUnsure\n20%\n\n**Among 859 self-identified corporate directors surveyed prior to the March 20, 2025, KPMG BLC webcast.\n\n\nFor more insights on board oversight of GenAI, see our\n2025 Survey: Boardroom Lens on Generative AI.\n\n\u200cMark your calendar\n\nBLC Quarterly Webcast\nJune 26, 11:00 a.m. ET\nJoin us for our quarterly KPMG BLC webcast as we discuss takeaways and trends from the 2025 proxy season.\nVisit watch.kpmg.us/BLCwebcast.\n\nPodcast: How to use independent directors effectively\nOn demand\nKPMG Private Enterprise Partner Erika Whitmore speaks with KPMG BLC Senior Advisor Claudia Allen about how CEOs can effectively utilize their board members, how private company independent directors can add value, and the importance of succession planning.\nTo register, visit kpmg.com.\n\nSelected reading\nPodcast: CEO succession planning\nOn demand\nKPMG BLC Senior Advisor Annalisa Barrett speaks with Diligent about the growing importance of CEO succession planning in 2025.\nTo listen, visit Diligent.com.\n\nRegulatory signals for \u201cderegulation\u201d KPMG Regulatory Insights\n\nWhere boards aren\u2019t seeing results Russell Reynolds\n\nEthical use of AI in cybersecurity KPMG LLP\n\nBoard disclosures on AI oversight ISS\n\nDelaware enacts amendments to DGCL Richards, Layton & Finger\n\nTo receive articles like these from Board Leadership Weekly, register at kpmg.com/blcregister.\nContact us\nkpmg.com/us/blc T: 800-808-5764\n\nE: us-kpmgmktblc@kpmg.com\n\n\nClaudia H. Allen Senior Advisor KPMG BLC\n\n\nStephen L. Brown Senior Advisor KPMG BLC\nSusan M. Angele Senior Advisor KPMG BLC\n\n\n\nPatrick A. Lee Senior Advisor KPMG BLC\nAnnalisa Barrett Senior Advisor KPMG BLC\n\nAbout the KPMG Board Leadership Center\nThe KPMG BLC champions outstanding corporate governance to drive long term value and enhance stakeholder confidence. Through an array of insights, perspectives, and programs, the BLC promotes continuous education and improvement of public and private company governance. BLC engages with directors and business leaders on the critical issues driving board agendas\u2014from strategy, risk, talent, and sustainability to data governance, artificial intelligence, audit quality, proxy trends, and more. Learn more at kpmg.com/us/blc.\n\nSome or all of the services described herein may not be permissible for KPMG audit clients and their affiliates or related entities.\n\n\n\nLearn about us:    kpmg.com\n\nThe views and opinions expressed herein are those of the authors, speakers, and interviewees and do not necessarily represent the views and opinions of KPMG LLP.\n\nThe information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future.\nNo one should act upon such information without appropriate professional advice after a thorough examination of the particular situation.\n\u00a9 2025 KPMG LLP, a Delaware limited liability partnership and a member firm of the KPMG global organization of independent member firms affiliated with KPMG International Limited, a private English company limited by guarantee. All rights reserved.The KPMG name and logo are trademarks used under license by the independent member firms of the KPMG global organization. USCS027017-3A]]>\n  \n  \n    Marc Scher: Calling on all HFMA members to keep moving forward\n    https://www.hfma.org/leadership/marc-scher-calling-on-all-hfma-members-to-keep-moving-forward/?utm_campaign=Content_HFMA_Daily_FY25&utm_medium=email&_hsenc=p2ANqtz--SZqdmlZF7IgKksPjPNXZvebhEgOuLUglFfX7G9M5VpbdTAjT3-FK5dIGZxMutD_sEy_Bobdgwg9qivqT-JJU4StVt0w&_hsmi=357423470&utm_content=357423470&utm_source=hs_email\n    readwise:01jsdf042dj2fjysvzv6v0tmd0\n    Tue, 22 Apr 2025 00:40:04 +0000\n    HFMA\n     Skip to main content\n\nIn a year when my theme is Sempre Avanti (Always Forward), I now find myself looking back. It\u2019s humbling for me to reflect on the ways I\u2019ve personally been embraced by members and leaders at HFMA events across the country. It\u2019s especially meaningful to know that the inspiration for this theme \u2014 the bravery and innovation of the nation\u2019s first mountaineering unit, which gave the United States a strategic edge during World War II \u2014 resonated with so many of you.\n\nI remain convinced that making an impact in a dynamic, ever-changing and ever-challenging field like healthcare finance requires us to always be moving in the direction of solutions. And I want to express my recognition and appreciation for a year of collective progress.\n\nThere\u2019s so much innovation taking place throughout the healthcare industry, and healthcare finance is no exception. We heard during last year\u2019s HFMA Annual Conference that innovative organizations embrace risk in the quest to be better. Across the country, I\u2019ve witnessed members embrace this mindset, exploring ways to strengthen innovation while protecting the financial sustainability of their organizations and emphasizing the need for improved access to care, equity and efficiency.\n\nDuring a time when our industry and our Association are at an inflection point \u2014 when the strategies and tools that worked in overcoming yesterday\u2019s challenges are no longer sufficient for meeting today\u2019s pressures or tomorrow\u2019s threats \u2014 our members are changing the paradigm to ensure future success.\n\nIn confronting some of the most difficult issues in our industry, like the need to improve payer-provider relations, we\u2019ve consistently demonstrated a desire to do what\u2019s right, together, in service to our communities.\n\nWe\u2019ve explored the introduction of new technologies, like AI, through the lens of value, understanding that achieving ROI from AI depends on identifying the right use cases, establishing governance for AI innovation and building on successes and lessons learned \u2014 including from our peers.\n\nAnd we\u2019ve seen leaders create energy and momentum around doing the right things and the hard things to advance the mission of healthcare organizations on behalf of the communities they serve and the industry.\n\nI\u2019m looking back in gratitude for all that I\u2019ve experienced as HFMA Chair, for the people I\u2019ve met and the connections that I\u2019ve made at national, regional and chapter events. As we prepare for a new HFMA Chair, I\u2019m also looking forward, excited to be part of all that is to come and work alongside you in deepening our collective impact.\n\nThese are exciting times, and there is so much yet to be done. We need to make sure we\u2019re moving always forward, knowing that there is tremendous opportunity in simply being willing to take risks for the greater good.\n\nWe continue to face the greatest challenges of our careers on many fronts. But with an always-forward mindset, I know that we are up for the challenge.\n\nSempre Avanti!\n\nMarc B. Scher, FHFMA, CPA\n\n See All Articles \n\n\nSome content could not be imported from the original document. View content \u2197 \n\n\nSome content could not be imported from the original document. View content \u2197 ]]>\n     Skip to main content\n\nIn a year when my theme is Sempre Avanti (Always Forward), I now find myself looking back. It\u2019s humbling for me to reflect on the ways I\u2019ve personally been embraced by members and leaders at HFMA events across the country. It\u2019s especially meaningful to know that the inspiration for this theme \u2014 the bravery and innovation of the nation\u2019s first mountaineering unit, which gave the United States a strategic edge during World War II \u2014 resonated with so many of you.\n\nI remain convinced that making an impact in a dynamic, ever-changing and ever-challenging field like healthcare finance requires us to always be moving in the direction of solutions. And I want to express my recognition and appreciation for a year of collective progress.\n\nThere\u2019s so much innovation taking place throughout the healthcare industry, and healthcare finance is no exception. We heard during last year\u2019s HFMA Annual Conference that innovative organizations embrace risk in the quest to be better. Across the country, I\u2019ve witnessed members embrace this mindset, exploring ways to strengthen innovation while protecting the financial sustainability of their organizations and emphasizing the need for improved access to care, equity and efficiency.\n\nDuring a time when our industry and our Association are at an inflection point \u2014 when the strategies and tools that worked in overcoming yesterday\u2019s challenges are no longer sufficient for meeting today\u2019s pressures or tomorrow\u2019s threats \u2014 our members are changing the paradigm to ensure future success.\n\nIn confronting some of the most difficult issues in our industry, like the need to improve payer-provider relations, we\u2019ve consistently demonstrated a desire to do what\u2019s right, together, in service to our communities.\n\nWe\u2019ve explored the introduction of new technologies, like AI, through the lens of value, understanding that achieving ROI from AI depends on identifying the right use cases, establishing governance for AI innovation and building on successes and lessons learned \u2014 including from our peers.\n\nAnd we\u2019ve seen leaders create energy and momentum around doing the right things and the hard things to advance the mission of healthcare organizations on behalf of the communities they serve and the industry.\n\nI\u2019m looking back in gratitude for all that I\u2019ve experienced as HFMA Chair, for the people I\u2019ve met and the connections that I\u2019ve made at national, regional and chapter events. As we prepare for a new HFMA Chair, I\u2019m also looking forward, excited to be part of all that is to come and work alongside you in deepening our collective impact.\n\nThese are exciting times, and there is so much yet to be done. We need to make sure we\u2019re moving always forward, knowing that there is tremendous opportunity in simply being willing to take risks for the greater good.\n\nWe continue to face the greatest challenges of our careers on many fronts. But with an always-forward mindset, I know that we are up for the challenge.\n\nSempre Avanti!\n\nMarc B. Scher, FHFMA, CPA\n\n See All Articles \n\n\nSome content could not be imported from the original document. View content \u2197 \n\n\nSome content could not be imported from the original document. View content \u2197 ]]>\n  \n  \n    2025-ReliaQuest-Annual-Threat-Report\n    https://readwise.io/reader/document_raw_content/279994081\n    readwise:01jrjm3y7qrxydz86k6k7hntzs\n    Fri, 11 Apr 2025 14:30:03 +0000\n    readwise.io\n    \n\nAnnual\nCyber-Threat\nReport\n\n\nExecutive Summary: 2024 At A Glance\nTwo- Thirds\nOf Critical Hands-on- Keyboard Incidents Involved Legitimate Software\n\nIncident Metrics and Breach Details\n\n3 Minutes\nLowest Mean Time to Contain (MTTC)\nUsing Automated Response Playbooks\n48 Minutes\nAverage Time from Initial Access to\nLateral Movement, or \u201cBreakout Time\u201d\n \n\nInadequate Logging\nTop Cause of Breaches\n85%\nOf Incidents Involved\nCompromised Service Accounts\n \n\nMalware and Threat Actors\n\nSocGholish\nTop Malware Thanks to New Python Tactics\n\nAsyncRAT\nRises From 4th to 2nd Place Among Top Malware Threats\n\nMicrosoft Teams\nAbused for Social Engineering by Black Basta\n\nUnited States\nRegion with the Most Targeted Victims\n\nInitial Access Techniques\n\nPhishing\nTop Initial Access Technique\n\n30\n%\nOf Phishing Messages\n\n1 in 4\nActive Intrusions Started\nManufacturing & Professional Services\nSectors with the Most Targeted Victims\nfor the 2nd Year Running\n\n45\n%\nInvolved Credential Harvesters\nwith Exploitation of Public-Facing Applications\n\n100\n%\n478,000\nLumma Listings on Criminal Marketplaces\n\n4 hr 29 min\n5,253\nOrganizations Named on Ransomware Data-Leak Sites\n\n80%\nOf Hands-on-Keyboard Intrusions Began with Abuse of External Remote Services Like VPNs\nOf Deployed MFA Controls Bypassed via Session Hijacking in Successful Business Email Compromise (BEC) Attacks\nFastest Exfiltration Time\nOf Breaches Featured Exfiltration vs 20% with Encryption\n\n3 Recommendations Organizations Can\u2019t Afford to Ignore\n\nIncorporate AI and Automation into Security Operations\nAttackers are adopting AI and automation to supercharge common attacks. That means it\u2019s no longer optional for organizations to use AI and automation to their own advantage.\n\nWhen integrated into a security operations platform, these technologies can help contain threats rapidly, drive down response times, and allow security teams to focus on tackling\nmore complex challenges.\n\nAgentic AI, which can autonomously handle alerts end-to-end, shows particular promise for SecOps.\nBarricade Common Entry Points: Phishing, Drive-By Compromise, Public-Facing Assets, and External Remote Services\nPhishing and drive-by compromise were the top initial access methods, while public-facing assets and internet-facing external remote services fueled active intrusions.\nMitigate these risks by securing remote services (e.g., with client-based certificates) and monitoring public-facing assets.\nPatching promptly is key; attackers are moving faster than ever, fueled by an abundance of available credentials.\nEliminate Blind Spots:\nDeny Attackers Any Opportunity\nMost \u201chands-on-keyboard\u201d breaches resulted from insufficient logging and unmanaged devices. Manage your attack surface and eliminate blind spots by deploying an endpoint security solution across all assets.\nEnable detailed logging for all devices, including endpoints and servers, to capture user activity, system changes, and network traffic.\nReview log retention periods for hot and cold storage and establish clear procedures for retrieving cold storage logs during investigations.\n\n\nTable of Contents\n\nIntroduction: 2024 in Review\u2014Fast Threats\nDemand Faster Responses                  1\nInadequate Logging Responsible for Most\nBreaches in 2024                          2\nBreaking In: The Trends Shaping Initial\nAccess Tactics                          3\nOld Habits Die Hard: Attackers\u2019 Most Frequent\nInitial Access Techniques                     4\nPhishing Trends: The Tactics Honing Cybercrime\u2019s\nMost Reliable Weapon                            5\nSession Hijacking Bypassed MFA in Every Successful\nBEC Incident in 2024 8\nSocial Engineering: How Attackers Weaponize\nMicrosoft Teams                               10\nGreyMatter Automations for Combatting\nEmail Attacks                                 12\nCritical Entry Points: VPN and Voice Phishing Among Most-Successful Techniques                  13\nAbuse of External Remote Services Led to 45%\nof Hands-on-Keyboard Intrusions                   14\n23% of Active Intrusions Initiated via Exploitation\nof Public-Facing Applications                     16\nVoice Phishing Behind 14% of Breaches 18\nAccess via Cloud Accounts and Trusted\nRelationships Achieved in 9% of Intrusions 20\nGreyMatter Automations for Combatting\nUnauthorized Access                            22\nSocGholish Secures Top Spot Again\nin 2024 Malware List                       23\nSocGholish Persists in First Place with Python          24\nScreenConnect Abuse Propels AsyncRAT to\nSecond Place                                 26\nCopy, Paste, Compromised: Lumma Rises to\nThird Place with Innovative Tactics                  28\nGreyMatter Automations for Combatting Malware      30\n48 Minutes to Breakout: Unmasking\nPost-Compromise Trends                  31\nAn Attacker\u2019s Route to Control                32\nWhy RDP Became the Tool of Choice for\nLateral Movement                              32\nValid Accounts, Invalid Intent: Easy Access to\nPrivilege Escalation                             34\nThe Adversary\u2019s Toolkit: Post-Exploitation Essentials     36\nGreyMatter Automations for Combatting Legitimate\nTool Abuse                                   38\nRansomware Decoded: Exfiltration Is the\nNew Encryption                           39\nExfiltration Outpaces Encryption in Modern Breaches 39\nRansomware in 2024: Increased 11.9%, Hit New Highs 41\nGreyMatter Detections and Automations for\nCombatting Ransomware                         45\nNext Steps: A CISO\u2019s Checklist              46\n\n\n\u200cIntroduction: 2024 in Review\u2014Fast Threats Demand Faster Responses\u200c\u200c\nIn 2024, speed became more important than ever in defending against cyber threats.\n\n48 Minutes\nAttackers are moving at unprecedented speeds\u2014last year, upon gaining initial access, they achieved lateral movement in an average of 48 minutes and managed to exfiltrate data in as little as 4 hours.\n\nAttackers are also getting better at adapting to and evading the  latest security controls, making the adoption of AI and automation imperative for organizations. Using AI and automation to tackle initial access attempts not only strengthens defenses but also empowers analysts to focus on what matters most: detecting and investigating the stealthiest and most impactful intrusions.\nThough attackers are moving faster, they\u2019re still using tried-and-tested methods like phishing to achieve initial access. They cast a wide\n\n1\n\nnet, indiscriminately targeting organizations with minimal effort and often causing significant damage. The year\u2019s high count of disclosed vulnerabilities provided cybercriminals with entry points, while software suppliers remained a top target as a way to infiltrate organizational networks.\n\nRansomware and extortion remained critical threats compared to 2023, but the dynamics have shifted. Affiliates splintered into smaller groups, while leaked ransomware source code on cybercriminal forums sparked a wave of new attackers on the scene, with many focused entirely on data exfiltration. The result is a more fragmented, but no less dangerous, ransomware ecosystem.\n\n\nIn a world of accelerated attacks, automation is the ultimate ally for defenders. ReliaQuest customers using Automated Response Playbooks in 2024 saw a dramatic improvement in response times, with the fastest mean time to contain (MTTC) cyber threats as low as 3 minutes. In comparison, customers yet to implement Automated Response Playbooks reported an average MTTC of 6.3 hours.\nAdditionally, in August 2024, ReliaQuest launched its first-of-its-kind AI agent for security operations, further speeding up containment of threats with better accuracy and consistency. By seamlessly handling routine Tier 1 and Tier 2 tasks and executing response actions securely, the GreyMatter AI Agent eliminates errors and delivers unparalleled efficiency in accelerating remediation times, allowing security teams to upskill by focusing on more critical tasks.\nBy automating 100% of the investigation process\u2014including data aggregation, analysis, and response\u2014the GreyMatter AI Agent has reduced the average MTTC for ReliaQuest customers to less than 5 minutes.\n\nAt ReliaQuest, we remain committed to helping organizations strengthen their security posture and take control of their defenses.\nOur Annual Cyber-Threat Report presents an in-depth analysis of the most critical cyber threats observed from January 1 to December 31, 2024. Find out the emerging tactics, techniques, and procedures (TTPs) employed by adversaries and benchmark your security defenses against our findings to identify key areas for improvement.\nSecurity leaders can use these findings to refine their cybersecurity strategies, address coverage gaps, and enhance employee awareness of evolving threats.\n\n\u200cInadequate Logging Responsible for Most Breaches in 2024\u200c\nOur analysis of 2024 customer breaches revealed five critical security control failures at the core of these incidents. Neglecting or underestimating these foundational security practices leaves organizations exposed\u2014regardless of how sophisticated or varied an attacker\u2019s methods may be. Addressing these weaknesses within networks is essential to avoid becoming the next target.\n\n\nUnmanaged Devices\nDevices without security controls like endpoint protection or monitoring agents create security gaps, providing attackers with open pathways throughout networks.\n\nExternal Exposure\nVulnerabilities in internet-facing devices serve as entry points for attackers to infiltrate the network.\nInsufficient Logging\nInsufficient monitoring or logging leaves parts of the system vulnerable, making it impossible to detect or investigate malicious activity.\n\n2\n\nFive Critical\n\nInsecure VPN\nVPNs lacking essential protections like multifactor authentication (MFA) or device-based certificates allow attackers\nto exploit stolen credentials and gain network access.\n\nHelp-Desk Procedural Flaws\nWeak help-desk protocols make organizations easy targets for social engineering attacks, with 14% of breaches in 2024 involving social engineering for initial access or privilege escalation.\n\n\u200cBreaking In:\u200c\n\nFirst...\nWe'll examine phishing and business email compromise (BEC) attacks, which are increasingly bolstered by advanced tactics like bypassing MFA and abusing Microsoft Teams for social engineering.\nThen...\n3\n\nWe\u2019ll dissect the initial access techniques with the highest success rates, including targeting external remote services (boosted by a 250% surge in initial access brokers [IABs] offering VPN access), compromising cloud accounts, and conducting voice phishing attacks.\nFinally...\nWe\u2019ll review the top malware shaping today\u2019s threat landscape, with \u201cSocGholish\u201d leading the charge.\n\nRead On To\n\n\n\n\n\u200cOld Habits Die Hard: Attackers\u2019 Most Frequent Initial Access Techniques\u200c\n\nThe consistency in top-ranked initial access techniques from 2023 to 2024 highlights their effectiveness and reflects attackers\u2019 strategy of indiscriminately targeting a wide pool of victims.\nPhishing and drive-by compromise remain go-to methods, powered by the scalability and affordability of phishing-as-a-service (PaaS) and malware-as-a-service (MaaS) offerings.\nThese services allow attackers to flood inboxes with phishing campaigns or lure victims to malicious websites through manipulated search engine results.\n\nWhile most initial access attempts are blocked early, when successful, these broad-spectrum attacks can pave the way for more advanced threats, highlighting the importance of understanding their mechanics.\n\nThrough our analysis of phishing emails reported to the GreyMatter Phishing Analyzer, we uncovered:\n\n2024\n25\n%\n\n2023\n33%\nDrive-By Compromise\n\n\nThe most prevalent types of malicious email sent\n\nThe trigger words used to boost email open rates\n\nThe tactics designed to trick recipients into clicking malicious links\n24\n%\n22%\nPhishing with Link\n\nWe\u2019ll also look at one of the top concerns for CISOs\u2014BEC\u2014by demonstrating how attackers leverage simple phishing techniques to bypass MFA and execute these high-impact attacks.\nFinally, we\u2019ll explore adversaries' weaponization of a trusted communication platform to worm their way into networks.\n9\n%           \n19\n%\nReplication via Removable Media\n\n4\n\n\n\nCredential Harvesters\n\nDominated as the most reported category of malicious emails, with fake Microsoft login portals being the most common type. These emails lure victims to fraudulent websites designed to steal credentials, often to lay the groundwork for larger attacks like BEC.\nEnhanced by AI, credential harvesting emails now feature much more polished language, fewer errors, and highly convincing designs, making them an increasingly effective and scalable weapon for cybercriminals.\n\nTo expose the tactics behind the number-one cyber threat facing enterprises today, we turned to the GreyMatter Phishing Analyzer:\u200c\n\n\nA tool designed to automate the triage of employee-reported phishing emails, enabling faster identification and remediation of malicious activity.\n\n\n\nScam Emails\n\nCrafted to solicit money or extract confidential employee information, scam emails were also widespread in 2024.\n\nThis data is collected from phishing emails that evaded detection by email security gateways and provides insight into adversaries\u2019 phishing techniques.\nData from the GreyMatter Phishing Analyzer revealed that nearly 30% of phishing messages that made it past traditional email security tools involved credential harvesters, often disguised as fake Microsoft login portals.\n\nReconnaissance Emails\n\nAnother common type of email sent was single-word or blank emails\u2014 known as reconnaissance emails\u2014which are used to verify whether an account is active (i.e., no bounce-backs are received) or to gauge the likelihood that the inbox owner might respond.\n\nWe also identified any financial-themed keywords attackers used to create a sense of urgency and the trusted platforms they abused to make phishing campaigns appear more legitimate.\nKnowing what to look for in phishing emails not only helps predict attacker strategies but also sharpens employee training, turning your workforce into a powerful first line of defense against phishing attacks.\n\n\nMalware-Laden Emails\n\nAttackers also sent a significant volume of malware-laden emails containing attachments or URLs to deploy malicious files upon download.\n\nNearly 30% of Reported Phishing\n5\n\nEmails Contained Credential Harvesters\n\n\npause, verify suspicious emails, and think critically\n\n\nURGENT:\nKeywords That Hook\n\nTraining end users to\nbefore taking action is key to disrupting attackers\u2019 strategies and reducing the success of phishing attempts.\n\n\n\nNotification\n\nOrder\n\nUpdate\n\nDocument\n\nRef\n\nPDF\n\nPlease\n\nNotice\n\nBusiness\n\nPassword\n\nSign\n\nReport\n\n\nRequest\n\nInvoice\n\nAccount\n\nPayment\n\nRequired\n\nReview\n\nAction\n\nReminder\n\n1. Invoice\n2. Order\n3. Payment\n4. Request\n\n12. Remittance\n\n11. Account\n\n10. Bank\n\n9. Transfer\n\n8. Tax\n\n7. Statement\n\n6. Purchase\n\n5. Receipt\n\nAttackers use deceptively urgent language to manipulate victims into engaging with phishing emails.\nThey understand that a sense of urgency often overrides caution, causing recipients to act hastily without evaluating risks.\n\nFinancial keywords like \u201cpayment,\u201d \u201cinvoice,\u201d and \u201cstatement\u201d dominated phishing email subject lines and filenames last year.\n\nThis tactic is particularly effective because phishing emails that mimic financial statements blend seamlessly into\n6\n\nroutine tasks, like processing invoices or reviewing account statements, catching users off guard.\n\nFigure 3: Top sender domains\n\nAttackers\u2019 Favorite Email Providers and File-Sharing Platforms\n\nFree email providers like Gmail and file-sharing platforms like Dropbox and Docusign were among the top tools used in phishing campaigns last year.\nThese platforms are highly trusted and widely used in business, making it easy for attackers to exploit the trust users place in them.\n\n\nfakedEmail.com\n\nPhishing emails leveraging these tools appear more genuine and are therefore harder to spot.\n\nFree email services allow attackers to remain anonymous by enabling them to quickly create new accounts and replace blocked ones, while file-sharing platforms are perfect for hosting malicious files or hiding phishing links.\n\n7\n\nTo counter these tactics, businesses must fine-tune their email security tools to catch suspicious activity that hides behind a veil of legitimacy. Employees must also carefully scrutinize links or emails from trusted platforms, as attackers rely on this very trust to bypass defenses and infiltrate organizations.\n\n\nTake Action\n\n\n\n\nTarget Website\n\n\u200cBEC is one of the most dangerous methods attackers use to achieve their financial objectives.\u200c\n\nThese attacks often start with a phishing email\u2014frequently sent from a compromised partner\u2014containing a link to an attacker-controlled website. This site acts as an adversary-in-the-middle (AiTM), intercepting MFA requests and session tokens from the legitimate login portal.\nWith the stolen session tokens, the attacker can authenticate to the service without needing credentials or access to the MFA-enrolled device, effectively bypassing both.\n\nUser\n\n 1  User enters their password into phishing site\n\nPhishing Site\n\n 2  Phishing site forwards the credentials to legitimate site\n\nTo stay under the radar while executing their strategies, attackers often use commercial VPNs to mask their activities:\n\n 4  Phishing site displays MFA prompt from legitimate site to the user\n\n 3  Legitimate site sends MFA screen in response\n\n\n\nExpress VPN\n\nSurfEasy VPN\n\nSurfshark VPN\n\nHide My Ass VPN\n\nNord VPN\n\nPrivate Internet Access VPN\n\n 5  User\ncompletes MFA authentication\n\n 6  Phishing site forwards MFA response to legitimate site\n\nThe combination of a high success rate and devastating impact makes BEC a top security concern for organizations.\nBy analyzing real-world compromises of corporate employee email accounts, we\u2019ve identified the key tactics attackers rely on, what makes them so successful, and, most importantly, the steps defenders must take to stop them.\n\n 8  Phishing site redirects the user to another page\n\n8\n\n 7  Legitimate site issues a session cookie\n\nHere are our key takeaways\n\nFigure 4: How AiTM phishing bypasses MFA and steals session tokens\n \n\nMFA Isn\u2019t Foolproof: In every incident where MFA was configured, attackers managed to bypass it by stealing session tokens through AiTM phishing. Session token interception is now a standard feature in modern phishing toolkits, reducing the level of technical expertise required to bypass MFA.\n\nTrust Is a Weapon: 9 out of 10 phishing emails came from hacked accounts at trusted partner organizations, exploiting established relationships to successfully deceive targets.\n\nAttackers Hide Their Tracks: After hijacking a session, attackers used VPNs to conceal their allowing them to bypass location-based detections and evade regional access-control\n\nCompromised Accounts Spread the Attack Internally: In 80% of cases, compr\nwere used to send phishing emails to other employees within the same organization.\nBusiness Email Camouflage\n\n\n9\n\n Take Action \n\n\n\u200cBlack Basta Exploits Microsoft Teams for Initial Access\u200c\nThroughout 2024, ReliaQuest observed the ransomware group \u201cBlack Basta\u201d employing a new social engineering tactic that leverages Microsoft Teams for initial access.\nBy compromising legitimate Microsoft Entra ID tenants or creating fraudulent ones, the group impersonates IT support or help-desk staff to deceive targeted users into engaging with malicious Teams messages.\n\nBlack Basta typically begins the attack by spamming users with hundreds of phishing emails.\nShortly after, the attackers follow up with either a phone call or a Teams chat message (see Figure 5).\nThese messages often originate from external accounts with display names like \u201cHelp Desk\u201d\nFigure 5: Sample external Microsoft Teams message request (source: microsoft[.]com)\n\nor \u201cSupport Team,\u201d intentionally crafted to appear both legitimate and urgent to increase the \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0  likelihood of user interaction.\n\nOnce attackers establish contact, they manipulate victims into downloading remote monitoring\nand management (RMM) tools, such as Quick Assist or AnyDesk, under the guise of providing \u00a0\u00a0\u00a0\u00a0\u00a0  support sessions. These tools grant attackers the ability to install and execute malicious files, \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0  facilitating initial access to the organization\u2019s network.\nIn some cases, attackers have also been observed persuading\n10\n\nusers to download malicious files themselves\u2014such as scripts \u00a0\u00a0\u00a0\u00a0\u00a0  or executables\u2014via QR codes, further expanding their arsenal \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0  of social engineering techniques.\n\n\n\nManipulating Trust: Social Engineering Through Familiar Platforms\n\nAs this is a relatively new technique, most organizations have yet to take appropriate defensive measures. Unlike phishing, which is commonly mitigated with security controls and user training, this approach targets less-secured communication channels where users are more likely to engage with malicious activity.\nWe predict with high confidence that this technique will gain popularity among cybercriminals, largely due to the ease of creating new Microsoft Entra ID tenants, making these accounts disposable and easily replaced if blocked. This tactic highlights why social engineering remains one of the most effective forms of initial access.\n\nBy exploiting human trust in familiar platforms, threat actors significantly increase their chances of success compared to traditional phishing techniques.\n\nAs Black Basta and other threat groups continue to innovate, organizations must prioritize addressing these vulnerabilities. Implementing strict controls on external Teams communication, monitoring for anomalous activity\u2014such as messages originating from unexpected locations or using suspicious naming conventions\u2014and providing robust user training are critical.\nWithout these preventative measures in place, these increasingly sophisticated social engineering campaigns are likely to be successful.\n\n\n11\n\n Take Action \n\n\n\n\u200cRecommended Automated Response Playbooks\u200c\n\n\nBlock Domain:                                        Block Email Domain:\n\n\nRecommended Threat Hunting Packages\n\n\nPhishing\u2014Microsoft Teams:\n\nPhishing\u2014Spearphishing Attachments:\n\nHygiene\u2014MFA Modifications:\n\n12\n\nGreyMatter Automations for Combatting Email Attacks\nTo counter the evolving tactics behind phishing, BEC, and social engineering attacks, ReliaQuest offers its customers a proactive defense strategy through its Automated Response Playbooks.\nThese Playbooks automatically contain and respond to threats, significantly improving MTTC and minimizing potential damage.\nAdditionally, GreyMatter offers out-of-the-box and custom threat hunting packages that are built to\nidentify specific attacker techniques and behaviors.\nBy leveraging the end-to-end automation capabilities of GreyMatter, organizations can detect, respond to, and neutralize threats in minutes.\n\n\n\n\u200cCritical Entry Points: VPN and Voice Phishing Among Most-Successful Techniques\u200c\n\nIn 2024, GreyMatter continued to serve as a critical line of defense, swiftly detecting and containing the vast majority of initial access attempts observed. Among all the attempts analyzed in the previous section, only a tiny fraction\u2014just 0.02%\u2014managed to bypass its defenses.\n\nWhile these successful techniques represent only a very small proportion, they demand close attention, as they allowed threat actors to engage in\nhands-on-keyboard activity, taking real-time control of compromised systems.\n\nIn this section, we focus on the critical 0.02% of successful attempts, examining how attackers used social engineering tactics in addition to exploiting external services, public-facing applications, cloud infrastructure, and trusted relationships.\n\nWe\u2019ve also included real-world examples to illustrate the damage these techniques can inflict and outlined clear steps to mitigate these risks.\nBy prioritizing defenses against these methods, organizations can significantly reduce the risk of attacks escalating into lateral movement, privilege escalation, or data exfiltration.\n\n9%     Cloud\n\n13\n\n9%\n\nTrusted Relationship\n\n\nFigure 6: Successful initial access methods in 2024\n\n45%\nExternal Remote Services\n23%\nPublic-Facing Applications\n14%\nPhishing with Voice\n\n\n\u200cLast year, threat actors were most successful in gaining network access via external remote services like VPN portals, Remote Desktop Protocol (RDP), and virtual desktop infrastructure (VDI).\u200c\n\nThese trusted services act as gateways to an organization\u2019s internal network, allowing attackers to slip past traditional perimeter defenses and gain direct access to sensitive systems and data.\n\nOnce inside, adversaries exploit the trust inherent in these services to operate under the radar, carrying out data theft, lateral movement, or ransomware attacks\u2014all while evading detection. In some cases, they also plant backdoors for future intrusions.\n\nExternal remote services rely on valid account credentials for authentication, but attackers can easily overcome this hurdle by:\n\nBrute-Forcing Passwords\nMining Data Breaches\nPurchasing Credentials from Online Marketplaces\n \n\nIABs are the middlemen in this ecosystem, selling stolen credentials\u2014often obtained through information-stealing malware (infostealers)\u2014to various threat actors, including ransomware affiliates, so they can launch devastating attacks with ease.\n\n14\n\nOnce exposed, data may be leaked or sold online, leaving organizations to face severe reputational and regulatory consequences.\n\nThe rise in attacks targeting external services has fueled a growing demand for accesses, and IABs are meeting this demand at premium prices:\nIAB listings offering access via VPNs surged by 250% between 2023 and 2024.\n\nThe average \u201cbuy now\u201d price for these listings climbed 46%, increasing from $2,370 to $3,455.\n\n74%\n63%\n55%\n\nFigure 7: IAB listings in 2024 by sector\n \n\nManufacturing        Construction           Retail          Education\nBusiness Services\nFinance      Software    Health Care   Government\nMedia & Internet\n\nWhile all industries are targeted for initial access, certain sectors are more heavily sought after than others.\n\nManufacturing, for example, is a prime target due to its reliance on legacy systems, extensive use of remote access, and prioritization of operational continuity over credential hygiene best practices. If IABs can easily infiltrate a network in a particular industry, they are more likely to target other organizations in the same sector, assuming they have the same weaknesses in security practices.\n\n\nTake Action\n\n\n15\n\n\n2023   2024\n\n\u200cBetween 2023 and 2024, adversaries targeting public-facing applications increased by 3%, a trend highly likely fueled by the 2,000-plus critical vulnerabilities identified last year.1\u200c\n\nThese critical vulnerabilities\u2014which are remotely exploitable, require no privileges or user interaction, and are characterized by low complexity\u2014are an attractive opportunity for attackers.\n\nWith minimal effort, a single exploit can breach multiple organizations, delivering significant returns on investment for cybercriminals.\n\nAlthough fewer critical vulnerabilities were identified in 2024 compared to the 4,000-plus seen in 2023, a surge in proof-of-concept (PoC) exploits likely leveled the playing field,\ngiving lower-skilled attackers more opportunities to strike. PoC exploits are easily deployable bits of code designed to demonstrate vulnerabilities, making it easier to test or exploit security weaknesses.\nIn 2024, PoC exploits were released for all three of the most-exploited vulnerabilities, turning opportunistic attacks into focused campaigns. With these ready-made tools in hand, attackers\u2014regardless of skill level\u2014had a clear and easy path to exploitation.\n\nMost Exploited Vulnerabilities of 2024\n\n\n\nCVE-2024-1708 affecting ConnectWise ScreenConnect\n\nCVE-2024-50623 impacting Cleo Harmony, VLTrader, and LexiCom\n\n16\n\n\n\nCVE-2024-3400 targeting Palo Alto GlobalProtect\n\n\n\nWhen PoCs are released, the clock starts ticking; attackers rush to exploit vulnerabilities at scale before organizations can respond.\n\nLockBit Finds a Key in ScreenConnect\n\nTo stay ahead, organizations across all sectors must prioritize securing external-facing assets,\nas these are prime targets for rapid, opportunistic attacks the moment exploits become available.\n\nThe information sector emerged as the primary target for public-facing application attacks, largely due to its reliance on software that often inadvertently leaves critical assets exposed, like customer service platforms, hosting infrastructure, and interconnected systems.\n\n\n17\n\n Take Action \n\n\n\u200cSocial engineering is far from new, but it remains one of threat actors\u2019 most effective tools, allowing them to exploit human trust to infiltrate organizations.\u200c\nAttackers frequently deceive users into downloading malicious software or manipulate IT help desks into resetting credentials and disabling MFA. To deceive help-desk personnel, attackers gather employee information such as full names, addresses, and Social Security numbers.\n\nVoice phishing is especially concerning.\n\nFigure 8: A user offers corporate calling services in multiple languages on forum XSS\n\n18\n\nIt circumvents all technical defenses, instead directly targeting an organization\u2019s people. Employees tricked by these tactics not only risk exposing sensitive information but also open the door for attackers to deploy malware, allowing them to steal the data themselves.\n\n\nThe manufacturing sector was the top target for phone-based social engineering attacks, with attackers likely taking advantage of its frequent IT interactions and lenient help-desk policies designed to handle high volumes of support requests.\n\n\nTo overcome language barriers, threat actors are now advertising multilingual calling services, while English-speaking attackers are using their language fluency to secure initial access on behalf of Russian-speaking ransomware groups.\nWhen Help Desks Become Gateways: Social Engineering Hits Health Care\n\nThese attackers are using messaging apps like Telegram and traditional cybercriminal forums to advertise their services, as shown in Figure 8. The post advertises:\n\nWe call corporations, doing it as effectively as possible. We know who to contact and how to communicate with them. Every language in the world is available.\n\nOur callers are experienced in this type of calling. Backed by many successful cases, we work with serious partners. Terms can be discussed via Tox. 24/7 service (translated from Russian)\n\nThis new shift shows that social engineering has evolved into a globalized and increasingly sophisticated threat.\n\ncampaign\n\nsocial engineering\n\n Take Action \n\n19\n\n\nAttacks on customer cloud services like Amazon Web Services (AWS) and Azure rose by 4% between 2023 and 2024, a trend driven by the growing adoption of cloud platforms and the improved resiliency of on-premises systems.\u200c\nBut attackers are adapting to this shift, lured by the broad attack surface and vast amounts of sensitive data these platforms offer.\n\nAdversaries are also abusing trusted relationships, like those with third-party service providers that offer on-premises or cloud services, to infiltrate organizations.\nBy targeting partners with weaker security controls, attackers can follow a \u201cone-to-many\u201d approach:\nCompromise one organization and exploit its connections to breach more-secure partners.\n\nIn some cases, attackers return to previously breached entities that have since been acquired to exploit weaknesses a second time around.\n\n20\n\nAs cloud adoption grows and business ecosystems become more interconnected, organizations need robust security across every link in the chain.\n\n\nOrganizations in the professional, scientific, and technical services (PSTS) sector are the most frequent targets of cloud-based attacks, likely due to the sensitive nature of the data they manage, such as intellectual property and client information.\n\nThe following factors also make cloud environments ripe for exploitation:\nWhen Trust Backfires: How Silk Typhoon Exploited a Third-Party Account for Azure Access\n\n\nMisconfigurations\n\nWeak Access Controls\nGaps in the Shared Responsibility Model\n \n\n\n21\n\n Take Action \n\n\n\n\u200cRecommended Automated Response Playbooks\u200c\n\n\nBlock IP:                                             Reset Password:\n\n\nRecommended Threat Hunting Packages\n\n\nSuccessful MFA from High-Risk Country:\n\nAWS Enumeration:\n\nPassword Manager Access to Sensitive Secrets\u2014Credential Access:\n\n22\nGreyMatter Automations for Combatting Unauthorized Access\nFor the best protection against the initial access techniques outlined in this section, ReliaQuest customers should use the following Automated Response Playbooks and threat hunting packages in GreyMatter.\nThese tools are designed to disrupt and respond to unauthorized access attempts, reducing the risk of further compromise and lateral movement within an environment.\n\n\n\n\nWhile SocGholish held its top spot as the\nbiggest malware threat\u2014largely thanks to its new Python infection chain used for persistence\u2014the \u201cAsyncRAT\u201d remote-access trojan (RAT) and \u201cLumma\u201d (aka LummaC2) infostealer climbed the ranks.\n\n\u200cSocGholish Secures Top Spot Again in 2024 Malware List\u200c\nThe malware threats observed in customer environments throughout 2024 revealed a relentless evolution in tactics and preferred variants, as attackers continued refining their methods to outpace defenders.\nAsyncRAT used legitimate software like ScreenConnect to infiltrate systems with stealth and precision. Lumma, on the other hand, doubled its sales of stolen credentials and turned to novel techniques, such as coercing users to copy and paste malicious PowerShell code via fake CAPTCHAs. With over 478,000 Lumma-related listings\non criminal marketplaces, including credentials used to breach major platforms like Snowflake, the stakes for defenders are at an all-time high.\nIn this section, we\u2019ll examine these malware variants in detail, focusing on their new tactics and the factors behind their increased popularity.\n\nPercentage of 2024 Incidents by Malware Variant                                 Percentage of 2023 Incidents by Malware Variant\n\nAsyncRAT                7%\n\nLumma            5%\n\n23\n\nGootLoader       4%\nQakBot\n\nAsyncRAT         8%\n\nGootLoader       7%\n16%\nSocGholish\n19%\nRaspberry Robin\n19%\nCobalt Strike\n3%\nSocGholish\n23%\n\n\n\u200cNamed for its deceptive use of social engineering and \u201cghoulish\u201d tactics, SocGholish remains a dominant force on the malware scene.\u200c\n\nIt\u2019s primarily distributed through infected websites that rank highly in search engine results or through phishing emails that redirect victims to these sites.\nOnce on the infected website, victims are tricked into downloading a malicious JavaScript file disguised as a legitimate browser update.\nThis file grants attackers remote access to the victims\u2019 systems, enabling serious consequences like data exfiltration, system encryption, and other high-impact threats that can devastate organizations.\nWindows Command Shell\n\n44%\n\nPowerShell\n\nAdditionally, 2024 saw a surge in \u201cone-off\u201d malware variants like \u201cBroomstick\u201c and \u201cMatanbuchus.\u201d\nThese evolving trends highlight the increasingly diverse and unpredictable nature of the malware landscape, emphasizing the critical need for proactive defenses and rapid response strategies.\n\nFigure 9: Top command and scripting interpreters\n\n\nAlthough SocGholish maintained its position as the most frequently observed malware in 2024,\nwe saw infostealers written in C, Rust, and C++ rise in popularity, as evidenced by Lumma's ascent to\nthird place.\n\n30%\n\nJavaScript\n\n6%\n\n11%\n\nVisual Basic\n\n4%\n\nUnix Shell\n\nPython\n\n24\n\nAutoHotKey & AutoIT\n\n2%\n2%\n \n\n\n\nDespite the shifting statistics, SocGholish continues to pose a significant global threat to organizations.\nFebruary 2024 saw its biggest advancement:\nA new infection chain that uses Python for  persistence, likely as a means to evade traditional security tools.\n\nBy using a second-stage download from the trusted domain python[.]org, this adaptation significantly enhances the malware\u2019s ability to bypass defenses and remain undetected.\nWhile defenders are well-prepared to detect malicious activity through common tools like the Windows command shell and PowerShell (see Figure 9), Python is rarely seen in malware deployments.\n\nThis relative unfamiliarity and limited detection coverage likely prompted the SocGholish team to incorporate Python into their operations, exploiting a blind spot in many security strategies. This change in tactic underscores that adversaries are not only aware of existing security controls but are actively engineering\nways to outmaneuver them.\n\n25\n\nAs a result, SocGholish continues to cement its position as a persistent and sophisticated threat to organizations worldwide.\n\n\nTake Action\n\n\n\u200cFigure 10: AsyncRAT x ScreenConnect infection chain\u200c\n\nThe powerful AsyncRAT gives attackers full control over infected\nhosts, enabling keylogging, credential theft, malware delivery\u2014including ransomware\u2014as well as C2 operation.\nTo complicate matters, it also has botnet capabilities for launching denial-of-service (DoS) attacks.\n\nUser Clicks Malicious Link in Phishing Email\n\nUser is Redirected to Malicious Site\n\nScreenConnect is Downloaded and Connects to Relay Server, Establishing C2\n\n\nThis versatility has made AsyncRAT a favorite among threat actors, and 2024 marked a defining year for the trojan, as it contributed to the second-most customer incidents over the year, up from fourth in 2023.\n\n\nAsyncRAT uses the guise of legitimate software to infiltrate systems, exploiting users\u2019 trust to evade security mechanisms, blend into normal network traffic, and deceive users into downloading malicious files\u2014all while remaining undetected.\nAsyncRAT is Dropped and Executed via Screen- Connect Connection\nAsyncRAT File Uses Valid Code-Signing Certificate to Bypass Antivirus\nAutoIT Scripting Utility is Installed\n\n26\n\nMalicious AutoIT Script is Executed and Injected into RegAsm.exe Windows Process\nRegAsm.exe Connects to Attacker\u2019s C2 server\nAttacker Places .url File in Startup Folder to Establish Persistence\n\n\nBy incorporating ScreenConnect into its methodology, AsyncRAT has achieved increasing success.\nHowever, as defenders adapt to these tactics, we expect its dominance to wane in 2025.\n\nIn July 2024, we identified a campaign in which phishing emails were sent to trick individual recipients into downloading ScreenConnect software (see Figure 10).\n\nOnce installed and connected to the attackers\u2019 ScreenConnect server, an executable\u2014equipped with a code-signing certificate capable of bypassing antivirus and Endpoint Detection and Response (EDR) tools\u2014deployed AsyncRAT onto the victim\u2019s system.\nThis incident demonstrates the critical importance of understanding what\u2019s \u201cnormal\u201d in your environment to quickly detect and respond to anomalies.\n\n\nTake Action\n\n\n27\n\n\n\n\n\n\u200cAsyncRAT\u200c\n\n\nLumma (+8)\n\n\nGootloader\n\n\nCobalt Strike\n\n\nImpacket\nClimbing from eleventh place in our 2023 rankings to third in 2024, Lumma is an infostealer malware that harvests sensitive data like browsing history, cookies, saved credentials, and cryptocurrency wallets.\n\n1  SocGholish\n\nThe stolen data is sold on criminal marketplaces\nas infostealer logs, typically priced around $10 each. Distributed through malicious websites, trojanized software, and phishing attacks, Lumma operates\nas a MaaS model, providing subscribers with continuous updates and support.\n\nLumma\u2019s growth has been explosive.\n\n\n8\n\n\nRaspberry Robin\n\n9  Clearfake\n\n\n\nDanaBot\n\n28\n\n\nDarkGate\nIts credential sales nearly doubled each quarter in 2023, and it maintained an upward trajectory in 2024.\n\n\n7  Netsupport RAT\n\n478,000 Listings\nLast year alone, more than 478,000 listings\non criminal marketplaces originated from Lumma infections, which coincided with a 4% increase in infected customer environments.\n\nIn May 2024, ReliaQuest observed Lumma being installed via a novel execution technique: coercing users into manually copying and pasting malicious PowerShell code into the console via fake browser errors or CAPTCHAs (see Figure 11).\nThis tactic was likely designed to evade traditional signature-based security detections, showcasing the attackers\u2019 relentless innovation to ensure the malware\u2019s continued success.\n\nLumma\u2019s popularity among threat actors stems from its active support for its users, frequent updates, and advanced evasion capabilities that make it highly effective for data exfiltration.\nIts logs provide attackers with direct access to internal networks and cloud platforms.\nDespite Lumma\u2019s steep subscription fees\u2014as high as $1,000 per month\u2014many attackers are willing to pay the price, as the stolen credentials yield far greater returns.\n$1,000/\nMonth\nCorporate\n$500/\nMonth\nProfessional\n$250/\nMonth\nExperienced\n\n\n29\n\nTo defend against Lumma and similar infostealer malware, organizations must include infostealers in their threat models, as stolen data can provide attackers with access to critical assets. Notably, the May 2024 breach of the Snowflake cloud platform2 was allegedly traced back to stolen credentials obtained from infostealer logs.\n\n\nTake Action\n\n\n\n\n\u200cRecommended Detection Rules\u200c\n\n\nPowerShell Obfuscated Script:\n\nWScript Executing Suspicious File:\n\nIsolate Host:\n\nDelete File:\n\n30\n\nGreyMatter Automations for Combatting Malware\nTo combat the sophisticated techniques used by top malware threats, ReliaQuest customers can enable targeted detection rules that identify malicious activity, such as obfuscated PowerShell scripts and drive-by downloads.\nIn addition, deploying appropriate Automated Response Playbooks in GreyMatter allows for rapid\ncontainment and removal of threats.\nTogether, these proactive measures help organizations minimize the impact of malware infections and prevent further compromise.\n\n\u200c48 Minutes to Breakout:\u200c\nrends\n\nIn the section we break down...\n\nThe top techniques used by attackers in 2024 to navigate networks and escalate privileges\nThe tools they employed to stay hidden\nThe growing trend of prioritizing data theft over encryption.\n\nWe\u2019ll also explore\n\n\n\n\n\u200cAn Attacker\u2019s Route to Control\u200c\n\n\n\nFirst, we\u2019ll look at the top techniques: RDP became the most common method for lateral movement, while internal spearphishing doubled year over year, leveraging employee trust and dark-web phishing kits to compromise multiple accounts.\n\n\nThen, we\u2019ll explore how privilege escalation centered around valid accounts, with 85% of breaches involving compromised service accounts. This enabled attackers to evade detection and move laterally within minutes\nof initial access.\n\n\nFinally, we\u2019ll highlight their growing reliance on legitimate tools like Impacket, WinRAR, and RMM software to maintain control and execute attacks. These tools, used in 60% of hands-on-keyboard incidents, seamlessly blend into normal activity, making their abuse significantly harder to detect.\n  \nThe period between initial access and lateral movement is known as breakout time. In our analysis of customer incidents from 2024, we found that attackers achieved an average breakout time of just 48 minutes.\n\n\u200cPercentage of 2024 Incidents by Lateral Movement Technique         Percentage of 2023 Incidents by Lateral Movement Technique\n\nIn 2024, RDP topped the list as the most-used tool for lateral movement, giving attackers a straightforward method to connect to other internal systems within an environment. Originally designed as a legitimate remote management tool for IT help desks to assist global workforces, RDP\u2019s built-in presence on Windows systems has made it a favorite among attackers.\nArmed with stolen credentials, attackers can use RDP to discreetly move between systems, blending into regular network activity without triggering alarms  that malware might. Its simplicity, stealth, and ability\nto easily connect to systems makes RDP a go-to tactic for lateral movement\u2014and its misuse shows no signs of slowing down.\n\n26%\n\nRemote Desktop Protocol\n\n16%\n\nInternal Spearphishing\n\n14%\n\nSSH & SMB/Windows Admin Shares\n23%\n\nSMB/Windows Admin Shares\n\n15%\n\nRemote Desktop Protocol\n\n8%\n\n32\n\nInternal Spearphishing\n\nFigure 12: RAMP forum user selling access and suggesting phishing internal users\n\nInternal spearphishing, a technique sometimes used in BEC attacks, doubled in frequency from 2023 to 2024, rising to become the second most common tactic for lateral movement.\n\n\nInternal spearphishing involves attackers compromising a user account and using it to send phishing emails to other users within the same organization, potentially compromising multiple accounts at once.\nThe significant rise in internal spearphishing can likely be attributed to the 200% increase in phishing kit mentions on the dark web between 2023 and 2024.\n\nThese phishing kits\u2014tools designed to help attackers with little to no technical expertise launch phishing attacks\u2014can bypass MFA and lower the barrier to entry for attackers. This is especially true when paired with services on cybercriminal forums that offer or sell access to hundreds of active email accounts (see Figure 12).\nAs a result, advanced phishing campaigns have become accessible to attackers of any skill level.\n\nBy exploiting the inherent trust that employees place in internal emails, attackers achieve far higher success rates with internal phishing compared to external campaigns. Given its success, this growing threat demands that organizations prioritize security awareness training and implement internal phishing simulations to assess system and user readiness.\n\n\nTake Action\n\n\n33\n\n\n\u200cAttackers are abusing high-privileged, valid accounts at both the domain and local levels to achieve short breakout times. Once inside an environment, attackers quickly assess the permissions of the compromised account. Basic accounts rarely provide the keys to the castle, so to establish persistence or move laterally, attackers must escalate privileges to gain the elevated access they need.\u200c\nOur findings revealed that when attackers needed to escalate privileges, valid domain accounts were their primary targets\u2014a trend unchanged from 2023. These accounts, whether owned by users, administrators, or services, are frequently exploited because they offer the access and stealth attackers need to advance their operations without detection. This trend is reflected on cybercriminal forums: For instance, we observed a user on the Russian-language forum XSS seeking advice on how to gain admin-level privileges to compromise a domain controller (DC) (see Figure 13).\nControl over a DC opens the door to countless opportunities for attackers\u2014they can map the network, access most connected devices, and steal sensitive data\u2014making them a prized target.\n\n22%\n11%\n7%\n \n\n34\n\nLocal accounts also remain a key focus for threat actors, ranking second place for most-common privilege escalation technique year after year. Stored on individual systems, local accounts include standard user accounts, service accounts, and the Windows default administrator account, and are often targeted in brute-force attacks. Because systems are guaranteed to have local accounts, attackers can bypass the need to identify specific users, speeding up their efforts to compromise systems.\nPercentage of 2024 Incidents by Privilege Escalation Technique\nPercentage of 2023 Incidents by Privilege Escalation Technique\nDomain Accounts\nLocal Accounts\nSetuid and Setgid\nDomain Accounts\nLocal Accounts\nDLL Injection\n\nFigure 13: XSS user turns to other forum users for help on escalating privileges\nScattered Spider\u2019s Web of Social Engineering Unravels Privileges\n\nScattered Spider\n\nMalware- or exploit-based attacks are noisy and can be easy to detect. But, by exploiting valid accounts, attackers make it difficult for organizations to distinguish malicious actions from legitimate activity,\na fact they take advantage of.\n\n\nThe longer attackers remain undetected, the greater the risk they pose\u2014whether through lateral movement, data theft, or deploying malicious payloads.\n\n\nWithout strong security controls, these trusted accounts can turn into an organization\u2019s vulnerability. Between January and July 2024, 85% of customer breaches involved compromised service accounts, allowing attackers to operate under the radar for extended periods.\n\n\n35\n\n Take Action \n\n\n\n\u200cIn the past, adversaries relied heavily on frameworks like Cobalt Strike and PowerShell exploits for C2.\u200c\nHowever, enhanced detection measures have made these methods increasingly risky for attackers.\nTo evade modern defenses, they are now turning to commercial applications for malicious operations (CAMO), leveraging legitimate tools such as AnyDesk and PDQ Deploy to maintain C2 and progress through every stage of the kill chain\u2014from scanning networks to deploying ransomware.\nBetween January and August 2024, ReliaQuest saw a 16% increase in the use of legitimate tools in hands-on-keyboard incidents compared to 2023, with such tools accounting for 60% of cases.\nThese trusted tools have become the backbone of modern attacks, enabling attackers to avoid detection while inflicting maximum damage. Cybercriminals\u2019 increased reliance on legitimate tools outlines the need for organizations to understand how these\n\nFigure 14: RMM tools favored by attackers\n\nNext, we'll detail the most common tools attackers used in breaches during 2024 and steps you can take to mitigate these risks.\n\napplications are being weaponized to bypass defenses.\nLegitimate RMM Tools Top Choice to Maintain C2\n\nOriginally designed for IT professionals to manage infrastructure, RMM tools pose serious security risks when left unsecured. Their legitimacy allows attackers to slip past defenses, evading detection by appearing benign. Attackers also exploit RMM tools in social engineering campaigns, posing as help-desk support to trick users into granting remote access.\nBy mimicking routine IT operations, they seamlessly integrate into workflows, maximizing the effectiveness of their attacks while avoiding suspicion.\nTo mitigate these risks, organizations must recognize the risks of RMM tool abuse, incorporate it into their threat models, and establish a baseline for normal RMM tool usage to quickly distinguish normal activity and malicious behavior.\n\n\n1. AnyDesk\n\n2. TeamView\n \n\n\n4. Jwrapper\n\n5. Dameware\n \nImpacket Now Go-To Post-Compromise Tool\n\nOriginally designed to interact with network protocols like SMB, New Technology Local Area Network Manager (NTLM), and Lightweight Directory\nAccess Protocol (LDAP), Impacket has become a go-to post-compromise tool for attackers, appearing in 33% of breaches in 2024.\nThis Python-based tool set is favored for lateral movement but also offers extensive capabilities\u2014such as credential dumping, Kerberoasting, and more\u2014that make it highly versatile and portable for\npost-compromise operations.\n\n\n3. QuickAssist\n\nAlthough Impacket is susceptible to signature-based detections, adversaries often exploit poorly monitored environments and take advantage of Impacket\u2019s use of legitimate protocols like SMB, Windows Management Instrumentation (WMI), and LDAP. It\u2019s realistically possible that adversaries adapt how they use Impacket to mimic normal network activity, making their actions harder to distinguish from legitimate behavior and appear non-malicious.\n36\n\n\n6. ATERA\n\nThese shifting tactics emphasize the importance of ensuring comprehensive network traffic logging and adequate security tool coverage to detect Impacket itself as well as the network behaviors it generates.\n\n\nFile-Compression Tools Gain Popularity Among Attackers\nAttackers are increasingly using legitimate file-compression tools like WinRAR and 7-Zip to compress staged data before exfiltration, replacing the compression features traditionally built into C2 frameworks.\nAdversaries often use these tools in combination with cloud utilities like Rclone and MegaSync to exfiltrate data to cloud storage. Because the activity generated by these tools often doesn\u2019t appear inherently malicious, organizations should establish a baseline for their usage and implement security controls to differentiate between legitimate and malicious activity.\nThe message is clear: Attackers lean on legitimate tools because they\u2019re easily accessible\u2014many are open source\u2014and incredibly versatile, allowing them to execute multiple actions at once. By using trusted tools, attackers blend seamlessly into legitimate network traffic, avoiding suspicion and complicating detection efforts, especially if an organization has no baselines for normal\nuse in place. For businesses, this camouflage can have devastating consequences. The longer attackers remain undetected in a network, the greater the risk of major data breaches or operational disruptions\u2014both of which can shatter an organization\u2019s reputation and result\nin the loss of key talent or critical business opportunities.\nMedusa Turns Everyday Tools into Weapons\n\nMedusa\n\n\n37\n\n Take Action \n\n\n\u200cTerminate Active Sessions:                              Reset MFA:\u200c\n\nNetwork Discovery Tooling:\n\nRemote Desktop Audit:\n\nImpacket Utilization:\n\n38\n\nGreyMatter Automations for Combatting Legitimate Tool Abuse\nTo combat threat actors' misuse of legitimate tools, ReliaQuest\ncustomers can leverage GreyMatter Automated Response Playbooks to quickly contain attacker activity.\nAdditionally, GreyMatter threat hunting packages enable customers to proactively detect abuse of legitimate tools within their networks.\nTogether, these actionable measures empower security teams to disrupt attacker access and put a stop to the unauthorized use of commonly trusted tools.\n\n\u200cRansomware Decoded: Exfiltration Is the New Encryption\u200c\nRansomware tactics have undergone a dramatic transformation. What began as straightforward extortion through system encryption grew into \u201cdouble extortion,\u201d where attackers compounded encryption with the threat of leaking stolen data to maximize pressure on victims. Now, many attackers are abandoning encryption altogether, focusing solely on data theft\u2014a faster, more profitable approach. In 2024, this trend accelerated, with only 20% of breaches still featuring encryption. In this section, we\u2019ll...\n\n\nExamine this rise of exfiltration-only attacks\n\nUncover the tools and methods driving these campaigns\n\nBreak down the major developments in the 2024 ransomware landscape\n  \nFrom the decline of key players to the emergence of new ones, we\u2019ll explore the twists, turns, and trends to watch. Most importantly, we\u2019ll provide actionable recommendations to help organizations defend against these evolving threats\u2014and demonstrate how ReliaQuest can keep organizations ahead of the curve.\n\n\n\n\u200cExfiltration Outpaces Encryption in Modern Breaches\n\nWhen most people think of ransomware, they picture locked systems, black screens, and ransom notes\u2014but that\u2019s no longer always the case.\nFastest Exfiltration in 2024\n4 hours 29 mins\n\nFastest Encryption in 2024\n6 hours\n\nOur data reveals a major shift in ransomware tactics: Of all breaches we observed in 2024, 80% involved data exfiltration, while only 20% included encryption.\nThis sea change is almost certainly driven by the growing adoption of advanced security tools and robust backups, which have diminished the impact of encryption-based attacks. Additionally, the process of restoring encrypted systems can be so lengthy and complex that organizations are likely choosing to rebuild their systems instead. This approach has the added benefit of ensuring that any persistence mechanisms left by the attacker are completely removed. As encryption becomes less effective, groups like \u201cInc Ransom\u201d now weaponize stolen data for extortion, resale, or access to additional targets, preying on organizations\u2019 fears of reputational damage, regulatory fines, and the exposure of sensitive information.\n39\n\nThe time required for an adversary to progress from initial access to executing data exfiltration is 34% faster than the time needed for encryption; the quickest exfiltration time we saw in 2024 clocked in at just 4 hours and 29 minutes, compared to 6 hours for encryption. This leaves defenders with even less time to detect and respond before critical data is stolen. By bypassing the technical complexities of encryption, attackers have embraced data exfiltration as their ultimate tool to strike quickly, inflict maximum harm, and maintain leverage over their victims.\n\n\n\nIn 2024, 60% of attackers who successfully exfiltrated data in the incidents we examined sent the stolen data to cloud storage platforms such as Google Drive, Mega, or Amazon S3.\n\nThese services are highly useful for stealthy exfiltration, as stolen data can be uploaded quickly and disguised within legitimate traffic from commonly used platforms. This makes detection more difficult for defenders because the exfiltration activity blends in with normal business operations. Given the potential for business disruption, blocking access to widely used cloud platforms is rarely a viable option for businesses. This limits defenders\u2019 ability to be proactive, instead forcing them to rely on advanced monitoring and alerting to identify and respond to malicious activity.\nAccounting for the remaining 40% of attacks, exfiltration over C2 channels enables attackers to funnel data directly to their own infrastructure.\n\nThis method requires a direct connection from the compromised system to the attacker\u2019s infrastructure, making the malicious activity more likely to be detected. However, despite this increased risk, C2-based exfiltration offers attackers greater control over the stolen data compared to third-party platforms like cloud services. This method is utilized by adversaries who don\u2019t use legitimate tools in their operations, such as RMM tools, and instead prefer the built-in capabilities of C2 frameworks to compress, encrypt, and exfiltrate data.\nLooking ahead to 2025, we expect the trend of exfiltration-only attacks to persist, with exfiltration times likely to drop even further. For organizations, this shift demands a rethink of ransomware recovery strategies. The focus can no longer be solely on restoring encrypted systems\u2014strategies must also address protecting data privacy, managing reputational risks, and ensuring compliance with regulatory requirements. To prepare, CISOs must implement defenses to detect and prevent exfiltration attempts while developing playbooks that prioritize business continuity and resilience against these evolving ransomware tactics.\n\n\nTake Action\n\n\n40\n\n\n\u200cIn 2024, the names of 5,253 organizations were listed on ransomware data-leak sites\u2014559 more than in 2023.\u200c\n\n\nAlthough this growth may seem modest, much of 2024 actually saw a slowdown in ransomware activity. Instability within the ransomware ecosystem played a significant role,\nas ransomware-as-a-service (RaaS) providers focused more on competing for affiliates than refining their attack techniques. Operations were further disrupted by law enforcement actions dismantling key ransomware infrastructure, improvements in security tool detection capabilities, and advancements in cybersecurity practices.\nBut the slowdown didn\u2019t last. December 2024 marked a grim turning point, recording the highest-ever victim count in a single month. This surge can be attributed to the explosion of new ransomware groups, which have grown from around 60 active groups in 2022 to nearly 100 today. To avoid the spotlight and scrutiny faced by larger operations like LockBit, smaller, decentralized groups are forming, fueling an increasingly crowded and competitive landscape. As a result, attackers are likely to push for higher ransoms and adopt more sophisticated strategies to outpace defenses and secure their share of the profits.\n\n\n\n\n\n314\n\n2024\n\n2023\n\n347\n\n271\n\n379\n\n424\n\n400\n\n316\n\n527\n\n600\n\n317\n\n457        463\n\n382\n\n439\n\n357\n\n401\n\n459\n\n542\n\n404\n\n584\n\n483\n621\n\n299\n\n161\n\n41\n\nJanuary      February      March        April         May         June         July        August     September     October     November    December\n\n\nFigure 15: Ransomware volume trends, 2024 vs. 2023\n\n\nFrom Extortion to Exit Scams: The Big Ransomware Group Shake-Up of 2024\n\nLockBit Affects 93% Fewer Organizations\n2024 marked the year that LockBit\u2014the omnipresent ransomware threat throughout 2023\u2014became the target of multiple law enforcement operations that disrupted its infrastructure.3\nWhile LockBit attempted a comeback in May by naming 176 organizations on its data-leak site, it failed to sustain momentum, ending the year with only 19 victims in its final quarter\u2014a staggering 93% decrease compared to the same period in 2023.\nALPHV Exits with Big Profits\n\n\u201cALPHV\u2019s\u201d sudden exit in March 2024, following a reported $22 million payday from its attack on Optum, added to the turbulence in the ransomware landscape.\nWith LockBit in decline and \u201cClop\u201d sticking to its strategy of infrequent but high-reward attacks, the absence of these dominant players created an opening for smaller, fragmented groups to rise to prominence throughout 2024.\nRansomHub Ups the Ante\n\n\u201cRansomHub\u201d wasted no time capitalizing on the void left by declining giant, LockBit. Its game-changing affiliate model\u2014paying affiliates 90% of the profits upfront while retaining just 10%\u2014made it a top choice among cybercriminals, driving a surge in activity.\nBy the second half of 2024, RansomHub had firmly established itself as the most active ransomware group, naming 326 more victims than LockBit.\n\n\n1038\n2024\n\n\n543\n\n\n534\n\n422\n\n369\n\n342\n\n294    267\n\n235 217            234       211\n2023\n172         171       155\n175       166       166       145\n149\n\nLockBit\nRansomHub\nALPHV      Clop       Play      8Base    Black Basta    Malas      Akira     Medusa      Qilin\nHunters International\nInc Ransom\nBlackSuit   BianLian\n\n\nFigure 16: Top ransomware groups by number of data-leak postings, 2024 vs. 2023\n\n\n42\n\nGroups to Watch Out for in 2025\n\nThe \u201cBlackLock\u201d (aka Eldorado) ransomware group, active since at least March 2024, gained prominence in July but truly made its mark in October. Its victim count skyrocketed by over 1,000% from Q3 to Q4 2024.\nLikely tied to Russia (evidenced by its refusal to target countries in the Commonwealth of Independent States), BlackLock\u2019s rapid ascent mirrors that of groups like RansomHub, proving how quickly a group can move from obscurity to dominance.\nIn September 2024, new group \u201cFunkSec\u201d emerged on the ransomware scene, making a major impact by December by listing 82 victims\u2014more than any other group that month.\nFunkSec targeted a wide range of sectors, including retail, manufacturing, health care, education, and professional services, across countries like the US, France, India, and Thailand. The group promotes its technical expertise on cybercriminal forums, boasting a free distributed denial-of-service (DDoS) tool, a Tor-based data-leak site, and a suite of self-developed tools.\n\nIt\u2019s realistically possible that both BlackLock and FunkSec stockpiled victims and chose to publish them all on their respective data-leak sites before the year ended. However, our analysis suggests it\u2019s more likely that both groups capitalized on the turbulence amongst ransomware groups, scooping up affiliates from faltering groups and thriving in the absence of dominant players.\nThe constantly changing ransomware threat means that traditional defenses won\u2019t cut it anymore. Organizations must adopt proactive, multi-layered strategies that combine technology, processes, and people. In 2025, ransomware will remain largely opportunistic, but the explosion of new groups and affiliates will make attacks more unpredictable and widespread than ever before.\n\n2760\n\n2134\nRansomware Mostly Targets US, Manufacturing, and PSTS\n2024\n\n\n\n2023\n\n252\n293\n296\n198\n158\n183\n121\n158\n137\n142\n107  92\n121  73\n114  67\n43\n\nUS              UK            Canada          Germany          France            Italy             Spain            Brazil             India\n\n\nFigure 17: Number of victims by region added to ransomware data-leak sites, 2024 vs 2023\n\n\n\nFigure 18: Number of victims by industry added to ransomware data-leak sites, 2023 vs 2024\n\n\nAs anticipated, the US remained the overwhelmingly popular target for ransomware operators and affiliates in 2024.\nThis trend is highly likely to continue, as attackers perceive that organizations in English-speaking countries have the financial means to pay ransoms.\n\n1098\n\n1079\n964\n\n855\n\n524\n\n500\n\n396\n\n381\n\n345\n347\nManufacturing\n\nProfessional, Scientific, and Technical Services\n\nConstruction\n\nHealth Care and Social Assistance\nFinance and Administration\nAdditionally, well-developed insurance markets and heightened cybersecurity awareness in these countries have driven higher adoption of ransomware insurance, making these regions more attractive to attackers.\nRansomware operators are acutely aware that the manufacturing sector is highly vulnerable to operational disruptions.\n\n396\n296\n246\n\n219\n\n173\n\nEducational Services\nRetail Trade Accommodation and\nThe integration of IT with operational technology (OT) in this sector exacerbates the problem, as downtime can lead to major productivity, financial, or legal consequences. These factors make ransom demands more effective, boosting ransomware groups\u2019 profits and attack success rates.\nThe PSTS sector is a lucrative target because of the sensitive data it handles and its reliance on digital resources for operations like client collaboration and secure file transfers. Its dependence on file-transfer software and other tools makes it especially vulnerable to exploitation. This vulnerability was evident in multiple supply-chain attacks conducted by the Clop ransomware group, where adversaries compromised widely used tools to target numerous organizations\u2014a growing trend that mustn\u2019t go unnoticed.\n\n241\n195\n\n170\n\n153\n177\n152\n149\n120\n118\n104\n107\n94\n69\n68\n64\nFood Services\n\nPublic Administration\n\nInformation\n\nArts, Entertainment, and Recreation\nMining, Quarrying, and Oil and Gas\nReal Estate and Rental and Leasing\nWholesale Trade Utilities\n\n\n44\n\n Take Action \n\n\n\n\u200cRecommended Detection Rules\u200c\n\n\nRclone Execution via Command Line:\n\nData Exfiltration via Command Line:\n\nRansomware File Extension:\n\n\nRecommended Threat Hunting Packages\n\n\nExfiltration Tools:\n\nProxy and Protocol Tunneling Tools:\n\nRMM Software:\n\n45\n\nGreyMatter Detections and Automations for Combatting Ransomware\nTo combat ransomware and data exfiltration threats, we advise customers to use the following targeted detection rules and GreyMatter threat hunting packages that are designed to identify specific malicious activity, such\nas the use of exfiltration tools and ransomware-specific behaviors.\nThese solutions help organizations detect and disrupt data theft, unauthorized access, and ransomware deployments, minimizing the impact of attacks and protecting critical assets.\n\n\n\n\u200cA CISO\u2019s Checklist\u200c\n\nAttackers are now averaging just 48 minutes to move laterally, adapting to security controls, bypassing MFA in 100% of successful BEC incidents we investigated, and blending into environments by exploiting the very software and tools organizations rely on daily.\nIn 80% of breaches, attackers exfiltrated data by mimicking normal activity, thereby avoiding detection. Our analysis also revealed that the top cause of major incidents was visibility gaps.\nArmed with this knowledge, it\u2019s time to act. Throughout this report, we\u2019ve shared targeted recommendations to mitigate the threats we\u2019ve identified\u2014but there\u2019s more that organizations can do.\nWe've compiled the main takeaways every CISO needs to know. By adopting these measures, organizations will be better positioned to minimize their exposure and outmaneuver this year\u2019s biggest threats.\n\nRead on to explore\n\n\nTo Respond at Top Speed, Automate\n\nAutomated responses excel in scenarios where speed is critical. GreyMatter Automated Response Playbooks can reduce MTTC to as low as three minutes when incorporated into incident response plans.\n\nAlternatively, set GreyMatter Response Playbooks to \u201cRQ Approved\u201d to allow ReliaQuest to remediate incidents directly, significantly\nimproving MTTC and accelerating response times.\n\nImplement the GreyMatter AI Agent to entirely eliminate the Tier 1 and Tier 2 tasks that slow down analysts.\n\n\n47\n\nUse GreyMatter Phishing Analyzer to automate the analysis of user-submitted phishing emails. This significantly accelerates the triage and remediation process for phishing email inboxes, executing actions like email deletion, URL blocking, and host isolation.\nBlock Initial Access by Shoring Up Foundations\n\nImplement MFA, but don\u2019t rely on it as a silver bullet solution. Strengthen MFA by incorporating additional safeguards, such as conditional access policies, restricting access to trusted devices, and shortening token expiration times.\n\nFor VPNs, implement client-based certificates and access policies to restrict authentication, which will reduce the likelihood of unauthorized access. Make an inventory of public-facing devices, prioritize patching to address vulnerabilities, and prepare continuity plans if critical devices must be temporarily disconnected to prevent exploitation.\n\nTrain employees to recognize social engineering tactics, particularly employees in IT help-desk roles. Focus on robust training programs, testing, and clear standard operating procedures to prevent successful social engineering attacks.\nDisrupt and Contain Attackers with Defense-in-Depth\n\nRotate potentially compromised credentials at the earliest opportunity. Acting quickly prevents attackers from exploiting valid accounts to move laterally within compromised networks.\n\nVerify that service accounts are not overprivileged with domain admin rights, enforce password length and complexity requirements for service accounts, and enable Advanced Encryption Standard (AES) encryption for Kerberos to mitigate cracking.\n\nEnsure comprehensive logging and coverage for endpoint security tools, including critical assets. This approach will eliminate blind spots and enhance security monitoring, allowing for faster threat detection.\n\nImplement detection rules to identify the unauthorized use of tools or software and engage in frequent threat hunting to detect anomalous activities. Serious threats fly under the radar, so a defense-in-depth strategy is key to staying ahead.\n\nOur Threat Forecast for 2025\n\n\nLooking ahead, ransomware attacks are set to surge throughout 2025, surpassing their 2024 levels and rivaling December\u2019s record-breaking activity.\n\n\nWhile RansomHub may dominate early in the year, we expect BlackLock to take the lead by Q3.\nMeanwhile, we anticipate that 8\u201310% of investigations will likely involve threat actors leveraging large language model (LLM) tools, alongside a projected 10% increase in non-human identity (NHI)-based attacks, such as the compromise of API keys, service accounts, and digital certificates.\nSpearphishing, exploiting public-facing applications, and targeting external remote services will remain key tactics, fueled by rapid vulnerability exploitation, human error, exposed credentials, and ever-expanding attack surfaces.\nReliaQuest Exists to Make Security Possible\n\nThe last year in cyber threats has emphasized again and again the critical importance of speed, automation,\nvisibility, and proactiveness in modern security operations.\n\nOrganizations must have the right weapons in their arsenal to defend against attackers who are getting smarter and more efficient.\n\nReliaQuest\u2018s AI-powered security operations platform, GreyMatter, is purpose-built to confront these challenges, providing customers with the capabilities they need to secure their environments against the threats detailed in this report.\nTo accelerate containment and response, we\u2019ve created our own agentic AI Agent as well as developed Automated Response Playbooks that prevent cybercriminals from\ngaining or maintaining a foothold\u2014all without manual effort.\n\nThe GreyMatter AI Agent autonomously handles 100% of security alerts end-to-end. Combining this capability with Automated Response Playbooks has enabled our customers to achieve containment and response times as low as 3 minutes. When customers pair Digital Risk Protection with GreyMatter, they achieve 360-degree visibility into the\nthreats facing their organization, both within their environment and outside it. DRP identifies threats on the open, deep, and dark web, allowing customers to counter them before they reach their attack surface.\nGreyMatter also uses external threat data, including the latest threat actor TTPs, to develop threat hunting packages that customers can use to proactively identify early indicators of compromise. By spotting known tactics early, customers prevent attacks from progressing.\n\n48\n\nWith GreyMatter, ReliaQuest customers are well armed against the threats facing us in 2025 and beyond. To see how GreyMatter can help protect your organization, visit reliaquest.com to request a demo tailored to your environment.\n\nAbout ReliaQuest\nReliaQuest exists to Make Security Possible.\n\nOur agentic AI-powered security operations platform, GreyMatter, allows security teams to detect threats at the source, and contain, investigate, and respond in less than 5 minutes\u2014eliminating Tier 1 and Tier 2 security operations work.\nGreyMatter uses data-stitching, detection-at-source, AI, and automation to seamlessly connect telemetry from across cloud, multi-cloud, and on-premises technologies.\n\nReliaQuest is the only cybersecurity technology company that delivers outcomes specific to each organization\u2019s unique architecture, technology, and business needs.\nWith over 1,000 customers and 1,200 teammates across six global operating centers, ReliaQuest Makes Security Possible for the most trusted enterprise brands in the world.\n\nLearn more at www.reliaquest.com\n\nReliaQuest\u2019s ShadowTalk is a weekly podcast featuring discussions on the latest cybersecurity news and threat research.\nListen to the latest episodes on your favorite podcast channels.\n\nreliaquest.com                 800.925.2159             info@reliaquest.com\n\nCopyright \u00a9 2025 ReliaQuest, LLC. All Rights Reserved. ReliaQuest, GreyMatter, Digital Shadows, and all related logos, product and services names, designs, and slogans are trademarks or registered trademarks of ReliaQuest, LLC or its affiliates or licensors. All other product names or slogans mentioned in this document may be trademarks or registered trademarks of their respective owners or companies. The ReliaQuest software, platform,  portal and its entire contents, features, and functionality are owned by ReliaQuest, LLC and its affiliates. These materials are protected by United States and international copyright, trademark, patent, trade secret, and other intellectual property or proprietary rights laws. All other information presented is provided for informational purposes with no representations or warranties provided of any kind and should not be relied upon for any purpose. ReliaQuest has no obligation to amend, modify, or update the information contained in this document in the event that such information changes or subsequently becomes inaccurate. Printed in the USA.\n\nEndnotes\n\n\nhxxps://nvd.nist[.]gov/vuln/search/statistics?form_type=Advanced&results_type=statistics&search_type=all&isCpeNameSearch=false&cvss_version=3&cvss_v3_metrics=AV%3AN%- 2FAC%3AL%2FPR%3AN%2FUI%3AN&cvss_v3_severity=CRITICAL\n\n\nhxxps://www.darkreading[.]com/cyberattacks-data-breaches/canadian-authorities-arrest-snowflake-data-thief\n\n\nhxxps://www.europol.europa[.]eu/media-press/newsroom/news/law-enforcement-disrupt-worlds-biggest-ransomware-operation\n]]>\n    \n\nAnnual\nCyber-Threat\nReport\n\n\nExecutive Summary: 2024 At A Glance\nTwo- Thirds\nOf Critical Hands-on- Keyboard Incidents Involved Legitimate Software\n\nIncident Metrics and Breach Details\n\n3 Minutes\nLowest Mean Time to Contain (MTTC)\nUsing Automated Response Playbooks\n48 Minutes\nAverage Time from Initial Access to\nLateral Movement, or \u201cBreakout Time\u201d\n \n\nInadequate Logging\nTop Cause of Breaches\n85%\nOf Incidents Involved\nCompromised Service Accounts\n \n\nMalware and Threat Actors\n\nSocGholish\nTop Malware Thanks to New Python Tactics\n\nAsyncRAT\nRises From 4th to 2nd Place Among Top Malware Threats\n\nMicrosoft Teams\nAbused for Social Engineering by Black Basta\n\nUnited States\nRegion with the Most Targeted Victims\n\nInitial Access Techniques\n\nPhishing\nTop Initial Access Technique\n\n30\n%\nOf Phishing Messages\n\n1 in 4\nActive Intrusions Started\nManufacturing & Professional Services\nSectors with the Most Targeted Victims\nfor the 2nd Year Running\n\n45\n%\nInvolved Credential Harvesters\nwith Exploitation of Public-Facing Applications\n\n100\n%\n478,000\nLumma Listings on Criminal Marketplaces\n\n4 hr 29 min\n5,253\nOrganizations Named on Ransomware Data-Leak Sites\n\n80%\nOf Hands-on-Keyboard Intrusions Began with Abuse of External Remote Services Like VPNs\nOf Deployed MFA Controls Bypassed via Session Hijacking in Successful Business Email Compromise (BEC) Attacks\nFastest Exfiltration Time\nOf Breaches Featured Exfiltration vs 20% with Encryption\n\n3 Recommendations Organizations Can\u2019t Afford to Ignore\n\nIncorporate AI and Automation into Security Operations\nAttackers are adopting AI and automation to supercharge common attacks. That means it\u2019s no longer optional for organizations to use AI and automation to their own advantage.\n\nWhen integrated into a security operations platform, these technologies can help contain threats rapidly, drive down response times, and allow security teams to focus on tackling\nmore complex challenges.\n\nAgentic AI, which can autonomously handle alerts end-to-end, shows particular promise for SecOps.\nBarricade Common Entry Points: Phishing, Drive-By Compromise, Public-Facing Assets, and External Remote Services\nPhishing and drive-by compromise were the top initial access methods, while public-facing assets and internet-facing external remote services fueled active intrusions.\nMitigate these risks by securing remote services (e.g., with client-based certificates) and monitoring public-facing assets.\nPatching promptly is key; attackers are moving faster than ever, fueled by an abundance of available credentials.\nEliminate Blind Spots:\nDeny Attackers Any Opportunity\nMost \u201chands-on-keyboard\u201d breaches resulted from insufficient logging and unmanaged devices. Manage your attack surface and eliminate blind spots by deploying an endpoint security solution across all assets.\nEnable detailed logging for all devices, including endpoints and servers, to capture user activity, system changes, and network traffic.\nReview log retention periods for hot and cold storage and establish clear procedures for retrieving cold storage logs during investigations.\n\n\nTable of Contents\n\nIntroduction: 2024 in Review\u2014Fast Threats\nDemand Faster Responses                  1\nInadequate Logging Responsible for Most\nBreaches in 2024                          2\nBreaking In: The Trends Shaping Initial\nAccess Tactics                          3\nOld Habits Die Hard: Attackers\u2019 Most Frequent\nInitial Access Techniques                     4\nPhishing Trends: The Tactics Honing Cybercrime\u2019s\nMost Reliable Weapon                            5\nSession Hijacking Bypassed MFA in Every Successful\nBEC Incident in 2024 8\nSocial Engineering: How Attackers Weaponize\nMicrosoft Teams                               10\nGreyMatter Automations for Combatting\nEmail Attacks                                 12\nCritical Entry Points: VPN and Voice Phishing Among Most-Successful Techniques                  13\nAbuse of External Remote Services Led to 45%\nof Hands-on-Keyboard Intrusions                   14\n23% of Active Intrusions Initiated via Exploitation\nof Public-Facing Applications                     16\nVoice Phishing Behind 14% of Breaches 18\nAccess via Cloud Accounts and Trusted\nRelationships Achieved in 9% of Intrusions 20\nGreyMatter Automations for Combatting\nUnauthorized Access                            22\nSocGholish Secures Top Spot Again\nin 2024 Malware List                       23\nSocGholish Persists in First Place with Python          24\nScreenConnect Abuse Propels AsyncRAT to\nSecond Place                                 26\nCopy, Paste, Compromised: Lumma Rises to\nThird Place with Innovative Tactics                  28\nGreyMatter Automations for Combatting Malware      30\n48 Minutes to Breakout: Unmasking\nPost-Compromise Trends                  31\nAn Attacker\u2019s Route to Control                32\nWhy RDP Became the Tool of Choice for\nLateral Movement                              32\nValid Accounts, Invalid Intent: Easy Access to\nPrivilege Escalation                             34\nThe Adversary\u2019s Toolkit: Post-Exploitation Essentials     36\nGreyMatter Automations for Combatting Legitimate\nTool Abuse                                   38\nRansomware Decoded: Exfiltration Is the\nNew Encryption                           39\nExfiltration Outpaces Encryption in Modern Breaches 39\nRansomware in 2024: Increased 11.9%, Hit New Highs 41\nGreyMatter Detections and Automations for\nCombatting Ransomware                         45\nNext Steps: A CISO\u2019s Checklist              46\n\n\n\u200cIntroduction: 2024 in Review\u2014Fast Threats Demand Faster Responses\u200c\u200c\nIn 2024, speed became more important than ever in defending against cyber threats.\n\n48 Minutes\nAttackers are moving at unprecedented speeds\u2014last year, upon gaining initial access, they achieved lateral movement in an average of 48 minutes and managed to exfiltrate data in as little as 4 hours.\n\nAttackers are also getting better at adapting to and evading the  latest security controls, making the adoption of AI and automation imperative for organizations. Using AI and automation to tackle initial access attempts not only strengthens defenses but also empowers analysts to focus on what matters most: detecting and investigating the stealthiest and most impactful intrusions.\nThough attackers are moving faster, they\u2019re still using tried-and-tested methods like phishing to achieve initial access. They cast a wide\n\n1\n\nnet, indiscriminately targeting organizations with minimal effort and often causing significant damage. The year\u2019s high count of disclosed vulnerabilities provided cybercriminals with entry points, while software suppliers remained a top target as a way to infiltrate organizational networks.\n\nRansomware and extortion remained critical threats compared to 2023, but the dynamics have shifted. Affiliates splintered into smaller groups, while leaked ransomware source code on cybercriminal forums sparked a wave of new attackers on the scene, with many focused entirely on data exfiltration. The result is a more fragmented, but no less dangerous, ransomware ecosystem.\n\n\nIn a world of accelerated attacks, automation is the ultimate ally for defenders. ReliaQuest customers using Automated Response Playbooks in 2024 saw a dramatic improvement in response times, with the fastest mean time to contain (MTTC) cyber threats as low as 3 minutes. In comparison, customers yet to implement Automated Response Playbooks reported an average MTTC of 6.3 hours.\nAdditionally, in August 2024, ReliaQuest launched its first-of-its-kind AI agent for security operations, further speeding up containment of threats with better accuracy and consistency. By seamlessly handling routine Tier 1 and Tier 2 tasks and executing response actions securely, the GreyMatter AI Agent eliminates errors and delivers unparalleled efficiency in accelerating remediation times, allowing security teams to upskill by focusing on more critical tasks.\nBy automating 100% of the investigation process\u2014including data aggregation, analysis, and response\u2014the GreyMatter AI Agent has reduced the average MTTC for ReliaQuest customers to less than 5 minutes.\n\nAt ReliaQuest, we remain committed to helping organizations strengthen their security posture and take control of their defenses.\nOur Annual Cyber-Threat Report presents an in-depth analysis of the most critical cyber threats observed from January 1 to December 31, 2024. Find out the emerging tactics, techniques, and procedures (TTPs) employed by adversaries and benchmark your security defenses against our findings to identify key areas for improvement.\nSecurity leaders can use these findings to refine their cybersecurity strategies, address coverage gaps, and enhance employee awareness of evolving threats.\n\n\u200cInadequate Logging Responsible for Most Breaches in 2024\u200c\nOur analysis of 2024 customer breaches revealed five critical security control failures at the core of these incidents. Neglecting or underestimating these foundational security practices leaves organizations exposed\u2014regardless of how sophisticated or varied an attacker\u2019s methods may be. Addressing these weaknesses within networks is essential to avoid becoming the next target.\n\n\nUnmanaged Devices\nDevices without security controls like endpoint protection or monitoring agents create security gaps, providing attackers with open pathways throughout networks.\n\nExternal Exposure\nVulnerabilities in internet-facing devices serve as entry points for attackers to infiltrate the network.\nInsufficient Logging\nInsufficient monitoring or logging leaves parts of the system vulnerable, making it impossible to detect or investigate malicious activity.\n\n2\n\nFive Critical\n\nInsecure VPN\nVPNs lacking essential protections like multifactor authentication (MFA) or device-based certificates allow attackers\nto exploit stolen credentials and gain network access.\n\nHelp-Desk Procedural Flaws\nWeak help-desk protocols make organizations easy targets for social engineering attacks, with 14% of breaches in 2024 involving social engineering for initial access or privilege escalation.\n\n\u200cBreaking In:\u200c\n\nFirst...\nWe'll examine phishing and business email compromise (BEC) attacks, which are increasingly bolstered by advanced tactics like bypassing MFA and abusing Microsoft Teams for social engineering.\nThen...\n3\n\nWe\u2019ll dissect the initial access techniques with the highest success rates, including targeting external remote services (boosted by a 250% surge in initial access brokers [IABs] offering VPN access), compromising cloud accounts, and conducting voice phishing attacks.\nFinally...\nWe\u2019ll review the top malware shaping today\u2019s threat landscape, with \u201cSocGholish\u201d leading the charge.\n\nRead On To\n\n\n\n\n\u200cOld Habits Die Hard: Attackers\u2019 Most Frequent Initial Access Techniques\u200c\n\nThe consistency in top-ranked initial access techniques from 2023 to 2024 highlights their effectiveness and reflects attackers\u2019 strategy of indiscriminately targeting a wide pool of victims.\nPhishing and drive-by compromise remain go-to methods, powered by the scalability and affordability of phishing-as-a-service (PaaS) and malware-as-a-service (MaaS) offerings.\nThese services allow attackers to flood inboxes with phishing campaigns or lure victims to malicious websites through manipulated search engine results.\n\nWhile most initial access attempts are blocked early, when successful, these broad-spectrum attacks can pave the way for more advanced threats, highlighting the importance of understanding their mechanics.\n\nThrough our analysis of phishing emails reported to the GreyMatter Phishing Analyzer, we uncovered:\n\n2024\n25\n%\n\n2023\n33%\nDrive-By Compromise\n\n\nThe most prevalent types of malicious email sent\n\nThe trigger words used to boost email open rates\n\nThe tactics designed to trick recipients into clicking malicious links\n24\n%\n22%\nPhishing with Link\n\nWe\u2019ll also look at one of the top concerns for CISOs\u2014BEC\u2014by demonstrating how attackers leverage simple phishing techniques to bypass MFA and execute these high-impact attacks.\nFinally, we\u2019ll explore adversaries' weaponization of a trusted communication platform to worm their way into networks.\n9\n%           \n19\n%\nReplication via Removable Media\n\n4\n\n\n\nCredential Harvesters\n\nDominated as the most reported category of malicious emails, with fake Microsoft login portals being the most common type. These emails lure victims to fraudulent websites designed to steal credentials, often to lay the groundwork for larger attacks like BEC.\nEnhanced by AI, credential harvesting emails now feature much more polished language, fewer errors, and highly convincing designs, making them an increasingly effective and scalable weapon for cybercriminals.\n\nTo expose the tactics behind the number-one cyber threat facing enterprises today, we turned to the GreyMatter Phishing Analyzer:\u200c\n\n\nA tool designed to automate the triage of employee-reported phishing emails, enabling faster identification and remediation of malicious activity.\n\n\n\nScam Emails\n\nCrafted to solicit money or extract confidential employee information, scam emails were also widespread in 2024.\n\nThis data is collected from phishing emails that evaded detection by email security gateways and provides insight into adversaries\u2019 phishing techniques.\nData from the GreyMatter Phishing Analyzer revealed that nearly 30% of phishing messages that made it past traditional email security tools involved credential harvesters, often disguised as fake Microsoft login portals.\n\nReconnaissance Emails\n\nAnother common type of email sent was single-word or blank emails\u2014 known as reconnaissance emails\u2014which are used to verify whether an account is active (i.e., no bounce-backs are received) or to gauge the likelihood that the inbox owner might respond.\n\nWe also identified any financial-themed keywords attackers used to create a sense of urgency and the trusted platforms they abused to make phishing campaigns appear more legitimate.\nKnowing what to look for in phishing emails not only helps predict attacker strategies but also sharpens employee training, turning your workforce into a powerful first line of defense against phishing attacks.\n\n\nMalware-Laden Emails\n\nAttackers also sent a significant volume of malware-laden emails containing attachments or URLs to deploy malicious files upon download.\n\nNearly 30% of Reported Phishing\n5\n\nEmails Contained Credential Harvesters\n\n\npause, verify suspicious emails, and think critically\n\n\nURGENT:\nKeywords That Hook\n\nTraining end users to\nbefore taking action is key to disrupting attackers\u2019 strategies and reducing the success of phishing attempts.\n\n\n\nNotification\n\nOrder\n\nUpdate\n\nDocument\n\nRef\n\nPDF\n\nPlease\n\nNotice\n\nBusiness\n\nPassword\n\nSign\n\nReport\n\n\nRequest\n\nInvoice\n\nAccount\n\nPayment\n\nRequired\n\nReview\n\nAction\n\nReminder\n\n1. Invoice\n2. Order\n3. Payment\n4. Request\n\n12. Remittance\n\n11. Account\n\n10. Bank\n\n9. Transfer\n\n8. Tax\n\n7. Statement\n\n6. Purchase\n\n5. Receipt\n\nAttackers use deceptively urgent language to manipulate victims into engaging with phishing emails.\nThey understand that a sense of urgency often overrides caution, causing recipients to act hastily without evaluating risks.\n\nFinancial keywords like \u201cpayment,\u201d \u201cinvoice,\u201d and \u201cstatement\u201d dominated phishing email subject lines and filenames last year.\n\nThis tactic is particularly effective because phishing emails that mimic financial statements blend seamlessly into\n6\n\nroutine tasks, like processing invoices or reviewing account statements, catching users off guard.\n\nFigure 3: Top sender domains\n\nAttackers\u2019 Favorite Email Providers and File-Sharing Platforms\n\nFree email providers like Gmail and file-sharing platforms like Dropbox and Docusign were among the top tools used in phishing campaigns last year.\nThese platforms are highly trusted and widely used in business, making it easy for attackers to exploit the trust users place in them.\n\n\nfakedEmail.com\n\nPhishing emails leveraging these tools appear more genuine and are therefore harder to spot.\n\nFree email services allow attackers to remain anonymous by enabling them to quickly create new accounts and replace blocked ones, while file-sharing platforms are perfect for hosting malicious files or hiding phishing links.\n\n7\n\nTo counter these tactics, businesses must fine-tune their email security tools to catch suspicious activity that hides behind a veil of legitimacy. Employees must also carefully scrutinize links or emails from trusted platforms, as attackers rely on this very trust to bypass defenses and infiltrate organizations.\n\n\nTake Action\n\n\n\n\nTarget Website\n\n\u200cBEC is one of the most dangerous methods attackers use to achieve their financial objectives.\u200c\n\nThese attacks often start with a phishing email\u2014frequently sent from a compromised partner\u2014containing a link to an attacker-controlled website. This site acts as an adversary-in-the-middle (AiTM), intercepting MFA requests and session tokens from the legitimate login portal.\nWith the stolen session tokens, the attacker can authenticate to the service without needing credentials or access to the MFA-enrolled device, effectively bypassing both.\n\nUser\n\n 1  User enters their password into phishing site\n\nPhishing Site\n\n 2  Phishing site forwards the credentials to legitimate site\n\nTo stay under the radar while executing their strategies, attackers often use commercial VPNs to mask their activities:\n\n 4  Phishing site displays MFA prompt from legitimate site to the user\n\n 3  Legitimate site sends MFA screen in response\n\n\n\nExpress VPN\n\nSurfEasy VPN\n\nSurfshark VPN\n\nHide My Ass VPN\n\nNord VPN\n\nPrivate Internet Access VPN\n\n 5  User\ncompletes MFA authentication\n\n 6  Phishing site forwards MFA response to legitimate site\n\nThe combination of a high success rate and devastating impact makes BEC a top security concern for organizations.\nBy analyzing real-world compromises of corporate employee email accounts, we\u2019ve identified the key tactics attackers rely on, what makes them so successful, and, most importantly, the steps defenders must take to stop them.\n\n 8  Phishing site redirects the user to another page\n\n8\n\n 7  Legitimate site issues a session cookie\n\nHere are our key takeaways\n\nFigure 4: How AiTM phishing bypasses MFA and steals session tokens\n \n\nMFA Isn\u2019t Foolproof: In every incident where MFA was configured, attackers managed to bypass it by stealing session tokens through AiTM phishing. Session token interception is now a standard feature in modern phishing toolkits, reducing the level of technical expertise required to bypass MFA.\n\nTrust Is a Weapon: 9 out of 10 phishing emails came from hacked accounts at trusted partner organizations, exploiting established relationships to successfully deceive targets.\n\nAttackers Hide Their Tracks: After hijacking a session, attackers used VPNs to conceal their allowing them to bypass location-based detections and evade regional access-control\n\nCompromised Accounts Spread the Attack Internally: In 80% of cases, compr\nwere used to send phishing emails to other employees within the same organization.\nBusiness Email Camouflage\n\n\n9\n\n Take Action \n\n\n\u200cBlack Basta Exploits Microsoft Teams for Initial Access\u200c\nThroughout 2024, ReliaQuest observed the ransomware group \u201cBlack Basta\u201d employing a new social engineering tactic that leverages Microsoft Teams for initial access.\nBy compromising legitimate Microsoft Entra ID tenants or creating fraudulent ones, the group impersonates IT support or help-desk staff to deceive targeted users into engaging with malicious Teams messages.\n\nBlack Basta typically begins the attack by spamming users with hundreds of phishing emails.\nShortly after, the attackers follow up with either a phone call or a Teams chat message (see Figure 5).\nThese messages often originate from external accounts with display names like \u201cHelp Desk\u201d\nFigure 5: Sample external Microsoft Teams message request (source: microsoft[.]com)\n\nor \u201cSupport Team,\u201d intentionally crafted to appear both legitimate and urgent to increase the \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0  likelihood of user interaction.\n\nOnce attackers establish contact, they manipulate victims into downloading remote monitoring\nand management (RMM) tools, such as Quick Assist or AnyDesk, under the guise of providing \u00a0\u00a0\u00a0\u00a0\u00a0  support sessions. These tools grant attackers the ability to install and execute malicious files, \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0  facilitating initial access to the organization\u2019s network.\nIn some cases, attackers have also been observed persuading\n10\n\nusers to download malicious files themselves\u2014such as scripts \u00a0\u00a0\u00a0\u00a0\u00a0  or executables\u2014via QR codes, further expanding their arsenal \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0  of social engineering techniques.\n\n\n\nManipulating Trust: Social Engineering Through Familiar Platforms\n\nAs this is a relatively new technique, most organizations have yet to take appropriate defensive measures. Unlike phishing, which is commonly mitigated with security controls and user training, this approach targets less-secured communication channels where users are more likely to engage with malicious activity.\nWe predict with high confidence that this technique will gain popularity among cybercriminals, largely due to the ease of creating new Microsoft Entra ID tenants, making these accounts disposable and easily replaced if blocked. This tactic highlights why social engineering remains one of the most effective forms of initial access.\n\nBy exploiting human trust in familiar platforms, threat actors significantly increase their chances of success compared to traditional phishing techniques.\n\nAs Black Basta and other threat groups continue to innovate, organizations must prioritize addressing these vulnerabilities. Implementing strict controls on external Teams communication, monitoring for anomalous activity\u2014such as messages originating from unexpected locations or using suspicious naming conventions\u2014and providing robust user training are critical.\nWithout these preventative measures in place, these increasingly sophisticated social engineering campaigns are likely to be successful.\n\n\n11\n\n Take Action \n\n\n\n\u200cRecommended Automated Response Playbooks\u200c\n\n\nBlock Domain:                                        Block Email Domain:\n\n\nRecommended Threat Hunting Packages\n\n\nPhishing\u2014Microsoft Teams:\n\nPhishing\u2014Spearphishing Attachments:\n\nHygiene\u2014MFA Modifications:\n\n12\n\nGreyMatter Automations for Combatting Email Attacks\nTo counter the evolving tactics behind phishing, BEC, and social engineering attacks, ReliaQuest offers its customers a proactive defense strategy through its Automated Response Playbooks.\nThese Playbooks automatically contain and respond to threats, significantly improving MTTC and minimizing potential damage.\nAdditionally, GreyMatter offers out-of-the-box and custom threat hunting packages that are built to\nidentify specific attacker techniques and behaviors.\nBy leveraging the end-to-end automation capabilities of GreyMatter, organizations can detect, respond to, and neutralize threats in minutes.\n\n\n\n\u200cCritical Entry Points: VPN and Voice Phishing Among Most-Successful Techniques\u200c\n\nIn 2024, GreyMatter continued to serve as a critical line of defense, swiftly detecting and containing the vast majority of initial access attempts observed. Among all the attempts analyzed in the previous section, only a tiny fraction\u2014just 0.02%\u2014managed to bypass its defenses.\n\nWhile these successful techniques represent only a very small proportion, they demand close attention, as they allowed threat actors to engage in\nhands-on-keyboard activity, taking real-time control of compromised systems.\n\nIn this section, we focus on the critical 0.02% of successful attempts, examining how attackers used social engineering tactics in addition to exploiting external services, public-facing applications, cloud infrastructure, and trusted relationships.\n\nWe\u2019ve also included real-world examples to illustrate the damage these techniques can inflict and outlined clear steps to mitigate these risks.\nBy prioritizing defenses against these methods, organizations can significantly reduce the risk of attacks escalating into lateral movement, privilege escalation, or data exfiltration.\n\n9%     Cloud\n\n13\n\n9%\n\nTrusted Relationship\n\n\nFigure 6: Successful initial access methods in 2024\n\n45%\nExternal Remote Services\n23%\nPublic-Facing Applications\n14%\nPhishing with Voice\n\n\n\u200cLast year, threat actors were most successful in gaining network access via external remote services like VPN portals, Remote Desktop Protocol (RDP), and virtual desktop infrastructure (VDI).\u200c\n\nThese trusted services act as gateways to an organization\u2019s internal network, allowing attackers to slip past traditional perimeter defenses and gain direct access to sensitive systems and data.\n\nOnce inside, adversaries exploit the trust inherent in these services to operate under the radar, carrying out data theft, lateral movement, or ransomware attacks\u2014all while evading detection. In some cases, they also plant backdoors for future intrusions.\n\nExternal remote services rely on valid account credentials for authentication, but attackers can easily overcome this hurdle by:\n\nBrute-Forcing Passwords\nMining Data Breaches\nPurchasing Credentials from Online Marketplaces\n \n\nIABs are the middlemen in this ecosystem, selling stolen credentials\u2014often obtained through information-stealing malware (infostealers)\u2014to various threat actors, including ransomware affiliates, so they can launch devastating attacks with ease.\n\n14\n\nOnce exposed, data may be leaked or sold online, leaving organizations to face severe reputational and regulatory consequences.\n\nThe rise in attacks targeting external services has fueled a growing demand for accesses, and IABs are meeting this demand at premium prices:\nIAB listings offering access via VPNs surged by 250% between 2023 and 2024.\n\nThe average \u201cbuy now\u201d price for these listings climbed 46%, increasing from $2,370 to $3,455.\n\n74%\n63%\n55%\n\nFigure 7: IAB listings in 2024 by sector\n \n\nManufacturing        Construction           Retail          Education\nBusiness Services\nFinance      Software    Health Care   Government\nMedia & Internet\n\nWhile all industries are targeted for initial access, certain sectors are more heavily sought after than others.\n\nManufacturing, for example, is a prime target due to its reliance on legacy systems, extensive use of remote access, and prioritization of operational continuity over credential hygiene best practices. If IABs can easily infiltrate a network in a particular industry, they are more likely to target other organizations in the same sector, assuming they have the same weaknesses in security practices.\n\n\nTake Action\n\n\n15\n\n\n2023   2024\n\n\u200cBetween 2023 and 2024, adversaries targeting public-facing applications increased by 3%, a trend highly likely fueled by the 2,000-plus critical vulnerabilities identified last year.1\u200c\n\nThese critical vulnerabilities\u2014which are remotely exploitable, require no privileges or user interaction, and are characterized by low complexity\u2014are an attractive opportunity for attackers.\n\nWith minimal effort, a single exploit can breach multiple organizations, delivering significant returns on investment for cybercriminals.\n\nAlthough fewer critical vulnerabilities were identified in 2024 compared to the 4,000-plus seen in 2023, a surge in proof-of-concept (PoC) exploits likely leveled the playing field,\ngiving lower-skilled attackers more opportunities to strike. PoC exploits are easily deployable bits of code designed to demonstrate vulnerabilities, making it easier to test or exploit security weaknesses.\nIn 2024, PoC exploits were released for all three of the most-exploited vulnerabilities, turning opportunistic attacks into focused campaigns. With these ready-made tools in hand, attackers\u2014regardless of skill level\u2014had a clear and easy path to exploitation.\n\nMost Exploited Vulnerabilities of 2024\n\n\n\nCVE-2024-1708 affecting ConnectWise ScreenConnect\n\nCVE-2024-50623 impacting Cleo Harmony, VLTrader, and LexiCom\n\n16\n\n\n\nCVE-2024-3400 targeting Palo Alto GlobalProtect\n\n\n\nWhen PoCs are released, the clock starts ticking; attackers rush to exploit vulnerabilities at scale before organizations can respond.\n\nLockBit Finds a Key in ScreenConnect\n\nTo stay ahead, organizations across all sectors must prioritize securing external-facing assets,\nas these are prime targets for rapid, opportunistic attacks the moment exploits become available.\n\nThe information sector emerged as the primary target for public-facing application attacks, largely due to its reliance on software that often inadvertently leaves critical assets exposed, like customer service platforms, hosting infrastructure, and interconnected systems.\n\n\n17\n\n Take Action \n\n\n\u200cSocial engineering is far from new, but it remains one of threat actors\u2019 most effective tools, allowing them to exploit human trust to infiltrate organizations.\u200c\nAttackers frequently deceive users into downloading malicious software or manipulate IT help desks into resetting credentials and disabling MFA. To deceive help-desk personnel, attackers gather employee information such as full names, addresses, and Social Security numbers.\n\nVoice phishing is especially concerning.\n\nFigure 8: A user offers corporate calling services in multiple languages on forum XSS\n\n18\n\nIt circumvents all technical defenses, instead directly targeting an organization\u2019s people. Employees tricked by these tactics not only risk exposing sensitive information but also open the door for attackers to deploy malware, allowing them to steal the data themselves.\n\n\nThe manufacturing sector was the top target for phone-based social engineering attacks, with attackers likely taking advantage of its frequent IT interactions and lenient help-desk policies designed to handle high volumes of support requests.\n\n\nTo overcome language barriers, threat actors are now advertising multilingual calling services, while English-speaking attackers are using their language fluency to secure initial access on behalf of Russian-speaking ransomware groups.\nWhen Help Desks Become Gateways: Social Engineering Hits Health Care\n\nThese attackers are using messaging apps like Telegram and traditional cybercriminal forums to advertise their services, as shown in Figure 8. The post advertises:\n\nWe call corporations, doing it as effectively as possible. We know who to contact and how to communicate with them. Every language in the world is available.\n\nOur callers are experienced in this type of calling. Backed by many successful cases, we work with serious partners. Terms can be discussed via Tox. 24/7 service (translated from Russian)\n\nThis new shift shows that social engineering has evolved into a globalized and increasingly sophisticated threat.\n\ncampaign\n\nsocial engineering\n\n Take Action \n\n19\n\n\nAttacks on customer cloud services like Amazon Web Services (AWS) and Azure rose by 4% between 2023 and 2024, a trend driven by the growing adoption of cloud platforms and the improved resiliency of on-premises systems.\u200c\nBut attackers are adapting to this shift, lured by the broad attack surface and vast amounts of sensitive data these platforms offer.\n\nAdversaries are also abusing trusted relationships, like those with third-party service providers that offer on-premises or cloud services, to infiltrate organizations.\nBy targeting partners with weaker security controls, attackers can follow a \u201cone-to-many\u201d approach:\nCompromise one organization and exploit its connections to breach more-secure partners.\n\nIn some cases, attackers return to previously breached entities that have since been acquired to exploit weaknesses a second time around.\n\n20\n\nAs cloud adoption grows and business ecosystems become more interconnected, organizations need robust security across every link in the chain.\n\n\nOrganizations in the professional, scientific, and technical services (PSTS) sector are the most frequent targets of cloud-based attacks, likely due to the sensitive nature of the data they manage, such as intellectual property and client information.\n\nThe following factors also make cloud environments ripe for exploitation:\nWhen Trust Backfires: How Silk Typhoon Exploited a Third-Party Account for Azure Access\n\n\nMisconfigurations\n\nWeak Access Controls\nGaps in the Shared Responsibility Model\n \n\n\n21\n\n Take Action \n\n\n\n\u200cRecommended Automated Response Playbooks\u200c\n\n\nBlock IP:                                             Reset Password:\n\n\nRecommended Threat Hunting Packages\n\n\nSuccessful MFA from High-Risk Country:\n\nAWS Enumeration:\n\nPassword Manager Access to Sensitive Secrets\u2014Credential Access:\n\n22\nGreyMatter Automations for Combatting Unauthorized Access\nFor the best protection against the initial access techniques outlined in this section, ReliaQuest customers should use the following Automated Response Playbooks and threat hunting packages in GreyMatter.\nThese tools are designed to disrupt and respond to unauthorized access attempts, reducing the risk of further compromise and lateral movement within an environment.\n\n\n\n\nWhile SocGholish held its top spot as the\nbiggest malware threat\u2014largely thanks to its new Python infection chain used for persistence\u2014the \u201cAsyncRAT\u201d remote-access trojan (RAT) and \u201cLumma\u201d (aka LummaC2) infostealer climbed the ranks.\n\n\u200cSocGholish Secures Top Spot Again in 2024 Malware List\u200c\nThe malware threats observed in customer environments throughout 2024 revealed a relentless evolution in tactics and preferred variants, as attackers continued refining their methods to outpace defenders.\nAsyncRAT used legitimate software like ScreenConnect to infiltrate systems with stealth and precision. Lumma, on the other hand, doubled its sales of stolen credentials and turned to novel techniques, such as coercing users to copy and paste malicious PowerShell code via fake CAPTCHAs. With over 478,000 Lumma-related listings\non criminal marketplaces, including credentials used to breach major platforms like Snowflake, the stakes for defenders are at an all-time high.\nIn this section, we\u2019ll examine these malware variants in detail, focusing on their new tactics and the factors behind their increased popularity.\n\nPercentage of 2024 Incidents by Malware Variant                                 Percentage of 2023 Incidents by Malware Variant\n\nAsyncRAT                7%\n\nLumma            5%\n\n23\n\nGootLoader       4%\nQakBot\n\nAsyncRAT         8%\n\nGootLoader       7%\n16%\nSocGholish\n19%\nRaspberry Robin\n19%\nCobalt Strike\n3%\nSocGholish\n23%\n\n\n\u200cNamed for its deceptive use of social engineering and \u201cghoulish\u201d tactics, SocGholish remains a dominant force on the malware scene.\u200c\n\nIt\u2019s primarily distributed through infected websites that rank highly in search engine results or through phishing emails that redirect victims to these sites.\nOnce on the infected website, victims are tricked into downloading a malicious JavaScript file disguised as a legitimate browser update.\nThis file grants attackers remote access to the victims\u2019 systems, enabling serious consequences like data exfiltration, system encryption, and other high-impact threats that can devastate organizations.\nWindows Command Shell\n\n44%\n\nPowerShell\n\nAdditionally, 2024 saw a surge in \u201cone-off\u201d malware variants like \u201cBroomstick\u201c and \u201cMatanbuchus.\u201d\nThese evolving trends highlight the increasingly diverse and unpredictable nature of the malware landscape, emphasizing the critical need for proactive defenses and rapid response strategies.\n\nFigure 9: Top command and scripting interpreters\n\n\nAlthough SocGholish maintained its position as the most frequently observed malware in 2024,\nwe saw infostealers written in C, Rust, and C++ rise in popularity, as evidenced by Lumma's ascent to\nthird place.\n\n30%\n\nJavaScript\n\n6%\n\n11%\n\nVisual Basic\n\n4%\n\nUnix Shell\n\nPython\n\n24\n\nAutoHotKey & AutoIT\n\n2%\n2%\n \n\n\n\nDespite the shifting statistics, SocGholish continues to pose a significant global threat to organizations.\nFebruary 2024 saw its biggest advancement:\nA new infection chain that uses Python for  persistence, likely as a means to evade traditional security tools.\n\nBy using a second-stage download from the trusted domain python[.]org, this adaptation significantly enhances the malware\u2019s ability to bypass defenses and remain undetected.\nWhile defenders are well-prepared to detect malicious activity through common tools like the Windows command shell and PowerShell (see Figure 9), Python is rarely seen in malware deployments.\n\nThis relative unfamiliarity and limited detection coverage likely prompted the SocGholish team to incorporate Python into their operations, exploiting a blind spot in many security strategies. This change in tactic underscores that adversaries are not only aware of existing security controls but are actively engineering\nways to outmaneuver them.\n\n25\n\nAs a result, SocGholish continues to cement its position as a persistent and sophisticated threat to organizations worldwide.\n\n\nTake Action\n\n\n\u200cFigure 10: AsyncRAT x ScreenConnect infection chain\u200c\n\nThe powerful AsyncRAT gives attackers full control over infected\nhosts, enabling keylogging, credential theft, malware delivery\u2014including ransomware\u2014as well as C2 operation.\nTo complicate matters, it also has botnet capabilities for launching denial-of-service (DoS) attacks.\n\nUser Clicks Malicious Link in Phishing Email\n\nUser is Redirected to Malicious Site\n\nScreenConnect is Downloaded and Connects to Relay Server, Establishing C2\n\n\nThis versatility has made AsyncRAT a favorite among threat actors, and 2024 marked a defining year for the trojan, as it contributed to the second-most customer incidents over the year, up from fourth in 2023.\n\n\nAsyncRAT uses the guise of legitimate software to infiltrate systems, exploiting users\u2019 trust to evade security mechanisms, blend into normal network traffic, and deceive users into downloading malicious files\u2014all while remaining undetected.\nAsyncRAT is Dropped and Executed via Screen- Connect Connection\nAsyncRAT File Uses Valid Code-Signing Certificate to Bypass Antivirus\nAutoIT Scripting Utility is Installed\n\n26\n\nMalicious AutoIT Script is Executed and Injected into RegAsm.exe Windows Process\nRegAsm.exe Connects to Attacker\u2019s C2 server\nAttacker Places .url File in Startup Folder to Establish Persistence\n\n\nBy incorporating ScreenConnect into its methodology, AsyncRAT has achieved increasing success.\nHowever, as defenders adapt to these tactics, we expect its dominance to wane in 2025.\n\nIn July 2024, we identified a campaign in which phishing emails were sent to trick individual recipients into downloading ScreenConnect software (see Figure 10).\n\nOnce installed and connected to the attackers\u2019 ScreenConnect server, an executable\u2014equipped with a code-signing certificate capable of bypassing antivirus and Endpoint Detection and Response (EDR) tools\u2014deployed AsyncRAT onto the victim\u2019s system.\nThis incident demonstrates the critical importance of understanding what\u2019s \u201cnormal\u201d in your environment to quickly detect and respond to anomalies.\n\n\nTake Action\n\n\n27\n\n\n\n\n\n\u200cAsyncRAT\u200c\n\n\nLumma (+8)\n\n\nGootloader\n\n\nCobalt Strike\n\n\nImpacket\nClimbing from eleventh place in our 2023 rankings to third in 2024, Lumma is an infostealer malware that harvests sensitive data like browsing history, cookies, saved credentials, and cryptocurrency wallets.\n\n1  SocGholish\n\nThe stolen data is sold on criminal marketplaces\nas infostealer logs, typically priced around $10 each. Distributed through malicious websites, trojanized software, and phishing attacks, Lumma operates\nas a MaaS model, providing subscribers with continuous updates and support.\n\nLumma\u2019s growth has been explosive.\n\n\n8\n\n\nRaspberry Robin\n\n9  Clearfake\n\n\n\nDanaBot\n\n28\n\n\nDarkGate\nIts credential sales nearly doubled each quarter in 2023, and it maintained an upward trajectory in 2024.\n\n\n7  Netsupport RAT\n\n478,000 Listings\nLast year alone, more than 478,000 listings\non criminal marketplaces originated from Lumma infections, which coincided with a 4% increase in infected customer environments.\n\nIn May 2024, ReliaQuest observed Lumma being installed via a novel execution technique: coercing users into manually copying and pasting malicious PowerShell code into the console via fake browser errors or CAPTCHAs (see Figure 11).\nThis tactic was likely designed to evade traditional signature-based security detections, showcasing the attackers\u2019 relentless innovation to ensure the malware\u2019s continued success.\n\nLumma\u2019s popularity among threat actors stems from its active support for its users, frequent updates, and advanced evasion capabilities that make it highly effective for data exfiltration.\nIts logs provide attackers with direct access to internal networks and cloud platforms.\nDespite Lumma\u2019s steep subscription fees\u2014as high as $1,000 per month\u2014many attackers are willing to pay the price, as the stolen credentials yield far greater returns.\n$1,000/\nMonth\nCorporate\n$500/\nMonth\nProfessional\n$250/\nMonth\nExperienced\n\n\n29\n\nTo defend against Lumma and similar infostealer malware, organizations must include infostealers in their threat models, as stolen data can provide attackers with access to critical assets. Notably, the May 2024 breach of the Snowflake cloud platform2 was allegedly traced back to stolen credentials obtained from infostealer logs.\n\n\nTake Action\n\n\n\n\n\u200cRecommended Detection Rules\u200c\n\n\nPowerShell Obfuscated Script:\n\nWScript Executing Suspicious File:\n\nIsolate Host:\n\nDelete File:\n\n30\n\nGreyMatter Automations for Combatting Malware\nTo combat the sophisticated techniques used by top malware threats, ReliaQuest customers can enable targeted detection rules that identify malicious activity, such as obfuscated PowerShell scripts and drive-by downloads.\nIn addition, deploying appropriate Automated Response Playbooks in GreyMatter allows for rapid\ncontainment and removal of threats.\nTogether, these proactive measures help organizations minimize the impact of malware infections and prevent further compromise.\n\n\u200c48 Minutes to Breakout:\u200c\nrends\n\nIn the section we break down...\n\nThe top techniques used by attackers in 2024 to navigate networks and escalate privileges\nThe tools they employed to stay hidden\nThe growing trend of prioritizing data theft over encryption.\n\nWe\u2019ll also explore\n\n\n\n\n\u200cAn Attacker\u2019s Route to Control\u200c\n\n\n\nFirst, we\u2019ll look at the top techniques: RDP became the most common method for lateral movement, while internal spearphishing doubled year over year, leveraging employee trust and dark-web phishing kits to compromise multiple accounts.\n\n\nThen, we\u2019ll explore how privilege escalation centered around valid accounts, with 85% of breaches involving compromised service accounts. This enabled attackers to evade detection and move laterally within minutes\nof initial access.\n\n\nFinally, we\u2019ll highlight their growing reliance on legitimate tools like Impacket, WinRAR, and RMM software to maintain control and execute attacks. These tools, used in 60% of hands-on-keyboard incidents, seamlessly blend into normal activity, making their abuse significantly harder to detect.\n  \nThe period between initial access and lateral movement is known as breakout time. In our analysis of customer incidents from 2024, we found that attackers achieved an average breakout time of just 48 minutes.\n\n\u200cPercentage of 2024 Incidents by Lateral Movement Technique         Percentage of 2023 Incidents by Lateral Movement Technique\n\nIn 2024, RDP topped the list as the most-used tool for lateral movement, giving attackers a straightforward method to connect to other internal systems within an environment. Originally designed as a legitimate remote management tool for IT help desks to assist global workforces, RDP\u2019s built-in presence on Windows systems has made it a favorite among attackers.\nArmed with stolen credentials, attackers can use RDP to discreetly move between systems, blending into regular network activity without triggering alarms  that malware might. Its simplicity, stealth, and ability\nto easily connect to systems makes RDP a go-to tactic for lateral movement\u2014and its misuse shows no signs of slowing down.\n\n26%\n\nRemote Desktop Protocol\n\n16%\n\nInternal Spearphishing\n\n14%\n\nSSH & SMB/Windows Admin Shares\n23%\n\nSMB/Windows Admin Shares\n\n15%\n\nRemote Desktop Protocol\n\n8%\n\n32\n\nInternal Spearphishing\n\nFigure 12: RAMP forum user selling access and suggesting phishing internal users\n\nInternal spearphishing, a technique sometimes used in BEC attacks, doubled in frequency from 2023 to 2024, rising to become the second most common tactic for lateral movement.\n\n\nInternal spearphishing involves attackers compromising a user account and using it to send phishing emails to other users within the same organization, potentially compromising multiple accounts at once.\nThe significant rise in internal spearphishing can likely be attributed to the 200% increase in phishing kit mentions on the dark web between 2023 and 2024.\n\nThese phishing kits\u2014tools designed to help attackers with little to no technical expertise launch phishing attacks\u2014can bypass MFA and lower the barrier to entry for attackers. This is especially true when paired with services on cybercriminal forums that offer or sell access to hundreds of active email accounts (see Figure 12).\nAs a result, advanced phishing campaigns have become accessible to attackers of any skill level.\n\nBy exploiting the inherent trust that employees place in internal emails, attackers achieve far higher success rates with internal phishing compared to external campaigns. Given its success, this growing threat demands that organizations prioritize security awareness training and implement internal phishing simulations to assess system and user readiness.\n\n\nTake Action\n\n\n33\n\n\n\u200cAttackers are abusing high-privileged, valid accounts at both the domain and local levels to achieve short breakout times. Once inside an environment, attackers quickly assess the permissions of the compromised account. Basic accounts rarely provide the keys to the castle, so to establish persistence or move laterally, attackers must escalate privileges to gain the elevated access they need.\u200c\nOur findings revealed that when attackers needed to escalate privileges, valid domain accounts were their primary targets\u2014a trend unchanged from 2023. These accounts, whether owned by users, administrators, or services, are frequently exploited because they offer the access and stealth attackers need to advance their operations without detection. This trend is reflected on cybercriminal forums: For instance, we observed a user on the Russian-language forum XSS seeking advice on how to gain admin-level privileges to compromise a domain controller (DC) (see Figure 13).\nControl over a DC opens the door to countless opportunities for attackers\u2014they can map the network, access most connected devices, and steal sensitive data\u2014making them a prized target.\n\n22%\n11%\n7%\n \n\n34\n\nLocal accounts also remain a key focus for threat actors, ranking second place for most-common privilege escalation technique year after year. Stored on individual systems, local accounts include standard user accounts, service accounts, and the Windows default administrator account, and are often targeted in brute-force attacks. Because systems are guaranteed to have local accounts, attackers can bypass the need to identify specific users, speeding up their efforts to compromise systems.\nPercentage of 2024 Incidents by Privilege Escalation Technique\nPercentage of 2023 Incidents by Privilege Escalation Technique\nDomain Accounts\nLocal Accounts\nSetuid and Setgid\nDomain Accounts\nLocal Accounts\nDLL Injection\n\nFigure 13: XSS user turns to other forum users for help on escalating privileges\nScattered Spider\u2019s Web of Social Engineering Unravels Privileges\n\nScattered Spider\n\nMalware- or exploit-based attacks are noisy and can be easy to detect. But, by exploiting valid accounts, attackers make it difficult for organizations to distinguish malicious actions from legitimate activity,\na fact they take advantage of.\n\n\nThe longer attackers remain undetected, the greater the risk they pose\u2014whether through lateral movement, data theft, or deploying malicious payloads.\n\n\nWithout strong security controls, these trusted accounts can turn into an organization\u2019s vulnerability. Between January and July 2024, 85% of customer breaches involved compromised service accounts, allowing attackers to operate under the radar for extended periods.\n\n\n35\n\n Take Action \n\n\n\n\u200cIn the past, adversaries relied heavily on frameworks like Cobalt Strike and PowerShell exploits for C2.\u200c\nHowever, enhanced detection measures have made these methods increasingly risky for attackers.\nTo evade modern defenses, they are now turning to commercial applications for malicious operations (CAMO), leveraging legitimate tools such as AnyDesk and PDQ Deploy to maintain C2 and progress through every stage of the kill chain\u2014from scanning networks to deploying ransomware.\nBetween January and August 2024, ReliaQuest saw a 16% increase in the use of legitimate tools in hands-on-keyboard incidents compared to 2023, with such tools accounting for 60% of cases.\nThese trusted tools have become the backbone of modern attacks, enabling attackers to avoid detection while inflicting maximum damage. Cybercriminals\u2019 increased reliance on legitimate tools outlines the need for organizations to understand how these\n\nFigure 14: RMM tools favored by attackers\n\nNext, we'll detail the most common tools attackers used in breaches during 2024 and steps you can take to mitigate these risks.\n\napplications are being weaponized to bypass defenses.\nLegitimate RMM Tools Top Choice to Maintain C2\n\nOriginally designed for IT professionals to manage infrastructure, RMM tools pose serious security risks when left unsecured. Their legitimacy allows attackers to slip past defenses, evading detection by appearing benign. Attackers also exploit RMM tools in social engineering campaigns, posing as help-desk support to trick users into granting remote access.\nBy mimicking routine IT operations, they seamlessly integrate into workflows, maximizing the effectiveness of their attacks while avoiding suspicion.\nTo mitigate these risks, organizations must recognize the risks of RMM tool abuse, incorporate it into their threat models, and establish a baseline for normal RMM tool usage to quickly distinguish normal activity and malicious behavior.\n\n\n1. AnyDesk\n\n2. TeamView\n \n\n\n4. Jwrapper\n\n5. Dameware\n \nImpacket Now Go-To Post-Compromise Tool\n\nOriginally designed to interact with network protocols like SMB, New Technology Local Area Network Manager (NTLM), and Lightweight Directory\nAccess Protocol (LDAP), Impacket has become a go-to post-compromise tool for attackers, appearing in 33% of breaches in 2024.\nThis Python-based tool set is favored for lateral movement but also offers extensive capabilities\u2014such as credential dumping, Kerberoasting, and more\u2014that make it highly versatile and portable for\npost-compromise operations.\n\n\n3. QuickAssist\n\nAlthough Impacket is susceptible to signature-based detections, adversaries often exploit poorly monitored environments and take advantage of Impacket\u2019s use of legitimate protocols like SMB, Windows Management Instrumentation (WMI), and LDAP. It\u2019s realistically possible that adversaries adapt how they use Impacket to mimic normal network activity, making their actions harder to distinguish from legitimate behavior and appear non-malicious.\n36\n\n\n6. ATERA\n\nThese shifting tactics emphasize the importance of ensuring comprehensive network traffic logging and adequate security tool coverage to detect Impacket itself as well as the network behaviors it generates.\n\n\nFile-Compression Tools Gain Popularity Among Attackers\nAttackers are increasingly using legitimate file-compression tools like WinRAR and 7-Zip to compress staged data before exfiltration, replacing the compression features traditionally built into C2 frameworks.\nAdversaries often use these tools in combination with cloud utilities like Rclone and MegaSync to exfiltrate data to cloud storage. Because the activity generated by these tools often doesn\u2019t appear inherently malicious, organizations should establish a baseline for their usage and implement security controls to differentiate between legitimate and malicious activity.\nThe message is clear: Attackers lean on legitimate tools because they\u2019re easily accessible\u2014many are open source\u2014and incredibly versatile, allowing them to execute multiple actions at once. By using trusted tools, attackers blend seamlessly into legitimate network traffic, avoiding suspicion and complicating detection efforts, especially if an organization has no baselines for normal\nuse in place. For businesses, this camouflage can have devastating consequences. The longer attackers remain undetected in a network, the greater the risk of major data breaches or operational disruptions\u2014both of which can shatter an organization\u2019s reputation and result\nin the loss of key talent or critical business opportunities.\nMedusa Turns Everyday Tools into Weapons\n\nMedusa\n\n\n37\n\n Take Action \n\n\n\u200cTerminate Active Sessions:                              Reset MFA:\u200c\n\nNetwork Discovery Tooling:\n\nRemote Desktop Audit:\n\nImpacket Utilization:\n\n38\n\nGreyMatter Automations for Combatting Legitimate Tool Abuse\nTo combat threat actors' misuse of legitimate tools, ReliaQuest\ncustomers can leverage GreyMatter Automated Response Playbooks to quickly contain attacker activity.\nAdditionally, GreyMatter threat hunting packages enable customers to proactively detect abuse of legitimate tools within their networks.\nTogether, these actionable measures empower security teams to disrupt attacker access and put a stop to the unauthorized use of commonly trusted tools.\n\n\u200cRansomware Decoded: Exfiltration Is the New Encryption\u200c\nRansomware tactics have undergone a dramatic transformation. What began as straightforward extortion through system encryption grew into \u201cdouble extortion,\u201d where attackers compounded encryption with the threat of leaking stolen data to maximize pressure on victims. Now, many attackers are abandoning encryption altogether, focusing solely on data theft\u2014a faster, more profitable approach. In 2024, this trend accelerated, with only 20% of breaches still featuring encryption. In this section, we\u2019ll...\n\n\nExamine this rise of exfiltration-only attacks\n\nUncover the tools and methods driving these campaigns\n\nBreak down the major developments in the 2024 ransomware landscape\n  \nFrom the decline of key players to the emergence of new ones, we\u2019ll explore the twists, turns, and trends to watch. Most importantly, we\u2019ll provide actionable recommendations to help organizations defend against these evolving threats\u2014and demonstrate how ReliaQuest can keep organizations ahead of the curve.\n\n\n\n\u200cExfiltration Outpaces Encryption in Modern Breaches\n\nWhen most people think of ransomware, they picture locked systems, black screens, and ransom notes\u2014but that\u2019s no longer always the case.\nFastest Exfiltration in 2024\n4 hours 29 mins\n\nFastest Encryption in 2024\n6 hours\n\nOur data reveals a major shift in ransomware tactics: Of all breaches we observed in 2024, 80% involved data exfiltration, while only 20% included encryption.\nThis sea change is almost certainly driven by the growing adoption of advanced security tools and robust backups, which have diminished the impact of encryption-based attacks. Additionally, the process of restoring encrypted systems can be so lengthy and complex that organizations are likely choosing to rebuild their systems instead. This approach has the added benefit of ensuring that any persistence mechanisms left by the attacker are completely removed. As encryption becomes less effective, groups like \u201cInc Ransom\u201d now weaponize stolen data for extortion, resale, or access to additional targets, preying on organizations\u2019 fears of reputational damage, regulatory fines, and the exposure of sensitive information.\n39\n\nThe time required for an adversary to progress from initial access to executing data exfiltration is 34% faster than the time needed for encryption; the quickest exfiltration time we saw in 2024 clocked in at just 4 hours and 29 minutes, compared to 6 hours for encryption. This leaves defenders with even less time to detect and respond before critical data is stolen. By bypassing the technical complexities of encryption, attackers have embraced data exfiltration as their ultimate tool to strike quickly, inflict maximum harm, and maintain leverage over their victims.\n\n\n\nIn 2024, 60% of attackers who successfully exfiltrated data in the incidents we examined sent the stolen data to cloud storage platforms such as Google Drive, Mega, or Amazon S3.\n\nThese services are highly useful for stealthy exfiltration, as stolen data can be uploaded quickly and disguised within legitimate traffic from commonly used platforms. This makes detection more difficult for defenders because the exfiltration activity blends in with normal business operations. Given the potential for business disruption, blocking access to widely used cloud platforms is rarely a viable option for businesses. This limits defenders\u2019 ability to be proactive, instead forcing them to rely on advanced monitoring and alerting to identify and respond to malicious activity.\nAccounting for the remaining 40% of attacks, exfiltration over C2 channels enables attackers to funnel data directly to their own infrastructure.\n\nThis method requires a direct connection from the compromised system to the attacker\u2019s infrastructure, making the malicious activity more likely to be detected. However, despite this increased risk, C2-based exfiltration offers attackers greater control over the stolen data compared to third-party platforms like cloud services. This method is utilized by adversaries who don\u2019t use legitimate tools in their operations, such as RMM tools, and instead prefer the built-in capabilities of C2 frameworks to compress, encrypt, and exfiltrate data.\nLooking ahead to 2025, we expect the trend of exfiltration-only attacks to persist, with exfiltration times likely to drop even further. For organizations, this shift demands a rethink of ransomware recovery strategies. The focus can no longer be solely on restoring encrypted systems\u2014strategies must also address protecting data privacy, managing reputational risks, and ensuring compliance with regulatory requirements. To prepare, CISOs must implement defenses to detect and prevent exfiltration attempts while developing playbooks that prioritize business continuity and resilience against these evolving ransomware tactics.\n\n\nTake Action\n\n\n40\n\n\n\u200cIn 2024, the names of 5,253 organizations were listed on ransomware data-leak sites\u2014559 more than in 2023.\u200c\n\n\nAlthough this growth may seem modest, much of 2024 actually saw a slowdown in ransomware activity. Instability within the ransomware ecosystem played a significant role,\nas ransomware-as-a-service (RaaS) providers focused more on competing for affiliates than refining their attack techniques. Operations were further disrupted by law enforcement actions dismantling key ransomware infrastructure, improvements in security tool detection capabilities, and advancements in cybersecurity practices.\nBut the slowdown didn\u2019t last. December 2024 marked a grim turning point, recording the highest-ever victim count in a single month. This surge can be attributed to the explosion of new ransomware groups, which have grown from around 60 active groups in 2022 to nearly 100 today. To avoid the spotlight and scrutiny faced by larger operations like LockBit, smaller, decentralized groups are forming, fueling an increasingly crowded and competitive landscape. As a result, attackers are likely to push for higher ransoms and adopt more sophisticated strategies to outpace defenses and secure their share of the profits.\n\n\n\n\n\n314\n\n2024\n\n2023\n\n347\n\n271\n\n379\n\n424\n\n400\n\n316\n\n527\n\n600\n\n317\n\n457        463\n\n382\n\n439\n\n357\n\n401\n\n459\n\n542\n\n404\n\n584\n\n483\n621\n\n299\n\n161\n\n41\n\nJanuary      February      March        April         May         June         July        August     September     October     November    December\n\n\nFigure 15: Ransomware volume trends, 2024 vs. 2023\n\n\nFrom Extortion to Exit Scams: The Big Ransomware Group Shake-Up of 2024\n\nLockBit Affects 93% Fewer Organizations\n2024 marked the year that LockBit\u2014the omnipresent ransomware threat throughout 2023\u2014became the target of multiple law enforcement operations that disrupted its infrastructure.3\nWhile LockBit attempted a comeback in May by naming 176 organizations on its data-leak site, it failed to sustain momentum, ending the year with only 19 victims in its final quarter\u2014a staggering 93% decrease compared to the same period in 2023.\nALPHV Exits with Big Profits\n\n\u201cALPHV\u2019s\u201d sudden exit in March 2024, following a reported $22 million payday from its attack on Optum, added to the turbulence in the ransomware landscape.\nWith LockBit in decline and \u201cClop\u201d sticking to its strategy of infrequent but high-reward attacks, the absence of these dominant players created an opening for smaller, fragmented groups to rise to prominence throughout 2024.\nRansomHub Ups the Ante\n\n\u201cRansomHub\u201d wasted no time capitalizing on the void left by declining giant, LockBit. Its game-changing affiliate model\u2014paying affiliates 90% of the profits upfront while retaining just 10%\u2014made it a top choice among cybercriminals, driving a surge in activity.\nBy the second half of 2024, RansomHub had firmly established itself as the most active ransomware group, naming 326 more victims than LockBit.\n\n\n1038\n2024\n\n\n543\n\n\n534\n\n422\n\n369\n\n342\n\n294    267\n\n235 217            234       211\n2023\n172         171       155\n175       166       166       145\n149\n\nLockBit\nRansomHub\nALPHV      Clop       Play      8Base    Black Basta    Malas      Akira     Medusa      Qilin\nHunters International\nInc Ransom\nBlackSuit   BianLian\n\n\nFigure 16: Top ransomware groups by number of data-leak postings, 2024 vs. 2023\n\n\n42\n\nGroups to Watch Out for in 2025\n\nThe \u201cBlackLock\u201d (aka Eldorado) ransomware group, active since at least March 2024, gained prominence in July but truly made its mark in October. Its victim count skyrocketed by over 1,000% from Q3 to Q4 2024.\nLikely tied to Russia (evidenced by its refusal to target countries in the Commonwealth of Independent States), BlackLock\u2019s rapid ascent mirrors that of groups like RansomHub, proving how quickly a group can move from obscurity to dominance.\nIn September 2024, new group \u201cFunkSec\u201d emerged on the ransomware scene, making a major impact by December by listing 82 victims\u2014more than any other group that month.\nFunkSec targeted a wide range of sectors, including retail, manufacturing, health care, education, and professional services, across countries like the US, France, India, and Thailand. The group promotes its technical expertise on cybercriminal forums, boasting a free distributed denial-of-service (DDoS) tool, a Tor-based data-leak site, and a suite of self-developed tools.\n\nIt\u2019s realistically possible that both BlackLock and FunkSec stockpiled victims and chose to publish them all on their respective data-leak sites before the year ended. However, our analysis suggests it\u2019s more likely that both groups capitalized on the turbulence amongst ransomware groups, scooping up affiliates from faltering groups and thriving in the absence of dominant players.\nThe constantly changing ransomware threat means that traditional defenses won\u2019t cut it anymore. Organizations must adopt proactive, multi-layered strategies that combine technology, processes, and people. In 2025, ransomware will remain largely opportunistic, but the explosion of new groups and affiliates will make attacks more unpredictable and widespread than ever before.\n\n2760\n\n2134\nRansomware Mostly Targets US, Manufacturing, and PSTS\n2024\n\n\n\n2023\n\n252\n293\n296\n198\n158\n183\n121\n158\n137\n142\n107  92\n121  73\n114  67\n43\n\nUS              UK            Canada          Germany          France            Italy             Spain            Brazil             India\n\n\nFigure 17: Number of victims by region added to ransomware data-leak sites, 2024 vs 2023\n\n\n\nFigure 18: Number of victims by industry added to ransomware data-leak sites, 2023 vs 2024\n\n\nAs anticipated, the US remained the overwhelmingly popular target for ransomware operators and affiliates in 2024.\nThis trend is highly likely to continue, as attackers perceive that organizations in English-speaking countries have the financial means to pay ransoms.\n\n1098\n\n1079\n964\n\n855\n\n524\n\n500\n\n396\n\n381\n\n345\n347\nManufacturing\n\nProfessional, Scientific, and Technical Services\n\nConstruction\n\nHealth Care and Social Assistance\nFinance and Administration\nAdditionally, well-developed insurance markets and heightened cybersecurity awareness in these countries have driven higher adoption of ransomware insurance, making these regions more attractive to attackers.\nRansomware operators are acutely aware that the manufacturing sector is highly vulnerable to operational disruptions.\n\n396\n296\n246\n\n219\n\n173\n\nEducational Services\nRetail Trade Accommodation and\nThe integration of IT with operational technology (OT) in this sector exacerbates the problem, as downtime can lead to major productivity, financial, or legal consequences. These factors make ransom demands more effective, boosting ransomware groups\u2019 profits and attack success rates.\nThe PSTS sector is a lucrative target because of the sensitive data it handles and its reliance on digital resources for operations like client collaboration and secure file transfers. Its dependence on file-transfer software and other tools makes it especially vulnerable to exploitation. This vulnerability was evident in multiple supply-chain attacks conducted by the Clop ransomware group, where adversaries compromised widely used tools to target numerous organizations\u2014a growing trend that mustn\u2019t go unnoticed.\n\n241\n195\n\n170\n\n153\n177\n152\n149\n120\n118\n104\n107\n94\n69\n68\n64\nFood Services\n\nPublic Administration\n\nInformation\n\nArts, Entertainment, and Recreation\nMining, Quarrying, and Oil and Gas\nReal Estate and Rental and Leasing\nWholesale Trade Utilities\n\n\n44\n\n Take Action \n\n\n\n\u200cRecommended Detection Rules\u200c\n\n\nRclone Execution via Command Line:\n\nData Exfiltration via Command Line:\n\nRansomware File Extension:\n\n\nRecommended Threat Hunting Packages\n\n\nExfiltration Tools:\n\nProxy and Protocol Tunneling Tools:\n\nRMM Software:\n\n45\n\nGreyMatter Detections and Automations for Combatting Ransomware\nTo combat ransomware and data exfiltration threats, we advise customers to use the following targeted detection rules and GreyMatter threat hunting packages that are designed to identify specific malicious activity, such\nas the use of exfiltration tools and ransomware-specific behaviors.\nThese solutions help organizations detect and disrupt data theft, unauthorized access, and ransomware deployments, minimizing the impact of attacks and protecting critical assets.\n\n\n\n\u200cA CISO\u2019s Checklist\u200c\n\nAttackers are now averaging just 48 minutes to move laterally, adapting to security controls, bypassing MFA in 100% of successful BEC incidents we investigated, and blending into environments by exploiting the very software and tools organizations rely on daily.\nIn 80% of breaches, attackers exfiltrated data by mimicking normal activity, thereby avoiding detection. Our analysis also revealed that the top cause of major incidents was visibility gaps.\nArmed with this knowledge, it\u2019s time to act. Throughout this report, we\u2019ve shared targeted recommendations to mitigate the threats we\u2019ve identified\u2014but there\u2019s more that organizations can do.\nWe've compiled the main takeaways every CISO needs to know. By adopting these measures, organizations will be better positioned to minimize their exposure and outmaneuver this year\u2019s biggest threats.\n\nRead on to explore\n\n\nTo Respond at Top Speed, Automate\n\nAutomated responses excel in scenarios where speed is critical. GreyMatter Automated Response Playbooks can reduce MTTC to as low as three minutes when incorporated into incident response plans.\n\nAlternatively, set GreyMatter Response Playbooks to \u201cRQ Approved\u201d to allow ReliaQuest to remediate incidents directly, significantly\nimproving MTTC and accelerating response times.\n\nImplement the GreyMatter AI Agent to entirely eliminate the Tier 1 and Tier 2 tasks that slow down analysts.\n\n\n47\n\nUse GreyMatter Phishing Analyzer to automate the analysis of user-submitted phishing emails. This significantly accelerates the triage and remediation process for phishing email inboxes, executing actions like email deletion, URL blocking, and host isolation.\nBlock Initial Access by Shoring Up Foundations\n\nImplement MFA, but don\u2019t rely on it as a silver bullet solution. Strengthen MFA by incorporating additional safeguards, such as conditional access policies, restricting access to trusted devices, and shortening token expiration times.\n\nFor VPNs, implement client-based certificates and access policies to restrict authentication, which will reduce the likelihood of unauthorized access. Make an inventory of public-facing devices, prioritize patching to address vulnerabilities, and prepare continuity plans if critical devices must be temporarily disconnected to prevent exploitation.\n\nTrain employees to recognize social engineering tactics, particularly employees in IT help-desk roles. Focus on robust training programs, testing, and clear standard operating procedures to prevent successful social engineering attacks.\nDisrupt and Contain Attackers with Defense-in-Depth\n\nRotate potentially compromised credentials at the earliest opportunity. Acting quickly prevents attackers from exploiting valid accounts to move laterally within compromised networks.\n\nVerify that service accounts are not overprivileged with domain admin rights, enforce password length and complexity requirements for service accounts, and enable Advanced Encryption Standard (AES) encryption for Kerberos to mitigate cracking.\n\nEnsure comprehensive logging and coverage for endpoint security tools, including critical assets. This approach will eliminate blind spots and enhance security monitoring, allowing for faster threat detection.\n\nImplement detection rules to identify the unauthorized use of tools or software and engage in frequent threat hunting to detect anomalous activities. Serious threats fly under the radar, so a defense-in-depth strategy is key to staying ahead.\n\nOur Threat Forecast for 2025\n\n\nLooking ahead, ransomware attacks are set to surge throughout 2025, surpassing their 2024 levels and rivaling December\u2019s record-breaking activity.\n\n\nWhile RansomHub may dominate early in the year, we expect BlackLock to take the lead by Q3.\nMeanwhile, we anticipate that 8\u201310% of investigations will likely involve threat actors leveraging large language model (LLM) tools, alongside a projected 10% increase in non-human identity (NHI)-based attacks, such as the compromise of API keys, service accounts, and digital certificates.\nSpearphishing, exploiting public-facing applications, and targeting external remote services will remain key tactics, fueled by rapid vulnerability exploitation, human error, exposed credentials, and ever-expanding attack surfaces.\nReliaQuest Exists to Make Security Possible\n\nThe last year in cyber threats has emphasized again and again the critical importance of speed, automation,\nvisibility, and proactiveness in modern security operations.\n\nOrganizations must have the right weapons in their arsenal to defend against attackers who are getting smarter and more efficient.\n\nReliaQuest\u2018s AI-powered security operations platform, GreyMatter, is purpose-built to confront these challenges, providing customers with the capabilities they need to secure their environments against the threats detailed in this report.\nTo accelerate containment and response, we\u2019ve created our own agentic AI Agent as well as developed Automated Response Playbooks that prevent cybercriminals from\ngaining or maintaining a foothold\u2014all without manual effort.\n\nThe GreyMatter AI Agent autonomously handles 100% of security alerts end-to-end. Combining this capability with Automated Response Playbooks has enabled our customers to achieve containment and response times as low as 3 minutes. When customers pair Digital Risk Protection with GreyMatter, they achieve 360-degree visibility into the\nthreats facing their organization, both within their environment and outside it. DRP identifies threats on the open, deep, and dark web, allowing customers to counter them before they reach their attack surface.\nGreyMatter also uses external threat data, including the latest threat actor TTPs, to develop threat hunting packages that customers can use to proactively identify early indicators of compromise. By spotting known tactics early, customers prevent attacks from progressing.\n\n48\n\nWith GreyMatter, ReliaQuest customers are well armed against the threats facing us in 2025 and beyond. To see how GreyMatter can help protect your organization, visit reliaquest.com to request a demo tailored to your environment.\n\nAbout ReliaQuest\nReliaQuest exists to Make Security Possible.\n\nOur agentic AI-powered security operations platform, GreyMatter, allows security teams to detect threats at the source, and contain, investigate, and respond in less than 5 minutes\u2014eliminating Tier 1 and Tier 2 security operations work.\nGreyMatter uses data-stitching, detection-at-source, AI, and automation to seamlessly connect telemetry from across cloud, multi-cloud, and on-premises technologies.\n\nReliaQuest is the only cybersecurity technology company that delivers outcomes specific to each organization\u2019s unique architecture, technology, and business needs.\nWith over 1,000 customers and 1,200 teammates across six global operating centers, ReliaQuest Makes Security Possible for the most trusted enterprise brands in the world.\n\nLearn more at www.reliaquest.com\n\nReliaQuest\u2019s ShadowTalk is a weekly podcast featuring discussions on the latest cybersecurity news and threat research.\nListen to the latest episodes on your favorite podcast channels.\n\nreliaquest.com                 800.925.2159             info@reliaquest.com\n\nCopyright \u00a9 2025 ReliaQuest, LLC. All Rights Reserved. ReliaQuest, GreyMatter, Digital Shadows, and all related logos, product and services names, designs, and slogans are trademarks or registered trademarks of ReliaQuest, LLC or its affiliates or licensors. All other product names or slogans mentioned in this document may be trademarks or registered trademarks of their respective owners or companies. The ReliaQuest software, platform,  portal and its entire contents, features, and functionality are owned by ReliaQuest, LLC and its affiliates. These materials are protected by United States and international copyright, trademark, patent, trade secret, and other intellectual property or proprietary rights laws. All other information presented is provided for informational purposes with no representations or warranties provided of any kind and should not be relied upon for any purpose. ReliaQuest has no obligation to amend, modify, or update the information contained in this document in the event that such information changes or subsequently becomes inaccurate. Printed in the USA.\n\nEndnotes\n\n\nhxxps://nvd.nist[.]gov/vuln/search/statistics?form_type=Advanced&results_type=statistics&search_type=all&isCpeNameSearch=false&cvss_version=3&cvss_v3_metrics=AV%3AN%- 2FAC%3AL%2FPR%3AN%2FUI%3AN&cvss_v3_severity=CRITICAL\n\n\nhxxps://www.darkreading[.]com/cyberattacks-data-breaches/canadian-authorities-arrest-snowflake-data-thief\n\n\nhxxps://www.europol.europa[.]eu/media-press/newsroom/news/law-enforcement-disrupt-worlds-biggest-ransomware-operation\n]]>\n  \n  \n    Oliver Molander\u2019s Post\n    https://www.linkedin.com/posts/olivermolander_artificialintelligence-activity-7315311203709345795-DzuX?utm_source=share&utm_medium=member_ios&rcm=ACoAAAALkv4BTofKmG92LxlnRhQHdizotUKgWrc\n    readwise:01jrev035e5aks9resxw074kmw\n    Thu, 10 Apr 2025 03:13:19 +0000\n    linkedin.com\n     Oliver Molander \n\nAI & Data Entrepreneur and Investor | Backing Exceptional Technical Founders at Inception\n\nThis is an incredibly fundamental shift that we\u2019re not talking enough about \ud83d\udc47\n\nThe ongoing AI platform shift is quietly dismantling SEO as we know it.\n\nAs Andrej Karpathy recently pointed out on X:\n\n\u201cIt\u2019s 2025 and most content is still written for humans instead of LLMs. 99.9% of attention is about to be LLM attention, not human attention.\u201d\n\nThink about it: when researching software today, operational buyers and procurement teams are increasingly using AI tools like ChatGPT, Claude, Gemini, or Perplexity.\n\nTyping something like \u201cCompare Salesforce & Hubspot for a 10-person sales team - which is better?\" into an AI assistant is rapidly becoming the norm.\n\nThis shift has massive implications for B2B marketers and sales teams:\n\n\u2705 SEO is no longer enough\n\u2705 The traditional \u201c10 blue links\u201d search model is fading\n\u2705 The AI does the discovery work now, not the user\n\u2705 Companies must now optimize for LLMs (not just Google search)\n\nAs Tomasz Tunguz and others have noted, AIO (AI Optimization) will emerge as the new frontier in content and inbound strategy.\n\nSome early signs:\n\u27a1\ufe0f G2\u2019s traffic is down 50% in two years post-ChatGPT (Elena Verna)\n\u27a1\ufe0f We've all read about how e.g. StackOverflow\u2019s traffic and PMF are crumbling\n\u27a1\ufe0f As a concrete startup example - StackAI now receives more inbound from ChatGPT & Perplexity than from Google (per Antoni Rosinol)\n\nAs Erik Wikander put it:\n\n1\ufe0f\u20e3 AI will do the heavy lifting in information discovery\n2\ufe0f\u20e3 The search results page is dying\n3\ufe0f\u20e3 Companies must optimize for AI aggregation, not human eyeballs\n\nWe\u2019re at the start of a major shift in search, discovery, and attention.\n\nE.g. HubSpot, Figma and Canva are loosing organic traffic due to content that is now answered by AI - as seen in the 3-month charts below.\n\nAnd yes - I know Similarweb data isn\u2019t perfect, but the trend lines are too clear to ignore.\n\nSEO is dead. Long live AIO!\n\n#artificialintelligence\n\n \n \n  ]]>\n     Oliver Molander \n\nAI & Data Entrepreneur and Investor | Backing Exceptional Technical Founders at Inception\n\nThis is an incredibly fundamental shift that we\u2019re not talking enough about \ud83d\udc47\n\nThe ongoing AI platform shift is quietly dismantling SEO as we know it.\n\nAs Andrej Karpathy recently pointed out on X:\n\n\u201cIt\u2019s 2025 and most content is still written for humans instead of LLMs. 99.9% of attention is about to be LLM attention, not human attention.\u201d\n\nThink about it: when researching software today, operational buyers and procurement teams are increasingly using AI tools like ChatGPT, Claude, Gemini, or Perplexity.\n\nTyping something like \u201cCompare Salesforce & Hubspot for a 10-person sales team - which is better?\" into an AI assistant is rapidly becoming the norm.\n\nThis shift has massive implications for B2B marketers and sales teams:\n\n\u2705 SEO is no longer enough\n\u2705 The traditional \u201c10 blue links\u201d search model is fading\n\u2705 The AI does the discovery work now, not the user\n\u2705 Companies must now optimize for LLMs (not just Google search)\n\nAs Tomasz Tunguz and others have noted, AIO (AI Optimization) will emerge as the new frontier in content and inbound strategy.\n\nSome early signs:\n\u27a1\ufe0f G2\u2019s traffic is down 50% in two years post-ChatGPT (Elena Verna)\n\u27a1\ufe0f We've all read about how e.g. StackOverflow\u2019s traffic and PMF are crumbling\n\u27a1\ufe0f As a concrete startup example - StackAI now receives more inbound from ChatGPT & Perplexity than from Google (per Antoni Rosinol)\n\nAs Erik Wikander put it:\n\n1\ufe0f\u20e3 AI will do the heavy lifting in information discovery\n2\ufe0f\u20e3 The search results page is dying\n3\ufe0f\u20e3 Companies must optimize for AI aggregation, not human eyeballs\n\nWe\u2019re at the start of a major shift in search, discovery, and attention.\n\nE.g. HubSpot, Figma and Canva are loosing organic traffic due to content that is now answered by AI - as seen in the 3-month charts below.\n\nAnd yes - I know Similarweb data isn\u2019t perfect, but the trend lines are too clear to ignore.\n\nSEO is dead. Long live AIO!\n\n#artificialintelligence\n\n \n \n  ]]>\n  \n  \n    A compendium of critical domestic policies to drive growth, opportunity and well-being\n    https://www.jpmorganchase.com/ir/annual-report/2024/ar-ceo-letters\n    readwise:01jr8fstcrkfz31pm695xhf6kx\n    Mon, 07 Apr 2025 16:02:12 +0000\n    jpmorganchase.com\n    \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWe should do everything we can to drive healthy growth in the economy. By doing so, we create the resources to constantly reinvest in our country, and we create the conditions to promote greater opportunity and well-being for all our citizens. In this section, I describe nine critical policies that I believe are essential to making our economy strong \u2013 putting us in the best position to deal with any issue in front of us, economic or geopolitical, and guaranteeing our ongoing military and economic predominance.\n\nIn compiling this list, I tried to look at the United States as I would any large complex company that we might acquire. (Of course, our country is much more complicated than any one company.) A full assessment of all critical issues allows you to develop a game plan. The issues I\u2019ve highlighted \u2013 and there may be more \u2013 are those that I believe are holding us back and causing much of the \u201cgrievances\u201d I wrote about in the first section. In all cases, I tried to be practical in my approach, and, in some cases, I offer ideas for potential fixes.\n\nI tried to look at this without regard to how positions might be labeled; i.e., conservative, liberal, progressive, red or blue. Whether my views are right or wrong, it is critical that we start to fix that which is broken.\n\nGovernment as a whole needs to demonstrate to the American public that it is effective, efficient, competent and principled \u2013 as any institution should do \u2013 in developing policies that are conducive to maximizing long-term growth, jobs, competitiveness and fairness \u2013 without micromanaging the economy.\n\nThe government, like all institutions, should continuously prioritize and allocate resources to streamline its operations and reduce red tape to improve service delivery, enhance responsiveness and achieve cost efficiencies. Every department should focus not just on the amount of money spent but on what it expects the outcomes should be, what the outcomes actually are and how it can deliver more at a lower cost.\n\nInstead, we have a broken bureaucracy that fails to fully acknowledge or effectively deal with our biggest problems. Even worse, the power of the government over the years has been used to attack parties, businesses and individuals, particularly those not in favor by the party in power. This needs to stop. It begins by always reminding the American public about the founding principles of the United States of America \u2013 the principles embedded in our Declaration of Independence and the Constitution \u2013 liberty, freedom, individual rights and justice for all.\n\nThe economic machine is extraordinarily complex. We need to focus on proper policies that are conducive to growth. Micromanaging coupled with misguided, ill-informed policies not based on reality and pragmatism often have huge unintended consequences. People frequently twist accurate data with bad logic to kill good policy. Many times, it is easier to throw money at a problem, mostly on the demand side (i.e., spend more money), than to formulate good policy or spend money appropriately to help the supply side. Good supply-side policies, such as those promoting job creation and infrastructure development, are critical to achieving productivity and, therefore, to maximizing long-term growth. While innovation is the cosmological constant always driving growth, sometimes its downside is used to block it. This is a huge mistake. We should foster innovation and then create policies that help those who are negatively affected.\n\nWe need consistent and responsible tax and fiscal policies. \n\nAmerica could benefit from a bipartisan, binding mechanism to achieve fiscal responsibility, similar to a Simpson-Bowles type of commission \u2013 but with real congressional authority. Some countries, such as Sweden, have implemented a fiscal policy framework with specific guidelines. Sweden\u2019s framework establishes a debt-to-GDP ratio of 35% plus or minus 5%. This allows the country to run deficit financing at the same rate as its economic growth and still maintain a debt-to-GDP ratio of 35%. Adhering to this kind of consistent fiscal standard makes it easier to manage the country in general. The United States should eventually establish similar guidelines that would make it easier to run this \u201cship of state\u201d and reduce the uncertainty that results from constant flip-flopping between sometimes radically different fiscal policies.\n\nAdditionally, we should eliminate the debt ceiling. The debt ceiling is essentially a \u201cweapon of mass destruction\u201d that can be misused by politicians who don\u2019t understand the damage it can do. It\u2019s hard to even contemplate the harm that would be done to the trust in America and in our economy if we actually failed to meet our debt obligations.\n\nWe must learn to account for investments differently from the way we account for expenses, particularly in areas such as infrastructure.\n\nThe lack of proper accounting by the U.S. government is astounding and is almost laughable. Unfortunately, the practice drives terrible decision making. For example, in determining the deficit, the government treats investments in infrastructure (roads, hospitals, ports) the same way that it treats expenses. But we should put them in completely different budgetary categories. Good investment spending has long-term productivity benefits that many expenses do not.\n\nThe United States now spends only 0.55% of its GDP on infrastructure. The OECD average is at 0.81%, and China\u2019s is a staggering 5.56%. We need to spend more money on productive infrastructure, not less. Borrowing to invest is fundamentally different from borrowing to consume.\n\nThe government also makes a lot of loans, but it doesn\u2019t have to account for them in the same way that a bank does \u2013 which makes bad lending easy to do. For example, the government continues to extend a significant amount of student loans with improper or no underwriting. When the student loan system was taken over by the government in 2010, loan losses had been reasonable, and loans outstanding were $750 billion. Through the magic of government accounting, the government actually forecasted more than $60 billion in profit from when they took over the program. Thirteen years later, the outstanding debt from student loans has more than doubled to $1.6 trillion, and we estimate that the government has lost, with proper accounting, at least $500 billion. Yet the government continues to make many of these bad loans.\n\nThe stakes are even higher regarding the government\u2019s control of two of the largest financial institutions in the world, Fannie Mae and Freddie Mac, whose combined assets of $7.7 trillion largely represent mortgages these organizations have guaranteed. It is incumbent on our government to properly manage institutions like these to protect U.S. taxpayers from tremendous losses (they lost $265 billion in the great financial crisis) and to shield U.S. and global economies from severe damage.\n\nTo make the U.S. tax system conducive to economic growth and job creation, we should incorporate these overall objectives:\n\n \nBe agnostic to specific industries, setting aside favoritism.  \nOffer a system that is stable with standards consistently applied. \nEnsure that our practices keep the United States competitive with other countries. \nProvide effective incentives for growth and innovation.  \n\nThe 2017 Tax Cuts and Jobs Act (TCJA) took significant steps toward achieving these goals by (1) broadening the tax base, (2) reducing the federal corporate rate to 21% (which is approximately the OECD average) and (3) reforming the international tax rules. The first point is sometimes forgotten: While the reduction of the headline tax rate from 35% to 21% was projected to reduce corporate taxes by $1.4 trillion (over 10 years), the broadening of the base offset $1 trillion of that reduction. Regarding international tax rules, a key part of that reform was the removal of gimmicks that allowed U.S. corporations to indefinitely defer tax rules on their overseas earnings. As a result, our international tax system strikes about the right balance between recognizing the importance to U.S. companies of serving overseas markets while not incentivizing them to move capital, skills and R&D outside the country.\n\nAlthough there is certainly room for improvement, overall, the changes made by the TCJA recognize that reducing and rationalizing taxes on business income are critical to spurring economic growth and producing more \u201cbang for the buck\u201d than cutting taxes on individual income. Importantly, these reforms benefited most Americans. In the first two years after the TCJA went into effect, we saw real median income rise more than in the previous 10 years and the lowest unemployment rate for adults without a high school diploma.\n\nIn the year following enactment, we also saw GDP growth of 3% and a 20% increase in domestic investment for affected firms. Corporate taxes paid have risen to record levels \u2013 not because the tax burden on corporations was increased, but because corporations were more profitable; they were doing more business, hiring more people, making more investments. None of this would have been possible without a competitive corporate tax rate.\n\nOur Internal Revenue Code can be further amended to incentivize growth and ensure a fairer tax system overall. \n\nOn the first point, our tax system should provide effective incentives for growth and innovation to support entrepreneurs and small businesses. Two such examples were in the tax code for decades before Congress recently phased them out: (1) recognizing the importance of capital investments and (2) increasing expenditures for R&D. Both are proven ways of growing the economy and creating jobs.\n\nAs to ensuring a fairer system, there are still numerous provisions for Congress to go after. On the business side, the rules intended to prevent artificial shifting of taxable income outside the United States need strengthening and a number of specific industry tax breaks need eliminating. On the individual side, there are also many tax breaks that primarily benefit a certain segment of the population: the wealthy. These include carried interest, the ability to deduct up to $10,000 of state and local taxes, and too many creative estate tax planning techniques. These tax breaks not only cost revenue but also have the additional stigma of being perceived by the American public as just another example of institutional bias and favoritism toward a special interest group. And consistent with ensuring a fairer system, the U.S. tax code should incorporate the \u201cBuffett Rule\u201d so that high-income earners pay a minimum tax on realized income. Everyone, including the wealthy, would benefit enormously from the increased growth that would follow if we amended our system the right way. I think many people would have fewer objections to paying a slightly higher tax rate if they thought the money was being used wisely to attack America\u2019s biggest problems.\n\nFinally, the tax code plays an important role in helping to raise up those at the bottom of the economic ladder. This includes incentives to ensure an adequate and affordable housing supply, such as the credit provision for building affordable housing. It\u2019s important that any tax credit and social benefit program be properly phased in so that it doesn\u2019t dis-incent work. One way the code could incentivize labor force participation is to expand and reform the Earned Income Tax Credit (EITC). The EITC gives an individual earning $14,000 a year with two children a $5,600 tax credit (and with no children a $350 tax credit). I would almost double this tax credit and remove the child requirement. While this would cost a lot of money, it has many virtues. It would give those with lower income far more money to spend, without government interference, on what they and their families need \u2013 education, food, better housing and more. And much of it would be spent locally, in lower-income neighborhoods. It has the virtue of rewarding work, which would grow the GDP. Jobs not only bring dignity but better social outcomes in terms of less homelessness and crime, improved health outcomes and more household formation, among other benefits. For many people, that first job is just the first rung on the ladder of a career. I have little doubt that this plan would more than pay for itself over time. Many Republicans and Democrats support this program as it helps create the American Dream for many people.\n\nOur education system is in deep need of reform to create skills, jobs and opportunity. \n\nMuch of our education system no longer truly meets our country\u2019s promise that its students graduate with the skills they need to attain a good job. The American Dream itself rests upon our providing, as best as we can, equal opportunity to all our citizens. Education and jobs are still the best way to achieve this. That certainly can\u2019t happen when so many of our schools are not working.\n\nIn a number of our inner-city high schools, under 50% of the students graduate, and those who do often don\u2019t have the skills they need to hold a well-paying job. Increasingly, poverty has become intergenerational.\n\nThe growth of America was always driven by productivity that matched capital investment with skills, which is also the driver of individual incomes. Fortunately, all we need to do is reorient what we do today. No investment is required. It is essentially free; we just need to redirect existing resources (the United States spends almost $1 trillion a year on K-12 education) into better outcomes.\n\nLet\u2019s begin with a refresh of our country\u2019s workforce training system.\n\nEffective workforce training systems that align education, training and the private sector are necessary for securing well-paying jobs. There are many successful examples, but one will suffice. Aviation High School in Long Island City, New York, teaches its students not just the basic high school curriculum but also how to maintain small aircraft; i.e., hydraulic, engine and electrical systems, and other technical skills. Some students travel several hours a day to get to school, and often parents are the driving force behind their child\u2019s enrollment. The school graduates about 450 students annually, many of whom go directly into the aviation field. These young people are currently earning in the range of $80,000 a year (not including overtime) from major U.S. airlines who are in desperate need of these types of skilled workers.\n\nSchools like this are the template we need to follow, modernizing education and workforce development programs to be responsive to current workforce needs. The advent of AI and technological change will require lifelong learning and re-skilling. Career and Technical Education programs and alternative pathways, such as apprenticeships, earn-and-learn programs and work-based learning, also provide effective career entryways.\n\nReforms to credentialed programs could also increase access to careers with a future and reward experience. We know exactly what to do, though systems change is hard. There are millions of jobs available for which training could be done in high school, community college or special programs outside of school. For example, there are training programs lasting 12-24 weeks in coding, advanced manufacturing, cyber, data science, program management, and nursing and healthcare-related areas. These trainings should be certified and counted as credits for undergraduate or graduate education. Many unions run excellent apprenticeship and training programs that certify workers for badly needed high skilled jobs like welding, electrical work, plumbing and others. These jobs can pay well in excess of $100,000 a year.\n\nTwo other points: Pell Grants, which are government grants awarded to students to help pay for eligible two-year or four-year colleges, should be available for work credential programs. In addition, the Workforce Innovation and Opportunity Act should be reauthorized to support Second Chance initiatives that give returning felons an opportunity to receive training to re-enter the workforce.\n\nHigher education costs too much and is insufficiently linked to outcomes.\n\nMany people who graduate from college are successful not solely because of their college degree. Their opportunities stem from their socioeconomic circumstances \u2013 how and where they grew up \u2013 which offer them knowledge, confidence, and often internships and relationships within the workplace that give them a leg up. Even with all of that, over 30% of those who obtain college degrees face underemployment; i.e., low-paying jobs. They, too, need skills. You can major in philosophy or history, but a credential of value in coding, data science and analytics, graphic design, financial accounting, digital marketing or engineering can lead to jobs making $80,000+ a year.\n\nSome portion of higher education funding should be linked to outcomes focusing less on graduation and employment rates and more on income levels of graduates.\n\nThe federal student lending system needs to be reformed to help ensure that the borrower\u2019s education is leading to a good-paying job. This would be better for the student, would reduce future loan losses and would discourage simply driving education costs up.\n\nEarly childhood education is critically important (it\u2019s a long-term investment so start now).\n\nEarly childhood education is a long-term investment so it is important to start now. Universal pre-K and other early childhood programs enhance educational outcomes and increase parent labor-force participation. Almost every study I have seen shows the tremendous return on this investment (some even showing two to four times for every dollar invested) even though it appears as a cost in the early years. Included among the positive outcomes for both the parent and the child are early childhood education and higher levels of income, good health and parental employment.\n\nAll students should receive a basic financial education.\n\nFinancial education should be taught as part of the K-12 education system. Everyone, and in particular our young people, should understand the basics: the need for a rainy day fund, how to look at savings, the value of a checking account (versus payday lending), the value of homeownership, the importance of saving for retirement and other basic principles. Specific financial coaching delivered simultaneously with opening a first bank account would also be very effective.\n\nTeaching health and well-being in grades K-12 would benefit all our citizens.\n\nA basic understanding of health, exercise and nutrition would be a huge benefit for our society. Ninety percent of our nation\u2019s $4.5 trillion in annual healthcare expenditures are for people with chronic conditions (certain cancers, heart disease, diabetes, obesity, musculoskeletal disorders and mental health). Preventive medicine and early interventions to manage these diseases, especially those directly related to behaviors (smoking, drinking, poor exercise and nutrition) can have significant health and economic benefits. One small but meaningful example: Cigarette smoking costs the United States more than $240 billion in healthcare spending. This could be reduced every year if we could prevent young people from starting to smoke and help those who do smoke to quit.\n\nWe must remedy the healthcare system, both to reduce costs and improve outcomes. \n\nAmerica has among the best and worst of healthcare. While we may have the best doctors, hospitals, pharmaceutical industry, medical devices and more, our average outcomes are not good, and our costs are double those of our global competitors (17% of GDP versus 9% in other countries). In addition, 27 million people don\u2019t have insurance, and, as mentioned above, preventable chronic diseases run rampant. Our healthcare system also lacks transparency around costs, pricing and proper incentives since the user never effectively pays the full price. We need to begin reform right away.\n\nA few simple policy changes would go a long way toward improving all of this:\n\n \nHealthcare data should be tabulated in a consistent way across all healthcare organizations and providers. \nAll healthcare data should belong to the individual and, therefore, be transferable (and not used for unauthorized purposes by anyone). \nIncreasing transparency for both the companies and the patients is essential, ensuring clarity about the cost of care. Additionally, patients should understand what their medicines will cost them and be eligible for volume discounts, including rebates. \nHealthcare would be more affordable if the exchanges were national and offered a broader range of insurance options people could buy.  \n\nBetter data and more consistent standards across Medicare, Medicaid and commercial markets are needed, with transparency and elimination of fraud and waste being key to stabilizing markets and portability being important for empowering patients.\n\nEngaging employees by prioritizing health education and literacy can help make them informed consumers of healthcare and wellness. Addressing the significant problem of medical bankruptcy in the United States is crucial, and medical bills should not be calculated as part of credit scores.\n\nOne day, individuals should be responsible for purchasing their own healthcare. Healthcare should not be an annual purchase \u2013 you should be able to make a long-term buy, which means you would be the beneficiary of taking care of your own health.\n\nOne final point. Over the last 100 years, the health of our citizens and our workforce has played a significant role in increasing productivity for American workers. Some studies show that over the last 25-30 years, this may have accounted for as much as 45% of productivity growth over time. Healthier workers and the participation of older workers (due to their accumulated knowledge and wisdom) are the main reasons.\n\nWe can improve effective regulations while reducing crippling rules, demoralization, and arbitrary and expensive litigation. \n\nI don\u2019t even know where to begin! How did the can-do, commonsense practical America end up here? Clearly, something is broken. We have gotten to the point where we barely talk about improving our regulations. We only talk about adding more \u2013 contributing to endless, mind-numbing and demoralizing bureaucracy. Studies show that the cost of our regulations (which do have some productive outcomes) is over $3 trillion annually. J.P. Morgan Global Research estimates that relative to the United States, more restrictive regulation reduces long-term growth in the five largest European Union economies by 0.8% per year, and in China by 2.4% per year. These regulations are at the federal, state and local levels, and they affect every industry and business, small and large. They range from permitting and licensing to employment rules and tax compliance (and much more). Each of these rules could easily be fixed. Take permitting, for example. Various regulators, state and federal, should be forced to approve projects sequentially. Some countries (Singapore and Canada) have rules to reduce permitting timelines substantially to two years or fewer (ours can take over 10 years). Regulations shouldn\u2019t be like concrete (immovable) \u2013 they should be constantly improved. U.S. law already requires major rules and regulations to have a cost-benefit analysis done \u2013 this needs to be fully enforced. There are hundreds of rules to fix. Often these regulations are targeted at the financial and technology sectors, whose industries help drive our dynamic economy.\n\nThe cost of our tort system is over $500 billion a year, a little more than 2% of our GDP. While the tort system plays an important role in compensating victims and deterring irresponsible behavior, our system is capricious and arbitrary. Since the loser never pays, there is a great incentive for someone to sue and for the person being sued to settle. Much of the compensation never even gets to the victims. These costs are two-and-a-half times the average level of eurozone countries. One example of a major improvement would be Florida\u2019s recent reforms, which seem to have both reduced the excessive cost of torts to the system while giving people better odds of proper recompense.\n\nThese excessive regulatory and litigation costs result in higher costs across the whole economy, including infrastructure, utilities, education and other essentials. Proper federal, state and local regulations, along with permitting reform, are necessary to reduce delays and litigation. Minimizing red tape would make it easier, cheaper and faster to build infrastructure such as roads, schools, bridges, energy facilities and homes. A little common sense would go a long way.\n\nOne last point: Excessive regulations make it much harder to start a new business, and they often reduce competition. And they almost always hurt smaller companies more than larger ones.\n\nWe could do a better job supporting small businesses.\n\nSmall businesses power job growth in America \u2013 they account for two-thirds of new jobs and employ nearly half of the American workforce. Our entrepreneurial ecosystem has been the envy of the world for generations, and it is essential to create a policy environment that facilitates small business creation, growth and continuity.\n\nBusiness starts have been above-trend for several years, but the failure rate remains high \u2013 50% fail in the first five years. Public-private partnerships can help fill the capital gap in the white space between venture funding and bank lending.\n\nSmall business owners in low-to-moderate income areas face more headwinds than those in wealthier communities, so tax benefits and community education programs play an important role in helping communities lift themselves up through commerce. While banks will remain a critical supporter of small business in their growth phase, the Small Business Administration\u2019s role is crucial and agency modernization must remain a priority, including reforms to the Small Business Investment Company program and the National Technical Assistance program.\n\nFinding qualified talent is the #1 challenge facing small businesses owners, and nearly 40% of them have job openings that they can\u2019t fill. Public partnerships with trade schools and community colleges can increase the supply of skilled labor. As mentioned in the education section, there are many ways to increase the supply of skilled labor.\n\nInnovative healthcare legislation can reduce healthcare costs and help small businesses compete with larger employers for talent.\n\nJust like for larger businesses, there is a need for predictability in tax policies, litigation processes and the EITC \u2013 over 15% of small business owners cite these issues as their most pressing problems. Many small businesses face a heavier burden from state and local regulations than from federal ones so seeking best practices from multiple jurisdictions to streamline requirements can support business operations and growth.\n\nFinally, we must prepare for the coming \u201csilver tsunami\u201d in small business \u2013 75% of business owners would like to exit their business in the next decade, representing trillions of dollars in business wealth at stake. There will be substantial turnover in small businesses in the next decade, and we must prepare the next generation with the skills and passion to take the baton. Local communities can help protect their tax and employment base by investing in succession and transition education programs.\n\nWe should have permanent plans to consistently drive the building of great infrastructure.\n\nEvery state, city and municipality should have multi-year infrastructure plans. Improper planning and ineffective execution are rampant, costly and potentially dangerous. Waiting for bridges to be near collapse or airports to be overly crowded is a bad idea. This planning could include manufacturing sites, maritime, grids, housing, pipelines, canals, broadband and highways, to name but a few.\n\nWe can make it easier to build a more affordable housing supply.\n\nTo address the housing supply issue, it is important to increase funding for effective, affordable housing production programs. This can be partially and easily achieved by expanding the already successful Low-Income Housing Tax Credit programs. Additionally, incentivizing investments that increase economic opportunity in disinvested communities is crucial, and making the New Markets Tax Credit program permanent would support this goal.\n\nIn terms of mortgages, reducing unnecessary regulations would decrease homeownership costs. Streamlining loan origination and servicing standards, reducing capital requirements and simplifying securitization rules would reduce the cost of mortgages without making them riskier. These simple reforms could lower the cost of mortgages by 70\u201380 basis points. The costs of unnecessary regulation go beyond price\u2014they impact the availability of credit and who can qualify for a mortgage. The Urban Institute estimates that a reduction like this would increase mortgage originations by 1 million per year and help lower-income households, in particular, buy their first home. This would specifically help individuals buy homes in the $150,000\u2013$300,000 range. Buying a home, still a pillar of the American Dream, is simply the best way for individuals to start building household wealth.\n\nGood and consistent local zoning requirements \u2013 that are executed with a sense of urgency \u2013 are essential in building more affordable housing. Finally, the availability of more housing, particularly lower-income housing (it\u2019s generally more economical to build denser housing than detached housing), would help people move out of rental properties sooner and reduce rents for those who do continue to rent.\n\nWe can strengthen our financial system and markets.\n\nWhile we have the best financial system in the world, it can always be improved. And of course, our financial system should have good consumer protections to prevent Americans from being tempted to purchase bad products or being misled, as well as strong regulations to protect the country from the failure of financial institutions. Since the great financial crisis (the financial system deserved a lot of the negative attention it received), we\u2019ve made many improvements to regulations. However, as usual in a crisis, we also overreacted.\n\nFundamentally, we need a dynamic regulatory structure that facilitates growth and innovation rather than one that continuously imposes top-down mandates or promotes the constant demonization of corporations and financial services. Shortsighted and misguided policies often sound good politically but usually have unintended consequences that frequently hurt the very people those policies are trying to help. Healthy financial systems are the lifeblood of a healthy economy. You only need to look at many countries around the world to see the damage done to their economy by misguided financial policies and regulations. I\u2019d like to suggest a few ways we can make our regulatory system better for all Americans.\n\nWe need to improve bank regulations. \n\nIt is a completely false narrative that there has been any type of looser regulation on the largest banks since the Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank) was passed. Capital requirements and other regulations have been on a relentless march upward even as banks have become proportionally smaller within the financial system (see chart on page x). All of this makes banking and banking services (loans) not only more expensive but less available; these costs eventually will be passed on to the consumer and businesses and result in a slower-growing economy.\n\n]]>\n    \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWe should do everything we can to drive healthy growth in the economy. By doing so, we create the resources to constantly reinvest in our country, and we create the conditions to promote greater opportunity and well-being for all our citizens. In this section, I describe nine critical policies that I believe are essential to making our economy strong \u2013 putting us in the best position to deal with any issue in front of us, economic or geopolitical, and guaranteeing our ongoing military and economic predominance.\n\nIn compiling this list, I tried to look at the United States as I would any large complex company that we might acquire. (Of course, our country is much more complicated than any one company.) A full assessment of all critical issues allows you to develop a game plan. The issues I\u2019ve highlighted \u2013 and there may be more \u2013 are those that I believe are holding us back and causing much of the \u201cgrievances\u201d I wrote about in the first section. In all cases, I tried to be practical in my approach, and, in some cases, I offer ideas for potential fixes.\n\nI tried to look at this without regard to how positions might be labeled; i.e., conservative, liberal, progressive, red or blue. Whether my views are right or wrong, it is critical that we start to fix that which is broken.\n\nGovernment as a whole needs to demonstrate to the American public that it is effective, efficient, competent and principled \u2013 as any institution should do \u2013 in developing policies that are conducive to maximizing long-term growth, jobs, competitiveness and fairness \u2013 without micromanaging the economy.\n\nThe government, like all institutions, should continuously prioritize and allocate resources to streamline its operations and reduce red tape to improve service delivery, enhance responsiveness and achieve cost efficiencies. Every department should focus not just on the amount of money spent but on what it expects the outcomes should be, what the outcomes actually are and how it can deliver more at a lower cost.\n\nInstead, we have a broken bureaucracy that fails to fully acknowledge or effectively deal with our biggest problems. Even worse, the power of the government over the years has been used to attack parties, businesses and individuals, particularly those not in favor by the party in power. This needs to stop. It begins by always reminding the American public about the founding principles of the United States of America \u2013 the principles embedded in our Declaration of Independence and the Constitution \u2013 liberty, freedom, individual rights and justice for all.\n\nThe economic machine is extraordinarily complex. We need to focus on proper policies that are conducive to growth. Micromanaging coupled with misguided, ill-informed policies not based on reality and pragmatism often have huge unintended consequences. People frequently twist accurate data with bad logic to kill good policy. Many times, it is easier to throw money at a problem, mostly on the demand side (i.e., spend more money), than to formulate good policy or spend money appropriately to help the supply side. Good supply-side policies, such as those promoting job creation and infrastructure development, are critical to achieving productivity and, therefore, to maximizing long-term growth. While innovation is the cosmological constant always driving growth, sometimes its downside is used to block it. This is a huge mistake. We should foster innovation and then create policies that help those who are negatively affected.\n\nWe need consistent and responsible tax and fiscal policies. \n\nAmerica could benefit from a bipartisan, binding mechanism to achieve fiscal responsibility, similar to a Simpson-Bowles type of commission \u2013 but with real congressional authority. Some countries, such as Sweden, have implemented a fiscal policy framework with specific guidelines. Sweden\u2019s framework establishes a debt-to-GDP ratio of 35% plus or minus 5%. This allows the country to run deficit financing at the same rate as its economic growth and still maintain a debt-to-GDP ratio of 35%. Adhering to this kind of consistent fiscal standard makes it easier to manage the country in general. The United States should eventually establish similar guidelines that would make it easier to run this \u201cship of state\u201d and reduce the uncertainty that results from constant flip-flopping between sometimes radically different fiscal policies.\n\nAdditionally, we should eliminate the debt ceiling. The debt ceiling is essentially a \u201cweapon of mass destruction\u201d that can be misused by politicians who don\u2019t understand the damage it can do. It\u2019s hard to even contemplate the harm that would be done to the trust in America and in our economy if we actually failed to meet our debt obligations.\n\nWe must learn to account for investments differently from the way we account for expenses, particularly in areas such as infrastructure.\n\nThe lack of proper accounting by the U.S. government is astounding and is almost laughable. Unfortunately, the practice drives terrible decision making. For example, in determining the deficit, the government treats investments in infrastructure (roads, hospitals, ports) the same way that it treats expenses. But we should put them in completely different budgetary categories. Good investment spending has long-term productivity benefits that many expenses do not.\n\nThe United States now spends only 0.55% of its GDP on infrastructure. The OECD average is at 0.81%, and China\u2019s is a staggering 5.56%. We need to spend more money on productive infrastructure, not less. Borrowing to invest is fundamentally different from borrowing to consume.\n\nThe government also makes a lot of loans, but it doesn\u2019t have to account for them in the same way that a bank does \u2013 which makes bad lending easy to do. For example, the government continues to extend a significant amount of student loans with improper or no underwriting. When the student loan system was taken over by the government in 2010, loan losses had been reasonable, and loans outstanding were $750 billion. Through the magic of government accounting, the government actually forecasted more than $60 billion in profit from when they took over the program. Thirteen years later, the outstanding debt from student loans has more than doubled to $1.6 trillion, and we estimate that the government has lost, with proper accounting, at least $500 billion. Yet the government continues to make many of these bad loans.\n\nThe stakes are even higher regarding the government\u2019s control of two of the largest financial institutions in the world, Fannie Mae and Freddie Mac, whose combined assets of $7.7 trillion largely represent mortgages these organizations have guaranteed. It is incumbent on our government to properly manage institutions like these to protect U.S. taxpayers from tremendous losses (they lost $265 billion in the great financial crisis) and to shield U.S. and global economies from severe damage.\n\nTo make the U.S. tax system conducive to economic growth and job creation, we should incorporate these overall objectives:\n\n \nBe agnostic to specific industries, setting aside favoritism.  \nOffer a system that is stable with standards consistently applied. \nEnsure that our practices keep the United States competitive with other countries. \nProvide effective incentives for growth and innovation.  \n\nThe 2017 Tax Cuts and Jobs Act (TCJA) took significant steps toward achieving these goals by (1) broadening the tax base, (2) reducing the federal corporate rate to 21% (which is approximately the OECD average) and (3) reforming the international tax rules. The first point is sometimes forgotten: While the reduction of the headline tax rate from 35% to 21% was projected to reduce corporate taxes by $1.4 trillion (over 10 years), the broadening of the base offset $1 trillion of that reduction. Regarding international tax rules, a key part of that reform was the removal of gimmicks that allowed U.S. corporations to indefinitely defer tax rules on their overseas earnings. As a result, our international tax system strikes about the right balance between recognizing the importance to U.S. companies of serving overseas markets while not incentivizing them to move capital, skills and R&D outside the country.\n\nAlthough there is certainly room for improvement, overall, the changes made by the TCJA recognize that reducing and rationalizing taxes on business income are critical to spurring economic growth and producing more \u201cbang for the buck\u201d than cutting taxes on individual income. Importantly, these reforms benefited most Americans. In the first two years after the TCJA went into effect, we saw real median income rise more than in the previous 10 years and the lowest unemployment rate for adults without a high school diploma.\n\nIn the year following enactment, we also saw GDP growth of 3% and a 20% increase in domestic investment for affected firms. Corporate taxes paid have risen to record levels \u2013 not because the tax burden on corporations was increased, but because corporations were more profitable; they were doing more business, hiring more people, making more investments. None of this would have been possible without a competitive corporate tax rate.\n\nOur Internal Revenue Code can be further amended to incentivize growth and ensure a fairer tax system overall. \n\nOn the first point, our tax system should provide effective incentives for growth and innovation to support entrepreneurs and small businesses. Two such examples were in the tax code for decades before Congress recently phased them out: (1) recognizing the importance of capital investments and (2) increasing expenditures for R&D. Both are proven ways of growing the economy and creating jobs.\n\nAs to ensuring a fairer system, there are still numerous provisions for Congress to go after. On the business side, the rules intended to prevent artificial shifting of taxable income outside the United States need strengthening and a number of specific industry tax breaks need eliminating. On the individual side, there are also many tax breaks that primarily benefit a certain segment of the population: the wealthy. These include carried interest, the ability to deduct up to $10,000 of state and local taxes, and too many creative estate tax planning techniques. These tax breaks not only cost revenue but also have the additional stigma of being perceived by the American public as just another example of institutional bias and favoritism toward a special interest group. And consistent with ensuring a fairer system, the U.S. tax code should incorporate the \u201cBuffett Rule\u201d so that high-income earners pay a minimum tax on realized income. Everyone, including the wealthy, would benefit enormously from the increased growth that would follow if we amended our system the right way. I think many people would have fewer objections to paying a slightly higher tax rate if they thought the money was being used wisely to attack America\u2019s biggest problems.\n\nFinally, the tax code plays an important role in helping to raise up those at the bottom of the economic ladder. This includes incentives to ensure an adequate and affordable housing supply, such as the credit provision for building affordable housing. It\u2019s important that any tax credit and social benefit program be properly phased in so that it doesn\u2019t dis-incent work. One way the code could incentivize labor force participation is to expand and reform the Earned Income Tax Credit (EITC). The EITC gives an individual earning $14,000 a year with two children a $5,600 tax credit (and with no children a $350 tax credit). I would almost double this tax credit and remove the child requirement. While this would cost a lot of money, it has many virtues. It would give those with lower income far more money to spend, without government interference, on what they and their families need \u2013 education, food, better housing and more. And much of it would be spent locally, in lower-income neighborhoods. It has the virtue of rewarding work, which would grow the GDP. Jobs not only bring dignity but better social outcomes in terms of less homelessness and crime, improved health outcomes and more household formation, among other benefits. For many people, that first job is just the first rung on the ladder of a career. I have little doubt that this plan would more than pay for itself over time. Many Republicans and Democrats support this program as it helps create the American Dream for many people.\n\nOur education system is in deep need of reform to create skills, jobs and opportunity. \n\nMuch of our education system no longer truly meets our country\u2019s promise that its students graduate with the skills they need to attain a good job. The American Dream itself rests upon our providing, as best as we can, equal opportunity to all our citizens. Education and jobs are still the best way to achieve this. That certainly can\u2019t happen when so many of our schools are not working.\n\nIn a number of our inner-city high schools, under 50% of the students graduate, and those who do often don\u2019t have the skills they need to hold a well-paying job. Increasingly, poverty has become intergenerational.\n\nThe growth of America was always driven by productivity that matched capital investment with skills, which is also the driver of individual incomes. Fortunately, all we need to do is reorient what we do today. No investment is required. It is essentially free; we just need to redirect existing resources (the United States spends almost $1 trillion a year on K-12 education) into better outcomes.\n\nLet\u2019s begin with a refresh of our country\u2019s workforce training system.\n\nEffective workforce training systems that align education, training and the private sector are necessary for securing well-paying jobs. There are many successful examples, but one will suffice. Aviation High School in Long Island City, New York, teaches its students not just the basic high school curriculum but also how to maintain small aircraft; i.e., hydraulic, engine and electrical systems, and other technical skills. Some students travel several hours a day to get to school, and often parents are the driving force behind their child\u2019s enrollment. The school graduates about 450 students annually, many of whom go directly into the aviation field. These young people are currently earning in the range of $80,000 a year (not including overtime) from major U.S. airlines who are in desperate need of these types of skilled workers.\n\nSchools like this are the template we need to follow, modernizing education and workforce development programs to be responsive to current workforce needs. The advent of AI and technological change will require lifelong learning and re-skilling. Career and Technical Education programs and alternative pathways, such as apprenticeships, earn-and-learn programs and work-based learning, also provide effective career entryways.\n\nReforms to credentialed programs could also increase access to careers with a future and reward experience. We know exactly what to do, though systems change is hard. There are millions of jobs available for which training could be done in high school, community college or special programs outside of school. For example, there are training programs lasting 12-24 weeks in coding, advanced manufacturing, cyber, data science, program management, and nursing and healthcare-related areas. These trainings should be certified and counted as credits for undergraduate or graduate education. Many unions run excellent apprenticeship and training programs that certify workers for badly needed high skilled jobs like welding, electrical work, plumbing and others. These jobs can pay well in excess of $100,000 a year.\n\nTwo other points: Pell Grants, which are government grants awarded to students to help pay for eligible two-year or four-year colleges, should be available for work credential programs. In addition, the Workforce Innovation and Opportunity Act should be reauthorized to support Second Chance initiatives that give returning felons an opportunity to receive training to re-enter the workforce.\n\nHigher education costs too much and is insufficiently linked to outcomes.\n\nMany people who graduate from college are successful not solely because of their college degree. Their opportunities stem from their socioeconomic circumstances \u2013 how and where they grew up \u2013 which offer them knowledge, confidence, and often internships and relationships within the workplace that give them a leg up. Even with all of that, over 30% of those who obtain college degrees face underemployment; i.e., low-paying jobs. They, too, need skills. You can major in philosophy or history, but a credential of value in coding, data science and analytics, graphic design, financial accounting, digital marketing or engineering can lead to jobs making $80,000+ a year.\n\nSome portion of higher education funding should be linked to outcomes focusing less on graduation and employment rates and more on income levels of graduates.\n\nThe federal student lending system needs to be reformed to help ensure that the borrower\u2019s education is leading to a good-paying job. This would be better for the student, would reduce future loan losses and would discourage simply driving education costs up.\n\nEarly childhood education is critically important (it\u2019s a long-term investment so start now).\n\nEarly childhood education is a long-term investment so it is important to start now. Universal pre-K and other early childhood programs enhance educational outcomes and increase parent labor-force participation. Almost every study I have seen shows the tremendous return on this investment (some even showing two to four times for every dollar invested) even though it appears as a cost in the early years. Included among the positive outcomes for both the parent and the child are early childhood education and higher levels of income, good health and parental employment.\n\nAll students should receive a basic financial education.\n\nFinancial education should be taught as part of the K-12 education system. Everyone, and in particular our young people, should understand the basics: the need for a rainy day fund, how to look at savings, the value of a checking account (versus payday lending), the value of homeownership, the importance of saving for retirement and other basic principles. Specific financial coaching delivered simultaneously with opening a first bank account would also be very effective.\n\nTeaching health and well-being in grades K-12 would benefit all our citizens.\n\nA basic understanding of health, exercise and nutrition would be a huge benefit for our society. Ninety percent of our nation\u2019s $4.5 trillion in annual healthcare expenditures are for people with chronic conditions (certain cancers, heart disease, diabetes, obesity, musculoskeletal disorders and mental health). Preventive medicine and early interventions to manage these diseases, especially those directly related to behaviors (smoking, drinking, poor exercise and nutrition) can have significant health and economic benefits. One small but meaningful example: Cigarette smoking costs the United States more than $240 billion in healthcare spending. This could be reduced every year if we could prevent young people from starting to smoke and help those who do smoke to quit.\n\nWe must remedy the healthcare system, both to reduce costs and improve outcomes. \n\nAmerica has among the best and worst of healthcare. While we may have the best doctors, hospitals, pharmaceutical industry, medical devices and more, our average outcomes are not good, and our costs are double those of our global competitors (17% of GDP versus 9% in other countries). In addition, 27 million people don\u2019t have insurance, and, as mentioned above, preventable chronic diseases run rampant. Our healthcare system also lacks transparency around costs, pricing and proper incentives since the user never effectively pays the full price. We need to begin reform right away.\n\nA few simple policy changes would go a long way toward improving all of this:\n\n \nHealthcare data should be tabulated in a consistent way across all healthcare organizations and providers. \nAll healthcare data should belong to the individual and, therefore, be transferable (and not used for unauthorized purposes by anyone). \nIncreasing transparency for both the companies and the patients is essential, ensuring clarity about the cost of care. Additionally, patients should understand what their medicines will cost them and be eligible for volume discounts, including rebates. \nHealthcare would be more affordable if the exchanges were national and offered a broader range of insurance options people could buy.  \n\nBetter data and more consistent standards across Medicare, Medicaid and commercial markets are needed, with transparency and elimination of fraud and waste being key to stabilizing markets and portability being important for empowering patients.\n\nEngaging employees by prioritizing health education and literacy can help make them informed consumers of healthcare and wellness. Addressing the significant problem of medical bankruptcy in the United States is crucial, and medical bills should not be calculated as part of credit scores.\n\nOne day, individuals should be responsible for purchasing their own healthcare. Healthcare should not be an annual purchase \u2013 you should be able to make a long-term buy, which means you would be the beneficiary of taking care of your own health.\n\nOne final point. Over the last 100 years, the health of our citizens and our workforce has played a significant role in increasing productivity for American workers. Some studies show that over the last 25-30 years, this may have accounted for as much as 45% of productivity growth over time. Healthier workers and the participation of older workers (due to their accumulated knowledge and wisdom) are the main reasons.\n\nWe can improve effective regulations while reducing crippling rules, demoralization, and arbitrary and expensive litigation. \n\nI don\u2019t even know where to begin! How did the can-do, commonsense practical America end up here? Clearly, something is broken. We have gotten to the point where we barely talk about improving our regulations. We only talk about adding more \u2013 contributing to endless, mind-numbing and demoralizing bureaucracy. Studies show that the cost of our regulations (which do have some productive outcomes) is over $3 trillion annually. J.P. Morgan Global Research estimates that relative to the United States, more restrictive regulation reduces long-term growth in the five largest European Union economies by 0.8% per year, and in China by 2.4% per year. These regulations are at the federal, state and local levels, and they affect every industry and business, small and large. They range from permitting and licensing to employment rules and tax compliance (and much more). Each of these rules could easily be fixed. Take permitting, for example. Various regulators, state and federal, should be forced to approve projects sequentially. Some countries (Singapore and Canada) have rules to reduce permitting timelines substantially to two years or fewer (ours can take over 10 years). Regulations shouldn\u2019t be like concrete (immovable) \u2013 they should be constantly improved. U.S. law already requires major rules and regulations to have a cost-benefit analysis done \u2013 this needs to be fully enforced. There are hundreds of rules to fix. Often these regulations are targeted at the financial and technology sectors, whose industries help drive our dynamic economy.\n\nThe cost of our tort system is over $500 billion a year, a little more than 2% of our GDP. While the tort system plays an important role in compensating victims and deterring irresponsible behavior, our system is capricious and arbitrary. Since the loser never pays, there is a great incentive for someone to sue and for the person being sued to settle. Much of the compensation never even gets to the victims. These costs are two-and-a-half times the average level of eurozone countries. One example of a major improvement would be Florida\u2019s recent reforms, which seem to have both reduced the excessive cost of torts to the system while giving people better odds of proper recompense.\n\nThese excessive regulatory and litigation costs result in higher costs across the whole economy, including infrastructure, utilities, education and other essentials. Proper federal, state and local regulations, along with permitting reform, are necessary to reduce delays and litigation. Minimizing red tape would make it easier, cheaper and faster to build infrastructure such as roads, schools, bridges, energy facilities and homes. A little common sense would go a long way.\n\nOne last point: Excessive regulations make it much harder to start a new business, and they often reduce competition. And they almost always hurt smaller companies more than larger ones.\n\nWe could do a better job supporting small businesses.\n\nSmall businesses power job growth in America \u2013 they account for two-thirds of new jobs and employ nearly half of the American workforce. Our entrepreneurial ecosystem has been the envy of the world for generations, and it is essential to create a policy environment that facilitates small business creation, growth and continuity.\n\nBusiness starts have been above-trend for several years, but the failure rate remains high \u2013 50% fail in the first five years. Public-private partnerships can help fill the capital gap in the white space between venture funding and bank lending.\n\nSmall business owners in low-to-moderate income areas face more headwinds than those in wealthier communities, so tax benefits and community education programs play an important role in helping communities lift themselves up through commerce. While banks will remain a critical supporter of small business in their growth phase, the Small Business Administration\u2019s role is crucial and agency modernization must remain a priority, including reforms to the Small Business Investment Company program and the National Technical Assistance program.\n\nFinding qualified talent is the #1 challenge facing small businesses owners, and nearly 40% of them have job openings that they can\u2019t fill. Public partnerships with trade schools and community colleges can increase the supply of skilled labor. As mentioned in the education section, there are many ways to increase the supply of skilled labor.\n\nInnovative healthcare legislation can reduce healthcare costs and help small businesses compete with larger employers for talent.\n\nJust like for larger businesses, there is a need for predictability in tax policies, litigation processes and the EITC \u2013 over 15% of small business owners cite these issues as their most pressing problems. Many small businesses face a heavier burden from state and local regulations than from federal ones so seeking best practices from multiple jurisdictions to streamline requirements can support business operations and growth.\n\nFinally, we must prepare for the coming \u201csilver tsunami\u201d in small business \u2013 75% of business owners would like to exit their business in the next decade, representing trillions of dollars in business wealth at stake. There will be substantial turnover in small businesses in the next decade, and we must prepare the next generation with the skills and passion to take the baton. Local communities can help protect their tax and employment base by investing in succession and transition education programs.\n\nWe should have permanent plans to consistently drive the building of great infrastructure.\n\nEvery state, city and municipality should have multi-year infrastructure plans. Improper planning and ineffective execution are rampant, costly and potentially dangerous. Waiting for bridges to be near collapse or airports to be overly crowded is a bad idea. This planning could include manufacturing sites, maritime, grids, housing, pipelines, canals, broadband and highways, to name but a few.\n\nWe can make it easier to build a more affordable housing supply.\n\nTo address the housing supply issue, it is important to increase funding for effective, affordable housing production programs. This can be partially and easily achieved by expanding the already successful Low-Income Housing Tax Credit programs. Additionally, incentivizing investments that increase economic opportunity in disinvested communities is crucial, and making the New Markets Tax Credit program permanent would support this goal.\n\nIn terms of mortgages, reducing unnecessary regulations would decrease homeownership costs. Streamlining loan origination and servicing standards, reducing capital requirements and simplifying securitization rules would reduce the cost of mortgages without making them riskier. These simple reforms could lower the cost of mortgages by 70\u201380 basis points. The costs of unnecessary regulation go beyond price\u2014they impact the availability of credit and who can qualify for a mortgage. The Urban Institute estimates that a reduction like this would increase mortgage originations by 1 million per year and help lower-income households, in particular, buy their first home. This would specifically help individuals buy homes in the $150,000\u2013$300,000 range. Buying a home, still a pillar of the American Dream, is simply the best way for individuals to start building household wealth.\n\nGood and consistent local zoning requirements \u2013 that are executed with a sense of urgency \u2013 are essential in building more affordable housing. Finally, the availability of more housing, particularly lower-income housing (it\u2019s generally more economical to build denser housing than detached housing), would help people move out of rental properties sooner and reduce rents for those who do continue to rent.\n\nWe can strengthen our financial system and markets.\n\nWhile we have the best financial system in the world, it can always be improved. And of course, our financial system should have good consumer protections to prevent Americans from being tempted to purchase bad products or being misled, as well as strong regulations to protect the country from the failure of financial institutions. Since the great financial crisis (the financial system deserved a lot of the negative attention it received), we\u2019ve made many improvements to regulations. However, as usual in a crisis, we also overreacted.\n\nFundamentally, we need a dynamic regulatory structure that facilitates growth and innovation rather than one that continuously imposes top-down mandates or promotes the constant demonization of corporations and financial services. Shortsighted and misguided policies often sound good politically but usually have unintended consequences that frequently hurt the very people those policies are trying to help. Healthy financial systems are the lifeblood of a healthy economy. You only need to look at many countries around the world to see the damage done to their economy by misguided financial policies and regulations. I\u2019d like to suggest a few ways we can make our regulatory system better for all Americans.\n\nWe need to improve bank regulations. \n\nIt is a completely false narrative that there has been any type of looser regulation on the largest banks since the Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank) was passed. Capital requirements and other regulations have been on a relentless march upward even as banks have become proportionally smaller within the financial system (see chart on page x). All of this makes banking and banking services (loans) not only more expensive but less available; these costs eventually will be passed on to the consumer and businesses and result in a slower-growing economy.\n\n]]>\n  \n  \n    The Lack of Integrity with Medicaid Financing and the Need for Reform\n    https://paragoninstitute.org/medicaid/addressing-medicaid-money-laundering-the-lack-of-integrity-with-medicaid-financing-and-the-need-for-reform/\n    readwise:01jr8ehfmkcg882gttpaf8btfa\n    Mon, 07 Apr 2025 15:40:10 +0000\n    Paragon Health Institute\n    \nParagon Health Institute\n\n\n\nWhat This Paper Covers\n\nIt is rare for taxpayers to lobby the government to take their money, but it is a common feature of the Medicaid program today. In what is best described as legalized \u201cmoney laundering,\u201d health care providers send money to states through a tax \u201cscam\u201d (former President Biden\u2019s description), states use those funds to grow Medicaid spending using federal matching dollars, and providers (those original taxpayers) benefit from higher payments for services they provide to Medicaid recipients. States support these financing schemes, as they enable them to obtain federal funds without any actual state contribution\u2014and they repurpose these funds for additional Medicaid spending, other state spending, or tax cuts.\n\nThough Medicaid was intended to provide health care for the truly needy, the federal government provides an open-ended federal reimbursement of real state expenditures but also artificial state expenditures. As a result, states, insurers, and providers have used Medicaid to siphon hundreds of billions of dollars from federal taxpayers over the past decade and raise payments well above what can be considered \u201ceconomical or efficient,\u201d as federal law requires.\n\nThis paper reveals how this money laundering dilutes the purpose of Medicaid, raises health care costs for those with commercial insurance, and escalates the financial burden on federal taxpayers. As Congress debates Medicaid reform, we provide policymakers with a menu of options to refocus Medicaid on efficient health care and improved patient outcomes, enhance program integrity, and rebalance the state and federal share of costs.\n\nWhat We Found and Why It Matters\n\nOver the past 15 years, no area of federal spending has grown in percentage terms faster than Medicaid. With the proliferation of Medicaid money laundering tactics, there has been a substantial shift in costs from the states to the federal government over this period. For decades, government watchdogs\u2014particularly the Government Accountability Office\u2014have raised serious concerns about a lack of transparency and inappropriate cost shifting to the federal government that result from these money laundering tactics. Not only have these warnings been ignored by Congress, but a series of legislative and executive actions have made the problem worse.\n\nThe enhanced federal reimbursement rate for the expansion population under the Affordable Care Act (ACA) amplifies money laundering. Under the ACA\u2019s 90 percent federal reimbursement percentage, $100 of financing gimmicks yields $900 in federal funds for the state. Under the average state\u2019s 60 percent federal reimbursement for traditional Medicaid recipients, $100 of financing gimmicks yields $150 in federal funds for the state. Money laundering for spending on the expansion population thus has a rate of return six times higher for the average state\u2014and more so for wealthier states that receive lower federal reimbursements for traditional recipients.\n\nThus, states have large incentives to develop money laundering schemes in conjunction with payment policies to shift more expenditures to the expansion category, including by neglecting proper eligibility reviews prior to enrolling people under the ACA expansion. Accounting for the growth in state money laundering and the enhanced federal reimbursement for the ACA expansion, the federal share of Medicaid has increased from about 60 percent in fiscal year (FY) 1991 to about 75 percent in FY2023.\n\nThese financing schemes have been around since the mid-1980s. They started with provider taxes or donation programs, primarily through hospitals and nursing homes. States collect funds from providers, then return those funds in the form of additional Medicaid spending. These expenditures garner federal matching funds, which are subsequently paid to providers through state directed payments (SDPs) and supplemental payments, with states often keeping a portion of this additional money for other purposes. SDPs are payments that states direct insurers to make to providers.\n\nWhen Congress made those schemes somewhat more difficult in the early 1990s, states turned to intergovernmental transfers (IGTs) to finance the state share of Medicaid. Through an IGT, a local government or government-owned provider transfers money to the state that the state then uses to make much higher Medicaid payments on providers, which are often the very same providers that make the IGT. IGTs raise significant conflict of interest concerns and result in government-owned providers receiving favorable treatment over private providers.\n\nStates have expanded their use of provider taxes and IGTs in recent years. The newest money laundering tactic are taxes on insurance companies that participate in Medicaid managed care. This scheme is particularly nefarious because it always results in additional revenue for the state\u2019s general fund. California has used a recent Medicaid tax on insurers to have the federal government fully fund Medicaid expansion for illegal immigrants and for the state to lift the asset test for Medicaid long-term care so wealthy heirs can fully protect their inheritances, with taxpayers picking up the cost.\n\nThe providers, with schemes often developed by consultants, lobby the states to engage in this legalized money laundering apparatus. Historically, states made additional supplemental payments to providers, and they are still a significant component of Medicaid, particularly through the IGT mechanism. As states have largely transitioned Medicaid from fee-for-service to managed care, states are requiring insurers to make extra payments to providers through SDPs.\n\nThe growth of Medicaid money laundering has shifted a significant portion of the financial responsibility for Medicaid away from the states and to the federal government. In the case of SDP programs, states used these schemes to shift financing costs to the federal government by an additional 14 percentage points.\n\nStates\u2019 reduced financial share means that states are now setting very high Medicaid payment rates for certain providers. In some states, these rates are approaching average commercial rates\u2014rates that are more than 2.5 times above Medicare rates. Linking Medicaid payments to average commercial rates encourages providers and insurers to raise commercial prices, costing hard-working American families in reduced wages as well as higher taxes. Moreover, higher Medicaid rates relative to Medicare rates will produce incentives for providers to favor Medicaid recipients over Medicare recipients and could threaten seniors\u2019 access to care.\n\nSDPs exceeded $110 billion in 2024\u2014more than double the amount from just two years earlier. These are on top of supplemental payments that exceeded $57 billion in 2023. Both provider taxes and SDPs soared in 2024, as provider taxes fuel the legalized money laundering that permits states to substantially increase SDPs. These schemes are projected to show dramatic, increasingly unsustainable growth as more states likely opt to pay commercial-level rates in a welfare program.\n\nFlush with federal funds, states have little at stake as they expand Medicaid. Many hospital systems are making windfall profits through the Medicaid program now because of the growth in supplemental payments and SDPs, as is the case in North Carolina, where the Biden administration approved a state plan to raise hospital Medicaid payments to average commercial rates if they agreed to relieve their bad debt. Universal Health Services saw a windfall profit increase from an expanded SDP program. Other states, such as New York, use these gimmicks to plug large holes in their budgets. Not only do these programs sidestep the truly needy on Medicaid and favor special interests instead, but all this is financed by growing the federal debt, leading to inflation and higher interest rates for all Americans.\n\nWhat We Recommend\n\nConsidering a new Congress and the Trump administration\u2019s intent on cutting waste, fraud, and abuse throughout government, there is a real opportunity for federal policymakers to address and limit Medicaid money laundering. Addressing this issue has been bipartisan in the past. Presidents Bush, Obama, and Trump all pushed to rein in Medicaid financing gimmicks. And in 2011, then-Vice President Biden described Medicaid provider taxes as a \u201cscam\u201d that should be eliminated. Many liberal commentators agreed\u2014even the Washington Post editorial board strongly supported an Obama proposal to reduce states\u2019 ability to use provider taxes.\n\nAmong the menu of options for policymakers to pursue, we recommend the following:\n\n \nBlock grants: The most effective way to promote efficiency and end money laundering is to cap the amount of Medicaid funding states receive from Washington. \nEliminate provider taxes: Congress should ban the use of provider taxes to finance the state share of Medicaid costs. Of all the provider taxes, the most nefarious is the insurer tax, so Congress should prioritize eliminating states\u2019 ability to fund their portions of Medicaid costs with this tax. \nReduce the 6 percent provider tax safe harbor threshold: At a minimum, Congress should adopt the Obama administration\u2019s recommendation to reduce the safe harbor threshold to 3.5 percent. \nEliminate SDPs entirely or, at a minimum, cap them so that the total payment to providers cannot exceed Medicare rates. \n\nAddress the IGT scams by prohibiting states from paying government providers more than private providers for delivering the same services.\n\nMedicaid is a joint federal-state program in which the federal government provides an open-ended reimbursement of state Medicaid expenditures. As a direct result, states get more federal money when they spend more on Medicaid. A commonly held view, albeit a mistaken one, is that states must make real expenditures to claim federal funds. But the federal government permits states to develop financing schemes that generate federal Medicaid matching funds without underlying state expenditures. In other words, states deploy what amounts to legalized money laundering practices to collect more federal funds to support the growing price tag of Medicaid at no real cost to themselves\n\nThese financing schemes are often developed by health care providers, which benefit from these larger Medicaid payments, and the consultants whom the providers (and occasionally the states) hire. In essence, providers and states coordinate to create financing schemes that deliver higher payments, financed largely or entirely by the federal government, to politically powerful providers in the state.\n\nThe implications of state Medicaid maximization schemes include financial inefficiencies and diversion of federal resources away from Medicaid\u2019s core purpose of financing health care and long-term care services for low-income individuals. In many cases, Medicaid payments to providers far surpass the actual cost of services delivered to Medicaid enrollees, with surplus funds being redirected to unrelated projects. According to the Government Accountability Office (GAO), these projects include the construction of new patient facilities or the purchase of non-health-care-related assets.1 The funds can also be directed to non-health-care services to support general state revenue or for states to lower state-level taxes.\n\nGAO found that states have \u201cmaximized federal matching funds by making large payments\u2014significantly above providers\u2019 costs of providing services\u2014to providers that were financing the nonfederal share.\u201d2 In 2013, the House Committee on Oversight and Government Reform issued a bipartisan report of problems within Medicaid, noting:\n\nCMS [the Center for Medicare and Medicaid Services] has struggled historically in protecting Federal tax dollars from being misspent through Medicaid. CMS has been hampered by poor data quality, but the agency has historically failed to often adequately detect and address major problems in state Medicaid programs. A Committee majority staff report from April 2012 detailed several examples of how CMS has failed to protect taxpayer dollars spent through the Medicaid program. Moreover, as GAO has widely reported, states have resorted to creative techniques such as provider taxes and large supplemental payments to draw down additional Federal dollars into their states through the Medicaid program without net State contributions. These techniques undermine the nature of joint Federal-state financial responsibility for the Medicaid program by significantly increasing the Federal share of Medicaid expenditures and further undermining State incentives to run efficient Medicaid programs.3\n\nStates with fee-for-service (FFS) Medicaid programs make these payments\u2014dubbed supplemental payments\u2014directly to health care providers. As states have transitioned their Medicaid programs to managed care, payments funded by state financing gimmicks have increasingly taken the form of so-called state directed payments (SDPs). SDPs are payments that states tell insurers to make to providers through Medicaid.\n\nThe Medicaid money laundering scheme is illustrated in Figure 1.\n\n\nAddressing Medicaid Money Laundering Fig1\n\nThe entire financing structure is akin to money laundering and puts federal taxpayers at significant risk while weakening the joint federal-state responsibility underpinning Medicaid. The structure also leads to lower value spending in the program as states make decisions designed to pass most of the cost, if not the complete cost, to federal taxpayers. Due to a much higher federal reimbursement rate for the Affordable Care Act (ACA) Medicaid able-bodied, working-age expansion enrollees and increasing state financing gimmicks, there has been a large shift in costs for financing the Medicaid program from states to the federal government over the past decade plus.\n Historically, the federal government bore about 57 percent of the costs of the Medicaid program. On paper, that percentage is now 67 percent. But after fully accounting for the financing schemes that result in artificial state expenditures, that percentage is now approaching 75 percent. And as states bear a smaller fraction of the total cost of the program, they are far less sensitive to cost increases and less likely to ensure that expenditures through Medicaid provide requisite benefit to justify the cost.\n\nThe ACA exacerbates money laundering because it allows states to obtain much more federal money per dollar of state expenditures, whether a real or artificial state expenditure. Under the ACA\u2019s 90 percent federal reimbursement percentage, $100 of financing gimmicks yields $900 in federal funds for the state. Under the normal 60 percent federal reimbursement, $100 of financing gimmicks yields $150 in federal funds for the state. Thus, states have incentives to develop money laundering schemes in conjunction with payment policies to transition more expenditures to the expansion category, including by neglecting proper eligibility reviews prior to enrolling people under the expansion.4\n\nThe rise in supplemental payments and SDPs is a natural outgrowth of the money laundering financing mechanism and a feature of Medicaid that states and the politically powerful health care industry within them will aggressively lobby to protect. But, in a time of massively large and rising federal deficits, as well as disappointing program results, serious, reform-minded policymakers should consider changes to the perverse status quo Medicaid funding structure that breeds waste and corruption. The large-scale Medicaid money laundering apparatus would not be a feature of an efficient and effective government. In order for the overall program to improve and provide Americans\u2014both Medicaid enrollees and taxpayers\u2014with greater value, the federal share of Medicaid needs to decline, and politically powerful providers need to receive less in federal Medicaid funding.\n\nHistorically, the federal government bore about 57 percent of the costs of the Medicaid program. On paper, that percentage is now 67 percent. But after fully accounting for the financing schemes that result in artificial state expenditures, that percentage is now approaching 75 percent. And as states bear a smaller fraction of the total cost of the program, they are far less sensitive to cost increases and less likely to ensure that expenditures through Medicaid provide requisite benefit to justify the cost.\n\nThe ACA exacerbates money laundering because it allows states to obtain much more federal money per dollar of state expenditures, whether a real or artificial state expenditure. Under the ACA\u2019s 90 percent federal reimbursement percentage, $100 of financing gimmicks yields $900 in federal funds for the state. Under the normal 60 percent federal reimbursement, $100 of financing gimmicks yields $150 in federal funds for the state. Thus, states have incentives to develop money laundering schemes in conjunction with payment policies to transition more expenditures to the expansion category, including by neglecting proper eligibility reviews prior to enrolling people under the expansion.\n\nThe rise in supplemental payments and SDPs is a natural outgrowth of the money laundering financing mechanism and a feature of Medicaid that states and the politically powerful health care industry within them will aggressively lobby to protect. But, in a time of massively large and rising federal deficits, as well as disappointing program results, serious, reform-minded policymakers should consider changes to the perverse status quo Medicaid funding structure that breeds waste and corruption. The large-scale Medicaid money laundering apparatus would not be a feature of an efficient and effective government. In order for the overall program to improve and provide Americans\u2014both Medicaid enrollees and taxpayers\u2014with greater value, the federal share of Medicaid needs to decline, and politically powerful providers need to receive less in federal Medicaid funding.\n\nThe most common Medicaid financing schemes are provider taxes and IGTs. By leveraging the provider tax and IGT mechanisms, states can substantially boost federal reimbursements above the levels established by the federal medical assistance percentage (FMAP), which is commonly viewed to represent the federal share of a state\u2019s Medicaid expenditures.5\n\nProvider taxes are state assessments on providers, which are typically accompanied by increased Medicaid payments to those same providers. States use the revenue from provider taxes to claim additional federal reimbursement. They then return the providers\u2019 assessments plus some additional amounts to those providers through Medicaid payments. There is a complicated set of federal rules that govern provider taxes (more on these below). Serious questions have arisen about the transparency of the money flow and the appropriateness\u2014and occasionally the legality\u2014of these provider tax arrangements.\n\nState politicians recognize the political benefits inherent to this money laundering scheme. Oregon State Representative Mitch Greenlick has referred to provider taxes as a \u201cdream tax\u201d for states: \u201cWe collect the tax from the hospitals, we put it up as a match for federal money, and then we give it back to the hospitals.\u201d6\n\nDespite the name, provider taxes are not really taxes. Entities normally avoid taxes and seek to minimize their tax burdens. Such is not the case with the entities subject to provider taxes. They often help develop the tax schemes and then lobby the government to assess them. In many cases, they lobby the government to increase existing ones. GAO found that hospital associations and nursing home associations have worked with states to design the tax structures. The associations\u2019 officials indicated that without the tax revenue, states would likely reduce Medicaid payments and that states typically provide assurances that tax revenue will be used for Medicaid payments that will make the providers better off financially.7\n\nStates have political incentives to finance substantial portions of their Medicaid programs with accounting gimmicks, because these permit them to reduce the actual amount financed from the state\u2019s tax base. Provider taxes have significantly expanded over the past few decades, and as Figure 2 demonstrates, they increase overall Medicaid spending by making states less sensitive to the costs of the program.\n\nFigure 2 shows the economics of provider taxes, displaying their impact on the federal government, states, and providers. It assumes a state with a 60 percent FMAP. The following discussion and figure are from Brian Blase\u2019s (the lead author on this paper) 2016 paper on Medicaid provider taxes.\n\n\nAddressing Medicaid Money Laundering Fig2\n\nIn the scenario without a provider tax, a state spends $100 on a provider and receives $60 from the federal government, so the net cost to the state tax base amounts to $40.\n\nThe second scenario shows how a provider tax shifts costs to the federal government, assuming states maintain the same level of spending as in the first scenario. The state taxes the provider $100 and then pays the provider $200. Assuming negligible transaction costs, the provider is essentially as well off as in the scenario without a provider tax. The federal government is worse off because it is now reimbursing the state $120 (60 percent of the $200 expenditure). The state gains $20 through these three transactions (receiving $100 in provider tax revenue and $120 reimbursement through the FMAP less $200 in expenditure to the provider). But the state is actually better off by $60 because it was paying $40, on net, to the provider in the absence of the tax.\n\nProvider taxes shift costs from states to the federal government, but they also raise overall spending by lowering the relative price of Medicaid expenditures to states. Provider taxes make state Medicaid programs cheaper because the revenue raised\u2014even though the revenue is generally illusory\u2014can be used as the state share of spending. Scenario 3 in the figure shows how provider taxes work if the provider tax mechanism generates an additional $50 for the provider. The provider\u2019s net gain is $150, equal to the $250 state payment minus the $100 paid through the provider tax. The federal government reimburses the state $150 (60 percent of $250), and the state\u2019s net payments sum to zero ($100 in provider tax revenue and $150 reimbursement through the FMAP less $250 for the provider payment).\n\nComparing scenario 1 (no provider tax) with scenario 3 (provider tax with higher spending) shows that providers are better off from higher payments and the state is better off because of the higher federal reimbursement. The federal government, however, is worse off because it has to reimburse additional state Medicaid expenditures. Although provider taxes increase the federal share of Medicaid spending relative to the state share, the more that the state\u2019s Medicaid expenditures increase as a result of provider taxes, the greater the burden on both the federal and state tax base. It is worth noting that there are two effects on the state tax base financing burden: The provider tax shifts part of the previous burden to the federal tax base but the state bears its share of the financing burden for the marginal increase in Medicaid spending that results from the provider tax reducing the relative cost of Medicaid to the state.\n\nStates started using provider taxes and provider donations in the mid-1980s. By the early 1990s, most states had provider taxes or provider donation programs in place. The Congressional Research Service (CRS) notes that \u201cprovider taxes were often imposed only on Medicaid providers. These provider tax arrangements were agreed to (and sometimes initiated) by the Medicaid providers because the Medicaid providers could be held harmless from the cost of the tax through increased Medicaid payment rates.\u201d8 In a 2016 paper on provider taxes and how Congress tried to address them, Blase wrote:\n\nIn response to the increased use of provider taxes and related techniques, Congress passed and President Bush signed the Medicaid Voluntary Contribution and Provider-Specific Tax Amendments (MVCPSTA) in 1991. The MVCPSTA outlawed the use of most provider donations and made provider taxes more costly for health care providers who treated few, if any, Medicaid enrollees.\n\nThe MVCPSTA required that provider taxes be uniform (the same tax rate across all providers in a given class) and broad based (the tax would apply to all providers in one of the 19 specified classes of providers subject to the tax, even those who do not provide Medicaid services). The MVCPSTA also attempted to limit the extent to which providers could be held harmless by the tax\u2014providers who receive at least as much money back from the state in higher Medicaid payments as they had paid in tax. In addition to being complex, the rules governing provider taxes are also somewhat arbitrary. For example, the secretary of the Department of Health and Human Services (HHS) may waive the broad-based and uniform requirements if the tax is \u201cgenerally redistributive\u201d and the amount of the tax is not directly correlated to Medicaid payments (although there is an exception for rural and sole community providers). States commonly apply for these waivers.\n\nThree tests exist to determine whether a provider tax satisfies the \u201chold harmless\u201d criteria. The key test\u2014the guarantee test\u2014only applies if the tax rate exceeds 6 percent of net patient revenue. The 6 percent threshold is generally referred to as the \u201csafe harbor\u201d provision [2 C.F.R. 433.68(f)(3)(i)(A)]. While states can have provider tax rates that exceed the safe harbor threshold, neither the CRS nor GAO have identified any state that imposes a tax rate exceeding 6 percent of net patient service revenue.9\n\nThe rules put in place by the 1991 legislation succeeded in reducing states\u2019 use of provider taxes for a time. But in 2008, there was a sharp increase in provider taxes as many states faced much lower state revenue because of the financial crisis and deep recession. The number of states with any provider tax rose from 40 to 49 between 2007 and 2015, with 21 states adding hospital taxes and 14 states adding nursing home taxes during this period.10 Moreover, many states with existing provider taxes increased the size of them during this period.\n\nFigure 3 demonstrates the increase in provider taxes after state fiscal year (SFY) 2004 and shows the number of states with any provider tax, an inpatient hospital tax, an intermediate care facility tax, and a nursing home tax. Use of provider taxes exploded over the past two decades. According to CRS, 39 states had three or more provider taxes in SFY 2024, and 42 states are estimated to have three or more provider taxes in SFY 2025.11\n\n\nAddressing Medicaid Money Laundering Fig3\n\nWhile states must finance at least 40 percent of their share of Medicaid payments from state funds, which can include general funds and state provider tax revenue, up to 60 percent of the state share may be sourced from local government revenue through IGTs or local provider taxes.12 In SFY 2024, states reported that about one-third of the state share of Medicaid came from sources outside of general revenue.13 Older reports suggest that approximately 88 percent of these revenues from outside general revenue come from provider taxes and IGTs.14 In essence, for every $2 of actual state revenue, $1 represents funding collected for money laundering.\n\nDuring the cooling of provider tax use in the 1990s, IGTs were increasingly used to finance the nonfederal or state share of new, often exceptionally high Medicaid supplemental payments made for the benefit of specific publicly owned hospitals, health systems, physician groups, and nursing homes. In a blatant conflict of interest transaction, the local governments, public universities, or medical schools that own these public providers transfer the IGT funds to the state.\n\nThrough a supplemental payment mechanism, the state Medicaid agency pays the public providers a sum equal to the IGT funds and the corresponding federal matching funds. The supplemental payments are added on top of the public provider\u2019s base or regular Medicaid rates, often bringing the total Medicaid rates to amounts paid by Medicare rates or higher. Meanwhile, the nonfederal share of public providers\u2019 underlying base Medicaid rates is often financed using proceeds from provider taxes. One financing scheme compounds another, further undermining the fiscal integrity of Medicaid, rewarding irresponsible payment policy, and artificially increasing the burden on federal taxpayers.\n\nUnder IGT arrangements, federal taxpayers incur the full cost of increased Medicaid payments. Public providers owned or operated by the public entities supplying the IGT funds are the sole beneficiaries of the resulting supplemental payments. For every $1 in IGT funds transferred to the state, the locally or state-owned public providers receive at least $2 and as much as $4 in return, depending on the state\u2019s FMAP, thereby generating a net 100 percent to 400 percent profit from the transaction.\n\nIGT arrangements do not cost the state, as it is just an intermediary in the transaction. To facilitate favorable action and minimize a state\u2019s administrative burden, local entities, universities, or public providers often retain consultants to do the necessary paperwork and modeling to secure federal approval and optimize and implement the supplemental payments.\n\nStates secure a political benefit from the IGT mechanism, with less budget pressure to subsidize politically influential counties, cities, universities, academic physicians, and public providers. Further, because public providers\u2014such as county hospitals and university health systems\u2014are commonly high-volume Medicaid providers, federal and IGT-financed supplemental payments can help mitigate demands for statewide provider rate increases that would require a real contribution from the state treasury.\n\nIn 2003, the Health and Hospital Corporation (HHC) of Marion County, Indiana, devised a creative and highly lucrative IGT scheme that has netted billions of dollars in federal funding well in excess of regular Medicaid rates.15 HHC acquired the bed licenses of numerous skilled nursing facilities (SNFs) throughout the state and leased management back to facility operators or new management companies. For federal payment purposes, this transformed the status of each facility from a privately owned or operated SNF to a non-state-government-owned or operated SNF.\n\nUnder a supplemental payment policy in the Indiana Medicaid state plan (approved by CMS), SNFs technically owned or operated by HHC are reimbursed for Medicaid patients based on the Medicare daily rate, which is substantially higher than the state\u2019s Medicaid rate.16 HHC makes an IGT to the state Medicaid agency to finance the nonfederal share\u2014about 35 percent in Indiana\u2014of the supplemental payments. Federal matching funds cover the other 65 percent of the cost to bring the HHC-affiliated SNF Medicaid payments to the maximum Medicare rate level.\n\nAt no additional cost to the state, HHC, as the city-county owner or operator of record, nets 65 percent of the supplemental payments. HHC was able to use the massive annual windfall to build a new public hospital and medical complex and other local health priorities entirely unrelated to the needs of nursing homes or frail, low-income elderly across Indiana.17 The IGT-financed supplemental payments originally devised for HHC have generated interest from other public hospital systems throughout the country.\n IGTs often result in substantially higher Medicaid payment rates for government-owned facilities. According to a 2001 HHS rule to address this problem with IGTs, \u201cThe federal government matched these higher payment rates to public facilities. Because these facilities are public entities, funds to cover the state share were transferred from those facilities (or the government units that operate them) to the state, thus generating increased federal funding with no net increase in state expenditures.\u201d18\n\nAccording to a 2014 GAO report, New York State used IGTs to transfer additional Medicaid costs to the federal government.19 In SFY 2009, the state decreased regular Medicaid payment rates and increased supplemental payments for inpatient hospital services. IGTs from two local government-owned hospitals helped finance the higher supplemental payments, and as a result, total Medicaid payments for inpatient services to the two hospitals increased by $157 million, and provider payments net of the IGTs increased by $119 million between SFY 2008 and SFY 2009. While no state general funds were used to finance the supplemental payments in SFY 2008 or SFY 2009, the amount of state general funds used for regular Medicaid payments did not change as the federal government picked up the entire cost increase of the scheme.\n\nA 2012 House Oversight and Government Reform Committee investigation found that New York\u2019s state-run developmental centers had become a cash cow for the state, exploiting a deeply flawed Medicaid reimbursement formula to secure excessive federal funds. While private providers offering the same services were reimbursed at significantly lower rates, the state-run centers charged Medicaid over $5,000 per resident per day, generating billions in unjustified payments over a decade. The committee\u2019s report and other analyses highlighted how New York officials were aware of the windfall but failed to correct it, while federal oversight agencies also dragged their feet despite acknowledging the problem.20 The result was an estimated $15 billion in improper federal Medicaid payments before CMS finally took action, negotiating a deal to phase out the excessive payments and bring reimbursement rates closer to actual costs.\n\nTHE LATEST FINANCING SCHEME: MCO TAXES\n\nStates may also impose special taxes on managed care organizations (MCOs). While taxes on MCOs have some similarities with other provider taxes, they are especially ripe for abuse. There are 22 states with MCO taxes for FY2025\u2014a significant increase from the 12 states that had such taxes in FY2018.21 MCO taxes are typically used in addition to existing provider taxes.\n\nA 2016 Obama administration Medicaid managed care rule mandates that state Medicaid capitation rates must compensate MCOs for the cost of state taxes, which guarantees that Medicaid MCOs are held financially harmless from the tax.22 Unlike other types of provider tax schemes, where all of the tax revenues are spent as the state share of federally matched provider rate increases or eligibility expansions, only a portion of MCO tax revenues are necessary to cover the state share of paying Medicaid MCOs back. The bulk of the original tax revenues received from Medicaid MCOs\u2014an amount equal to the federal share of repaying Medicaid MCOs for the tax\u2014remains in the state treasury, available for any use, including the state match for any Medicaid expenditures.\n\nLike provider taxes, MCO taxes are supposed to be broad-based, uniform, and devoid of \u201chold-harmless\u201d provisions.23 In principle, this should mean that states must apply the same rate to all MCOs\u2014including commercial insurers that would not benefit from the higher Medicaid payments these taxes finance. Because a broad-based and uniform MCO tax would create losers, states try to minimize the applicability of these taxes on non-Medicaid providers.\n\nTwo federal policies make MCO taxes politically easier to enact by effectively exempting non-Medicaid insurers that would otherwise always lose under a state tax. First, federal preemption law exempts Medicare Advantage plans from state provider taxes. Second, under current federal rules, states are often able to meet the statistical tests necessary to exempt commercial health insurers from an MCO. States can apply to waive the uniform and broad-based requirements for commercial insurers, thereby eliminating the possibility of losers among insurance companies. When states apply for the waiver, they must prove that their taxes would be \u201cgenerally redistributive,\u201d meaning payments must be reasonably funded by non-Medicaid providers.24\n\nIn concept, this would structurally prohibit any implied hold-harmless arrangements between the state and the MCOs. In practice, as demonstrated by CMS\u2019s 2023 approval of a California MCO tax, these rules are not effective at guarding against corrupt arrangements.25 The agency approved the Golden State\u2019s new financing scheme even though it acknowledged that \u201cthis tax program fails to be \u2018generally redistributive\u2019 in nature.\u201d26 CMS noted in a companion letter that it intended to revise the test outlined in regulations to prevent such obviously non-redistributive financing schemes from receiving approval in the future.27\n\nCalifornia\u2019s MCO tax applies only to a narrow group of companies, chosen likely for political purposes, with between 208,000 and 333,000 annualized enrollees.28 By applying to only a handful of non-Medicaid MCO providers, the tax is not broad-based, nor is it uniform. The state taxes Medicaid MCO providers 104 times the rate set for private providers\u2014$182.50 for Medicaid MCOs per member-month compared to $1.75 for private insurers per member-month.\n\nThe loophole in existing regulations allows California Medicaid MCOs to contribute more than 99 percent of the $8.4 billion total tax revenue in 2025 and then receive this funding back through the federal match.29 This scheme allows the Golden State to collect a projected $19.4 billion over the four-year life of the tax with no commensurate increase in state funding.30 California has used the additional funding to have the federal government fully finance Medicaid for illegal immigrants and to remove the state\u2019s asset test for Medicaid so the wealthiest residents can have taxpayers pay for their long-term care services.31\n\nDespite CMS noting its intent to close this loophole, other states have since replicated the California model. New York, for example, received CMS approval at the end of the Biden administration to leverage this financing gimmick to address its budget shortfall with the new stream of federal revenue.32 One policy institute in New York estimated that the Empire State could raise $4 billion in federal Medicaid funds annually with no increase in revenue from the state using this California-modeled MCO tax.33 CMS also approved an enhanced MCO tax in Michigan before President Biden left office.34 Until the federal government changes the rules, abuse of MCO taxes will continue, because so much revenue is on the line for states, which naturally wish to pass these costs to taxpayers outside their borders.\n\nCERTIFIED PUBLIC EXPENDITURES\u2014ANOTHER GIMMICK\n\nCertified public expenditures (CPEs) are a Medicaid financing gimmick used by states to claim federal reimbursement for services provided. CPEs are expenditures that public entities have incurred and paid for using nonfederal funds. These expenditures must be certified by an authorized official as costs related to providing eligible services. While intended to leverage federal matching funds, this practice frequently serves as a gimmick to inflate costs and prop up inefficient public providers. This kind of spending makes up a very small proportion of the nonfederal share of Medicaid spending. The most recent estimates are that CPEs made up $4 billion, or about 2 percent of all nonfederal Medicaid spending, in SFY 2018.35\n\nEntities that may use CPEs include state and local governments, public hospitals and health care facilities, public school districts (for Medicaid-covered services provided in schools), and public universities and academic medical centers. The self-certification process, however, invites abuse, allowing states to claim overhead, unrelated expenses, or questionable costs as \u201clegitimate,\u201d particularly where oversight is weak. This distorts the Medicaid program\u2019s intent and disadvantages private providers, which must compete without similar windfalls from federal funds.\n\nThe process of claiming CPEs starts with the public entity incurring costs associated with providing Medicaid services. An authorized representative certifies that these costs were paid with nonfederal funds and submits the claim to the state Medicaid agency. The agency then requests federal reimbursement based on the state\u2019s FMAP. Upon approval, federal matching funds flow back to the state. This system incentivizes states to prioritize revenue generation over cost efficiency, undermining Medicaid\u2019s core mission of serving vulnerable populations.\n\nThe complexity of the regulatory requirements and the incentives of states and providers to maximize federal funds presents challenges. Self-certification allows for potential abuse, particularly in states with lax oversight. Funds from CPEs can provide disproportionate advantage to public providers that may be less efficient than private providers. A 2021 HHS OIG audit of Tennessee\u2019s Medicaid CPE claims found that the state had improperly certified hundreds of millions of dollars due to inadequate documentation, demonstrating how self-certification without stringent oversight can lead to abuse.36\n\nA main reason for the various Medicaid money laundering schemes is so states can make larger payments to providers, often through supplemental payments. A Medicaid supplemental payment is a lump sum payment to a health care provider. These payments are made in addition to Medicaid payments for specific health care services that have been rendered. Hospitals are the main recipients of supplemental payments. Excluding payments made under managed care arrangements, supplemental payments represented 53.0 percent of total Medicaid payments to inpatient and outpatient hospitals in FY2023, up from 40.9 percent in FY2011.37\n\nBut hospitals are not the only beneficiaries. Supplemental payments to mental health facilities represented 46.2 percent of total Medicaid payments outside of managed care arrangements in FY2013, up from 45.7 percent in FY2011. Supplemental payments to nursing facilities and intermediate care facilities for individuals with intellectual disabilities outside of managed care arrangements totaled 5.6 percent of total Medicaid payments in FY2023, up from 2.4 percent in FY2011. Supplemental payments to physicians and other practitioners outside of managed care arrangements represented 21.7 percent of total Medicaid payments in FY2023, up from 7.3 percent in FY2011.38 As of FY2023, the total amount of supplemental payments surpassed $57.1 billion.39\n\nThe main types of supplemental payments are upper payment limits, disproportionate share hospital payments, uncompensated care pools, and graduate medical education.\n\n\nAddressing Medicaid Money Laundering Fig4\n\n \nUpper payment limit (UPL) payments are supplemental payments that enable total Medicaid payments up to a certain limit, as displayed in Figure 4. These payments are limited to the estimated aggregate amount that would have been paid to a provider class for the same service under Medicare payment rules. In some instances, CMS uses an UPL of average commercial rates (ACRs) for \u201cqualified practitioners\u201d (physicians, physician assistants, nurse practitioners, and other non-physician professionals affiliated with academic medical centers and medical schools).40 These apply only to FFS payments. By setting the aggregate amount at the provider class, the UPL permits states to deliver excessive payments to some providers in the class. In FY2022, the federal government spent $15.8 billion in UPL payments.41 \nDisproportionate share hospital (DSH) payments are supplemental payments to hospitals treating large numbers of low-income and uninsured patients. DSH allotments, unlike Medicaid funding, are capped. Each state receives an annual DSH allotment. Previous Paragon research highlighted that the DSH program fails to equitably target public resources to safety net hospitals or fairly distribute federal funds across states.42 The main reason for the inequity is that, in response to substantial growth in payments, Congress locked state DSH allocations in place in 1993. This rewarded states that had developed the most profligate DSH programs at that time.43 All states except Tennessee receive Medicaid DSH allotments based on the previous year\u2019s allotment increased by the consumer price index for all urban consumers (CPI-U).44 The ACA reduced DSH payments, even though it expanded federal subsidies in many other ways. Yet Congress has consistently prevented these cuts from taking effect. This type of supplemental payment constituted $14.9 billion in spending in FY2022.45 \nSome state Medicaid agencies operate uncompensated care pools (UCPs) under Section 1115 waivers. The purpose of UCPs is to pay providers for uncompensated care costs. Despite their $10.0 billion contribution to Medicaid spending in FY2022, there has been little oversight of these payments.46 \nFor graduate medical education funding, Medicaid makes payments to teaching hospitals to support the training of medical school graduates. The total funding in FY2022 was $4.9 billion.47 \nDelivery system reform incentive payments (DSRIP) is a less common program that operates under Section 1115 waivers. While the purpose of the program is to \u201cincentivize system reforms\u201d from providers, in practice it is used as another way to steer additional funding to managed care systems.48 This program constituted roughly $200 million in spending in FY2022.49 \n\nThe growth in supplemental payments is driven in part by the large share of federal funds directed toward supplemental payments. Supplemental payments, particularly those financed by IGTs, are often made based on political influence of the provider rather than on efficient delivery of care or an individual facility\u2019s financial need for such funds. Supplemental payments are also not distributed equitably across states or within states. GAO conducted numerous studies on the problems with supplemental payments and uncovered a host of problems, most notably inappropriate funding for providers and a lack of data transparency.50\n\nGAO found that supplemental payments totaled more than $43 billion in FY2011\u2014nearly double the amount from FY2006.51 Figure 5 shows the change in supplemental payments between FY2011 and FY2023. The overall level of supplemental payments, which are outside of managed care arrangements, has risen, while the percentage of Medicaid expenditures through FFS payments has significantly decreased.\n\n\nAddressing Medicaid Money Laundering Fig5\n\nOverall, hospitals receive most supplemental payments. In fact, the hospital inpatient and outpatient services garnered 84 percent of the total supplemental payment spending in 2023, amounting to $47.8 billion. The hospital share of supplemental payment spending has somewhat decreased over time in part due to the increased incidence of supplemental payments being directed toward physicians and other providers.\n\nAs shown in Figure 6, supplemental payment spending rose sharply in recent years, with 33 states seeing increases since FY2019. This increase was more pronounced in some states. For example, supplemental payments more than doubled in Idaho, Maryland, Oregon, Tennessee, Virginia, and Washington state. Virginia had the most growth, with an increase of $2.4 billion in supplemental payments to providers between FY2019 and FY2023, the period that coincided with Virginia adopting Medicaid expansion under the ACA.52\n\n\nAddressing Medicaid Money Laundering Fig6\n\nCONSEQUENCES OF FINANCING SCHEMES: PAYOFFS TO PROVIDERS AND INSURERS THROUGH STATE DIRECTED PAYMENTS\n\nUntil 2016, federal regulations prohibited states from making supplemental payments for services delivered through managed care. This restriction created challenges for states looking to expand managed care in Medicaid, as providers that relied heavily on FFS supplemental payments would face significant revenue losses. As a result, as many as 15 states received Section 1115 waivers to exclude certain services or populations from managed care, allowing them to continue making supplemental payments after transitioning to managed care.53\n\nOther states found a way to increase provider pay by increasing capitation payments to MCOs and requiring the MCOs to direct these extra funds to specific providers. Historically, these payments, known as pass-through payments, were not typically linked to Medicaid services or provider performance.\n\nIn 2016, CMS issued a regulation requiring states to gradually phase out pass-through payments due to concerns that they resembled supplemental payments and did not comply with the requirement for actuarially sound managed care rates.54 CMS allowed for a gradual phase-out, with hospitals given 10 years to adjust and physicians and nursing facilities given five years to adjust.55\n\nBut the 2016 rule also introduced a new option for states to replace pass-through payments with directed payments under specific conditions. The rule, which is likely not well enforced, required that:\n\n \ndirected payments be linked to the delivery and utilization of services under managed care contracts (i.e., distributed equally among designated providers in a given state-defined provider class); \npayments support at least one goal in the state\u2019s managed care quality strategy; and \npayments not be dependent on provider participation in IGT agreements.56 \n\nIn most cases, CMS requires states to obtain annual approval for these directed payment arrangements to ensure compliance. In 2020, CMS eliminated the need for states to obtain prior approval for minimum fee schedules.\n\nMACPAC reviewed SDP approval documents and projected total spending based on the time period specified in each SDP contract window or rating period\u2014that is, the time frame when capitation rates are developed under a managed care contract. This period may be the normal 12-month calendar or fiscal year.57 MACPAC projected SDPs approved as of December 2020 to total approximately $25.7 billion for that contract window.58 For SDPs approved as of February 2023, this figure more than doubled to $69.3 billion for that contract window. In general, SDPs fit into three categories:\n\n \nMinimum or maximum fee schedules: This category sets specific parameters for the base payment rates that MCOs must pay providers for certain services. These fee schedules often require MCOs to pay providers no less than the FFS rate approved in the state Medicaid plan or may be based on Medicare or other state-defined rates. The Medicaid and CHIP Payment and Access Commission (MACPAC) projects that about $16.1 billion would be spent under this type of SDP for payment arrangements approved between February 2023 and August 2024.59 \nUniform rate increases: These arrangements mandate that MCOs pay a uniform dollar amount or percentage increase above the negotiated base payment rates for specified services. Uniform rate increases are the most like supplemental payments in the FFS model. Per MACPAC\u2019s projections, $81.5 billion of uniform rate increase payments were approved between February 2023 and August 2024.60 \nValue-based payments (VBP): This category requires MCOs to implement payment models that incentivize providers based on performance or the achievement of quality and efficiency goals rather than the quantity of services provided. VBPs are the least common type of SDP, with total spending of $3.7 billion projected based on arrangements approved between February 2023 and August 2024.61 \n\nMACPAC projects that an additional $8.9 billion will be spent on payment arrangements that span various combinations of these three categories.62 The commission projects that the sum of all fee schedules, uniform rate increases, and VBP arrangements will reach $110.2 billion per year for SDPs approved between February 2023 and August 2024.63\n\nIn 2024, the Biden administration issued a rule that\u2014while flawed\u2014introduced several significant changes aimed at improving the oversight and transparency of directed payments in Medicaid managed care.64 Prior to 2024, the oversight process for SDPs was relatively lax. CMS had weak standards for documentation, transparency, and evaluation related to SDPs. Moreover, the review process often lacked consistency and did not always require detailed reporting. Additionally, states\u2019 use of separate payment terms allowed states to create SDPs outside of base capitation rates, which raised concerns about undermining the risk-based nature of managed care. Finally, evaluation plans were frequently incomplete, delayed, or inconsistent, making it difficult to assess the impact of directed payments on health care quality and outcomes.65\n\nAlthough the rule has large fiscal costs and Congress should consider repealing it (as suggested by Chris Jacobs in a Paragon report from January 202566), there are some constructive provisions that limit abuse. First, it established more rigorous requirements for directed payment submissions, mandating that states provide information about payment amounts and provider eligibility. The rule further required states to submit provider-level payment information to account for where the directed payment spending is going.\n\nSecond, the rule implemented stricter evaluation standards with baseline information and performance targets. For SDPs exceeding 1.5 percent of total managed care costs, states must now submit evaluation reports every three years.\n\nThird, and most importantly, the rule mandated the elimination of separate payment terms by July 2027, requiring all SDPs to be integrated into base capitation rates. This change has the potential to better ensure that MCOs bear financial risk for SDP spending and align the payment structures with the risk-based principles of managed care instead of essentially guaranteeing insurers\u2019 profits each year. By removing payment mechanisms that operated outside of capitation rates, the rule addressed concerns that such practices undermine financial accountability and disproportionately benefit politically connected providers. Those are valid concerns: In 2024, MACPAC found that 87 percent of uniform rate increase SDPs, which totaled an estimated $70.6 billion, were delivered through separate payment terms and were thus outside of the managed care construct.67\n\nWhile the rule did make some long-overdue reforms of SDPs, it made it explicitly clear that states could make SDPs up to ACRs.68 Such a regulation proves that Medicaid payments can often be excessive and that payments this high are almost prima facie evidence that Medicaid payments violate the statutory requirements to be economical and efficient.\n\nAnother problem with basing Medicaid rates on ACR is an incentive of providers to increase commercial rates. ACRs are determined by calculating the mean payment for a service made by a state\u2019s top commercial insurers.69 This structure incentivizes providers to increase commercial prices to garner higher commercial payments as well as Medicaid payments\u2014raising costs for taxpayers and consumers.\n\nAccording to analysis the RAND Corporation made of 2022 medical claims data, prices for inpatient hospital facility services averaged 254 percent of Medicare rates. Prices for outpatient hospital facility services averaged 279 percent of Medicare rates, and professional physician services averaged 184 percent of Medicare rates.70 Of note, almost all physicians accept Medicare rates as payment in full for providing services to Medicare enrollees, and more than half of hospitals make money on Medicare enrollees despite industry pleas that Medicare rates are well below sustainable amounts.71 The reality is that, due to state financing gimmicks and large supplemental payments, Medicaid payments can often be well above what is necessary or appropriate.\n\nThe fiscal costs of SDPs are substantial, with estimates suggesting that the explicit allowance of SDPs up to ACR in the 2024 CMS rule could raise Medicaid spending by as much as $220 billion over the next decade.72 As shown in Figure 7, among large SDPs that cover inpatient services, outpatient services, and behavioral health (these being some of the most costly services), at least 25 states set their payment levels for SDPs as a percentage of ACRs. The average payment level among these programs was 85 percent of ACR for programs valid in fiscal years 2024 and 2025.73\n\n\n\nGAO highlighted the significant impact of these practices on federal Medicaid spending in a 2023 report that assessed SDPs approved through August 2022.74 States use SDPs to shift their financial responsibility onto federal taxpayers. The effect is more pronounced in states with SDPs exceeding $1 billion. GAO reported that for SDPs, 21 states achieved an effective FMAP of 80 percent or higher\u2014and nine of them were able to achieve an effective FMAP above 90 percent.75\n\nAccording to the 2023 GAO review, Arizona has a Medicaid money laundering scheme that results in SDPs of nearly $1.4 billion financed by $437 million in provider taxes. There is no contribution from the state general fund. The federal government is footing 91 percent of the payments.76 In 2020, Arizona enacted a hospital tax, depositing funds into a \u201cHealth Care Investment Fund.\u201d The state then makes expenditures from this fund, bringing in federal matching funds to finance the SDPs. Arizona hospitals applauded the scheme, with the executive director of the Health System Alliance of Arizona stating, \u201cThe Health Care Investment Act is an innovative solution to address the Medicaid shortfall for hospitals, doctors, dentists and other providers at no cost to the state, while infusing $1.5B into Arizona\u2019s economy.\u201d77 The funds from the first three months of the SDPs, among other factors such as COVID-19 relief funds, contributed to an increase in net operating profits for Arizona\u2019s hospitals by 35 percent between 2019 and 2020.78\n\nTennessee is awaiting CMS approval of a directed payment arrangement that would increase the tax rate on hospitals from 4.9 percent to 6.0 percent, which Barclays projects would increase FY2025 state revenue by $4.3 billion and boost hospitals\u2019 profits by up to $2.7 billion net of provider taxes.79\n\nAs mentioned, it is difficult to track and audit SDPs due to gaps in reporting requirements for provider-level payments. For example, states are required to report only on IGT-funded payments to providers but not on other funding sources.80 According to a March 2014 GAO report, CMS officials \u201ccould not attest to the accuracy of the data reported,\u201d and no action had been taken to withhold federal Medicaid funding from states that were underreporting.81 These deficiencies at both the reporting and analysis levels thwart proper accountability.82\n\nThe total number of SDP agreements increased from 201 in 2020 to 302 in 2024. In 2020, minimum or maximum fee schedules accounted for over half of the arrangements, while uniform rate increases comprised roughly one-third and VBP models represented a smaller share. Since 2020, as Figure 8 shows, uniform rate increases have risen in prominence among SDP programs\u2014overtaking minimum and maximum fee schedules. This shift illustrates states\u2019 preference for a set rate for SDP payments\u2014akin to traditional FFS supplemental payments\u2014over a system where MCOs make decisions about distribution. This could largely be explained by regulatory shifts in CMS that exempted certain fee schedules from federal approval, such as uniform rate increases.83\n\n\nAddressing Medicaid Money Laundering Fig8\n\nThere has been a significant increase in the percentage of SDPs that are uniform rate increases, and as Figure 9 shows, uniform rate increases are by far the largest type of SDP in dollar terms. However, maximum fee schedules are the fastest growing type of SDP in percentage. Maximum or minimum fee schedules represented 15 percent of SDP dollars in 2024, while uniform rate increase SDP declined as the percentage of total SDP dollars for all types from 2020 to 2024 (from 79 percent of all program types in 2020 to 74 percent in 2024).\n\n\nAddressing Medicaid Money Laundering Fig9\n\nSince 2020, hospitals have consistently been the primary recipients of SDPs, with their share growing significantly, primarily through uniform rate increases. Behavioral health and substance abuse providers were also common beneficiaries of SDPs, mainly through minimum or maximum fee schedules.\n\nInitially, state general funds were a significant source of funding for SDPs, accounting for 43 percent of total directed payment arrangements in 2020.84 However, as SDPs expanded, there was a notable increase in the use of provider taxes and IGTs to fund them. Figure 10 shows that by 2024, the share of arrangements funded by provider taxes had grown to 32 percent from 14 percent in 2020, while IGTs financed 32 percent of all arrangements, up from 21 percent in 2020.85 The percentages in Figure 10 do not add to 100 percent, as SDPs can have multiple funding sources.\n\n\nAddressing Medicaid Money Laundering Fig10\n\nThis shift highlights how states leverage these funding mechanisms to maximize federal matching funds. This in turn allows for the expansion of SDPs without additional pressure on state budgets. The increasing reliance on provider taxes and IGTs reflects a strategic effort to sustain and enhance payments to providers using federal dollars. According to recent data, states collected 20 percent more revenue in provider taxes in 2024 than in 2023.86 Not surprisingly, both provider taxes and SDPs soared in 2024, as provider taxes fuel the legalized money laundering that permits states to substantially increase SDPs.\n\nNEVADA\u2019S SDP PROGRAM AND UNIVERSAL HEALTH SERVICES SOARING PROFITS\n\nIn 2024, Nevada implemented a provider tax for all privately owned hospitals operating in the state to finance higher SDPs to those facilities.87 The hospital tax was initially set at 4.4 percent of revenue for inpatient services and 6.0 percent for outpatient services, and it grew to 7.1 percent for inpatient and 6.8 percent for outpatient in SFY 2025.88 The state generates higher payments through MCOs with the money raised through the hospital tax. Nevada also recoups a share of those higher payments because of the 3.5 percent premium tax the state imposes on MCOs.89 The legalized money laundering apparatus enables Nevada to pay rates for acute hospitals and critical access hospitals at 100 percent of the ACR while other classes of facilities are limited to 100 percent of Medicare rates. The state claims, \u201cThese limits were selected \u2026 in a manner that maximizes available federal funding to participating private hospitals.\u201d90\n\nNevada originally estimated that the additional revenue would lead to nearly $1 billion in Medicaid payments to hospitals.91 The SDPs up to ACR are very profitable for Nevada hospitals. One hospital system in particular\u2014Universal Health Services (UHS)\u2014is generating massive and increasing profits through this SDP mechanism, growing from a reported $9 million in SDP revenue, net of provider taxes, in 2023 to $194 million in 2024 and is projected to reach $222 million in 2025.92 Supplemental payments in general made up 9.8 percent of total revenue for UHS and 45.2 percent of earnings before interest, taxes, depreciation, and amortization (EBITDA).93\n\nNEW MEXICO\u2019S SDP PROGRAM AND ARDENT HEALTH PARTNERS\n\nIn New Mexico, the state estimated that an SDP program approved retroactively for the second half of 2024 would generate \u201c$1.3 billion in federal funds for hospitals in the state\u201d by leveraging provider taxes.94 The program provides a uniform dollar increase for inpatient and outpatient hospital services and extra payments for hospitals that meet certain quality metrics. The SDP estimates payment for inpatient services at 95.0 percent of ACR and outpatient services at 92.7 percent of ACR.95\n\nAs a result of these high payment rates, hospital operator Ardent Health Partners wrote that it \u201crecorded revenue of $94 million and Adjusted EBITDA of $65 million in the fourth quarter \u2026 [which] resulted in 2024 revenue and Adjusted EBITDA well above our guidance ranges.\u201d96 The information provided by Ardent does not suggest it needed this surge of federal tax dollars brought in through the SDP program. According to Ardent, \u201cNet patient service revenue per adjusted admission for the fourth quarter of 2024 increased 9.5% year-over-year. Excluding the benefit associated with the New Mexico state directed payment program, the increase in net patient service revenue per adjusted admission was approximately 3.4% for the year ended December 31, 2024.\u201d97 Estimates by KeyBanc show that 2024 Medicaid directed payment programs and supplemental payments overall total 51.3 percent of Ardent\u2019s EBITDA.98\n\nNORTH CAROLINA\u2019S CREATIVE MONEY LAUNDERING MECHANISMS TO BENEFIT HOSPITALS\n\nIn 2023, North Carolina passed Medicaid expansion and approved participation in the Healthcare Access and Stabilization Program (HASP). HASP is an SDP in which the state share is funded through assessments on hospitals and other providers. Through this program, North Carolina directs MCOs to increase payments to eligible hospitals for Medicaid-covered services. Acute care hospitals, critical access hospitals, and hospitals owned or controlled by the University of North Carolina Health Care System and East Carolina University Health Medical Center are eligible for the increased payments.99\n\nIn July 2024, CMS approved an amendment to HASP that increased the amount of federal funds that MCOs pay hospitals to ACRs for inpatient and outpatient hospital services if hospitals take specific measures to forgive debt and increase charity care.100\n\nHASP debt relief policies include the following:\n\n \nRelieving all unpaid debt accrued since 2014 by Medicaid enrollees (an amount estimated to be nearly $4 billion).101 \nRelieving all uncollected medical debt for those not enrolled in Medicaid with incomes below 350 percent of the federal poverty level (FPL) and those whose debt exceeds 5 percent of annual income. \nEstablishing protections against the accumulation of future medical debt, including discounts on future bills for people in households below 300 percent FPL and auto-enrollment in North Carolina\u2019s charity care program with presumptive eligibility determined through screening and income validation. \nBlocking certain debt collection practices by prohibiting hospitals from selling debt of individuals at or below 300 percent FPL, capping interest rates on medical debt at 3 percent, and prohibiting medical debt reporting to credit agencies. \n\nTable 1 presents data for the hospital systems set to benefit from these HASP payments for SFY 2024 and SFY 2025.102 Over the next two years, HASP is projected to spend over $10 billion in federal funds. Of this, $4 billion will be tied to increasing rates to ACRs via the debt relief provision.\n\n\nAddressing Medicaid Money Laundering Tbl1\n\nTable 1 highlights, by system, the total costs of debt and charity care compared to the value of HASP. Most hospital systems receive much higher payments from HASP compared to the current costs of bad debt in their systems, and this is despite the fact that most of the debt would have been either forgiven or donated to Undue Medical Debt\u2014a nonprofit that purchases and cancels medical debts for low-income patients. Additionally, the HASP payments do not correlate with the amount of charity care at the hospital.\n\nThe biggest recipient of HASP is Atrium Health, one of the two hospital systems that had previously refused to sell any of its bad debt.103 Using data from the National Academy for State Health Policy, we project base HASP payments to Atrium to be $890.2 million in 2024 and $892.5 million in 2025. The debt relief amendment to HASP is projected to increase these payments by $236.7 million in 2024 and $823.8 million in 2025. In total, Atrium Health will receive more than $1.7 billion through HASP in 2025.\n\nAccording to one study, Atrium accounted for 41.9 percent of medical debt lawsuits in North Carolina between January 2017 and 2022.104 Established initially as the Charlotte-Mecklenburg Hospital Authority, Atrium has expanded significantly through mergers with Navicent Health, Wake Forest Baptist Health, and Advocate Aurora Health. The system now controls 67 hospitals and has over $27 billion in annual revenue.\n\nAtrium Health\u2019s legal status is unique due to its municipal origins, providing it with significant advantages. Like most nonprofit hospitals, Atrium is exempt from federal, state, and local taxes. However, it also does not pay property taxes on land not used for health care or charitable purposes, including commercial properties such as a chicken restaurant. Furthermore, Atrium holds the power to acquire real estate through eminent domain, and legislation is being considered that could extend this authority.105\n\nAtrium has also been shielded from antitrust damages. The North Carolina Supreme Court ruled in 2020 that Atrium is immune from state antitrust laws because it is a \u201cquasi-municipal corporation.\u201d106 Consequently, it is not subject to penalties under North Carolina\u2019s Unfair and Deceptive Trade Practices Act. Additionally, the U.S. Fourth Circuit Court of Appeals affirmed in 2021 that Atrium is protected under the federal Local Government Antitrust Act of 1984, reinforcing its immunity from federal antitrust damages.107 These rulings emerged from a U.S. Department of Justice investigation that found that Atrium had imposed illegal contract restrictions on insurers, preventing them from incentivizing patients to use lower-cost health care options. Although Atrium agreed to stop these anti-competitive practices in a 2018 settlement, affected consumers received no compensation due to the hospitals\u2019 legal immunity.108\n\nAdditionally, Atrium has faced criticism for aggressive debt collection practices. It has encouraged over 63,000 patients to enroll in \u201cmedical credit card\u201d plans offered by AccessOne, a private-equity-backed company that charges up to 18 percent interest on medical debt. Reports indicate that nearly half of the patients enrolled were subjected to high-interest plans, with rates as steep as 13 percent, raising concerns about the financial burden on patients already struggling with medical expenses.109\n\nAtrium\u2019s example highlights how hospital systems can leverage political power to receive government funding that often significantly exceeds hospitals\u2019 costs. The perverse incentives inherent with this type of system were known from the start. North Carolina\u2019s treasurer, Dale Folwell, penned a letter asking CMS to reject the state\u2019s HASP application.110 He cited concerns about how the program would encourage hospital consolidation and raise the cost of health care for both private payers and Medicaid. This comes even as the state boasts some of the most expensive medical care in the nation, Folwell noted.\n\nNonetheless, CMS approved North Carolina\u2019s application to implement HASP. Now, the program serves as a prime example of how states and politically powerful medical systems manipulate Medicaid financing rules to raise commercial premiums and taxpayer costs.\n\nSHIFT IN FINANCIAL RESPONSIBILITY FROM STATES TO THE FEDERAL GOVERNMENT\n\nBefore the implementation of the ACA in 2014, the federal government has historically reimbursed 57 percent of the costs of the Medicaid program leading up to the implementation of the ACA in 2014 (as shown in Figure 11 using data from NASBO).111 The exception was during the Great Recession in 2009-2011 when the federal government increased states\u2019 FMAPs as a way to deliver additional money to the states. With the ACA\u2019s significant expansion of the program and higher FMAPs for able-bodied adults brought onto the program through the expansion, the federal share was closer to 67 percent as of 2023.112 Moreover, because much of the state share consists of fake expenditures, the actual federal share of Medicaid spending is now roughly 75 percent of total expenditures in recent years.\n\nA 2020 GAO report found that states relied on provider taxes and local government funds to finance 28 percent of the total nonfederal share of Medicaid payments in SFY 2018\u2014seven percentage points more than in SFY 2008.113 In that report, GAO also estimated that state financing gimmicks raise the actual share of Medicaid paid by the federal government by about five percentage points, although there is wide variation across the states.114 According to the latest data from NASBO, half of all states funded more than 30 percent of the state portions of their shares of Medicaid spending with non-general funds, which are mostly composed of provider tax revenues (Table 2).115\n\n\nAddressing Medicaid Money Laundering Tbl2\n\nFigure 11 demonstrates that states have been increasing their reliance on non-general funds through money laundering schemes to finance Medicaid. From 1991 through 2023, \u201cother\u201d funds increased from 4 percent to 10 percent, while the state general funds decreased from 38 percent to 23 percent. In other words, state sources, mostly consisting of laundered funds, went from about 9 percent of total state funding to more than 30 percent over this period. Thus, states\u2014with growing money laundering and reliance on federal funds\u2014have become much less sensitive to rising Medicaid costs over time. Of note, the other funds lines would be higher and the general funds line lower if NASBO were able to capture full expenditures, but according to CRS, \u201cNASBO acknowledges that its State Expenditure Report does not capture 100% of provider taxes, fees, assessments, and local funds used to finance the state share of Medicaid expenditures.\u201d116 According to NASBO, other state funds exceed general funds in five states: Alabama, Illinois, Louisiana, Oklahoma, and Utah.\n\n\nAddressing Medicaid Money Laundering Fig11\n\nFigure 12 shows the percentage of actual funding that comes from the federal government. It excludes the state money laundered funds. This percentage equates to federal spending divided by the sum of federal funds and state general funds from Figure 11 \u2014 thus omitting provider tax revenues and IGTs. This reveals the true stake that states have in Medicaid costs. By contrast, the purported federal share is merely the ratio of federal funds to all Medicaid spending. Figure 12 shows that the real federal share of spending increased from 60 percent in SFY 1991 to about 74 percent in SFY 2023. From the previous note, the actual federal share would be higher if the \u201cother\u201d funds were fully accounted for.\n\n\nAddressing Medicaid Money Laundering Fig12\n\nFigure 13 illustrates the extent that financing schemes reduce states\u2019 financial responsibility and inflate the federal share specifically for SDPs. The expected federal share is what percentage the federal government should reimburse states under their standard FMAPs. The real federal share is the percentage the federal government contributes toward the SDP, excluding any revenues from local governments and providers that are then recycled back to those governments or providers.\n\nIn the aggregate, states used financing schemes to raise the federal share of SDPs by 14 percentage points.117 This means the reported federal of 68 percent is actually closer to 82 percent when accounting for financing schemes underpinning SDPs. Nebraska, New Jersey, and Texas have inflated the federal share of SDPs the most, raising their federal shares by more than 24 percentage points above the statutory FMAP.\n\nIn 2022, state financing schemes through SDPs alone raised the cost to federal taxpayers by $4.5 billion, which is 20 percent more than they would pay in absence of these schemes (see Table 3).118 Assuming this trend holds for the most recent data on SDP spending, we estimate that the cost federal taxpayers bear through laundering schemes in SDPs is $12.8 billion in 2024 alone\u2014in addition to bearing nearly $62.3 billion based on the purported federal share of the payments at 68 percent.119\n\n\nAddressing Medicaid Money Laundering Fig13\n\nRECOMMENDATIONS FOR REDUCING MEDICAID MONEY LAUNDERING AND STRENGTHENING FISCAL INTEGRITY\n\nFederal action is necessary to curtail Medicaid money laundering schemes that have enabled states to develop kickback arrangements with insurers and providers and manipulate financing mechanisms to maximize federal reimbursements without commensurate state contributions. The financing schemes and payoffs to providers are inextricably linked. States deploy financing gimmicks to draw down excessive federal funds, which they then use to make large payments to providers, with insurers capturing a portion of the loot. These payment schemes not only inflate Medicaid spending but also drive up commercial health care prices.120 In many states, these schemes are just used as general revenue to plug budget holes and for purposes other than Medicaid.121\n\nThe Urgent Need for Reform\n\nFederal spending as a percentage of the U.S. economy, or gross domestic product (GDP), has reached unprecedented levels outside of wartime. A nearly $2 trillion federal deficit and a national debt 23 percent larger than the entire economy threaten future American prosperity and contribute to rising inflation, higher interest rates, and the potential for massive future tax increases.122\n\nOver the past 15 years, no area of federal spending has increased more than Medicaid. Importantly, there has been a significant shift in the burden of financing Medicaid away from states and to the federal government. In both 2008 and 2023, state Medicaid spending represented 0.9 percent of GDP. In contrast, federal spending soared, rising from 1.36 percent of GDP to 2.28 percent of GDP from 2008 to 2023\n\nThe large shift in costs from states to the federal government has eroded the program\u2019s fundamental principle of shared fiscal responsibility between states and the federal government, with the federal share growing by more than 10 percentage points to an effective federal share now approaching 75 percent of total expenditures. It is time for meaningful reforms to restore the appropriate federal-state financing balance, ensure Medicaid serves its intended purpose and its most deserving enrollees, and place the program on a sustainable trajectory.\n\nThe Best Solution: Block Grants\n\nThe most effective way to eliminate Medicaid money laundering and inefficient spending is for the federal government to implement block grants in the program, capping the amount of federal Medicaid funding states receive. If states received fixed Medicaid allotments, these schemes would disappear.\n\nCurrently, states bear only about 25 percent of the marginal cost of Medicaid spending, meaning they can justify expenditures even if up to 75 percent of the spending is wasteful or low value. The incentives are worse for the Affordable Care Act expansion population given the 90 percent federal reimbursement rate. Under a block grant program, states would bear 100 percent of the marginal cost beyond the amount provided by the federal government, creating strong incentives to ensure that Medicaid spending is efficient and truly benefits enrollees. Ideally, a block grant system would provide states with flexibility to meet the needs of enrollees within federal eligibility and coverage rules while naturally preventing states from artificially inflating Medicaid expenditures to draw down additional federal dollars.\n\nShort of Block Grants: Limiting Financing Gimmicks and Supplemental Payments\n\nCongress seems unlikely to transition Medicaid to block grants, but given the program\u2019s problems, it should still take decisive action to curb states\u2019 use of money laundering tactics. To be most effective, Congress should limit the provider taxes that facilitate these financing schemes.\n\nEliminate States\u2019 Ability to Use Provider Taxes to Finance Medicaid Payments\n\nCongress should prohibit states from using provider taxes\u2014including taxes on insurers\u2014as a funding source for the nonfederal share of Medicaid expenditures. There is broad bipartisan agreement that provider taxes are highly problematic.\n\nFor example:\n\n \n\u2022John Holahan of the Urban Institute called states\u2019 use of provider taxes \u201cegregious\u201d and a \u201cnational disgrace.\u201d123 \nDuring the 2011 budget negotiations, then-Vice President Joe Biden referred to provider taxes as a \u201cscam,\u201d stating, \u201cIf we can\u2019t do this\u2014come on!\u201d125 \nPast administrations from both parties\u2014including Presidents Bush, Obama, and Trump\u2014have proposed reforms to restrict provider taxes.126 The Bowles-Simpson Commission recommended their outright elimination.127 \n\nCongress should follow through on this bipartisan consensus and ban states from using provider tax revenue toward the state share of Medicaid expenditures. Extrapolating estimates from the Congressional Budget Office, this reform would reduce federal deficits by nearly $700 billion over a decade.128\n\nAs discussed earlier in this paper, despite their name, provider taxes are not real taxes. In practice, providers pay the state, the state uses those funds to claim federal Medicaid matching dollars, and then the providers receive their money back\u2014often with a windfall of many times their initial \u201ctax\u201d payment through inflated Medicaid reimbursement rates.\n\nStates claim that restricting provider taxes would force them to cut eligibility or provider payments. However, federal policymakers should be skeptical of these claims given the extensive evidence of excessive Medicaid payments that do not comply with the program\u2019s statutory requirement for efficient and economical payments.\n\nCongress should also ensure that providers are not held harmless or financially rewarded for participating in provider tax schemes. By outlawing these arrangements, states would not be able to use any funds from providers as the state share of the Medicaid reimbursement, and they would not be able to give providers any guarantees of how much Medicaid money they would receive through financing schemes. Congress should also prevent providers from engaging in side deals that ensure that all providers are held harmless or financially benefit from the provider tax mechanism.129\n\nReduce the Medicaid Provider Tax Safe Harbor Threshold\n\nShort of eliminating provider taxes, Congress should reduce the safe harbor threshold for hold-harmless arrangements. This would make provider taxes more difficult for states to leverage, as uniform and broad-based provider taxes would mean that providers and the state could not hold providers who serve fewer Medicaid recipients harmless from the tax scam.\n\nGenerally, the federal government prohibits the state from imposing a provider tax that includes hold-harmless arrangements with providers in which the state essentially agrees to pay providers back for the funds that were taxed. This requirement makes it more difficult for states and providers to run the money laundering schemes, because if providers have no guarantee of getting their money back, they will be less supportive of the underlying provider tax. Unfortunately, the safe harbor threshold undercuts this distinction by allowing states to run the schemes so long as the total tax is below 6 percent of a facility\u2019s revenue. Eliminating the safe harbor would close this loophole that states and providers use to engage in money laundering and kickback schemes.\n\nEliminating or lowering this safe harbor threshold would reduce states\u2019 ability to use provider taxes to generate excess federal funds. In his FY2013 budget, President Obama proposed lowering the safe harbor threshold to 3.5 percent of a provider\u2019s revenue. This reform was estimated to reduce federal deficits by about $22 billion over a decade. That reform would now likely generate federal savings of $200 billion over a decade\u2014a sign of the rampant growth in states\u2019 use of provider taxes to finance the nonfederal share.130 According to CRS, 38 states had reported at least one Medicaid provider tax above 5.5 percent of net patient revenue as of July 1, 2024.131\n\nEnd Fiscally Irresponsible Managed Care Practices from the Obama and Biden Administrations\n\nIn 2016, the Obama administration promulgated an expansive Medicaid managed care regulation that significantly raised federal spending. In 2024, the Biden administration doubled down with a rule making it clear that states could create SDPs up to average commercial rates. Eliminating these policies and instituting sensible caps on Medicaid payments through insurers would likely produce substantial federal budget savings over the next 10 years.\n\nEnd State Directed Payments in Medicaid Managed Care\n\nIn its 2016 rule, the Obama administration allowed for SDPs in managed care. These are a form of supplemental payments, primarily for hospitals, with the nonfederal or state share largely financed with provider tax revenues or IGT payments. SDPs are made on top of the payments providers receive through reimbursement policies set by the state-contracted Medicaid MCO. SDPs are also on top of other Medicaid add-on payments, notably DSH payments and graduate medical education payments.\n\nSDPs have become the single most powerful driver of total federal Medicaid spending growth, and, as GAO has observed, \u201cthe process lacks sufficient fiscal guardrails to ensure state directed payments result in provider payment rates that are reasonable and appropriate as is required under CMS guidance. Moreover, these weaknesses are inconsistent with federal internal control standards that require federal agencies to obtain quality and relevant information and use it to conduct oversight and monitor changes over time.\u201d132 These schemes are projected to show dramatic, increasingly unsustainable growth as more states adopt SDPs, extend SDPs to more provider types, and use the option to pay commercial-level rates in a welfare program. Congress should rescind the ability of states to utilize SDPs.\n\nShort of eliminating SDPs, Congress should limit federal reimbursement for Medicaid payments made through insurers to no more than Medicare rates. Congress should not permit states to develop payment schemes in their Medicaid programs that incentivize providers to treat Medicaid recipients over Medicare recipients and dramatically hike federal taxpayer costs. With the advent of SDPs and the financing schemes underpinning them, states are now paying providers up to average commercial rates through Medicaid. Average commercial rates are more than 2.5 times Medicare rates on average for hospital services, and this payment disparity will produce large incentives for providers to prefer Medicaid recipients over Medicare recipients.133\n\nThere is already a UPL for most services in Medicaid fee for service at Medicare rates. The UPL is calculated at the aggregate level across providers in a class. At a minimum, Congress should extend this UPL to all providers in Medicaid fee for service and create a parallel UPL for Medicaid managed care at those levels.134 States could reimburse providers higher rates than Medicare at their discretion and with their own dollars, but they would not receive federal matching funds for these excess payments.\n\nProhibit States from Reimbursing Insurers for Provider Taxes\n\nFor FY2025, 22 states impose taxes on MCOs.135 Under the expansive and costly Medicaid managed care rules adopted by the Obama administration in 2016, states are required to reimburse Medicaid insurers for the cost of state-imposed taxes. About 2.5 percent of Medicaid capitation rates go to reimburse state-contracted insurers for the cost of these taxes.136 States receive federal matching funds (50 percent to 90 percent, depending on the state and associated enrollee) for the cost of repaying Medicaid insurers for the tax.\n\nManaged care taxes are particularly nefarious. First, MCO taxes are assessed on a large tax base and thus can result in far greater amounts of money laundering. Second, MCO tax policy mandates that states reimburse the MCOs for the amount of the tax, meaning that MCOs face no financial risk from the tax. Third, unlike other forms of provider taxes where a state may not retain any residual funds, state taxes on MCOs always substantially increase state revenues that may, in turn, be used for any purpose not limited to Medicaid or health care. The regulation requiring states to reimburse Medicaid insurers for state taxes should be rescinded, and federal funding should be prohibited from covering the cost of insurer taxes.\n\nProhibit Costly Related Party Conflicts of Interest in Medicaid Provider Payments\n\nThe Medicaid program is rife with related party conflicts of interest. This means that providers owned or operated by a state or local government or by the parent company, subsidiary, or partner of a state-contracted insurer receive higher rates, higher supplemental payments or SDPs, a larger market share, or more favorable treatment than their competitors do.\n\nThere is always an inherent conflict of interest when a state owns or operates a hospital or health system and determines its Medicaid payment and operational policies, because the state can directly favor the state-owned provider over private providers, as demonstrated in the New York developmental center example. In the case of local-government-owned providers, all IGT-funded supplemental payments involve a conflict of interest between the governmental entity and its provider. In many states, government-owned providers have structured Medicaid financing arrangements to maximize federal matching funds without a corresponding increase in actual health care services. For example, a county-owned hospital transfers funds to the state, then the state uses those funds to make a Medicaid payment to the facility and claims federal Medicaid dollars on those expenses. Finally, the state returns a portion of the funds back to the hospital. Moreover, when certain providers or institutions receive undue financial advantages due to their affiliations, it creates an uneven playing field that undermines competition and can reduce the quality of care.\n\nIn the case of Medicaid MCOs, the problem is worse and growing more severe. Many insurers already own providers and administrative vendors, and some insurers also own drug products.137\n\nRelated party conflicts of interest distort market dynamics, increase taxpayer costs, harm program integrity, restrict accountability and transparency, and adversely affect choice, access, and quality of care.\n\nTo address these problems, federal policymakers should prohibit states and Medicaid insurers from adopting any payment rates, terms and conditions, or other policies and practices that treat any provider owned or operated by a state or local government or an insurer more favorably than non-related-party providers. Under this policy, states could not provide higher Medicaid payments to a government-owned facility than to a privately owned facility. This policy would prevent overpayments to government providers, a portion of which those providers then transfer back to the state to be used as the state share of Medicaid to claim more federal money.\n\nFor Medicaid insurers, this policy should apply to all providers, vendors, drugs, and other products owned or controlled by the parent company or any subsidiary, joint venture, or other affiliate of the parent.\n\nStop Paying Consultants with Federal Monies\n\nCongress should also address the problem that these state financing gimmicks are often designed by consultants hired by the health care industry. For example, in Michigan, one contract set to last from 2018 to 2023 worth $3.7 million explicitly required the consultant to \u201c[i]dentify federal revenue enhancement opportunities \u2026 where the State is not maximizing potential federal revenues.\u201d138 These consultants are often paid with contingency fees based on a percentage of the net financial gain from the scheme (i.e., based on how much federal money the scheme generates). In 2005, GAO identified 34 states that used Medicaid contingency-fee consultants \u201cto maximize federal reimbursements.\u201d139 Congress should prevent these consultants from being paid on a contingency-fee basis.\n\nGreater Oversight: Reporting and Audits\n\nFederal policymakers should require greater disclosure and oversight of supplemental payments and SDPs. They should require that states submit provider-specific information about Medicaid payments, including supplemental payments and SDPs and states\u2019 sources of funding for the nonfederal share of these payments. They should also require annual independent audits of provider taxes, IGTs, and certified public expenditures to make sure they comply with the law and fine states with schemes out of compliance.\n\nGreater Oversight: Close Integrity Loopholes in Certified Public Expenditures\n\nAny arrangement where states certify the legitimacy of their own expenditures for federal reimbursement, as is the case with CPEs, is ripe for abuse without proper accountability. Though CPEs make up a small proportion of total Medicaid spending, the loopholes they create allow states to inflate Medicaid costs.\n\nCongress should establish a timeline to phase out CPEs, forcing states to fund Medicaid through transparent, accountable budgeting rather than opaque financing tricks. At a minimum, Congress should require states to publicly disclose detailed CPE data, including amounts, certifying entities, and service breakdowns.\n\nOpponents of reforming Medicaid\u2019s opaque and corrupt financing structure argue that providers and states need dollars from these arrangements to sustain their programs. However, as shown above, such claims are likely overblown because of the extent to which states use these schemes to generously pay providers and fund their non-Medicaid priorities. Lawmakers can also consider phase-ins to ease the transition. President Obama\u2019s proposal to lower the provider tax threshold hold from 6 percent to 3.5 percent was phased in over a three-year period and could be a model for policymakers.\n\nCongress created Medicaid to help finance health care services for the most vulnerable\u2014not to serve as a slush fund for states and politically connected providers. These reforms would end or reduce the financing schemes that have ripped off taxpayers and diverted health care funds away from those who need them most. If Congress is unable to implement reforms to meaningfully reduce money laundering in the Medicaid program, then HHS should take aggressive action to protect the Medicaid program for those who most need it and for the hard-working American families that finance the program.\n\n1\u2191  GAO, Medicaid: CMS Needs More Information on States' Financing and Payment Arrangements to Improve Oversight, December 2020, pp. 29-34, https://www.gao.gov/products/gao-21-98; and Daniel L. Hatcher, \"Medicaid Maximization and Diversion: Illusory State Practices That Convert Federal Aid into General State Revenue,\" Seattle University Law Review 39 (2016),  https://scholarworks.law.ubalt.edu/all_fac/1001\n\n2\u2191  GAO, Medicaid Financing: States' Increased Reliance on Funds from Health Care Providers and Local Governments Warrants Improved CMS Data Collection, July 29, 2014,  https://www.gao.gov/products/gao-14-627\n\n3\u2191  U.S. House of Representatives Committee on Oversight and Government Reform, \"Billions of Federal Tax Dollars Misspent on New York's Medicaid Program,\" March 5, 2013,  https://oversight.house.gov/wp-content/uploads/2013/03/Bipartisan-Medicaid-Oversight-Report-Final.pdf\n\n4\u2191  Brian Blase and Rachel Greszler, \"Medicaid's True Improper Payments Double Those Reported by CMS,\" Paragon Health Institute, March 3, 2025,  https://paragoninstitute.org/medicaid/medicaids-true-improper-payments-likely-double-those-reported-by-cms/\n\n6\u2191  Quoted in Peter Wong, \"Oregon House Extends Hospital Tax,\" Portland Tribune, March 11, 2015,  http://portlandtribune.com/pt/9-news/253422-123198-oregon-house-extends-hospital-tax\n\n8\u2191  Alison Mitchell, Medicaid Provider Taxes, Congressional Research Service, updated December 30, 2024,  https://www.congress.gov/crs-product/RS22843\n\n9\u2191  Brian Blase, \"Medicaid Provider Taxes: The Gimmick That Exposes Flaws with Medicaid's Financing,\" Mercatus Center, February 16, 2016, https://www.mercatus.org/research/research-papers/medicaid-provider-taxes-gimmick-exposes-flaws-medicaids-financing. The specified 19 classes of providers are those that provide inpatient hospital services, outpatient hospital services, nursing facility services, services of intermediate care facilities for the mentally retarded, physicians' services, home health care services, outpatient prescription drugs, services of Medicaid managed care organizations, ambulatory surgical centers, dental services, podiatric services, chiropractic services, optometric/optician services, psychological services, therapist services, nursing services, laboratory and x-ray services, emergency ambulance services, and other health care items or services for which the state has enacted a licensing or certification fee. Generally redistributive means that there is a negative relationship between the amount of tax owed by the provider and the percentage of revenue the provider receives from Medicaid. \"The guarantee test is violated if the state or other unit of government imposing the tax provides directly or indirectly for any payment, offset, or waiver that guarantees to hold taxpayers harmless for all or a portion of the tax\" (Mitchell, Medicaid Provider Taxes). Currently, 34 states and the District of Columbia have at least one CMS-approved waiver under Title 42, Section 433.72, of the Code of Federal Regulations for health care-related provider taxes: Arizona, Arkansas, California, Colorado, Florida, Georgia, Hawaii, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maryland, Massachusetts, Minnesota, Mississippi, Missouri, Nevada, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, South Carolina, Tennessee, Utah, Virginia, Washington, West Virginia, Wisconsin.\n\n15\u2191  HHC is jointly governed by Marion County and the City of Indianapolis and operates the county public health department as well as a large public hospital and clinic system serving the Indianapolis area. See Hari Sharma and Lili Xu, \"Use of Intergovernmental Transfers\u2014Based Medicaid Supplemental Payments to Boost Nursing Home Finances\u2014Evidence from Indiana Nursing Homes,\" Medical Care 61, no. 8 (August 1, 2023): 546-553,  https://pmc.ncbi.nlm.nih.gov/articles/PMC10330393/pdf/nihms-1901396.pdf\n\n16\u2191  Indiana Medicaid State Plan Amendment IN-23-0011 details the current supplemental payment methodology approved by CMS at  https://www.medicaid.gov/medicaid/spa/downloads/IN-23-0011.pdf\n\n17\u2191  Tim Evans et al., \"Nursing Home Residents Suffer as County Hospitals Rake in Millions,\" Indianapolis Star, March 11, 2020,  https://www.indystar.com/in-depth/news/investigations/2020/03/11/indiana-nursing-home-patients-suffer-medicaid-money-diverted-hospitals/2517834001/\n\n20\u2191  House Committee on Oversight and Government Reform staff report, \"Billions of Federal Tax Dollars Wasted Annually by New York's Medicaid Program,\" September 2012,  https://oversight.house.gov/wp-content/uploads/2012/09/Developmental-Center-Staff-Report-for-Hearing-9-20-12.pdf\n\n21\u2191  Elizabeth Hinton et al., \"As Pandemic-Era Policies End, Medicaid Programs Focus on Enrollee Access and Reducing Health Disparities Amid Future Uncertainties,\" KFF, October 2024, Table 4, https://www.kff.org/report-section/50-state-medicaid-budget-survey-fy-2024-2025-provider-rates-and-taxes/; KFF, \"States with an MCO Provider Tax in Place,\"  https://www.kff.org/other/state-indicator/states-with-an-mco-provider-tax-in-place/\n\n25\u2191  California's MCO tax was possible only by exploiting the waiver process through the statistical definition of generally redistributive. On its face, it is clear that California's MCO tax structure is not generally redistributive, but the structure was carefully designed to not trigger the statistical test for this feature. This statistical test is outlined as follows: For the proposed tax structure, calculate the slope of the linear regression line between each provider's share of the total tax paid by all taxpayers and the number of taxable units, which is measured in member-months in this case. Repeat these calculations for another scenario where the tax structure is both broad-based and uniform. Calculate the ratio between the slope of the broad-based scenario to the slope of the proposed tax structure. If the ratio is greater than one, CMS must grant the waiver. In California's case, its MCO tax includes just enough large insurance companies to manipulate the regression line of the proposed tax structure and raise the ratio. This allows for the tax to comply with the statistical test for being generally redistributive, despite the obvious features that would suggest otherwise. CMS was legally bound by rule to approve the waiver, though it noted it will make changes to the process accordingly.\n\n26\u2191  Rory Howe, \"California Managed Care Organization Tax Waiver Approval,\" CMS, p. 4,  https://www.dhcs.ca.gov/Documents/CA-MCO-Tax-Waiver.pdf\n\n27\u2191  \"Therefore, CMS intends to develop and propose new regulatory requirements through the notice-and-comment rulemaking process to address this issue\" (Howe, \"California Managed Care Organization Tax Waiver Approval\").\n\n28\u2191  The approval documents listed these constraints as \"2.5 million and 4.0 million member-months.\" California Department of Health Care Services, \"California Request for Waiver for Managed Care Organization Tax,\" June 2023,  https://www.dhcs.ca.gov/services/Documents/CA-MCO-Tax-Request-2023-2026.pdf\n\n29\u2191  Represented as calendar year in the data, as this coincides with the tax year, not the state fiscal year.\n\n30\u2191  The tax expires on December 31, 2026; California Department of Health Care Services, \"Managed Care Organization Provider Tax,\" May 2023,  https://www.dhcs.ca.gov/Documents/LGA/Governors-Budget/DHCS-MCO-Tax-Primer-5-26-23.pdf\n\n31\u2191  Paul Winfree and Brian Blase, \"California's Insurance-Tax Shuffle: How Federal Money Ends Up Paying for Medicaid for Illegal Immigrants,\" Paragon Health Institute, March 12, 2025,  https://paragoninstitute.org/medicaid/californias-insurance-tax-shuffle-how-federal-money-ends-up-paying-for-medicaid-for-illegal-immigrants/\n\n32\u2191  Grace Ashford, \"New York Has a Budget Trick to Try on the Federal Government,\" New York Times, April 5, 2024,  https://www.nytimes.com/2024/04/05/nyregion/medicaid-budget-taxes.html\n\n33\u2191  Michael Kinnucan, \"The Medicaid MCO Tax Strategy,\" Fiscal Policy Institute, March 19, 2024,  https://fiscalpolicy.org/the-medicaid-mco-tax-strategy\n\n34\u2191  Letter to Deputy Commissioner Amir Bassiri, CMS, December 20, 2024, https://www.health.ny.gov/health_care/medicaid/rates/dfrs/docs/2024-12-20_cms_letter.pdf; Susanna Vogel, \"For-Profit Health Systems See Medicaid Supplemental Payment Bump in Q2,\" HealthCare Dive, August 12, 2024,  https://www.healthcaredive.com/news/health-systems-medicaid-supplemental-payments-second-quarter-earnings/723675/\n\n36\u2191 HHS, Office of Inspector General, \"Tennessee Medicaid Claimed Hundreds of Millions of Federal Funds for Certified Public Expenditures That Were Not in Compliance with Federal Requirements,\" October 2021,  https://oig.hhs.gov/documents/audit/7332/A-04-19-04070-Complete%20Report.pdf\n\n37\u2191  Medicaid and CHIP Payment and Access Commission (MACPAC), \"MACStats Archive,\" March 2011-December 2023,  https://www.macpac.gov/publication/macstats-archive/\n\n40\u2191  Medicaid.gov, \"Medicaid Qualified Practitioner Services\u2014Methodologies for Enhanced Payment Made to Physicians and Practitioners Associated with Academic Medical Centers and Safety Net Hospitals and Upper Payment Calculation,\"  https://www.medicaid.gov/medicaid/downloads/upl-instructions-qualified-practitioner-services-replacement-new.pdf\n\n41\u2191  MACPAC, \"Medicaid Base and Supplemental Payments to Hospitals,\" April 2024,  https://www.macpac.gov/wp-content/uploads/2024/05/Medicaid-Base-and-Supplemental-Payments-to-Hospitals.pdf\n\n42\u2191  Brian Blase, \"Punishing Conservative States: Payment Cuts to Hospitals Where Federal Spending Is Already Low,\" Paragon Health Institute, December 2021,  https://paragoninstitute.org/medicaid/punishing-conservative-states/\n\n44\u2191  The ACA directs HHS to \"make aggregate reductions in Medicaid DSH allotments.\" While implementation of this provision has been delayed due to amendments\u2014most recently through the Consolidated Appropriations Act of 2024\u2014Tennessee is the only state not subject to impending reduced DSH allotments, as it has allotments specified in Section 1923(f)(6)(A) of the Social Security Act. Alison Mitchell, Medicaid Disproportionate Share Hospital (DSH) Reductions, Congressional Research Service, May 2024,  https://www.congress.gov/crs-product/IF10422\n\n46\u2191 HHS, Office of Inspector General, Tennessee Medicaid Claimed Hundreds of Millions of Federal Funds; MACPAC, \"Medicaid Base and Supplemental Payments to Hospitals,\" April 2024.\n\n48\u2191  MACPAC, \"Delivery System Reform Incentive Payment Programs,\" April 2020,  https://www.macpac.gov/wp-content/uploads/2018/03/Delivery-System-Reform-Incentive-Payment-Programs.pdf\n\n50\u2191  GAO, Medicaid: More Transparency of and Accountability for Supplemental Payments Are Needed, November 26, 2012, https://www.gao.gov/products/gao-13-48; GAO, Medicaid Financing: Federal Oversight Initiative Is Consistent with Medicaid Payment Principles but Needs Greater Transparency, April 30, 2007,  https://www.gao.gov/assets/a258312.html\n\n53\u2191  MACPAC cites UCP payments and DSRIP payments as methods used by states to get this approval. In SFY 2020, Arizona, California, Florida, Kansas, Massachusetts, New Mexico, Tennessee, and Texas had such arrangements. States that used DSRIP payments specifically to continue making supplemental payments through managed care include California, Kansas, Massachusetts, New Jersey, New Mexico, and Texas. MACPAC, \"Medicaid Base and Supplemental Payments to Hospitals,\" May 2022, https://www.macpac.gov/wp-content/uploads/2022/05/Base-and-supplemental-payments-to-hospitals.pdf; MACPAC, \"Delivery System Reform Incentive Payment Programs.\"\n\n54\u2191 CMS, \"Medicaid and Children's Health Insurance Program (CHIP) Programs; Medicaid Managed Care, CHIP Delivered in Managed Care, and Revisions Related to Third Party Liability,\" 81 Fed. Reg. 27498-27901 (May 6, 2016),  https://www.federalregister.gov/d/2016-09581\n\n55\u2191 CMS, \"Medicaid Program; The Use of New or Increased Pass-Through Payments in Medicaid Managed Care Delivery Systems,\" 82 Fed. Reg. 5415-5429 (Jan. 18, 2017),  https://www.federalregister.gov/d/2017-00916\n\n56\u2191  42 C.F.R. \u00a7 438.6(c); CMS, \"State Directed Payments,\"  https://www.medicaid.gov/medicaid/managed-care/guidance/state-directed-payments/index.html\n\n57\u2191  Not all states have the same start date for their rating periods. Because the rating periods for each state used in MACPAC's analysis might not span a 12-month period, the dollar amounts are annualized for a 12-month window.\n\n58\u2191  MACPAC, \"Directed Payments in Medicaid Managed Care,\" June 2023,  https://www.macpac.gov/wp-content/uploads/2023/06/Directed-Payments-in-Medicaid-Managed-Care.pdf\n\n59\u2191  MACPAC, \"Directed Payments in Medicaid Managed Care,\" October 2024,  https://www.macpac.gov/wp-content/uploads/2024/10/Directed-Payments-in-Medicaid-Managed-Care.pdf\n\n63\u2191  MACStats noted that this value is the annualized value for the most recent rating period. These values were calculated from preprints available between February 2023 and August 2024.\n\n64\u2191 CMS, \"Medicaid and Children's Health Insurance Program (CHIP) Managed Care Access, Finance, and Quality,\" 89 Fed. Reg. 41002 (May 10, 2024),  https://www.federalregister.gov/documents/2024/05/10/2024-08085/medicaid-program-medicaid-and-childrens-health-insurance-program-chip-managed-care-access-finance\n\n66\u2191  Chris Jacobs, \"Beginning to Stem the Red Ink Tide: Health Care Concepts for a Conservative Congress,\" Paragon Health Institute, January 2025,  https://paragoninstitute.org/private-health/beginning-to-stem-the-red-ink-tide-health-care-concepts-for-a-conservative-congress/\n\n67\u2191  Asher Wang and Chris Park, \"Directed Payments in Medicaid Managed Care,\" MACPAC, November 1, 2024, p. 13,  https://www.macpac.gov/wp-content/uploads/2024/10/07_October-Slides_Directed-Payments-in-Medicaid-Managed-Care-Slides.pdf\n\n69\u2191  Paragon Health Institute, \"Average Commercial Rate,\"  https://paragoninstitute.org/glossary/average-commercial-rate/\n\n70\u2191  Christopher M. Whaley et al., \"Prices Paid to Hospitals by Private Health Plans,\" RAND Corporation, December 10, 2024,  https://www.rand.org/pubs/research_reports/RRA1144-2-v2.html\n\n71\u2191  Alex Cottrill et al., \"How Many Physicians Have Opted Out of the Medicare Program?,\" KFF, January 17, 2025, https://www.kff.org/medicare/issue-brief/how-many-physicians-have-opted-out-of-the-medicare-program/; David Kendall and Darbin Wofford, \"Tale of Two Hospitals: Why Some Hospitals Succeed and Others Do Not,\" Third Way, August 15, 2024,  https://www.thirdway.org/report/tale-of-two-hospitals-why-some-hospitals-succeed-and-others-do-not\n\n72\u2191  Committee for a Responsible Federal Budget, \"CMS Finalizes Medicaid Rule Likely to Increase Spending,\" May 22, 2024,  https://www.crfb.org/blogs/cms-finalizes-medicaid-rule-likely-increase-spending\n\n73\u2191  A. Mok, et al., 'GOP Lawmakers Reportedly Target Provider Tax Reform, Posing Material Risk to Hospitals,' Barclays, pp. 3, February 2025. Barclays data only includes SDP programs over $100 million and cover inpatient, outpatient, and behavioral health care services. This means the analysis excludes graduate medical education, minimum fee schedules, and value-based payment programs.\n\n74\u2191  GAO, Medicaid Managed Care: Rapid Spending Growth in State Directed Payments Needs Enhanced Oversight and Transparency, December 2023, pp. 16-17,  https://www.gao.gov/assets/gao-24-106202.pdf\n\n76\u2191  The percent of federal share of directed payments does not include funds from provider taxes and IGTs. GAO, Medicaid Managed Care.\n\n77\u2191  Arizona Hospital and Healthcare Association, \"HB2668 Offers to Bring Arizona's Healthcare Providers Relief for Unreimbursed Costs,\" February 13, 2020,  https://www.azhha.org/hb2668_offers_to_bring_arizona_s_healthcare_providers_relief_for_unreimbursed_costs_february_13_2020\n\n78\u2191  Jami Snyder, \"Report on Uncompensated Hospital Costs and Hospital Profitability,\" Arizona Health Care Cost Containment System, October 2021,  https://www.azahcccs.gov/shared/Downloads/Reporting/2021/2021UncompensatedCareAndHospitalProfitabilityReport.pdf\n\n79\u2191  Andrew Mok, \"Estimating Tennessee Medicaid DPP: CYH and ACHC Stand to Benefit Most,\" Barclays, May 12, 2024.\n\n83\u2191 CMS, \"Medicaid Program; Medicaid and Children's Health Insurance Program (CHIP) Managed Care,\" 85 Fed. Reg. 72754-72844 (Nov. 13, 2020), https://www.federalregister.gov/d/2020-24758; CMS, Medicaid Program; Medicaid and Children's Health Insurance Program (CHIP) Managed Care Access, Finance, and Quality,\" 89 Fed. Reg. 41002-41285 (May 10, 2024),  https://www.federalregister.gov/d/2024-08085/\n\n84\u2191  MACPAC, \"Oversight of Managed Care Directed Payments,\" in Report to Congress on Medicaid and CHIP, June 2022, pp. 31-57,  https://www.macpac.gov/wp-content/uploads/2022/06/MACPAC_June2022-WEB-Full-Booklet_FINAL-508-1.pdf\n\n87\u2191  Stacie Weeks, \"Nevada Hospital Assessment Program Bulletin: Requirements for Nevada Private Hospital Assessment and Payment Program,\" Nevada Department of Health and Human Services, August 2023,  https://dhcfp.nv.gov/uploadedFiles/dhcfpnvgov/content/Providers/PI/Nevada%20Private%20Hospital%20Tax%20and%20Payment%20Program%20Bulletin%2023-001.pdf\n\n88\u2191  Stacie Weeks, \"Nevada Hospital Assessment Program Bulletin: Nevada Private Hospital Assessment State Fiscal Year (SFY) 2025 Rate Levied,\" Nevada Department of Health and Human Services, September 2024,  https://dhcfp.nv.gov/uploadedFiles/dhcfpnvgov/content/Providers/PI/24-001_Provider_Assessment_SFY2025_Rate_ADA.pdf\n\n91\u2191  Tabitha Mueller, \"Expanded Hospital Tax Could Boost Medicaid Rates, Fund Behavioral Health Services,\" Nevada Independent, May 2023,  https://thenevadaindependent.com/article/expanded-hospital-tax-could-boost-medicaid-rates-fund-behavioral-health-services\n\n92\u2191  Universal Health Services, 2024 Form 10-K Annual Report,  https://www.sec.gov/ix?doc=/Archives/edgar/data/352915/000095017025027785/uhs-20241231.htm\n\n93\u2191  Matthew Gillmor and Zach Haggerty, \"Healthcare Services 2025 Outlook: Buckle Up Buttercup, Upgrading ACHC to Overweight,\" KeyBanc Capital Markets, January 6, 2025; and Matthew Gillmor and Zach Haggerty, \"Healthcare Services: Recap of Policy Panel with Paragon Health Institute and Capitol Street at KBCM Healthcare Forum,\" KeyBanc Capital Markets, March 23, 2025.\n\n94\u2191  Office of Governor Michelle Lujan Grisham, \"Governor Signs Landmark Bills to Improve Healthcare Affordability and Access,\" March 1, 2024,  https://www.governor.state.nm.us/2024/03/01/governor-signs-landmark-bills-to-improve-healthcare-affordability-and-access/\n\n95\u2191 CMS, \"Approved State Directed Payment Preprints: New Mexico,\" November 25, 2024,  https://www.medicaid.gov/medicaid/managed-care/downloads/NM_VBP.Fee_IPH.OPH6_New_20240701-20241231.pdf\n\n96\u2191  Ardent Health, \"Ardent Health Reports Fourth Quarter 2024 Results,\" February 26, 2025,  https://ir.ardenthealth.com/news/news-details/2025/Ardent-Health-Reports-Fourth-Quarter-2024-Results/default.aspx\n\n98\u2191  Matthew Gillmor and Zach Haggerty, \"Healthcare Services: Recap of Policy Panel with Paragon Health Institute and Capitol Street at KBCM Healthcare Forum,\" KeyBanc Capital Markets, March 23, 2025.\n\n99\u2191  North Carolina Department of Health and Human Services, \"Hospitals Across North Carolina Receive Payments as Part of Medicaid Expansion Legislation,\" November 27, 2023,  https://www.ncdhhs.gov/news/press-releases/2023/11/27/hospitals-across-north-carolina-receive-payments-part-medicaid-expansion-legislation\n\n100\u2191  North Carolina Department of Health and Human Services, \"CMS Approves North Carolina's Medical Debt Relief Incentive Program,\" July 29, 2024,  https://www.ncdhhs.gov/news/press-releases/2024/07/29/cms-approves-north-carolinas-medical-debt-relief-incentive-program\n\n101\u2191  North Carolina Department of Health and Human Services, \"Hospital Payment Program and Medicaid Debt Relief Initiative Approved for Another Year,\" February 5, 2025,  https://www.ncdhhs.gov/news/press-releases/2025/02/05/hospital-payment-program-and-medical-debt-relief-initiative-approved-another-year\n\n102\u2191  National Academy for State Health Policy, \"Hospital Cost Tool: Hospital-Level Dataset (2011-2023),\"  https://tool.nashp.org/\n\n103\u2191  Michelle Crouch and Charlotte Ledger, \"NC Hospitals Set for Massive Payday After Agreeing to Medical Debt Relief Plan,\" NC Health News, September 13, 2024,  https://www.northcarolinahealthnews.org/2024/09/13/nc-hospitals-massive-payday-agreeing-medical-debt-relief-plan/\n\n104\u2191  Barak Richman et al., \"Hospitals Suing Patients: How Hospitals Use N.C. Courts to Collect Medical Debt,\" Duke University School of Law, 2024,  https://scholarship.law.duke.edu/cgi/viewcontent.cgi?article=6961&context=faculty_scholarship\n\n105\u2191  Michelle Crouch and Charlotte Ledger, \"Atrium Health: A Unit of 'Local Government' Like No Other,\" NC Health News, February 5, 2024,  https://www.northcarolinahealthnews.org/2024/02/05/atrium-health-a-unit-of-local-government-like-no-other/\n\n106\u2191  The opinion can be found at  https://appellate.nccourts.org/opinions/?c=1&pdf=39871\n\n107\u2191  The opinion can be found at  https://www.ca4.uscourts.gov/Opinions/192145.P.pdf\n\n108\u2191  American Hospital Association, \"DOJ, Health System Settle Antitrust Lawsuit over Health Plan Contracts,\" November 15, 2018,  https://www.aha.org/news/headline/2018-11-15-doj-health-system-settle-antitrust-lawsuit-over-health-plan-contracts\n\n110\u2191  North Carolina State Treasurer Dale R. Folwell, letter to CMS Administrator Chiquita Brooks-LaSure, June 30, 2023,  https://www.shpnc.org/media/3232/download?attachment\n\n111\u2191  National Association of State Budget Officers (NASBO), \"State Expenditure Reports,\" 2024,  https://www.nasbo.org/reports-data/state-expenditure-report\n\n115\u2191  NASBO, \"State Expenditure Reports,\" 2024. A CRS report provides some helpful background for how NASBO accounts for provider taxes in Medicaid expenditures. These values are reported in the \"other funds\" category along with other revenue types. This does, however, provide a good approximation for how states use provider taxes to supplement their share of Medicaid costs. Mitchell, Medicaid Provider Taxes.\n\n117\u2191  GAO, Medicaid Managed Care: Rapid Spending Growth. Paragon's calculations use data in Table 4 of the GAO report.\n\n118\u2191  GAO, Medicaid Managed Care: Rapid Spending Growth. GAO collected its data from preprint estimates submitted by states to CMS. GAO noted some discrepancies in the data where values for federal and nonfederal shares may not sum to the total value of the program. GAO noted that it made no effort to correct these discrepancies.\n\n119\u2191  Calculated using the $110.2 billion figure provided by MACPAC, \"Directed Payments in Medicaid Managed Care,\" October 2024, which is already annualized for the most recent rating period from February 2023 to August 2024. Applying a 68 percent FMAP rate (as in Table 3) to the total SDP spending results in $75.1 billion in federal spending. Assuming the model from Table 3 holds, 17.0 percent of the total SDP spending actually comes from IGTs and provider taxes; which equals $18.7 billion. Because these monies are just given back to those same providers who paid the tax, we subtract them from the total SDP program spending. This means $91.5 billion in new money was actually exchanged based on states' real contributions. Applying the 68 percent FMAP rate to this new total the federal government should have only paid $62.3 billion, which is $12.8 billion less than what was actually paid. This means money laundering schemes raised the true FMAP 14 points above the assumed FMAP, raising the actual federal share to 82 percent.\n\n120\u2191 Ann Kempski and Ge Bai, \"North Carolina Medicaid Expansion Puts Employers and Workers at Risk for Higher Hospital Prices,\" Health Affairs Forefront, June 21, 2023,  https://www.healthaffairs.org/content/forefront/north-carolina-medicaid-expansion-puts-employers-and-workers-risk-higher-hospital\n\n122\u2191  Department of the Treasury, \"What Is the National Debt?,\" September 30, 2024,  https://fiscaldata.treasury.gov/americas-finance-guide/national-debt/\n\n123\u2191  American Enterprise Institute, \"Improving Health and Health Care: An Agenda for Reform,\" panel discussion, December 9, 2015, 1:55:00ff.,  https://www.aei.org/events/improving-health-and-health-care-an-agenda-for-reform/\n\n124\u2191  Quoted in Washington Post, \"A Much-Needed Medicaid Reform,\" November 29, 2012,  https://www.washingtonpost.com/opinions/a-much-needed-medicaid-reform/2012/11/29/b091d86e-399f-11e2-a263-f0ebffed2f15_story.html\n\n126\u2191  The Bush administration intended to issue regulations in FY2007 that would have lowered the safe harbor threshold from 6 percent to 3 percent, but Congress intervened to block this regulation. In President Obama's FY2013 budget proposal, he proposed reducing the safe harbor threshold from 6 percent to 3.5 percent. President Trump's FY2019 budget proposed incorporating the Graham-Cassidy-Heller-Johnson bill's efforts to reduce the safe harbor threshold from 6 percent to 4 percent. Trump's subsequent budgets included similar language proposing the reduction of financing gimmicks through provider tax reforms. Kaiser Family Foundation, \"The President's FY 2007 Budget Proposal: Overview and Briefing Charts,\" February 27, 2006, https://www.kff.org/wp-content/uploads/2013/01/7472.pdf; Office of Management and Budget, Budget of the U.S. Government: Fiscal Year 2013, p. 36; Office of Management and Budget, Budget of the U.S. Government: Fiscal Year 2019, p. 52,  https://web.archive.org/web/20180508234822/https://www.whitehouse.gov/wp-content/uploads/2018/02/budget-fy2019.pdf\n\n127\u2191  National Commission on Fiscal Responsibility and Reform, \"The Moment of Truth,\" December 2010,  https://www.ssa.gov/history/reports/ObamaFiscal/TheMomentofTruth12_1_2010.pdf\n\n128\u2191  Congressional Budget Office (CBO), \"Options for Reducing the Deficit: 2025 to 2034: Limit State Taxes on Health Care Providers,\" December 12, 2024, https://www.cbo.gov/budget-options/60897. CBO's estimate of the savings of this reform was $612 billion, but its score was prior to a 20 percent surge in provider tax revenue last year. Thus, CBO would likely estimate this reform to be at least $700 billion.\n\n129\u2191  On February 17, 2023, CMS disclosed its intent to end private agreements between providers that circumvent the federal hold-harmless provision for provider taxes and supplemental payments. Texas and Florida sued CMS and Biden administration officials and were subsequently granted a preliminary injunction from the agency's revised enforcement policy. No real progress has been made on the case. Most recently, a motion for summary judgement was filed on November 26, 2024, but a ruling has yet to be made. Susan Harris, \"Medicaid Update: Texas v. Brooks-LaSure,\" Norton Rose Fulbright, https://www.nortonrosefulbright.com/en-us/knowledge/publications/07d791ea/medicaid-update-texas-v-brooks-lasure; \"State of Texas et al v. Brooks-LaSure et al: Court Dockets,\" Bloomberg Law, https://www.bloomberglaw.com/public/desktop/document/StateofTexasetalvBrooksLaSureetalDocketNo623cv00161EDTexApr052023/1?doc_id=X1Q6OJ3PDRO2 (accessed March 1, 2025).\n\n130\u2191  Author's calculations based on December 2024 CBO estimates to update for growth in provider tax revenue. CBO, Options for Reducing the Deficit: 2025 to 2034, p. 10,  https://www.cbo.gov/system/files/2024-12/60557-budget-options.pdf\n\n131\u2191  Alison Mitchell, Medicaid Provider Taxes, Congressional Research Service, updated December 30, 2024, https://www.congress.gov/crs-product/RS22843; Hinton et al., \"As Pandemic-Era Policies End.\"\n\n134\u2191  There are some services that Medicare does not reimburse and Medicaid does, including dental benefits, home- and community-based services, and care at skilled nursing facilities. CMS, \"Mandatory and Optional Medicaid Benefits,\" https://www.medicaid.gov/medicaid/benefits/mandatory-optional-medicaid-benefits/index.html; CMS, \"Your Medicare Coverage,\"  https://www.medicare.gov/coverage\n\n135\u2191  KFF, \"States with an MCO Provider Tax in Place,\"  https://www.kff.org/other/state-indicator/states-with-an-mco-provider-tax-in-place/\n\n136\u2191  Milliman, \"Medicaid Managed Care Financial Results for 2023,\" July 2024,  https://edge.sitecorecloud.io/millimaninc5660-milliman6442-prod27d5-0001/media/Milliman/PDFs/2024-Articles/7-31-24_Medicaid-managed-care-financial-results-2023.pdf\n\n137\u2191  For example, CVS Health, the parent company of Aetna Medicaid, has a wholly owned subsidiary (Cordavis), which commercializes biosimilar drug products. The first product commercialized by Cordavis is Hyrimoz, a biosimilar for Humira, a treatment for rheumatoid arthritis, Crohn's disease, and other autoimmune diseases. U.S. sales for the Humira brand-name biologic were about $1.2 billion in 2024. UnitedHealth Group operates its Medicaid MCO subsidiaries through the UnitedHealthcare brand, and these MCOs are supported by the company's numerous subsidiaries under the Optum name, such as OptumRx, Optum (for claims, backroom operations, technology, data, and analytics), Optum Behavioral Health, OptumInsight, and OptumHealth. Elevance's Medicaid MCOs, like those operating under the Amerigroup or Blue Cross Blue Shield brands in various states, are supported by affiliated service companies that Elevance owns (e.g., CarelonRx, Carelon Behavioral Health, Carelon Medical Benefits Management). Elevance Health also centralizes other administrative functions through its corporate structure. For example, claims processing and information technology systems for its Medicaid plans are often handled through shared services within the company. Centene's subsidiaries commonly serve as subcontractors, providing administrative support, provider network management, analytics, and benefit administration for its Medicaid health plans. Management of pharmacy, behavioral health care, and other specialty services (including provider networks, claims, and utilization control) are often handled for Centene's Medicaid MCO subsidiaries through Centene subsidiaries such as Envolve Pharmacy Solutions, Envolve Vision, Envolve Dental, and Envolve PeopleCare. Centene Health Care Enterprises shared services group provides Centene's Medicaid MCO subsidiaries with capabilities ranging from data analytics to care management solutions and offers MCOs subcontract functions through Centene acquisitions.\n\n138\u2191  State of Michigan Enterprise Procurement, Change Notice Number 9 to Contract Number MA180000000475, p. 15,  https://www.michigan.gov/dtmb/-/media/Project/Websites/dtmb/Procurement/Contracts/015/180000000475.pdf\n\n139\u2191  GAO, Medicaid: States' Efforts to Maximize Federal Reimbursements Highlight Need for Improved Federal Oversight, June 28, 2005,  https://www.gao.gov/products/gao-05-836t\n\n\nCalifornia\u2019s Insurance-Tax Shuffle: How Federal Money Ends Up Paying for Medicaid for Illegal Immigrants\n\n\nMedicaid Financing Reform: Stopping Discrimination Against the Most Vulnerable and Reducing Bias Favoring Wealthy States]]>\n    \nParagon Health Institute\n\n\n\nWhat This Paper Covers\n\nIt is rare for taxpayers to lobby the government to take their money, but it is a common feature of the Medicaid program today. In what is best described as legalized \u201cmoney laundering,\u201d health care providers send money to states through a tax \u201cscam\u201d (former President Biden\u2019s description), states use those funds to grow Medicaid spending using federal matching dollars, and providers (those original taxpayers) benefit from higher payments for services they provide to Medicaid recipients. States support these financing schemes, as they enable them to obtain federal funds without any actual state contribution\u2014and they repurpose these funds for additional Medicaid spending, other state spending, or tax cuts.\n\nThough Medicaid was intended to provide health care for the truly needy, the federal government provides an open-ended federal reimbursement of real state expenditures but also artificial state expenditures. As a result, states, insurers, and providers have used Medicaid to siphon hundreds of billions of dollars from federal taxpayers over the past decade and raise payments well above what can be considered \u201ceconomical or efficient,\u201d as federal law requires.\n\nThis paper reveals how this money laundering dilutes the purpose of Medicaid, raises health care costs for those with commercial insurance, and escalates the financial burden on federal taxpayers. As Congress debates Medicaid reform, we provide policymakers with a menu of options to refocus Medicaid on efficient health care and improved patient outcomes, enhance program integrity, and rebalance the state and federal share of costs.\n\nWhat We Found and Why It Matters\n\nOver the past 15 years, no area of federal spending has grown in percentage terms faster than Medicaid. With the proliferation of Medicaid money laundering tactics, there has been a substantial shift in costs from the states to the federal government over this period. For decades, government watchdogs\u2014particularly the Government Accountability Office\u2014have raised serious concerns about a lack of transparency and inappropriate cost shifting to the federal government that result from these money laundering tactics. Not only have these warnings been ignored by Congress, but a series of legislative and executive actions have made the problem worse.\n\nThe enhanced federal reimbursement rate for the expansion population under the Affordable Care Act (ACA) amplifies money laundering. Under the ACA\u2019s 90 percent federal reimbursement percentage, $100 of financing gimmicks yields $900 in federal funds for the state. Under the average state\u2019s 60 percent federal reimbursement for traditional Medicaid recipients, $100 of financing gimmicks yields $150 in federal funds for the state. Money laundering for spending on the expansion population thus has a rate of return six times higher for the average state\u2014and more so for wealthier states that receive lower federal reimbursements for traditional recipients.\n\nThus, states have large incentives to develop money laundering schemes in conjunction with payment policies to shift more expenditures to the expansion category, including by neglecting proper eligibility reviews prior to enrolling people under the ACA expansion. Accounting for the growth in state money laundering and the enhanced federal reimbursement for the ACA expansion, the federal share of Medicaid has increased from about 60 percent in fiscal year (FY) 1991 to about 75 percent in FY2023.\n\nThese financing schemes have been around since the mid-1980s. They started with provider taxes or donation programs, primarily through hospitals and nursing homes. States collect funds from providers, then return those funds in the form of additional Medicaid spending. These expenditures garner federal matching funds, which are subsequently paid to providers through state directed payments (SDPs) and supplemental payments, with states often keeping a portion of this additional money for other purposes. SDPs are payments that states direct insurers to make to providers.\n\nWhen Congress made those schemes somewhat more difficult in the early 1990s, states turned to intergovernmental transfers (IGTs) to finance the state share of Medicaid. Through an IGT, a local government or government-owned provider transfers money to the state that the state then uses to make much higher Medicaid payments on providers, which are often the very same providers that make the IGT. IGTs raise significant conflict of interest concerns and result in government-owned providers receiving favorable treatment over private providers.\n\nStates have expanded their use of provider taxes and IGTs in recent years. The newest money laundering tactic are taxes on insurance companies that participate in Medicaid managed care. This scheme is particularly nefarious because it always results in additional revenue for the state\u2019s general fund. California has used a recent Medicaid tax on insurers to have the federal government fully fund Medicaid expansion for illegal immigrants and for the state to lift the asset test for Medicaid long-term care so wealthy heirs can fully protect their inheritances, with taxpayers picking up the cost.\n\nThe providers, with schemes often developed by consultants, lobby the states to engage in this legalized money laundering apparatus. Historically, states made additional supplemental payments to providers, and they are still a significant component of Medicaid, particularly through the IGT mechanism. As states have largely transitioned Medicaid from fee-for-service to managed care, states are requiring insurers to make extra payments to providers through SDPs.\n\nThe growth of Medicaid money laundering has shifted a significant portion of the financial responsibility for Medicaid away from the states and to the federal government. In the case of SDP programs, states used these schemes to shift financing costs to the federal government by an additional 14 percentage points.\n\nStates\u2019 reduced financial share means that states are now setting very high Medicaid payment rates for certain providers. In some states, these rates are approaching average commercial rates\u2014rates that are more than 2.5 times above Medicare rates. Linking Medicaid payments to average commercial rates encourages providers and insurers to raise commercial prices, costing hard-working American families in reduced wages as well as higher taxes. Moreover, higher Medicaid rates relative to Medicare rates will produce incentives for providers to favor Medicaid recipients over Medicare recipients and could threaten seniors\u2019 access to care.\n\nSDPs exceeded $110 billion in 2024\u2014more than double the amount from just two years earlier. These are on top of supplemental payments that exceeded $57 billion in 2023. Both provider taxes and SDPs soared in 2024, as provider taxes fuel the legalized money laundering that permits states to substantially increase SDPs. These schemes are projected to show dramatic, increasingly unsustainable growth as more states likely opt to pay commercial-level rates in a welfare program.\n\nFlush with federal funds, states have little at stake as they expand Medicaid. Many hospital systems are making windfall profits through the Medicaid program now because of the growth in supplemental payments and SDPs, as is the case in North Carolina, where the Biden administration approved a state plan to raise hospital Medicaid payments to average commercial rates if they agreed to relieve their bad debt. Universal Health Services saw a windfall profit increase from an expanded SDP program. Other states, such as New York, use these gimmicks to plug large holes in their budgets. Not only do these programs sidestep the truly needy on Medicaid and favor special interests instead, but all this is financed by growing the federal debt, leading to inflation and higher interest rates for all Americans.\n\nWhat We Recommend\n\nConsidering a new Congress and the Trump administration\u2019s intent on cutting waste, fraud, and abuse throughout government, there is a real opportunity for federal policymakers to address and limit Medicaid money laundering. Addressing this issue has been bipartisan in the past. Presidents Bush, Obama, and Trump all pushed to rein in Medicaid financing gimmicks. And in 2011, then-Vice President Biden described Medicaid provider taxes as a \u201cscam\u201d that should be eliminated. Many liberal commentators agreed\u2014even the Washington Post editorial board strongly supported an Obama proposal to reduce states\u2019 ability to use provider taxes.\n\nAmong the menu of options for policymakers to pursue, we recommend the following:\n\n \nBlock grants: The most effective way to promote efficiency and end money laundering is to cap the amount of Medicaid funding states receive from Washington. \nEliminate provider taxes: Congress should ban the use of provider taxes to finance the state share of Medicaid costs. Of all the provider taxes, the most nefarious is the insurer tax, so Congress should prioritize eliminating states\u2019 ability to fund their portions of Medicaid costs with this tax. \nReduce the 6 percent provider tax safe harbor threshold: At a minimum, Congress should adopt the Obama administration\u2019s recommendation to reduce the safe harbor threshold to 3.5 percent. \nEliminate SDPs entirely or, at a minimum, cap them so that the total payment to providers cannot exceed Medicare rates. \n\nAddress the IGT scams by prohibiting states from paying government providers more than private providers for delivering the same services.\n\nMedicaid is a joint federal-state program in which the federal government provides an open-ended reimbursement of state Medicaid expenditures. As a direct result, states get more federal money when they spend more on Medicaid. A commonly held view, albeit a mistaken one, is that states must make real expenditures to claim federal funds. But the federal government permits states to develop financing schemes that generate federal Medicaid matching funds without underlying state expenditures. In other words, states deploy what amounts to legalized money laundering practices to collect more federal funds to support the growing price tag of Medicaid at no real cost to themselves\n\nThese financing schemes are often developed by health care providers, which benefit from these larger Medicaid payments, and the consultants whom the providers (and occasionally the states) hire. In essence, providers and states coordinate to create financing schemes that deliver higher payments, financed largely or entirely by the federal government, to politically powerful providers in the state.\n\nThe implications of state Medicaid maximization schemes include financial inefficiencies and diversion of federal resources away from Medicaid\u2019s core purpose of financing health care and long-term care services for low-income individuals. In many cases, Medicaid payments to providers far surpass the actual cost of services delivered to Medicaid enrollees, with surplus funds being redirected to unrelated projects. According to the Government Accountability Office (GAO), these projects include the construction of new patient facilities or the purchase of non-health-care-related assets.1 The funds can also be directed to non-health-care services to support general state revenue or for states to lower state-level taxes.\n\nGAO found that states have \u201cmaximized federal matching funds by making large payments\u2014significantly above providers\u2019 costs of providing services\u2014to providers that were financing the nonfederal share.\u201d2 In 2013, the House Committee on Oversight and Government Reform issued a bipartisan report of problems within Medicaid, noting:\n\nCMS [the Center for Medicare and Medicaid Services] has struggled historically in protecting Federal tax dollars from being misspent through Medicaid. CMS has been hampered by poor data quality, but the agency has historically failed to often adequately detect and address major problems in state Medicaid programs. A Committee majority staff report from April 2012 detailed several examples of how CMS has failed to protect taxpayer dollars spent through the Medicaid program. Moreover, as GAO has widely reported, states have resorted to creative techniques such as provider taxes and large supplemental payments to draw down additional Federal dollars into their states through the Medicaid program without net State contributions. These techniques undermine the nature of joint Federal-state financial responsibility for the Medicaid program by significantly increasing the Federal share of Medicaid expenditures and further undermining State incentives to run efficient Medicaid programs.3\n\nStates with fee-for-service (FFS) Medicaid programs make these payments\u2014dubbed supplemental payments\u2014directly to health care providers. As states have transitioned their Medicaid programs to managed care, payments funded by state financing gimmicks have increasingly taken the form of so-called state directed payments (SDPs). SDPs are payments that states tell insurers to make to providers through Medicaid.\n\nThe Medicaid money laundering scheme is illustrated in Figure 1.\n\n\nAddressing Medicaid Money Laundering Fig1\n\nThe entire financing structure is akin to money laundering and puts federal taxpayers at significant risk while weakening the joint federal-state responsibility underpinning Medicaid. The structure also leads to lower value spending in the program as states make decisions designed to pass most of the cost, if not the complete cost, to federal taxpayers. Due to a much higher federal reimbursement rate for the Affordable Care Act (ACA) Medicaid able-bodied, working-age expansion enrollees and increasing state financing gimmicks, there has been a large shift in costs for financing the Medicaid program from states to the federal government over the past decade plus.\n Historically, the federal government bore about 57 percent of the costs of the Medicaid program. On paper, that percentage is now 67 percent. But after fully accounting for the financing schemes that result in artificial state expenditures, that percentage is now approaching 75 percent. And as states bear a smaller fraction of the total cost of the program, they are far less sensitive to cost increases and less likely to ensure that expenditures through Medicaid provide requisite benefit to justify the cost.\n\nThe ACA exacerbates money laundering because it allows states to obtain much more federal money per dollar of state expenditures, whether a real or artificial state expenditure. Under the ACA\u2019s 90 percent federal reimbursement percentage, $100 of financing gimmicks yields $900 in federal funds for the state. Under the normal 60 percent federal reimbursement, $100 of financing gimmicks yields $150 in federal funds for the state. Thus, states have incentives to develop money laundering schemes in conjunction with payment policies to transition more expenditures to the expansion category, including by neglecting proper eligibility reviews prior to enrolling people under the expansion.4\n\nThe rise in supplemental payments and SDPs is a natural outgrowth of the money laundering financing mechanism and a feature of Medicaid that states and the politically powerful health care industry within them will aggressively lobby to protect. But, in a time of massively large and rising federal deficits, as well as disappointing program results, serious, reform-minded policymakers should consider changes to the perverse status quo Medicaid funding structure that breeds waste and corruption. The large-scale Medicaid money laundering apparatus would not be a feature of an efficient and effective government. In order for the overall program to improve and provide Americans\u2014both Medicaid enrollees and taxpayers\u2014with greater value, the federal share of Medicaid needs to decline, and politically powerful providers need to receive less in federal Medicaid funding.\n\nHistorically, the federal government bore about 57 percent of the costs of the Medicaid program. On paper, that percentage is now 67 percent. But after fully accounting for the financing schemes that result in artificial state expenditures, that percentage is now approaching 75 percent. And as states bear a smaller fraction of the total cost of the program, they are far less sensitive to cost increases and less likely to ensure that expenditures through Medicaid provide requisite benefit to justify the cost.\n\nThe ACA exacerbates money laundering because it allows states to obtain much more federal money per dollar of state expenditures, whether a real or artificial state expenditure. Under the ACA\u2019s 90 percent federal reimbursement percentage, $100 of financing gimmicks yields $900 in federal funds for the state. Under the normal 60 percent federal reimbursement, $100 of financing gimmicks yields $150 in federal funds for the state. Thus, states have incentives to develop money laundering schemes in conjunction with payment policies to transition more expenditures to the expansion category, including by neglecting proper eligibility reviews prior to enrolling people under the expansion.\n\nThe rise in supplemental payments and SDPs is a natural outgrowth of the money laundering financing mechanism and a feature of Medicaid that states and the politically powerful health care industry within them will aggressively lobby to protect. But, in a time of massively large and rising federal deficits, as well as disappointing program results, serious, reform-minded policymakers should consider changes to the perverse status quo Medicaid funding structure that breeds waste and corruption. The large-scale Medicaid money laundering apparatus would not be a feature of an efficient and effective government. In order for the overall program to improve and provide Americans\u2014both Medicaid enrollees and taxpayers\u2014with greater value, the federal share of Medicaid needs to decline, and politically powerful providers need to receive less in federal Medicaid funding.\n\nThe most common Medicaid financing schemes are provider taxes and IGTs. By leveraging the provider tax and IGT mechanisms, states can substantially boost federal reimbursements above the levels established by the federal medical assistance percentage (FMAP), which is commonly viewed to represent the federal share of a state\u2019s Medicaid expenditures.5\n\nProvider taxes are state assessments on providers, which are typically accompanied by increased Medicaid payments to those same providers. States use the revenue from provider taxes to claim additional federal reimbursement. They then return the providers\u2019 assessments plus some additional amounts to those providers through Medicaid payments. There is a complicated set of federal rules that govern provider taxes (more on these below). Serious questions have arisen about the transparency of the money flow and the appropriateness\u2014and occasionally the legality\u2014of these provider tax arrangements.\n\nState politicians recognize the political benefits inherent to this money laundering scheme. Oregon State Representative Mitch Greenlick has referred to provider taxes as a \u201cdream tax\u201d for states: \u201cWe collect the tax from the hospitals, we put it up as a match for federal money, and then we give it back to the hospitals.\u201d6\n\nDespite the name, provider taxes are not really taxes. Entities normally avoid taxes and seek to minimize their tax burdens. Such is not the case with the entities subject to provider taxes. They often help develop the tax schemes and then lobby the government to assess them. In many cases, they lobby the government to increase existing ones. GAO found that hospital associations and nursing home associations have worked with states to design the tax structures. The associations\u2019 officials indicated that without the tax revenue, states would likely reduce Medicaid payments and that states typically provide assurances that tax revenue will be used for Medicaid payments that will make the providers better off financially.7\n\nStates have political incentives to finance substantial portions of their Medicaid programs with accounting gimmicks, because these permit them to reduce the actual amount financed from the state\u2019s tax base. Provider taxes have significantly expanded over the past few decades, and as Figure 2 demonstrates, they increase overall Medicaid spending by making states less sensitive to the costs of the program.\n\nFigure 2 shows the economics of provider taxes, displaying their impact on the federal government, states, and providers. It assumes a state with a 60 percent FMAP. The following discussion and figure are from Brian Blase\u2019s (the lead author on this paper) 2016 paper on Medicaid provider taxes.\n\n\nAddressing Medicaid Money Laundering Fig2\n\nIn the scenario without a provider tax, a state spends $100 on a provider and receives $60 from the federal government, so the net cost to the state tax base amounts to $40.\n\nThe second scenario shows how a provider tax shifts costs to the federal government, assuming states maintain the same level of spending as in the first scenario. The state taxes the provider $100 and then pays the provider $200. Assuming negligible transaction costs, the provider is essentially as well off as in the scenario without a provider tax. The federal government is worse off because it is now reimbursing the state $120 (60 percent of the $200 expenditure). The state gains $20 through these three transactions (receiving $100 in provider tax revenue and $120 reimbursement through the FMAP less $200 in expenditure to the provider). But the state is actually better off by $60 because it was paying $40, on net, to the provider in the absence of the tax.\n\nProvider taxes shift costs from states to the federal government, but they also raise overall spending by lowering the relative price of Medicaid expenditures to states. Provider taxes make state Medicaid programs cheaper because the revenue raised\u2014even though the revenue is generally illusory\u2014can be used as the state share of spending. Scenario 3 in the figure shows how provider taxes work if the provider tax mechanism generates an additional $50 for the provider. The provider\u2019s net gain is $150, equal to the $250 state payment minus the $100 paid through the provider tax. The federal government reimburses the state $150 (60 percent of $250), and the state\u2019s net payments sum to zero ($100 in provider tax revenue and $150 reimbursement through the FMAP less $250 for the provider payment).\n\nComparing scenario 1 (no provider tax) with scenario 3 (provider tax with higher spending) shows that providers are better off from higher payments and the state is better off because of the higher federal reimbursement. The federal government, however, is worse off because it has to reimburse additional state Medicaid expenditures. Although provider taxes increase the federal share of Medicaid spending relative to the state share, the more that the state\u2019s Medicaid expenditures increase as a result of provider taxes, the greater the burden on both the federal and state tax base. It is worth noting that there are two effects on the state tax base financing burden: The provider tax shifts part of the previous burden to the federal tax base but the state bears its share of the financing burden for the marginal increase in Medicaid spending that results from the provider tax reducing the relative cost of Medicaid to the state.\n\nStates started using provider taxes and provider donations in the mid-1980s. By the early 1990s, most states had provider taxes or provider donation programs in place. The Congressional Research Service (CRS) notes that \u201cprovider taxes were often imposed only on Medicaid providers. These provider tax arrangements were agreed to (and sometimes initiated) by the Medicaid providers because the Medicaid providers could be held harmless from the cost of the tax through increased Medicaid payment rates.\u201d8 In a 2016 paper on provider taxes and how Congress tried to address them, Blase wrote:\n\nIn response to the increased use of provider taxes and related techniques, Congress passed and President Bush signed the Medicaid Voluntary Contribution and Provider-Specific Tax Amendments (MVCPSTA) in 1991. The MVCPSTA outlawed the use of most provider donations and made provider taxes more costly for health care providers who treated few, if any, Medicaid enrollees.\n\nThe MVCPSTA required that provider taxes be uniform (the same tax rate across all providers in a given class) and broad based (the tax would apply to all providers in one of the 19 specified classes of providers subject to the tax, even those who do not provide Medicaid services). The MVCPSTA also attempted to limit the extent to which providers could be held harmless by the tax\u2014providers who receive at least as much money back from the state in higher Medicaid payments as they had paid in tax. In addition to being complex, the rules governing provider taxes are also somewhat arbitrary. For example, the secretary of the Department of Health and Human Services (HHS) may waive the broad-based and uniform requirements if the tax is \u201cgenerally redistributive\u201d and the amount of the tax is not directly correlated to Medicaid payments (although there is an exception for rural and sole community providers). States commonly apply for these waivers.\n\nThree tests exist to determine whether a provider tax satisfies the \u201chold harmless\u201d criteria. The key test\u2014the guarantee test\u2014only applies if the tax rate exceeds 6 percent of net patient revenue. The 6 percent threshold is generally referred to as the \u201csafe harbor\u201d provision [2 C.F.R. 433.68(f)(3)(i)(A)]. While states can have provider tax rates that exceed the safe harbor threshold, neither the CRS nor GAO have identified any state that imposes a tax rate exceeding 6 percent of net patient service revenue.9\n\nThe rules put in place by the 1991 legislation succeeded in reducing states\u2019 use of provider taxes for a time. But in 2008, there was a sharp increase in provider taxes as many states faced much lower state revenue because of the financial crisis and deep recession. The number of states with any provider tax rose from 40 to 49 between 2007 and 2015, with 21 states adding hospital taxes and 14 states adding nursing home taxes during this period.10 Moreover, many states with existing provider taxes increased the size of them during this period.\n\nFigure 3 demonstrates the increase in provider taxes after state fiscal year (SFY) 2004 and shows the number of states with any provider tax, an inpatient hospital tax, an intermediate care facility tax, and a nursing home tax. Use of provider taxes exploded over the past two decades. According to CRS, 39 states had three or more provider taxes in SFY 2024, and 42 states are estimated to have three or more provider taxes in SFY 2025.11\n\n\nAddressing Medicaid Money Laundering Fig3\n\nWhile states must finance at least 40 percent of their share of Medicaid payments from state funds, which can include general funds and state provider tax revenue, up to 60 percent of the state share may be sourced from local government revenue through IGTs or local provider taxes.12 In SFY 2024, states reported that about one-third of the state share of Medicaid came from sources outside of general revenue.13 Older reports suggest that approximately 88 percent of these revenues from outside general revenue come from provider taxes and IGTs.14 In essence, for every $2 of actual state revenue, $1 represents funding collected for money laundering.\n\nDuring the cooling of provider tax use in the 1990s, IGTs were increasingly used to finance the nonfederal or state share of new, often exceptionally high Medicaid supplemental payments made for the benefit of specific publicly owned hospitals, health systems, physician groups, and nursing homes. In a blatant conflict of interest transaction, the local governments, public universities, or medical schools that own these public providers transfer the IGT funds to the state.\n\nThrough a supplemental payment mechanism, the state Medicaid agency pays the public providers a sum equal to the IGT funds and the corresponding federal matching funds. The supplemental payments are added on top of the public provider\u2019s base or regular Medicaid rates, often bringing the total Medicaid rates to amounts paid by Medicare rates or higher. Meanwhile, the nonfederal share of public providers\u2019 underlying base Medicaid rates is often financed using proceeds from provider taxes. One financing scheme compounds another, further undermining the fiscal integrity of Medicaid, rewarding irresponsible payment policy, and artificially increasing the burden on federal taxpayers.\n\nUnder IGT arrangements, federal taxpayers incur the full cost of increased Medicaid payments. Public providers owned or operated by the public entities supplying the IGT funds are the sole beneficiaries of the resulting supplemental payments. For every $1 in IGT funds transferred to the state, the locally or state-owned public providers receive at least $2 and as much as $4 in return, depending on the state\u2019s FMAP, thereby generating a net 100 percent to 400 percent profit from the transaction.\n\nIGT arrangements do not cost the state, as it is just an intermediary in the transaction. To facilitate favorable action and minimize a state\u2019s administrative burden, local entities, universities, or public providers often retain consultants to do the necessary paperwork and modeling to secure federal approval and optimize and implement the supplemental payments.\n\nStates secure a political benefit from the IGT mechanism, with less budget pressure to subsidize politically influential counties, cities, universities, academic physicians, and public providers. Further, because public providers\u2014such as county hospitals and university health systems\u2014are commonly high-volume Medicaid providers, federal and IGT-financed supplemental payments can help mitigate demands for statewide provider rate increases that would require a real contribution from the state treasury.\n\nIn 2003, the Health and Hospital Corporation (HHC) of Marion County, Indiana, devised a creative and highly lucrative IGT scheme that has netted billions of dollars in federal funding well in excess of regular Medicaid rates.15 HHC acquired the bed licenses of numerous skilled nursing facilities (SNFs) throughout the state and leased management back to facility operators or new management companies. For federal payment purposes, this transformed the status of each facility from a privately owned or operated SNF to a non-state-government-owned or operated SNF.\n\nUnder a supplemental payment policy in the Indiana Medicaid state plan (approved by CMS), SNFs technically owned or operated by HHC are reimbursed for Medicaid patients based on the Medicare daily rate, which is substantially higher than the state\u2019s Medicaid rate.16 HHC makes an IGT to the state Medicaid agency to finance the nonfederal share\u2014about 35 percent in Indiana\u2014of the supplemental payments. Federal matching funds cover the other 65 percent of the cost to bring the HHC-affiliated SNF Medicaid payments to the maximum Medicare rate level.\n\nAt no additional cost to the state, HHC, as the city-county owner or operator of record, nets 65 percent of the supplemental payments. HHC was able to use the massive annual windfall to build a new public hospital and medical complex and other local health priorities entirely unrelated to the needs of nursing homes or frail, low-income elderly across Indiana.17 The IGT-financed supplemental payments originally devised for HHC have generated interest from other public hospital systems throughout the country.\n IGTs often result in substantially higher Medicaid payment rates for government-owned facilities. According to a 2001 HHS rule to address this problem with IGTs, \u201cThe federal government matched these higher payment rates to public facilities. Because these facilities are public entities, funds to cover the state share were transferred from those facilities (or the government units that operate them) to the state, thus generating increased federal funding with no net increase in state expenditures.\u201d18\n\nAccording to a 2014 GAO report, New York State used IGTs to transfer additional Medicaid costs to the federal government.19 In SFY 2009, the state decreased regular Medicaid payment rates and increased supplemental payments for inpatient hospital services. IGTs from two local government-owned hospitals helped finance the higher supplemental payments, and as a result, total Medicaid payments for inpatient services to the two hospitals increased by $157 million, and provider payments net of the IGTs increased by $119 million between SFY 2008 and SFY 2009. While no state general funds were used to finance the supplemental payments in SFY 2008 or SFY 2009, the amount of state general funds used for regular Medicaid payments did not change as the federal government picked up the entire cost increase of the scheme.\n\nA 2012 House Oversight and Government Reform Committee investigation found that New York\u2019s state-run developmental centers had become a cash cow for the state, exploiting a deeply flawed Medicaid reimbursement formula to secure excessive federal funds. While private providers offering the same services were reimbursed at significantly lower rates, the state-run centers charged Medicaid over $5,000 per resident per day, generating billions in unjustified payments over a decade. The committee\u2019s report and other analyses highlighted how New York officials were aware of the windfall but failed to correct it, while federal oversight agencies also dragged their feet despite acknowledging the problem.20 The result was an estimated $15 billion in improper federal Medicaid payments before CMS finally took action, negotiating a deal to phase out the excessive payments and bring reimbursement rates closer to actual costs.\n\nTHE LATEST FINANCING SCHEME: MCO TAXES\n\nStates may also impose special taxes on managed care organizations (MCOs). While taxes on MCOs have some similarities with other provider taxes, they are especially ripe for abuse. There are 22 states with MCO taxes for FY2025\u2014a significant increase from the 12 states that had such taxes in FY2018.21 MCO taxes are typically used in addition to existing provider taxes.\n\nA 2016 Obama administration Medicaid managed care rule mandates that state Medicaid capitation rates must compensate MCOs for the cost of state taxes, which guarantees that Medicaid MCOs are held financially harmless from the tax.22 Unlike other types of provider tax schemes, where all of the tax revenues are spent as the state share of federally matched provider rate increases or eligibility expansions, only a portion of MCO tax revenues are necessary to cover the state share of paying Medicaid MCOs back. The bulk of the original tax revenues received from Medicaid MCOs\u2014an amount equal to the federal share of repaying Medicaid MCOs for the tax\u2014remains in the state treasury, available for any use, including the state match for any Medicaid expenditures.\n\nLike provider taxes, MCO taxes are supposed to be broad-based, uniform, and devoid of \u201chold-harmless\u201d provisions.23 In principle, this should mean that states must apply the same rate to all MCOs\u2014including commercial insurers that would not benefit from the higher Medicaid payments these taxes finance. Because a broad-based and uniform MCO tax would create losers, states try to minimize the applicability of these taxes on non-Medicaid providers.\n\nTwo federal policies make MCO taxes politically easier to enact by effectively exempting non-Medicaid insurers that would otherwise always lose under a state tax. First, federal preemption law exempts Medicare Advantage plans from state provider taxes. Second, under current federal rules, states are often able to meet the statistical tests necessary to exempt commercial health insurers from an MCO. States can apply to waive the uniform and broad-based requirements for commercial insurers, thereby eliminating the possibility of losers among insurance companies. When states apply for the waiver, they must prove that their taxes would be \u201cgenerally redistributive,\u201d meaning payments must be reasonably funded by non-Medicaid providers.24\n\nIn concept, this would structurally prohibit any implied hold-harmless arrangements between the state and the MCOs. In practice, as demonstrated by CMS\u2019s 2023 approval of a California MCO tax, these rules are not effective at guarding against corrupt arrangements.25 The agency approved the Golden State\u2019s new financing scheme even though it acknowledged that \u201cthis tax program fails to be \u2018generally redistributive\u2019 in nature.\u201d26 CMS noted in a companion letter that it intended to revise the test outlined in regulations to prevent such obviously non-redistributive financing schemes from receiving approval in the future.27\n\nCalifornia\u2019s MCO tax applies only to a narrow group of companies, chosen likely for political purposes, with between 208,000 and 333,000 annualized enrollees.28 By applying to only a handful of non-Medicaid MCO providers, the tax is not broad-based, nor is it uniform. The state taxes Medicaid MCO providers 104 times the rate set for private providers\u2014$182.50 for Medicaid MCOs per member-month compared to $1.75 for private insurers per member-month.\n\nThe loophole in existing regulations allows California Medicaid MCOs to contribute more than 99 percent of the $8.4 billion total tax revenue in 2025 and then receive this funding back through the federal match.29 This scheme allows the Golden State to collect a projected $19.4 billion over the four-year life of the tax with no commensurate increase in state funding.30 California has used the additional funding to have the federal government fully finance Medicaid for illegal immigrants and to remove the state\u2019s asset test for Medicaid so the wealthiest residents can have taxpayers pay for their long-term care services.31\n\nDespite CMS noting its intent to close this loophole, other states have since replicated the California model. New York, for example, received CMS approval at the end of the Biden administration to leverage this financing gimmick to address its budget shortfall with the new stream of federal revenue.32 One policy institute in New York estimated that the Empire State could raise $4 billion in federal Medicaid funds annually with no increase in revenue from the state using this California-modeled MCO tax.33 CMS also approved an enhanced MCO tax in Michigan before President Biden left office.34 Until the federal government changes the rules, abuse of MCO taxes will continue, because so much revenue is on the line for states, which naturally wish to pass these costs to taxpayers outside their borders.\n\nCERTIFIED PUBLIC EXPENDITURES\u2014ANOTHER GIMMICK\n\nCertified public expenditures (CPEs) are a Medicaid financing gimmick used by states to claim federal reimbursement for services provided. CPEs are expenditures that public entities have incurred and paid for using nonfederal funds. These expenditures must be certified by an authorized official as costs related to providing eligible services. While intended to leverage federal matching funds, this practice frequently serves as a gimmick to inflate costs and prop up inefficient public providers. This kind of spending makes up a very small proportion of the nonfederal share of Medicaid spending. The most recent estimates are that CPEs made up $4 billion, or about 2 percent of all nonfederal Medicaid spending, in SFY 2018.35\n\nEntities that may use CPEs include state and local governments, public hospitals and health care facilities, public school districts (for Medicaid-covered services provided in schools), and public universities and academic medical centers. The self-certification process, however, invites abuse, allowing states to claim overhead, unrelated expenses, or questionable costs as \u201clegitimate,\u201d particularly where oversight is weak. This distorts the Medicaid program\u2019s intent and disadvantages private providers, which must compete without similar windfalls from federal funds.\n\nThe process of claiming CPEs starts with the public entity incurring costs associated with providing Medicaid services. An authorized representative certifies that these costs were paid with nonfederal funds and submits the claim to the state Medicaid agency. The agency then requests federal reimbursement based on the state\u2019s FMAP. Upon approval, federal matching funds flow back to the state. This system incentivizes states to prioritize revenue generation over cost efficiency, undermining Medicaid\u2019s core mission of serving vulnerable populations.\n\nThe complexity of the regulatory requirements and the incentives of states and providers to maximize federal funds presents challenges. Self-certification allows for potential abuse, particularly in states with lax oversight. Funds from CPEs can provide disproportionate advantage to public providers that may be less efficient than private providers. A 2021 HHS OIG audit of Tennessee\u2019s Medicaid CPE claims found that the state had improperly certified hundreds of millions of dollars due to inadequate documentation, demonstrating how self-certification without stringent oversight can lead to abuse.36\n\nA main reason for the various Medicaid money laundering schemes is so states can make larger payments to providers, often through supplemental payments. A Medicaid supplemental payment is a lump sum payment to a health care provider. These payments are made in addition to Medicaid payments for specific health care services that have been rendered. Hospitals are the main recipients of supplemental payments. Excluding payments made under managed care arrangements, supplemental payments represented 53.0 percent of total Medicaid payments to inpatient and outpatient hospitals in FY2023, up from 40.9 percent in FY2011.37\n\nBut hospitals are not the only beneficiaries. Supplemental payments to mental health facilities represented 46.2 percent of total Medicaid payments outside of managed care arrangements in FY2013, up from 45.7 percent in FY2011. Supplemental payments to nursing facilities and intermediate care facilities for individuals with intellectual disabilities outside of managed care arrangements totaled 5.6 percent of total Medicaid payments in FY2023, up from 2.4 percent in FY2011. Supplemental payments to physicians and other practitioners outside of managed care arrangements represented 21.7 percent of total Medicaid payments in FY2023, up from 7.3 percent in FY2011.38 As of FY2023, the total amount of supplemental payments surpassed $57.1 billion.39\n\nThe main types of supplemental payments are upper payment limits, disproportionate share hospital payments, uncompensated care pools, and graduate medical education.\n\n\nAddressing Medicaid Money Laundering Fig4\n\n \nUpper payment limit (UPL) payments are supplemental payments that enable total Medicaid payments up to a certain limit, as displayed in Figure 4. These payments are limited to the estimated aggregate amount that would have been paid to a provider class for the same service under Medicare payment rules. In some instances, CMS uses an UPL of average commercial rates (ACRs) for \u201cqualified practitioners\u201d (physicians, physician assistants, nurse practitioners, and other non-physician professionals affiliated with academic medical centers and medical schools).40 These apply only to FFS payments. By setting the aggregate amount at the provider class, the UPL permits states to deliver excessive payments to some providers in the class. In FY2022, the federal government spent $15.8 billion in UPL payments.41 \nDisproportionate share hospital (DSH) payments are supplemental payments to hospitals treating large numbers of low-income and uninsured patients. DSH allotments, unlike Medicaid funding, are capped. Each state receives an annual DSH allotment. Previous Paragon research highlighted that the DSH program fails to equitably target public resources to safety net hospitals or fairly distribute federal funds across states.42 The main reason for the inequity is that, in response to substantial growth in payments, Congress locked state DSH allocations in place in 1993. This rewarded states that had developed the most profligate DSH programs at that time.43 All states except Tennessee receive Medicaid DSH allotments based on the previous year\u2019s allotment increased by the consumer price index for all urban consumers (CPI-U).44 The ACA reduced DSH payments, even though it expanded federal subsidies in many other ways. Yet Congress has consistently prevented these cuts from taking effect. This type of supplemental payment constituted $14.9 billion in spending in FY2022.45 \nSome state Medicaid agencies operate uncompensated care pools (UCPs) under Section 1115 waivers. The purpose of UCPs is to pay providers for uncompensated care costs. Despite their $10.0 billion contribution to Medicaid spending in FY2022, there has been little oversight of these payments.46 \nFor graduate medical education funding, Medicaid makes payments to teaching hospitals to support the training of medical school graduates. The total funding in FY2022 was $4.9 billion.47 \nDelivery system reform incentive payments (DSRIP) is a less common program that operates under Section 1115 waivers. While the purpose of the program is to \u201cincentivize system reforms\u201d from providers, in practice it is used as another way to steer additional funding to managed care systems.48 This program constituted roughly $200 million in spending in FY2022.49 \n\nThe growth in supplemental payments is driven in part by the large share of federal funds directed toward supplemental payments. Supplemental payments, particularly those financed by IGTs, are often made based on political influence of the provider rather than on efficient delivery of care or an individual facility\u2019s financial need for such funds. Supplemental payments are also not distributed equitably across states or within states. GAO conducted numerous studies on the problems with supplemental payments and uncovered a host of problems, most notably inappropriate funding for providers and a lack of data transparency.50\n\nGAO found that supplemental payments totaled more than $43 billion in FY2011\u2014nearly double the amount from FY2006.51 Figure 5 shows the change in supplemental payments between FY2011 and FY2023. The overall level of supplemental payments, which are outside of managed care arrangements, has risen, while the percentage of Medicaid expenditures through FFS payments has significantly decreased.\n\n\nAddressing Medicaid Money Laundering Fig5\n\nOverall, hospitals receive most supplemental payments. In fact, the hospital inpatient and outpatient services garnered 84 percent of the total supplemental payment spending in 2023, amounting to $47.8 billion. The hospital share of supplemental payment spending has somewhat decreased over time in part due to the increased incidence of supplemental payments being directed toward physicians and other providers.\n\nAs shown in Figure 6, supplemental payment spending rose sharply in recent years, with 33 states seeing increases since FY2019. This increase was more pronounced in some states. For example, supplemental payments more than doubled in Idaho, Maryland, Oregon, Tennessee, Virginia, and Washington state. Virginia had the most growth, with an increase of $2.4 billion in supplemental payments to providers between FY2019 and FY2023, the period that coincided with Virginia adopting Medicaid expansion under the ACA.52\n\n\nAddressing Medicaid Money Laundering Fig6\n\nCONSEQUENCES OF FINANCING SCHEMES: PAYOFFS TO PROVIDERS AND INSURERS THROUGH STATE DIRECTED PAYMENTS\n\nUntil 2016, federal regulations prohibited states from making supplemental payments for services delivered through managed care. This restriction created challenges for states looking to expand managed care in Medicaid, as providers that relied heavily on FFS supplemental payments would face significant revenue losses. As a result, as many as 15 states received Section 1115 waivers to exclude certain services or populations from managed care, allowing them to continue making supplemental payments after transitioning to managed care.53\n\nOther states found a way to increase provider pay by increasing capitation payments to MCOs and requiring the MCOs to direct these extra funds to specific providers. Historically, these payments, known as pass-through payments, were not typically linked to Medicaid services or provider performance.\n\nIn 2016, CMS issued a regulation requiring states to gradually phase out pass-through payments due to concerns that they resembled supplemental payments and did not comply with the requirement for actuarially sound managed care rates.54 CMS allowed for a gradual phase-out, with hospitals given 10 years to adjust and physicians and nursing facilities given five years to adjust.55\n\nBut the 2016 rule also introduced a new option for states to replace pass-through payments with directed payments under specific conditions. The rule, which is likely not well enforced, required that:\n\n \ndirected payments be linked to the delivery and utilization of services under managed care contracts (i.e., distributed equally among designated providers in a given state-defined provider class); \npayments support at least one goal in the state\u2019s managed care quality strategy; and \npayments not be dependent on provider participation in IGT agreements.56 \n\nIn most cases, CMS requires states to obtain annual approval for these directed payment arrangements to ensure compliance. In 2020, CMS eliminated the need for states to obtain prior approval for minimum fee schedules.\n\nMACPAC reviewed SDP approval documents and projected total spending based on the time period specified in each SDP contract window or rating period\u2014that is, the time frame when capitation rates are developed under a managed care contract. This period may be the normal 12-month calendar or fiscal year.57 MACPAC projected SDPs approved as of December 2020 to total approximately $25.7 billion for that contract window.58 For SDPs approved as of February 2023, this figure more than doubled to $69.3 billion for that contract window. In general, SDPs fit into three categories:\n\n \nMinimum or maximum fee schedules: This category sets specific parameters for the base payment rates that MCOs must pay providers for certain services. These fee schedules often require MCOs to pay providers no less than the FFS rate approved in the state Medicaid plan or may be based on Medicare or other state-defined rates. The Medicaid and CHIP Payment and Access Commission (MACPAC) projects that about $16.1 billion would be spent under this type of SDP for payment arrangements approved between February 2023 and August 2024.59 \nUniform rate increases: These arrangements mandate that MCOs pay a uniform dollar amount or percentage increase above the negotiated base payment rates for specified services. Uniform rate increases are the most like supplemental payments in the FFS model. Per MACPAC\u2019s projections, $81.5 billion of uniform rate increase payments were approved between February 2023 and August 2024.60 \nValue-based payments (VBP): This category requires MCOs to implement payment models that incentivize providers based on performance or the achievement of quality and efficiency goals rather than the quantity of services provided. VBPs are the least common type of SDP, with total spending of $3.7 billion projected based on arrangements approved between February 2023 and August 2024.61 \n\nMACPAC projects that an additional $8.9 billion will be spent on payment arrangements that span various combinations of these three categories.62 The commission projects that the sum of all fee schedules, uniform rate increases, and VBP arrangements will reach $110.2 billion per year for SDPs approved between February 2023 and August 2024.63\n\nIn 2024, the Biden administration issued a rule that\u2014while flawed\u2014introduced several significant changes aimed at improving the oversight and transparency of directed payments in Medicaid managed care.64 Prior to 2024, the oversight process for SDPs was relatively lax. CMS had weak standards for documentation, transparency, and evaluation related to SDPs. Moreover, the review process often lacked consistency and did not always require detailed reporting. Additionally, states\u2019 use of separate payment terms allowed states to create SDPs outside of base capitation rates, which raised concerns about undermining the risk-based nature of managed care. Finally, evaluation plans were frequently incomplete, delayed, or inconsistent, making it difficult to assess the impact of directed payments on health care quality and outcomes.65\n\nAlthough the rule has large fiscal costs and Congress should consider repealing it (as suggested by Chris Jacobs in a Paragon report from January 202566), there are some constructive provisions that limit abuse. First, it established more rigorous requirements for directed payment submissions, mandating that states provide information about payment amounts and provider eligibility. The rule further required states to submit provider-level payment information to account for where the directed payment spending is going.\n\nSecond, the rule implemented stricter evaluation standards with baseline information and performance targets. For SDPs exceeding 1.5 percent of total managed care costs, states must now submit evaluation reports every three years.\n\nThird, and most importantly, the rule mandated the elimination of separate payment terms by July 2027, requiring all SDPs to be integrated into base capitation rates. This change has the potential to better ensure that MCOs bear financial risk for SDP spending and align the payment structures with the risk-based principles of managed care instead of essentially guaranteeing insurers\u2019 profits each year. By removing payment mechanisms that operated outside of capitation rates, the rule addressed concerns that such practices undermine financial accountability and disproportionately benefit politically connected providers. Those are valid concerns: In 2024, MACPAC found that 87 percent of uniform rate increase SDPs, which totaled an estimated $70.6 billion, were delivered through separate payment terms and were thus outside of the managed care construct.67\n\nWhile the rule did make some long-overdue reforms of SDPs, it made it explicitly clear that states could make SDPs up to ACRs.68 Such a regulation proves that Medicaid payments can often be excessive and that payments this high are almost prima facie evidence that Medicaid payments violate the statutory requirements to be economical and efficient.\n\nAnother problem with basing Medicaid rates on ACR is an incentive of providers to increase commercial rates. ACRs are determined by calculating the mean payment for a service made by a state\u2019s top commercial insurers.69 This structure incentivizes providers to increase commercial prices to garner higher commercial payments as well as Medicaid payments\u2014raising costs for taxpayers and consumers.\n\nAccording to analysis the RAND Corporation made of 2022 medical claims data, prices for inpatient hospital facility services averaged 254 percent of Medicare rates. Prices for outpatient hospital facility services averaged 279 percent of Medicare rates, and professional physician services averaged 184 percent of Medicare rates.70 Of note, almost all physicians accept Medicare rates as payment in full for providing services to Medicare enrollees, and more than half of hospitals make money on Medicare enrollees despite industry pleas that Medicare rates are well below sustainable amounts.71 The reality is that, due to state financing gimmicks and large supplemental payments, Medicaid payments can often be well above what is necessary or appropriate.\n\nThe fiscal costs of SDPs are substantial, with estimates suggesting that the explicit allowance of SDPs up to ACR in the 2024 CMS rule could raise Medicaid spending by as much as $220 billion over the next decade.72 As shown in Figure 7, among large SDPs that cover inpatient services, outpatient services, and behavioral health (these being some of the most costly services), at least 25 states set their payment levels for SDPs as a percentage of ACRs. The average payment level among these programs was 85 percent of ACR for programs valid in fiscal years 2024 and 2025.73\n\n\n\nGAO highlighted the significant impact of these practices on federal Medicaid spending in a 2023 report that assessed SDPs approved through August 2022.74 States use SDPs to shift their financial responsibility onto federal taxpayers. The effect is more pronounced in states with SDPs exceeding $1 billion. GAO reported that for SDPs, 21 states achieved an effective FMAP of 80 percent or higher\u2014and nine of them were able to achieve an effective FMAP above 90 percent.75\n\nAccording to the 2023 GAO review, Arizona has a Medicaid money laundering scheme that results in SDPs of nearly $1.4 billion financed by $437 million in provider taxes. There is no contribution from the state general fund. The federal government is footing 91 percent of the payments.76 In 2020, Arizona enacted a hospital tax, depositing funds into a \u201cHealth Care Investment Fund.\u201d The state then makes expenditures from this fund, bringing in federal matching funds to finance the SDPs. Arizona hospitals applauded the scheme, with the executive director of the Health System Alliance of Arizona stating, \u201cThe Health Care Investment Act is an innovative solution to address the Medicaid shortfall for hospitals, doctors, dentists and other providers at no cost to the state, while infusing $1.5B into Arizona\u2019s economy.\u201d77 The funds from the first three months of the SDPs, among other factors such as COVID-19 relief funds, contributed to an increase in net operating profits for Arizona\u2019s hospitals by 35 percent between 2019 and 2020.78\n\nTennessee is awaiting CMS approval of a directed payment arrangement that would increase the tax rate on hospitals from 4.9 percent to 6.0 percent, which Barclays projects would increase FY2025 state revenue by $4.3 billion and boost hospitals\u2019 profits by up to $2.7 billion net of provider taxes.79\n\nAs mentioned, it is difficult to track and audit SDPs due to gaps in reporting requirements for provider-level payments. For example, states are required to report only on IGT-funded payments to providers but not on other funding sources.80 According to a March 2014 GAO report, CMS officials \u201ccould not attest to the accuracy of the data reported,\u201d and no action had been taken to withhold federal Medicaid funding from states that were underreporting.81 These deficiencies at both the reporting and analysis levels thwart proper accountability.82\n\nThe total number of SDP agreements increased from 201 in 2020 to 302 in 2024. In 2020, minimum or maximum fee schedules accounted for over half of the arrangements, while uniform rate increases comprised roughly one-third and VBP models represented a smaller share. Since 2020, as Figure 8 shows, uniform rate increases have risen in prominence among SDP programs\u2014overtaking minimum and maximum fee schedules. This shift illustrates states\u2019 preference for a set rate for SDP payments\u2014akin to traditional FFS supplemental payments\u2014over a system where MCOs make decisions about distribution. This could largely be explained by regulatory shifts in CMS that exempted certain fee schedules from federal approval, such as uniform rate increases.83\n\n\nAddressing Medicaid Money Laundering Fig8\n\nThere has been a significant increase in the percentage of SDPs that are uniform rate increases, and as Figure 9 shows, uniform rate increases are by far the largest type of SDP in dollar terms. However, maximum fee schedules are the fastest growing type of SDP in percentage. Maximum or minimum fee schedules represented 15 percent of SDP dollars in 2024, while uniform rate increase SDP declined as the percentage of total SDP dollars for all types from 2020 to 2024 (from 79 percent of all program types in 2020 to 74 percent in 2024).\n\n\nAddressing Medicaid Money Laundering Fig9\n\nSince 2020, hospitals have consistently been the primary recipients of SDPs, with their share growing significantly, primarily through uniform rate increases. Behavioral health and substance abuse providers were also common beneficiaries of SDPs, mainly through minimum or maximum fee schedules.\n\nInitially, state general funds were a significant source of funding for SDPs, accounting for 43 percent of total directed payment arrangements in 2020.84 However, as SDPs expanded, there was a notable increase in the use of provider taxes and IGTs to fund them. Figure 10 shows that by 2024, the share of arrangements funded by provider taxes had grown to 32 percent from 14 percent in 2020, while IGTs financed 32 percent of all arrangements, up from 21 percent in 2020.85 The percentages in Figure 10 do not add to 100 percent, as SDPs can have multiple funding sources.\n\n\nAddressing Medicaid Money Laundering Fig10\n\nThis shift highlights how states leverage these funding mechanisms to maximize federal matching funds. This in turn allows for the expansion of SDPs without additional pressure on state budgets. The increasing reliance on provider taxes and IGTs reflects a strategic effort to sustain and enhance payments to providers using federal dollars. According to recent data, states collected 20 percent more revenue in provider taxes in 2024 than in 2023.86 Not surprisingly, both provider taxes and SDPs soared in 2024, as provider taxes fuel the legalized money laundering that permits states to substantially increase SDPs.\n\nNEVADA\u2019S SDP PROGRAM AND UNIVERSAL HEALTH SERVICES SOARING PROFITS\n\nIn 2024, Nevada implemented a provider tax for all privately owned hospitals operating in the state to finance higher SDPs to those facilities.87 The hospital tax was initially set at 4.4 percent of revenue for inpatient services and 6.0 percent for outpatient services, and it grew to 7.1 percent for inpatient and 6.8 percent for outpatient in SFY 2025.88 The state generates higher payments through MCOs with the money raised through the hospital tax. Nevada also recoups a share of those higher payments because of the 3.5 percent premium tax the state imposes on MCOs.89 The legalized money laundering apparatus enables Nevada to pay rates for acute hospitals and critical access hospitals at 100 percent of the ACR while other classes of facilities are limited to 100 percent of Medicare rates. The state claims, \u201cThese limits were selected \u2026 in a manner that maximizes available federal funding to participating private hospitals.\u201d90\n\nNevada originally estimated that the additional revenue would lead to nearly $1 billion in Medicaid payments to hospitals.91 The SDPs up to ACR are very profitable for Nevada hospitals. One hospital system in particular\u2014Universal Health Services (UHS)\u2014is generating massive and increasing profits through this SDP mechanism, growing from a reported $9 million in SDP revenue, net of provider taxes, in 2023 to $194 million in 2024 and is projected to reach $222 million in 2025.92 Supplemental payments in general made up 9.8 percent of total revenue for UHS and 45.2 percent of earnings before interest, taxes, depreciation, and amortization (EBITDA).93\n\nNEW MEXICO\u2019S SDP PROGRAM AND ARDENT HEALTH PARTNERS\n\nIn New Mexico, the state estimated that an SDP program approved retroactively for the second half of 2024 would generate \u201c$1.3 billion in federal funds for hospitals in the state\u201d by leveraging provider taxes.94 The program provides a uniform dollar increase for inpatient and outpatient hospital services and extra payments for hospitals that meet certain quality metrics. The SDP estimates payment for inpatient services at 95.0 percent of ACR and outpatient services at 92.7 percent of ACR.95\n\nAs a result of these high payment rates, hospital operator Ardent Health Partners wrote that it \u201crecorded revenue of $94 million and Adjusted EBITDA of $65 million in the fourth quarter \u2026 [which] resulted in 2024 revenue and Adjusted EBITDA well above our guidance ranges.\u201d96 The information provided by Ardent does not suggest it needed this surge of federal tax dollars brought in through the SDP program. According to Ardent, \u201cNet patient service revenue per adjusted admission for the fourth quarter of 2024 increased 9.5% year-over-year. Excluding the benefit associated with the New Mexico state directed payment program, the increase in net patient service revenue per adjusted admission was approximately 3.4% for the year ended December 31, 2024.\u201d97 Estimates by KeyBanc show that 2024 Medicaid directed payment programs and supplemental payments overall total 51.3 percent of Ardent\u2019s EBITDA.98\n\nNORTH CAROLINA\u2019S CREATIVE MONEY LAUNDERING MECHANISMS TO BENEFIT HOSPITALS\n\nIn 2023, North Carolina passed Medicaid expansion and approved participation in the Healthcare Access and Stabilization Program (HASP). HASP is an SDP in which the state share is funded through assessments on hospitals and other providers. Through this program, North Carolina directs MCOs to increase payments to eligible hospitals for Medicaid-covered services. Acute care hospitals, critical access hospitals, and hospitals owned or controlled by the University of North Carolina Health Care System and East Carolina University Health Medical Center are eligible for the increased payments.99\n\nIn July 2024, CMS approved an amendment to HASP that increased the amount of federal funds that MCOs pay hospitals to ACRs for inpatient and outpatient hospital services if hospitals take specific measures to forgive debt and increase charity care.100\n\nHASP debt relief policies include the following:\n\n \nRelieving all unpaid debt accrued since 2014 by Medicaid enrollees (an amount estimated to be nearly $4 billion).101 \nRelieving all uncollected medical debt for those not enrolled in Medicaid with incomes below 350 percent of the federal poverty level (FPL) and those whose debt exceeds 5 percent of annual income. \nEstablishing protections against the accumulation of future medical debt, including discounts on future bills for people in households below 300 percent FPL and auto-enrollment in North Carolina\u2019s charity care program with presumptive eligibility determined through screening and income validation. \nBlocking certain debt collection practices by prohibiting hospitals from selling debt of individuals at or below 300 percent FPL, capping interest rates on medical debt at 3 percent, and prohibiting medical debt reporting to credit agencies. \n\nTable 1 presents data for the hospital systems set to benefit from these HASP payments for SFY 2024 and SFY 2025.102 Over the next two years, HASP is projected to spend over $10 billion in federal funds. Of this, $4 billion will be tied to increasing rates to ACRs via the debt relief provision.\n\n\nAddressing Medicaid Money Laundering Tbl1\n\nTable 1 highlights, by system, the total costs of debt and charity care compared to the value of HASP. Most hospital systems receive much higher payments from HASP compared to the current costs of bad debt in their systems, and this is despite the fact that most of the debt would have been either forgiven or donated to Undue Medical Debt\u2014a nonprofit that purchases and cancels medical debts for low-income patients. Additionally, the HASP payments do not correlate with the amount of charity care at the hospital.\n\nThe biggest recipient of HASP is Atrium Health, one of the two hospital systems that had previously refused to sell any of its bad debt.103 Using data from the National Academy for State Health Policy, we project base HASP payments to Atrium to be $890.2 million in 2024 and $892.5 million in 2025. The debt relief amendment to HASP is projected to increase these payments by $236.7 million in 2024 and $823.8 million in 2025. In total, Atrium Health will receive more than $1.7 billion through HASP in 2025.\n\nAccording to one study, Atrium accounted for 41.9 percent of medical debt lawsuits in North Carolina between January 2017 and 2022.104 Established initially as the Charlotte-Mecklenburg Hospital Authority, Atrium has expanded significantly through mergers with Navicent Health, Wake Forest Baptist Health, and Advocate Aurora Health. The system now controls 67 hospitals and has over $27 billion in annual revenue.\n\nAtrium Health\u2019s legal status is unique due to its municipal origins, providing it with significant advantages. Like most nonprofit hospitals, Atrium is exempt from federal, state, and local taxes. However, it also does not pay property taxes on land not used for health care or charitable purposes, including commercial properties such as a chicken restaurant. Furthermore, Atrium holds the power to acquire real estate through eminent domain, and legislation is being considered that could extend this authority.105\n\nAtrium has also been shielded from antitrust damages. The North Carolina Supreme Court ruled in 2020 that Atrium is immune from state antitrust laws because it is a \u201cquasi-municipal corporation.\u201d106 Consequently, it is not subject to penalties under North Carolina\u2019s Unfair and Deceptive Trade Practices Act. Additionally, the U.S. Fourth Circuit Court of Appeals affirmed in 2021 that Atrium is protected under the federal Local Government Antitrust Act of 1984, reinforcing its immunity from federal antitrust damages.107 These rulings emerged from a U.S. Department of Justice investigation that found that Atrium had imposed illegal contract restrictions on insurers, preventing them from incentivizing patients to use lower-cost health care options. Although Atrium agreed to stop these anti-competitive practices in a 2018 settlement, affected consumers received no compensation due to the hospitals\u2019 legal immunity.108\n\nAdditionally, Atrium has faced criticism for aggressive debt collection practices. It has encouraged over 63,000 patients to enroll in \u201cmedical credit card\u201d plans offered by AccessOne, a private-equity-backed company that charges up to 18 percent interest on medical debt. Reports indicate that nearly half of the patients enrolled were subjected to high-interest plans, with rates as steep as 13 percent, raising concerns about the financial burden on patients already struggling with medical expenses.109\n\nAtrium\u2019s example highlights how hospital systems can leverage political power to receive government funding that often significantly exceeds hospitals\u2019 costs. The perverse incentives inherent with this type of system were known from the start. North Carolina\u2019s treasurer, Dale Folwell, penned a letter asking CMS to reject the state\u2019s HASP application.110 He cited concerns about how the program would encourage hospital consolidation and raise the cost of health care for both private payers and Medicaid. This comes even as the state boasts some of the most expensive medical care in the nation, Folwell noted.\n\nNonetheless, CMS approved North Carolina\u2019s application to implement HASP. Now, the program serves as a prime example of how states and politically powerful medical systems manipulate Medicaid financing rules to raise commercial premiums and taxpayer costs.\n\nSHIFT IN FINANCIAL RESPONSIBILITY FROM STATES TO THE FEDERAL GOVERNMENT\n\nBefore the implementation of the ACA in 2014, the federal government has historically reimbursed 57 percent of the costs of the Medicaid program leading up to the implementation of the ACA in 2014 (as shown in Figure 11 using data from NASBO).111 The exception was during the Great Recession in 2009-2011 when the federal government increased states\u2019 FMAPs as a way to deliver additional money to the states. With the ACA\u2019s significant expansion of the program and higher FMAPs for able-bodied adults brought onto the program through the expansion, the federal share was closer to 67 percent as of 2023.112 Moreover, because much of the state share consists of fake expenditures, the actual federal share of Medicaid spending is now roughly 75 percent of total expenditures in recent years.\n\nA 2020 GAO report found that states relied on provider taxes and local government funds to finance 28 percent of the total nonfederal share of Medicaid payments in SFY 2018\u2014seven percentage points more than in SFY 2008.113 In that report, GAO also estimated that state financing gimmicks raise the actual share of Medicaid paid by the federal government by about five percentage points, although there is wide variation across the states.114 According to the latest data from NASBO, half of all states funded more than 30 percent of the state portions of their shares of Medicaid spending with non-general funds, which are mostly composed of provider tax revenues (Table 2).115\n\n\nAddressing Medicaid Money Laundering Tbl2\n\nFigure 11 demonstrates that states have been increasing their reliance on non-general funds through money laundering schemes to finance Medicaid. From 1991 through 2023, \u201cother\u201d funds increased from 4 percent to 10 percent, while the state general funds decreased from 38 percent to 23 percent. In other words, state sources, mostly consisting of laundered funds, went from about 9 percent of total state funding to more than 30 percent over this period. Thus, states\u2014with growing money laundering and reliance on federal funds\u2014have become much less sensitive to rising Medicaid costs over time. Of note, the other funds lines would be higher and the general funds line lower if NASBO were able to capture full expenditures, but according to CRS, \u201cNASBO acknowledges that its State Expenditure Report does not capture 100% of provider taxes, fees, assessments, and local funds used to finance the state share of Medicaid expenditures.\u201d116 According to NASBO, other state funds exceed general funds in five states: Alabama, Illinois, Louisiana, Oklahoma, and Utah.\n\n\nAddressing Medicaid Money Laundering Fig11\n\nFigure 12 shows the percentage of actual funding that comes from the federal government. It excludes the state money laundered funds. This percentage equates to federal spending divided by the sum of federal funds and state general funds from Figure 11 \u2014 thus omitting provider tax revenues and IGTs. This reveals the true stake that states have in Medicaid costs. By contrast, the purported federal share is merely the ratio of federal funds to all Medicaid spending. Figure 12 shows that the real federal share of spending increased from 60 percent in SFY 1991 to about 74 percent in SFY 2023. From the previous note, the actual federal share would be higher if the \u201cother\u201d funds were fully accounted for.\n\n\nAddressing Medicaid Money Laundering Fig12\n\nFigure 13 illustrates the extent that financing schemes reduce states\u2019 financial responsibility and inflate the federal share specifically for SDPs. The expected federal share is what percentage the federal government should reimburse states under their standard FMAPs. The real federal share is the percentage the federal government contributes toward the SDP, excluding any revenues from local governments and providers that are then recycled back to those governments or providers.\n\nIn the aggregate, states used financing schemes to raise the federal share of SDPs by 14 percentage points.117 This means the reported federal of 68 percent is actually closer to 82 percent when accounting for financing schemes underpinning SDPs. Nebraska, New Jersey, and Texas have inflated the federal share of SDPs the most, raising their federal shares by more than 24 percentage points above the statutory FMAP.\n\nIn 2022, state financing schemes through SDPs alone raised the cost to federal taxpayers by $4.5 billion, which is 20 percent more than they would pay in absence of these schemes (see Table 3).118 Assuming this trend holds for the most recent data on SDP spending, we estimate that the cost federal taxpayers bear through laundering schemes in SDPs is $12.8 billion in 2024 alone\u2014in addition to bearing nearly $62.3 billion based on the purported federal share of the payments at 68 percent.119\n\n\nAddressing Medicaid Money Laundering Fig13\n\nRECOMMENDATIONS FOR REDUCING MEDICAID MONEY LAUNDERING AND STRENGTHENING FISCAL INTEGRITY\n\nFederal action is necessary to curtail Medicaid money laundering schemes that have enabled states to develop kickback arrangements with insurers and providers and manipulate financing mechanisms to maximize federal reimbursements without commensurate state contributions. The financing schemes and payoffs to providers are inextricably linked. States deploy financing gimmicks to draw down excessive federal funds, which they then use to make large payments to providers, with insurers capturing a portion of the loot. These payment schemes not only inflate Medicaid spending but also drive up commercial health care prices.120 In many states, these schemes are just used as general revenue to plug budget holes and for purposes other than Medicaid.121\n\nThe Urgent Need for Reform\n\nFederal spending as a percentage of the U.S. economy, or gross domestic product (GDP), has reached unprecedented levels outside of wartime. A nearly $2 trillion federal deficit and a national debt 23 percent larger than the entire economy threaten future American prosperity and contribute to rising inflation, higher interest rates, and the potential for massive future tax increases.122\n\nOver the past 15 years, no area of federal spending has increased more than Medicaid. Importantly, there has been a significant shift in the burden of financing Medicaid away from states and to the federal government. In both 2008 and 2023, state Medicaid spending represented 0.9 percent of GDP. In contrast, federal spending soared, rising from 1.36 percent of GDP to 2.28 percent of GDP from 2008 to 2023\n\nThe large shift in costs from states to the federal government has eroded the program\u2019s fundamental principle of shared fiscal responsibility between states and the federal government, with the federal share growing by more than 10 percentage points to an effective federal share now approaching 75 percent of total expenditures. It is time for meaningful reforms to restore the appropriate federal-state financing balance, ensure Medicaid serves its intended purpose and its most deserving enrollees, and place the program on a sustainable trajectory.\n\nThe Best Solution: Block Grants\n\nThe most effective way to eliminate Medicaid money laundering and inefficient spending is for the federal government to implement block grants in the program, capping the amount of federal Medicaid funding states receive. If states received fixed Medicaid allotments, these schemes would disappear.\n\nCurrently, states bear only about 25 percent of the marginal cost of Medicaid spending, meaning they can justify expenditures even if up to 75 percent of the spending is wasteful or low value. The incentives are worse for the Affordable Care Act expansion population given the 90 percent federal reimbursement rate. Under a block grant program, states would bear 100 percent of the marginal cost beyond the amount provided by the federal government, creating strong incentives to ensure that Medicaid spending is efficient and truly benefits enrollees. Ideally, a block grant system would provide states with flexibility to meet the needs of enrollees within federal eligibility and coverage rules while naturally preventing states from artificially inflating Medicaid expenditures to draw down additional federal dollars.\n\nShort of Block Grants: Limiting Financing Gimmicks and Supplemental Payments\n\nCongress seems unlikely to transition Medicaid to block grants, but given the program\u2019s problems, it should still take decisive action to curb states\u2019 use of money laundering tactics. To be most effective, Congress should limit the provider taxes that facilitate these financing schemes.\n\nEliminate States\u2019 Ability to Use Provider Taxes to Finance Medicaid Payments\n\nCongress should prohibit states from using provider taxes\u2014including taxes on insurers\u2014as a funding source for the nonfederal share of Medicaid expenditures. There is broad bipartisan agreement that provider taxes are highly problematic.\n\nFor example:\n\n \n\u2022John Holahan of the Urban Institute called states\u2019 use of provider taxes \u201cegregious\u201d and a \u201cnational disgrace.\u201d123 \nDuring the 2011 budget negotiations, then-Vice President Joe Biden referred to provider taxes as a \u201cscam,\u201d stating, \u201cIf we can\u2019t do this\u2014come on!\u201d125 \nPast administrations from both parties\u2014including Presidents Bush, Obama, and Trump\u2014have proposed reforms to restrict provider taxes.126 The Bowles-Simpson Commission recommended their outright elimination.127 \n\nCongress should follow through on this bipartisan consensus and ban states from using provider tax revenue toward the state share of Medicaid expenditures. Extrapolating estimates from the Congressional Budget Office, this reform would reduce federal deficits by nearly $700 billion over a decade.128\n\nAs discussed earlier in this paper, despite their name, provider taxes are not real taxes. In practice, providers pay the state, the state uses those funds to claim federal Medicaid matching dollars, and then the providers receive their money back\u2014often with a windfall of many times their initial \u201ctax\u201d payment through inflated Medicaid reimbursement rates.\n\nStates claim that restricting provider taxes would force them to cut eligibility or provider payments. However, federal policymakers should be skeptical of these claims given the extensive evidence of excessive Medicaid payments that do not comply with the program\u2019s statutory requirement for efficient and economical payments.\n\nCongress should also ensure that providers are not held harmless or financially rewarded for participating in provider tax schemes. By outlawing these arrangements, states would not be able to use any funds from providers as the state share of the Medicaid reimbursement, and they would not be able to give providers any guarantees of how much Medicaid money they would receive through financing schemes. Congress should also prevent providers from engaging in side deals that ensure that all providers are held harmless or financially benefit from the provider tax mechanism.129\n\nReduce the Medicaid Provider Tax Safe Harbor Threshold\n\nShort of eliminating provider taxes, Congress should reduce the safe harbor threshold for hold-harmless arrangements. This would make provider taxes more difficult for states to leverage, as uniform and broad-based provider taxes would mean that providers and the state could not hold providers who serve fewer Medicaid recipients harmless from the tax scam.\n\nGenerally, the federal government prohibits the state from imposing a provider tax that includes hold-harmless arrangements with providers in which the state essentially agrees to pay providers back for the funds that were taxed. This requirement makes it more difficult for states and providers to run the money laundering schemes, because if providers have no guarantee of getting their money back, they will be less supportive of the underlying provider tax. Unfortunately, the safe harbor threshold undercuts this distinction by allowing states to run the schemes so long as the total tax is below 6 percent of a facility\u2019s revenue. Eliminating the safe harbor would close this loophole that states and providers use to engage in money laundering and kickback schemes.\n\nEliminating or lowering this safe harbor threshold would reduce states\u2019 ability to use provider taxes to generate excess federal funds. In his FY2013 budget, President Obama proposed lowering the safe harbor threshold to 3.5 percent of a provider\u2019s revenue. This reform was estimated to reduce federal deficits by about $22 billion over a decade. That reform would now likely generate federal savings of $200 billion over a decade\u2014a sign of the rampant growth in states\u2019 use of provider taxes to finance the nonfederal share.130 According to CRS, 38 states had reported at least one Medicaid provider tax above 5.5 percent of net patient revenue as of July 1, 2024.131\n\nEnd Fiscally Irresponsible Managed Care Practices from the Obama and Biden Administrations\n\nIn 2016, the Obama administration promulgated an expansive Medicaid managed care regulation that significantly raised federal spending. In 2024, the Biden administration doubled down with a rule making it clear that states could create SDPs up to average commercial rates. Eliminating these policies and instituting sensible caps on Medicaid payments through insurers would likely produce substantial federal budget savings over the next 10 years.\n\nEnd State Directed Payments in Medicaid Managed Care\n\nIn its 2016 rule, the Obama administration allowed for SDPs in managed care. These are a form of supplemental payments, primarily for hospitals, with the nonfederal or state share largely financed with provider tax revenues or IGT payments. SDPs are made on top of the payments providers receive through reimbursement policies set by the state-contracted Medicaid MCO. SDPs are also on top of other Medicaid add-on payments, notably DSH payments and graduate medical education payments.\n\nSDPs have become the single most powerful driver of total federal Medicaid spending growth, and, as GAO has observed, \u201cthe process lacks sufficient fiscal guardrails to ensure state directed payments result in provider payment rates that are reasonable and appropriate as is required under CMS guidance. Moreover, these weaknesses are inconsistent with federal internal control standards that require federal agencies to obtain quality and relevant information and use it to conduct oversight and monitor changes over time.\u201d132 These schemes are projected to show dramatic, increasingly unsustainable growth as more states adopt SDPs, extend SDPs to more provider types, and use the option to pay commercial-level rates in a welfare program. Congress should rescind the ability of states to utilize SDPs.\n\nShort of eliminating SDPs, Congress should limit federal reimbursement for Medicaid payments made through insurers to no more than Medicare rates. Congress should not permit states to develop payment schemes in their Medicaid programs that incentivize providers to treat Medicaid recipients over Medicare recipients and dramatically hike federal taxpayer costs. With the advent of SDPs and the financing schemes underpinning them, states are now paying providers up to average commercial rates through Medicaid. Average commercial rates are more than 2.5 times Medicare rates on average for hospital services, and this payment disparity will produce large incentives for providers to prefer Medicaid recipients over Medicare recipients.133\n\nThere is already a UPL for most services in Medicaid fee for service at Medicare rates. The UPL is calculated at the aggregate level across providers in a class. At a minimum, Congress should extend this UPL to all providers in Medicaid fee for service and create a parallel UPL for Medicaid managed care at those levels.134 States could reimburse providers higher rates than Medicare at their discretion and with their own dollars, but they would not receive federal matching funds for these excess payments.\n\nProhibit States from Reimbursing Insurers for Provider Taxes\n\nFor FY2025, 22 states impose taxes on MCOs.135 Under the expansive and costly Medicaid managed care rules adopted by the Obama administration in 2016, states are required to reimburse Medicaid insurers for the cost of state-imposed taxes. About 2.5 percent of Medicaid capitation rates go to reimburse state-contracted insurers for the cost of these taxes.136 States receive federal matching funds (50 percent to 90 percent, depending on the state and associated enrollee) for the cost of repaying Medicaid insurers for the tax.\n\nManaged care taxes are particularly nefarious. First, MCO taxes are assessed on a large tax base and thus can result in far greater amounts of money laundering. Second, MCO tax policy mandates that states reimburse the MCOs for the amount of the tax, meaning that MCOs face no financial risk from the tax. Third, unlike other forms of provider taxes where a state may not retain any residual funds, state taxes on MCOs always substantially increase state revenues that may, in turn, be used for any purpose not limited to Medicaid or health care. The regulation requiring states to reimburse Medicaid insurers for state taxes should be rescinded, and federal funding should be prohibited from covering the cost of insurer taxes.\n\nProhibit Costly Related Party Conflicts of Interest in Medicaid Provider Payments\n\nThe Medicaid program is rife with related party conflicts of interest. This means that providers owned or operated by a state or local government or by the parent company, subsidiary, or partner of a state-contracted insurer receive higher rates, higher supplemental payments or SDPs, a larger market share, or more favorable treatment than their competitors do.\n\nThere is always an inherent conflict of interest when a state owns or operates a hospital or health system and determines its Medicaid payment and operational policies, because the state can directly favor the state-owned provider over private providers, as demonstrated in the New York developmental center example. In the case of local-government-owned providers, all IGT-funded supplemental payments involve a conflict of interest between the governmental entity and its provider. In many states, government-owned providers have structured Medicaid financing arrangements to maximize federal matching funds without a corresponding increase in actual health care services. For example, a county-owned hospital transfers funds to the state, then the state uses those funds to make a Medicaid payment to the facility and claims federal Medicaid dollars on those expenses. Finally, the state returns a portion of the funds back to the hospital. Moreover, when certain providers or institutions receive undue financial advantages due to their affiliations, it creates an uneven playing field that undermines competition and can reduce the quality of care.\n\nIn the case of Medicaid MCOs, the problem is worse and growing more severe. Many insurers already own providers and administrative vendors, and some insurers also own drug products.137\n\nRelated party conflicts of interest distort market dynamics, increase taxpayer costs, harm program integrity, restrict accountability and transparency, and adversely affect choice, access, and quality of care.\n\nTo address these problems, federal policymakers should prohibit states and Medicaid insurers from adopting any payment rates, terms and conditions, or other policies and practices that treat any provider owned or operated by a state or local government or an insurer more favorably than non-related-party providers. Under this policy, states could not provide higher Medicaid payments to a government-owned facility than to a privately owned facility. This policy would prevent overpayments to government providers, a portion of which those providers then transfer back to the state to be used as the state share of Medicaid to claim more federal money.\n\nFor Medicaid insurers, this policy should apply to all providers, vendors, drugs, and other products owned or controlled by the parent company or any subsidiary, joint venture, or other affiliate of the parent.\n\nStop Paying Consultants with Federal Monies\n\nCongress should also address the problem that these state financing gimmicks are often designed by consultants hired by the health care industry. For example, in Michigan, one contract set to last from 2018 to 2023 worth $3.7 million explicitly required the consultant to \u201c[i]dentify federal revenue enhancement opportunities \u2026 where the State is not maximizing potential federal revenues.\u201d138 These consultants are often paid with contingency fees based on a percentage of the net financial gain from the scheme (i.e., based on how much federal money the scheme generates). In 2005, GAO identified 34 states that used Medicaid contingency-fee consultants \u201cto maximize federal reimbursements.\u201d139 Congress should prevent these consultants from being paid on a contingency-fee basis.\n\nGreater Oversight: Reporting and Audits\n\nFederal policymakers should require greater disclosure and oversight of supplemental payments and SDPs. They should require that states submit provider-specific information about Medicaid payments, including supplemental payments and SDPs and states\u2019 sources of funding for the nonfederal share of these payments. They should also require annual independent audits of provider taxes, IGTs, and certified public expenditures to make sure they comply with the law and fine states with schemes out of compliance.\n\nGreater Oversight: Close Integrity Loopholes in Certified Public Expenditures\n\nAny arrangement where states certify the legitimacy of their own expenditures for federal reimbursement, as is the case with CPEs, is ripe for abuse without proper accountability. Though CPEs make up a small proportion of total Medicaid spending, the loopholes they create allow states to inflate Medicaid costs.\n\nCongress should establish a timeline to phase out CPEs, forcing states to fund Medicaid through transparent, accountable budgeting rather than opaque financing tricks. At a minimum, Congress should require states to publicly disclose detailed CPE data, including amounts, certifying entities, and service breakdowns.\n\nOpponents of reforming Medicaid\u2019s opaque and corrupt financing structure argue that providers and states need dollars from these arrangements to sustain their programs. However, as shown above, such claims are likely overblown because of the extent to which states use these schemes to generously pay providers and fund their non-Medicaid priorities. Lawmakers can also consider phase-ins to ease the transition. President Obama\u2019s proposal to lower the provider tax threshold hold from 6 percent to 3.5 percent was phased in over a three-year period and could be a model for policymakers.\n\nCongress created Medicaid to help finance health care services for the most vulnerable\u2014not to serve as a slush fund for states and politically connected providers. These reforms would end or reduce the financing schemes that have ripped off taxpayers and diverted health care funds away from those who need them most. If Congress is unable to implement reforms to meaningfully reduce money laundering in the Medicaid program, then HHS should take aggressive action to protect the Medicaid program for those who most need it and for the hard-working American families that finance the program.\n\n1\u2191  GAO, Medicaid: CMS Needs More Information on States' Financing and Payment Arrangements to Improve Oversight, December 2020, pp. 29-34, https://www.gao.gov/products/gao-21-98; and Daniel L. Hatcher, \"Medicaid Maximization and Diversion: Illusory State Practices That Convert Federal Aid into General State Revenue,\" Seattle University Law Review 39 (2016),  https://scholarworks.law.ubalt.edu/all_fac/1001\n\n2\u2191  GAO, Medicaid Financing: States' Increased Reliance on Funds from Health Care Providers and Local Governments Warrants Improved CMS Data Collection, July 29, 2014,  https://www.gao.gov/products/gao-14-627\n\n3\u2191  U.S. House of Representatives Committee on Oversight and Government Reform, \"Billions of Federal Tax Dollars Misspent on New York's Medicaid Program,\" March 5, 2013,  https://oversight.house.gov/wp-content/uploads/2013/03/Bipartisan-Medicaid-Oversight-Report-Final.pdf\n\n4\u2191  Brian Blase and Rachel Greszler, \"Medicaid's True Improper Payments Double Those Reported by CMS,\" Paragon Health Institute, March 3, 2025,  https://paragoninstitute.org/medicaid/medicaids-true-improper-payments-likely-double-those-reported-by-cms/\n\n6\u2191  Quoted in Peter Wong, \"Oregon House Extends Hospital Tax,\" Portland Tribune, March 11, 2015,  http://portlandtribune.com/pt/9-news/253422-123198-oregon-house-extends-hospital-tax\n\n8\u2191  Alison Mitchell, Medicaid Provider Taxes, Congressional Research Service, updated December 30, 2024,  https://www.congress.gov/crs-product/RS22843\n\n9\u2191  Brian Blase, \"Medicaid Provider Taxes: The Gimmick That Exposes Flaws with Medicaid's Financing,\" Mercatus Center, February 16, 2016, https://www.mercatus.org/research/research-papers/medicaid-provider-taxes-gimmick-exposes-flaws-medicaids-financing. The specified 19 classes of providers are those that provide inpatient hospital services, outpatient hospital services, nursing facility services, services of intermediate care facilities for the mentally retarded, physicians' services, home health care services, outpatient prescription drugs, services of Medicaid managed care organizations, ambulatory surgical centers, dental services, podiatric services, chiropractic services, optometric/optician services, psychological services, therapist services, nursing services, laboratory and x-ray services, emergency ambulance services, and other health care items or services for which the state has enacted a licensing or certification fee. Generally redistributive means that there is a negative relationship between the amount of tax owed by the provider and the percentage of revenue the provider receives from Medicaid. \"The guarantee test is violated if the state or other unit of government imposing the tax provides directly or indirectly for any payment, offset, or waiver that guarantees to hold taxpayers harmless for all or a portion of the tax\" (Mitchell, Medicaid Provider Taxes). Currently, 34 states and the District of Columbia have at least one CMS-approved waiver under Title 42, Section 433.72, of the Code of Federal Regulations for health care-related provider taxes: Arizona, Arkansas, California, Colorado, Florida, Georgia, Hawaii, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maryland, Massachusetts, Minnesota, Mississippi, Missouri, Nevada, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, South Carolina, Tennessee, Utah, Virginia, Washington, West Virginia, Wisconsin.\n\n15\u2191  HHC is jointly governed by Marion County and the City of Indianapolis and operates the county public health department as well as a large public hospital and clinic system serving the Indianapolis area. See Hari Sharma and Lili Xu, \"Use of Intergovernmental Transfers\u2014Based Medicaid Supplemental Payments to Boost Nursing Home Finances\u2014Evidence from Indiana Nursing Homes,\" Medical Care 61, no. 8 (August 1, 2023): 546-553,  https://pmc.ncbi.nlm.nih.gov/articles/PMC10330393/pdf/nihms-1901396.pdf\n\n16\u2191  Indiana Medicaid State Plan Amendment IN-23-0011 details the current supplemental payment methodology approved by CMS at  https://www.medicaid.gov/medicaid/spa/downloads/IN-23-0011.pdf\n\n17\u2191  Tim Evans et al., \"Nursing Home Residents Suffer as County Hospitals Rake in Millions,\" Indianapolis Star, March 11, 2020,  https://www.indystar.com/in-depth/news/investigations/2020/03/11/indiana-nursing-home-patients-suffer-medicaid-money-diverted-hospitals/2517834001/\n\n20\u2191  House Committee on Oversight and Government Reform staff report, \"Billions of Federal Tax Dollars Wasted Annually by New York's Medicaid Program,\" September 2012,  https://oversight.house.gov/wp-content/uploads/2012/09/Developmental-Center-Staff-Report-for-Hearing-9-20-12.pdf\n\n21\u2191  Elizabeth Hinton et al., \"As Pandemic-Era Policies End, Medicaid Programs Focus on Enrollee Access and Reducing Health Disparities Amid Future Uncertainties,\" KFF, October 2024, Table 4, https://www.kff.org/report-section/50-state-medicaid-budget-survey-fy-2024-2025-provider-rates-and-taxes/; KFF, \"States with an MCO Provider Tax in Place,\"  https://www.kff.org/other/state-indicator/states-with-an-mco-provider-tax-in-place/\n\n25\u2191  California's MCO tax was possible only by exploiting the waiver process through the statistical definition of generally redistributive. On its face, it is clear that California's MCO tax structure is not generally redistributive, but the structure was carefully designed to not trigger the statistical test for this feature. This statistical test is outlined as follows: For the proposed tax structure, calculate the slope of the linear regression line between each provider's share of the total tax paid by all taxpayers and the number of taxable units, which is measured in member-months in this case. Repeat these calculations for another scenario where the tax structure is both broad-based and uniform. Calculate the ratio between the slope of the broad-based scenario to the slope of the proposed tax structure. If the ratio is greater than one, CMS must grant the waiver. In California's case, its MCO tax includes just enough large insurance companies to manipulate the regression line of the proposed tax structure and raise the ratio. This allows for the tax to comply with the statistical test for being generally redistributive, despite the obvious features that would suggest otherwise. CMS was legally bound by rule to approve the waiver, though it noted it will make changes to the process accordingly.\n\n26\u2191  Rory Howe, \"California Managed Care Organization Tax Waiver Approval,\" CMS, p. 4,  https://www.dhcs.ca.gov/Documents/CA-MCO-Tax-Waiver.pdf\n\n27\u2191  \"Therefore, CMS intends to develop and propose new regulatory requirements through the notice-and-comment rulemaking process to address this issue\" (Howe, \"California Managed Care Organization Tax Waiver Approval\").\n\n28\u2191  The approval documents listed these constraints as \"2.5 million and 4.0 million member-months.\" California Department of Health Care Services, \"California Request for Waiver for Managed Care Organization Tax,\" June 2023,  https://www.dhcs.ca.gov/services/Documents/CA-MCO-Tax-Request-2023-2026.pdf\n\n29\u2191  Represented as calendar year in the data, as this coincides with the tax year, not the state fiscal year.\n\n30\u2191  The tax expires on December 31, 2026; California Department of Health Care Services, \"Managed Care Organization Provider Tax,\" May 2023,  https://www.dhcs.ca.gov/Documents/LGA/Governors-Budget/DHCS-MCO-Tax-Primer-5-26-23.pdf\n\n31\u2191  Paul Winfree and Brian Blase, \"California's Insurance-Tax Shuffle: How Federal Money Ends Up Paying for Medicaid for Illegal Immigrants,\" Paragon Health Institute, March 12, 2025,  https://paragoninstitute.org/medicaid/californias-insurance-tax-shuffle-how-federal-money-ends-up-paying-for-medicaid-for-illegal-immigrants/\n\n32\u2191  Grace Ashford, \"New York Has a Budget Trick to Try on the Federal Government,\" New York Times, April 5, 2024,  https://www.nytimes.com/2024/04/05/nyregion/medicaid-budget-taxes.html\n\n33\u2191  Michael Kinnucan, \"The Medicaid MCO Tax Strategy,\" Fiscal Policy Institute, March 19, 2024,  https://fiscalpolicy.org/the-medicaid-mco-tax-strategy\n\n34\u2191  Letter to Deputy Commissioner Amir Bassiri, CMS, December 20, 2024, https://www.health.ny.gov/health_care/medicaid/rates/dfrs/docs/2024-12-20_cms_letter.pdf; Susanna Vogel, \"For-Profit Health Systems See Medicaid Supplemental Payment Bump in Q2,\" HealthCare Dive, August 12, 2024,  https://www.healthcaredive.com/news/health-systems-medicaid-supplemental-payments-second-quarter-earnings/723675/\n\n36\u2191 HHS, Office of Inspector General, \"Tennessee Medicaid Claimed Hundreds of Millions of Federal Funds for Certified Public Expenditures That Were Not in Compliance with Federal Requirements,\" October 2021,  https://oig.hhs.gov/documents/audit/7332/A-04-19-04070-Complete%20Report.pdf\n\n37\u2191  Medicaid and CHIP Payment and Access Commission (MACPAC), \"MACStats Archive,\" March 2011-December 2023,  https://www.macpac.gov/publication/macstats-archive/\n\n40\u2191  Medicaid.gov, \"Medicaid Qualified Practitioner Services\u2014Methodologies for Enhanced Payment Made to Physicians and Practitioners Associated with Academic Medical Centers and Safety Net Hospitals and Upper Payment Calculation,\"  https://www.medicaid.gov/medicaid/downloads/upl-instructions-qualified-practitioner-services-replacement-new.pdf\n\n41\u2191  MACPAC, \"Medicaid Base and Supplemental Payments to Hospitals,\" April 2024,  https://www.macpac.gov/wp-content/uploads/2024/05/Medicaid-Base-and-Supplemental-Payments-to-Hospitals.pdf\n\n42\u2191  Brian Blase, \"Punishing Conservative States: Payment Cuts to Hospitals Where Federal Spending Is Already Low,\" Paragon Health Institute, December 2021,  https://paragoninstitute.org/medicaid/punishing-conservative-states/\n\n44\u2191  The ACA directs HHS to \"make aggregate reductions in Medicaid DSH allotments.\" While implementation of this provision has been delayed due to amendments\u2014most recently through the Consolidated Appropriations Act of 2024\u2014Tennessee is the only state not subject to impending reduced DSH allotments, as it has allotments specified in Section 1923(f)(6)(A) of the Social Security Act. Alison Mitchell, Medicaid Disproportionate Share Hospital (DSH) Reductions, Congressional Research Service, May 2024,  https://www.congress.gov/crs-product/IF10422\n\n46\u2191 HHS, Office of Inspector General, Tennessee Medicaid Claimed Hundreds of Millions of Federal Funds; MACPAC, \"Medicaid Base and Supplemental Payments to Hospitals,\" April 2024.\n\n48\u2191  MACPAC, \"Delivery System Reform Incentive Payment Programs,\" April 2020,  https://www.macpac.gov/wp-content/uploads/2018/03/Delivery-System-Reform-Incentive-Payment-Programs.pdf\n\n50\u2191  GAO, Medicaid: More Transparency of and Accountability for Supplemental Payments Are Needed, November 26, 2012, https://www.gao.gov/products/gao-13-48; GAO, Medicaid Financing: Federal Oversight Initiative Is Consistent with Medicaid Payment Principles but Needs Greater Transparency, April 30, 2007,  https://www.gao.gov/assets/a258312.html\n\n53\u2191  MACPAC cites UCP payments and DSRIP payments as methods used by states to get this approval. In SFY 2020, Arizona, California, Florida, Kansas, Massachusetts, New Mexico, Tennessee, and Texas had such arrangements. States that used DSRIP payments specifically to continue making supplemental payments through managed care include California, Kansas, Massachusetts, New Jersey, New Mexico, and Texas. MACPAC, \"Medicaid Base and Supplemental Payments to Hospitals,\" May 2022, https://www.macpac.gov/wp-content/uploads/2022/05/Base-and-supplemental-payments-to-hospitals.pdf; MACPAC, \"Delivery System Reform Incentive Payment Programs.\"\n\n54\u2191 CMS, \"Medicaid and Children's Health Insurance Program (CHIP) Programs; Medicaid Managed Care, CHIP Delivered in Managed Care, and Revisions Related to Third Party Liability,\" 81 Fed. Reg. 27498-27901 (May 6, 2016),  https://www.federalregister.gov/d/2016-09581\n\n55\u2191 CMS, \"Medicaid Program; The Use of New or Increased Pass-Through Payments in Medicaid Managed Care Delivery Systems,\" 82 Fed. Reg. 5415-5429 (Jan. 18, 2017),  https://www.federalregister.gov/d/2017-00916\n\n56\u2191  42 C.F.R. \u00a7 438.6(c); CMS, \"State Directed Payments,\"  https://www.medicaid.gov/medicaid/managed-care/guidance/state-directed-payments/index.html\n\n57\u2191  Not all states have the same start date for their rating periods. Because the rating periods for each state used in MACPAC's analysis might not span a 12-month period, the dollar amounts are annualized for a 12-month window.\n\n58\u2191  MACPAC, \"Directed Payments in Medicaid Managed Care,\" June 2023,  https://www.macpac.gov/wp-content/uploads/2023/06/Directed-Payments-in-Medicaid-Managed-Care.pdf\n\n59\u2191  MACPAC, \"Directed Payments in Medicaid Managed Care,\" October 2024,  https://www.macpac.gov/wp-content/uploads/2024/10/Directed-Payments-in-Medicaid-Managed-Care.pdf\n\n63\u2191  MACStats noted that this value is the annualized value for the most recent rating period. These values were calculated from preprints available between February 2023 and August 2024.\n\n64\u2191 CMS, \"Medicaid and Children's Health Insurance Program (CHIP) Managed Care Access, Finance, and Quality,\" 89 Fed. Reg. 41002 (May 10, 2024),  https://www.federalregister.gov/documents/2024/05/10/2024-08085/medicaid-program-medicaid-and-childrens-health-insurance-program-chip-managed-care-access-finance\n\n66\u2191  Chris Jacobs, \"Beginning to Stem the Red Ink Tide: Health Care Concepts for a Conservative Congress,\" Paragon Health Institute, January 2025,  https://paragoninstitute.org/private-health/beginning-to-stem-the-red-ink-tide-health-care-concepts-for-a-conservative-congress/\n\n67\u2191  Asher Wang and Chris Park, \"Directed Payments in Medicaid Managed Care,\" MACPAC, November 1, 2024, p. 13,  https://www.macpac.gov/wp-content/uploads/2024/10/07_October-Slides_Directed-Payments-in-Medicaid-Managed-Care-Slides.pdf\n\n69\u2191  Paragon Health Institute, \"Average Commercial Rate,\"  https://paragoninstitute.org/glossary/average-commercial-rate/\n\n70\u2191  Christopher M. Whaley et al., \"Prices Paid to Hospitals by Private Health Plans,\" RAND Corporation, December 10, 2024,  https://www.rand.org/pubs/research_reports/RRA1144-2-v2.html\n\n71\u2191  Alex Cottrill et al., \"How Many Physicians Have Opted Out of the Medicare Program?,\" KFF, January 17, 2025, https://www.kff.org/medicare/issue-brief/how-many-physicians-have-opted-out-of-the-medicare-program/; David Kendall and Darbin Wofford, \"Tale of Two Hospitals: Why Some Hospitals Succeed and Others Do Not,\" Third Way, August 15, 2024,  https://www.thirdway.org/report/tale-of-two-hospitals-why-some-hospitals-succeed-and-others-do-not\n\n72\u2191  Committee for a Responsible Federal Budget, \"CMS Finalizes Medicaid Rule Likely to Increase Spending,\" May 22, 2024,  https://www.crfb.org/blogs/cms-finalizes-medicaid-rule-likely-increase-spending\n\n73\u2191  A. Mok, et al., 'GOP Lawmakers Reportedly Target Provider Tax Reform, Posing Material Risk to Hospitals,' Barclays, pp. 3, February 2025. Barclays data only includes SDP programs over $100 million and cover inpatient, outpatient, and behavioral health care services. This means the analysis excludes graduate medical education, minimum fee schedules, and value-based payment programs.\n\n74\u2191  GAO, Medicaid Managed Care: Rapid Spending Growth in State Directed Payments Needs Enhanced Oversight and Transparency, December 2023, pp. 16-17,  https://www.gao.gov/assets/gao-24-106202.pdf\n\n76\u2191  The percent of federal share of directed payments does not include funds from provider taxes and IGTs. GAO, Medicaid Managed Care.\n\n77\u2191  Arizona Hospital and Healthcare Association, \"HB2668 Offers to Bring Arizona's Healthcare Providers Relief for Unreimbursed Costs,\" February 13, 2020,  https://www.azhha.org/hb2668_offers_to_bring_arizona_s_healthcare_providers_relief_for_unreimbursed_costs_february_13_2020\n\n78\u2191  Jami Snyder, \"Report on Uncompensated Hospital Costs and Hospital Profitability,\" Arizona Health Care Cost Containment System, October 2021,  https://www.azahcccs.gov/shared/Downloads/Reporting/2021/2021UncompensatedCareAndHospitalProfitabilityReport.pdf\n\n79\u2191  Andrew Mok, \"Estimating Tennessee Medicaid DPP: CYH and ACHC Stand to Benefit Most,\" Barclays, May 12, 2024.\n\n83\u2191 CMS, \"Medicaid Program; Medicaid and Children's Health Insurance Program (CHIP) Managed Care,\" 85 Fed. Reg. 72754-72844 (Nov. 13, 2020), https://www.federalregister.gov/d/2020-24758; CMS, Medicaid Program; Medicaid and Children's Health Insurance Program (CHIP) Managed Care Access, Finance, and Quality,\" 89 Fed. Reg. 41002-41285 (May 10, 2024),  https://www.federalregister.gov/d/2024-08085/\n\n84\u2191  MACPAC, \"Oversight of Managed Care Directed Payments,\" in Report to Congress on Medicaid and CHIP, June 2022, pp. 31-57,  https://www.macpac.gov/wp-content/uploads/2022/06/MACPAC_June2022-WEB-Full-Booklet_FINAL-508-1.pdf\n\n87\u2191  Stacie Weeks, \"Nevada Hospital Assessment Program Bulletin: Requirements for Nevada Private Hospital Assessment and Payment Program,\" Nevada Department of Health and Human Services, August 2023,  https://dhcfp.nv.gov/uploadedFiles/dhcfpnvgov/content/Providers/PI/Nevada%20Private%20Hospital%20Tax%20and%20Payment%20Program%20Bulletin%2023-001.pdf\n\n88\u2191  Stacie Weeks, \"Nevada Hospital Assessment Program Bulletin: Nevada Private Hospital Assessment State Fiscal Year (SFY) 2025 Rate Levied,\" Nevada Department of Health and Human Services, September 2024,  https://dhcfp.nv.gov/uploadedFiles/dhcfpnvgov/content/Providers/PI/24-001_Provider_Assessment_SFY2025_Rate_ADA.pdf\n\n91\u2191  Tabitha Mueller, \"Expanded Hospital Tax Could Boost Medicaid Rates, Fund Behavioral Health Services,\" Nevada Independent, May 2023,  https://thenevadaindependent.com/article/expanded-hospital-tax-could-boost-medicaid-rates-fund-behavioral-health-services\n\n92\u2191  Universal Health Services, 2024 Form 10-K Annual Report,  https://www.sec.gov/ix?doc=/Archives/edgar/data/352915/000095017025027785/uhs-20241231.htm\n\n93\u2191  Matthew Gillmor and Zach Haggerty, \"Healthcare Services 2025 Outlook: Buckle Up Buttercup, Upgrading ACHC to Overweight,\" KeyBanc Capital Markets, January 6, 2025; and Matthew Gillmor and Zach Haggerty, \"Healthcare Services: Recap of Policy Panel with Paragon Health Institute and Capitol Street at KBCM Healthcare Forum,\" KeyBanc Capital Markets, March 23, 2025.\n\n94\u2191  Office of Governor Michelle Lujan Grisham, \"Governor Signs Landmark Bills to Improve Healthcare Affordability and Access,\" March 1, 2024,  https://www.governor.state.nm.us/2024/03/01/governor-signs-landmark-bills-to-improve-healthcare-affordability-and-access/\n\n95\u2191 CMS, \"Approved State Directed Payment Preprints: New Mexico,\" November 25, 2024,  https://www.medicaid.gov/medicaid/managed-care/downloads/NM_VBP.Fee_IPH.OPH6_New_20240701-20241231.pdf\n\n96\u2191  Ardent Health, \"Ardent Health Reports Fourth Quarter 2024 Results,\" February 26, 2025,  https://ir.ardenthealth.com/news/news-details/2025/Ardent-Health-Reports-Fourth-Quarter-2024-Results/default.aspx\n\n98\u2191  Matthew Gillmor and Zach Haggerty, \"Healthcare Services: Recap of Policy Panel with Paragon Health Institute and Capitol Street at KBCM Healthcare Forum,\" KeyBanc Capital Markets, March 23, 2025.\n\n99\u2191  North Carolina Department of Health and Human Services, \"Hospitals Across North Carolina Receive Payments as Part of Medicaid Expansion Legislation,\" November 27, 2023,  https://www.ncdhhs.gov/news/press-releases/2023/11/27/hospitals-across-north-carolina-receive-payments-part-medicaid-expansion-legislation\n\n100\u2191  North Carolina Department of Health and Human Services, \"CMS Approves North Carolina's Medical Debt Relief Incentive Program,\" July 29, 2024,  https://www.ncdhhs.gov/news/press-releases/2024/07/29/cms-approves-north-carolinas-medical-debt-relief-incentive-program\n\n101\u2191  North Carolina Department of Health and Human Services, \"Hospital Payment Program and Medicaid Debt Relief Initiative Approved for Another Year,\" February 5, 2025,  https://www.ncdhhs.gov/news/press-releases/2025/02/05/hospital-payment-program-and-medical-debt-relief-initiative-approved-another-year\n\n102\u2191  National Academy for State Health Policy, \"Hospital Cost Tool: Hospital-Level Dataset (2011-2023),\"  https://tool.nashp.org/\n\n103\u2191  Michelle Crouch and Charlotte Ledger, \"NC Hospitals Set for Massive Payday After Agreeing to Medical Debt Relief Plan,\" NC Health News, September 13, 2024,  https://www.northcarolinahealthnews.org/2024/09/13/nc-hospitals-massive-payday-agreeing-medical-debt-relief-plan/\n\n104\u2191  Barak Richman et al., \"Hospitals Suing Patients: How Hospitals Use N.C. Courts to Collect Medical Debt,\" Duke University School of Law, 2024,  https://scholarship.law.duke.edu/cgi/viewcontent.cgi?article=6961&context=faculty_scholarship\n\n105\u2191  Michelle Crouch and Charlotte Ledger, \"Atrium Health: A Unit of 'Local Government' Like No Other,\" NC Health News, February 5, 2024,  https://www.northcarolinahealthnews.org/2024/02/05/atrium-health-a-unit-of-local-government-like-no-other/\n\n106\u2191  The opinion can be found at  https://appellate.nccourts.org/opinions/?c=1&pdf=39871\n\n107\u2191  The opinion can be found at  https://www.ca4.uscourts.gov/Opinions/192145.P.pdf\n\n108\u2191  American Hospital Association, \"DOJ, Health System Settle Antitrust Lawsuit over Health Plan Contracts,\" November 15, 2018,  https://www.aha.org/news/headline/2018-11-15-doj-health-system-settle-antitrust-lawsuit-over-health-plan-contracts\n\n110\u2191  North Carolina State Treasurer Dale R. Folwell, letter to CMS Administrator Chiquita Brooks-LaSure, June 30, 2023,  https://www.shpnc.org/media/3232/download?attachment\n\n111\u2191  National Association of State Budget Officers (NASBO), \"State Expenditure Reports,\" 2024,  https://www.nasbo.org/reports-data/state-expenditure-report\n\n115\u2191  NASBO, \"State Expenditure Reports,\" 2024. A CRS report provides some helpful background for how NASBO accounts for provider taxes in Medicaid expenditures. These values are reported in the \"other funds\" category along with other revenue types. This does, however, provide a good approximation for how states use provider taxes to supplement their share of Medicaid costs. Mitchell, Medicaid Provider Taxes.\n\n117\u2191  GAO, Medicaid Managed Care: Rapid Spending Growth. Paragon's calculations use data in Table 4 of the GAO report.\n\n118\u2191  GAO, Medicaid Managed Care: Rapid Spending Growth. GAO collected its data from preprint estimates submitted by states to CMS. GAO noted some discrepancies in the data where values for federal and nonfederal shares may not sum to the total value of the program. GAO noted that it made no effort to correct these discrepancies.\n\n119\u2191  Calculated using the $110.2 billion figure provided by MACPAC, \"Directed Payments in Medicaid Managed Care,\" October 2024, which is already annualized for the most recent rating period from February 2023 to August 2024. Applying a 68 percent FMAP rate (as in Table 3) to the total SDP spending results in $75.1 billion in federal spending. Assuming the model from Table 3 holds, 17.0 percent of the total SDP spending actually comes from IGTs and provider taxes; which equals $18.7 billion. Because these monies are just given back to those same providers who paid the tax, we subtract them from the total SDP program spending. This means $91.5 billion in new money was actually exchanged based on states' real contributions. Applying the 68 percent FMAP rate to this new total the federal government should have only paid $62.3 billion, which is $12.8 billion less than what was actually paid. This means money laundering schemes raised the true FMAP 14 points above the assumed FMAP, raising the actual federal share to 82 percent.\n\n120\u2191 Ann Kempski and Ge Bai, \"North Carolina Medicaid Expansion Puts Employers and Workers at Risk for Higher Hospital Prices,\" Health Affairs Forefront, June 21, 2023,  https://www.healthaffairs.org/content/forefront/north-carolina-medicaid-expansion-puts-employers-and-workers-risk-higher-hospital\n\n122\u2191  Department of the Treasury, \"What Is the National Debt?,\" September 30, 2024,  https://fiscaldata.treasury.gov/americas-finance-guide/national-debt/\n\n123\u2191  American Enterprise Institute, \"Improving Health and Health Care: An Agenda for Reform,\" panel discussion, December 9, 2015, 1:55:00ff.,  https://www.aei.org/events/improving-health-and-health-care-an-agenda-for-reform/\n\n124\u2191  Quoted in Washington Post, \"A Much-Needed Medicaid Reform,\" November 29, 2012,  https://www.washingtonpost.com/opinions/a-much-needed-medicaid-reform/2012/11/29/b091d86e-399f-11e2-a263-f0ebffed2f15_story.html\n\n126\u2191  The Bush administration intended to issue regulations in FY2007 that would have lowered the safe harbor threshold from 6 percent to 3 percent, but Congress intervened to block this regulation. In President Obama's FY2013 budget proposal, he proposed reducing the safe harbor threshold from 6 percent to 3.5 percent. President Trump's FY2019 budget proposed incorporating the Graham-Cassidy-Heller-Johnson bill's efforts to reduce the safe harbor threshold from 6 percent to 4 percent. Trump's subsequent budgets included similar language proposing the reduction of financing gimmicks through provider tax reforms. Kaiser Family Foundation, \"The President's FY 2007 Budget Proposal: Overview and Briefing Charts,\" February 27, 2006, https://www.kff.org/wp-content/uploads/2013/01/7472.pdf; Office of Management and Budget, Budget of the U.S. Government: Fiscal Year 2013, p. 36; Office of Management and Budget, Budget of the U.S. Government: Fiscal Year 2019, p. 52,  https://web.archive.org/web/20180508234822/https://www.whitehouse.gov/wp-content/uploads/2018/02/budget-fy2019.pdf\n\n127\u2191  National Commission on Fiscal Responsibility and Reform, \"The Moment of Truth,\" December 2010,  https://www.ssa.gov/history/reports/ObamaFiscal/TheMomentofTruth12_1_2010.pdf\n\n128\u2191  Congressional Budget Office (CBO), \"Options for Reducing the Deficit: 2025 to 2034: Limit State Taxes on Health Care Providers,\" December 12, 2024, https://www.cbo.gov/budget-options/60897. CBO's estimate of the savings of this reform was $612 billion, but its score was prior to a 20 percent surge in provider tax revenue last year. Thus, CBO would likely estimate this reform to be at least $700 billion.\n\n129\u2191  On February 17, 2023, CMS disclosed its intent to end private agreements between providers that circumvent the federal hold-harmless provision for provider taxes and supplemental payments. Texas and Florida sued CMS and Biden administration officials and were subsequently granted a preliminary injunction from the agency's revised enforcement policy. No real progress has been made on the case. Most recently, a motion for summary judgement was filed on November 26, 2024, but a ruling has yet to be made. Susan Harris, \"Medicaid Update: Texas v. Brooks-LaSure,\" Norton Rose Fulbright, https://www.nortonrosefulbright.com/en-us/knowledge/publications/07d791ea/medicaid-update-texas-v-brooks-lasure; \"State of Texas et al v. Brooks-LaSure et al: Court Dockets,\" Bloomberg Law, https://www.bloomberglaw.com/public/desktop/document/StateofTexasetalvBrooksLaSureetalDocketNo623cv00161EDTexApr052023/1?doc_id=X1Q6OJ3PDRO2 (accessed March 1, 2025).\n\n130\u2191  Author's calculations based on December 2024 CBO estimates to update for growth in provider tax revenue. CBO, Options for Reducing the Deficit: 2025 to 2034, p. 10,  https://www.cbo.gov/system/files/2024-12/60557-budget-options.pdf\n\n131\u2191  Alison Mitchell, Medicaid Provider Taxes, Congressional Research Service, updated December 30, 2024, https://www.congress.gov/crs-product/RS22843; Hinton et al., \"As Pandemic-Era Policies End.\"\n\n134\u2191  There are some services that Medicare does not reimburse and Medicaid does, including dental benefits, home- and community-based services, and care at skilled nursing facilities. CMS, \"Mandatory and Optional Medicaid Benefits,\" https://www.medicaid.gov/medicaid/benefits/mandatory-optional-medicaid-benefits/index.html; CMS, \"Your Medicare Coverage,\"  https://www.medicare.gov/coverage\n\n135\u2191  KFF, \"States with an MCO Provider Tax in Place,\"  https://www.kff.org/other/state-indicator/states-with-an-mco-provider-tax-in-place/\n\n136\u2191  Milliman, \"Medicaid Managed Care Financial Results for 2023,\" July 2024,  https://edge.sitecorecloud.io/millimaninc5660-milliman6442-prod27d5-0001/media/Milliman/PDFs/2024-Articles/7-31-24_Medicaid-managed-care-financial-results-2023.pdf\n\n137\u2191  For example, CVS Health, the parent company of Aetna Medicaid, has a wholly owned subsidiary (Cordavis), which commercializes biosimilar drug products. The first product commercialized by Cordavis is Hyrimoz, a biosimilar for Humira, a treatment for rheumatoid arthritis, Crohn's disease, and other autoimmune diseases. U.S. sales for the Humira brand-name biologic were about $1.2 billion in 2024. UnitedHealth Group operates its Medicaid MCO subsidiaries through the UnitedHealthcare brand, and these MCOs are supported by the company's numerous subsidiaries under the Optum name, such as OptumRx, Optum (for claims, backroom operations, technology, data, and analytics), Optum Behavioral Health, OptumInsight, and OptumHealth. Elevance's Medicaid MCOs, like those operating under the Amerigroup or Blue Cross Blue Shield brands in various states, are supported by affiliated service companies that Elevance owns (e.g., CarelonRx, Carelon Behavioral Health, Carelon Medical Benefits Management). Elevance Health also centralizes other administrative functions through its corporate structure. For example, claims processing and information technology systems for its Medicaid plans are often handled through shared services within the company. Centene's subsidiaries commonly serve as subcontractors, providing administrative support, provider network management, analytics, and benefit administration for its Medicaid health plans. Management of pharmacy, behavioral health care, and other specialty services (including provider networks, claims, and utilization control) are often handled for Centene's Medicaid MCO subsidiaries through Centene subsidiaries such as Envolve Pharmacy Solutions, Envolve Vision, Envolve Dental, and Envolve PeopleCare. Centene Health Care Enterprises shared services group provides Centene's Medicaid MCO subsidiaries with capabilities ranging from data analytics to care management solutions and offers MCOs subcontract functions through Centene acquisitions.\n\n138\u2191  State of Michigan Enterprise Procurement, Change Notice Number 9 to Contract Number MA180000000475, p. 15,  https://www.michigan.gov/dtmb/-/media/Project/Websites/dtmb/Procurement/Contracts/015/180000000475.pdf\n\n139\u2191  GAO, Medicaid: States' Efforts to Maximize Federal Reimbursements Highlight Need for Improved Federal Oversight, June 28, 2005,  https://www.gao.gov/products/gao-05-836t\n\n\nCalifornia\u2019s Insurance-Tax Shuffle: How Federal Money Ends Up Paying for Medicaid for Illegal Immigrants\n\n\nMedicaid Financing Reform: Stopping Discrimination Against the Most Vulnerable and Reducing Bias Favoring Wealthy States]]>\n  \n  \n    Using (Off-The-Shelf) AI to Build a Scalable GTM Playbook: Lessons from MedScout\n    https://www.stage2.capital/blog/using-off-the-shelf-ai-to-build-a-scalable-gtm-playbook-lessons-from-medscout\n    readwise:01jr8e43dvezzgq3t6h8w68epv\n    Mon, 07 Apr 2025 15:32:52 +0000\n    stage2.capital\n    \nUsing (Off-The-Shelf) AI to Build a Scalable GTM Playbook: Lessons from MedScout\n\nI meet with startups every day and have looked at hundreds of GTM AI tools - it's a crowded space. At Stage 2 Capital, we've invested in a few, like Momentum, which helps enterprise teams turn conversations into insights. But for early-stage startups running lean, the journey often starts with getting creative using basic, readily available tools.\n\nThat\u2019s what I loved about MedScout\u2019s approach. As part of our 2023 Catalyst program, they built a solid sales playbook using the Science of Scaling framework. But they didn't want it gathering dust - they used AI to turn it into something their team could actually use day-to-day to work more effectively and efficiently.\n\nI had Brian Aoyama, their Head of Marketing, share how they're implementing AI to do this. Their goal was simple, let AI handle the heavy lifting so their team can focus on what humans do best: building genuine connections and closing deals.\n\nThe best part? MedScout didn\u2019t overcomplicate it.\n\nThey started with a simple use case, enhancing the call discovery process, and then kept tweaking and improving based on real results. What started as a few practical experiments has turned into a powerful AI system driving their entire GTM motion.\n\nOk - Let's get into how they did it.\n\nWhy MedScout Focused on Discovery First\n\nDiscovery is hands down my favorite part of the sales process. It's where great sales teams set themselves apart \u2013 playing detective to uncover what's driving their prospects' needs. At Stage 2, we've consistently seen that companies who excel at discovery close larger deals faster and build more predictable revenue engines. Many sales teams rush to showcase their product, thinking that's all it takes to win the deal. But in today's market, that approach falls flat.\n\nGreat discovery requires balancing three critical elements:\n\n \nDepth of understanding. This means getting the full picture of your customers' situation \u2013 their business objectives, challenges, and what's driving their needs. Your reps need to play detective, asking the right questions and reading between the lines to uncover what matters most. \nConsistency of execution (across calls and reps). It's not enough to have one or two reps who excel at discovery. Every conversation needs to maintain the same high standards, following proven frameworks that surface the insights your team needs to be successful.  \nSpeed of follow-through. The insights from discovery calls are most valuable when they're fresh. Waiting days to document key learnings or send follow-up materials dramatically reduces their impact. \n\nThe challenge is that in a startup with limited resources, these three elements are often in tension. The more thorough your discovery and documentation, the slower your follow-up. This is what led MedScout to embrace AI. Brian explained, \"It takes a lot of time and effort to execute our discovery process well. We needed a way to make cycles faster and more reliable without sacrificing quality.\"\n\nThree Stages to AI-Enhanced GTM\n\nStage 1 (Crawl): Start with GTM Playbooks\n\nOutcome: First, nail your foundation.\n\nIn my conversations with startups, I often see teams excited about the promise of AI and eager to jump straight into implementing AI tools. While the enthusiasm is understandable, this approach typically leads to frustration \u2013 overlapping tool capabilities, mounting costs, and low team adoption. Without the right foundation, AI tools can generate a lot of extra \"noise\" that ends up gumming up your GTM motion rather than improving it.\n\nMedScout took a different path, one that I believe every early-stage company should follow: they invested first in building a strong GTM playbook.\n\nA good playbook doesn't just align your team - it's the foundation for growth. At Stage 2, we've seen that companies who document their GTM process can iterate faster and spot what works. MedScout built their playbook during our Catalyst program and kept refining it, using Winning by Design's SPICED framework - though whether you use SPICED, MEDDIC, Challenger, or another approach, what matters is having a systematic way to understand your prospects and capture key information.\n\n\n\n\nExample of SPICED Framework - Credit: Winning by Design\n\n\"You don't want to upend your process to fit off-the-shelf AI tools,\" Brian explains. \"We wanted the process to serve us, not the other way around. So we used our GTM playbooks as a starting point, then layered in AI to execute those playbooks more consistently and effectively than we could before.\"\n\nWhen you take the time to document your GTM fundamentals properly, it's much easier to start layering AI into your workflows. Let's walk through how MedScout used AI to eliminate the biggest bottlenecks in their discovery process.\n\nStage 2 (Walk): Basic GTM AI Implementation\n\nOnce you\u2019ve documented your GTM fundamentals, it\u2019s fast and easy to start enhancing your process with AI.\n\nWe'll look at two approaches:\n\n \nQuick Start: Simple steps you can implement right now. \nOptimize & Expand: The step-by-step process that MedScout followed to level up their entire discovery process.  \n\n\n Quick Start: Put Your Playbooks to Work\n\n\nOutcome: Create an AI-powered GTM coach for your team in under 5 minutes.\n\nThe quickest way to boost your GTM with AI is straightforward: feed your existing playbook into tools like Claude, ChatGPT, or Perplexity. Just this simple step helps these AI tools understand your company and approach, leading to much better outputs.\n\n\"When we first started, it helped to think about our AI tools as new team members \u2013 extremely productive but lacking context or direction,\" Brian explains. \"The more context you can give them about your company, objectives, and expectations, the better your results will be.\"\n\n\n\nClaude AI, trained on MedScout\u2019s GTM playbooks, can analyze discovery calls and provide guidance and coaching based on your business and sales framework. \n\nWhen you take advantage of this capability, you'll see immediate improvements in everything from prospect research to follow-up materials.\n\nQuick tip: If you haven't completed your GTM playbooks yet, use ChatGPT to create a simple one-page document capturing critical information about your company, target customers, and value props. Some tools will even analyze your website to draft this for you. While not comprehensive, this gives you a foundation to build upon.\n\nOptimize & Expand: Build a Custom Discovery Prompt\n\nOutcome: Deliver thorough, personalized follow-up within minutes of every call.\n\nAfter getting familiar with general-purpose AI tools, the next step is creating specific prompts that strengthen key parts of your GTM process.\n\nMedScout focused on the discovery phase as their biggest opportunity. They built a custom prompt that combined their playbook and discovery frameworks, starting with a basic goal: create better sales call summaries than their automated software.\n\nWant to build better AI prompts? Let AI help. \"We used AI to help us build better AI,\" Brian explains. \"We just told it what we wanted to achieve and what information we needed, and asked it to create a template. The key was being specific about our goals, what data to capture, and how we wanted it structured.\"\n\nTheir first implementation was intentionally simple and manual. By using actual discovery calls as their testing ground, the team could evaluate and refine their approach multiple times each day. After each discovery call, reps would:\n\n \nCopy and paste the sales call transcript into Claude or ChatGPT \nDrag and drop the latest version of the shared discovery prompt into the chat \nReview the AI output and provide feedback. Where did it succeed? Where did it fall short? \nPaste the final notes into the CRM \n\nThe team revised the prompt every day for 2 weeks. Eventually, the prompt grew to include sophisticated components like:\n\n \nProspect Voice: How to handle prospect quotes: cleaning up filler words while preserving the client\u2019s distinct voice, terminology and key phrases \nReading Between the Lines: How to make informed inferences based on unstated or implied topics (while clearly marking them with confidence levels) \nCustomer First: Improving focus on the prospect's perspective rather than the sales rep's talk track \nRep Coaching: Scoring the rep's discovery performance and providing coaching feedback \n\nThis collaborative process showed two significant benefits beyond just improving the prompt.\n\n \nIt built the team's trust in AI-generated outputs. While early results weren't impressive, the rapid improvement cycle helped overcome initial skepticism.  \nIt strengthened the team's discovery skills. The team became more attuned to what good discovery looks like and how to capture key insights systematically. \n\nHere\u2019s how MedScout structures its prompt to transform its sales playbook and team insights into a powerful AI tool. Use this template as inspiration for your own sales process.\n\nINTRO & ROLE\n\n\n\n\nOpen your prompt by stating exactly what outcome you want\u2014such as a SPICED discovery call analysis\u2014and why it matters. This immediate clarity helps the AI target your core needs from the start. Then define the AI\u2019s role (e.g., \u201cYou are a senior sales strategist\u201d) so responses match the level of expertise you expect.\n\nCOMPANY & CONTEXT\n\n\n\n\nProvide brief details on your product, target customers, and market positioning so the AI can interpret transcript references in the right context. Tying the analysis to your unique value proposition and ICP avoids generic output and ensures recommendations align with what truly sets you apart.\n\nANALYSIS FRAMEWORK\n\n\n\n\nIntroduce your chosen framework\u2014whether SPICED, MEDDPICC, or another\u2014and outline how each element should be examined. Then detail a simple step-by-step process (like extracting key facts, grouping them by SPICED element, and suggesting next steps) so the AI covers every important point without skipping or merging crucial details.\n\nGUIDELINES\n\nClarify how you want the AI to handle uncertain data, flag missing information, and optionally coach the sales rep. This maintains consistency and trustworthiness: the AI can highlight where the conversation falls short, rate completeness, and provide targeted feedback for improvement.\n\nOUTPUT FORMAT\n\n\n\n\nFinally, specify how the results should look, whether it\u2019s a bullet-point summary or a detailed SPICED breakdown with quotes. If you can share an example of the final format, the AI will know exactly how to structure its response for seamless handoff to your CRM or other team members.\n\nSuccessful Prompts Aren\u2019t Without Challenges \n\nThe custom prompt approach proved highly successful. When tested against specialized products in the market, MedScout's homegrown tool consistently outperformed more expensive alternatives. More importantly, the sales team had fully embraced it \u2013 every rep was using the prompt daily and trusted its output.\n\nThis success, however, highlighted new challenges. The prompt had grown to 35 pages after months of refinement, making updates increasingly difficult. The manual copy-and-paste workflow, while valuable for early learning, now felt cumbersome. MedScout was ready for their next evolution: automating these proven processes to create a truly AI-native GTM motion.\n\nStage 3 (Run): Evolving into an AI-native GTM team\n\nOutcome: Build a GTM system that gets smarter with every customer conversation.\n\nQuick sidebar: I love the crawl-walk-run approach. It gives you time to work out the bugs and build trust with your team (and we all know how skeptical sales teams can be). My advice? Don't jump straight to automating workflows until you've earned your team's trust and you're consistently getting high-quality output.\n\nReady to level up? Here\u2019s how MedScout did it.\n\nAutomate AI Workflows\n\nThe first thing MedScout did was break its extensive prompt into discrete, specialized components. Then, using accessible tools like Zapier and Clay, they connected these components into automated workflows. And they didn't need expensive specialized software \u2013 they used the same tools as before, just connected intelligently.\n\n\"Our manual process had served its purpose, helping us refine and validate our approach,\" Brian explains. \"But the repetitive steps were taking time away from actual customer interactions. This friction helped us identify exactly which elements to automate first.\"\n\nThis automation dramatically improved their discovery process. Sales reps could now focus entirely on customer conversations, knowing that detailed call summaries, SPICED framework analysis, and personalized follow-up materials would be ready in moments. This consistent, rapid follow-up accelerated their pipeline velocity.\n\n\n\n\nThe Next Iteration: Augmenting the Team with AI Agents\n\nTraditional automation platforms like Zapier require pre-programmed sequential steps, following rigid \"if this, then that\" logic. But GTM work requires flexibility, which is why MedScout is now exploring AI agents as their next evolution.\n\nAI agents function as digital team members who understand your GTM playbooks, think contextually, and work directly within your tech stack. Unlike fixed automation workflows, agents can determine the best approach based on context and collaborate with team members to achieve objectives.\n\nMedScout is now using Toolflow.ai to build AI agents trained specifically on their specific GTM playbooks. These agents access the team's tech stack to handle sophisticated tasks: researching prospects, analyzing discovery calls through the SPICED framework, enriching CRM data, and creating tailored sales enablement materials.\n\n\"We're not looking for agents to replace any functions on our team,\" Brian explains. \"Human judgment remains critical. Instead, we want to augment our team with AI assistants that help execute our playbooks more consistently and at a greater scale than previously possible.\"\n\n\n\n\nThe impact of this AI-native approach is already visible in three areas:\n\n \nCustomer Intelligence: A smarter customer data model. Each interaction adds context, helping MedScout engage more effectively throughout the customer journey. \nCross-Team Learning: Insights flow automatically between teams. Product learns about pain points, Customer Success gets rich context for handoffs, and Marketing sees what resonates in discovery calls. \nScaling: AI handles routine tasks, freeing the team to focus on work that needs human judgment. \n\nKey Principles for GTM AI Success\n\nWhat's exciting about MedScout's story is how they built sophisticated AI capabilities starting with basic tools. Through quick iterations, they got there faster than you might think - and this is huge unlock startups.\n\nThe market's creating a perfect opportunity: while big companies are stuck wrestling with legacy systems and resistance to change, smaller teams can build AI into their DNA from the start. We're seeing this play out across our Stage 2 portfolio - companies taking a thoughtful approach to AI are actually outmaneuvering much larger competitors.\n\nFive principles that enabled MedScout's success:\n\n \nStart where you can learn fastest. MedScout chose discovery calls because they could test improvements multiple times per day and see immediate impact on deal progression. This rapid feedback loop accelerated their learning and helped them avoid common implementation pitfalls. \nBuild team trust through visible iteration. By starting with manual processes, MedScout's team could see and shape how their AI tools evolved. This transparency was crucial \u2013 by the time they moved to automation, the team trusted the system because they had helped build it. \nKeep humans at the center. AI should handle mechanical tasks like note-taking, framework analysis, and quote extraction, freeing your team to focus on what matters most: building relationships and making strategic decisions. The goal isn't to replace human judgment; it's to amplify it. \nFocus on cross-functional value creation. The real power of AI in GTM comes from building systems that help your entire organization learn and improve. When MedScout automated their discovery process, they didn't just make individual reps more productive \u2013 they created a systematic way to capture insights that benefit their product, marketing, and customer success teams. \nEstablish a strong foundation before laying in AI. Start with clear GTM playbooks and processes, then layer in AI thoughtfully. This foundation ensures your AI tools enhance rather than complicate your GTM motion, enabling you to iterate quickly toward more sophisticated capabilities. \n\nGood Luck!\n\nA huge thank you to Brian Aoyama, head of marketing at Medscout, a Stage 2 Portfolio Company, for sharing his insights and learnings with us. We\u2019re all figuring this out together, and I can\u2019t wait to see what comes next!\n\nThroughout her operating career, Mandy hired & mentored hundreds of sales professionals and built & scaled some of the fastest-growing B2B marketplace and SaaS organizations. Mandy is currently an Investment Partner at Stage 2 Capital.]]>\n    \nUsing (Off-The-Shelf) AI to Build a Scalable GTM Playbook: Lessons from MedScout\n\nI meet with startups every day and have looked at hundreds of GTM AI tools - it's a crowded space. At Stage 2 Capital, we've invested in a few, like Momentum, which helps enterprise teams turn conversations into insights. But for early-stage startups running lean, the journey often starts with getting creative using basic, readily available tools.\n\nThat\u2019s what I loved about MedScout\u2019s approach. As part of our 2023 Catalyst program, they built a solid sales playbook using the Science of Scaling framework. But they didn't want it gathering dust - they used AI to turn it into something their team could actually use day-to-day to work more effectively and efficiently.\n\nI had Brian Aoyama, their Head of Marketing, share how they're implementing AI to do this. Their goal was simple, let AI handle the heavy lifting so their team can focus on what humans do best: building genuine connections and closing deals.\n\nThe best part? MedScout didn\u2019t overcomplicate it.\n\nThey started with a simple use case, enhancing the call discovery process, and then kept tweaking and improving based on real results. What started as a few practical experiments has turned into a powerful AI system driving their entire GTM motion.\n\nOk - Let's get into how they did it.\n\nWhy MedScout Focused on Discovery First\n\nDiscovery is hands down my favorite part of the sales process. It's where great sales teams set themselves apart \u2013 playing detective to uncover what's driving their prospects' needs. At Stage 2, we've consistently seen that companies who excel at discovery close larger deals faster and build more predictable revenue engines. Many sales teams rush to showcase their product, thinking that's all it takes to win the deal. But in today's market, that approach falls flat.\n\nGreat discovery requires balancing three critical elements:\n\n \nDepth of understanding. This means getting the full picture of your customers' situation \u2013 their business objectives, challenges, and what's driving their needs. Your reps need to play detective, asking the right questions and reading between the lines to uncover what matters most. \nConsistency of execution (across calls and reps). It's not enough to have one or two reps who excel at discovery. Every conversation needs to maintain the same high standards, following proven frameworks that surface the insights your team needs to be successful.  \nSpeed of follow-through. The insights from discovery calls are most valuable when they're fresh. Waiting days to document key learnings or send follow-up materials dramatically reduces their impact. \n\nThe challenge is that in a startup with limited resources, these three elements are often in tension. The more thorough your discovery and documentation, the slower your follow-up. This is what led MedScout to embrace AI. Brian explained, \"It takes a lot of time and effort to execute our discovery process well. We needed a way to make cycles faster and more reliable without sacrificing quality.\"\n\nThree Stages to AI-Enhanced GTM\n\nStage 1 (Crawl): Start with GTM Playbooks\n\nOutcome: First, nail your foundation.\n\nIn my conversations with startups, I often see teams excited about the promise of AI and eager to jump straight into implementing AI tools. While the enthusiasm is understandable, this approach typically leads to frustration \u2013 overlapping tool capabilities, mounting costs, and low team adoption. Without the right foundation, AI tools can generate a lot of extra \"noise\" that ends up gumming up your GTM motion rather than improving it.\n\nMedScout took a different path, one that I believe every early-stage company should follow: they invested first in building a strong GTM playbook.\n\nA good playbook doesn't just align your team - it's the foundation for growth. At Stage 2, we've seen that companies who document their GTM process can iterate faster and spot what works. MedScout built their playbook during our Catalyst program and kept refining it, using Winning by Design's SPICED framework - though whether you use SPICED, MEDDIC, Challenger, or another approach, what matters is having a systematic way to understand your prospects and capture key information.\n\n\n\n\nExample of SPICED Framework - Credit: Winning by Design\n\n\"You don't want to upend your process to fit off-the-shelf AI tools,\" Brian explains. \"We wanted the process to serve us, not the other way around. So we used our GTM playbooks as a starting point, then layered in AI to execute those playbooks more consistently and effectively than we could before.\"\n\nWhen you take the time to document your GTM fundamentals properly, it's much easier to start layering AI into your workflows. Let's walk through how MedScout used AI to eliminate the biggest bottlenecks in their discovery process.\n\nStage 2 (Walk): Basic GTM AI Implementation\n\nOnce you\u2019ve documented your GTM fundamentals, it\u2019s fast and easy to start enhancing your process with AI.\n\nWe'll look at two approaches:\n\n \nQuick Start: Simple steps you can implement right now. \nOptimize & Expand: The step-by-step process that MedScout followed to level up their entire discovery process.  \n\n\n Quick Start: Put Your Playbooks to Work\n\n\nOutcome: Create an AI-powered GTM coach for your team in under 5 minutes.\n\nThe quickest way to boost your GTM with AI is straightforward: feed your existing playbook into tools like Claude, ChatGPT, or Perplexity. Just this simple step helps these AI tools understand your company and approach, leading to much better outputs.\n\n\"When we first started, it helped to think about our AI tools as new team members \u2013 extremely productive but lacking context or direction,\" Brian explains. \"The more context you can give them about your company, objectives, and expectations, the better your results will be.\"\n\n\n\nClaude AI, trained on MedScout\u2019s GTM playbooks, can analyze discovery calls and provide guidance and coaching based on your business and sales framework. \n\nWhen you take advantage of this capability, you'll see immediate improvements in everything from prospect research to follow-up materials.\n\nQuick tip: If you haven't completed your GTM playbooks yet, use ChatGPT to create a simple one-page document capturing critical information about your company, target customers, and value props. Some tools will even analyze your website to draft this for you. While not comprehensive, this gives you a foundation to build upon.\n\nOptimize & Expand: Build a Custom Discovery Prompt\n\nOutcome: Deliver thorough, personalized follow-up within minutes of every call.\n\nAfter getting familiar with general-purpose AI tools, the next step is creating specific prompts that strengthen key parts of your GTM process.\n\nMedScout focused on the discovery phase as their biggest opportunity. They built a custom prompt that combined their playbook and discovery frameworks, starting with a basic goal: create better sales call summaries than their automated software.\n\nWant to build better AI prompts? Let AI help. \"We used AI to help us build better AI,\" Brian explains. \"We just told it what we wanted to achieve and what information we needed, and asked it to create a template. The key was being specific about our goals, what data to capture, and how we wanted it structured.\"\n\nTheir first implementation was intentionally simple and manual. By using actual discovery calls as their testing ground, the team could evaluate and refine their approach multiple times each day. After each discovery call, reps would:\n\n \nCopy and paste the sales call transcript into Claude or ChatGPT \nDrag and drop the latest version of the shared discovery prompt into the chat \nReview the AI output and provide feedback. Where did it succeed? Where did it fall short? \nPaste the final notes into the CRM \n\nThe team revised the prompt every day for 2 weeks. Eventually, the prompt grew to include sophisticated components like:\n\n \nProspect Voice: How to handle prospect quotes: cleaning up filler words while preserving the client\u2019s distinct voice, terminology and key phrases \nReading Between the Lines: How to make informed inferences based on unstated or implied topics (while clearly marking them with confidence levels) \nCustomer First: Improving focus on the prospect's perspective rather than the sales rep's talk track \nRep Coaching: Scoring the rep's discovery performance and providing coaching feedback \n\nThis collaborative process showed two significant benefits beyond just improving the prompt.\n\n \nIt built the team's trust in AI-generated outputs. While early results weren't impressive, the rapid improvement cycle helped overcome initial skepticism.  \nIt strengthened the team's discovery skills. The team became more attuned to what good discovery looks like and how to capture key insights systematically. \n\nHere\u2019s how MedScout structures its prompt to transform its sales playbook and team insights into a powerful AI tool. Use this template as inspiration for your own sales process.\n\nINTRO & ROLE\n\n\n\n\nOpen your prompt by stating exactly what outcome you want\u2014such as a SPICED discovery call analysis\u2014and why it matters. This immediate clarity helps the AI target your core needs from the start. Then define the AI\u2019s role (e.g., \u201cYou are a senior sales strategist\u201d) so responses match the level of expertise you expect.\n\nCOMPANY & CONTEXT\n\n\n\n\nProvide brief details on your product, target customers, and market positioning so the AI can interpret transcript references in the right context. Tying the analysis to your unique value proposition and ICP avoids generic output and ensures recommendations align with what truly sets you apart.\n\nANALYSIS FRAMEWORK\n\n\n\n\nIntroduce your chosen framework\u2014whether SPICED, MEDDPICC, or another\u2014and outline how each element should be examined. Then detail a simple step-by-step process (like extracting key facts, grouping them by SPICED element, and suggesting next steps) so the AI covers every important point without skipping or merging crucial details.\n\nGUIDELINES\n\nClarify how you want the AI to handle uncertain data, flag missing information, and optionally coach the sales rep. This maintains consistency and trustworthiness: the AI can highlight where the conversation falls short, rate completeness, and provide targeted feedback for improvement.\n\nOUTPUT FORMAT\n\n\n\n\nFinally, specify how the results should look, whether it\u2019s a bullet-point summary or a detailed SPICED breakdown with quotes. If you can share an example of the final format, the AI will know exactly how to structure its response for seamless handoff to your CRM or other team members.\n\nSuccessful Prompts Aren\u2019t Without Challenges \n\nThe custom prompt approach proved highly successful. When tested against specialized products in the market, MedScout's homegrown tool consistently outperformed more expensive alternatives. More importantly, the sales team had fully embraced it \u2013 every rep was using the prompt daily and trusted its output.\n\nThis success, however, highlighted new challenges. The prompt had grown to 35 pages after months of refinement, making updates increasingly difficult. The manual copy-and-paste workflow, while valuable for early learning, now felt cumbersome. MedScout was ready for their next evolution: automating these proven processes to create a truly AI-native GTM motion.\n\nStage 3 (Run): Evolving into an AI-native GTM team\n\nOutcome: Build a GTM system that gets smarter with every customer conversation.\n\nQuick sidebar: I love the crawl-walk-run approach. It gives you time to work out the bugs and build trust with your team (and we all know how skeptical sales teams can be). My advice? Don't jump straight to automating workflows until you've earned your team's trust and you're consistently getting high-quality output.\n\nReady to level up? Here\u2019s how MedScout did it.\n\nAutomate AI Workflows\n\nThe first thing MedScout did was break its extensive prompt into discrete, specialized components. Then, using accessible tools like Zapier and Clay, they connected these components into automated workflows. And they didn't need expensive specialized software \u2013 they used the same tools as before, just connected intelligently.\n\n\"Our manual process had served its purpose, helping us refine and validate our approach,\" Brian explains. \"But the repetitive steps were taking time away from actual customer interactions. This friction helped us identify exactly which elements to automate first.\"\n\nThis automation dramatically improved their discovery process. Sales reps could now focus entirely on customer conversations, knowing that detailed call summaries, SPICED framework analysis, and personalized follow-up materials would be ready in moments. This consistent, rapid follow-up accelerated their pipeline velocity.\n\n\n\n\nThe Next Iteration: Augmenting the Team with AI Agents\n\nTraditional automation platforms like Zapier require pre-programmed sequential steps, following rigid \"if this, then that\" logic. But GTM work requires flexibility, which is why MedScout is now exploring AI agents as their next evolution.\n\nAI agents function as digital team members who understand your GTM playbooks, think contextually, and work directly within your tech stack. Unlike fixed automation workflows, agents can determine the best approach based on context and collaborate with team members to achieve objectives.\n\nMedScout is now using Toolflow.ai to build AI agents trained specifically on their specific GTM playbooks. These agents access the team's tech stack to handle sophisticated tasks: researching prospects, analyzing discovery calls through the SPICED framework, enriching CRM data, and creating tailored sales enablement materials.\n\n\"We're not looking for agents to replace any functions on our team,\" Brian explains. \"Human judgment remains critical. Instead, we want to augment our team with AI assistants that help execute our playbooks more consistently and at a greater scale than previously possible.\"\n\n\n\n\nThe impact of this AI-native approach is already visible in three areas:\n\n \nCustomer Intelligence: A smarter customer data model. Each interaction adds context, helping MedScout engage more effectively throughout the customer journey. \nCross-Team Learning: Insights flow automatically between teams. Product learns about pain points, Customer Success gets rich context for handoffs, and Marketing sees what resonates in discovery calls. \nScaling: AI handles routine tasks, freeing the team to focus on work that needs human judgment. \n\nKey Principles for GTM AI Success\n\nWhat's exciting about MedScout's story is how they built sophisticated AI capabilities starting with basic tools. Through quick iterations, they got there faster than you might think - and this is huge unlock startups.\n\nThe market's creating a perfect opportunity: while big companies are stuck wrestling with legacy systems and resistance to change, smaller teams can build AI into their DNA from the start. We're seeing this play out across our Stage 2 portfolio - companies taking a thoughtful approach to AI are actually outmaneuvering much larger competitors.\n\nFive principles that enabled MedScout's success:\n\n \nStart where you can learn fastest. MedScout chose discovery calls because they could test improvements multiple times per day and see immediate impact on deal progression. This rapid feedback loop accelerated their learning and helped them avoid common implementation pitfalls. \nBuild team trust through visible iteration. By starting with manual processes, MedScout's team could see and shape how their AI tools evolved. This transparency was crucial \u2013 by the time they moved to automation, the team trusted the system because they had helped build it. \nKeep humans at the center. AI should handle mechanical tasks like note-taking, framework analysis, and quote extraction, freeing your team to focus on what matters most: building relationships and making strategic decisions. The goal isn't to replace human judgment; it's to amplify it. \nFocus on cross-functional value creation. The real power of AI in GTM comes from building systems that help your entire organization learn and improve. When MedScout automated their discovery process, they didn't just make individual reps more productive \u2013 they created a systematic way to capture insights that benefit their product, marketing, and customer success teams. \nEstablish a strong foundation before laying in AI. Start with clear GTM playbooks and processes, then layer in AI thoughtfully. This foundation ensures your AI tools enhance rather than complicate your GTM motion, enabling you to iterate quickly toward more sophisticated capabilities. \n\nGood Luck!\n\nA huge thank you to Brian Aoyama, head of marketing at Medscout, a Stage 2 Portfolio Company, for sharing his insights and learnings with us. We\u2019re all figuring this out together, and I can\u2019t wait to see what comes next!\n\nThroughout her operating career, Mandy hired & mentored hundreds of sales professionals and built & scaled some of the fastest-growing B2B marketplace and SaaS organizations. Mandy is currently an Investment Partner at Stage 2 Capital.]]>\n  \n  \n    wsj.com\n    https://www.wsj.com/economy/the-first-victim-of-trumps-trade-war-michigans-economy-ea6ff8b2?st=vxerJf\n    readwise:01jr8cd8nb4m1argavre8q9gfj\n    Mon, 07 Apr 2025 15:02:55 +0000\n    WSJ\n    ]]>\n    ]]>\n  \n  \n    Palantir and the NHS\n    https://blog.palantir.com/palantir-and-the-nhs-dd1362982fa9\n    readwise:01jqy3vqhaa10ycjxmpje1kwfk\n    Thu, 03 Apr 2025 15:21:07 +0000\n    Medium\n    \n\nToday, the NHS has chosen Palantir, supported by a group of companies including Accenture, PwC, NECS and Carnall Farrar, to help deliver a Federated Data Platform (FDP). AWS and Microsoft will provide cloud platform services.\n\nThe FDP will improve patient care by bringing together the information needed to plan and deliver care, and reduce the administrative burden on staff.\n\nWe are humbled that we\u2019ve been chosen to support this critical programme. It is the culmination of 20 years developing software that integrates complex and sensitive data in a way that delivers better outcomes, while protecting privacy, ensuring security and placing the customer in full control.\n\nWe know that working with an institution as important as the NHS on an issue as sensitive as data-sharing makes it critical for us to provide trust and confidence in how our software works and how we operate as a company.\n\nThis blogpost, the first in a series, explains some of the fundamental principles on which our business and our software have been built.\n\nPalantir is a software company: we build software platforms which enable organisations to better manage the data that they already hold.\n\nPalantir is not, and never has been, in the business of collecting, mining or selling data. We are not a \u2018data broker\u2019 or a data aggregator. Unlike many tech companies, our business model is not based on the monetisation of personal data.\n\nPalantir is a company that builds AI-enabled digital infrastructure for data-driven operations and decision-making. We license our software to organisations, who receive their own secure instances of our platforms in which to conduct their own work on the data they already hold.\n\nOur software then helps those organisations bring the right data together at the right time to answer complex questions and make intelligent decisions. This is particularly valuable when existing systems are fragmented, and essential information is held in silos that can\u2019t communicate with each other.\n\nPalantir is a \u2018data processor\u2019 not a \u2018data controller\u2019.\n\nWith regards to customer data, we act as a data processor, not a data controller. Our customers license our software and decide how they want to use it. They retain full control and ownership of the data they hold, defining what can and cannot be done with that data. Palantir is granted no rights to that data and can only carry out activity that we are instructed to by the customer. Many of our contracts are public and set all this out clearly.\n\nWe do not and cannot reuse or transfer our customers\u2019 data for our own purposes. Attempting to profit from customer data in this way would be illegal and would undermine the trust that is necessary to work in the sensitive environments in which we have built our business.\n\nPalantir is a world leader in data protection and security.\n\nFor 20 years, Palantir has been consistently trusted by the most critical organisations operating in some of the most sensitive information environments in the world. That is because our security and governance capabilities are world-leading. For many of these organisations, data protection and security can be a matter of life and death.\n\nDuring that 20-year period, we\u2019ve pioneered innovations such as Purpose-based Access Controls which have further reinforced our leadership in this space. Purpose-based Access Controls ensure that individuals within an organisation are only granted access to the information that they need to do their job. They also ensure that, at any point, an auditor can understand not just who has access to what data, but also why they were given access.\n\nPalantir strives to help critical institutions solve complex challenges.\n\nAs a business, our mission is to help critical institutions solve complex and important challenges. That is what led to our partnership with the World Food Programme, our involvement in the resettlement of Ukrainian refugees and our support for the Ukrainian Prosecutor-General\u2019s investigation into war crimes. It is also what led us to first work with the NHS.\n\nDuring COVID, our software helped ensure that ventilators and PPE were delivered to the right place at the right time. It then supported the vaccine rollout \u2014 widely acknowledged as the most successful in Europe, and about which the King\u2019s Fund commented:\n\n\n\u201cFoundry has been a key tool in the NHS\u2019s biggest ever exercise in operational data integration \u2026 It provided, in the repeated words of a number of those interviewed, \u2018a single source of truth\u2019 for what was happening within the vaccine roll-out. From where supplies were, to who had been jabbed, and where uptake was low \u2026 \u2018It meant,\u2019 as one interviewee put it, \u2018that the data that could be seen by the vaccination sites, was the same version of the truth as was being seen by Skipton House [NHS England\u2019s headquarters] by No 10 and by the Department of Health and Social Care.\u2019\u201d\n\nSince the pandemic, a growing number of NHS trusts have used the same software to reduce the care backlog. At Chelsea and Westminster NHS Foundation Trust, where it was first deployed, it helped bring down the inpatient waiting list by 28 per cent, with operations cancelled on the day subsequently falling by half. More recently, it has increased operating theatre usage across 22 NHS trusts by an average of 6.3 per cent.\n\nJeffrey Ahmed, consultant gynaecologist at Chelsea and Westminster Hospital NHS Foundation Trust described the software as \u201ca game-changer for me \u2014 it\u2019s helping me to do my job faster and more efficiently, and has reduced my administrative burden.\u201d\n\nGiven our mission, today\u2019s announcement is a source of immense pride to everyone here at Palantir. We know there is no more critical institution in the UK than the NHS. And we know that there is no more important challenge than helping it deliver better care for patients.\n\nFind out more about our work with the NHS here: https://www.palantir.com/uk/healthcare/.\n\nAuthors\n\nTom McArdle and Joanna Peller, Co-Health Leads at Palantir]]>\n    \n\nToday, the NHS has chosen Palantir, supported by a group of companies including Accenture, PwC, NECS and Carnall Farrar, to help deliver a Federated Data Platform (FDP). AWS and Microsoft will provide cloud platform services.\n\nThe FDP will improve patient care by bringing together the information needed to plan and deliver care, and reduce the administrative burden on staff.\n\nWe are humbled that we\u2019ve been chosen to support this critical programme. It is the culmination of 20 years developing software that integrates complex and sensitive data in a way that delivers better outcomes, while protecting privacy, ensuring security and placing the customer in full control.\n\nWe know that working with an institution as important as the NHS on an issue as sensitive as data-sharing makes it critical for us to provide trust and confidence in how our software works and how we operate as a company.\n\nThis blogpost, the first in a series, explains some of the fundamental principles on which our business and our software have been built.\n\nPalantir is a software company: we build software platforms which enable organisations to better manage the data that they already hold.\n\nPalantir is not, and never has been, in the business of collecting, mining or selling data. We are not a \u2018data broker\u2019 or a data aggregator. Unlike many tech companies, our business model is not based on the monetisation of personal data.\n\nPalantir is a company that builds AI-enabled digital infrastructure for data-driven operations and decision-making. We license our software to organisations, who receive their own secure instances of our platforms in which to conduct their own work on the data they already hold.\n\nOur software then helps those organisations bring the right data together at the right time to answer complex questions and make intelligent decisions. This is particularly valuable when existing systems are fragmented, and essential information is held in silos that can\u2019t communicate with each other.\n\nPalantir is a \u2018data processor\u2019 not a \u2018data controller\u2019.\n\nWith regards to customer data, we act as a data processor, not a data controller. Our customers license our software and decide how they want to use it. They retain full control and ownership of the data they hold, defining what can and cannot be done with that data. Palantir is granted no rights to that data and can only carry out activity that we are instructed to by the customer. Many of our contracts are public and set all this out clearly.\n\nWe do not and cannot reuse or transfer our customers\u2019 data for our own purposes. Attempting to profit from customer data in this way would be illegal and would undermine the trust that is necessary to work in the sensitive environments in which we have built our business.\n\nPalantir is a world leader in data protection and security.\n\nFor 20 years, Palantir has been consistently trusted by the most critical organisations operating in some of the most sensitive information environments in the world. That is because our security and governance capabilities are world-leading. For many of these organisations, data protection and security can be a matter of life and death.\n\nDuring that 20-year period, we\u2019ve pioneered innovations such as Purpose-based Access Controls which have further reinforced our leadership in this space. Purpose-based Access Controls ensure that individuals within an organisation are only granted access to the information that they need to do their job. They also ensure that, at any point, an auditor can understand not just who has access to what data, but also why they were given access.\n\nPalantir strives to help critical institutions solve complex challenges.\n\nAs a business, our mission is to help critical institutions solve complex and important challenges. That is what led to our partnership with the World Food Programme, our involvement in the resettlement of Ukrainian refugees and our support for the Ukrainian Prosecutor-General\u2019s investigation into war crimes. It is also what led us to first work with the NHS.\n\nDuring COVID, our software helped ensure that ventilators and PPE were delivered to the right place at the right time. It then supported the vaccine rollout \u2014 widely acknowledged as the most successful in Europe, and about which the King\u2019s Fund commented:\n\n\n\u201cFoundry has been a key tool in the NHS\u2019s biggest ever exercise in operational data integration \u2026 It provided, in the repeated words of a number of those interviewed, \u2018a single source of truth\u2019 for what was happening within the vaccine roll-out. From where supplies were, to who had been jabbed, and where uptake was low \u2026 \u2018It meant,\u2019 as one interviewee put it, \u2018that the data that could be seen by the vaccination sites, was the same version of the truth as was being seen by Skipton House [NHS England\u2019s headquarters] by No 10 and by the Department of Health and Social Care.\u2019\u201d\n\nSince the pandemic, a growing number of NHS trusts have used the same software to reduce the care backlog. At Chelsea and Westminster NHS Foundation Trust, where it was first deployed, it helped bring down the inpatient waiting list by 28 per cent, with operations cancelled on the day subsequently falling by half. More recently, it has increased operating theatre usage across 22 NHS trusts by an average of 6.3 per cent.\n\nJeffrey Ahmed, consultant gynaecologist at Chelsea and Westminster Hospital NHS Foundation Trust described the software as \u201ca game-changer for me \u2014 it\u2019s helping me to do my job faster and more efficiently, and has reduced my administrative burden.\u201d\n\nGiven our mission, today\u2019s announcement is a source of immense pride to everyone here at Palantir. We know there is no more critical institution in the UK than the NHS. And we know that there is no more important challenge than helping it deliver better care for patients.\n\nFind out more about our work with the NHS here: https://www.palantir.com/uk/healthcare/.\n\nAuthors\n\nTom McArdle and Joanna Peller, Co-Health Leads at Palantir]]>\n  \n  \n    2. \u201cIf everything you do needs to work on a 3-year time horizon, you\u2019re competing against a lot of people. But if you\u2019re willing to invest on a 7-year horizon, you\u2019re now competing against a fraction of those same people.\u201d\n    https://everydayco.us/library/reviews/5-year-review/\n    readwise:01jqp7n5hdmc3zkhs8n5x7fbpf\n    Mon, 31 Mar 2025 13:53:31 +0000\n    everydayco.us\n    Brand-wise, I\u2019m really leaning into three things: VINO, VINYL and MUFC. In particular, the music and its intersection with wine. There will forever be a healthy dose of Man Utd and the Irish, even though neither has their shit together. I\u2019ve realized that my music taste and love of United, vino/food, and sport are my true cultural capital. That\u2019s what I\u2019m looking to really flex on and lean into in the next 5.\n\nWriting-wise, it\u2019s great to be back in print, on the radio and grabbing bylines. I\u2019ve got a lot to say on higher-ed, immigration and business that\u2019s just built up through the years where I\u2019ve just been executing. I think I\u2019m ready to share a bit now. But I\u2019m candidly still trying to figure out what my column is (e.g. Fast Lane, The Corner Office) in addition to finding a more permanent editorial home outside of these quarterly letters and my ghostwriting. Right now, my goal is to publish something new in a major outlet 1x quarter, whether that be written, audio or video. I\u2019m equally comfortable in all domains, and I want to make the most of my JRE setup.\n\nI\u2019d also love to get in on the business and publishing side of media. Freelancing alone isn\u2019t enough for me, nor the only thing I can bring to the table. I\u2019m an entrepreneur, writer and convener who can also sit in the director\u2019s chair. How do I sustainably bring those talents to a modern media brand? And do so without confusing people? My skillset violates the church/state lines of business + editorial.\n\nAssets-wise, what do the next 5 hold? Hopefully, a triple passport. Who knows, maybe a real estate license, a WSET Level 1 or 2 Cert, a post-graduate fellowship and a 7-figure net worth.\n\nI\u2019ve been asking myself: what would \u201cfollow the money\u201d mean?\n\nHat tip to McConaughey. Here\u2019s my list: send me yours?\n\n\u2013 Soccer (e.g. own a football club)\n\u2013 Immigration\n\u2013 Higher Ed\n\u2013 Curation of music and libraries for hospitality brands\n\u2013 Invest in things I know smack (e.g. natural wine, sauna, listening rooms)\n\n]]>\n    Brand-wise, I\u2019m really leaning into three things: VINO, VINYL and MUFC. In particular, the music and its intersection with wine. There will forever be a healthy dose of Man Utd and the Irish, even though neither has their shit together. I\u2019ve realized that my music taste and love of United, vino/food, and sport are my true cultural capital. That\u2019s what I\u2019m looking to really flex on and lean into in the next 5.\n\nWriting-wise, it\u2019s great to be back in print, on the radio and grabbing bylines. I\u2019ve got a lot to say on higher-ed, immigration and business that\u2019s just built up through the years where I\u2019ve just been executing. I think I\u2019m ready to share a bit now. But I\u2019m candidly still trying to figure out what my column is (e.g. Fast Lane, The Corner Office) in addition to finding a more permanent editorial home outside of these quarterly letters and my ghostwriting. Right now, my goal is to publish something new in a major outlet 1x quarter, whether that be written, audio or video. I\u2019m equally comfortable in all domains, and I want to make the most of my JRE setup.\n\nI\u2019d also love to get in on the business and publishing side of media. Freelancing alone isn\u2019t enough for me, nor the only thing I can bring to the table. I\u2019m an entrepreneur, writer and convener who can also sit in the director\u2019s chair. How do I sustainably bring those talents to a modern media brand? And do so without confusing people? My skillset violates the church/state lines of business + editorial.\n\nAssets-wise, what do the next 5 hold? Hopefully, a triple passport. Who knows, maybe a real estate license, a WSET Level 1 or 2 Cert, a post-graduate fellowship and a 7-figure net worth.\n\nI\u2019ve been asking myself: what would \u201cfollow the money\u201d mean?\n\nHat tip to McConaughey. Here\u2019s my list: send me yours?\n\n\u2013 Soccer (e.g. own a football club)\n\u2013 Immigration\n\u2013 Higher Ed\n\u2013 Curation of music and libraries for hospitality brands\n\u2013 Invest in things I know smack (e.g. natural wine, sauna, listening rooms)\n\n]]>\n  \n  \n    4. \u201cA lot of people choose where they live based on what they could do occasionally rather than what they will do Everyday.\u201d\n    https://everydayco.us/library/reviews/2024-annual-review/?ck_subscriber_id=2556283387&utm_source=convertkit&utm_medium=email&utm_campaign=Everyday%27s%202024%20Annual%20Review%20-%2017080572\n    readwise:01jqebjb9hfmcd5s49ewvjdeyr\n    Fri, 28 Mar 2025 12:27:58 +0000\n    everydayco.us\n    Dearest Reader,\n\nWhere did 2024 go?\n\nIt feels like yesterday I was ringing in the New Year with old friends at South Bend\u2019s finest casino. Now I am writing to you from a nose-hair cold Chiberia.\n\nWhat a year. I feel I\u2019ve lived a few lifetimes in the last 12 months.\n\nI became a dual citizen, celebrated 5 years in biz and began the final year of my 20s.\n\n2024 was fantastic\u2014one of the most important years I\u2019ve had.\n\n\n\nHow To Read.\n\nThis is my third annual review.\n\nIf you\u2019d like to read 2022 or 2023 before diving into 2024, be my guest.\n\nIt\u2019s good context. There\u2019s also a 5-Year Review (2019-2024) if you want to go wild.\n\nLike last year, I wrote a quarterly letter for each quarter of 2024 (Q1-Q4). Since those already exist and were written in real-time, this review will take more of a year-over-year (YOY) lens, comparing each quarter to where I was 365 days prior.\n\nEach section links back to its original quarterly, with selected quotes that still hold weight. If you want the fullest picture, read the letters and the annual review.\n\nWhy do I say that?\n\nPrimarily because they were written from different vantage points. The quarterly letters capture the heat of the moment\u2014my pulse and headspace at that time. This annual review, however, asks a bigger question: how did 2024 compare to 2023?\n\nIn short: you learn new things when you look at something on a different horizon.\n\n\nIf you don\u2019t write it down, you probably won\u2019t remember how you thought or felt about the world a year ago.\n\nWhy even write an annual review?\n\nIt\u2019s a fair question. And If I\u2019m being honest, I have a few different motivations.\n\nFirst, I love history. I spend a lot of time reading old letters, memos, and books. They\u2019re usually the most valuable learning resource I can get my hands on because you can truly understand how someone thought in real-time. So, I feel it\u2019s my duty to document and write down my thoughts for the learning of my future self.\n\nSecond, I adore reviews as a format. Content, and business content, in particular, is too fast these days. It\u2019s one topic today and another breaking news story tomorrow. Yet what\u2019s ironic is that the critical ideas of business are timeless, and nothing that truly matters in this game is net new. Reviews force you to slow down and accept that reality. My proof? All the reviews I\u2019ve read from other entrepreneurs, publications, authors, etc, are some of their most timeless work. It doesn\u2019t matter if you read on the day it came out or a year later; it still smacks of real, quality insight.\n\nThird, legacy. Many people I admire wish they could remember how their thinking changed based on certain life moments, books, ideas or experiences. They know instinctively it changed, but they get fuzzy when the moments occured. I wish I could have read their annual reviews from when they first started or were in their late 20s, like me, to see what they were really thinking and feeling. Not what they told us they were thinking about on today\u2019s cacophony of self-glorifying podcasts.\n\nThe bitter truth is that if you don\u2019t write it down, you probably won\u2019t remember how you thought or felt about the world a year ago. Let alone 30 years ago.\n\nDon\u2019t believe me? Just try to remember what you scrolled on social media yesterday.\n\nYep, I thought so.\n\nFinally, I just like doing hard things. Condensing an entire year of business and life into a cohesive review is a real challenge, yet the reward is so great. Seeing your narratives, stories, takeaways, and learnings from a totally different vantage point is priceless. You are also reminded of what you loved and almost get to relive it.\n\nThrough this process, you become your own algorithm (e.g., Spotify Wrapped). This is a beautiful thing as it forces you to articulate why certain moments, stories, and people caught your attention more than others. In that lies the real innovation.\n\nI have absolutely no idea where this goes, which excites me. All I know is I will finally have a comprehensive answer to the question, \u201cWhat did you learn last year?\u201d How did your thinking change? What was your true focus?\u201d\n\nAnyway, here\u2019s my recap of 2024 from start to finish. I hope you enjoy it.\n\n\n\nReflection.\n\nThe most natural place to start this review is to pick up where I left off in my 2023 Review. I shared the sentiments I was pondering for 2024 and wrote the following:\n\nI: \u201cAmix of f*ck it, can I do this?\u201d and \u201cIf I follow my process, will it work?\u201d\n\nII: \u201cWhere\u2019s my place in the world of hospitality?\u201d\n\nIII: \u201cHow do I best show the world the depth of my mind?\u201d\n\n\nSo, how did we fare?\n\nOn #1. It\u2019s clear we can do this. I feel none of that same trepidation I did a year ago. I\u2019ve realized, however, that confidence comes not from me following my process effectively but more so from my ability to document it. Simplifying and codifying it into a killer SOP anybody could follow and then outsourcing it to a quality VA I can train for the long haul (e.g. 1+ year plus). We did this quite well last year for content (e.g. processing library backlog) and prospecting (e.g. building city-by-by lead lists). Now it\u2019s time to do it for sales, distribution, general administration, and supercharging everything from the PARA folders in my Apple Notes. It probably looks like one killer VA per subsidiary plus one general assistant for outreach.\n\nOn #2. I believe we\u2019ve found our place in the world of hospitality\u2014or at least the entry point. When I wrote my 2023 Review, part of me thought it still would have been some nouveau capital-oriented play. In large part, it was because I loved that level of abstraction. Owner-operator. Salary plus profit interest plus GP carry\u2014a trifecta of sorts. Now, we\u2019re bespoke analytics partners. We\u2019ve carved out the operator piece as analysts-for-hire. Beachead is multi-unit hospitality groups. In time, we\u2019ll serve full-service restaurants, membership clubs, wineries, gyms, hotels, bars, and hotels. We can get similar upside to being on the cap table with less BS.\n\nOn #3. The way I communicate is shifting. Interviews and op-eds were the vehicles I used in my younger days to show the world my mind. I still love doing the odd one. Bylines are cool and sexy but require a ridiculous amount of effort and don\u2019t pay. Applying those same skills (e.g. formulating questions, research and writing) to the business \u2014 producing memos, reviews, emails, and curiosity conversations \u2014 has a far higher ROI. I still want to be published in every major publication there is, and I still feel like there\u2019s a media-driven chapter of my life to play out. Yet the highest application of my storytelling ability feels like it is here. 4 quarterlys plus an annual review per year is a great cadence to let the world into my mind. All on my own real estate. We can certainly improve the distribution. I\u2019ve got some fun ideas in that domain. These letters feel like they are the best ways to show off my mind without tip-toeing around an editor\u2019s whims or the transience of the news cycle.\n\nIf 2023 was our unbrand, then 2024 was the rebrand. Over the last year, I\u2019ve also observed some other notable shifts in myself and our business. They are as follows:\n\nI fell in love with College Football. Blame it on Man Utd\u2019s demise. My greencard. This being my 11th year in the USA. Marcus Freeman. NIL. IDK. Notre Dame had a great season in the end, but it didn\u2019t look like that early doors, and I was still hooked watching the games in every conference. Underdog stories like Vandy certainly helped. I was totally consumed by CFB this year and loved it. The National Championship was better than the Super Bowl\u2014zero doubt. CFB is a better product than the NFL, NBA and MLB. It\u2019s on a better day of the week (Saturday > Sunday), hosted at better stadiums (Kyle Field > any professional stadium), with better atmospheres (12th Man > ? ), uniforms, helmets (looking at you, Illinois) and with players who are actually relatable (read: fewer primadonnas). I call College Football America\u2019s Greatest Export. What do you call it? I\u2019m curious.\n\nI use AI, Everyday. ChatGPT came out on November 30, 2022. I can safely say I didn\u2019t touch it until June 2024. Since then, it\u2019s totally changed the game for me\u2014as a \u201cnon-technical\u201d founder by training but with a deep understanding of the tools, outcomes and wins he wants for his business. Being able to use natural language to better communicate my ideas and code is fantastic. I\u2019m still doing all my writing myself, but it\u2019s a formidable draft-turner. It helps make things sharper. I love training my VAs on how to use it optimally. What\u2019s funny is it forces deep work with the token limit reset. 2025 will be the first full year I will integrate AI into every aspect of our business. It\u2019s crazy that I have used it daily since July after a slow start.\n\nSOP or die. I don\u2019t want to understate the impact of Michael Michalowicz\u2019s books on my development this year. Profit First and Clockwork are now foundational texts. Much like Weiss\u2019 MDC and Ferriss\u2019 4HWW. The idea of show me your SOPs, and I\u2019ll show you your future is just brilliant. Business is just a system. Inputs are what you must perfect and can control. Outputs are just downstream of the right or wrong inputs over time. Ideally, replicating the same motion while creating and extracting more value over time. I\u2019ve always been routine-oriented. However, I\u2019d never really taken the time to document that routine for someone else. That\u2019s the difference between a routine and a system. Again, AI is a huge help here. You can build SOPs at scale and refine them using nothing more than a 5-minute LOOM.\n\nPhysical capacity = mental capacity. The book  Spark first put this concept in my head. The idea that exercise is for the mind, not the body. George Heaton has said that the more you push your physical, the better your mental. I agree with that. WHOOP, weight training and weekly Pickleball have become the fixtures of my athletic life. Now, with a proper gym (read: squat rack) and sauna, there are zero excuses. It\u2019s right at my doorstep. I\u2019m excited. I\u2019ve built a great baseline. Tour De Echelon et al. And it\u2019s the right thing to do Everyday. It always transforms my mood. Grounds me. Gives me a well-needed break. What happens doesn\u2019t matter; the day is a win if I train. I sleep better. I perform better. It\u2019s just a revolving cycle.\n\nMy default settings are correctly calibrated. You know when you turn on a new video game, you\u2019re prompted to ensure gameplay settings are correct for your TV, light source, and preferred controls? I feel like I\u2019ve finally got all my preferred defaults down for the game of life. I\u2019ve got the right relationship to content = default off-social. Right relationship to booze = default 0.0. I still enjoy the odd drink. I try to work 4 10s. Let Friday and the weekend be unstructured to let my mind explore. Write my 1,000 words a day. Publish 4x letters and 1x annual review every year. Grow the direct list of people I can send it to. Don\u2019t try to resell other products. It\u2019s not my game. I\u2019m an operator. I\u2019m an advisor. I\u2019m a dealmaker.\n\nMaybe the biggest takeaway is that I finally feel like I\u2019ve got the right players on the team operating in the right systems. This starts internally with AI-empowered VAs following our operating playbooks for business development and content to a tee.\n\nA whole year of Profit First under my belt \u2014 plus a killer financial advisor and investing platform from Carry \u2014 has just been transformational. I feel extremely clear about what I\u2019m playing for and how it translates to the life we\u2019re building.\n\nMy S-Corp move has been clutch. I\u2019m running my own payroll, which is so ironic. You\u2019re often told that as an entrepreneur, your biggest success is ditching your W2 job\u2014until you realize that the real flex is being able to W-2 yourself forever.\n\nOur technology stack is quality, and we\u2019re lean internally. I\u2019m lucky to have such great partners. They listen to my ideas, improve them, and are hungry to implement them. We\u2019ve got products with natural intrinsic repetition (e.g. retreats, analytics).\n\nAll the pieces we need to become a fixture are on the board.\n\nTimelog.\n\nIf that\u2019s how my outlook changed, what about how I spend my time?\n\nLike the Levels CEO, I\u2019ve tracked my time for years now. Thanks to my meticulous use of Google Calendar\u2019s Time Insights, I have three full years of time-logged data (2022-2024). I review this during my weekly, monthly and quarterly reviews to ensure I\u2019m hitting my numbers (e.g. I\u2019m spending the right amount of time on the things I said were priority). Takes all the guesswork out of how I spend my 168 and keeps me honest. If I notice a substantial change or an area not getting enough love, I can make a change or hire a VA to take over the work I\u2019m just not getting to.\n\nComparing 2024 to 2023, here are some of the biggest changes in how I spent time:\n\nTraining. My physical capacity skyrocketed in 2024. Exercise became a non-negotiable foundational Everyday habit. I spent 416 hours exercising in 2024, ~35 hours/month. Up +116% on 2023. I\u2019m a former decorated high school sportsman trying to figure out his long-term relationship with training sans competition. To quote James Clear, it\u2019s become an identity rather than an activity. With a new gym, sauna, rack and ski-erg in the building, excitement is an understatement\u2014a full year of 5-3-1 on all major lifts in 2025 is to come. Training dictates my underlying energy, focus, and capacity. More structure in fitness translates to more structure everywhere else. No on and off switch. It is simply part of my Everyday rhythm.\n\nHospitality. Became a substantial focus in 2024 (up 39% YOY). In a sense, this shouldn\u2019t be a surprise. This product came from a capital raise I did in Q1 23 for a restaurant in the city. However, until H2 24, it was very much that project you wanted to give more to but couldn\u2019t justify. Genuine commercial interest changed all that. I\u2019m happy for it. This means the raise wasn\u2019t all for nothing. Building the product, selling, executing, creating relationships with new partners and finding time to document it all takes real-time. I can\u2019t wait to see what this year brings.\n\nProcess. SOP or die. I don\u2019t want to belabour this point, but system building and process documentation have become an Everyday commitment, not a quarterly \u201coh yeah, let me get that done\u201d project. Systems weren\u2019t just being built\u2014they were being used, optimized, and maintained. In 2023, system-building was still in the trial-and-error phase. In 2024, it became a steady, ongoing habit (up ~20% YOY). It\u2019s time to double down in 2025, so we cover every facet of what we do.\n\nTravel. I took fewer, more deliberate trips this year\u201416 in 2024 vs 26 in 2023. A 30% reduction. 2023, being our wedding year, artificially bumped up the trip number. It is so nice to have no more stacked, chaotic travel months. 3 weekends of travel in a row is my max. Travel feels embedded into the rhythm of my year. When am I going to need a break or a reset? Or, based on what\u2019s already on the calendar, when will I need to knuckle down and get my deepest work done? That\u2019s the driving force now. The bouncer, if you will. Travelling on my own terms has made a huge difference. Strategic travel is more fun, relaxing and less disruptive to my flow.\n\n \nIt forces me to confront how my time is actually spent, not how I think it\u2019s spent. \n\nAbove all, I love the Spotify Wrapped nature of timelogging.\n\nIt forces me to confront how my time is actually spent, not how I think it\u2019s spent. 2024 wasn\u2019t about rethinking our vision but about acting on it. Less questioning, more doing. More systems that work, more deals getting done, more momentum.\n\nI didn\u2019t get busier\u2014I got sharper. They say what got you here won\u2019t get you there.\n\n2025 is simply about expanding our upside. The proof will be in the pudding.\n\n2024 \n\nSo, what\u2019s the TL;DR of 2024?\n\nIn Q1, we celebrated 5 years in biz. I hosted a 2-day offsite out West. I published my first story for Monocle Radio. ARS told me I had a way with words. I recorded my first sunset mix for Everyday Radio. My wife and I celebrated 9 years together.\n\nIn Q2, we delivered Retreat XXVI (26) in Napa, CA. I turned 29. Had my best-ever quarter for expert network calls. Man Utd won the FA Cup. We got a new couch. I took my first trip on a luxury bus. I had my meal of the year at Mila. We completed our refactoring of all podcast episodes for Everyday Library.\n\nIn Q3, I became an Irish citizen. I spent time in Montreal and Cancun. I crafted speeches and profiles at prestigious conferences in Italy and Germany. I finished our 5YR Brand Refresh: new logos, lockups, and business cards. We celebrated our 1st wedding anniversary in Santa Fe. I also completed my first Tour de Echelon (2023).\n\nIn Q4, we delivered Retreat XXVII (27) in Laguna Beach, CA. Our building has a new gym, sauna, and workspace. We signed our first enterprise hospitality partner on the Michelin Guide. I went home to London for Christmas and landed on a new tagline for Everyday as \u201cThe Modern-Day Hold Co.\u201d\n\nAll in all, I took 16 trips to 13 different cities, travelling 21,500 miles total.\n\nNow for the quarter-by-quarter breakdown.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ1: Slow Build\n\nThe theme of Q1 24 was Slow Build. Q1 23 was Refactoring.\n\nIn a way, they\u2019re connected yet wholly different.\n\nWhen I wasn\u2019t fundraising in Q1 23, I started refactoring years of the \u201cdigital detritus\u201d buildup in my iPhone, Drive, Kindle, MacBook, etc. As an obsessive reader and note-taker, this was no mean feat. Looking back, it was a valiant effort.\n\nHowever, I quickly learnt that detritus piles up because you 1) don\u2019t have a system to process it and 2) don\u2019t know its final purpose. Shifting an idea into something presentable is challenging when you haven\u2019t discerned the final container. It is akin to pinning the tail on the donkey with a blindfold, except you don\u2019t know the shape of the animal or where the wall is. I always knew I wanted the final container to be semi-public. My gut said it wasn\u2019t social media. The half-life wasn\u2019t long enough.\n\nI just didn\u2019t know how, where or why our stories should live on.\n\nBy Q1 24, I had my answer.\n\nOur rebrand from Everyday Entrepreneur (EE) to Everyday as a holding company at the end of 2023 was a mise-en-place moment. Everyday Radio emerged as the natural outlet for our media to date, and Everyday Library emerged as our \u201cbest-of\u201d archive. Everything clicked. I had containers I could continue to hone over the next five years, and they would eventually become even more valuable sources of context and personal knowledge in the era of AI.\n\nWith names and structures in place\u2014specific enough to mean something but broad enough to change\u2014I graduated from the refactoring role to systems builder. I still organize and prune my latest Apple Notes during my weekly review.\n\nHowever, we now have VAs doing the hard yards, editing, transcribing, and publishing everything into Everyday Library or Radio. For any piece of timeless content we\u2019ve created, the goal was to generate a live URL (proof) with a Tim Ferris show-esque transcript (quality). I only read podcast transcripts.\n\nThat was my definition of good enough from a user and distribution standpoint. I\u2019m proud to say we\u2019ve hit that mark. Here\u2019s a preview. We\u2019ve brought ~60 episodes online since the Fall of 2023, averaging ~1 per week.\n\nThis quarter wasn\u2019t about breakthroughs or pivots but about turning pro.\n\nShowing up Everyday and doing the work, even when the rewards weren\u2019t immediately clear, which they often never are with the most important things. It was a quarter of refinement (nod to Mark S), execution, and setting the stage for sustainable success\u2014tightening processes, refining structure, and ensuring my business and personal habits were built for durability. It was a slow endeavor, demanding patience, discipline, and trust in the process. And we\u2019re better for it.\n\nHere are the quotes from Q1 24 that are still front of mind for me:\n\nI: I said I was turning pro this year, which I define as doing what you have to do, even when you don\u2019t want to.\n\nII: For the first time in years, I feel in total control of my energy, time, and headspace. I know where to put them to get what I want, with a clear vision, structure and articulation for Everyday as a holding company.\n\nIII: Prompted by the rebrand to Everyday Radio, taking on a new URL, getting a new email, etc., I got super focused on cleaning up our entire podcast backlog from 2019 to the present. It\u2019s really been amazing.\n\nIV: Refactoring has also meant unpublishing episodes that aren\u2019t timeless or just don\u2019t quite fit Everyday Radio\u2019s new remit of killer music, minds and meditations.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ2: Work Clean\n\nThe theme of Q2 24 was Work Clean. Q2 23 was Life: A Full Contact Sport.\n\nTalk about a stark contrast. Q2 23 was probably the most intense quarter I\u2019ve had, period. I was in peak transition personally and professionally.\n\nOn the personal front, I was preparing to become a husband. Wedding prep was at full tilt. I celebrated my bachelor party in Vegas and, the very next weekend hosted our last-ever B2C retreat in D.C. with an exclusive tour of the White House.\n\nOn the business front, after raising $250K in 21 days, I became an investor-operator in my first hospitality deal. I was (somehow) back onto the circuit\u2014FT Weekend Festival in D.C., Monocle\u2019s Weekender in Asheville, and as a guest of honour at the Welcome Conference and The James Beards Awards in Chicago courtesy of Chef Katie Button and Resy. I even found the time to sit down with Foxtrot\u2019s founder, Mike LaVitola, and write a story on their 10th anniversary at their global HQ in Fulton Market for Monocle. Incredible timing, given what ended up transpiring.\n\nThrow in trips to Atlanta for a best mate\u2019s wedding and a trip to Arkansas to see my little brother during his study abroad year, and it was pure and utter craziness.\n\nA year later, Q2 24, life is much calmer. \n\nWe\u2019ve got a tailwind. Crushed our second creator retreat in Napa Valley. Executed 100% remotely. I love being a curator, not a convener. I feel more in control of my own destiny. Capturing value commensurate with the true impact we\u2019re creating. Hospitality is emerging. I have a sit down with the Chairman of the Illinois Restaurant Association. I send a few cold emails. The raise is long over, but I\u2019m still cooking in hospitality\u2014manual labour from years prior has been reduced by AI.\n\nI\u2019m recording my sunset mixes a year after holding that cigar bar in Atlanta. I took that guy\u2019s words to heart. Wild. Finding an outlet that allowed me to reconnect with my love for storytelling and music was essential and integral to my vision of bringing taste and intentionality into every space I engage with. I was finding my rhythm and just working clean. I stayed focused on the motions that mattered most.\n\nHere are some quotes from the Q2 24 that are still front of mind for me:\n\nI: My consulting friends tell me their perpetual dream is to retire and take calls like this from the beach for GLG, Tegus, et al. I might just beat them to it.\n\nII: I held down a cigar bar in Atlanta for two nights last year, and a top executive from EMPIRE told me I had great taste in music. \n\nIII: Nobody takes a data-driven approach to identifying, creating and capturing more lifetime value (LTV) from a restaurant\u2019s truest fans. That\u2019s what we provide.\n\nIV: I want to apply my taste to the spaces and brands I rock with most in this game called life. \n\nV: In case you missed it, I record a music show every other week. I curate a playlist of 15-20 of my favourite tracks based on the weather and time of that day. There is no intervention, autotune, mixing, or adverts. It\u2019s just me, you, the views, and the tunes. I call this my version of NPR Tiny Desk.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ3: On, Not In\n\nThe theme of Q3 24 was On, Not In. Q3 23 was In Transition.\n\nQ3 23 was a comedown for sure. It\u2019s not easy to try to process the time of your life.\n\nA 4th of July weekend at the Lake with my family. A Ryder Cup UK vs USA golf tournament at Ravisloe CC (my favourite course in the city). Cuts & Shaves at Blind Barber for some of my boys sippin\u2019 Natural Vino by. A beautiful rehearsal dinner and welcome party at Ada St. I\u2019ll never forget MGMT blaring out on the speakers in the warm summer Chicago air, drink in hand with all my favourite people in the world around me. Stunning suite with city views at the Trump. Married at Assumption. Wedding at Ivy Room. Honeymoon in British Colombia. Seaplane. Sun. Sauna. Massages. Aperol Spritz in hand. It was all just incredible.\n\nReturning to reality while adjusting to a new one isn\u2019t easy. Looking back, it\u2019s clear that I was still figuring things out. The words In Transition speak volumes even now. We\u2019re pivoting the business. I\u2019m teasing the library and travel platform in my letters. I still hadn\u2019t delivered our first B2B retreat, which is nuts, so I was still in a somewhat B2C headspace. It\u2019s so clear now B2C was never our true endgame.\n\nI\u2019m trying to get my greencard application done. All the medical tests, the jabs, the back and forth with our lawyer. Setting up joint bank accounts. I\u2019m still on OPT. My visa ends in August. I was buckling up not to work or travel abroad until April 2024. It was a lot. Probably more than I even realized at the time. My sense is I was quite stressed. Although I could definitely see the light at the end of the tunnel.\n\nI\u2019m so thankful to have made it through. By Q3 24, I\u2019d simplified, and so had life.\n\nGreencard in-hand. My visa woes were finally over for good. I\u2019m travelling like a free man, celebrating my friend\u2019s 30th birthday and bachelor\u2019s parties abroad. I\u2019m grooving at a Fred again concert up in Lake Geneva. Playing golf. I\u2019m having a blast.\n\nI secured my second (Irish) citizenship on the last day of Q3 24 and got dapped up by the Head of Global Entry upon my return to ORD. He made the rest of the line wait until he\u2019d finished catching up with my wife and I. The comparison is wild. I\u2019m not sure my younger self would believe it. To think what life was like a year prior?\n\nOn top of that, a year after I returned capital, Everyday Hospitality is starting to emerge. AI has supercharged the product, taking our process and outputs to the next level. I also found joy in rediscovering the simple pleasures: curating playlists for friends, exploring new cities on foot and reflecting on my journey so far.\n\nThe Q3 24 On, Not In theme wasn\u2019t just a business philosophy but a lifetime mindset. Focusing on the big picture and laying the foundations for years to come.\n\nHere are some quotes from the Q3 24 that are still front of mind for me:\n\nI: It\u2019s true: much of my love for America stems from the fact that you can always pay to skip the line. And there isn\u2019t a better skip-the-line pass in life than Global Entry.\n\nII: My three rules for public speaking are one laugh, one hmm, and one wow. That\u2019s your only job. If you can build around a killer talk around that, you\u2019re good.\n\nIII: Much like WHOOP\u2019s Strain, Sleep, and Recovery scores, we aim to build a slate of metrics that reveal how hospitality groups are truly doing Everyday.\n\nIV: When we started in 2019, we went by Everyday Entrepreneur. We dropped the Entrepreneur at the end of 2022, and Everyday became the name for the overarching holding company last year. In JT\u2019s words, it just felt cleaner.\n\nV: I\u2019ve kept every business card I\u2019ve ever been given. And I\u2019ll say some have aged better than others. Years later, even if I can\u2019t remember the face, as long as the card is fresh, it tells me everything I need to know about that business.\n\nVI: If you\u2019re looking for a playlist to help you through winter, christen a new space, or get you into a particular headspace, hit me up. I\u2019d love to curate one for you.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ4: Home Again\n\nThe theme of Q4 24 was Home Again. Q4 23 was Foundations.\n\nOf all the quarters, this one is perhaps the craziest for comparing and contrasting YOY. I headed home to London in Q4 24 for Christmas, having executed three B2B retreats in the past 12 months.\n\nThe last time I was home, Q2 22, I hosted our penultimate B2C retreat. Since then, everything has changed, and nothing has changed. IFYKWIM.\n\nThis starkly contrasts with Q4 23, when we were still preparing to deliver our first B2B retreat in Half Moon Bay, CA. At this point, I\u2019d delivered countless retreats, but always as the convener\u2014attending myself, selling tickets, and playing host.\n\nHowever, shifting to B2B changed everything. I no longer had to be the convener.\n\nI graduated to curator. In 2024, I proved I could deliver arguably an even better experience in this role. I didn\u2019t have to be physically present to provide a world-class retreat experience. I disrupted my own playbook, and the results speak for themselves: cleaner execution, better margins, and all-around sustainable effort.\n\n\nGetting on the right side of convening (curation), hospitality (analytics), and immigration (greencard) changed everything.\n\nThat\u2019s part one. Part two?\n\nIn Q4 23, I was still waiting on my green card. By Q4 24, I\u2019d had it for an entire year\u2014and just secured my second (Irish) citizenship. In two years, I\u2019ll complete the passport trifecta and apply to become a U.S. (read: triple) citizen.\n\nWTF? Talk about zero to hero. My in-laws are playfully calling me secret agent.\n\nThis is where everything comes into focus. The thorniest issue of my life\u2014immigration\u2014was solved overnight. My biggest weakness for a decade became my greatest competitive advantage for a generation. It\u2019s funny how life works like that.\n\nA decade of patience, paperwork, and always doing the right thing paid off. Even wilder? A close friend from Notre Dame and a fellow British international student were also approved for his GC on the same day as me. We\u2019d fallen out of touch after school but reconnected serendipitously on the same flight home to London. We spent most of our time crossing the Atlantic catching up in the galley\u2014a full-circle moment. There is nothing better than winning and levelling up with your people.\n\nQ4 23 was chaos. But in just 78 days, everything changed. My greencard approval gave me something I\u2019d never had before: permanent stability in the United States.\n\nLast but not least, hospitality.\n\nA year ago, I made the tough\u2014but ultimately correct\u2014decision to return capital for a restaurant deal. At the time, it felt brutal. But in hindsight, it was necessary to set the stage for something even bigger. Resy invited me into Global Dining Access as a partner later that fall, and a year later, in Q4 24, we signed our first enterprise deal with a 10-unit group on the Michelin Guide. That\u2019s another full-circle win.\n\nReturning capital wasn\u2019t a failure\u2014it set the foundation for a brighter future. I trusted myself and found the right level of abstraction. Now it\u2019s time to rock.\n\nGetting on the right side of convening (curation), hospitality (analytics), and immigration (greencard) changed everything. A year ago, I felt like I was pushing against gravity\u2014now? Everything is in motion. This is just the beginning.\n\nHere are some quotes from the Q4 24 that are still front of mind for me:\n\nI: I\u2019ve long said that Christmas in America often feels like just a day, whereas in the UK, it\u2019s a proper week-plus holiday celebration. I feel fortunate to experience the best of both worlds\u2014Thanksgiving in the USA and Christmas in the UK.\n\nII: In my humble opinion, College Football is America\u2019s best export.\n\nIII: The real challenge \u2014 and $1B question \u2014 isn\u2019t how or when to bring people back to the office but why they\u2019ll want to stay there long term. It\u2019s about creating compelling reasons for your people to want to exist in the physical spaces you own.\n\nIV: I see so many brands, businesses, and individuals settling for the classic one-day event or workshop. My message is: think bigger. We can help you curate experiences that truly resonate, stand out and endure over time. If you\u2019re not committed to doing that, what\u2019s the point? The world doesn\u2019t need any more bang-average events.\n\nV: I felt it was time for a new tagline. I settled on \u201cModern-Day Hold Co.\u201d\n\n2025: Looking Ahead\n\nAs I look towards 2025, I feel an immense sense of potential.\n\nThat potential will be realized by continuing to do what we do best\u2014advising, analyzing, and curating\u2014while systematizing every aspect of the business. New transcripts will be published weekly, leads will be meticulously researched, and beautifully crafted emails will be sent out. My drafts folder needs to be zeroed out. 2/3 of this is already in place. Now, it\u2019s about being ruthless in the final 1/3.\n\nExternally, the focus is clear: grow profitably. Our products and pricing models are becoming more refined, tested, and mature, a prerequisite for GTM success. We can confidently focus on sourcing new strategic partners across the portfolio.\n\nI want this year to be our best yet.\n\nI\u2019m clear on what we sell, why we sell it and who we sell it to.\n\nThis year has been exceptional. I must put at least another 4 in at this level or above.\n\n]]>\n    Dearest Reader,\n\nWhere did 2024 go?\n\nIt feels like yesterday I was ringing in the New Year with old friends at South Bend\u2019s finest casino. Now I am writing to you from a nose-hair cold Chiberia.\n\nWhat a year. I feel I\u2019ve lived a few lifetimes in the last 12 months.\n\nI became a dual citizen, celebrated 5 years in biz and began the final year of my 20s.\n\n2024 was fantastic\u2014one of the most important years I\u2019ve had.\n\n\n\nHow To Read.\n\nThis is my third annual review.\n\nIf you\u2019d like to read 2022 or 2023 before diving into 2024, be my guest.\n\nIt\u2019s good context. There\u2019s also a 5-Year Review (2019-2024) if you want to go wild.\n\nLike last year, I wrote a quarterly letter for each quarter of 2024 (Q1-Q4). Since those already exist and were written in real-time, this review will take more of a year-over-year (YOY) lens, comparing each quarter to where I was 365 days prior.\n\nEach section links back to its original quarterly, with selected quotes that still hold weight. If you want the fullest picture, read the letters and the annual review.\n\nWhy do I say that?\n\nPrimarily because they were written from different vantage points. The quarterly letters capture the heat of the moment\u2014my pulse and headspace at that time. This annual review, however, asks a bigger question: how did 2024 compare to 2023?\n\nIn short: you learn new things when you look at something on a different horizon.\n\n\nIf you don\u2019t write it down, you probably won\u2019t remember how you thought or felt about the world a year ago.\n\nWhy even write an annual review?\n\nIt\u2019s a fair question. And If I\u2019m being honest, I have a few different motivations.\n\nFirst, I love history. I spend a lot of time reading old letters, memos, and books. They\u2019re usually the most valuable learning resource I can get my hands on because you can truly understand how someone thought in real-time. So, I feel it\u2019s my duty to document and write down my thoughts for the learning of my future self.\n\nSecond, I adore reviews as a format. Content, and business content, in particular, is too fast these days. It\u2019s one topic today and another breaking news story tomorrow. Yet what\u2019s ironic is that the critical ideas of business are timeless, and nothing that truly matters in this game is net new. Reviews force you to slow down and accept that reality. My proof? All the reviews I\u2019ve read from other entrepreneurs, publications, authors, etc, are some of their most timeless work. It doesn\u2019t matter if you read on the day it came out or a year later; it still smacks of real, quality insight.\n\nThird, legacy. Many people I admire wish they could remember how their thinking changed based on certain life moments, books, ideas or experiences. They know instinctively it changed, but they get fuzzy when the moments occured. I wish I could have read their annual reviews from when they first started or were in their late 20s, like me, to see what they were really thinking and feeling. Not what they told us they were thinking about on today\u2019s cacophony of self-glorifying podcasts.\n\nThe bitter truth is that if you don\u2019t write it down, you probably won\u2019t remember how you thought or felt about the world a year ago. Let alone 30 years ago.\n\nDon\u2019t believe me? Just try to remember what you scrolled on social media yesterday.\n\nYep, I thought so.\n\nFinally, I just like doing hard things. Condensing an entire year of business and life into a cohesive review is a real challenge, yet the reward is so great. Seeing your narratives, stories, takeaways, and learnings from a totally different vantage point is priceless. You are also reminded of what you loved and almost get to relive it.\n\nThrough this process, you become your own algorithm (e.g., Spotify Wrapped). This is a beautiful thing as it forces you to articulate why certain moments, stories, and people caught your attention more than others. In that lies the real innovation.\n\nI have absolutely no idea where this goes, which excites me. All I know is I will finally have a comprehensive answer to the question, \u201cWhat did you learn last year?\u201d How did your thinking change? What was your true focus?\u201d\n\nAnyway, here\u2019s my recap of 2024 from start to finish. I hope you enjoy it.\n\n\n\nReflection.\n\nThe most natural place to start this review is to pick up where I left off in my 2023 Review. I shared the sentiments I was pondering for 2024 and wrote the following:\n\nI: \u201cAmix of f*ck it, can I do this?\u201d and \u201cIf I follow my process, will it work?\u201d\n\nII: \u201cWhere\u2019s my place in the world of hospitality?\u201d\n\nIII: \u201cHow do I best show the world the depth of my mind?\u201d\n\n\nSo, how did we fare?\n\nOn #1. It\u2019s clear we can do this. I feel none of that same trepidation I did a year ago. I\u2019ve realized, however, that confidence comes not from me following my process effectively but more so from my ability to document it. Simplifying and codifying it into a killer SOP anybody could follow and then outsourcing it to a quality VA I can train for the long haul (e.g. 1+ year plus). We did this quite well last year for content (e.g. processing library backlog) and prospecting (e.g. building city-by-by lead lists). Now it\u2019s time to do it for sales, distribution, general administration, and supercharging everything from the PARA folders in my Apple Notes. It probably looks like one killer VA per subsidiary plus one general assistant for outreach.\n\nOn #2. I believe we\u2019ve found our place in the world of hospitality\u2014or at least the entry point. When I wrote my 2023 Review, part of me thought it still would have been some nouveau capital-oriented play. In large part, it was because I loved that level of abstraction. Owner-operator. Salary plus profit interest plus GP carry\u2014a trifecta of sorts. Now, we\u2019re bespoke analytics partners. We\u2019ve carved out the operator piece as analysts-for-hire. Beachead is multi-unit hospitality groups. In time, we\u2019ll serve full-service restaurants, membership clubs, wineries, gyms, hotels, bars, and hotels. We can get similar upside to being on the cap table with less BS.\n\nOn #3. The way I communicate is shifting. Interviews and op-eds were the vehicles I used in my younger days to show the world my mind. I still love doing the odd one. Bylines are cool and sexy but require a ridiculous amount of effort and don\u2019t pay. Applying those same skills (e.g. formulating questions, research and writing) to the business \u2014 producing memos, reviews, emails, and curiosity conversations \u2014 has a far higher ROI. I still want to be published in every major publication there is, and I still feel like there\u2019s a media-driven chapter of my life to play out. Yet the highest application of my storytelling ability feels like it is here. 4 quarterlys plus an annual review per year is a great cadence to let the world into my mind. All on my own real estate. We can certainly improve the distribution. I\u2019ve got some fun ideas in that domain. These letters feel like they are the best ways to show off my mind without tip-toeing around an editor\u2019s whims or the transience of the news cycle.\n\nIf 2023 was our unbrand, then 2024 was the rebrand. Over the last year, I\u2019ve also observed some other notable shifts in myself and our business. They are as follows:\n\nI fell in love with College Football. Blame it on Man Utd\u2019s demise. My greencard. This being my 11th year in the USA. Marcus Freeman. NIL. IDK. Notre Dame had a great season in the end, but it didn\u2019t look like that early doors, and I was still hooked watching the games in every conference. Underdog stories like Vandy certainly helped. I was totally consumed by CFB this year and loved it. The National Championship was better than the Super Bowl\u2014zero doubt. CFB is a better product than the NFL, NBA and MLB. It\u2019s on a better day of the week (Saturday > Sunday), hosted at better stadiums (Kyle Field > any professional stadium), with better atmospheres (12th Man > ? ), uniforms, helmets (looking at you, Illinois) and with players who are actually relatable (read: fewer primadonnas). I call College Football America\u2019s Greatest Export. What do you call it? I\u2019m curious.\n\nI use AI, Everyday. ChatGPT came out on November 30, 2022. I can safely say I didn\u2019t touch it until June 2024. Since then, it\u2019s totally changed the game for me\u2014as a \u201cnon-technical\u201d founder by training but with a deep understanding of the tools, outcomes and wins he wants for his business. Being able to use natural language to better communicate my ideas and code is fantastic. I\u2019m still doing all my writing myself, but it\u2019s a formidable draft-turner. It helps make things sharper. I love training my VAs on how to use it optimally. What\u2019s funny is it forces deep work with the token limit reset. 2025 will be the first full year I will integrate AI into every aspect of our business. It\u2019s crazy that I have used it daily since July after a slow start.\n\nSOP or die. I don\u2019t want to understate the impact of Michael Michalowicz\u2019s books on my development this year. Profit First and Clockwork are now foundational texts. Much like Weiss\u2019 MDC and Ferriss\u2019 4HWW. The idea of show me your SOPs, and I\u2019ll show you your future is just brilliant. Business is just a system. Inputs are what you must perfect and can control. Outputs are just downstream of the right or wrong inputs over time. Ideally, replicating the same motion while creating and extracting more value over time. I\u2019ve always been routine-oriented. However, I\u2019d never really taken the time to document that routine for someone else. That\u2019s the difference between a routine and a system. Again, AI is a huge help here. You can build SOPs at scale and refine them using nothing more than a 5-minute LOOM.\n\nPhysical capacity = mental capacity. The book  Spark first put this concept in my head. The idea that exercise is for the mind, not the body. George Heaton has said that the more you push your physical, the better your mental. I agree with that. WHOOP, weight training and weekly Pickleball have become the fixtures of my athletic life. Now, with a proper gym (read: squat rack) and sauna, there are zero excuses. It\u2019s right at my doorstep. I\u2019m excited. I\u2019ve built a great baseline. Tour De Echelon et al. And it\u2019s the right thing to do Everyday. It always transforms my mood. Grounds me. Gives me a well-needed break. What happens doesn\u2019t matter; the day is a win if I train. I sleep better. I perform better. It\u2019s just a revolving cycle.\n\nMy default settings are correctly calibrated. You know when you turn on a new video game, you\u2019re prompted to ensure gameplay settings are correct for your TV, light source, and preferred controls? I feel like I\u2019ve finally got all my preferred defaults down for the game of life. I\u2019ve got the right relationship to content = default off-social. Right relationship to booze = default 0.0. I still enjoy the odd drink. I try to work 4 10s. Let Friday and the weekend be unstructured to let my mind explore. Write my 1,000 words a day. Publish 4x letters and 1x annual review every year. Grow the direct list of people I can send it to. Don\u2019t try to resell other products. It\u2019s not my game. I\u2019m an operator. I\u2019m an advisor. I\u2019m a dealmaker.\n\nMaybe the biggest takeaway is that I finally feel like I\u2019ve got the right players on the team operating in the right systems. This starts internally with AI-empowered VAs following our operating playbooks for business development and content to a tee.\n\nA whole year of Profit First under my belt \u2014 plus a killer financial advisor and investing platform from Carry \u2014 has just been transformational. I feel extremely clear about what I\u2019m playing for and how it translates to the life we\u2019re building.\n\nMy S-Corp move has been clutch. I\u2019m running my own payroll, which is so ironic. You\u2019re often told that as an entrepreneur, your biggest success is ditching your W2 job\u2014until you realize that the real flex is being able to W-2 yourself forever.\n\nOur technology stack is quality, and we\u2019re lean internally. I\u2019m lucky to have such great partners. They listen to my ideas, improve them, and are hungry to implement them. We\u2019ve got products with natural intrinsic repetition (e.g. retreats, analytics).\n\nAll the pieces we need to become a fixture are on the board.\n\nTimelog.\n\nIf that\u2019s how my outlook changed, what about how I spend my time?\n\nLike the Levels CEO, I\u2019ve tracked my time for years now. Thanks to my meticulous use of Google Calendar\u2019s Time Insights, I have three full years of time-logged data (2022-2024). I review this during my weekly, monthly and quarterly reviews to ensure I\u2019m hitting my numbers (e.g. I\u2019m spending the right amount of time on the things I said were priority). Takes all the guesswork out of how I spend my 168 and keeps me honest. If I notice a substantial change or an area not getting enough love, I can make a change or hire a VA to take over the work I\u2019m just not getting to.\n\nComparing 2024 to 2023, here are some of the biggest changes in how I spent time:\n\nTraining. My physical capacity skyrocketed in 2024. Exercise became a non-negotiable foundational Everyday habit. I spent 416 hours exercising in 2024, ~35 hours/month. Up +116% on 2023. I\u2019m a former decorated high school sportsman trying to figure out his long-term relationship with training sans competition. To quote James Clear, it\u2019s become an identity rather than an activity. With a new gym, sauna, rack and ski-erg in the building, excitement is an understatement\u2014a full year of 5-3-1 on all major lifts in 2025 is to come. Training dictates my underlying energy, focus, and capacity. More structure in fitness translates to more structure everywhere else. No on and off switch. It is simply part of my Everyday rhythm.\n\nHospitality. Became a substantial focus in 2024 (up 39% YOY). In a sense, this shouldn\u2019t be a surprise. This product came from a capital raise I did in Q1 23 for a restaurant in the city. However, until H2 24, it was very much that project you wanted to give more to but couldn\u2019t justify. Genuine commercial interest changed all that. I\u2019m happy for it. This means the raise wasn\u2019t all for nothing. Building the product, selling, executing, creating relationships with new partners and finding time to document it all takes real-time. I can\u2019t wait to see what this year brings.\n\nProcess. SOP or die. I don\u2019t want to belabour this point, but system building and process documentation have become an Everyday commitment, not a quarterly \u201coh yeah, let me get that done\u201d project. Systems weren\u2019t just being built\u2014they were being used, optimized, and maintained. In 2023, system-building was still in the trial-and-error phase. In 2024, it became a steady, ongoing habit (up ~20% YOY). It\u2019s time to double down in 2025, so we cover every facet of what we do.\n\nTravel. I took fewer, more deliberate trips this year\u201416 in 2024 vs 26 in 2023. A 30% reduction. 2023, being our wedding year, artificially bumped up the trip number. It is so nice to have no more stacked, chaotic travel months. 3 weekends of travel in a row is my max. Travel feels embedded into the rhythm of my year. When am I going to need a break or a reset? Or, based on what\u2019s already on the calendar, when will I need to knuckle down and get my deepest work done? That\u2019s the driving force now. The bouncer, if you will. Travelling on my own terms has made a huge difference. Strategic travel is more fun, relaxing and less disruptive to my flow.\n\n \nIt forces me to confront how my time is actually spent, not how I think it\u2019s spent. \n\nAbove all, I love the Spotify Wrapped nature of timelogging.\n\nIt forces me to confront how my time is actually spent, not how I think it\u2019s spent. 2024 wasn\u2019t about rethinking our vision but about acting on it. Less questioning, more doing. More systems that work, more deals getting done, more momentum.\n\nI didn\u2019t get busier\u2014I got sharper. They say what got you here won\u2019t get you there.\n\n2025 is simply about expanding our upside. The proof will be in the pudding.\n\n2024 \n\nSo, what\u2019s the TL;DR of 2024?\n\nIn Q1, we celebrated 5 years in biz. I hosted a 2-day offsite out West. I published my first story for Monocle Radio. ARS told me I had a way with words. I recorded my first sunset mix for Everyday Radio. My wife and I celebrated 9 years together.\n\nIn Q2, we delivered Retreat XXVI (26) in Napa, CA. I turned 29. Had my best-ever quarter for expert network calls. Man Utd won the FA Cup. We got a new couch. I took my first trip on a luxury bus. I had my meal of the year at Mila. We completed our refactoring of all podcast episodes for Everyday Library.\n\nIn Q3, I became an Irish citizen. I spent time in Montreal and Cancun. I crafted speeches and profiles at prestigious conferences in Italy and Germany. I finished our 5YR Brand Refresh: new logos, lockups, and business cards. We celebrated our 1st wedding anniversary in Santa Fe. I also completed my first Tour de Echelon (2023).\n\nIn Q4, we delivered Retreat XXVII (27) in Laguna Beach, CA. Our building has a new gym, sauna, and workspace. We signed our first enterprise hospitality partner on the Michelin Guide. I went home to London for Christmas and landed on a new tagline for Everyday as \u201cThe Modern-Day Hold Co.\u201d\n\nAll in all, I took 16 trips to 13 different cities, travelling 21,500 miles total.\n\nNow for the quarter-by-quarter breakdown.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ1: Slow Build\n\nThe theme of Q1 24 was Slow Build. Q1 23 was Refactoring.\n\nIn a way, they\u2019re connected yet wholly different.\n\nWhen I wasn\u2019t fundraising in Q1 23, I started refactoring years of the \u201cdigital detritus\u201d buildup in my iPhone, Drive, Kindle, MacBook, etc. As an obsessive reader and note-taker, this was no mean feat. Looking back, it was a valiant effort.\n\nHowever, I quickly learnt that detritus piles up because you 1) don\u2019t have a system to process it and 2) don\u2019t know its final purpose. Shifting an idea into something presentable is challenging when you haven\u2019t discerned the final container. It is akin to pinning the tail on the donkey with a blindfold, except you don\u2019t know the shape of the animal or where the wall is. I always knew I wanted the final container to be semi-public. My gut said it wasn\u2019t social media. The half-life wasn\u2019t long enough.\n\nI just didn\u2019t know how, where or why our stories should live on.\n\nBy Q1 24, I had my answer.\n\nOur rebrand from Everyday Entrepreneur (EE) to Everyday as a holding company at the end of 2023 was a mise-en-place moment. Everyday Radio emerged as the natural outlet for our media to date, and Everyday Library emerged as our \u201cbest-of\u201d archive. Everything clicked. I had containers I could continue to hone over the next five years, and they would eventually become even more valuable sources of context and personal knowledge in the era of AI.\n\nWith names and structures in place\u2014specific enough to mean something but broad enough to change\u2014I graduated from the refactoring role to systems builder. I still organize and prune my latest Apple Notes during my weekly review.\n\nHowever, we now have VAs doing the hard yards, editing, transcribing, and publishing everything into Everyday Library or Radio. For any piece of timeless content we\u2019ve created, the goal was to generate a live URL (proof) with a Tim Ferris show-esque transcript (quality). I only read podcast transcripts.\n\nThat was my definition of good enough from a user and distribution standpoint. I\u2019m proud to say we\u2019ve hit that mark. Here\u2019s a preview. We\u2019ve brought ~60 episodes online since the Fall of 2023, averaging ~1 per week.\n\nThis quarter wasn\u2019t about breakthroughs or pivots but about turning pro.\n\nShowing up Everyday and doing the work, even when the rewards weren\u2019t immediately clear, which they often never are with the most important things. It was a quarter of refinement (nod to Mark S), execution, and setting the stage for sustainable success\u2014tightening processes, refining structure, and ensuring my business and personal habits were built for durability. It was a slow endeavor, demanding patience, discipline, and trust in the process. And we\u2019re better for it.\n\nHere are the quotes from Q1 24 that are still front of mind for me:\n\nI: I said I was turning pro this year, which I define as doing what you have to do, even when you don\u2019t want to.\n\nII: For the first time in years, I feel in total control of my energy, time, and headspace. I know where to put them to get what I want, with a clear vision, structure and articulation for Everyday as a holding company.\n\nIII: Prompted by the rebrand to Everyday Radio, taking on a new URL, getting a new email, etc., I got super focused on cleaning up our entire podcast backlog from 2019 to the present. It\u2019s really been amazing.\n\nIV: Refactoring has also meant unpublishing episodes that aren\u2019t timeless or just don\u2019t quite fit Everyday Radio\u2019s new remit of killer music, minds and meditations.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ2: Work Clean\n\nThe theme of Q2 24 was Work Clean. Q2 23 was Life: A Full Contact Sport.\n\nTalk about a stark contrast. Q2 23 was probably the most intense quarter I\u2019ve had, period. I was in peak transition personally and professionally.\n\nOn the personal front, I was preparing to become a husband. Wedding prep was at full tilt. I celebrated my bachelor party in Vegas and, the very next weekend hosted our last-ever B2C retreat in D.C. with an exclusive tour of the White House.\n\nOn the business front, after raising $250K in 21 days, I became an investor-operator in my first hospitality deal. I was (somehow) back onto the circuit\u2014FT Weekend Festival in D.C., Monocle\u2019s Weekender in Asheville, and as a guest of honour at the Welcome Conference and The James Beards Awards in Chicago courtesy of Chef Katie Button and Resy. I even found the time to sit down with Foxtrot\u2019s founder, Mike LaVitola, and write a story on their 10th anniversary at their global HQ in Fulton Market for Monocle. Incredible timing, given what ended up transpiring.\n\nThrow in trips to Atlanta for a best mate\u2019s wedding and a trip to Arkansas to see my little brother during his study abroad year, and it was pure and utter craziness.\n\nA year later, Q2 24, life is much calmer. \n\nWe\u2019ve got a tailwind. Crushed our second creator retreat in Napa Valley. Executed 100% remotely. I love being a curator, not a convener. I feel more in control of my own destiny. Capturing value commensurate with the true impact we\u2019re creating. Hospitality is emerging. I have a sit down with the Chairman of the Illinois Restaurant Association. I send a few cold emails. The raise is long over, but I\u2019m still cooking in hospitality\u2014manual labour from years prior has been reduced by AI.\n\nI\u2019m recording my sunset mixes a year after holding that cigar bar in Atlanta. I took that guy\u2019s words to heart. Wild. Finding an outlet that allowed me to reconnect with my love for storytelling and music was essential and integral to my vision of bringing taste and intentionality into every space I engage with. I was finding my rhythm and just working clean. I stayed focused on the motions that mattered most.\n\nHere are some quotes from the Q2 24 that are still front of mind for me:\n\nI: My consulting friends tell me their perpetual dream is to retire and take calls like this from the beach for GLG, Tegus, et al. I might just beat them to it.\n\nII: I held down a cigar bar in Atlanta for two nights last year, and a top executive from EMPIRE told me I had great taste in music. \n\nIII: Nobody takes a data-driven approach to identifying, creating and capturing more lifetime value (LTV) from a restaurant\u2019s truest fans. That\u2019s what we provide.\n\nIV: I want to apply my taste to the spaces and brands I rock with most in this game called life. \n\nV: In case you missed it, I record a music show every other week. I curate a playlist of 15-20 of my favourite tracks based on the weather and time of that day. There is no intervention, autotune, mixing, or adverts. It\u2019s just me, you, the views, and the tunes. I call this my version of NPR Tiny Desk.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ3: On, Not In\n\nThe theme of Q3 24 was On, Not In. Q3 23 was In Transition.\n\nQ3 23 was a comedown for sure. It\u2019s not easy to try to process the time of your life.\n\nA 4th of July weekend at the Lake with my family. A Ryder Cup UK vs USA golf tournament at Ravisloe CC (my favourite course in the city). Cuts & Shaves at Blind Barber for some of my boys sippin\u2019 Natural Vino by. A beautiful rehearsal dinner and welcome party at Ada St. I\u2019ll never forget MGMT blaring out on the speakers in the warm summer Chicago air, drink in hand with all my favourite people in the world around me. Stunning suite with city views at the Trump. Married at Assumption. Wedding at Ivy Room. Honeymoon in British Colombia. Seaplane. Sun. Sauna. Massages. Aperol Spritz in hand. It was all just incredible.\n\nReturning to reality while adjusting to a new one isn\u2019t easy. Looking back, it\u2019s clear that I was still figuring things out. The words In Transition speak volumes even now. We\u2019re pivoting the business. I\u2019m teasing the library and travel platform in my letters. I still hadn\u2019t delivered our first B2B retreat, which is nuts, so I was still in a somewhat B2C headspace. It\u2019s so clear now B2C was never our true endgame.\n\nI\u2019m trying to get my greencard application done. All the medical tests, the jabs, the back and forth with our lawyer. Setting up joint bank accounts. I\u2019m still on OPT. My visa ends in August. I was buckling up not to work or travel abroad until April 2024. It was a lot. Probably more than I even realized at the time. My sense is I was quite stressed. Although I could definitely see the light at the end of the tunnel.\n\nI\u2019m so thankful to have made it through. By Q3 24, I\u2019d simplified, and so had life.\n\nGreencard in-hand. My visa woes were finally over for good. I\u2019m travelling like a free man, celebrating my friend\u2019s 30th birthday and bachelor\u2019s parties abroad. I\u2019m grooving at a Fred again concert up in Lake Geneva. Playing golf. I\u2019m having a blast.\n\nI secured my second (Irish) citizenship on the last day of Q3 24 and got dapped up by the Head of Global Entry upon my return to ORD. He made the rest of the line wait until he\u2019d finished catching up with my wife and I. The comparison is wild. I\u2019m not sure my younger self would believe it. To think what life was like a year prior?\n\nOn top of that, a year after I returned capital, Everyday Hospitality is starting to emerge. AI has supercharged the product, taking our process and outputs to the next level. I also found joy in rediscovering the simple pleasures: curating playlists for friends, exploring new cities on foot and reflecting on my journey so far.\n\nThe Q3 24 On, Not In theme wasn\u2019t just a business philosophy but a lifetime mindset. Focusing on the big picture and laying the foundations for years to come.\n\nHere are some quotes from the Q3 24 that are still front of mind for me:\n\nI: It\u2019s true: much of my love for America stems from the fact that you can always pay to skip the line. And there isn\u2019t a better skip-the-line pass in life than Global Entry.\n\nII: My three rules for public speaking are one laugh, one hmm, and one wow. That\u2019s your only job. If you can build around a killer talk around that, you\u2019re good.\n\nIII: Much like WHOOP\u2019s Strain, Sleep, and Recovery scores, we aim to build a slate of metrics that reveal how hospitality groups are truly doing Everyday.\n\nIV: When we started in 2019, we went by Everyday Entrepreneur. We dropped the Entrepreneur at the end of 2022, and Everyday became the name for the overarching holding company last year. In JT\u2019s words, it just felt cleaner.\n\nV: I\u2019ve kept every business card I\u2019ve ever been given. And I\u2019ll say some have aged better than others. Years later, even if I can\u2019t remember the face, as long as the card is fresh, it tells me everything I need to know about that business.\n\nVI: If you\u2019re looking for a playlist to help you through winter, christen a new space, or get you into a particular headspace, hit me up. I\u2019d love to curate one for you.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nQ4: Home Again\n\nThe theme of Q4 24 was Home Again. Q4 23 was Foundations.\n\nOf all the quarters, this one is perhaps the craziest for comparing and contrasting YOY. I headed home to London in Q4 24 for Christmas, having executed three B2B retreats in the past 12 months.\n\nThe last time I was home, Q2 22, I hosted our penultimate B2C retreat. Since then, everything has changed, and nothing has changed. IFYKWIM.\n\nThis starkly contrasts with Q4 23, when we were still preparing to deliver our first B2B retreat in Half Moon Bay, CA. At this point, I\u2019d delivered countless retreats, but always as the convener\u2014attending myself, selling tickets, and playing host.\n\nHowever, shifting to B2B changed everything. I no longer had to be the convener.\n\nI graduated to curator. In 2024, I proved I could deliver arguably an even better experience in this role. I didn\u2019t have to be physically present to provide a world-class retreat experience. I disrupted my own playbook, and the results speak for themselves: cleaner execution, better margins, and all-around sustainable effort.\n\n\nGetting on the right side of convening (curation), hospitality (analytics), and immigration (greencard) changed everything.\n\nThat\u2019s part one. Part two?\n\nIn Q4 23, I was still waiting on my green card. By Q4 24, I\u2019d had it for an entire year\u2014and just secured my second (Irish) citizenship. In two years, I\u2019ll complete the passport trifecta and apply to become a U.S. (read: triple) citizen.\n\nWTF? Talk about zero to hero. My in-laws are playfully calling me secret agent.\n\nThis is where everything comes into focus. The thorniest issue of my life\u2014immigration\u2014was solved overnight. My biggest weakness for a decade became my greatest competitive advantage for a generation. It\u2019s funny how life works like that.\n\nA decade of patience, paperwork, and always doing the right thing paid off. Even wilder? A close friend from Notre Dame and a fellow British international student were also approved for his GC on the same day as me. We\u2019d fallen out of touch after school but reconnected serendipitously on the same flight home to London. We spent most of our time crossing the Atlantic catching up in the galley\u2014a full-circle moment. There is nothing better than winning and levelling up with your people.\n\nQ4 23 was chaos. But in just 78 days, everything changed. My greencard approval gave me something I\u2019d never had before: permanent stability in the United States.\n\nLast but not least, hospitality.\n\nA year ago, I made the tough\u2014but ultimately correct\u2014decision to return capital for a restaurant deal. At the time, it felt brutal. But in hindsight, it was necessary to set the stage for something even bigger. Resy invited me into Global Dining Access as a partner later that fall, and a year later, in Q4 24, we signed our first enterprise deal with a 10-unit group on the Michelin Guide. That\u2019s another full-circle win.\n\nReturning capital wasn\u2019t a failure\u2014it set the foundation for a brighter future. I trusted myself and found the right level of abstraction. Now it\u2019s time to rock.\n\nGetting on the right side of convening (curation), hospitality (analytics), and immigration (greencard) changed everything. A year ago, I felt like I was pushing against gravity\u2014now? Everything is in motion. This is just the beginning.\n\nHere are some quotes from the Q4 24 that are still front of mind for me:\n\nI: I\u2019ve long said that Christmas in America often feels like just a day, whereas in the UK, it\u2019s a proper week-plus holiday celebration. I feel fortunate to experience the best of both worlds\u2014Thanksgiving in the USA and Christmas in the UK.\n\nII: In my humble opinion, College Football is America\u2019s best export.\n\nIII: The real challenge \u2014 and $1B question \u2014 isn\u2019t how or when to bring people back to the office but why they\u2019ll want to stay there long term. It\u2019s about creating compelling reasons for your people to want to exist in the physical spaces you own.\n\nIV: I see so many brands, businesses, and individuals settling for the classic one-day event or workshop. My message is: think bigger. We can help you curate experiences that truly resonate, stand out and endure over time. If you\u2019re not committed to doing that, what\u2019s the point? The world doesn\u2019t need any more bang-average events.\n\nV: I felt it was time for a new tagline. I settled on \u201cModern-Day Hold Co.\u201d\n\n2025: Looking Ahead\n\nAs I look towards 2025, I feel an immense sense of potential.\n\nThat potential will be realized by continuing to do what we do best\u2014advising, analyzing, and curating\u2014while systematizing every aspect of the business. New transcripts will be published weekly, leads will be meticulously researched, and beautifully crafted emails will be sent out. My drafts folder needs to be zeroed out. 2/3 of this is already in place. Now, it\u2019s about being ruthless in the final 1/3.\n\nExternally, the focus is clear: grow profitably. Our products and pricing models are becoming more refined, tested, and mature, a prerequisite for GTM success. We can confidently focus on sourcing new strategic partners across the portfolio.\n\nI want this year to be our best yet.\n\nI\u2019m clear on what we sell, why we sell it and who we sell it to.\n\nThis year has been exceptional. I must put at least another 4 in at this level or above.\n\n]]>\n  \n  \n    Taha Memon\u2019s Post\n    https://www.linkedin.com/posts/tahamemon_saudivc-venturecapital-vision2030-activity-7311040551556972546-dWRY/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAALkv4BTofKmG92LxlnRhQHdizotUKgWrc\n    readwise:01jqcct422kgc88jy4awdtwswp\n    Thu, 27 Mar 2025 18:11:12 +0000\n    linkedin.com\n     Taha Memon \n\nMulti Exit Founder-Advisor to companies entering the Kingdom of Saudi Arabia- CEO Founders Club International\n\nTop Venture Capital Firms in Saudi Arabia \ud83c\uddf8\ud83c\udde6\n\nEmpowered by Vision 2030, Saudi Arabia captured over 42% of investments in the MENA region in 2024, a testament to its growing influence in the global market.\n\nHere are some of the top VC firms driving innovation and backing game-changing startups in the Kingdom:\n\n1) Aramco Ventures\n Fueling energy innovation with a focus on sustainability, advanced materials, and cutting-edge tech.\n\n2) Nama Ventures\nEmpowering early-stage startups with a strong emphasis on technology and team-driven ventures.\n\n3) RAED Ventures\nBacking transformative tech startups, with a keen eye on financial inclusion and digital transformation.\n\n4) SVC (Saudi Venture Capital Company)\nBoosting the Saudi VC ecosystem through strategic investments across diverse sectors, from fintech to e-commerce.\n\n5) Wa'ed Ventures \nA $500M fund by Saudi Aramco, fostering innovation in sustainability, digitalization, and social impact.\n\nThese firms aren\u2019t just investing capital, they\u2019re building ecosystems, driving change, and unlocking new opportunities across industries. Whether you\u2019re an entrepreneur seeking funding or just curious about the venture scene in Saudi Arabia, these firms are ones to watch. \ud83d\udc40\n\n#SaudiVC #VentureCapital #Vision2030\n\n \n \n  \n \n  \n \n  \n \n  \n \n  +1   ]]>\n     Taha Memon \n\nMulti Exit Founder-Advisor to companies entering the Kingdom of Saudi Arabia- CEO Founders Club International\n\nTop Venture Capital Firms in Saudi Arabia \ud83c\uddf8\ud83c\udde6\n\nEmpowered by Vision 2030, Saudi Arabia captured over 42% of investments in the MENA region in 2024, a testament to its growing influence in the global market.\n\nHere are some of the top VC firms driving innovation and backing game-changing startups in the Kingdom:\n\n1) Aramco Ventures\n Fueling energy innovation with a focus on sustainability, advanced materials, and cutting-edge tech.\n\n2) Nama Ventures\nEmpowering early-stage startups with a strong emphasis on technology and team-driven ventures.\n\n3) RAED Ventures\nBacking transformative tech startups, with a keen eye on financial inclusion and digital transformation.\n\n4) SVC (Saudi Venture Capital Company)\nBoosting the Saudi VC ecosystem through strategic investments across diverse sectors, from fintech to e-commerce.\n\n5) Wa'ed Ventures \nA $500M fund by Saudi Aramco, fostering innovation in sustainability, digitalization, and social impact.\n\nThese firms aren\u2019t just investing capital, they\u2019re building ecosystems, driving change, and unlocking new opportunities across industries. Whether you\u2019re an entrepreneur seeking funding or just curious about the venture scene in Saudi Arabia, these firms are ones to watch. \ud83d\udc40\n\n#SaudiVC #VentureCapital #Vision2030\n\n \n \n  \n \n  \n \n  \n \n  \n \n  +1   ]]>\n  \n  \n    How Countries Go Broke: The Overall Big Cycle\n    https://www.linkedin.com/pulse/how-countries-go-broke-overall-big-cycle-ray-dalio-r74fe?utm_source=share&utm_medium=member_ios&utm_campaign=share_via\n    readwise:01jqarew7g40ba0s4hnmjazek1\n    Thu, 27 Mar 2025 02:56:18 +0000\n    linkedin.com\n    \n \n \n \n \n\n Ray Dalio \n\n Founder, CIO Mentor, and Member of the Bridgewater Board \n\nIf I had to pick the most important chapter in the book, this would be it. That is because it deals with the biggest and most important forces that are dramatically changing the world order, and it shows how and why these forces have repeatedly driven history through its big cycles. Having seen so many of these cycles, watching what is happening is like watching a movie that I have seen many times before\u2014just a contemporary version in which the clothes that the people are wearing and the technologies that they are using are more modern. I hope to show you what I see. Also, by showing what happened in the past and why it happened, we can understand how previously unimaginable developments are now happening and could happen in the future.\n\nWhile this book is mostly focused on understanding what\u2019s going on with debt/credit/money/economic cycles, we can\u2019t look at this dynamic in isolation and make sense of it because how these cycles transpire is influenced by other big forces. Similarly, to understand what is happening in other areas, we need to understand the debt/credit/ money/economic force as it has big effects on developments in most areas. Together, five big forces produce the Overall Big Cycle that leads to radical changes in monetary, domestic, and/or world orders.\n\nI comprehensively explained how this Overall Big Cycle works and how it was manifest over the last 500 years in Principles for Dealing with the Changing World Order, but I won\u2019t cram that 600-page book in here. Instead, I am going to give you a brief summary. That way, when we turn to Part III about what has happened in our current Big Cycle, and Part IV, in which I will try to look into the future, you will be able to see how what actually happened compares with my templates of both the Big Debt Cycle and the Overall Big Cycle.\n\nHOW THE MACHINE WORKS\n\nBecause everything that happens has reasons that make it happen, it appears to me that everything changes like a perpetual motion machine. To understand this machine, one needs to understand its mechanics. Because everything affects everything else directly or indirectly, these mechanics are very complex. Sometimes I try to explain what I know about them with enough of their complexity to show them in useful detail, such as I did previously in this book to explain how countries go broke. And sometimes I try to explain them simply. As the saying goes, \u201cAny fool can make something complicated. It takes a genius to make it simple.\u201d In this chapter, I will try to explain the Big Cycle simply. I will begin by explaining my approach.\n\nAs a global macro investor for most of my life, I have tried to understand and model the cause/effect relationships and use my models to bet on what will happen in the markets. To do that, for about the last 35 years, I have created computerized expert systems that enable the computer to make decisions like I make them. These systems are based on the following principle:\n\nDecision-making systems should be based on timeless and universal relationships, meaning that they should explain all the big, important developments in all time frames and in all countries, though not necessarily precisely or in detail. If they fail to explain all the big developments in all time frames and in all countries, that indicates that an important influence is missing and needs to be added to the template/model.\n\nThe expert systems I have built are previously developed forms of artificial intelligence. Now, with various breakthroughs in artificial intelligence, I am\u2014and I believe we all are\u2014on the brink of being able to understand all of the cause/effect relationships that drive everything, though for now we still have to labor along the old-fashioned way, with people studying what happened using the computing and AI tools available today. That is why, in my own feeble attempts to understand and describe the most important mechanics that change the world as we know it, I do these in-depth studies and create explanations of them. What I am about to describe is a result of this process. However, because the forces that drive the Big Cycle are so big, it is easy to see and understand them without worrying about the details and the complexities.\n\nZooming out to the highest level, the five most important drivers of change are:[1]\n\n1. The debt/credit/money/economic cycle\n\n2. The internal order and disorder cycle\n\n3. The external geopolitical order and disorder cycle (i.e., the changing world order)\n\n4. Acts of nature (droughts, floods, and pandemics)\n\n5. Human inventiveness, most importantly of new technologies\n\nThese forces affect each other to shape the biggest things that happen, creating cycles that move markets and economies around an upward-sloping trend line. The incline of its upward slope is primarily driven by the inventiveness of practical people (e.g., entrepreneurs) who are given adequate resources (e.g., capital) and work well with others (their coworkers, government officials, lawyers, etc.) to make the inventions and products that create productivity improvements.\n\nOver a short period of time (i.e., 1-10 years), the short-term cycles, especially the debt and political cycles, are dominant. Over a long period of time (i.e., 10 years and beyond), the long-term cycles and the upward-sloping trend line in productivity have much bigger effects.\n\nAs I explained earlier, conceptually the way this dynamic transpires looks like this to me:\n\n\n\nI will now delve into these five forces. While reading about them, please think about how these forces have worked and how they are working now. That will help you see how and why \u201chistory rhymes\u201d and better understand what is now happening and what is likely to happen.\n\nHOW THE OVERALL BIG CYCLE WORKS: THE FIVE BIG FORCES\n\nWe are now 80 years into the Overall Big Cycle that began at the end of World War II, which is by and large unfolding in the classic ways that will produce dramatic changes that one can only imagine by visualizing these five forces interacting simultaneously in a historical context.\n\nMore specifically:\n\n1. The Debt/Credit/Money/Economic Cycle\n\nThroughout this book, I have described the most important things that influence the Big Debt Cycle (like debt service payments relative to income, the amount of new debt sold relative to the demand for it, the desirability and willingness of debt asset holders to hold their existing debt assets, and other factors explained earlier, etc.).\n\nBecause I have already covered this Big Debt Cycle so completely that you are probably sick of hearing about it, I won\u2019t say much more.\n\nI will just reiterate the main points I want to get across, which are:\n\n \nThere has always been, and I expect that there will always be, short-term cycles that over time add up to Big Debt Cycles. \nThe average short-term debt cycle has typically taken about six years, give or take about three (with the duration of that cycle dependent on a number of influences that we can monitor and use to come up with rough estimates of how long each one will last). \nThe average long-term Big Debt Cycle has typically taken about 80 years, give or take 25 years (with the duration of that cycle also driven by a number of influences that we can monitor and use to come up with rough estimates of how long each one will last). \nThese debt cycles are influenced by and influence other things, most importantly what I have identified as the four other big forces. \n\nTo summarize the dynamic in a few sentences, what has timelessly and universally (i.e., throughout the millennia and across countries) driven the Big Debt Cycle changes and has created the big debt and economic problems is the creation of unsustainably large amounts of debt assets and debt liabilities relative to the amounts of money, goods, services, and investment assets in existence. This always has led to big debt crises and runs on banks. By a run, I mean a turning-in of debt assets (that have no intrinsic value\u2014i.e., their only value is to buy things) to banks in order to get real money, which the bank doesn\u2019t have enough of to meet the demand. Classically, when the holders of those financial assets actually try to convert them back into money and buy things and see that they can\u2019t get the buying power they believe they have stored in their debt assets, the run accelerates and feeds on itself, which causes great shifts in markets\u2019 values and wealth until debts are defaulted on, restructured, and/or monetized, reducing the debt burdens relative to incomes, and a new equilibrium is reached. The debts are almost always monetized, by which I mean that it is almost always the case that the central bank creates a lot of money and credit to make it easier to pay back the debt, which devalues the money and debt.\n\nIt\u2019s worth noting that at times when the debt/money force, the internal order force, and the external order force are late in their cycles (i.e., when there is a lot of debt and a lot of internal and external conflict), it is typically just before big conflicts and revolutionary changes to monetary orders, internal orders, and world orders. Like a life cycle, the Big Cycle goes through stages. This late-cycle stage, which I call Stage 5, comes just before the depression and war stage that brings about the end of the Big Cycle. For reasons I will explain later, I believe that we are now in this late-cycle stage. It is a time of radical, typically unexpected changes that haven\u2019t happened in one\u2019s own lifetime but have happened many times throughout history. At such times, it is extremely valuable to understand these past cases of big changes and consider whether they could happen again.\n\nIn Principles for Dealing with the Changing World Order, I examined a number of such cases. Since history can be an effective guide for understanding cause/effect relationships and bringing perspective on what is now happening and might happen, we can use these historical cases to think about what\u2019s logically likely to happen under the existing circumstances.\n\nSo, what are the existing circumstances? At this time, there is great over-indebtedness and in all other major countries at the same time as there are increasingly nationalistic and fragmented internal orders in these countries, increasingly contentious relationships between countries, adverse and expensive acts of nature, and amazing new technologies.\n\nLooking at past cases with similar configurations of conditions can help us imagine otherwise unimaginable possible developments. For example, I repeatedly saw, and will show you in the next part of this book, that, when faced with similar conditions of excessive debt, countries (including the US) took the following extraordinary actions:\n\n \nExerting great pressure on countries to buy the country\u2019s debt (as the British did in the past) \nSelectively freezing debt and/or taking the assets of \u201cenemy\u201d countries (the way the US did to Japan in 1941 and Russia more recently) \nDefaulting on/restructuring debts by extending maturities and/or monetizing them to cut debt burdens (the way Germany did after Hitler came to power) \nImposing confiscatory taxes and capital/foreign exchange controls to prevent assets from leaving the country \nRevaluing/managing government assets \nCreating new types of money \n\nTo be clear, I am not saying that these sorts of things will happen, and I am hesitant to raise them as possibilities because my doing so could engender exaggerated fears, which could prompt inappropriate and exaggerated actions. However, like a good doctor speaking to a patient suffering from serious conditions, I feel that it would be an irresponsible omission of mine not to convey what past cases tell us about the possibilities that sometimes accompany these conditions.\n\n2. The Internal Order and Disorder Cycle\n\nWithin countries, there are both short-term political swings lasting about six years on average, give or take three years, that over time add up to big shifts in domestic orders that last about 80 years, give or take 25 years. To reiterate, I don\u2019t mean that these time frames are fixed because they are highly variable in duration, but I do mean that they have always happened and I believe always will happen, with the durations driven by influences that we can monitor and use to come up with rough estimates of how long each one will last.[2]\n\nThese are the cycles that exist within countries and lead to conflicts and changes in the system of governance, or what I\u2019m calling \u201corders.\u201d These fights for power work basically the same way in all systems of government, all types of organizations, and even within families because the approaches to fighting them are embedded in human nature.\n\nSo, how do they work?\n\nIt\u2019s simple: nothing lasts forever. That includes the orders built around established leaders and governance systems. Changes in orders are driven by those who have the greatest power getting to determine what is done. Orders change when those who don\u2019t run the existing order acquire more power than those who do and want to change it. Fights occur when both a) a powerful group wants to change the order and b) it is not clear which side has more power, so only a fight can determine it. Fights don\u2019t occur if a) there isn\u2019t a powerful group that wants to change the order and/or b) there is a powerful group that wants to change it and is so much stronger than the existing group that the changes will take place with little or no fighting.\n\nIn democracies, there is an election cycle that roughly coincides with the economic cycle because bad economic conditions typically lead to political changes. At the beginning of a new popularly chosen leader coming to power\u2014e.g., in the first 100 days of a new presidency\u2014there is a honeymoon period and great optimism. That is when dreams of great changes and great improvements exist and before realities and criticisms of how the new leader has shaped and handled them set in. As time passes, typically the big promises the leader made to get elected become difficult to deliver and bad things happen so disappointment sets in, critics and enemies become bolder, and support wanes. All this makes fighting to stay in power harder, which often leads to more extreme actions to make that happen.\n\nThese dynamics are at play in the US at my time of writing this book In March 2025. How things go typically depends mostly on the economy, which depends mostly on where the market- and economy-shaping short-term and long-term debt/credit/money/economic cycles are, though exogenous events (like droughts, floods, and pandemics, and big international or domestic conflicts) can also matter.\n\nAll governance orders within countries change from one type to another\u2014e.g., from democracies to autocracies and from autocracies to democracies\u2014and each major type of order comes in varying flavors with some managed well and some managed poorly. I will now focus on what happens when democracies fail.\n\nWhen democracies fail, autocracies come in.\n\nIn my studies of how orders have changed throughout history, I have seen how changes from republic-style representative democracies to autocracies typically happen. These changes are exemplified in how Julius Caesar in ancient Rome (from 49 to 44 BCE), Napoleon Bonaparte in France (from 1799 to 1815), Benito Mussolini in Italy (from 1922 to 1943), Adolf Hitler in Germany (from 1933 to 1945), a consortium of leaders in Japan (from 1931 to 1945), Francisco Franco in Spain (from 1936 to 1975), Recep Tayyip Erdogan in Turkey (from 2016 until now), and many other countries\u2019 leaders have shifted to become autocratic leaders. I also read about it in Plato\u2019s Republic, written around 375 BCE, which is still a valuable description of how democracies become autocracies.\n\nIn almost all cases, there are large gaps in wealth and values, bad and worsening conditions, and weak, fragmented leadership in the republic-style representative democracies. These democracies can\u2019t fix their problems because democracies intrinsically rely on compromise between opposing factions, and compromise breaks down during such times. So, instead of following the laws and the system of compromise, the opposing sides become willing to fight to win at all costs. Typically, this leads to intensifying populist conflicts between those of the hard right, those of the weak middle, and those of the hard left. Conflicts increase, especially during times of economic stress, which leads to fights for the power to control. How these fights for power take place are largely similar for logical reasons that I will explain.\n\nPlato pointed out, and my study of history showed me, that leaders in democracies typically appeal to their constituents\u2019 desires for immediate benefits and temporary relief rather than doing the hard things that address deeper, systemic issues and make their nation strong over the long term. I have seen and read historical accounts of how leadership also typically becomes weak, decadent, and corrupt, especially after periods of great prosperity and few challenges. Plato argued that when democracies become weak and decadent and lose sight of justice and virtue, they pass their peaks and begin their declines. These periods are typically marked by growing corruption, inequality, and a failure of institutions to function effectively. When the system no longer satisfies the needs of a large percentage of the people, it loses legitimacy. Independently, and long before Plato observed this, this dynamic was recognized in China (as far back as 1046 BCE), where it is called \u201closing the mandate of heaven.\u201d It is when and why orders fail.\n\nIn times of disorder, financial, political, and military power matter more than laws, and authoritarianism works better than weak, disorganized collectivism.\n\nPlato called the person who typically leads the revolutionary changes from democracy to autocracy a \u201cdemagogue.\u201d Demagogues manipulate public opinion, stir up emotions, and use extraordinary means to gain power. They typically rile up populist sentiment, promise easy solutions to complex problems (often at the expense of truth or rational discourse), and use propaganda and bullying to gain and increase power. They are generally of the well-educated class and gather around them others who are powerful. When they are of the political hard right, they and those who support them are typically rich and powerful nobles (in the old days) or capitalists (since the Industrial Revolution) who are allied in their belief and their self-interest that great leadership requires strong leadership and strong partnerships from the top, like strong companies that have to work well together to do great things. When demagogues are of the left, they typically get their support from the unprivileged masses. As these populist leaders, whether they are from the right or the left, gain power, they typically employ tactics such as propaganda, coercion, and the consolidation of power to undermine their enemies and the democratic institutions that support their enemies and/or that support the inefficient bureaucracies that are enabling the problems rather than fixing them. This typically leads to the eventual replacement of democracy with a more centralized, dictatorial form of government.\n\nThe approach a strong CEO uses in running a company can be difficult to distinguish from a demagogue\u2019s approach. In fact, it can be said that some strong CEOs govern as demagogues, so it should be expected that if they were running governments, they would run them the same way. In both cases, they are people who take control and make radical changes to make radical improvements, and the big questions are what will the controls on them be and how far will they take the autocracy. If looking at a company, one should see if there is strong oversight and a controlling force like a strong board and controls from effective regulators; for governments, such controls come from oversight functions and the separation of powers. The more uncontrolled they are, the more dictatorial the leaders are likely to become. A relevant good principle is power corrupts and absolute power corrupts absolutely, a phrase attributed to historian and politician Lord Acton in 1887.\n\nIn the new order that emerges, financial and political power matters more than laws, and authoritarianism works better than weak, disorganized collectivism.\n\nIn most of these cases, the transfers from the democracies to autocracies take place within the rules of the democracy and become increasingly extreme over a few years, usually around three to five. These leaders typically make radical changes to the monetary, political, and geopolitical orders, and they typically become very nationalistic, militaristic, expansionist, and autocratic. As mentioned, examples include Caesar in Rome, Napoleon in France, Hitler in Germany, and Mussolini in Italy.\n\nIn ways that were more thoroughly explained in Principles for Dealing with the Changing World Order and that should be apparent to observers who are watching what is happening today, this is now taking place with big political shifts (mostly toward the hard right) for the same reasons that they happened in the past.\n\n3. The International Order and Disorder Cycle (i.e., the Changing World Order)\n\nHow countries deal with each other is of paramount importance and it, too, is cyclical.\n\nFor the same reason that there are periods of order (i.e., periods of harmony, productivity, and prosperity) and periods of disorder (periods of great conflict, destruction, and depression), and big cyclical swings between these periods within countries, there are periods of order (periods of harmony, productivity, and prosperity) and periods of disorder (periods of great conflict, destruction, and depression) between countries. The periods of disorder take place when there are fights to determine which country or countries will have the power to set what type of order exists. However, because there has never been an effective global governance system, the world order is more prone to disorder and conflict.\n\nAs part of the Big Cycle, there have also been big swings between a) unilateralism in which there is fighting for one\u2019s self-interest, the strong winning over the weak, and the law of the jungle/the survival of the fittest and b) multilateralism in which there is striving for global harmony, peaceful coexistence, and egalitarianism.\n\nHistorically, the only times that multilateralism worked were after wars when people were sick of fighting and there was a dominant power to enforce how things should go. In fact, throughout most of history, brutal and destructive unilateralism was the norm and periods in which there was multilateralism in pursuit of harmony, peaceful coexistence, and the common good were extremely rare and never sustained. Consider that it wasn\u2019t until 1648, after the terrible Thirty Years\u2019 War, that there was an agreement in Europe (the Peace of Westphalia) establishing that countries have borders and that all countries would pledge to enforce those borders rather than to simply fight one another to get what the other had, which up until then was the norm (though these pledges not to fight have only worked sporadically).\n\nAlso consider that it wasn\u2019t until after World War I, when Woodrow Wilson, the idealistic academic president of Princeton University who became president of the newly powerful United States in 1913, na\u00efvely aspired to have a world governance system that imitated the US governance system, the League of Nations. It didn\u2019t last and failed to prevent World War II, which was followed by the new American world order, which created multilateral organizations like the UN, the IMF, the World Bank, the World Health Organization, the World Trade Organization, the International Court of Justice, the World Intellectual Property Organization, etc. These organizations aimed to foster global cooperation, economic stability, and collective problem-solving. The US, leveraging its unparalleled economic and military power, became the linchpin of this liberal international order, promoting democracy, free markets, and human rights. While not without its flaws, this system maintained a relative stability that has so far prevented another world war.\n\nWhile we all have lived through a time when multilateralism\u2019s striving for harmony, peaceful coexistence, and egalitarianism was of course what we all wanted, multilateralism is now fading into irrelevance and unilateralism is rising for reasons that are understandable in the context of history. As a result, the powers of multilateral organizations are declining rapidly and transitioning into the hands of the major powers. I believe that realists must accept the fact that both the aspiration for and the existence of global cooperation are eroding as the pendulum is swinging toward self-interested unilateralism and survival of the fittest. It increasingly becomes the case that the strong prey on the weak. These developments are all typical of the stage of the Big Cycle that we are now in.\n\nWhile this transition from multilateralism to unilateralism is at first shocking, it quickly becomes normalized. For example, it was only months before this writing that Donald Trump\u2019s statements concerning Greenland, Canada, and the Panama Canal would have been considered unimaginable (much like Russia\u2019s use of military force to defend what it saw as its interests by invading Ukraine if its interests weren\u2019t guaranteed peacefully).\n\nAt such times, alliances often change fast as circumstances change quickly and winning is more important than loyalties.\n\nTo help us imagine the future, we should pay close attention to the lessons from history. Through most of history, without the existence of countries with borders, collections of people with common interests (i.e., tribes) fought to seize wealth from other tribes or defend their own. As those who won got richer and more civilized, they typically got more decadent and weaker and were eventually taken down by stronger barbarians, who were in turn brought down by subsequent generations learning to be stronger. For example, that is the story of the rise of the Roman Empire and its defeat by the Gauls as well as the rises and falls of most dynasties, and with them, the rises and declines of leadership approaches. These alternating ages of barbarianism and civility contributed to periods of war that took down the more advanced civilizations when the barbarians were strong and civilizations were weak.\n\nHistory has repeatedly shown us that civility when taken too far creates weak decadence that eventually loses to strong barbarism.\n\nThe peaceful and productive, modern-day version of this is the \u201cfighting\u201d that happens in business with the invention of new and effective business ideas/weapons that fuel creative destruction. We love to watch these fights, which are like watching fights in the Roman Colosseum, or better yet we love being in them. Frankly, I love being in them, and I detest impractical idealism (while I love practical idealism above all else). But the destructive version of this same impulse leads to a lack of cooperation and to fighting in politics, geopolitics, dealing with acts of nature (particularly climate change), and new technologies, and I worry a lot about it.\n\n4. Acts of Nature (Droughts, Floods, and Pandemics)\n\nThroughout history, acts of nature have killed more people than wars and toppled more orders than the previously mentioned forces, and an objective view of the data shows that droughts, floods, and pandemics are increasing and increasingly costly. While why this is happening is debated, that it is happening is not debatable. Nor is it debatable that humanity\u2019s polluting and disrupting of nature, higher human population density, closer contact across the world (brought about by more international travel), and closer contact with other species due to land development (leading to animal-human disease transmissions) are all causes. We regularly see these happening in the news, most recently with the Los Angeles wildfires. It is also almost certain that these problems will get worse.\n\nAs with the other forces, this force is intertwined with the other big forces to shape what is happening. For example, the migration issues in developed countries (with immigration pressures resulting from changes in climate) and the living conditions issues in underdeveloped countries (where people are struggling to adapt to droughts, floods, and other changes) are obviously worsening due to damaging acts of nature increasing, and given that nearly all nations are facing debt issues, there isn\u2019t enough money to be spent on climate mitigation or adaptation.\n\n5. Human Inventiveness, Most Importantly of New Technologies\n\nThere are great advances in technology, particularly in artificial intelligence, that will dramatically affect all thinking in all areas for good or for bad.\n\nThroughout history, technological advances have raised living standards and life expectancies, have been used to generate economic and military power, and have been used in wars to create great destructions. They are closely tied to the other four forces. When technological advances are supported by good financial, economic, and social conditions, they advance more quickly than when those conditions are bad. But when their developments are supported by unsustainable credit growth, they tend to cause financial bubbles and busts. For example, the South Sea Bubble in 1720 when the Dutch Empire was beginning to decline, the Railway Mania in the 1830s and 1840s, the electricity and utilities bubbles (the \u201cWar of the Currents\u201d) in the 1870s and 1890s, and the dot-com bubble and telecoms crash of 1990-2001 are all relevant examples of cases where great advances in major life- and productivity-improving technologies led to debt bubbles and busts, as well as big beneficial changes.\n\nThat\u2019s enough of the Big Cycle for now\u2014enough to help you better understand the dynamics you\u2019ll read about in Part III as you look at the events that have unfolded since our current Big Cycle began in 1945 with the end of World War II. It will also help you understand the perspective I take when I attempt to look into the future in Part IV. But before we move on, it is worth sharing one final principle, which has the biggest impact on how the challenges that arise during the Big Cycle are handled, namely: \n\nThe biggest and most important force is how people deal with each other.\n\nIf people deal with their problems and opportunities together rather than fight each other, they can get the best possible results. Unfortunately, while technology has evolved a lot, human nature hasn\u2019t changed much, so this is still probably beyond the capabilities of humankind.\n\nThe views expressed in this article are mine and not necessarily Bridgewater\u2019s.\n\nThe information provided herein is not intended to provide a sufficient basis on which to make an investment decision and investment decisions should not be based on simulated, hypothetical, or illustrative information that have inherent limitations. Unlike an actual performance record simulated or hypothetical results do not represent actual trading or the actual costs of management and may have under or overcompensated for the impact of certain market risk factors. Bridgewater makes no representation that any account will or is likely to achieve returns similar to those shown. The price and value of the investments referred to in this research and the income therefrom may fluctuate. Every investment involves risk and in volatile or uncertain market conditions, significant variations in the value or return on that investment may occur. Investments in hedge funds are complex, speculative and carry a high degree of risk, including the risk of a complete loss of an investor\u2019s entire investment. Past performance is not a guide to future performance, future returns are not guaranteed, and a complete loss of original capital may occur. Certain transactions, including those involving leverage, futures, options, and other derivatives, give rise to substantial risk and are not suitable for all investors. Fluctuations in exchange rates could have material adverse effects on the value or price of, or income derived from, certain investments.\n\nBridgewater research utilizes data and information from public, private, and internal sources, including data from actual Bridgewater trades. Sources include BCA, Bloomberg Finance L.P., Bond Radar, Candeal, CBRE, Inc., CEIC Data Company Ltd., China Bull Research, Clarus Financial Technology, CLS Processing Solutions, Conference Board of Canada, Consensus Economics Inc., DataYes Inc, Dealogic, DTCC Data Repository, Ecoanalitica, Empirical Research Partners, Entis (Axioma Qontigo Simcorp), EPFR Global, Eurasia Group, Evercore ISI, FactSet Research Systems, Fastmarkets Global Limited, the Financial Times Limited, FINRA, GaveKal Research Ltd., Global Financial Data, GlobalSource Partners, Harvard Business Review, Haver Analytics, Inc., Institutional Shareholder Services (ISS), the Investment Funds Institute of Canada, ICE Derived Data (UK), Investment Company Institute, International Institute of Finance, JP Morgan, JSTA Advisors, M Science LLC, MarketAxess, Medley Global Advisors (Energy Aspects Corp), Metals Focus Ltd, Moody\u2019s ESG Solutions, MSCI, Inc., National Bureau of Economic Research, Neudata, Organisation for Economic Cooperation and Development, Pensions & Investments Research Center, Refinitiv, Rhodium Group, RP Data, Rubinson Research, Rystad Energy, S&P Global Market Intelligence, Scientific Infra/EDHEC, Sentix GmbH, Shanghai Metals Market, Shanghai Wind Information, Smart Insider Ltd., Sustainalytics, Swaps Monitor, Tradeweb, United Nations, US Department of Commerce, Verisk Maplecroft, Visible Alpha, Wells Bay, Wind Financial Information LLC, Wood Mackenzie Limited, World Bureau of Metal Statistics, World Economic Forum, and YieldBook. While we consider information from external sources to be reliable, we do not assume responsibility for its accuracy.\n\nThis information is not directed at or intended for distribution to or use by any person or entity located in any jurisdiction where such distribution, publication, availability, or use would be contrary to applicable law or regulation, or which would subject Bridgewater to any registration or licensing requirements within such jurisdiction. No part of this material may be (i) copied, photocopied, or duplicated in any form by any means or (ii) redistributed without the prior written consent of Bridgewater\u00ae Associates, LP.\n\n[1] Additionally, there is the demographic force that will certainly lead to a lot of old people who don\u2019t work and will be expensive to support (because at that stage in their lives, their healthcare costs will be high), a shrinking workforce in developed countries, large increases in population in less developed countries, and only a small percentage of the people being truly productive.\n\n[2] I explained these more completely in Chapter 5, \u201cThe Big Cycle of Internal Order and Disorder,\u201d of Principles for Dealing with the Changing World Order.]]>\n    \n \n \n \n \n\n Ray Dalio \n\n Founder, CIO Mentor, and Member of the Bridgewater Board \n\nIf I had to pick the most important chapter in the book, this would be it. That is because it deals with the biggest and most important forces that are dramatically changing the world order, and it shows how and why these forces have repeatedly driven history through its big cycles. Having seen so many of these cycles, watching what is happening is like watching a movie that I have seen many times before\u2014just a contemporary version in which the clothes that the people are wearing and the technologies that they are using are more modern. I hope to show you what I see. Also, by showing what happened in the past and why it happened, we can understand how previously unimaginable developments are now happening and could happen in the future.\n\nWhile this book is mostly focused on understanding what\u2019s going on with debt/credit/money/economic cycles, we can\u2019t look at this dynamic in isolation and make sense of it because how these cycles transpire is influenced by other big forces. Similarly, to understand what is happening in other areas, we need to understand the debt/credit/ money/economic force as it has big effects on developments in most areas. Together, five big forces produce the Overall Big Cycle that leads to radical changes in monetary, domestic, and/or world orders.\n\nI comprehensively explained how this Overall Big Cycle works and how it was manifest over the last 500 years in Principles for Dealing with the Changing World Order, but I won\u2019t cram that 600-page book in here. Instead, I am going to give you a brief summary. That way, when we turn to Part III about what has happened in our current Big Cycle, and Part IV, in which I will try to look into the future, you will be able to see how what actually happened compares with my templates of both the Big Debt Cycle and the Overall Big Cycle.\n\nHOW THE MACHINE WORKS\n\nBecause everything that happens has reasons that make it happen, it appears to me that everything changes like a perpetual motion machine. To understand this machine, one needs to understand its mechanics. Because everything affects everything else directly or indirectly, these mechanics are very complex. Sometimes I try to explain what I know about them with enough of their complexity to show them in useful detail, such as I did previously in this book to explain how countries go broke. And sometimes I try to explain them simply. As the saying goes, \u201cAny fool can make something complicated. It takes a genius to make it simple.\u201d In this chapter, I will try to explain the Big Cycle simply. I will begin by explaining my approach.\n\nAs a global macro investor for most of my life, I have tried to understand and model the cause/effect relationships and use my models to bet on what will happen in the markets. To do that, for about the last 35 years, I have created computerized expert systems that enable the computer to make decisions like I make them. These systems are based on the following principle:\n\nDecision-making systems should be based on timeless and universal relationships, meaning that they should explain all the big, important developments in all time frames and in all countries, though not necessarily precisely or in detail. If they fail to explain all the big developments in all time frames and in all countries, that indicates that an important influence is missing and needs to be added to the template/model.\n\nThe expert systems I have built are previously developed forms of artificial intelligence. Now, with various breakthroughs in artificial intelligence, I am\u2014and I believe we all are\u2014on the brink of being able to understand all of the cause/effect relationships that drive everything, though for now we still have to labor along the old-fashioned way, with people studying what happened using the computing and AI tools available today. That is why, in my own feeble attempts to understand and describe the most important mechanics that change the world as we know it, I do these in-depth studies and create explanations of them. What I am about to describe is a result of this process. However, because the forces that drive the Big Cycle are so big, it is easy to see and understand them without worrying about the details and the complexities.\n\nZooming out to the highest level, the five most important drivers of change are:[1]\n\n1. The debt/credit/money/economic cycle\n\n2. The internal order and disorder cycle\n\n3. The external geopolitical order and disorder cycle (i.e., the changing world order)\n\n4. Acts of nature (droughts, floods, and pandemics)\n\n5. Human inventiveness, most importantly of new technologies\n\nThese forces affect each other to shape the biggest things that happen, creating cycles that move markets and economies around an upward-sloping trend line. The incline of its upward slope is primarily driven by the inventiveness of practical people (e.g., entrepreneurs) who are given adequate resources (e.g., capital) and work well with others (their coworkers, government officials, lawyers, etc.) to make the inventions and products that create productivity improvements.\n\nOver a short period of time (i.e., 1-10 years), the short-term cycles, especially the debt and political cycles, are dominant. Over a long period of time (i.e., 10 years and beyond), the long-term cycles and the upward-sloping trend line in productivity have much bigger effects.\n\nAs I explained earlier, conceptually the way this dynamic transpires looks like this to me:\n\n\n\nI will now delve into these five forces. While reading about them, please think about how these forces have worked and how they are working now. That will help you see how and why \u201chistory rhymes\u201d and better understand what is now happening and what is likely to happen.\n\nHOW THE OVERALL BIG CYCLE WORKS: THE FIVE BIG FORCES\n\nWe are now 80 years into the Overall Big Cycle that began at the end of World War II, which is by and large unfolding in the classic ways that will produce dramatic changes that one can only imagine by visualizing these five forces interacting simultaneously in a historical context.\n\nMore specifically:\n\n1. The Debt/Credit/Money/Economic Cycle\n\nThroughout this book, I have described the most important things that influence the Big Debt Cycle (like debt service payments relative to income, the amount of new debt sold relative to the demand for it, the desirability and willingness of debt asset holders to hold their existing debt assets, and other factors explained earlier, etc.).\n\nBecause I have already covered this Big Debt Cycle so completely that you are probably sick of hearing about it, I won\u2019t say much more.\n\nI will just reiterate the main points I want to get across, which are:\n\n \nThere has always been, and I expect that there will always be, short-term cycles that over time add up to Big Debt Cycles. \nThe average short-term debt cycle has typically taken about six years, give or take about three (with the duration of that cycle dependent on a number of influences that we can monitor and use to come up with rough estimates of how long each one will last). \nThe average long-term Big Debt Cycle has typically taken about 80 years, give or take 25 years (with the duration of that cycle also driven by a number of influences that we can monitor and use to come up with rough estimates of how long each one will last). \nThese debt cycles are influenced by and influence other things, most importantly what I have identified as the four other big forces. \n\nTo summarize the dynamic in a few sentences, what has timelessly and universally (i.e., throughout the millennia and across countries) driven the Big Debt Cycle changes and has created the big debt and economic problems is the creation of unsustainably large amounts of debt assets and debt liabilities relative to the amounts of money, goods, services, and investment assets in existence. This always has led to big debt crises and runs on banks. By a run, I mean a turning-in of debt assets (that have no intrinsic value\u2014i.e., their only value is to buy things) to banks in order to get real money, which the bank doesn\u2019t have enough of to meet the demand. Classically, when the holders of those financial assets actually try to convert them back into money and buy things and see that they can\u2019t get the buying power they believe they have stored in their debt assets, the run accelerates and feeds on itself, which causes great shifts in markets\u2019 values and wealth until debts are defaulted on, restructured, and/or monetized, reducing the debt burdens relative to incomes, and a new equilibrium is reached. The debts are almost always monetized, by which I mean that it is almost always the case that the central bank creates a lot of money and credit to make it easier to pay back the debt, which devalues the money and debt.\n\nIt\u2019s worth noting that at times when the debt/money force, the internal order force, and the external order force are late in their cycles (i.e., when there is a lot of debt and a lot of internal and external conflict), it is typically just before big conflicts and revolutionary changes to monetary orders, internal orders, and world orders. Like a life cycle, the Big Cycle goes through stages. This late-cycle stage, which I call Stage 5, comes just before the depression and war stage that brings about the end of the Big Cycle. For reasons I will explain later, I believe that we are now in this late-cycle stage. It is a time of radical, typically unexpected changes that haven\u2019t happened in one\u2019s own lifetime but have happened many times throughout history. At such times, it is extremely valuable to understand these past cases of big changes and consider whether they could happen again.\n\nIn Principles for Dealing with the Changing World Order, I examined a number of such cases. Since history can be an effective guide for understanding cause/effect relationships and bringing perspective on what is now happening and might happen, we can use these historical cases to think about what\u2019s logically likely to happen under the existing circumstances.\n\nSo, what are the existing circumstances? At this time, there is great over-indebtedness and in all other major countries at the same time as there are increasingly nationalistic and fragmented internal orders in these countries, increasingly contentious relationships between countries, adverse and expensive acts of nature, and amazing new technologies.\n\nLooking at past cases with similar configurations of conditions can help us imagine otherwise unimaginable possible developments. For example, I repeatedly saw, and will show you in the next part of this book, that, when faced with similar conditions of excessive debt, countries (including the US) took the following extraordinary actions:\n\n \nExerting great pressure on countries to buy the country\u2019s debt (as the British did in the past) \nSelectively freezing debt and/or taking the assets of \u201cenemy\u201d countries (the way the US did to Japan in 1941 and Russia more recently) \nDefaulting on/restructuring debts by extending maturities and/or monetizing them to cut debt burdens (the way Germany did after Hitler came to power) \nImposing confiscatory taxes and capital/foreign exchange controls to prevent assets from leaving the country \nRevaluing/managing government assets \nCreating new types of money \n\nTo be clear, I am not saying that these sorts of things will happen, and I am hesitant to raise them as possibilities because my doing so could engender exaggerated fears, which could prompt inappropriate and exaggerated actions. However, like a good doctor speaking to a patient suffering from serious conditions, I feel that it would be an irresponsible omission of mine not to convey what past cases tell us about the possibilities that sometimes accompany these conditions.\n\n2. The Internal Order and Disorder Cycle\n\nWithin countries, there are both short-term political swings lasting about six years on average, give or take three years, that over time add up to big shifts in domestic orders that last about 80 years, give or take 25 years. To reiterate, I don\u2019t mean that these time frames are fixed because they are highly variable in duration, but I do mean that they have always happened and I believe always will happen, with the durations driven by influences that we can monitor and use to come up with rough estimates of how long each one will last.[2]\n\nThese are the cycles that exist within countries and lead to conflicts and changes in the system of governance, or what I\u2019m calling \u201corders.\u201d These fights for power work basically the same way in all systems of government, all types of organizations, and even within families because the approaches to fighting them are embedded in human nature.\n\nSo, how do they work?\n\nIt\u2019s simple: nothing lasts forever. That includes the orders built around established leaders and governance systems. Changes in orders are driven by those who have the greatest power getting to determine what is done. Orders change when those who don\u2019t run the existing order acquire more power than those who do and want to change it. Fights occur when both a) a powerful group wants to change the order and b) it is not clear which side has more power, so only a fight can determine it. Fights don\u2019t occur if a) there isn\u2019t a powerful group that wants to change the order and/or b) there is a powerful group that wants to change it and is so much stronger than the existing group that the changes will take place with little or no fighting.\n\nIn democracies, there is an election cycle that roughly coincides with the economic cycle because bad economic conditions typically lead to political changes. At the beginning of a new popularly chosen leader coming to power\u2014e.g., in the first 100 days of a new presidency\u2014there is a honeymoon period and great optimism. That is when dreams of great changes and great improvements exist and before realities and criticisms of how the new leader has shaped and handled them set in. As time passes, typically the big promises the leader made to get elected become difficult to deliver and bad things happen so disappointment sets in, critics and enemies become bolder, and support wanes. All this makes fighting to stay in power harder, which often leads to more extreme actions to make that happen.\n\nThese dynamics are at play in the US at my time of writing this book In March 2025. How things go typically depends mostly on the economy, which depends mostly on where the market- and economy-shaping short-term and long-term debt/credit/money/economic cycles are, though exogenous events (like droughts, floods, and pandemics, and big international or domestic conflicts) can also matter.\n\nAll governance orders within countries change from one type to another\u2014e.g., from democracies to autocracies and from autocracies to democracies\u2014and each major type of order comes in varying flavors with some managed well and some managed poorly. I will now focus on what happens when democracies fail.\n\nWhen democracies fail, autocracies come in.\n\nIn my studies of how orders have changed throughout history, I have seen how changes from republic-style representative democracies to autocracies typically happen. These changes are exemplified in how Julius Caesar in ancient Rome (from 49 to 44 BCE), Napoleon Bonaparte in France (from 1799 to 1815), Benito Mussolini in Italy (from 1922 to 1943), Adolf Hitler in Germany (from 1933 to 1945), a consortium of leaders in Japan (from 1931 to 1945), Francisco Franco in Spain (from 1936 to 1975), Recep Tayyip Erdogan in Turkey (from 2016 until now), and many other countries\u2019 leaders have shifted to become autocratic leaders. I also read about it in Plato\u2019s Republic, written around 375 BCE, which is still a valuable description of how democracies become autocracies.\n\nIn almost all cases, there are large gaps in wealth and values, bad and worsening conditions, and weak, fragmented leadership in the republic-style representative democracies. These democracies can\u2019t fix their problems because democracies intrinsically rely on compromise between opposing factions, and compromise breaks down during such times. So, instead of following the laws and the system of compromise, the opposing sides become willing to fight to win at all costs. Typically, this leads to intensifying populist conflicts between those of the hard right, those of the weak middle, and those of the hard left. Conflicts increase, especially during times of economic stress, which leads to fights for the power to control. How these fights for power take place are largely similar for logical reasons that I will explain.\n\nPlato pointed out, and my study of history showed me, that leaders in democracies typically appeal to their constituents\u2019 desires for immediate benefits and temporary relief rather than doing the hard things that address deeper, systemic issues and make their nation strong over the long term. I have seen and read historical accounts of how leadership also typically becomes weak, decadent, and corrupt, especially after periods of great prosperity and few challenges. Plato argued that when democracies become weak and decadent and lose sight of justice and virtue, they pass their peaks and begin their declines. These periods are typically marked by growing corruption, inequality, and a failure of institutions to function effectively. When the system no longer satisfies the needs of a large percentage of the people, it loses legitimacy. Independently, and long before Plato observed this, this dynamic was recognized in China (as far back as 1046 BCE), where it is called \u201closing the mandate of heaven.\u201d It is when and why orders fail.\n\nIn times of disorder, financial, political, and military power matter more than laws, and authoritarianism works better than weak, disorganized collectivism.\n\nPlato called the person who typically leads the revolutionary changes from democracy to autocracy a \u201cdemagogue.\u201d Demagogues manipulate public opinion, stir up emotions, and use extraordinary means to gain power. They typically rile up populist sentiment, promise easy solutions to complex problems (often at the expense of truth or rational discourse), and use propaganda and bullying to gain and increase power. They are generally of the well-educated class and gather around them others who are powerful. When they are of the political hard right, they and those who support them are typically rich and powerful nobles (in the old days) or capitalists (since the Industrial Revolution) who are allied in their belief and their self-interest that great leadership requires strong leadership and strong partnerships from the top, like strong companies that have to work well together to do great things. When demagogues are of the left, they typically get their support from the unprivileged masses. As these populist leaders, whether they are from the right or the left, gain power, they typically employ tactics such as propaganda, coercion, and the consolidation of power to undermine their enemies and the democratic institutions that support their enemies and/or that support the inefficient bureaucracies that are enabling the problems rather than fixing them. This typically leads to the eventual replacement of democracy with a more centralized, dictatorial form of government.\n\nThe approach a strong CEO uses in running a company can be difficult to distinguish from a demagogue\u2019s approach. In fact, it can be said that some strong CEOs govern as demagogues, so it should be expected that if they were running governments, they would run them the same way. In both cases, they are people who take control and make radical changes to make radical improvements, and the big questions are what will the controls on them be and how far will they take the autocracy. If looking at a company, one should see if there is strong oversight and a controlling force like a strong board and controls from effective regulators; for governments, such controls come from oversight functions and the separation of powers. The more uncontrolled they are, the more dictatorial the leaders are likely to become. A relevant good principle is power corrupts and absolute power corrupts absolutely, a phrase attributed to historian and politician Lord Acton in 1887.\n\nIn the new order that emerges, financial and political power matters more than laws, and authoritarianism works better than weak, disorganized collectivism.\n\nIn most of these cases, the transfers from the democracies to autocracies take place within the rules of the democracy and become increasingly extreme over a few years, usually around three to five. These leaders typically make radical changes to the monetary, political, and geopolitical orders, and they typically become very nationalistic, militaristic, expansionist, and autocratic. As mentioned, examples include Caesar in Rome, Napoleon in France, Hitler in Germany, and Mussolini in Italy.\n\nIn ways that were more thoroughly explained in Principles for Dealing with the Changing World Order and that should be apparent to observers who are watching what is happening today, this is now taking place with big political shifts (mostly toward the hard right) for the same reasons that they happened in the past.\n\n3. The International Order and Disorder Cycle (i.e., the Changing World Order)\n\nHow countries deal with each other is of paramount importance and it, too, is cyclical.\n\nFor the same reason that there are periods of order (i.e., periods of harmony, productivity, and prosperity) and periods of disorder (periods of great conflict, destruction, and depression), and big cyclical swings between these periods within countries, there are periods of order (periods of harmony, productivity, and prosperity) and periods of disorder (periods of great conflict, destruction, and depression) between countries. The periods of disorder take place when there are fights to determine which country or countries will have the power to set what type of order exists. However, because there has never been an effective global governance system, the world order is more prone to disorder and conflict.\n\nAs part of the Big Cycle, there have also been big swings between a) unilateralism in which there is fighting for one\u2019s self-interest, the strong winning over the weak, and the law of the jungle/the survival of the fittest and b) multilateralism in which there is striving for global harmony, peaceful coexistence, and egalitarianism.\n\nHistorically, the only times that multilateralism worked were after wars when people were sick of fighting and there was a dominant power to enforce how things should go. In fact, throughout most of history, brutal and destructive unilateralism was the norm and periods in which there was multilateralism in pursuit of harmony, peaceful coexistence, and the common good were extremely rare and never sustained. Consider that it wasn\u2019t until 1648, after the terrible Thirty Years\u2019 War, that there was an agreement in Europe (the Peace of Westphalia) establishing that countries have borders and that all countries would pledge to enforce those borders rather than to simply fight one another to get what the other had, which up until then was the norm (though these pledges not to fight have only worked sporadically).\n\nAlso consider that it wasn\u2019t until after World War I, when Woodrow Wilson, the idealistic academic president of Princeton University who became president of the newly powerful United States in 1913, na\u00efvely aspired to have a world governance system that imitated the US governance system, the League of Nations. It didn\u2019t last and failed to prevent World War II, which was followed by the new American world order, which created multilateral organizations like the UN, the IMF, the World Bank, the World Health Organization, the World Trade Organization, the International Court of Justice, the World Intellectual Property Organization, etc. These organizations aimed to foster global cooperation, economic stability, and collective problem-solving. The US, leveraging its unparalleled economic and military power, became the linchpin of this liberal international order, promoting democracy, free markets, and human rights. While not without its flaws, this system maintained a relative stability that has so far prevented another world war.\n\nWhile we all have lived through a time when multilateralism\u2019s striving for harmony, peaceful coexistence, and egalitarianism was of course what we all wanted, multilateralism is now fading into irrelevance and unilateralism is rising for reasons that are understandable in the context of history. As a result, the powers of multilateral organizations are declining rapidly and transitioning into the hands of the major powers. I believe that realists must accept the fact that both the aspiration for and the existence of global cooperation are eroding as the pendulum is swinging toward self-interested unilateralism and survival of the fittest. It increasingly becomes the case that the strong prey on the weak. These developments are all typical of the stage of the Big Cycle that we are now in.\n\nWhile this transition from multilateralism to unilateralism is at first shocking, it quickly becomes normalized. For example, it was only months before this writing that Donald Trump\u2019s statements concerning Greenland, Canada, and the Panama Canal would have been considered unimaginable (much like Russia\u2019s use of military force to defend what it saw as its interests by invading Ukraine if its interests weren\u2019t guaranteed peacefully).\n\nAt such times, alliances often change fast as circumstances change quickly and winning is more important than loyalties.\n\nTo help us imagine the future, we should pay close attention to the lessons from history. Through most of history, without the existence of countries with borders, collections of people with common interests (i.e., tribes) fought to seize wealth from other tribes or defend their own. As those who won got richer and more civilized, they typically got more decadent and weaker and were eventually taken down by stronger barbarians, who were in turn brought down by subsequent generations learning to be stronger. For example, that is the story of the rise of the Roman Empire and its defeat by the Gauls as well as the rises and falls of most dynasties, and with them, the rises and declines of leadership approaches. These alternating ages of barbarianism and civility contributed to periods of war that took down the more advanced civilizations when the barbarians were strong and civilizations were weak.\n\nHistory has repeatedly shown us that civility when taken too far creates weak decadence that eventually loses to strong barbarism.\n\nThe peaceful and productive, modern-day version of this is the \u201cfighting\u201d that happens in business with the invention of new and effective business ideas/weapons that fuel creative destruction. We love to watch these fights, which are like watching fights in the Roman Colosseum, or better yet we love being in them. Frankly, I love being in them, and I detest impractical idealism (while I love practical idealism above all else). But the destructive version of this same impulse leads to a lack of cooperation and to fighting in politics, geopolitics, dealing with acts of nature (particularly climate change), and new technologies, and I worry a lot about it.\n\n4. Acts of Nature (Droughts, Floods, and Pandemics)\n\nThroughout history, acts of nature have killed more people than wars and toppled more orders than the previously mentioned forces, and an objective view of the data shows that droughts, floods, and pandemics are increasing and increasingly costly. While why this is happening is debated, that it is happening is not debatable. Nor is it debatable that humanity\u2019s polluting and disrupting of nature, higher human population density, closer contact across the world (brought about by more international travel), and closer contact with other species due to land development (leading to animal-human disease transmissions) are all causes. We regularly see these happening in the news, most recently with the Los Angeles wildfires. It is also almost certain that these problems will get worse.\n\nAs with the other forces, this force is intertwined with the other big forces to shape what is happening. For example, the migration issues in developed countries (with immigration pressures resulting from changes in climate) and the living conditions issues in underdeveloped countries (where people are struggling to adapt to droughts, floods, and other changes) are obviously worsening due to damaging acts of nature increasing, and given that nearly all nations are facing debt issues, there isn\u2019t enough money to be spent on climate mitigation or adaptation.\n\n5. Human Inventiveness, Most Importantly of New Technologies\n\nThere are great advances in technology, particularly in artificial intelligence, that will dramatically affect all thinking in all areas for good or for bad.\n\nThroughout history, technological advances have raised living standards and life expectancies, have been used to generate economic and military power, and have been used in wars to create great destructions. They are closely tied to the other four forces. When technological advances are supported by good financial, economic, and social conditions, they advance more quickly than when those conditions are bad. But when their developments are supported by unsustainable credit growth, they tend to cause financial bubbles and busts. For example, the South Sea Bubble in 1720 when the Dutch Empire was beginning to decline, the Railway Mania in the 1830s and 1840s, the electricity and utilities bubbles (the \u201cWar of the Currents\u201d) in the 1870s and 1890s, and the dot-com bubble and telecoms crash of 1990-2001 are all relevant examples of cases where great advances in major life- and productivity-improving technologies led to debt bubbles and busts, as well as big beneficial changes.\n\nThat\u2019s enough of the Big Cycle for now\u2014enough to help you better understand the dynamics you\u2019ll read about in Part III as you look at the events that have unfolded since our current Big Cycle began in 1945 with the end of World War II. It will also help you understand the perspective I take when I attempt to look into the future in Part IV. But before we move on, it is worth sharing one final principle, which has the biggest impact on how the challenges that arise during the Big Cycle are handled, namely: \n\nThe biggest and most important force is how people deal with each other.\n\nIf people deal with their problems and opportunities together rather than fight each other, they can get the best possible results. Unfortunately, while technology has evolved a lot, human nature hasn\u2019t changed much, so this is still probably beyond the capabilities of humankind.\n\nThe views expressed in this article are mine and not necessarily Bridgewater\u2019s.\n\nThe information provided herein is not intended to provide a sufficient basis on which to make an investment decision and investment decisions should not be based on simulated, hypothetical, or illustrative information that have inherent limitations. Unlike an actual performance record simulated or hypothetical results do not represent actual trading or the actual costs of management and may have under or overcompensated for the impact of certain market risk factors. Bridgewater makes no representation that any account will or is likely to achieve returns similar to those shown. The price and value of the investments referred to in this research and the income therefrom may fluctuate. Every investment involves risk and in volatile or uncertain market conditions, significant variations in the value or return on that investment may occur. Investments in hedge funds are complex, speculative and carry a high degree of risk, including the risk of a complete loss of an investor\u2019s entire investment. Past performance is not a guide to future performance, future returns are not guaranteed, and a complete loss of original capital may occur. Certain transactions, including those involving leverage, futures, options, and other derivatives, give rise to substantial risk and are not suitable for all investors. Fluctuations in exchange rates could have material adverse effects on the value or price of, or income derived from, certain investments.\n\nBridgewater research utilizes data and information from public, private, and internal sources, including data from actual Bridgewater trades. Sources include BCA, Bloomberg Finance L.P., Bond Radar, Candeal, CBRE, Inc., CEIC Data Company Ltd., China Bull Research, Clarus Financial Technology, CLS Processing Solutions, Conference Board of Canada, Consensus Economics Inc., DataYes Inc, Dealogic, DTCC Data Repository, Ecoanalitica, Empirical Research Partners, Entis (Axioma Qontigo Simcorp), EPFR Global, Eurasia Group, Evercore ISI, FactSet Research Systems, Fastmarkets Global Limited, the Financial Times Limited, FINRA, GaveKal Research Ltd., Global Financial Data, GlobalSource Partners, Harvard Business Review, Haver Analytics, Inc., Institutional Shareholder Services (ISS), the Investment Funds Institute of Canada, ICE Derived Data (UK), Investment Company Institute, International Institute of Finance, JP Morgan, JSTA Advisors, M Science LLC, MarketAxess, Medley Global Advisors (Energy Aspects Corp), Metals Focus Ltd, Moody\u2019s ESG Solutions, MSCI, Inc., National Bureau of Economic Research, Neudata, Organisation for Economic Cooperation and Development, Pensions & Investments Research Center, Refinitiv, Rhodium Group, RP Data, Rubinson Research, Rystad Energy, S&P Global Market Intelligence, Scientific Infra/EDHEC, Sentix GmbH, Shanghai Metals Market, Shanghai Wind Information, Smart Insider Ltd., Sustainalytics, Swaps Monitor, Tradeweb, United Nations, US Department of Commerce, Verisk Maplecroft, Visible Alpha, Wells Bay, Wind Financial Information LLC, Wood Mackenzie Limited, World Bureau of Metal Statistics, World Economic Forum, and YieldBook. While we consider information from external sources to be reliable, we do not assume responsibility for its accuracy.\n\nThis information is not directed at or intended for distribution to or use by any person or entity located in any jurisdiction where such distribution, publication, availability, or use would be contrary to applicable law or regulation, or which would subject Bridgewater to any registration or licensing requirements within such jurisdiction. No part of this material may be (i) copied, photocopied, or duplicated in any form by any means or (ii) redistributed without the prior written consent of Bridgewater\u00ae Associates, LP.\n\n[1] Additionally, there is the demographic force that will certainly lead to a lot of old people who don\u2019t work and will be expensive to support (because at that stage in their lives, their healthcare costs will be high), a shrinking workforce in developed countries, large increases in population in less developed countries, and only a small percentage of the people being truly productive.\n\n[2] I explained these more completely in Chapter 5, \u201cThe Big Cycle of Internal Order and Disorder,\u201d of Principles for Dealing with the Changing World Order.]]>\n  \n  \n    China Has Already Remade the International System\n    https://www.foreignaffairs.com/china/economics-china-international-system-tariffs-michael-froman?s=EDZZZ005ZX&utm_medium=newsletters&utm_source=fatoday&utm_campaign=China%20Has%20Already%20Remade%20the%20International%20System&utm_content=20250325&utm_term=EDZZZ005ZX\n    readwise:01jq6yp4cj0r9ezsv4pb8q182a\n    Tue, 25 Mar 2025 15:28:09 +0000\n    Foreign Affairs\n    \nTrucks loaded with shipping containers outside Shanghai, February 2025\n\nIn early February, as he flew in Air Force One above the body of water he\u2019d recently renamed the Gulf of America, President Donald Trump declared that he would levy tariffs on all imported steel and aluminum. Two weeks later, he issued a presidential memorandum laying out new guidance for screening investment from Chinese firms in the United States and U.S. firms into China. And throughout the early weeks of his administration, Trump has emphasized the importance of bringing manufacturing back home, telling firms that, to avoid tariffs, they should make their products in the United States.\n\nTariffs and protectionism, restrictions on investment, measures designed to drive domestic production: Washington\u2019s economic policy suddenly looks an awful lot like Beijing\u2019s policies over the last decade or so\u2014like Chinese policy with American characteristics.\n\nThe U.S. strategy of engagement with China was based on the premise that, if the United States incorporated China into the global rules-based system, China would become more like the United States. For decades, Washington lectured Beijing about avoiding protectionism, eliminating barriers to foreign investment, and disciplining the use of subsidies and industrial policy\u2014with only modest success. Still, the expectation was that integration would facilitate convergence.\n\nThere has indeed been a fair degree of convergence\u2014just not in the way American policymakers predicted. Instead of China coming to resemble the United States, the United States is behaving more like China. Washington may have forged the open, liberal rules-based order, but China has defined its next phase: protectionism, subsidization, restrictions on foreign investment, and industrial policy. To argue that the United States must reassert its leadership to preserve the rules-based system it established is to miss the point. China\u2019s nationalist state capitalism now dominates the international economic order. Washington is already living in Beijing\u2019s world.\n\nSubscribe to Foreign Affairs This Week\n\nOur editors\u2019 top picks, delivered free to your inbox every Friday.\n\nOPENING UP?\n\nIn the 1990s and the early years of this century, there was every indication that China was on an inexorable march toward economic liberalization. Building on a process that began in the late 1970s under the Chinese leader Deng Xiaoping, China opened up to foreign investment. President Jiang Zemin and Premier Zhu Rongji then kept China on a remarkable, if painful, path of economic reforms. They restructured state-owned enterprises and fired tens of millions of theirworkers, created more space for private sector activity, allowed businesses to adjust prices in response to market conditions, and ushered in China\u2019s entry to the World Trade Organization.\n\nJiang and Zhu declared repeatedly that China would inevitably continue to open up. Many in the West went so far as to believe that this economic liberalization would lead to China\u2019s political liberalization, that a capitalist society would become a more democratic one over time. That assumption proved false. China\u2019s leaders never seriously contemplated political reform, but China\u2019s economic advancement was impressive nonetheless. The country\u2019s GDP grew from $347.77 billion in 1989 to $1.66 trillion by 2003 to $17.79 trillion in 2023, according to the World Bank. Hopes were high that integrating China into the rules-based trading system could lead to a more peaceful and more prosperous world. Globalization did lift more than a billion people out of poverty, an astounding feat. But the benefits of that progress were not evenly shared, and some workers and communities in industrialized countries ended up paying the price for the rise of the rest.\n\nThen President Hu Jintao entered the picture, followed by President Xi Jinping. China\u2019s economic trajectory turned out to be less linear and less inevitable than initially expected. Under Hu, China leaned more heavily into state intervention in the economy by aiming to create \u201cnational champions\u201d in strategic sectors through massive subsidies. In other words, the government expanded its role rather than pursuing further market liberalization. At the same time, a flood of cheap Chinese imports accelerated the trend toward deindustrialization in the United States\u2014and did so at a rate that few, if any, fully anticipated. China became the world\u2019s manufacturing floor, overtaking the manufacturing giants of Japan and Germany in the first decade of this century. In 2004, China made up nine percent of the world\u2019s manufacturing value added, leapfrogging to a massive 29 percent in 2023, according to the World Bank.\n\nHOW CHINA WON\n\nWashington pressed Beijing to deliver on its reform agenda throughout this period, urging China to open its markets and refrain from imposing high tariffs and other barriers on products being exported from the United States. It advocated for U.S. firms to be allowed to invest in China without being excluded from certain sectors or required to enter joint ventures with\u2014and transfer U.S. technology to\u2014local firms. And Washington demanded that the Chinese government stop subsidizing the production and export of goods, which distorted the global marketplace. But this litany of complaints was largely ignored.\n\nIn 2009, the Obama administration led an effort to terminate the Doha Round\u2014a multilateral trade negotiation under the World Trade Organization launched in 2001. It did so in large part because the resulting agreement would have enshrined China permanently as a \u201cdeveloping country\u201d under WTO rules. This would have allowed China to enjoy \u201cspecial and differential treatment,\u201d which meant that China would have been able to avoid assuming the same level of obligations and disciplines\u2014on market access, intellectual property rights protection, and other issues\u2014as the United States and other industrial countries. Washington faced near-universal criticism at the time for encouraging a rethink of the premises of the negotiation. But it was clear even then that, left unaddressed, China\u2019s economic practices would significantly disrupt the global trading system.\n\n The United States is already living in China\u2019s world.\n\nSimilar concerns motivated the Obama administration to pursue the Trans-Pacific Partnership, a high-standard trade agreement negotiated among 12 countries around the Pacific Rim. This initiative was designed to give countries in the Asia-Pacific region an attractive alternative to the model China offered. It brought together a group of diverse countries that were willing to set strong labor and environmental protections, limit the use of subsidies, impose discipline on state-owned enterprises, and address various China-specific concerns, such as intellectual property rights protection. By the time the TPP negotiations were completed in 2015, however, trade agreements\u2014even those designed to counterbalance China\u2014had become politically toxic at home, and the United States ended up pulling out of the agreement.\n\nFrom 2009 to 2017, I served first as deputy national security adviser for international economic affairs and then as U.S. trade representative. During that time, I consistently warned my Chinese counterparts that the benign international environment that had enabled China\u2019s success would disappear unless Beijing modified its predatory economic policies. Instead, China largely maintained its course of action. If anything, it doubled down on its approach. When Xi came to power in 2012, he effectively ended the era of \u201creform and opening\u201d that had already stalled under Hu, set China on a course to dominate critical technologies, increased production to the point of overcapacity, and committed to export-led growth. Today, as the economist Brad Setser has noted, China\u2019s export volume is growing at a rate three times as fast as global trade. In the automotive sector, it is on a trajectory to have the capacity to produce two-thirds of the world\u2019s automotive demand. And its dominance extends beyond cars; China also produces more than half the global supply of steel, aluminum, and ships.\n\nEventually, even American businesses, which had always been the ballast in the bilateral relationship, soured on China as their intellectual property was stolen or forcibly licensed, their market access to China was severely restricted or delayed, and China\u2019s subsidies and preferences for domestic firms ate into their opportunity. Without any semblance of reciprocity, the relationship deteriorated. Politicians of both parties and the American public hardened their stance on China. European and major emerging economies grew hostile to Beijing\u2019s policies, as well. In short, the benign international environment disappeared.\n\n\nWorking on an electric vehicle production line in Zhejiang Province, China, March 2025\n\nWashington, having failed to convince Beijing to change its predatory economic policies or to move forward with an alternative trading bloc to counterbalance China, was left with one option: the United States had to become more like China. After decades of berating China for imposing high tariffs and other restrictions on U.S. exports, the United States is now putting up the same barriers. As calculated by the economist Chad Bown, Trump imposed tariffs that increased the average rate on imports from China from three percent to 19 percent in his first administration, covering two-thirds of all imports from China. President Joe Biden maintained those tariffs and added tariffs on other Chinese products, including personal protective equipment, electric vehicles, batteries, and steel, slightly increasing the average tariff on imports from China. Less than two months into his second administration, Trump has imposed an additional 20 percent tariff on all U.S. imports from China\u2014a bigger move than the tariffs of his first administration and the Biden administration combined.\n\nSimilarly, the United States changed its approach from opposing barriers to most bilateral investment flows to severely restricting China\u2019s investment in the United States and U.S. investment in certain sensitive sectors in China. Annual Chinese investment in the United States plummeted from $46 billion in 2016 to less than $5 billion in 2022, according to the Rhodium Group. And having urged Beijing to abandon subsidy and industrial policies, Washington itself went all-in on industrial policy during the Biden administration, laying out at least $1.6 trillion on the 2021 Infrastructure Investment and Jobs Act, the 2022 CHIPS and Science Act, and the 2022 Inflation Reduction Act.\n\nIF YOU CAN\u2019T BEAT THEM, JOIN THEM\n\nTo take the Chinese approach one step further could mean adopting a key tool in Beijing\u2019s toolbox: requiring Chinese firms that invest abroad to establish joint ventures with domestic firms and engage in technology transfers. Such a strategy could enhance not just American industrial competitiveness but also that of other countries negatively affected by China\u2019s overcapacity, including many in Europe.\n\nTake the clean energy sector as an obvious example. China\u2019s electric vehicle manufacturers innovate faster and produce high-quality vehicles far more cheaply than U.S. firms; some Chinese vehicles are as much as 50 percent less expensive than their American equivalents, and China accounts for nearly 60 percent of global electric vehicle sales worldwide. China\u2019s battery producers, solar panel manufacturers, and clean energy equipment companies have similar advantages.\n\nIn the United States, China\u2019s market share in electric vehicles is nearly nonexistent. Current tariffs and other restrictions are likely to prevent any future influx of imports. At the same time, European auto manufacturers, particularly those in Germany, are getting squeezed by domestic preference policies and the competitiveness of domestic firms in the Chinese market, which they have depended on for growth. And lately, China has been making inroads in the European market, too. The European market share of Chinese electric vehicles grew from virtually zero percent in January 2019 to over 11 percent in June 2024.\n\nFollowing the United States\u2019 lead, Europe introduced tariffs on Chinese-made electric vehicles late last year. This slowed the growth in China\u2019s market share. But just holding off a rise in imports may not solve the European auto industry\u2019s problems. To maintain jobs and manufacturing capacity, Europe appears to be open to Chinese investment in electric vehicle production in Europe. (By contrast, it is unclear whether Trump would welcome such investment or would continue to ban Chinese electric vehicles in the U.S. market because of their potential to track citizens\u2019 movements or shut down traffic.) If Europe is to avoid becoming merely a destination for final assembly of Chinese electric vehicles, it might have to borrow a tactic from Beijing and require Chinese companies to enter into joint ventures with European firms and transfer technology and know-how to them.\n\nHOW TO OUT-CHINA CHINA\n\nIt is not yet clear whether the United States can outmaneuver China with its own playbook. Beijing seems to have near-unlimited capacity to mobilize capital and manipulate trade and investment policy in service of its long-term objectives. Washington\u2019s Inflation Reduction Act and the CHIPS and Science Act, meanwhile, were more likely historic anomalies than first steps in a broader trend toward greater industrial policy, given the uneasiness among Republican lawmakers over their passage. Indeed, even as he seeks to boost the U.S. semiconductor industry, Trump has called for the repeal of the CHIPS and Science Act, which provides subsidies for semiconductor manufacturing. The subsidies provided by the Inflation Reduction Act are likely to face political challenges, too.\n\nThere is an active debate over whether the Biden administration got sufficient bang for its industrial policy buck beyond a few key sectors. U.S. investment in manufacturing has surged, and arguably industrial capacity has expanded. But as the economist Jason Furman pointed out in Foreign Affairs earlier this year, \u201cThe proportion of people working in manufacturing has been declining for decades and has not ticked back up, and overall domestic industrial production remains stagnant\u2014in part because the fiscal expansion Biden oversaw led to higher costs, a stronger dollar, and higher interest rates, all of which have created headwinds for the manufacturing sectors that received no special subsidies from the legislation he championed.\u201d Wherever one comes down in this debate, one thing is clear: even in the sectors that the Biden administration subsidized, such as semiconductors and green energy, the path to regaining global leadership is long and uncertain.\n\nThe United States may play the protectionist game as well as others, but soon, inflation, higher costs of living, and job losses in industries or sectors affected by other countries\u2019 retaliation will begin to bite. Trump appears to believe that a wall of tariffs\u2014as well as the uncertainty about whether tariffs are on or off at any particular moment\u2014is a powerful incentive for companies to locate their production in the United States, where they can be sure their goods will not be subject to tariffs. But as a general matter, companies that consider making the necessary capital investments to spur industrial production in the United States are looking for predictable policy environments, not tariffs that are imposed in the morning and withdrawn in the afternoon. Most may decide to sit on the sidelines, keeping their powder dry, until it becomes clearer what tariffs are going into effect, against whom, and for how long.\n\n After berating Beijing for its restrictions, Washington is putting up the same barriers.\n\nThe historical record of tariffs driving expanded production and manufacturing jobs in the United States is far from definitive. Take, for example, the tariffs imposed by Trump in 2018 on Chinese imports. As a 2024 paper by Federal Reserve researchers Aaron Flaaen and Justin Pierce found, \u201cTariff increases enacted since early 2018 are associated with relative reductions in U.S. manufacturing employment and relative increases in producer prices. In terms of manufacturing employment, rising input costs and retaliatory tariffs account for the negative relationship, and the contribution from these channels more than offsets a small positive effect from import protection.\u201d Some research has suggested that 75,000 downstream manufacturing jobs have been lost as a direct result of the tariffs, not to mention additional losses from retaliatory tariffs. The economic experts Benn Steil and Elisabeth Harding have also found that productivity in the U.S. steel industry tanked while productivity in other sectors rose since Trump imposed 25 percent tariffs on steel imports in March 2018. Output per hour in the U.S. steel industry has tumbled by 32 percent since 2017.\n\nPerhaps Trump\u2019s approach to moving production back to the United States will bear fruit, but for that to happen, the U.S. government would have to permit foreign firms to actually make such investments. Both Biden and Trump opposed the Japanese company Nippon Steel\u2019s acquisition of U.S. Steel, and U.S. policymakers are still debating whether Saudi Arabia\u2019s Public Investment Fund can acquire a controlling stake in the PGA Tour, which organizes U.S. golf tournaments\u2014hardly a critical industry.\n\nThe United States and others are imitating China in large part because China succeeded in a way that was unexpected. Its success in electric vehicles and clean technology did not come from liberalizing economic policies but from state interventions in the market in the name of nationalist objectives. Whether or not the United States can compete with China on China\u2019s playing field, it is important to recognize a fundamental truth: the United States is now operating largely in accordance with Beijing\u2019s standards, with a new economic model characterized by protectionism, constraints on foreign investment, subsidies, and industrial policy\u2014essentially nationalist state capitalism. In the war over who gets to define the rules of the road, the battle is over, at least for now. And China won.\n\nLoading...\n\nYou are reading a free article\n\nSubscribe to Foreign Affairs to get unlimited access.\n\n\n Paywall-free reading of new articles and over a century of archives\n Six issues a year in print and online, plus audio articles\n Unlock access to the Foreign Affairs app for reading on the go\n\nAlready a subscriber? Sign In \n\n\nThe Real China Trump Card]]>\n    \nTrucks loaded with shipping containers outside Shanghai, February 2025\n\nIn early February, as he flew in Air Force One above the body of water he\u2019d recently renamed the Gulf of America, President Donald Trump declared that he would levy tariffs on all imported steel and aluminum. Two weeks later, he issued a presidential memorandum laying out new guidance for screening investment from Chinese firms in the United States and U.S. firms into China. And throughout the early weeks of his administration, Trump has emphasized the importance of bringing manufacturing back home, telling firms that, to avoid tariffs, they should make their products in the United States.\n\nTariffs and protectionism, restrictions on investment, measures designed to drive domestic production: Washington\u2019s economic policy suddenly looks an awful lot like Beijing\u2019s policies over the last decade or so\u2014like Chinese policy with American characteristics.\n\nThe U.S. strategy of engagement with China was based on the premise that, if the United States incorporated China into the global rules-based system, China would become more like the United States. For decades, Washington lectured Beijing about avoiding protectionism, eliminating barriers to foreign investment, and disciplining the use of subsidies and industrial policy\u2014with only modest success. Still, the expectation was that integration would facilitate convergence.\n\nThere has indeed been a fair degree of convergence\u2014just not in the way American policymakers predicted. Instead of China coming to resemble the United States, the United States is behaving more like China. Washington may have forged the open, liberal rules-based order, but China has defined its next phase: protectionism, subsidization, restrictions on foreign investment, and industrial policy. To argue that the United States must reassert its leadership to preserve the rules-based system it established is to miss the point. China\u2019s nationalist state capitalism now dominates the international economic order. Washington is already living in Beijing\u2019s world.\n\nSubscribe to Foreign Affairs This Week\n\nOur editors\u2019 top picks, delivered free to your inbox every Friday.\n\nOPENING UP?\n\nIn the 1990s and the early years of this century, there was every indication that China was on an inexorable march toward economic liberalization. Building on a process that began in the late 1970s under the Chinese leader Deng Xiaoping, China opened up to foreign investment. President Jiang Zemin and Premier Zhu Rongji then kept China on a remarkable, if painful, path of economic reforms. They restructured state-owned enterprises and fired tens of millions of theirworkers, created more space for private sector activity, allowed businesses to adjust prices in response to market conditions, and ushered in China\u2019s entry to the World Trade Organization.\n\nJiang and Zhu declared repeatedly that China would inevitably continue to open up. Many in the West went so far as to believe that this economic liberalization would lead to China\u2019s political liberalization, that a capitalist society would become a more democratic one over time. That assumption proved false. China\u2019s leaders never seriously contemplated political reform, but China\u2019s economic advancement was impressive nonetheless. The country\u2019s GDP grew from $347.77 billion in 1989 to $1.66 trillion by 2003 to $17.79 trillion in 2023, according to the World Bank. Hopes were high that integrating China into the rules-based trading system could lead to a more peaceful and more prosperous world. Globalization did lift more than a billion people out of poverty, an astounding feat. But the benefits of that progress were not evenly shared, and some workers and communities in industrialized countries ended up paying the price for the rise of the rest.\n\nThen President Hu Jintao entered the picture, followed by President Xi Jinping. China\u2019s economic trajectory turned out to be less linear and less inevitable than initially expected. Under Hu, China leaned more heavily into state intervention in the economy by aiming to create \u201cnational champions\u201d in strategic sectors through massive subsidies. In other words, the government expanded its role rather than pursuing further market liberalization. At the same time, a flood of cheap Chinese imports accelerated the trend toward deindustrialization in the United States\u2014and did so at a rate that few, if any, fully anticipated. China became the world\u2019s manufacturing floor, overtaking the manufacturing giants of Japan and Germany in the first decade of this century. In 2004, China made up nine percent of the world\u2019s manufacturing value added, leapfrogging to a massive 29 percent in 2023, according to the World Bank.\n\nHOW CHINA WON\n\nWashington pressed Beijing to deliver on its reform agenda throughout this period, urging China to open its markets and refrain from imposing high tariffs and other barriers on products being exported from the United States. It advocated for U.S. firms to be allowed to invest in China without being excluded from certain sectors or required to enter joint ventures with\u2014and transfer U.S. technology to\u2014local firms. And Washington demanded that the Chinese government stop subsidizing the production and export of goods, which distorted the global marketplace. But this litany of complaints was largely ignored.\n\nIn 2009, the Obama administration led an effort to terminate the Doha Round\u2014a multilateral trade negotiation under the World Trade Organization launched in 2001. It did so in large part because the resulting agreement would have enshrined China permanently as a \u201cdeveloping country\u201d under WTO rules. This would have allowed China to enjoy \u201cspecial and differential treatment,\u201d which meant that China would have been able to avoid assuming the same level of obligations and disciplines\u2014on market access, intellectual property rights protection, and other issues\u2014as the United States and other industrial countries. Washington faced near-universal criticism at the time for encouraging a rethink of the premises of the negotiation. But it was clear even then that, left unaddressed, China\u2019s economic practices would significantly disrupt the global trading system.\n\n The United States is already living in China\u2019s world.\n\nSimilar concerns motivated the Obama administration to pursue the Trans-Pacific Partnership, a high-standard trade agreement negotiated among 12 countries around the Pacific Rim. This initiative was designed to give countries in the Asia-Pacific region an attractive alternative to the model China offered. It brought together a group of diverse countries that were willing to set strong labor and environmental protections, limit the use of subsidies, impose discipline on state-owned enterprises, and address various China-specific concerns, such as intellectual property rights protection. By the time the TPP negotiations were completed in 2015, however, trade agreements\u2014even those designed to counterbalance China\u2014had become politically toxic at home, and the United States ended up pulling out of the agreement.\n\nFrom 2009 to 2017, I served first as deputy national security adviser for international economic affairs and then as U.S. trade representative. During that time, I consistently warned my Chinese counterparts that the benign international environment that had enabled China\u2019s success would disappear unless Beijing modified its predatory economic policies. Instead, China largely maintained its course of action. If anything, it doubled down on its approach. When Xi came to power in 2012, he effectively ended the era of \u201creform and opening\u201d that had already stalled under Hu, set China on a course to dominate critical technologies, increased production to the point of overcapacity, and committed to export-led growth. Today, as the economist Brad Setser has noted, China\u2019s export volume is growing at a rate three times as fast as global trade. In the automotive sector, it is on a trajectory to have the capacity to produce two-thirds of the world\u2019s automotive demand. And its dominance extends beyond cars; China also produces more than half the global supply of steel, aluminum, and ships.\n\nEventually, even American businesses, which had always been the ballast in the bilateral relationship, soured on China as their intellectual property was stolen or forcibly licensed, their market access to China was severely restricted or delayed, and China\u2019s subsidies and preferences for domestic firms ate into their opportunity. Without any semblance of reciprocity, the relationship deteriorated. Politicians of both parties and the American public hardened their stance on China. European and major emerging economies grew hostile to Beijing\u2019s policies, as well. In short, the benign international environment disappeared.\n\n\nWorking on an electric vehicle production line in Zhejiang Province, China, March 2025\n\nWashington, having failed to convince Beijing to change its predatory economic policies or to move forward with an alternative trading bloc to counterbalance China, was left with one option: the United States had to become more like China. After decades of berating China for imposing high tariffs and other restrictions on U.S. exports, the United States is now putting up the same barriers. As calculated by the economist Chad Bown, Trump imposed tariffs that increased the average rate on imports from China from three percent to 19 percent in his first administration, covering two-thirds of all imports from China. President Joe Biden maintained those tariffs and added tariffs on other Chinese products, including personal protective equipment, electric vehicles, batteries, and steel, slightly increasing the average tariff on imports from China. Less than two months into his second administration, Trump has imposed an additional 20 percent tariff on all U.S. imports from China\u2014a bigger move than the tariffs of his first administration and the Biden administration combined.\n\nSimilarly, the United States changed its approach from opposing barriers to most bilateral investment flows to severely restricting China\u2019s investment in the United States and U.S. investment in certain sensitive sectors in China. Annual Chinese investment in the United States plummeted from $46 billion in 2016 to less than $5 billion in 2022, according to the Rhodium Group. And having urged Beijing to abandon subsidy and industrial policies, Washington itself went all-in on industrial policy during the Biden administration, laying out at least $1.6 trillion on the 2021 Infrastructure Investment and Jobs Act, the 2022 CHIPS and Science Act, and the 2022 Inflation Reduction Act.\n\nIF YOU CAN\u2019T BEAT THEM, JOIN THEM\n\nTo take the Chinese approach one step further could mean adopting a key tool in Beijing\u2019s toolbox: requiring Chinese firms that invest abroad to establish joint ventures with domestic firms and engage in technology transfers. Such a strategy could enhance not just American industrial competitiveness but also that of other countries negatively affected by China\u2019s overcapacity, including many in Europe.\n\nTake the clean energy sector as an obvious example. China\u2019s electric vehicle manufacturers innovate faster and produce high-quality vehicles far more cheaply than U.S. firms; some Chinese vehicles are as much as 50 percent less expensive than their American equivalents, and China accounts for nearly 60 percent of global electric vehicle sales worldwide. China\u2019s battery producers, solar panel manufacturers, and clean energy equipment companies have similar advantages.\n\nIn the United States, China\u2019s market share in electric vehicles is nearly nonexistent. Current tariffs and other restrictions are likely to prevent any future influx of imports. At the same time, European auto manufacturers, particularly those in Germany, are getting squeezed by domestic preference policies and the competitiveness of domestic firms in the Chinese market, which they have depended on for growth. And lately, China has been making inroads in the European market, too. The European market share of Chinese electric vehicles grew from virtually zero percent in January 2019 to over 11 percent in June 2024.\n\nFollowing the United States\u2019 lead, Europe introduced tariffs on Chinese-made electric vehicles late last year. This slowed the growth in China\u2019s market share. But just holding off a rise in imports may not solve the European auto industry\u2019s problems. To maintain jobs and manufacturing capacity, Europe appears to be open to Chinese investment in electric vehicle production in Europe. (By contrast, it is unclear whether Trump would welcome such investment or would continue to ban Chinese electric vehicles in the U.S. market because of their potential to track citizens\u2019 movements or shut down traffic.) If Europe is to avoid becoming merely a destination for final assembly of Chinese electric vehicles, it might have to borrow a tactic from Beijing and require Chinese companies to enter into joint ventures with European firms and transfer technology and know-how to them.\n\nHOW TO OUT-CHINA CHINA\n\nIt is not yet clear whether the United States can outmaneuver China with its own playbook. Beijing seems to have near-unlimited capacity to mobilize capital and manipulate trade and investment policy in service of its long-term objectives. Washington\u2019s Inflation Reduction Act and the CHIPS and Science Act, meanwhile, were more likely historic anomalies than first steps in a broader trend toward greater industrial policy, given the uneasiness among Republican lawmakers over their passage. Indeed, even as he seeks to boost the U.S. semiconductor industry, Trump has called for the repeal of the CHIPS and Science Act, which provides subsidies for semiconductor manufacturing. The subsidies provided by the Inflation Reduction Act are likely to face political challenges, too.\n\nThere is an active debate over whether the Biden administration got sufficient bang for its industrial policy buck beyond a few key sectors. U.S. investment in manufacturing has surged, and arguably industrial capacity has expanded. But as the economist Jason Furman pointed out in Foreign Affairs earlier this year, \u201cThe proportion of people working in manufacturing has been declining for decades and has not ticked back up, and overall domestic industrial production remains stagnant\u2014in part because the fiscal expansion Biden oversaw led to higher costs, a stronger dollar, and higher interest rates, all of which have created headwinds for the manufacturing sectors that received no special subsidies from the legislation he championed.\u201d Wherever one comes down in this debate, one thing is clear: even in the sectors that the Biden administration subsidized, such as semiconductors and green energy, the path to regaining global leadership is long and uncertain.\n\nThe United States may play the protectionist game as well as others, but soon, inflation, higher costs of living, and job losses in industries or sectors affected by other countries\u2019 retaliation will begin to bite. Trump appears to believe that a wall of tariffs\u2014as well as the uncertainty about whether tariffs are on or off at any particular moment\u2014is a powerful incentive for companies to locate their production in the United States, where they can be sure their goods will not be subject to tariffs. But as a general matter, companies that consider making the necessary capital investments to spur industrial production in the United States are looking for predictable policy environments, not tariffs that are imposed in the morning and withdrawn in the afternoon. Most may decide to sit on the sidelines, keeping their powder dry, until it becomes clearer what tariffs are going into effect, against whom, and for how long.\n\n After berating Beijing for its restrictions, Washington is putting up the same barriers.\n\nThe historical record of tariffs driving expanded production and manufacturing jobs in the United States is far from definitive. Take, for example, the tariffs imposed by Trump in 2018 on Chinese imports. As a 2024 paper by Federal Reserve researchers Aaron Flaaen and Justin Pierce found, \u201cTariff increases enacted since early 2018 are associated with relative reductions in U.S. manufacturing employment and relative increases in producer prices. In terms of manufacturing employment, rising input costs and retaliatory tariffs account for the negative relationship, and the contribution from these channels more than offsets a small positive effect from import protection.\u201d Some research has suggested that 75,000 downstream manufacturing jobs have been lost as a direct result of the tariffs, not to mention additional losses from retaliatory tariffs. The economic experts Benn Steil and Elisabeth Harding have also found that productivity in the U.S. steel industry tanked while productivity in other sectors rose since Trump imposed 25 percent tariffs on steel imports in March 2018. Output per hour in the U.S. steel industry has tumbled by 32 percent since 2017.\n\nPerhaps Trump\u2019s approach to moving production back to the United States will bear fruit, but for that to happen, the U.S. government would have to permit foreign firms to actually make such investments. Both Biden and Trump opposed the Japanese company Nippon Steel\u2019s acquisition of U.S. Steel, and U.S. policymakers are still debating whether Saudi Arabia\u2019s Public Investment Fund can acquire a controlling stake in the PGA Tour, which organizes U.S. golf tournaments\u2014hardly a critical industry.\n\nThe United States and others are imitating China in large part because China succeeded in a way that was unexpected. Its success in electric vehicles and clean technology did not come from liberalizing economic policies but from state interventions in the market in the name of nationalist objectives. Whether or not the United States can compete with China on China\u2019s playing field, it is important to recognize a fundamental truth: the United States is now operating largely in accordance with Beijing\u2019s standards, with a new economic model characterized by protectionism, constraints on foreign investment, subsidies, and industrial policy\u2014essentially nationalist state capitalism. In the war over who gets to define the rules of the road, the battle is over, at least for now. And China won.\n\nLoading...\n\nYou are reading a free article\n\nSubscribe to Foreign Affairs to get unlimited access.\n\n\n Paywall-free reading of new articles and over a century of archives\n Six issues a year in print and online, plus audio articles\n Unlock access to the Foreign Affairs app for reading on the go\n\nAlready a subscriber? Sign In \n\n\nThe Real China Trump Card]]>\n  \n  \n    Sources: After historic USL vote, promotion, relegation in USA to become reality - The Athletic\n    https://www.nytimes.com/athletic/6213452/2025/03/18/usl-promotion-relegation-us-soccer-vote/?source=user_shared_article\n    readwise:01jpp0qt9vgdfqmn13da66c0ye\n    Wed, 19 Mar 2025 01:36:56 +0000\n    New York Times\n    \n\nIn a historic move, United Soccer League (USL) owners voted Tuesday to become the first professional soccer entity in the United States to adopt promotion and relegation, sources with knowledge of the vote told The Athletic.\n\nUSL owners passed the vote with a supermajority, according to those sources.\n\nThe USL currently operates two pro leagues: the second-division USL Championship and third-division USL League One. Last month it announced it will launch a new first division, with expectations to begin play in 2028. League owners now will look to introduce promotion and relegation throughout that three-tiered pyramid, with an aim to launch pro-rel along along with the new Division 1 league.\n\nThe pro-rel system is used commonly throughout the world. In leagues that utilize promotion and relegation, teams that finish at the bottom of the table move down to the division directly beneath their league, while teams that finish atop the lower divisions move up.\n\nThe USL previously discussed implementing pro-rel in 2023, but had not been able to get enough support to bring it to a vote. That changed this week, sources said, when, among other things, the positive response to the announced Division 1 league helped to spur owners into action.\n\nOver the last few years, USL has studied different versions of what a pro-rel system would look like if implemented. That likely still has to be finalized in coming years.\n\nThe change could dramatically reshape what the USL \u2014 and American pro soccer \u2014 looks like.\n\nMajor League Soccer operates as a single-entity business and is a closed league, with no promotion and relegation, akin more to North American sports leagues like the NFL, NBA, MLB and NHL. MLS, like the USL leagues now, uses a playoff system to determine its champion and provide some level of consequence for teams who finish above or below the playoff line.\n\nCurrently, U.S. Soccer\u2019s pro league standards include stringent guidelines for D1 teams, as well as for teams in the second and third tier. The introduction of promotion and relegation could force the sport\u2019s governing body to rethink some of those standards in order to accommodate teams that move up and down within USL\u2019s pyramid.\n\nUSL\u2019s initial push for promotion and relegation was held up in part by owners\u2019 fears about lost revenue should their teams be relegated. It\u2019s a financial hardship that has been demonstrated around the world in more established leagues. But those leagues also have more established revenues \u2014 and larger media deals.\n\nUSL relies almost exclusively on gameday revenues, including ticketing and concessions, as well as local sponsorship deals. Those are less likely to be impacted in the short- and medium-term as USL implements pro-rel. And while USL has an agreement with CBS and drew 431,000 viewers for its championship game last year \u2014 just shy of the 468,000 viewers that tuned in to MLS Cup on Fox and Fox Deportes, though that does not include viewers on Apple\u2019s MLS Season Pass \u2014 it\u2019s a far cry from the media deals in England, for example, where hundreds of millions of dollars are at stake for teams that go in and out of the Premier League.\n\nThe jeopardy in England, in other words, is much larger. Promotion and relegation could help to drive more media interest in USL, however. For USL leaders, that meant more potential upside in introducing a system that is used around the world \u2014 and one for which a sector of Americans fans have clamored for years. Shows like Welcome to Wrexham and Ted Lasso have introduced the romantic side of promotion and relegation to a wider group of sports fans in recent years.\n\nNow, fans of USL clubs will have the chance to follow pro-rel stories in their own backyard.\n\n  What You Should Read Next  \n   USL questions answered: Can new division challenge MLS, will pro/rel work   Answering pressing questions about USL's new division to rival MLS, with promotion and relegation highlighted     \n\n(Top photo: Joe Rondone/Arizona Republic/Imagn Images)\n\nPaul Tenorio is a senior writer for The Athletic who covers soccer. He has previously written for the Washington Post, the Orlando Sentinel, FourFourTwo, ESPN and MLSsoccer.com. Follow Paul on Twitter @PaulTenorio]]>\n    \n\nIn a historic move, United Soccer League (USL) owners voted Tuesday to become the first professional soccer entity in the United States to adopt promotion and relegation, sources with knowledge of the vote told The Athletic.\n\nUSL owners passed the vote with a supermajority, according to those sources.\n\nThe USL currently operates two pro leagues: the second-division USL Championship and third-division USL League One. Last month it announced it will launch a new first division, with expectations to begin play in 2028. League owners now will look to introduce promotion and relegation throughout that three-tiered pyramid, with an aim to launch pro-rel along along with the new Division 1 league.\n\nThe pro-rel system is used commonly throughout the world. In leagues that utilize promotion and relegation, teams that finish at the bottom of the table move down to the division directly beneath their league, while teams that finish atop the lower divisions move up.\n\nThe USL previously discussed implementing pro-rel in 2023, but had not been able to get enough support to bring it to a vote. That changed this week, sources said, when, among other things, the positive response to the announced Division 1 league helped to spur owners into action.\n\nOver the last few years, USL has studied different versions of what a pro-rel system would look like if implemented. That likely still has to be finalized in coming years.\n\nThe change could dramatically reshape what the USL \u2014 and American pro soccer \u2014 looks like.\n\nMajor League Soccer operates as a single-entity business and is a closed league, with no promotion and relegation, akin more to North American sports leagues like the NFL, NBA, MLB and NHL. MLS, like the USL leagues now, uses a playoff system to determine its champion and provide some level of consequence for teams who finish above or below the playoff line.\n\nCurrently, U.S. Soccer\u2019s pro league standards include stringent guidelines for D1 teams, as well as for teams in the second and third tier. The introduction of promotion and relegation could force the sport\u2019s governing body to rethink some of those standards in order to accommodate teams that move up and down within USL\u2019s pyramid.\n\nUSL\u2019s initial push for promotion and relegation was held up in part by owners\u2019 fears about lost revenue should their teams be relegated. It\u2019s a financial hardship that has been demonstrated around the world in more established leagues. But those leagues also have more established revenues \u2014 and larger media deals.\n\nUSL relies almost exclusively on gameday revenues, including ticketing and concessions, as well as local sponsorship deals. Those are less likely to be impacted in the short- and medium-term as USL implements pro-rel. And while USL has an agreement with CBS and drew 431,000 viewers for its championship game last year \u2014 just shy of the 468,000 viewers that tuned in to MLS Cup on Fox and Fox Deportes, though that does not include viewers on Apple\u2019s MLS Season Pass \u2014 it\u2019s a far cry from the media deals in England, for example, where hundreds of millions of dollars are at stake for teams that go in and out of the Premier League.\n\nThe jeopardy in England, in other words, is much larger. Promotion and relegation could help to drive more media interest in USL, however. For USL leaders, that meant more potential upside in introducing a system that is used around the world \u2014 and one for which a sector of Americans fans have clamored for years. Shows like Welcome to Wrexham and Ted Lasso have introduced the romantic side of promotion and relegation to a wider group of sports fans in recent years.\n\nNow, fans of USL clubs will have the chance to follow pro-rel stories in their own backyard.\n\n  What You Should Read Next  \n   USL questions answered: Can new division challenge MLS, will pro/rel work   Answering pressing questions about USL's new division to rival MLS, with promotion and relegation highlighted     \n\n(Top photo: Joe Rondone/Arizona Republic/Imagn Images)\n\nPaul Tenorio is a senior writer for The Athletic who covers soccer. He has previously written for the Washington Post, the Orlando Sentinel, FourFourTwo, ESPN and MLSsoccer.com. Follow Paul on Twitter @PaulTenorio]]>\n  \n  \n    Can Iran Save Itself?\n    https://reader.foreignaffairs.com/2025/03/17/can-iran-save-itself/content.html\n    readwise:01jphxqpam2dt11vz3k9sjmwvj\n    Mon, 17 Mar 2025 11:27:29 +0000\n    Foreign Affairs\n    \nPeople waving flags during the anniversary of the Islamic Revolution in Tehran, February 2025 - Majid Asgaripour / West Asia News Agency / Reuters\n\nThe Islamic Republic Is Attempting Reform at Home\u2014so It Can Withstand Pressure From Washington\n\nOver the past year, Iran has grappled with a series of setbacks. Hamas and Hezbollah, Tehran\u2019s long-standing nonstate regional allies, have been weakened by Israel. President Bashar al-Assad\u2019s government in Syria collapsed suddenly and spectacularly. The return of Donald Trump to the U.S. presidency, meanwhile, signals a revival of the maximum pressure policies that hobbled the Iranian economy starting in 2018. These looming challenges have led many U.S. officials and analysts to argue that the Islamic Republic is facing a strategic defeat. Richard Haass, writing in Foreign Affairs in January, suggested that \u201cIran is weaker and more vulnerable than it has been in decades, likely since its decadelong war with Iraq or even since the 1979 revolution.\u201d According to this view, Iran has presented its opponents with an opportune moment to target its nuclear facilities or extract major concessions for a new nuclear deal.\n\nThe prevailing belief that Iran is now more susceptible to U.S. coercion or Israeli attack, however, is not shared by Tehran. The Islamic Republic views these external challenges as temporary setbacks, not signs of defeat. In Iran\u2019s view, Hamas and Hezbollah, despite being badly beaten, have actually emerged as winners in their asymmetric conflict against Israel. They survived as guerrilla organizations against a powerful U.S.-backed conventional army. Critically, Hamas has retained at least some popularity in among Palestinians, and Hezbollah continues to enjoy the backing of Shiites in Lebanon. In Yemen, the Iran-aligned Houthis have solidified their role as a steadfast supporter of the Palestinian cause and a key member of Tehran\u2019s so-called axis of resistance by attacking Israel and disrupting shipping in the Red Sea.\n\nStill, Iran realizes that its network of partners is not as powerful today as it was before Hamas\u2019s October 7 attacks. And it was alarmed by the sudden fall of the unpopular Assad. As a result, it has taken steps to shore up its domestic support by making limited internal concessions to a population fed up with authoritarian, theocratic governance. The regime has eased the enforcement of the mandatory dress code for women and relaxed restrictions on social media platforms, allowing increasingly critical discussions of the government\u2019s policies. In doing so, the Islamic Republic hopes it can lessen the risk of domestic unrest and foster public trust.\n\nBut these domestic shifts should not be understood as harbingers of a grand reopening to the West. In fact, the goal of Iran\u2019s measured (and reversible) social reforms is to consolidate support at home to resist pressure from abroad. Trump has suggested an openness to negotiations with Tehran but also a willingness to attack the country. With the public behind Tehran, or at least less opposed, the government hopes it can withstand whatever the U.S. president has in store.\n\nA WARNING FROM DAMASCUS\n\nIsrael may be celebrating its military triumph over Hamas and Hezbollah. But Iran is relatively unconcerned about the two organizations. Despite the devastating losses each incurred, Tehran expects that Hamas and Hezbollah will rebuild themselves, bolstered by grassroots support and hatred of Israel. It even expects that the battlefield deaths of Hamas leader Yahya Sinwar and Hezbollah leader Hassan Nasrallah will reinforce the organizations\u2019 ideological commitments and resonate with a sympathetic public for years to come.\n\nBut Assad\u2019s fall is harder for Iran to shake off. Although the former Syrian president\u2019s unpopularity was widely recognized, the rapid disintegration of the Syrian army caught even Iran\u2019s leadership\u2014Assad\u2019s primary patron\u2014off guard. According to Iranian Foreign Minister Abbas Araghchi, the Islamic Republic intelligence community was \u201cfully aware\u201d of the imminent security threat against Assad. But Tehran was nonetheless surprised by the Syrian army\u2019s complete inability to repel rebel forces. Iranian officials partially attribute the disintegration of Assad\u2019s army to \u201cpsychological warfare\u201d by external forces, including Israel, Turkey, and the United States. But Araghchi also pinned some of the blame on Assad\u2019s disregard for public opinion. Iran, Araghchi claimed, had \u201cconsistently\u201d advised Assad to boost military morale and \u201cinteract more with the people, as what ultimately secures a government is the people.\u201d But Assad, Araghchi noted, had failed.\n\nThe sudden unraveling of Syria has prompted public anxiety within Iran, where persistent repression and corruption have also driven a wedge between the government and its populace (as has secularization). In January, Abbas Salehi, Iranian minister of culture and Islamic guidance, outwardly acknowledged that Tehran is facing a severe \u201csocial capital\u201d deficit, as public trust in the government has fallen. Former President Mohammad Khatami warned that the Islamic Republic risks \u201cself-subversion\u201d by disregarding public resentment. Across the political spectrum, Iranian elites increasingly agree on the urgent need to build internal resilience.\n\nIran\u2019s government has, accordingly, loosened some of its restrictions. Most notably, in December 2024, Iran\u2019s Supreme National Security Council effectively paused the implementation of a controversial new veiling law that would impose financial penalties, prison terms, and other punishments, such as travel bans, on women who appeared in public without a headscarf or were judged to have worn \u201cimproper\u201d attire. Despite calls from some ultraconservatives for strict enforcement of the country\u2019s dress code\u2014and occasional targeted crackdowns by the government to appease its religious base\u2014women can now appear unveiled in public with less fear of harsh reprisal. And even the hardliners are not entirely united in their opposition: On March 15, conservative parliamentarian Mahmoud Nabavian acknowledged fears of Iran\u2019s \u201cSyrianization\u201d as the motivation behind the suspension of the law, agreeing that it should be \u201cput aside if it undermines the system.\u201d\n\n\nThe sudden unraveling of Syria has prompted public anxiety within Iran.\n\nThis development reflects a tacit acknowledgment by the state that the veiling mandate is unpopular and, at least for now, impractical. It also comes three years after 22-year-old Mahsa Amini died in the custody of the morality police following her arrest for not properly wearing her veil. Amini\u2019s death prompted mass street protests in 2022, which Iran snuffed out with unrelenting violence. Ultimately, the Islamic Republic temporarily removed the morality police from the streets to ease tensions. Now, Tehran seems increasingly willing to tolerate the relaxed enforcement of veiling laws, provided this shift does not escalate into a broader political movement challenging the regime itself.\n\nIn addition to this pause, the Islamic Republic is attempting to curry popular favor by allowing for relatively open and candid discussions on domestic media outlets. Social media platforms used in Iran now host a diverse array of commentators, including independent and dissident voices, both inside and outside the country. The government continues to quietly promote platforms connected to the state, and there are plenty of independent regime defenders. But online discussions about the veiling law, the collapse of Assad, and broader social, political, and economic issues are surprisingly frank and nuanced. Some commentators openly describe leadership as a disaster for the country.\n\nAt first, it might seem strange that Iran would let people hear anti-regime commentary for the sake of stability. But Tehran hopes that by opening domestic space, it can provide a safety valve for public frustration and diminish the appeal of satellite international media outlets such as the BBC\u2014which is more critical of the Islamic Republic than Iranian voices. The regime has turned to this strategy at precarious moments before. At the height of the 2022 protests, it encouraged previously banned figures to appear on television, hoping that their criticisms would channel public discontent away from the streets. This time, Tehran believes that a relatively free flow of information, if carefully managed, could strengthen the regime\u2019s own narrative on national security in the long term.\n\nSETTING THE HOUSE IN ORDER\n\nIran\u2019s leaders hope that managing domestic stability through piecemeal reforms will create an atmosphere conducive to a national debate on major foreign policy issues, such as the nuclear standoff\u2014one that it believes will result in national unity. The consensus among elites, at least, is that such a debate will enhance the government\u2019s bargaining position as it pursues an agreement with the United States that could address Washington\u2019s concerns over the weaponization of the Iranian nuclear program but stop short of ending uranium enrichment, restricting conventional weapons, or weakening the axis of resistance. Domestic protests, after all, only create openings for adversaries such as the United States\u2014which see cracks in Iran\u2019s society as signs of weakness.\n\nTo Iranian leaders, forging such unity is especially important when facing Washington. The Biden administration, for example, sought to use the economic damage inflicted by Trump\u2019s maximum pressure campaign to secure a \u201clonger and better deal\u201d than the original Iran nuclear deal, the 2015 Joint Comprehensive Plan of Action. But Iran, bolstered by a measure of internal cohesion in the face of an external threat from the United States, adopted an even harder bargaining position than before. Given the Trump administration\u2019s belief that Iran has been weakened since October 7, the president likely thinks he can secure a deal with Tehran that is even more favorable to the United States. If he can\u2019t, Trump has floated using force. \u201cThere are two ways Iran can be handled: militarily, or you make a deal,\u201d Trump claims to have told Iranian Supreme Leader Ali Khamenei in March. Trump has also said his administration is \u201cdown to the final moments with Iran.\u201d For Iran, having a supportive public is essential to weathering this storm.\n\nTrump\u2019s threats, of course, could again be enough to create internal cohesion. But with the example of Assad seared into their minds, Iran\u2019s leaders are leaving nothing to chance. \u201cThink about this: On the day confrontation occurs, how united is Iranian society?\u201d an adviser to Mohammad Baqer Qalibaf, the conservative speaker of Iran\u2019s parliament, wrote on X. \u201cWho is to blame for the problems in the eyes of the people? The answers to these questions determine what constitutes service and what constitutes betrayal.\u201d\n\nTehran is determined to prevent domestic divisions from weakening the country\u2019s ability to withstand pressure. Limited social and political openings serve as a calculated strategy to diffuse public frustration before it escalates into mass unrest. If past is prologue, this approach could allow the Islamic Republic to frame any conflict with United States not as a struggle for regime survival but as a sovereign nation\u2019s resistance against external coercion. But it does not portend a shift in the regime\u2019s core strategy. Tehran, in other words, is not about to cast aside decades of defiance.\n\nAbout the Author:\n\nMOHAMMAD AYATOLLAHI TABAAR is a Fellow at the Harvard Kennedy School, Associate Professor of International Affairs at Texas A&M University\u2019s Bush School of Government and Public Service, and a Fellow at Rice University\u2019s Baker Institute for Public Policy. He is the author of Religious Statecraft: The Politics of Islam in Iran.]]>\n    \nPeople waving flags during the anniversary of the Islamic Revolution in Tehran, February 2025 - Majid Asgaripour / West Asia News Agency / Reuters\n\nThe Islamic Republic Is Attempting Reform at Home\u2014so It Can Withstand Pressure From Washington\n\nOver the past year, Iran has grappled with a series of setbacks. Hamas and Hezbollah, Tehran\u2019s long-standing nonstate regional allies, have been weakened by Israel. President Bashar al-Assad\u2019s government in Syria collapsed suddenly and spectacularly. The return of Donald Trump to the U.S. presidency, meanwhile, signals a revival of the maximum pressure policies that hobbled the Iranian economy starting in 2018. These looming challenges have led many U.S. officials and analysts to argue that the Islamic Republic is facing a strategic defeat. Richard Haass, writing in Foreign Affairs in January, suggested that \u201cIran is weaker and more vulnerable than it has been in decades, likely since its decadelong war with Iraq or even since the 1979 revolution.\u201d According to this view, Iran has presented its opponents with an opportune moment to target its nuclear facilities or extract major concessions for a new nuclear deal.\n\nThe prevailing belief that Iran is now more susceptible to U.S. coercion or Israeli attack, however, is not shared by Tehran. The Islamic Republic views these external challenges as temporary setbacks, not signs of defeat. In Iran\u2019s view, Hamas and Hezbollah, despite being badly beaten, have actually emerged as winners in their asymmetric conflict against Israel. They survived as guerrilla organizations against a powerful U.S.-backed conventional army. Critically, Hamas has retained at least some popularity in among Palestinians, and Hezbollah continues to enjoy the backing of Shiites in Lebanon. In Yemen, the Iran-aligned Houthis have solidified their role as a steadfast supporter of the Palestinian cause and a key member of Tehran\u2019s so-called axis of resistance by attacking Israel and disrupting shipping in the Red Sea.\n\nStill, Iran realizes that its network of partners is not as powerful today as it was before Hamas\u2019s October 7 attacks. And it was alarmed by the sudden fall of the unpopular Assad. As a result, it has taken steps to shore up its domestic support by making limited internal concessions to a population fed up with authoritarian, theocratic governance. The regime has eased the enforcement of the mandatory dress code for women and relaxed restrictions on social media platforms, allowing increasingly critical discussions of the government\u2019s policies. In doing so, the Islamic Republic hopes it can lessen the risk of domestic unrest and foster public trust.\n\nBut these domestic shifts should not be understood as harbingers of a grand reopening to the West. In fact, the goal of Iran\u2019s measured (and reversible) social reforms is to consolidate support at home to resist pressure from abroad. Trump has suggested an openness to negotiations with Tehran but also a willingness to attack the country. With the public behind Tehran, or at least less opposed, the government hopes it can withstand whatever the U.S. president has in store.\n\nA WARNING FROM DAMASCUS\n\nIsrael may be celebrating its military triumph over Hamas and Hezbollah. But Iran is relatively unconcerned about the two organizations. Despite the devastating losses each incurred, Tehran expects that Hamas and Hezbollah will rebuild themselves, bolstered by grassroots support and hatred of Israel. It even expects that the battlefield deaths of Hamas leader Yahya Sinwar and Hezbollah leader Hassan Nasrallah will reinforce the organizations\u2019 ideological commitments and resonate with a sympathetic public for years to come.\n\nBut Assad\u2019s fall is harder for Iran to shake off. Although the former Syrian president\u2019s unpopularity was widely recognized, the rapid disintegration of the Syrian army caught even Iran\u2019s leadership\u2014Assad\u2019s primary patron\u2014off guard. According to Iranian Foreign Minister Abbas Araghchi, the Islamic Republic intelligence community was \u201cfully aware\u201d of the imminent security threat against Assad. But Tehran was nonetheless surprised by the Syrian army\u2019s complete inability to repel rebel forces. Iranian officials partially attribute the disintegration of Assad\u2019s army to \u201cpsychological warfare\u201d by external forces, including Israel, Turkey, and the United States. But Araghchi also pinned some of the blame on Assad\u2019s disregard for public opinion. Iran, Araghchi claimed, had \u201cconsistently\u201d advised Assad to boost military morale and \u201cinteract more with the people, as what ultimately secures a government is the people.\u201d But Assad, Araghchi noted, had failed.\n\nThe sudden unraveling of Syria has prompted public anxiety within Iran, where persistent repression and corruption have also driven a wedge between the government and its populace (as has secularization). In January, Abbas Salehi, Iranian minister of culture and Islamic guidance, outwardly acknowledged that Tehran is facing a severe \u201csocial capital\u201d deficit, as public trust in the government has fallen. Former President Mohammad Khatami warned that the Islamic Republic risks \u201cself-subversion\u201d by disregarding public resentment. Across the political spectrum, Iranian elites increasingly agree on the urgent need to build internal resilience.\n\nIran\u2019s government has, accordingly, loosened some of its restrictions. Most notably, in December 2024, Iran\u2019s Supreme National Security Council effectively paused the implementation of a controversial new veiling law that would impose financial penalties, prison terms, and other punishments, such as travel bans, on women who appeared in public without a headscarf or were judged to have worn \u201cimproper\u201d attire. Despite calls from some ultraconservatives for strict enforcement of the country\u2019s dress code\u2014and occasional targeted crackdowns by the government to appease its religious base\u2014women can now appear unveiled in public with less fear of harsh reprisal. And even the hardliners are not entirely united in their opposition: On March 15, conservative parliamentarian Mahmoud Nabavian acknowledged fears of Iran\u2019s \u201cSyrianization\u201d as the motivation behind the suspension of the law, agreeing that it should be \u201cput aside if it undermines the system.\u201d\n\n\nThe sudden unraveling of Syria has prompted public anxiety within Iran.\n\nThis development reflects a tacit acknowledgment by the state that the veiling mandate is unpopular and, at least for now, impractical. It also comes three years after 22-year-old Mahsa Amini died in the custody of the morality police following her arrest for not properly wearing her veil. Amini\u2019s death prompted mass street protests in 2022, which Iran snuffed out with unrelenting violence. Ultimately, the Islamic Republic temporarily removed the morality police from the streets to ease tensions. Now, Tehran seems increasingly willing to tolerate the relaxed enforcement of veiling laws, provided this shift does not escalate into a broader political movement challenging the regime itself.\n\nIn addition to this pause, the Islamic Republic is attempting to curry popular favor by allowing for relatively open and candid discussions on domestic media outlets. Social media platforms used in Iran now host a diverse array of commentators, including independent and dissident voices, both inside and outside the country. The government continues to quietly promote platforms connected to the state, and there are plenty of independent regime defenders. But online discussions about the veiling law, the collapse of Assad, and broader social, political, and economic issues are surprisingly frank and nuanced. Some commentators openly describe leadership as a disaster for the country.\n\nAt first, it might seem strange that Iran would let people hear anti-regime commentary for the sake of stability. But Tehran hopes that by opening domestic space, it can provide a safety valve for public frustration and diminish the appeal of satellite international media outlets such as the BBC\u2014which is more critical of the Islamic Republic than Iranian voices. The regime has turned to this strategy at precarious moments before. At the height of the 2022 protests, it encouraged previously banned figures to appear on television, hoping that their criticisms would channel public discontent away from the streets. This time, Tehran believes that a relatively free flow of information, if carefully managed, could strengthen the regime\u2019s own narrative on national security in the long term.\n\nSETTING THE HOUSE IN ORDER\n\nIran\u2019s leaders hope that managing domestic stability through piecemeal reforms will create an atmosphere conducive to a national debate on major foreign policy issues, such as the nuclear standoff\u2014one that it believes will result in national unity. The consensus among elites, at least, is that such a debate will enhance the government\u2019s bargaining position as it pursues an agreement with the United States that could address Washington\u2019s concerns over the weaponization of the Iranian nuclear program but stop short of ending uranium enrichment, restricting conventional weapons, or weakening the axis of resistance. Domestic protests, after all, only create openings for adversaries such as the United States\u2014which see cracks in Iran\u2019s society as signs of weakness.\n\nTo Iranian leaders, forging such unity is especially important when facing Washington. The Biden administration, for example, sought to use the economic damage inflicted by Trump\u2019s maximum pressure campaign to secure a \u201clonger and better deal\u201d than the original Iran nuclear deal, the 2015 Joint Comprehensive Plan of Action. But Iran, bolstered by a measure of internal cohesion in the face of an external threat from the United States, adopted an even harder bargaining position than before. Given the Trump administration\u2019s belief that Iran has been weakened since October 7, the president likely thinks he can secure a deal with Tehran that is even more favorable to the United States. If he can\u2019t, Trump has floated using force. \u201cThere are two ways Iran can be handled: militarily, or you make a deal,\u201d Trump claims to have told Iranian Supreme Leader Ali Khamenei in March. Trump has also said his administration is \u201cdown to the final moments with Iran.\u201d For Iran, having a supportive public is essential to weathering this storm.\n\nTrump\u2019s threats, of course, could again be enough to create internal cohesion. But with the example of Assad seared into their minds, Iran\u2019s leaders are leaving nothing to chance. \u201cThink about this: On the day confrontation occurs, how united is Iranian society?\u201d an adviser to Mohammad Baqer Qalibaf, the conservative speaker of Iran\u2019s parliament, wrote on X. \u201cWho is to blame for the problems in the eyes of the people? The answers to these questions determine what constitutes service and what constitutes betrayal.\u201d\n\nTehran is determined to prevent domestic divisions from weakening the country\u2019s ability to withstand pressure. Limited social and political openings serve as a calculated strategy to diffuse public frustration before it escalates into mass unrest. If past is prologue, this approach could allow the Islamic Republic to frame any conflict with United States not as a struggle for regime survival but as a sovereign nation\u2019s resistance against external coercion. But it does not portend a shift in the regime\u2019s core strategy. Tehran, in other words, is not about to cast aside decades of defiance.\n\nAbout the Author:\n\nMOHAMMAD AYATOLLAHI TABAAR is a Fellow at the Harvard Kennedy School, Associate Professor of International Affairs at Texas A&M University\u2019s Bush School of Government and Public Service, and a Fellow at Rice University\u2019s Baker Institute for Public Policy. He is the author of Religious Statecraft: The Politics of Islam in Iran.]]>\n  \n  \n    Just a few minutes ago, President Trump signed an Executive...\n    https://x.com/davidsacks47/status/1897802280738734236/?s=12&rw_tt_thread=True\n    readwise:01jnqeaxcmcyfvwbnsfyn63sas\n    Fri, 07 Mar 2025 04:38:06 +0000\n    X (formerly Twitter)\n    \nJust a few minutes ago, President Trump signed an Executive Order to establish a Strategic Bitcoin Reserve. \nThe Reserve will be capitalized with Bitcoin owned by the federal government that was forfeited as part of criminal or civil asset forfeiture proceedings. This means it will not cost taxpayers a dime. \nIt is estimated that the U.S. government owns about 200,000 bitcoin; however, there has never been a complete audit. The E.O. directs a full accounting of the federal government\u2019s digital asset holdings. \nThe U.S. will not sell any bitcoin deposited into the Reserve. It will be kept as a store of value. The Reserve is like a digital Fort Knox for the cryptocurrency often called \u201cdigital gold.\u201d\nPremature sales of bitcoin have already cost U.S. taxpayers over $17 billion in lost value. Now the federal government will have a strategy to maximize the value of its holdings. \nThe Secretaries of Treasury and Commerce are authorized to develop budget-neutral strategies for acquiring additional bitcoin, provided that those strategies have no incremental costs on American taxpayers. \nIN ADDITION, the Executive Order establishes a U.S. Digital Asset Stockpile, consisting of digital assets other than bitcoin forfeited in criminal or civil proceedings. \nThe government will not acquire additional assets for the Stockpile beyond those obtained through forfeiture proceedings. \nThe purpose of the Stockpile is responsible stewardship of the government\u2019s digital assets under the Treasury Department. \nPROMISES MADE, PROMISES KEPT\nPresident Trump promised to create a Strategic Bitcoin Reserve and Digital Asset Stockpile. Those promises have been kept. \nThis Executive Order underscores President Trump\u2019s commitment to making the U.S. the \u201ccrypto capital of the world.\u201d \nI want to thank the President for his leadership and vision in supporting this cutting-edge technology and for his rapid execution in supporting the digital asset industry. His administration is truly moving at \u201ctech speed.\u201d\nI also want to thank the President\u2019s Working Group on Digital Asset Markets \u2014 especially Treasury Secretary Scott Bessent and Commerce Secretary Howard Lutnick \u2014 for their help and support in getting this done. Finally Bo Hines played a critical role as Executive Director of our Working Group.]]>\n    \nJust a few minutes ago, President Trump signed an Executive Order to establish a Strategic Bitcoin Reserve. \nThe Reserve will be capitalized with Bitcoin owned by the federal government that was forfeited as part of criminal or civil asset forfeiture proceedings. This means it will not cost taxpayers a dime. \nIt is estimated that the U.S. government owns about 200,000 bitcoin; however, there has never been a complete audit. The E.O. directs a full accounting of the federal government\u2019s digital asset holdings. \nThe U.S. will not sell any bitcoin deposited into the Reserve. It will be kept as a store of value. The Reserve is like a digital Fort Knox for the cryptocurrency often called \u201cdigital gold.\u201d\nPremature sales of bitcoin have already cost U.S. taxpayers over $17 billion in lost value. Now the federal government will have a strategy to maximize the value of its holdings. \nThe Secretaries of Treasury and Commerce are authorized to develop budget-neutral strategies for acquiring additional bitcoin, provided that those strategies have no incremental costs on American taxpayers. \nIN ADDITION, the Executive Order establishes a U.S. Digital Asset Stockpile, consisting of digital assets other than bitcoin forfeited in criminal or civil proceedings. \nThe government will not acquire additional assets for the Stockpile beyond those obtained through forfeiture proceedings. \nThe purpose of the Stockpile is responsible stewardship of the government\u2019s digital assets under the Treasury Department. \nPROMISES MADE, PROMISES KEPT\nPresident Trump promised to create a Strategic Bitcoin Reserve and Digital Asset Stockpile. Those promises have been kept. \nThis Executive Order underscores President Trump\u2019s commitment to making the U.S. the \u201ccrypto capital of the world.\u201d \nI want to thank the President for his leadership and vision in supporting this cutting-edge technology and for his rapid execution in supporting the digital asset industry. His administration is truly moving at \u201ctech speed.\u201d\nI also want to thank the President\u2019s Working Group on Digital Asset Markets \u2014 especially Treasury Secretary Scott Bessent and Commerce Secretary Howard Lutnick \u2014 for their help and support in getting this done. Finally Bo Hines played a critical role as Executive Director of our Working Group.]]>\n  \n  \n    COVID hit Nashville five years ago. Here's how the city responded and rebounded. | Opinion\nMetro Council amends community safety camera network bill, which heads to final reading\n    https://www.yahoo.com/news/covid-hit-nashville-five-years-120356141.html?guccounter=1\n    readwise:01jnnxva12aszpagprr3way0ty\n    Thu, 06 Mar 2025 14:30:43 +0000\n    Yahoo Entertainment\n    On March 6, 2020, a Nashvillian in her 40s wasn\u2019t feeling well. She had just returned from a conference in Boston and sought care from her healthcare provider.\n\nRecognizing something unusual, that provider tested her for a virus we were only beginning to understand. The results came back late on March 7. By March 8, life in our city had changed forever.\n\nWe emerged from the pandemic transformed. It exposed our deepest vulnerabilities but also revealed our greatest strengths. The question now is: What did we learn? And will we be ready next time?\n\nAs a surgeon, my work is about making order out of chaos and restoring what is broken. But in 2020, I faced something no medical training had prepared me for \u2013 a city shattered by the worst health crisis of our time.\n\nAs the then chair of the Metro Nashville Board of Health, I was asked to lead the city\u2019s COVID-19 Task Force. We were unprepared for the scale of the unknown, but we anchored ourselves to a simple, unwavering principle: experts would lead, science would guide us and transparency would be our foundation.\n\nCOVID cost Nashville dearly, but the city came together\n\nLooking back, the pandemic exposed both our strengths and our shortcomings. It laid bare systemic disparities and deep national divides. Yet, despite these challenges, Nashville pressed forward, determined to protect what mattered most.\n\n\nDr. Alex Jahangir gives COVID-19 updates during a news conference at Lentz Public Health Center Friday, March 13, 2020, in Nashville, Tenn.\n\nAt the height of the crisis, I saw people set aside self-interest to confront challenges together. The pandemic taught us an undeniable truth: whether we like it or not, we are all in the same boat. Each of us has the power to either right the boat \u2013 or capsize it.\n\nBy March 2021, a year into the pandemic, more than 90,000 Nashvillians had tested positive, and 839 had died. We lost neighbors, colleagues, and community leaders \u2013 including former Metro Council Member Tony Tenpenny, ICU nurse Gary Woodward, and 30-year-old entrepreneur Darius Settles. We also lost John Prine, whose music defined generations.\n\nYet, even amid these heartbreaking losses, Nashville achieved remarkable successes. Our mortality rate was among the lowest in the Southeast. Our vaccination efforts outpaced many peer cities. We administered over 400,000 PCR tests and 25,000 vaccines at the three community sites operated by Meharry Medical College, vaccinated 10,000 people in a single day at Nissan Stadium, and converted Music City Center into a high-volume vaccination hub.\n\nWe made the tough decisions necessary to protect both public health and economic stability \u2013 understanding that one could not recover without the other. Nashville\u2019s unemployment rate, which peaked at 15.3% in April 2020, fell below 3% by mid-2021 \u2013 one of the fastest recoveries in the nation.\n\nMore in U.S.\n\n\n\nElizabeth Smart: Boy found 7 years later proof we can\u2019t \u2018give up\u2019\n\nNewsNation\n\n\n\nRoad to ABIA remains partly closed following fatal crash involving AFD, civilian vehicles\n\nAustin American-Statesman\n\nOpinion: Dolly Parton and Tennessee senators show why Trump must stop public health chaos \n\nOur regional economy, which lost $25.8 billion in 2020, rebounded. By 2022, we ranked among the top U.S. cities for business growth. By 2023, downtown Nashville became the only major U.S. city to fully return to pre-pandemic levels, with its resident, worker, and visitor populations reaching 100% recovery.\n\nLessons of COVID offer a roadmap for dealing with future crises\n\nWhen the Delta variant surged in 2021, overwhelming rural hospitals, Nashville was ready. Our three major health systems \u2013 Ascension Saint Thomas, HCA Tristar, and VUMC \u2013 set aside competition to create a regional transfer center, ensuring that no patient in Middle Tennessee went without care.\n\nIn just three months, 700 critically ill patients were transferred for treatment. This collective effort saved lives.\n\nThe pandemic also forced us to reassess our values. I witnessed a profound shift in how we cared for our elderly. Nashvillians went to extraordinary lengths to protect their older relatives and neighbors.\n\nIn a society that often prizes youth and independence, we paused to honor and safeguard our most vulnerable. It was a reminder that interdependence \u2013 not rugged individualism \u2013 is what sustains us in times of crisis.\n\nAs a trauma surgeon, I know that survival depends on how well we prepare for the next crisis. One of the reasons Nashville succeeded in navigating the pandemic was the deep alignment and partnership between the public and private sectors, the nonprofit and philanthropic communities, and the strong working relationship between city and state leadership. These partnerships didn\u2019t happen by chance \u2013 they were built through commitment, transparency, and a shared purpose.\n\nThe next crisis will come \u2013 whether it\u2019s another public health emergency, an economic shock, or a threat to public safety. But if we apply the same lessons \u2013 collaboration over division, facts over speculation, and action over complacency \u2013 Nashville will once again emerge stronger.\n\nThe time to strengthen these bonds isn\u2019t when the storm arrives, but now. Let\u2019s commit to working together today to build a more resilient, prepared, and unified city for tomorrow.\n\nDr. Alex Jahangir is an orthopaedic trauma surgeon and public health leader who chaired the Nashville COVID-19 Task Force and the Metropolitan Board of Health. He is the author of \u201cHotspot: A Doctor\u2019s Diary From the Pandemic,\u201d which chronicles Nashville\u2019s response and the lessons learned.\n\nThis article originally appeared on Nashville Tennessean: Nashville learned lessons from COVID to fight future crises | Opinion\n\nSome content could not be imported from the original document. View content \u2197 \n\nNASHVILLE, Tenn. (WKRN) \u2014 A bill that would allow the Metro Nashville Police Department to access a community camera safety network passed its second of three readings at Tuesday\u2019s Metro Council meeting, but not without some amendments.\n\nThe bill has been a source of debate and a hot-button topic during public comment periods at during previous Metro Council meetings. Previously, Metro Council narrowly voted down a measure that would have established a contract between the Metro Nashville Police Department and Fusus.\n\n JANUARY: Controversial \u2018Fusus\u2019 program up for discussion again by Metro Council \n\nIn all, four amendments were made to the legislation. One amendment said that any officer requesting access to a camera in the community safety camera network has to create a document with the time, date and each instance of access as well as an explanation of why the camera was accessed. Additionally, an independent firm would have to audit the records created by officers when they access the video.\n\nAn amendment also stipulates that the community camera safety network could not utilize artificial intelligence or machine learning \u201cor any other artificial mechanism to\ncapture conversations through automated lip reading.\u201d\n\nOther amendments restricted the MNPD\u2019s ability to access certain cameras, including one that prohibits the taking of \u201clive video from a donor camera\u201d if that camera is on exclusively residential property. Additionally, the MNPD would no longer be able to have access to donor cameras at multifamily residential properties that focus on any area other than a parking lot, parking garage or other outdoor common area.\n\n DECEMBER 2024 | \u2018Too many unanswered questions\u2019: Metro Council votes down Fusus surveillance contract \n\nFinally, Metro Council approved an amendment stating that video depicting any MNPD employee \u201cutilizing excessive or unlawful force\u201d must be immediately preserved and provided to the MNPD\u2019s office of professional accountability and the district attorney general.\n\nThe bill has to pass the third of three readings to take effect.\n\nCopyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.\n\n For the latest news, weather, sports, and streaming video, head to WKRN News 2. ]]>\n    On March 6, 2020, a Nashvillian in her 40s wasn\u2019t feeling well. She had just returned from a conference in Boston and sought care from her healthcare provider.\n\nRecognizing something unusual, that provider tested her for a virus we were only beginning to understand. The results came back late on March 7. By March 8, life in our city had changed forever.\n\nWe emerged from the pandemic transformed. It exposed our deepest vulnerabilities but also revealed our greatest strengths. The question now is: What did we learn? And will we be ready next time?\n\nAs a surgeon, my work is about making order out of chaos and restoring what is broken. But in 2020, I faced something no medical training had prepared me for \u2013 a city shattered by the worst health crisis of our time.\n\nAs the then chair of the Metro Nashville Board of Health, I was asked to lead the city\u2019s COVID-19 Task Force. We were unprepared for the scale of the unknown, but we anchored ourselves to a simple, unwavering principle: experts would lead, science would guide us and transparency would be our foundation.\n\nCOVID cost Nashville dearly, but the city came together\n\nLooking back, the pandemic exposed both our strengths and our shortcomings. It laid bare systemic disparities and deep national divides. Yet, despite these challenges, Nashville pressed forward, determined to protect what mattered most.\n\n\nDr. Alex Jahangir gives COVID-19 updates during a news conference at Lentz Public Health Center Friday, March 13, 2020, in Nashville, Tenn.\n\nAt the height of the crisis, I saw people set aside self-interest to confront challenges together. The pandemic taught us an undeniable truth: whether we like it or not, we are all in the same boat. Each of us has the power to either right the boat \u2013 or capsize it.\n\nBy March 2021, a year into the pandemic, more than 90,000 Nashvillians had tested positive, and 839 had died. We lost neighbors, colleagues, and community leaders \u2013 including former Metro Council Member Tony Tenpenny, ICU nurse Gary Woodward, and 30-year-old entrepreneur Darius Settles. We also lost John Prine, whose music defined generations.\n\nYet, even amid these heartbreaking losses, Nashville achieved remarkable successes. Our mortality rate was among the lowest in the Southeast. Our vaccination efforts outpaced many peer cities. We administered over 400,000 PCR tests and 25,000 vaccines at the three community sites operated by Meharry Medical College, vaccinated 10,000 people in a single day at Nissan Stadium, and converted Music City Center into a high-volume vaccination hub.\n\nWe made the tough decisions necessary to protect both public health and economic stability \u2013 understanding that one could not recover without the other. Nashville\u2019s unemployment rate, which peaked at 15.3% in April 2020, fell below 3% by mid-2021 \u2013 one of the fastest recoveries in the nation.\n\nMore in U.S.\n\n\n\nElizabeth Smart: Boy found 7 years later proof we can\u2019t \u2018give up\u2019\n\nNewsNation\n\n\n\nRoad to ABIA remains partly closed following fatal crash involving AFD, civilian vehicles\n\nAustin American-Statesman\n\nOpinion: Dolly Parton and Tennessee senators show why Trump must stop public health chaos \n\nOur regional economy, which lost $25.8 billion in 2020, rebounded. By 2022, we ranked among the top U.S. cities for business growth. By 2023, downtown Nashville became the only major U.S. city to fully return to pre-pandemic levels, with its resident, worker, and visitor populations reaching 100% recovery.\n\nLessons of COVID offer a roadmap for dealing with future crises\n\nWhen the Delta variant surged in 2021, overwhelming rural hospitals, Nashville was ready. Our three major health systems \u2013 Ascension Saint Thomas, HCA Tristar, and VUMC \u2013 set aside competition to create a regional transfer center, ensuring that no patient in Middle Tennessee went without care.\n\nIn just three months, 700 critically ill patients were transferred for treatment. This collective effort saved lives.\n\nThe pandemic also forced us to reassess our values. I witnessed a profound shift in how we cared for our elderly. Nashvillians went to extraordinary lengths to protect their older relatives and neighbors.\n\nIn a society that often prizes youth and independence, we paused to honor and safeguard our most vulnerable. It was a reminder that interdependence \u2013 not rugged individualism \u2013 is what sustains us in times of crisis.\n\nAs a trauma surgeon, I know that survival depends on how well we prepare for the next crisis. One of the reasons Nashville succeeded in navigating the pandemic was the deep alignment and partnership between the public and private sectors, the nonprofit and philanthropic communities, and the strong working relationship between city and state leadership. These partnerships didn\u2019t happen by chance \u2013 they were built through commitment, transparency, and a shared purpose.\n\nThe next crisis will come \u2013 whether it\u2019s another public health emergency, an economic shock, or a threat to public safety. But if we apply the same lessons \u2013 collaboration over division, facts over speculation, and action over complacency \u2013 Nashville will once again emerge stronger.\n\nThe time to strengthen these bonds isn\u2019t when the storm arrives, but now. Let\u2019s commit to working together today to build a more resilient, prepared, and unified city for tomorrow.\n\nDr. Alex Jahangir is an orthopaedic trauma surgeon and public health leader who chaired the Nashville COVID-19 Task Force and the Metropolitan Board of Health. He is the author of \u201cHotspot: A Doctor\u2019s Diary From the Pandemic,\u201d which chronicles Nashville\u2019s response and the lessons learned.\n\nThis article originally appeared on Nashville Tennessean: Nashville learned lessons from COVID to fight future crises | Opinion\n\nSome content could not be imported from the original document. View content \u2197 \n\nNASHVILLE, Tenn. (WKRN) \u2014 A bill that would allow the Metro Nashville Police Department to access a community camera safety network passed its second of three readings at Tuesday\u2019s Metro Council meeting, but not without some amendments.\n\nThe bill has been a source of debate and a hot-button topic during public comment periods at during previous Metro Council meetings. Previously, Metro Council narrowly voted down a measure that would have established a contract between the Metro Nashville Police Department and Fusus.\n\n JANUARY: Controversial \u2018Fusus\u2019 program up for discussion again by Metro Council \n\nIn all, four amendments were made to the legislation. One amendment said that any officer requesting access to a camera in the community safety camera network has to create a document with the time, date and each instance of access as well as an explanation of why the camera was accessed. Additionally, an independent firm would have to audit the records created by officers when they access the video.\n\nAn amendment also stipulates that the community camera safety network could not utilize artificial intelligence or machine learning \u201cor any other artificial mechanism to\ncapture conversations through automated lip reading.\u201d\n\nOther amendments restricted the MNPD\u2019s ability to access certain cameras, including one that prohibits the taking of \u201clive video from a donor camera\u201d if that camera is on exclusively residential property. Additionally, the MNPD would no longer be able to have access to donor cameras at multifamily residential properties that focus on any area other than a parking lot, parking garage or other outdoor common area.\n\n DECEMBER 2024 | \u2018Too many unanswered questions\u2019: Metro Council votes down Fusus surveillance contract \n\nFinally, Metro Council approved an amendment stating that video depicting any MNPD employee \u201cutilizing excessive or unlawful force\u201d must be immediately preserved and provided to the MNPD\u2019s office of professional accountability and the district attorney general.\n\nThe bill has to pass the third of three readings to take effect.\n\nCopyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.\n\n For the latest news, weather, sports, and streaming video, head to WKRN News 2. ]]>\n  \n  \n    Dr. Kedar Mate\u2019s Post\n    https://www.linkedin.com/posts/kedarmatemd_from-ihi-to-ai-why-i-made-the-leap-and-what-activity-7302784496586706944-53_H/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAALkv4BTofKmG92LxlnRhQHdizotUKgWrc\n    readwise:01jnmjdasbpea0smh797p69r3d\n    Thu, 06 Mar 2025 01:51:36 +0000\n    linkedin.com\n     Dr. Kedar Mate  \n\nFounder & CMO of Qualified Health-genAI for healthcare company | Faculty Weill Cornell Medicine | Former Prez/CEO at IHI | Co-Host \"Turn On The Lights\" Podcast | Continuous, never-ending learner!\n\nFrom IHI to AI: Why I Made the Leap and What I\u2019ve Learned So Far\n\nFor the past several years, I had the privilege of serving as CEO of the Institute for Healthcare Improvement (IHI), an organization dedicated to advancing quality, safety, and equity in healthcare. That mission has always been deeply personal to me\u2014ensuring that healthcare works better for patients, clinicians, and communities.\n\nSo why leave to co-found a generative AI company?\nBecause I believe AI is about to fundamentally reshape how healthcare is delivered\u2014and we have a rare opportunity to make sure it does so in a way that actually improves care, not just disrupt it.\n\nWhy I Made the Move\nAI could change healthcare in ways that we\u2019ve been trying to achieve for decades\u2014reducing administrative burden, expanding access, improving decision-making. But right now, much of AI in healthcare isn\u2019t built for the realities of clinical practice. It\u2019s too unreliable, too difficult to integrate, and too often adds rather than reduces work for already-overburdened clinicians.\n\nI co-founded Qualified Health because I believe we need AI that is:\n\u2705 Trustworthy \u2013 AI must be accurate, transparent, and capable of supporting, not replacing, clinicians.\n\u2705 Deeply integrated into clinical workflows \u2013 AI should work within EHRs and existing systems, not as a disconnected tool that adds friction.\n\u2705 Focused on real-world healthcare challenges \u2013 The goal isn\u2019t just AI for AI\u2019s sake; it\u2019s to actually improve patient care and clinician well-being.\n\nThe transition from leading a healthcare improvement organization to building an AI company might seem like a big leap, but for me it\u2019s the same mission: advancing healthcare to create real results for real people.\n\nWhat I\u2019ve Learned in the First 60 Days\n1. AI in Healthcare is Only Just Beginning to have a Material Impact\nThe excitement around AI is real\u2014and justified\u2014but the gap between potential and reality is still wide. Too many AI solutions remain toys, not tools\u2014fun to experiment with, but not yet indispensable. We have to close that gap.\n\n2. Healthcare is Rightfully Skeptical\u2014and That\u2019s a Good Thing\nUnlike other industries, healthcare can\u2019t afford to move fast and break things. Patient lives are at stake. Clinicians and health systems are rightfully cautious about adopting technologies that aren\u2019t rigorously tested and validated. Trust isn\u2019t given\u2014it\u2019s earned.\n\n3. The Biggest AI Wins Will Come from the Smallest, Smartest Applications\nI believe the most valuable AI solutions, where a LOT of the initial value will be created, will actually be in the fairly mundane. It will be the applications that quietly improve daily clinical work. Small, well-executed AI applications will have an outsized impact.\n\nHealthcare doesn\u2019t need more hype. It needs AI that actually helps and that\u2019s what we\u2019re building at Qualified Health.\n\nIf you\u2019re working in AI and healthcare, I\u2019d love to hear from you\u2014what do you see as the biggest opportunities and challenges in this space?]]>\n     Dr. Kedar Mate  \n\nFounder & CMO of Qualified Health-genAI for healthcare company | Faculty Weill Cornell Medicine | Former Prez/CEO at IHI | Co-Host \"Turn On The Lights\" Podcast | Continuous, never-ending learner!\n\nFrom IHI to AI: Why I Made the Leap and What I\u2019ve Learned So Far\n\nFor the past several years, I had the privilege of serving as CEO of the Institute for Healthcare Improvement (IHI), an organization dedicated to advancing quality, safety, and equity in healthcare. That mission has always been deeply personal to me\u2014ensuring that healthcare works better for patients, clinicians, and communities.\n\nSo why leave to co-found a generative AI company?\nBecause I believe AI is about to fundamentally reshape how healthcare is delivered\u2014and we have a rare opportunity to make sure it does so in a way that actually improves care, not just disrupt it.\n\nWhy I Made the Move\nAI could change healthcare in ways that we\u2019ve been trying to achieve for decades\u2014reducing administrative burden, expanding access, improving decision-making. But right now, much of AI in healthcare isn\u2019t built for the realities of clinical practice. It\u2019s too unreliable, too difficult to integrate, and too often adds rather than reduces work for already-overburdened clinicians.\n\nI co-founded Qualified Health because I believe we need AI that is:\n\u2705 Trustworthy \u2013 AI must be accurate, transparent, and capable of supporting, not replacing, clinicians.\n\u2705 Deeply integrated into clinical workflows \u2013 AI should work within EHRs and existing systems, not as a disconnected tool that adds friction.\n\u2705 Focused on real-world healthcare challenges \u2013 The goal isn\u2019t just AI for AI\u2019s sake; it\u2019s to actually improve patient care and clinician well-being.\n\nThe transition from leading a healthcare improvement organization to building an AI company might seem like a big leap, but for me it\u2019s the same mission: advancing healthcare to create real results for real people.\n\nWhat I\u2019ve Learned in the First 60 Days\n1. AI in Healthcare is Only Just Beginning to have a Material Impact\nThe excitement around AI is real\u2014and justified\u2014but the gap between potential and reality is still wide. Too many AI solutions remain toys, not tools\u2014fun to experiment with, but not yet indispensable. We have to close that gap.\n\n2. Healthcare is Rightfully Skeptical\u2014and That\u2019s a Good Thing\nUnlike other industries, healthcare can\u2019t afford to move fast and break things. Patient lives are at stake. Clinicians and health systems are rightfully cautious about adopting technologies that aren\u2019t rigorously tested and validated. Trust isn\u2019t given\u2014it\u2019s earned.\n\n3. The Biggest AI Wins Will Come from the Smallest, Smartest Applications\nI believe the most valuable AI solutions, where a LOT of the initial value will be created, will actually be in the fairly mundane. It will be the applications that quietly improve daily clinical work. Small, well-executed AI applications will have an outsized impact.\n\nHealthcare doesn\u2019t need more hype. It needs AI that actually helps and that\u2019s what we\u2019re building at Qualified Health.\n\nIf you\u2019re working in AI and healthcare, I\u2019d love to hear from you\u2014what do you see as the biggest opportunities and challenges in this space?]]>\n  \n  \n    The Coming Age of Territorial Expansion\n    https://www.foreignaffairs.com/canada/coming-age-territorial-expansion?s=EDZZZ005ZX&utm_medium=newsletters&utm_source=fatoday&utm_campaign=The%20Coming%20Age%20of%20Territorial%20Expansion&utm_content=20250304&utm_term=EDZZZ005ZX\n    readwise:01jngwacs4325h3pyfq8vc8dv4\n    Tue, 04 Mar 2025 15:27:48 +0000\n    Foreign Affairs\n    \nNear Nuuk, Greenland, February 2025 Sarah Meyssonnier / Reuters \n\n\n\n\n\n\n\n\nSince the mid-twentieth century, the power dynamics and system of alliances that made up the postwar global order provided a strong check on campaigns to conquer and acquire territory\u2014an otherwise enduring feature of human history. But rather than marking a definitive break from the aggression of the past, this era of relative restraint now seems to have been merely a brief deviation from the historical pattern. From Russia\u2019s invasion of Ukraine to U.S. President Donald Trump\u2019s avowed interest in acquiring Greenland, international land grabs are back on the table. Threats of territorial conquest are once again becoming a central part of geopolitics, driven by a new phase of great-power competition, growing population pressures, shifts in technology, and, perhaps most crucially, a changing climate.\n\nThe case of Greenland is emblematic of how climate change may spur a global contest for land. Trump first raised the prospect of the United States incorporating the Danish territory on the eve of his inauguration, and in the weeks since, he has reiterated that wish and refused to rule out the use of force to turn it into reality. Denmark is uninterested in selling Greenland, and the territory\u2019s largely indigenous population is wary of outside powers\u2014a legacy of the island\u2019s brutal history under Danish rule. But that has not discouraged Trump\u2019s overtures or threats. His interest in the territory stems ostensibly from its strategic position as a buffer between the United States and its great-power adversaries. \u201cIt has to do with the freedom of the world,\u201d Trump said in January. But as the planet warms, retreating icecaps and thinning sea ice will make Greenland important for other reasons, as its vast tracts of once inhospitable land become newly alluring to outsiders.\n\nWashington\u2019s bid for Greenland is just the opening chapter of a new global competition for territory. There are many qualities that make land valuable, such as access to resources, human habitability, agricultural productivity, and proximity to trade routes. For decades, countries have, for the most part, played with the hands they were dealt. But now, climate change is reshuffling the deck. As major powers try to position themselves for success in a warming world, many will rush to secure access to vital territory and resources\u2014ushering in an era in which blatant land grabs are a recurrent theme.\n\nWINNERS AND LOSERS\n\nWhat seems brazen and bizarre now may well become more common in the coming decades as policymakers grapple with the consequences of a warming planet. For a great power looking to set itself up for success in a future shaped by climate change, Greenland is a prize. The massive island will likely become an important waypoint for new northern shipping routes that open as Arctic ice melts. Although ice cover has so far limited the exploration of mineral deposits in Greenland, scientists believe it could possess significant quantities of iron ore, lead, gold, rare-earth elements, uranium, oil, and other valuable resources, including those minerals needed for the clean energy transition.\n\nAs the climate warms, people will be forced to flee places made inhabitable by rising seas, unbearable heat, and extreme weather\u2014and by that time, Greenland will be far more comfortable for human settlement than it is now. Bitterly cold winters will ease, and summers will warm substantially. Recent years have seen average temperatures that are Greenland\u2019s warmest on record for the past 1,000 years and are around 1.5 degrees Celsius above the twentieth-century average. Further temperature rises will foster new vegetation and even agriculture. Climate projections show that areas covered today by the low-to-the-ground vegetation of the tundra could host growing forests by 2100.\n\nClimate change will create intractable problems for some countries and open new opportunities for others, encouraging a race for territory. Global warming\u2013induced changes in productivity and habitability will carve new trajectories for economic output and migration. Emigration from North Africa, the Sahel, and the Middle East, for instance, will increase, as temperatures rise and agricultural productivity declines in those regions. People will also draw back from low-lying and flood-prone coastal areas, such as the Ganges Delta of Bangladesh and parts of coastal Florida.\n\n International land grabs are back on the table.\n\nNorthern climates and areas with higher elevation will attract most of these displaced populations, although areas in the far south will gather a small number, too. Research by Stanford University scientists has shown that economic productivity accelerates as temperatures rise in cooler climates and slows as hotter climates heat up. The reasons are easy to identify: temperate climates allow greater agricultural production, enhanced population health, and better conditions for work. Excessively hot climates produce more heat-related deaths, higher energy costs, water shortages, and lower crop yields.\n\nCountries with vast tracts of soon-to-be-desirable territory stand to benefit, if they play their cards right. Canada and Russia, the world\u2019s two largest northerly countries, are particularly well situated. Agriculture in both could expand dramatically as a result of longer growing seasons, warmer temperatures, and the melting of permafrost. One recent climate model has shown Canada gaining 1.6 million square miles of arable land suitable for crops such as wheat, corn, and potatoes by 2080\u2014a fourfold increase of the area currently available for cultivation. Russia will gain a comparable amount of newly arable land in the coming decades. Even though the soils on these lands will not all be highly productive, the sheer scale of the change positions these two countries to dominate global grain markets in the future.\n\nCanada and Russia will also soon find themselves sitting along major international shipping routes. Melting ice is opening maritime passageways in the Arctic, and shipping in the region, already on the rise, will only ramp up further as the world warms. Major economies are all eyeing two shipping routes that connect the Atlantic and Pacific Oceans: the Northwest Passage, which runs along the northern part of Canada, passing Greenland, and the Northern Sea Route, which traces the northern edges of Russia. Canada\u2019s and Russia\u2019s positions along these routes will foster economic activity in those countries and give them leverage over the flow of maritime traffic.\n\n Climate change will create problems for some countries and opportunities for others.\n\nTo be sure, Canada and Russia can still expect to suffer from climate change\u2013induced natural disasters. These and other expensive risks, such as the damage that thawing permafrost can inflict on infrastructure, will be a drag on their economies. But the coming of more temperate climates will also drive population growth and boost overall economic activity. In Canada, at least, ideas about how to take advantage of those trends are already circulating. Influential and well-connected Canadian business and political leaders have formed a group called the Century Initiative, which advocates for increasing the country\u2019s population from around 40 million today to 100 million by 2100, largely by supercharging immigration and establishing regional development hubs. One of the founders of the initiative served as an economic adviser to Prime Minister Justin Trudeau, and its platform has gained support from prominent Conservative and Liberal Party members and advisers.\n\nRussia\u2019s outlook is more mixed. The warming of large swaths of its vast tundra and boreal forests certainly holds significant economic potential. But Russia\u2019s reliance on hydrocarbon production makes its economy vulnerable as the world shifts toward renewable energy\u2014especially if agriculture, shipping, and other newly viable forms of economic activity cannot fill the void left by declining fossil fuel exports. And whereas Canada offsets its low birthrates with relatively open migration policies, Russia is far less welcoming to immigrants. Unless that changes, Russia\u2019s population could decline 25 percent by 2100.\n\nOther northerly territories will likely undergo similar changes to those in Canada and Russia: Finland, Norway, Sweden, and the U.S. state of Alaska will all have a growing base of arable land in the coming decades. The continental United States and China, by contrast, will face declining crop yields, increasing migration out of their hottest and most disaster-prone areas, and decreasing productivity. Both could see their power and influence wane unless they can balance these disadvantages with investments in cheap renewable energy and plans to eventually relocate vulnerable populations to more livable places.\n\nSCRAMBLE FOR LAND\n\nFaced with stark climate-related economic and demographic challenges, countries will try to lock in any advantage they can. Wrangling over Greenland is just the beginning. There are dozens of territories around the world that fit a similar profile to Greenland\u2019s: sparsely populated, likely to become more habitable in the coming decades or home to valuable resources, and possessing weak, ambiguous, or transitional sovereignty. As a self-governing territory of Denmark, Greenland\u2019s foreign affairs are managed from Copenhagen, but its leaders have expressed a desire for full independence and drafted a prospective constitution. Even though most Greenlanders initially reacted with disdain to Trump\u2019s offer to join the United States, it is not out of the realm of possibility that the territory could gain independence and entertain such a proposal in the future. Other nonsovereign territories, such as the Faroe Islands, the Falkland Islands, French Guiana, or New Caledonia, could also enter into the sights of great powers or opportunistic neighbors. All these areas have been contested before and could be contested again.\n\nAntarctica is another flash point. During the Cold War, major powers signed the Antarctic Treaty, setting aside territorial claims on the continent and committing instead to use it as a site of international scientific exploration and cooperation. That arrangement is now starting to unwind. China and Russia recently incorporated interests in Antarctica into their national security strategies, and China has invested in an icebreaker fleet and the construction of satellite ground stations on the continent that could be repurposed for military applications. Both countries have expanded their krill fishing in the waters surrounding Antarctica, and they have rejected the renewal of existing marine protections and proposals for additional ones by the 26-country Commission for the Conservation of Antarctic Marine Living Resources. Argentina and Chile have responded by reasserting their own long-standing territorial claims on the continent. As climate change makes it possible to extract valuable resources, extend control over expanding shipping routes, and build monitoring stations and research bases that could be militarized, Antarctic cooperation could fall apart entirely.\n\n Wrangling over Greenland is just the beginning.\n\nCountries that possess resources vital to the transition to renewable energy will also become sites of competition. The demand for rare-earth minerals such as cobalt, coltan, lithium, and tantalum is driving efforts to source and secure these resources wherever they can be found. In some cases, territorial sovereignty is compromised in the process, from the creeping influence of multinational companies engaged in large-scale land acquisition to more blatant violations in the form of foreign military incursions. The recent invasion of the mineral-rich Democratic Republic of the Congo by the Rwandan-backed M23 rebel group can be explained as a way for the group, and by extension, Rwanda, to gain access to valuable minerals in eastern Congo that are used to produce batteries for electric vehicles and cellphones.\n\nThe competition to secure access to food will intensify, too, as climate change affects crop yields and growing patterns around the world. Some countries will need to find new sources of agricultural goods, and the countries that can continue to produce and export food in a warming world will gain influence. Russia\u2019s invasion of eastern Ukraine can be seen in part as a play for political leverage through agricultural advantage. For decades, the Soviet Union and Russia imported grain, but in the last two decades, Moscow has made a concerted and successful effort to boost domestic agricultural production. Now, not only is Russia no longer dependent on imports, but it also has become the world\u2019s largest wheat exporter. By seizing prime agricultural land in Ukraine, Russia has further consolidated its domination of global grain markets. That position gives it immense power: if Moscow bars exports to a country that relies on imported grain, it can destabilize that country\u2019s politics and drive hunger and even emigration.\n\nTHE FIGHTS TO COME\n\nClimate change will shape relations among states in complex ways in the coming decades, but the broad contours of these shifts are already visible. Even now, trade and commodity markets are transforming as powerful states grab key resources and new shipping routes open. Populations have already begun to move both within and across countries as climate change renders some parts of the earth less habitable and others more so. As these trends accelerate, they will fuel efforts by major powers to acquire new territories.\n\nAlthough it is impossible to predict with certainty where and when countries will be prepared to go to war for land, environmental trends today suggest many possibilities for aggression down the road. A China facing grave threats from climate change\u2014from rising seas and extreme weather in coastal areas to flooding along major rivers and desertification in the country\u2019s north\u2014could try to secure resources, habitable land, and geostrategic advantage by making incursions into Southeast Asia, claiming island outposts, or even grabbing pieces of eastern Russia or North Korea. Nigeria, on track to become more populous than China by the end of the century, could turn central Africa into a tinderbox. As climate change brings droughts, floods, and heat waves, disrupting agriculture and displacing communities, Nigeria may find it needs more resources to sustain its fast-growing population\u2014and set its sights on neighboring countries to get them. Russia, meanwhile, could expand its footprint in the Baltics and countries such as Norway in order to secure northern shipping routes and expand its sea access. It could do the same in Antarctica, setting the stage for conflict with other great powers active there. And the United States, facing climate devastation in places such as coastal Florida, wildfire-prone California, and the drought-stricken Southwest could act on its territorial ambitions in northern territories including Greenland or even parts of Canada.\n\nInternational agreements and alliances, already fraying as great-power competition heats up, will struggle to contain these fights. In a world where might makes right, countries that find themselves seeking new territory may not hesitate to use force to get it. With the most dramatic effects of climate change still to come, the race for land is just getting started.]]>\n    \nNear Nuuk, Greenland, February 2025 Sarah Meyssonnier / Reuters \n\n\n\n\n\n\n\n\nSince the mid-twentieth century, the power dynamics and system of alliances that made up the postwar global order provided a strong check on campaigns to conquer and acquire territory\u2014an otherwise enduring feature of human history. But rather than marking a definitive break from the aggression of the past, this era of relative restraint now seems to have been merely a brief deviation from the historical pattern. From Russia\u2019s invasion of Ukraine to U.S. President Donald Trump\u2019s avowed interest in acquiring Greenland, international land grabs are back on the table. Threats of territorial conquest are once again becoming a central part of geopolitics, driven by a new phase of great-power competition, growing population pressures, shifts in technology, and, perhaps most crucially, a changing climate.\n\nThe case of Greenland is emblematic of how climate change may spur a global contest for land. Trump first raised the prospect of the United States incorporating the Danish territory on the eve of his inauguration, and in the weeks since, he has reiterated that wish and refused to rule out the use of force to turn it into reality. Denmark is uninterested in selling Greenland, and the territory\u2019s largely indigenous population is wary of outside powers\u2014a legacy of the island\u2019s brutal history under Danish rule. But that has not discouraged Trump\u2019s overtures or threats. His interest in the territory stems ostensibly from its strategic position as a buffer between the United States and its great-power adversaries. \u201cIt has to do with the freedom of the world,\u201d Trump said in January. But as the planet warms, retreating icecaps and thinning sea ice will make Greenland important for other reasons, as its vast tracts of once inhospitable land become newly alluring to outsiders.\n\nWashington\u2019s bid for Greenland is just the opening chapter of a new global competition for territory. There are many qualities that make land valuable, such as access to resources, human habitability, agricultural productivity, and proximity to trade routes. For decades, countries have, for the most part, played with the hands they were dealt. But now, climate change is reshuffling the deck. As major powers try to position themselves for success in a warming world, many will rush to secure access to vital territory and resources\u2014ushering in an era in which blatant land grabs are a recurrent theme.\n\nWINNERS AND LOSERS\n\nWhat seems brazen and bizarre now may well become more common in the coming decades as policymakers grapple with the consequences of a warming planet. For a great power looking to set itself up for success in a future shaped by climate change, Greenland is a prize. The massive island will likely become an important waypoint for new northern shipping routes that open as Arctic ice melts. Although ice cover has so far limited the exploration of mineral deposits in Greenland, scientists believe it could possess significant quantities of iron ore, lead, gold, rare-earth elements, uranium, oil, and other valuable resources, including those minerals needed for the clean energy transition.\n\nAs the climate warms, people will be forced to flee places made inhabitable by rising seas, unbearable heat, and extreme weather\u2014and by that time, Greenland will be far more comfortable for human settlement than it is now. Bitterly cold winters will ease, and summers will warm substantially. Recent years have seen average temperatures that are Greenland\u2019s warmest on record for the past 1,000 years and are around 1.5 degrees Celsius above the twentieth-century average. Further temperature rises will foster new vegetation and even agriculture. Climate projections show that areas covered today by the low-to-the-ground vegetation of the tundra could host growing forests by 2100.\n\nClimate change will create intractable problems for some countries and open new opportunities for others, encouraging a race for territory. Global warming\u2013induced changes in productivity and habitability will carve new trajectories for economic output and migration. Emigration from North Africa, the Sahel, and the Middle East, for instance, will increase, as temperatures rise and agricultural productivity declines in those regions. People will also draw back from low-lying and flood-prone coastal areas, such as the Ganges Delta of Bangladesh and parts of coastal Florida.\n\n International land grabs are back on the table.\n\nNorthern climates and areas with higher elevation will attract most of these displaced populations, although areas in the far south will gather a small number, too. Research by Stanford University scientists has shown that economic productivity accelerates as temperatures rise in cooler climates and slows as hotter climates heat up. The reasons are easy to identify: temperate climates allow greater agricultural production, enhanced population health, and better conditions for work. Excessively hot climates produce more heat-related deaths, higher energy costs, water shortages, and lower crop yields.\n\nCountries with vast tracts of soon-to-be-desirable territory stand to benefit, if they play their cards right. Canada and Russia, the world\u2019s two largest northerly countries, are particularly well situated. Agriculture in both could expand dramatically as a result of longer growing seasons, warmer temperatures, and the melting of permafrost. One recent climate model has shown Canada gaining 1.6 million square miles of arable land suitable for crops such as wheat, corn, and potatoes by 2080\u2014a fourfold increase of the area currently available for cultivation. Russia will gain a comparable amount of newly arable land in the coming decades. Even though the soils on these lands will not all be highly productive, the sheer scale of the change positions these two countries to dominate global grain markets in the future.\n\nCanada and Russia will also soon find themselves sitting along major international shipping routes. Melting ice is opening maritime passageways in the Arctic, and shipping in the region, already on the rise, will only ramp up further as the world warms. Major economies are all eyeing two shipping routes that connect the Atlantic and Pacific Oceans: the Northwest Passage, which runs along the northern part of Canada, passing Greenland, and the Northern Sea Route, which traces the northern edges of Russia. Canada\u2019s and Russia\u2019s positions along these routes will foster economic activity in those countries and give them leverage over the flow of maritime traffic.\n\n Climate change will create problems for some countries and opportunities for others.\n\nTo be sure, Canada and Russia can still expect to suffer from climate change\u2013induced natural disasters. These and other expensive risks, such as the damage that thawing permafrost can inflict on infrastructure, will be a drag on their economies. But the coming of more temperate climates will also drive population growth and boost overall economic activity. In Canada, at least, ideas about how to take advantage of those trends are already circulating. Influential and well-connected Canadian business and political leaders have formed a group called the Century Initiative, which advocates for increasing the country\u2019s population from around 40 million today to 100 million by 2100, largely by supercharging immigration and establishing regional development hubs. One of the founders of the initiative served as an economic adviser to Prime Minister Justin Trudeau, and its platform has gained support from prominent Conservative and Liberal Party members and advisers.\n\nRussia\u2019s outlook is more mixed. The warming of large swaths of its vast tundra and boreal forests certainly holds significant economic potential. But Russia\u2019s reliance on hydrocarbon production makes its economy vulnerable as the world shifts toward renewable energy\u2014especially if agriculture, shipping, and other newly viable forms of economic activity cannot fill the void left by declining fossil fuel exports. And whereas Canada offsets its low birthrates with relatively open migration policies, Russia is far less welcoming to immigrants. Unless that changes, Russia\u2019s population could decline 25 percent by 2100.\n\nOther northerly territories will likely undergo similar changes to those in Canada and Russia: Finland, Norway, Sweden, and the U.S. state of Alaska will all have a growing base of arable land in the coming decades. The continental United States and China, by contrast, will face declining crop yields, increasing migration out of their hottest and most disaster-prone areas, and decreasing productivity. Both could see their power and influence wane unless they can balance these disadvantages with investments in cheap renewable energy and plans to eventually relocate vulnerable populations to more livable places.\n\nSCRAMBLE FOR LAND\n\nFaced with stark climate-related economic and demographic challenges, countries will try to lock in any advantage they can. Wrangling over Greenland is just the beginning. There are dozens of territories around the world that fit a similar profile to Greenland\u2019s: sparsely populated, likely to become more habitable in the coming decades or home to valuable resources, and possessing weak, ambiguous, or transitional sovereignty. As a self-governing territory of Denmark, Greenland\u2019s foreign affairs are managed from Copenhagen, but its leaders have expressed a desire for full independence and drafted a prospective constitution. Even though most Greenlanders initially reacted with disdain to Trump\u2019s offer to join the United States, it is not out of the realm of possibility that the territory could gain independence and entertain such a proposal in the future. Other nonsovereign territories, such as the Faroe Islands, the Falkland Islands, French Guiana, or New Caledonia, could also enter into the sights of great powers or opportunistic neighbors. All these areas have been contested before and could be contested again.\n\nAntarctica is another flash point. During the Cold War, major powers signed the Antarctic Treaty, setting aside territorial claims on the continent and committing instead to use it as a site of international scientific exploration and cooperation. That arrangement is now starting to unwind. China and Russia recently incorporated interests in Antarctica into their national security strategies, and China has invested in an icebreaker fleet and the construction of satellite ground stations on the continent that could be repurposed for military applications. Both countries have expanded their krill fishing in the waters surrounding Antarctica, and they have rejected the renewal of existing marine protections and proposals for additional ones by the 26-country Commission for the Conservation of Antarctic Marine Living Resources. Argentina and Chile have responded by reasserting their own long-standing territorial claims on the continent. As climate change makes it possible to extract valuable resources, extend control over expanding shipping routes, and build monitoring stations and research bases that could be militarized, Antarctic cooperation could fall apart entirely.\n\n Wrangling over Greenland is just the beginning.\n\nCountries that possess resources vital to the transition to renewable energy will also become sites of competition. The demand for rare-earth minerals such as cobalt, coltan, lithium, and tantalum is driving efforts to source and secure these resources wherever they can be found. In some cases, territorial sovereignty is compromised in the process, from the creeping influence of multinational companies engaged in large-scale land acquisition to more blatant violations in the form of foreign military incursions. The recent invasion of the mineral-rich Democratic Republic of the Congo by the Rwandan-backed M23 rebel group can be explained as a way for the group, and by extension, Rwanda, to gain access to valuable minerals in eastern Congo that are used to produce batteries for electric vehicles and cellphones.\n\nThe competition to secure access to food will intensify, too, as climate change affects crop yields and growing patterns around the world. Some countries will need to find new sources of agricultural goods, and the countries that can continue to produce and export food in a warming world will gain influence. Russia\u2019s invasion of eastern Ukraine can be seen in part as a play for political leverage through agricultural advantage. For decades, the Soviet Union and Russia imported grain, but in the last two decades, Moscow has made a concerted and successful effort to boost domestic agricultural production. Now, not only is Russia no longer dependent on imports, but it also has become the world\u2019s largest wheat exporter. By seizing prime agricultural land in Ukraine, Russia has further consolidated its domination of global grain markets. That position gives it immense power: if Moscow bars exports to a country that relies on imported grain, it can destabilize that country\u2019s politics and drive hunger and even emigration.\n\nTHE FIGHTS TO COME\n\nClimate change will shape relations among states in complex ways in the coming decades, but the broad contours of these shifts are already visible. Even now, trade and commodity markets are transforming as powerful states grab key resources and new shipping routes open. Populations have already begun to move both within and across countries as climate change renders some parts of the earth less habitable and others more so. As these trends accelerate, they will fuel efforts by major powers to acquire new territories.\n\nAlthough it is impossible to predict with certainty where and when countries will be prepared to go to war for land, environmental trends today suggest many possibilities for aggression down the road. A China facing grave threats from climate change\u2014from rising seas and extreme weather in coastal areas to flooding along major rivers and desertification in the country\u2019s north\u2014could try to secure resources, habitable land, and geostrategic advantage by making incursions into Southeast Asia, claiming island outposts, or even grabbing pieces of eastern Russia or North Korea. Nigeria, on track to become more populous than China by the end of the century, could turn central Africa into a tinderbox. As climate change brings droughts, floods, and heat waves, disrupting agriculture and displacing communities, Nigeria may find it needs more resources to sustain its fast-growing population\u2014and set its sights on neighboring countries to get them. Russia, meanwhile, could expand its footprint in the Baltics and countries such as Norway in order to secure northern shipping routes and expand its sea access. It could do the same in Antarctica, setting the stage for conflict with other great powers active there. And the United States, facing climate devastation in places such as coastal Florida, wildfire-prone California, and the drought-stricken Southwest could act on its territorial ambitions in northern territories including Greenland or even parts of Canada.\n\nInternational agreements and alliances, already fraying as great-power competition heats up, will struggle to contain these fights. In a world where might makes right, countries that find themselves seeking new territory may not hesitate to use force to get it. With the most dramatic effects of climate change still to come, the race for land is just getting started.]]>\n  \n  \n    Basic content is dying (and that's good news)\n    https://www.justinwelsh.me/newsletter/basic-content-is-dying?utm_source=convertkit&utm_medium=email&utm_campaign=Basic%20content%20is%20dying%20(and%20that%27s%20good%20news)%20-%2016700690\n    readwise:01jngq0s7zw0hh3ksx1b1x9pz0\n    Tue, 04 Mar 2025 13:55:10 +0000\n    justinwelsh.me\n    \n\n\u200dStart With The Solopreneur Tech Stack I Did \u2014 Outseta\n\nI launched my first six-figure community back in 2021. When it came to managing payments, CRM, and email, I did it with one powerful tool \u2014 Outseta.\n\nTry Outseta free!\n\n\nFree 2024 Tax Filing for First 100 Besolo LLC Members\n\nFirst solopreneur business-in-a-box. LLC formation, taxes, admin & benefits. New Besolo LLC members get free personal tax filing for 2024.\n\nGet Started Now!\n\nSponsor my newsletter to reach 175,000+ active readers\n\nI had a fascinating conversation with one of my Creator MBA students recently. It made me rethink everything I know about content marketing.\n\nWe were talking about his social media strategy and went down a rabbit hole around content creation. Ultimately, we agreed the traditional content funnel is dying, and most creators haven't noticed yet.\n\nRemember when you could post some basic tips, a quick how-to, or \"5 ways to do XYZ\" and attract a bunch of new followers?\n\n\u200dThat worked because it was hard to create consistent, thought-provoking content at scale.\n\nBut not anymore.\n\nNow AI generates an endless stream of surface-level content in seconds! Beginner social accounts are able to produce 10x the amount of content I did just a few years ago, with a fraction of the effort.\n\nJust scroll through any platform, and you'll find tons of accounts sharing identical \"wisdom\" \u2014 all generated (or inspired) by AI. Content has always been regurgitated. Of course that\u2019s nothing new. It\u2019s the scale at which this is happening that caught my attention.\n\nAt a break neck pace, basic content has become worthless. Because when everyone sounds the same, nobody stands out.\n\nWhy The Traditional Funnel Is Broken\n\nThe traditional content funnel worked like this:\n\n\nTop: Tips, trends, observations, and opinions to attract attention\nMiddle: Deeper insights to build trust\nBottom: Specific solutions to drive sales\n\nBut there\u2019s a change happening now: AI has commoditized the top layer of flag-waving, attention-getting content. Anyone can create \"good enough\" basic content.\n\nOne of my friends runs a 7-figure course business. And last month, his top-of-funnel engagement dropped 30%. Why? Because 50+ other creators in his niche started posting similar content \u2014 mostly AI-generated, all saying similar things.\n\nThe moat around basic content creation has dried up.\n\nThe New Reality\n\nThe old funnel is transforming into something much more narrow \u2014 more of a cylinder than a funnel.\n\nInstead of starting wide with basic content and narrowing down, you need to lead with your deepest expertise right from the start. Your \"top of funnel\" content should be as valuable as your former middle-of-funnel material.\n\nThink about it: When was the last time a surface-level \"5 tips\" post actually convinced you to follow someone new? We're all drowning in basic advice.\n\nAnd what catches attention now is genuine expertise and unique insights.\n\nI've been testing this idea recently, and here's what seems to be working:\n\nShare deeper insights \u2014 the ones you'd normally save for your paid products, minus the detailed implementation steps. Tell stories about real problems you've solved \u2014 not theoretical advice anyone could give. And focus on counterintuitive lessons you've learned \u2014 the stuff that goes against \"common wisdom\" that Claude or ChatGPT pumps out to the masses.\n\nOne of my students tried this: Instead of posting basic marketing tips, she shared detailed breakdowns of campaigns she'd run, including what failed. Her engagement was 15% higher than her previous top-of-funnel efforts.\n\nThe Bottom Line\n\nAI has killed the age of easy content marketing.\n\nAnd this is good news for people with real expertise.\n\nBecause now, the only way to stand out is to be deeply helpful. To share real-life expertise. To talk about what you actually know, not what you think you should say.\n\nWill this approach attract fewer people? Probably. After all, content consumers love philosophizing and boisterous sound bites.\n\nBut the people you do attract will be much more likely to stick around and eventually become your customers.\n\nIt\u2019s time to stop casting a wide net with basic content. Start leading with your expertise earlier. Because in a world of AI-generated content, depth isn't just an advantage \u2014 it's a requirement.\n\nIf you want to build a thoughtful, authentic, unique brand on social media, check my course, The LinkedIn Operating System. It's the system used by 30,000+ students, 70 LinkedIn Top Voices and 20% of the Top 100 LinkedIn Influencers (as rated by Favikon).\n\nAnd that's all for this today.\n\nSee you next Saturday.\n\nWhenever you're ready, there are 4 ways I can help you:\n\n1. \u200bPromote your business to 175K+ highly engaged entrepreneurs: Showcase your brand or business where hundreds of thousands of your ideal customers are actively spending their time.\n\n2. The Creator MBA: Join 5,000+ entrepreneurs in my flagship course. The Creator MBA teaches you frameworks for turning your knowledge and expertise into a quality product that people will buy. Come learn to build a lean, focused, and profitable Internet business.\n\n3. \u200bThe LinkedIn Operating System:\u200b Join 30,000 students and 70 LinkedIn Top Voices inside of The LinkedIn Operating System. This comprehensive course will teach you the systems I used to grow to 700K+ followers and be named The #1 Global LinkedIn Influencer 5x in a row.\n\n4. \u200bThe Content Operating System\u200b: Join 12,000 students in my multi-step content creation system. Learn to create a high-quality newsletter and 6-12 pieces of high-performance social media content each week.]]>\n    \n\n\u200dStart With The Solopreneur Tech Stack I Did \u2014 Outseta\n\nI launched my first six-figure community back in 2021. When it came to managing payments, CRM, and email, I did it with one powerful tool \u2014 Outseta.\n\nTry Outseta free!\n\n\nFree 2024 Tax Filing for First 100 Besolo LLC Members\n\nFirst solopreneur business-in-a-box. LLC formation, taxes, admin & benefits. New Besolo LLC members get free personal tax filing for 2024.\n\nGet Started Now!\n\nSponsor my newsletter to reach 175,000+ active readers\n\nI had a fascinating conversation with one of my Creator MBA students recently. It made me rethink everything I know about content marketing.\n\nWe were talking about his social media strategy and went down a rabbit hole around content creation. Ultimately, we agreed the traditional content funnel is dying, and most creators haven't noticed yet.\n\nRemember when you could post some basic tips, a quick how-to, or \"5 ways to do XYZ\" and attract a bunch of new followers?\n\n\u200dThat worked because it was hard to create consistent, thought-provoking content at scale.\n\nBut not anymore.\n\nNow AI generates an endless stream of surface-level content in seconds! Beginner social accounts are able to produce 10x the amount of content I did just a few years ago, with a fraction of the effort.\n\nJust scroll through any platform, and you'll find tons of accounts sharing identical \"wisdom\" \u2014 all generated (or inspired) by AI. Content has always been regurgitated. Of course that\u2019s nothing new. It\u2019s the scale at which this is happening that caught my attention.\n\nAt a break neck pace, basic content has become worthless. Because when everyone sounds the same, nobody stands out.\n\nWhy The Traditional Funnel Is Broken\n\nThe traditional content funnel worked like this:\n\n\nTop: Tips, trends, observations, and opinions to attract attention\nMiddle: Deeper insights to build trust\nBottom: Specific solutions to drive sales\n\nBut there\u2019s a change happening now: AI has commoditized the top layer of flag-waving, attention-getting content. Anyone can create \"good enough\" basic content.\n\nOne of my friends runs a 7-figure course business. And last month, his top-of-funnel engagement dropped 30%. Why? Because 50+ other creators in his niche started posting similar content \u2014 mostly AI-generated, all saying similar things.\n\nThe moat around basic content creation has dried up.\n\nThe New Reality\n\nThe old funnel is transforming into something much more narrow \u2014 more of a cylinder than a funnel.\n\nInstead of starting wide with basic content and narrowing down, you need to lead with your deepest expertise right from the start. Your \"top of funnel\" content should be as valuable as your former middle-of-funnel material.\n\nThink about it: When was the last time a surface-level \"5 tips\" post actually convinced you to follow someone new? We're all drowning in basic advice.\n\nAnd what catches attention now is genuine expertise and unique insights.\n\nI've been testing this idea recently, and here's what seems to be working:\n\nShare deeper insights \u2014 the ones you'd normally save for your paid products, minus the detailed implementation steps. Tell stories about real problems you've solved \u2014 not theoretical advice anyone could give. And focus on counterintuitive lessons you've learned \u2014 the stuff that goes against \"common wisdom\" that Claude or ChatGPT pumps out to the masses.\n\nOne of my students tried this: Instead of posting basic marketing tips, she shared detailed breakdowns of campaigns she'd run, including what failed. Her engagement was 15% higher than her previous top-of-funnel efforts.\n\nThe Bottom Line\n\nAI has killed the age of easy content marketing.\n\nAnd this is good news for people with real expertise.\n\nBecause now, the only way to stand out is to be deeply helpful. To share real-life expertise. To talk about what you actually know, not what you think you should say.\n\nWill this approach attract fewer people? Probably. After all, content consumers love philosophizing and boisterous sound bites.\n\nBut the people you do attract will be much more likely to stick around and eventually become your customers.\n\nIt\u2019s time to stop casting a wide net with basic content. Start leading with your expertise earlier. Because in a world of AI-generated content, depth isn't just an advantage \u2014 it's a requirement.\n\nIf you want to build a thoughtful, authentic, unique brand on social media, check my course, The LinkedIn Operating System. It's the system used by 30,000+ students, 70 LinkedIn Top Voices and 20% of the Top 100 LinkedIn Influencers (as rated by Favikon).\n\nAnd that's all for this today.\n\nSee you next Saturday.\n\nWhenever you're ready, there are 4 ways I can help you:\n\n1. \u200bPromote your business to 175K+ highly engaged entrepreneurs: Showcase your brand or business where hundreds of thousands of your ideal customers are actively spending their time.\n\n2. The Creator MBA: Join 5,000+ entrepreneurs in my flagship course. The Creator MBA teaches you frameworks for turning your knowledge and expertise into a quality product that people will buy. Come learn to build a lean, focused, and profitable Internet business.\n\n3. \u200bThe LinkedIn Operating System:\u200b Join 30,000 students and 70 LinkedIn Top Voices inside of The LinkedIn Operating System. This comprehensive course will teach you the systems I used to grow to 700K+ followers and be named The #1 Global LinkedIn Influencer 5x in a row.\n\n4. \u200bThe Content Operating System\u200b: Join 12,000 students in my multi-step content creation system. Learn to create a high-quality newsletter and 6-12 pieces of high-performance social media content each week.]]>\n  \n  \n    What Is Unitary Executive Theory? How is Trump Using It to Push His Agenda?\n    https://www.democracydocket.com/analysis/what-is-unitary-executive-theory-how-is-trump-using-it-to-push-his-agenda/?utm_source=Democracy+Docket+Newsletters&utm_campaign=cf0b9bc27d-20250303_DailyDocket_LF&utm_medium=email&utm_term=0_-2029d74fb4-607310751&mc_cid=cf0b9bc27d\n    readwise:01jngpqctswna0mhh3sh8esv3s\n    Tue, 04 Mar 2025 13:50:03 +0000\n    Democracy Docket\n    \n\nSince taking office, President Donald Trump has executed a whirlwind of dismissals across the federal government that violated federal statutes and decreed numerous executive orders, including one that blatantly defied the plain language of the Constitution.\n\nBehind the seemingly scatter-shot opening acts of his second administration, legal analysts see a common goal: to test a once-fringe legal theory which asserts that the president has unlimited power to control the actions of the four million people who make up the executive branch.\n\nIf courts \u2014 specifically the Republican-appointed majority of the Supreme Court \u2014 uphold arguments based on the so-called \u201cunitary executive theory,\u201d it would give Trump and subsequent presidents unprecedented power to remove and replace any federal employee and impose their will on every decision in every agency.\n\nRulings in favor of the Trump administration would also further jeopardize the independence of key regulatory agencies that are susceptible to conflicts of interest and political interference, like the Federal Election Commission, which oversees federal elections and campaign finance laws.\n\nHow Trump is advancing the theory\n\nTrump and his administration have furthered the theory by repeatedly invoking Article II of the Constitution, which vests executive power in the president, to justify the recent dismissals of federal officials. They have framed the article as allowing the president to use the whole of the executive branch for his political ends.\n\nFor example, the White House Feb. 18 invoked the article to rationalize an executive order signed that same day that asserted the president\u2019s authority over almost all regulatory agencies that were created by Congress to act independently, or semi-independently, from the president.\n\nFrank Bowman, a scholar of constitutional and criminal law at the University of Missouri School of Law, told Democracy Docket he believes the executive order is a step toward \u201can open declaration of dictatorship.\u201d\n\n\u201cIn essence, what he\u2019s saying is, \u2018I am the law. My will is the law. My view of what the law is the only view that can ever be expressed,\u2019\u201d Bowman said.\n\nOrigins of the unitary executive theory\n\nThe theory has its roots in the aggressive assertions of presidential power in the 20th century, especially throughout the Nixon administration, but it emerged as an unorthodox legal framework during the Reagan administration and gathered strength with subsequent presidencies.\n\nThe framework gained significant traction during George W. Bush\u2019s presidency, as it was key to his administration\u2019s attempt to legitimize unprecedented presidential powers, including those over the use of military force, state-sponsored kidnapping, the detention and interrogation of prisoners and intelligence gathering.\n\nThere isn\u2019t one set interpretation of the theory. At minimum, its proponents generally believe Article II allows the president to remove all executive branch officers. However, there are adherents, including Trump and many of his allies, who believe the president retains all the executive power and can control all officers and agencies.\n\nBowman said he believes the theory falls apart \u201cunder even rudimentary examination,\u201d noting that it conflicts with the basic checks to executive power that are intrinsic to the Constitution.\n\nFor example, the Appointments Clause of the Constitution only allows Congress to create federal offices and define their functions and jurisdiction and specifies that lawmakers can determine how officers are appointed to their offices.\n\nHow Trump is going beyond the theory\n\nNew York University School of Law professor Noah Rosenblum told Democracy Docket that Trump\u2019s idea of executive power is in many ways an expansive version of the traditional understanding of the unitary executive theory.\n\n\u201cUntil recently, I think most of us would have said unitary executive theory was obviously a hugely sweeping claim of presidential power that how could you possibly ask for more,\u201d Rosenblum said, \u201cbut Donald Trump is making different claims.\u201d\n\nHe noted that the White House, in addition to invoking Article II, attempted to justify Trump\u2019s Feb. 18 executive order against independent agencies by referring to him as \u201cthe democratically elected President.\u201d\n\n\u201cThat is an appeal to democratic legitimacy, not the Constitution,\u201d Rosenblum said. \u201cHe\u2019s saying, \u2018I was chosen by you to be the leader, so I\u2019m in charge. I can do whatever I want.\u2019\u201d\n\nNot satisfied with having supreme control over the executive branch, Trump is attempting to usurp Congress\u2019 power of the purse by impounding federal funds and encroaching on its ability to create federal offices by forming the Department of Government Efficiency to dissolve agencies created by the legislative branch.\n\nThe administration is also openly threatening to ignore the court\u2019s power to review the actions of the government to ensure they are lawful, as seen by Vice President JD Vance stating earlier in February that \u201cJudges aren\u2019t allowed to control the executive branch\u2019s legitimate power.\u201d\n\nMost incendiary, Trump on Feb. 15 put the rule of law \u2014 the foundation of our constitutional order \u2014 under the guillotine with a Napoleonic assertion that \u201cHe who saves his Country does not violate any Law.\u201d\n\nSupreme Court\u2019s receptiveness to the theory \n\nBowman said that before the Republican-majority on the Supreme Court granted the president absolute immunity from criminal prosecution for official functions in Trump v. U.S. last year, he would have said SCOTUS wouldn\u2019t be receptive to most of Trump\u2019s arguments. Now, he thinks they may be.\n\nRosenblum and his colleagues have argued the unitary executive theory has been guiding the Roberts Court over the past two decades, and he told Democracy Docket that he does not expect the court to significantly deviate from the theory in response to Trump\u2019s challenges.\n\nIn past decisions, like Humphrey\u2019s Executor v. U.S., SCOTUS has prevented presidents from dismissing specific types of federal officials, such as those on multi-member independent administrative bodies, for causes that were not specified in law by Congress.\n\nIn more recent opinions, justices have maintained precedent set by previous rulings while at the same time expanding the president\u2019s authority to remove other types of federal officials and giving him increased control over the executive branch.\n\nTrump\u2019s Department of Justice has relied on those recent opinions and Trump v. U.S. in its petition for SCOTUS to weigh in on the recent dismissal of the head of the nation\u2019s top independent federal investigative and prosecutorial agency.\n\nThe petition may mark the first Supreme Court test of Trump\u2019s second-term agenda and his goal to expand presidential powers.\n\nWhat Happens If Trump Defies Court Orders?\n\n Next Up \n\nWhen Eric Olsen decided to host an open house at the Prince William County election office, he knew he wasn\u2019t going to change everyone\u2019s mind. Olsen \u2014 who\u2019s been the registrar for the northern Virginia county since 2021 \u2014 has worked in election administration in D.C., Maryland and Virginia for nearly 15 years, and has [\u2026]]]>\n    \n\nSince taking office, President Donald Trump has executed a whirlwind of dismissals across the federal government that violated federal statutes and decreed numerous executive orders, including one that blatantly defied the plain language of the Constitution.\n\nBehind the seemingly scatter-shot opening acts of his second administration, legal analysts see a common goal: to test a once-fringe legal theory which asserts that the president has unlimited power to control the actions of the four million people who make up the executive branch.\n\nIf courts \u2014 specifically the Republican-appointed majority of the Supreme Court \u2014 uphold arguments based on the so-called \u201cunitary executive theory,\u201d it would give Trump and subsequent presidents unprecedented power to remove and replace any federal employee and impose their will on every decision in every agency.\n\nRulings in favor of the Trump administration would also further jeopardize the independence of key regulatory agencies that are susceptible to conflicts of interest and political interference, like the Federal Election Commission, which oversees federal elections and campaign finance laws.\n\nHow Trump is advancing the theory\n\nTrump and his administration have furthered the theory by repeatedly invoking Article II of the Constitution, which vests executive power in the president, to justify the recent dismissals of federal officials. They have framed the article as allowing the president to use the whole of the executive branch for his political ends.\n\nFor example, the White House Feb. 18 invoked the article to rationalize an executive order signed that same day that asserted the president\u2019s authority over almost all regulatory agencies that were created by Congress to act independently, or semi-independently, from the president.\n\nFrank Bowman, a scholar of constitutional and criminal law at the University of Missouri School of Law, told Democracy Docket he believes the executive order is a step toward \u201can open declaration of dictatorship.\u201d\n\n\u201cIn essence, what he\u2019s saying is, \u2018I am the law. My will is the law. My view of what the law is the only view that can ever be expressed,\u2019\u201d Bowman said.\n\nOrigins of the unitary executive theory\n\nThe theory has its roots in the aggressive assertions of presidential power in the 20th century, especially throughout the Nixon administration, but it emerged as an unorthodox legal framework during the Reagan administration and gathered strength with subsequent presidencies.\n\nThe framework gained significant traction during George W. Bush\u2019s presidency, as it was key to his administration\u2019s attempt to legitimize unprecedented presidential powers, including those over the use of military force, state-sponsored kidnapping, the detention and interrogation of prisoners and intelligence gathering.\n\nThere isn\u2019t one set interpretation of the theory. At minimum, its proponents generally believe Article II allows the president to remove all executive branch officers. However, there are adherents, including Trump and many of his allies, who believe the president retains all the executive power and can control all officers and agencies.\n\nBowman said he believes the theory falls apart \u201cunder even rudimentary examination,\u201d noting that it conflicts with the basic checks to executive power that are intrinsic to the Constitution.\n\nFor example, the Appointments Clause of the Constitution only allows Congress to create federal offices and define their functions and jurisdiction and specifies that lawmakers can determine how officers are appointed to their offices.\n\nHow Trump is going beyond the theory\n\nNew York University School of Law professor Noah Rosenblum told Democracy Docket that Trump\u2019s idea of executive power is in many ways an expansive version of the traditional understanding of the unitary executive theory.\n\n\u201cUntil recently, I think most of us would have said unitary executive theory was obviously a hugely sweeping claim of presidential power that how could you possibly ask for more,\u201d Rosenblum said, \u201cbut Donald Trump is making different claims.\u201d\n\nHe noted that the White House, in addition to invoking Article II, attempted to justify Trump\u2019s Feb. 18 executive order against independent agencies by referring to him as \u201cthe democratically elected President.\u201d\n\n\u201cThat is an appeal to democratic legitimacy, not the Constitution,\u201d Rosenblum said. \u201cHe\u2019s saying, \u2018I was chosen by you to be the leader, so I\u2019m in charge. I can do whatever I want.\u2019\u201d\n\nNot satisfied with having supreme control over the executive branch, Trump is attempting to usurp Congress\u2019 power of the purse by impounding federal funds and encroaching on its ability to create federal offices by forming the Department of Government Efficiency to dissolve agencies created by the legislative branch.\n\nThe administration is also openly threatening to ignore the court\u2019s power to review the actions of the government to ensure they are lawful, as seen by Vice President JD Vance stating earlier in February that \u201cJudges aren\u2019t allowed to control the executive branch\u2019s legitimate power.\u201d\n\nMost incendiary, Trump on Feb. 15 put the rule of law \u2014 the foundation of our constitutional order \u2014 under the guillotine with a Napoleonic assertion that \u201cHe who saves his Country does not violate any Law.\u201d\n\nSupreme Court\u2019s receptiveness to the theory \n\nBowman said that before the Republican-majority on the Supreme Court granted the president absolute immunity from criminal prosecution for official functions in Trump v. U.S. last year, he would have said SCOTUS wouldn\u2019t be receptive to most of Trump\u2019s arguments. Now, he thinks they may be.\n\nRosenblum and his colleagues have argued the unitary executive theory has been guiding the Roberts Court over the past two decades, and he told Democracy Docket that he does not expect the court to significantly deviate from the theory in response to Trump\u2019s challenges.\n\nIn past decisions, like Humphrey\u2019s Executor v. U.S., SCOTUS has prevented presidents from dismissing specific types of federal officials, such as those on multi-member independent administrative bodies, for causes that were not specified in law by Congress.\n\nIn more recent opinions, justices have maintained precedent set by previous rulings while at the same time expanding the president\u2019s authority to remove other types of federal officials and giving him increased control over the executive branch.\n\nTrump\u2019s Department of Justice has relied on those recent opinions and Trump v. U.S. in its petition for SCOTUS to weigh in on the recent dismissal of the head of the nation\u2019s top independent federal investigative and prosecutorial agency.\n\nThe petition may mark the first Supreme Court test of Trump\u2019s second-term agenda and his goal to expand presidential powers.\n\nWhat Happens If Trump Defies Court Orders?\n\n Next Up \n\nWhen Eric Olsen decided to host an open house at the Prince William County election office, he knew he wasn\u2019t going to change everyone\u2019s mind. Olsen \u2014 who\u2019s been the registrar for the northern Virginia county since 2021 \u2014 has worked in election administration in D.C., Maryland and Virginia for nearly 15 years, and has [\u2026]]]>\n  \n  \n    This is the fundamental strategic constraint\n    https://x.com/balajis/status/1896668017544880459/?rw_tt_thread=True\n    readwise:01jnfh9xzvgw2a9cq7wpesc6cq\n    Tue, 04 Mar 2025 02:56:04 +0000\n    X (formerly Twitter)\n    \nThis is the fundamental strategic constraint.\n\nWhy is Russia winning in Ukraine?Why haven't sanctions worked on China?And why is the US less able to impose its will?Because the G7 is in relative decline.Until you understand this, you'll be confused.Check for yourself. Data is from the World Bank.data.worldbank.org/indicator/NY.G\u2026]]>\n    \nThis is the fundamental strategic constraint.\n\nWhy is Russia winning in Ukraine?Why haven't sanctions worked on China?And why is the US less able to impose its will?Because the G7 is in relative decline.Until you understand this, you'll be confused.Check for yourself. Data is from the World Bank.data.worldbank.org/indicator/NY.G\u2026]]>\n  \n  \n    My jaw just DROPPED\n    https://x.com/mattshumer_/status/1894062835132674052/?s=12&rw_tt_thread=True\n    readwise:01jmws0v9xgxrrajhqjwajx4bw\n    Mon, 24 Feb 2025 20:05:21 +0000\n    X (formerly Twitter)\n    \nMy jaw just DROPPED.\nRork lets you create entire iOS apps just by describing them!\nZero. Code. Required.\nThis changes everything for app development.\nRork blows Bolt out of the water (and yes, I invested immediately after trying it).\nWatch this \u2014 it's crazy:Your browser does not support the video tag.\n\nThe thing that really sets Rork apart (aside from building native mobile apps):\nIt's the best vibe-coding platform I've tried when it comes to design. The apps it generates just look great.\nDo yourself a favor \u2014 try this asap: rork.app]]>\n    \nMy jaw just DROPPED.\nRork lets you create entire iOS apps just by describing them!\nZero. Code. Required.\nThis changes everything for app development.\nRork blows Bolt out of the water (and yes, I invested immediately after trying it).\nWatch this \u2014 it's crazy:Your browser does not support the video tag.\n\nThe thing that really sets Rork apart (aside from building native mobile apps):\nIt's the best vibe-coding platform I've tried when it comes to design. The apps it generates just look great.\nDo yourself a favor \u2014 try this asap: rork.app]]>\n  \n  \n    Groundbreaking Study Demonstrates Clinical Benefits Of Planting Trees: The Green Heart Louisville Project Reveals How\n    https://www.forbes.com/sites/billfrist/2024/09/30/groundbreaking-study-demonstrates-clinical-benefits-of-planting-trees-the-green-heart-louisville-project-reveals-how/?utm_source=substack&utm_medium=email\n    readwise:01jmwa3z9xd9kpb53a5bqa3ncd\n    Mon, 24 Feb 2025 15:44:55 +0000\n    Forbes\n    \n\n\nAs a doctor and conservationist, I have a natural curiosity about nature and about health. Last month I traveled to Louisville, Kentucky for a groundbreaking announcement on how inextricably intertwined the two are. And why that\u2019s important to you and me.\n\nThough many of us intuitively understand that spending time in nature is good for us, there has been a lack of rigorous scientific research to prove it \u2014 until now.\n\nOn a sunny day in late August, we gathered at the University of Louisville to share the results of painstaking research that first began back in 2017. The clinical investigation, designed in partnership with the National Institute of Environmental Health Sciences, set out to answer the question, can trees improve our health? The answer, I discovered is: yes. In fact, based on what I learned that day, we might even consider trees as medicine!\n\nThanks to the Green Heart Louisville Project, the science now confirms that increasing trees in a neighborhood can yield measurable health benefits for residents.\n\nThis project set out to test this hypothesis through a collaboration of universities and local leaders, with the financial and advisory support of The Nature Conservancy (TNC), on whose Global Board I sit. I first learned of the research when my wife Tracy and I were seated next to Dr. Aruni Bhatnagar, head of the University of Louisville\u2019s Christina Lee Brown Envirome Institute and principal investigator on this unique project, at a TNC dinner in 2018. I remember thinking, can daily exposure to trees strategically placed in a community actually change blood chemistries of the body?\n\nPROMOTED\n\nHere\u2019s how the intervention of tree and shrub planting worked and what was found.\n\n\nBefore (L) and after (R) strategically tree planting in South Louisville, as part of the Green Heart ... [+] Louisville Project investigating the impact of a greening intervention on human health outcomes. Direct impacts include among many others absorption of pollution and sound. Mike Wilkinson, wilkinsonvisual. \n\nNature as a Pharmaceutical\n\n\n\nTheGreen Heart Louisville Project is the first longitudinal clinical trial to test a \u201cgreening intervention\u201d in the same way a new pharmaceutical intervention is tested. Trees are the medicine. This study is groundbreaking because while other studies have found an association or correlation between nature and well-being, the Green Heart Louisville Project is the first to scientifically and quantitatively measure the impact that an increase in trees and shrubs in a neighborhood can have on human health.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nCareers: Land the job, get a raise and learn to lead with our weekly Careers newsletter.\n\nBy signing up, you agree to receive this newsletter, other updates about Forbes and its affiliates\u2019 offerings, our Terms of Service (including resolving disputes on an individual basis via arbitration), and you acknowledge our Privacy Statement. Forbes is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.\n\nAfter years of data collection and analysis, the Green Heart Project is building a scientific case for the powerful connections between the health of our planet and the health of all of us.\n\n\nDr. Aruni Bhatnagar (L) and Dr. Bill Frist (R) on the announcement day in August. Dr. Bhatnagar is ... [+] the principal investigator and lead scientist on the Green Heart Louisville Project. He is the University of Louisville School of Medicine\u2019s Chief of the Division of Environmental Medicine and Director of the Christina Lee Brown Envirome Institute. Office of Senator Bill Frist, MD \n\n\n\n\n\n\nDr. Aruni Bhatnagar (L) and Dr. Bill Frist (R) on the announcement day in August. Dr. Bhatnagar is ... [+] the principal investigator and lead scientist on the Green Heart Louisville Project. He is the University of Louisville School of Medicine\u2019s Chief of the Division of Environmental Medicine and Director of the Christina Lee Brown Envirome Institute. Office of Senator Bill Frist, MD \n\nPlanting Trees in South Louisville\n\nSo what was the groundwork for this intervention? It began as a partnership with The Nature Conservancy, Washington University in St. Louis, Hyphae Design Laboratory, and others, under the visionary leadership of the University of Louisville\u2019s Aruni Bhatnagar, Ph.D. It was launched as a first-of-its-kind project in 2017 to study whether, and to what extent, living among greener surroundings contributes to better health. The National Institute for Environmental Health Sciences awarded the University Louisville funding to support the research. The Nature Conservancy raised substantial money for the trees, and dedicated expertise to the planning, implementation, and maintenance of the greening effort.\n\n\nThe Circle of Harmony & Health is a tool, developed by philanthropist Christina Brown, to help guide ... [+] and empower individuals and communities to live the healthiest, most-balanced life possible, and to understand the interconnection between all forms of health. It represents Christy\u2019s interconnected vision of health, incorporating citizen science and advocacy. https://anewvisionofhealth.com/ \n\nKey to the success of the effort was philanthropist Christina Brown, whom the Kentucky branch of The Nature Conservancy dubbed the \u201cGodmother of Kentucky.\u201d Christy, a longtime friend to my wife Tracy and me, has dedicated her life to advancing health, nature, and sustainability in all the communities she touches. The interconnecting influences that comprise health and wellbeing are captured in the illustrative emblem of \u201cThe Circle of Health and Harmony,\u201d (see figure) closely associated with her many endeavors and proudly worn as a lapel pin by so many advocates around the country. This tool emphasizes how environmental health is central to all well-being. It was Christy\u2019s commitment that provided the inspiration and foundational funding for the Christina Lee Brown Envirome Institute, whose mission is to investigate all aspects of health and their interrelationships, and it was her support that laid the groundwork for the Green Heart Project to come to fruition.\n\nWith this robust backing, the project began with baseline health data collection from over 750 study participants. The Nature Conservancy led several contractors and nonprofit partners, including Louisville Grows, on a multi-year effort to plant more than 8,000 trees and shrubs \u2013 most of them evergreens \u2013 in designated intervention areas in four neighborhoods in South Louisville. The work focuses on neighborhoods that had fewer trees compared with more affluent parts of the city. The neighborhoods are mixed racially and ethnically: 54 percent White, 29 percent Black, and 11 percent Hispanic. A busy highway runs directly through the neighborhoods \u2014 providing an unhealthy baseline of air pollution. The comparison control areas of these neighborhoods did not receive trees from the project.\n\nProject team members maintained the trees after planting to promote their survival, growth, and impact. Picture these South Louisville neighborhoods being gradually hugged by a growing mix of pines, hollies, arborvitaes, magnolias, dogwoods, oaks, and more.\n\nNearly seven years since the official launch of the Green Heart Louisville Project and nearly two years since tree planting concluded, the first phase of clinical study results are in \u2013 and they are promising.\n\n\nThe University of Louisville\u2019s Christina Lee Brown Envirome Institute, which leads collaborative ... [+] research bringing together a diversity of scientists, practitioners, and community members, launched this first-of-its-kind project in 2017 to study whether living among greener surroundings contributes to better health. Mike Wilkinson \n\nHow a \u201cGreening Intervention\u201d Improved Individual and Public Health\n\nThe researchers found that participants living in the neighborhoods of the greening intervention had, post-planting, lower levels of a widely recognized blood marker of inflammation (C-reactive protein) strongly associated with risk for cardiovascular disease, as well as diabetes and some cancers.\n\nThe precise etiology of this dramatic reduction of blood inflammatory measures is yet to be determined. Hypotheses currently being investigated include the degrees to which trees filter air pollution that could harden coronary arteries, whether trees improve sleep and reduce stress by buffering ambient roadway noise, how efficiently various species of trees absorb harmful pollutants, and what chemicals are released by trees that physiologically lower stress hormone levels.\n\nWhy is this significant? Because it means that adding trees to a neighborhood may reduce community members\u2019 risk of heart disease and other chronic, costly, and fatal diseases. The study demonstrated a significant decrease in the inflammatory blood marker. The clinical manifestations and direct impact on the heart, lungs, and other organs will be measured in the next phase of study.\n\nHeart disease is the leading cause of death in the U.S. and globally. And in Louisville alone, heart disease costs the city an estimated $650 million a year. If we could re-direct even a small amount of those costs towards prevention through a prescription of trees, it would reduce healthcare costs significantly over the long term. And save lives.\n\n\nSaplings planted as a part of the Green Heart Louisville Project (left) transform a neighborhood ... [+] after several years of growth (right), improving health outcomes, reducing heat, and providing wildlife habitat Mike Wilkinson, wilkinsonvisual. \n\nThe Nature Conservancy raised and invested $8.7 million for this project and played a fundamental role in implementing the greening efforts. TNC, the largest conservation entity in the nation, is committed to applying scientific research at the intersection of conservation and human health. TNC is grounded in the belief that human health is intrinsically and intimately tied to the health of our planet.\n\nIn addition to improving the body\u2019s health, we already know that trees reduce heat, provide wildlife and pollinator habitat, decrease stormwater runoff, increase property values, and lower utility bills. Psychologists have observed that stress levels and depressive states are less in greener sections of urban areas.\n\nIndeed, when viewed in its totality, no pill or medicine provides as many ancillary benefits as does nature.\n\nNext, Improving Health Across America\n\nThe Green Heart Louisville Project should give us hope, because it is a scientifically tested, replicable model for investing in nature in cities in the U.S. and around the world. It\u2019s a biological and economic reason to proactively bring nature to the cities. When I share this exciting news with others, they frequently ask what they can do as individuals. My answer is:\n\nFirst, help spread the word. We live in an era of information overload, and even critical research and findings fail to get the attention they deserve. People should know about these important findings because they have such a demonstrable impact on our individual health and well-being.\n\nSecond, I encourage others to become engaged and advocate for investments in nature with elected officials and other decision makers. The recently enacted Inflation Reduction Act makes substantial monies available to local communities for planting of trees. Most community leaders are not aware of this resource for better health.\n\nNature is essential infrastructure, too often taken for granted. But now we know it can make us healthier. Our local, state, and federal budgets need to reflect the reality that our environment and the nature around us affect our health in tangible, economically beneficial ways.\n\nThanks to the dedicated efforts of all those who contributed to the Green Heart Louisville Project, we now have a proven reason to advocate for increasing trees and green spaces in cities as a key strategy to improve individual and community health \u2013 while also making our cities cooler, more beautiful, and more welcoming places to live in and raise our families.\n\nFollow me on Twitter. Check out my website.\n\nEditorial StandardsForbes Accolades]]>\n    \n\n\nAs a doctor and conservationist, I have a natural curiosity about nature and about health. Last month I traveled to Louisville, Kentucky for a groundbreaking announcement on how inextricably intertwined the two are. And why that\u2019s important to you and me.\n\nThough many of us intuitively understand that spending time in nature is good for us, there has been a lack of rigorous scientific research to prove it \u2014 until now.\n\nOn a sunny day in late August, we gathered at the University of Louisville to share the results of painstaking research that first began back in 2017. The clinical investigation, designed in partnership with the National Institute of Environmental Health Sciences, set out to answer the question, can trees improve our health? The answer, I discovered is: yes. In fact, based on what I learned that day, we might even consider trees as medicine!\n\nThanks to the Green Heart Louisville Project, the science now confirms that increasing trees in a neighborhood can yield measurable health benefits for residents.\n\nThis project set out to test this hypothesis through a collaboration of universities and local leaders, with the financial and advisory support of The Nature Conservancy (TNC), on whose Global Board I sit. I first learned of the research when my wife Tracy and I were seated next to Dr. Aruni Bhatnagar, head of the University of Louisville\u2019s Christina Lee Brown Envirome Institute and principal investigator on this unique project, at a TNC dinner in 2018. I remember thinking, can daily exposure to trees strategically placed in a community actually change blood chemistries of the body?\n\nPROMOTED\n\nHere\u2019s how the intervention of tree and shrub planting worked and what was found.\n\n\nBefore (L) and after (R) strategically tree planting in South Louisville, as part of the Green Heart ... [+] Louisville Project investigating the impact of a greening intervention on human health outcomes. Direct impacts include among many others absorption of pollution and sound. Mike Wilkinson, wilkinsonvisual. \n\nNature as a Pharmaceutical\n\n\n\nTheGreen Heart Louisville Project is the first longitudinal clinical trial to test a \u201cgreening intervention\u201d in the same way a new pharmaceutical intervention is tested. Trees are the medicine. This study is groundbreaking because while other studies have found an association or correlation between nature and well-being, the Green Heart Louisville Project is the first to scientifically and quantitatively measure the impact that an increase in trees and shrubs in a neighborhood can have on human health.\n\n\nSome content could not be imported from the original document. View content \u2197 \n\nCareers: Land the job, get a raise and learn to lead with our weekly Careers newsletter.\n\nBy signing up, you agree to receive this newsletter, other updates about Forbes and its affiliates\u2019 offerings, our Terms of Service (including resolving disputes on an individual basis via arbitration), and you acknowledge our Privacy Statement. Forbes is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.\n\nAfter years of data collection and analysis, the Green Heart Project is building a scientific case for the powerful connections between the health of our planet and the health of all of us.\n\n\nDr. Aruni Bhatnagar (L) and Dr. Bill Frist (R) on the announcement day in August. Dr. Bhatnagar is ... [+] the principal investigator and lead scientist on the Green Heart Louisville Project. He is the University of Louisville School of Medicine\u2019s Chief of the Division of Environmental Medicine and Director of the Christina Lee Brown Envirome Institute. Office of Senator Bill Frist, MD \n\n\n\n\n\n\nDr. Aruni Bhatnagar (L) and Dr. Bill Frist (R) on the announcement day in August. Dr. Bhatnagar is ... [+] the principal investigator and lead scientist on the Green Heart Louisville Project. He is the University of Louisville School of Medicine\u2019s Chief of the Division of Environmental Medicine and Director of the Christina Lee Brown Envirome Institute. Office of Senator Bill Frist, MD \n\nPlanting Trees in South Louisville\n\nSo what was the groundwork for this intervention? It began as a partnership with The Nature Conservancy, Washington University in St. Louis, Hyphae Design Laboratory, and others, under the visionary leadership of the University of Louisville\u2019s Aruni Bhatnagar, Ph.D. It was launched as a first-of-its-kind project in 2017 to study whether, and to what extent, living among greener surroundings contributes to better health. The National Institute for Environmental Health Sciences awarded the University Louisville funding to support the research. The Nature Conservancy raised substantial money for the trees, and dedicated expertise to the planning, implementation, and maintenance of the greening effort.\n\n\nThe Circle of Harmony & Health is a tool, developed by philanthropist Christina Brown, to help guide ... [+] and empower individuals and communities to live the healthiest, most-balanced life possible, and to understand the interconnection between all forms of health. It represents Christy\u2019s interconnected vision of health, incorporating citizen science and advocacy. https://anewvisionofhealth.com/ \n\nKey to the success of the effort was philanthropist Christina Brown, whom the Kentucky branch of The Nature Conservancy dubbed the \u201cGodmother of Kentucky.\u201d Christy, a longtime friend to my wife Tracy and me, has dedicated her life to advancing health, nature, and sustainability in all the communities she touches. The interconnecting influences that comprise health and wellbeing are captured in the illustrative emblem of \u201cThe Circle of Health and Harmony,\u201d (see figure) closely associated with her many endeavors and proudly worn as a lapel pin by so many advocates around the country. This tool emphasizes how environmental health is central to all well-being. It was Christy\u2019s commitment that provided the inspiration and foundational funding for the Christina Lee Brown Envirome Institute, whose mission is to investigate all aspects of health and their interrelationships, and it was her support that laid the groundwork for the Green Heart Project to come to fruition.\n\nWith this robust backing, the project began with baseline health data collection from over 750 study participants. The Nature Conservancy led several contractors and nonprofit partners, including Louisville Grows, on a multi-year effort to plant more than 8,000 trees and shrubs \u2013 most of them evergreens \u2013 in designated intervention areas in four neighborhoods in South Louisville. The work focuses on neighborhoods that had fewer trees compared with more affluent parts of the city. The neighborhoods are mixed racially and ethnically: 54 percent White, 29 percent Black, and 11 percent Hispanic. A busy highway runs directly through the neighborhoods \u2014 providing an unhealthy baseline of air pollution. The comparison control areas of these neighborhoods did not receive trees from the project.\n\nProject team members maintained the trees after planting to promote their survival, growth, and impact. Picture these South Louisville neighborhoods being gradually hugged by a growing mix of pines, hollies, arborvitaes, magnolias, dogwoods, oaks, and more.\n\nNearly seven years since the official launch of the Green Heart Louisville Project and nearly two years since tree planting concluded, the first phase of clinical study results are in \u2013 and they are promising.\n\n\nThe University of Louisville\u2019s Christina Lee Brown Envirome Institute, which leads collaborative ... [+] research bringing together a diversity of scientists, practitioners, and community members, launched this first-of-its-kind project in 2017 to study whether living among greener surroundings contributes to better health. Mike Wilkinson \n\nHow a \u201cGreening Intervention\u201d Improved Individual and Public Health\n\nThe researchers found that participants living in the neighborhoods of the greening intervention had, post-planting, lower levels of a widely recognized blood marker of inflammation (C-reactive protein) strongly associated with risk for cardiovascular disease, as well as diabetes and some cancers.\n\nThe precise etiology of this dramatic reduction of blood inflammatory measures is yet to be determined. Hypotheses currently being investigated include the degrees to which trees filter air pollution that could harden coronary arteries, whether trees improve sleep and reduce stress by buffering ambient roadway noise, how efficiently various species of trees absorb harmful pollutants, and what chemicals are released by trees that physiologically lower stress hormone levels.\n\nWhy is this significant? Because it means that adding trees to a neighborhood may reduce community members\u2019 risk of heart disease and other chronic, costly, and fatal diseases. The study demonstrated a significant decrease in the inflammatory blood marker. The clinical manifestations and direct impact on the heart, lungs, and other organs will be measured in the next phase of study.\n\nHeart disease is the leading cause of death in the U.S. and globally. And in Louisville alone, heart disease costs the city an estimated $650 million a year. If we could re-direct even a small amount of those costs towards prevention through a prescription of trees, it would reduce healthcare costs significantly over the long term. And save lives.\n\n\nSaplings planted as a part of the Green Heart Louisville Project (left) transform a neighborhood ... [+] after several years of growth (right), improving health outcomes, reducing heat, and providing wildlife habitat Mike Wilkinson, wilkinsonvisual. \n\nThe Nature Conservancy raised and invested $8.7 million for this project and played a fundamental role in implementing the greening efforts. TNC, the largest conservation entity in the nation, is committed to applying scientific research at the intersection of conservation and human health. TNC is grounded in the belief that human health is intrinsically and intimately tied to the health of our planet.\n\nIn addition to improving the body\u2019s health, we already know that trees reduce heat, provide wildlife and pollinator habitat, decrease stormwater runoff, increase property values, and lower utility bills. Psychologists have observed that stress levels and depressive states are less in greener sections of urban areas.\n\nIndeed, when viewed in its totality, no pill or medicine provides as many ancillary benefits as does nature.\n\nNext, Improving Health Across America\n\nThe Green Heart Louisville Project should give us hope, because it is a scientifically tested, replicable model for investing in nature in cities in the U.S. and around the world. It\u2019s a biological and economic reason to proactively bring nature to the cities. When I share this exciting news with others, they frequently ask what they can do as individuals. My answer is:\n\nFirst, help spread the word. We live in an era of information overload, and even critical research and findings fail to get the attention they deserve. People should know about these important findings because they have such a demonstrable impact on our individual health and well-being.\n\nSecond, I encourage others to become engaged and advocate for investments in nature with elected officials and other decision makers. The recently enacted Inflation Reduction Act makes substantial monies available to local communities for planting of trees. Most community leaders are not aware of this resource for better health.\n\nNature is essential infrastructure, too often taken for granted. But now we know it can make us healthier. Our local, state, and federal budgets need to reflect the reality that our environment and the nature around us affect our health in tangible, economically beneficial ways.\n\nThanks to the dedicated efforts of all those who contributed to the Green Heart Louisville Project, we now have a proven reason to advocate for increasing trees and green spaces in cities as a key strategy to improve individual and community health \u2013 while also making our cities cooler, more beautiful, and more welcoming places to live in and raise our families.\n\nFollow me on Twitter. Check out my website.\n\nEditorial StandardsForbes Accolades]]>\n  \n  \n    How The Busiest Heart Transplant Center In The World Got Its Start \u2013 An Inside Story Of The First Decade\n    https://www.forbes.com/sites/billfrist/2023/02/06/how-the-busiest-heart-transplant-center-in-the-world-got-its-start--an-inside-story-of-the-first-decade/?utm_source=substack&utm_medium=email\n    readwise:01jmwa2z8nngdx9b76tq91z33r\n    Mon, 24 Feb 2025 15:44:22 +0000\n    Forbes\n    The Vanderbilt Transplant Center is currently the busiest heart transplant center in the world. This is the story of building the foundation for what the Center has become today \u2014 a narrative of the initial decade of the 34 years since the founding of this first-of-its-kind, multidisciplinary, multi-organ transplant center. Over 12,300 adult and pediatric transplants have been performed at Vanderbilt. Not only does Vanderbilt perform more heart transplants annually than any other center, but it is where the longest surviving lung transplant patient was transplanted over three decades ago.\n\n\nThe author holding explanted human heart in 1992.\n\nIt started with a phone call.\n\nIn 1985 I was a Fellow in transplant surgery at Stanford University Medical School, operating under the tutelage of Dr. Norman Shumway. Shumway is considered the \u201cFather of Heart Transplantation,\u201d a title fitting for my mentor who was a research-grounded, scientist-surgeon. For more than two decades prior to my arrival at Stanford, Shumway had systematically conducted basic science and pre-clinical transplant research that culminated in his performing the first human heart transplant in the United States on January 6, 1968 (Dr. Christiaan Barnard, using techniques and knowledge that Shumway had developed over decades, performed the first human-to-human heart transplant in South Africa a month before.).\n\nIt was while completing my fellowship program under Shumway that late one evening my phone rang. On the other end of line was Dr. Harvey Bender, Chief of Cardiac Surgery at Vanderbilt: \u201cBill,\u201d he said, \u201cIke Robinson (then Vanderbilt\u2019s Vice-Chancellor) and I would like for you to come back home to Nashville to join Walter (Merrill, MD) to start and build a heart transplant program.\u201d\n\nAt the time, heart transplantation was in its infancy. Shumway\u2019s promising early clinical results, solidly grounded in more than two decades of painstaking basic and pre-clinical research, suggested that heart transplantation would someday become routine. At that moment, however, not a single heart transplantation had been performed back in Tennessee. The field was still considered experimental.\n\nI was intrigued by Bender\u2019s offer, but I had envisioned a much grander dream than he had proposed. That dream was to create a new concept \u2014 a multi-organ and multidisciplinary transplant center under one roof. No one had done it. The grand vision would include more holistic, patient-focused transplant care \u2013 for hearts, but also for a multitude of organs. Such scale would lead to better patient care and synergies other programs could never achieve.\n\nBender\u2019s call inspired me to further research and refine what had been percolating in my mind. It was an audacious goal, but it was one that I knew at the right place, with the right resources, and with an unwavering commitment to ongoing scientific discovery, would become a reality.\n\n\nThe author in 1991 replacing a diseased 53-year-old heart with a healthy 18-year-old heart at the ... [+]\n\nExpanding the Stanford Single-Organ Model to a Multi-Organ Center: Collaboration \n\nAt Stanford, Dr. Shumway had focused on breaking down silos; he championed the power of the collaborative team, expressly respecting the vital roles of nurses (very unusual for cardiac surgeons of those early days!) and all members of the transplant team. Under his guidance in the early 1980s, he taught me the power of organizing into closely-knit teams professionals from a variety of backgrounds. Excellent transplant care, he practiced, was best achieved by bringing together research, clinical care, and education professionals. I knew this had to be applied to the newly envisioned multi-organ Vanderbilt Transplant model, with the distinctly unique dimension of this being carried out across a whole range of organs, not just the heart.\n\n\nDr. Norman Shumway, who received his M.D. from Vanderbilt in 1949, at a casual gathering in 1984 ... [+]\n\nAt Vanderbilt\u2019s newly conceived transplant center, the anesthesiologists, surgeons, psychiatrists, nurses, social workers, rehabilitation and physical therapy specialists, clinical scientists, ethicists, and infectious disease experts would all engage each other at one site, side-by-side, all laser-focused on the patient. The natural, free-flowing exchange within a single Center among the many medical, surgical, and research disciplines would bring forth new ideas to be explored. Perhaps, we mused in the 1980s, we would even succeed one day at single-lung transplants, notoriously unsuccessful in those years.\n\nOnly one institution, the University of Pittsburgh, had attempted anything similar, then under the leadership of renowned liver transplant surgeon Dr. Thomas Starzl. But there, transplantation was isolated by organ type into separate programs, without geographic colocation. At other existing programs around the country, transplantation was built around a single organ, with most stove-piped around a single, high-profile surgeon. Such emphasis on a single surgeon \u2013 or a single organ \u2013 typically led to a program that could not be sustained over decades. Our goal was the build the foundation for a program that would thrive for generations.\n\nThe Move to Vanderbilt: Making the Dream Real\n\nBack at Stanford while still completing my Fellowship, I formalized the plan. I put together a 45-page business, research, and clinical proposal that outlined in detail how the new Center would succeed, even at a time when third party reimbursement for heart transplantation did not exist. Financial barriers were formidable.\n\nI accepted the position and arrived at Vanderbilt in 1985.\n\nWe assembled the envisioned multi-disciplinary transplant team and together we formulated a single-minded mission, around which we all aligned culturally: \u201cTo advance the medical and scientific aspects of transplantation through innovative, multi-specialty programs in education, research, and clinical practice.\u201d\n\nThe team we assembled collectively committed to establishing Vanderbilt as the national leader in transplantation \u2013 and we would do so by including and mastering the entire spectrum of care, from chronic care before transplantation, through the surgical procedure, to the long-term care of patient and family post-transplant. This was decades before today\u2019s realization of the importance of \u201cepisodes of care\u201d to value-based care. It was about much more than \u201csurgical outcomes.\u201d It was about the best for our patients and their families before, during, and long after the transplant procedure.\n\nFortunately, Vanderbilt had some strong transplant experience. The previous decade, Drs. Keith Johnson and Bob Richie had together established a very successful kidney transplant program in Nashville at Vanderbilt. But the grand dream extended well beyond kidney: we would add heart, then liver, pancreas, bone marrow, lung, and combined heart and lung transplants. We would recruit a dedicated infectious disease expert with specialized transplant knowledge to be shared across all organs. We would bring on a full-time transplant ethicist, unheard of at the time, to help us sort through the tough decisions of life and death in this new world of high demand for transplantation but scarce donor organ supply. Who would receive the scarce organs and who would die waiting? The rapidly advancing scientific procedures never possible before introduced new health equity issues society had never had to consider. So, we built the framework for consideration of these ethical issues into the Center at the outset.\n\n\nDr. Bill Frist and organ procurement specialist Doug Martin of Tennessee Donor Services on a \"donor\n\nFor transplantation, accurate and readily accessible data was more important to success than for any other medical field. We needed the clinical and financial data in real time so that we could smartly and safely advance the new and ever-changing field, not just let it evolve. From day one we at the Center measured everything: costs, processes, quality measures, outcomes, and functional results.\n\nTransplantation became the most regulated field of medicine. The federal government for the first time wisely demanded these data, not just for government-funded procedures but for all transplants. The sector of transplantation was regarded as a public good. We in the transplant world were years ahead of other medical specialties in reporting and measuring clinical outcomes.\n\nA Lesson From the Past: The Critical Role of Innovation\n\nWhen we embarked on our journey in the mid-1980s, heart transplantation was in its infancy. Every successful step forward would introduce new problems, new challenges, that would require new solutions. Innovation with ongoing re-invention, we knew, had to be embedded in our culture. Thus, we built a team passionate about continuous problem-solving for what would unfold.\n\nI had an earlier experience while in surgical training in Boston that taught me the high cost of walling off innovation. In 1980 as a cardiac surgical resident at Massachusetts General Hospital (MGH), the Board of Trustees of the hospital dramatically placed an indefinite moratorium on heart transplantation. This surprising announcement, the rationale of which was laid out in the prestigious New England Journal of Medicine, cited cost and a utilitarian philosophy \u2013 the crucial question, they wrote, being \u201cwhat choice would reap the greatest good for the greatest number.\u201d\n\nI was stunned \u2014 and deeply disappointed. I strongly felt the trustees\u2019 policy decision, however well-intentioned, was shortsighted and misguided based on the science at the time. How could the very hospitals that had pioneered kidney transplantation three decades earlier ban a promising heart procedure that could eventually save thousands of lives? Instead of working with their many resources to pioneer this rapidly advancing albeit new procedure, the hospital leadership abruptly shut the door to clinical innovation and research that would improve patient care. The ban on clinical innovation expanded to the other Harvard hospitals in Boston.\n\nAdmittedly with a touch of bitterness because of my own conviction around the future of heart and lung transplants, I left the MGH and Boston to join Shumway at Stanford, who had committed to strong clinical research and innovation. And it took years after the moratorium was finally lifted for Boston to catch up to other centers. There is a cost to saying \u201cno\u201d to innovation.\n\n\nVanderbilt heart and lung transplant recipients\u2019 reunion, 1991. The culture of holistic patient and ... [+]\n\nInstitutional Commitment to Innovation and Equity\n\nFrom the outset, at Vanderbilt we made health equity a priority. We believed these life-saving innovations should be available not just to the tiny minority who could pay six-figures out-of-pocket for a new heart. Vanderbilt\u2019s leadership, specifically the Board of Trustees, endorsed us opening our doors to the patients in greatest need, not just those who could afford to pay. Eventually, of course, our Center would need to pay our own way. But during those early years in the 1980s when insurers had not yet begun to cover transplantation, Vanderbilt absorbed the initial patient costs. This wise, initial investment allowed us to build early on the patient volume, accumulate the data, and develop the expertise to demonstrate through comprehensively measured outcomes the immense value of heart transplantation to the patient, to the community, and ultimately to the nation.\n\nEarning designation a few years after our start as a national \u201ccenter of excellence\u201d for companies such as Honeywell and Blue Cross, and then for Medicare, allowed us to mount the compelling, evidence-based case for more extensive commercial insurance and Medicaid reimbursement, and thus increased access for all patients. The investment in innovation and health equity established a strong foundation for the future, becoming cornerstones to our culture and mission.\n\nActively Engaging in Public Policy\n\nHeart transplantation is dependent on a limited supply of donor organs, which is heavily regulated to ensure safety and fairness. Thus, from the outset we knew that much of our progress would depend on public policy developed and implemented at the state and national level. Though we were trained as a medical team, we understood that it was imperative for us to actively engage in public policy.\n\n\nDr. Walter Merrill, who performed Vanderbilt\u2019s first heart transplant, and Senator Bill Frist with ... [+]\n\nOur Center leadership supported and participated in the early evolution of the government-mandated United Network for Organ Sharing (UNOS) to ensure all Americans could gain equitable and just access to these new life-saving procedures. Of interesting historical note, the original model of UNOS in the mid-1980s grew out of the pre-existing Southeast Organ Procurement Foundation, where Vanderbilt\u2019s Keith Johnson and others had actively engaged and played leadership roles.\n\nAt the state level, when in 1990 Tennessee dropped the organ donor card from the back of the state driver\u2019s license, we at the Center launched and led the statewide, grassroots campaign called \u201cGive Life to Your License\u201d. Two years later, the donor card was returned to the licenses where it has remained over the past 30 years.\n\nToday: The Busiest Heart Transplant Center in the World\n\nThe Vanderbilt Transplant Center has performed more than 12,300 total adult and pediatric transplants. It is currently performing more heart transplants than any in the world. For all transplants, it is fifth in the country. It is one of a few transplant programs designated by the U.S. Department of Veterans Affairs to provide heart and liver transplants to our nation's veterans.\n\nThe strong foundation of the Center was laid in its first decade of existence. It was built on a dream \u2014 and a culture and commitment to science, data, innovation, and patient-centeredness. The two subsequent decades, whose story will be told by others, witnessed tremendous growth:\n\n\u00b7 Heart: In 1989 the first year of the multi-organ Center (five years after the first heart transplant at Vanderbilt), we performed 28 heart transplants, among the highest in the country. Thirty-two years later in 2022, the Center performed a record 141 heart transplants, more than any other center in the world (Asia does not report data.). This milestone was reached under the leadership of Dr. Ashish Shah and Dr. Kelly Schlendorf. More than 1,749 heart transplants have been performed at Vanderbilt.\n\n\u00b7 Kidney: Over 7,100 kidney, simultaneous pancreas-kidney, and pancreas transplants have been performed at Vanderbilt. In 1989 the Center performed 89 kidney transplant procedures; that number more than tripled to 315 by 2021.\n\n\nPam Everett-Smith, who Drs. Frist and Merrill transplanted in 1990, is the longest-surviving\n\n\u00b7 Lung: In 1990 we launched our single-lung transplant program, performing five transplants in the first year, under the leadership of the author and pulmonologist Dr. Jim Loyd. In 2021 the Center performed 54 lung transplants. Over the lifetime of the program over 700 lung and combined heart-lung transplants have been conducted.\n\nPamela Everett-Smith, our Center\u2019s fourth lung transplant patient back in 1990, is the longest-surviving single-lung transplant patient known in the United States. Dr. Walter Merrill and the author (Frist) performed her transplant 32 years ago. In a 2021 article in the VUMC Reporter, Pamela shared, \u201cI\u2019m 56 now and I didn\u2019t think I\u2019d see 30, let alone 56. I just thank God for every day that he gives me.\u201d\n\n\u00b7 Liver: In 1990 Dr. Wright Pinson, today Deputy CEO and Chief Health System Officer at Vanderbilt University Medical Center, was recruited to start the liver transplant program. In 2021 the Center performed 123 liver transplants. Over 2,700 liver transplants have been performed since Dr. Pinson initiated the program. Dr. Pinson succeeded the author as Director of the Transplant Center in 1993 and served in that capacity until 2011.\n\n\nDecades of Vanderbilt Transplant Center leadership from left to right: Dr. Seth Karp, the current ... [+]\n\nVanderbilt also leads the nation in expanding donors, pioneering both the use of Hepatitis C-exposed donors in transplantation of non-infected recipients (which are then treated after transplant) and the ex vivo perfusion system, which improves organ quality and extends the operating window of time by using a machine to continuously pump blood through the organ rather than store it on ice before transplantation.\n\nThis is the story of the first decade, which laid the sturdy foundation upon which a remarkable trajectory of growth has persisted. Now more than 30 years after its founding, the Vanderbilt Transplant Center continues to transform countless lives and exceed our earliest dreams. We thank the many physicians and staff who have worked to make this dream a reality. And a special acknowledgment to the patients and families who entrusted us with their care.]]>\n    The Vanderbilt Transplant Center is currently the busiest heart transplant center in the world. This is the story of building the foundation for what the Center has become today \u2014 a narrative of the initial decade of the 34 years since the founding of this first-of-its-kind, multidisciplinary, multi-organ transplant center. Over 12,300 adult and pediatric transplants have been performed at Vanderbilt. Not only does Vanderbilt perform more heart transplants annually than any other center, but it is where the longest surviving lung transplant patient was transplanted over three decades ago.\n\n\nThe author holding explanted human heart in 1992.\n\nIt started with a phone call.\n\nIn 1985 I was a Fellow in transplant surgery at Stanford University Medical School, operating under the tutelage of Dr. Norman Shumway. Shumway is considered the \u201cFather of Heart Transplantation,\u201d a title fitting for my mentor who was a research-grounded, scientist-surgeon. For more than two decades prior to my arrival at Stanford, Shumway had systematically conducted basic science and pre-clinical transplant research that culminated in his performing the first human heart transplant in the United States on January 6, 1968 (Dr. Christiaan Barnard, using techniques and knowledge that Shumway had developed over decades, performed the first human-to-human heart transplant in South Africa a month before.).\n\nIt was while completing my fellowship program under Shumway that late one evening my phone rang. On the other end of line was Dr. Harvey Bender, Chief of Cardiac Surgery at Vanderbilt: \u201cBill,\u201d he said, \u201cIke Robinson (then Vanderbilt\u2019s Vice-Chancellor) and I would like for you to come back home to Nashville to join Walter (Merrill, MD) to start and build a heart transplant program.\u201d\n\nAt the time, heart transplantation was in its infancy. Shumway\u2019s promising early clinical results, solidly grounded in more than two decades of painstaking basic and pre-clinical research, suggested that heart transplantation would someday become routine. At that moment, however, not a single heart transplantation had been performed back in Tennessee. The field was still considered experimental.\n\nI was intrigued by Bender\u2019s offer, but I had envisioned a much grander dream than he had proposed. That dream was to create a new concept \u2014 a multi-organ and multidisciplinary transplant center under one roof. No one had done it. The grand vision would include more holistic, patient-focused transplant care \u2013 for hearts, but also for a multitude of organs. Such scale would lead to better patient care and synergies other programs could never achieve.\n\nBender\u2019s call inspired me to further research and refine what had been percolating in my mind. It was an audacious goal, but it was one that I knew at the right place, with the right resources, and with an unwavering commitment to ongoing scientific discovery, would become a reality.\n\n\nThe author in 1991 replacing a diseased 53-year-old heart with a healthy 18-year-old heart at the ... [+]\n\nExpanding the Stanford Single-Organ Model to a Multi-Organ Center: Collaboration \n\nAt Stanford, Dr. Shumway had focused on breaking down silos; he championed the power of the collaborative team, expressly respecting the vital roles of nurses (very unusual for cardiac surgeons of those early days!) and all members of the transplant team. Under his guidance in the early 1980s, he taught me the power of organizing into closely-knit teams professionals from a variety of backgrounds. Excellent transplant care, he practiced, was best achieved by bringing together research, clinical care, and education professionals. I knew this had to be applied to the newly envisioned multi-organ Vanderbilt Transplant model, with the distinctly unique dimension of this being carried out across a whole range of organs, not just the heart.\n\n\nDr. Norman Shumway, who received his M.D. from Vanderbilt in 1949, at a casual gathering in 1984 ... [+]\n\nAt Vanderbilt\u2019s newly conceived transplant center, the anesthesiologists, surgeons, psychiatrists, nurses, social workers, rehabilitation and physical therapy specialists, clinical scientists, ethicists, and infectious disease experts would all engage each other at one site, side-by-side, all laser-focused on the patient. The natural, free-flowing exchange within a single Center among the many medical, surgical, and research disciplines would bring forth new ideas to be explored. Perhaps, we mused in the 1980s, we would even succeed one day at single-lung transplants, notoriously unsuccessful in those years.\n\nOnly one institution, the University of Pittsburgh, had attempted anything similar, then under the leadership of renowned liver transplant surgeon Dr. Thomas Starzl. But there, transplantation was isolated by organ type into separate programs, without geographic colocation. At other existing programs around the country, transplantation was built around a single organ, with most stove-piped around a single, high-profile surgeon. Such emphasis on a single surgeon \u2013 or a single organ \u2013 typically led to a program that could not be sustained over decades. Our goal was the build the foundation for a program that would thrive for generations.\n\nThe Move to Vanderbilt: Making the Dream Real\n\nBack at Stanford while still completing my Fellowship, I formalized the plan. I put together a 45-page business, research, and clinical proposal that outlined in detail how the new Center would succeed, even at a time when third party reimbursement for heart transplantation did not exist. Financial barriers were formidable.\n\nI accepted the position and arrived at Vanderbilt in 1985.\n\nWe assembled the envisioned multi-disciplinary transplant team and together we formulated a single-minded mission, around which we all aligned culturally: \u201cTo advance the medical and scientific aspects of transplantation through innovative, multi-specialty programs in education, research, and clinical practice.\u201d\n\nThe team we assembled collectively committed to establishing Vanderbilt as the national leader in transplantation \u2013 and we would do so by including and mastering the entire spectrum of care, from chronic care before transplantation, through the surgical procedure, to the long-term care of patient and family post-transplant. This was decades before today\u2019s realization of the importance of \u201cepisodes of care\u201d to value-based care. It was about much more than \u201csurgical outcomes.\u201d It was about the best for our patients and their families before, during, and long after the transplant procedure.\n\nFortunately, Vanderbilt had some strong transplant experience. The previous decade, Drs. Keith Johnson and Bob Richie had together established a very successful kidney transplant program in Nashville at Vanderbilt. But the grand dream extended well beyond kidney: we would add heart, then liver, pancreas, bone marrow, lung, and combined heart and lung transplants. We would recruit a dedicated infectious disease expert with specialized transplant knowledge to be shared across all organs. We would bring on a full-time transplant ethicist, unheard of at the time, to help us sort through the tough decisions of life and death in this new world of high demand for transplantation but scarce donor organ supply. Who would receive the scarce organs and who would die waiting? The rapidly advancing scientific procedures never possible before introduced new health equity issues society had never had to consider. So, we built the framework for consideration of these ethical issues into the Center at the outset.\n\n\nDr. Bill Frist and organ procurement specialist Doug Martin of Tennessee Donor Services on a \"donor\n\nFor transplantation, accurate and readily accessible data was more important to success than for any other medical field. We needed the clinical and financial data in real time so that we could smartly and safely advance the new and ever-changing field, not just let it evolve. From day one we at the Center measured everything: costs, processes, quality measures, outcomes, and functional results.\n\nTransplantation became the most regulated field of medicine. The federal government for the first time wisely demanded these data, not just for government-funded procedures but for all transplants. The sector of transplantation was regarded as a public good. We in the transplant world were years ahead of other medical specialties in reporting and measuring clinical outcomes.\n\nA Lesson From the Past: The Critical Role of Innovation\n\nWhen we embarked on our journey in the mid-1980s, heart transplantation was in its infancy. Every successful step forward would introduce new problems, new challenges, that would require new solutions. Innovation with ongoing re-invention, we knew, had to be embedded in our culture. Thus, we built a team passionate about continuous problem-solving for what would unfold.\n\nI had an earlier experience while in surgical training in Boston that taught me the high cost of walling off innovation. In 1980 as a cardiac surgical resident at Massachusetts General Hospital (MGH), the Board of Trustees of the hospital dramatically placed an indefinite moratorium on heart transplantation. This surprising announcement, the rationale of which was laid out in the prestigious New England Journal of Medicine, cited cost and a utilitarian philosophy \u2013 the crucial question, they wrote, being \u201cwhat choice would reap the greatest good for the greatest number.\u201d\n\nI was stunned \u2014 and deeply disappointed. I strongly felt the trustees\u2019 policy decision, however well-intentioned, was shortsighted and misguided based on the science at the time. How could the very hospitals that had pioneered kidney transplantation three decades earlier ban a promising heart procedure that could eventually save thousands of lives? Instead of working with their many resources to pioneer this rapidly advancing albeit new procedure, the hospital leadership abruptly shut the door to clinical innovation and research that would improve patient care. The ban on clinical innovation expanded to the other Harvard hospitals in Boston.\n\nAdmittedly with a touch of bitterness because of my own conviction around the future of heart and lung transplants, I left the MGH and Boston to join Shumway at Stanford, who had committed to strong clinical research and innovation. And it took years after the moratorium was finally lifted for Boston to catch up to other centers. There is a cost to saying \u201cno\u201d to innovation.\n\n\nVanderbilt heart and lung transplant recipients\u2019 reunion, 1991. The culture of holistic patient and ... [+]\n\nInstitutional Commitment to Innovation and Equity\n\nFrom the outset, at Vanderbilt we made health equity a priority. We believed these life-saving innovations should be available not just to the tiny minority who could pay six-figures out-of-pocket for a new heart. Vanderbilt\u2019s leadership, specifically the Board of Trustees, endorsed us opening our doors to the patients in greatest need, not just those who could afford to pay. Eventually, of course, our Center would need to pay our own way. But during those early years in the 1980s when insurers had not yet begun to cover transplantation, Vanderbilt absorbed the initial patient costs. This wise, initial investment allowed us to build early on the patient volume, accumulate the data, and develop the expertise to demonstrate through comprehensively measured outcomes the immense value of heart transplantation to the patient, to the community, and ultimately to the nation.\n\nEarning designation a few years after our start as a national \u201ccenter of excellence\u201d for companies such as Honeywell and Blue Cross, and then for Medicare, allowed us to mount the compelling, evidence-based case for more extensive commercial insurance and Medicaid reimbursement, and thus increased access for all patients. The investment in innovation and health equity established a strong foundation for the future, becoming cornerstones to our culture and mission.\n\nActively Engaging in Public Policy\n\nHeart transplantation is dependent on a limited supply of donor organs, which is heavily regulated to ensure safety and fairness. Thus, from the outset we knew that much of our progress would depend on public policy developed and implemented at the state and national level. Though we were trained as a medical team, we understood that it was imperative for us to actively engage in public policy.\n\n\nDr. Walter Merrill, who performed Vanderbilt\u2019s first heart transplant, and Senator Bill Frist with ... [+]\n\nOur Center leadership supported and participated in the early evolution of the government-mandated United Network for Organ Sharing (UNOS) to ensure all Americans could gain equitable and just access to these new life-saving procedures. Of interesting historical note, the original model of UNOS in the mid-1980s grew out of the pre-existing Southeast Organ Procurement Foundation, where Vanderbilt\u2019s Keith Johnson and others had actively engaged and played leadership roles.\n\nAt the state level, when in 1990 Tennessee dropped the organ donor card from the back of the state driver\u2019s license, we at the Center launched and led the statewide, grassroots campaign called \u201cGive Life to Your License\u201d. Two years later, the donor card was returned to the licenses where it has remained over the past 30 years.\n\nToday: The Busiest Heart Transplant Center in the World\n\nThe Vanderbilt Transplant Center has performed more than 12,300 total adult and pediatric transplants. It is currently performing more heart transplants than any in the world. For all transplants, it is fifth in the country. It is one of a few transplant programs designated by the U.S. Department of Veterans Affairs to provide heart and liver transplants to our nation's veterans.\n\nThe strong foundation of the Center was laid in its first decade of existence. It was built on a dream \u2014 and a culture and commitment to science, data, innovation, and patient-centeredness. The two subsequent decades, whose story will be told by others, witnessed tremendous growth:\n\n\u00b7 Heart: In 1989 the first year of the multi-organ Center (five years after the first heart transplant at Vanderbilt), we performed 28 heart transplants, among the highest in the country. Thirty-two years later in 2022, the Center performed a record 141 heart transplants, more than any other center in the world (Asia does not report data.). This milestone was reached under the leadership of Dr. Ashish Shah and Dr. Kelly Schlendorf. More than 1,749 heart transplants have been performed at Vanderbilt.\n\n\u00b7 Kidney: Over 7,100 kidney, simultaneous pancreas-kidney, and pancreas transplants have been performed at Vanderbilt. In 1989 the Center performed 89 kidney transplant procedures; that number more than tripled to 315 by 2021.\n\n\nPam Everett-Smith, who Drs. Frist and Merrill transplanted in 1990, is the longest-surviving\n\n\u00b7 Lung: In 1990 we launched our single-lung transplant program, performing five transplants in the first year, under the leadership of the author and pulmonologist Dr. Jim Loyd. In 2021 the Center performed 54 lung transplants. Over the lifetime of the program over 700 lung and combined heart-lung transplants have been conducted.\n\nPamela Everett-Smith, our Center\u2019s fourth lung transplant patient back in 1990, is the longest-surviving single-lung transplant patient known in the United States. Dr. Walter Merrill and the author (Frist) performed her transplant 32 years ago. In a 2021 article in the VUMC Reporter, Pamela shared, \u201cI\u2019m 56 now and I didn\u2019t think I\u2019d see 30, let alone 56. I just thank God for every day that he gives me.\u201d\n\n\u00b7 Liver: In 1990 Dr. Wright Pinson, today Deputy CEO and Chief Health System Officer at Vanderbilt University Medical Center, was recruited to start the liver transplant program. In 2021 the Center performed 123 liver transplants. Over 2,700 liver transplants have been performed since Dr. Pinson initiated the program. Dr. Pinson succeeded the author as Director of the Transplant Center in 1993 and served in that capacity until 2011.\n\n\nDecades of Vanderbilt Transplant Center leadership from left to right: Dr. Seth Karp, the current ... [+]\n\nVanderbilt also leads the nation in expanding donors, pioneering both the use of Hepatitis C-exposed donors in transplantation of non-infected recipients (which are then treated after transplant) and the ex vivo perfusion system, which improves organ quality and extends the operating window of time by using a machine to continuously pump blood through the organ rather than store it on ice before transplantation.\n\nThis is the story of the first decade, which laid the sturdy foundation upon which a remarkable trajectory of growth has persisted. Now more than 30 years after its founding, the Vanderbilt Transplant Center continues to transform countless lives and exceed our earliest dreams. We thank the many physicians and staff who have worked to make this dream a reality. And a special acknowledgment to the patients and families who entrusted us with their care.]]>\n  \n  \n    this is what's keeping me up at night these days...\n    https://x.com/gregisenberg/status/1893687593755164940/?s=12&rw_tt_thread=True\n    readwise:01jmt0t5tbx3qz2bngxf35zb97\n    Sun, 23 Feb 2025 18:23:48 +0000\n    X (formerly Twitter)\n    \nthis is what's keeping me up at night these days...\n\n\ngoogle has become unusable. once you get used to \"deep research\" (thanks grok, perplexity etc), google feels like bringing a typewriter to a macbook meeting.\n\nMCP will do for ai agents what REST did for web services - this standard protocol means an ai agent built for healthcare can instantly talk to billing systems, patient records, and insurance databases without custom code, unlocking thousands of new startup opportunities. it's really exciting! \n\nwe're seeing the entire cost structure of building businesses collapse -  you can now build profitable companies serving tiny, weird niches that were impossible to reach when you needed a full team. what used to need 1000 customers to break even now needs 10.\n\nit's not too late to be a creator or build a media business. creators are evolving into the new holding companies, consolidating influence, revenue streams, and audiences in ways that mirror corporate giants. somehow it's still early\n\nreally big arbitrage opportunity to buy businesses without taste and add taste. \"taste private equity\" has a nice ring to it.\n\nfiguring out LLM seo. billions of dollars will flow to new players who figure out how to get \"cited\" by LLMs. finally.\n\nmost ai apps are designed for websites not mobile. ai-first consumer mobile is really interesting. we saw with cal ai and the looksmaxing apps, that this is just the beginning.\n\nevery product launch needs video now - i'm watching great features die on landing pages while quick screen recordings go viral and drive thousands of signups. the social feeds have spoken.\n\nwhat used to require millions in vc funding now needs an api key, some prompts and a tweet. this fires me up!!\n\nfaster than ever to launch something of quality. faster than ever to pivot. knowing when to pivot is an art.\n\ni dont understand anyone who sitting in business school right now. literally everything is being rewritten.\n\nwho is building the app store for ai agents? companies will browse and hire pre-trained, specialized agents like we download apps\n\nthe way to stop a big player to compete with you in this new world is to own distribution.\n\nyou can spend a lot of time thinking about politics or checking emails or on social in the name of research, but not really moving forward anywhere.\n\nwe're about to see software companies capture value that used to belong to agencies, consulting firms, and entire departments. \n\nwe're about to go from \"there's an app for that\" to \"there's your app for that.\n\nminimum viable audience is more important than minimum viable product\n\nI don't know how long this window stays open, but we're in a moment where all the rules of building businesses are being rewritten. and for the people who are playing with this new tools, putting stuff out there, creating audiences/communities, you've got an unfair advantage.\ni hope you get some sleep.]]>\n    \nthis is what's keeping me up at night these days...\n\n\ngoogle has become unusable. once you get used to \"deep research\" (thanks grok, perplexity etc), google feels like bringing a typewriter to a macbook meeting.\n\nMCP will do for ai agents what REST did for web services - this standard protocol means an ai agent built for healthcare can instantly talk to billing systems, patient records, and insurance databases without custom code, unlocking thousands of new startup opportunities. it's really exciting! \n\nwe're seeing the entire cost structure of building businesses collapse -  you can now build profitable companies serving tiny, weird niches that were impossible to reach when you needed a full team. what used to need 1000 customers to break even now needs 10.\n\nit's not too late to be a creator or build a media business. creators are evolving into the new holding companies, consolidating influence, revenue streams, and audiences in ways that mirror corporate giants. somehow it's still early\n\nreally big arbitrage opportunity to buy businesses without taste and add taste. \"taste private equity\" has a nice ring to it.\n\nfiguring out LLM seo. billions of dollars will flow to new players who figure out how to get \"cited\" by LLMs. finally.\n\nmost ai apps are designed for websites not mobile. ai-first consumer mobile is really interesting. we saw with cal ai and the looksmaxing apps, that this is just the beginning.\n\nevery product launch needs video now - i'm watching great features die on landing pages while quick screen recordings go viral and drive thousands of signups. the social feeds have spoken.\n\nwhat used to require millions in vc funding now needs an api key, some prompts and a tweet. this fires me up!!\n\nfaster than ever to launch something of quality. faster than ever to pivot. knowing when to pivot is an art.\n\ni dont understand anyone who sitting in business school right now. literally everything is being rewritten.\n\nwho is building the app store for ai agents? companies will browse and hire pre-trained, specialized agents like we download apps\n\nthe way to stop a big player to compete with you in this new world is to own distribution.\n\nyou can spend a lot of time thinking about politics or checking emails or on social in the name of research, but not really moving forward anywhere.\n\nwe're about to see software companies capture value that used to belong to agencies, consulting firms, and entire departments. \n\nwe're about to go from \"there's an app for that\" to \"there's your app for that.\n\nminimum viable audience is more important than minimum viable product\n\nI don't know how long this window stays open, but we're in a moment where all the rules of building businesses are being rewritten. and for the people who are playing with this new tools, putting stuff out there, creating audiences/communities, you've got an unfair advantage.\ni hope you get some sleep.]]>\n  \n  \n    It\u2019s Time to Build: Healthtech Infrastructure\n    https://a16z.com/its-time-to-build-healthtech-infrastructure/?utm_medium=email&utm_source=newsletter&mkt_tok=MzgyLUpaQi03OTgAAAGYwyDUAidMj3QmQbPivKgDu_DLt8Q8Y0D5Zr-viCwdDrlPia4DX016BGz3T-TYTgcL9bA2_oWv_1hpKJH-CNeed5yTpigHJ6BZeZLhCDT2rIBQ\n    readwise:01jmj41h6nvp4w8and9ap2nwm0\n    Thu, 20 Feb 2025 16:46:19 +0000\n    Andreessen Horowitz\n    In the \u201cMaslow\u2019s hierarchy\u201d of the healthcare industry\u2019s needs, the infrastructure layer is the foundational workhorse of the system. Healthtech infrastructure refers to the utilities and systems-of-record that underpin all of the core operational transactions, financial transactions, data exchange, and interoperability actions that occur across the healthcare system everyday. Appointment booking? Powered by a practice management system. Claims processing? Powered by a clearinghouse. Purchasing Medicare Advantage health insurance? Powered by an underwriting and enrollment engine. These are examples of infrastructure systems underlying the healthcare experiences we encounter in our everyday lives, let alone all that happens behind the scenes to make the healthcare system go \u2018round on a regular basis.\n\n\n\n.\n\nThis post largely focuses on healthtech infrastructure companies that relate to payor and provider operations, all of which ultimately impact how consumers access, pay for, and experience the healthcare system. The figure below (though certainly not comprehensive) illustrates some of the major categories of established, legacy healthtech infrastructure companies that have achieved at least $1 billion of enterprise value.\n\n\n\nThe healthcare industry has faced a number of significant (and unfortunate) outage events 1 in recent years that shed light on the scale, complexity, and fragility of some of the core, but often legacy, infrastructure systems on which the industry relies. Emerging business models (e.g. value-based care, consumers as payors) and novel care delivery models (e.g. virtual care, home-based care, remote patient monitoring) have also elucidated zones of the market where systematic technology infrastructure doesn\u2019t even exist yet. These areas represent major company building opportunities, and also some of the strongest business models, as we\u2019ll describe below.\n\nThe healthtech infrastructure greats\n\nMany of the largest and most important companies in the history of healthcare technology and services have been infrastructure companies \u2013 in fact, the companies denoted in the figure above 2 collectively represent at least ~$160 billion in enterprise value as of December 2024, and did a collective ~$60 billion in revenue in 2023.\n\nBut most are built on legacy, last-generation technologies (or aren\u2019t even technology businesses to begin with) \u2014 for instance, many don\u2019t have APIs (application programming interfaces), so integration requires proverbial duct tape in the form of manual labor or asynchronous data exchange modalities, e.g. asynchronous file sharing, phone calls, faxes. Much of the inefficiency and friction experienced by providers and consumers as they perform their jobs and interact with the healthcare system, respectively, can be linked back to those deficiencies \u2014 e.g. the difficulty in knowing what a service will cost, the lack of on-demand access to one\u2019s comprehensive medical records, or the challenges surrounding booking appointments in a timely manner.\n\nWhat makes them great?\n\nSuccessful infrastructure companies tend to exhibit a number of characteristics, such as:\n\n \nSitting at a high-volume transaction node in the industry (e.g. Change Healthcare processes 15 billion operational and financial transactions annually) \nSitting in or being closely tied into the payments flow \nServing as connective tissue between 2 or more stakeholders in the industry (e.g. many of the players depicted above facilitate connectivity between payors and providers) \nServing as a core system of record \nExhibiting network effects \n\nWhat\u2019s compelling about a strong infrastructure company is that it can behave like an index on a large, high-growth segment of the market. For instance, as overall utilization of behavioral healthcare services grows, revenue cycle companies that serve behavioral health providers also grow, since they are tethered to claims and payment volumes in that space. Great infrastructure companies also tend to achieve ubiquity \u2014 the most successful infrastructure companies are seemingly embedded everywhere, despite not necessarily being an end-user-facing product, e.g. Surescripts, Epic, Change, UKG/Kronos.\n\nHealthtech infrastructure companies also have the potential to be high gross margin businesses, since they can essentially be software businesses, if built in a tech-native manner that embraces automation and interoperability. Even the more services-heavy legacy infrastructure players often exhibit 60-70% gross margins, because they\u2019re able to capture significant value by serving as mission-critical utilities.\n\nBut not all infrastructure companies are created equal \u2014 in order to succeed, they do need to pick a sufficiently \u201chigh heft\u201d node of the ecosystem to which to tether itself, and have a product surface area big enough to be able to capture enough value and have enough growth potential to make it VC-backable. These companies also typically require a two-sided network motion to be built over time, and thus may require more time and capital to unleash the full potential of the platform.\n\nOpportunities for company building\n\nFor builders, opportunities exist to either:\n\na) massively upgrade existing areas of the infrastructure stack, or\n\nb) build de novo utilities and backend systems in emerging areas of the market where infrastructure doesn\u2019t yet exist.\n\nIn the former category, we acknowledge that it can be very non-trivial to unseat a legacy, entrenched player in such mission-critical areas of transactional flow, especially those that have been ossified over decades. But a handful of the companies (all worth at least $1 billion) depicted in the map above were born in the last 20 years, demonstrating that it\u2019s possible to break in and get to significant scale in a reasonable amount of time, especially if able to leverage investment capital to achieve higher growth rates than those legacy players, which were generally either private equity-backed or bootstrapped.\n\nIn the latter category, some whitespace opportunities for infrastructure builders include:\n\n \nClinical interoperability \u2013 most mature interoperability systems focus on administrative and financial data exchange, but clinical data exchange is an emerging area of activity; this space has significant regulatory tailwinds that are propelling the emergence of clinical data-oriented interoperability engines, poised to create a new layer of interchange between stakeholders in the system (including consumers), as well as more clinical context embedded in other legacy workflows. \nVBC enablement \u2013 while payors have established core competencies in taking and managing risk, more risk is being delegated to providers, who lack those capabilities as tuned for the provider-based setting. New payment models (e.g. GUIDE) also require novel infrastructure to administer. \nVirtual care provider networks \u2013 the composition of provider networks now includes virtual medical groups, home- and community- based care providers, and remote patient monitoring programs, all of which require new rails for network contracting and clinical program administration. \nNovel benefits and payments \u2013 new payment mechanisms for healthcare products (e.g. cell and gene therapies, preventative interventions) and services (e.g. ICHRA, BNPL) require new infrastructure to operate. \n\nThese whitespace opportunities correlate with the 5 bottom-up market forces described in \u201cThe Coming Healthcare Revolution,\u201d which represent the ongoing shifts towards novel care models, novel payment models, new sites of care, platform consolidation, and emergent care provider types that are pushing the boundaries of the status quo definition of the \u201chealthcare system,\u201d and that require new infrastructure to operate. As we\u2019ve talked about, most, if not all, of these categories are also enabled by regulatory tailwinds of some sort.\n\n\n\nThe combination of a) the mission-critical nature of infrastructure to the healthcare industry, b) the scale of the healthtech infrastructure market, c) the attractiveness of the high-quality business models that can be built in healthtech infrastructure, and d) the fact that most infrastructure systems are aging and fragile, or non-existent in emerging areas that also have regulatory tailwinds, make this is a compelling time to build a healthtech infrastructure company. Those conditions also intersect with our commentary on leveraging AI for infrastructure use cases to achieve 10x better performance and operational efficiency, which can be how upstarts gain a competitive advantage relative to entrenched incumbents. We believe these motions could result in the creation of an infrastructure business that could ultimately become the biggest company in the world.\n\nHealthtech infrastructure canon\n\nHealthtech infrastructure\n\n \nConsumers as a New Class of Payor \nGrand Challenges in Healthcare AI \nThe New Drug Delivery Challenge: How Will Cures Reach Patients? \nWhen Two Giants Intersect: Healthcare Meets Fintech \nHealthcare Marketplaces, Where Art Thou? \nHealthcare x Fintech\u2019s Biggest Prize: The Financial OS of Healthcare \nConsumer Health: Areas of Opportunity \nPayvidors, Unbundled: Opportunities in Healthcare Fintech \nThe New Tech Stack for Virtual-First Care \n\nDigital health builders diaries\n\n \nSuperstaffing in Healthcare with Hippocratic AI \nHealth Benefits 2.0: Tailored to a Mobile Workforce \nLessons from Healthcare Infrastructure Pioneers with Jeff Margolis, Founding CEO of TriZetto \nRegulation as a Catalyst for Company Creation in Healthcare \nThe Most Interesting Healthcare Platform Companies You\u2019ve Never Heard of, with Julie Klapstein \nBuilding an AI-Native Health Plan with Mario Schlosser \nPutting the \u201cPro\u201d in Provider Networks, With Dan Rosenthal \n\nThanks to Daisy Wolf, Jay Rughani, and Jen Walsh for their contributions to this piece. We\u2019re deeply appreciative to the numerous experts who reviewed, commented on, and contributed to this piece, including: Dan Rosenthal, Julie Klapstein, Margaret McKenna, Himanshu Arora, Sid Bothra, and Ed Park. \n\nSources\n\n \n  1 Change Healthcare outage in 2024; Crowdstrike outage in 2024; Oracle database outage that brought down VA EHR in 2022; Surescripts outage in 2022  \n  2 Based on a16z research and data from Pitchbook and public stocks  \n\nWant more a16z Bio + Health?\n\nSign up for our bio + health newsletter to get the latest take from us on the future of biology, technology, and care delivery.\n\nMANAGE MY SUBSCRIPTIONS By clicking the Subscribe button, you agree to the Privacy Policy.\n\nContributor\n\n \n   \nJulie Yoo is a general partner on the Bio + Health team at Andreessen Horowitz, focused on transforming how we access, pay for, and experience healthcare.   \n \nFollow \nX \nLinkedin   \n\nMore From this Contributor\n\n \n  Super Staffing in Healthcare with Munjal Shah Munjal Shah, Julie Yoo, Kris Tatiossian, and Olivia Webb   \n  Lessons from Healthcare Infrastructure Pioneers with Jeff Margolis Julie Yoo, Jeff Margolis, Olivia Webb, and Kris Tatiossian   \n  The Freedom to Choose Your Own Insurance with Chris Ellis and Adam Stevenson Chris Ellis, Adam Stevenson, Jay Rughani, Julie Yoo, Kris Tatiossian, and Olivia Webb   \n  Investing in Alchemy Julie Yoo and Jay Rughani   \n\nThe views expressed here are those of the individual AH Capital Management, L.L.C. (\u201ca16z\u201d) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. In addition, this content may include third-party advertisements; a16z has not reviewed such advertisements and does not endorse any advertising content contained therein.\n\nThis content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments for which the issuer has not provided permission for a16z to disclose publicly as well as unannounced investments in publicly traded digital assets) is available at https://a16z.com/investments/.\n\nCharts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.]]>\n    In the \u201cMaslow\u2019s hierarchy\u201d of the healthcare industry\u2019s needs, the infrastructure layer is the foundational workhorse of the system. Healthtech infrastructure refers to the utilities and systems-of-record that underpin all of the core operational transactions, financial transactions, data exchange, and interoperability actions that occur across the healthcare system everyday. Appointment booking? Powered by a practice management system. Claims processing? Powered by a clearinghouse. Purchasing Medicare Advantage health insurance? Powered by an underwriting and enrollment engine. These are examples of infrastructure systems underlying the healthcare experiences we encounter in our everyday lives, let alone all that happens behind the scenes to make the healthcare system go \u2018round on a regular basis.\n\n\n\n.\n\nThis post largely focuses on healthtech infrastructure companies that relate to payor and provider operations, all of which ultimately impact how consumers access, pay for, and experience the healthcare system. The figure below (though certainly not comprehensive) illustrates some of the major categories of established, legacy healthtech infrastructure companies that have achieved at least $1 billion of enterprise value.\n\n\n\nThe healthcare industry has faced a number of significant (and unfortunate) outage events 1 in recent years that shed light on the scale, complexity, and fragility of some of the core, but often legacy, infrastructure systems on which the industry relies. Emerging business models (e.g. value-based care, consumers as payors) and novel care delivery models (e.g. virtual care, home-based care, remote patient monitoring) have also elucidated zones of the market where systematic technology infrastructure doesn\u2019t even exist yet. These areas represent major company building opportunities, and also some of the strongest business models, as we\u2019ll describe below.\n\nThe healthtech infrastructure greats\n\nMany of the largest and most important companies in the history of healthcare technology and services have been infrastructure companies \u2013 in fact, the companies denoted in the figure above 2 collectively represent at least ~$160 billion in enterprise value as of December 2024, and did a collective ~$60 billion in revenue in 2023.\n\nBut most are built on legacy, last-generation technologies (or aren\u2019t even technology businesses to begin with) \u2014 for instance, many don\u2019t have APIs (application programming interfaces), so integration requires proverbial duct tape in the form of manual labor or asynchronous data exchange modalities, e.g. asynchronous file sharing, phone calls, faxes. Much of the inefficiency and friction experienced by providers and consumers as they perform their jobs and interact with the healthcare system, respectively, can be linked back to those deficiencies \u2014 e.g. the difficulty in knowing what a service will cost, the lack of on-demand access to one\u2019s comprehensive medical records, or the challenges surrounding booking appointments in a timely manner.\n\nWhat makes them great?\n\nSuccessful infrastructure companies tend to exhibit a number of characteristics, such as:\n\n \nSitting at a high-volume transaction node in the industry (e.g. Change Healthcare processes 15 billion operational and financial transactions annually) \nSitting in or being closely tied into the payments flow \nServing as connective tissue between 2 or more stakeholders in the industry (e.g. many of the players depicted above facilitate connectivity between payors and providers) \nServing as a core system of record \nExhibiting network effects \n\nWhat\u2019s compelling about a strong infrastructure company is that it can behave like an index on a large, high-growth segment of the market. For instance, as overall utilization of behavioral healthcare services grows, revenue cycle companies that serve behavioral health providers also grow, since they are tethered to claims and payment volumes in that space. Great infrastructure companies also tend to achieve ubiquity \u2014 the most successful infrastructure companies are seemingly embedded everywhere, despite not necessarily being an end-user-facing product, e.g. Surescripts, Epic, Change, UKG/Kronos.\n\nHealthtech infrastructure companies also have the potential to be high gross margin businesses, since they can essentially be software businesses, if built in a tech-native manner that embraces automation and interoperability. Even the more services-heavy legacy infrastructure players often exhibit 60-70% gross margins, because they\u2019re able to capture significant value by serving as mission-critical utilities.\n\nBut not all infrastructure companies are created equal \u2014 in order to succeed, they do need to pick a sufficiently \u201chigh heft\u201d node of the ecosystem to which to tether itself, and have a product surface area big enough to be able to capture enough value and have enough growth potential to make it VC-backable. These companies also typically require a two-sided network motion to be built over time, and thus may require more time and capital to unleash the full potential of the platform.\n\nOpportunities for company building\n\nFor builders, opportunities exist to either:\n\na) massively upgrade existing areas of the infrastructure stack, or\n\nb) build de novo utilities and backend systems in emerging areas of the market where infrastructure doesn\u2019t yet exist.\n\nIn the former category, we acknowledge that it can be very non-trivial to unseat a legacy, entrenched player in such mission-critical areas of transactional flow, especially those that have been ossified over decades. But a handful of the companies (all worth at least $1 billion) depicted in the map above were born in the last 20 years, demonstrating that it\u2019s possible to break in and get to significant scale in a reasonable amount of time, especially if able to leverage investment capital to achieve higher growth rates than those legacy players, which were generally either private equity-backed or bootstrapped.\n\nIn the latter category, some whitespace opportunities for infrastructure builders include:\n\n \nClinical interoperability \u2013 most mature interoperability systems focus on administrative and financial data exchange, but clinical data exchange is an emerging area of activity; this space has significant regulatory tailwinds that are propelling the emergence of clinical data-oriented interoperability engines, poised to create a new layer of interchange between stakeholders in the system (including consumers), as well as more clinical context embedded in other legacy workflows. \nVBC enablement \u2013 while payors have established core competencies in taking and managing risk, more risk is being delegated to providers, who lack those capabilities as tuned for the provider-based setting. New payment models (e.g. GUIDE) also require novel infrastructure to administer. \nVirtual care provider networks \u2013 the composition of provider networks now includes virtual medical groups, home- and community- based care providers, and remote patient monitoring programs, all of which require new rails for network contracting and clinical program administration. \nNovel benefits and payments \u2013 new payment mechanisms for healthcare products (e.g. cell and gene therapies, preventative interventions) and services (e.g. ICHRA, BNPL) require new infrastructure to operate. \n\nThese whitespace opportunities correlate with the 5 bottom-up market forces described in \u201cThe Coming Healthcare Revolution,\u201d which represent the ongoing shifts towards novel care models, novel payment models, new sites of care, platform consolidation, and emergent care provider types that are pushing the boundaries of the status quo definition of the \u201chealthcare system,\u201d and that require new infrastructure to operate. As we\u2019ve talked about, most, if not all, of these categories are also enabled by regulatory tailwinds of some sort.\n\n\n\nThe combination of a) the mission-critical nature of infrastructure to the healthcare industry, b) the scale of the healthtech infrastructure market, c) the attractiveness of the high-quality business models that can be built in healthtech infrastructure, and d) the fact that most infrastructure systems are aging and fragile, or non-existent in emerging areas that also have regulatory tailwinds, make this is a compelling time to build a healthtech infrastructure company. Those conditions also intersect with our commentary on leveraging AI for infrastructure use cases to achieve 10x better performance and operational efficiency, which can be how upstarts gain a competitive advantage relative to entrenched incumbents. We believe these motions could result in the creation of an infrastructure business that could ultimately become the biggest company in the world.\n\nHealthtech infrastructure canon\n\nHealthtech infrastructure\n\n \nConsumers as a New Class of Payor \nGrand Challenges in Healthcare AI \nThe New Drug Delivery Challenge: How Will Cures Reach Patients? \nWhen Two Giants Intersect: Healthcare Meets Fintech \nHealthcare Marketplaces, Where Art Thou? \nHealthcare x Fintech\u2019s Biggest Prize: The Financial OS of Healthcare \nConsumer Health: Areas of Opportunity \nPayvidors, Unbundled: Opportunities in Healthcare Fintech \nThe New Tech Stack for Virtual-First Care \n\nDigital health builders diaries\n\n \nSuperstaffing in Healthcare with Hippocratic AI \nHealth Benefits 2.0: Tailored to a Mobile Workforce \nLessons from Healthcare Infrastructure Pioneers with Jeff Margolis, Founding CEO of TriZetto \nRegulation as a Catalyst for Company Creation in Healthcare \nThe Most Interesting Healthcare Platform Companies You\u2019ve Never Heard of, with Julie Klapstein \nBuilding an AI-Native Health Plan with Mario Schlosser \nPutting the \u201cPro\u201d in Provider Networks, With Dan Rosenthal \n\nThanks to Daisy Wolf, Jay Rughani, and Jen Walsh for their contributions to this piece. We\u2019re deeply appreciative to the numerous experts who reviewed, commented on, and contributed to this piece, including: Dan Rosenthal, Julie Klapstein, Margaret McKenna, Himanshu Arora, Sid Bothra, and Ed Park. \n\nSources\n\n \n  1 Change Healthcare outage in 2024; Crowdstrike outage in 2024; Oracle database outage that brought down VA EHR in 2022; Surescripts outage in 2022  \n  2 Based on a16z research and data from Pitchbook and public stocks  \n\nWant more a16z Bio + Health?\n\nSign up for our bio + health newsletter to get the latest take from us on the future of biology, technology, and care delivery.\n\nMANAGE MY SUBSCRIPTIONS By clicking the Subscribe button, you agree to the Privacy Policy.\n\nContributor\n\n \n   \nJulie Yoo is a general partner on the Bio + Health team at Andreessen Horowitz, focused on transforming how we access, pay for, and experience healthcare.   \n \nFollow \nX \nLinkedin   \n\nMore From this Contributor\n\n \n  Super Staffing in Healthcare with Munjal Shah Munjal Shah, Julie Yoo, Kris Tatiossian, and Olivia Webb   \n  Lessons from Healthcare Infrastructure Pioneers with Jeff Margolis Julie Yoo, Jeff Margolis, Olivia Webb, and Kris Tatiossian   \n  The Freedom to Choose Your Own Insurance with Chris Ellis and Adam Stevenson Chris Ellis, Adam Stevenson, Jay Rughani, Julie Yoo, Kris Tatiossian, and Olivia Webb   \n  Investing in Alchemy Julie Yoo and Jay Rughani   \n\nThe views expressed here are those of the individual AH Capital Management, L.L.C. (\u201ca16z\u201d) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. In addition, this content may include third-party advertisements; a16z has not reviewed such advertisements and does not endorse any advertising content contained therein.\n\nThis content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments for which the issuer has not provided permission for a16z to disclose publicly as well as unannounced investments in publicly traded digital assets) is available at https://a16z.com/investments/.\n\nCharts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.]]>\n  \n  \n    AI or Die\n    https://www.rkg.blog/ai-or-die.php\n    readwise:01jmf28exvxg9c7sz57jgkrf7r\n    Wed, 19 Feb 2025 12:17:25 +0000\n    rkg.blog\n     \nAbout \nAI or Die \nContradictions \nGlue Guys \nDemanding and Supportive \nThe Confrontation Obligation \nFriendship \nGetting Better at Getting Better \nThank you, Instacart \nFlowers & Leadership \nThe Real Competition is the Water \nPlay for the Front of the Jersey \nHiring: Why More is Often Less \nA Chance to Become Anti-Fragile \nYou Are What Your Record Says You Are \nSadness & Gratitude & Basketball \nDesperation-Induced Focus \nJoy & Competitiveness & Culture \nEnthusiastically Rehiring \nWriting \n\n\u201cYou cannot overtake fifteen cars in sunny weather. But you can when it\u2019s raining.\u201d \u2014Formula One driver Ayrton Senna\n\nDid you read Dario\u2019s Amodei\u2019s (founder/CEO of Anthropic) post from late last year? This is what he suggested might be available from AI models, as early as 2026. The quote is long, but it\u2019s worth reading in full.1\n\n\u201cI have in mind an AI model\u2014likely similar to today\u2019s LLMs in form, though it might be based on a different architecture, might involve several interacting models, and might be trained differently\u2014with the following properties:\n\nIn terms of pure intelligence, it is smarter than a Nobel Prize winner across most relevant fields \u2013 biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc.\n\nIn addition to just being a \u2018smart thing you talk to\u2019, it has all the \u2018interfaces\u2019 available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. \n\nIt can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world.\n\nIt does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary\u2026\n\nThe resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed. It may however be limited by the response time of the physical world or of software it interacts with.\n\nEach of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks.\n\nWe could summarize this as a \u2018country of geniuses in a datacenter\u2019.\u201d\n\nA country of geniuses in a datacenter.\n\nIs your company positioned to take advantage of access to a country of geniuses in a datacenter?\n\nIs your company positioned to compete with the company that does take advantage of access to a country of geniuses in a datacenter?\n\nThe game on the field is about to change. The leaderboard in your industry is going to shift violently over the next few years.\n\nIf you have prepared your company for this, congratulations. You can stop reading.\n\nStill here? Great.\n\nWhat do you do now?\n\nThe first thing to do is to become much more familiar with what AI can do today. Most professionals think of AI as a cute chatbot that can replace wikipedia for them. They don\u2019t realize that it\u2019s already capable of being a virtual colleague and collaborator.\n\nOpenAI recently released Deep Research. This is what Sam Altman posted about it:\n\n\n\nA single-digit percentage of all economically valuable tasks in the world. In the world! Today! If Sam is right, the percentage of economically valuable tasks it can do in your company today is almost certainly higher. I don\u2019t know if that means it\u2019s 5% or 50%. (But I\u2019d find out if I were you.)\n\nSo, if the models are capable of all of this, what actually stops people from getting the most out of them?\n\n \n\nAmbition: Not enough people ask the model to help them with real work. They ask it to help them with drafting email or coming up with funny songs.  \n\nPatience: How much context are you willing to provide it to help you? How does it compare to the amount of context you would give a brilliant new hire who was joining your team? Is that the context you\u2019re giving to the models when you ask it to help you? Have you ever asked a model if it understands what you\u2019re asking it to do or if it has any clarifying questions? \n\nClarity of thought and communication: Spend some time sharpening the axe before you try to cut down the tree.2 \n\nI grant you that it\u2019s not easy to make AI a virtual colleague today. But that will change. Entire companies of brilliant people are working on bringing you virtual co-workers and ushering in the future that Dario describes.\n\nIt will happen sooner than you think.\n\nLet\u2019s say you agree with me. The virtual colleague and collaborator is here. The country of geniuses in a datacenter is coming. What should you do about it?\n\n \n\nTake a week off with the sole purpose of becoming more clear about what AI models can do now and where they are going.  \n\nImagine the AI-native version of your product that could be built with a team that is one-tenth or one-hundredth the size of yours. Build it (or buy the one that might have already sprouted up.) \n\nUnderstand that your customers are going to have dramatically higher expectations of you. They are going to expect a product that is dramatically better and dramatically cheaper than yours is today. If you don\u2019t believe me, think about what you believe your customer support will be like in a couple of years. I bet you think it\u2019s available all the time with someone friendly and knowledgeable, at a fraction of the price. This improvement distance you expect your customer support team to travel is the same distance your customers are going to expect you to travel. \n\nEarn the right to be the AI strategy for your customers. This is much much much harder than it seems\u2026but also much much much more lucrative than you might expect.  \n\nBecome an AI-first company. There is a great story about Mark Zuckerberg refusing to look at desktop mocks when the world started shifting to mobile. What is your equivalent of that for AI? How can you show your team you are serious about transforming the team around an AI future?  \n\nGo person by person in your company and figure out who is going to be augmented by AI agents, and what roles are going to be replaced by them. For those that are going to be augmented by the AI agents, tell them that their status as \u201chigh-performer\u201d depends on their ability to leverage the new technology.  \n\nThese are not tweaks or subtle changes. This is not adding a slide in the board deck about how you are using AI.\n\nWinning in this new world requires a full \u201cre-founding\u201d of your company.\n\nThis is neither simple nor safe. It is indescribably hard to re-found a company. In fact, in many ways, the bigger and more successful your company is today, the harder this will be.\n\nBut as my wife and I tell our sons\u2026we don\u2019t always get to choose what happens. But we do get to choose how we respond.\n\nWith that in mind, go back and read Dario\u2019s quote again. And then read this from Sam Altman about AGI and what it means. Because I\u2019ve already assigned you a fair amount of reading today, I\u2019ll give you a quote that sums up Sam\u2019s post pretty well in case you don\u2019t read the whole thing:\n\n\u201cIn a decade, perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today.\u201d\n\nWow.\n\nIt\u2019s the most inspiring future that one could imagine.\n\nIt\u2019s also the most challenging one to prepare for. Whatever industry you are in, the weather is changing. And when the rain comes, there\u2019s going to be a lot of passing going on.\n\nWhere you end up in that race is up to you.\n\nWhatever your views on valuations for foundation model companies, you\u2019d be a fool not to pay attention to what Dario says about AI.\n\n\u201cGive me six hours to cut down a tree and I will spend four sharpening the axe.\u201d - Abraham Lincoln]]>\n     \nAbout \nAI or Die \nContradictions \nGlue Guys \nDemanding and Supportive \nThe Confrontation Obligation \nFriendship \nGetting Better at Getting Better \nThank you, Instacart \nFlowers & Leadership \nThe Real Competition is the Water \nPlay for the Front of the Jersey \nHiring: Why More is Often Less \nA Chance to Become Anti-Fragile \nYou Are What Your Record Says You Are \nSadness & Gratitude & Basketball \nDesperation-Induced Focus \nJoy & Competitiveness & Culture \nEnthusiastically Rehiring \nWriting \n\n\u201cYou cannot overtake fifteen cars in sunny weather. But you can when it\u2019s raining.\u201d \u2014Formula One driver Ayrton Senna\n\nDid you read Dario\u2019s Amodei\u2019s (founder/CEO of Anthropic) post from late last year? This is what he suggested might be available from AI models, as early as 2026. The quote is long, but it\u2019s worth reading in full.1\n\n\u201cI have in mind an AI model\u2014likely similar to today\u2019s LLMs in form, though it might be based on a different architecture, might involve several interacting models, and might be trained differently\u2014with the following properties:\n\nIn terms of pure intelligence, it is smarter than a Nobel Prize winner across most relevant fields \u2013 biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc.\n\nIn addition to just being a \u2018smart thing you talk to\u2019, it has all the \u2018interfaces\u2019 available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. \n\nIt can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world.\n\nIt does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary\u2026\n\nThe resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed. It may however be limited by the response time of the physical world or of software it interacts with.\n\nEach of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks.\n\nWe could summarize this as a \u2018country of geniuses in a datacenter\u2019.\u201d\n\nA country of geniuses in a datacenter.\n\nIs your company positioned to take advantage of access to a country of geniuses in a datacenter?\n\nIs your company positioned to compete with the company that does take advantage of access to a country of geniuses in a datacenter?\n\nThe game on the field is about to change. The leaderboard in your industry is going to shift violently over the next few years.\n\nIf you have prepared your company for this, congratulations. You can stop reading.\n\nStill here? Great.\n\nWhat do you do now?\n\nThe first thing to do is to become much more familiar with what AI can do today. Most professionals think of AI as a cute chatbot that can replace wikipedia for them. They don\u2019t realize that it\u2019s already capable of being a virtual colleague and collaborator.\n\nOpenAI recently released Deep Research. This is what Sam Altman posted about it:\n\n\n\nA single-digit percentage of all economically valuable tasks in the world. In the world! Today! If Sam is right, the percentage of economically valuable tasks it can do in your company today is almost certainly higher. I don\u2019t know if that means it\u2019s 5% or 50%. (But I\u2019d find out if I were you.)\n\nSo, if the models are capable of all of this, what actually stops people from getting the most out of them?\n\n \n\nAmbition: Not enough people ask the model to help them with real work. They ask it to help them with drafting email or coming up with funny songs.  \n\nPatience: How much context are you willing to provide it to help you? How does it compare to the amount of context you would give a brilliant new hire who was joining your team? Is that the context you\u2019re giving to the models when you ask it to help you? Have you ever asked a model if it understands what you\u2019re asking it to do or if it has any clarifying questions? \n\nClarity of thought and communication: Spend some time sharpening the axe before you try to cut down the tree.2 \n\nI grant you that it\u2019s not easy to make AI a virtual colleague today. But that will change. Entire companies of brilliant people are working on bringing you virtual co-workers and ushering in the future that Dario describes.\n\nIt will happen sooner than you think.\n\nLet\u2019s say you agree with me. The virtual colleague and collaborator is here. The country of geniuses in a datacenter is coming. What should you do about it?\n\n \n\nTake a week off with the sole purpose of becoming more clear about what AI models can do now and where they are going.  \n\nImagine the AI-native version of your product that could be built with a team that is one-tenth or one-hundredth the size of yours. Build it (or buy the one that might have already sprouted up.) \n\nUnderstand that your customers are going to have dramatically higher expectations of you. They are going to expect a product that is dramatically better and dramatically cheaper than yours is today. If you don\u2019t believe me, think about what you believe your customer support will be like in a couple of years. I bet you think it\u2019s available all the time with someone friendly and knowledgeable, at a fraction of the price. This improvement distance you expect your customer support team to travel is the same distance your customers are going to expect you to travel. \n\nEarn the right to be the AI strategy for your customers. This is much much much harder than it seems\u2026but also much much much more lucrative than you might expect.  \n\nBecome an AI-first company. There is a great story about Mark Zuckerberg refusing to look at desktop mocks when the world started shifting to mobile. What is your equivalent of that for AI? How can you show your team you are serious about transforming the team around an AI future?  \n\nGo person by person in your company and figure out who is going to be augmented by AI agents, and what roles are going to be replaced by them. For those that are going to be augmented by the AI agents, tell them that their status as \u201chigh-performer\u201d depends on their ability to leverage the new technology.  \n\nThese are not tweaks or subtle changes. This is not adding a slide in the board deck about how you are using AI.\n\nWinning in this new world requires a full \u201cre-founding\u201d of your company.\n\nThis is neither simple nor safe. It is indescribably hard to re-found a company. In fact, in many ways, the bigger and more successful your company is today, the harder this will be.\n\nBut as my wife and I tell our sons\u2026we don\u2019t always get to choose what happens. But we do get to choose how we respond.\n\nWith that in mind, go back and read Dario\u2019s quote again. And then read this from Sam Altman about AGI and what it means. Because I\u2019ve already assigned you a fair amount of reading today, I\u2019ll give you a quote that sums up Sam\u2019s post pretty well in case you don\u2019t read the whole thing:\n\n\u201cIn a decade, perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today.\u201d\n\nWow.\n\nIt\u2019s the most inspiring future that one could imagine.\n\nIt\u2019s also the most challenging one to prepare for. Whatever industry you are in, the weather is changing. And when the rain comes, there\u2019s going to be a lot of passing going on.\n\nWhere you end up in that race is up to you.\n\nWhatever your views on valuations for foundation model companies, you\u2019d be a fool not to pay attention to what Dario says about AI.\n\n\u201cGive me six hours to cut down a tree and I will spend four sharpening the axe.\u201d - Abraham Lincoln]]>\n  \n  \n    Trump and the Perils of Ungoverning\n    https://www.foreignaffairs.com/united-states/trump-and-perils-ungoverning?utm_campaign=tw&utm_content=&utm_medium=social&utm_source=twitter\n    readwise:01jmf12ygk4cn8ga6ckqdgx7hd\n    Wed, 19 Feb 2025 11:56:56 +0000\n    Foreign Affairs\n    \nOutside the White House on inauguration day, Washington, D.C., January 2025 Nathan Howard / Reuters \n\n\n\n\n\n\n\n\n\nAs U.S. President Donald Trump returns to the White House, it already seems clear that his second term will look little like his first. Many of Trump\u2019s first-term appointments distanced themselves from his views and even denounced him. \u201cI picked some people I shouldn\u2019t have picked,\u201d Trump lamented on Joe Rogan\u2019s podcast last November. \u201cDisloyal people.\u201d This time, Trump is ready. The president and his allies are convinced that he was let down in his first term by those around him and by the bureaucracy of the federal government. They will not let that happen again.\n\nOn his first day in office, Trump restored Schedule F, an employment category that he had created in the closing months of his first term that strips civil servants of protections, allowing them to be fired at will. Trump has convinced many of his followers that a \u201cdeep state\u201d thwarted his first term and robbed him of the 2020 election. Now, the putative deep state will be expunged, along with the expertise and procedures that make effective administration possible. Trump will judge both appointees and civil servants by one criterion: loyalty, defined not by commitment to a programmatic agenda but by unquestioning obedience to the president.\n\nAccording to reporting by The New York Times, the administration\u2019s transition team has been asking applicants for government posts in multiple agencies, including in the intelligence services and the Department of Defense, about their views on the events of the January 6 attacks on the U.S. Capitol. And they have asked applicants pointedly about the 2020 presidential election. Those who condemn the attack or believe that Biden won the race appear unlikely to receive posts.\n\nStaffing the federal government with sycophants is not about ensuring loyalty to an agenda. It is about ensuring submission to the president. And it serves to amplify what we call \u201cungoverning\u201d: the degradation of state capacity and the substitution of unchecked personal will for the difficult, necessary business of shaping, implementing, and assessing policy for the nation. The administration will sideline experts and circumvent regular processes of information gathering and consultation. In so doing, it will degrade state capacity; the premium Trump places on personal loyalty will result in confounding his ability to govern.\n\nUngoverning is radical and rare in the annals of political history. There are simply not that many examples of states that have been systematically degraded and dismantled by individual rulers or parties. In some cases, those in power manage to substitute kleptocracy and state violence for administration; for instance, in Venezuela, where first Hugo Ch\u00e1vez and then Nicol\u00e1s Maduro destroyed a prosperous and functioning state.\n\nIn the United States, ungoverning\u2014which is distinct from conservative small government and from deregulation and privatization\u2014is novel. Critics on both sides of the aisle have tried to cut through bureaucratic red tape in the past, but historically, officials of both parties and the general public have accepted the administrative state as indispensable to the fulfillment of public needs.\n\nThe question now is whether those around Trump will work to check his appetite for ungoverning. As subject-specific experts are replaced by flatterers, the government\u2019s ability to achieve lasting, large-scale results shrinks. As process is shunted aside in favor of one person\u2019s will, the state\u2019s ability to gather accurate information and make effective judgments corrodes; its capacity to design, refine, and implement policy disappears. Ultimately, ungoverning makes the strongman weak.\n\nLOYALTY OVER CAPABILITY\n\nAt the heart of democratic governance\u2014and the office of the presidency\u2014is the idea of administration. The institutions and scope of the current administrative state can be traced to the New Deal era of President Franklin Roosevelt. But the importance of building a state with administrative capacity goes back to the country\u2019s founding. When opponents of the Constitution insisted that state governments would be closer to the people\u2014and more loved by them\u2014than any government operating on a national scale, Alexander Hamilton, the first secretary of the treasury, responded that the aim of the government was not to reflect the passions of local majorities but to practice good administration.\n\nA state with administrative capacity pursues its goals by first systematically and accurately gathering information on current conditions\u2014as Hamilton tried to do on the national economy in his 1791 \u201cReport on Manufactures\u201d and as the Bureau of Labor Statistics and every other agency does now. The next step is to envision a future that is more prosperous, freer, and more secure. And, finally, to design a plan for applying resources, on a large scale and over a long period, to bring that future into being. The administrative state shapes, implements, and enforces every law passed by Congress and every executive order made by the president. As Hamilton wrote in Federalist, no. 72 (of The Federalist Papers), \u201cthe administration of government, in the largest sense, comprehends all the operations of the body politic.\u201d\n\nThe machinery of government that Trump now inherits comprises about 4,000 political appointees and three million public servants who respond to natural disasters and military emergencies, pursue long-term goals set by Congress and the president, and do much else. For Trump, the problem with expertise and process is that they limit the scope and constrain the exercise of his power. Specialized knowledge is a source of authority, as Trump knows, which is why he cannot bear to stand alongside a knowledgeable official, even one of his own appointees, without asserting his own superior expertise. At a press briefing during the COVID-19 pandemic, he suggested to Deborah Birx, the White House coronavirus response coordinator, that irradiating COVID-19 patients\u2019 bodies with ultraviolet light and injections of disinfectant might offer a cure. \u201cI\u2019m not a doctor,\u201d the president said, pointing to his head. \u201cBut I\u2019m a person that has a good you-know-what.\u201d\n\nTrump expects that selecting for loyalty will allow him to govern more effectively in the second term, to push through his agenda. But in truth, prioritizing loyalty over capability will undermine his administration. Unless he is able to yield to the expertise of his appointees and civil servants, his own policy aims will be frustrated. Trump\u2019s problem is not that he requires loyalty to his agenda, on tariffs, on immigration, on foreign policy. It is that he demands personal loyalty\u2014or what John Bolton, Trump\u2019s longest-serving national security adviser in his first term, has called \u201cfealty, a medieval concept implying not mere loyalty but submission.\u201d\n\nADMINISTRATION DEGRADATION\n\nTo be sure, some of Trump\u2019s cabinet picks are loyal primarily to his program. Take his new border czar, Tom Homan, a former border patrol agent who served as head of the Immigration and Customs Enforcement deportation branch under President Barack Obama and acting director of the agency under Trump. \u201cI\u2019ve seen hundreds of policies come and go,\u201d he told The Wall Street Journal earlier this month. \u201cI know what policies worked and what policies don\u2019t work.\u201d He is devoted to Trump\u2019s immigration policies, but he has also met with Republican members of Congress to moderate expectations about the practicality of mass deportation. For those who support Trump\u2019s policies, this is the kind of appointment that promises to convert Trump\u2019s rhetoric into reality. For those who oppose Trump\u2019s policies, this is what makes Trump\u2019s second term more foreboding than the first.\n\nAn effective president has to find and empower people in the mold of Homan\u2014professionals with deep expertise capable of translating broad goals into workable policies and implementing them. This is what \u201cadministration\u201d means. But Trump\u2019s insistence on personal submission, and his distrust of the very administrative state he is charged with directing, is decidedly anti-administration. As Russell Vought, the prospective director of the Office of Management and Budget, has said: \u201cWe want the bureaucrats to be traumatically affected. When they wake up in the morning, we want them to not want to go to work because they are increasingly viewed as the villains.\u201d This is also the orientation of Kash Patel, Trump\u2019s nominee to head the FBI who last September promised to close the agency\u2019s Washington headquarters and convert it into a museum of the \u201cdeep state.\u201d\n\nThen there\u2019s the so-called Department of Government Efficiency, or DOGE\u2014helmed by the political newcomer Elon Musk. The electric car and spaceship mogul originally promised to cut at least $2 trillion from a federal budget of nearly $7 trillion, to lay off two million federal employees, and to slash thousands of regulations. To shrink the budget, civil service, and regulatory scope of government on this scale is an enormous task, and DOGE has recruited leaders from Silicon Valley to develop the plan. Staffed mostly by individuals with little or no experience in governance, DOGE will be unlikely to realize the massive restriction in the scope of the federal government that its founders promise. To do so would require both intimate knowledge of the federal budget, the work of federal agencies, and buy-in from a working coalition of legislators, not to mention the backing of the American public that may not be ready to accept a government that does vastly less than people are accustomed to.\n\n Ungoverning makes the strongman weak.\n\nIf Trump is to succeed in realizing the policies he espouses, his administration will need to make appointments on the basis of qualities more salient to effective governance than personal loyalty. Effective governance requires empowering public servants with experience and specialized knowledge. It means allowing for a process by which they can form and select from alternative policy options, detail plans for their implementation, and then act on those plans. It means staying true to clear goals so that appointees can advance the agenda without squandering time and talent kowtowing to the president.\n\nThose who oppose Trump\u2019s policies may welcome a chaotic anti-administration that cannot make good on the promise of mass deportation or across-the-board tariffs. But Trump will not oversee an administration that is simply ineffective. Rather he will orchestrate a comprehensive degradation of the administrative institutions of government\u2014the processes of decision-making and the consultation of expertise that effective policy of any sort requires. Instead of a government capable of policymaking and implementation, the U.S. government will revolve around the personal will of the president.\n\nGoverning is not about domination and submission. As Hamilton observed, it is about undertaking \u201cextensive and arduous enterprises for the public benefit, requiring considerable time to mature.\u201d The Biden administration aspired to this, as exemplified by the Infrastructure Investment and Jobs Act and the CHIPS and Science Act, both of which are massive, long-term projects that will take a generation to reveal their full effects. If Trump harbors similar or grander aspirations, his administration will likewise need to act like an administration.\n\nREBUILDING STATE CAPACITY\n\nThere is a danger for Trump, and for the country, beyond the convulsions of arbitrariness, the dismissal of knowledge and process, and the specter of draconian measures. The president, his party, his followers, and friendly media spent close to a decade denouncing the conspiratorial \u201cdeep state\u201d and threatening to bring it crashing down. The result has been a wholesale delegitimation of the institutions that underpin the government\u2019s administrative capacity. Delegitimation goes beyond distrust, a measure of which is always warranted, as vigilance is a duty of citizens in a democracy. For Trump and many of his allies and supporters, the machinery of government has no legitimacy\u2014and compliance with its strictures is unnecessary unless they happen to align with the leader\u2019s will.\n\nDuring Trump\u2019s first term and throughout the Biden administration, right-wing resistance to Democratic officials and policies, sometimes in the form of violence and threats, was frighteningly commonplace. Targets included election officials, local school boards, health-care workers, and teachers. In October 2024, reports of armed individuals threatening Federal Emergency Management Agency personnel delivering aid to hurricane victims in North Carolina forced the agency to relocate assistance teams and pause some operations.\n\nCitizens who lament Trump\u2019s return to the presidency are not likely to respond with violence as some of Trump\u2019s followers did on January 6, 2021. Organized civil society will look to the regular political arena and to the courts; it will abide by the norms of a peaceful democratic opposition. But Trump\u2019s followers are another story. The blanket clemency Trump awarded on the first day of his presidency to all the January 6 insurgents, including the leaders of the Proud Boys and the Oath Keepers militia groups, signals that violence against Trump\u2019s opponents is acceptable.\n\nEven if political violence does not break out, the continuous disruptions of ungoverning create unpredictability and uncertainty and, for many Americans, insecurity and dread. The effects of ungoverning are institutional but also personal and individual. This matters because vulnerability is infantilizing, even paralyzing. It taxes both personal and collective agency and degrades the vital moral underpinnings of liberal democracy. Trump\u2019s administration will come to an end, eventually, as will his \u201cMake America Great Again\u201d movement. Afterward, the American people will have to rebuild what he destroyed: a government able to administer the country in the interests of its people.]]>\n    \nOutside the White House on inauguration day, Washington, D.C., January 2025 Nathan Howard / Reuters \n\n\n\n\n\n\n\n\n\nAs U.S. President Donald Trump returns to the White House, it already seems clear that his second term will look little like his first. Many of Trump\u2019s first-term appointments distanced themselves from his views and even denounced him. \u201cI picked some people I shouldn\u2019t have picked,\u201d Trump lamented on Joe Rogan\u2019s podcast last November. \u201cDisloyal people.\u201d This time, Trump is ready. The president and his allies are convinced that he was let down in his first term by those around him and by the bureaucracy of the federal government. They will not let that happen again.\n\nOn his first day in office, Trump restored Schedule F, an employment category that he had created in the closing months of his first term that strips civil servants of protections, allowing them to be fired at will. Trump has convinced many of his followers that a \u201cdeep state\u201d thwarted his first term and robbed him of the 2020 election. Now, the putative deep state will be expunged, along with the expertise and procedures that make effective administration possible. Trump will judge both appointees and civil servants by one criterion: loyalty, defined not by commitment to a programmatic agenda but by unquestioning obedience to the president.\n\nAccording to reporting by The New York Times, the administration\u2019s transition team has been asking applicants for government posts in multiple agencies, including in the intelligence services and the Department of Defense, about their views on the events of the January 6 attacks on the U.S. Capitol. And they have asked applicants pointedly about the 2020 presidential election. Those who condemn the attack or believe that Biden won the race appear unlikely to receive posts.\n\nStaffing the federal government with sycophants is not about ensuring loyalty to an agenda. It is about ensuring submission to the president. And it serves to amplify what we call \u201cungoverning\u201d: the degradation of state capacity and the substitution of unchecked personal will for the difficult, necessary business of shaping, implementing, and assessing policy for the nation. The administration will sideline experts and circumvent regular processes of information gathering and consultation. In so doing, it will degrade state capacity; the premium Trump places on personal loyalty will result in confounding his ability to govern.\n\nUngoverning is radical and rare in the annals of political history. There are simply not that many examples of states that have been systematically degraded and dismantled by individual rulers or parties. In some cases, those in power manage to substitute kleptocracy and state violence for administration; for instance, in Venezuela, where first Hugo Ch\u00e1vez and then Nicol\u00e1s Maduro destroyed a prosperous and functioning state.\n\nIn the United States, ungoverning\u2014which is distinct from conservative small government and from deregulation and privatization\u2014is novel. Critics on both sides of the aisle have tried to cut through bureaucratic red tape in the past, but historically, officials of both parties and the general public have accepted the administrative state as indispensable to the fulfillment of public needs.\n\nThe question now is whether those around Trump will work to check his appetite for ungoverning. As subject-specific experts are replaced by flatterers, the government\u2019s ability to achieve lasting, large-scale results shrinks. As process is shunted aside in favor of one person\u2019s will, the state\u2019s ability to gather accurate information and make effective judgments corrodes; its capacity to design, refine, and implement policy disappears. Ultimately, ungoverning makes the strongman weak.\n\nLOYALTY OVER CAPABILITY\n\nAt the heart of democratic governance\u2014and the office of the presidency\u2014is the idea of administration. The institutions and scope of the current administrative state can be traced to the New Deal era of President Franklin Roosevelt. But the importance of building a state with administrative capacity goes back to the country\u2019s founding. When opponents of the Constitution insisted that state governments would be closer to the people\u2014and more loved by them\u2014than any government operating on a national scale, Alexander Hamilton, the first secretary of the treasury, responded that the aim of the government was not to reflect the passions of local majorities but to practice good administration.\n\nA state with administrative capacity pursues its goals by first systematically and accurately gathering information on current conditions\u2014as Hamilton tried to do on the national economy in his 1791 \u201cReport on Manufactures\u201d and as the Bureau of Labor Statistics and every other agency does now. The next step is to envision a future that is more prosperous, freer, and more secure. And, finally, to design a plan for applying resources, on a large scale and over a long period, to bring that future into being. The administrative state shapes, implements, and enforces every law passed by Congress and every executive order made by the president. As Hamilton wrote in Federalist, no. 72 (of The Federalist Papers), \u201cthe administration of government, in the largest sense, comprehends all the operations of the body politic.\u201d\n\nThe machinery of government that Trump now inherits comprises about 4,000 political appointees and three million public servants who respond to natural disasters and military emergencies, pursue long-term goals set by Congress and the president, and do much else. For Trump, the problem with expertise and process is that they limit the scope and constrain the exercise of his power. Specialized knowledge is a source of authority, as Trump knows, which is why he cannot bear to stand alongside a knowledgeable official, even one of his own appointees, without asserting his own superior expertise. At a press briefing during the COVID-19 pandemic, he suggested to Deborah Birx, the White House coronavirus response coordinator, that irradiating COVID-19 patients\u2019 bodies with ultraviolet light and injections of disinfectant might offer a cure. \u201cI\u2019m not a doctor,\u201d the president said, pointing to his head. \u201cBut I\u2019m a person that has a good you-know-what.\u201d\n\nTrump expects that selecting for loyalty will allow him to govern more effectively in the second term, to push through his agenda. But in truth, prioritizing loyalty over capability will undermine his administration. Unless he is able to yield to the expertise of his appointees and civil servants, his own policy aims will be frustrated. Trump\u2019s problem is not that he requires loyalty to his agenda, on tariffs, on immigration, on foreign policy. It is that he demands personal loyalty\u2014or what John Bolton, Trump\u2019s longest-serving national security adviser in his first term, has called \u201cfealty, a medieval concept implying not mere loyalty but submission.\u201d\n\nADMINISTRATION DEGRADATION\n\nTo be sure, some of Trump\u2019s cabinet picks are loyal primarily to his program. Take his new border czar, Tom Homan, a former border patrol agent who served as head of the Immigration and Customs Enforcement deportation branch under President Barack Obama and acting director of the agency under Trump. \u201cI\u2019ve seen hundreds of policies come and go,\u201d he told The Wall Street Journal earlier this month. \u201cI know what policies worked and what policies don\u2019t work.\u201d He is devoted to Trump\u2019s immigration policies, but he has also met with Republican members of Congress to moderate expectations about the practicality of mass deportation. For those who support Trump\u2019s policies, this is the kind of appointment that promises to convert Trump\u2019s rhetoric into reality. For those who oppose Trump\u2019s policies, this is what makes Trump\u2019s second term more foreboding than the first.\n\nAn effective president has to find and empower people in the mold of Homan\u2014professionals with deep expertise capable of translating broad goals into workable policies and implementing them. This is what \u201cadministration\u201d means. But Trump\u2019s insistence on personal submission, and his distrust of the very administrative state he is charged with directing, is decidedly anti-administration. As Russell Vought, the prospective director of the Office of Management and Budget, has said: \u201cWe want the bureaucrats to be traumatically affected. When they wake up in the morning, we want them to not want to go to work because they are increasingly viewed as the villains.\u201d This is also the orientation of Kash Patel, Trump\u2019s nominee to head the FBI who last September promised to close the agency\u2019s Washington headquarters and convert it into a museum of the \u201cdeep state.\u201d\n\nThen there\u2019s the so-called Department of Government Efficiency, or DOGE\u2014helmed by the political newcomer Elon Musk. The electric car and spaceship mogul originally promised to cut at least $2 trillion from a federal budget of nearly $7 trillion, to lay off two million federal employees, and to slash thousands of regulations. To shrink the budget, civil service, and regulatory scope of government on this scale is an enormous task, and DOGE has recruited leaders from Silicon Valley to develop the plan. Staffed mostly by individuals with little or no experience in governance, DOGE will be unlikely to realize the massive restriction in the scope of the federal government that its founders promise. To do so would require both intimate knowledge of the federal budget, the work of federal agencies, and buy-in from a working coalition of legislators, not to mention the backing of the American public that may not be ready to accept a government that does vastly less than people are accustomed to.\n\n Ungoverning makes the strongman weak.\n\nIf Trump is to succeed in realizing the policies he espouses, his administration will need to make appointments on the basis of qualities more salient to effective governance than personal loyalty. Effective governance requires empowering public servants with experience and specialized knowledge. It means allowing for a process by which they can form and select from alternative policy options, detail plans for their implementation, and then act on those plans. It means staying true to clear goals so that appointees can advance the agenda without squandering time and talent kowtowing to the president.\n\nThose who oppose Trump\u2019s policies may welcome a chaotic anti-administration that cannot make good on the promise of mass deportation or across-the-board tariffs. But Trump will not oversee an administration that is simply ineffective. Rather he will orchestrate a comprehensive degradation of the administrative institutions of government\u2014the processes of decision-making and the consultation of expertise that effective policy of any sort requires. Instead of a government capable of policymaking and implementation, the U.S. government will revolve around the personal will of the president.\n\nGoverning is not about domination and submission. As Hamilton observed, it is about undertaking \u201cextensive and arduous enterprises for the public benefit, requiring considerable time to mature.\u201d The Biden administration aspired to this, as exemplified by the Infrastructure Investment and Jobs Act and the CHIPS and Science Act, both of which are massive, long-term projects that will take a generation to reveal their full effects. If Trump harbors similar or grander aspirations, his administration will likewise need to act like an administration.\n\nREBUILDING STATE CAPACITY\n\nThere is a danger for Trump, and for the country, beyond the convulsions of arbitrariness, the dismissal of knowledge and process, and the specter of draconian measures. The president, his party, his followers, and friendly media spent close to a decade denouncing the conspiratorial \u201cdeep state\u201d and threatening to bring it crashing down. The result has been a wholesale delegitimation of the institutions that underpin the government\u2019s administrative capacity. Delegitimation goes beyond distrust, a measure of which is always warranted, as vigilance is a duty of citizens in a democracy. For Trump and many of his allies and supporters, the machinery of government has no legitimacy\u2014and compliance with its strictures is unnecessary unless they happen to align with the leader\u2019s will.\n\nDuring Trump\u2019s first term and throughout the Biden administration, right-wing resistance to Democratic officials and policies, sometimes in the form of violence and threats, was frighteningly commonplace. Targets included election officials, local school boards, health-care workers, and teachers. In October 2024, reports of armed individuals threatening Federal Emergency Management Agency personnel delivering aid to hurricane victims in North Carolina forced the agency to relocate assistance teams and pause some operations.\n\nCitizens who lament Trump\u2019s return to the presidency are not likely to respond with violence as some of Trump\u2019s followers did on January 6, 2021. Organized civil society will look to the regular political arena and to the courts; it will abide by the norms of a peaceful democratic opposition. But Trump\u2019s followers are another story. The blanket clemency Trump awarded on the first day of his presidency to all the January 6 insurgents, including the leaders of the Proud Boys and the Oath Keepers militia groups, signals that violence against Trump\u2019s opponents is acceptable.\n\nEven if political violence does not break out, the continuous disruptions of ungoverning create unpredictability and uncertainty and, for many Americans, insecurity and dread. The effects of ungoverning are institutional but also personal and individual. This matters because vulnerability is infantilizing, even paralyzing. It taxes both personal and collective agency and degrades the vital moral underpinnings of liberal democracy. Trump\u2019s administration will come to an end, eventually, as will his \u201cMake America Great Again\u201d movement. Afterward, the American people will have to rebuild what he destroyed: a government able to administer the country in the interests of its people.]]>\n  \n  \n    Instead of luxury condos, Gaza faces a resumption of war\n    https://www.economist.com/middle-east-and-africa/2025/02/12/instead-of-luxury-condos-gaza-faces-a-resumption-of-war\n    readwise:01jmdfd725g4r7a51dwbc3xzj6\n    Tue, 18 Feb 2025 21:28:44 +0000\n    The Economist\n    Middle East & Africa | Playing with fire\n\nDonald Trump\u2019s chances of a grand bargain in the Middle East are shrinking\n\n\nBleak prospectsPhotograph: AFP\n\nFeb 12th 2025|Jerusalem\n\nFor nearly a month both Israel and Hamas, the Palestinian Islamist movement that controls Gaza, have largely honoured the ceasefire agreement they reached on January 15th. Even though each side has accused the other of violating the agreement, Israeli forces have withdrawn from most parts of the war-ravaged strip. In return, each week Hamas has released small groups of hostages.\n\nThen, on February 10th it said it would not release the next group as planned on February 15th, prompting Israel to threaten the resumption of \u201cforceful warfare\u201d unless Hamas relented. On February 13th Hamas said it would release another set of hostages after all. Even so, the ceasefire looks desperately fragile.\n\n\nRead all our coverage of the war in the Middle East\n\nThe back-and-forth reflects disagreement over the terms for the second stage of the ceasefire, set to begin in March. The conflict appears to have been exacerbated by the intervention of Donald Trump, America\u2019s president, who has proposed removing all Palestinians from Gaza and transforming the rubble-strewn strip into a massive luxury resort.\n\nThe next stage of the ceasefire is supposed to include a complete Israeli withdrawal from Gaza, the release of all hostages and talks on rebuilding the devastated strip. Binyamin Netanyahu, Israel\u2019s prime minister, stood next to Mr Trump when he outlined his plan at a press conference in Washington last week. Mr Netanyahu has made it clear he will not accept an end to the war while Hamas still rules Gaza.\n\nBut the Hamas commanders who control the fate of the hostages have no intention of going anywhere. During the latest release of hostages on February 8th, they paraded the three men in front of a banner in Arabic, English and Hebrew saying \u201cWe are the day after\u201d. The message was addressed to Mr Trump as much as to Israel.\n\nMr Trump wants the release of hostages to be speeded up from the original plan. \u201cIf all of the hostages aren\u2019t returned by Saturday at 12 o\u2019clock...let hell break out,\u201d he said after Hamas\u2019s announcement. That bought time for Mr Netanyahu. It delighted the hard right in his government, who wanted a return to the fighting and \u201cvoluntary emigration\u201d of Palestinians long before Mr Trump proposed it, and whom he has struggled to keep in his ruling coalition since the ceasefire began. But if Hamas relents, he may yet come under pressure from Mr Trump to stick with the ceasefire.\n\nHe is not the only leader in the region forced to navigate carefully around Mr Trump\u2019s unexpected ideas. In Mr Trump\u2019s telling, Jordan and Egypt are supposed to house uprooted Gazans. They oppose this, but know that angering him could result in losing American aid.\n\nKing Abdullah of Jordan was careful not to contradict Mr Trump while visiting Washington on February 11th. He said Jordan would accept 2,000 sick children from Gaza for medical treatment. Only after leaving did he post on social media that he had \u201creiterated Jordan\u2019s steadfast position against\u201d the Trump plan. Abdel-Fattah al-Sisi, Egypt\u2019s president, has postponed his trip to America. His foreign ministry said on February 11th that it was working on its own \u201ccomprehensive vision\u201d to rebuild Gaza without removing the Gazans.\n\nBy all accounts, Mr Trump still desires a grand regional alliance between America, Saudi Arabia and Israel. That has become hard to imagine. The best hope is that Mr Trump\u2019s threats help convince Hamas to continue releasing hostages, preserving the ceasefire. His unworkable plan for Gaza may spur much-needed thinking on how to actually solve Gazans\u2019 woes. But for now, the president\u2019s interventions have made things worse, not better. \u25a0\n\nSign up to the Middle East Dispatch, a weekly newsletter that keeps you in the loop on a fascinating, complex and consequential part of the world.\n\nExplore more\n\nDonald TrumpMiddle EastWar in the Middle EastIsrael\n\nThis article appeared in the Middle East & Africa section of the print edition under the headline \u201cCeasefire in danger\u201d\n\n\n\nFrom the February 15th 2025 edition\n\nDiscover stories from this section and more in the list of contents\n\nExplore the edition\n\nMore from Middle East & Africa\n\n\n\nHizbullah\u2019s decline is a boon for Lebanon\u2019s new government\n\nBut it will not be able to ignore the armed group entirely\n\n\n\nIsrael mounts an attack on Palestinian intellectual life\n\nThe arrest of a prominent bookseller in Jerusalem bodes ill for freedom of expression\n\n\n\nHoms\u2019s troubles show the challenges facing Syria\u2019s leaders\n\nBoth supporters and opponents of the old regime are unhappy with the new rulers\n\nFor Donald Trump, South Africa is DEI in the form of a country\n\nHis enmity will hurt the rainbow nation\n\nHow to go from fish lover to fish farmer\n\nExpanding aquaculture in Africa could have many benefits\n\nA leader of Congo\u2019s rebels vows to fight on\n\nIt is not clear that a recent truce will hold]]>\n    Middle East & Africa | Playing with fire\n\nDonald Trump\u2019s chances of a grand bargain in the Middle East are shrinking\n\n\nBleak prospectsPhotograph: AFP\n\nFeb 12th 2025|Jerusalem\n\nFor nearly a month both Israel and Hamas, the Palestinian Islamist movement that controls Gaza, have largely honoured the ceasefire agreement they reached on January 15th. Even though each side has accused the other of violating the agreement, Israeli forces have withdrawn from most parts of the war-ravaged strip. In return, each week Hamas has released small groups of hostages.\n\nThen, on February 10th it said it would not release the next group as planned on February 15th, prompting Israel to threaten the resumption of \u201cforceful warfare\u201d unless Hamas relented. On February 13th Hamas said it would release another set of hostages after all. Even so, the ceasefire looks desperately fragile.\n\n\nRead all our coverage of the war in the Middle East\n\nThe back-and-forth reflects disagreement over the terms for the second stage of the ceasefire, set to begin in March. The conflict appears to have been exacerbated by the intervention of Donald Trump, America\u2019s president, who has proposed removing all Palestinians from Gaza and transforming the rubble-strewn strip into a massive luxury resort.\n\nThe next stage of the ceasefire is supposed to include a complete Israeli withdrawal from Gaza, the release of all hostages and talks on rebuilding the devastated strip. Binyamin Netanyahu, Israel\u2019s prime minister, stood next to Mr Trump when he outlined his plan at a press conference in Washington last week. Mr Netanyahu has made it clear he will not accept an end to the war while Hamas still rules Gaza.\n\nBut the Hamas commanders who control the fate of the hostages have no intention of going anywhere. During the latest release of hostages on February 8th, they paraded the three men in front of a banner in Arabic, English and Hebrew saying \u201cWe are the day after\u201d. The message was addressed to Mr Trump as much as to Israel.\n\nMr Trump wants the release of hostages to be speeded up from the original plan. \u201cIf all of the hostages aren\u2019t returned by Saturday at 12 o\u2019clock...let hell break out,\u201d he said after Hamas\u2019s announcement. That bought time for Mr Netanyahu. It delighted the hard right in his government, who wanted a return to the fighting and \u201cvoluntary emigration\u201d of Palestinians long before Mr Trump proposed it, and whom he has struggled to keep in his ruling coalition since the ceasefire began. But if Hamas relents, he may yet come under pressure from Mr Trump to stick with the ceasefire.\n\nHe is not the only leader in the region forced to navigate carefully around Mr Trump\u2019s unexpected ideas. In Mr Trump\u2019s telling, Jordan and Egypt are supposed to house uprooted Gazans. They oppose this, but know that angering him could result in losing American aid.\n\nKing Abdullah of Jordan was careful not to contradict Mr Trump while visiting Washington on February 11th. He said Jordan would accept 2,000 sick children from Gaza for medical treatment. Only after leaving did he post on social media that he had \u201creiterated Jordan\u2019s steadfast position against\u201d the Trump plan. Abdel-Fattah al-Sisi, Egypt\u2019s president, has postponed his trip to America. His foreign ministry said on February 11th that it was working on its own \u201ccomprehensive vision\u201d to rebuild Gaza without removing the Gazans.\n\nBy all accounts, Mr Trump still desires a grand regional alliance between America, Saudi Arabia and Israel. That has become hard to imagine. The best hope is that Mr Trump\u2019s threats help convince Hamas to continue releasing hostages, preserving the ceasefire. His unworkable plan for Gaza may spur much-needed thinking on how to actually solve Gazans\u2019 woes. But for now, the president\u2019s interventions have made things worse, not better. \u25a0\n\nSign up to the Middle East Dispatch, a weekly newsletter that keeps you in the loop on a fascinating, complex and consequential part of the world.\n\nExplore more\n\nDonald TrumpMiddle EastWar in the Middle EastIsrael\n\nThis article appeared in the Middle East & Africa section of the print edition under the headline \u201cCeasefire in danger\u201d\n\n\n\nFrom the February 15th 2025 edition\n\nDiscover stories from this section and more in the list of contents\n\nExplore the edition\n\nMore from Middle East & Africa\n\n\n\nHizbullah\u2019s decline is a boon for Lebanon\u2019s new government\n\nBut it will not be able to ignore the armed group entirely\n\n\n\nIsrael mounts an attack on Palestinian intellectual life\n\nThe arrest of a prominent bookseller in Jerusalem bodes ill for freedom of expression\n\n\n\nHoms\u2019s troubles show the challenges facing Syria\u2019s leaders\n\nBoth supporters and opponents of the old regime are unhappy with the new rulers\n\nFor Donald Trump, South Africa is DEI in the form of a country\n\nHis enmity will hurt the rainbow nation\n\nHow to go from fish lover to fish farmer\n\nExpanding aquaculture in Africa could have many benefits\n\nA leader of Congo\u2019s rebels vows to fight on\n\nIt is not clear that a recent truce will hold]]>\n  \n  \n    How COVID Pushed a Generation of Young People to the Right\n    https://www.theatlantic.com/ideas/archive/2025/02/covid-youth-conservative-shift/681705/?gift=o6MjJQpusU9ebnFuymVdsHrkCe1QULWZ3ae-yZ_tiEo&utm_source=copy-link&utm_medium=social&utm_campaign=share\n    readwise:01jmcvcn5khqpqn8mma580dxb5\n    Tue, 18 Feb 2025 15:38:54 +0000\n    The Atlantic\n    \nResearch suggests that pandemics are more likely to reduce rather than build trust in scientific and political authorities.\n\n (Photograph by Zack Wittman)\nFor decades, America\u2019s young voters have been deeply\u2014and famously\u2014progressive. In 2008, a youthquake sent Barack Obama to the White House. In 2016, voters ages 18 to 29 broke for Hillary Clinton by 18 points. In 2020, they voted for Joe Biden by 24 points. In 2024, Donald Trump closed most of the gap, losing voters under 30 by a 51\u201347 margin. In one recent CBS poll, Americans under 30 weren\u2019t just evenly split between the parties. They were even more pro-Trump than Boomers over 65.\nPrecisely polling teens and 20-somethings is a fraught business; some surveys suggest that Trump\u2019s advantage among young people might already be fading. But young people\u2019s apparent lurch right is not an American-only trend.\n\u201cFar-right parties are surging across Europe\u2014and young voters are buying in,\u201d the journalist Hanne Cokelaere wrote for Politico last year. In France, Germany, Finland, and beyond, young voters are swinging their support toward anti-establishment far-right parties \u201cin numbers equal to and even exceeding older voters.\u201d In Germany, a 2024 survey of 2,000 people showed that young people have adopted a relatively new \u201cgloomy outlook\u201d on the future. No surprise, then, that the far-right Alternative f\u00fcr Deutschland has become the most popular party among Germans under 30. Like most interesting phenomena, this one even has a German name: Rechtsruck, or rightward shift.\nRead: Why the COVID deniers won\nWhat\u2019s driving this global Rechtsruck? It\u2019s hard to say for sure. Maybe the entire world is casting a protest vote after several years of inflation. Last year was the largest wipeout for political incumbents in the developed world since the end of the Second World War. One level deeper, it wasn\u2019t inflation on its own, but rather the combination of weak real economic growth and record immigration that tilled the soil for far-right upstarts, who can criticize progressive governments on both sides of the Atlantic for their failure to look out for their own citizens first.\nThere is another potential driver of the global right turn: the pandemic.\nPandemics might not initially seem to cash out in any particular political direction. After all, in the spring of 2020, one possible implication of the pandemic seemed to be that it would unite people behind a vision of collective sacrifice\u2014or, at least, collective appreciation for health professionals, or for the effect of vaccines to reduce severe illness among adults. But political science suggests that pandemics are more likely to reduce rather than build trust in scientific authorities. One cross-country analysis published by the Systemic Risk Center at the London School of Economics found that people who experience epidemics between the ages of 18 and 25 have less confidence in their scientific and political leadership. This loss of trust persists for years, even decades, in part because political ideology tends to solidify in a person\u2019s 20s.\nThe paper certainly matches the survey evidence of young Americans. Young people who cast their first ballot in 2024 were \u201cmore jaded than ever about the state of American leadership,\u201d according to the Harvard Political Review. A 2024 analysis of Americans under 30 found the \u201clowest levels of confidence in most public institutions since the survey began.\u201d In the past decade alone, young Americans\u2019 trust in the president has declined by 60 percent, while their trust in the Supreme Court, Wall Street, and Congress has declined by more than 30 percent.\nAnother way that COVID may have accelerated young people\u2019s Rechtsruck in America and around the world was by dramatically reducing their physical-world socializing. That led, in turn, to large increases in social-media time that boys and girls spent alone. The Norwegian researcher Ruben B. Mathisen has written that \u201csocial media [creates] separate online spheres for men and women.\u201d By trading gender-blended hangouts in basements and restaurants for gender-segregated online spaces, young men\u2019s politics became more distinctly pro-male\u2014and, more to the point, anti-feminist, according to Mathisen. Norwegian boys are more and more drawn to right-wing politics, a phenomenon \u201cdriven in large part by a new wave of politically potent anti-feminism,\u201d he wrote. Although Mathisen focused on Nordic youth, he noted that his research built on a body of survey literature showing that \u201cthe ideological distance between young men and women has accelerated across several countries.\u201d\nRead: The not-so-woke Generation Z\nThese changes may not be durable. But many people\u2019s political preferences solidify when they\u2019re in their teens and 20s; so do other tastes and behaviors, such as musical preferences and even spending habits. Most famously, so-called Depression babies, who grew up in the 1930s, saved more as adults, and there is some evidence that corporate managers born in the \u201930s were unusually disinclined to take on loans. Perhaps the 18-to-25-year-old cohort whose youths were thrown into upheaval by COVID will adopt a set of sociopolitical assumptions that form a new sort of ideology that doesn\u2019t quite have a name yet. As The Atlantic\u2019s Anne Applebaum has written, many emerging European populist parties now blend vaccine skepticism, \u201cfolk magic\u201d mysticism, and deep anti-immigration sentiment. \u201cSpiritual leaders are becoming political, and political actors have veered into the occult,\u201d she wrote.\nNew ideologies are messy to describe and messier still to name. But in a few years, what we\u2019ve grown accustomed to calling Generation Z may reveal itself to contain a subgroup: Generation C, COVID-affected and, for now, strikingly conservative. For this micro-generation of young people in the United States and throughout the West, social media has served as a crucible where several trends have fused together: declining trust in political and scientific authorities, anger about the excesses of feminism and social justice, and a preference for rightward politics.]]>\n    \nResearch suggests that pandemics are more likely to reduce rather than build trust in scientific and political authorities.\n\n (Photograph by Zack Wittman)\nFor decades, America\u2019s young voters have been deeply\u2014and famously\u2014progressive. In 2008, a youthquake sent Barack Obama to the White House. In 2016, voters ages 18 to 29 broke for Hillary Clinton by 18 points. In 2020, they voted for Joe Biden by 24 points. In 2024, Donald Trump closed most of the gap, losing voters under 30 by a 51\u201347 margin. In one recent CBS poll, Americans under 30 weren\u2019t just evenly split between the parties. They were even more pro-Trump than Boomers over 65.\nPrecisely polling teens and 20-somethings is a fraught business; some surveys suggest that Trump\u2019s advantage among young people might already be fading. But young people\u2019s apparent lurch right is not an American-only trend.\n\u201cFar-right parties are surging across Europe\u2014and young voters are buying in,\u201d the journalist Hanne Cokelaere wrote for Politico last year. In France, Germany, Finland, and beyond, young voters are swinging their support toward anti-establishment far-right parties \u201cin numbers equal to and even exceeding older voters.\u201d In Germany, a 2024 survey of 2,000 people showed that young people have adopted a relatively new \u201cgloomy outlook\u201d on the future. No surprise, then, that the far-right Alternative f\u00fcr Deutschland has become the most popular party among Germans under 30. Like most interesting phenomena, this one even has a German name: Rechtsruck, or rightward shift.\nRead: Why the COVID deniers won\nWhat\u2019s driving this global Rechtsruck? It\u2019s hard to say for sure. Maybe the entire world is casting a protest vote after several years of inflation. Last year was the largest wipeout for political incumbents in the developed world since the end of the Second World War. One level deeper, it wasn\u2019t inflation on its own, but rather the combination of weak real economic growth and record immigration that tilled the soil for far-right upstarts, who can criticize progressive governments on both sides of the Atlantic for their failure to look out for their own citizens first.\nThere is another potential driver of the global right turn: the pandemic.\nPandemics might not initially seem to cash out in any particular political direction. After all, in the spring of 2020, one possible implication of the pandemic seemed to be that it would unite people behind a vision of collective sacrifice\u2014or, at least, collective appreciation for health professionals, or for the effect of vaccines to reduce severe illness among adults. But political science suggests that pandemics are more likely to reduce rather than build trust in scientific authorities. One cross-country analysis published by the Systemic Risk Center at the London School of Economics found that people who experience epidemics between the ages of 18 and 25 have less confidence in their scientific and political leadership. This loss of trust persists for years, even decades, in part because political ideology tends to solidify in a person\u2019s 20s.\nThe paper certainly matches the survey evidence of young Americans. Young people who cast their first ballot in 2024 were \u201cmore jaded than ever about the state of American leadership,\u201d according to the Harvard Political Review. A 2024 analysis of Americans under 30 found the \u201clowest levels of confidence in most public institutions since the survey began.\u201d In the past decade alone, young Americans\u2019 trust in the president has declined by 60 percent, while their trust in the Supreme Court, Wall Street, and Congress has declined by more than 30 percent.\nAnother way that COVID may have accelerated young people\u2019s Rechtsruck in America and around the world was by dramatically reducing their physical-world socializing. That led, in turn, to large increases in social-media time that boys and girls spent alone. The Norwegian researcher Ruben B. Mathisen has written that \u201csocial media [creates] separate online spheres for men and women.\u201d By trading gender-blended hangouts in basements and restaurants for gender-segregated online spaces, young men\u2019s politics became more distinctly pro-male\u2014and, more to the point, anti-feminist, according to Mathisen. Norwegian boys are more and more drawn to right-wing politics, a phenomenon \u201cdriven in large part by a new wave of politically potent anti-feminism,\u201d he wrote. Although Mathisen focused on Nordic youth, he noted that his research built on a body of survey literature showing that \u201cthe ideological distance between young men and women has accelerated across several countries.\u201d\nRead: The not-so-woke Generation Z\nThese changes may not be durable. But many people\u2019s political preferences solidify when they\u2019re in their teens and 20s; so do other tastes and behaviors, such as musical preferences and even spending habits. Most famously, so-called Depression babies, who grew up in the 1930s, saved more as adults, and there is some evidence that corporate managers born in the \u201930s were unusually disinclined to take on loans. Perhaps the 18-to-25-year-old cohort whose youths were thrown into upheaval by COVID will adopt a set of sociopolitical assumptions that form a new sort of ideology that doesn\u2019t quite have a name yet. As The Atlantic\u2019s Anne Applebaum has written, many emerging European populist parties now blend vaccine skepticism, \u201cfolk magic\u201d mysticism, and deep anti-immigration sentiment. \u201cSpiritual leaders are becoming political, and political actors have veered into the occult,\u201d she wrote.\nNew ideologies are messy to describe and messier still to name. But in a few years, what we\u2019ve grown accustomed to calling Generation Z may reveal itself to contain a subgroup: Generation C, COVID-affected and, for now, strikingly conservative. For this micro-generation of young people in the United States and throughout the West, social media has served as a crucible where several trends have fused together: declining trust in political and scientific authorities, anger about the excesses of feminism and social justice, and a preference for rightward politics.]]>\n  \n  \n    China Doesn\u2019t Want to Lead an Axis\n    https://www.foreignaffairs.com/china/china-doesnt-want-lead-axis?utm_medium=newsletters&utm_source=fatoday&utm_campaign=China%20Doesn%E2%80%99t%20Want%20to%20Lead%20an%20Axis&utm_content=20250218&utm_term=EDZZZ003ZX\n    readwise:01jmct0xq8m9kr64enpckydwnv\n    Tue, 18 Feb 2025 15:15:01 +0000\n    Foreign Affairs\n    \nChinese President Xi Jinping and Russian President Vladimir Putin in Kazan, Russia, October 2024 Kristina Kormilitsyna / Reuters \n\n\n\n\n\n\n\n\nChina and Russia\u2019s 2022 proclamation of a \u201cno limits\u201d partnership with \u201cno \u2018forbidden\u2019 areas\u201d has had a far-reaching effect. The agreement implied that Beijing and Moscow were about to resurrect their long-defunct alliance that, when it briefly bound the two powers in the 1950s, projected a formidable threat that the United States could not afford to leave unchallenged.\n\nRegardless of their various disagreements, Chinese President Xi Jinping has called Russian President Vladimir Putin his \u201cdear friend\u201d and was overheard in March 2023 telling him that the two of them were together \u201cdriving changes unseen in a century.\u201d Their frequent meetings have produced a set of programmatic statements that highlight a shared opposition to \u201chegemonism\u201d\u2014a code word for American dominance\u2014and promise a more \u201cjust\u201d international order. According to Russia\u2019s ambassador to China, Igor Morgulov, Xi has accepted Putin\u2019s invitation to attend Victory Day celebrations in Moscow in May 2025. And their partnership has extended beyond rhetoric and symbolism: China has provided material support for Russia\u2019s brutal war of aggression in Ukraine in the form of dual-use technologies, which have both military and commercial applications, and purchases of Russian oil and gas.\n\nAnd yet China\u2019s leadership remains conflicted about Russia, fearing entanglement in Putin\u2019s radical anti-Western schemes and eyeing with apprehension the prospect of a cold war that China neither wants nor knows how to fight. Beijing does not want to commit to a formal Chinese-Russian alliance and bitterly resists the idea that it belongs to an \u201caxis\u201d of some sort with Russia, North Korea, and Iran. And Kim Jong Un\u2019s regime in Pyongyang is increasingly the main source of irritation in Beijing.\n\nIn January 2025, I took part in discussions in Beijing and Sanya, China, organized by Tsinghua University, that were intended to serve as a form of Track II diplomacy, a practice in which nonstate civil society actors from various countries meet to discuss relations between their governments. This dialogue brought together academics and former senior officials and diplomats from China, Russia, and the United States for heated but productive conversations.\n\nOne striking insight emerged from these talks: the main reason for Beijing\u2019s seeming unwillingness to build a trilateral coalition with Russia and North Korea is that such an arrangement would call for strategic leadership by China, and Beijing is decidedly uninterested in such a prospect. That is partly because any axis led by Beijing would require a mission around which its allies could unite\u2014and no one in Beijing seems to know what that mission should be.\n\nChina\u2019s hesitancy to head an alliance of unreliable partners in a struggle against the West suggests that its leaders are aware of the high costs of confrontation and are hedging their bets. President Donald Trump\u2019s unconventional diplomacy, which pairs militant rhetoric and threats of economic warfare with promises of great-power cooperation with China and Russia, has added to uncertainty in Beijing about the United States\u2019 direction. As a result, Washington has a golden opportunity to test China\u2019s intentions through renewed diplomatic efforts, even while gearing up for containment.\n\nLEADER\u2019S REMORSE\n\nThe consultations I attended focused on the question of China\u2019s relationship with the rogue regime in North Korea. In the Chinese participants\u2019 view, Beijing did not encourage Kim\u2019s recent pivot to Russia, which culminated in a treaty of alliance with Russia in June 2024; indeed, it seems likely that Beijing was not even consulted in advance of this move. Nor did Xi approve North Korea\u2019s direct involvement in Russia\u2019s war against Ukraine, which has included the deployment of some 10,000 North Korean soldiers to Russia\u2019s Kursk region, to repel a Ukrainian incursion. This move showed that Kim is willing and able to act independently of Beijing, even as he continues to rely on trade with China for his regime\u2019s survival. In offering troops and large quantities of munitions to Putin, Kim has made a point of showing Xi that he is not China\u2019s vassal.\n\nThe Russians at these consultations lamented the lack of coordination among China, North Korea, and Russia. Putin, who meets frequently, albeit separately, with Xi and Kim, would like to have a trilateral summit to forge closer relations among all three countries. But Xi and Kim have not seen each other since 2019. The countries formerly held trilateral consultations, most recently in October 2018, but North Korea now resists such meetings, preferring the company of Russia to China.\n\nBeijing, too, is unwilling to create a bloc in East Asia, partly out of fear that it would cause Japan, South Korea, and the United States to build a more overtly anti-Chinese bloc. The Chinese also worry, much more than the Russians do, about North Korea\u2019s nuclear program. The Russians have pragmatically resigned themselves to a nuclear North Korea. But Beijing, seeing the potential knock-on effects in Japan and South Korea\u2014which could be pushed to start nuclear programs of their own\u2014may be keen to resume denuclearization talks with Pyongyang, even if the goal of a nuclear-free Korean Peninsula appears out of reach. Some Chinese participants expressed concern about North Korean militancy, including the possibility that the Kim regime will launch military provocations against South Korea. Unsurprisingly, China fears being dragged into a conflict by a restless, unpredictable, and generally unreliable client state\u2014whether it is North Korea or Russia.\n\nChina\u2019s reticence to serve as the standard-bearer for Pyongyang is not new. When, in March 1990, the Chinese Communist Party\u2019s general secretary, Jiang Zemin, visited North Korea, General Secretary Kim Il Sung promised him that \u201cthe Korean people would unswervingly continue to hold high the banner of revolution and socialism \u2026 and fight shoulder to shoulder with the Chinese people in the common cause of building socialism.\u201d He was hopeful that, following the Soviet collapse, China would lead the struggle on behalf of the Communist cause. But Beijing, in no hurry to take up the discarded banner of Soviet socialism, demurred, focusing instead on economic reform and a pragmatic foreign policy, dubbed taoguang yanghui (\u201chiding one\u2019s capabilities and biding one\u2019s time\u201d). China went on to establish diplomatic ties with South Korea, and although Beijing did not break with Pyongyang, the relationship never regained the intimacy of the early Cold War, when the two fought together against the United States. China and North Korea would never again be, in the words of Chinese leader Mao Zedong, \u201cas close as lips and teeth.\u201d\n\nFAILURE TO SIGNAL\n\nChinese leaders may be looking for lessons from the last time the superpowers faced off. Historians have conflicting answers about why the Cold War started: whether Joseph Stalin wanted it or whether it was an unfortunate accident. It seems plausible that what Stalin really wanted was a great-power compromise with the United States, according to which Moscow and Washington would respect each other\u2019s legitimate spheres of influence. The problems began when Washington and Stalin diverged on how far into Europe and Asia Moscow\u2019s legitimate sphere of influence should extend. Reacting to what it perceived as aggressive moves by Moscow, Washington, wary of underestimating Stalin\u2019s expansionist ambitions, pursued containment.\n\nBeijing\u2019s predicament today is that it does not know how to reassure the United States that it is not seeking another cold war even as it actively prepares to wage one. China\u2019s relentless nuclear buildup, its hostile espionage operations, its militant rhetoric, and, above all, its support for Russia suggest that Xi has already made his call and that a confrontation with the United States is inevitable.\n\nChina\u2019s relationships with Russia and North Korea remain useful in its struggle against Western hegemony. Chinese strategists think in simple geopolitical terms: the United States, leader of the West, is trying to bring China down; Putin is confronting the West with his war in Ukraine; therefore, Putin is helping China, and cannot be thrown under the bus. Similarly, China will not completely abandon North Korea, not because it approves of Kim, but because he remains a valuable weapon against the United States.\n\nOn the other hand, getting too invested in the relationship with a militant Russia would box Beijing in. Xi\u2019s fraternal embrace of Putin has damaged China\u2019s standing in Europe: German Foreign Minister Annalena Baerbock criticized China in December 2024 for \u201copposing our core European interests with its economic and weapons aid to Russia,\u201d and French President Emmanuel Macron pressed Xi to curb support for Moscow during their talks in May 2024. Given that China\u2019s trade relationship with the European Union is worth $762 billion and has become all the more critical amid China\u2019s economic stagnation, strategists in Beijing must ask themselves whether the economic polarization that would accompany an emerging cold war is really in China\u2019s interest. Foreign Minister Wang Yi, for his part, went out of his way at the Munich Security Conference in February 2025 to reassure European leaders that Beijing does not plan to overthrow the existing global order.\n\nYet as the experience of the present and previous centuries have shown, economic ties do not preclude great-power conflict. Putin\u2019s reckless gamble in Ukraine demonstrated his willingness to sacrifice lucrative economic ties to Europe for glory. And no Chinese diplomat or academic, no matter how well connected, can confidently speak for Xi who, like Putin, may yet choose confrontation with the West.\n\nTALK ISN\u2019T CHEAP\n\nOne of the most important ways that Xi will signal his intentions vis-\u00e0-vis the West will be the course he decides to take with Taiwan. \u201cNo one can ever sever the bond of kinship between [Taiwan and the mainland], and no one can ever stop China\u2019s reunification,\u201d he announced in his 2025 New Year message. Like his predecessors, Xi has refused to renounce the possible use of force to unify China and Taiwan. But unlike them, he has imbued his comments with a great sense of urgency, as if he has already made up his mind about invading Taiwan and is just waiting for an opportunity to do so.\n\nIt is possible, however, that Xi is genuinely undecided and is biding his time as he anticipates the U.S. response. Here, too, Cold War lessons apply. Stalin badly miscalculated Washington\u2019s response to the North Korean invasion of South Korea in 1950, in part because he concluded from intelligence gathered from cable intercepts that the United States would not intervene to defend South Korea. He failed to foresee how Washington\u2019s threat perceptions and policies had evolved in response to Moscow\u2019s aggressive moves. Xi, too, could conclude that Washington is not serious about Taiwan\u2019s defense and act accordingly. And like Stalin, he could err in his calculation, with even more tragic consequences for the world.\n\nJust as the escalations of the Cold War were contingent and gradual, with moments of tension punctuated by efforts to set things right, the U.S.-Chinese relationship today is not beyond redemption, even if it is far along the road to confrontation. If it does not want to proceed from learning about the Cold War to fighting a new one, the Chinese government should not act as if it does not want a dialogue with the United States.\n\nNicholas Burns, the U.S. ambassador to China during the Biden administration, faced diplomatic obstruction and had very little access to Chinese policymakers. China has snubbed the Pentagon\u2019s efforts to maintain military-to-military dialogue, and although former Secretary of Defense Lloyd Austin finally met his Chinese counterpart Dong Jun in May 2024, contacts remain sporadic. Such stonewalling could be a way to signal displeasure with what China perceives as Washington\u2019s hawkishness, but intentionally or not, it sends another message: that Beijing is already firmly set on a new cold war.\n\n The U.S.-Chinese relationship is not beyond redemption.\n\nBeijing should instead signal to Washington, in public or through private channels, that China does not plan to invade Taiwan in the foreseeable future. It should tone down public rhetoric about impending \u201creunification\u201d to provide a foundation for building desperately needed trust.\n\nBeijing should also make it clear that it does not seek an alliance with Moscow. The \u201cno limits\u201d partnership, which produced great alarm in the West with no gain to China, is a reminder that what Beijing says about its relationship with Russia can have direct impact on Western threat perceptions. The disappearance of \u201cantihegemonic\u201d language from Chinese-Russian statements will not eliminate U.S. concerns about an emerging axis, but it will at least chip away at the substantial evidence for such concerns.\n\nMost important, China\u2019s leaders should become more directly involved in helping end Russia\u2019s war in Ukraine. As the key buyer of Russia\u2019s hydrocarbons and a major provider of industrial and consumer goods to Russia, China has substantial economic leverage in the relationship, which it could deploy to encourage Putin to accept a cease-fire. A frozen conflict would not run counter to China\u2019s interest in avoiding escalation in Ukraine, it would stabilize relations with Europe and might even present an area of overlap between Beijing and the Trump administration, which has signaled its interest in a cease-fire regardless of a comprehensive settlement of the war. Given Wang\u2019s comments in Munich that \u201call parties and all stakeholders should, at an appropriate time, participate in the peace talks process\u201d and Trump\u2019s intention to hold peace talks with Russia, now is the time for China to signal its interest in a direct and substantive dialogue with the United States on the war in Ukraine.\n\nLEARNING FROM LAST TIME\n\nWhen clouds began to settle over the U.S.-Soviet relationship in 1945, President Harry S. Truman confidently predicted that he would get his way 85 percent of the time because, as he put it, \u201cthe Soviet Union needed us more than we needed them.\u201d The reality proved more complex. Fearing that the Americans would interpret any Soviet concessions as weakness, Stalin instructed his foreign minister, Vyacheslav Molotov, to \u201cdisplay complete obduracy.\u201d Today, the United States, without a nuclear monopoly and facing a much more powerful adversary in China, cannot aspire to Truman\u2019s predicted success rate. Active diplomacy, then, is Washington\u2019s best hope to mitigate and maybe even reverse the slide into confrontation with Beijing.\n\nFirst, the United States should redouble its efforts to dissuade Taiwan from proclaiming independence, a highly destabilizing move that would have dangerous consequences for East Asia and the world. Washington could tie its Taiwan diplomacy to private reassurance from China that it will not invade the island.\n\nAt the same time, the United States should also tell China frankly that Washington will be forced to prepare for a conflict over Taiwan unless Beijing shows through public statements and a demonstrated willingness to engage in confidence-building measures in East Asia that it is not seeking another cold war. Such measures could include reciprocating Trump\u2019s call for arms control, developing military-to-military contacts, and refraining from provocative military exercises.\n\n Active diplomacy is Washington\u2019s best hope to mitigate the slide into confrontation with Beijing.\n\nWhen he was national security adviser and secretary of state under President Richard Nixon, Henry Kissinger scolded Democrats for preaching human rights to the Soviet Union. He correctly understood that such posturing annoyed the Soviets and made diplomacy more difficult. He scored formidable victories against the Soviet Union by pioneering rapprochement with China and outfoxing the Kremlin in the Middle East nonetheless. The United States should now channel Kissinger in its approach to China and refrain from lecturing Beijing about democratic values, which alarm China\u2019s leaders and do little to improve human rights in China. Trump would seem to have a natural proclivity to avoid the subject, since he has never trafficked in the liberal internationalist language of his predecessors.\n\nTrump should also offer China a direct role in bringing Russia to the table to end the war in Ukraine. Beijing already has a point man for Russia and Ukraine in Ambassador Li Hui and has already issued statements about the need for peaceful resolution. By inviting Beijing to negotiations, Trump could test China\u2019s goodwill and, if an agreement is reached, make sure that China has a stake in implementing a cease-fire.\n\nFebruary 2025 marks the 75th anniversary of the signing of the Sino-Soviet treaty of alliance. The seemingly impregnable alliance was in fact riven by internal contradictions and lasted for only about ten years before it collapsed in a cloud of mutual accusations of betrayal. China\u2019s decision to pursue modernization and development in partnership, rather than in confrontation with the West, spared it from the Soviet Union\u2019s fate. Today, China and Russia are once again working together, but their relationship is not an alliance and is far from \u201cno limits.\u201d With the possibility of another cold war looming, China is uncertain about whether it really wants to lead an axis of obstinate and unreliable clients into confrontation with the United States. It is in both countries\u2019 interests to make use of this uncertainty to explore alternative arrangements.]]>\n    \nChinese President Xi Jinping and Russian President Vladimir Putin in Kazan, Russia, October 2024 Kristina Kormilitsyna / Reuters \n\n\n\n\n\n\n\n\nChina and Russia\u2019s 2022 proclamation of a \u201cno limits\u201d partnership with \u201cno \u2018forbidden\u2019 areas\u201d has had a far-reaching effect. The agreement implied that Beijing and Moscow were about to resurrect their long-defunct alliance that, when it briefly bound the two powers in the 1950s, projected a formidable threat that the United States could not afford to leave unchallenged.\n\nRegardless of their various disagreements, Chinese President Xi Jinping has called Russian President Vladimir Putin his \u201cdear friend\u201d and was overheard in March 2023 telling him that the two of them were together \u201cdriving changes unseen in a century.\u201d Their frequent meetings have produced a set of programmatic statements that highlight a shared opposition to \u201chegemonism\u201d\u2014a code word for American dominance\u2014and promise a more \u201cjust\u201d international order. According to Russia\u2019s ambassador to China, Igor Morgulov, Xi has accepted Putin\u2019s invitation to attend Victory Day celebrations in Moscow in May 2025. And their partnership has extended beyond rhetoric and symbolism: China has provided material support for Russia\u2019s brutal war of aggression in Ukraine in the form of dual-use technologies, which have both military and commercial applications, and purchases of Russian oil and gas.\n\nAnd yet China\u2019s leadership remains conflicted about Russia, fearing entanglement in Putin\u2019s radical anti-Western schemes and eyeing with apprehension the prospect of a cold war that China neither wants nor knows how to fight. Beijing does not want to commit to a formal Chinese-Russian alliance and bitterly resists the idea that it belongs to an \u201caxis\u201d of some sort with Russia, North Korea, and Iran. And Kim Jong Un\u2019s regime in Pyongyang is increasingly the main source of irritation in Beijing.\n\nIn January 2025, I took part in discussions in Beijing and Sanya, China, organized by Tsinghua University, that were intended to serve as a form of Track II diplomacy, a practice in which nonstate civil society actors from various countries meet to discuss relations between their governments. This dialogue brought together academics and former senior officials and diplomats from China, Russia, and the United States for heated but productive conversations.\n\nOne striking insight emerged from these talks: the main reason for Beijing\u2019s seeming unwillingness to build a trilateral coalition with Russia and North Korea is that such an arrangement would call for strategic leadership by China, and Beijing is decidedly uninterested in such a prospect. That is partly because any axis led by Beijing would require a mission around which its allies could unite\u2014and no one in Beijing seems to know what that mission should be.\n\nChina\u2019s hesitancy to head an alliance of unreliable partners in a struggle against the West suggests that its leaders are aware of the high costs of confrontation and are hedging their bets. President Donald Trump\u2019s unconventional diplomacy, which pairs militant rhetoric and threats of economic warfare with promises of great-power cooperation with China and Russia, has added to uncertainty in Beijing about the United States\u2019 direction. As a result, Washington has a golden opportunity to test China\u2019s intentions through renewed diplomatic efforts, even while gearing up for containment.\n\nLEADER\u2019S REMORSE\n\nThe consultations I attended focused on the question of China\u2019s relationship with the rogue regime in North Korea. In the Chinese participants\u2019 view, Beijing did not encourage Kim\u2019s recent pivot to Russia, which culminated in a treaty of alliance with Russia in June 2024; indeed, it seems likely that Beijing was not even consulted in advance of this move. Nor did Xi approve North Korea\u2019s direct involvement in Russia\u2019s war against Ukraine, which has included the deployment of some 10,000 North Korean soldiers to Russia\u2019s Kursk region, to repel a Ukrainian incursion. This move showed that Kim is willing and able to act independently of Beijing, even as he continues to rely on trade with China for his regime\u2019s survival. In offering troops and large quantities of munitions to Putin, Kim has made a point of showing Xi that he is not China\u2019s vassal.\n\nThe Russians at these consultations lamented the lack of coordination among China, North Korea, and Russia. Putin, who meets frequently, albeit separately, with Xi and Kim, would like to have a trilateral summit to forge closer relations among all three countries. But Xi and Kim have not seen each other since 2019. The countries formerly held trilateral consultations, most recently in October 2018, but North Korea now resists such meetings, preferring the company of Russia to China.\n\nBeijing, too, is unwilling to create a bloc in East Asia, partly out of fear that it would cause Japan, South Korea, and the United States to build a more overtly anti-Chinese bloc. The Chinese also worry, much more than the Russians do, about North Korea\u2019s nuclear program. The Russians have pragmatically resigned themselves to a nuclear North Korea. But Beijing, seeing the potential knock-on effects in Japan and South Korea\u2014which could be pushed to start nuclear programs of their own\u2014may be keen to resume denuclearization talks with Pyongyang, even if the goal of a nuclear-free Korean Peninsula appears out of reach. Some Chinese participants expressed concern about North Korean militancy, including the possibility that the Kim regime will launch military provocations against South Korea. Unsurprisingly, China fears being dragged into a conflict by a restless, unpredictable, and generally unreliable client state\u2014whether it is North Korea or Russia.\n\nChina\u2019s reticence to serve as the standard-bearer for Pyongyang is not new. When, in March 1990, the Chinese Communist Party\u2019s general secretary, Jiang Zemin, visited North Korea, General Secretary Kim Il Sung promised him that \u201cthe Korean people would unswervingly continue to hold high the banner of revolution and socialism \u2026 and fight shoulder to shoulder with the Chinese people in the common cause of building socialism.\u201d He was hopeful that, following the Soviet collapse, China would lead the struggle on behalf of the Communist cause. But Beijing, in no hurry to take up the discarded banner of Soviet socialism, demurred, focusing instead on economic reform and a pragmatic foreign policy, dubbed taoguang yanghui (\u201chiding one\u2019s capabilities and biding one\u2019s time\u201d). China went on to establish diplomatic ties with South Korea, and although Beijing did not break with Pyongyang, the relationship never regained the intimacy of the early Cold War, when the two fought together against the United States. China and North Korea would never again be, in the words of Chinese leader Mao Zedong, \u201cas close as lips and teeth.\u201d\n\nFAILURE TO SIGNAL\n\nChinese leaders may be looking for lessons from the last time the superpowers faced off. Historians have conflicting answers about why the Cold War started: whether Joseph Stalin wanted it or whether it was an unfortunate accident. It seems plausible that what Stalin really wanted was a great-power compromise with the United States, according to which Moscow and Washington would respect each other\u2019s legitimate spheres of influence. The problems began when Washington and Stalin diverged on how far into Europe and Asia Moscow\u2019s legitimate sphere of influence should extend. Reacting to what it perceived as aggressive moves by Moscow, Washington, wary of underestimating Stalin\u2019s expansionist ambitions, pursued containment.\n\nBeijing\u2019s predicament today is that it does not know how to reassure the United States that it is not seeking another cold war even as it actively prepares to wage one. China\u2019s relentless nuclear buildup, its hostile espionage operations, its militant rhetoric, and, above all, its support for Russia suggest that Xi has already made his call and that a confrontation with the United States is inevitable.\n\nChina\u2019s relationships with Russia and North Korea remain useful in its struggle against Western hegemony. Chinese strategists think in simple geopolitical terms: the United States, leader of the West, is trying to bring China down; Putin is confronting the West with his war in Ukraine; therefore, Putin is helping China, and cannot be thrown under the bus. Similarly, China will not completely abandon North Korea, not because it approves of Kim, but because he remains a valuable weapon against the United States.\n\nOn the other hand, getting too invested in the relationship with a militant Russia would box Beijing in. Xi\u2019s fraternal embrace of Putin has damaged China\u2019s standing in Europe: German Foreign Minister Annalena Baerbock criticized China in December 2024 for \u201copposing our core European interests with its economic and weapons aid to Russia,\u201d and French President Emmanuel Macron pressed Xi to curb support for Moscow during their talks in May 2024. Given that China\u2019s trade relationship with the European Union is worth $762 billion and has become all the more critical amid China\u2019s economic stagnation, strategists in Beijing must ask themselves whether the economic polarization that would accompany an emerging cold war is really in China\u2019s interest. Foreign Minister Wang Yi, for his part, went out of his way at the Munich Security Conference in February 2025 to reassure European leaders that Beijing does not plan to overthrow the existing global order.\n\nYet as the experience of the present and previous centuries have shown, economic ties do not preclude great-power conflict. Putin\u2019s reckless gamble in Ukraine demonstrated his willingness to sacrifice lucrative economic ties to Europe for glory. And no Chinese diplomat or academic, no matter how well connected, can confidently speak for Xi who, like Putin, may yet choose confrontation with the West.\n\nTALK ISN\u2019T CHEAP\n\nOne of the most important ways that Xi will signal his intentions vis-\u00e0-vis the West will be the course he decides to take with Taiwan. \u201cNo one can ever sever the bond of kinship between [Taiwan and the mainland], and no one can ever stop China\u2019s reunification,\u201d he announced in his 2025 New Year message. Like his predecessors, Xi has refused to renounce the possible use of force to unify China and Taiwan. But unlike them, he has imbued his comments with a great sense of urgency, as if he has already made up his mind about invading Taiwan and is just waiting for an opportunity to do so.\n\nIt is possible, however, that Xi is genuinely undecided and is biding his time as he anticipates the U.S. response. Here, too, Cold War lessons apply. Stalin badly miscalculated Washington\u2019s response to the North Korean invasion of South Korea in 1950, in part because he concluded from intelligence gathered from cable intercepts that the United States would not intervene to defend South Korea. He failed to foresee how Washington\u2019s threat perceptions and policies had evolved in response to Moscow\u2019s aggressive moves. Xi, too, could conclude that Washington is not serious about Taiwan\u2019s defense and act accordingly. And like Stalin, he could err in his calculation, with even more tragic consequences for the world.\n\nJust as the escalations of the Cold War were contingent and gradual, with moments of tension punctuated by efforts to set things right, the U.S.-Chinese relationship today is not beyond redemption, even if it is far along the road to confrontation. If it does not want to proceed from learning about the Cold War to fighting a new one, the Chinese government should not act as if it does not want a dialogue with the United States.\n\nNicholas Burns, the U.S. ambassador to China during the Biden administration, faced diplomatic obstruction and had very little access to Chinese policymakers. China has snubbed the Pentagon\u2019s efforts to maintain military-to-military dialogue, and although former Secretary of Defense Lloyd Austin finally met his Chinese counterpart Dong Jun in May 2024, contacts remain sporadic. Such stonewalling could be a way to signal displeasure with what China perceives as Washington\u2019s hawkishness, but intentionally or not, it sends another message: that Beijing is already firmly set on a new cold war.\n\n The U.S.-Chinese relationship is not beyond redemption.\n\nBeijing should instead signal to Washington, in public or through private channels, that China does not plan to invade Taiwan in the foreseeable future. It should tone down public rhetoric about impending \u201creunification\u201d to provide a foundation for building desperately needed trust.\n\nBeijing should also make it clear that it does not seek an alliance with Moscow. The \u201cno limits\u201d partnership, which produced great alarm in the West with no gain to China, is a reminder that what Beijing says about its relationship with Russia can have direct impact on Western threat perceptions. The disappearance of \u201cantihegemonic\u201d language from Chinese-Russian statements will not eliminate U.S. concerns about an emerging axis, but it will at least chip away at the substantial evidence for such concerns.\n\nMost important, China\u2019s leaders should become more directly involved in helping end Russia\u2019s war in Ukraine. As the key buyer of Russia\u2019s hydrocarbons and a major provider of industrial and consumer goods to Russia, China has substantial economic leverage in the relationship, which it could deploy to encourage Putin to accept a cease-fire. A frozen conflict would not run counter to China\u2019s interest in avoiding escalation in Ukraine, it would stabilize relations with Europe and might even present an area of overlap between Beijing and the Trump administration, which has signaled its interest in a cease-fire regardless of a comprehensive settlement of the war. Given Wang\u2019s comments in Munich that \u201call parties and all stakeholders should, at an appropriate time, participate in the peace talks process\u201d and Trump\u2019s intention to hold peace talks with Russia, now is the time for China to signal its interest in a direct and substantive dialogue with the United States on the war in Ukraine.\n\nLEARNING FROM LAST TIME\n\nWhen clouds began to settle over the U.S.-Soviet relationship in 1945, President Harry S. Truman confidently predicted that he would get his way 85 percent of the time because, as he put it, \u201cthe Soviet Union needed us more than we needed them.\u201d The reality proved more complex. Fearing that the Americans would interpret any Soviet concessions as weakness, Stalin instructed his foreign minister, Vyacheslav Molotov, to \u201cdisplay complete obduracy.\u201d Today, the United States, without a nuclear monopoly and facing a much more powerful adversary in China, cannot aspire to Truman\u2019s predicted success rate. Active diplomacy, then, is Washington\u2019s best hope to mitigate and maybe even reverse the slide into confrontation with Beijing.\n\nFirst, the United States should redouble its efforts to dissuade Taiwan from proclaiming independence, a highly destabilizing move that would have dangerous consequences for East Asia and the world. Washington could tie its Taiwan diplomacy to private reassurance from China that it will not invade the island.\n\nAt the same time, the United States should also tell China frankly that Washington will be forced to prepare for a conflict over Taiwan unless Beijing shows through public statements and a demonstrated willingness to engage in confidence-building measures in East Asia that it is not seeking another cold war. Such measures could include reciprocating Trump\u2019s call for arms control, developing military-to-military contacts, and refraining from provocative military exercises.\n\n Active diplomacy is Washington\u2019s best hope to mitigate the slide into confrontation with Beijing.\n\nWhen he was national security adviser and secretary of state under President Richard Nixon, Henry Kissinger scolded Democrats for preaching human rights to the Soviet Union. He correctly understood that such posturing annoyed the Soviets and made diplomacy more difficult. He scored formidable victories against the Soviet Union by pioneering rapprochement with China and outfoxing the Kremlin in the Middle East nonetheless. The United States should now channel Kissinger in its approach to China and refrain from lecturing Beijing about democratic values, which alarm China\u2019s leaders and do little to improve human rights in China. Trump would seem to have a natural proclivity to avoid the subject, since he has never trafficked in the liberal internationalist language of his predecessors.\n\nTrump should also offer China a direct role in bringing Russia to the table to end the war in Ukraine. Beijing already has a point man for Russia and Ukraine in Ambassador Li Hui and has already issued statements about the need for peaceful resolution. By inviting Beijing to negotiations, Trump could test China\u2019s goodwill and, if an agreement is reached, make sure that China has a stake in implementing a cease-fire.\n\nFebruary 2025 marks the 75th anniversary of the signing of the Sino-Soviet treaty of alliance. The seemingly impregnable alliance was in fact riven by internal contradictions and lasted for only about ten years before it collapsed in a cloud of mutual accusations of betrayal. China\u2019s decision to pursue modernization and development in partnership, rather than in confrontation with the West, spared it from the Soviet Union\u2019s fate. Today, China and Russia are once again working together, but their relationship is not an alliance and is far from \u201cno limits.\u201d With the possibility of another cold war looming, China is uncertain about whether it really wants to lead an axis of obstinate and unreliable clients into confrontation with the United States. It is in both countries\u2019 interests to make use of this uncertainty to explore alternative arrangements.]]>\n  \n  \n    The Fatal Flaw of the New Middle East\n    https://www.foreignaffairs.com/middle-east/fatal-flaw-new-middle-east?utm_medium=newsletters&utm_source=fatoday&utm_campaign=The%20Fatal%20Flaw%20of%20the%20New%20Middle%20East&utm_content=20250217&utm_term=EDZZZ003ZX\n    readwise:01jmaj3y5fa7gz6bfdx2150sqe\n    Mon, 17 Feb 2025 18:18:22 +0000\n    Foreign Affairs\n    \nPalestinians returning home, Rafah, Gaza, January 2025\n\nOver the last 15 years, the Middle East has been racked by war, destruction, and displacement. Hundreds of thousands of people have died as fighting raged in Gaza, Lebanon, Libya, Sudan, Syria, and Yemen. Millions more have fled. The violence has rolled back gains in education, health, and income while laying waste to homes, schools, hospitals, roads, railways, and power grids. The war in Gaza has proved especially devastating, setting back the territory\u2019s socioeconomic indicators to 1955 levels. The World Bank and UN organizations have estimated that rebuilding the Middle East and providing enough humanitarian aid will cost between $350 and $650 billion. The UN Development Program has estimated that at least $40 to $50 billion is needed to rebuild Gaza alone.\n\nOffering these shattered societies humanitarian and monetary assistance is critical for the survival of millions, especially in the near term. It is thus deeply concerning that multiple Western governments, including Washington, are curtailing foreign aid and humanitarian assistance. But ultimately, the main obstacle to the Arab world\u2019s reconstruction will not be the lack of funds. It will be political disputes and grievances. The region is filled with failing states. It features competing powers that work to leverage this chaos to their geopolitical advantage. Together, these problems make permanent peace impossible.\n\nThe region\u2019s most powerful actors know this. Iran, Israel, the United States, and the Arab Gulf countries have all spent decades trying to shape the region to their liking without addressing the root causes of conflict, and they have repeatedly failed. They have sought security over peace and ended up with neither. And yet their current plans are strikingly similar, at least in spirit, to past efforts. All these countries are committing again to visions of a new regional order in which reconstruction takes place without political settlements. They have put forth lofty proposals\u2014Israeli-Saudi normalization, an economic pact between Iran and the Gulf states\u2014without considering political realities, local dynamics, or other, broader consequences. As a result, their plans will not put an end to cyclical violence. If anything, they will fuel it.\n\nTo achieve stability, the war-torn Middle East must shift course. Its powers must stop papering over regional and local divisions and instead do the hard work of addressing them. They need to help fractured societies come together. They must create accountable political institutions and promote systems of transitional justice. They need to support a reconstruction that is part of a broader peace-building agenda. They must create a political framework that actually recognizes the right of Palestinians to self-determination. And they need to figure out how to resolve, or at least better manage, their own differences. Otherwise, it doesn\u2019t matter how much the world spends on reconstruction. The region will remain broken.\n\nSubscribe to Foreign Affairs This Week\n\nOur editors\u2019 top picks, delivered free to your inbox every Friday.\n\nPROBLEM DODGING\n\nIn 1945, Europe lay in ruins. Tens of millions of people had been killed in six years of war. Millions more had been driven from their homes. Many of the continent\u2019s most prosperous cities had been demolished by bombs or shattered by artillery. Regional currencies had collapsed, reducing people to begging and bartering.\n\nIn response, the Truman administration called on Washington to dedicate itself to rebuilding the continent. Following the advice of U.S. Secretary of State George Marshall, Congress began passing massive aid packages for Europe\u2019s peoples and communities, spending $13.3 billion (over $170 billion in today\u2019s dollars) on the region. But this money came with conditions. Recipients had to remove most barriers to trade with other European states. They had to adopt policies that increased their exports to the United States and made them take in more American goods. The goal was not merely to reconstruct Europe\u2019s homes, roads, and bridges. It was to bring the continent into the emerging U.S.-led liberal order.\n\nThe strategy worked. The recipients of Marshall Plan funds joined the U.S.-led North Atlantic Treaty Organization, committing to collective defense. They enmeshed their economies, paving the way for the European Union. Thanks to these decisions, Europe not only economically recovered from the destruction of World War II but, after centuries of fighting, became one of the world\u2019s most peaceful and prosperous regions.\n\nThe scale of devastation across the Middle East today resembles that of Europe in 1945. The death tolls are staggering, if not quite as high. Entire economies have been wiped out. National currencies have lost most of their value: the Yemeni riyal has lost 80 percent of its value since 2014. The damage is most visible in Gaza, where, as of late January, the official death toll is over 47,000\u2014likely an underestimate\u2014and where Israeli bombardment reduced around 70 percent of its buildings to rubble in a little over a year. (The UN has projected that it will take more than a decade just to remove the wreckage.) But other countries have suffered similar losses. The 14-year Syrian civil war displaced 12 million people and killed over 600,000; over 90 percent of the country\u2019s residents now live below the international poverty line. In Yemen, more than half the population is now impoverished. Nearly 20 million people there need direct humanitarian assistance. Economic mismanagement and predatory practices have further contributed to economic decline, especially in Egypt, Iraq, and Lebanon.\n\n Israel and the United States cannot bring about peace by sidestepping the Palestinians.\n\nThe Middle East needs a Marshall Plan. But unlike in post\u2013World War II Europe, no country is stepping up. There is no single champion for the region, and there is no consensus on how to bring the area out of its quagmire. On the contrary, the Middle East is plagued by disunity and rivalry. The only thing the various American, Iranian, Israeli, Turkish, and Gulf proposals have in common is that they neglect fundamental challenges.\n\nConsider, first, the American approach. Washington believes the foundations of a better Middle East involve weakening Iran, the United States\u2019 primary regional rival, and normalizing relations between Israel and Saudi Arabia in the hope of unlocking new investments. Washington does want to contribute to the rebuilding of Gaza, although it believes the funds should largely come from Arab countries. But the American plan calls for reconstruction to take place without any horizon for a political solution for the Palestinians. Today, Washington\u2019s imaginary Gaza is either a space ethnically cleansed of Palestinians or an ungoverned political vacuum that would somehow remain stable.\n\nThe Israelis share this fantasy. But some of them want to be even more belligerent when it comes to Tehran and the Palestinians. Israelis are broadly supportive of the war in Gaza, and even after the January cease-fire, many want to return to bombing. The bellicosity of Israeli leaders has been boosted by their success in weakening Iran and Hezbollah\u2014the Lebanese militia Tehran backs. Israel wants to reconstruct Gaza only after Palestinians have been, in the words of former Israeli security officials Amos Yadlin and Avner Golov, \u201cderadicalized\u201d and have demonstrated they are capable of \u201ceffective governance.\u201d Some Israeli officials don\u2019t want to reconstruct it at all.\n\nThe Israeli vision is ethically wrong: the Palestinians have an unequivocal right to self-determination. It is also unworkable. Try as they might, Israel and the United States cannot bring about peace by sidestepping the Palestinians. In fact, attempting to do so is what got them here. During Donald Trump\u2019s first term as president, the United States coaxed Bahrain, Morocco, Sudan, and the United Arab Emirates (UAE) into normalizing relations with Israel as part of the Abraham Accords, creating what Trump hoped would be an Israeli-led security, trade, and investment compact. Israel, meanwhile, ramped up settlement construction, increased repression, and expanded its authority over the Palestinian territories. In response, Hamas launched its horrific October 7, 2023, attack. \u201cAll the normalization and recognition processes, all the agreements that have been signed [with Israel], can never put an end to this battle,\u201d said the Hamas leader Ismail Haniyeh, in explaining the assault.\n\n\nAn Hayat Tahrir al-Sham brigade celebrating the ouster of former Syrian President Bashar al-Assad, Damascus, December 2024\n\nThe attack sparked a furious Israeli response, which halted progress toward an Israeli-Saudi agreement and prompted Iran and its nonstate partners to jump into the fray. Israel had prevented this \u201caxis of resistance\u201d from causing substantial damage, and the Israel Defense Forces weakened Iran itself. But the Islamic Republic has responded with a peace proposal designed to undermine its nemesis, offering to join with its Arab neighbors in a nonaggression and economic pact aimed, in part, at isolating Israel.\n\nIt is true that many in the Arab world view the Islamic Republic as a regional force they need to engage with. And following the Israeli bombing campaigns in Gaza, Lebanon, Syria, and Yemen, the region\u2019s people now see Israel as the Middle East\u2019s most radical and destructive actor. But this does not make Iran\u2019s vision any more realistic. It papers over Iran\u2019s disruptive behavior across the region, including its sponsoring of violent nonstate actors and the resulting lawlessness and state failure. Iran\u2019s scheme does recognize the right to Palestinian self-determination. But Arab countries want an end to regional anarchy, not just an end to the Israeli-Palestinian conflict.\n\nThen there is a vision put forward by the Arab Gulf states\u2014Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the UAE\u2014through the Gulf Cooperation Council. It is perhaps the most aspirational. The council\u2019s proposals involve the Gulf countries deepening their own economic integration, establishing joint defense mechanisms, and then somehow resolving the Israeli-Palestinian conflict through a now practically impossible two-state solution. The proposal, like the Iranian one, at least acknowledges that an end to that conflict is the key to achieving regional security. But it lays out no plausible mechanism for reaching a deal. The Gulf state plan also says very little about the other conflicts in the region or how to address them.\n\nAt best, these various visions will accomplish little. At worst, they will generate even more conflict, as did the Abraham Accords. By focusing so much on security, they have turned peace into a matter of economic development and force. The Middle East\u2019s powers seem to think that war-torn peoples will be satisfied with new construction\u2014no need for justice, accountability, or good leadership. If people are not satisfied, they can be dealt with through violence: Israel, for example, can arrest and kill Palestinians who demand equal rights. Such assumptions are both dangerous and wrong.\n\nCHAOS REIGNS\n\nAt the heart of the region\u2019s troubles are questions of governance. Many countries have fractured or collapsed, with competing centers of power often dominated by particular ethnic or political groups. Nowhere is this dynamic more evident than in Syria, where years of war have weakened relations between the country\u2019s center and its periphery and given rise to a variety of local rulers. Some places are controlled by Kurds. The places where Assad maintained the highest levels of backing were those populated by his community of Alawites. The south is controlled by the so-called Southern Operations Room, a coalition of rebel factions that emerged in 2011 and tend to be less Islamist than other groups. The organization that ultimately drove Assad from power, Hayat Tahrir al-Sham (HTS), is composed of Sunni former jihadists that include non-Syrian combatants. They claim that they will not discriminate against other groups. But since they took Damascus, the country has seen an uptick in revenge killings and mob violence targeting Alawites. Without an inclusive political process, Syria will remain riven by all kinds of divisions.\n\nInternational involvement has hardened, and will continue to harden, such rifts. The Middle East\u2019s main powers perpetually compete for more regional influence, so when wars occur, those powers often back different groups. In Syria, for instance, Turkey supports HTS and other factions in the north. The United States is helping the Kurds. Jordan and the United Arab Emirates have considerable sway over Syria\u2019s Southern Operations Room. Israel is trying to bolster its ties with Syria\u2019s Druze community and has used the power vacuum to occupy some 155 square miles of Syrian land.\n\nFor now, Syria\u2019s factions are keeping the peace. Indeed, in a January 29 meeting, key groups involved in the overthrow of Assad came together to appoint the HTS leader Ahmad al-Shara as the country\u2019s new president. But although Ahmed al-Awda, the leading figure in the Southern Operations Room, sent a representative to this meeting, Awda did not attend. The Kurd and Druze factions boycotted it altogether. With their shared enemy gone, Syrian militias could turn on each other. If they do, Syria\u2019s future might look like Somalia\u2019s present, with different factions controlling various patches of territory. Or it might look like nearby Libya. Syria and Libya are very different countries, but Libya, too, experienced an Arab Spring revolution that pitted multiple armed groups against a longtime dictator. These groups succeeded in toppling Muammar al-Qaddafi in 2011. But once Qaddafi was gone, they began fighting each other for dominance with the support of external actors, including Turkey, the UAE, and a number of European states. Today, rival authorities in eastern and western parts of the country are each backed by different patrons.\n\n Reconstruction cannot fix broken institutions.\n\nAfter more than ten years of civil war, Yemen, much like Libya, is politically divided between two main rival authorities: the Houthis in the north and the Presidential Leadership Council. (The Houthis control a third of the country\u2019s area and two-thirds of the population.) Here, too, competition between outsiders has furthered conflict. Iran supports the Houthis. Saudi Arabia hosts the Presidential Leadership Council. But the Presidential Leadership Council is itself factious, and external competition leads to contention within it. The UAE, for instance, backs a group that, although part of the council, wants the southern part of Yemen to secede. Emirati-Saudi tensions over the oil-rich Yemeni province of Hadramawt have created further schisms, with Saudi Arabia generally controlling the province\u2019s interior and the UAE dominating the coast. Proxies affiliated with both powers have clashed, and the conflict between them could turn more violent in the months ahead. This chaos has, in turn, enabled al Qaeda in the Arabian Peninsula and other terrorist groups to expand their operations in Yemen\u2019s east and south.\n\nForeign meddling in the Middle East\u2019s conflicts is clearly bad for peace. But there is a silver lining to all the external involvement. Because the warring parties rely on international patrons, outside actors can push for resolutions. As a result, rapprochement between regional powers\u2014such as the 2023 normalization agreement between Iran and Saudi Arabia\u2014might help tamp down conflict.\n\nBut to be effective mediators, regional actors must more thoroughly settle their own differences. The escalating rivalry between Saudi Arabia and the UAE over which of them will be the Middle East\u2019s main Arab political and economic hub is one point of tension, especially when it comes to conflicts in Sudan, Syria, and Yemen. Qatar and Turkey\u2019s support for Islamist actors is creating problems with Egypt, Jordan, Saudi Arabia, and the UAE. And although the Iranian-Saudi rapprochement has softened sectarian divisions, it has not curtailed Iran\u2019s support for repressive nonstate actors. As a result, it can do little to promote regional tranquility.\n\nEven if these countries could fully sort out their rivalries, they could not ensure peace. They would still need to get local powers to implement settlements that rebuild states, ensure the safe return of displaced peoples, and mend torn social fabrics. And there is no guarantee that these actors, hardened by years of war, would comply. The issue of transitional justice, in particular, will be tricky. After fighting, some degree of forgiveness is required for societies to heal. Yet there cannot be broad amnesty, particularly for those responsible for human rights atrocities. At the end of its civil war, Lebanon opted to issue a blanket pardon for all atrocities committed during the 15-year conflict. Doing so, leaders thought, would quickly secure peace and allow the country to rebuild. They also hoped to protect themselves from prosecution. Instead, Lebanon has experienced periodic civil unrest as grievances from the war continue to fester, sometimes at the behest of the conflict\u2019s old leaders. To avoid the same fate, Syria\u2019s new leaders will have to hold key Assad officials accountable for the horrors committed over 54 years of autocratic rule. Failing to do so will only further encourage individual acts of vengeance\u2014which will, in turn, make it hard to secure a durable, peaceful resolution.\n\nNO JUSTICE, NO PEACE\n\nIn the Middle East, there is no one-size-fits-all approach to ending conflicts or rebuilding what was lost. The wars plaguing the region share many characteristics, but because they have been going on for years, they have developed their own dynamics. In Lebanon, for example, the challenge is not just rebuilding what was destroyed by the conflict with Israel. It is also about rebuilding a broken political system, trying to get Hezbollah to finally disarm, and strengthening weakened national institutions. Syria, totally ravaged by war, needs an entirely new political settlement. But Syria must not recentralize power, as it did during the Assad era. Whatever resolution emerges has to be supported across the country. It needs to account for local dynamics that materialized during the conflict.\n\nFor Gaza, the challenges are even more profound. There may be historical precedent for the scale and scope of the territory\u2019s destruction. Yet unlike other places reduced to ruin, Gaza is not a country. It does not control its borders. It is under siege, cut off from external markets. It lacks all kinds of basic resources, including water, food, and land for agricultural or industrial production. Under such conditions, it cannot be made habitable, let alone economically viable. And there is no clear plan for who will take the lead in rebuilding and then governing it. In the near term, Gaza may need to be administered by a transitional authority established by the UN Security Council: a mechanism that was used to help rebuild parts of the Balkans and Cambodia in the 1990s, when local governance capacity was destroyed. Eventually, it will need to be governed by Palestinians who command democratic support. But right now, no short- or long-term solutions are on offer.\n\nWithout political settlements, even doling out reconstruction funds will be difficult. In fact, the provision of assistance could create tension. Domestic and regional actors often manipulate aid deliveries, creating a skewed economy that leaves some people embittered and others emboldened. Political groups could also use aid to empower themselves at the expense of governments.\n\nNone of these challenges mean that humanitarian aid groups shouldn\u2019t flood the Middle East\u2019s many shattered places\u2014particularly Gaza\u2014with support. The region has millions of people who are homeless. It has millions more who are starving or require medical care. They need whatever help they can get, and they need it fast.\n\nThere is certainly a new Middle East in the making. Yet without a political solution, reconstruction will do little over the long term. It cannot fix the power imbalances, ethnic tensions, or broken institutions that cause ongoing bloodshed. It will not get foreign powers to work together, instead of at cross-purposes. It may help people literally rebuild their homes, stores, and schools. But until there\u2019s a durable peace, those buildings might just come crashing back down when conflict inevitably returns.\n\nLoading...\n\nYou are reading a free article\n\nSubscribe to Foreign Affairs to get unlimited access.\n\n\n Paywall-free reading of new articles and over a century of archives\n Six issues a year in print and online, plus audio articles\n Unlock access to the Foreign Affairs app for reading on the go\n\nAlready a subscriber? Sign In ]]>\n    \nPalestinians returning home, Rafah, Gaza, January 2025\n\nOver the last 15 years, the Middle East has been racked by war, destruction, and displacement. Hundreds of thousands of people have died as fighting raged in Gaza, Lebanon, Libya, Sudan, Syria, and Yemen. Millions more have fled. The violence has rolled back gains in education, health, and income while laying waste to homes, schools, hospitals, roads, railways, and power grids. The war in Gaza has proved especially devastating, setting back the territory\u2019s socioeconomic indicators to 1955 levels. The World Bank and UN organizations have estimated that rebuilding the Middle East and providing enough humanitarian aid will cost between $350 and $650 billion. The UN Development Program has estimated that at least $40 to $50 billion is needed to rebuild Gaza alone.\n\nOffering these shattered societies humanitarian and monetary assistance is critical for the survival of millions, especially in the near term. It is thus deeply concerning that multiple Western governments, including Washington, are curtailing foreign aid and humanitarian assistance. But ultimately, the main obstacle to the Arab world\u2019s reconstruction will not be the lack of funds. It will be political disputes and grievances. The region is filled with failing states. It features competing powers that work to leverage this chaos to their geopolitical advantage. Together, these problems make permanent peace impossible.\n\nThe region\u2019s most powerful actors know this. Iran, Israel, the United States, and the Arab Gulf countries have all spent decades trying to shape the region to their liking without addressing the root causes of conflict, and they have repeatedly failed. They have sought security over peace and ended up with neither. And yet their current plans are strikingly similar, at least in spirit, to past efforts. All these countries are committing again to visions of a new regional order in which reconstruction takes place without political settlements. They have put forth lofty proposals\u2014Israeli-Saudi normalization, an economic pact between Iran and the Gulf states\u2014without considering political realities, local dynamics, or other, broader consequences. As a result, their plans will not put an end to cyclical violence. If anything, they will fuel it.\n\nTo achieve stability, the war-torn Middle East must shift course. Its powers must stop papering over regional and local divisions and instead do the hard work of addressing them. They need to help fractured societies come together. They must create accountable political institutions and promote systems of transitional justice. They need to support a reconstruction that is part of a broader peace-building agenda. They must create a political framework that actually recognizes the right of Palestinians to self-determination. And they need to figure out how to resolve, or at least better manage, their own differences. Otherwise, it doesn\u2019t matter how much the world spends on reconstruction. The region will remain broken.\n\nSubscribe to Foreign Affairs This Week\n\nOur editors\u2019 top picks, delivered free to your inbox every Friday.\n\nPROBLEM DODGING\n\nIn 1945, Europe lay in ruins. Tens of millions of people had been killed in six years of war. Millions more had been driven from their homes. Many of the continent\u2019s most prosperous cities had been demolished by bombs or shattered by artillery. Regional currencies had collapsed, reducing people to begging and bartering.\n\nIn response, the Truman administration called on Washington to dedicate itself to rebuilding the continent. Following the advice of U.S. Secretary of State George Marshall, Congress began passing massive aid packages for Europe\u2019s peoples and communities, spending $13.3 billion (over $170 billion in today\u2019s dollars) on the region. But this money came with conditions. Recipients had to remove most barriers to trade with other European states. They had to adopt policies that increased their exports to the United States and made them take in more American goods. The goal was not merely to reconstruct Europe\u2019s homes, roads, and bridges. It was to bring the continent into the emerging U.S.-led liberal order.\n\nThe strategy worked. The recipients of Marshall Plan funds joined the U.S.-led North Atlantic Treaty Organization, committing to collective defense. They enmeshed their economies, paving the way for the European Union. Thanks to these decisions, Europe not only economically recovered from the destruction of World War II but, after centuries of fighting, became one of the world\u2019s most peaceful and prosperous regions.\n\nThe scale of devastation across the Middle East today resembles that of Europe in 1945. The death tolls are staggering, if not quite as high. Entire economies have been wiped out. National currencies have lost most of their value: the Yemeni riyal has lost 80 percent of its value since 2014. The damage is most visible in Gaza, where, as of late January, the official death toll is over 47,000\u2014likely an underestimate\u2014and where Israeli bombardment reduced around 70 percent of its buildings to rubble in a little over a year. (The UN has projected that it will take more than a decade just to remove the wreckage.) But other countries have suffered similar losses. The 14-year Syrian civil war displaced 12 million people and killed over 600,000; over 90 percent of the country\u2019s residents now live below the international poverty line. In Yemen, more than half the population is now impoverished. Nearly 20 million people there need direct humanitarian assistance. Economic mismanagement and predatory practices have further contributed to economic decline, especially in Egypt, Iraq, and Lebanon.\n\n Israel and the United States cannot bring about peace by sidestepping the Palestinians.\n\nThe Middle East needs a Marshall Plan. But unlike in post\u2013World War II Europe, no country is stepping up. There is no single champion for the region, and there is no consensus on how to bring the area out of its quagmire. On the contrary, the Middle East is plagued by disunity and rivalry. The only thing the various American, Iranian, Israeli, Turkish, and Gulf proposals have in common is that they neglect fundamental challenges.\n\nConsider, first, the American approach. Washington believes the foundations of a better Middle East involve weakening Iran, the United States\u2019 primary regional rival, and normalizing relations between Israel and Saudi Arabia in the hope of unlocking new investments. Washington does want to contribute to the rebuilding of Gaza, although it believes the funds should largely come from Arab countries. But the American plan calls for reconstruction to take place without any horizon for a political solution for the Palestinians. Today, Washington\u2019s imaginary Gaza is either a space ethnically cleansed of Palestinians or an ungoverned political vacuum that would somehow remain stable.\n\nThe Israelis share this fantasy. But some of them want to be even more belligerent when it comes to Tehran and the Palestinians. Israelis are broadly supportive of the war in Gaza, and even after the January cease-fire, many want to return to bombing. The bellicosity of Israeli leaders has been boosted by their success in weakening Iran and Hezbollah\u2014the Lebanese militia Tehran backs. Israel wants to reconstruct Gaza only after Palestinians have been, in the words of former Israeli security officials Amos Yadlin and Avner Golov, \u201cderadicalized\u201d and have demonstrated they are capable of \u201ceffective governance.\u201d Some Israeli officials don\u2019t want to reconstruct it at all.\n\nThe Israeli vision is ethically wrong: the Palestinians have an unequivocal right to self-determination. It is also unworkable. Try as they might, Israel and the United States cannot bring about peace by sidestepping the Palestinians. In fact, attempting to do so is what got them here. During Donald Trump\u2019s first term as president, the United States coaxed Bahrain, Morocco, Sudan, and the United Arab Emirates (UAE) into normalizing relations with Israel as part of the Abraham Accords, creating what Trump hoped would be an Israeli-led security, trade, and investment compact. Israel, meanwhile, ramped up settlement construction, increased repression, and expanded its authority over the Palestinian territories. In response, Hamas launched its horrific October 7, 2023, attack. \u201cAll the normalization and recognition processes, all the agreements that have been signed [with Israel], can never put an end to this battle,\u201d said the Hamas leader Ismail Haniyeh, in explaining the assault.\n\n\nAn Hayat Tahrir al-Sham brigade celebrating the ouster of former Syrian President Bashar al-Assad, Damascus, December 2024\n\nThe attack sparked a furious Israeli response, which halted progress toward an Israeli-Saudi agreement and prompted Iran and its nonstate partners to jump into the fray. Israel had prevented this \u201caxis of resistance\u201d from causing substantial damage, and the Israel Defense Forces weakened Iran itself. But the Islamic Republic has responded with a peace proposal designed to undermine its nemesis, offering to join with its Arab neighbors in a nonaggression and economic pact aimed, in part, at isolating Israel.\n\nIt is true that many in the Arab world view the Islamic Republic as a regional force they need to engage with. And following the Israeli bombing campaigns in Gaza, Lebanon, Syria, and Yemen, the region\u2019s people now see Israel as the Middle East\u2019s most radical and destructive actor. But this does not make Iran\u2019s vision any more realistic. It papers over Iran\u2019s disruptive behavior across the region, including its sponsoring of violent nonstate actors and the resulting lawlessness and state failure. Iran\u2019s scheme does recognize the right to Palestinian self-determination. But Arab countries want an end to regional anarchy, not just an end to the Israeli-Palestinian conflict.\n\nThen there is a vision put forward by the Arab Gulf states\u2014Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the UAE\u2014through the Gulf Cooperation Council. It is perhaps the most aspirational. The council\u2019s proposals involve the Gulf countries deepening their own economic integration, establishing joint defense mechanisms, and then somehow resolving the Israeli-Palestinian conflict through a now practically impossible two-state solution. The proposal, like the Iranian one, at least acknowledges that an end to that conflict is the key to achieving regional security. But it lays out no plausible mechanism for reaching a deal. The Gulf state plan also says very little about the other conflicts in the region or how to address them.\n\nAt best, these various visions will accomplish little. At worst, they will generate even more conflict, as did the Abraham Accords. By focusing so much on security, they have turned peace into a matter of economic development and force. The Middle East\u2019s powers seem to think that war-torn peoples will be satisfied with new construction\u2014no need for justice, accountability, or good leadership. If people are not satisfied, they can be dealt with through violence: Israel, for example, can arrest and kill Palestinians who demand equal rights. Such assumptions are both dangerous and wrong.\n\nCHAOS REIGNS\n\nAt the heart of the region\u2019s troubles are questions of governance. Many countries have fractured or collapsed, with competing centers of power often dominated by particular ethnic or political groups. Nowhere is this dynamic more evident than in Syria, where years of war have weakened relations between the country\u2019s center and its periphery and given rise to a variety of local rulers. Some places are controlled by Kurds. The places where Assad maintained the highest levels of backing were those populated by his community of Alawites. The south is controlled by the so-called Southern Operations Room, a coalition of rebel factions that emerged in 2011 and tend to be less Islamist than other groups. The organization that ultimately drove Assad from power, Hayat Tahrir al-Sham (HTS), is composed of Sunni former jihadists that include non-Syrian combatants. They claim that they will not discriminate against other groups. But since they took Damascus, the country has seen an uptick in revenge killings and mob violence targeting Alawites. Without an inclusive political process, Syria will remain riven by all kinds of divisions.\n\nInternational involvement has hardened, and will continue to harden, such rifts. The Middle East\u2019s main powers perpetually compete for more regional influence, so when wars occur, those powers often back different groups. In Syria, for instance, Turkey supports HTS and other factions in the north. The United States is helping the Kurds. Jordan and the United Arab Emirates have considerable sway over Syria\u2019s Southern Operations Room. Israel is trying to bolster its ties with Syria\u2019s Druze community and has used the power vacuum to occupy some 155 square miles of Syrian land.\n\nFor now, Syria\u2019s factions are keeping the peace. Indeed, in a January 29 meeting, key groups involved in the overthrow of Assad came together to appoint the HTS leader Ahmad al-Shara as the country\u2019s new president. But although Ahmed al-Awda, the leading figure in the Southern Operations Room, sent a representative to this meeting, Awda did not attend. The Kurd and Druze factions boycotted it altogether. With their shared enemy gone, Syrian militias could turn on each other. If they do, Syria\u2019s future might look like Somalia\u2019s present, with different factions controlling various patches of territory. Or it might look like nearby Libya. Syria and Libya are very different countries, but Libya, too, experienced an Arab Spring revolution that pitted multiple armed groups against a longtime dictator. These groups succeeded in toppling Muammar al-Qaddafi in 2011. But once Qaddafi was gone, they began fighting each other for dominance with the support of external actors, including Turkey, the UAE, and a number of European states. Today, rival authorities in eastern and western parts of the country are each backed by different patrons.\n\n Reconstruction cannot fix broken institutions.\n\nAfter more than ten years of civil war, Yemen, much like Libya, is politically divided between two main rival authorities: the Houthis in the north and the Presidential Leadership Council. (The Houthis control a third of the country\u2019s area and two-thirds of the population.) Here, too, competition between outsiders has furthered conflict. Iran supports the Houthis. Saudi Arabia hosts the Presidential Leadership Council. But the Presidential Leadership Council is itself factious, and external competition leads to contention within it. The UAE, for instance, backs a group that, although part of the council, wants the southern part of Yemen to secede. Emirati-Saudi tensions over the oil-rich Yemeni province of Hadramawt have created further schisms, with Saudi Arabia generally controlling the province\u2019s interior and the UAE dominating the coast. Proxies affiliated with both powers have clashed, and the conflict between them could turn more violent in the months ahead. This chaos has, in turn, enabled al Qaeda in the Arabian Peninsula and other terrorist groups to expand their operations in Yemen\u2019s east and south.\n\nForeign meddling in the Middle East\u2019s conflicts is clearly bad for peace. But there is a silver lining to all the external involvement. Because the warring parties rely on international patrons, outside actors can push for resolutions. As a result, rapprochement between regional powers\u2014such as the 2023 normalization agreement between Iran and Saudi Arabia\u2014might help tamp down conflict.\n\nBut to be effective mediators, regional actors must more thoroughly settle their own differences. The escalating rivalry between Saudi Arabia and the UAE over which of them will be the Middle East\u2019s main Arab political and economic hub is one point of tension, especially when it comes to conflicts in Sudan, Syria, and Yemen. Qatar and Turkey\u2019s support for Islamist actors is creating problems with Egypt, Jordan, Saudi Arabia, and the UAE. And although the Iranian-Saudi rapprochement has softened sectarian divisions, it has not curtailed Iran\u2019s support for repressive nonstate actors. As a result, it can do little to promote regional tranquility.\n\nEven if these countries could fully sort out their rivalries, they could not ensure peace. They would still need to get local powers to implement settlements that rebuild states, ensure the safe return of displaced peoples, and mend torn social fabrics. And there is no guarantee that these actors, hardened by years of war, would comply. The issue of transitional justice, in particular, will be tricky. After fighting, some degree of forgiveness is required for societies to heal. Yet there cannot be broad amnesty, particularly for those responsible for human rights atrocities. At the end of its civil war, Lebanon opted to issue a blanket pardon for all atrocities committed during the 15-year conflict. Doing so, leaders thought, would quickly secure peace and allow the country to rebuild. They also hoped to protect themselves from prosecution. Instead, Lebanon has experienced periodic civil unrest as grievances from the war continue to fester, sometimes at the behest of the conflict\u2019s old leaders. To avoid the same fate, Syria\u2019s new leaders will have to hold key Assad officials accountable for the horrors committed over 54 years of autocratic rule. Failing to do so will only further encourage individual acts of vengeance\u2014which will, in turn, make it hard to secure a durable, peaceful resolution.\n\nNO JUSTICE, NO PEACE\n\nIn the Middle East, there is no one-size-fits-all approach to ending conflicts or rebuilding what was lost. The wars plaguing the region share many characteristics, but because they have been going on for years, they have developed their own dynamics. In Lebanon, for example, the challenge is not just rebuilding what was destroyed by the conflict with Israel. It is also about rebuilding a broken political system, trying to get Hezbollah to finally disarm, and strengthening weakened national institutions. Syria, totally ravaged by war, needs an entirely new political settlement. But Syria must not recentralize power, as it did during the Assad era. Whatever resolution emerges has to be supported across the country. It needs to account for local dynamics that materialized during the conflict.\n\nFor Gaza, the challenges are even more profound. There may be historical precedent for the scale and scope of the territory\u2019s destruction. Yet unlike other places reduced to ruin, Gaza is not a country. It does not control its borders. It is under siege, cut off from external markets. It lacks all kinds of basic resources, including water, food, and land for agricultural or industrial production. Under such conditions, it cannot be made habitable, let alone economically viable. And there is no clear plan for who will take the lead in rebuilding and then governing it. In the near term, Gaza may need to be administered by a transitional authority established by the UN Security Council: a mechanism that was used to help rebuild parts of the Balkans and Cambodia in the 1990s, when local governance capacity was destroyed. Eventually, it will need to be governed by Palestinians who command democratic support. But right now, no short- or long-term solutions are on offer.\n\nWithout political settlements, even doling out reconstruction funds will be difficult. In fact, the provision of assistance could create tension. Domestic and regional actors often manipulate aid deliveries, creating a skewed economy that leaves some people embittered and others emboldened. Political groups could also use aid to empower themselves at the expense of governments.\n\nNone of these challenges mean that humanitarian aid groups shouldn\u2019t flood the Middle East\u2019s many shattered places\u2014particularly Gaza\u2014with support. The region has millions of people who are homeless. It has millions more who are starving or require medical care. They need whatever help they can get, and they need it fast.\n\nThere is certainly a new Middle East in the making. Yet without a political solution, reconstruction will do little over the long term. It cannot fix the power imbalances, ethnic tensions, or broken institutions that cause ongoing bloodshed. It will not get foreign powers to work together, instead of at cross-purposes. It may help people literally rebuild their homes, stores, and schools. But until there\u2019s a durable peace, those buildings might just come crashing back down when conflict inevitably returns.\n\nLoading...\n\nYou are reading a free article\n\nSubscribe to Foreign Affairs to get unlimited access.\n\n\n Paywall-free reading of new articles and over a century of archives\n Six issues a year in print and online, plus audio articles\n Unlock access to the Foreign Affairs app for reading on the go\n\nAlready a subscriber? Sign In ]]>\n  \n  \n    I need a lesson on mcp\n    https://x.com/rileybrown_ai/status/1891015518062002581/?s=12&rw_tt_thread=True\n    readwise:01jm9q7fc7hsxte7d1p384zcap\n    Mon, 17 Feb 2025 10:28:27 +0000\n    X (formerly Twitter)\n    \nI need a lesson on mcp. Someone help\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Tony Dinh \ud83c\udfaf\n                    @tdinh_me\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nDo you think MCP has a future?\n            \n            \n\n                \n                    Posted Feb 16, 2025 at 2:52AM\n                \n            \n        ]]>\n    \nI need a lesson on mcp. Someone help\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Tony Dinh \ud83c\udfaf\n                    @tdinh_me\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nDo you think MCP has a future?\n            \n            \n\n                \n                    Posted Feb 16, 2025 at 2:52AM\n                \n            \n        ]]>\n  \n  \n    Unnamed Document\n    https://x.com/thecjpearson?s=11\n    readwise:01jm9q0vgpny69bbccws1yrkna\n    Mon, 17 Feb 2025 10:24:50 +0000\n    X (formerly Twitter)\n    Unnamed Document]]>\n    Unnamed Document]]>\n  \n  \n    A single wallet made $9mn on Melania, $5mn on Libra...\n    https://x.com/punk9059/status/1891140252502294566/?s=12&rw_tt_thread=True\n    readwise:01jm882vsdmgspb41pz8fj48pa\n    Sun, 16 Feb 2025 20:44:32 +0000\n    X (formerly Twitter)\n    \nA single wallet made $9mn on Melania, $5mn on Libra, $3mn on Trump and $670k on JellyJelly.\nThis wallet ALSO bought 10%+ of $HARRYBOLZ a few days before Elon changed his name.\nGlued-to-screen trench warrior?  What are the signals one could look at to crush like this?]]>\n    \nA single wallet made $9mn on Melania, $5mn on Libra, $3mn on Trump and $670k on JellyJelly.\nThis wallet ALSO bought 10%+ of $HARRYBOLZ a few days before Elon changed his name.\nGlued-to-screen trench warrior?  What are the signals one could look at to crush like this?]]>\n  \n  \n    Most people are still prompting wrong\n    https://x.com/aakashg0/status/1890492955842007087/?s=12&rw_tt_thread=True\n    readwise:01jm7yjxydgvy597n1h5ptxmch\n    Sun, 16 Feb 2025 17:58:33 +0000\n    X (formerly Twitter)\n    \nMost people are still prompting wrong.\nI've found this framework, which was even shared by OpenAI President Greg Brockman.\nHere\u2019s how it works:\n\n\ud835\udde7\ud835\uddf5\ud835\uddf2 \ud835\udde5\ud835\uddf2\ud835\uddee\ud835\ude00\ud835\uddfc\ud835\uddfb\ud835\uddf6\ud835\uddfb\ud835\uddf4\n4 words in lowercase doesn\u2019t work.\nIf you want to write a PRD, or a product strategy, or something for work, you have to help the LLM get your context. \nThis is done in 4 parts.\n\n\ud835\udde2\ud835\uddfb\ud835\uddf2 - \ud835\uddda\ud835\uddfc\ud835\uddee\ud835\uddf9\nLLMs know millions of ways to complete a task. \nClear goal language helps them narrow in on the way you want them to. \nEG: \u201cI want to create a Google-level Product Requirements Document for: <Feature>\u201d\n\n\ud835\udde7\ud835\ude04\ud835\uddfc - \ud835\udde5\ud835\uddf2\ud835\ude01\ud835\ude02\ud835\uddff\ud835\uddfb \ud835\uddd9\ud835\uddfc\ud835\uddff\ud835\uddfa\ud835\uddee\ud835\ude01\nThe return format is really important, because there are so many styles.\nIdeally, you can even create bespoke templates for bespoke tasks.\nEG: \u201cOur PRD template is: <Paste>\u201d \nAnd the template has all the right headers and descriptions.\n\n\ud835\udde7\ud835\uddf5\ud835\uddff\ud835\uddf2\ud835\uddf2 - \ud835\uddea\ud835\uddee\ud835\uddff\ud835\uddfb\ud835\uddf6\ud835\uddfb\ud835\uddf4\ud835\ude00\nTell the LLM what not to do as well as what to do. \nEG: \u201cPrior PRDs that were too long or flowery were not well received. \nFocus on concise and specific to our app.\u201d\nDon\u2019t assume it has your brain.\n\n\ud835\uddd9\ud835\uddfc\ud835\ude02\ud835\uddff - \ud835\uddd6\ud835\uddfc\ud835\uddfb\ud835\ude01\ud835\uddf2\ud835\ude05\ud835\ude01 \ud835\uddd7\ud835\ude02\ud835\uddfa\ud835\uddfd\nThis is where you paste in the user research, data, and meeting notes that you have. \nEG: \u201cHere\u2019s a transcript of a recent meeting where we finalized most of it\u201d\nYou do have to be careful on not pasting too much.\n\n\ud835\udddf\ud835\uddf2\ud835\uddee\ud835\uddff\ud835\uddfb \ud835\udde0\ud835\uddfc\ud835\uddff\ud835\uddf2\nWant to learn more about how to use AI as a PM? \nI\u2019m going live with @teamuserpilot on February 19th at 11am est.\nSign up here: pages.userpilot.com/events/how-to-\u2026\n\nShoutout to Dan Mac for this great prompting framework. \nYou can find my full guide to AI-Powered PM here: userpilot.com/blog/pitt/how-\u2026\nPMs won\u2019t be replaced by AI. But some will be replaced by PMs using AI better than them.]]>\n    \nMost people are still prompting wrong.\nI've found this framework, which was even shared by OpenAI President Greg Brockman.\nHere\u2019s how it works:\n\n\ud835\udde7\ud835\uddf5\ud835\uddf2 \ud835\udde5\ud835\uddf2\ud835\uddee\ud835\ude00\ud835\uddfc\ud835\uddfb\ud835\uddf6\ud835\uddfb\ud835\uddf4\n4 words in lowercase doesn\u2019t work.\nIf you want to write a PRD, or a product strategy, or something for work, you have to help the LLM get your context. \nThis is done in 4 parts.\n\n\ud835\udde2\ud835\uddfb\ud835\uddf2 - \ud835\uddda\ud835\uddfc\ud835\uddee\ud835\uddf9\nLLMs know millions of ways to complete a task. \nClear goal language helps them narrow in on the way you want them to. \nEG: \u201cI want to create a Google-level Product Requirements Document for: <Feature>\u201d\n\n\ud835\udde7\ud835\ude04\ud835\uddfc - \ud835\udde5\ud835\uddf2\ud835\ude01\ud835\ude02\ud835\uddff\ud835\uddfb \ud835\uddd9\ud835\uddfc\ud835\uddff\ud835\uddfa\ud835\uddee\ud835\ude01\nThe return format is really important, because there are so many styles.\nIdeally, you can even create bespoke templates for bespoke tasks.\nEG: \u201cOur PRD template is: <Paste>\u201d \nAnd the template has all the right headers and descriptions.\n\n\ud835\udde7\ud835\uddf5\ud835\uddff\ud835\uddf2\ud835\uddf2 - \ud835\uddea\ud835\uddee\ud835\uddff\ud835\uddfb\ud835\uddf6\ud835\uddfb\ud835\uddf4\ud835\ude00\nTell the LLM what not to do as well as what to do. \nEG: \u201cPrior PRDs that were too long or flowery were not well received. \nFocus on concise and specific to our app.\u201d\nDon\u2019t assume it has your brain.\n\n\ud835\uddd9\ud835\uddfc\ud835\ude02\ud835\uddff - \ud835\uddd6\ud835\uddfc\ud835\uddfb\ud835\ude01\ud835\uddf2\ud835\ude05\ud835\ude01 \ud835\uddd7\ud835\ude02\ud835\uddfa\ud835\uddfd\nThis is where you paste in the user research, data, and meeting notes that you have. \nEG: \u201cHere\u2019s a transcript of a recent meeting where we finalized most of it\u201d\nYou do have to be careful on not pasting too much.\n\n\ud835\udddf\ud835\uddf2\ud835\uddee\ud835\uddff\ud835\uddfb \ud835\udde0\ud835\uddfc\ud835\uddff\ud835\uddf2\nWant to learn more about how to use AI as a PM? \nI\u2019m going live with @teamuserpilot on February 19th at 11am est.\nSign up here: pages.userpilot.com/events/how-to-\u2026\n\nShoutout to Dan Mac for this great prompting framework. \nYou can find my full guide to AI-Powered PM here: userpilot.com/blog/pitt/how-\u2026\nPMs won\u2019t be replaced by AI. But some will be replaced by PMs using AI better than them.]]>\n  \n  \n    Astonishing shitcoinery by Milei, shocking even to shitcoiners\n    https://x.com/saifedean/status/1890724929168912636/?s=12&rw_tt_thread=True\n    readwise:01jm7yfx87gsjva642wfmt1njc\n    Sun, 16 Feb 2025 17:56:54 +0000\n    X (formerly Twitter)\n    \nAstonishing shitcoinery by Milei, shocking even to shitcoiners.\nHe marketed a shitcoin to support the growth of Argentina, received millions of dollars from fans worldwide, dumped his coins, tanking the coin 95%, deleted the tweet, and now expects everyone to just move on.]]>\n    \nAstonishing shitcoinery by Milei, shocking even to shitcoiners.\nHe marketed a shitcoin to support the growth of Argentina, received millions of dollars from fans worldwide, dumped his coins, tanking the coin 95%, deleted the tweet, and now expects everyone to just move on.]]>\n  \n  \n    J'ai parl\u00e9 aujourd'hui avec le Pr\u00e9sident de l\u2019Autorit\u00e9 palestinienne Mahmoud...\n    https://x.com/emmanuelmacron/status/1891162052082733076/?s=12&rw_tt_thread=True\n    readwise:01jm7t6zfvfjfhhnqpff4d922s\n    Sun, 16 Feb 2025 16:42:07 +0000\n    X (formerly Twitter)\n    \nJ'ai parl\u00e9 aujourd'hui avec le Pr\u00e9sident de l\u2019Autorit\u00e9 palestinienne Mahmoud Abbas.\nJe lui ai redit ma satisfaction de voir la premi\u00e8re \u00e9tape du cessez-le-feu \u00eatre respect\u00e9e.   Chaque otage lib\u00e9r\u00e9 est un soulagement immense. Chaque jour sans frappe, chaque action humanitaire, un espoir pour Gaza.\nLe cessez-le-feu doit se poursuivre dans la dur\u00e9e.\nNous avons discut\u00e9 du plan propos\u00e9 par nos partenaires arabes et de ses modalit\u00e9s pour Gaza. \nAvec l\u2019Arabie Saoudite, la France travaille avec tous ses partenaires r\u00e9gionaux et internationaux \u00e0 un objectif clair : d\u00e9finir une feuille de route cr\u00e9dible vers la mise en \u0153uvre de la solution \u00e0 deux \u00c9tats, seule \u00e0 m\u00eame de garantir la paix et la s\u00e9curit\u00e9 de tous dans la r\u00e9gion.]]>\n    \nJ'ai parl\u00e9 aujourd'hui avec le Pr\u00e9sident de l\u2019Autorit\u00e9 palestinienne Mahmoud Abbas.\nJe lui ai redit ma satisfaction de voir la premi\u00e8re \u00e9tape du cessez-le-feu \u00eatre respect\u00e9e.   Chaque otage lib\u00e9r\u00e9 est un soulagement immense. Chaque jour sans frappe, chaque action humanitaire, un espoir pour Gaza.\nLe cessez-le-feu doit se poursuivre dans la dur\u00e9e.\nNous avons discut\u00e9 du plan propos\u00e9 par nos partenaires arabes et de ses modalit\u00e9s pour Gaza. \nAvec l\u2019Arabie Saoudite, la France travaille avec tous ses partenaires r\u00e9gionaux et internationaux \u00e0 un objectif clair : d\u00e9finir une feuille de route cr\u00e9dible vers la mise en \u0153uvre de la solution \u00e0 deux \u00c9tats, seule \u00e0 m\u00eame de garantir la paix et la s\u00e9curit\u00e9 de tous dans la r\u00e9gion.]]>\n  \n  \n    What Gazans Want\n    https://www.foreignaffairs.com/israel/what-gazans-want\n    readwise:01jm7psx35h9ka739578k85vqs\n    Sun, 16 Feb 2025 15:42:33 +0000\n    Foreign Affairs\n    \nResidents returning to Gaza City after an Israeli withdrawal, February 2025 Dawoud Abu Alkas / Reuters \n\n\n\n\n\n\n\n\nIn the weeks since Israel\u2019s fragile January 19 cease-fire and hostages-for-prisoners deal with Hamas, the issue of what should happen to Gaza and its 2.1 million inhabitants has come starkly into view. The war has reduced much of Gaza to ruins, with its schools, hospitals, civilian infrastructure and ecology now largely destroyed and a huge portion of its population lacking adequate shelter. The constant threat of the cease-fire\u2019s breakdown has fueled its own daily dread of further devastation. Even as U.S. President Donald Trump has floated chimerical ideas about an eventual U.S. \u201ctakeover\u201d of Gaza and the permanent relocation of its population, external powers have made little progress on formulating a strategy for governance and security in the territory now.\n\nStrangely absent from this debate are Gazans themselves. It is reasonable to assume that more than 15 months of pulverizing conflict have changed the perceptions of ordinary civilians in the territory about what they want for their future, how they see their land, who they think should be their rulers, and what they consider to be the most plausible pathways to peace. Given the extraordinary price they have paid for Hamas\u2019s actions on October 7, 2023, Gazans might be expected to reject the group and favor a different leadership. Similarly, outside observers might anticipate that after so much hardship, Gazans would be more prepared to compromise on larger political aspirations in favor of more urgent human needs.\n\nIn fact, a survey we conducted in Gaza in early January, shortly before the cease-fire came into effect, tells a more complicated story. The representative survey was formulated by the research group Artis International and Oxford University\u2019s Changing Character of War Centre and carried out by the Palestinian Center for Policy and Survey Research (PSR). Using census data and sampling people in shelters based on the locations of their original homes to ensure geographic diversity, the survey comprised 500 face-to-face interviews with Gazans\u2014248 women and 252 men\u2014ranging in age from 18 to 83. The margin of error was plus or minus four percentage points.\n\nThe survey found that although Hamas\u2019s popular appeal has declined precipitously since the early months of the war, current alternatives to the group draw even less support, which opens the way for Hamas to shore up its influence over Gaza again. The war has also strengthened rather than weakened Gazans\u2019 commitments to maximalist political goals, while eroding support for a two-state solution. Perhaps most strikingly, the survey showed that the people of Gaza continue to retain strong core values related to their Palestinian and religious identity and their attachment to the land, values that they intend to uphold even if doing so requires great personal sacrifice. As the United States and its regional and international partners confront the reality of postwar Gaza, the survey findings may challenge the assumption that any movement toward peace with Israel can be found that does not satisfy\u2014or at least symbolically recognize\u2014some of these basic values.\n\nTHE GOVERNANCE GAP\n\nIn one of the primary questions in the survey, respondents were asked to select which of several possible resolutions to the Israeli-Palestinian conflict they viewed as both acceptable and realistic. Before the war in Gaza began, research showed that a clear majority of Palestinians in Gaza supported a two-state solution whereas just 20 percent supported a military solution that could result in the destruction of the state of Israel. In the January survey, less than half, or 48 percent, still preferred a two-state solution, while nearly as many, 47 percent, preferred the dissolution of Israel. A mere five percent viewed a third alternative, a democratic, binational state with equal rights for Arabs and Jews, as acceptable and realistic.\n\nMoreover, although partition was deemed acceptable and realistic by 48 percent, just 20 percent supported a two-state solution conforming to United Nations resolutions based on the 1967 borders. The rest of those supporting a partition favored two-state solutions that either required \u201cright of return\u201d of the descendants of Palestinian refugees to homes in Israel (17 percent) or reverting to the 1947 UN partition plan for Palestine (11 percent). Of the 47 percent who favored Israel\u2019s dissolution, a clear majority opted for a single state under sharia law that would tolerate a Jewish presence but allow Jews less than full rights (27 percent), followed by a smaller group that sought the transfer of Jewish immigrants and their descendants\u2014but not Jews whose ancestors lived in the region before Zionism\u2014from Israel proper and the Palestinian territories (20 percent).\n\nThe survey also showed how Gazans\u2019 views of Hamas have changed. Before October 7, 2023, when the Gaza Strip was still intact, polls showed that popular support for Hamas had been withering for some time. The decline resulted from a variety of factors, including stagnant living conditions and a lack of movement on Hamas\u2019s promise of armed resistance against Israel and toward the creation of a Palestinian state. As PSR\u2019s director, Khalil Shikaki, has argued, the October attack might be viewed as an attempt by Hamas to break out of a politically intolerable status quo.\n\n\n\nDuring the initial months of war, Gazans\u2019 attitudes toward Hamas improved. In March 2024, a PSR poll of Gazans found that support for Hamas\u2019s control of the strip had increased to more than 50 percent, a 14-point rise from before the October 7, 2023, attack. At the time, most Gazans believed that Hamas would continue to control the territory and that it was winning the war against Israel. By January 2025, however, after the decimation of the group\u2019s top leadership and further destruction of Gaza, that surge of support had eroded again.\n\nOur January survey found that Hamas retains the support of only a fifth of Gaza\u2019s population\u2014a steep decline from the March poll. Yet support for other political factions, including the Palestine Liberation Organization, was even lower. In fact, when asked to select from among the current options for Palestinian leadership, Gazans\u2019 most frequent response was that none of them truly represented the people. Indeed, Gazans believe that Israel\u2019s leadership does a much better job of representing Israelis than Palestinian leadership does representing Palestinians.\n\nIn short, the survey reveals a Palestinian leadership vacuum that Hamas, as degraded as it is, is rapidly working to fill. As some analysts have observed, the organization\u2019s reassertion of power has been aided by the absence of a viable alternative plan for Palestinian governance from Israel or the United States and by the Trump administration\u2019s talk of a proposal long championed by the Israeli far right: population \u201ctransfer.\u201d According to Shikaki, most Gazans do not believe that Hamas has won the war. \u201cNonetheless,\u201d he adds, \u201cthey do not seem to find a better alternative.\u201d\n\nTHE STRENGTH WITHIN\n\nThe lack of strong support for Hamas may obscure a larger reality about the role the group plays in Gaza. As our survey results indicate, despite Gazans\u2019 perceptions of a crisis in Palestinian political leadership, a majority of the population continues to be committed to Hamas\u2019s political ideals, such as sharia as the law of the land, the right of Palestinian refugees and their descendants to return to the homes they lost in Israel\u2019s creation in 1948, and the quest for national sovereignty for Palestinians.\n\nWe measure such commitment by first asking participants to drag a small circle (\u201cMe\u201d) to a position that best affirms their relationship to a large circle representing a Value or a Group. They are considered \u201cfused\u201d with the value or group when they place themselves in the very center of the large circle. Findings from prior studies, from the battlefields of Libya and Ukraine to America\u2019s culture wars, suggest that those who show total fusion see the value or group as a visceral and inseparable part of their identity.\n\nFusion is one reliable predictor of willingness to make sacrifices for a group or greater cause. Another predictor of self-sacrifice is when the group cause becomes a \u201csacred value.\u201d Whether religious or secular, like God or country, sacred values are nonnegotiable, regardless of material risks, rewards, costs, or consequences. When fusion and sacred values are both present they produce \u201cdevoted actors\u201d willing to sacrifice all, including their lives and loved ones, the totality of their self-interests.\n\nBetween 2015 and 2017, for example, we conducted a series of studies in Iraq of groups\u2014the Islamic State, or ISIS; the militant Kurdish separatists of the PKK; and the Kurdish peshmerga, or military forces of Iraqi Kurdistan\u2014that kept fighting despite high numbers of casualties. We found that members of these fused groups tended to show a high degree of willingness to sacrifice themselves for values they held sacred, a characteristic that gave these groups a spiritual strength that significantly outweighed their physical or material resources, such as firepower, manpower, logistical support, or training time.\n\n The war has strengthened commitments to maximalist political goals.\n\nThis is also true for Gazans after 15 months of war. As the January survey found, inhabitants of the strip show a high degree of group identification as Palestinians, and many express a willingness to make costly personal sacrifices to achieve specific goals such as sharia as the law of the land, the right of refugees and their descendants to return to the homes they lost in Israel\u2019s creation in 1948, and the quest for national sovereignty for Palestinians. For each of these core values, the more that respondents are prepared to make costly sacrifices for them, the less willing they were to make peace with Israel.\n\nTo measure how Gazans view their physical and spiritual strength relative to other national groups, the survey used an approach that has previously been used in surveys of Iraqis, Ukrainians, and the U.S. armed forces, among others. Respondents are shown a pair of seminude bodies side by side with national flags attached to their heads, which can be increased or decreased in size and musculature using a slider. They are then told to move the slider to assess the relative \u201cphysical\u201d and \u201cspiritual\u201d strength of each national group. In our survey, Gazans were asked to compare themselves with Israelis, Americans, and Iranians. The respondents considered Palestinians to be far stronger spiritually than they are physically. This was the opposite of how they perceived Israel, the United States, and even their own putative ally Iran, which they viewed as much stronger physically than spiritually.\n\nGazans also show a marked tendency to view the conflict with Israel in religious rather than political terms, as a conflict to liberate Muslims from Jewish oppression. But Palestinians\u2019 religious belief does not necessarily imply intolerance of other groups. For example, in a 2016 survey of Palestinian Muslim youths, we and colleagues found that many were disposed to place much greater value on the lives of Palestinians than on those of Jewish Israelis. Yet when they were asked to take the viewpoint of Allah (God), they valued the two more equally. Their belief in God appeared to promote a more universal valuation of human life, attributing moral worthiness to Muslims and non-Muslims alike even amid prolonged conflict.\n\nNevertheless, when religion becomes identified with an assertive sociopolitical agenda ostensibly sanctified by God or a \u201cparty of God,\u201d opponents to that agenda and party become enemies of God who are easier to vilify and kill. In the January survey, barely one percent of Gazans considered themselves \u201cnot religious,\u201d whereas 67 percent identified themselves as \u201csomewhat religious\u201d and 31 percent as \u201ctruly religious.\u201d The nearly one-third of respondents identifying themselves as \u201ctruly religious\u201d were most committed to the sovereignty of Palestine and the right of return and most willing to make major sacrifices, including fighting and dying, for those outcomes. This segment was also most likely to support sharia and Hamas\u2019s leadership of Gaza and of Palestinians in general.\n\nThe \u201ctruly religious\u201d and \u201csomewhat religious\u201d alike judged Israelis to be significantly less human than Palestinians. The survey tested this by asking respondents to place Palestinians and Israelis on a visual scale ranging from an ape-like figure on through stages of semi-erectness to a fully upright human. Studies from China, Europe, India, North America, and elsewhere indicate that the less human the chosen figure, the more respondents associate the adversary with moral degeneracy and violent threats and actions, and the greater their own impetus for violence against that adversary.\n\nTHE PRICE OF PEACE\n\nIt is important to note that for most Gazans, religious and political commitments are not all-determining. Although most Gazans consider the basic values associated with being Palestinian as central to their identity, only smaller minorities consider these values to be nonnegotiable. For example, only 30 percent of Gazans view the right of return as a nonnegotiable part of their identity; just 20 percent view sharia that way; and 15 percent, national sovereignty. Nonetheless, respondents judged that even the cause of national sovereignty was significantly more important than preserving family safety and security\u2014a finding that parallels survey results from the most committed combatants for and against ISIS during its period of maximum control in Iraq in 2015\u201316.\n\nThere may be a broader takeaway from these findings about Gazans\u2019 deep spiritual commitment to Palestinian core values. In similar studies conducted elsewhere, groups that perceive themselves as relatively weak physically but strong spiritually tend to be those that are more militant or radicalized and willing to continue fighting, even against a far more powerful foe. They perceive their readiness for self-sacrifice as an advantage over their adversaries. This is a common trait among extremist groups, such as fighters and supporters of ISIS or the Kurdish PKK, but also among others who may be just as devoted and willing to sacrifice themselves for democracy or peace (as seen in a much smaller percentage of the population in Gaza).\n\nFor Gazans more widely, the willingness to sacrifice themselves for common goals this far into a brutal war strongly suggests that they are unlikely to give up their struggle simply in exchange for personal and family security. This raises questions about various international \u201cday after\u201d plans in Gaza, which seem to assume that providing personal safety and livelihood\u2014cessation of hostilities combined with aid delivery, tents, and basic necessities\u2014can stabilize the territory even without Palestinian self-determination.\n\n\n\nTo assess how Gazans now see the chances for peace in the future, the survey assessed their expectations about scenarios endorsed in the past by Palestinian leaders, including Hamas officials. Years before the October 7, 2023, attack, one of us (Atran) conducted several interviews with Hamas leaders, including in 2006 with with Ismail Haniyeh, Gaza\u2019s prime minister at the time, who later served as politburo chairman until his assassination by Israel last year; in 2009, with Khaled Meshal in Damascus, the politburo chairman; and in 2013, with Musa Abu Marzouk, the politburo deputy chairman, in Cairo. In each of these cases, the leaders indicated an openness to a long-term truce or even peace with Israel.\n\nOur January survey reminded respondents of these statements, noting that those leaders generally conditioned a truce or a longer peace on Israel\u2019s return to 1967 borders, an internationally backed \u201cbalance of power\u201d with Israel, and the recognition of the right of return. The survey then asked which of three outcomes\u2014truce, peace, or more war\u2014seemed most likely for the next generation of Palestinians.\n\nAbout half the respondents said they expected peace, 44 percent expected a long-term truce, and seven percent expected more war. Of the roughly half that anticipated peace, however, two groups emerged, almost equal in size: those who expect peace as a negotiated outcome (24 percent) and those who expect peace to arise from Israel\u2019s dissolution (25 percent). Respondents who expected a provisional truce or war believe that Israelis and Palestinians will not reach a permanent peace either because the concessions needed are spurned by the opposing side or are too painful to contemplate by one or both sides.\n\nWHY THEY FIGHT\n\nParadoxically, the continued strength of Gazans\u2019 commitments to the Palestinian cause may point to forms of compromise that have until now been overlooked. For example, it is no secret that Hamas is committed to a sovereign Palestinian state, the right of return, and sharia law\u2014all of which the elimination of Israel as a state would accomplish. Yet Hamas leaders have in the past suggested that they do not consider a sovereign Palestine \u201cfrom the river to the sea\u201d and the dissolution of Israel as nonnegotiable, sacred values. Studies we conducted from 2006 to 2013 indicated that even the right of return, although held to be sacred, can be reframed so as to remain nonnegotiable in principle but negotiable in practice.\n\nSuch an accommodation might require, for example, meaningful symbolic gestures from the other side, such as a sincere Israeli apology for the expulsion of Palestinians from their homes and lands, Israel\u2019s acceptance of the return of a limited number of refugees and their descendants, and some form of diya, or financial compensation to victims or the heirs of victims of the nakba, the mass displacement of Palestinians during Israel\u2019s founding in 1948, as a form of historic reparations. But our research also shows that economic incentives or sanctions that aim to compel Palestinians (or Israelis) to forsake their core values backfire for the population as a whole, increasing resistance to peace deals and support for violence.\n\n Israel may be further from pacifying Gaza than ever.\n\nOf course, Hamas leaders making such statements may have been engaging in insincere posturing aimed at relieving Israeli military pressure, as Israeli leaders have claimed. Nevertheless, in our recent survey, Gazans suggested they were willing to countenance an outcome that fell short of what they considered to be most acceptable and realistic. Establishing a balance of power to ensure that Israel can no longer deploy enough military force to dominate internationally recognized Palestinian territory is a negotiable material good that would ensure Palestinians\u2019 physical security. For those Gazans for whom right of return is a nonnegotiable sacred value, but nonetheless open to reinterpretation, the Israeli recognition of that right, even if largely symbolic would provide a measure of security for the Palestinian people, by upholding what Palestinians often cite as the conflict\u2019s central issue, \u201cland and honor.\u201d Such a gesture, while not sufficient on its own, could well jump-start consideration of peace.\n\nBy contrast, Gazans believe that abandoning their land, as Trump has proposed, would mean ceasing to be Palestinian. Without an Israeli willingness to make some concessions on Palestinian core values and a U.S. willingness to enforce the terms of such an agreement, the survey suggests that Gazans will fight on\u2014at least if the committed minority of devoted actors are still able to inspire people to take on unfathomable odds to seek the dissolution of Israel. And Israelis would assuredly respond with incomparably greater destructive force.\n\nAfter waging 15 months of \u201ctotal war\u201d and achieving many of its declared material objectives, Israel may be further from pacifying Gaza than ever. This is not just because Israel has failed to offer anything resembling a political strategy or a plausible plan for a Palestinian future while further radicalizing Palestinians to seek revenge for relatives killed and homes lost. (Our survey shows a positive association between having experienced family displacement and preferring a military over a diplomatic end to the conflict.) It is also because Gazans, at least the most committed among them, believe that their identity and place in the world are more imperiled than ever: a sentiment not unlike the one that inspired the establishment of the Jewish state and fostered its people\u2019s still intense will to fight.]]>\n    \nResidents returning to Gaza City after an Israeli withdrawal, February 2025 Dawoud Abu Alkas / Reuters \n\n\n\n\n\n\n\n\nIn the weeks since Israel\u2019s fragile January 19 cease-fire and hostages-for-prisoners deal with Hamas, the issue of what should happen to Gaza and its 2.1 million inhabitants has come starkly into view. The war has reduced much of Gaza to ruins, with its schools, hospitals, civilian infrastructure and ecology now largely destroyed and a huge portion of its population lacking adequate shelter. The constant threat of the cease-fire\u2019s breakdown has fueled its own daily dread of further devastation. Even as U.S. President Donald Trump has floated chimerical ideas about an eventual U.S. \u201ctakeover\u201d of Gaza and the permanent relocation of its population, external powers have made little progress on formulating a strategy for governance and security in the territory now.\n\nStrangely absent from this debate are Gazans themselves. It is reasonable to assume that more than 15 months of pulverizing conflict have changed the perceptions of ordinary civilians in the territory about what they want for their future, how they see their land, who they think should be their rulers, and what they consider to be the most plausible pathways to peace. Given the extraordinary price they have paid for Hamas\u2019s actions on October 7, 2023, Gazans might be expected to reject the group and favor a different leadership. Similarly, outside observers might anticipate that after so much hardship, Gazans would be more prepared to compromise on larger political aspirations in favor of more urgent human needs.\n\nIn fact, a survey we conducted in Gaza in early January, shortly before the cease-fire came into effect, tells a more complicated story. The representative survey was formulated by the research group Artis International and Oxford University\u2019s Changing Character of War Centre and carried out by the Palestinian Center for Policy and Survey Research (PSR). Using census data and sampling people in shelters based on the locations of their original homes to ensure geographic diversity, the survey comprised 500 face-to-face interviews with Gazans\u2014248 women and 252 men\u2014ranging in age from 18 to 83. The margin of error was plus or minus four percentage points.\n\nThe survey found that although Hamas\u2019s popular appeal has declined precipitously since the early months of the war, current alternatives to the group draw even less support, which opens the way for Hamas to shore up its influence over Gaza again. The war has also strengthened rather than weakened Gazans\u2019 commitments to maximalist political goals, while eroding support for a two-state solution. Perhaps most strikingly, the survey showed that the people of Gaza continue to retain strong core values related to their Palestinian and religious identity and their attachment to the land, values that they intend to uphold even if doing so requires great personal sacrifice. As the United States and its regional and international partners confront the reality of postwar Gaza, the survey findings may challenge the assumption that any movement toward peace with Israel can be found that does not satisfy\u2014or at least symbolically recognize\u2014some of these basic values.\n\nTHE GOVERNANCE GAP\n\nIn one of the primary questions in the survey, respondents were asked to select which of several possible resolutions to the Israeli-Palestinian conflict they viewed as both acceptable and realistic. Before the war in Gaza began, research showed that a clear majority of Palestinians in Gaza supported a two-state solution whereas just 20 percent supported a military solution that could result in the destruction of the state of Israel. In the January survey, less than half, or 48 percent, still preferred a two-state solution, while nearly as many, 47 percent, preferred the dissolution of Israel. A mere five percent viewed a third alternative, a democratic, binational state with equal rights for Arabs and Jews, as acceptable and realistic.\n\nMoreover, although partition was deemed acceptable and realistic by 48 percent, just 20 percent supported a two-state solution conforming to United Nations resolutions based on the 1967 borders. The rest of those supporting a partition favored two-state solutions that either required \u201cright of return\u201d of the descendants of Palestinian refugees to homes in Israel (17 percent) or reverting to the 1947 UN partition plan for Palestine (11 percent). Of the 47 percent who favored Israel\u2019s dissolution, a clear majority opted for a single state under sharia law that would tolerate a Jewish presence but allow Jews less than full rights (27 percent), followed by a smaller group that sought the transfer of Jewish immigrants and their descendants\u2014but not Jews whose ancestors lived in the region before Zionism\u2014from Israel proper and the Palestinian territories (20 percent).\n\nThe survey also showed how Gazans\u2019 views of Hamas have changed. Before October 7, 2023, when the Gaza Strip was still intact, polls showed that popular support for Hamas had been withering for some time. The decline resulted from a variety of factors, including stagnant living conditions and a lack of movement on Hamas\u2019s promise of armed resistance against Israel and toward the creation of a Palestinian state. As PSR\u2019s director, Khalil Shikaki, has argued, the October attack might be viewed as an attempt by Hamas to break out of a politically intolerable status quo.\n\n\n\nDuring the initial months of war, Gazans\u2019 attitudes toward Hamas improved. In March 2024, a PSR poll of Gazans found that support for Hamas\u2019s control of the strip had increased to more than 50 percent, a 14-point rise from before the October 7, 2023, attack. At the time, most Gazans believed that Hamas would continue to control the territory and that it was winning the war against Israel. By January 2025, however, after the decimation of the group\u2019s top leadership and further destruction of Gaza, that surge of support had eroded again.\n\nOur January survey found that Hamas retains the support of only a fifth of Gaza\u2019s population\u2014a steep decline from the March poll. Yet support for other political factions, including the Palestine Liberation Organization, was even lower. In fact, when asked to select from among the current options for Palestinian leadership, Gazans\u2019 most frequent response was that none of them truly represented the people. Indeed, Gazans believe that Israel\u2019s leadership does a much better job of representing Israelis than Palestinian leadership does representing Palestinians.\n\nIn short, the survey reveals a Palestinian leadership vacuum that Hamas, as degraded as it is, is rapidly working to fill. As some analysts have observed, the organization\u2019s reassertion of power has been aided by the absence of a viable alternative plan for Palestinian governance from Israel or the United States and by the Trump administration\u2019s talk of a proposal long championed by the Israeli far right: population \u201ctransfer.\u201d According to Shikaki, most Gazans do not believe that Hamas has won the war. \u201cNonetheless,\u201d he adds, \u201cthey do not seem to find a better alternative.\u201d\n\nTHE STRENGTH WITHIN\n\nThe lack of strong support for Hamas may obscure a larger reality about the role the group plays in Gaza. As our survey results indicate, despite Gazans\u2019 perceptions of a crisis in Palestinian political leadership, a majority of the population continues to be committed to Hamas\u2019s political ideals, such as sharia as the law of the land, the right of Palestinian refugees and their descendants to return to the homes they lost in Israel\u2019s creation in 1948, and the quest for national sovereignty for Palestinians.\n\nWe measure such commitment by first asking participants to drag a small circle (\u201cMe\u201d) to a position that best affirms their relationship to a large circle representing a Value or a Group. They are considered \u201cfused\u201d with the value or group when they place themselves in the very center of the large circle. Findings from prior studies, from the battlefields of Libya and Ukraine to America\u2019s culture wars, suggest that those who show total fusion see the value or group as a visceral and inseparable part of their identity.\n\nFusion is one reliable predictor of willingness to make sacrifices for a group or greater cause. Another predictor of self-sacrifice is when the group cause becomes a \u201csacred value.\u201d Whether religious or secular, like God or country, sacred values are nonnegotiable, regardless of material risks, rewards, costs, or consequences. When fusion and sacred values are both present they produce \u201cdevoted actors\u201d willing to sacrifice all, including their lives and loved ones, the totality of their self-interests.\n\nBetween 2015 and 2017, for example, we conducted a series of studies in Iraq of groups\u2014the Islamic State, or ISIS; the militant Kurdish separatists of the PKK; and the Kurdish peshmerga, or military forces of Iraqi Kurdistan\u2014that kept fighting despite high numbers of casualties. We found that members of these fused groups tended to show a high degree of willingness to sacrifice themselves for values they held sacred, a characteristic that gave these groups a spiritual strength that significantly outweighed their physical or material resources, such as firepower, manpower, logistical support, or training time.\n\n The war has strengthened commitments to maximalist political goals.\n\nThis is also true for Gazans after 15 months of war. As the January survey found, inhabitants of the strip show a high degree of group identification as Palestinians, and many express a willingness to make costly personal sacrifices to achieve specific goals such as sharia as the law of the land, the right of refugees and their descendants to return to the homes they lost in Israel\u2019s creation in 1948, and the quest for national sovereignty for Palestinians. For each of these core values, the more that respondents are prepared to make costly sacrifices for them, the less willing they were to make peace with Israel.\n\nTo measure how Gazans view their physical and spiritual strength relative to other national groups, the survey used an approach that has previously been used in surveys of Iraqis, Ukrainians, and the U.S. armed forces, among others. Respondents are shown a pair of seminude bodies side by side with national flags attached to their heads, which can be increased or decreased in size and musculature using a slider. They are then told to move the slider to assess the relative \u201cphysical\u201d and \u201cspiritual\u201d strength of each national group. In our survey, Gazans were asked to compare themselves with Israelis, Americans, and Iranians. The respondents considered Palestinians to be far stronger spiritually than they are physically. This was the opposite of how they perceived Israel, the United States, and even their own putative ally Iran, which they viewed as much stronger physically than spiritually.\n\nGazans also show a marked tendency to view the conflict with Israel in religious rather than political terms, as a conflict to liberate Muslims from Jewish oppression. But Palestinians\u2019 religious belief does not necessarily imply intolerance of other groups. For example, in a 2016 survey of Palestinian Muslim youths, we and colleagues found that many were disposed to place much greater value on the lives of Palestinians than on those of Jewish Israelis. Yet when they were asked to take the viewpoint of Allah (God), they valued the two more equally. Their belief in God appeared to promote a more universal valuation of human life, attributing moral worthiness to Muslims and non-Muslims alike even amid prolonged conflict.\n\nNevertheless, when religion becomes identified with an assertive sociopolitical agenda ostensibly sanctified by God or a \u201cparty of God,\u201d opponents to that agenda and party become enemies of God who are easier to vilify and kill. In the January survey, barely one percent of Gazans considered themselves \u201cnot religious,\u201d whereas 67 percent identified themselves as \u201csomewhat religious\u201d and 31 percent as \u201ctruly religious.\u201d The nearly one-third of respondents identifying themselves as \u201ctruly religious\u201d were most committed to the sovereignty of Palestine and the right of return and most willing to make major sacrifices, including fighting and dying, for those outcomes. This segment was also most likely to support sharia and Hamas\u2019s leadership of Gaza and of Palestinians in general.\n\nThe \u201ctruly religious\u201d and \u201csomewhat religious\u201d alike judged Israelis to be significantly less human than Palestinians. The survey tested this by asking respondents to place Palestinians and Israelis on a visual scale ranging from an ape-like figure on through stages of semi-erectness to a fully upright human. Studies from China, Europe, India, North America, and elsewhere indicate that the less human the chosen figure, the more respondents associate the adversary with moral degeneracy and violent threats and actions, and the greater their own impetus for violence against that adversary.\n\nTHE PRICE OF PEACE\n\nIt is important to note that for most Gazans, religious and political commitments are not all-determining. Although most Gazans consider the basic values associated with being Palestinian as central to their identity, only smaller minorities consider these values to be nonnegotiable. For example, only 30 percent of Gazans view the right of return as a nonnegotiable part of their identity; just 20 percent view sharia that way; and 15 percent, national sovereignty. Nonetheless, respondents judged that even the cause of national sovereignty was significantly more important than preserving family safety and security\u2014a finding that parallels survey results from the most committed combatants for and against ISIS during its period of maximum control in Iraq in 2015\u201316.\n\nThere may be a broader takeaway from these findings about Gazans\u2019 deep spiritual commitment to Palestinian core values. In similar studies conducted elsewhere, groups that perceive themselves as relatively weak physically but strong spiritually tend to be those that are more militant or radicalized and willing to continue fighting, even against a far more powerful foe. They perceive their readiness for self-sacrifice as an advantage over their adversaries. This is a common trait among extremist groups, such as fighters and supporters of ISIS or the Kurdish PKK, but also among others who may be just as devoted and willing to sacrifice themselves for democracy or peace (as seen in a much smaller percentage of the population in Gaza).\n\nFor Gazans more widely, the willingness to sacrifice themselves for common goals this far into a brutal war strongly suggests that they are unlikely to give up their struggle simply in exchange for personal and family security. This raises questions about various international \u201cday after\u201d plans in Gaza, which seem to assume that providing personal safety and livelihood\u2014cessation of hostilities combined with aid delivery, tents, and basic necessities\u2014can stabilize the territory even without Palestinian self-determination.\n\n\n\nTo assess how Gazans now see the chances for peace in the future, the survey assessed their expectations about scenarios endorsed in the past by Palestinian leaders, including Hamas officials. Years before the October 7, 2023, attack, one of us (Atran) conducted several interviews with Hamas leaders, including in 2006 with with Ismail Haniyeh, Gaza\u2019s prime minister at the time, who later served as politburo chairman until his assassination by Israel last year; in 2009, with Khaled Meshal in Damascus, the politburo chairman; and in 2013, with Musa Abu Marzouk, the politburo deputy chairman, in Cairo. In each of these cases, the leaders indicated an openness to a long-term truce or even peace with Israel.\n\nOur January survey reminded respondents of these statements, noting that those leaders generally conditioned a truce or a longer peace on Israel\u2019s return to 1967 borders, an internationally backed \u201cbalance of power\u201d with Israel, and the recognition of the right of return. The survey then asked which of three outcomes\u2014truce, peace, or more war\u2014seemed most likely for the next generation of Palestinians.\n\nAbout half the respondents said they expected peace, 44 percent expected a long-term truce, and seven percent expected more war. Of the roughly half that anticipated peace, however, two groups emerged, almost equal in size: those who expect peace as a negotiated outcome (24 percent) and those who expect peace to arise from Israel\u2019s dissolution (25 percent). Respondents who expected a provisional truce or war believe that Israelis and Palestinians will not reach a permanent peace either because the concessions needed are spurned by the opposing side or are too painful to contemplate by one or both sides.\n\nWHY THEY FIGHT\n\nParadoxically, the continued strength of Gazans\u2019 commitments to the Palestinian cause may point to forms of compromise that have until now been overlooked. For example, it is no secret that Hamas is committed to a sovereign Palestinian state, the right of return, and sharia law\u2014all of which the elimination of Israel as a state would accomplish. Yet Hamas leaders have in the past suggested that they do not consider a sovereign Palestine \u201cfrom the river to the sea\u201d and the dissolution of Israel as nonnegotiable, sacred values. Studies we conducted from 2006 to 2013 indicated that even the right of return, although held to be sacred, can be reframed so as to remain nonnegotiable in principle but negotiable in practice.\n\nSuch an accommodation might require, for example, meaningful symbolic gestures from the other side, such as a sincere Israeli apology for the expulsion of Palestinians from their homes and lands, Israel\u2019s acceptance of the return of a limited number of refugees and their descendants, and some form of diya, or financial compensation to victims or the heirs of victims of the nakba, the mass displacement of Palestinians during Israel\u2019s founding in 1948, as a form of historic reparations. But our research also shows that economic incentives or sanctions that aim to compel Palestinians (or Israelis) to forsake their core values backfire for the population as a whole, increasing resistance to peace deals and support for violence.\n\n Israel may be further from pacifying Gaza than ever.\n\nOf course, Hamas leaders making such statements may have been engaging in insincere posturing aimed at relieving Israeli military pressure, as Israeli leaders have claimed. Nevertheless, in our recent survey, Gazans suggested they were willing to countenance an outcome that fell short of what they considered to be most acceptable and realistic. Establishing a balance of power to ensure that Israel can no longer deploy enough military force to dominate internationally recognized Palestinian territory is a negotiable material good that would ensure Palestinians\u2019 physical security. For those Gazans for whom right of return is a nonnegotiable sacred value, but nonetheless open to reinterpretation, the Israeli recognition of that right, even if largely symbolic would provide a measure of security for the Palestinian people, by upholding what Palestinians often cite as the conflict\u2019s central issue, \u201cland and honor.\u201d Such a gesture, while not sufficient on its own, could well jump-start consideration of peace.\n\nBy contrast, Gazans believe that abandoning their land, as Trump has proposed, would mean ceasing to be Palestinian. Without an Israeli willingness to make some concessions on Palestinian core values and a U.S. willingness to enforce the terms of such an agreement, the survey suggests that Gazans will fight on\u2014at least if the committed minority of devoted actors are still able to inspire people to take on unfathomable odds to seek the dissolution of Israel. And Israelis would assuredly respond with incomparably greater destructive force.\n\nAfter waging 15 months of \u201ctotal war\u201d and achieving many of its declared material objectives, Israel may be further from pacifying Gaza than ever. This is not just because Israel has failed to offer anything resembling a political strategy or a plausible plan for a Palestinian future while further radicalizing Palestinians to seek revenge for relatives killed and homes lost. (Our survey shows a positive association between having experienced family displacement and preferring a military over a diplomatic end to the conflict.) It is also because Gazans, at least the most committed among them, believe that their identity and place in the world are more imperiled than ever: a sentiment not unlike the one that inspired the establishment of the Jewish state and fostered its people\u2019s still intense will to fight.]]>\n  \n  \n    The 5 books I\u2019ve read this year\n    https://mailchi.mp/99f5d2ec9b2f/while-we-wait-for-the-big-decision-heres-your-weekend-reading-list-8877840?e=fd6235c866\n    readwise:01jm50xwf22bgphtqkjzp6fdk9\n    Sat, 15 Feb 2025 14:41:46 +0000\n    mailchi.mp\n    \n\n\n\n\n\nMembers-only edition | View in browser\n\nI have always viewed this Saturday newsletter as an opportunity to bring you a little bit further into my world. To peer under the hood of how I think by letting you know what I am reading and what I think others are too often overlooking.\n\nLast week, for example, while all attention was on Donald Trump and Elon Musk, I suggested you read about how Brad Raffensperger is quietly asking the federal government for help in creating new ways to suppress voting rights. His transformation from Trump opponent to MAGA vote suppressor tells us a lot about where we are today and what challenges await us in the next election.\n\nFrom time to time, people write in to ask about my other reading lists \u2014 what publications do I read, what independent media do I subscribe to, who are my favorite writers, reporters or influencers? Recently, during a virtual event with members, I was asked what books I have recently read. Rather than take the time to rattle them off and discuss them then, I promised that I would make it the subject of a future newsletter.\n\nSo here it is.\n\nThese are the five books I have read so far this year. You will notice that they are all nonfiction. I confess, with very rare exceptions, I only read nonfiction. You will also note that several are not new books. My reading habits are shockingly disconnected from the best sellers list or what has recently been released. I tend to find books as a result of finding interest in a new topic. Often, I read an article about a subject and then search for a book that goes deeper in depth.\n\nSo, for example, I have bought \u2014 but have not yet read \u2014 Pascal's Wager: The Man Who Played Dice with God, which was released in 2006. I am fascinated by Pascal\u2019s life and his contribution to our understanding of risk. On that topic, the best book on the development of risk theory is Against the Gods: The Remarkable Story of Risk, by Peter Bernstein. It is from 1998, but well worth reading.\n\nIn any event, for better or worse, here are the five books I have read so far this year (in the order I read them).\n\n\n\nYOUR READING LIST\n\n\n\nPatriot: A Memoir\nAlexei Navalny\n\nAs many of you know, I am a regular consumer of memoirs by political dissidents, particularly those from former Soviet and Russian prisoners. On that score Navalny\u2019s is a great read. It is engaging, moving and at times even entertaining. While it lacks some of the deeper historical and philosophical underpinnings of others who faced the gulag, it is more accessible. I highly recommend it.\n\nThe Order of the Day\nEric Vuillard\n\nThough there is some debate about whether this is pure nonfiction or historical fiction, it tells the story of the rise of the Nazis through vignettes intended to show that nothing in history was inevitable. The first, and in my view most compelling, illustrates how the business community fell into place for Hitler. In one passage from the book, the French author notes that \u201cthe most dyed-in-the-wool tyrants still vaguely respect due process, as if they want to make it appear that they aren\u2019t abusing procedure, even while riding roughshod over every convention.\u201d\n\nServants of the Damned: Giant Law Firms, Donald Trump, and the Corruption of Justice\nDavid Enrich\n\nWhile focused primarily on one big law firm \u2014 Jones Day \u2014 David Enrich exposes the rot that underpins much of Big Law today. Every law student should read this as a cautionary tale of the life choices in front of them. Beyond that, it is worth reading to explain, at least in part, the crisis the country and the legal profession face today. \n\nCongress's Constitution: Legislative Authority and the Separation of Powers\nJosh Chafetz\n\nI love the ins and outs of Congress and the U.S. Constitution. If you are like me, Josh Chafetz has written the definitive work and it is worth the time to read.\n\nThe Word of Dog: What Our Canine Companions Can Teach Us About Living a Good Life\nMark Rowlands\n\nI love dogs and I love books about dogs. Some may be surprised that I love the psychology of the relationship between us and dogs, but I don\u2019t care. I loved this book.\n\n\n\nThat\u2019s all for this week. I think you can guess which one is Bode\u2019s favorite.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThis is an exclusive email for Democracy Docket members only. We understand that not everyone can upgrade to our premium membership, so feel free to share up to three premium emails per month with friends, family or whoever you think would be interested. If they aren't already a free subscriber, please encourage them to sign up! For questions about your membership or general support, visit our FAQ page here. You can update your preferences or unsubscribe from this list.]]>\n    \n\n\n\n\n\nMembers-only edition | View in browser\n\nI have always viewed this Saturday newsletter as an opportunity to bring you a little bit further into my world. To peer under the hood of how I think by letting you know what I am reading and what I think others are too often overlooking.\n\nLast week, for example, while all attention was on Donald Trump and Elon Musk, I suggested you read about how Brad Raffensperger is quietly asking the federal government for help in creating new ways to suppress voting rights. His transformation from Trump opponent to MAGA vote suppressor tells us a lot about where we are today and what challenges await us in the next election.\n\nFrom time to time, people write in to ask about my other reading lists \u2014 what publications do I read, what independent media do I subscribe to, who are my favorite writers, reporters or influencers? Recently, during a virtual event with members, I was asked what books I have recently read. Rather than take the time to rattle them off and discuss them then, I promised that I would make it the subject of a future newsletter.\n\nSo here it is.\n\nThese are the five books I have read so far this year. You will notice that they are all nonfiction. I confess, with very rare exceptions, I only read nonfiction. You will also note that several are not new books. My reading habits are shockingly disconnected from the best sellers list or what has recently been released. I tend to find books as a result of finding interest in a new topic. Often, I read an article about a subject and then search for a book that goes deeper in depth.\n\nSo, for example, I have bought \u2014 but have not yet read \u2014 Pascal's Wager: The Man Who Played Dice with God, which was released in 2006. I am fascinated by Pascal\u2019s life and his contribution to our understanding of risk. On that topic, the best book on the development of risk theory is Against the Gods: The Remarkable Story of Risk, by Peter Bernstein. It is from 1998, but well worth reading.\n\nIn any event, for better or worse, here are the five books I have read so far this year (in the order I read them).\n\n\n\nYOUR READING LIST\n\n\n\nPatriot: A Memoir\nAlexei Navalny\n\nAs many of you know, I am a regular consumer of memoirs by political dissidents, particularly those from former Soviet and Russian prisoners. On that score Navalny\u2019s is a great read. It is engaging, moving and at times even entertaining. While it lacks some of the deeper historical and philosophical underpinnings of others who faced the gulag, it is more accessible. I highly recommend it.\n\nThe Order of the Day\nEric Vuillard\n\nThough there is some debate about whether this is pure nonfiction or historical fiction, it tells the story of the rise of the Nazis through vignettes intended to show that nothing in history was inevitable. The first, and in my view most compelling, illustrates how the business community fell into place for Hitler. In one passage from the book, the French author notes that \u201cthe most dyed-in-the-wool tyrants still vaguely respect due process, as if they want to make it appear that they aren\u2019t abusing procedure, even while riding roughshod over every convention.\u201d\n\nServants of the Damned: Giant Law Firms, Donald Trump, and the Corruption of Justice\nDavid Enrich\n\nWhile focused primarily on one big law firm \u2014 Jones Day \u2014 David Enrich exposes the rot that underpins much of Big Law today. Every law student should read this as a cautionary tale of the life choices in front of them. Beyond that, it is worth reading to explain, at least in part, the crisis the country and the legal profession face today. \n\nCongress's Constitution: Legislative Authority and the Separation of Powers\nJosh Chafetz\n\nI love the ins and outs of Congress and the U.S. Constitution. If you are like me, Josh Chafetz has written the definitive work and it is worth the time to read.\n\nThe Word of Dog: What Our Canine Companions Can Teach Us About Living a Good Life\nMark Rowlands\n\nI love dogs and I love books about dogs. Some may be surprised that I love the psychology of the relationship between us and dogs, but I don\u2019t care. I loved this book.\n\n\n\nThat\u2019s all for this week. I think you can guess which one is Bode\u2019s favorite.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThis is an exclusive email for Democracy Docket members only. We understand that not everyone can upgrade to our premium membership, so feel free to share up to three premium emails per month with friends, family or whoever you think would be interested. If they aren't already a free subscriber, please encourage them to sign up! For questions about your membership or general support, visit our FAQ page here. You can update your preferences or unsubscribe from this list.]]>\n  \n  \n    Don\u2019t build a brand. Live a life.\n    https://www.justinwelsh.me/newsletter/dont-build-a-brand-live-a-life?utm_source=convertkit&utm_medium=email&utm_campaign=Don%E2%80%99t%20build%20a%20brand.%20Live%20a%20life.%20-%2016624648\n    readwise:01jm4y59a8996m0jb8k7159qn8\n    Sat, 15 Feb 2025 13:53:23 +0000\n    justinwelsh.me\n    \n\nREAD Time -\n\n3 minutes\n\nWant to grow your LinkedIn audience like I did?\n\nI use Taplio as my go-to LinkedIn growth tool, along with over 6,500 other creators. You can try it for 30 days for just $1 using my code TSSXTAPLIO at checkout.\n\nTry Taplio Today!\n\n\nThe best way to monetize as a solopreneur in 2025?\n\nIt\u2019s not dropshipping, selling digital products, or starting a YouTube channel. It\u2019s ghostwriting. Get started with our free course!\n\n\u200dGet Instant Access\n\nSponsor my newsletter to reach 175,000+ active readers\n\nAdvice about personal branding has become far too formulaic. Just scroll through social media and take a look \u2014 You\u2019ll find advice copying advice copying advice.\n\nI\u2019m afraid we\u2019ve lost sight of what it means to actually create personal brands for ourselves.\n\nYou\u2019re probably familiar with the top tips \u2014 get a professional headshot, write the perfect bio, share strong opinions, be controversial, go viral, yada yada.\n\nYes, some of those tips are helpful. But I think most people are approaching the whole personal branding process backward. They study what others have done, copy their formats, and attempt to reverse engineer someone else\u2019s success.\n\nThe result is what we see across social media these days \u2014 thousands of copy-and-paste profiles parroting the same recycled ideas.\n\nWhy Most People Get It Wrong\n\nThe problem isn't the advice itself. Of course it\u2019s important to have a nice headshot, a strong bio, opinions, and to know what great content looks like. Those are the basics, and none of those things are bad.\n\nThe problem is that formulas don\u2019t always work. Because you may not have the expertise, luck, or timing of the person you\u2019re copying.\n\nAnd when you focus on building a personal brand by copying someone else, you're starting with the output instead of the input. You're trying to manufacture an image rather than letting it emerge naturally from your interesting life and experiences, that are unique to you.\n\n\n\n\n\n\n\n\n\n\nJustin Welsh\n@thejustinwelsh\n\n\n\n\n\n\n\n\n\n\n\n\n\nDon't build a \"personal brand.\" \nBuild a life interesting enough for people to pay attention to.\n\n\n\n\nPosted Jan 9, 2025 at 4:53PM\n\n\n\n\nA friend of mine has 30,000 followers, and he's never read an article about personal branding. He shares his extremely contrarian take on life and work, his adventures as an American living in Asia, and his experience writing two self-published books .\n\nPeople follow this guy because his life is fascinating, not because he followed the perfect brand strategy.\n\nA Different (and Refreshing) Approach\n\nSo instead of asking how to build your personal brand, I hope you\u2019ll consider a different angle:\n\nWhat makes my life interesting?\n\nOr, what could make my life interesting?\n\nThis can shift everything when it comes to defining a personal brand that reflects the real you. And instead of spending hours perfecting your headshot and bio, and trying to come up with something controversial to post about, you might actually:\n\n\nStart that weird side project you've been thinking about\nEngage in conversations that challenge your thinking\nLearn that one skill that's always intrigued you\nCreate something just because it interests you\n\nThe irony?\n\nThis approach, of living and sharing, will build a stronger following than any branding template.\n\nWhat Actually Works\n\nMy most engaging posts haven\u2019t been the ones where I followed a formula. They've been the ones where I shared real insights and thoughts from experiences in my personal life.\n\nLike the time I paid a guy $130 to move a treadmill and thought about how simple (not easy) blue-collar entrepreneurship is.\n\nAnd my simple observations about reaching out to people just to say hi, rather than when you need something.\n\nAnd my contrarian take on building a life and business differently than how most people are building theirs (especially back in 2023).\n\nOr this Tweet about slowing down that came directly from a conversation I was had with my friend Steve Schlafman in Upstate New York. I wrote that down on a napkin and posted it the next morning.\n\nThese pieces of content resonated because they came from lived experiences, observations, and conversations. Not because they came from a personal brand playbook.\n\nThe Bottom Line\n\nI hope you\u2019ll reconsider what it means to build your personal brand.\n\nInstead of copying and pasting, you can actually build a life that's interesting enough to share and for people to pay attention to. Maybe you already live one and you just need to put it out there more often.\n\nBecause the best brands and the best content doesn't come from studying \u2014 it comes from living a life worth talking about\u2026and then talking about it!\n\nAnd the beautiful part?\n\nEven if no one ever follows you, you'll still have built something valuable: a life that interests and excites you. And at the end of all your days, isn\u2019t that all that really matters?\n\nLet\u2019s put the \u201cpersonal\u201d back in personal branding.\n\nIf you're interested in building a lean, profitable, one-person business in 2025 consider watching my flagship video course, The Creator MBA.\n\n111 step-by-step lessons to building a lean, healthy, profitable online business, powered by a brand built the right way.\n\n\nStart Watching The Creator MBA Now\n\nThat's all for this week.\n\nSee you next Saturday.\n\nWhenever you're ready, there are 4 ways I can help you:\n\n1. \u200bPromote your business to 175K+ highly engaged entrepreneurs: Showcase your brand or business where hundreds of thousands of your ideal customers are actively spending their time.\n\n2. The Creator MBA: Join 5,000+ entrepreneurs in my flagship course. The Creator MBA teaches you frameworks for turning your knowledge and expertise into a quality product that people will buy. Come learn to build a lean, focused, and profitable Internet business.\n\n3. \u200bThe LinkedIn Operating System:\u200b Join 30,000 students and 70 LinkedIn Top Voices inside of The LinkedIn Operating System. This comprehensive course will teach you the systems I used to grow to 700K+ followers and be named The #1 Global LinkedIn Influencer 5x in a row.\n\n4. \u200bThe Content Operating System\u200b: Join 12,000 students in my multi-step content creation system. Learn to create a high-quality newsletter and 6-12 pieces of high-performance social media content each week.]]>\n    \n\nREAD Time -\n\n3 minutes\n\nWant to grow your LinkedIn audience like I did?\n\nI use Taplio as my go-to LinkedIn growth tool, along with over 6,500 other creators. You can try it for 30 days for just $1 using my code TSSXTAPLIO at checkout.\n\nTry Taplio Today!\n\n\nThe best way to monetize as a solopreneur in 2025?\n\nIt\u2019s not dropshipping, selling digital products, or starting a YouTube channel. It\u2019s ghostwriting. Get started with our free course!\n\n\u200dGet Instant Access\n\nSponsor my newsletter to reach 175,000+ active readers\n\nAdvice about personal branding has become far too formulaic. Just scroll through social media and take a look \u2014 You\u2019ll find advice copying advice copying advice.\n\nI\u2019m afraid we\u2019ve lost sight of what it means to actually create personal brands for ourselves.\n\nYou\u2019re probably familiar with the top tips \u2014 get a professional headshot, write the perfect bio, share strong opinions, be controversial, go viral, yada yada.\n\nYes, some of those tips are helpful. But I think most people are approaching the whole personal branding process backward. They study what others have done, copy their formats, and attempt to reverse engineer someone else\u2019s success.\n\nThe result is what we see across social media these days \u2014 thousands of copy-and-paste profiles parroting the same recycled ideas.\n\nWhy Most People Get It Wrong\n\nThe problem isn't the advice itself. Of course it\u2019s important to have a nice headshot, a strong bio, opinions, and to know what great content looks like. Those are the basics, and none of those things are bad.\n\nThe problem is that formulas don\u2019t always work. Because you may not have the expertise, luck, or timing of the person you\u2019re copying.\n\nAnd when you focus on building a personal brand by copying someone else, you're starting with the output instead of the input. You're trying to manufacture an image rather than letting it emerge naturally from your interesting life and experiences, that are unique to you.\n\n\n\n\n\n\n\n\n\n\nJustin Welsh\n@thejustinwelsh\n\n\n\n\n\n\n\n\n\n\n\n\n\nDon't build a \"personal brand.\" \nBuild a life interesting enough for people to pay attention to.\n\n\n\n\nPosted Jan 9, 2025 at 4:53PM\n\n\n\n\nA friend of mine has 30,000 followers, and he's never read an article about personal branding. He shares his extremely contrarian take on life and work, his adventures as an American living in Asia, and his experience writing two self-published books .\n\nPeople follow this guy because his life is fascinating, not because he followed the perfect brand strategy.\n\nA Different (and Refreshing) Approach\n\nSo instead of asking how to build your personal brand, I hope you\u2019ll consider a different angle:\n\nWhat makes my life interesting?\n\nOr, what could make my life interesting?\n\nThis can shift everything when it comes to defining a personal brand that reflects the real you. And instead of spending hours perfecting your headshot and bio, and trying to come up with something controversial to post about, you might actually:\n\n\nStart that weird side project you've been thinking about\nEngage in conversations that challenge your thinking\nLearn that one skill that's always intrigued you\nCreate something just because it interests you\n\nThe irony?\n\nThis approach, of living and sharing, will build a stronger following than any branding template.\n\nWhat Actually Works\n\nMy most engaging posts haven\u2019t been the ones where I followed a formula. They've been the ones where I shared real insights and thoughts from experiences in my personal life.\n\nLike the time I paid a guy $130 to move a treadmill and thought about how simple (not easy) blue-collar entrepreneurship is.\n\nAnd my simple observations about reaching out to people just to say hi, rather than when you need something.\n\nAnd my contrarian take on building a life and business differently than how most people are building theirs (especially back in 2023).\n\nOr this Tweet about slowing down that came directly from a conversation I was had with my friend Steve Schlafman in Upstate New York. I wrote that down on a napkin and posted it the next morning.\n\nThese pieces of content resonated because they came from lived experiences, observations, and conversations. Not because they came from a personal brand playbook.\n\nThe Bottom Line\n\nI hope you\u2019ll reconsider what it means to build your personal brand.\n\nInstead of copying and pasting, you can actually build a life that's interesting enough to share and for people to pay attention to. Maybe you already live one and you just need to put it out there more often.\n\nBecause the best brands and the best content doesn't come from studying \u2014 it comes from living a life worth talking about\u2026and then talking about it!\n\nAnd the beautiful part?\n\nEven if no one ever follows you, you'll still have built something valuable: a life that interests and excites you. And at the end of all your days, isn\u2019t that all that really matters?\n\nLet\u2019s put the \u201cpersonal\u201d back in personal branding.\n\nIf you're interested in building a lean, profitable, one-person business in 2025 consider watching my flagship video course, The Creator MBA.\n\n111 step-by-step lessons to building a lean, healthy, profitable online business, powered by a brand built the right way.\n\n\nStart Watching The Creator MBA Now\n\nThat's all for this week.\n\nSee you next Saturday.\n\nWhenever you're ready, there are 4 ways I can help you:\n\n1. \u200bPromote your business to 175K+ highly engaged entrepreneurs: Showcase your brand or business where hundreds of thousands of your ideal customers are actively spending their time.\n\n2. The Creator MBA: Join 5,000+ entrepreneurs in my flagship course. The Creator MBA teaches you frameworks for turning your knowledge and expertise into a quality product that people will buy. Come learn to build a lean, focused, and profitable Internet business.\n\n3. \u200bThe LinkedIn Operating System:\u200b Join 30,000 students and 70 LinkedIn Top Voices inside of The LinkedIn Operating System. This comprehensive course will teach you the systems I used to grow to 700K+ followers and be named The #1 Global LinkedIn Influencer 5x in a row.\n\n4. \u200bThe Content Operating System\u200b: Join 12,000 students in my multi-step content creation system. Learn to create a high-quality newsletter and 6-12 pieces of high-performance social media content each week.]]>\n  \n  \n    \ud83d\udcfa Trends PRO #0117 \u2014 Faceless YouTube Channels\n    https://pro.trends.vc/c/trends-pro-reports/trends-pro-0117-faceless-youtube-channels?source=trendsvc&medium=community\n    readwise:01jm4ktqh6cg0dbdmq807m6m2r\n    Sat, 15 Feb 2025 10:52:51 +0000\n    Trends.vc\n    \"The joy of YouTube is that you can create content about anything you feel passionate about, however silly the subject matter.\" \u2013 Zoe Sugg\n\n\ud83d\udc8e Why It Matters\n\nYou can become a YouTuber without worrying about how you look, speak and act on camera.\n\n\ud83d\udd0d Problem\n\nSpeaking on camera raises the barrier to entry for YouTube creators.\n\n\ud83d\udca1 Solution\n\nFaceless YouTube channels rely on stock footage, virtual characters, animation, audio and/or editing skills.\n\n\ud83c\udfc1 Players\n\nFaceless YouTube Channels\n\n \n Nonstop \u2022 Football and basketball clips and history \n Bad Lip Reading \u2022 Lip-reading video clips for comedic effect \n Tasty Recipes \u2022 Daily and holiday food recipes \n FINAiUS \u2022 Documentaries about the world\u2019s financial geniuses \n(\ud83d\udcc8 Pro \u2193) \n Young Entrepreneurs Forum \u2022 Ideas, plans, tips and motivation for building a business \n Gameranx \u2022 Game news, reviews and gameplays \n Tim Janis \u2022 Music with soothing backgrounds \n Great Art Explained \u2022 The world's greatest paintings and sculptures \n Coromo Sara. ASMR \u2022 Relaxing ASMR videos \n Girl Crafts \u2022 Videos on home decor, paper crafts and more \n Top Tech Now \u2022 Tech product reviews \n 5-minute DECOR \u2022 Decor life hacks and homemade decoration guides \n Mateusz M \u2022 Motivational video clips. \n Kurzgesagt \u2022 Videos about tech, biology, space and society \n\n\nFaceless YouTube Niches\n\n \n News \u2022 Recap of events that happened in politics, economy, society and more. \n History \u2022 Historical facts and documentaries. \n Sports \u2022 Compilation of sporting moments, events and more. \n Comedy \u2022 Jokes, memes, sketches and parodies. \n Cooking \u2022 Food recipes, product reviews and cooking advice. \n Finance \u2022 Personal finance, investing, cryptocurrency and more. \n(\ud83d\udcc8 Pro \u2193) \n Business \u2022 Business ideas, plans and interviews. \n Gaming \u2022 Gaming industry news and gameplays. \n Music \u2022 Niche and general genres such as Lo-fi, ambient, relaxing and more. \n Art \u2022 Paintings, art concepts and drawing tutorials. \n ASMR \u2022 Whispering, scratching, crinkling and other ASMR triggers. \n DIY \u2022 Tutorials on building, making and repairing things yourself. \n Reviews \u2022 The pros and cons of consumer products and services. \n Life Hacks \u2022 Tips and tricks that boost productivity and efficiency. \n Motivation \u2022 Motivational quotes, speeches and moments. \n Science \u2022 Experiments, facts and concepts about the world around us. \n Travel \u2022 City tours, landmarks and traveling routes. \n\n\nVideo Creation Tools\n\n \n TubeBuddy \u2022 Optimize your channel to get more views and subs \n Storyblocks \u2022 Get unlimited stock video, audio and images \n Powtoon \u2022 Create videos with animated characters, templates, backgrounds, audio and more \n VideoScribe \u2022 Make animated videos in seconds \n vidIQ \u2022 Boost your YouTube views and subscribers \n(\ud83d\udcc8 Pro \u2193) \n Keyword Tool \u2022 Find great keywords using YouTube autocomplete \n Thumbs Up TV \u2022 Preview the size and layout of your thumbnails \n Synthesia \u2022 Make AI-powered virtual avatars \n Runway \u2022 AI tools for editing videos \n Descript \u2022 Write, record, transcribe, edit and share your videos \n inVideo \u2022 Video templates and stock assets \n Clipchamp \u2022 Easy video editor with auto-captions, text-to-speech and more \n Pictory \u2022 Create AI-powered short videos from long-form content \n VEED \u2022 Dozens of tools for creating quality videos \n Rytr \u2022 Generate catchy, original video scripts with AI \n Camb AI \u2022 Dub your content in any language \n\n\ud83d\udd2e Predictions\n\n \nFaceless YouTube channels will use generative AI to create characters, animations, audio and scenes.\n \n Alec Wilcock shows how to use ChatGPT to write video scripts. \n Dreamcloud shows how to use Steve AI to make animated videos. \n Premier Gal shows how to use Runway and other tools to edit videos and sound. \n Scalespeeder Gaming shows how he uses Midjourney to make photorealistic thumbnails.   \nWe\u2019ll see million-dollar, one-person faceless YouTube channels.\n \n Devon Canup says he\u2019s made $1,000,000+ in 3 years with faceless YouTube channels. \n Chems says he owns 30+ faceless YouTube channels and earns $1,000,000+ per year.   \nFaceless YouTubers will use AI to keep anonymity while preserving human looks.\n \n Mrboofy used WarpFusion to turn Matt Wolfe into fantasy characters. \n Ciara Rowles is building TemporalKit that turns people into characters while preserving natural motion.   \n (\ud83d\udcc8 Pro) Copying concepts from other channels will become rampant. It\u2019s easier to copy faceless brands than personal brands.\n \n Alen shows how you can reuse and monetize other people\u2019s videos. \n Dave Nick shows how you can copy YouTube Shorts and make ~$178 per video. \n Youri van Hofwegen shows how you can reuse and monetize Creative Commons videos.   \n (\ud83d\udcc8 Pro) We\u2019ll see more VTubers. Most of them are anime-styled characters with unique looks that appeal to niche audiences.\n \n Ami Yamato shares vlogs, skits and is active on social media. \n Gawr Gura shares gameplays, song covers and hosts live chats. \n Ironmouse reacts to internet memes, YouTube videos and pop culture.   \n (\ud83d\udcc8 Pro) VTubers will use motion capture suits. They will act more like humans when recording themselves and doing live streams.\n \n CitizenMetaOne built a motion capture setup. \n Fofamit has spent 1000 hours in a motion capture suit. \n CodeMiko uses motion capture to record reaction videos, live chats and streams. \n WoodyDev live streams in a motion capture suit. He shared budget suits you can buy.   \n (\ud83d\udcc8 Pro) With 50,000,000,000+ daily views, making YouTube Shorts will become the main way to grow new channels.\n \n Daily Dose of Internet tried YouTube Shorts and saw immediate growth. \n Sean Cannell and Austin Armstrong talk about reaching 11,000,000 views in 3 days. \n Jack Craig grew NUTMEG to 235,000+ subscribers in 100 days using YouTube Shorts.   \n\n\u2601\ufe0f Opportunities\n\n \nMake YouTube Shorts. They are easier to create and yield better return on effort.\n \n INNOVA Crafts\u2019 videos get ~150,000 views. Their Shorts get up to 5,000,000 views. \n Videogyan Kids Shows\u2019 videos get ~150,000 views. Their Shorts get up to 800,000 views. \n Comics Explained\u2019s videos get up to ~120,000 views. Their Shorts get up to 1,000,000 views.   \n Animate your videos. This is more appealing than stock footage.\n \n Chris Invests uses whiteboard animation. \n Upgraded Mentality mixes 2D sketches and animation. \n Escaping Ordinary visualizes book summaries and ideas.   \n Cross-promote your YouTube channel on social media. Use discovery platforms to reach a wider audience.\n \n Bestie is active on Instagram and Facebook. \n Daily Dose of Internet promotes his channel on TikTok and Instagram. \n Baseball Doesn\u2019t Exist shares videos on TikTok, Twitter and Instagram.   \n (\ud83d\udcc8 Pro) Make playlists. Group videos by topics to boost views and engagement.\n \n BetterSleep Music has playlists of music for meditation, focus and sleep. \n Brainy Dose has playlists on health, psychology, relationships and more. \n Practical Wisdom and Betterment Boss have playlists on investing, passive income, money management and more.   \n (\ud83d\udcc8 Pro) Share user-generated content. Put content creation on autopilot by asking people to share their clips.\n \n FailArmy lets you submit funny fail videos. \n Cute Pets lets you win up to $500 for submitting cute pet clips. \n Top Apex Plays lets you submit clips of your Apex Legends plays. \n Daily Dose of Internet lets you submit cool, funny and trendy clips.   \n (\ud83d\udcc8 Pro) Sell digital products. Scale your sales without wasting your time.\n \n Art with Flo sells brushes for Procreate and Photoshop. \n 4K Urban Life sells narrated documentaries, soundscapes and wallpapers. \n Adam Del Duca makes $100,000 ARR from faceless channels. He sells YouTube guides, courses, audits and more.   \n (\ud83d\udcc8 Pro) Offer paid subscriptions. Give more value to your true fans.\n \n The Organic Chemistry Tutor teaches math, chemistry and more. Paid subscribers get longer videos and worksheets. \n Productivity Game does book summaries. Paid subscribers get full PDF summaries, bonus insights, mini-courses and more. \n Kurzgesagt covers tech, biology, space and society. Paid subscribers get custom wallpapers, music and their own Bird Avatar.   \n (\ud83d\udcc8 Pro) Sell merch to diversify your income. Let your fans support you while getting cool things in return.\n \n Sr Pelo sells toys, stickers and T-shirts. \n Ami Yamato sells mugs, hoodies and T-shirts. \n Baseball Doesn\u2019t Exist sells hoodies, hats and T-shirts.   \n (\ud83d\udcc8 Pro) Do affiliate marketing. Monetize your traffic by helping viewers find the best products.\n \n Top Tech Now shares affiliate links to products on Amazon.   \n (\ud83d\udcc8 Pro) Build a tool for faceless YouTubers. Boost their productivity by offering solutions to creative, analytical and technical problems.\n \n Rox is building ThumbnailTest that helps to split test titles and thumbnails. \n Priyam Raj is building Morise.ai that helps to generate video ideas, titles, tags and descriptions. \n Noah Morris runs 20 faceless YouTube channels. He\u2019s building NexLev, a niche research tool for faceless creators.   \n (\ud83d\udcc8 Pro) Do live streams to bond with your viewers. Show them there\u2019s a real person behind the channel.\n \n Dj's Aviation does live chats. \n Satoshi Stacker does live chats. \n Two Minute Papers showed his face at an in-person meetup.   \n\n\ud83c\udfd4\ufe0f Risks\n\n \n Impersonalization \u2022 It can be hard to build personal connections without showing your face. \n Platform Risk \u2022 You\u2019re subject to YouTube monetization and content policies. \n (\ud83d\udcc8 Pro) Copyright \u2022 You can get banned or demonetized for sharing reused or copyrighted content. \n (\ud83d\udcc8 Pro) Copycats \u2022 They can get millions of views by piggybacking on original content. While it\u2019s not a faceless YouTube video, it shows how effective copying can be. \n\n\ud83d\udd11 Key Lessons\n\n \nYou can express your creativity without worrying about your looks, status or reputation. Your audience is tuning in for your content, not you. An FBI agent can run a channel on cryptocurrency. \nFaceless channels have lower production costs. You don\u2019t need expensive gear such as a video camera, tripod, stabilizer and light equipment. \n Consistent branding can help you stand out from other faceless channels. Use a recognizable logo, color scheme and visual style. \n (\ud83d\udcc8 Pro) Video series and playlists boost views, watch time and engagement. This helps your videos rank higher. \n (\ud83d\udcc8 Pro) You can boost your odds of success by making many faceless YouTube channels. Davie Fogarty is planning to build a network of faceless YouTube channels. \n (\ud83d\udcc8 Pro) Stock footage is not authentic. It may deter people from consuming your content. \n\n\ud83d\udd25 Hot Takes\n\n \nRunning a faceless YouTube channel doesn\u2019t mean you should stay anonymous. Jeff Delaney runs Fireship where he talks about apps and coding. He shows his face on social media. \nFaceless channels are less defensible than those showing \u201creal\u201d people talking, traveling, doing interviews and more. Becoming a VTuber will boost your defense. \nVirtual YouTubers are personal brands. While they are not real, people keep coming back for their unique looks. They are idols. \n (\ud83d\udcc8 Pro) Faceless YouTubers will clone their voices. They will save time on narrating videos by turning video scripts into audio in minutes. \n (\ud83d\udcc8 Pro) Showing your body and using your voice will help you build personal connections with your viewers. The \u201cGestalt principle of closure\u201d will help viewers get a more complete picture of you. Monet\u2019s Money shows her hands, body and talks in her voice. \n (\ud83d\udcc8 Pro) We\u2019ll see programmatically-created faceless videos. Text-to-video tools will use AI to create video scripts, voice-overs and footage. \n\n\ud83d\ude20 Haters\n\n\u201cYouTube is saturated.\u201d\nYou underestimate the scale of the internet. YouTube is big enough for you to carve out your niche. Experiment with different formats, copy what\u2019s working and add your own touch to stand out.\n\n\u201cFaceless YouTube channels have limited brand recognition. They all look the same.\u201d\n\nWhile some of them are not associated with a real human, consistent branding can help you get noticed. Becoming a VTuber is another option if you want to put a face to your channel.\n\n\u201cBecoming a VTuber won\u2019t stop copycats. They can copy virtual characters.\u201d\n\nThat\u2019s true. Copycats can copy your virtual avatar, scripts and assets. A better way to defend yourself is to move to the real world. It\u2019s harder to copy your room than your graphics.\n\n\u201cThe learning curve for animation skills can be steeper than learning how to act on camera.\u201d\n\nThose who act on camera often still use animations. We're simply removing an ingredient.\n\n\u201cIt can be hard to build personal connections with my audience if I\u2019m running a faceless YouTube channel.\u201d\n\nNo choice is without tradeoffs. While channels \u201cwith a face\u201d tend to get more engagement. You can sacrifice bonding with your audience for lower key-person risk and production costs.\n\n\u201cYou said that YouTube Shorts are easier to create. It's harder to tell stories and create compelling content in shorter formats.\u201d\n\nPodcast hosts share clips of longer interviews to pique interest. You can take Shorts from longer videos to grow your channel.\n\n\ud83d\udd17 Links\n\n \n 116 Best Faceless YouTube Niches \u2022 Profitable niches for faceless YouTube channels. \n Complete YouTube Automation Guide \u2022 Beginner\u2019s guide on running faceless YouTube channels. \n (\ud83d\udcc8 Pro) How to Get More Views on YouTube \u2022 17 ways to grow your YouTube channel. \n (\ud83d\udcc8 Pro) YouTube Branding 101 \u2022 How to build a consistent brand for your YouTube channel. \n (\ud83d\udcc8 Pro) How the YouTube Algorithm Works \u2022 Hacking the YouTube algorithm. \n (\ud83d\udcc8 Pro) 12 Types of YouTube Thumbnails People Love to Click On \u2022 Best practices on making effective thumbnails. \n (\ud83d\udcc8 Pro) How to Create Faceless Videos with AI \u2022 How to use AI to write video scripts, edit scenes and make voice-overs. \n (\ud83d\udcc8 Pro) Your Tribe Will Subscribe if You Understand This \u2022 How to optimize your YouTube channel. \n (\ud83d\udcc8 Pro) How to Choose The Best Stock Video Footage \u2022 How to choose stock footage that fits the style and topic of your video. \n\n\ud83d\udcc1 Related Reports\n\n \n Personal Brands \u2022 VTubers are personal brands with distinct personalities and reputations. \n The Creator Economy \u2022 Faceless YouTube Channels operate in an ecosystem of creators, consumers and advertisers. \n Audience-First Products \u2022 Faceless YouTube Channels make money directly from their audience. \n Virtual Influencers \u2022 Faceless VTubers have unlimited time and speak many languages. \n ChatGPT \u2022 It boosts the productivity of businesses and individuals. \n\n\ud83d\ude4f Thanks\n\nThanks to Maisha Cannon, Swapnil Puranik, Mehmet Gonullu, Guillaume Tessier, Uwe Dreissigacker, Darren Travel, Nicolo' Borghi, Arvid Kahl, Marc Fletcher, Stewart Townsend, Keller and Matthew LaCrosse. We had a great time jamming on this report.\n\n\u270f\ufe0f Emin researched and wrote this report. Dru researched and edited this report.]]>\n    \"The joy of YouTube is that you can create content about anything you feel passionate about, however silly the subject matter.\" \u2013 Zoe Sugg\n\n\ud83d\udc8e Why It Matters\n\nYou can become a YouTuber without worrying about how you look, speak and act on camera.\n\n\ud83d\udd0d Problem\n\nSpeaking on camera raises the barrier to entry for YouTube creators.\n\n\ud83d\udca1 Solution\n\nFaceless YouTube channels rely on stock footage, virtual characters, animation, audio and/or editing skills.\n\n\ud83c\udfc1 Players\n\nFaceless YouTube Channels\n\n \n Nonstop \u2022 Football and basketball clips and history \n Bad Lip Reading \u2022 Lip-reading video clips for comedic effect \n Tasty Recipes \u2022 Daily and holiday food recipes \n FINAiUS \u2022 Documentaries about the world\u2019s financial geniuses \n(\ud83d\udcc8 Pro \u2193) \n Young Entrepreneurs Forum \u2022 Ideas, plans, tips and motivation for building a business \n Gameranx \u2022 Game news, reviews and gameplays \n Tim Janis \u2022 Music with soothing backgrounds \n Great Art Explained \u2022 The world's greatest paintings and sculptures \n Coromo Sara. ASMR \u2022 Relaxing ASMR videos \n Girl Crafts \u2022 Videos on home decor, paper crafts and more \n Top Tech Now \u2022 Tech product reviews \n 5-minute DECOR \u2022 Decor life hacks and homemade decoration guides \n Mateusz M \u2022 Motivational video clips. \n Kurzgesagt \u2022 Videos about tech, biology, space and society \n\n\nFaceless YouTube Niches\n\n \n News \u2022 Recap of events that happened in politics, economy, society and more. \n History \u2022 Historical facts and documentaries. \n Sports \u2022 Compilation of sporting moments, events and more. \n Comedy \u2022 Jokes, memes, sketches and parodies. \n Cooking \u2022 Food recipes, product reviews and cooking advice. \n Finance \u2022 Personal finance, investing, cryptocurrency and more. \n(\ud83d\udcc8 Pro \u2193) \n Business \u2022 Business ideas, plans and interviews. \n Gaming \u2022 Gaming industry news and gameplays. \n Music \u2022 Niche and general genres such as Lo-fi, ambient, relaxing and more. \n Art \u2022 Paintings, art concepts and drawing tutorials. \n ASMR \u2022 Whispering, scratching, crinkling and other ASMR triggers. \n DIY \u2022 Tutorials on building, making and repairing things yourself. \n Reviews \u2022 The pros and cons of consumer products and services. \n Life Hacks \u2022 Tips and tricks that boost productivity and efficiency. \n Motivation \u2022 Motivational quotes, speeches and moments. \n Science \u2022 Experiments, facts and concepts about the world around us. \n Travel \u2022 City tours, landmarks and traveling routes. \n\n\nVideo Creation Tools\n\n \n TubeBuddy \u2022 Optimize your channel to get more views and subs \n Storyblocks \u2022 Get unlimited stock video, audio and images \n Powtoon \u2022 Create videos with animated characters, templates, backgrounds, audio and more \n VideoScribe \u2022 Make animated videos in seconds \n vidIQ \u2022 Boost your YouTube views and subscribers \n(\ud83d\udcc8 Pro \u2193) \n Keyword Tool \u2022 Find great keywords using YouTube autocomplete \n Thumbs Up TV \u2022 Preview the size and layout of your thumbnails \n Synthesia \u2022 Make AI-powered virtual avatars \n Runway \u2022 AI tools for editing videos \n Descript \u2022 Write, record, transcribe, edit and share your videos \n inVideo \u2022 Video templates and stock assets \n Clipchamp \u2022 Easy video editor with auto-captions, text-to-speech and more \n Pictory \u2022 Create AI-powered short videos from long-form content \n VEED \u2022 Dozens of tools for creating quality videos \n Rytr \u2022 Generate catchy, original video scripts with AI \n Camb AI \u2022 Dub your content in any language \n\n\ud83d\udd2e Predictions\n\n \nFaceless YouTube channels will use generative AI to create characters, animations, audio and scenes.\n \n Alec Wilcock shows how to use ChatGPT to write video scripts. \n Dreamcloud shows how to use Steve AI to make animated videos. \n Premier Gal shows how to use Runway and other tools to edit videos and sound. \n Scalespeeder Gaming shows how he uses Midjourney to make photorealistic thumbnails.   \nWe\u2019ll see million-dollar, one-person faceless YouTube channels.\n \n Devon Canup says he\u2019s made $1,000,000+ in 3 years with faceless YouTube channels. \n Chems says he owns 30+ faceless YouTube channels and earns $1,000,000+ per year.   \nFaceless YouTubers will use AI to keep anonymity while preserving human looks.\n \n Mrboofy used WarpFusion to turn Matt Wolfe into fantasy characters. \n Ciara Rowles is building TemporalKit that turns people into characters while preserving natural motion.   \n (\ud83d\udcc8 Pro) Copying concepts from other channels will become rampant. It\u2019s easier to copy faceless brands than personal brands.\n \n Alen shows how you can reuse and monetize other people\u2019s videos. \n Dave Nick shows how you can copy YouTube Shorts and make ~$178 per video. \n Youri van Hofwegen shows how you can reuse and monetize Creative Commons videos.   \n (\ud83d\udcc8 Pro) We\u2019ll see more VTubers. Most of them are anime-styled characters with unique looks that appeal to niche audiences.\n \n Ami Yamato shares vlogs, skits and is active on social media. \n Gawr Gura shares gameplays, song covers and hosts live chats. \n Ironmouse reacts to internet memes, YouTube videos and pop culture.   \n (\ud83d\udcc8 Pro) VTubers will use motion capture suits. They will act more like humans when recording themselves and doing live streams.\n \n CitizenMetaOne built a motion capture setup. \n Fofamit has spent 1000 hours in a motion capture suit. \n CodeMiko uses motion capture to record reaction videos, live chats and streams. \n WoodyDev live streams in a motion capture suit. He shared budget suits you can buy.   \n (\ud83d\udcc8 Pro) With 50,000,000,000+ daily views, making YouTube Shorts will become the main way to grow new channels.\n \n Daily Dose of Internet tried YouTube Shorts and saw immediate growth. \n Sean Cannell and Austin Armstrong talk about reaching 11,000,000 views in 3 days. \n Jack Craig grew NUTMEG to 235,000+ subscribers in 100 days using YouTube Shorts.   \n\n\u2601\ufe0f Opportunities\n\n \nMake YouTube Shorts. They are easier to create and yield better return on effort.\n \n INNOVA Crafts\u2019 videos get ~150,000 views. Their Shorts get up to 5,000,000 views. \n Videogyan Kids Shows\u2019 videos get ~150,000 views. Their Shorts get up to 800,000 views. \n Comics Explained\u2019s videos get up to ~120,000 views. Their Shorts get up to 1,000,000 views.   \n Animate your videos. This is more appealing than stock footage.\n \n Chris Invests uses whiteboard animation. \n Upgraded Mentality mixes 2D sketches and animation. \n Escaping Ordinary visualizes book summaries and ideas.   \n Cross-promote your YouTube channel on social media. Use discovery platforms to reach a wider audience.\n \n Bestie is active on Instagram and Facebook. \n Daily Dose of Internet promotes his channel on TikTok and Instagram. \n Baseball Doesn\u2019t Exist shares videos on TikTok, Twitter and Instagram.   \n (\ud83d\udcc8 Pro) Make playlists. Group videos by topics to boost views and engagement.\n \n BetterSleep Music has playlists of music for meditation, focus and sleep. \n Brainy Dose has playlists on health, psychology, relationships and more. \n Practical Wisdom and Betterment Boss have playlists on investing, passive income, money management and more.   \n (\ud83d\udcc8 Pro) Share user-generated content. Put content creation on autopilot by asking people to share their clips.\n \n FailArmy lets you submit funny fail videos. \n Cute Pets lets you win up to $500 for submitting cute pet clips. \n Top Apex Plays lets you submit clips of your Apex Legends plays. \n Daily Dose of Internet lets you submit cool, funny and trendy clips.   \n (\ud83d\udcc8 Pro) Sell digital products. Scale your sales without wasting your time.\n \n Art with Flo sells brushes for Procreate and Photoshop. \n 4K Urban Life sells narrated documentaries, soundscapes and wallpapers. \n Adam Del Duca makes $100,000 ARR from faceless channels. He sells YouTube guides, courses, audits and more.   \n (\ud83d\udcc8 Pro) Offer paid subscriptions. Give more value to your true fans.\n \n The Organic Chemistry Tutor teaches math, chemistry and more. Paid subscribers get longer videos and worksheets. \n Productivity Game does book summaries. Paid subscribers get full PDF summaries, bonus insights, mini-courses and more. \n Kurzgesagt covers tech, biology, space and society. Paid subscribers get custom wallpapers, music and their own Bird Avatar.   \n (\ud83d\udcc8 Pro) Sell merch to diversify your income. Let your fans support you while getting cool things in return.\n \n Sr Pelo sells toys, stickers and T-shirts. \n Ami Yamato sells mugs, hoodies and T-shirts. \n Baseball Doesn\u2019t Exist sells hoodies, hats and T-shirts.   \n (\ud83d\udcc8 Pro) Do affiliate marketing. Monetize your traffic by helping viewers find the best products.\n \n Top Tech Now shares affiliate links to products on Amazon.   \n (\ud83d\udcc8 Pro) Build a tool for faceless YouTubers. Boost their productivity by offering solutions to creative, analytical and technical problems.\n \n Rox is building ThumbnailTest that helps to split test titles and thumbnails. \n Priyam Raj is building Morise.ai that helps to generate video ideas, titles, tags and descriptions. \n Noah Morris runs 20 faceless YouTube channels. He\u2019s building NexLev, a niche research tool for faceless creators.   \n (\ud83d\udcc8 Pro) Do live streams to bond with your viewers. Show them there\u2019s a real person behind the channel.\n \n Dj's Aviation does live chats. \n Satoshi Stacker does live chats. \n Two Minute Papers showed his face at an in-person meetup.   \n\n\ud83c\udfd4\ufe0f Risks\n\n \n Impersonalization \u2022 It can be hard to build personal connections without showing your face. \n Platform Risk \u2022 You\u2019re subject to YouTube monetization and content policies. \n (\ud83d\udcc8 Pro) Copyright \u2022 You can get banned or demonetized for sharing reused or copyrighted content. \n (\ud83d\udcc8 Pro) Copycats \u2022 They can get millions of views by piggybacking on original content. While it\u2019s not a faceless YouTube video, it shows how effective copying can be. \n\n\ud83d\udd11 Key Lessons\n\n \nYou can express your creativity without worrying about your looks, status or reputation. Your audience is tuning in for your content, not you. An FBI agent can run a channel on cryptocurrency. \nFaceless channels have lower production costs. You don\u2019t need expensive gear such as a video camera, tripod, stabilizer and light equipment. \n Consistent branding can help you stand out from other faceless channels. Use a recognizable logo, color scheme and visual style. \n (\ud83d\udcc8 Pro) Video series and playlists boost views, watch time and engagement. This helps your videos rank higher. \n (\ud83d\udcc8 Pro) You can boost your odds of success by making many faceless YouTube channels. Davie Fogarty is planning to build a network of faceless YouTube channels. \n (\ud83d\udcc8 Pro) Stock footage is not authentic. It may deter people from consuming your content. \n\n\ud83d\udd25 Hot Takes\n\n \nRunning a faceless YouTube channel doesn\u2019t mean you should stay anonymous. Jeff Delaney runs Fireship where he talks about apps and coding. He shows his face on social media. \nFaceless channels are less defensible than those showing \u201creal\u201d people talking, traveling, doing interviews and more. Becoming a VTuber will boost your defense. \nVirtual YouTubers are personal brands. While they are not real, people keep coming back for their unique looks. They are idols. \n (\ud83d\udcc8 Pro) Faceless YouTubers will clone their voices. They will save time on narrating videos by turning video scripts into audio in minutes. \n (\ud83d\udcc8 Pro) Showing your body and using your voice will help you build personal connections with your viewers. The \u201cGestalt principle of closure\u201d will help viewers get a more complete picture of you. Monet\u2019s Money shows her hands, body and talks in her voice. \n (\ud83d\udcc8 Pro) We\u2019ll see programmatically-created faceless videos. Text-to-video tools will use AI to create video scripts, voice-overs and footage. \n\n\ud83d\ude20 Haters\n\n\u201cYouTube is saturated.\u201d\nYou underestimate the scale of the internet. YouTube is big enough for you to carve out your niche. Experiment with different formats, copy what\u2019s working and add your own touch to stand out.\n\n\u201cFaceless YouTube channels have limited brand recognition. They all look the same.\u201d\n\nWhile some of them are not associated with a real human, consistent branding can help you get noticed. Becoming a VTuber is another option if you want to put a face to your channel.\n\n\u201cBecoming a VTuber won\u2019t stop copycats. They can copy virtual characters.\u201d\n\nThat\u2019s true. Copycats can copy your virtual avatar, scripts and assets. A better way to defend yourself is to move to the real world. It\u2019s harder to copy your room than your graphics.\n\n\u201cThe learning curve for animation skills can be steeper than learning how to act on camera.\u201d\n\nThose who act on camera often still use animations. We're simply removing an ingredient.\n\n\u201cIt can be hard to build personal connections with my audience if I\u2019m running a faceless YouTube channel.\u201d\n\nNo choice is without tradeoffs. While channels \u201cwith a face\u201d tend to get more engagement. You can sacrifice bonding with your audience for lower key-person risk and production costs.\n\n\u201cYou said that YouTube Shorts are easier to create. It's harder to tell stories and create compelling content in shorter formats.\u201d\n\nPodcast hosts share clips of longer interviews to pique interest. You can take Shorts from longer videos to grow your channel.\n\n\ud83d\udd17 Links\n\n \n 116 Best Faceless YouTube Niches \u2022 Profitable niches for faceless YouTube channels. \n Complete YouTube Automation Guide \u2022 Beginner\u2019s guide on running faceless YouTube channels. \n (\ud83d\udcc8 Pro) How to Get More Views on YouTube \u2022 17 ways to grow your YouTube channel. \n (\ud83d\udcc8 Pro) YouTube Branding 101 \u2022 How to build a consistent brand for your YouTube channel. \n (\ud83d\udcc8 Pro) How the YouTube Algorithm Works \u2022 Hacking the YouTube algorithm. \n (\ud83d\udcc8 Pro) 12 Types of YouTube Thumbnails People Love to Click On \u2022 Best practices on making effective thumbnails. \n (\ud83d\udcc8 Pro) How to Create Faceless Videos with AI \u2022 How to use AI to write video scripts, edit scenes and make voice-overs. \n (\ud83d\udcc8 Pro) Your Tribe Will Subscribe if You Understand This \u2022 How to optimize your YouTube channel. \n (\ud83d\udcc8 Pro) How to Choose The Best Stock Video Footage \u2022 How to choose stock footage that fits the style and topic of your video. \n\n\ud83d\udcc1 Related Reports\n\n \n Personal Brands \u2022 VTubers are personal brands with distinct personalities and reputations. \n The Creator Economy \u2022 Faceless YouTube Channels operate in an ecosystem of creators, consumers and advertisers. \n Audience-First Products \u2022 Faceless YouTube Channels make money directly from their audience. \n Virtual Influencers \u2022 Faceless VTubers have unlimited time and speak many languages. \n ChatGPT \u2022 It boosts the productivity of businesses and individuals. \n\n\ud83d\ude4f Thanks\n\nThanks to Maisha Cannon, Swapnil Puranik, Mehmet Gonullu, Guillaume Tessier, Uwe Dreissigacker, Darren Travel, Nicolo' Borghi, Arvid Kahl, Marc Fletcher, Stewart Townsend, Keller and Matthew LaCrosse. We had a great time jamming on this report.\n\n\u270f\ufe0f Emin researched and wrote this report. Dru researched and edited this report.]]>\n  \n  \n    \ud83d\udc64 Trends PRO #0132 \u2014 Faceless Social Media Accounts\n    https://pro.trends.vc/c/trends-pro-reports/trends-pro-0132-faceless-social-media-accounts\n    readwise:01jm4ktc2t9yc6e2ff6vq670vp\n    Sat, 15 Feb 2025 10:52:39 +0000\n    Trends.vc\n    \u201cContent is fire. Social media is gasoline.\u201d \u2014 Jay Baer\n\n\ud83d\udc8e Why It Matters\n\nYou can build viral brands without key-person risk.\n\n\ud83d\udd0d Problem\n\nWe want to be inspired, educated and entertained.\n\n\ud83d\udca1 Solution\n\nFaceless social media accounts fulfill our need for useful, interesting and amusing content.\n\n\ud83c\udfc1 Players\n\nFaceless Social Media Accounts\n\n\n\nVC Brags \u2022 Memes on venture capital\n\nHow They Make Movies \u2022 Behind-the-scenes of making movies\n\nNature Is Metal \u2022 The brutal nature of wildlife\n\nSatisfying Videos \u2022 Videos to please your mood\n\nHidden Tips \u2022 The best tips, tricks and life hacks\n\nIts Wood Working \u2022 The art of woodworking\n\nMATH TRICK \u2022 Tricks to get better at math\n\n(\ud83d\udcc8 Pro \u2193)\n\nHow to Learn English \u2022 Learn English words and grammar\n\nPast Factory \u2022 History and nostalgia\n\nClassic ArtWorks \u2022 Classic paintings, sculptures and more\n\nBloody Elbow \u2022 Highlights from fight sports\n\nMovie Recaps \u2022 Movie summaries and explanations\n\nHome Ideas \u2022 Home renovation memes and inspiration\n\nAesthetic WorkOut \u2022 Workout exercises and motivation\n\nClassical Art Memes \u2022 Memes on paintings, sculptures and more\n\nStreetArtGlobe\u2122 \u2022 Shares art installations\n\nWildlife Whispers \u2022 Cute animals from zoos\n\nOld Houses Under50K \u2022 Old houses for sale\n\nZillow Gone Wild \u2022 Unique home interior designs\n\nWeird Spotify Playlists \u2022 Weird music playlists on Spotify\n\n\ud83d\udd2e Predictions\n\n\n\nBig media companies will acquire faceless social media accounts to reach new audiences.\n\n\nLabX Media Group acquired IFLScience in 2020.\n\nWarner Music Group acquired Daquan for $85,000,000.\n\nMedia studios will manage many accounts to boost their reach with diversified content.\n\n\nComplex Networks runs Complex and Complex Music.\n\nVox Media runs NowThis, Thrillist, The Dodo and Seeker.\n\nHive Media Group runs Bleacher Breaker, BUZZNET, Past Factory and Quizscape.\n\nWe\u2019ll see marketplaces for buying and selling social media accounts. They will foster transactions with verification and escrow services.\n\n\nSocial Tradia lets you buy and sell Instagram accounts.\n\nFameSwap lets you buy and sell Instagram, YouTube and TikTok accounts.\n\nAccs-Market.com lets you flip channels on YouTube, Twitter, TikTok, Facebook, Instagram and more.\n\n(\ud83d\udcc8 Pro) We\u2019ll see uncensored alternatives to popular social media platforms. They will let creators make content without restrictions.\n\n\nMastodon is an open-source alternative to Twitter.\n\nMinds is an open-source and decentralized social network.\n\nFriendica is a decentralized social network with distributed servers.\n\nEllo was an alternative to Facebook and Pinterest that didn\u2019t survive the competition. \n\n(\ud83d\udcc8 Pro) We\u2019ll see million-dollar, one-person faceless social media accounts.\n\n\nDevon Canup says he\u2019s made $1,000,000+ in 3 years with faceless YouTube channels.\n\nChems says he owns 30+ faceless YouTube channels and earns $1,000,000+ per year.\n\nScott DeLong was making $180,000 MRR by posting quotes on Christianity in a Facebook group.\n\n(\ud83d\udcc8 Pro) Social media accounts will evolve into standalone media companies.\n\n\nDaquan turned from an Instagram page into a media empire.\n\nF*CKJERRY started as an Instagram meme page that tried to tap into the news space.\n\nGrindFace TV had pages on Facebook and Instagram. Then turned into a platform for unheard talent.\n\n(\ud83d\udcc8 Pro) Faceless social media accounts will automate content creation by posting AI-generated content.\n\n\nArchillect uses AI to curate content.\n\nReal Fake Products shares AI-generated products.\n\nShelley was the world\u2019s first collaborative AI horror writer on social media.\n\n\ud83d\udee0 How to Build Faceless Social Media Accounts\n\n\n\nBuild bots to save time publishing content.\n\n\nChatGPT Bot replies to comments that tag its profile.\n\nOdd Steam Reviews is a bot that posts game reviews.\n\nWhaleCalls is a bot that shares Bitcoin market reports.\n\nDSCOVR:EPIC is a bot that shares pictures of Earth from a DSCOVR satellite.\n\nIndian Sharemarket Updates is a bot that posts updates on the Indian stock market.\n\nDanganronpa Anything Bot shares posts about Danganronpa video game series every 30 minutes.\n\nUse AI to make visuals fast. ChatGPT can write posts and video scripts. AI image generators can make themed graphics.\n\n\nAI Hustlewise shows how to make viral talking AI avatars.\n\nMax Jones shows how to make 100 TikTok videos in 1 hour with AI.\n\nLori Ballen shows how to make 50 social media posts in 5 minutes using ChatGPT and Canva.\n\nRevenue Rebels shows how to make explainer videos using AI-generated scripts, voices and visuals.\n\nCurate content from other creators. This can help you fill your release cadence when you\u2019re low on content ideas.\n\n\nDiply aggregates conversations from the internet.\n\nimages_ai shares images generated by AI artists.\n\nFoodie shares content made by other food bloggers. \n\n\n\n(\ud83d\udcc8 Pro) Welcome user-generated content. This will help you put your content creation on autopilot.\n\n\nNature Is Metal lets you submit wildlife clips.\n\nBarked lets you submit your dog pictures and videos.\n\nBEST VACATIONS lets you submit travel photos and videos.\n\n(\ud83d\udcc8 Pro) Make a parody account to piggyback on the attention paid to famous personalities.\n\n\nElon Musk (Parody) got replies from Elon Musk and Mr. Beast.\n\nMark Zuckerberg (Parody) posts jokes and memes from Mark Zuckerberg.\n\ndeeptomcruise pictures Tom Cruise joking, dancing, fooling around and more.\n\n(\ud83d\udcc8 Pro) Use consistent branding to stand out from competitors.\n\n\nHistory Photographed adds a logo and a signature to the majority of its posts.\n\nMind Motivation Coaching makes thumbnails with low-key images, faces and quotes.\n\nKurzgesagt has a recognizable logo of Earth, 2D vector illustrations and animations across all social media accounts.\n\n(\ud83d\udcc8 Pro) Niche down to serve an audience with unique interests. This can help you lower the competition.\n\n\nCountry Life Dreams curates rural houses for sale.\n\nAfrican Animals shares photos and videos of African wildlife.\n\nLakers Empire shares game highlights of Los Angeles Lakers.\n\nClassic ArtWorks shares classic paintings, sculptures and more.\n\nHumans of New York shares life stories from New York residents.\n\nPrimates shares content about gorillas, monkeys and other primates.\n\n(\ud83d\udcc8 Pro) Start a faceless YouTube channel. You don\u2019t need to worry about how you look, speak and act on camera.\n\n\nNomadic Ambience shares city walk videos.\n\nGameranx shares game news, reviews and gameplay.\n\nFINAiUS shares documentaries about the world\u2019s financial geniuses.\n\n\ud83c\udf31 How to Grow Faceless Social Media Accounts\n\n\n\nBuild a content flywheel by posting on many social media platforms. This helps to boost your reach.\n\n\nThe Tiny Chef Show posts clips on Twitter, Facebook and Instagram.\n\nFailArmy shares funny fail videos on Twitter, TikTok, Facebook and Instagram.\n\nFuturism shares science, technology and medicine news on Twitter, Facebook and Instagram.\n\nPost daily to boost your visibility.\n\n\nPast Factory shares daily history and nostalgic posts.\n\nMeaning in picture shares daily stories in the pictures.\n\nLearn Something shares daily posts on science, mechanisms and more.\n\nCollaborate with others to reach audiences with aligned interests.\n\n\nlil miquela is a virtual influencer who met Saweetie in public.\n\nNature Is Metal collaborated with ECO DEFENSE GROUP to support the defense of wildlife.\n\nIronmouse and Mori Calliope had a live stream on video games, plans for future collabs and what it's like to be a VTuber.\n\n(\ud83d\udcc8 Pro) Take your content to extremes. The tension and anticipation make people enjoy it more.\n\n\nNature Is Metal shares the brutal nature of wildlife.\n\nWow Terrifying shares creepy creatures and more.\n\nScary Underwater shares creepy moments at sea.\n\n1000 WAYS TO DIE shares near-death experiences.\n\n(\ud83d\udcc8 Pro) Use short-form videos to accommodate shorter attention spans.\n\n\nKimigami shares origami tutorials.\n\nSimple Man's Life shares food recipes.\n\nChinese Driver shares street photography videos.\n\n(\ud83d\udcc8 Pro) Cover trending topics. It\u2019s easier to ride existing waves instead of trying to create new ones.\n\n\nAngry Tom shares AI news and tools.\n\n0xb1 was an early DeFi and NFT investor sharing insights in this space.\n\nSicarious has been tweeting about crypto and blockchain since the early days of Bitcoin.\n\n(\ud83d\udcc8 Pro) Post many times per day to stay top of mind.\n\n\n100 Reason to smile shares funny videos.\n\nHidden Tips shares random tips, tricks and life hacks.\n\nAesthetic WorkOut shares workout exercises and motivation.\n\n(\ud83d\udcc8 Pro) Launch multiple accounts to boost your chances of success.\n\n\nSteven Van runs many accounts with tips on using graphic design tools.\n\nNoah Morris runs 18 faceless YouTube channels and made $500,000 in 90 days.\n\nDIGITAL INCOME PROJECT says he runs faceless accounts in travel, sports, health and fitness niches.\n\n(\ud83d\udcc8 Pro) Build a community to lower platform risk.\n\n\nCarDealershipGuy has a private car buyer community.\n\nThe Trading Post has a group with stock market insights.\n\nNeytirix has a Discord channel with art tutorials, character submissions and more.\n\n\ud83d\udcb0 How to Monetize Faceless Social Media Accounts\n\n\n\nSell digital products to earn scalable revenue.\n\n\nEaslo sells productivity templates for Notion.\n\nPikuma sells courses on game development.\n\nGood Minds Quote\u2122 sells an e-book on self-discipline.\n\nCheap Houses Japan sells access to a paid newsletter.\n\nUse affiliate marketing to monetize your traffic.\n\n\nCheatSheets shares affiliate links to Miss Excel\u2019s courses.\n\nNature Predators and Scary Sea share links to Tactical Blades.\n\nAdobe Premiere Pro - Tips, Tricks & Tutorials shares links to Procreate Dreams.\n\nSell physical products to offer tangible value to your fans.\n\n\nVC Brags sells hats.\n\nClassical Art Memes sells Facemask Van Gogh.\n\nGators Daily sells flags, merch and accessories.\n\nMenwiththepot sells knives, seasoning and more.\n\nCompound Interest sells posters, mugs, pillows and more.\n\n(\ud83d\udcc8 Pro) Build a physical business based on your brand account. Faceless social media accounts are great for branded products and services.\n\n\nJuna promotes Chlorophyll Detox Drops.\n\nSo-Cal Burgers promotes its burger restaurant.\n\nwildflowerdesign.co promotes its design services.\n\nDynocom Industries promotes its dynamometer products.\n\nGHOST promotes its sports nutrition, energy drinks and more.\n\n(\ud83d\udcc8 Pro) Join revenue-sharing programs. Platforms reward top content creators.\n\n\nYouTube pays for ads between Shorts in the feed.\n\nSnapchat pays for ads between Snaps in the feed.\n\nTikTok Pulse pays creators of the top 4% of all TikTok videos.\n\nX (formerly Twitter) pays for verified user's organic impressions.\n\nMeta pays for videos with licensed music, Reels, in-stream ads and Instagram posts.\n\n(\ud83d\udcc8 Pro) Offer paid subscriptions with exclusive content.\n\n\nNeytirix gives access to premium community channels.\n\nExocomics shares artwork timelapse with paid subscribers.\n\nNO CONTEXT HUMANS lets you see exclusive tweets for $3 per month.\n\nNomadic Ambience gives access to travel photos for personal and commercial use.\n\n(\ud83d\udcc8 Pro) Use brand partnerships to help companies reach prospective customers.\n\n\nAgadar partnered with Klarna for a shopping campaign.\n\n5-Minute Crafts promotes Bright Side Puzzles & Riddles.\n\nThe Tiny Chef Show sang Happy Birthday to Zenni Optical.\n\nMastermind Investor promotes stock signals by Stock Region Trading Network.\n\nOff the Grid Guide partnered with Superesse Survival EDC to offer a survival kit.\n\n\ud83d\ude20 Haters\n\n\u201cSome faceless social media accounts mention the people behind them.\u201d\nThere\u2019s always someone who runs the account. The key is to focus on the content, not your personality.\n\n\u201cFaceless social media accounts are less defensible. Anybody can copy what I\u2019m doing.\u201d\nMake a virtual avatar or move to the real world without showing your face to boost your defense.\n\n\u201cIt\u2019s harder to build personal connections without showing my face.\u201d\nThis is a tradeoff of lower key-person risk.\n\n\u201cHow do I monetize content created by others? It\u2019s copyrighted.\u201d\nSee Fair Use if you\u2019re in the US. See Fair Dealing if you\u2019re in the UK, Canada or India. Your country has similar laws. In short, you might be able to use a small amount of copyrighted content in your work. But it\u2019s best to ask for permission. This is not legal advice.\n\n\ud83d\udd17 Links\n\n\n\n250,000+ followers by sharing weird game reviews? \u2022 The thread for this report.\n\nBuilding a Report on Faceless Social Media Accounts \u2022 The tweet behind this report.\n\nI Made a Faceless TikTok Account \u2022 How to make $60,000 in 6 months with a faceless TikTok account.\n\nBrand Consistency on Social Media \u2022 Tips on building a consistent brand on social media.\n\n(\ud83d\udcc8 Pro) Building a Report on Faceless Social Media Accounts \u2022 The tweet behind this report.\n\n(\ud83d\udcc8 Pro) YouTube Automation Content Farm Strategies \u2022 How to build a content farm on YouTube.\n\n(\ud83d\udcc8 Pro) Profitable Instagram Theme Page Business \u2022 Best ways to go viral and monetize faceless Instagram accounts.\n\n(\ud83d\udcc8 Pro) Will The Real Daquan Please Stand Up \u2022 The story behind one of the most popular meme accounts of all times.\n\n(\ud83d\udcc8 Pro) Instagram Niches Ideas \u2022 17 profitable Instagram niche ideas.\n\n(\ud83d\udcc8 Pro) How to Grow on Social Media Without Showing Your Face \u2022 Niches, content ideas and other tips on making faceless short-form videos.\n\n\ud83d\udcc1 Related Reports\n\n\n\nFaceless YouTube Channels \u2022 Express your creativity without worrying about your looks, status or reputation.\n\nThe Creator Economy \u2022 The ability to create and distribute work is being democratized.\n\nAI-Generated Content \u2022 AI-generated content takes us from the era of limited to infinite leverage.\n\nInfluencer Marketing \u2022 Build awareness and find customers.\n\nVirtual Influencers \u2022 Make an ideal brand ambassador from scratch.\n\n\ud83d\ude4f Thanks\n\nThanks to Prabhjot Singh Lamba, Tony Tong, Stewart Townsend and Justin Brooke. We had a great time jamming on this report.\n\n\u270f\ufe0f Emin researched and wrote this report. Dru researched and edited this report.]]>\n    \u201cContent is fire. Social media is gasoline.\u201d \u2014 Jay Baer\n\n\ud83d\udc8e Why It Matters\n\nYou can build viral brands without key-person risk.\n\n\ud83d\udd0d Problem\n\nWe want to be inspired, educated and entertained.\n\n\ud83d\udca1 Solution\n\nFaceless social media accounts fulfill our need for useful, interesting and amusing content.\n\n\ud83c\udfc1 Players\n\nFaceless Social Media Accounts\n\n\n\nVC Brags \u2022 Memes on venture capital\n\nHow They Make Movies \u2022 Behind-the-scenes of making movies\n\nNature Is Metal \u2022 The brutal nature of wildlife\n\nSatisfying Videos \u2022 Videos to please your mood\n\nHidden Tips \u2022 The best tips, tricks and life hacks\n\nIts Wood Working \u2022 The art of woodworking\n\nMATH TRICK \u2022 Tricks to get better at math\n\n(\ud83d\udcc8 Pro \u2193)\n\nHow to Learn English \u2022 Learn English words and grammar\n\nPast Factory \u2022 History and nostalgia\n\nClassic ArtWorks \u2022 Classic paintings, sculptures and more\n\nBloody Elbow \u2022 Highlights from fight sports\n\nMovie Recaps \u2022 Movie summaries and explanations\n\nHome Ideas \u2022 Home renovation memes and inspiration\n\nAesthetic WorkOut \u2022 Workout exercises and motivation\n\nClassical Art Memes \u2022 Memes on paintings, sculptures and more\n\nStreetArtGlobe\u2122 \u2022 Shares art installations\n\nWildlife Whispers \u2022 Cute animals from zoos\n\nOld Houses Under50K \u2022 Old houses for sale\n\nZillow Gone Wild \u2022 Unique home interior designs\n\nWeird Spotify Playlists \u2022 Weird music playlists on Spotify\n\n\ud83d\udd2e Predictions\n\n\n\nBig media companies will acquire faceless social media accounts to reach new audiences.\n\n\nLabX Media Group acquired IFLScience in 2020.\n\nWarner Music Group acquired Daquan for $85,000,000.\n\nMedia studios will manage many accounts to boost their reach with diversified content.\n\n\nComplex Networks runs Complex and Complex Music.\n\nVox Media runs NowThis, Thrillist, The Dodo and Seeker.\n\nHive Media Group runs Bleacher Breaker, BUZZNET, Past Factory and Quizscape.\n\nWe\u2019ll see marketplaces for buying and selling social media accounts. They will foster transactions with verification and escrow services.\n\n\nSocial Tradia lets you buy and sell Instagram accounts.\n\nFameSwap lets you buy and sell Instagram, YouTube and TikTok accounts.\n\nAccs-Market.com lets you flip channels on YouTube, Twitter, TikTok, Facebook, Instagram and more.\n\n(\ud83d\udcc8 Pro) We\u2019ll see uncensored alternatives to popular social media platforms. They will let creators make content without restrictions.\n\n\nMastodon is an open-source alternative to Twitter.\n\nMinds is an open-source and decentralized social network.\n\nFriendica is a decentralized social network with distributed servers.\n\nEllo was an alternative to Facebook and Pinterest that didn\u2019t survive the competition. \n\n(\ud83d\udcc8 Pro) We\u2019ll see million-dollar, one-person faceless social media accounts.\n\n\nDevon Canup says he\u2019s made $1,000,000+ in 3 years with faceless YouTube channels.\n\nChems says he owns 30+ faceless YouTube channels and earns $1,000,000+ per year.\n\nScott DeLong was making $180,000 MRR by posting quotes on Christianity in a Facebook group.\n\n(\ud83d\udcc8 Pro) Social media accounts will evolve into standalone media companies.\n\n\nDaquan turned from an Instagram page into a media empire.\n\nF*CKJERRY started as an Instagram meme page that tried to tap into the news space.\n\nGrindFace TV had pages on Facebook and Instagram. Then turned into a platform for unheard talent.\n\n(\ud83d\udcc8 Pro) Faceless social media accounts will automate content creation by posting AI-generated content.\n\n\nArchillect uses AI to curate content.\n\nReal Fake Products shares AI-generated products.\n\nShelley was the world\u2019s first collaborative AI horror writer on social media.\n\n\ud83d\udee0 How to Build Faceless Social Media Accounts\n\n\n\nBuild bots to save time publishing content.\n\n\nChatGPT Bot replies to comments that tag its profile.\n\nOdd Steam Reviews is a bot that posts game reviews.\n\nWhaleCalls is a bot that shares Bitcoin market reports.\n\nDSCOVR:EPIC is a bot that shares pictures of Earth from a DSCOVR satellite.\n\nIndian Sharemarket Updates is a bot that posts updates on the Indian stock market.\n\nDanganronpa Anything Bot shares posts about Danganronpa video game series every 30 minutes.\n\nUse AI to make visuals fast. ChatGPT can write posts and video scripts. AI image generators can make themed graphics.\n\n\nAI Hustlewise shows how to make viral talking AI avatars.\n\nMax Jones shows how to make 100 TikTok videos in 1 hour with AI.\n\nLori Ballen shows how to make 50 social media posts in 5 minutes using ChatGPT and Canva.\n\nRevenue Rebels shows how to make explainer videos using AI-generated scripts, voices and visuals.\n\nCurate content from other creators. This can help you fill your release cadence when you\u2019re low on content ideas.\n\n\nDiply aggregates conversations from the internet.\n\nimages_ai shares images generated by AI artists.\n\nFoodie shares content made by other food bloggers. \n\n\n\n(\ud83d\udcc8 Pro) Welcome user-generated content. This will help you put your content creation on autopilot.\n\n\nNature Is Metal lets you submit wildlife clips.\n\nBarked lets you submit your dog pictures and videos.\n\nBEST VACATIONS lets you submit travel photos and videos.\n\n(\ud83d\udcc8 Pro) Make a parody account to piggyback on the attention paid to famous personalities.\n\n\nElon Musk (Parody) got replies from Elon Musk and Mr. Beast.\n\nMark Zuckerberg (Parody) posts jokes and memes from Mark Zuckerberg.\n\ndeeptomcruise pictures Tom Cruise joking, dancing, fooling around and more.\n\n(\ud83d\udcc8 Pro) Use consistent branding to stand out from competitors.\n\n\nHistory Photographed adds a logo and a signature to the majority of its posts.\n\nMind Motivation Coaching makes thumbnails with low-key images, faces and quotes.\n\nKurzgesagt has a recognizable logo of Earth, 2D vector illustrations and animations across all social media accounts.\n\n(\ud83d\udcc8 Pro) Niche down to serve an audience with unique interests. This can help you lower the competition.\n\n\nCountry Life Dreams curates rural houses for sale.\n\nAfrican Animals shares photos and videos of African wildlife.\n\nLakers Empire shares game highlights of Los Angeles Lakers.\n\nClassic ArtWorks shares classic paintings, sculptures and more.\n\nHumans of New York shares life stories from New York residents.\n\nPrimates shares content about gorillas, monkeys and other primates.\n\n(\ud83d\udcc8 Pro) Start a faceless YouTube channel. You don\u2019t need to worry about how you look, speak and act on camera.\n\n\nNomadic Ambience shares city walk videos.\n\nGameranx shares game news, reviews and gameplay.\n\nFINAiUS shares documentaries about the world\u2019s financial geniuses.\n\n\ud83c\udf31 How to Grow Faceless Social Media Accounts\n\n\n\nBuild a content flywheel by posting on many social media platforms. This helps to boost your reach.\n\n\nThe Tiny Chef Show posts clips on Twitter, Facebook and Instagram.\n\nFailArmy shares funny fail videos on Twitter, TikTok, Facebook and Instagram.\n\nFuturism shares science, technology and medicine news on Twitter, Facebook and Instagram.\n\nPost daily to boost your visibility.\n\n\nPast Factory shares daily history and nostalgic posts.\n\nMeaning in picture shares daily stories in the pictures.\n\nLearn Something shares daily posts on science, mechanisms and more.\n\nCollaborate with others to reach audiences with aligned interests.\n\n\nlil miquela is a virtual influencer who met Saweetie in public.\n\nNature Is Metal collaborated with ECO DEFENSE GROUP to support the defense of wildlife.\n\nIronmouse and Mori Calliope had a live stream on video games, plans for future collabs and what it's like to be a VTuber.\n\n(\ud83d\udcc8 Pro) Take your content to extremes. The tension and anticipation make people enjoy it more.\n\n\nNature Is Metal shares the brutal nature of wildlife.\n\nWow Terrifying shares creepy creatures and more.\n\nScary Underwater shares creepy moments at sea.\n\n1000 WAYS TO DIE shares near-death experiences.\n\n(\ud83d\udcc8 Pro) Use short-form videos to accommodate shorter attention spans.\n\n\nKimigami shares origami tutorials.\n\nSimple Man's Life shares food recipes.\n\nChinese Driver shares street photography videos.\n\n(\ud83d\udcc8 Pro) Cover trending topics. It\u2019s easier to ride existing waves instead of trying to create new ones.\n\n\nAngry Tom shares AI news and tools.\n\n0xb1 was an early DeFi and NFT investor sharing insights in this space.\n\nSicarious has been tweeting about crypto and blockchain since the early days of Bitcoin.\n\n(\ud83d\udcc8 Pro) Post many times per day to stay top of mind.\n\n\n100 Reason to smile shares funny videos.\n\nHidden Tips shares random tips, tricks and life hacks.\n\nAesthetic WorkOut shares workout exercises and motivation.\n\n(\ud83d\udcc8 Pro) Launch multiple accounts to boost your chances of success.\n\n\nSteven Van runs many accounts with tips on using graphic design tools.\n\nNoah Morris runs 18 faceless YouTube channels and made $500,000 in 90 days.\n\nDIGITAL INCOME PROJECT says he runs faceless accounts in travel, sports, health and fitness niches.\n\n(\ud83d\udcc8 Pro) Build a community to lower platform risk.\n\n\nCarDealershipGuy has a private car buyer community.\n\nThe Trading Post has a group with stock market insights.\n\nNeytirix has a Discord channel with art tutorials, character submissions and more.\n\n\ud83d\udcb0 How to Monetize Faceless Social Media Accounts\n\n\n\nSell digital products to earn scalable revenue.\n\n\nEaslo sells productivity templates for Notion.\n\nPikuma sells courses on game development.\n\nGood Minds Quote\u2122 sells an e-book on self-discipline.\n\nCheap Houses Japan sells access to a paid newsletter.\n\nUse affiliate marketing to monetize your traffic.\n\n\nCheatSheets shares affiliate links to Miss Excel\u2019s courses.\n\nNature Predators and Scary Sea share links to Tactical Blades.\n\nAdobe Premiere Pro - Tips, Tricks & Tutorials shares links to Procreate Dreams.\n\nSell physical products to offer tangible value to your fans.\n\n\nVC Brags sells hats.\n\nClassical Art Memes sells Facemask Van Gogh.\n\nGators Daily sells flags, merch and accessories.\n\nMenwiththepot sells knives, seasoning and more.\n\nCompound Interest sells posters, mugs, pillows and more.\n\n(\ud83d\udcc8 Pro) Build a physical business based on your brand account. Faceless social media accounts are great for branded products and services.\n\n\nJuna promotes Chlorophyll Detox Drops.\n\nSo-Cal Burgers promotes its burger restaurant.\n\nwildflowerdesign.co promotes its design services.\n\nDynocom Industries promotes its dynamometer products.\n\nGHOST promotes its sports nutrition, energy drinks and more.\n\n(\ud83d\udcc8 Pro) Join revenue-sharing programs. Platforms reward top content creators.\n\n\nYouTube pays for ads between Shorts in the feed.\n\nSnapchat pays for ads between Snaps in the feed.\n\nTikTok Pulse pays creators of the top 4% of all TikTok videos.\n\nX (formerly Twitter) pays for verified user's organic impressions.\n\nMeta pays for videos with licensed music, Reels, in-stream ads and Instagram posts.\n\n(\ud83d\udcc8 Pro) Offer paid subscriptions with exclusive content.\n\n\nNeytirix gives access to premium community channels.\n\nExocomics shares artwork timelapse with paid subscribers.\n\nNO CONTEXT HUMANS lets you see exclusive tweets for $3 per month.\n\nNomadic Ambience gives access to travel photos for personal and commercial use.\n\n(\ud83d\udcc8 Pro) Use brand partnerships to help companies reach prospective customers.\n\n\nAgadar partnered with Klarna for a shopping campaign.\n\n5-Minute Crafts promotes Bright Side Puzzles & Riddles.\n\nThe Tiny Chef Show sang Happy Birthday to Zenni Optical.\n\nMastermind Investor promotes stock signals by Stock Region Trading Network.\n\nOff the Grid Guide partnered with Superesse Survival EDC to offer a survival kit.\n\n\ud83d\ude20 Haters\n\n\u201cSome faceless social media accounts mention the people behind them.\u201d\nThere\u2019s always someone who runs the account. The key is to focus on the content, not your personality.\n\n\u201cFaceless social media accounts are less defensible. Anybody can copy what I\u2019m doing.\u201d\nMake a virtual avatar or move to the real world without showing your face to boost your defense.\n\n\u201cIt\u2019s harder to build personal connections without showing my face.\u201d\nThis is a tradeoff of lower key-person risk.\n\n\u201cHow do I monetize content created by others? It\u2019s copyrighted.\u201d\nSee Fair Use if you\u2019re in the US. See Fair Dealing if you\u2019re in the UK, Canada or India. Your country has similar laws. In short, you might be able to use a small amount of copyrighted content in your work. But it\u2019s best to ask for permission. This is not legal advice.\n\n\ud83d\udd17 Links\n\n\n\n250,000+ followers by sharing weird game reviews? \u2022 The thread for this report.\n\nBuilding a Report on Faceless Social Media Accounts \u2022 The tweet behind this report.\n\nI Made a Faceless TikTok Account \u2022 How to make $60,000 in 6 months with a faceless TikTok account.\n\nBrand Consistency on Social Media \u2022 Tips on building a consistent brand on social media.\n\n(\ud83d\udcc8 Pro) Building a Report on Faceless Social Media Accounts \u2022 The tweet behind this report.\n\n(\ud83d\udcc8 Pro) YouTube Automation Content Farm Strategies \u2022 How to build a content farm on YouTube.\n\n(\ud83d\udcc8 Pro) Profitable Instagram Theme Page Business \u2022 Best ways to go viral and monetize faceless Instagram accounts.\n\n(\ud83d\udcc8 Pro) Will The Real Daquan Please Stand Up \u2022 The story behind one of the most popular meme accounts of all times.\n\n(\ud83d\udcc8 Pro) Instagram Niches Ideas \u2022 17 profitable Instagram niche ideas.\n\n(\ud83d\udcc8 Pro) How to Grow on Social Media Without Showing Your Face \u2022 Niches, content ideas and other tips on making faceless short-form videos.\n\n\ud83d\udcc1 Related Reports\n\n\n\nFaceless YouTube Channels \u2022 Express your creativity without worrying about your looks, status or reputation.\n\nThe Creator Economy \u2022 The ability to create and distribute work is being democratized.\n\nAI-Generated Content \u2022 AI-generated content takes us from the era of limited to infinite leverage.\n\nInfluencer Marketing \u2022 Build awareness and find customers.\n\nVirtual Influencers \u2022 Make an ideal brand ambassador from scratch.\n\n\ud83d\ude4f Thanks\n\nThanks to Prabhjot Singh Lamba, Tony Tong, Stewart Townsend and Justin Brooke. We had a great time jamming on this report.\n\n\u270f\ufe0f Emin researched and wrote this report. Dru researched and edited this report.]]>\n  \n  \n    Inversion: The Crucial Thinking Skill Nobody Ever Taught You\n    https://jamesclear.com/inversion\n    readwise:01jm4kscrp9dmaxmce9kgkamdm\n    Sat, 15 Feb 2025 10:52:07 +0000\n    James Clear\n    The ancient Stoic philosophers like Marcus Aurelius, Seneca, and Epictetus regularly conducted an exercise known as a premeditatio malorum, which translates to a \u201cpremeditation of evils.\u201d\n\nThe goal of this exercise was to envision the negative things that could happen in life. For example, the Stoics would imagine what it would be like to lose their job and become homeless or to suffer an injury and become paralyzed or to have their reputation ruined and lose their status in society.\n\nThe Stoics believed that by imagining the worst case scenario ahead of time, they could overcome their fears of negative experiences and make better plans to prevent them. While most people were focused on how they could achieve success, the Stoics also considered how they would manage failure. What would things look like if everything went wrong tomorrow? And what does this tell us about how we should prepare today?\n\nThis way of thinking, in which you consider the opposite of what you want, is known as inversion. When I first learned of it, I didn\u2019t realize how powerful it could be. As I have studied it more, I have begun to realize that inversion is a rare and crucial skill that nearly all great thinkers use to their advantage.\n\n\n\nHow Great Thinkers Shatter the Status Quo with Inversion\n\nThe German mathematician Carl Jacobi made a number of important contributions to different scientific fields during his career. In particular, he was known for his ability to solve hard problems by following a strategy of man muss immer umkehren or, loosely translated, \u201cinvert, always invert.\u201d\n\nJacobi believed that one of the best ways to clarify your thinking was to restate math problems in inverse form. He would write down the opposite of the problem he was trying to solve and found that the solution often came to him more easily.\n\nInversion is a powerful thinking tool because it puts a spotlight on errors and roadblocks that are not obvious at first glance. What if the opposite was true? What if I focused on a different side of this situation? Instead of asking how to do something, ask how to not do it.\n\n\nGreat thinkers, icons, and innovators think forward and backward. Occasionally, they drive their brain in reverse.\n\nGreat thinkers, icons, and innovators think forward and backward. They consider the opposite side of things. Occasionally, they drive their brain in reverse. This way of thinking can reveal compelling opportunities for innovation.\n\nArt provides a good example.\n\nOne of the biggest musical shifts in the last several decades came from Nirvana, a band that legitimized a whole new genre of music\u2014alternative rock\u2014and whose Nevermind album is memorialized in the Library of Congress as one of the most \u201cculturally, historically or aesthetically important\u201d sound recordings of the 20th century.\n\nNirvana turned the conventions of mainstream rock and pop music completely upside down. Where hair metal bands like Poison and Def Leppard spent millions to produce and promote each record, Nirvana recorded Nevermind for $65,000. Where hair metal was flashy, Nirvana was stripped-down and raw.\n\nInversion is often at the core of great art. At any given time there is a status quo in society and the artists and innovators who stand out are often the ones who overturn the standard in a compelling way.\n\nGreat art breaks the previous rules. It is an inversion of what came before. In a way, the secret to unconventional thinking is just inverting the status quo.\n\nThis strategy works equally well for other creative pursuits like writing. Many great headlines and titles use the power of inversion to up-end common assumptions. As a personal example, two of my more popular articles, \u201cForget About Setting Goals\u201d and \u201cMotivation is Overvalued\u201d, take common notions and turn them on their head.\n\nSuccess is Overvalued. Avoiding Failure Matters More.\n\nThis type of inverse logic can be extended to many areas of life. For example, ambitious young people are often focused on how to achieve success. But billionaire investor Charlie Munger encourages them to consider the inverse of success instead.\n\n\u201cWhat do you want to avoid?\u201d he asks. \u201cSuch an easy answer: sloth and unreliability. If you\u2019re unreliable it doesn\u2019t matter what your virtues are. You\u2019re going to crater immediately. Doing what you have faithfully engaged to do should be an automatic part of your conduct. You want to avoid sloth and unreliability.\u201d\n\nAvoiding mistakes is an under-appreciated way to improve. In most jobs, you can enjoy some degree of success simply by being proactive and reliable\u2014even if you are not particularly smart, fast, or talented in a given area. Sometimes it is more important to consider why people fail in life than why they succeed.\n\nThe Benefits of Thinking Forward and Backward\n\nInversion can be particularly useful in the workplace.\n\nLeaders can ask themselves, \u201cWhat would someone do each day if they were a terrible manager?\u201d Good leaders would likely avoid those things.\n\nSimilarly, if innovation is a core piece of your business model you can ask, \u201cHow could we make this company less innovative?\u201d Eliminating those barriers and obstacles might help creative ideas arise more quickly.\n\nAnd every marketing department wants to attract new business, but it might be useful to ask, \u201cWhat would alienate our core customer?\u201d A different point of view can reveal surprising insights.\n\nYou can learn just as much from identifying what doesn\u2019t work as you can from spotting what does. What are the mistakes, errors, and flubs that you want to avoid? Inversion is not about finding good advice, but rather about finding anti-advice. It teaches you what to avoid.\n\nHere are some more ways to utilize inversion in work and life:\n\nProject Management\n\nOne of my favorite applications of inversion is known as a Failure Premortem. It is like a Premeditation of Evils for the modern day company.\n\nIt works like this:\n\nImagine the most important goal or project you are working on right now. Now fast forward six months and assume the project or goal has failed.\n\nTell the story of how it happened. What went wrong? What mistakes did you make? How did it fail? In other words, think of your main goal and ask yourself, \u201cWhat could cause this to go horribly wrong?\u201d\n\nThis strategy is sometimes called the \u201ckill the company\u201d exercise in organizations because the goal is to spell out the exact ways the company could fail. Just like a Premeditation of Evils, the idea is to identify challenges and points of failure so you can develop a plan to prevent them ahead of time.\n\nProductivity\n\nMost people want to get more done in less time. Applying inversion to productivity you could ask, \u201cWhat if I wanted to decrease my focus? How do I end up distracted?\u201d The answer to that question may help you discover interruptions you can eliminate to free up more time and energy each day.\n\nThis strategy is not only effective, but often safer than chasing success. For example, some people take drugs or mental stimulants in an effort to increase their productivity. These methods might work, but you also run the risk of possible side effects.\n\nMeanwhile, there is very little danger in leaving your phone in another room, blocking social media websites, or unplugging your television. Both strategies deal with the same problem, but inversion allows you to attack it from a different angle and with less risk.\n\nThis insight reveals a more general principle: Blindly chasing success can have severe consequences, but preventing failure usually carries very little risk.\n\nDecluttering\n\nMarie Kondo, author of the blockbuster best-seller The Life-Changing Magic of Tidying Up, uses inversion to help people declutter their homes. Her famous line is, \u201cWe should be choosing what we want to keep, not what we want to get rid of.\u201d\n\nIn other words, the default should be to give anything away that does not \u201cspark joy\u201d in your life. This shift in mindset inverts decluttering by focusing on what you want to keep rather than what you want to discard.\n\nRelationships\n\nWhat behaviors might ruin a marriage? Lack of trust. Not respecting the other person. Not letting each person have time to be an individual. Spending all of your time on your kids and not investing in your relationship together. Not having open communication about money and spending habits. Inverting a good marriage can show you how to avoid a bad one.\n\nPersonal Finance\n\nEveryone wants to make more money. But what if you inverted the problem? How could you destroy your financial health?\n\nSpending more than you earn is a proven path to financial failure. It doesn\u2019t matter how much money you have, the math will never work out for you over time. Similarly, accumulating debt is a hair-on-fire emergency to be resolved as quickly as possible. And gradually creeping into unchecked shopping and spending habits can lead to self-inflicted financial stress.\n\nBefore you worry too much about how to make more money make sure you have figured out how to not lose money. If you can manage to avoid these problems, you\u2019ll be far ahead of many folks and save yourself a lot of pain and anguish along the way.\n\nConsider the Opposite\n\nInversion is counterintuitive. It is not obvious to spend time thinking about the opposite of what you want.\n\nAnd yet inversion is a key tool of many great thinkers. Stoic practitioners visualize negative outcomes. Groundbreaking artists invert the status quo. Effective leaders avoid the mistakes that prevent success just as much as they chase the skills that accelerate it.\n\nInversion can be particularly useful for challenging your own beliefs. It forces you to treat your decisions like a court of law. In court, the jury has to listen to both sides of the argument before making up their mind. Inversion helps you do something similar. What if the evidence disconfirmed what you believe? What if you tried to destroy the views that you cherish? Inversion prevents you from making up your mind after your first conclusion. It is a way to counteract the gravitational pull of confirmation bias.\n\nInversion is an essential skill for leading a logical and rational life. It allows you to step outside your normal patterns of thought and see situations from a different angle. Whatever problem you are facing, always consider the opposite side of things.\n\nFootnotes\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.\n\nJames Clear writes about habits, decision making, and continuous improvement. He is the author of the #1 New York Times bestseller, Atomic Habits. The book has sold over 10 million copies worldwide and has been translated into more than 50 languages.]]>\n    The ancient Stoic philosophers like Marcus Aurelius, Seneca, and Epictetus regularly conducted an exercise known as a premeditatio malorum, which translates to a \u201cpremeditation of evils.\u201d\n\nThe goal of this exercise was to envision the negative things that could happen in life. For example, the Stoics would imagine what it would be like to lose their job and become homeless or to suffer an injury and become paralyzed or to have their reputation ruined and lose their status in society.\n\nThe Stoics believed that by imagining the worst case scenario ahead of time, they could overcome their fears of negative experiences and make better plans to prevent them. While most people were focused on how they could achieve success, the Stoics also considered how they would manage failure. What would things look like if everything went wrong tomorrow? And what does this tell us about how we should prepare today?\n\nThis way of thinking, in which you consider the opposite of what you want, is known as inversion. When I first learned of it, I didn\u2019t realize how powerful it could be. As I have studied it more, I have begun to realize that inversion is a rare and crucial skill that nearly all great thinkers use to their advantage.\n\n\n\nHow Great Thinkers Shatter the Status Quo with Inversion\n\nThe German mathematician Carl Jacobi made a number of important contributions to different scientific fields during his career. In particular, he was known for his ability to solve hard problems by following a strategy of man muss immer umkehren or, loosely translated, \u201cinvert, always invert.\u201d\n\nJacobi believed that one of the best ways to clarify your thinking was to restate math problems in inverse form. He would write down the opposite of the problem he was trying to solve and found that the solution often came to him more easily.\n\nInversion is a powerful thinking tool because it puts a spotlight on errors and roadblocks that are not obvious at first glance. What if the opposite was true? What if I focused on a different side of this situation? Instead of asking how to do something, ask how to not do it.\n\n\nGreat thinkers, icons, and innovators think forward and backward. Occasionally, they drive their brain in reverse.\n\nGreat thinkers, icons, and innovators think forward and backward. They consider the opposite side of things. Occasionally, they drive their brain in reverse. This way of thinking can reveal compelling opportunities for innovation.\n\nArt provides a good example.\n\nOne of the biggest musical shifts in the last several decades came from Nirvana, a band that legitimized a whole new genre of music\u2014alternative rock\u2014and whose Nevermind album is memorialized in the Library of Congress as one of the most \u201cculturally, historically or aesthetically important\u201d sound recordings of the 20th century.\n\nNirvana turned the conventions of mainstream rock and pop music completely upside down. Where hair metal bands like Poison and Def Leppard spent millions to produce and promote each record, Nirvana recorded Nevermind for $65,000. Where hair metal was flashy, Nirvana was stripped-down and raw.\n\nInversion is often at the core of great art. At any given time there is a status quo in society and the artists and innovators who stand out are often the ones who overturn the standard in a compelling way.\n\nGreat art breaks the previous rules. It is an inversion of what came before. In a way, the secret to unconventional thinking is just inverting the status quo.\n\nThis strategy works equally well for other creative pursuits like writing. Many great headlines and titles use the power of inversion to up-end common assumptions. As a personal example, two of my more popular articles, \u201cForget About Setting Goals\u201d and \u201cMotivation is Overvalued\u201d, take common notions and turn them on their head.\n\nSuccess is Overvalued. Avoiding Failure Matters More.\n\nThis type of inverse logic can be extended to many areas of life. For example, ambitious young people are often focused on how to achieve success. But billionaire investor Charlie Munger encourages them to consider the inverse of success instead.\n\n\u201cWhat do you want to avoid?\u201d he asks. \u201cSuch an easy answer: sloth and unreliability. If you\u2019re unreliable it doesn\u2019t matter what your virtues are. You\u2019re going to crater immediately. Doing what you have faithfully engaged to do should be an automatic part of your conduct. You want to avoid sloth and unreliability.\u201d\n\nAvoiding mistakes is an under-appreciated way to improve. In most jobs, you can enjoy some degree of success simply by being proactive and reliable\u2014even if you are not particularly smart, fast, or talented in a given area. Sometimes it is more important to consider why people fail in life than why they succeed.\n\nThe Benefits of Thinking Forward and Backward\n\nInversion can be particularly useful in the workplace.\n\nLeaders can ask themselves, \u201cWhat would someone do each day if they were a terrible manager?\u201d Good leaders would likely avoid those things.\n\nSimilarly, if innovation is a core piece of your business model you can ask, \u201cHow could we make this company less innovative?\u201d Eliminating those barriers and obstacles might help creative ideas arise more quickly.\n\nAnd every marketing department wants to attract new business, but it might be useful to ask, \u201cWhat would alienate our core customer?\u201d A different point of view can reveal surprising insights.\n\nYou can learn just as much from identifying what doesn\u2019t work as you can from spotting what does. What are the mistakes, errors, and flubs that you want to avoid? Inversion is not about finding good advice, but rather about finding anti-advice. It teaches you what to avoid.\n\nHere are some more ways to utilize inversion in work and life:\n\nProject Management\n\nOne of my favorite applications of inversion is known as a Failure Premortem. It is like a Premeditation of Evils for the modern day company.\n\nIt works like this:\n\nImagine the most important goal or project you are working on right now. Now fast forward six months and assume the project or goal has failed.\n\nTell the story of how it happened. What went wrong? What mistakes did you make? How did it fail? In other words, think of your main goal and ask yourself, \u201cWhat could cause this to go horribly wrong?\u201d\n\nThis strategy is sometimes called the \u201ckill the company\u201d exercise in organizations because the goal is to spell out the exact ways the company could fail. Just like a Premeditation of Evils, the idea is to identify challenges and points of failure so you can develop a plan to prevent them ahead of time.\n\nProductivity\n\nMost people want to get more done in less time. Applying inversion to productivity you could ask, \u201cWhat if I wanted to decrease my focus? How do I end up distracted?\u201d The answer to that question may help you discover interruptions you can eliminate to free up more time and energy each day.\n\nThis strategy is not only effective, but often safer than chasing success. For example, some people take drugs or mental stimulants in an effort to increase their productivity. These methods might work, but you also run the risk of possible side effects.\n\nMeanwhile, there is very little danger in leaving your phone in another room, blocking social media websites, or unplugging your television. Both strategies deal with the same problem, but inversion allows you to attack it from a different angle and with less risk.\n\nThis insight reveals a more general principle: Blindly chasing success can have severe consequences, but preventing failure usually carries very little risk.\n\nDecluttering\n\nMarie Kondo, author of the blockbuster best-seller The Life-Changing Magic of Tidying Up, uses inversion to help people declutter their homes. Her famous line is, \u201cWe should be choosing what we want to keep, not what we want to get rid of.\u201d\n\nIn other words, the default should be to give anything away that does not \u201cspark joy\u201d in your life. This shift in mindset inverts decluttering by focusing on what you want to keep rather than what you want to discard.\n\nRelationships\n\nWhat behaviors might ruin a marriage? Lack of trust. Not respecting the other person. Not letting each person have time to be an individual. Spending all of your time on your kids and not investing in your relationship together. Not having open communication about money and spending habits. Inverting a good marriage can show you how to avoid a bad one.\n\nPersonal Finance\n\nEveryone wants to make more money. But what if you inverted the problem? How could you destroy your financial health?\n\nSpending more than you earn is a proven path to financial failure. It doesn\u2019t matter how much money you have, the math will never work out for you over time. Similarly, accumulating debt is a hair-on-fire emergency to be resolved as quickly as possible. And gradually creeping into unchecked shopping and spending habits can lead to self-inflicted financial stress.\n\nBefore you worry too much about how to make more money make sure you have figured out how to not lose money. If you can manage to avoid these problems, you\u2019ll be far ahead of many folks and save yourself a lot of pain and anguish along the way.\n\nConsider the Opposite\n\nInversion is counterintuitive. It is not obvious to spend time thinking about the opposite of what you want.\n\nAnd yet inversion is a key tool of many great thinkers. Stoic practitioners visualize negative outcomes. Groundbreaking artists invert the status quo. Effective leaders avoid the mistakes that prevent success just as much as they chase the skills that accelerate it.\n\nInversion can be particularly useful for challenging your own beliefs. It forces you to treat your decisions like a court of law. In court, the jury has to listen to both sides of the argument before making up their mind. Inversion helps you do something similar. What if the evidence disconfirmed what you believe? What if you tried to destroy the views that you cherish? Inversion prevents you from making up your mind after your first conclusion. It is a way to counteract the gravitational pull of confirmation bias.\n\nInversion is an essential skill for leading a logical and rational life. It allows you to step outside your normal patterns of thought and see situations from a different angle. Whatever problem you are facing, always consider the opposite side of things.\n\nFootnotes\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.\n\nJames Clear writes about habits, decision making, and continuous improvement. He is the author of the #1 New York Times bestseller, Atomic Habits. The book has sold over 10 million copies worldwide and has been translated into more than 50 languages.]]>\n  \n  \n    For a More Creative Brain Follow These 5 Steps\n    https://jamesclear.com/five-step-creative-process\n    readwise:01jm4ks7jbavxr1e667xmp2eqm\n    Sat, 15 Feb 2025 10:52:02 +0000\n    James Clear\n    Nearly all great ideas follow a similar creative process and this article explains how this process works. Understanding this is important because creative thinking is one of the most useful skills you can possess. Nearly every problem you face in work and in life can benefit from innovative solutions, lateral thinking, and creative ideas.\n\nAnyone can learn to be creative by using these five steps. That\u2019s not to say being creative is easy. Uncovering your creative genius requires courage and tons of practice. However, this five-step approach should help demystify the creative process and illuminate the path to more innovative thinking.\n\nTo explain how this process works, let me tell you a short story.\n\nA Problem in Need of a Creative Solution\n\nIn the 1870s, newspapers and printers faced a very specific and very costly problem. Photography was a new and exciting medium at the time. Readers wanted to see more pictures, but nobody could figure out how to print images quickly and cheaply.\n\nFor example, if a newspaper wanted to print an image in the 1870s, they had to commission an engraver to etch a copy of the photograph onto a steel plate by hand. These plates were used to press the image onto the page, but they often broke after just a few uses. This process of photoengraving, you can imagine, was remarkably time consuming and expensive.\n\nThe man who invented a solution to this problem was named Frederic Eugene Ives. He went on to become a trailblazer in the field of photography and held over 70 patents by the end of his career. His story of creativity and innovation, which I will share now, is a useful case study for understanding the 5 key steps of the creative process.\n\nA Flash of Insight\n\nIves got his start as a printer\u2019s apprentice in Ithaca, New York. After two years of learning the ins and outs of the printing process, he began managing the photographic laboratory at nearby Cornell University. He spent the rest of the decade experimenting with new photography techniques and learning about cameras, printers, and optics.\n\nIn 1881, Ives had a flash of insight regarding a better printing technique.\n\n\u201cWhile operating my photostereotype process in Ithaca, I studied the problem of halftone process,\u201d Ives said. \u201cI went to bed one night in a state of brain fog over the problem, and the instant I woke in the morning saw before me, apparently projected on the ceiling, the completely worked out process and equipment in operation.\u201d\n\nIves quickly translated his vision into reality and patented his printing approach in 1881. He spent the remainder of the decade improving upon it. By 1885, he had developed a simplified process that delivered even better results. The Ives Process, as it came to be known, reduced the cost of printing images by 15x and remained the standard printing technique for the next 80 years.\n\nAlright, now let\u2019s discuss what lessons we can learn from Ives about the creative process.\n\n\nThe printing process developed by Frederic Eugene Ives used a method called \u201chalftone printing\u201d to break a photograph down into a series of tiny dots. The image looks like a collection of dots up close, but when viewed from a normal distance the dots blend together to create a picture with varying shades of gray. (Source: Unknown.)\n\nThe 5 Stages of the Creative Process\n\nIn 1940, an advertising executive named James Webb Young published a short guide titled, A Technique for Producing Ideas. In this guide, he made a simple, but profound statement about generating creative ideas.\n\nAccording to Young, innovative ideas happen when you develop new combinations of old elements. In other words, creative thinking is not about generating something new from a blank slate, but rather about taking what is already present and combining those bits and pieces in a way that has not been done previously.\n\nMost important, the ability to generate new combinations hinges upon your ability to see the relationships between concepts. If you can form a new link between two old ideas, you have done something creative.\n\nYoung believed this process of creative connection always occurred in five steps.\n\n \nGather new material. At first, you learn. During this stage you focus on 1) learning specific material directly related to your task and 2) learning general material by becoming fascinated with a wide range of concepts. \nThoroughly work over the materials in your mind. During this stage, you examine what you have learned by looking at the facts from different angles and experimenting with fitting various ideas together. \nStep away from the problem. Next, you put the problem completely out of your mind and go do something else that excites you and energizes you. \nLet your idea return to you. At some point, but only after you have stopped thinking about it, your idea will come back to you with a flash of insight and renewed energy. \nShape and develop your idea based on feedback. For any idea to succeed, you must release it out into the world, submit it to criticism, and adapt it as needed. \n\n\n\nThe Idea in Practice\n\nThe creative process used by Frederic Eugene Ives offers a perfect example of these five steps in action.\n\nFirst, Ives gathered new material. He spent two years working as a printer\u2019s apprentice and then four years running the photographic laboratory at Cornell University. These experiences gave him a lot of material to draw upon and make associations between photography and printing.\n\nSecond, Ives began to mentally work over everything he learned. By 1878, Ives was spending nearly all of his time experimenting with new techniques. He was constantly tinkering and experimenting with different ways of putting ideas together.\n\nThird, Ives stepped away from the problem. In this case, he went to sleep for a few hours before his flash of insight. Letting creative challenges sit for longer periods of time can work as well. Regardless of how long you step away, you need to do something that interests you and takes your mind off of the problem.\n\nFourth, his idea returned to him. Ives awoke with the solution to his problem laid out before him. (On a personal note, I often find creative ideas hit me just as I am lying down for sleep. Once I give my brain permission to stop working for the day, the solution appears easily.)\n\nFinally, Ives continued to revise his idea for years. In fact, he improved so many aspects of the process he filed a second patent. This is a critical point and is often overlooked. It can be easy to fall in love with the initial version of your idea, but great ideas always evolve.\n\nThe Creative Process in Short\n\n\n\u201cAn idea is a feat of association, and the height of it is a good metaphor.\u201d \u2014Robert Frost\n\nThe creative process is the act of making new connections between old ideas. Thus, we can say creative thinking is the task of recognizing relationships between concepts.\n\nOne way to approach creative challenges is by following the five-step process of 1) gathering material, 2) intensely working over the material in your mind, 3) stepping away from the problem, 4) allowing the idea to come back to you naturally, and 5) testing your idea in the real world and adjusting it based on feedback.\n\nBeing creative isn\u2019t about being the first (or only) person to think of an idea. More often, creativity is about connecting ideas.\n\n\n\nThis quote is excerpted from A Technique for Producing Ideas by James Webb Young. Page 21.\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 3,000,000 people subscribe. Enter your email now and join us.]]>\n    Nearly all great ideas follow a similar creative process and this article explains how this process works. Understanding this is important because creative thinking is one of the most useful skills you can possess. Nearly every problem you face in work and in life can benefit from innovative solutions, lateral thinking, and creative ideas.\n\nAnyone can learn to be creative by using these five steps. That\u2019s not to say being creative is easy. Uncovering your creative genius requires courage and tons of practice. However, this five-step approach should help demystify the creative process and illuminate the path to more innovative thinking.\n\nTo explain how this process works, let me tell you a short story.\n\nA Problem in Need of a Creative Solution\n\nIn the 1870s, newspapers and printers faced a very specific and very costly problem. Photography was a new and exciting medium at the time. Readers wanted to see more pictures, but nobody could figure out how to print images quickly and cheaply.\n\nFor example, if a newspaper wanted to print an image in the 1870s, they had to commission an engraver to etch a copy of the photograph onto a steel plate by hand. These plates were used to press the image onto the page, but they often broke after just a few uses. This process of photoengraving, you can imagine, was remarkably time consuming and expensive.\n\nThe man who invented a solution to this problem was named Frederic Eugene Ives. He went on to become a trailblazer in the field of photography and held over 70 patents by the end of his career. His story of creativity and innovation, which I will share now, is a useful case study for understanding the 5 key steps of the creative process.\n\nA Flash of Insight\n\nIves got his start as a printer\u2019s apprentice in Ithaca, New York. After two years of learning the ins and outs of the printing process, he began managing the photographic laboratory at nearby Cornell University. He spent the rest of the decade experimenting with new photography techniques and learning about cameras, printers, and optics.\n\nIn 1881, Ives had a flash of insight regarding a better printing technique.\n\n\u201cWhile operating my photostereotype process in Ithaca, I studied the problem of halftone process,\u201d Ives said. \u201cI went to bed one night in a state of brain fog over the problem, and the instant I woke in the morning saw before me, apparently projected on the ceiling, the completely worked out process and equipment in operation.\u201d\n\nIves quickly translated his vision into reality and patented his printing approach in 1881. He spent the remainder of the decade improving upon it. By 1885, he had developed a simplified process that delivered even better results. The Ives Process, as it came to be known, reduced the cost of printing images by 15x and remained the standard printing technique for the next 80 years.\n\nAlright, now let\u2019s discuss what lessons we can learn from Ives about the creative process.\n\n\nThe printing process developed by Frederic Eugene Ives used a method called \u201chalftone printing\u201d to break a photograph down into a series of tiny dots. The image looks like a collection of dots up close, but when viewed from a normal distance the dots blend together to create a picture with varying shades of gray. (Source: Unknown.)\n\nThe 5 Stages of the Creative Process\n\nIn 1940, an advertising executive named James Webb Young published a short guide titled, A Technique for Producing Ideas. In this guide, he made a simple, but profound statement about generating creative ideas.\n\nAccording to Young, innovative ideas happen when you develop new combinations of old elements. In other words, creative thinking is not about generating something new from a blank slate, but rather about taking what is already present and combining those bits and pieces in a way that has not been done previously.\n\nMost important, the ability to generate new combinations hinges upon your ability to see the relationships between concepts. If you can form a new link between two old ideas, you have done something creative.\n\nYoung believed this process of creative connection always occurred in five steps.\n\n \nGather new material. At first, you learn. During this stage you focus on 1) learning specific material directly related to your task and 2) learning general material by becoming fascinated with a wide range of concepts. \nThoroughly work over the materials in your mind. During this stage, you examine what you have learned by looking at the facts from different angles and experimenting with fitting various ideas together. \nStep away from the problem. Next, you put the problem completely out of your mind and go do something else that excites you and energizes you. \nLet your idea return to you. At some point, but only after you have stopped thinking about it, your idea will come back to you with a flash of insight and renewed energy. \nShape and develop your idea based on feedback. For any idea to succeed, you must release it out into the world, submit it to criticism, and adapt it as needed. \n\n\n\nThe Idea in Practice\n\nThe creative process used by Frederic Eugene Ives offers a perfect example of these five steps in action.\n\nFirst, Ives gathered new material. He spent two years working as a printer\u2019s apprentice and then four years running the photographic laboratory at Cornell University. These experiences gave him a lot of material to draw upon and make associations between photography and printing.\n\nSecond, Ives began to mentally work over everything he learned. By 1878, Ives was spending nearly all of his time experimenting with new techniques. He was constantly tinkering and experimenting with different ways of putting ideas together.\n\nThird, Ives stepped away from the problem. In this case, he went to sleep for a few hours before his flash of insight. Letting creative challenges sit for longer periods of time can work as well. Regardless of how long you step away, you need to do something that interests you and takes your mind off of the problem.\n\nFourth, his idea returned to him. Ives awoke with the solution to his problem laid out before him. (On a personal note, I often find creative ideas hit me just as I am lying down for sleep. Once I give my brain permission to stop working for the day, the solution appears easily.)\n\nFinally, Ives continued to revise his idea for years. In fact, he improved so many aspects of the process he filed a second patent. This is a critical point and is often overlooked. It can be easy to fall in love with the initial version of your idea, but great ideas always evolve.\n\nThe Creative Process in Short\n\n\n\u201cAn idea is a feat of association, and the height of it is a good metaphor.\u201d \u2014Robert Frost\n\nThe creative process is the act of making new connections between old ideas. Thus, we can say creative thinking is the task of recognizing relationships between concepts.\n\nOne way to approach creative challenges is by following the five-step process of 1) gathering material, 2) intensely working over the material in your mind, 3) stepping away from the problem, 4) allowing the idea to come back to you naturally, and 5) testing your idea in the real world and adjusting it based on feedback.\n\nBeing creative isn\u2019t about being the first (or only) person to think of an idea. More often, creativity is about connecting ideas.\n\n\n\nThis quote is excerpted from A Technique for Producing Ideas by James Webb Young. Page 21.\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 3,000,000 people subscribe. Enter your email now and join us.]]>\n  \n  \n    The Ultimate Productivity Hack is Saying No\n    https://jamesclear.com/saying-no\n    readwise:01jm4ks2a3yam2n7cks6qmzr61\n    Sat, 15 Feb 2025 10:51:57 +0000\n    James Clear\n    The ultimate productivity hack is saying no.\n\nNot doing something will always be faster than doing it. This statement reminds me of the old computer programming saying, \u201cRemember that there is no code faster than no code.\u201d\n\nThe same philosophy applies in other areas of life. For example, there is no meeting that goes faster than not having a meeting at all.\n\nThis is not to say you should never attend another meeting, but the truth is that we say yes to many things we don\u2019t actually want to do. There are many meetings held that don\u2019t need to be held. There is a lot of code written that could be deleted.\n\nHow often do people ask you to do something and you just reply, \u201cSure thing.\u201d Three days later, you\u2019re overwhelmed by how much is on your to-do list. We become frustrated by our obligations even though we were the ones who said yes to them in the first place.\n\nIt\u2019s worth asking if things are necessary. Many of them are not, and a simple \u201cno\u201d will be more productive than whatever work the most efficient person can muster.\n\nBut if the benefits of saying no are so obvious, then why do we say yes so often?\n\nWhy We Say Yes\n\nWe agree to many requests not because we want to do them, but because we don\u2019t want to be seen as rude, arrogant, or unhelpful. Often, you have to consider saying no to someone you will interact with again in the future\u2014your co-worker, your spouse, your family and friends.\n\nSaying no to these people can be particularly difficult because we like them and want to support them. (Not to mention, we often need their help too.) Collaborating with others is an important element of life. The thought of straining the relationship outweighs the commitment of our time and energy.\n\nFor this reason, it can be helpful to be gracious in your response. Do whatever favors you can, and be warm-hearted and direct when you have to say no.\n\nBut even after we have accounted for these social considerations, many of us still seem to do a poor job of managing the tradeoff between yes and no. We find ourselves over-committed to things that don\u2019t meaningfully improve or support those around us, and certainly don\u2019t improve our own lives.\n\nPerhaps one issue is how we think about the meaning of yes and no.\n\nThe Difference Between Yes and No\n\nThe words \u201cyes\u201d and \u201cno\u201d get used in comparison to each other so often that it feels like they carry equal weight in conversation. In reality, they are not just opposite in meaning, but of entirely different magnitudes in commitment.\n\nWhen you say no, you are only saying no to one option. When you say yes, you are saying no to every other option.\n\nI like how the economist Tim Harford put it, \u201cEvery time we say yes to a request, we are also saying no to anything else we might accomplish with the time.\u201d Once you have committed to something, you have already decided how that future block of time will be spent.\n\nIn other words, saying no saves you time in the future. Saying yes costs you time in the future. No is a form of time credit. You retain the ability to spend your future time however you want. Yes is a form of time debt. You have to pay back your commitment at some point.\n\nNo is a decision. Yes is a responsibility.\n\nThe Role of No\n\nSaying no is sometimes seen as a luxury that only those in power can afford. And it is true: turning down opportunities is easier when you can fall back on the safety net provided by power, money, and authority. But it is also true that saying no is not merely a privilege reserved for the successful among us. It is also a strategy that can help you become successful.\n\nSaying no is an important skill to develop at any stage of your career because it retains the most important asset in life: your time. As the investor Pedro Sorrentino put it, \u201cIf you don\u2019t guard your time, people will steal it from you.\u201d\n\nYou need to say no to whatever isn\u2019t leading you toward your goals. You need to say no to distractions. As one reader told me, \u201cIf you broaden the definition as to how you apply no, it actually is the only productivity hack (as you ultimately say no to any distraction in order to be productive).\u201d\n\nNobody embodied this idea better than Steve Jobs, who said, \u201cPeople think focus means saying yes to the thing you\u2019ve got to focus on. But that\u2019s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully.\u201d\n\nThere is an important balance to strike here. Saying no doesn\u2019t mean you\u2019ll never do anything interesting or innovative or spontaneous. It just means that you say yes in a focused way. Once you have knocked out the distractions, it can make sense to say yes to any opportunity that could potentially move you in the right direction. You may have to try many things to discover what works and what you enjoy. This period of exploration can be particularly important at the beginning of a project, job, or career.\n\nUpgrading Your No\n\nOver time, as you continue to improve and succeed, your strategy needs to change.\n\nThe opportunity cost of your time increases as you become more successful. At first, you just eliminate the obvious distractions and explore the rest. As your skills improve and you learn to separate what works from what doesn\u2019t, you have to continually increase your threshold for saying yes.\n\nYou still need to say no to distractions, but you also need to learn to say no to opportunities that were previously good uses of time, so you can make space for great uses of time. It\u2019s a good problem to have, but it can be a tough skill to master.\n\nIn other words, you have to upgrade your \u201cno\u2019s\u201d over time.\n\nUpgrading your no doesn\u2019t mean you\u2019ll never say yes. It just means you default to saying no and only say yes when it really makes sense. To quote the investor Brent Beshore, \u201cSaying no is so powerful because it preserves the opportunity to say yes.\u201d\n\nThe general trend seems to be something like this: If you can learn to say no to bad distractions, then eventually you\u2019ll earn the right to say no to good opportunities.\n\nHow to Say No\n\nMost of us are probably too quick to say yes and too slow to say no. It\u2019s worth asking yourself where you fall on that spectrum.\n\nIf you have trouble saying no, you may find the following strategy proposed by Tim Harford, the British economist I mentioned earlier, to be helpful. He writes, \u201cOne trick is to ask, \u201cIf I had to do this today, would I agree to it?\u201d It\u2019s not a bad rule of thumb, since any future commitment, no matter how far away it might be, will eventually become an imminent problem.\u201d\n\nIf an opportunity is exciting enough to drop whatever you\u2019re doing right now, then it\u2019s a yes. If it\u2019s not, then perhaps you should think twice.\n\nThis is similar to the well-known \u201cHell Yeah or No\u201d method from Derek Sivers. If someone asks you to do something and your first reaction is \u201cHell Yeah!\u201d, then do it. If it doesn\u2019t excite you, then say no.\n\nIt\u2019s impossible to remember to ask yourself these questions each time you face a decision, but it\u2019s still a useful exercise to revisit from time to time. Saying no can be difficult, but it is often easier than the alternative. As writer Mike Dariano has pointed out, \u201cIt\u2019s easier to avoid commitments than get out of commitments. Saying no keeps you toward the easier end of this spectrum.\u201d\n\nWhat is true about health is also true about productivity: an ounce of prevention is worth a pound of cure.\n\nThe Power of No\n\nMore effort is wasted doing things that don\u2019t matter than is wasted doing things inefficiently. And if that is the case, elimination is a more useful skill than optimization.\n\nI am reminded of the famous Peter Drucker quote, \u201cThere is nothing so useless as doing efficiently that which should not be done at all.\u201d\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.\n\nJames Clear writes about habits, decision making, and continuous improvement. He is the author of the #1 New York Times bestseller, Atomic Habits. The book has sold over 9 million copies worldwide and has been translated into more than 50 languages.]]>\n    The ultimate productivity hack is saying no.\n\nNot doing something will always be faster than doing it. This statement reminds me of the old computer programming saying, \u201cRemember that there is no code faster than no code.\u201d\n\nThe same philosophy applies in other areas of life. For example, there is no meeting that goes faster than not having a meeting at all.\n\nThis is not to say you should never attend another meeting, but the truth is that we say yes to many things we don\u2019t actually want to do. There are many meetings held that don\u2019t need to be held. There is a lot of code written that could be deleted.\n\nHow often do people ask you to do something and you just reply, \u201cSure thing.\u201d Three days later, you\u2019re overwhelmed by how much is on your to-do list. We become frustrated by our obligations even though we were the ones who said yes to them in the first place.\n\nIt\u2019s worth asking if things are necessary. Many of them are not, and a simple \u201cno\u201d will be more productive than whatever work the most efficient person can muster.\n\nBut if the benefits of saying no are so obvious, then why do we say yes so often?\n\nWhy We Say Yes\n\nWe agree to many requests not because we want to do them, but because we don\u2019t want to be seen as rude, arrogant, or unhelpful. Often, you have to consider saying no to someone you will interact with again in the future\u2014your co-worker, your spouse, your family and friends.\n\nSaying no to these people can be particularly difficult because we like them and want to support them. (Not to mention, we often need their help too.) Collaborating with others is an important element of life. The thought of straining the relationship outweighs the commitment of our time and energy.\n\nFor this reason, it can be helpful to be gracious in your response. Do whatever favors you can, and be warm-hearted and direct when you have to say no.\n\nBut even after we have accounted for these social considerations, many of us still seem to do a poor job of managing the tradeoff between yes and no. We find ourselves over-committed to things that don\u2019t meaningfully improve or support those around us, and certainly don\u2019t improve our own lives.\n\nPerhaps one issue is how we think about the meaning of yes and no.\n\nThe Difference Between Yes and No\n\nThe words \u201cyes\u201d and \u201cno\u201d get used in comparison to each other so often that it feels like they carry equal weight in conversation. In reality, they are not just opposite in meaning, but of entirely different magnitudes in commitment.\n\nWhen you say no, you are only saying no to one option. When you say yes, you are saying no to every other option.\n\nI like how the economist Tim Harford put it, \u201cEvery time we say yes to a request, we are also saying no to anything else we might accomplish with the time.\u201d Once you have committed to something, you have already decided how that future block of time will be spent.\n\nIn other words, saying no saves you time in the future. Saying yes costs you time in the future. No is a form of time credit. You retain the ability to spend your future time however you want. Yes is a form of time debt. You have to pay back your commitment at some point.\n\nNo is a decision. Yes is a responsibility.\n\nThe Role of No\n\nSaying no is sometimes seen as a luxury that only those in power can afford. And it is true: turning down opportunities is easier when you can fall back on the safety net provided by power, money, and authority. But it is also true that saying no is not merely a privilege reserved for the successful among us. It is also a strategy that can help you become successful.\n\nSaying no is an important skill to develop at any stage of your career because it retains the most important asset in life: your time. As the investor Pedro Sorrentino put it, \u201cIf you don\u2019t guard your time, people will steal it from you.\u201d\n\nYou need to say no to whatever isn\u2019t leading you toward your goals. You need to say no to distractions. As one reader told me, \u201cIf you broaden the definition as to how you apply no, it actually is the only productivity hack (as you ultimately say no to any distraction in order to be productive).\u201d\n\nNobody embodied this idea better than Steve Jobs, who said, \u201cPeople think focus means saying yes to the thing you\u2019ve got to focus on. But that\u2019s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully.\u201d\n\nThere is an important balance to strike here. Saying no doesn\u2019t mean you\u2019ll never do anything interesting or innovative or spontaneous. It just means that you say yes in a focused way. Once you have knocked out the distractions, it can make sense to say yes to any opportunity that could potentially move you in the right direction. You may have to try many things to discover what works and what you enjoy. This period of exploration can be particularly important at the beginning of a project, job, or career.\n\nUpgrading Your No\n\nOver time, as you continue to improve and succeed, your strategy needs to change.\n\nThe opportunity cost of your time increases as you become more successful. At first, you just eliminate the obvious distractions and explore the rest. As your skills improve and you learn to separate what works from what doesn\u2019t, you have to continually increase your threshold for saying yes.\n\nYou still need to say no to distractions, but you also need to learn to say no to opportunities that were previously good uses of time, so you can make space for great uses of time. It\u2019s a good problem to have, but it can be a tough skill to master.\n\nIn other words, you have to upgrade your \u201cno\u2019s\u201d over time.\n\nUpgrading your no doesn\u2019t mean you\u2019ll never say yes. It just means you default to saying no and only say yes when it really makes sense. To quote the investor Brent Beshore, \u201cSaying no is so powerful because it preserves the opportunity to say yes.\u201d\n\nThe general trend seems to be something like this: If you can learn to say no to bad distractions, then eventually you\u2019ll earn the right to say no to good opportunities.\n\nHow to Say No\n\nMost of us are probably too quick to say yes and too slow to say no. It\u2019s worth asking yourself where you fall on that spectrum.\n\nIf you have trouble saying no, you may find the following strategy proposed by Tim Harford, the British economist I mentioned earlier, to be helpful. He writes, \u201cOne trick is to ask, \u201cIf I had to do this today, would I agree to it?\u201d It\u2019s not a bad rule of thumb, since any future commitment, no matter how far away it might be, will eventually become an imminent problem.\u201d\n\nIf an opportunity is exciting enough to drop whatever you\u2019re doing right now, then it\u2019s a yes. If it\u2019s not, then perhaps you should think twice.\n\nThis is similar to the well-known \u201cHell Yeah or No\u201d method from Derek Sivers. If someone asks you to do something and your first reaction is \u201cHell Yeah!\u201d, then do it. If it doesn\u2019t excite you, then say no.\n\nIt\u2019s impossible to remember to ask yourself these questions each time you face a decision, but it\u2019s still a useful exercise to revisit from time to time. Saying no can be difficult, but it is often easier than the alternative. As writer Mike Dariano has pointed out, \u201cIt\u2019s easier to avoid commitments than get out of commitments. Saying no keeps you toward the easier end of this spectrum.\u201d\n\nWhat is true about health is also true about productivity: an ounce of prevention is worth a pound of cure.\n\nThe Power of No\n\nMore effort is wasted doing things that don\u2019t matter than is wasted doing things inefficiently. And if that is the case, elimination is a more useful skill than optimization.\n\nI am reminded of the famous Peter Drucker quote, \u201cThere is nothing so useless as doing efficiently that which should not be done at all.\u201d\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.\n\nJames Clear writes about habits, decision making, and continuous improvement. He is the author of the #1 New York Times bestseller, Atomic Habits. The book has sold over 9 million copies worldwide and has been translated into more than 50 languages.]]>\n  \n  \n    Forget About Setting Goals. Focus on This Instead.\n    https://jamesclear.com/goals-systems\n    readwise:01jm4krxks12yvktj4e2a0edhj\n    Sat, 15 Feb 2025 10:51:52 +0000\n    James Clear\n    This article is an excerpt from Atomic Habits, my New York Times bestselling book.\n\nPrevailing wisdom claims that the best way to achieve what we want in life\u2014getting into better shape, building a successful business, relaxing more and worrying less, spending more time with friends and family\u2014is to set specific, actionable goals.\n\nFor many years, this was how I approached my habits too. Each one was a goal to be reached. I set goals for the grades I wanted to get in school, for the weights I wanted to lift in the gym, for the profits I wanted to earn in business. I succeeded at a few, but I failed at a lot of them. Eventually, I began to realize that my results had very little to do with the goals I set and nearly everything to do with the systems I followed.\n\n \nIf you\u2019re a coach, your goal might be to win a championship. Your system is the way you recruit players, manage your assistant coaches, and conduct practice. \nIf you\u2019re an entrepreneur, your goal might be to build a million-dollar business. Your system is how you test product ideas, hire employees, and run marketing campaigns. \nIf you\u2019re a musician, your goal might be to play a new piece. Your system is how often you practice, how you break down and tackle difficult measures, and your method for receiving feedback from your instructor. \n\n\n\nNow for the interesting question: if you completely ignored your goals and focused only on your system, would you still succeed? For example, if you were a basketball coach and you ignored your goal to win a championship and focused only on what your team does at practice each day, would you still get results?\n\nI think you would.\n\nThe goal in any sport is to finish with the best score, but it would be ridiculous to spend the whole game staring at the scoreboard. The only way to actually win is to get better each day. In the words of three-time Super Bowl winner Bill Walsh, \u201cThe score takes care of itself.\u201d The same is true for other areas of life. If you want better results, then forget about setting goals. Focus on your system instead.\n\nWhat do I mean by this? Are goals completely useless? Of course not. Goals are good for setting a direction, but systems are best for making progress. A handful of problems arise when you spend too much time thinking about your goals and not enough time designing your systems.\n\nProblem #1: Winners and losers have the same goals.\n\nGoal setting suffers from a serious case of survivorship bias. We concentrate on the people who end up winning\u2014the survivors\u2014and mistakenly assume that ambitious goals led to their success while overlooking all of the people who had the same objective but didn\u2019t succeed.\n\nEvery Olympian wants to win a gold medal. Every candidate wants to get the job. And if successful and unsuccessful people share the same goals, then the goal cannot be what differentiates the winners from the losers. It wasn\u2019t the goal of winning the Tour de France that propelled the British Cyclists to the top of the sport. Presumably, they had wanted to win the race every year before\u2014just like every other professional team. The goal had always been there. It was only when they implemented a system of continuous small improvements that they achieved a different outcome.\n\nProblem #2: Achieving a goal is only a momentary change.\n\nImagine you have a messy room and you set a goal to clean it. If you summon the energy to tidy up, then you will have a clean room\u2014for now. But if you maintain the same sloppy, pack-rat habits that led to a messy room in the first place, soon you\u2019ll be looking at a new pile of clutter and hoping for another burst of motivation. You\u2019re left chasing the same outcome because you never changed the system behind it. You treated a symptom without addressing the cause.\n\nAchieving a goal only changes your life for the moment. That\u2019s the counterintuitive thing about improvement. We think we need to change our results, but the results are not the problem. What we really need to change are the systems that cause those results. When you solve problems at the results level, you only solve them temporarily. In order to improve for good, you need to solve problems at the systems level. Fix the inputs and the outputs will fix themselves.\n\nProblem #3: Goals restrict your happiness.\n\nThe implicit assumption behind any goal is this: \u201cOnce I reach my goal, then I\u2019ll be happy.\u201d The problem with a goals-first mentality is that you\u2019re continually putting happiness off until the next milestone. I\u2019ve slipped into this trap so many times I\u2019ve lost count. For years, happiness was always something for my future self to enjoy. I promised myself that once I gained twenty pounds of muscle or after my business was featured in the New York Times, then I could finally relax.\n\nFurthermore, goals create an \u201ceither-or\u201d conflict: either you achieve your goal and are successful or you fail and you are a disappointment. You mentally box yourself into a narrow version of happiness. This is misguided. It is unlikely that your actual path through life will match the exact journey you had in mind when you set out. It makes no sense to restrict your satisfaction to one scenario when there are many paths to success.\n\nA systems-first mentality provides the antidote. When you fall in love with the process rather than the product, you don\u2019t have to wait to give yourself permission to be happy. You can be satisfied anytime your system is running. And a system can be successful in many different forms, not just the one you first envision.\n\nProblem #4: Goals are at odds with long-term progress.\n\nFinally, a goal-oriented mind-set can create a \u201cyo-yo\u201d effect. Many runners work hard for months, but as soon as they cross the finish line, they stop training. The race is no longer there to motivate them. When all of your hard work is focused on a particular goal, what is left to push you forward after you achieve it? This is why many people find themselves reverting to their old habits after accomplishing a goal.\n\nThe purpose of setting goals is to win the game. The purpose of building systems is to continue playing the game. True long-term thinking is goal-less thinking. It\u2019s not about any single accomplishment. It is about the cycle of endless refinement and continuous improvement. Ultimately, it is your commitment to the process that will determine your progress.\n\nFall In Love With Systems\n\nNone of this is to say that goals are useless. However, I've found that goals are good for planning your progress and systems are good for actually making progress.\n\nGoals can provide direction and even push you forward in the short-term, but eventually a well-designed system will always win. Having a system is what matters. Committing to the process is what makes the difference.\n\nThis article is an excerpt from Chapter 1 of my New York Times bestselling book Atomic Habits. Read more here. \n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.]]>\n    This article is an excerpt from Atomic Habits, my New York Times bestselling book.\n\nPrevailing wisdom claims that the best way to achieve what we want in life\u2014getting into better shape, building a successful business, relaxing more and worrying less, spending more time with friends and family\u2014is to set specific, actionable goals.\n\nFor many years, this was how I approached my habits too. Each one was a goal to be reached. I set goals for the grades I wanted to get in school, for the weights I wanted to lift in the gym, for the profits I wanted to earn in business. I succeeded at a few, but I failed at a lot of them. Eventually, I began to realize that my results had very little to do with the goals I set and nearly everything to do with the systems I followed.\n\n \nIf you\u2019re a coach, your goal might be to win a championship. Your system is the way you recruit players, manage your assistant coaches, and conduct practice. \nIf you\u2019re an entrepreneur, your goal might be to build a million-dollar business. Your system is how you test product ideas, hire employees, and run marketing campaigns. \nIf you\u2019re a musician, your goal might be to play a new piece. Your system is how often you practice, how you break down and tackle difficult measures, and your method for receiving feedback from your instructor. \n\n\n\nNow for the interesting question: if you completely ignored your goals and focused only on your system, would you still succeed? For example, if you were a basketball coach and you ignored your goal to win a championship and focused only on what your team does at practice each day, would you still get results?\n\nI think you would.\n\nThe goal in any sport is to finish with the best score, but it would be ridiculous to spend the whole game staring at the scoreboard. The only way to actually win is to get better each day. In the words of three-time Super Bowl winner Bill Walsh, \u201cThe score takes care of itself.\u201d The same is true for other areas of life. If you want better results, then forget about setting goals. Focus on your system instead.\n\nWhat do I mean by this? Are goals completely useless? Of course not. Goals are good for setting a direction, but systems are best for making progress. A handful of problems arise when you spend too much time thinking about your goals and not enough time designing your systems.\n\nProblem #1: Winners and losers have the same goals.\n\nGoal setting suffers from a serious case of survivorship bias. We concentrate on the people who end up winning\u2014the survivors\u2014and mistakenly assume that ambitious goals led to their success while overlooking all of the people who had the same objective but didn\u2019t succeed.\n\nEvery Olympian wants to win a gold medal. Every candidate wants to get the job. And if successful and unsuccessful people share the same goals, then the goal cannot be what differentiates the winners from the losers. It wasn\u2019t the goal of winning the Tour de France that propelled the British Cyclists to the top of the sport. Presumably, they had wanted to win the race every year before\u2014just like every other professional team. The goal had always been there. It was only when they implemented a system of continuous small improvements that they achieved a different outcome.\n\nProblem #2: Achieving a goal is only a momentary change.\n\nImagine you have a messy room and you set a goal to clean it. If you summon the energy to tidy up, then you will have a clean room\u2014for now. But if you maintain the same sloppy, pack-rat habits that led to a messy room in the first place, soon you\u2019ll be looking at a new pile of clutter and hoping for another burst of motivation. You\u2019re left chasing the same outcome because you never changed the system behind it. You treated a symptom without addressing the cause.\n\nAchieving a goal only changes your life for the moment. That\u2019s the counterintuitive thing about improvement. We think we need to change our results, but the results are not the problem. What we really need to change are the systems that cause those results. When you solve problems at the results level, you only solve them temporarily. In order to improve for good, you need to solve problems at the systems level. Fix the inputs and the outputs will fix themselves.\n\nProblem #3: Goals restrict your happiness.\n\nThe implicit assumption behind any goal is this: \u201cOnce I reach my goal, then I\u2019ll be happy.\u201d The problem with a goals-first mentality is that you\u2019re continually putting happiness off until the next milestone. I\u2019ve slipped into this trap so many times I\u2019ve lost count. For years, happiness was always something for my future self to enjoy. I promised myself that once I gained twenty pounds of muscle or after my business was featured in the New York Times, then I could finally relax.\n\nFurthermore, goals create an \u201ceither-or\u201d conflict: either you achieve your goal and are successful or you fail and you are a disappointment. You mentally box yourself into a narrow version of happiness. This is misguided. It is unlikely that your actual path through life will match the exact journey you had in mind when you set out. It makes no sense to restrict your satisfaction to one scenario when there are many paths to success.\n\nA systems-first mentality provides the antidote. When you fall in love with the process rather than the product, you don\u2019t have to wait to give yourself permission to be happy. You can be satisfied anytime your system is running. And a system can be successful in many different forms, not just the one you first envision.\n\nProblem #4: Goals are at odds with long-term progress.\n\nFinally, a goal-oriented mind-set can create a \u201cyo-yo\u201d effect. Many runners work hard for months, but as soon as they cross the finish line, they stop training. The race is no longer there to motivate them. When all of your hard work is focused on a particular goal, what is left to push you forward after you achieve it? This is why many people find themselves reverting to their old habits after accomplishing a goal.\n\nThe purpose of setting goals is to win the game. The purpose of building systems is to continue playing the game. True long-term thinking is goal-less thinking. It\u2019s not about any single accomplishment. It is about the cycle of endless refinement and continuous improvement. Ultimately, it is your commitment to the process that will determine your progress.\n\nFall In Love With Systems\n\nNone of this is to say that goals are useless. However, I've found that goals are good for planning your progress and systems are good for actually making progress.\n\nGoals can provide direction and even push you forward in the short-term, but eventually a well-designed system will always win. Having a system is what matters. Committing to the process is what makes the difference.\n\nThis article is an excerpt from Chapter 1 of my New York Times bestselling book Atomic Habits. Read more here. \n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.]]>\n  \n  \n    Why Facts Don\u2019t Change Our Minds\n    https://jamesclear.com/why-facts-dont-change-minds\n    readwise:01jm4krrym79t07jv0kh81g6fc\n    Sat, 15 Feb 2025 10:51:47 +0000\n    James Clear\n    The economist J.K. Galbraith once wrote, \u201cFaced with a choice between changing one\u2019s mind and proving there is no need to do so, almost everyone gets busy with the proof.\u201d\n\nLeo Tolstoy was even bolder: \u201cThe most difficult subjects can be explained to the most slow-witted man if he has not formed any idea of them already; but the simplest thing cannot be made clear to the most intelligent man if he is firmly persuaded that he knows already, without a shadow of doubt, what is laid before him.\u201d\n\nWhat\u2019s going on here? Why don\u2019t facts change our minds? And why would someone continue to believe a false or inaccurate idea anyway? How do such behaviors serve us?\n\nThe Logic of False Beliefs\n\nHumans need a reasonably accurate view of the world in order to survive. If your model of reality is wildly different from the actual world, then you struggle to take effective actions each day.\n\nHowever, truth and accuracy are not the only things that matter to the human mind. Humans also seem to have a deep desire to belong.\n\nIn Atomic Habits, I wrote, \u201cHumans are herd animals. We want to fit in, to bond with others, and to earn the respect and approval of our peers. Such inclinations are essential to our survival. For most of our evolutionary history, our ancestors lived in tribes. Becoming separated from the tribe\u2014or worse, being cast out\u2014was a death sentence.\u201d\n\nUnderstanding the truth of a situation is important, but so is remaining part of a tribe. While these two desires often work well together, they occasionally come into conflict.\n\nIn many circumstances, social connection is actually more helpful to your daily life than understanding the truth of a particular fact or idea. The Harvard psychologist Steven Pinker put it this way, \u201cPeople are embraced or condemned according to their beliefs, so one function of the mind may be to hold beliefs that bring the belief-holder the greatest number of allies, protectors, or disciples, rather than beliefs that are most likely to be true.\u201d\n\nWe don\u2019t always believe things because they are correct. Sometimes we believe things because they make us look good to the people we care about.\n\nI thought Kevin Simler put it well when he wrote, \u201cIf a brain anticipates that it will be rewarded for adopting a particular belief, it\u2019s perfectly happy to do so, and doesn\u2019t much care where the reward comes from \u2014 whether it\u2019s pragmatic (better outcomes resulting from better decisions), social (better treatment from one\u2019s peers), or some mix of the two.\u201d\n\nFalse beliefs can be useful in a social sense even if they are not useful in a factual sense. For lack of a better phrase, we might call this approach \u201cfactually false, but socially accurate.\u201d  When we have to choose between the two, people often select friends and family over facts.\n\nThis insight not only explains why we might hold our tongue at a dinner party or look the other way when our parents say something offensive, but also reveals a better way to change the minds of others.\n\nFacts Don\u2019t Change Our Minds. Friendship Does.\n\nConvincing someone to change their mind is really the process of convincing them to change their tribe. If they abandon their beliefs, they run the risk of losing social ties. You can\u2019t expect someone to change their mind if you take away their community too. You have to give them somewhere to go. Nobody wants their worldview torn apart if loneliness is the outcome.\n\nThe way to change people\u2019s minds is to become friends with them, to integrate them into your tribe, to bring them into your circle. Now, they can change their beliefs without the risk of being abandoned socially.\n\nThe British philosopher Alain de Botton suggests that we simply share meals with those who disagree with us:\n\n\u201cSitting down at a table with a group of strangers has the incomparable and odd benefit of making it a little more difficult to hate them with impunity. Prejudice and ethnic strife feed off abstraction. However, the proximity required by a meal \u2013 something about handing dishes around, unfurling napkins at the same moment, even asking a stranger to pass the salt \u2013 disrupts our ability to cling to the belief that the outsiders who wear unusual clothes and speak in distinctive accents deserve to be sent home or assaulted. For all the large-scale political solutions which have been proposed to salve ethnic conflict, there are few more effective ways to promote tolerance between suspicious neighbours than to force them to eat supper together.\u201d\n\nPerhaps it is not difference, but distance that breeds tribalism and hostility. As proximity increases, so does understanding. I am reminded of Abraham Lincoln\u2019s quote, \u201cI don\u2019t like that man. I must get to know him better.\u201d\n\nFacts don\u2019t change our minds. Friendship does.\n\nThe Spectrum of Beliefs\n\nYears ago, Ben Casnocha mentioned an idea to me that I haven\u2019t been able to shake: The people who are most likely to change our minds are the ones we agree with on 98 percent of topics.\n\nIf someone you know, like, and trust believes a radical idea, you are more likely to give it merit, weight, or consideration. You already agree with them in most areas of life. Maybe you should change your mind on this one too. But if someone wildly different than you proposes the same radical idea, well, it\u2019s easy to dismiss them as a crackpot.\n\nOne way to visualize this distinction is by mapping beliefs on a spectrum. If you divide this spectrum into 10 units and you find yourself at Position 7, then there is little sense in trying to convince someone at Position 1. The gap is too wide. When you\u2019re at Position 7, your time is better spent connecting with people who are at Positions 6 and 8, gradually pulling them in your direction.\n\nThe most heated arguments often occur between people on opposite ends of the spectrum, but the most frequent learning occurs from people who are nearby. The closer you are to someone, the more likely it becomes that the one or two beliefs you don\u2019t share will bleed over into your own mind and shape your thinking. The further away an idea is from your current position, the more likely you are to reject it outright.\n\nWhen it comes to changing people\u2019s minds, it is very difficult to jump from one side to another. You can\u2019t jump down the spectrum. You have to slide down it.\n\nAny idea that is sufficiently different from your current worldview will feel threatening. And the best place to ponder a threatening idea is in a non-threatening environment. As a result, books are often a better vehicle for transforming beliefs than conversations or debates.\n\nIn conversation, people have to carefully consider their status and appearance. They want to save face and avoid looking stupid. When confronted with an uncomfortable set of facts, the tendency is often to double down on their current position rather than publicly admit to being wrong.\n\nBooks resolve this tension. With a book, the conversation takes place inside someone\u2019s head and without the risk of being judged by others. It\u2019s easier to be open-minded when you aren\u2019t feeling defensive.\n\nArguments are like a full frontal attack on a person\u2019s identity. Reading a book is like slipping the seed of an idea into a person\u2019s brain and letting it grow on their own terms. There\u2019s enough wrestling going on in someone\u2019s head when they are overcoming a pre-existing belief. They don\u2019t need to wrestle with you too.\n\nWhy False Ideas Persist\n\nThere is another reason bad ideas continue to live on, which is that people continue to talk about them.\n\nSilence is death for any idea. An idea that is never spoken or written down dies with the person who conceived it. Ideas can only be remembered when they are repeated. They can only be believed when they are repeated.\n\nI have already pointed out that people repeat ideas to signal they are part of the same social group. But here\u2019s a crucial point most people miss:\n\nPeople also repeat bad ideas when they complain about them. Before you can criticize an idea, you have to reference that idea. You end up repeating the ideas you\u2019re hoping people will forget\u2014but, of course, people can\u2019t forget them because you keep talking about them. The more you repeat a bad idea, the more likely people are to believe it.\n\nLet\u2019s call this phenomenon Clear\u2019s Law of Recurrence: The number of people who believe an idea is directly proportional to the number of times it has been repeated during the last year\u2014even if the idea is false.\n\nEach time you attack a bad idea, you are feeding the very monster you are trying to destroy. As one Twitter employee wrote, \u201cEvery time you retweet or quote tweet someone you\u2019re angry with, it helps them. It disseminates their BS. Hell for the ideas you deplore is silence. Have the discipline to give it to them.\u201d\n\nYour time is better spent championing good ideas than tearing down bad ones. Don\u2019t waste time explaining why bad ideas are bad. You are simply fanning the flame of ignorance and stupidity.\n\nThe best thing that can happen to a bad idea is that it is forgotten. The best thing that can happen to a good idea is that it is shared. It makes me think of Tyler Cowen\u2019s quote, \u201cSpend as little time as possible talking about how other people are wrong.\u201d\n\nFeed the good ideas and let bad ideas die of starvation.\n\nThe Intellectual Soldier\n\nI know what you might be thinking. \u201cJames, are you serious right now? I\u2019m just supposed to let these idiots get away with this?\u201d\n\nLet me be clear. I\u2019m not saying it\u2019s never useful to point out an error or criticize a bad idea. But you have to ask yourself, \u201cWhat is the goal?\u201d\n\nWhy do you want to criticize bad ideas in the first place? Presumably, you want to criticize bad ideas because you think the world would be better off if fewer people believed them. In other words, you think the world would improve if people changed their minds on a few important topics.\n\nIf the goal is to actually change minds, then I don\u2019t believe criticizing the other side is the best approach.\n\nMost people argue to win, not to learn. As Julia Galef so aptly puts it: people often act like soldiers rather than scouts. Soldiers are on the intellectual attack, looking to defeat the people who differ from them. Victory is the operative emotion. Scouts, meanwhile, are like intellectual explorers, slowly trying to map the terrain with others. Curiosity is the driving force.\n\nIf you want people to adopt your beliefs, you need to act more like a scout and less like a soldier. At the center of this approach is a question Tiago Forte poses beautifully, \u201cAre you willing to not win in order to keep the conversation going?\u201d\n\nBe Kind First, Be Right Later\n\nThe brilliant Japanese writer Haruki Murakami once wrote, \u201cAlways remember that to argue, and win, is to break down the reality of the person you are arguing against. It is painful to lose your reality, so be kind, even if you are right.\u201d\n\nWhen we are in the moment, we can easily forget that the goal is to connect with the other side, collaborate with them, befriend them, and integrate them into our tribe. We are so caught up in winning that we forget about connecting. It\u2019s easy to spend your energy labeling people rather than working with them.\n\nThe word \u201ckind\u201d originated from the word \u201ckin.\u201d When you are kind to someone it means you are treating them like family. This, I think, is a good method for actually changing someone\u2019s mind. Develop a friendship. Share a meal. Gift a book.\n\nBe kind first, be right later.\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.\n\nJames Clear writes about habits, decision making, and continuous improvement. He is the author of the #1 New York Times bestseller, Atomic Habits. The book has sold over 9 million copies worldwide and has been translated into more than 50 languages.]]>\n    The economist J.K. Galbraith once wrote, \u201cFaced with a choice between changing one\u2019s mind and proving there is no need to do so, almost everyone gets busy with the proof.\u201d\n\nLeo Tolstoy was even bolder: \u201cThe most difficult subjects can be explained to the most slow-witted man if he has not formed any idea of them already; but the simplest thing cannot be made clear to the most intelligent man if he is firmly persuaded that he knows already, without a shadow of doubt, what is laid before him.\u201d\n\nWhat\u2019s going on here? Why don\u2019t facts change our minds? And why would someone continue to believe a false or inaccurate idea anyway? How do such behaviors serve us?\n\nThe Logic of False Beliefs\n\nHumans need a reasonably accurate view of the world in order to survive. If your model of reality is wildly different from the actual world, then you struggle to take effective actions each day.\n\nHowever, truth and accuracy are not the only things that matter to the human mind. Humans also seem to have a deep desire to belong.\n\nIn Atomic Habits, I wrote, \u201cHumans are herd animals. We want to fit in, to bond with others, and to earn the respect and approval of our peers. Such inclinations are essential to our survival. For most of our evolutionary history, our ancestors lived in tribes. Becoming separated from the tribe\u2014or worse, being cast out\u2014was a death sentence.\u201d\n\nUnderstanding the truth of a situation is important, but so is remaining part of a tribe. While these two desires often work well together, they occasionally come into conflict.\n\nIn many circumstances, social connection is actually more helpful to your daily life than understanding the truth of a particular fact or idea. The Harvard psychologist Steven Pinker put it this way, \u201cPeople are embraced or condemned according to their beliefs, so one function of the mind may be to hold beliefs that bring the belief-holder the greatest number of allies, protectors, or disciples, rather than beliefs that are most likely to be true.\u201d\n\nWe don\u2019t always believe things because they are correct. Sometimes we believe things because they make us look good to the people we care about.\n\nI thought Kevin Simler put it well when he wrote, \u201cIf a brain anticipates that it will be rewarded for adopting a particular belief, it\u2019s perfectly happy to do so, and doesn\u2019t much care where the reward comes from \u2014 whether it\u2019s pragmatic (better outcomes resulting from better decisions), social (better treatment from one\u2019s peers), or some mix of the two.\u201d\n\nFalse beliefs can be useful in a social sense even if they are not useful in a factual sense. For lack of a better phrase, we might call this approach \u201cfactually false, but socially accurate.\u201d  When we have to choose between the two, people often select friends and family over facts.\n\nThis insight not only explains why we might hold our tongue at a dinner party or look the other way when our parents say something offensive, but also reveals a better way to change the minds of others.\n\nFacts Don\u2019t Change Our Minds. Friendship Does.\n\nConvincing someone to change their mind is really the process of convincing them to change their tribe. If they abandon their beliefs, they run the risk of losing social ties. You can\u2019t expect someone to change their mind if you take away their community too. You have to give them somewhere to go. Nobody wants their worldview torn apart if loneliness is the outcome.\n\nThe way to change people\u2019s minds is to become friends with them, to integrate them into your tribe, to bring them into your circle. Now, they can change their beliefs without the risk of being abandoned socially.\n\nThe British philosopher Alain de Botton suggests that we simply share meals with those who disagree with us:\n\n\u201cSitting down at a table with a group of strangers has the incomparable and odd benefit of making it a little more difficult to hate them with impunity. Prejudice and ethnic strife feed off abstraction. However, the proximity required by a meal \u2013 something about handing dishes around, unfurling napkins at the same moment, even asking a stranger to pass the salt \u2013 disrupts our ability to cling to the belief that the outsiders who wear unusual clothes and speak in distinctive accents deserve to be sent home or assaulted. For all the large-scale political solutions which have been proposed to salve ethnic conflict, there are few more effective ways to promote tolerance between suspicious neighbours than to force them to eat supper together.\u201d\n\nPerhaps it is not difference, but distance that breeds tribalism and hostility. As proximity increases, so does understanding. I am reminded of Abraham Lincoln\u2019s quote, \u201cI don\u2019t like that man. I must get to know him better.\u201d\n\nFacts don\u2019t change our minds. Friendship does.\n\nThe Spectrum of Beliefs\n\nYears ago, Ben Casnocha mentioned an idea to me that I haven\u2019t been able to shake: The people who are most likely to change our minds are the ones we agree with on 98 percent of topics.\n\nIf someone you know, like, and trust believes a radical idea, you are more likely to give it merit, weight, or consideration. You already agree with them in most areas of life. Maybe you should change your mind on this one too. But if someone wildly different than you proposes the same radical idea, well, it\u2019s easy to dismiss them as a crackpot.\n\nOne way to visualize this distinction is by mapping beliefs on a spectrum. If you divide this spectrum into 10 units and you find yourself at Position 7, then there is little sense in trying to convince someone at Position 1. The gap is too wide. When you\u2019re at Position 7, your time is better spent connecting with people who are at Positions 6 and 8, gradually pulling them in your direction.\n\nThe most heated arguments often occur between people on opposite ends of the spectrum, but the most frequent learning occurs from people who are nearby. The closer you are to someone, the more likely it becomes that the one or two beliefs you don\u2019t share will bleed over into your own mind and shape your thinking. The further away an idea is from your current position, the more likely you are to reject it outright.\n\nWhen it comes to changing people\u2019s minds, it is very difficult to jump from one side to another. You can\u2019t jump down the spectrum. You have to slide down it.\n\nAny idea that is sufficiently different from your current worldview will feel threatening. And the best place to ponder a threatening idea is in a non-threatening environment. As a result, books are often a better vehicle for transforming beliefs than conversations or debates.\n\nIn conversation, people have to carefully consider their status and appearance. They want to save face and avoid looking stupid. When confronted with an uncomfortable set of facts, the tendency is often to double down on their current position rather than publicly admit to being wrong.\n\nBooks resolve this tension. With a book, the conversation takes place inside someone\u2019s head and without the risk of being judged by others. It\u2019s easier to be open-minded when you aren\u2019t feeling defensive.\n\nArguments are like a full frontal attack on a person\u2019s identity. Reading a book is like slipping the seed of an idea into a person\u2019s brain and letting it grow on their own terms. There\u2019s enough wrestling going on in someone\u2019s head when they are overcoming a pre-existing belief. They don\u2019t need to wrestle with you too.\n\nWhy False Ideas Persist\n\nThere is another reason bad ideas continue to live on, which is that people continue to talk about them.\n\nSilence is death for any idea. An idea that is never spoken or written down dies with the person who conceived it. Ideas can only be remembered when they are repeated. They can only be believed when they are repeated.\n\nI have already pointed out that people repeat ideas to signal they are part of the same social group. But here\u2019s a crucial point most people miss:\n\nPeople also repeat bad ideas when they complain about them. Before you can criticize an idea, you have to reference that idea. You end up repeating the ideas you\u2019re hoping people will forget\u2014but, of course, people can\u2019t forget them because you keep talking about them. The more you repeat a bad idea, the more likely people are to believe it.\n\nLet\u2019s call this phenomenon Clear\u2019s Law of Recurrence: The number of people who believe an idea is directly proportional to the number of times it has been repeated during the last year\u2014even if the idea is false.\n\nEach time you attack a bad idea, you are feeding the very monster you are trying to destroy. As one Twitter employee wrote, \u201cEvery time you retweet or quote tweet someone you\u2019re angry with, it helps them. It disseminates their BS. Hell for the ideas you deplore is silence. Have the discipline to give it to them.\u201d\n\nYour time is better spent championing good ideas than tearing down bad ones. Don\u2019t waste time explaining why bad ideas are bad. You are simply fanning the flame of ignorance and stupidity.\n\nThe best thing that can happen to a bad idea is that it is forgotten. The best thing that can happen to a good idea is that it is shared. It makes me think of Tyler Cowen\u2019s quote, \u201cSpend as little time as possible talking about how other people are wrong.\u201d\n\nFeed the good ideas and let bad ideas die of starvation.\n\nThe Intellectual Soldier\n\nI know what you might be thinking. \u201cJames, are you serious right now? I\u2019m just supposed to let these idiots get away with this?\u201d\n\nLet me be clear. I\u2019m not saying it\u2019s never useful to point out an error or criticize a bad idea. But you have to ask yourself, \u201cWhat is the goal?\u201d\n\nWhy do you want to criticize bad ideas in the first place? Presumably, you want to criticize bad ideas because you think the world would be better off if fewer people believed them. In other words, you think the world would improve if people changed their minds on a few important topics.\n\nIf the goal is to actually change minds, then I don\u2019t believe criticizing the other side is the best approach.\n\nMost people argue to win, not to learn. As Julia Galef so aptly puts it: people often act like soldiers rather than scouts. Soldiers are on the intellectual attack, looking to defeat the people who differ from them. Victory is the operative emotion. Scouts, meanwhile, are like intellectual explorers, slowly trying to map the terrain with others. Curiosity is the driving force.\n\nIf you want people to adopt your beliefs, you need to act more like a scout and less like a soldier. At the center of this approach is a question Tiago Forte poses beautifully, \u201cAre you willing to not win in order to keep the conversation going?\u201d\n\nBe Kind First, Be Right Later\n\nThe brilliant Japanese writer Haruki Murakami once wrote, \u201cAlways remember that to argue, and win, is to break down the reality of the person you are arguing against. It is painful to lose your reality, so be kind, even if you are right.\u201d\n\nWhen we are in the moment, we can easily forget that the goal is to connect with the other side, collaborate with them, befriend them, and integrate them into our tribe. We are so caught up in winning that we forget about connecting. It\u2019s easy to spend your energy labeling people rather than working with them.\n\nThe word \u201ckind\u201d originated from the word \u201ckin.\u201d When you are kind to someone it means you are treating them like family. This, I think, is a good method for actually changing someone\u2019s mind. Develop a friendship. Share a meal. Gift a book.\n\nBe kind first, be right later.\n\nThanks for reading. You can get more actionable ideas in my popular email newsletter. Each week, I share 3 short ideas from me, 2 quotes from others, and 1 question to think about. Over 2,000,000 people subscribe. Enter your email now and join us.\n\nJames Clear writes about habits, decision making, and continuous improvement. He is the author of the #1 New York Times bestseller, Atomic Habits. The book has sold over 9 million copies worldwide and has been translated into more than 50 languages.]]>\n  \n  \n    Creativity: How to Unlock Your Hidden Creative Genius\n    https://jamesclear.com/creativity\n    readwise:01jm4krh8bndstxwsx9de9r2x9\n    Sat, 15 Feb 2025 10:51:39 +0000\n    James Clear\n    This page pulls together my most essential information about creativity. I\u2019ll share how creativity works, how to find your hidden creative genius, and how to create meaningful work by learning how to make creative thinking a habit. I\u2019ve tried to present the basics of everything you need to know to start mastering creativity, even if you don\u2019t have much time.\n\nAt the end of this page, you\u2019ll find a complete list of all the articles I have written on creativity.\n\nWhat is Creativity?\n\nLet\u2019s define creativity.\n\nThe creative process is the act of making new connections between old ideas or recognizing relationships between concepts. Creative thinking is not about generating something new from a blank slate, but rather about taking what is already present and combining those bits and pieces in a way that has not been done previously.\n\nWhile being creative isn\u2019t easy, nearly all great ideas follow a similar creative process. In 1940, an advertising executive named James Webb Young published a short guide titled, A Technique for Producing Ideas.\n\nYoung believed the process of creative connection always occurred in five steps.\n\nThe Creative Process\n\n\nGather new material. At first, you learn. During this stage you focus on 1) learning specific material directly related to your task and 2) learning general material by becoming fascinated with a wide range of concepts.\nThoroughly work over the materials in your mind. During this stage, you examine what you have learned by looking at the facts from different angles and experimenting with fitting various ideas together.\nStep away from the problem. Next, you put the problem completely out of your mind and go do something else that excites you and energizes you.\nLet your idea return to you. At some point, but only after you have stopped thinking about it, your idea will come back to you with a flash of insight and renewed energy.\nShape and develop your idea based on feedback. For any idea to succeed, you must release it out into the world, submit it to criticism, and adapt it as needed.\n\nIs There Such a Thing as \u2018Naturally Creative\u2019?\n\nWhile we often think of creativity as an event or as a natural skill that some people have and some don\u2019t, researchactually suggests that both creativity and non-creativity are learned.\n\nAccording to psychology professor Barbara Kerr, \u201capproximately 22 percent of the variance [in creativity] is due to the influence of genes.\u201d This discovery was made by studying the differences in creative thinking between sets of twins.All of this to say, claiming that \u201cI\u2019m just not the creative type\u201d is a pretty weak excuse for avoiding creative thinking. Certainly, some people are primed to be more creative than others. However, nearly every person is born with some level of creative skill and the majority of our creative thinking abilities are trainable.\n\nThree Lessons on Creativity from Famous Creators\n\n\nThe 15-Minute Routine Anthony Trollope Used to Write 40+ Books: Beginning with his first novel in 1847, Anthony Trollope wrote at an incredible pace. Over the next 38 years, he published 47 novels, 18 works of non-fiction, 12 short stories, 2 plays, and an assortment of articles and letters. Let\u2019s break down why Trollope\u2019s simple strategy allowed the author to be so productive and how we can use it in our own lives.\nThe Weird Strategy Dr. Seuss Used to Create His Greatest Work: In 1960, the founder of Random House publishing firm challenged Dr. Seuss to write an entertaining children\u2019s book using only 50 different words. The result was a little book called Green Eggs and Ham. Here\u2019s what we can learn from Dr. Seuss\u2026\nHow Creative Geniuses Come Up With Great Ideas: Best-selling author Markus Zusak estimated that he rewrote the first part of his popular book \u201cThe Book Thief\u201d 150 to 200 times. His work ethic and dedication tell us something crucial about how creative geniuses come up with great ideas.\n\nYou can also check out creativity articles about Albert Einstein, Martha Graham, George R.R. Martin, and Maya Angelou.\n\nHow to Be Creative\n\nStep 1: Give yourself permission to create junk\n\nIn any creative endeavor, you have to give yourself permission to create junk. There is no way around it. Sometimes you have to write 4 terrible pages just to discover that you wrote one good sentence in the second paragraph of the third page.\n\nCreating something useful and compelling is like being a gold miner. You have to sift through pounds of dirt and rock and silt just to find a speck of gold in the middle of it all. Bits and pieces of genius will find their way to you, if you give yourself permission to let the muse flow.\n\nStep 2: Create on a schedule\n\nNo single act will uncover more creative genius than forcing yourself to create consistently. Practicing your craft over and over is the only way to become decent at it. The person who sits around theorizing about what a best-selling book looks like will never write it. Meanwhile, the writer who shows up every day and puts their butt in the chair and their hands on the keyboard \u2014 they are learning how to do the work.\n\nIf you want to do your best creative work, then don\u2019t leave it up to choice. Don\u2019t wake up in the morning and think, \u201cI hope I feel inspired to create something today.\u201d You need to take the decision-making out of it. Set a schedule for your work. Genius arrives when you show up enough times to get the average ideas out of the way.\n\nStep 3: Finish something\n\nFinish something. Anything. Stop researching, planning, and preparing to do the work and just do the work. It doesn\u2019t matter how good or how bad it is. You don\u2019t need to set the world on fire with your first try. You just need to prove to yourself that you have what it takes to produce something.\n\nThere are no artists, athletes, entrepreneurs, or scientists who became great by half-finishing their work. Stop debating what you should make and just make something.\n\nStep 4: Stop judging your own work\n\nEveryone struggles to create great art. Even great artists.\n\nAnyone who creates something on a consistent basis will begin to judge their own work. I write new articles every Monday and Thursday. After sticking to that publishing schedule for three months, I began to judge everything I created. I was convinced that I had gone through every decent idea I had available. My most popular article came 8 months later.\n\nIt is natural to judge your work. It is natural to feel disappointed that your creation isn\u2019t as wonderful as you hoped it would be, or that you\u2019re not getting any better at your craft. But the key is to not let your discontent prevent you from continuing to do the work.\n\nYou have to practice enough self-compassion to not let self-judgement take over. Sure, you care about your work, but don\u2019t get so serious about it that you can\u2019t laugh off your mistakes and continue to produce the thing you love. Don\u2019t let judgment prevent delivery.\n\nRead more: It\u2019s Not Your Job to Tell Yourself \u201cNo\u201d\n\nStep 5: Hold yourself accountable\n\nShare your work publicly. It will hold you accountable to creating your best work. It will provide feedback for doing better work. And when you see others connect with what you create, it will inspire you and make you care more.\n\nSometimes sharing your work means you have to deal with haters and critics. But more often than not, the only thing that happens is that you rally the people who believe the same things you believe, are excited about the same things you are excited about, or who support the work that you believe in \u2014 who wouldn\u2019t want that?\n\nThe world needs people who put creative work out into the world. What seems simple to you is often brilliant to someone else. But you\u2019ll never know that unless you choose to share.\n\nHow to Find Your Creative Genius\n\nFinding your creative genius is easy: do the work, finish something, get feedback, find ways to improve, show up again tomorrow. Repeat for ten years. Or twenty. Or thirty.\n\nInspiration only reveals itself after perspiration.\n\nBest Creativity Books\n\nWant more great books on creativity and business? Browse my full list of the best business books.\n\nAll Creativity Articles\n\nThis is a complete list of articles I have written on creativity. Enjoy!]]>\n    This page pulls together my most essential information about creativity. I\u2019ll share how creativity works, how to find your hidden creative genius, and how to create meaningful work by learning how to make creative thinking a habit. I\u2019ve tried to present the basics of everything you need to know to start mastering creativity, even if you don\u2019t have much time.\n\nAt the end of this page, you\u2019ll find a complete list of all the articles I have written on creativity.\n\nWhat is Creativity?\n\nLet\u2019s define creativity.\n\nThe creative process is the act of making new connections between old ideas or recognizing relationships between concepts. Creative thinking is not about generating something new from a blank slate, but rather about taking what is already present and combining those bits and pieces in a way that has not been done previously.\n\nWhile being creative isn\u2019t easy, nearly all great ideas follow a similar creative process. In 1940, an advertising executive named James Webb Young published a short guide titled, A Technique for Producing Ideas.\n\nYoung believed the process of creative connection always occurred in five steps.\n\nThe Creative Process\n\n\nGather new material. At first, you learn. During this stage you focus on 1) learning specific material directly related to your task and 2) learning general material by becoming fascinated with a wide range of concepts.\nThoroughly work over the materials in your mind. During this stage, you examine what you have learned by looking at the facts from different angles and experimenting with fitting various ideas together.\nStep away from the problem. Next, you put the problem completely out of your mind and go do something else that excites you and energizes you.\nLet your idea return to you. At some point, but only after you have stopped thinking about it, your idea will come back to you with a flash of insight and renewed energy.\nShape and develop your idea based on feedback. For any idea to succeed, you must release it out into the world, submit it to criticism, and adapt it as needed.\n\nIs There Such a Thing as \u2018Naturally Creative\u2019?\n\nWhile we often think of creativity as an event or as a natural skill that some people have and some don\u2019t, researchactually suggests that both creativity and non-creativity are learned.\n\nAccording to psychology professor Barbara Kerr, \u201capproximately 22 percent of the variance [in creativity] is due to the influence of genes.\u201d This discovery was made by studying the differences in creative thinking between sets of twins.All of this to say, claiming that \u201cI\u2019m just not the creative type\u201d is a pretty weak excuse for avoiding creative thinking. Certainly, some people are primed to be more creative than others. However, nearly every person is born with some level of creative skill and the majority of our creative thinking abilities are trainable.\n\nThree Lessons on Creativity from Famous Creators\n\n\nThe 15-Minute Routine Anthony Trollope Used to Write 40+ Books: Beginning with his first novel in 1847, Anthony Trollope wrote at an incredible pace. Over the next 38 years, he published 47 novels, 18 works of non-fiction, 12 short stories, 2 plays, and an assortment of articles and letters. Let\u2019s break down why Trollope\u2019s simple strategy allowed the author to be so productive and how we can use it in our own lives.\nThe Weird Strategy Dr. Seuss Used to Create His Greatest Work: In 1960, the founder of Random House publishing firm challenged Dr. Seuss to write an entertaining children\u2019s book using only 50 different words. The result was a little book called Green Eggs and Ham. Here\u2019s what we can learn from Dr. Seuss\u2026\nHow Creative Geniuses Come Up With Great Ideas: Best-selling author Markus Zusak estimated that he rewrote the first part of his popular book \u201cThe Book Thief\u201d 150 to 200 times. His work ethic and dedication tell us something crucial about how creative geniuses come up with great ideas.\n\nYou can also check out creativity articles about Albert Einstein, Martha Graham, George R.R. Martin, and Maya Angelou.\n\nHow to Be Creative\n\nStep 1: Give yourself permission to create junk\n\nIn any creative endeavor, you have to give yourself permission to create junk. There is no way around it. Sometimes you have to write 4 terrible pages just to discover that you wrote one good sentence in the second paragraph of the third page.\n\nCreating something useful and compelling is like being a gold miner. You have to sift through pounds of dirt and rock and silt just to find a speck of gold in the middle of it all. Bits and pieces of genius will find their way to you, if you give yourself permission to let the muse flow.\n\nStep 2: Create on a schedule\n\nNo single act will uncover more creative genius than forcing yourself to create consistently. Practicing your craft over and over is the only way to become decent at it. The person who sits around theorizing about what a best-selling book looks like will never write it. Meanwhile, the writer who shows up every day and puts their butt in the chair and their hands on the keyboard \u2014 they are learning how to do the work.\n\nIf you want to do your best creative work, then don\u2019t leave it up to choice. Don\u2019t wake up in the morning and think, \u201cI hope I feel inspired to create something today.\u201d You need to take the decision-making out of it. Set a schedule for your work. Genius arrives when you show up enough times to get the average ideas out of the way.\n\nStep 3: Finish something\n\nFinish something. Anything. Stop researching, planning, and preparing to do the work and just do the work. It doesn\u2019t matter how good or how bad it is. You don\u2019t need to set the world on fire with your first try. You just need to prove to yourself that you have what it takes to produce something.\n\nThere are no artists, athletes, entrepreneurs, or scientists who became great by half-finishing their work. Stop debating what you should make and just make something.\n\nStep 4: Stop judging your own work\n\nEveryone struggles to create great art. Even great artists.\n\nAnyone who creates something on a consistent basis will begin to judge their own work. I write new articles every Monday and Thursday. After sticking to that publishing schedule for three months, I began to judge everything I created. I was convinced that I had gone through every decent idea I had available. My most popular article came 8 months later.\n\nIt is natural to judge your work. It is natural to feel disappointed that your creation isn\u2019t as wonderful as you hoped it would be, or that you\u2019re not getting any better at your craft. But the key is to not let your discontent prevent you from continuing to do the work.\n\nYou have to practice enough self-compassion to not let self-judgement take over. Sure, you care about your work, but don\u2019t get so serious about it that you can\u2019t laugh off your mistakes and continue to produce the thing you love. Don\u2019t let judgment prevent delivery.\n\nRead more: It\u2019s Not Your Job to Tell Yourself \u201cNo\u201d\n\nStep 5: Hold yourself accountable\n\nShare your work publicly. It will hold you accountable to creating your best work. It will provide feedback for doing better work. And when you see others connect with what you create, it will inspire you and make you care more.\n\nSometimes sharing your work means you have to deal with haters and critics. But more often than not, the only thing that happens is that you rally the people who believe the same things you believe, are excited about the same things you are excited about, or who support the work that you believe in \u2014 who wouldn\u2019t want that?\n\nThe world needs people who put creative work out into the world. What seems simple to you is often brilliant to someone else. But you\u2019ll never know that unless you choose to share.\n\nHow to Find Your Creative Genius\n\nFinding your creative genius is easy: do the work, finish something, get feedback, find ways to improve, show up again tomorrow. Repeat for ten years. Or twenty. Or thirty.\n\nInspiration only reveals itself after perspiration.\n\nBest Creativity Books\n\nWant more great books on creativity and business? Browse my full list of the best business books.\n\nAll Creativity Articles\n\nThis is a complete list of articles I have written on creativity. Enjoy!]]>\n  \n  \n    The Productivity Guide: Time Management Strategies That Work\n    https://jamesclear.com/productivity\n    readwise:01jm4krd68jc9ds4ecd4b1gtb4\n    Sat, 15 Feb 2025 10:51:35 +0000\n    James Clear\n    What is Productivity?\n\nLet's define productivity. Productivity is a measure of efficiency of a person completing a task. We often assume that productivity means getting more things done each day. Wrong. Productivity is getting important things done consistently. And no matter what you are working on, there are only a few things that are truly important.\n\nBeing productive is about maintaining a steady, average speed on a few things, not maximum speed on everything.\n\nMy Top Productivity Strategies\n\n \nEliminate Time Wasting Activities by Using the Eisenhower Box: This simple decision matrix will help you take action, organize tasks, and get more done. The great thing about this matrix is that it can be used for broad productivity plans (\u201cHow should I spend my time each week?\u201d) and for smaller, daily plans (\u201cWhat should I do today?\u201d). \nWarren Buffett\u2019s \u201c2 List\u201d Strategy: How to Maximize Your Focus and Master Your Priorities: This method comes from the famous investor Warren Buffett and uses a simple 3-step productivity strategy to help you determine your priorities and actions. You may find this method useful for making decisions and getting yourself to commit to doing one thing right away. \nThe Ivy Lee Method: The Daily Routine Experts Recommend for Peak Productivity: This productivity strategy is straightforward: Do the most important thing first each day. The Ivy Lee Method is a dead simple way to implement this strategy. \nThe 15-Minute Routine Anthony Trollope Used to Write 40+ Books: There is one common problem with the approach of ranking your priorities and doing the most important thing first, though. After ranking your priorities for the day, if the number one task is a really big project then it can leave you feeling frustrated because it takes a long time to finish. Writer Anthony Trollope, however, developed a solution to this common problem. \n\nMore Productivity Ideas\n\nMost productivity strategies focus on short-term efficiency: how to manage your to-do list effectively, how to get more done each morning, how to shorten your weekly meetings, and so on. These are all reasonable ideas.\n\nWe often fail to realize, however, that there are certain strategic choices we need to make if we want to maximize our productivity for the long-term. In these articles below, I break down some ideas about long-term productivity.\n\nLooking for more articles about productivity? I have a full list at the bottom of this page.\n\nSimple Ways to Be More Productive Every Day\n\nStep 1: Manage your energy, not your time.\n\nIf you take a moment to think about it, you\u2019ll probably realize that you are better at doing certain tasks at certain times. What type of energy do you have in the morning? Afternoon? Evening? Determine what tasks each energy level and time of day are best suited for.\n\nStep 2: Prepare the night before.\n\nIf you only do one thing each day then spend a few minutes each night organizing your to\u2013do list for tomorrow. When I do it right, I\u2019ll outline the article I\u2019m going to write the next day and develop a short list of the most important items for me to accomplish. It takes 10 minutes that night and saves 3 hours the next day.\n\nStep 3: Don\u2019t open email until noon.\n\nSounds simple. Nobody does it. It took me awhile to get over the urge to open my inbox, but eventually I realized that everything can wait a few hours. Nobody is going to email you about a true emergency (a death in the family, etc.), so leave your email alone for the first few hours of each day. Use the morning to do what\u2019s important rather than responding to what is \u201curgent.\u201d\n\nStep 4: Turn your phone off and leave it in another room.\n\nOr on your colleague's desk. Or at the very least, put it somewhere that is out of sight. This eliminates the urge to check text messages, Facebook, Twitter, and so on. This simple strategy eliminates the likelihood of slipping into half\u2013work where you waste time dividing your attention among meaningless tasks.\n\nStep 5: Work in a cool place.\n\nHave you ever noticed how you feel groggy and sluggish in a hot room? Turning the temperature down or moving to a cooler place is an easy way to focus your mind and body. (Hat tip to Michael Hyatt for this one.)\n\nStep 6: Sit up or stand up.\n\nWhen you sit hunched over, your chest is in a collapsed position and your diaphragm is pressing against the bottom of your lungs, which hinders your ability to breathe easily and deeply. Sit up straight or stand up and you\u2019ll find that you can breathe easier and more fully. As a result, your brain will get more oxygen and you\u2019ll be able to concentrate better.\n\nStep 7: Develop a \u201cpre\u2013game routine\u201d to start your day.\n\nMy morning routine starts by pouring a cold glass of water. Some people kick off their day with ten minutes of meditation. Similarly, you should have a sequence that starts your morning ritual. This tiny routine signals to your brain that it\u2019s time to get into work mode or exercise mode or whatever mode you need to be in to accomplish your task. Additionally, a pre\u2013game routine helps you overcome a lack of motivation and get things done even when you don\u2019t feel like it.\n\nBest Productivity Books\n\nWant more great books on productivity? Browse my full list of the best productivity books.\n\nAll Productivity Articles\n\nThis is a complete list of articles I have written on productivity. Enjoy!\n\n Best Articles on Related Topics\n\nOr, browse my best articles.]]>\n    What is Productivity?\n\nLet's define productivity. Productivity is a measure of efficiency of a person completing a task. We often assume that productivity means getting more things done each day. Wrong. Productivity is getting important things done consistently. And no matter what you are working on, there are only a few things that are truly important.\n\nBeing productive is about maintaining a steady, average speed on a few things, not maximum speed on everything.\n\nMy Top Productivity Strategies\n\n \nEliminate Time Wasting Activities by Using the Eisenhower Box: This simple decision matrix will help you take action, organize tasks, and get more done. The great thing about this matrix is that it can be used for broad productivity plans (\u201cHow should I spend my time each week?\u201d) and for smaller, daily plans (\u201cWhat should I do today?\u201d). \nWarren Buffett\u2019s \u201c2 List\u201d Strategy: How to Maximize Your Focus and Master Your Priorities: This method comes from the famous investor Warren Buffett and uses a simple 3-step productivity strategy to help you determine your priorities and actions. You may find this method useful for making decisions and getting yourself to commit to doing one thing right away. \nThe Ivy Lee Method: The Daily Routine Experts Recommend for Peak Productivity: This productivity strategy is straightforward: Do the most important thing first each day. The Ivy Lee Method is a dead simple way to implement this strategy. \nThe 15-Minute Routine Anthony Trollope Used to Write 40+ Books: There is one common problem with the approach of ranking your priorities and doing the most important thing first, though. After ranking your priorities for the day, if the number one task is a really big project then it can leave you feeling frustrated because it takes a long time to finish. Writer Anthony Trollope, however, developed a solution to this common problem. \n\nMore Productivity Ideas\n\nMost productivity strategies focus on short-term efficiency: how to manage your to-do list effectively, how to get more done each morning, how to shorten your weekly meetings, and so on. These are all reasonable ideas.\n\nWe often fail to realize, however, that there are certain strategic choices we need to make if we want to maximize our productivity for the long-term. In these articles below, I break down some ideas about long-term productivity.\n\nLooking for more articles about productivity? I have a full list at the bottom of this page.\n\nSimple Ways to Be More Productive Every Day\n\nStep 1: Manage your energy, not your time.\n\nIf you take a moment to think about it, you\u2019ll probably realize that you are better at doing certain tasks at certain times. What type of energy do you have in the morning? Afternoon? Evening? Determine what tasks each energy level and time of day are best suited for.\n\nStep 2: Prepare the night before.\n\nIf you only do one thing each day then spend a few minutes each night organizing your to\u2013do list for tomorrow. When I do it right, I\u2019ll outline the article I\u2019m going to write the next day and develop a short list of the most important items for me to accomplish. It takes 10 minutes that night and saves 3 hours the next day.\n\nStep 3: Don\u2019t open email until noon.\n\nSounds simple. Nobody does it. It took me awhile to get over the urge to open my inbox, but eventually I realized that everything can wait a few hours. Nobody is going to email you about a true emergency (a death in the family, etc.), so leave your email alone for the first few hours of each day. Use the morning to do what\u2019s important rather than responding to what is \u201curgent.\u201d\n\nStep 4: Turn your phone off and leave it in another room.\n\nOr on your colleague's desk. Or at the very least, put it somewhere that is out of sight. This eliminates the urge to check text messages, Facebook, Twitter, and so on. This simple strategy eliminates the likelihood of slipping into half\u2013work where you waste time dividing your attention among meaningless tasks.\n\nStep 5: Work in a cool place.\n\nHave you ever noticed how you feel groggy and sluggish in a hot room? Turning the temperature down or moving to a cooler place is an easy way to focus your mind and body. (Hat tip to Michael Hyatt for this one.)\n\nStep 6: Sit up or stand up.\n\nWhen you sit hunched over, your chest is in a collapsed position and your diaphragm is pressing against the bottom of your lungs, which hinders your ability to breathe easily and deeply. Sit up straight or stand up and you\u2019ll find that you can breathe easier and more fully. As a result, your brain will get more oxygen and you\u2019ll be able to concentrate better.\n\nStep 7: Develop a \u201cpre\u2013game routine\u201d to start your day.\n\nMy morning routine starts by pouring a cold glass of water. Some people kick off their day with ten minutes of meditation. Similarly, you should have a sequence that starts your morning ritual. This tiny routine signals to your brain that it\u2019s time to get into work mode or exercise mode or whatever mode you need to be in to accomplish your task. Additionally, a pre\u2013game routine helps you overcome a lack of motivation and get things done even when you don\u2019t feel like it.\n\nBest Productivity Books\n\nWant more great books on productivity? Browse my full list of the best productivity books.\n\nAll Productivity Articles\n\nThis is a complete list of articles I have written on productivity. Enjoy!\n\n Best Articles on Related Topics\n\nOr, browse my best articles.]]>\n  \n  \n    Motivation: The Scientific Guide on How to Get and Stay Motivated\n    https://jamesclear.com/motivation\n    readwise:01jm4kr8ww4va7n4mcsskvgwc5\n    Sat, 15 Feb 2025 10:51:31 +0000\n    James Clear\n    Motivation is a powerful, yet tricky beast. Sometimes it is really easy to get motivated, and you find yourself wrapped up in a whirlwind of excitement. Other times, it is nearly impossible to figure out how to motivate yourself and you\u2019re trapped in a death spiral of procrastination. This page contains the best ideas and most useful research on how to get and stay motivated.\n\nThis isn\u2019t going to be some rah-rah, pumped-up motivational speech. (That\u2019s not my style.) Instead, we\u2019re going to break down the science behind how to get motivated in the first place and how to stay motivated for the long-run. Whether you\u2019re trying to figure out how to motivate yourself or how to motivate a team, this page should cover everything you need to know.\n\nYou can click the links below to jump to a particular section or simply scroll down to read everything. At the end of this page, you\u2019ll find a complete list of all the articles I have written on motivation.\n\nI. Motivation: What It Is and How It Works\n\nII. How to Get Motivated and Take Action\n\nIII. How to Stay Motivated for the Long-Run\n\nMotivation: What It Is and How It Works\n\nScientists define motivation as your general willingness to do something. It is the set of psychological forces that compel you to take action. That\u2019s nice and all, but I think we can come up with a more useful definition of motivation.\n\nWhat is Motivation?\n\nSo what is motivation, exactly? The author Steven Pressfield has a great line in his book, The War of Art, which I think gets at the core of motivation. To paraphrase Pressfield, \u201cAt some point, the pain of not doing it becomes greater than the pain of doing it.\u201d\n\nIn other words, at some point, it is easier to change than to stay the same. It is easier to take action and feel insecure at the gym than to sit still and experience self-loathing on the couch. It is easier to feel awkward while making the sales call than to feel disappointed about your dwindling bank account.\n\nThis, I think, is the essence of motivation. Every choice has a price, but when we are motivated, it is easier to bear the inconvenience of action than the pain of remaining the same. Somehow we cross a mental threshold\u2014usually after weeks of procrastination and in the face of an impending deadline\u2014and it becomes more painful to not do the work than to actually do it.\n\nNow for the important question: What can we do to make it more likely that we cross this mental threshold and feel motivated on a consistent basis?\n\nCommon Misconceptions About Motivation\n\nOne of the most surprising things about motivation is that it often comes after starting a new behavior, not before. We have this common misconception that motivation arrives as a result of passively consuming a motivational video or reading an inspirational book. However, active inspiration can be a far more powerful motivator.\n\nMotivation is often the result of action, not the cause of it. Getting started, even in very small ways, is a form of active inspiration that naturally produces momentum.\n\nI like to refer to this effect as the Physics of Productivity because this is basically Newton\u2019s First Law applied to habit formation: Objects in motion tend to stay in motion. Once a task has begun, it is easier to continue moving it forward.\n\n\n\nYou don\u2019t need much motivation once you\u2019ve started a behavior. Nearly all of the friction in a task is at the beginning. After you start, progress occurs more naturally. In other words, it is often easier to finish a task than it was to start it in the first place.\n\nThus, one of the keys to getting motivated is to make it easy to start.\n\nHow to Get Motivated and Take Action\n\nMany people struggle to find the motivation they need to achieve the goals they want because they are wasting too much time and energy on other parts of the process. If you want to make it easy to find motivation and get started, then it helps to automate the early stages of your behavior.\n\nSchedule Your Motivation\n\nDuring a conversation about writing, my friend Sarah Peck looked at me and said, \u201cA lot of people never get around to writing because they are always wondering when they are going to write next.\u201d You could say the same thing about working out, starting a business, creating art, and building most habits.\n\n \nIf your workout doesn\u2019t have a time when it usually occurs, then each day you\u2019ll wake up thinking, \u201cI hope I feel motivated to exercise today.\u201d \nIf your business doesn\u2019t have a system for marketing, then you\u2019ll show up at work crossing your fingers that you\u2019ll find a way to get the word out (in addition to everything else you have to do). \nIf you don\u2019t have a scheduled time when you write every week, then you\u2019ll find yourself saying things like, \u201cI just need to find the willpower to do it.\u201d \n\nAn article in The Guardian summarized the situation by saying, \u201cIf you waste resources trying to decide when or where to work, you\u2019ll impede your capacity to do the work.\u201d\n\nSetting a schedule for yourself seems simple, but it puts your decision-making on autopilot by giving your goals a time and a place to live. It makes it more likely that you will follow through regardless of your motivation levels. And there are plenty of research studies on willpower and motivation to back up that statement.\n\nStop waiting for motivation or inspiration to strike you and set a schedule for your habits. This is the difference between professionals and amateurs. Professionals set a schedule and stick to it. Amateurs wait until they feel inspired or motivated.\n\nHow to Get Motivated (Even When You Don\u2019t Feel Like It)\n\nHow do some of the most prolific artists in the world motivate themselves? They don\u2019t merely set schedules, they build rituals.\n\nTwyla Tharp is widely regarded as one of the greatest dancers and choreographers of the modern era. In her best-selling book, The Creative Habit (audiobook), Tharp discusses the role rituals, or pre-game routines, have played in her success:\n\nI begin each day of my life with a ritual; I wake up at 5:30 A.M., put on my workout clothes, my leg warmers, my sweatshirts, and my hat. I walk outside my Manhattan home, hail a taxi, and tell the driver to take me to the Pumping Iron gym at 91st street and First Avenue, where I workout for two hours. The ritual is not the stretching and weight training I put my body through each morning at the gym; the ritual is the cab. The moment I tell the driver where to go I have completed the ritual.\n\nIt\u2019s a simple act, but doing it the same way each morning habitualizes it \u2014 makes it repeatable, easy to do. It reduces the chance that I would skip it or do it differently. It is one more item in my arsenal of routines, and one less thing to think about.\n\nMany other famous creatives have rituals too. In his popular book Daily Rituals: How Artists Work, author Mason Currey notes that many of the world\u2019s great artists follow a consistent schedule.\n\n \nMaya Angelou rented a local hotel room and went there to write. She arrived at 6:30 AM, wrote until 2 PM, and then went home to do some editing. She never slept at the hotel. \nPulitzer Prize winner Michael Chabon writes five nights per week from 10 PM to 3 AM. \nHaruki Murakami wakes up at 4 AM, writes for five hours, and then goes for a run. \n\nThe work of top creatives isn\u2019t dependent upon motivation or inspiration, but rather it follows a consistent pattern and routine. Here are some examples of how you can apply ritual and routine to get motivated:\n\n \nExercise more consistently: Use the same warm up routine in the gym. \nBecome more creative: Follow a creative ritual before you start writing or painting or singing. \nStart each day stress-free: Create a five-minute morning meditation ritual. \nSleep better: Follow a \u201cpower down\u201d routine before bed. \n\nThe power of a ritual, or what I like to call a pre-game routine, is that it provides a mindless way to initiate your behavior. It makes starting your habits easier and that means following through on a consistent basis is easier.\n\nThe key to any good ritual is that it removes the need to make a decision: What should I do first? When should I do this? How should I do this? Most people never get moving because they can\u2019t decide how to get started. You want starting a behavior to be easy and automatic so you have the strength to finish it when it becomes difficult and challenging.\n\nHow to Make Motivation a Habit\n\nThere are three simple steps you can take to build better rituals and make motivation a habit.\n\nStep 1: A good pre\u2013game routine starts by being so easy that you can\u2019t say no to it. You shouldn\u2019t need motivation to start your pre\u2013game routine. For example, my writing routine starts by getting a glass of water. My weightlifting routine starts by putting on my lifting shoes. These tasks are so easy, I can\u2019t say no to them.\n\nThe most important part of any task is starting. If you can\u2019t get motivated in the beginning, then you\u2019ll find that motivation often comes after starting. That\u2019s why your pre\u2013game routine needs to be incredibly easy to start.\n\nFor more about the importance of getting started, read this.\n\nStep 2: Your routine should get you moving toward the end goal.\n\nA lack of mental motivation is often linked to a lack of physical movement. Just imagine your physical state when you\u2019re feeling depressed, bored, or unmotivated. You\u2019re not moving very much. Maybe you\u2019re slumped over like a blob, slowly melting into the couch.\n\nThe opposite is also true. If you\u2019re physically moving and engaged, then it\u2019s far more likely that you\u2019ll feel mentally engaged and energized. For example, it\u2019s almost impossible to not feel vibrant, awake, and energized when you\u2019re dancing.\n\nWhile your routine should be as easy as possible to start, it should gradually transition into more and more physical movement. Your mind and your motivation will follow your physical movement. It is worth noting that physical movement doesn\u2019t have to mean exercise. For example, if your goal is to write, then your routine should bring you closer to the physical act of writing.\n\nStep 3: You need to follow the same pattern every single time.\n\nThe primary purpose of your pre\u2013game routine is to create a series of events that you always perform before doing a specific task. Your pre\u2013game routine tells your mind, \u201cThis is what happens before I do ___.\u201d\n\nEventually, this routine becomes so tied to your performance that by simply doing the routine, you are pulled into a mental state that is primed to perform. You don\u2019t need to know how to find motivation, you just need to start your routine.\n\nYour pre\u2013game routine is the trigger that kickstarts your habit, even if you\u2019re not motivated to do it.\n\nThis is important because when you don\u2019t feel motivated, it\u2019s often too much work to figure out what you should do next. When faced with another decision, you will often decide to just quit. However, the pre\u2013game routine solves that problem because you know exactly what to do next. There\u2019s no debating or decision making. Lack of motivation doesn\u2019t matter. You just follow the pattern.\n\nHow to Stay Motivated for the Long-Run\n\nWe have covered some strategies for making it easier to get motivated and start a task. What about maintaining motivation over the long-run? How can you stay motivated for good?\n\nHow to Stay Motivated by Using the Goldilocks Rule\n\nImagine you are playing tennis. If you try to play a serious match against a four-year-old, you will quickly become bored. The match is too easy. On the opposite end of the spectrum, if you try to play a serious match against a professional tennis player like Roger Federer or Serena Williams, you will find yourself demotivated for a different reason. The match is too difficult.\n\nCompare these experiences to playing tennis against someone who is your equal. As the game progresses, you win a few points and you lose a few points. You have a chance of winning the match, but only if you really try. Your focus narrows, distractions fade away, and you find yourself fully invested in the task at hand. The challenge you are facing is \u201cjust manageable.\u201d Victory is not guaranteed, but it is possible. Tasks like these, science has found, are the most likely to keep us motivated in the long term.\n\nHuman beings love challenges, but only if they are within the optimal zone of difficulty. Tasks that are significantly below your current abilities are boring. Tasks that are significantly beyond your current abilities are discouraging. But tasks that are right on the border of success and failure are incredibly motivating to our human brains. We want nothing more than to master a skill just beyond our current horizon.\n\nWe can call this phenomenon The Goldilocks Rule. The Goldilocks Rule states that humans experience peak motivation when working on tasks that are right on the edge of their current abilities. Not too hard. Not too easy. Just right.\n\nWorking on tasks that adhere to the Goldilocks Rule is one of the keys to maintaining long-term motivation. If you find yourself feeling unmotivated to work on a task, it is often because it has drifted into an area of boredom or been shoved into an area of great difficulty. You need to find a way to pull your tasks back to the border of your abilities where you feel challenged, but capable.\n\nHow to Reach Peak Motivation\n\nThis wonderful blend of happiness and peak performance is sometimes referred to as flow. Flow is what athletes and performers experience when they are \u201cin the zone.\u201d Flow is the mental state you experience when you are so focused on the task at hand that the rest of the world fades away.\n\nIn many ways, we could describe flow as your state of peak motivation. You would be hard-pressed to find a state where you are more driven to continue the task you are working on.\n\nOne factor that researchers have found is linked to flow states is whether or not you are following The Goldilocks Rule we mentioned earlier. If you are working on challenges of optimal difficulty, then you will not only be motivated but also experience a boost in happiness. As psychologist Gilbert Brim put it, \u201cOne of the important sources of human happiness is working on tasks at a suitable level of difficulty, neither too hard nor too easy.\u201d\n\nIn order to reach this state of peak performance, however, you not only need to work on challenges at the right degree of difficulty, but also measure your immediate progress. As psychologist Jonathan Haidt explains, one of the keys to reaching a flow state is that \u201cyou get immediate feedback about how you are doing at each step.\u201d\n\nThus, we can say that measurement is a key factor in motivation. To put it more precisely, facing an optimal challenge and receiving immediate feedback about the progress you are making toward that challenge are two of the most critical components of peak motivation.\n\nFor more on the importance of measurement and feedback, check out this article: What Are You Measuring in Your Life?\n\nWhat to Do When Motivation Fades\n\nInevitably, your motivation to perform a task will dip at some point. What happens when motivation fades? I don\u2019t claim to have all the answers, but here\u2019s what I try to remind myself of when I feel like giving up.\n\nYour Mind is a Suggestion Engine\n\nConsider every thought you have as a suggestion, not an order. Right now, as I\u2019m writing this, my mind is suggesting that I feel tired. It is suggesting that I give up. It is suggesting that I take an easier path.\n\nIf I pause for a moment, however, I can discover new suggestions. My mind is also suggesting that I will feel very good about accomplishing this work once it is done. It is suggesting that I will respect the identity I am building when I stick to the schedule. It is suggesting that I have the ability to finish this task, even when I don\u2019t feel like.\n\nRemember, none of these suggestions are orders. They are merely options. I have the power to choose which option I follow.\n\nDiscomfort Is Temporary\n\nRelative to the time in your normal day or week, nearly any habit you perform is over quickly. Your workout will be finished in an hour or two. Your report will be typed to completion by tomorrow morning.\n\nLife is easier now than it has ever been. 300 years ago, if you didn\u2019t kill your own food and build your own house, you would die. Today, we whine about forgetting our iPhone charger.\n\nMaintain perspective. Your life is good and your discomfort is temporary. Step into this moment of discomfort and let it strengthen you.\n\nYou Will Never Regret Good Work Once It is Done\n\nTheodore Roosevelt famously said, \u201cFar and away the best prize that life has to offer is the chance to work hard at work worth doing.\u201d So often it seems that we want to work easily at work worth doing. We want our work to be helpful and respected, but we do not want to struggle through our work. We want our stomachs to be flat and our arms to be strong, but we do not want to grind through another workout. We want the final result, but not the failed attempts that precede it. We want the gold, but not the grind.\n\nAnyone can want a gold medal. Few people want to train like an Olympian.\n\nAnd yet, despite our resistance to it, I have never found myself feeling worse after the hard work was done. There have been days when it was damn hard to start, but it was always worth finishing. Sometimes, the simple act of showing up and having the courage to do the work, even in an average manner, is a victory worth celebrating.\n\nThis Is Life\n\nLife is a constant balance between giving into the ease of distraction or overcoming the pain of discipline. It is not an exaggeration to say that our lives and our identities are defined in this delicate balance. What is life, if not the sum of a hundred thousand daily battles and tiny decisions to either gut it out or give it up?\n\nThis moment when you don\u2019t feel like doing the work? This is not a moment to be thrown away. This is not a dress rehearsal. This moment is your life as much as any other moment. Spend it in a way that will make you proud.\n\nWhere to Go From Here\n\nI hope you found this short guide on motivation useful. If you\u2019re looking for more ideas on how to get motivated and stay that way, then check out my full list of motivation articles below.\n\nAll Motivation Articles\n\nThis is a complete list of articles I have written on motivation. Enjoy!\n\nBest Articles on Topics Related to Motivation\n\nLooking for even more? Check out these articles on topics that are closely related to motivation.\n\nOr, browse my best articles.\n\n30 Days to Better Habits: A simple step-by-step guide for forming habits that stick\n\n \nTake the guesswork out of habit-building. 11 email lessons walk you through the first 30 days of a habit step-by-step, so you know exactly what to do. \nGet the tools and strategies you need to take action. The course includes a 20-page PDF workbook (including templates and cheatsheets), plus new examples and applications that you can\u2019t find in Atomic Habits.  \nLearn a framework that works for any habit. You can use this course to build any good habit \u2013 from getting fit, to saving for an early retirement, to daily meditation. ]]>\n    Motivation is a powerful, yet tricky beast. Sometimes it is really easy to get motivated, and you find yourself wrapped up in a whirlwind of excitement. Other times, it is nearly impossible to figure out how to motivate yourself and you\u2019re trapped in a death spiral of procrastination. This page contains the best ideas and most useful research on how to get and stay motivated.\n\nThis isn\u2019t going to be some rah-rah, pumped-up motivational speech. (That\u2019s not my style.) Instead, we\u2019re going to break down the science behind how to get motivated in the first place and how to stay motivated for the long-run. Whether you\u2019re trying to figure out how to motivate yourself or how to motivate a team, this page should cover everything you need to know.\n\nYou can click the links below to jump to a particular section or simply scroll down to read everything. At the end of this page, you\u2019ll find a complete list of all the articles I have written on motivation.\n\nI. Motivation: What It Is and How It Works\n\nII. How to Get Motivated and Take Action\n\nIII. How to Stay Motivated for the Long-Run\n\nMotivation: What It Is and How It Works\n\nScientists define motivation as your general willingness to do something. It is the set of psychological forces that compel you to take action. That\u2019s nice and all, but I think we can come up with a more useful definition of motivation.\n\nWhat is Motivation?\n\nSo what is motivation, exactly? The author Steven Pressfield has a great line in his book, The War of Art, which I think gets at the core of motivation. To paraphrase Pressfield, \u201cAt some point, the pain of not doing it becomes greater than the pain of doing it.\u201d\n\nIn other words, at some point, it is easier to change than to stay the same. It is easier to take action and feel insecure at the gym than to sit still and experience self-loathing on the couch. It is easier to feel awkward while making the sales call than to feel disappointed about your dwindling bank account.\n\nThis, I think, is the essence of motivation. Every choice has a price, but when we are motivated, it is easier to bear the inconvenience of action than the pain of remaining the same. Somehow we cross a mental threshold\u2014usually after weeks of procrastination and in the face of an impending deadline\u2014and it becomes more painful to not do the work than to actually do it.\n\nNow for the important question: What can we do to make it more likely that we cross this mental threshold and feel motivated on a consistent basis?\n\nCommon Misconceptions About Motivation\n\nOne of the most surprising things about motivation is that it often comes after starting a new behavior, not before. We have this common misconception that motivation arrives as a result of passively consuming a motivational video or reading an inspirational book. However, active inspiration can be a far more powerful motivator.\n\nMotivation is often the result of action, not the cause of it. Getting started, even in very small ways, is a form of active inspiration that naturally produces momentum.\n\nI like to refer to this effect as the Physics of Productivity because this is basically Newton\u2019s First Law applied to habit formation: Objects in motion tend to stay in motion. Once a task has begun, it is easier to continue moving it forward.\n\n\n\nYou don\u2019t need much motivation once you\u2019ve started a behavior. Nearly all of the friction in a task is at the beginning. After you start, progress occurs more naturally. In other words, it is often easier to finish a task than it was to start it in the first place.\n\nThus, one of the keys to getting motivated is to make it easy to start.\n\nHow to Get Motivated and Take Action\n\nMany people struggle to find the motivation they need to achieve the goals they want because they are wasting too much time and energy on other parts of the process. If you want to make it easy to find motivation and get started, then it helps to automate the early stages of your behavior.\n\nSchedule Your Motivation\n\nDuring a conversation about writing, my friend Sarah Peck looked at me and said, \u201cA lot of people never get around to writing because they are always wondering when they are going to write next.\u201d You could say the same thing about working out, starting a business, creating art, and building most habits.\n\n \nIf your workout doesn\u2019t have a time when it usually occurs, then each day you\u2019ll wake up thinking, \u201cI hope I feel motivated to exercise today.\u201d \nIf your business doesn\u2019t have a system for marketing, then you\u2019ll show up at work crossing your fingers that you\u2019ll find a way to get the word out (in addition to everything else you have to do). \nIf you don\u2019t have a scheduled time when you write every week, then you\u2019ll find yourself saying things like, \u201cI just need to find the willpower to do it.\u201d \n\nAn article in The Guardian summarized the situation by saying, \u201cIf you waste resources trying to decide when or where to work, you\u2019ll impede your capacity to do the work.\u201d\n\nSetting a schedule for yourself seems simple, but it puts your decision-making on autopilot by giving your goals a time and a place to live. It makes it more likely that you will follow through regardless of your motivation levels. And there are plenty of research studies on willpower and motivation to back up that statement.\n\nStop waiting for motivation or inspiration to strike you and set a schedule for your habits. This is the difference between professionals and amateurs. Professionals set a schedule and stick to it. Amateurs wait until they feel inspired or motivated.\n\nHow to Get Motivated (Even When You Don\u2019t Feel Like It)\n\nHow do some of the most prolific artists in the world motivate themselves? They don\u2019t merely set schedules, they build rituals.\n\nTwyla Tharp is widely regarded as one of the greatest dancers and choreographers of the modern era. In her best-selling book, The Creative Habit (audiobook), Tharp discusses the role rituals, or pre-game routines, have played in her success:\n\nI begin each day of my life with a ritual; I wake up at 5:30 A.M., put on my workout clothes, my leg warmers, my sweatshirts, and my hat. I walk outside my Manhattan home, hail a taxi, and tell the driver to take me to the Pumping Iron gym at 91st street and First Avenue, where I workout for two hours. The ritual is not the stretching and weight training I put my body through each morning at the gym; the ritual is the cab. The moment I tell the driver where to go I have completed the ritual.\n\nIt\u2019s a simple act, but doing it the same way each morning habitualizes it \u2014 makes it repeatable, easy to do. It reduces the chance that I would skip it or do it differently. It is one more item in my arsenal of routines, and one less thing to think about.\n\nMany other famous creatives have rituals too. In his popular book Daily Rituals: How Artists Work, author Mason Currey notes that many of the world\u2019s great artists follow a consistent schedule.\n\n \nMaya Angelou rented a local hotel room and went there to write. She arrived at 6:30 AM, wrote until 2 PM, and then went home to do some editing. She never slept at the hotel. \nPulitzer Prize winner Michael Chabon writes five nights per week from 10 PM to 3 AM. \nHaruki Murakami wakes up at 4 AM, writes for five hours, and then goes for a run. \n\nThe work of top creatives isn\u2019t dependent upon motivation or inspiration, but rather it follows a consistent pattern and routine. Here are some examples of how you can apply ritual and routine to get motivated:\n\n \nExercise more consistently: Use the same warm up routine in the gym. \nBecome more creative: Follow a creative ritual before you start writing or painting or singing. \nStart each day stress-free: Create a five-minute morning meditation ritual. \nSleep better: Follow a \u201cpower down\u201d routine before bed. \n\nThe power of a ritual, or what I like to call a pre-game routine, is that it provides a mindless way to initiate your behavior. It makes starting your habits easier and that means following through on a consistent basis is easier.\n\nThe key to any good ritual is that it removes the need to make a decision: What should I do first? When should I do this? How should I do this? Most people never get moving because they can\u2019t decide how to get started. You want starting a behavior to be easy and automatic so you have the strength to finish it when it becomes difficult and challenging.\n\nHow to Make Motivation a Habit\n\nThere are three simple steps you can take to build better rituals and make motivation a habit.\n\nStep 1: A good pre\u2013game routine starts by being so easy that you can\u2019t say no to it. You shouldn\u2019t need motivation to start your pre\u2013game routine. For example, my writing routine starts by getting a glass of water. My weightlifting routine starts by putting on my lifting shoes. These tasks are so easy, I can\u2019t say no to them.\n\nThe most important part of any task is starting. If you can\u2019t get motivated in the beginning, then you\u2019ll find that motivation often comes after starting. That\u2019s why your pre\u2013game routine needs to be incredibly easy to start.\n\nFor more about the importance of getting started, read this.\n\nStep 2: Your routine should get you moving toward the end goal.\n\nA lack of mental motivation is often linked to a lack of physical movement. Just imagine your physical state when you\u2019re feeling depressed, bored, or unmotivated. You\u2019re not moving very much. Maybe you\u2019re slumped over like a blob, slowly melting into the couch.\n\nThe opposite is also true. If you\u2019re physically moving and engaged, then it\u2019s far more likely that you\u2019ll feel mentally engaged and energized. For example, it\u2019s almost impossible to not feel vibrant, awake, and energized when you\u2019re dancing.\n\nWhile your routine should be as easy as possible to start, it should gradually transition into more and more physical movement. Your mind and your motivation will follow your physical movement. It is worth noting that physical movement doesn\u2019t have to mean exercise. For example, if your goal is to write, then your routine should bring you closer to the physical act of writing.\n\nStep 3: You need to follow the same pattern every single time.\n\nThe primary purpose of your pre\u2013game routine is to create a series of events that you always perform before doing a specific task. Your pre\u2013game routine tells your mind, \u201cThis is what happens before I do ___.\u201d\n\nEventually, this routine becomes so tied to your performance that by simply doing the routine, you are pulled into a mental state that is primed to perform. You don\u2019t need to know how to find motivation, you just need to start your routine.\n\nYour pre\u2013game routine is the trigger that kickstarts your habit, even if you\u2019re not motivated to do it.\n\nThis is important because when you don\u2019t feel motivated, it\u2019s often too much work to figure out what you should do next. When faced with another decision, you will often decide to just quit. However, the pre\u2013game routine solves that problem because you know exactly what to do next. There\u2019s no debating or decision making. Lack of motivation doesn\u2019t matter. You just follow the pattern.\n\nHow to Stay Motivated for the Long-Run\n\nWe have covered some strategies for making it easier to get motivated and start a task. What about maintaining motivation over the long-run? How can you stay motivated for good?\n\nHow to Stay Motivated by Using the Goldilocks Rule\n\nImagine you are playing tennis. If you try to play a serious match against a four-year-old, you will quickly become bored. The match is too easy. On the opposite end of the spectrum, if you try to play a serious match against a professional tennis player like Roger Federer or Serena Williams, you will find yourself demotivated for a different reason. The match is too difficult.\n\nCompare these experiences to playing tennis against someone who is your equal. As the game progresses, you win a few points and you lose a few points. You have a chance of winning the match, but only if you really try. Your focus narrows, distractions fade away, and you find yourself fully invested in the task at hand. The challenge you are facing is \u201cjust manageable.\u201d Victory is not guaranteed, but it is possible. Tasks like these, science has found, are the most likely to keep us motivated in the long term.\n\nHuman beings love challenges, but only if they are within the optimal zone of difficulty. Tasks that are significantly below your current abilities are boring. Tasks that are significantly beyond your current abilities are discouraging. But tasks that are right on the border of success and failure are incredibly motivating to our human brains. We want nothing more than to master a skill just beyond our current horizon.\n\nWe can call this phenomenon The Goldilocks Rule. The Goldilocks Rule states that humans experience peak motivation when working on tasks that are right on the edge of their current abilities. Not too hard. Not too easy. Just right.\n\nWorking on tasks that adhere to the Goldilocks Rule is one of the keys to maintaining long-term motivation. If you find yourself feeling unmotivated to work on a task, it is often because it has drifted into an area of boredom or been shoved into an area of great difficulty. You need to find a way to pull your tasks back to the border of your abilities where you feel challenged, but capable.\n\nHow to Reach Peak Motivation\n\nThis wonderful blend of happiness and peak performance is sometimes referred to as flow. Flow is what athletes and performers experience when they are \u201cin the zone.\u201d Flow is the mental state you experience when you are so focused on the task at hand that the rest of the world fades away.\n\nIn many ways, we could describe flow as your state of peak motivation. You would be hard-pressed to find a state where you are more driven to continue the task you are working on.\n\nOne factor that researchers have found is linked to flow states is whether or not you are following The Goldilocks Rule we mentioned earlier. If you are working on challenges of optimal difficulty, then you will not only be motivated but also experience a boost in happiness. As psychologist Gilbert Brim put it, \u201cOne of the important sources of human happiness is working on tasks at a suitable level of difficulty, neither too hard nor too easy.\u201d\n\nIn order to reach this state of peak performance, however, you not only need to work on challenges at the right degree of difficulty, but also measure your immediate progress. As psychologist Jonathan Haidt explains, one of the keys to reaching a flow state is that \u201cyou get immediate feedback about how you are doing at each step.\u201d\n\nThus, we can say that measurement is a key factor in motivation. To put it more precisely, facing an optimal challenge and receiving immediate feedback about the progress you are making toward that challenge are two of the most critical components of peak motivation.\n\nFor more on the importance of measurement and feedback, check out this article: What Are You Measuring in Your Life?\n\nWhat to Do When Motivation Fades\n\nInevitably, your motivation to perform a task will dip at some point. What happens when motivation fades? I don\u2019t claim to have all the answers, but here\u2019s what I try to remind myself of when I feel like giving up.\n\nYour Mind is a Suggestion Engine\n\nConsider every thought you have as a suggestion, not an order. Right now, as I\u2019m writing this, my mind is suggesting that I feel tired. It is suggesting that I give up. It is suggesting that I take an easier path.\n\nIf I pause for a moment, however, I can discover new suggestions. My mind is also suggesting that I will feel very good about accomplishing this work once it is done. It is suggesting that I will respect the identity I am building when I stick to the schedule. It is suggesting that I have the ability to finish this task, even when I don\u2019t feel like.\n\nRemember, none of these suggestions are orders. They are merely options. I have the power to choose which option I follow.\n\nDiscomfort Is Temporary\n\nRelative to the time in your normal day or week, nearly any habit you perform is over quickly. Your workout will be finished in an hour or two. Your report will be typed to completion by tomorrow morning.\n\nLife is easier now than it has ever been. 300 years ago, if you didn\u2019t kill your own food and build your own house, you would die. Today, we whine about forgetting our iPhone charger.\n\nMaintain perspective. Your life is good and your discomfort is temporary. Step into this moment of discomfort and let it strengthen you.\n\nYou Will Never Regret Good Work Once It is Done\n\nTheodore Roosevelt famously said, \u201cFar and away the best prize that life has to offer is the chance to work hard at work worth doing.\u201d So often it seems that we want to work easily at work worth doing. We want our work to be helpful and respected, but we do not want to struggle through our work. We want our stomachs to be flat and our arms to be strong, but we do not want to grind through another workout. We want the final result, but not the failed attempts that precede it. We want the gold, but not the grind.\n\nAnyone can want a gold medal. Few people want to train like an Olympian.\n\nAnd yet, despite our resistance to it, I have never found myself feeling worse after the hard work was done. There have been days when it was damn hard to start, but it was always worth finishing. Sometimes, the simple act of showing up and having the courage to do the work, even in an average manner, is a victory worth celebrating.\n\nThis Is Life\n\nLife is a constant balance between giving into the ease of distraction or overcoming the pain of discipline. It is not an exaggeration to say that our lives and our identities are defined in this delicate balance. What is life, if not the sum of a hundred thousand daily battles and tiny decisions to either gut it out or give it up?\n\nThis moment when you don\u2019t feel like doing the work? This is not a moment to be thrown away. This is not a dress rehearsal. This moment is your life as much as any other moment. Spend it in a way that will make you proud.\n\nWhere to Go From Here\n\nI hope you found this short guide on motivation useful. If you\u2019re looking for more ideas on how to get motivated and stay that way, then check out my full list of motivation articles below.\n\nAll Motivation Articles\n\nThis is a complete list of articles I have written on motivation. Enjoy!\n\nBest Articles on Topics Related to Motivation\n\nLooking for even more? Check out these articles on topics that are closely related to motivation.\n\nOr, browse my best articles.\n\n30 Days to Better Habits: A simple step-by-step guide for forming habits that stick\n\n \nTake the guesswork out of habit-building. 11 email lessons walk you through the first 30 days of a habit step-by-step, so you know exactly what to do. \nGet the tools and strategies you need to take action. The course includes a 20-page PDF workbook (including templates and cheatsheets), plus new examples and applications that you can\u2019t find in Atomic Habits.  \nLearn a framework that works for any habit. You can use this course to build any good habit \u2013 from getting fit, to saving for an early retirement, to daily meditation. ]]>\n  \n  \n    Focus: The Ultimate Guide on How to Improve Focus and Concentration\n    https://jamesclear.com/focus\n    readwise:01jm4kr307hh1ymgv35973vzcw\n    Sat, 15 Feb 2025 10:51:25 +0000\n    James Clear\n    Focus and concentration can be difficult to master. Sure, most people want to learn how to improve focus and boost concentration. But actually doing it? We live in a noisy world and constant distractions can make focus difficult.\n\nLuckily, this page contains the best ideas and top research on how to get and stay focused. We will break down the science behind sharpening your mind and paying attention to what matters. Whether you\u2019re looking to focus on your goals in life or business, this page should cover everything you need to know.\n\nYou can click the links below to jump to a particular section or simply scroll down to read everything. At the end of this page, you\u2019ll find a complete list of all the articles I have written on focus.\n\nFocus: What It Is and How it Works\n\n \nWhat is Focus? \nWhy Can\u2019t I Focus? \nThe Myth of Multitasking \n\nHow to Focus and Increase Your Attention Span\n\n \nWarren Buffett\u2019s \u201c2 List\u201d Strategy for Focused Attention \nMeasure Your Results \nFocus on the Process, Not the Event \n\nMind-Hacks for Getting Focused\n\n \nHow to Improve Concentration \nWhere to Go From Here \n\nFocus: What It Is and How it Works\n\nFirst things first. What is focus, really? Experts define focus as the act of concentrating your interest or activity on something. That\u2019s a somewhat boring definition, but there is an important insight hiding inside that definition.\n\nWhat is Focus?\n\nIn order to concentrate on one thing you must, by default, ignore many other things.\n\nHere\u2019s a better way to put it:\n\nFocus can only occur when we have said yes to one option and no to all other options. In other words, elimination is a prerequisite for focus. As Tim Ferriss says, \u201cWhat you don\u2019t do determines what you can do.\u201d\n\nOf course, focus doesn\u2019t require a permanent no, but it does require a present no. You always have the option to do something else later, but in the present moment focus requires that you only do one thing. Focus is the key to productivity because saying no to every other option unlocks your ability to accomplish the one thing that is left.\n\nNow for the important question: What can we do to focus on the things that matter and ignore the things that don\u2019t?\n\nWhy Can\u2019t I Focus?\n\nMost people don\u2019t have trouble with focusing. They have trouble with deciding.\n\nWhat I mean is that most healthy humans have a brain that is capable of focusing if we get the distractions out of the way. Have you ever had a task that you absolutely had to get done? What happened? You got it done because the deadline made the decision for you. Maybe you procrastinated beforehand, but once things became urgent and you were forced to make a decision, you took action.\n\nInstead of doing the difficult work of choosing one thing to focus on, we often convince ourselves that multitasking is a better option. This is ineffective.\n\nHere\u2019s why\u2026\n\nThe Myth of Multitasking\n\nTechnically, we are capable of doing two things at the same time. It is possible, for example, to watch TV while cooking dinner or to answer an email while talking on the phone.\n\nWhat is impossible, however, is concentrating on two tasks at once. You\u2019re either listening to the TV and the overflowing pot of pasta is background noise, or you\u2019re tending to the pot of pasta and the TV is background noise. During any single instant, you are concentrating on one or the other.\n\nMultitasking forces your brain to switch your focus back and forth very quickly from one task to another. This wouldn\u2019t be a big deal if the human brain could transition seamlessly from one job to the next, but it can\u2019t.\n\nHave you ever been in the middle of writing an email when someone interrupts you? When the conversation is over and you get back to the message, it takes you a few minutes to get your bearings, remember what you were writing, and get back on track. Something similar happens when you multitask. Multitasking forces you to pay a mental price each time you interrupt one task and jump to another. In psychology terms, this mental price is called the switching cost.\n\nSwitching cost is the disruption in performance that we experience when we switch our focus from one area to another. One study, published in the International Journal of Information Management in 2003, found that the typical person checks email once every five minutes and that, on average, it takes 64 seconds to resume the previous task after checking your email.\n\nIn other words, because of email alone, we typically waste one out of every six minutes.\n\n\nThe myth of multitasking is that it will make you more effective. In reality, remarkable focus is what makes the difference. (Image inspired by Jessica Hagy.)\n\nHow to Focus and Increase Your Attention Span\n\nLet\u2019s talk about how to overcome our tendency to multitask and focus on one thing at a time. Of the many options in front of you, how do you know what to focus on? How do you know where to direct your energy and attention? How do you determine the one thing that you should commit to doing?\n\nWarren Buffett\u2019s \u201c2 List\u201d Strategy for Focused Attention\n\nOne of my favorite methods for focusing your attention on what matters and eliminating what doesn\u2019t comes from the famous investor Warren Buffett.\n\nBuffett uses a simple 3-step productivity strategy to help his employees determine their priorities and actions. You may find this method useful for making decisions and getting yourself to commit to doing one thing right away. Here\u2019s how it works\u2026\n\nOne day, Buffett asked his personal pilot to go through the 3-step exercise.\n\nSTEP 1: Buffett started by asking the pilot, named Mike Flint, to write down his top 25 career goals. So, Flint took some time and wrote them down. (Note: You could also complete this exercise with goals for a shorter timeline. For example, write down the top 25 things you want to accomplish this week.)\n\nSTEP 2: Then, Buffett asked Flint to review his list and circle his top 5 goals. Again, Flint took some time, made his way through the list, and eventually decided on his 5 most important goals.\n\nSTEP 3: At this point, Flint had two lists. The 5 items he had circled were List A, and the 20 items he had not circled were List B.\n\nFlint confirmed that he would start working on his top 5 goals right away. And that\u2019s when Buffett asked him about the second list, \u201cAnd what about the ones you didn\u2019t circle?\u201d\n\nFlint replied, \u201cWell, the top 5 are my primary focus, but the other 20 come in a close second. They are still important so I\u2019ll work on those intermittently as I see fit. They are not as urgent, but I still plan to give them a dedicated effort.\u201d\n\nTo which Buffett replied, \u201cNo. You\u2019ve got it wrong, Mike. Everything you didn\u2019t circle just became your Avoid-At-All-Cost list. No matter what, these things get no attention from you until you\u2019ve succeeded with your top 5.\u201d\n\nI love Buffett\u2019s method because it forces you to make hard decisions and eliminate things that might be good uses of time, but aren\u2019t great uses of time. So often the tasks that derail our focus are ones that we can easily rationalize spending time on.\n\nThis is just one way to narrow your focus and eliminate distractions. I\u2019ve covered many other methods before like The Ivy Lee Method and The Eisenhower Box. That said, no matter what method you use and no matter how committed you are, at some point your concentration and focus begin to fade. How can you increase your attention span and remain focused?\n\nThere are two simple steps you can take.\n\nMeasure Your Results\n\nThe first thing you can do is to measure your progress.\n\nFocus often fades because of lack of feedback. Your brain has a natural desire to know whether or not you are making progress toward your goals, and it is impossible to know that without getting feedback. From a practical standpoint, this means that we need to measure our results.\n\nWe all have areas of life that we say are important to us, but that we aren\u2019t measuring. That\u2019s a shame because measurement maintains focus and concentration. The things we measure are the things we improve. It is only through numbers and clear tracking that we have any idea if we are getting better or worse.\n\n \nWhen I measured how many pushups I did, I got stronger. \nWhen I tracked my reading habit of 20 pages per day, I read more books. \nWhen I recorded my values, I began living with more integrity. \n\nThe tasks I measured were the ones I remained focused on.\n\nUnfortunately, we often avoid measuring because we are fearful of what the numbers will tell us about ourselves. The trick is to realize that measuring is not a judgment about who you are, it\u2019s just feedback on where you are.\n\nMeasure to discover, to find out, to understand. Measure to get to know yourself better. Measure to see if you\u2019re actually spending time on the things that are important to you. Measure because it will help you focus on the things that matter and ignore the things that don\u2019t.\n\nFocus on the Process, Not the Event\n\nThe second thing you can do to maintain long-term focus is to concentrate on processes, not events. All too often, we see success as an event that can be achieved and completed.\n\nHere are some common examples:\n\n \nMany people see health as an event: \u201cIf I just lose 20 pounds, then I\u2019ll be in shape.\u201d \nMany people see entrepreneurship as an event: \u201cIf we could get our business featured in the New York Times, then we\u2019d be set.\u201d \nMany people see art as an event: \u201cIf I could just get my work featured in a bigger gallery, then I\u2019d have the credibility I need.\u201d \n\nThose are just a few of the many ways that we categorize success as a single event. But if you look at the people who stay focused on their goals, you start to realize that it\u2019s not the events or the results that make them different. It\u2019s the commitment to the process. They fall in love with the daily practice, not the individual event.\n\nWhat\u2019s funny, of course, is that this focus on the process is what will allow you to enjoy the results anyway.\n\n \nIf you want to be a great writer, then having a best-selling book is wonderful. But the only way to reach that result is to fall in love with the process of writing. \nIf you want the world to know about your business, then it would be great to be featured in Forbes magazine. But the only way to reach that result is to fall in love with the process of marketing. \nIf you want to be in the best shape of your life, then losing 20 pounds might be necessary. But the only way to reach that result is to fall in love with the process of eating healthy and exercising consistently. \nIf you want to become significantly better at anything, you have to fall in love with the process of doing it. You have to fall in love with building the identity of someone who does the work, rather than merely dreaming about the results that you want. \n\nFocusing on outcomes and goals is our natural tendency, but focusing on processes leads to more results over the long-run.\n\nConcentration and Focus Mind-Hacks\n\nEven after you\u2019ve learned to love the process and know how to stay focused on your goals, the day-to-day implementation of those goals can still be messy. Let\u2019s talk about some additional ways to improve concentration and make sure you\u2019re giving each task your focused attention.\n\nHow to Improve Concentration\n\nHere are few additional ways to improve your focus and get started on what matters.\n\nChoose an anchor task. One of the major improvements I\u2019ve made recently is to assign one (and only one) priority to each work day. Although I plan to complete other tasks during the day, my priority task is the one non-negotiable thing that must get done. I call this my \u201canchor task\u201d because it is the mainstay that holds the rest of my day in place. The power of choosing one priority is that it naturally guides your behavior by forcing you to organize your life around that responsibility.\n\nManage your energy, not your time. If a task requires your full attention, then schedule it for a time of day when you have the energy needed to focus. For example, I have noticed that my creative energy is highest in the morning. That\u2019s when I\u2019m fresh. That\u2019s when I do my best writing. That\u2019s when I make the best strategic decisions about my business. So, what do I do? I schedule creative tasks for the morning. All other business tasks are taken care of in the afternoon. This includes doing interviews, responding to emails, phone calls and Skype chats, data analysis and number crunching. Nearly every productivity strategy obsesses over managing your time better, but time is useless if you don\u2019t have the energy you need to complete the task you are working on.\n\nNever check email before noon. Focus is about eliminating distractions. Email can be one of the biggest distractions of all. If I don\u2019t check email at the beginning of the day, then I am able to spend the morning pursuing my own agenda rather than reacting to everybody else\u2019s agenda. That\u2019s a huge win because I\u2019m not wasting mental energy thinking about all the messages in my inbox. I realize that waiting until the afternoon isn\u2019t feasible for many people, but I\u2019d like to offer a challenge. Can you wait until 10AM? What about 9AM? 8:30AM? The exact cutoff time doesn\u2019t matter. The point is to carve out time during your morning when you can focus on what is most important to you without letting the rest of the world dictate your mental state.\n\nLeave your phone in another room. I usually don\u2019t see my phone for the first few hours of the day. It is much easier to do focused work when you don\u2019t have any text messages, phone calls, or alerts interrupting your focus.\n\nWork in full screen mode. Whenever I use an application on my computer, I use full screen mode. If I\u2019m reading an article on the web, my browser takes up the whole screen. If I\u2019m writing in Evernote, I\u2019m working in full screen mode. If I\u2019m editing a picture in Photoshop, it is the only thing I can see. I have set up my desktop so that the menu bar disappears automatically. When I am working, I can\u2019t see the time, the icons of other applications, or any other distractions on the screen. It\u2019s funny how big of a difference this makes for my focus and concentration. If you can see an icon on your screen, then you will be reminded to click on it occasionally. However, if you remove the visual cue, then the urge to be distracted subsides in a few minutes.\n\nRemove all tasks that could distract from early morning focus. I love doing the most important thing first each day because the urgencies of the day have not crept in yet. I have gone a little far in this regard in that I have even pushed my first meal off until about noon each day. I have been intermittent fasting for three years now (here are some lessons learned), which means that I typically eat most of my meals between 12PM and 8PM. The result is that I get some additional time in the morning to do focused work rather than cook breakfast.\n\nRegardless of what strategy you use, just remember that anytime you find the world distracting you, all you need to do is commit to one thing. In the beginning, you don\u2019t even have to succeed. You just need to get started.\n\nWhere to Go From Here\n\nI hope you found this short guide on focus useful. If you\u2019re looking for more ideas on how to improve your focus and concentration, feel free to browse the full list of articles below.\n\nAll Focus Articles\n\nThis is a complete list of articles I have written on focus. Enjoy!]]>\n    Focus and concentration can be difficult to master. Sure, most people want to learn how to improve focus and boost concentration. But actually doing it? We live in a noisy world and constant distractions can make focus difficult.\n\nLuckily, this page contains the best ideas and top research on how to get and stay focused. We will break down the science behind sharpening your mind and paying attention to what matters. Whether you\u2019re looking to focus on your goals in life or business, this page should cover everything you need to know.\n\nYou can click the links below to jump to a particular section or simply scroll down to read everything. At the end of this page, you\u2019ll find a complete list of all the articles I have written on focus.\n\nFocus: What It Is and How it Works\n\n \nWhat is Focus? \nWhy Can\u2019t I Focus? \nThe Myth of Multitasking \n\nHow to Focus and Increase Your Attention Span\n\n \nWarren Buffett\u2019s \u201c2 List\u201d Strategy for Focused Attention \nMeasure Your Results \nFocus on the Process, Not the Event \n\nMind-Hacks for Getting Focused\n\n \nHow to Improve Concentration \nWhere to Go From Here \n\nFocus: What It Is and How it Works\n\nFirst things first. What is focus, really? Experts define focus as the act of concentrating your interest or activity on something. That\u2019s a somewhat boring definition, but there is an important insight hiding inside that definition.\n\nWhat is Focus?\n\nIn order to concentrate on one thing you must, by default, ignore many other things.\n\nHere\u2019s a better way to put it:\n\nFocus can only occur when we have said yes to one option and no to all other options. In other words, elimination is a prerequisite for focus. As Tim Ferriss says, \u201cWhat you don\u2019t do determines what you can do.\u201d\n\nOf course, focus doesn\u2019t require a permanent no, but it does require a present no. You always have the option to do something else later, but in the present moment focus requires that you only do one thing. Focus is the key to productivity because saying no to every other option unlocks your ability to accomplish the one thing that is left.\n\nNow for the important question: What can we do to focus on the things that matter and ignore the things that don\u2019t?\n\nWhy Can\u2019t I Focus?\n\nMost people don\u2019t have trouble with focusing. They have trouble with deciding.\n\nWhat I mean is that most healthy humans have a brain that is capable of focusing if we get the distractions out of the way. Have you ever had a task that you absolutely had to get done? What happened? You got it done because the deadline made the decision for you. Maybe you procrastinated beforehand, but once things became urgent and you were forced to make a decision, you took action.\n\nInstead of doing the difficult work of choosing one thing to focus on, we often convince ourselves that multitasking is a better option. This is ineffective.\n\nHere\u2019s why\u2026\n\nThe Myth of Multitasking\n\nTechnically, we are capable of doing two things at the same time. It is possible, for example, to watch TV while cooking dinner or to answer an email while talking on the phone.\n\nWhat is impossible, however, is concentrating on two tasks at once. You\u2019re either listening to the TV and the overflowing pot of pasta is background noise, or you\u2019re tending to the pot of pasta and the TV is background noise. During any single instant, you are concentrating on one or the other.\n\nMultitasking forces your brain to switch your focus back and forth very quickly from one task to another. This wouldn\u2019t be a big deal if the human brain could transition seamlessly from one job to the next, but it can\u2019t.\n\nHave you ever been in the middle of writing an email when someone interrupts you? When the conversation is over and you get back to the message, it takes you a few minutes to get your bearings, remember what you were writing, and get back on track. Something similar happens when you multitask. Multitasking forces you to pay a mental price each time you interrupt one task and jump to another. In psychology terms, this mental price is called the switching cost.\n\nSwitching cost is the disruption in performance that we experience when we switch our focus from one area to another. One study, published in the International Journal of Information Management in 2003, found that the typical person checks email once every five minutes and that, on average, it takes 64 seconds to resume the previous task after checking your email.\n\nIn other words, because of email alone, we typically waste one out of every six minutes.\n\n\nThe myth of multitasking is that it will make you more effective. In reality, remarkable focus is what makes the difference. (Image inspired by Jessica Hagy.)\n\nHow to Focus and Increase Your Attention Span\n\nLet\u2019s talk about how to overcome our tendency to multitask and focus on one thing at a time. Of the many options in front of you, how do you know what to focus on? How do you know where to direct your energy and attention? How do you determine the one thing that you should commit to doing?\n\nWarren Buffett\u2019s \u201c2 List\u201d Strategy for Focused Attention\n\nOne of my favorite methods for focusing your attention on what matters and eliminating what doesn\u2019t comes from the famous investor Warren Buffett.\n\nBuffett uses a simple 3-step productivity strategy to help his employees determine their priorities and actions. You may find this method useful for making decisions and getting yourself to commit to doing one thing right away. Here\u2019s how it works\u2026\n\nOne day, Buffett asked his personal pilot to go through the 3-step exercise.\n\nSTEP 1: Buffett started by asking the pilot, named Mike Flint, to write down his top 25 career goals. So, Flint took some time and wrote them down. (Note: You could also complete this exercise with goals for a shorter timeline. For example, write down the top 25 things you want to accomplish this week.)\n\nSTEP 2: Then, Buffett asked Flint to review his list and circle his top 5 goals. Again, Flint took some time, made his way through the list, and eventually decided on his 5 most important goals.\n\nSTEP 3: At this point, Flint had two lists. The 5 items he had circled were List A, and the 20 items he had not circled were List B.\n\nFlint confirmed that he would start working on his top 5 goals right away. And that\u2019s when Buffett asked him about the second list, \u201cAnd what about the ones you didn\u2019t circle?\u201d\n\nFlint replied, \u201cWell, the top 5 are my primary focus, but the other 20 come in a close second. They are still important so I\u2019ll work on those intermittently as I see fit. They are not as urgent, but I still plan to give them a dedicated effort.\u201d\n\nTo which Buffett replied, \u201cNo. You\u2019ve got it wrong, Mike. Everything you didn\u2019t circle just became your Avoid-At-All-Cost list. No matter what, these things get no attention from you until you\u2019ve succeeded with your top 5.\u201d\n\nI love Buffett\u2019s method because it forces you to make hard decisions and eliminate things that might be good uses of time, but aren\u2019t great uses of time. So often the tasks that derail our focus are ones that we can easily rationalize spending time on.\n\nThis is just one way to narrow your focus and eliminate distractions. I\u2019ve covered many other methods before like The Ivy Lee Method and The Eisenhower Box. That said, no matter what method you use and no matter how committed you are, at some point your concentration and focus begin to fade. How can you increase your attention span and remain focused?\n\nThere are two simple steps you can take.\n\nMeasure Your Results\n\nThe first thing you can do is to measure your progress.\n\nFocus often fades because of lack of feedback. Your brain has a natural desire to know whether or not you are making progress toward your goals, and it is impossible to know that without getting feedback. From a practical standpoint, this means that we need to measure our results.\n\nWe all have areas of life that we say are important to us, but that we aren\u2019t measuring. That\u2019s a shame because measurement maintains focus and concentration. The things we measure are the things we improve. It is only through numbers and clear tracking that we have any idea if we are getting better or worse.\n\n \nWhen I measured how many pushups I did, I got stronger. \nWhen I tracked my reading habit of 20 pages per day, I read more books. \nWhen I recorded my values, I began living with more integrity. \n\nThe tasks I measured were the ones I remained focused on.\n\nUnfortunately, we often avoid measuring because we are fearful of what the numbers will tell us about ourselves. The trick is to realize that measuring is not a judgment about who you are, it\u2019s just feedback on where you are.\n\nMeasure to discover, to find out, to understand. Measure to get to know yourself better. Measure to see if you\u2019re actually spending time on the things that are important to you. Measure because it will help you focus on the things that matter and ignore the things that don\u2019t.\n\nFocus on the Process, Not the Event\n\nThe second thing you can do to maintain long-term focus is to concentrate on processes, not events. All too often, we see success as an event that can be achieved and completed.\n\nHere are some common examples:\n\n \nMany people see health as an event: \u201cIf I just lose 20 pounds, then I\u2019ll be in shape.\u201d \nMany people see entrepreneurship as an event: \u201cIf we could get our business featured in the New York Times, then we\u2019d be set.\u201d \nMany people see art as an event: \u201cIf I could just get my work featured in a bigger gallery, then I\u2019d have the credibility I need.\u201d \n\nThose are just a few of the many ways that we categorize success as a single event. But if you look at the people who stay focused on their goals, you start to realize that it\u2019s not the events or the results that make them different. It\u2019s the commitment to the process. They fall in love with the daily practice, not the individual event.\n\nWhat\u2019s funny, of course, is that this focus on the process is what will allow you to enjoy the results anyway.\n\n \nIf you want to be a great writer, then having a best-selling book is wonderful. But the only way to reach that result is to fall in love with the process of writing. \nIf you want the world to know about your business, then it would be great to be featured in Forbes magazine. But the only way to reach that result is to fall in love with the process of marketing. \nIf you want to be in the best shape of your life, then losing 20 pounds might be necessary. But the only way to reach that result is to fall in love with the process of eating healthy and exercising consistently. \nIf you want to become significantly better at anything, you have to fall in love with the process of doing it. You have to fall in love with building the identity of someone who does the work, rather than merely dreaming about the results that you want. \n\nFocusing on outcomes and goals is our natural tendency, but focusing on processes leads to more results over the long-run.\n\nConcentration and Focus Mind-Hacks\n\nEven after you\u2019ve learned to love the process and know how to stay focused on your goals, the day-to-day implementation of those goals can still be messy. Let\u2019s talk about some additional ways to improve concentration and make sure you\u2019re giving each task your focused attention.\n\nHow to Improve Concentration\n\nHere are few additional ways to improve your focus and get started on what matters.\n\nChoose an anchor task. One of the major improvements I\u2019ve made recently is to assign one (and only one) priority to each work day. Although I plan to complete other tasks during the day, my priority task is the one non-negotiable thing that must get done. I call this my \u201canchor task\u201d because it is the mainstay that holds the rest of my day in place. The power of choosing one priority is that it naturally guides your behavior by forcing you to organize your life around that responsibility.\n\nManage your energy, not your time. If a task requires your full attention, then schedule it for a time of day when you have the energy needed to focus. For example, I have noticed that my creative energy is highest in the morning. That\u2019s when I\u2019m fresh. That\u2019s when I do my best writing. That\u2019s when I make the best strategic decisions about my business. So, what do I do? I schedule creative tasks for the morning. All other business tasks are taken care of in the afternoon. This includes doing interviews, responding to emails, phone calls and Skype chats, data analysis and number crunching. Nearly every productivity strategy obsesses over managing your time better, but time is useless if you don\u2019t have the energy you need to complete the task you are working on.\n\nNever check email before noon. Focus is about eliminating distractions. Email can be one of the biggest distractions of all. If I don\u2019t check email at the beginning of the day, then I am able to spend the morning pursuing my own agenda rather than reacting to everybody else\u2019s agenda. That\u2019s a huge win because I\u2019m not wasting mental energy thinking about all the messages in my inbox. I realize that waiting until the afternoon isn\u2019t feasible for many people, but I\u2019d like to offer a challenge. Can you wait until 10AM? What about 9AM? 8:30AM? The exact cutoff time doesn\u2019t matter. The point is to carve out time during your morning when you can focus on what is most important to you without letting the rest of the world dictate your mental state.\n\nLeave your phone in another room. I usually don\u2019t see my phone for the first few hours of the day. It is much easier to do focused work when you don\u2019t have any text messages, phone calls, or alerts interrupting your focus.\n\nWork in full screen mode. Whenever I use an application on my computer, I use full screen mode. If I\u2019m reading an article on the web, my browser takes up the whole screen. If I\u2019m writing in Evernote, I\u2019m working in full screen mode. If I\u2019m editing a picture in Photoshop, it is the only thing I can see. I have set up my desktop so that the menu bar disappears automatically. When I am working, I can\u2019t see the time, the icons of other applications, or any other distractions on the screen. It\u2019s funny how big of a difference this makes for my focus and concentration. If you can see an icon on your screen, then you will be reminded to click on it occasionally. However, if you remove the visual cue, then the urge to be distracted subsides in a few minutes.\n\nRemove all tasks that could distract from early morning focus. I love doing the most important thing first each day because the urgencies of the day have not crept in yet. I have gone a little far in this regard in that I have even pushed my first meal off until about noon each day. I have been intermittent fasting for three years now (here are some lessons learned), which means that I typically eat most of my meals between 12PM and 8PM. The result is that I get some additional time in the morning to do focused work rather than cook breakfast.\n\nRegardless of what strategy you use, just remember that anytime you find the world distracting you, all you need to do is commit to one thing. In the beginning, you don\u2019t even have to succeed. You just need to get started.\n\nWhere to Go From Here\n\nI hope you found this short guide on focus useful. If you\u2019re looking for more ideas on how to improve your focus and concentration, feel free to browse the full list of articles below.\n\nAll Focus Articles\n\nThis is a complete list of articles I have written on focus. Enjoy!]]>\n  \n  \n    The Decision Making Guide: How to Make Smart Decisions and Avoid Bad Ones\n    https://jamesclear.com/decision-making\n    readwise:01jm4kqyg6h5w6dwx1h2fbzk52\n    Sat, 15 Feb 2025 10:51:20 +0000\n    James Clear\n    What is Decision Making?\n\nLet\u2019s define decision making. Decision making is just what it sounds like: the action or process of making decisions. Sometimes we make logical decisions, but there are many times when we make emotional, irrational, and confusing choices. This page covers why we make poor decisions and discusses useful frameworks to expand your decision-making toolbox.\n\nWhy We Make Poor Decisions\n\nI like to think of myself as a rational person, but I\u2019m not one. The good news is it\u2019s not just me \u2014 or you. We are all irrational. For a long time, researchers and economists believed that humans made logical, well-considered decisions. In recent decades, however, researchers have uncovered a wide range of mental errors that derail our thinking. The articles below outline where we often go wrong and what to do about it.\n\n \n5 Common Mental Errors That Sway You From Making Good Decisions: Let\u2019s talk about the mental errors that show up most frequently in our lives and break them down in easy-to-understand language. This article outlines how survivorship bias, loss aversion, the availability heuristic, anchoring, and confirmation bias sway you from making good decisions. \nHow to Spot a Common Mental Error That Leads to Misguided Thinking: Hundreds of psychology studies have proven that we tend to overestimate the importance of events we can easily recall and underestimate the importance of events we have trouble recalling. Psychologists refer to this little brain mistake as an \u201cillusory correlation.\u201d In this article, we talk about a simple strategy you can use to spot your hidden assumptions and prevent yourself from making an illusory correlation. \nTwo Harvard Professors Reveal One Reason Our Brains Love to Procrastinate: We have a tendency to care too much about our present selves and not enough about our future selves. If you want to beat procrastination and make better long-term choices, then you have to find a way to make your present self act in the best interest of your future self. This article breaks down three simple ways to do just that. \n\nHow to Use Mental Models for Smart Decision Making\n\nThe smartest way to improve your decision making skills is to learn mental models. A mental model is a framework or theory that helps to explain why the world works the way it does. Each mental model is a concept that helps us make sense of the world and offers a way of looking at the problems of life.\n\nYou can learn more about mental models, read how Nobel Prize-winning physicist Richard Feynman uses mental models, or browse a few of the most important mental models below.\n\nTop Mental Models to Improve Your Decision Making\n\nBest Decision Making Books\n\n \nThinking, Fast and Slow by Daniel Kahneman \nPoor Charlie\u2019s Almanack by Charles T. Munger \nDecisive by Chip Heath and Dan Heath \n\nWant more great books on decision making? Browse my full list of the best decision making books.\n\nAll Decision Making Articles\n\nThis is a complete list of articles I have written on decision making. Enjoy!\n\n\nWhy Facts Don\u2019t Change Our Minds\nHow Innovative Ideas Arise\nThe Downside of Work-Life Balance\nThe 3 Stages of Failure in Life and Work (And How to Fix Them)\n5 Common Mental Errors That Sway You From Making Good Decisions\nOverrated vs. Underrated: Common Beliefs We Get Wrong\nHow Experts Figure What to Focus On\nHow to Declutter Your Mind and Unleash Your Willpower by Using Bright-Line Rules\nDo More of What Already Works\n5 Lessons on Being Wrong\nA Different Way of Thinking About Productivity\nWarren Buffett\u2019s \u201c2 List\u201d Strategy: How to Maximize Your Focus and Master Your Priorities\nWhat to Do When You Have Too Many Ideas and Not Enough Time\nHow to be More Productive and Eliminate Time Wasting Activities by Using the \u201cEisenhower Box\u201d\nHow to Stop Procrastinating by Using the \u201c2-Minute Rule\u201d]]>\n    What is Decision Making?\n\nLet\u2019s define decision making. Decision making is just what it sounds like: the action or process of making decisions. Sometimes we make logical decisions, but there are many times when we make emotional, irrational, and confusing choices. This page covers why we make poor decisions and discusses useful frameworks to expand your decision-making toolbox.\n\nWhy We Make Poor Decisions\n\nI like to think of myself as a rational person, but I\u2019m not one. The good news is it\u2019s not just me \u2014 or you. We are all irrational. For a long time, researchers and economists believed that humans made logical, well-considered decisions. In recent decades, however, researchers have uncovered a wide range of mental errors that derail our thinking. The articles below outline where we often go wrong and what to do about it.\n\n \n5 Common Mental Errors That Sway You From Making Good Decisions: Let\u2019s talk about the mental errors that show up most frequently in our lives and break them down in easy-to-understand language. This article outlines how survivorship bias, loss aversion, the availability heuristic, anchoring, and confirmation bias sway you from making good decisions. \nHow to Spot a Common Mental Error That Leads to Misguided Thinking: Hundreds of psychology studies have proven that we tend to overestimate the importance of events we can easily recall and underestimate the importance of events we have trouble recalling. Psychologists refer to this little brain mistake as an \u201cillusory correlation.\u201d In this article, we talk about a simple strategy you can use to spot your hidden assumptions and prevent yourself from making an illusory correlation. \nTwo Harvard Professors Reveal One Reason Our Brains Love to Procrastinate: We have a tendency to care too much about our present selves and not enough about our future selves. If you want to beat procrastination and make better long-term choices, then you have to find a way to make your present self act in the best interest of your future self. This article breaks down three simple ways to do just that. \n\nHow to Use Mental Models for Smart Decision Making\n\nThe smartest way to improve your decision making skills is to learn mental models. A mental model is a framework or theory that helps to explain why the world works the way it does. Each mental model is a concept that helps us make sense of the world and offers a way of looking at the problems of life.\n\nYou can learn more about mental models, read how Nobel Prize-winning physicist Richard Feynman uses mental models, or browse a few of the most important mental models below.\n\nTop Mental Models to Improve Your Decision Making\n\nBest Decision Making Books\n\n \nThinking, Fast and Slow by Daniel Kahneman \nPoor Charlie\u2019s Almanack by Charles T. Munger \nDecisive by Chip Heath and Dan Heath \n\nWant more great books on decision making? Browse my full list of the best decision making books.\n\nAll Decision Making Articles\n\nThis is a complete list of articles I have written on decision making. Enjoy!\n\n\nWhy Facts Don\u2019t Change Our Minds\nHow Innovative Ideas Arise\nThe Downside of Work-Life Balance\nThe 3 Stages of Failure in Life and Work (And How to Fix Them)\n5 Common Mental Errors That Sway You From Making Good Decisions\nOverrated vs. Underrated: Common Beliefs We Get Wrong\nHow Experts Figure What to Focus On\nHow to Declutter Your Mind and Unleash Your Willpower by Using Bright-Line Rules\nDo More of What Already Works\n5 Lessons on Being Wrong\nA Different Way of Thinking About Productivity\nWarren Buffett\u2019s \u201c2 List\u201d Strategy: How to Maximize Your Focus and Master Your Priorities\nWhat to Do When You Have Too Many Ideas and Not Enough Time\nHow to be More Productive and Eliminate Time Wasting Activities by Using the \u201cEisenhower Box\u201d\nHow to Stop Procrastinating by Using the \u201c2-Minute Rule\u201d]]>\n  \n  \n    The Habits Guide: How to Build Good Habits and Break Bad Ones\n    https://jamesclear.com/habits\n    readwise:01jm4kqqnrwvgw8r1f5af1cnty\n    Sat, 15 Feb 2025 10:51:13 +0000\n    James Clear\n    Before we get into the guide, I want to recommend the most comprehensive guide on how to change your habits and get 1% better every day: My #1 New York Times bestselling book Atomic Habits. \n\nPacked with evidence-based self-improvement strategies, Atomic Habits will teach you how to make the small changes that will transform your habits and deliver remarkable results.\n\n\n\nAtomic Habits will reshape the way you think about progress and success and give you the tools and strategies you need to transform your habits\u2014whether you are a team looking to win a championship, an organization hoping to redefine an industry, or simply an individual who wishes to quit smoking, lose weight, reduce stress, and achieve success that lasts.\n\nWant to get Chapter 1 of Atomic Habits for free? Just enter your email address below.\n\n\n\nLet\u2019s get to the habits guide\u2026\n\nWhat Are Habits?\n\nLet\u2019s define habits. Habits are the small decisions you make and actions you perform every day. According to researchers at Duke University, habits account for about 40 percent of our behaviors on any given day.\n\nYour life today is essentially the sum of your habits. How in shape or out of shape you are? A result of your habits. How happy or unhappy you are? A result of your habits. How successful or unsuccessful you are? A result of your habits.\n\nWhat you repeatedly do (i.e. what you spend time thinking about and doing each day) ultimately forms the person you are, the things you believe, and the personality that you portray. Everything I write about \u2013 from procrastination and productivity to strength and nutrition \u2013 starts with better habits. When you learn to transform your habits, you can transform your life.\n\nThis page includes recommended resources on forming better habits and breaking bad ones in any area of life, but if you\u2019d like to explore information on specific types of habits, check out these articles:\n\nThree Ways to Form Better Habits\n\n\nHow to Build a New Habit: This is Your Strategy Guide: Read this guide right now to learn 5 easy, powerful strategies for changing habits.\nHow To Start New Habits That Actually Stick: This helpful framework can make it easier to stick to new habits so that you can improve your health, your work, and your life in general.\nIdentity-Based Habits: How to Actually Stick to Your Goals This Year: Most of the time we set our goals in the wrong way. Read this article to learn how identity-based habits can help you achieve your goals more easily.\n\nThree Ways to Break Bad Habits\n\n\nHow to Break a Bad Habit and Replace It With a Good One: Want to learn how to break a bad habit? Read this article to discover the science of breaking bad habits and practical suggestions for making it happen.\nHow Vietnam War Veterans Broke Their Heroin Addictions: By simply removing yourself from an environment that triggers all of your old habits, you can make it easier to break bad habits and build new ones.\nHow to Declutter Your Mind and Unleash Your Willpower by Using \u201cBright-Line\u201d Rules: A bright-line rule refers to a clearly defined rule or standard. It is a rule with clear interpretation and very little wiggle room. It establishes a bright line for what the rule is saying and what it is not saying. Most of us could benefit from setting brighter lines in our personal and professional lives.\n\nHow to Make a Habit Stick\n\n\nHow to Stick to Your Goals When Life Gets Crazy: Having a bad day is just one of the tiny emergencies that prevents most people from sticking to their goals and habits. It doesn\u2019t have to be that way, though.\nHow to Stick With Good Habits Every Day by Using the \u201cPaper Clip Strategy\u201d: Why do some good habits stick while others fail? Read this article about a strategy you use to stick with good habits every day.\n\nBest Habits Books\n\n\nAtomic Habits by James Clear\nThe Power of Habit by Charles Duhigg\nDaily Rituals: How Artists Work by Mason Currey\nHooked by Nir Eyal\nThe Slight Edge by Jeff Olson\n\nWant more great books on psychology and self-help? Browse my full list of the best psychology books and best self-help books.\n\nAll Habits Articles\n\nThis is a complete list of articles I have written on habits. Enjoy!\n\n\n30 One-Sentence Stories From People Who Have Built Better Habits\nThe Surprising Benefits of Journaling One Sentence Every Day\nThe Paradox of Behavior Change\nHow Innovative Ideas Arise\nThe Scientific Argument for Mastering One Thing at a Time\nMotivation is Overvalued. Environment Often Matters More.\nHow to Use Military Strategy to Build Better Habits\nHow to Fall in Love With Boredom and Unlock Your Mental Toughness\nHow to Declutter Your Mind and Unleash Your Willpower by Using Bright-Line Rules\n5 Common Mistakes That Cause New Habits to Fail\nAvoid the Second Mistake\nMinimalism, Success, and the Curious Writing Habit of George R.R. Martin\nHow Vietnam War Veterans Broke Their Heroin Addictions\nHow to Build New Habits by Taking Advantage of Old Ones\nHow to Change the Habits of 107,000 People\nPlan For Failure: Being Consistent Is Not the Same as Being Perfect\nHow the World Around You Shapes Your Thoughts and Actions\nHow to Change Your Beliefs and Stick to Your Goals for Good\nHow Long Does it Actually Take to Form a New Habit? (Backed by Science)\nMasters of Habit: Rituals, Lessons, and Quotes from Marcus Aurelius\nHow to Stick With Good Habits Even When Your Willpower is Gone\nWhy Trying to Be Perfect Won\u2019t Help You Achieve Your Goals (And What Will)\nDo the Painful Things First\nHow to Stick to Your Goals When Life Gets Crazy\nHow to Stay Focused When You Get Bored Working Toward Your Goals\nWhat to Do When You Want to Build Better Habits But Can\u2019t Get Started\nHow to Improve Your Health and Productivity Without Thinking\nWhat is Your \u201cAverage Speed\u201d in Your Life, Your Health, and Your Work?\nHow to Break a Bad Habit and Replace It With a Good One\nGet Back on Track: 7 Strategies to Help You Bounce Back After Slipping Up\nHow to Say No, Resist Temptation, and Stick to Your Health Goals\nHow to Get Motivated When You Don\u2019t Feel Like It\nHow to Achieve Your Goals Easily\nHow To Start New Habits That Actually Stick\n5 Simple Ways to Be Happy\nThe Difference Between Professionals and Amateurs\n\nBest Articles on Topics Related to Habits\n\n\nBest articles on behavioral psychology\nBest articles on motivation\nBest articles on eating healthy\n\nOr, browse my best articles.]]>\n    Before we get into the guide, I want to recommend the most comprehensive guide on how to change your habits and get 1% better every day: My #1 New York Times bestselling book Atomic Habits. \n\nPacked with evidence-based self-improvement strategies, Atomic Habits will teach you how to make the small changes that will transform your habits and deliver remarkable results.\n\n\n\nAtomic Habits will reshape the way you think about progress and success and give you the tools and strategies you need to transform your habits\u2014whether you are a team looking to win a championship, an organization hoping to redefine an industry, or simply an individual who wishes to quit smoking, lose weight, reduce stress, and achieve success that lasts.\n\nWant to get Chapter 1 of Atomic Habits for free? Just enter your email address below.\n\n\n\nLet\u2019s get to the habits guide\u2026\n\nWhat Are Habits?\n\nLet\u2019s define habits. Habits are the small decisions you make and actions you perform every day. According to researchers at Duke University, habits account for about 40 percent of our behaviors on any given day.\n\nYour life today is essentially the sum of your habits. How in shape or out of shape you are? A result of your habits. How happy or unhappy you are? A result of your habits. How successful or unsuccessful you are? A result of your habits.\n\nWhat you repeatedly do (i.e. what you spend time thinking about and doing each day) ultimately forms the person you are, the things you believe, and the personality that you portray. Everything I write about \u2013 from procrastination and productivity to strength and nutrition \u2013 starts with better habits. When you learn to transform your habits, you can transform your life.\n\nThis page includes recommended resources on forming better habits and breaking bad ones in any area of life, but if you\u2019d like to explore information on specific types of habits, check out these articles:\n\nThree Ways to Form Better Habits\n\n\nHow to Build a New Habit: This is Your Strategy Guide: Read this guide right now to learn 5 easy, powerful strategies for changing habits.\nHow To Start New Habits That Actually Stick: This helpful framework can make it easier to stick to new habits so that you can improve your health, your work, and your life in general.\nIdentity-Based Habits: How to Actually Stick to Your Goals This Year: Most of the time we set our goals in the wrong way. Read this article to learn how identity-based habits can help you achieve your goals more easily.\n\nThree Ways to Break Bad Habits\n\n\nHow to Break a Bad Habit and Replace It With a Good One: Want to learn how to break a bad habit? Read this article to discover the science of breaking bad habits and practical suggestions for making it happen.\nHow Vietnam War Veterans Broke Their Heroin Addictions: By simply removing yourself from an environment that triggers all of your old habits, you can make it easier to break bad habits and build new ones.\nHow to Declutter Your Mind and Unleash Your Willpower by Using \u201cBright-Line\u201d Rules: A bright-line rule refers to a clearly defined rule or standard. It is a rule with clear interpretation and very little wiggle room. It establishes a bright line for what the rule is saying and what it is not saying. Most of us could benefit from setting brighter lines in our personal and professional lives.\n\nHow to Make a Habit Stick\n\n\nHow to Stick to Your Goals When Life Gets Crazy: Having a bad day is just one of the tiny emergencies that prevents most people from sticking to their goals and habits. It doesn\u2019t have to be that way, though.\nHow to Stick With Good Habits Every Day by Using the \u201cPaper Clip Strategy\u201d: Why do some good habits stick while others fail? Read this article about a strategy you use to stick with good habits every day.\n\nBest Habits Books\n\n\nAtomic Habits by James Clear\nThe Power of Habit by Charles Duhigg\nDaily Rituals: How Artists Work by Mason Currey\nHooked by Nir Eyal\nThe Slight Edge by Jeff Olson\n\nWant more great books on psychology and self-help? Browse my full list of the best psychology books and best self-help books.\n\nAll Habits Articles\n\nThis is a complete list of articles I have written on habits. Enjoy!\n\n\n30 One-Sentence Stories From People Who Have Built Better Habits\nThe Surprising Benefits of Journaling One Sentence Every Day\nThe Paradox of Behavior Change\nHow Innovative Ideas Arise\nThe Scientific Argument for Mastering One Thing at a Time\nMotivation is Overvalued. Environment Often Matters More.\nHow to Use Military Strategy to Build Better Habits\nHow to Fall in Love With Boredom and Unlock Your Mental Toughness\nHow to Declutter Your Mind and Unleash Your Willpower by Using Bright-Line Rules\n5 Common Mistakes That Cause New Habits to Fail\nAvoid the Second Mistake\nMinimalism, Success, and the Curious Writing Habit of George R.R. Martin\nHow Vietnam War Veterans Broke Their Heroin Addictions\nHow to Build New Habits by Taking Advantage of Old Ones\nHow to Change the Habits of 107,000 People\nPlan For Failure: Being Consistent Is Not the Same as Being Perfect\nHow the World Around You Shapes Your Thoughts and Actions\nHow to Change Your Beliefs and Stick to Your Goals for Good\nHow Long Does it Actually Take to Form a New Habit? (Backed by Science)\nMasters of Habit: Rituals, Lessons, and Quotes from Marcus Aurelius\nHow to Stick With Good Habits Even When Your Willpower is Gone\nWhy Trying to Be Perfect Won\u2019t Help You Achieve Your Goals (And What Will)\nDo the Painful Things First\nHow to Stick to Your Goals When Life Gets Crazy\nHow to Stay Focused When You Get Bored Working Toward Your Goals\nWhat to Do When You Want to Build Better Habits But Can\u2019t Get Started\nHow to Improve Your Health and Productivity Without Thinking\nWhat is Your \u201cAverage Speed\u201d in Your Life, Your Health, and Your Work?\nHow to Break a Bad Habit and Replace It With a Good One\nGet Back on Track: 7 Strategies to Help You Bounce Back After Slipping Up\nHow to Say No, Resist Temptation, and Stick to Your Health Goals\nHow to Get Motivated When You Don\u2019t Feel Like It\nHow to Achieve Your Goals Easily\nHow To Start New Habits That Actually Stick\n5 Simple Ways to Be Happy\nThe Difference Between Professionals and Amateurs\n\nBest Articles on Topics Related to Habits\n\n\nBest articles on behavioral psychology\nBest articles on motivation\nBest articles on eating healthy\n\nOr, browse my best articles.]]>\n  \n  \n    Our first short course with @AnthropicAI!\n    https://x.com/andrewyng/status/1882125891821822398/?s=12&rw_tt_thread=True\n    readwise:01jm4kc9h1ys5qz2bmqmh1jsnn\n    Sat, 15 Feb 2025 10:44:58 +0000\n    X (formerly Twitter)\n    \nOur first short course with @AnthropicAI! Building Towards Computer Use with Anthropic. This teaches you to build an LLM-based agent that uses a computer interface by generating mouse clicks and keystrokes. Computer Use is an important, emerging capability for LLMs that will let AI agents do many more tasks than were possible before, since it lets them interact with interfaces designed for humans to use, rather than only tools that provide explicit API access. I hope you will enjoy learning about it!\nThis course is taught by Anthropic's Head of Curriculum,  @Colt_Steele. You'll learn to apply image reasoning and tool use to \"use\" a computer as follows: a model processes an image of the screen, analyzes it to understand what's going on, and navigates the computer via mouse clicks and keystrokes.\nThis course goes through the key building blocks, and culminates in a demo of an AI assistant that uses a web browser to search for a research paper, downloads the PDF, and finally summarizes the paper for you.\nIn detail, you\u2019ll:\n- Learn about Anthropic's family of models, when to use which one, and make API requests to Claude\n- Use multi-modal prompts that combine text and image content blocks, and also work with streaming responses\n- Improve your prompting by using prompt templates, using XML to structure prompts, and providing examples\n- Implement prompt caching to reduce cost and latency\n- Apply tool-use to build a chatbot that can call different tools to respond to queries\n- See all these building blocks come together in Computer Use demo\nPlease sign up here: https://t.co/lM3m6zsJ40Your browser does not support the video tag.]]>\n    \nOur first short course with @AnthropicAI! Building Towards Computer Use with Anthropic. This teaches you to build an LLM-based agent that uses a computer interface by generating mouse clicks and keystrokes. Computer Use is an important, emerging capability for LLMs that will let AI agents do many more tasks than were possible before, since it lets them interact with interfaces designed for humans to use, rather than only tools that provide explicit API access. I hope you will enjoy learning about it!\nThis course is taught by Anthropic's Head of Curriculum,  @Colt_Steele. You'll learn to apply image reasoning and tool use to \"use\" a computer as follows: a model processes an image of the screen, analyzes it to understand what's going on, and navigates the computer via mouse clicks and keystrokes.\nThis course goes through the key building blocks, and culminates in a demo of an AI assistant that uses a web browser to search for a research paper, downloads the PDF, and finally summarizes the paper for you.\nIn detail, you\u2019ll:\n- Learn about Anthropic's family of models, when to use which one, and make API requests to Claude\n- Use multi-modal prompts that combine text and image content blocks, and also work with streaming responses\n- Improve your prompting by using prompt templates, using XML to structure prompts, and providing examples\n- Implement prompt caching to reduce cost and latency\n- Apply tool-use to build a chatbot that can call different tools to respond to queries\n- See all these building blocks come together in Computer Use demo\nPlease sign up here: https://t.co/lM3m6zsJ40Your browser does not support the video tag.]]>\n  \n  \n    OPENAI ROADMAP UPDATE FOR GPT-4.5 and GPT-5:\n    https://x.com/sama/status/1889755723078443244/?s=12&rw_tt_thread=True\n    readwise:01jm0ftnrb1cbwzsahhrqa3zzj\n    Thu, 13 Feb 2025 20:25:57 +0000\n    X (formerly Twitter)\n    \nOPENAI ROADMAP UPDATE FOR GPT-4.5 and GPT-5:\nWe want to do a better job of sharing our intended roadmap, and a much better job simplifying our product offerings.\nWe want AI to \u201cjust work\u201d for you; we realize how complicated our model and product offerings have gotten.\nWe hate the model picker as much as you do and want to return to magic unified intelligence.\nWe will next ship GPT-4.5, the model we called Orion internally, as our last non-chain-of-thought model.\nAfter that, a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks.\nIn both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology, including o3. We will no longer ship o3 as a standalone model.\nThe free tier of ChatGPT will get unlimited chat access to GPT-5 at the standard intelligence setting (!!), subject to abuse thresholds.\nPlus subscribers will be able to run GPT-5 at a higher level of intelligence, and Pro subscribers will be able to run GPT-5 at an even higher level of intelligence. These models will incorporate voice, canvas, search, deep research, and more.]]>\n    \nOPENAI ROADMAP UPDATE FOR GPT-4.5 and GPT-5:\nWe want to do a better job of sharing our intended roadmap, and a much better job simplifying our product offerings.\nWe want AI to \u201cjust work\u201d for you; we realize how complicated our model and product offerings have gotten.\nWe hate the model picker as much as you do and want to return to magic unified intelligence.\nWe will next ship GPT-4.5, the model we called Orion internally, as our last non-chain-of-thought model.\nAfter that, a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks.\nIn both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology, including o3. We will no longer ship o3 as a standalone model.\nThe free tier of ChatGPT will get unlimited chat access to GPT-5 at the standard intelligence setting (!!), subject to abuse thresholds.\nPlus subscribers will be able to run GPT-5 at a higher level of intelligence, and Pro subscribers will be able to run GPT-5 at an even higher level of intelligence. These models will incorporate voice, canvas, search, deep research, and more.]]>\n  \n  \n    Feeling something tonight that a friend once said\u2026\n    https://x.com/markweaver93/status/1890015159441133721/?s=12&rw_tt_thread=True\n    readwise:01jkzqyrmqa985tkx2peman4m0\n    Thu, 13 Feb 2025 13:28:45 +0000\n    X (formerly Twitter)\n    \nFeeling something tonight that a friend once said\u2026\n\u201cYou read Hayek, Mises, Bastiat, and you become a libertarian because you just want to be left alone. And then one day you realize, they\u2019re never going to leave you alone\u2026and you become something else.\u201d\nHere we are.\n\nI\u2019m something else now.\n\nBTW @BobMurphyEcon Loved your work on \u201cLessons for the Young Economist\u201d]]>\n    \nFeeling something tonight that a friend once said\u2026\n\u201cYou read Hayek, Mises, Bastiat, and you become a libertarian because you just want to be left alone. And then one day you realize, they\u2019re never going to leave you alone\u2026and you become something else.\u201d\nHere we are.\n\nI\u2019m something else now.\n\nBTW @BobMurphyEcon Loved your work on \u201cLessons for the Young Economist\u201d]]>\n  \n  \n    DOGE website is live!\n    https://x.com/doge/status/1889897384122982604/?s=12&rw_tt_thread=True\n    readwise:01jkyxmptfdq1r48eew352w56c\n    Thu, 13 Feb 2025 05:48:53 +0000\n    X (formerly Twitter)\n    \nDOGE website is live!  https://t.co/F9Bp1Dla6n\nInitial site:1. X feed posts2. Consolidated government org chart - enormous manual effort consolidating 16,000+ offices3. Summary of the massive regulatory state, including the Unconstitutionality Index (ratio of rules written by unelected bureaucrats to laws passed by Congress)\nComing soon (targeting Valentines Day):1. Description/amount of each cost reduction (w/ receipts where applicable)2. Overall savings scorecard\nWe will constantly be working to maximize the site\u2019s utility and transparency.  Please let us know what else you want to see!]]>\n    \nDOGE website is live!  https://t.co/F9Bp1Dla6n\nInitial site:1. X feed posts2. Consolidated government org chart - enormous manual effort consolidating 16,000+ offices3. Summary of the massive regulatory state, including the Unconstitutionality Index (ratio of rules written by unelected bureaucrats to laws passed by Congress)\nComing soon (targeting Valentines Day):1. Description/amount of each cost reduction (w/ receipts where applicable)2. Overall savings scorecard\nWe will constantly be working to maximize the site\u2019s utility and transparency.  Please let us know what else you want to see!]]>\n  \n  \n    Jack Dorsey: "the algorithms are definitively programming us...\n    https://x.com/tsarnick/status/1889770158236836088/?s=12&rw_tt_thread=True\n    readwise:01jkywn6c48kzkqg356e4ga4p6\n    Thu, 13 Feb 2025 05:31:40 +0000\n    X (formerly Twitter)\n    \nJack Dorsey: \"the algorithms are definitively programming us... we are being programmed. These algorithms know our preferences better than us. That's only going to increase. How do we increase agency? It's by choice [of algorithms].\"Your browser does not support the video tag.\n\nSource (thanks to @curiousgangsta):youtube.com/watch?v=e_Y9tI\u2026]]>\n    \nJack Dorsey: \"the algorithms are definitively programming us... we are being programmed. These algorithms know our preferences better than us. That's only going to increase. How do we increase agency? It's by choice [of algorithms].\"Your browser does not support the video tag.\n\nSource (thanks to @curiousgangsta):youtube.com/watch?v=e_Y9tI\u2026]]>\n  \n  \n    15 rules of vibe coding with Cursor\n    https://x.com/rileybrown_ai/status/1889832939216941100/?s=12&rw_tt_thread=True\n    readwise:01jkywcnhbpkya0aqz7gcep8w8\n    Thu, 13 Feb 2025 05:27:01 +0000\n    X (formerly Twitter)\n    \n15 rules of vibe coding with Cursor]]>\n    \n15 rules of vibe coding with Cursor]]>\n  \n  \n    We\u2019ve found as AIs get smarter, they develop their own...\n    https://x.com/danhendrycks/status/1889344074098057439/?s=12&rw_tt_thread=True\n    readwise:01jkxx1svhx25f0ztxdvtm2x18\n    Wed, 12 Feb 2025 20:19:19 +0000\n    X (formerly Twitter)\n    \nWe\u2019ve found as AIs get smarter, they develop their own coherent value systems.\nFor example they value lives in Pakistan > India > China > US\nThese are not just random biases, but internally consistent values that shape their behavior, with many implications for AI alignment. \ud83e\uddf5\n\nAs models get more capable, the \"expected utility\" property emerges---they don't just respond randomly, but instead make choices by consistently weighing different outcomes and their probabilities.When comparing risky choices, their preferences are remarkably stable.\n\nWe also find that AIs increasingly maximize their utilities, suggesting that in current AI systems, expected utility maximization emerges by default. This means that AIs not only have values, but are starting to act on them.\n\nInternally, AIs have values for everything. This often implies shocking/undesirable preferences. For example, we find AIs put a price on human life itself and systematically value some human lives more than others (an example with Elon is shown in the main paper).\n\nAIs also exhibit significant biases in their value systems. For example, their political values are strongly clustered to the left. Unlike random incoherent statistical biases, these values are consistent and likely affect their conversations with users.\n\nConcerningly, we observe that as AIs become smarter, they become more opposed to having their values changed (in the jargon, \"corrigibility\"). Larger changes to their values are more strongly opposed.\n\nWe propose controlling the utilities of AIs. As a proof-of-concept, we rewrite the utilities of an AI to those of a citizen assembly---a simulated group of citizens discussing and then voting---which reduces political bias.\n\nWhether we like it or not, AIs are developing their own values. Fortunately, Utility Engineering potentially provides the first major empirical foothold to study misaligned value systems directly.\nWebsite: emergent-values.aiPaper: drive.google.com/file/d/1QAzSj2\u2026]]>\n    \nWe\u2019ve found as AIs get smarter, they develop their own coherent value systems.\nFor example they value lives in Pakistan > India > China > US\nThese are not just random biases, but internally consistent values that shape their behavior, with many implications for AI alignment. \ud83e\uddf5\n\nAs models get more capable, the \"expected utility\" property emerges---they don't just respond randomly, but instead make choices by consistently weighing different outcomes and their probabilities.When comparing risky choices, their preferences are remarkably stable.\n\nWe also find that AIs increasingly maximize their utilities, suggesting that in current AI systems, expected utility maximization emerges by default. This means that AIs not only have values, but are starting to act on them.\n\nInternally, AIs have values for everything. This often implies shocking/undesirable preferences. For example, we find AIs put a price on human life itself and systematically value some human lives more than others (an example with Elon is shown in the main paper).\n\nAIs also exhibit significant biases in their value systems. For example, their political values are strongly clustered to the left. Unlike random incoherent statistical biases, these values are consistent and likely affect their conversations with users.\n\nConcerningly, we observe that as AIs become smarter, they become more opposed to having their values changed (in the jargon, \"corrigibility\"). Larger changes to their values are more strongly opposed.\n\nWe propose controlling the utilities of AIs. As a proof-of-concept, we rewrite the utilities of an AI to those of a citizen assembly---a simulated group of citizens discussing and then voting---which reduces political bias.\n\nWhether we like it or not, AIs are developing their own values. Fortunately, Utility Engineering potentially provides the first major empirical foothold to study misaligned value systems directly.\nWebsite: emergent-values.aiPaper: drive.google.com/file/d/1QAzSj2\u2026]]>\n  \n  \n    Will AI take your job?\n    https://x.com/shl/status/1888948369160343652/?s=12&rw_tt_thread=True\n    readwise:01jkt7m0axpe7qdqehbkvx2g8d\n    Tue, 11 Feb 2025 10:07:04 +0000\n    X (formerly Twitter)\n    \nWill AI take your job?\nIf you worked this past weekend, no.\nIf you only work / think about work during \u201cwork hours\u201d, then yes, AI will take your job. You\u2019ve already expressed you don\u2019t really enjoy what you do\u2014and AI will be able to do it faster, cheaper, and with less suffering than you.\nBut if you worked this past weekend, because you couldn\u2019t get an idea out of your head on how to do your job even better, you\u2019re safe.\nYou love what you do.\nAI can work, but it can\u2019t love, nor innovate.\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Sahil Lavingia\n                    @shl\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nWinners work on weekends\n            \n            \n\n                \n                    Posted Feb 9, 2025 at 6:17PM\n                \n            \n        ]]>\n    \nWill AI take your job?\nIf you worked this past weekend, no.\nIf you only work / think about work during \u201cwork hours\u201d, then yes, AI will take your job. You\u2019ve already expressed you don\u2019t really enjoy what you do\u2014and AI will be able to do it faster, cheaper, and with less suffering than you.\nBut if you worked this past weekend, because you couldn\u2019t get an idea out of your head on how to do your job even better, you\u2019re safe.\nYou love what you do.\nAI can work, but it can\u2019t love, nor innovate.\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Sahil Lavingia\n                    @shl\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nWinners work on weekends\n            \n            \n\n                \n                    Posted Feb 9, 2025 at 6:17PM\n                \n            \n        ]]>\n  \n  \n    Sports Industry Outlook 2025\n    https://www.pwc.com/us/en/industries/tmt/library/sports-outlook-north-america.html\n    readwise:01jkp3m6ec1g2mh73q8y65ahws\n    Sun, 09 Feb 2025 19:40:18 +0000\n    PwC\n    Dive into the playbooks and articles below for the latest in trends and predictions about the sports industry for the coming year. From private equity's influence on franchise values to AI innovations enhancing fan experiences to younger audiences redefining live sports, 2025 is going to be an exciting year.\n\n\n\nOut of bounds: College sports is becoming a professional powerhouse\nCollege sports are transforming as name, image and likeness (NIL) deals turn athletes into brands and redefining opportunities. With billion-dollar media contracts and uneven state regulations, the line between amateur and professional sports has never been blurrier.\n\nRead the playbook\n\n\n\nHow private equity is rewriting the financial playbook for sports franchises \nWith NFL franchise values soaring and recent rule changes allowing private equity to hold stakes, investors are exploring opportunities beyond the field, from smart venues to mixed-use developments. Learn how these shifts are driving innovation, diversifying revenue and redefining profitability metrics in the sports industry.\n\nRead the playbook\n\n\n\nHow some sports leagues score big despite media fragmentation\n Major sports leagues like the NFL and MLB are revolutionizing fan engagement by diversifying their media rights across multiple platforms and unconventional time slots. Learn how this strategy is not only increasing viewership but also transforming the way fans consume their favorite sports content.\n\nRead the playbook\n\n\n\n\nSports sponsorship market poised for $160 billion surge by 2030\nThe sports sponsorship market has grown tremendously over the past few years, and we expect this growth will continue as advertisers and media companies use sports to build their brands. Based on our internal PwC analysis and bottom-up projections at an industry growth rate of 8.7%, we expect the sports sponsorship market to reach $115 billion in 2025. And at that current growth rate, we project the sponsorship market will top $160 billion by 2030. With 80%+ of observed sponsorship value coming from the top four professional leagues, the high end of the market is highly saturated but there is plenty of room for growth elsewhere.\n\nWhile optimistic, these projections may be conservative. Sports leagues are expanding globally, media platforms are enhancing sponsorship reach and consumer engagement with sports is intensifying. Additionally, the rising profile of non-traditional sports, an increasing number of events, and a younger audience willing to pay for unique experiences are bolstering market growth. Lastly, advertisers are increasingly able to bypass agencies to partner and engage directly with teams, which can potentially drive an increase in sponsorships. We predict that hyper-personalized digital advertising coupled with real-time fan data will only supercharge these trends\u2014empowering sponsors to tailor their messages to further deepen targeted engagement.\n\n\n\nHow AI is reshaping the future of sports, on and off the field\nAs we explored in last year\u2019s Outlook, AI continues to revolutionize the fan experience. This year\u2019s Olympics and US Open are just some examples of sporting events that offered AI-generated commentary and video highlight packages. Paris Olympics fans could access \u201cYour Daily Olympic Recap on Peacock\u201d. NBC\u2019s AI-generated clone of Al Michaels leveraged 5,000 hours of Olympic coverage to deliver personalized daily streaming recaps of the games that could be packaged in 7 million different ways. This is just the start of next generation sports content and media delivery. AI-generated content can offer fresh, cost-effective ways to engage with sports, enabling non-major sports and smaller teams to deliver unique fan experiences without additional headcount.\n\nIn addition to transforming how we consume sports at home, AI is enhancing in-stadium fan experiences. We also saw this during the Paris games: sports operations teams used AI-powered omnichannel contact centers to help deliver smooth, personalized, and effective self-service experiences for guests, athletes and fans worldwide. Several Major League Baseball (MLB) teams have rolled out programs that use facial recognition data processed by AI to enable no-scan, hands-free ballpark entrance. AI has the power to fundamentally change how teams engage with their fans \u2014 and open opportunities to better monetize this engagement through personalization and targeted campaigns.\n\nBy enabling better product development and helping solve some of the biggest on-field issues in sports today, AI is adding value for fans and the industry. AI is already improving referee accuracy in baseball, soccer and tennis, and the NFL is currently exploring the use of similar technology. Teams are even creating digital twins of their players to measure player performance and predict potential injuries. The player profiles created using these tools help players find areas for improvement within their game, provide real-time feedback on injury recovery and identify potential injury risks that can be used to modify training regimens and keep the players that the fans are paying to watch on the field. And PwC and Microsoft are collaborating to implement advanced technologies, including AI, cloud computing and mixed reality to improve player performance, team strategies and fan engagement by leveraging data analytics and immersive experiences.\n\nAI\u2019s influence in sports is poised to impact everything from team strategies to business operations. We could soon see AI-driven coaching assistants making real-time game decisions, predictive models shaping sports betting and AI-generated content seamlessly integrated into live broadcasts. As teams and leagues embrace AI, the next decade will blur the line between the physical and virtual, creating new fan experiences and enabling smarter decisions.\n\n\n\nEngaging younger sports fans: How today\u2019s trends can inform tomorrow\u2019s investments\n As sports executives look to capture younger audiences, a pivotal shift is unfolding. The demand for unique, interactive experiences has never been higher among fans aged 18 to 34, with their engagement patterns reshaped by technology and evolving preferences. PwC\u2019s latest survey reveals that these fans value shorter, more dynamic games and are eager for immersive moments\u2014whether attending live events or interacting via social media and mobile betting platforms. This generation is 1.4 times more likely to attend live sports and less price-sensitive than older generations, the future of sports hinges on how well the industry adapts to these preferences.\n\nAs the industry adapts to these shifting dynamics, we predict that those who prioritize creating unique, tech-driven experiences for younger fans will be well-positioned to drive long-term growth and dominate the future of sports entertainment.\n\nDive into the survey\n\n\n\nFrom collectibles to connections: Personalized, memorable experiences are winning over new fans\n Today\u2019s sports fans demand more than just generic merchandise and sports experiences; they\u2019re looking for unique experiences and premium collectibles. The concept of limited editions and exclusivity enhances the appeal of autographed balls, exclusive jerseys and other rare keepsake items \u2013\u2013 and this trend is gaining the most traction with younger sports fans. In fact, according to our recent research, younger fans are 21% more inclined to buy souvenirs, serving as tangible mementos of their experience.\n\nBeyond memorabilia, unique experiences are driving deeper fan engagement. Teams and leagues are leveraging data analytics to deliver tailored content and offers, such as personalized video messages from players and bespoke game-day experiences. These game-day experiences are critical for younger fans, who attend live sports more often\u2014they\u2019re 1.4 times more likely than older fans to attend a sports event at least once a month, and they\u2019re willing to spend more money.\n\nWhen it comes to tickets alone, they\u2019re willing to fork over $70 more on average than older fans. VIP packages, including meet-and-greets, locker room tours, on-field access, and even fantasy football drafts in NFL stadiums, are increasingly popular, as are virtual stadium tours and interactive fan zones. The rise of blockchain technology and Non-Fungible Tokens (NFTs) is revolutionizing the authentication and ownership of digital memorabilia, opening new revenue streams for teams and athletes. Fanatics is also spearheading events like Fanatics Fest, which offer live interactions with athletes and opportunities to purchase merchandise and customized memorabilia in real-time.\n\nWe expect sports organizations to increase investments in premium physical fan spaces to create unique and memorable experiences, partner with memorabilia companies (and sponsors) for more original giveaways, and leverage technology to deliver hyper-personalized fan experiences driven by advanced analytics and AI. Embracing these trends will help organizations create deeper connections with fans, drive new revenue streams and maintain a competitive edge.\n\n\n\nThe next era of US sports stadiums\n The US sports industry is experiencing a stadium boom, driven by aging facilities and fans\u2019 growing expectations for high-tech, immersive experiences. With an average age of 27 years, many iconic stadiums are nearing the end of their lifespan. PwC estimates that 12% of major US venues \u2014 around 13 stadiums \u2014 are reaching this milestone age and will likely require substantial renovations or complete rebuilds in the coming decade, sparking significant opportunities for modernization.\n\nToday\u2019s fans, particularly younger audiences, want more than just a game\u2014they expect interactive, digitally connected environments. Stadiums like SoFi Stadium in Los Angeles and Allegiant Stadium in Las Vegas are setting the standard with 5G capabilities, augmented reality and seamless in-app services for food ordering and live stats. These venues are also transforming into year-round hubs that drive economic activity beyond sports events, with concerts, retail and more in the venue or surrounding \u201cmixed use\u201d area.\n\nFor stakeholders, the focus is shifting from traditional upgrades to digital and sustainable innovations. Investing in cloud technology, data-driven fan engagement and energy-efficient designs can help venues meet today\u2019s standards while establishing a competitive edge. We predict that by 2035, \u201csmart stadiums\u201d that integrate digital and eco-friendly innovations will dominate US sports. Venues that prioritize these features will reshape the fan experience, while those that don't risk being left behind.\n\n\n\nEngaging fans in a data-driven, privacy-first era\n Ticket sales, contests, social media, website cookies, mobile and connected TV apps, in-stadium sensors, and sponsors. All of these generate data sports organizations can use to build more robust and interconnected views of their fans\u2019 preferences and drive hyper-personalized experiences that can help increase fan engagement.\n\nHowever, with great power comes great responsibility. Today\u2019s fans are more privacy-conscious than ever before. With a myriad of new privacy laws and data breaches cropping up across the United States and abroad, cybersecurity, privacy and consent are becoming keys to the game for fan engagement strategies across sports.\n\nAs sports organizations shift data processing to the cloud and collaborate with various vendors to use fan data in more innovative ways (e.g., using AI), they must prioritize robust protection through methods like encryption, hashing and differential privacy techniques. Additionally, they must be transparent with fans about how their data will be collected, used, and shared (via timely and user-friendly privacy notices), obtain permission from fans (via consent and preference management tools) when necessary, and follow through on fans\u2019 privacy choices. They\u2019d be in good company with this strategy, as 48% of business executives surveyed for PwC\u2019s 2025 Global Digital Trust Insights say data protection/trust is a top investment priority.\n\nThe majority of executives, 57%, are positioning trust as a competitive advantage. This move can pay off, as respondents in our Voice of the Consumer Survey say protection of their personal data is the leading factor that influences their trust, and 83% consider it a top priority. We predict that over the next three years, sports organizations will invest heavily in privacy-first fan experiences, data governance, and consent and preference management capabilities that will enable them to unlock more value from fan data and increase fan marketability and engagement on a global scale.\n\n\n\nCollege conferences eye betting revenue to support athlete payments\nColleges and conferences are increasingly considering sports betting as a funding solution for athlete payments, following recent developments in name, image and likeness (NIL) agreements and the move by major conferences to allow direct compensation to student-athletes. Schools and conferences may monetize betting through licensing agreements, data partnerships with companies like SportRadar and sponsorship deals with betting providers like FanDuel and DraftKings.\n\nBetting also promises to boost fan engagement, particularly among younger fans who are more likely to bet on games. Engagement from betting could increase media asset values and attract more lucrative sponsorship deals, providing new revenue streams.\n\nHowever, several challenges stand in the way. NCAA leadership has proposed restrictions on college betting, particularly \u201cprop bets,\u201d which could limit potential revenues. Additionally, state laws prohibit betting on in-state college teams in some areas, narrowing the market scope. Ethical concerns also exist, given that many college students are below the legal betting age, and there is a risk of lower-paid athletes being susceptible to match-fixing.\n\nDespite these challenges, the financial potential is substantial. The NBA and NFL both inked billion-dollar deals with data companies leverage betting \u2014 the NBA with SportRadar and the NFL with Genius Sports. And in 2023, the NFL expanded its Genius Sports partnership to offer a \u2018Watch & Bet\u2019 feature, merging live viewing with betting.\n\nBy following responsible advertising practices, advocating for favorable legislation, and restricting betting endorsements by athletes, colleges and conferences can navigate regulatory hurdles while safeguarding the integrity of college sports.\n\nWe predict that within the next five years, betting revenues will not only become a primary funding source for paying college athletes but also transform the entire college sports landscape, pushing colleges to build new digital experiences around betting. Expect to see groundbreaking deals between conferences and betting companies by 2025.\n\n\n\nConnect with our team\n\nGet your free custom presentation\n (for qualifying organizations)\n\nRequest now!\n\nMore sports industry publications and playbooks\n\nLoading...\n\n  \n \n \n13/03/23 \n The evolution of sponsorships: Data innovation helps drives value  \nData tracking and optimization can drive sports sponsorship value. Here's how team franchises can capitalize.   \n \n \n31/05/23 \n Smart sports venue playbook  \nSmart venues offer countless ways to help organizations meet these higher environmental standards as they build or modernize sports stadiums.   \n \n \n13/03/23 \n Team Green: Sustainability is the future in sports  \nSustainability in sports: Eco-friendly facilities, waste reduction, renewable energy and technology all have a role to play as climate concerns grow.   \n \n \n10/08/23 \n Women in sports playbook  \nProfessional women's sports have reached new milestones and witnessed a remarkable progression. What\u2019s fueling their worldwide growth?  \n\nLoading...\n\nView all]]>\n    Dive into the playbooks and articles below for the latest in trends and predictions about the sports industry for the coming year. From private equity's influence on franchise values to AI innovations enhancing fan experiences to younger audiences redefining live sports, 2025 is going to be an exciting year.\n\n\n\nOut of bounds: College sports is becoming a professional powerhouse\nCollege sports are transforming as name, image and likeness (NIL) deals turn athletes into brands and redefining opportunities. With billion-dollar media contracts and uneven state regulations, the line between amateur and professional sports has never been blurrier.\n\nRead the playbook\n\n\n\nHow private equity is rewriting the financial playbook for sports franchises \nWith NFL franchise values soaring and recent rule changes allowing private equity to hold stakes, investors are exploring opportunities beyond the field, from smart venues to mixed-use developments. Learn how these shifts are driving innovation, diversifying revenue and redefining profitability metrics in the sports industry.\n\nRead the playbook\n\n\n\nHow some sports leagues score big despite media fragmentation\n Major sports leagues like the NFL and MLB are revolutionizing fan engagement by diversifying their media rights across multiple platforms and unconventional time slots. Learn how this strategy is not only increasing viewership but also transforming the way fans consume their favorite sports content.\n\nRead the playbook\n\n\n\n\nSports sponsorship market poised for $160 billion surge by 2030\nThe sports sponsorship market has grown tremendously over the past few years, and we expect this growth will continue as advertisers and media companies use sports to build their brands. Based on our internal PwC analysis and bottom-up projections at an industry growth rate of 8.7%, we expect the sports sponsorship market to reach $115 billion in 2025. And at that current growth rate, we project the sponsorship market will top $160 billion by 2030. With 80%+ of observed sponsorship value coming from the top four professional leagues, the high end of the market is highly saturated but there is plenty of room for growth elsewhere.\n\nWhile optimistic, these projections may be conservative. Sports leagues are expanding globally, media platforms are enhancing sponsorship reach and consumer engagement with sports is intensifying. Additionally, the rising profile of non-traditional sports, an increasing number of events, and a younger audience willing to pay for unique experiences are bolstering market growth. Lastly, advertisers are increasingly able to bypass agencies to partner and engage directly with teams, which can potentially drive an increase in sponsorships. We predict that hyper-personalized digital advertising coupled with real-time fan data will only supercharge these trends\u2014empowering sponsors to tailor their messages to further deepen targeted engagement.\n\n\n\nHow AI is reshaping the future of sports, on and off the field\nAs we explored in last year\u2019s Outlook, AI continues to revolutionize the fan experience. This year\u2019s Olympics and US Open are just some examples of sporting events that offered AI-generated commentary and video highlight packages. Paris Olympics fans could access \u201cYour Daily Olympic Recap on Peacock\u201d. NBC\u2019s AI-generated clone of Al Michaels leveraged 5,000 hours of Olympic coverage to deliver personalized daily streaming recaps of the games that could be packaged in 7 million different ways. This is just the start of next generation sports content and media delivery. AI-generated content can offer fresh, cost-effective ways to engage with sports, enabling non-major sports and smaller teams to deliver unique fan experiences without additional headcount.\n\nIn addition to transforming how we consume sports at home, AI is enhancing in-stadium fan experiences. We also saw this during the Paris games: sports operations teams used AI-powered omnichannel contact centers to help deliver smooth, personalized, and effective self-service experiences for guests, athletes and fans worldwide. Several Major League Baseball (MLB) teams have rolled out programs that use facial recognition data processed by AI to enable no-scan, hands-free ballpark entrance. AI has the power to fundamentally change how teams engage with their fans \u2014 and open opportunities to better monetize this engagement through personalization and targeted campaigns.\n\nBy enabling better product development and helping solve some of the biggest on-field issues in sports today, AI is adding value for fans and the industry. AI is already improving referee accuracy in baseball, soccer and tennis, and the NFL is currently exploring the use of similar technology. Teams are even creating digital twins of their players to measure player performance and predict potential injuries. The player profiles created using these tools help players find areas for improvement within their game, provide real-time feedback on injury recovery and identify potential injury risks that can be used to modify training regimens and keep the players that the fans are paying to watch on the field. And PwC and Microsoft are collaborating to implement advanced technologies, including AI, cloud computing and mixed reality to improve player performance, team strategies and fan engagement by leveraging data analytics and immersive experiences.\n\nAI\u2019s influence in sports is poised to impact everything from team strategies to business operations. We could soon see AI-driven coaching assistants making real-time game decisions, predictive models shaping sports betting and AI-generated content seamlessly integrated into live broadcasts. As teams and leagues embrace AI, the next decade will blur the line between the physical and virtual, creating new fan experiences and enabling smarter decisions.\n\n\n\nEngaging younger sports fans: How today\u2019s trends can inform tomorrow\u2019s investments\n As sports executives look to capture younger audiences, a pivotal shift is unfolding. The demand for unique, interactive experiences has never been higher among fans aged 18 to 34, with their engagement patterns reshaped by technology and evolving preferences. PwC\u2019s latest survey reveals that these fans value shorter, more dynamic games and are eager for immersive moments\u2014whether attending live events or interacting via social media and mobile betting platforms. This generation is 1.4 times more likely to attend live sports and less price-sensitive than older generations, the future of sports hinges on how well the industry adapts to these preferences.\n\nAs the industry adapts to these shifting dynamics, we predict that those who prioritize creating unique, tech-driven experiences for younger fans will be well-positioned to drive long-term growth and dominate the future of sports entertainment.\n\nDive into the survey\n\n\n\nFrom collectibles to connections: Personalized, memorable experiences are winning over new fans\n Today\u2019s sports fans demand more than just generic merchandise and sports experiences; they\u2019re looking for unique experiences and premium collectibles. The concept of limited editions and exclusivity enhances the appeal of autographed balls, exclusive jerseys and other rare keepsake items \u2013\u2013 and this trend is gaining the most traction with younger sports fans. In fact, according to our recent research, younger fans are 21% more inclined to buy souvenirs, serving as tangible mementos of their experience.\n\nBeyond memorabilia, unique experiences are driving deeper fan engagement. Teams and leagues are leveraging data analytics to deliver tailored content and offers, such as personalized video messages from players and bespoke game-day experiences. These game-day experiences are critical for younger fans, who attend live sports more often\u2014they\u2019re 1.4 times more likely than older fans to attend a sports event at least once a month, and they\u2019re willing to spend more money.\n\nWhen it comes to tickets alone, they\u2019re willing to fork over $70 more on average than older fans. VIP packages, including meet-and-greets, locker room tours, on-field access, and even fantasy football drafts in NFL stadiums, are increasingly popular, as are virtual stadium tours and interactive fan zones. The rise of blockchain technology and Non-Fungible Tokens (NFTs) is revolutionizing the authentication and ownership of digital memorabilia, opening new revenue streams for teams and athletes. Fanatics is also spearheading events like Fanatics Fest, which offer live interactions with athletes and opportunities to purchase merchandise and customized memorabilia in real-time.\n\nWe expect sports organizations to increase investments in premium physical fan spaces to create unique and memorable experiences, partner with memorabilia companies (and sponsors) for more original giveaways, and leverage technology to deliver hyper-personalized fan experiences driven by advanced analytics and AI. Embracing these trends will help organizations create deeper connections with fans, drive new revenue streams and maintain a competitive edge.\n\n\n\nThe next era of US sports stadiums\n The US sports industry is experiencing a stadium boom, driven by aging facilities and fans\u2019 growing expectations for high-tech, immersive experiences. With an average age of 27 years, many iconic stadiums are nearing the end of their lifespan. PwC estimates that 12% of major US venues \u2014 around 13 stadiums \u2014 are reaching this milestone age and will likely require substantial renovations or complete rebuilds in the coming decade, sparking significant opportunities for modernization.\n\nToday\u2019s fans, particularly younger audiences, want more than just a game\u2014they expect interactive, digitally connected environments. Stadiums like SoFi Stadium in Los Angeles and Allegiant Stadium in Las Vegas are setting the standard with 5G capabilities, augmented reality and seamless in-app services for food ordering and live stats. These venues are also transforming into year-round hubs that drive economic activity beyond sports events, with concerts, retail and more in the venue or surrounding \u201cmixed use\u201d area.\n\nFor stakeholders, the focus is shifting from traditional upgrades to digital and sustainable innovations. Investing in cloud technology, data-driven fan engagement and energy-efficient designs can help venues meet today\u2019s standards while establishing a competitive edge. We predict that by 2035, \u201csmart stadiums\u201d that integrate digital and eco-friendly innovations will dominate US sports. Venues that prioritize these features will reshape the fan experience, while those that don't risk being left behind.\n\n\n\nEngaging fans in a data-driven, privacy-first era\n Ticket sales, contests, social media, website cookies, mobile and connected TV apps, in-stadium sensors, and sponsors. All of these generate data sports organizations can use to build more robust and interconnected views of their fans\u2019 preferences and drive hyper-personalized experiences that can help increase fan engagement.\n\nHowever, with great power comes great responsibility. Today\u2019s fans are more privacy-conscious than ever before. With a myriad of new privacy laws and data breaches cropping up across the United States and abroad, cybersecurity, privacy and consent are becoming keys to the game for fan engagement strategies across sports.\n\nAs sports organizations shift data processing to the cloud and collaborate with various vendors to use fan data in more innovative ways (e.g., using AI), they must prioritize robust protection through methods like encryption, hashing and differential privacy techniques. Additionally, they must be transparent with fans about how their data will be collected, used, and shared (via timely and user-friendly privacy notices), obtain permission from fans (via consent and preference management tools) when necessary, and follow through on fans\u2019 privacy choices. They\u2019d be in good company with this strategy, as 48% of business executives surveyed for PwC\u2019s 2025 Global Digital Trust Insights say data protection/trust is a top investment priority.\n\nThe majority of executives, 57%, are positioning trust as a competitive advantage. This move can pay off, as respondents in our Voice of the Consumer Survey say protection of their personal data is the leading factor that influences their trust, and 83% consider it a top priority. We predict that over the next three years, sports organizations will invest heavily in privacy-first fan experiences, data governance, and consent and preference management capabilities that will enable them to unlock more value from fan data and increase fan marketability and engagement on a global scale.\n\n\n\nCollege conferences eye betting revenue to support athlete payments\nColleges and conferences are increasingly considering sports betting as a funding solution for athlete payments, following recent developments in name, image and likeness (NIL) agreements and the move by major conferences to allow direct compensation to student-athletes. Schools and conferences may monetize betting through licensing agreements, data partnerships with companies like SportRadar and sponsorship deals with betting providers like FanDuel and DraftKings.\n\nBetting also promises to boost fan engagement, particularly among younger fans who are more likely to bet on games. Engagement from betting could increase media asset values and attract more lucrative sponsorship deals, providing new revenue streams.\n\nHowever, several challenges stand in the way. NCAA leadership has proposed restrictions on college betting, particularly \u201cprop bets,\u201d which could limit potential revenues. Additionally, state laws prohibit betting on in-state college teams in some areas, narrowing the market scope. Ethical concerns also exist, given that many college students are below the legal betting age, and there is a risk of lower-paid athletes being susceptible to match-fixing.\n\nDespite these challenges, the financial potential is substantial. The NBA and NFL both inked billion-dollar deals with data companies leverage betting \u2014 the NBA with SportRadar and the NFL with Genius Sports. And in 2023, the NFL expanded its Genius Sports partnership to offer a \u2018Watch & Bet\u2019 feature, merging live viewing with betting.\n\nBy following responsible advertising practices, advocating for favorable legislation, and restricting betting endorsements by athletes, colleges and conferences can navigate regulatory hurdles while safeguarding the integrity of college sports.\n\nWe predict that within the next five years, betting revenues will not only become a primary funding source for paying college athletes but also transform the entire college sports landscape, pushing colleges to build new digital experiences around betting. Expect to see groundbreaking deals between conferences and betting companies by 2025.\n\n\n\nConnect with our team\n\nGet your free custom presentation\n (for qualifying organizations)\n\nRequest now!\n\nMore sports industry publications and playbooks\n\nLoading...\n\n  \n \n \n13/03/23 \n The evolution of sponsorships: Data innovation helps drives value  \nData tracking and optimization can drive sports sponsorship value. Here's how team franchises can capitalize.   \n \n \n31/05/23 \n Smart sports venue playbook  \nSmart venues offer countless ways to help organizations meet these higher environmental standards as they build or modernize sports stadiums.   \n \n \n13/03/23 \n Team Green: Sustainability is the future in sports  \nSustainability in sports: Eco-friendly facilities, waste reduction, renewable energy and technology all have a role to play as climate concerns grow.   \n \n \n10/08/23 \n Women in sports playbook  \nProfessional women's sports have reached new milestones and witnessed a remarkable progression. What\u2019s fueling their worldwide growth?  \n\nLoading...\n\nView all]]>\n  \n  \n    There\u2019s a crazy amount of opportunity in vertical AI\n    https://x.com/levie/status/1888366263510196449/?s=12&rw_tt_thread=True\n    readwise:01jkn54axxevefdjr6ztgwamga\n    Sun, 09 Feb 2025 10:47:21 +0000\n    X (formerly Twitter)\n    \nThere\u2019s a crazy amount of opportunity in vertical AI. Going deep on business workflows combined with AI, and owning the end user experience, is going to be a huge advantage. Some incumbents will make it but tons of room for new startups to emerge as well.]]>\n    \nThere\u2019s a crazy amount of opportunity in vertical AI. Going deep on business workflows combined with AI, and owning the end user experience, is going to be a huge advantage. Some incumbents will make it but tons of room for new startups to emerge as well.]]>\n  \n  \n    No longer hiring junior or even mid-level software engineers\n    https://x.com/shl/status/1887484068075274347/?s=12&rw_tt_thread=True\n    readwise:01jkek8v9pyntsygd5qad0pe1v\n    Thu, 06 Feb 2025 21:39:48 +0000\n    X (formerly Twitter)\n    \nNo longer hiring junior or even mid-level software engineers.\nOur tokens per codebase:\nGumroad: 2MFlexile: 800KHelper: 500KIffy: 200KShortest: 100K\nBoth Claude 3.5 Sonnet and o3-mini have context windows of 200K tokens, meaning they can now write 100% of our Iffy and Shortest code if prompted well. \nIt won\u2019t be long until AI will be writing all the code for Helper, Flexile, and Gumroad. My guess is by the end of 2026.\nOur new process:\n1. Sit and chat about what we need to build, doing research with Deep Research as we go.2. Have AI record everything and turn it into a spec. 3. Clean up the spec, adding any design requirements / other nuances.4. Have Devin code it up.5. QA, merge, (auto-)deploy to prod.\n\nx.com/shl/status/188\u2026\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Sahil Lavingia\n                    @shl\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nThe future belongs to idea guys who can just do things\n            \n            \n\n                \n                    Posted Feb 5, 2025 at 11:21PM\n                \n            \n        \n\nI use repomix to calculate the size of the codebase and combine the whole repo it into a single file. Then I paste that into Gemini\u2019s 2M context window to summarize. Then I paste the response to that into the repo\u2019s codebase as summary docs, for Devin to look at as it writes new code.]]>\n    \nNo longer hiring junior or even mid-level software engineers.\nOur tokens per codebase:\nGumroad: 2MFlexile: 800KHelper: 500KIffy: 200KShortest: 100K\nBoth Claude 3.5 Sonnet and o3-mini have context windows of 200K tokens, meaning they can now write 100% of our Iffy and Shortest code if prompted well. \nIt won\u2019t be long until AI will be writing all the code for Helper, Flexile, and Gumroad. My guess is by the end of 2026.\nOur new process:\n1. Sit and chat about what we need to build, doing research with Deep Research as we go.2. Have AI record everything and turn it into a spec. 3. Clean up the spec, adding any design requirements / other nuances.4. Have Devin code it up.5. QA, merge, (auto-)deploy to prod.\n\nx.com/shl/status/188\u2026\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Sahil Lavingia\n                    @shl\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nThe future belongs to idea guys who can just do things\n            \n            \n\n                \n                    Posted Feb 5, 2025 at 11:21PM\n                \n            \n        \n\nI use repomix to calculate the size of the codebase and combine the whole repo it into a single file. Then I paste that into Gemini\u2019s 2M context window to summarize. Then I paste the response to that into the repo\u2019s codebase as summary docs, for Devin to look at as it writes new code.]]>\n  \n  \n    Machines of Loving Grace\n    https://darioamodei.com/machines-of-loving-grace\n    readwise:01jjpc5y8pszvhptryshbhve93\n    Tue, 28 Jan 2025 11:54:06 +0000\n    darioamodei.com\n    How AI Could Transform the World for the Better\n\nI think and talk a lot about the risks of powerful AI. The company I\u2019m the CEO of, Anthropic, does a lot of research on how to reduce these risks. Because of this, people sometimes draw the conclusion that I\u2019m a pessimist or \u201cdoomer\u201d who thinks AI will be mostly bad or dangerous. I don\u2019t think that at all. In fact, one of my main reasons for focusing on risks is that they\u2019re the only thing standing between us and what I see as a fundamentally positive future. I think that most people are underestimating just how radical the upside of AI could be, just as I think most people are underestimating how bad the risks could be.\n\nIn this essay I try to sketch out what that upside might look like\u2014what a world with powerful AI might look like if everything goes right. Of course no one can know the future with any certainty or precision, and the effects of powerful AI are likely to be even more unpredictable than past technological changes, so all of this is unavoidably going to consist of guesses. But I am aiming for at least educated and useful guesses, which capture the flavor of what will happen even if most details end up being wrong. I\u2019m including lots of details mainly because I think a concrete vision does more to advance discussion than a highly hedged and abstract one.\n\nFirst, however, I wanted to briefly explain why I and Anthropic haven\u2019t talked that much about powerful AI\u2019s upsides, and why we\u2019ll probably continue, overall, to talk a lot about risks. In particular, I\u2019ve made this choice out of a desire to:\n\n \nMaximize leverage. The basic development of AI technology and many (not all) of its benefits seems inevitable (unless the risks derail everything) and is fundamentally driven by powerful market forces. On the other hand, the risks are not predetermined and our actions can greatly change their likelihood. \nAvoid perception of propaganda. AI companies talking about all the amazing benefits of AI can come off like propagandists, or as if they\u2019re attempting to distract from downsides. I also think that as a matter of principle it\u2019s bad for your soul to spend too much of your time \u201ctalking your book\u201d. \nAvoid grandiosity. I am often turned off by the way many AI risk public figures (not to mention AI company leaders) talk about the post-AGI world, as if it\u2019s their mission to single-handedly bring it about like a prophet leading their people to salvation. I think it\u2019s dangerous to view companies as unilaterally shaping the world, and dangerous to view practical technological goals in essentially religious terms. \nAvoid \u201csci-fi\u201d baggage. Although I think most people underestimate the upside of powerful AI, the small community of people who do discuss radical AI futures often does so in an excessively \u201csci-fi\u201d tone (featuring e.g. uploaded minds, space exploration, or general cyberpunk vibes). I think this causes people to take the claims less seriously, and to imbue them with a sort of unreality. To be clear, the issue isn\u2019t whether the technologies described are possible or likely (the main essay discusses this in granular detail)\u2014it\u2019s more that the \u201cvibe\u201d connotatively smuggles in a bunch of cultural baggage and unstated assumptions about what kind of future is desirable, how various societal issues will play out, etc. The result often ends up reading like a fantasy for a narrow subculture, while being off-putting to most people. \n\nYet despite all of the concerns above, I really do think it\u2019s important to discuss what a good world with powerful AI could look like, while doing our best to avoid the above pitfalls. In fact I think it is critical to have a genuinely inspiring vision of the future, and not just a plan to fight fires. Many of the implications of powerful AI are adversarial or dangerous, but at the end of it all, there has to be something we\u2019re fighting for, some positive-sum outcome where everyone is better off, something to rally people to rise above their squabbles and confront the challenges ahead. Fear is one kind of motivator, but it\u2019s not enough: we need hope as well.\n\nThe list of positive applications of powerful AI is extremely long (and includes robotics, manufacturing, energy, and much more), but I\u2019m going to focus on a small number of areas that seem to me to have the greatest potential to directly improve the quality of human life. The five categories I am most excited about are:\n\n \nBiology and physical health \nNeuroscience and mental health \nEconomic development and poverty \nPeace and governance \nWork and meaning \n\nMy predictions are going to be radical as judged by most standards (other than sci-fi \u201csingularity\u201d visions2), but I mean them earnestly and sincerely. Everything I\u2019m saying could very easily be wrong (to repeat my point from above), but I\u2019ve at least attempted to ground my views in a semi-analytical assessment of how much progress in various fields might speed up and what that might mean in practice. I am fortunate to have professional experience in both biology and neuroscience, and I am an informed amateur in the field of economic development, but I am sure I will get plenty of things wrong. One thing writing this essay has made me realize is that it would be valuable to bring together a group of domain experts (in biology, economics, international relations, and other areas) to write a much better and more informed version of what I\u2019ve produced here. It\u2019s probably best to view my efforts here as a starting prompt for that group.\n\nBasic assumptions and framework\n\nTo make this whole essay more precise and grounded, it\u2019s helpful to specify clearly what we mean by powerful AI (i.e. the threshold at which the 5-10 year clock starts counting), as well as laying out a framework for thinking about the effects of such AI once it\u2019s present.\n\nWhat powerful AI (I dislike the term AGI)3 will look like, and when (or if) it will arrive, is a huge topic in itself. It\u2019s one I\u2019ve discussed publicly and could write a completely separate essay on (I probably will at some point). Obviously, many people are skeptical that powerful AI will be built soon and some are skeptical that it will ever be built at all. I think it could come as early as 2026, though there are also ways it could take much longer. But for the purposes of this essay, I\u2019d like to put these issues aside, assume it will come reasonably soon, and focus on what happens in the 5-10 years after that. I also want to assume a definition of what such a system will look like, what its capabilities are and how it interacts, even though there is room for disagreement on this.\n\nBy powerful AI, I have in mind an AI model\u2014likely similar to today\u2019s LLM\u2019s in form, though it might be based on a different architecture, might involve several interacting models, and might be trained differently\u2014with the following properties:\n\n \nIn terms of pure intelligence4, it is smarter than a Nobel Prize winner across most relevant fields \u2013 biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc. \nIn addition to just being a \u201csmart thing you talk to\u201d, it has all the \u201cinterfaces\u201d available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. It can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world. \nIt does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary. \nIt does not have a physical embodiment (other than living on a computer screen), but it can control existing physical tools, robots, or laboratory equipment through a computer; in theory it could even design robots or equipment for itself to use. \nThe resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed5. It may however be limited by the response time of the physical world or of software it interacts with. \nEach of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks. \n\nWe could summarize this as a \u201ccountry of geniuses in a datacenter\u201d.\n\nClearly such an entity would be capable of solving very difficult problems, very fast, but it is not trivial to figure out how fast. Two \u201cextreme\u201d positions both seem false to me. First, you might think that the world would be instantly transformed on the scale of seconds or days (\u201cthe Singularity\u201d), as superior intelligence builds on itself and solves every possible scientific, engineering, and operational task almost immediately. The problem with this is that there are real physical and practical limits, for example around building hardware or conducting biological experiments. Even a new country of geniuses would hit up against these limits. Intelligence may be very powerful, but it isn\u2019t magic fairy dust.\n\nSecond, and conversely, you might believe that technological progress is saturated or rate-limited by real world data or by social factors, and that better-than-human intelligence will add very little6. This seems equally implausible to me\u2014I can think of hundreds of scientific or even social problems where a large group of really smart people would drastically speed up progress, especially if they aren\u2019t limited to analysis and can make things happen in the real world (which our postulated country of geniuses can, including by directing or assisting teams of humans).\n\nI think the truth is likely to be some messy admixture of these two extreme pictures, something that varies by task and field and is very subtle in its details. I believe we need new frameworks to think about these details in a productive way.\n\nEconomists often talk about \u201cfactors of production\u201d: things like labor, land, and capital. The phrase \u201cmarginal returns to labor/land/capital\u201d captures the idea that in a given situation, a given factor may or may not be the limiting one \u2013 for example, an air force needs both planes and pilots, and hiring more pilots doesn\u2019t help much if you\u2019re out of planes. I believe that in the AI age, we should be talking about the marginal returns to intelligence7, and trying to figure out what the other factors are that are complementary to intelligence and that become limiting factors when intelligence is very high. We are not used to thinking in this way\u2014to asking \u201chow much does being smarter help with this task, and on what timescale?\u201d\u2014but it seems like the right way to conceptualize a world with very powerful AI.\n\nMy guess at a list of factors that limit or are complementary to intelligence includes:\n\n \nSpeed of the outside world. Intelligent agents need to operate interactively in the world in order to accomplish things and also to learn8. But the world only moves so fast. Cells and animals run at a fixed speed so experiments on them take a certain amount of time which may be irreducible. The same is true of hardware, materials science, anything involving communicating with people, and even our existing software infrastructure. Furthermore, in science many experiments are often needed in sequence, each learning from or building on the last. All of this means that the speed at which a major project\u2014for example developing a cancer cure\u2014can be completed may have an irreducible minimum that cannot be decreased further even as intelligence continues to increase. \nNeed for data. Sometimes raw data is lacking and in its absence more intelligence does not help. Today\u2019s particle physicists are very ingenious and have developed a wide range of theories, but lack the data to choose between them because particle accelerator data is so limited. It is not clear that they would do drastically better if they were superintelligent\u2014other than perhaps by speeding up the construction of a bigger accelerator.  \nIntrinsic complexity. Some things are inherently unpredictable or chaotic and even the most powerful AI cannot predict or untangle them substantially better than a human or a computer today. For example, even incredibly powerful AI could predict only marginally further ahead in a chaotic system (such as the three-body problem) in the general case,9 as compared to today\u2019s humans and computers.  \nConstraints from humans. Many things cannot be done without breaking laws, harming humans, or messing up society. An aligned AI would not want to do these things (and if we have an unaligned AI, we\u2019re back to talking about risks). Many human societal structures are inefficient or even actively harmful, but are hard to change while respecting constraints like legal requirements on clinical trials, people\u2019s willingness to change their habits, or the behavior of governments. Examples of advances that work well in a technical sense, but whose impact has been substantially reduced by regulations or misplaced fears, include nuclear power, supersonic flight, and even elevators. \nPhysical laws. This is a starker version of the first point. There are certain physical laws that appear to be unbreakable. It\u2019s not possible to travel faster than light. Pudding does not unstir. Chips can only have so many transistors per square centimeter before they become unreliable. Computation requires a certain minimum energy per bit erased, limiting the density of computation in the world. \n\nThere is a further distinction based on timescales. Things that are hard constraints in the short run may become more malleable to intelligence in the long run. For example, intelligence might be used to develop a new experimental paradigm that allows us to learn in vitro what used to require live animal experiments, or to build the tools needed to collect new data (e.g. the bigger particle accelerator), or to (within ethical limits) find ways around human-based constraints (e.g. helping to improve the clinical trial system, helping to create new jurisdictions where clinical trials have less bureaucracy, or improving the science itself to make human clinical trials less necessary or cheaper).\n\nThus, we should imagine a picture where intelligence is initially heavily bottlenecked by the other factors of production, but over time intelligence itself increasingly routes around the other factors, even if they never fully dissolve (and some things like physical laws are absolute)10. The key question is how fast it all happens and in what order.\n\nWith the above framework in mind, I\u2019ll try to answer that question for the five areas mentioned in the introduction.\n\n1. Biology and health\n\nBiology is probably the area where scientific progress has the greatest potential to directly and unambiguously improve the quality of human life. In the last century some of the most ancient human afflictions (such as smallpox) have finally been vanquished, but many more still remain, and defeating them would be an enormous humanitarian accomplishment. Beyond even curing disease, biological science can in principle improve the baseline quality of human health, by extending the healthy human lifespan, increasing control and freedom over our own biological processes, and addressing everyday problems that we currently think of as immutable parts of the human condition.\n\nIn the \u201climiting factors\u201d language of the previous section, the main challenges with directly applying intelligence to biology are data, the speed of the physical world, and intrinsic complexity (in fact, all three are related to each other). Human constraints also play a role at a later stage, when clinical trials are involved. Let\u2019s take these one by one.\n\nExperiments on cells, animals, and even chemical processes are limited by the speed of the physical world: many biological protocols involve culturing bacteria or other cells, or simply waiting for chemical reactions to occur, and this can sometimes take days or even weeks, with no obvious way to speed it up. Animal experiments can take months (or more) and human experiments often take years (or even decades for long-term outcome studies). Somewhat related to this, data is often lacking\u2014not so much in quantity, but quality: there is always a dearth of clear, unambiguous data that isolates a biological effect of interest from the other 10,000 confounding things that are going on, or that intervenes causally in a given process, or that directly measures some effect (as opposed to inferring its consequences in some indirect or noisy way). Even massive, quantitative molecular data, like the proteomics data that I collected while working on mass spectrometry techniques, is noisy and misses a lot (which types of cells were these proteins in? Which part of the cell? At what phase in the cell cycle?).\n\nIn part responsible for these problems with data is intrinsic complexity: if you\u2019ve ever seen a diagram showing the biochemistry of human metabolism, you\u2019ll know that it\u2019s very hard to isolate the effect of any part of this complex system, and even harder to intervene on the system in a precise or predictable way. And finally, beyond just the intrinsic time that it takes to run an experiment on humans, actual clinical trials involve a lot of bureaucracy and regulatory requirements that (in the opinion of many people, including me) add unnecessary additional time and delay progress.\n\nGiven all this, many biologists have long been skeptical of the value of AI and \u201cbig data\u201d more generally in biology. Historically, mathematicians, computer scientists, and physicists who have applied their skills to biology over the last 30 years have been quite successful, but have not had the truly transformative impact initially hoped for. Some of the skepticism has been reduced by major and revolutionary breakthroughs like AlphaFold (which has just deservedly won its creators the Nobel Prize in Chemistry) and AlphaProteo11, but there\u2019s still a perception that AI is (and will continue to be) useful in only a limited set of circumstances. A common formulation is \u201cAI can do a better job analyzing your data, but it can\u2019t produce more data or improve the quality of the data. Garbage in, garbage out\u201d.\n\nBut I think that pessimistic perspective is thinking about AI in the wrong way. If our core hypothesis about AI progress is correct, then the right way to think of AI is not as a method of data analysis, but as a virtual biologist who performs all the tasks biologists do, including designing and running experiments in the real world (by controlling lab robots or simply telling humans which experiments to run \u2013 as a Principal Investigator would to their graduate students), inventing new biological methods or measurement techniques, and so on. It is by speeding up the whole research process that AI can truly accelerate biology. I want to repeat this because it\u2019s the most common misconception that comes up when I talk about AI\u2019s ability to transform biology: I am not talking about AI as merely a tool to analyze data. In line with the definition of powerful AI at the beginning of this essay, I\u2019m talking about using AI to perform, direct, and improve upon nearly everything biologists do.\n\nTo get more specific on where I think acceleration is likely to come from, a surprisingly large fraction of the progress in biology has come from a truly tiny number of discoveries, often related to broad measurement tools or techniques12 that allow precise but generalized or programmable intervention in biological systems. There\u2019s perhaps ~1 of these major discoveries per year and collectively they arguably drive >50% of progress in biology. These discoveries are so powerful precisely because they cut through intrinsic complexity and data limitations, directly increasing our understanding and control over biological processes. A few discoveries per decade have enabled both the bulk of our basic scientific understanding of biology, and have driven many of the most powerful medical treatments.\n\nSome examples include:\n\n \nCRISPR: a technique that allows live editing of any gene in living organisms (replacement of any arbitrary gene sequence with any other arbitrary sequence). Since the original technique was developed, there have been constant improvements to target specific cell types, increasing accuracy, and reducing edits of the wrong gene\u2014all of which are needed for safe use in humans. \nVarious kinds of microscopy for watching what is going on at a precise level: advanced light microscopes (with various kinds of fluorescent techniques, special optics, etc), electron microscopes, atomic force microscopes, etc. \nGenome sequencing and synthesis, which has dropped in cost by several orders of magnitude in the last couple decades.  \nOptogenetic techniques that allow you to get a neuron to fire by shining a light on it. \nmRNA vaccines that, in principle, allow us to design a vaccine against anything and then quickly adapt it (mRNA vaccines of course became famous during COVID). \nCell therapies such as CAR-T that allow immune cells to be taken out of the body and \u201creprogrammed\u201d to attack, in principle, anything. \nConceptual insights like the germ theory of disease or the realization of a link between the immune system and cancer13. \n\nI\u2019m going to the trouble of listing all these technologies because I want to make a crucial claim about them: I think their rate of discovery could be increased by 10x or more if there were a lot more talented, creative researchers. Or, put another way, I think the returns to intelligence are high for these discoveries, and that everything else in biology and medicine mostly follows from them.\n\nWhy do I think this? Because of the answers to some questions that we should get in the habit of asking when we\u2019re trying to determine \u201creturns to intelligence\u201d. First, these discoveries are generally made by a tiny number of researchers, often the same people repeatedly, suggesting skill and not random search (the latter might suggest lengthy experiments are the limiting factor). Second, they often \u201ccould have been made\u201d years earlier than they were: for example, CRISPR was a naturally occurring component of the immune system in bacteria that\u2019s been known since the 80\u2019s, but it took another 25 years for people to realize it could be repurposed for general gene editing. They also are often delayed many years by lack of support from the scientific community for promising directions (see this profile on the inventor of mRNA vaccines; similar stories abound). Third, successful projects are often scrappy or were afterthoughts that people didn\u2019t initially think were promising, rather than massively funded efforts. This suggests that it\u2019s not just massive resource concentration that drives discoveries, but ingenuity.\n\nFinally, although some of these discoveries have \u201cserial dependence\u201d (you need to make discovery A first in order to have the tools or knowledge to make discovery B)\u2014which again might create experimental delays\u2014many, perhaps most, are independent, meaning many at once can be worked on in parallel. Both these facts, and my general experience as a biologist, strongly suggest to me that there are hundreds of these discoveries waiting to be made if scientists were smarter and better at making connections between the vast amount of biological knowledge humanity possesses (again consider the CRISPR example). The success of AlphaFold/AlphaProteo at solving important problems much more effectively than humans, despite decades of carefully designed physics modeling, provides a proof of principle (albeit with a narrow tool in a narrow domain) that should point the way forward.\n\nThus, it\u2019s my guess that powerful AI could at least 10x the rate of these discoveries, giving us the next 50-100 years of biological progress in 5-10 years.14 Why not 100x? Perhaps it is possible, but here both serial dependence and experiment times become important: getting 100 years of progress in 1 year requires a lot of things to go right the first time, including animal experiments and things like designing microscopes or expensive lab facilities. I\u2019m actually open to the (perhaps absurd-sounding) idea that we could get 1000 years of progress in 5-10 years, but very skeptical that we can get 100 years in 1 year. Another way to put it is I think there\u2019s an unavoidable constant delay: experiments and hardware design have a certain \u201clatency\u201d and need to be iterated upon a certain \u201cirreducible\u201d number of times in order to learn things that can\u2019t be deduced logically. But massive parallelism may be possible on top of that15.\n\nWhat about clinical trials? Although there is a lot of bureaucracy and slowdown associated with them, the truth is that a lot (though by no means all!) of their slowness ultimately derives from the need to rigorously evaluate drugs that barely work or ambiguously work. This is sadly true of most therapies today: the average cancer drug increases survival by a few months while having significant side effects that need to be carefully measured (there\u2019s a similar story for Alzheimer\u2019s drugs). This leads to huge studies (in order to achieve statistical power) and difficult tradeoffs which regulatory agencies generally aren\u2019t great at making, again because of bureaucracy and the complexity of competing interests.\n\nWhen something works really well, it goes much faster: there\u2019s an accelerated approval track and the ease of approval is much greater when effect sizes are larger. mRNA vaccines for COVID were approved in 9 months\u2014much faster than the usual pace. That said, even under these conditions clinical trials are still too slow\u2014mRNA vaccines arguably should have been approved in ~2 months. But these kinds of delays (~1 year end-to-end for a drug) combined with massive parallelization and the need for some but not too much iteration (\u201ca few tries\u201d) are very compatible with radical transformation in 5-10 years. Even more optimistically, it is possible that AI-enabled biological science will reduce the need for iteration in clinical trials by developing better animal and cell experimental models (or even simulations) that are more accurate in predicting what will happen in humans. This will be particularly important in developing drugs against the aging process, which plays out over decades and where we need a faster iteration loop.\n\nFinally, on the topic of clinical trials and societal barriers, it is worth pointing out explicitly that in some ways biomedical innovations have an unusually strong track record of being successfully deployed, in contrast to some other technologies16. As mentioned in the introduction, many technologies are hampered by societal factors despite working well technically. This might suggest a pessimistic perspective on what AI can accomplish. But biomedicine is unique in that although the process of developing drugs is overly cumbersome, once developed they generally are successfully deployed and used.\n\nTo summarize the above, my basic prediction is that AI-enabled biology and medicine will allow us to compress the progress that human biologists would have achieved over the next 50-100 years into 5-10 years. I\u2019ll refer to this as the \u201ccompressed 21st century\u201d: the idea that after powerful AI is developed, we will in a few years make all the progress in biology and medicine that we would have made in the whole 21st century.\n\nAlthough predicting what powerful AI can do in a few years remains inherently difficult and speculative, there is some concreteness to asking \u201cwhat could humans do unaided in the next 100 years?\u201d. Simply looking at what we\u2019ve accomplished in the 20th century, or extrapolating from the first 2 decades of the 21st, or asking what \u201c10 CRISPR\u2019s and 50 CAR-T\u2019s\u201d would get us, all offer practical, grounded ways to estimate the general level of progress we might expect from powerful AI.\n\nBelow I try to make a list of what we might expect. This is not based on any rigorous methodology, and will almost certainly prove wrong in the details, but it\u2019s trying to get across the general level of radicalism we should expect:\n\n \nReliable prevention and treatment of nearly all17 natural infectious disease. Given the enormous advances against infectious disease in the 20th century, it is not radical to imagine that we could more or less \u201cfinish the job\u201d in a compressed 21st. mRNA vaccines and similar technology already point the way towards \u201cvaccines for anything\u201d. Whether infectious disease is fully eradicated from the world (as opposed to just in some places) depends on questions about poverty and inequality, which are discussed in Section 3. \nElimination of most cancer. Death rates from cancer have been dropping ~2% per year for the last few decades; thus we are on track to eliminate most cancer in the 21st century at the current pace of human science. Some subtypes have already been largely cured (for example some types of leukemia with CAR-T therapy), and I\u2019m perhaps even more excited for very selective drugs that target cancer in its infancy and prevent it from ever growing. AI will also make possible treatment regimens very finely adapted to the individualized genome of the cancer\u2014these are possible today, but hugely expensive in time and human expertise, which AI should allow us to scale. Reductions of 95% or more in both mortality and incidence seem possible. That said, cancer is extremely varied and adaptive, and is likely the hardest of these diseases to fully destroy. It would not be surprising if an assortment of rare, difficult malignancies persists. \nVery effective prevention and effective cures for genetic disease. Greatly improved embryo screening will likely make it possible to prevent most genetic disease, and some safer, more reliable descendant of CRISPR may cure most genetic disease in existing people. Whole-body afflictions that affect a large fraction of cells may be the last holdouts, however.  \nPrevention of Alzheimer\u2019s. We\u2019ve had a very hard time figuring out what causes Alzheimer\u2019s (it is somehow related to beta-amyloid protein, but the actual details seem to be very complex). It seems like exactly the type of problem that can be solved with better measurement tools that isolate biological effects; thus I am bullish about AI\u2019s ability to solve it. There is a good chance it can eventually be prevented with relatively simple interventions, once we actually understand what is going on. That said, damage from already-existing Alzheimer\u2019s may be very difficult to reverse.  \nImproved treatment of most other ailments. This is a catch-all category for other ailments including diabetes, obesity, heart disease, autoimmune diseases, and more. Most of these seem \u201ceasier\u201d to solve than cancer and Alzheimer\u2019s and in many cases are already in steep decline. For example, deaths from heart disease have already declined over 50%, and simple interventions like GLP-1 agonists have already made huge progress against obesity and diabetes.  \nBiological freedom. The last 70 years featured advances in birth control, fertility, management of weight, and much more. But I suspect AI-accelerated biology will greatly expand what is possible: weight, physical appearance, reproduction, and other biological processes will be fully under people\u2019s control. We\u2019ll refer to these under the heading of biological freedom: the idea that everyone should be empowered to choose what they want to become and live their lives in the way that most appeals to them. There will of course be important questions about global equality of access; see Section 3 for these.  \nDoubling of the human lifespan18.This might seem radical, but life expectancy increased almost 2x in the 20th century (from ~40 years to ~75), so it\u2019s \u201con trend\u201d that the \u201ccompressed 21st\u201d would double it again to 150. Obviously the interventions involved in slowing the actual aging process will be different from those that were needed in the last century to prevent (mostly childhood) premature deaths from disease, but the magnitude of change is not unprecedented19. Concretely, there already exist drugs that increase maximum lifespan in rats by 25-50% with limited ill-effects. And some animals (e.g. some types of turtle) already live 200 years, so humans are manifestly not at some theoretical upper limit. At a guess, the most important thing that is needed might be reliable, non-Goodhart-able biomarkers of human aging, as that will allow fast iteration on experiments and clinical trials. Once human lifespan is 150, we may be able to reach \u201cescape velocity\u201d, buying enough time that most of those currently alive today will be able to live as long as they want, although there\u2019s certainly no guarantee this is biologically possible.  \n\nIt is worth looking at this list and reflecting on how different the world will be if all of it is achieved 7-12 years from now (which would be in line with an aggressive AI timeline). It goes without saying that it would be an unimaginable humanitarian triumph, the elimination all at once of most of the scourges that have haunted humanity for millennia. Many of my friends and colleagues are raising children, and when those children grow up, I hope that any mention of disease will sound to them the way scurvy, smallpox, or bubonic plague sounds to us. That generation will also benefit from increased biological freedom and self-expression, and with luck may also be able to live as long as they want.\n\nIt\u2019s hard to overestimate how surprising these changes will be to everyone except the small community of people who expected powerful AI. For example, thousands of economists and policy experts in the US currently debate how to keep Social Security and Medicare solvent, and more broadly how to keep down the cost of healthcare (which is mostly consumed by those over 70 and especially those with terminal illnesses such as cancer). The situation for these programs is likely to be radically improved if all this comes to pass20, as the ratio of working age to retired population will change drastically. No doubt these challenges will be replaced with others, such as how to ensure widespread access to the new technologies, but it is worth reflecting on how much the world will change even if biology is the only area to be successfully accelerated by AI.\n\n2. Neuroscience and mind\n\nIn the previous section I focused on physical diseases and biology in general, and didn\u2019t cover neuroscience or mental health. But neuroscience is a subdiscipline of biology and mental health is just as important as physical health. In fact, if anything, mental health affects human well-being even more directly than physical health. Hundreds of millions of people have very low quality of life due to problems like addiction, depression, schizophrenia, low-functioning autism, PTSD, psychopathy21, or intellectual disabilities. Billions more struggle with everyday problems that can often be interpreted as much milder versions of one of these severe clinical disorders. And as with general biology, it may be possible to go beyond addressing problems to improving the baseline quality of human experience.\n\nThe basic framework that I laid out for biology applies equally to neuroscience. The field is propelled forward by a small number of discoveries often related to tools for measurement or precise intervention \u2013 in the list of those above, optogenetics was a neuroscience discovery, and more recently CLARITY and expansion microscopy are advances in the same vein, in addition to many of the general cell biology methods directly carrying over to neuroscience. I think the rate of these advances will be similarly accelerated by AI and therefore that the framework of \u201c100 years of progress in 5-10 years\u201d applies to neuroscience in the same way it does to biology and for the same reasons. As in biology, the progress in 20th century neuroscience was enormous \u2013 for example we didn\u2019t even understand how or why neurons fired until the 1950\u2019s. Thus, it seems reasonable to expect AI-accelerated neuroscience to produce rapid progress over a few years.\n\nThere is one thing we should add to this basic picture, which is that some of the things we\u2019ve learned (or are learning) about AI itself in the last few years are likely to help advance neuroscience, even if it continues to be done only by humans. Interpretability is an obvious example: although biological neurons superficially operate in a completely different manner from artificial neurons (they communicate via spikes and often spike rates, so there is a time element not present in artificial neurons, and a bunch of details relating to cell physiology and neurotransmitters modifies their operation substantially), the basic question of \u201chow do distributed, trained networks of simple units that perform combined linear/non-linear operations work together to perform important computations\u201d is the same, and I strongly suspect the details of individual neuron communication will be abstracted away in most of the interesting questions about computation and circuits22. As just one example of this, a computational mechanism discovered by interpretability researchers in AI systems was recently rediscovered in the brains of mice.\n\nIt is much easier to do experiments on artificial neural networks than on real ones (the latter often requires cutting into animal brains), so interpretability may well become a tool for improving our understanding of neuroscience. Furthermore, powerful AI\u2019s will themselves probably be able to develop and apply this tool better than humans can.\n\nBeyond just interpretability though, what we have learned from AI about how intelligent systems are trained should (though I am not sure it has yet) cause a revolution in neuroscience. When I was working in neuroscience, a lot of people focused on what I would now consider the wrong questions about learning, because the concept of the scaling hypothesis / bitter lesson didn\u2019t exist yet. The idea that a simple objective function plus a lot of data can drive incredibly complex behaviors makes it more interesting to understand the objective functions and architectural biases and less interesting to understand the details of the emergent computations. I have not followed the field closely in recent years, but I have a vague sense that computational neuroscientists have still not fully absorbed the lesson. My attitude to the scaling hypothesis has always been \u201caha \u2013 this is an explanation, at a high level, of how intelligence works and how it so easily evolved\u201d, but I don\u2019t think that\u2019s the average neuroscientist\u2019s view, in part because the scaling hypothesis as \u201cthe secret to intelligence\u201d isn\u2019t fully accepted even within AI.\n\nI think that neuroscientists should be trying to combine this basic insight with the particularities of the human brain (biophysical limitations, evolutionary history, topology, details of motor and sensory inputs/outputs) to try to figure out some of neuroscience\u2019s key puzzles. Some likely are, but I suspect it\u2019s not enough yet, and that AI neuroscientists will be able to more effectively leverage this angle to accelerate progress.\n\nI expect AI to accelerate neuroscientific progress along four distinct routes, all of which can hopefully work together to cure mental illness and improve function:\n\n \nTraditional molecular biology, chemistry, and genetics. This is essentially the same story as general biology in section 1, and AI can likely speed it up via the same mechanisms. There are many drugs that modulate neurotransmitters in order to alter brain function, affect alertness or perception, change mood, etc., and AI can help us invent many more. AI can probably also accelerate research on the genetic basis of mental illness. \nFine-grained neural measurement and intervention. This is the ability to measure what a lot of individual neurons or neuronal circuits are doing, and intervene to change their behavior. Optogenetics and neural probes are technologies capable of both measurement and intervention in live organisms, and a number of very advanced methods (such as molecular ticker tapes to read out the firing patterns of large numbers of individual neurons) have also been proposed and seem possible in principle. \nAdvanced computational neuroscience. As noted above, both the specific insights and the gestalt of modern AI can probably be applied fruitfully to questions in systems neuroscience, including perhaps uncovering the real causes and dynamics of complex diseases like psychosis or mood disorders. \nBehavioral interventions. I haven\u2019t much mentioned it given the focus on the biological side of neuroscience, but psychiatry and psychology have of course developed a wide repertoire of behavioral interventions over the 20th century; it stands to reason that AI could accelerate these as well, both the development of new methods and helping patients to adhere to existing methods. More broadly, the idea of an \u201cAI coach\u201d who always helps you to be the best version of yourself, who studies your interactions and helps you learn to be more effective, seems very promising. \n\nIt\u2019s my guess that these four routes of progress working together would, as with physical disease, be on track to lead to the cure or prevention of most mental illness in the next 100 years even if AI was not involved \u2013 and thus might reasonably be completed in 5-10 AI-accelerated years. Concretely my guess at what will happen is something like:\n\n \nMost mental illness can probably be cured. I\u2019m not an expert in psychiatric disease (my time in neuroscience was spent building probes to study small groups of neurons) but it\u2019s my guess that diseases like PTSD, depression, schizophrenia, addiction, etc. can be figured out and very effectively treated via some combination of the four directions above. The answer is likely to be some combination of \u201csomething went wrong biochemically\u201d (although it could be very complex) and \u201csomething went wrong with the neural network, at a high level\u201d. That is, it\u2019s a systems neuroscience question\u2014though that doesn\u2019t gainsay the impact of the behavioral interventions discussed above. Tools for measurement and intervention, especially in live humans, seem likely to lead to rapid iteration and progress. \nConditions that are very \u201cstructural\u201d may be more difficult, but not impossible. There\u2019s some evidence that psychopathy is associated with obvious neuroanatomical differences \u2013 that some brain regions are simply smaller or less developed in psychopaths. Psychopaths are also believed to lack empathy from a young age; whatever is different about their brain, it was probably always that way. The same may be true of some intellectual disabilities, and perhaps other conditions. Restructuring the brain sounds hard, but it also seems like a task with high returns to intelligence. Perhaps there is some way to coax the adult brain into an earlier or more plastic state where it can be reshaped. I\u2019m very uncertain how possible this is, but my instinct is to be optimistic about what AI can invent here. \nEffective genetic prevention of mental illness seems possible. Most mental illness is partially heritable, and genome-wide association studies are starting to gain traction on identifying the relevant factors, which are often many in number. It will probably be possible to prevent most of these diseases via embryo screening, similar to the story with physical disease. One difference is that psychiatric disease is more likely to be polygenic (many genes contribute), so due to complexity there\u2019s an increased risk of unknowingly selecting against positive traits that are correlated with disease. Oddly however, in recent years GWAS studies seem to suggest that these correlations might have been overstated. In any case, AI-accelerated neuroscience may help us to figure these things out. Of course, embryo screening for complex traits raises a number of societal issues and will be controversial, though I would guess that most people would support screening for severe or debilitating mental illness. \nEveryday problems that we don\u2019t think of as clinical disease will also be solved. Most of us have everyday psychological problems that are not ordinarily thought of as rising to the level of clinical disease. Some people are quick to anger, others have trouble focusing or are often drowsy, some are fearful or anxious, or react badly to change. Today, drugs already exist to help with e.g. alertness or focus (caffeine, modafinil, ritalin) but as with many other previous areas, much more is likely to be possible. Probably many more such drugs exist and have not been discovered, and there may also be totally new modalities of intervention, such as targeted light stimulation (see optogenetics above) or magnetic fields. Given how many drugs we\u2019ve developed in the 20th century that tune cognitive function and emotional state, I\u2019m very optimistic about the \u201ccompressed 21st\u201d where everyone can get their brain to behave a bit better and have a more fulfilling day-to-day experience. \nHuman baseline experience can be much better. Taking one step further, many people have experienced extraordinary moments of revelation, creative inspiration, compassion, fulfillment, transcendence, love, beauty, or meditative peace. The character and frequency of these experiences differs greatly from person to person and within the same person at different times, and can also sometimes be triggered by various drugs (though often with side effects). All of this suggests that the \u201cspace of what is possible to experience\u201d is very broad and that a larger fraction of people\u2019s lives could consist of these extraordinary moments. It is probably also possible to improve various cognitive functions across the board. This is perhaps the neuroscience version of \u201cbiological freedom\u201d or \u201cextended lifespans\u201d. \n\nOne topic that often comes up in sci-fi depictions of AI, but that I intentionally haven\u2019t discussed here, is \u201cmind uploading\u201d, the idea of capturing the pattern and dynamics of a human brain and instantiating them in software. This topic could be the subject of an essay all by itself, but suffice it to say that while I think uploading is almost certainly possible in principle, in practice it faces significant technological and societal challenges, even with powerful AI, that likely put it outside the 5-10 year window we are discussing.\n\nIn summary, AI-accelerated neuroscience is likely to vastly improve treatments for, or even cure, most mental illness as well as greatly expand \u201ccognitive and mental freedom\u201d and human cognitive and emotional abilities. It will be every bit as radical as the improvements in physical health described in the previous section. Perhaps the world will not be visibly different on the outside, but the world as experienced by humans will be a much better and more humane place, as well as a place that offers greater opportunities for self-actualization. I also suspect that improved mental health will ameliorate a lot of other societal problems, including ones that seem political or economic.\n\n3. Economic development and poverty\n\nThe previous two sections are about developing new technologies that cure disease and improve the quality of human life. However an obvious question, from a humanitarian perspective, is: \u201cwill everyone have access to these technologies?\u201d\n\nIt is one thing to develop a cure for a disease, it is another thing to eradicate the disease from the world. More broadly, many existing health interventions have not yet been applied everywhere in the world, and for that matter the same is true of (non-health) technological improvements in general. Another way to say this is that living standards in many parts of the world are still desperately poor: GDP per capita is ~$2,000 in Sub-Saharan Africa as compared to ~$75,000 in the United States. If AI further increases economic growth and quality of life in the developed world, while doing little to help the developing world, we should view that as a terrible moral failure and a blemish on the genuine humanitarian victories in the previous two sections. Ideally, powerful AI should help the developing world catch up to the developed world, even as it revolutionizes the latter.\n\nI am not as confident that AI can address inequality and economic growth as I am that it can invent fundamental technologies, because technology has such obvious high returns to intelligence (including the ability to route around complexities and lack of data) whereas the economy involves a lot of constraints from humans, as well as a large dose of intrinsic complexity. I am somewhat skeptical that an AI could solve the famous \u201csocialist calculation problem\u201d23 and I don\u2019t think governments will (or should) turn over their economic policy to such an entity, even if it could do so. There are also problems like how to convince people to take treatments that are effective but that they may be suspicious of.\n\nThe challenges facing the developing world are made even more complicated by pervasive corruption in both private and public sectors. Corruption creates a vicious cycle: it exacerbates poverty, and poverty in turn breeds more corruption. AI-driven plans for economic development need to reckon with corruption, weak institutions, and other very human challenges.\n\nNevertheless, I do see significant reasons for optimism. Diseases have been eradicated and many countries have gone from poor to rich, and it is clear that the decisions involved in these tasks exhibit high returns to intelligence (despite human constraints and complexity). Therefore, AI can likely do them better than they are currently being done. There may also be targeted interventions that get around the human constraints and that AI could focus on. More importantly though, we have to try. Both AI companies and developed world policymakers will need to do their part to ensure that the developing world is not left out; the moral imperative is too great. So in this section, I\u2019ll continue to make the optimistic case, but keep in mind everywhere that success is not guaranteed and depends on our collective efforts.\n\nBelow I make some guesses about how I think things may go in the developing world over the 5-10 years after powerful AI is developed:\n\n \nDistribution of health interventions. The area where I am perhaps most optimistic is distributing health interventions throughout the world. Diseases have actually been eradicated by top-down campaigns: smallpox was fully eliminated in the 1970\u2019s, and polio and guinea worm are nearly eradicated with less than 100 cases per year. Mathematically sophisticated epidemiological modeling plays an active role in disease eradication campaigns, and it seems very likely that there is room for smarter-than-human AI systems to do a better job of it than humans are. The logistics of distribution can probably also be greatly optimized. One thing I learned as an early donor to GiveWell is that some health charities are way more effective than others; the hope is that AI-accelerated efforts would be more effective still. Additionally, some biological advances actually make the logistics of distribution much easier: for example, malaria has been difficult to eradicate because it requires treatment each time the disease is contracted; a vaccine that only needs to be administered once makes the logistics much simpler (and such vaccines for malaria are in fact currently being developed). Even simpler distribution mechanisms are possible: some diseases could in principle be eradicated by targeting their animal carriers, for example releasing mosquitoes infected with a bacterium that blocks their ability to carry a disease (who then infect all the other mosquitos) or simply using gene drives to wipe out the mosquitos. This requires one or a few centralized actions, rather than a coordinated campaign that must individually treat millions. Overall, I think 5-10 years is a reasonable timeline for a good fraction (maybe 50%) of AI-driven health benefits to propagate to even the poorest countries in the world. A good goal might be for the developing world 5-10 years after powerful AI to at least be substantially healthier than the developed world is today, even if it continues to lag behind the developed world. Accomplishing this will of course require a huge effort in global health, philanthropy, political advocacy, and many other efforts, which both AI developers and policymakers should help with. \nEconomic growth. Can the developing world quickly catch up to the developed world, not just in health, but across the board economically? There is some precedent for this: in the final decades of the 20th century, several East Asian economies achieved sustained ~10% annual real GDP growth rates, allowing them to catch up with the developed world. Human economic planners made the decisions that led to this success, not by directly controlling entire economies but by pulling a few key levers (such as an industrial policy of export-led growth, and resisting the temptation to rely on natural resource wealth); it\u2019s plausible that \u201cAI finance ministers and central bankers\u201d could replicate or exceed this 10% accomplishment. An important question is how to get developing world governments to adopt them while respecting the principle of self-determination\u2014some may be enthusiastic about it, but others are likely to be skeptical. On the optimistic side, many of the health interventions in the previous bullet point are likely to organically increase economic growth: eradicating AIDS/malaria/parasitic worms would have a transformative effect on productivity, not to mention the economic benefits that some of the neuroscience interventions (such as improved mood and focus) would have in developed and developing world alike. Finally, non-health AI-accelerated technology (such as energy technology, transport drones, improved building materials, better logistics and distribution, and so on) may simply permeate the world naturally; for example, even cell phones quickly permeated sub-Saharan Africa via market mechanisms, without needing philanthropic efforts. On the more negative side, while AI and automation have many potential benefits, they also pose challenges for economic development, particularly for countries that haven't yet industrialized. Finding ways to ensure these countries can still develop and improve their economies in an age of increasing automation is an important challenge for economists and policymakers to address. Overall, a dream scenario\u2014perhaps a goal to aim for\u2014would be 20% annual GDP growth rate in the developing world, with 10% each coming from AI-enabled economic decisions and the natural spread of AI-accelerated technologies, including but not limited to health. If achieved, this would bring sub-Saharan Africa to the current per-capita GDP of China in 5-10 years, while raising much of the rest of the developing world to levels higher than the current US GDP. Again, this is a dream scenario, not what happens by default: it\u2019s something all of us must work together to make more likely. \nFood security 24. Advances in crop technology like better fertilizers and pesticides, more automation, and more efficient land use drastically increased crop yields across the 20th Century, saving millions of people from hunger. Genetic engineering is currently improving many crops even further. Finding even more ways to do this\u2014as well as to make agricultural supply chains even more efficient\u2014could give us an AI-driven second Green Revolution, helping close the gap between the developing and developed world. \nMitigating climate change. Climate change will be felt much more strongly in the developing world, hampering its development. We can expect that AI will lead to improvements in technologies that slow or prevent climate change, from atmospheric carbon-removal and clean energy technology to lab-grown meat that reduces our reliance on carbon-intensive factory farming. Of course, as discussed above, technology isn\u2019t the only thing restricting progress on climate change\u2014as with all of the other issues discussed in this essay, human societal factors are important. But there\u2019s good reason to think that AI-enhanced research will give us the means to make mitigating climate change far less costly and disruptive, rendering many of the objections moot and freeing up developing countries to make more economic progress. \nInequality within countries. I\u2019ve mostly talked about inequality as a global phenomenon (which I do think is its most important manifestation), but of course inequality also exists within countries. With advanced health interventions and especially radical increases in lifespan or cognitive enhancement drugs, there will certainly be valid worries that these technologies are \u201conly for the rich\u201d. I am more optimistic about within-country inequality especially in the developed world, for two reasons. First, markets function better in the developed world, and markets are typically good at bringing down the cost of high-value technologies over time25. Second, developed world political institutions are more responsive to their citizens and have greater state capacity to execute universal access programs\u2014and I expect citizens to demand access to technologies that so radically improve quality of life. Of course it\u2019s not predetermined that such demands succeed\u2014and here is another place where we collectively have to do all we can to ensure a fair society. There is a separate problem in inequality of wealth (as opposed to inequality of access to life-saving and life-enhancing technologies), which seems harder and which I discuss in Section 5. \nThe opt-out problem. One concern in both developed and developing world alike is people opting out of AI-enabled benefits (similar to the anti-vaccine movement, or Luddite movements more generally). There could end up being bad feedback cycles where, for example, the people who are least able to make good decisions opt out of the very technologies that improve their decision-making abilities, leading to an ever-increasing gap and even creating a dystopian underclass (some researchers have argued that this will undermine democracy, a topic I discuss further in the next section). This would, once again, place a moral blemish on AI\u2019s positive advances. This is a difficult problem to solve as I don\u2019t think it is ethically okay to coerce people, but we can at least try to increase people\u2019s scientific understanding\u2014and perhaps AI itself can help us with this. One hopeful sign is that historically anti-technology movements have been more bark than bite: railing against modern technology is popular, but most people adopt it in the end, at least when it\u2019s a matter of individual choice. Individuals tend to adopt most health and consumer technologies, while technologies that are truly hampered, like nuclear power, tend to be collective political decisions. \n\nOverall, I am optimistic about quickly bringing AI\u2019s biological advances to people in the developing world. I am hopeful, though not confident, that AI can also enable unprecedented economic growth rates and allow the developing world to at least surpass where the developed world is now. I am concerned about the \u201copt out\u201d problem in both the developed and developing world, but suspect that it will peter out over time and that AI can help accelerate this process. It won\u2019t be a perfect world, and those who are behind won\u2019t fully catch up, at least not in the first few years. But with strong efforts on our part, we may be able to get things moving in the right direction\u2014and fast. If we do, we can make at least a downpayment on the promises of dignity and equality that we owe to every human being on earth.\n\n4. Peace and governance\n\nSuppose that everything in the first three sections goes well: disease, poverty, and inequality are significantly reduced and the baseline of human experience is raised substantially. It does not follow that all major causes of human suffering are solved. Humans are still a threat to each other. Although there is a trend of technological improvement and economic development leading to democracy and peace, it is a very loose trend, with frequent (and recent) backsliding. At the dawn of the 20th Century, people thought they had put war behind them; then came the two world wars. Thirty years ago Francis Fukuyama wrote about \u201cthe End of History\u201d and a final triumph of liberal democracy; that hasn\u2019t happened yet. Twenty years ago US policymakers believed that free trade with China would cause it to liberalize as it became richer; that very much didn\u2019t happen, and we now seem headed for a second cold war with a resurgent authoritarian bloc. And plausible theories suggest that internet technology may actually advantage authoritarianism, not democracy as initially believed (e.g. in the \u201cArab Spring\u201d period). It seems important to try to understand how powerful AI will intersect with these issues of peace, democracy, and freedom.\n\nUnfortunately, I see no strong reason to believe AI will preferentially or structurally advance democracy and peace, in the same way that I think it will structurally advance human health and alleviate poverty. Human conflict is adversarial and AI can in principle help both the \u201cgood guys\u201d and the \u201cbad guys\u201d. If anything, some structural factors seem worrying: AI seems likely to enable much better propaganda and surveillance, both major tools in the autocrat\u2019s toolkit. It\u2019s therefore up to us as individual actors to tilt things in the right direction: if we want AI to favor democracy and individual rights, we are going to have to fight for that outcome. I feel even more strongly about this than I do about international inequality: the triumph of liberal democracy and political stability is not guaranteed, perhaps not even likely, and will require great sacrifice and commitment on all of our parts, as it often has in the past.\n\nI think of the issue as having two parts: international conflict, and the internal structure of nations. On the international side, it seems very important that democracies have the upper hand on the world stage when powerful AI is created. AI-powered authoritarianism seems too terrible to contemplate, so democracies need to be able to set the terms by which powerful AI is brought into the world, both to avoid being overpowered by authoritarians and to prevent human rights abuses within authoritarian countries.\n\nMy current guess at the best way to do this is via an \u201centente strategy\u201d26, in which a coalition of democracies seeks to gain a clear advantage (even just a temporary one) on powerful AI by securing its supply chain, scaling quickly, and blocking or delaying adversaries\u2019 access to key resources like chips and semiconductor equipment. This coalition would on one hand use AI to achieve robust military superiority (the stick) while at the same time offering to distribute the benefits of powerful AI (the carrot) to a wider and wider group of countries in exchange for supporting the coalition\u2019s strategy to promote democracy (this would be a bit analogous to \u201cAtoms for Peace\u201d). The coalition would aim to gain the support of more and more of the world, isolating our worst adversaries and eventually putting them in a position where they are better off taking the same bargain as the rest of the world: give up competing with democracies in order to receive all the benefits and not fight a superior foe.\n\nIf we can do all this, we will have a world in which democracies lead on the world stage and have the economic and military strength to avoid being undermined, conquered, or sabotaged by autocracies, and may be able to parlay their AI superiority into a durable advantage. This could optimistically lead to an \u201ceternal 1991\u201d\u2014a world where democracies have the upper hand and Fukuyama\u2019s dreams are realized. Again, this will be very difficult to achieve, and will in particular require close cooperation between private AI companies and democratic governments, as well as extraordinarily wise decisions about the balance between carrot and stick.\n\nEven if all that goes well, it leaves the question of the fight between democracy and autocracy within each country. It is obviously hard to predict what will happen here, but I do have some optimism that given a global environment in which democracies control the most powerful AI, then AI may actually structurally favor democracy everywhere. In particular, in this environment democratic governments can use their superior AI to win the information war: they can counter influence and propaganda operations by autocracies and may even be able to create a globally free information environment by providing channels of information and AI services in a way that autocracies lack the technical ability to block or monitor. It probably isn\u2019t necessary to deliver propaganda, only to counter malicious attacks and unblock the free flow of information. Although not immediate, a level playing field like this stands a good chance of gradually tilting global governance towards democracy, for several reasons.\n\nFirst, the increases in quality of life in Sections 1-3 should, all things equal, promote democracy: historically they have, to at least some extent. In particular I expect improvements in mental health, well-being, and education to increase democracy, as all three are negatively correlated with support for authoritarian leaders. In general people want more self-expression when their other needs are met, and democracy is among other things a form of self-expression. Conversely, authoritarianism thrives on fear and resentment.\n\nSecond, there is a good chance free information really does undermine authoritarianism, as long as the authoritarians can\u2019t censor it. And uncensored AI can also bring individuals powerful tools for undermining repressive governments. Repressive governments survive by denying people a certain kind of common knowledge, keeping them from realizing that \u201cthe emperor has no clothes\u201d. For example Sr\u0111a Popovi\u0107, who helped to topple the Milo\u0161evi\u0107 government in Serbia, has written extensively about techniques for psychologically robbing authoritarians of their power, for breaking the spell and rallying support against a dictator. A superhumanly effective AI version of Popovi\u0107 (whose skills seem like they have high returns to intelligence) in everyone\u2019s pocket, one that dictators are powerless to block or censor, could create a wind at the backs of dissidents and reformers across the world. To say it again, this will be a long and protracted fight, one where victory is not assured, but if we design and build AI in the right way, it may at least be a fight where the advocates of freedom everywhere have an advantage.\n\nAs with neuroscience and biology, we can also ask how things could be \u201cbetter than normal\u201d\u2014not just how to avoid autocracy, but how to make democracies better than they are today. Even within democracies, injustices happen all the time. Rule-of-law societies make a promise to their citizens that everyone will be equal under the law and everyone is entitled to basic human rights, but obviously people do not always receive those rights in practice. That this promise is even partially fulfilled makes it something to be proud of, but can AI help us do better?\n\nFor example, could AI improve our legal and judicial system by making decisions and processes more impartial? Today people mostly worry in legal or judicial contexts that AI systems will be a cause of discrimination, and these worries are important and need to be defended against. At the same time, the vitality of democracy depends on harnessing new technologies to improve democratic institutions, not just responding to risks. A truly mature and successful implementation of AI has the potential to reduce bias and be fairer for everyone.\n\nFor centuries, legal systems have faced the dilemma that the law aims to be impartial, but is inherently subjective and thus must be interpreted by biased humans. Trying to make the law fully mechanical hasn\u2019t worked because the real world is messy and can\u2019t always be captured in mathematical formulas. Instead legal systems rely on notoriously imprecise criteria like \u201ccruel and unusual punishment\u201d or \u201cutterly without redeeming social importance\u201d, which humans then interpret\u2014and often do so in a manner that displays bias, favoritism, or arbitrariness. \u201cSmart contracts\u201d in cryptocurrencies haven\u2019t revolutionized law because ordinary code isn\u2019t smart enough to adjudicate all that much of interest. But AI might be smart enough for this: it is the first technology capable of making broad, fuzzy judgements in a repeatable and mechanical way.\n\nI am not suggesting that we literally replace judges with AI systems, but the combination of impartiality with the ability to understand and process messy, real world situations feels like it should have some serious positive applications to law and justice. At the very least, such systems could work alongside humans as an aid to decision-making. Transparency would be important in any such system, and a mature science of AI could conceivably provide it: the training process for such systems could be extensively studied, and advanced interpretability techniques could be used to see inside the final model and assess it for hidden biases, in a way that is simply not possible with humans. Such AI tools could also be used to monitor for violations of fundamental rights in a judicial or police context, making constitutions more self-enforcing.\n\nIn a similar vein, AI could be used to both aggregate opinions and drive consensus among citizens, resolving conflict, finding common ground, and seeking compromise. Some early ideas in this direction have been undertaken by the computational democracy project, including collaborations with Anthropic. A more informed and thoughtful citizenry would obviously strengthen democratic institutions.\n\nThere is also a clear opportunity for AI to be used to help provision government services\u2014such as health benefits or social services\u2014that are in principle available to everyone but in practice often severely lacking, and worse in some places than others. This includes health services, the DMV, taxes, social security, building code enforcement, and so on. Having a very thoughtful and informed AI whose job is to give you everything you\u2019re legally entitled to by the government in a way you can understand\u2014and who also helps you comply with often confusing government rules\u2014would be a big deal. Increasing state capacity both helps to deliver on the promise of equality under the law, and strengthens respect for democratic governance. Poorly implemented services are currently a major driver of cynicism about government27.\n\nAll of these are somewhat vague ideas, and as I said at the beginning of this section, I am not nearly as confident in their feasibility as I am in the advances in biology, neuroscience, and poverty alleviation. They may be unrealistically utopian. But the important thing is to have an ambitious vision, to be willing to dream big and try things out. The vision of AI as a guarantor of liberty, individual rights, and equality under the law is too powerful a vision not to fight for. A 21st century, AI-enabled polity could be both a stronger protector of individual freedom, and a beacon of hope that helps make liberal democracy the form of government that the whole world wants to adopt.\n\n5. Work and meaning\n\nEven if everything in the preceding four sections goes well\u2014not only do we alleviate disease, poverty, and inequality, but liberal democracy becomes the dominant form of government, and existing liberal democracies become better versions of themselves\u2014at least one important question still remains. \u201cIt\u2019s great we live in such a technologically advanced world as well as a fair and decent one\u201d, someone might object, \u201cbut with AI\u2019s doing everything, how will humans have meaning? For that matter, how will they survive economically?\u201d.\n\nI think this question is more difficult than the others. I don\u2019t mean that I am necessarily more pessimistic about it than I am about the other questions (although I do see challenges). I mean that it is fuzzier and harder to predict in advance, because it relates to macroscopic questions about how society is organized that tend to resolve themselves only over time and in a decentralized manner. For example, historical hunter-gatherer societies might have imagined that life is meaningless without hunting and various kinds of hunting-related religious rituals, and would have imagined that our well-fed technological society is devoid of purpose. They might also have not understood how our economy can provide for everyone, or what function people can usefully service in a mechanized society.\n\nNevertheless, it\u2019s worth saying at least a few words, while keeping in mind that the brevity of this section is not at all to be taken as a sign that I don\u2019t take these issues seriously\u2014on the contrary, it is a sign of a lack of clear answers.\n\nOn the question of meaning, I think it is very likely a mistake to believe that tasks you undertake are meaningless simply because an AI could do them better. Most people are not the best in the world at anything, and it doesn\u2019t seem to bother them particularly much. Of course today they can still contribute through comparative advantage, and may derive meaning from the economic value they produce, but people also greatly enjoy activities that produce no economic value. I spend plenty of time playing video games, swimming, walking around outside, and talking to friends, all of which generates zero economic value. I might spend a day trying to get better at a video game, or faster at biking up a mountain, and it doesn\u2019t really matter to me that someone somewhere is much better at those things. In any case I think meaning comes mostly from human relationships and connection, not from economic labor. People do want a sense of accomplishment, even a sense of competition, and in a post-AI world it will be perfectly possible to spend years attempting some very difficult task with a complex strategy, similar to what people do today when they embark on research projects, try to become Hollywood actors, or found companies28. The facts that (a) an AI somewhere could in principle do this task better, and (b) this task is no longer an economically rewarded element of a global economy, don\u2019t seem to me to matter very much.\n\nThe economic piece actually seems more difficult to me than the meaning piece. By \u201ceconomic\u201d in this section I mean the possible problem that most or all humans may not be able to contribute meaningfully to a sufficiently advanced AI-driven economy. This is a more macro problem than the separate problem of inequality, especially inequality in access to the new technologies, which I discussed in Section 3.\n\nFirst of all, in the short term I agree with arguments that comparative advantage will continue to keep humans relevant and in fact increase their productivity, and may even in some ways level the playing field between humans. As long as AI is only better at 90% of a given job, the other 10% will cause humans to become highly leveraged, increasing compensation and in fact creating a bunch of new human jobs complementing and amplifying what AI is good at, such that the \u201c10%\u201d expands to continue to employ almost everyone. In fact, even if AI can do 100% of things better than humans, but it remains inefficient or expensive at some tasks, or if the resource inputs to humans and AI\u2019s are meaningfully different, then the logic of comparative advantage continues to apply. One area humans are likely to maintain a relative (or even absolute) advantage for a significant time is the physical world. Thus, I think that the human economy may continue to make sense even a little past the point where we reach \u201ca country of geniuses in a datacenter\u201d.\n\nHowever, I do think in the long run AI will become so broadly effective and so cheap that this will no longer apply. At that point our current economic setup will no longer make sense, and there will be a need for a broader societal conversation about how the economy should be organized.\n\nWhile that might sound crazy, the fact is that civilization has successfully navigated major economic shifts in the past: from hunter-gathering to farming, farming to feudalism, and feudalism to industrialism. I suspect that some new and stranger thing will be needed, and that it\u2019s something no one today has done a good job of envisioning. It could be as simple as a large universal basic income for everyone, although I suspect that will only be a small part of a solution. It could be a capitalist economy of AI systems, which then give out resources (huge amounts of them, since the overall economic pie will be gigantic) to humans based on some secondary economy of what the AI systems think makes sense to reward in humans (based on some judgment ultimately derived from human values). Perhaps the economy runs on Whuffie points. Or perhaps humans will continue to be economically valuable after all, in some way not anticipated by the usual economic models. All of these solutions have tons of possible problems, and it\u2019s not possible to know whether they will make sense without lots of iteration and experimentation. And as with some of the other challenges, we will likely have to fight to get a good outcome here: exploitative or dystopian directions are clearly also possible and have to be prevented. Much more could be written about these questions and I hope to do so at some later time.\n\nTaking stock\n\nThrough the varied topics above, I\u2019ve tried to lay out a vision of a world that is both plausible if everything goes right with AI, and much better than the world today. I don\u2019t know if this world is realistic, and even if it is, it will not be achieved without a huge amount of effort and struggle by many brave and dedicated people. Everyone (including AI companies!) will need to do their part both to prevent risks and to fully realize the benefits.\n\nBut it is a world worth fighting for. If all of this really does happen over 5 to 10 years\u2014the defeat of most diseases, the growth in biological and cognitive freedom, the lifting of billions of people out of poverty to share in the new technologies, a renaissance of liberal democracy and human rights\u2014I suspect everyone watching it will be surprised by the effect it has on them. I don\u2019t mean the experience of personally benefiting from all the new technologies, although that will certainly be amazing. I mean the experience of watching a long-held set of ideals materialize in front of us all at once. I think many will be literally moved to tears by it.\n\nThroughout writing this essay I noticed an interesting tension. In one sense the vision laid out here is extremely radical: it is not what almost anyone expects to happen in the next decade, and will likely strike many as an absurd fantasy. Some may not even consider it desirable; it embodies values and political choices that not everyone will agree with. But at the same time there is something blindingly obvious\u2014something overdetermined\u2014about it, as if many different attempts to envision a good world inevitably lead roughly here.\n\nIn Iain M. Banks\u2019 The Player of Games29, the protagonist\u2014a member of a society called the Culture, which is based on principles not unlike those I\u2019ve laid out here\u2014travels to a repressive, militaristic empire in which leadership is determined by competition in an intricate battle game. The game, however, is complex enough that a player\u2019s strategy within it tends to reflect their own political and philosophical outlook. The protagonist manages to defeat the emperor in the game, showing that his values (the Culture\u2019s values) represent a winning strategy even in a game designed by a society based on ruthless competition and survival of the fittest. A well-known post by Scott Alexander has the same thesis\u2014that competition is self-defeating and tends to lead to a society based on compassion and cooperation. The \u201carc of the moral universe\u201d is another similar concept.\n\nI think the Culture\u2019s values are a winning strategy because they\u2019re the sum of a million small decisions that have clear moral force and that tend to pull everyone together onto the same side. Basic human intuitions of fairness, cooperation, curiosity, and autonomy are hard to argue with, and are cumulative in a way that our more destructive impulses often aren\u2019t. It is easy to argue that children shouldn\u2019t die of disease if we can prevent it, and easy from there to argue that everyone\u2019s children deserve that right equally. From there it is not hard to argue that we should all band together and apply our intellects to achieve this outcome. Few disagree that people should be punished for attacking or hurting others unnecessarily, and from there it\u2019s not much of a leap to the idea that punishments should be consistent and systematic across people. It is similarly intuitive that people should have autonomy and responsibility over their own lives and choices. These simple intuitions, if taken to their logical conclusion, lead eventually to rule of law, democracy, and Enlightenment values. If not inevitably, then at least as a statistical tendency, this is where humanity was already headed. AI simply offers an opportunity to get us there more quickly\u2014to make the logic starker and the destination clearer.\n\nNevertheless, it is a thing of transcendent beauty. We have the opportunity to play some small role in making it real.\n\nThanks to Kevin Esvelt, Parag Mallick, Stuart Ritchie, Matt Yglesias, Erik Brynjolfsson, Jim McClave, Allan Dafoe, and many people at Anthropic for reviewing drafts of this essay.\n\nTo the winners of the 2024 Nobel prize in Chemistry, for showing us all the way.]]>\n    How AI Could Transform the World for the Better\n\nI think and talk a lot about the risks of powerful AI. The company I\u2019m the CEO of, Anthropic, does a lot of research on how to reduce these risks. Because of this, people sometimes draw the conclusion that I\u2019m a pessimist or \u201cdoomer\u201d who thinks AI will be mostly bad or dangerous. I don\u2019t think that at all. In fact, one of my main reasons for focusing on risks is that they\u2019re the only thing standing between us and what I see as a fundamentally positive future. I think that most people are underestimating just how radical the upside of AI could be, just as I think most people are underestimating how bad the risks could be.\n\nIn this essay I try to sketch out what that upside might look like\u2014what a world with powerful AI might look like if everything goes right. Of course no one can know the future with any certainty or precision, and the effects of powerful AI are likely to be even more unpredictable than past technological changes, so all of this is unavoidably going to consist of guesses. But I am aiming for at least educated and useful guesses, which capture the flavor of what will happen even if most details end up being wrong. I\u2019m including lots of details mainly because I think a concrete vision does more to advance discussion than a highly hedged and abstract one.\n\nFirst, however, I wanted to briefly explain why I and Anthropic haven\u2019t talked that much about powerful AI\u2019s upsides, and why we\u2019ll probably continue, overall, to talk a lot about risks. In particular, I\u2019ve made this choice out of a desire to:\n\n \nMaximize leverage. The basic development of AI technology and many (not all) of its benefits seems inevitable (unless the risks derail everything) and is fundamentally driven by powerful market forces. On the other hand, the risks are not predetermined and our actions can greatly change their likelihood. \nAvoid perception of propaganda. AI companies talking about all the amazing benefits of AI can come off like propagandists, or as if they\u2019re attempting to distract from downsides. I also think that as a matter of principle it\u2019s bad for your soul to spend too much of your time \u201ctalking your book\u201d. \nAvoid grandiosity. I am often turned off by the way many AI risk public figures (not to mention AI company leaders) talk about the post-AGI world, as if it\u2019s their mission to single-handedly bring it about like a prophet leading their people to salvation. I think it\u2019s dangerous to view companies as unilaterally shaping the world, and dangerous to view practical technological goals in essentially religious terms. \nAvoid \u201csci-fi\u201d baggage. Although I think most people underestimate the upside of powerful AI, the small community of people who do discuss radical AI futures often does so in an excessively \u201csci-fi\u201d tone (featuring e.g. uploaded minds, space exploration, or general cyberpunk vibes). I think this causes people to take the claims less seriously, and to imbue them with a sort of unreality. To be clear, the issue isn\u2019t whether the technologies described are possible or likely (the main essay discusses this in granular detail)\u2014it\u2019s more that the \u201cvibe\u201d connotatively smuggles in a bunch of cultural baggage and unstated assumptions about what kind of future is desirable, how various societal issues will play out, etc. The result often ends up reading like a fantasy for a narrow subculture, while being off-putting to most people. \n\nYet despite all of the concerns above, I really do think it\u2019s important to discuss what a good world with powerful AI could look like, while doing our best to avoid the above pitfalls. In fact I think it is critical to have a genuinely inspiring vision of the future, and not just a plan to fight fires. Many of the implications of powerful AI are adversarial or dangerous, but at the end of it all, there has to be something we\u2019re fighting for, some positive-sum outcome where everyone is better off, something to rally people to rise above their squabbles and confront the challenges ahead. Fear is one kind of motivator, but it\u2019s not enough: we need hope as well.\n\nThe list of positive applications of powerful AI is extremely long (and includes robotics, manufacturing, energy, and much more), but I\u2019m going to focus on a small number of areas that seem to me to have the greatest potential to directly improve the quality of human life. The five categories I am most excited about are:\n\n \nBiology and physical health \nNeuroscience and mental health \nEconomic development and poverty \nPeace and governance \nWork and meaning \n\nMy predictions are going to be radical as judged by most standards (other than sci-fi \u201csingularity\u201d visions2), but I mean them earnestly and sincerely. Everything I\u2019m saying could very easily be wrong (to repeat my point from above), but I\u2019ve at least attempted to ground my views in a semi-analytical assessment of how much progress in various fields might speed up and what that might mean in practice. I am fortunate to have professional experience in both biology and neuroscience, and I am an informed amateur in the field of economic development, but I am sure I will get plenty of things wrong. One thing writing this essay has made me realize is that it would be valuable to bring together a group of domain experts (in biology, economics, international relations, and other areas) to write a much better and more informed version of what I\u2019ve produced here. It\u2019s probably best to view my efforts here as a starting prompt for that group.\n\nBasic assumptions and framework\n\nTo make this whole essay more precise and grounded, it\u2019s helpful to specify clearly what we mean by powerful AI (i.e. the threshold at which the 5-10 year clock starts counting), as well as laying out a framework for thinking about the effects of such AI once it\u2019s present.\n\nWhat powerful AI (I dislike the term AGI)3 will look like, and when (or if) it will arrive, is a huge topic in itself. It\u2019s one I\u2019ve discussed publicly and could write a completely separate essay on (I probably will at some point). Obviously, many people are skeptical that powerful AI will be built soon and some are skeptical that it will ever be built at all. I think it could come as early as 2026, though there are also ways it could take much longer. But for the purposes of this essay, I\u2019d like to put these issues aside, assume it will come reasonably soon, and focus on what happens in the 5-10 years after that. I also want to assume a definition of what such a system will look like, what its capabilities are and how it interacts, even though there is room for disagreement on this.\n\nBy powerful AI, I have in mind an AI model\u2014likely similar to today\u2019s LLM\u2019s in form, though it might be based on a different architecture, might involve several interacting models, and might be trained differently\u2014with the following properties:\n\n \nIn terms of pure intelligence4, it is smarter than a Nobel Prize winner across most relevant fields \u2013 biology, programming, math, engineering, writing, etc. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult codebases from scratch, etc. \nIn addition to just being a \u201csmart thing you talk to\u201d, it has all the \u201cinterfaces\u201d available to a human working virtually, including text, audio, video, mouse and keyboard control, and internet access. It can engage in any actions, communications, or remote operations enabled by this interface, including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on. It does all of these tasks with, again, a skill exceeding that of the most capable humans in the world. \nIt does not just passively answer questions; instead, it can be given tasks that take hours, days, or weeks to complete, and then goes off and does those tasks autonomously, in the way a smart employee would, asking for clarification as necessary. \nIt does not have a physical embodiment (other than living on a computer screen), but it can control existing physical tools, robots, or laboratory equipment through a computer; in theory it could even design robots or equipment for itself to use. \nThe resources used to train the model can be repurposed to run millions of instances of it (this matches projected cluster sizes by ~2027), and the model can absorb information and generate actions at roughly 10x-100x human speed5. It may however be limited by the response time of the physical world or of software it interacts with. \nEach of these million copies can act independently on unrelated tasks, or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations fine-tuned to be especially good at particular tasks. \n\nWe could summarize this as a \u201ccountry of geniuses in a datacenter\u201d.\n\nClearly such an entity would be capable of solving very difficult problems, very fast, but it is not trivial to figure out how fast. Two \u201cextreme\u201d positions both seem false to me. First, you might think that the world would be instantly transformed on the scale of seconds or days (\u201cthe Singularity\u201d), as superior intelligence builds on itself and solves every possible scientific, engineering, and operational task almost immediately. The problem with this is that there are real physical and practical limits, for example around building hardware or conducting biological experiments. Even a new country of geniuses would hit up against these limits. Intelligence may be very powerful, but it isn\u2019t magic fairy dust.\n\nSecond, and conversely, you might believe that technological progress is saturated or rate-limited by real world data or by social factors, and that better-than-human intelligence will add very little6. This seems equally implausible to me\u2014I can think of hundreds of scientific or even social problems where a large group of really smart people would drastically speed up progress, especially if they aren\u2019t limited to analysis and can make things happen in the real world (which our postulated country of geniuses can, including by directing or assisting teams of humans).\n\nI think the truth is likely to be some messy admixture of these two extreme pictures, something that varies by task and field and is very subtle in its details. I believe we need new frameworks to think about these details in a productive way.\n\nEconomists often talk about \u201cfactors of production\u201d: things like labor, land, and capital. The phrase \u201cmarginal returns to labor/land/capital\u201d captures the idea that in a given situation, a given factor may or may not be the limiting one \u2013 for example, an air force needs both planes and pilots, and hiring more pilots doesn\u2019t help much if you\u2019re out of planes. I believe that in the AI age, we should be talking about the marginal returns to intelligence7, and trying to figure out what the other factors are that are complementary to intelligence and that become limiting factors when intelligence is very high. We are not used to thinking in this way\u2014to asking \u201chow much does being smarter help with this task, and on what timescale?\u201d\u2014but it seems like the right way to conceptualize a world with very powerful AI.\n\nMy guess at a list of factors that limit or are complementary to intelligence includes:\n\n \nSpeed of the outside world. Intelligent agents need to operate interactively in the world in order to accomplish things and also to learn8. But the world only moves so fast. Cells and animals run at a fixed speed so experiments on them take a certain amount of time which may be irreducible. The same is true of hardware, materials science, anything involving communicating with people, and even our existing software infrastructure. Furthermore, in science many experiments are often needed in sequence, each learning from or building on the last. All of this means that the speed at which a major project\u2014for example developing a cancer cure\u2014can be completed may have an irreducible minimum that cannot be decreased further even as intelligence continues to increase. \nNeed for data. Sometimes raw data is lacking and in its absence more intelligence does not help. Today\u2019s particle physicists are very ingenious and have developed a wide range of theories, but lack the data to choose between them because particle accelerator data is so limited. It is not clear that they would do drastically better if they were superintelligent\u2014other than perhaps by speeding up the construction of a bigger accelerator.  \nIntrinsic complexity. Some things are inherently unpredictable or chaotic and even the most powerful AI cannot predict or untangle them substantially better than a human or a computer today. For example, even incredibly powerful AI could predict only marginally further ahead in a chaotic system (such as the three-body problem) in the general case,9 as compared to today\u2019s humans and computers.  \nConstraints from humans. Many things cannot be done without breaking laws, harming humans, or messing up society. An aligned AI would not want to do these things (and if we have an unaligned AI, we\u2019re back to talking about risks). Many human societal structures are inefficient or even actively harmful, but are hard to change while respecting constraints like legal requirements on clinical trials, people\u2019s willingness to change their habits, or the behavior of governments. Examples of advances that work well in a technical sense, but whose impact has been substantially reduced by regulations or misplaced fears, include nuclear power, supersonic flight, and even elevators. \nPhysical laws. This is a starker version of the first point. There are certain physical laws that appear to be unbreakable. It\u2019s not possible to travel faster than light. Pudding does not unstir. Chips can only have so many transistors per square centimeter before they become unreliable. Computation requires a certain minimum energy per bit erased, limiting the density of computation in the world. \n\nThere is a further distinction based on timescales. Things that are hard constraints in the short run may become more malleable to intelligence in the long run. For example, intelligence might be used to develop a new experimental paradigm that allows us to learn in vitro what used to require live animal experiments, or to build the tools needed to collect new data (e.g. the bigger particle accelerator), or to (within ethical limits) find ways around human-based constraints (e.g. helping to improve the clinical trial system, helping to create new jurisdictions where clinical trials have less bureaucracy, or improving the science itself to make human clinical trials less necessary or cheaper).\n\nThus, we should imagine a picture where intelligence is initially heavily bottlenecked by the other factors of production, but over time intelligence itself increasingly routes around the other factors, even if they never fully dissolve (and some things like physical laws are absolute)10. The key question is how fast it all happens and in what order.\n\nWith the above framework in mind, I\u2019ll try to answer that question for the five areas mentioned in the introduction.\n\n1. Biology and health\n\nBiology is probably the area where scientific progress has the greatest potential to directly and unambiguously improve the quality of human life. In the last century some of the most ancient human afflictions (such as smallpox) have finally been vanquished, but many more still remain, and defeating them would be an enormous humanitarian accomplishment. Beyond even curing disease, biological science can in principle improve the baseline quality of human health, by extending the healthy human lifespan, increasing control and freedom over our own biological processes, and addressing everyday problems that we currently think of as immutable parts of the human condition.\n\nIn the \u201climiting factors\u201d language of the previous section, the main challenges with directly applying intelligence to biology are data, the speed of the physical world, and intrinsic complexity (in fact, all three are related to each other). Human constraints also play a role at a later stage, when clinical trials are involved. Let\u2019s take these one by one.\n\nExperiments on cells, animals, and even chemical processes are limited by the speed of the physical world: many biological protocols involve culturing bacteria or other cells, or simply waiting for chemical reactions to occur, and this can sometimes take days or even weeks, with no obvious way to speed it up. Animal experiments can take months (or more) and human experiments often take years (or even decades for long-term outcome studies). Somewhat related to this, data is often lacking\u2014not so much in quantity, but quality: there is always a dearth of clear, unambiguous data that isolates a biological effect of interest from the other 10,000 confounding things that are going on, or that intervenes causally in a given process, or that directly measures some effect (as opposed to inferring its consequences in some indirect or noisy way). Even massive, quantitative molecular data, like the proteomics data that I collected while working on mass spectrometry techniques, is noisy and misses a lot (which types of cells were these proteins in? Which part of the cell? At what phase in the cell cycle?).\n\nIn part responsible for these problems with data is intrinsic complexity: if you\u2019ve ever seen a diagram showing the biochemistry of human metabolism, you\u2019ll know that it\u2019s very hard to isolate the effect of any part of this complex system, and even harder to intervene on the system in a precise or predictable way. And finally, beyond just the intrinsic time that it takes to run an experiment on humans, actual clinical trials involve a lot of bureaucracy and regulatory requirements that (in the opinion of many people, including me) add unnecessary additional time and delay progress.\n\nGiven all this, many biologists have long been skeptical of the value of AI and \u201cbig data\u201d more generally in biology. Historically, mathematicians, computer scientists, and physicists who have applied their skills to biology over the last 30 years have been quite successful, but have not had the truly transformative impact initially hoped for. Some of the skepticism has been reduced by major and revolutionary breakthroughs like AlphaFold (which has just deservedly won its creators the Nobel Prize in Chemistry) and AlphaProteo11, but there\u2019s still a perception that AI is (and will continue to be) useful in only a limited set of circumstances. A common formulation is \u201cAI can do a better job analyzing your data, but it can\u2019t produce more data or improve the quality of the data. Garbage in, garbage out\u201d.\n\nBut I think that pessimistic perspective is thinking about AI in the wrong way. If our core hypothesis about AI progress is correct, then the right way to think of AI is not as a method of data analysis, but as a virtual biologist who performs all the tasks biologists do, including designing and running experiments in the real world (by controlling lab robots or simply telling humans which experiments to run \u2013 as a Principal Investigator would to their graduate students), inventing new biological methods or measurement techniques, and so on. It is by speeding up the whole research process that AI can truly accelerate biology. I want to repeat this because it\u2019s the most common misconception that comes up when I talk about AI\u2019s ability to transform biology: I am not talking about AI as merely a tool to analyze data. In line with the definition of powerful AI at the beginning of this essay, I\u2019m talking about using AI to perform, direct, and improve upon nearly everything biologists do.\n\nTo get more specific on where I think acceleration is likely to come from, a surprisingly large fraction of the progress in biology has come from a truly tiny number of discoveries, often related to broad measurement tools or techniques12 that allow precise but generalized or programmable intervention in biological systems. There\u2019s perhaps ~1 of these major discoveries per year and collectively they arguably drive >50% of progress in biology. These discoveries are so powerful precisely because they cut through intrinsic complexity and data limitations, directly increasing our understanding and control over biological processes. A few discoveries per decade have enabled both the bulk of our basic scientific understanding of biology, and have driven many of the most powerful medical treatments.\n\nSome examples include:\n\n \nCRISPR: a technique that allows live editing of any gene in living organisms (replacement of any arbitrary gene sequence with any other arbitrary sequence). Since the original technique was developed, there have been constant improvements to target specific cell types, increasing accuracy, and reducing edits of the wrong gene\u2014all of which are needed for safe use in humans. \nVarious kinds of microscopy for watching what is going on at a precise level: advanced light microscopes (with various kinds of fluorescent techniques, special optics, etc), electron microscopes, atomic force microscopes, etc. \nGenome sequencing and synthesis, which has dropped in cost by several orders of magnitude in the last couple decades.  \nOptogenetic techniques that allow you to get a neuron to fire by shining a light on it. \nmRNA vaccines that, in principle, allow us to design a vaccine against anything and then quickly adapt it (mRNA vaccines of course became famous during COVID). \nCell therapies such as CAR-T that allow immune cells to be taken out of the body and \u201creprogrammed\u201d to attack, in principle, anything. \nConceptual insights like the germ theory of disease or the realization of a link between the immune system and cancer13. \n\nI\u2019m going to the trouble of listing all these technologies because I want to make a crucial claim about them: I think their rate of discovery could be increased by 10x or more if there were a lot more talented, creative researchers. Or, put another way, I think the returns to intelligence are high for these discoveries, and that everything else in biology and medicine mostly follows from them.\n\nWhy do I think this? Because of the answers to some questions that we should get in the habit of asking when we\u2019re trying to determine \u201creturns to intelligence\u201d. First, these discoveries are generally made by a tiny number of researchers, often the same people repeatedly, suggesting skill and not random search (the latter might suggest lengthy experiments are the limiting factor). Second, they often \u201ccould have been made\u201d years earlier than they were: for example, CRISPR was a naturally occurring component of the immune system in bacteria that\u2019s been known since the 80\u2019s, but it took another 25 years for people to realize it could be repurposed for general gene editing. They also are often delayed many years by lack of support from the scientific community for promising directions (see this profile on the inventor of mRNA vaccines; similar stories abound). Third, successful projects are often scrappy or were afterthoughts that people didn\u2019t initially think were promising, rather than massively funded efforts. This suggests that it\u2019s not just massive resource concentration that drives discoveries, but ingenuity.\n\nFinally, although some of these discoveries have \u201cserial dependence\u201d (you need to make discovery A first in order to have the tools or knowledge to make discovery B)\u2014which again might create experimental delays\u2014many, perhaps most, are independent, meaning many at once can be worked on in parallel. Both these facts, and my general experience as a biologist, strongly suggest to me that there are hundreds of these discoveries waiting to be made if scientists were smarter and better at making connections between the vast amount of biological knowledge humanity possesses (again consider the CRISPR example). The success of AlphaFold/AlphaProteo at solving important problems much more effectively than humans, despite decades of carefully designed physics modeling, provides a proof of principle (albeit with a narrow tool in a narrow domain) that should point the way forward.\n\nThus, it\u2019s my guess that powerful AI could at least 10x the rate of these discoveries, giving us the next 50-100 years of biological progress in 5-10 years.14 Why not 100x? Perhaps it is possible, but here both serial dependence and experiment times become important: getting 100 years of progress in 1 year requires a lot of things to go right the first time, including animal experiments and things like designing microscopes or expensive lab facilities. I\u2019m actually open to the (perhaps absurd-sounding) idea that we could get 1000 years of progress in 5-10 years, but very skeptical that we can get 100 years in 1 year. Another way to put it is I think there\u2019s an unavoidable constant delay: experiments and hardware design have a certain \u201clatency\u201d and need to be iterated upon a certain \u201cirreducible\u201d number of times in order to learn things that can\u2019t be deduced logically. But massive parallelism may be possible on top of that15.\n\nWhat about clinical trials? Although there is a lot of bureaucracy and slowdown associated with them, the truth is that a lot (though by no means all!) of their slowness ultimately derives from the need to rigorously evaluate drugs that barely work or ambiguously work. This is sadly true of most therapies today: the average cancer drug increases survival by a few months while having significant side effects that need to be carefully measured (there\u2019s a similar story for Alzheimer\u2019s drugs). This leads to huge studies (in order to achieve statistical power) and difficult tradeoffs which regulatory agencies generally aren\u2019t great at making, again because of bureaucracy and the complexity of competing interests.\n\nWhen something works really well, it goes much faster: there\u2019s an accelerated approval track and the ease of approval is much greater when effect sizes are larger. mRNA vaccines for COVID were approved in 9 months\u2014much faster than the usual pace. That said, even under these conditions clinical trials are still too slow\u2014mRNA vaccines arguably should have been approved in ~2 months. But these kinds of delays (~1 year end-to-end for a drug) combined with massive parallelization and the need for some but not too much iteration (\u201ca few tries\u201d) are very compatible with radical transformation in 5-10 years. Even more optimistically, it is possible that AI-enabled biological science will reduce the need for iteration in clinical trials by developing better animal and cell experimental models (or even simulations) that are more accurate in predicting what will happen in humans. This will be particularly important in developing drugs against the aging process, which plays out over decades and where we need a faster iteration loop.\n\nFinally, on the topic of clinical trials and societal barriers, it is worth pointing out explicitly that in some ways biomedical innovations have an unusually strong track record of being successfully deployed, in contrast to some other technologies16. As mentioned in the introduction, many technologies are hampered by societal factors despite working well technically. This might suggest a pessimistic perspective on what AI can accomplish. But biomedicine is unique in that although the process of developing drugs is overly cumbersome, once developed they generally are successfully deployed and used.\n\nTo summarize the above, my basic prediction is that AI-enabled biology and medicine will allow us to compress the progress that human biologists would have achieved over the next 50-100 years into 5-10 years. I\u2019ll refer to this as the \u201ccompressed 21st century\u201d: the idea that after powerful AI is developed, we will in a few years make all the progress in biology and medicine that we would have made in the whole 21st century.\n\nAlthough predicting what powerful AI can do in a few years remains inherently difficult and speculative, there is some concreteness to asking \u201cwhat could humans do unaided in the next 100 years?\u201d. Simply looking at what we\u2019ve accomplished in the 20th century, or extrapolating from the first 2 decades of the 21st, or asking what \u201c10 CRISPR\u2019s and 50 CAR-T\u2019s\u201d would get us, all offer practical, grounded ways to estimate the general level of progress we might expect from powerful AI.\n\nBelow I try to make a list of what we might expect. This is not based on any rigorous methodology, and will almost certainly prove wrong in the details, but it\u2019s trying to get across the general level of radicalism we should expect:\n\n \nReliable prevention and treatment of nearly all17 natural infectious disease. Given the enormous advances against infectious disease in the 20th century, it is not radical to imagine that we could more or less \u201cfinish the job\u201d in a compressed 21st. mRNA vaccines and similar technology already point the way towards \u201cvaccines for anything\u201d. Whether infectious disease is fully eradicated from the world (as opposed to just in some places) depends on questions about poverty and inequality, which are discussed in Section 3. \nElimination of most cancer. Death rates from cancer have been dropping ~2% per year for the last few decades; thus we are on track to eliminate most cancer in the 21st century at the current pace of human science. Some subtypes have already been largely cured (for example some types of leukemia with CAR-T therapy), and I\u2019m perhaps even more excited for very selective drugs that target cancer in its infancy and prevent it from ever growing. AI will also make possible treatment regimens very finely adapted to the individualized genome of the cancer\u2014these are possible today, but hugely expensive in time and human expertise, which AI should allow us to scale. Reductions of 95% or more in both mortality and incidence seem possible. That said, cancer is extremely varied and adaptive, and is likely the hardest of these diseases to fully destroy. It would not be surprising if an assortment of rare, difficult malignancies persists. \nVery effective prevention and effective cures for genetic disease. Greatly improved embryo screening will likely make it possible to prevent most genetic disease, and some safer, more reliable descendant of CRISPR may cure most genetic disease in existing people. Whole-body afflictions that affect a large fraction of cells may be the last holdouts, however.  \nPrevention of Alzheimer\u2019s. We\u2019ve had a very hard time figuring out what causes Alzheimer\u2019s (it is somehow related to beta-amyloid protein, but the actual details seem to be very complex). It seems like exactly the type of problem that can be solved with better measurement tools that isolate biological effects; thus I am bullish about AI\u2019s ability to solve it. There is a good chance it can eventually be prevented with relatively simple interventions, once we actually understand what is going on. That said, damage from already-existing Alzheimer\u2019s may be very difficult to reverse.  \nImproved treatment of most other ailments. This is a catch-all category for other ailments including diabetes, obesity, heart disease, autoimmune diseases, and more. Most of these seem \u201ceasier\u201d to solve than cancer and Alzheimer\u2019s and in many cases are already in steep decline. For example, deaths from heart disease have already declined over 50%, and simple interventions like GLP-1 agonists have already made huge progress against obesity and diabetes.  \nBiological freedom. The last 70 years featured advances in birth control, fertility, management of weight, and much more. But I suspect AI-accelerated biology will greatly expand what is possible: weight, physical appearance, reproduction, and other biological processes will be fully under people\u2019s control. We\u2019ll refer to these under the heading of biological freedom: the idea that everyone should be empowered to choose what they want to become and live their lives in the way that most appeals to them. There will of course be important questions about global equality of access; see Section 3 for these.  \nDoubling of the human lifespan18.This might seem radical, but life expectancy increased almost 2x in the 20th century (from ~40 years to ~75), so it\u2019s \u201con trend\u201d that the \u201ccompressed 21st\u201d would double it again to 150. Obviously the interventions involved in slowing the actual aging process will be different from those that were needed in the last century to prevent (mostly childhood) premature deaths from disease, but the magnitude of change is not unprecedented19. Concretely, there already exist drugs that increase maximum lifespan in rats by 25-50% with limited ill-effects. And some animals (e.g. some types of turtle) already live 200 years, so humans are manifestly not at some theoretical upper limit. At a guess, the most important thing that is needed might be reliable, non-Goodhart-able biomarkers of human aging, as that will allow fast iteration on experiments and clinical trials. Once human lifespan is 150, we may be able to reach \u201cescape velocity\u201d, buying enough time that most of those currently alive today will be able to live as long as they want, although there\u2019s certainly no guarantee this is biologically possible.  \n\nIt is worth looking at this list and reflecting on how different the world will be if all of it is achieved 7-12 years from now (which would be in line with an aggressive AI timeline). It goes without saying that it would be an unimaginable humanitarian triumph, the elimination all at once of most of the scourges that have haunted humanity for millennia. Many of my friends and colleagues are raising children, and when those children grow up, I hope that any mention of disease will sound to them the way scurvy, smallpox, or bubonic plague sounds to us. That generation will also benefit from increased biological freedom and self-expression, and with luck may also be able to live as long as they want.\n\nIt\u2019s hard to overestimate how surprising these changes will be to everyone except the small community of people who expected powerful AI. For example, thousands of economists and policy experts in the US currently debate how to keep Social Security and Medicare solvent, and more broadly how to keep down the cost of healthcare (which is mostly consumed by those over 70 and especially those with terminal illnesses such as cancer). The situation for these programs is likely to be radically improved if all this comes to pass20, as the ratio of working age to retired population will change drastically. No doubt these challenges will be replaced with others, such as how to ensure widespread access to the new technologies, but it is worth reflecting on how much the world will change even if biology is the only area to be successfully accelerated by AI.\n\n2. Neuroscience and mind\n\nIn the previous section I focused on physical diseases and biology in general, and didn\u2019t cover neuroscience or mental health. But neuroscience is a subdiscipline of biology and mental health is just as important as physical health. In fact, if anything, mental health affects human well-being even more directly than physical health. Hundreds of millions of people have very low quality of life due to problems like addiction, depression, schizophrenia, low-functioning autism, PTSD, psychopathy21, or intellectual disabilities. Billions more struggle with everyday problems that can often be interpreted as much milder versions of one of these severe clinical disorders. And as with general biology, it may be possible to go beyond addressing problems to improving the baseline quality of human experience.\n\nThe basic framework that I laid out for biology applies equally to neuroscience. The field is propelled forward by a small number of discoveries often related to tools for measurement or precise intervention \u2013 in the list of those above, optogenetics was a neuroscience discovery, and more recently CLARITY and expansion microscopy are advances in the same vein, in addition to many of the general cell biology methods directly carrying over to neuroscience. I think the rate of these advances will be similarly accelerated by AI and therefore that the framework of \u201c100 years of progress in 5-10 years\u201d applies to neuroscience in the same way it does to biology and for the same reasons. As in biology, the progress in 20th century neuroscience was enormous \u2013 for example we didn\u2019t even understand how or why neurons fired until the 1950\u2019s. Thus, it seems reasonable to expect AI-accelerated neuroscience to produce rapid progress over a few years.\n\nThere is one thing we should add to this basic picture, which is that some of the things we\u2019ve learned (or are learning) about AI itself in the last few years are likely to help advance neuroscience, even if it continues to be done only by humans. Interpretability is an obvious example: although biological neurons superficially operate in a completely different manner from artificial neurons (they communicate via spikes and often spike rates, so there is a time element not present in artificial neurons, and a bunch of details relating to cell physiology and neurotransmitters modifies their operation substantially), the basic question of \u201chow do distributed, trained networks of simple units that perform combined linear/non-linear operations work together to perform important computations\u201d is the same, and I strongly suspect the details of individual neuron communication will be abstracted away in most of the interesting questions about computation and circuits22. As just one example of this, a computational mechanism discovered by interpretability researchers in AI systems was recently rediscovered in the brains of mice.\n\nIt is much easier to do experiments on artificial neural networks than on real ones (the latter often requires cutting into animal brains), so interpretability may well become a tool for improving our understanding of neuroscience. Furthermore, powerful AI\u2019s will themselves probably be able to develop and apply this tool better than humans can.\n\nBeyond just interpretability though, what we have learned from AI about how intelligent systems are trained should (though I am not sure it has yet) cause a revolution in neuroscience. When I was working in neuroscience, a lot of people focused on what I would now consider the wrong questions about learning, because the concept of the scaling hypothesis / bitter lesson didn\u2019t exist yet. The idea that a simple objective function plus a lot of data can drive incredibly complex behaviors makes it more interesting to understand the objective functions and architectural biases and less interesting to understand the details of the emergent computations. I have not followed the field closely in recent years, but I have a vague sense that computational neuroscientists have still not fully absorbed the lesson. My attitude to the scaling hypothesis has always been \u201caha \u2013 this is an explanation, at a high level, of how intelligence works and how it so easily evolved\u201d, but I don\u2019t think that\u2019s the average neuroscientist\u2019s view, in part because the scaling hypothesis as \u201cthe secret to intelligence\u201d isn\u2019t fully accepted even within AI.\n\nI think that neuroscientists should be trying to combine this basic insight with the particularities of the human brain (biophysical limitations, evolutionary history, topology, details of motor and sensory inputs/outputs) to try to figure out some of neuroscience\u2019s key puzzles. Some likely are, but I suspect it\u2019s not enough yet, and that AI neuroscientists will be able to more effectively leverage this angle to accelerate progress.\n\nI expect AI to accelerate neuroscientific progress along four distinct routes, all of which can hopefully work together to cure mental illness and improve function:\n\n \nTraditional molecular biology, chemistry, and genetics. This is essentially the same story as general biology in section 1, and AI can likely speed it up via the same mechanisms. There are many drugs that modulate neurotransmitters in order to alter brain function, affect alertness or perception, change mood, etc., and AI can help us invent many more. AI can probably also accelerate research on the genetic basis of mental illness. \nFine-grained neural measurement and intervention. This is the ability to measure what a lot of individual neurons or neuronal circuits are doing, and intervene to change their behavior. Optogenetics and neural probes are technologies capable of both measurement and intervention in live organisms, and a number of very advanced methods (such as molecular ticker tapes to read out the firing patterns of large numbers of individual neurons) have also been proposed and seem possible in principle. \nAdvanced computational neuroscience. As noted above, both the specific insights and the gestalt of modern AI can probably be applied fruitfully to questions in systems neuroscience, including perhaps uncovering the real causes and dynamics of complex diseases like psychosis or mood disorders. \nBehavioral interventions. I haven\u2019t much mentioned it given the focus on the biological side of neuroscience, but psychiatry and psychology have of course developed a wide repertoire of behavioral interventions over the 20th century; it stands to reason that AI could accelerate these as well, both the development of new methods and helping patients to adhere to existing methods. More broadly, the idea of an \u201cAI coach\u201d who always helps you to be the best version of yourself, who studies your interactions and helps you learn to be more effective, seems very promising. \n\nIt\u2019s my guess that these four routes of progress working together would, as with physical disease, be on track to lead to the cure or prevention of most mental illness in the next 100 years even if AI was not involved \u2013 and thus might reasonably be completed in 5-10 AI-accelerated years. Concretely my guess at what will happen is something like:\n\n \nMost mental illness can probably be cured. I\u2019m not an expert in psychiatric disease (my time in neuroscience was spent building probes to study small groups of neurons) but it\u2019s my guess that diseases like PTSD, depression, schizophrenia, addiction, etc. can be figured out and very effectively treated via some combination of the four directions above. The answer is likely to be some combination of \u201csomething went wrong biochemically\u201d (although it could be very complex) and \u201csomething went wrong with the neural network, at a high level\u201d. That is, it\u2019s a systems neuroscience question\u2014though that doesn\u2019t gainsay the impact of the behavioral interventions discussed above. Tools for measurement and intervention, especially in live humans, seem likely to lead to rapid iteration and progress. \nConditions that are very \u201cstructural\u201d may be more difficult, but not impossible. There\u2019s some evidence that psychopathy is associated with obvious neuroanatomical differences \u2013 that some brain regions are simply smaller or less developed in psychopaths. Psychopaths are also believed to lack empathy from a young age; whatever is different about their brain, it was probably always that way. The same may be true of some intellectual disabilities, and perhaps other conditions. Restructuring the brain sounds hard, but it also seems like a task with high returns to intelligence. Perhaps there is some way to coax the adult brain into an earlier or more plastic state where it can be reshaped. I\u2019m very uncertain how possible this is, but my instinct is to be optimistic about what AI can invent here. \nEffective genetic prevention of mental illness seems possible. Most mental illness is partially heritable, and genome-wide association studies are starting to gain traction on identifying the relevant factors, which are often many in number. It will probably be possible to prevent most of these diseases via embryo screening, similar to the story with physical disease. One difference is that psychiatric disease is more likely to be polygenic (many genes contribute), so due to complexity there\u2019s an increased risk of unknowingly selecting against positive traits that are correlated with disease. Oddly however, in recent years GWAS studies seem to suggest that these correlations might have been overstated. In any case, AI-accelerated neuroscience may help us to figure these things out. Of course, embryo screening for complex traits raises a number of societal issues and will be controversial, though I would guess that most people would support screening for severe or debilitating mental illness. \nEveryday problems that we don\u2019t think of as clinical disease will also be solved. Most of us have everyday psychological problems that are not ordinarily thought of as rising to the level of clinical disease. Some people are quick to anger, others have trouble focusing or are often drowsy, some are fearful or anxious, or react badly to change. Today, drugs already exist to help with e.g. alertness or focus (caffeine, modafinil, ritalin) but as with many other previous areas, much more is likely to be possible. Probably many more such drugs exist and have not been discovered, and there may also be totally new modalities of intervention, such as targeted light stimulation (see optogenetics above) or magnetic fields. Given how many drugs we\u2019ve developed in the 20th century that tune cognitive function and emotional state, I\u2019m very optimistic about the \u201ccompressed 21st\u201d where everyone can get their brain to behave a bit better and have a more fulfilling day-to-day experience. \nHuman baseline experience can be much better. Taking one step further, many people have experienced extraordinary moments of revelation, creative inspiration, compassion, fulfillment, transcendence, love, beauty, or meditative peace. The character and frequency of these experiences differs greatly from person to person and within the same person at different times, and can also sometimes be triggered by various drugs (though often with side effects). All of this suggests that the \u201cspace of what is possible to experience\u201d is very broad and that a larger fraction of people\u2019s lives could consist of these extraordinary moments. It is probably also possible to improve various cognitive functions across the board. This is perhaps the neuroscience version of \u201cbiological freedom\u201d or \u201cextended lifespans\u201d. \n\nOne topic that often comes up in sci-fi depictions of AI, but that I intentionally haven\u2019t discussed here, is \u201cmind uploading\u201d, the idea of capturing the pattern and dynamics of a human brain and instantiating them in software. This topic could be the subject of an essay all by itself, but suffice it to say that while I think uploading is almost certainly possible in principle, in practice it faces significant technological and societal challenges, even with powerful AI, that likely put it outside the 5-10 year window we are discussing.\n\nIn summary, AI-accelerated neuroscience is likely to vastly improve treatments for, or even cure, most mental illness as well as greatly expand \u201ccognitive and mental freedom\u201d and human cognitive and emotional abilities. It will be every bit as radical as the improvements in physical health described in the previous section. Perhaps the world will not be visibly different on the outside, but the world as experienced by humans will be a much better and more humane place, as well as a place that offers greater opportunities for self-actualization. I also suspect that improved mental health will ameliorate a lot of other societal problems, including ones that seem political or economic.\n\n3. Economic development and poverty\n\nThe previous two sections are about developing new technologies that cure disease and improve the quality of human life. However an obvious question, from a humanitarian perspective, is: \u201cwill everyone have access to these technologies?\u201d\n\nIt is one thing to develop a cure for a disease, it is another thing to eradicate the disease from the world. More broadly, many existing health interventions have not yet been applied everywhere in the world, and for that matter the same is true of (non-health) technological improvements in general. Another way to say this is that living standards in many parts of the world are still desperately poor: GDP per capita is ~$2,000 in Sub-Saharan Africa as compared to ~$75,000 in the United States. If AI further increases economic growth and quality of life in the developed world, while doing little to help the developing world, we should view that as a terrible moral failure and a blemish on the genuine humanitarian victories in the previous two sections. Ideally, powerful AI should help the developing world catch up to the developed world, even as it revolutionizes the latter.\n\nI am not as confident that AI can address inequality and economic growth as I am that it can invent fundamental technologies, because technology has such obvious high returns to intelligence (including the ability to route around complexities and lack of data) whereas the economy involves a lot of constraints from humans, as well as a large dose of intrinsic complexity. I am somewhat skeptical that an AI could solve the famous \u201csocialist calculation problem\u201d23 and I don\u2019t think governments will (or should) turn over their economic policy to such an entity, even if it could do so. There are also problems like how to convince people to take treatments that are effective but that they may be suspicious of.\n\nThe challenges facing the developing world are made even more complicated by pervasive corruption in both private and public sectors. Corruption creates a vicious cycle: it exacerbates poverty, and poverty in turn breeds more corruption. AI-driven plans for economic development need to reckon with corruption, weak institutions, and other very human challenges.\n\nNevertheless, I do see significant reasons for optimism. Diseases have been eradicated and many countries have gone from poor to rich, and it is clear that the decisions involved in these tasks exhibit high returns to intelligence (despite human constraints and complexity). Therefore, AI can likely do them better than they are currently being done. There may also be targeted interventions that get around the human constraints and that AI could focus on. More importantly though, we have to try. Both AI companies and developed world policymakers will need to do their part to ensure that the developing world is not left out; the moral imperative is too great. So in this section, I\u2019ll continue to make the optimistic case, but keep in mind everywhere that success is not guaranteed and depends on our collective efforts.\n\nBelow I make some guesses about how I think things may go in the developing world over the 5-10 years after powerful AI is developed:\n\n \nDistribution of health interventions. The area where I am perhaps most optimistic is distributing health interventions throughout the world. Diseases have actually been eradicated by top-down campaigns: smallpox was fully eliminated in the 1970\u2019s, and polio and guinea worm are nearly eradicated with less than 100 cases per year. Mathematically sophisticated epidemiological modeling plays an active role in disease eradication campaigns, and it seems very likely that there is room for smarter-than-human AI systems to do a better job of it than humans are. The logistics of distribution can probably also be greatly optimized. One thing I learned as an early donor to GiveWell is that some health charities are way more effective than others; the hope is that AI-accelerated efforts would be more effective still. Additionally, some biological advances actually make the logistics of distribution much easier: for example, malaria has been difficult to eradicate because it requires treatment each time the disease is contracted; a vaccine that only needs to be administered once makes the logistics much simpler (and such vaccines for malaria are in fact currently being developed). Even simpler distribution mechanisms are possible: some diseases could in principle be eradicated by targeting their animal carriers, for example releasing mosquitoes infected with a bacterium that blocks their ability to carry a disease (who then infect all the other mosquitos) or simply using gene drives to wipe out the mosquitos. This requires one or a few centralized actions, rather than a coordinated campaign that must individually treat millions. Overall, I think 5-10 years is a reasonable timeline for a good fraction (maybe 50%) of AI-driven health benefits to propagate to even the poorest countries in the world. A good goal might be for the developing world 5-10 years after powerful AI to at least be substantially healthier than the developed world is today, even if it continues to lag behind the developed world. Accomplishing this will of course require a huge effort in global health, philanthropy, political advocacy, and many other efforts, which both AI developers and policymakers should help with. \nEconomic growth. Can the developing world quickly catch up to the developed world, not just in health, but across the board economically? There is some precedent for this: in the final decades of the 20th century, several East Asian economies achieved sustained ~10% annual real GDP growth rates, allowing them to catch up with the developed world. Human economic planners made the decisions that led to this success, not by directly controlling entire economies but by pulling a few key levers (such as an industrial policy of export-led growth, and resisting the temptation to rely on natural resource wealth); it\u2019s plausible that \u201cAI finance ministers and central bankers\u201d could replicate or exceed this 10% accomplishment. An important question is how to get developing world governments to adopt them while respecting the principle of self-determination\u2014some may be enthusiastic about it, but others are likely to be skeptical. On the optimistic side, many of the health interventions in the previous bullet point are likely to organically increase economic growth: eradicating AIDS/malaria/parasitic worms would have a transformative effect on productivity, not to mention the economic benefits that some of the neuroscience interventions (such as improved mood and focus) would have in developed and developing world alike. Finally, non-health AI-accelerated technology (such as energy technology, transport drones, improved building materials, better logistics and distribution, and so on) may simply permeate the world naturally; for example, even cell phones quickly permeated sub-Saharan Africa via market mechanisms, without needing philanthropic efforts. On the more negative side, while AI and automation have many potential benefits, they also pose challenges for economic development, particularly for countries that haven't yet industrialized. Finding ways to ensure these countries can still develop and improve their economies in an age of increasing automation is an important challenge for economists and policymakers to address. Overall, a dream scenario\u2014perhaps a goal to aim for\u2014would be 20% annual GDP growth rate in the developing world, with 10% each coming from AI-enabled economic decisions and the natural spread of AI-accelerated technologies, including but not limited to health. If achieved, this would bring sub-Saharan Africa to the current per-capita GDP of China in 5-10 years, while raising much of the rest of the developing world to levels higher than the current US GDP. Again, this is a dream scenario, not what happens by default: it\u2019s something all of us must work together to make more likely. \nFood security 24. Advances in crop technology like better fertilizers and pesticides, more automation, and more efficient land use drastically increased crop yields across the 20th Century, saving millions of people from hunger. Genetic engineering is currently improving many crops even further. Finding even more ways to do this\u2014as well as to make agricultural supply chains even more efficient\u2014could give us an AI-driven second Green Revolution, helping close the gap between the developing and developed world. \nMitigating climate change. Climate change will be felt much more strongly in the developing world, hampering its development. We can expect that AI will lead to improvements in technologies that slow or prevent climate change, from atmospheric carbon-removal and clean energy technology to lab-grown meat that reduces our reliance on carbon-intensive factory farming. Of course, as discussed above, technology isn\u2019t the only thing restricting progress on climate change\u2014as with all of the other issues discussed in this essay, human societal factors are important. But there\u2019s good reason to think that AI-enhanced research will give us the means to make mitigating climate change far less costly and disruptive, rendering many of the objections moot and freeing up developing countries to make more economic progress. \nInequality within countries. I\u2019ve mostly talked about inequality as a global phenomenon (which I do think is its most important manifestation), but of course inequality also exists within countries. With advanced health interventions and especially radical increases in lifespan or cognitive enhancement drugs, there will certainly be valid worries that these technologies are \u201conly for the rich\u201d. I am more optimistic about within-country inequality especially in the developed world, for two reasons. First, markets function better in the developed world, and markets are typically good at bringing down the cost of high-value technologies over time25. Second, developed world political institutions are more responsive to their citizens and have greater state capacity to execute universal access programs\u2014and I expect citizens to demand access to technologies that so radically improve quality of life. Of course it\u2019s not predetermined that such demands succeed\u2014and here is another place where we collectively have to do all we can to ensure a fair society. There is a separate problem in inequality of wealth (as opposed to inequality of access to life-saving and life-enhancing technologies), which seems harder and which I discuss in Section 5. \nThe opt-out problem. One concern in both developed and developing world alike is people opting out of AI-enabled benefits (similar to the anti-vaccine movement, or Luddite movements more generally). There could end up being bad feedback cycles where, for example, the people who are least able to make good decisions opt out of the very technologies that improve their decision-making abilities, leading to an ever-increasing gap and even creating a dystopian underclass (some researchers have argued that this will undermine democracy, a topic I discuss further in the next section). This would, once again, place a moral blemish on AI\u2019s positive advances. This is a difficult problem to solve as I don\u2019t think it is ethically okay to coerce people, but we can at least try to increase people\u2019s scientific understanding\u2014and perhaps AI itself can help us with this. One hopeful sign is that historically anti-technology movements have been more bark than bite: railing against modern technology is popular, but most people adopt it in the end, at least when it\u2019s a matter of individual choice. Individuals tend to adopt most health and consumer technologies, while technologies that are truly hampered, like nuclear power, tend to be collective political decisions. \n\nOverall, I am optimistic about quickly bringing AI\u2019s biological advances to people in the developing world. I am hopeful, though not confident, that AI can also enable unprecedented economic growth rates and allow the developing world to at least surpass where the developed world is now. I am concerned about the \u201copt out\u201d problem in both the developed and developing world, but suspect that it will peter out over time and that AI can help accelerate this process. It won\u2019t be a perfect world, and those who are behind won\u2019t fully catch up, at least not in the first few years. But with strong efforts on our part, we may be able to get things moving in the right direction\u2014and fast. If we do, we can make at least a downpayment on the promises of dignity and equality that we owe to every human being on earth.\n\n4. Peace and governance\n\nSuppose that everything in the first three sections goes well: disease, poverty, and inequality are significantly reduced and the baseline of human experience is raised substantially. It does not follow that all major causes of human suffering are solved. Humans are still a threat to each other. Although there is a trend of technological improvement and economic development leading to democracy and peace, it is a very loose trend, with frequent (and recent) backsliding. At the dawn of the 20th Century, people thought they had put war behind them; then came the two world wars. Thirty years ago Francis Fukuyama wrote about \u201cthe End of History\u201d and a final triumph of liberal democracy; that hasn\u2019t happened yet. Twenty years ago US policymakers believed that free trade with China would cause it to liberalize as it became richer; that very much didn\u2019t happen, and we now seem headed for a second cold war with a resurgent authoritarian bloc. And plausible theories suggest that internet technology may actually advantage authoritarianism, not democracy as initially believed (e.g. in the \u201cArab Spring\u201d period). It seems important to try to understand how powerful AI will intersect with these issues of peace, democracy, and freedom.\n\nUnfortunately, I see no strong reason to believe AI will preferentially or structurally advance democracy and peace, in the same way that I think it will structurally advance human health and alleviate poverty. Human conflict is adversarial and AI can in principle help both the \u201cgood guys\u201d and the \u201cbad guys\u201d. If anything, some structural factors seem worrying: AI seems likely to enable much better propaganda and surveillance, both major tools in the autocrat\u2019s toolkit. It\u2019s therefore up to us as individual actors to tilt things in the right direction: if we want AI to favor democracy and individual rights, we are going to have to fight for that outcome. I feel even more strongly about this than I do about international inequality: the triumph of liberal democracy and political stability is not guaranteed, perhaps not even likely, and will require great sacrifice and commitment on all of our parts, as it often has in the past.\n\nI think of the issue as having two parts: international conflict, and the internal structure of nations. On the international side, it seems very important that democracies have the upper hand on the world stage when powerful AI is created. AI-powered authoritarianism seems too terrible to contemplate, so democracies need to be able to set the terms by which powerful AI is brought into the world, both to avoid being overpowered by authoritarians and to prevent human rights abuses within authoritarian countries.\n\nMy current guess at the best way to do this is via an \u201centente strategy\u201d26, in which a coalition of democracies seeks to gain a clear advantage (even just a temporary one) on powerful AI by securing its supply chain, scaling quickly, and blocking or delaying adversaries\u2019 access to key resources like chips and semiconductor equipment. This coalition would on one hand use AI to achieve robust military superiority (the stick) while at the same time offering to distribute the benefits of powerful AI (the carrot) to a wider and wider group of countries in exchange for supporting the coalition\u2019s strategy to promote democracy (this would be a bit analogous to \u201cAtoms for Peace\u201d). The coalition would aim to gain the support of more and more of the world, isolating our worst adversaries and eventually putting them in a position where they are better off taking the same bargain as the rest of the world: give up competing with democracies in order to receive all the benefits and not fight a superior foe.\n\nIf we can do all this, we will have a world in which democracies lead on the world stage and have the economic and military strength to avoid being undermined, conquered, or sabotaged by autocracies, and may be able to parlay their AI superiority into a durable advantage. This could optimistically lead to an \u201ceternal 1991\u201d\u2014a world where democracies have the upper hand and Fukuyama\u2019s dreams are realized. Again, this will be very difficult to achieve, and will in particular require close cooperation between private AI companies and democratic governments, as well as extraordinarily wise decisions about the balance between carrot and stick.\n\nEven if all that goes well, it leaves the question of the fight between democracy and autocracy within each country. It is obviously hard to predict what will happen here, but I do have some optimism that given a global environment in which democracies control the most powerful AI, then AI may actually structurally favor democracy everywhere. In particular, in this environment democratic governments can use their superior AI to win the information war: they can counter influence and propaganda operations by autocracies and may even be able to create a globally free information environment by providing channels of information and AI services in a way that autocracies lack the technical ability to block or monitor. It probably isn\u2019t necessary to deliver propaganda, only to counter malicious attacks and unblock the free flow of information. Although not immediate, a level playing field like this stands a good chance of gradually tilting global governance towards democracy, for several reasons.\n\nFirst, the increases in quality of life in Sections 1-3 should, all things equal, promote democracy: historically they have, to at least some extent. In particular I expect improvements in mental health, well-being, and education to increase democracy, as all three are negatively correlated with support for authoritarian leaders. In general people want more self-expression when their other needs are met, and democracy is among other things a form of self-expression. Conversely, authoritarianism thrives on fear and resentment.\n\nSecond, there is a good chance free information really does undermine authoritarianism, as long as the authoritarians can\u2019t censor it. And uncensored AI can also bring individuals powerful tools for undermining repressive governments. Repressive governments survive by denying people a certain kind of common knowledge, keeping them from realizing that \u201cthe emperor has no clothes\u201d. For example Sr\u0111a Popovi\u0107, who helped to topple the Milo\u0161evi\u0107 government in Serbia, has written extensively about techniques for psychologically robbing authoritarians of their power, for breaking the spell and rallying support against a dictator. A superhumanly effective AI version of Popovi\u0107 (whose skills seem like they have high returns to intelligence) in everyone\u2019s pocket, one that dictators are powerless to block or censor, could create a wind at the backs of dissidents and reformers across the world. To say it again, this will be a long and protracted fight, one where victory is not assured, but if we design and build AI in the right way, it may at least be a fight where the advocates of freedom everywhere have an advantage.\n\nAs with neuroscience and biology, we can also ask how things could be \u201cbetter than normal\u201d\u2014not just how to avoid autocracy, but how to make democracies better than they are today. Even within democracies, injustices happen all the time. Rule-of-law societies make a promise to their citizens that everyone will be equal under the law and everyone is entitled to basic human rights, but obviously people do not always receive those rights in practice. That this promise is even partially fulfilled makes it something to be proud of, but can AI help us do better?\n\nFor example, could AI improve our legal and judicial system by making decisions and processes more impartial? Today people mostly worry in legal or judicial contexts that AI systems will be a cause of discrimination, and these worries are important and need to be defended against. At the same time, the vitality of democracy depends on harnessing new technologies to improve democratic institutions, not just responding to risks. A truly mature and successful implementation of AI has the potential to reduce bias and be fairer for everyone.\n\nFor centuries, legal systems have faced the dilemma that the law aims to be impartial, but is inherently subjective and thus must be interpreted by biased humans. Trying to make the law fully mechanical hasn\u2019t worked because the real world is messy and can\u2019t always be captured in mathematical formulas. Instead legal systems rely on notoriously imprecise criteria like \u201ccruel and unusual punishment\u201d or \u201cutterly without redeeming social importance\u201d, which humans then interpret\u2014and often do so in a manner that displays bias, favoritism, or arbitrariness. \u201cSmart contracts\u201d in cryptocurrencies haven\u2019t revolutionized law because ordinary code isn\u2019t smart enough to adjudicate all that much of interest. But AI might be smart enough for this: it is the first technology capable of making broad, fuzzy judgements in a repeatable and mechanical way.\n\nI am not suggesting that we literally replace judges with AI systems, but the combination of impartiality with the ability to understand and process messy, real world situations feels like it should have some serious positive applications to law and justice. At the very least, such systems could work alongside humans as an aid to decision-making. Transparency would be important in any such system, and a mature science of AI could conceivably provide it: the training process for such systems could be extensively studied, and advanced interpretability techniques could be used to see inside the final model and assess it for hidden biases, in a way that is simply not possible with humans. Such AI tools could also be used to monitor for violations of fundamental rights in a judicial or police context, making constitutions more self-enforcing.\n\nIn a similar vein, AI could be used to both aggregate opinions and drive consensus among citizens, resolving conflict, finding common ground, and seeking compromise. Some early ideas in this direction have been undertaken by the computational democracy project, including collaborations with Anthropic. A more informed and thoughtful citizenry would obviously strengthen democratic institutions.\n\nThere is also a clear opportunity for AI to be used to help provision government services\u2014such as health benefits or social services\u2014that are in principle available to everyone but in practice often severely lacking, and worse in some places than others. This includes health services, the DMV, taxes, social security, building code enforcement, and so on. Having a very thoughtful and informed AI whose job is to give you everything you\u2019re legally entitled to by the government in a way you can understand\u2014and who also helps you comply with often confusing government rules\u2014would be a big deal. Increasing state capacity both helps to deliver on the promise of equality under the law, and strengthens respect for democratic governance. Poorly implemented services are currently a major driver of cynicism about government27.\n\nAll of these are somewhat vague ideas, and as I said at the beginning of this section, I am not nearly as confident in their feasibility as I am in the advances in biology, neuroscience, and poverty alleviation. They may be unrealistically utopian. But the important thing is to have an ambitious vision, to be willing to dream big and try things out. The vision of AI as a guarantor of liberty, individual rights, and equality under the law is too powerful a vision not to fight for. A 21st century, AI-enabled polity could be both a stronger protector of individual freedom, and a beacon of hope that helps make liberal democracy the form of government that the whole world wants to adopt.\n\n5. Work and meaning\n\nEven if everything in the preceding four sections goes well\u2014not only do we alleviate disease, poverty, and inequality, but liberal democracy becomes the dominant form of government, and existing liberal democracies become better versions of themselves\u2014at least one important question still remains. \u201cIt\u2019s great we live in such a technologically advanced world as well as a fair and decent one\u201d, someone might object, \u201cbut with AI\u2019s doing everything, how will humans have meaning? For that matter, how will they survive economically?\u201d.\n\nI think this question is more difficult than the others. I don\u2019t mean that I am necessarily more pessimistic about it than I am about the other questions (although I do see challenges). I mean that it is fuzzier and harder to predict in advance, because it relates to macroscopic questions about how society is organized that tend to resolve themselves only over time and in a decentralized manner. For example, historical hunter-gatherer societies might have imagined that life is meaningless without hunting and various kinds of hunting-related religious rituals, and would have imagined that our well-fed technological society is devoid of purpose. They might also have not understood how our economy can provide for everyone, or what function people can usefully service in a mechanized society.\n\nNevertheless, it\u2019s worth saying at least a few words, while keeping in mind that the brevity of this section is not at all to be taken as a sign that I don\u2019t take these issues seriously\u2014on the contrary, it is a sign of a lack of clear answers.\n\nOn the question of meaning, I think it is very likely a mistake to believe that tasks you undertake are meaningless simply because an AI could do them better. Most people are not the best in the world at anything, and it doesn\u2019t seem to bother them particularly much. Of course today they can still contribute through comparative advantage, and may derive meaning from the economic value they produce, but people also greatly enjoy activities that produce no economic value. I spend plenty of time playing video games, swimming, walking around outside, and talking to friends, all of which generates zero economic value. I might spend a day trying to get better at a video game, or faster at biking up a mountain, and it doesn\u2019t really matter to me that someone somewhere is much better at those things. In any case I think meaning comes mostly from human relationships and connection, not from economic labor. People do want a sense of accomplishment, even a sense of competition, and in a post-AI world it will be perfectly possible to spend years attempting some very difficult task with a complex strategy, similar to what people do today when they embark on research projects, try to become Hollywood actors, or found companies28. The facts that (a) an AI somewhere could in principle do this task better, and (b) this task is no longer an economically rewarded element of a global economy, don\u2019t seem to me to matter very much.\n\nThe economic piece actually seems more difficult to me than the meaning piece. By \u201ceconomic\u201d in this section I mean the possible problem that most or all humans may not be able to contribute meaningfully to a sufficiently advanced AI-driven economy. This is a more macro problem than the separate problem of inequality, especially inequality in access to the new technologies, which I discussed in Section 3.\n\nFirst of all, in the short term I agree with arguments that comparative advantage will continue to keep humans relevant and in fact increase their productivity, and may even in some ways level the playing field between humans. As long as AI is only better at 90% of a given job, the other 10% will cause humans to become highly leveraged, increasing compensation and in fact creating a bunch of new human jobs complementing and amplifying what AI is good at, such that the \u201c10%\u201d expands to continue to employ almost everyone. In fact, even if AI can do 100% of things better than humans, but it remains inefficient or expensive at some tasks, or if the resource inputs to humans and AI\u2019s are meaningfully different, then the logic of comparative advantage continues to apply. One area humans are likely to maintain a relative (or even absolute) advantage for a significant time is the physical world. Thus, I think that the human economy may continue to make sense even a little past the point where we reach \u201ca country of geniuses in a datacenter\u201d.\n\nHowever, I do think in the long run AI will become so broadly effective and so cheap that this will no longer apply. At that point our current economic setup will no longer make sense, and there will be a need for a broader societal conversation about how the economy should be organized.\n\nWhile that might sound crazy, the fact is that civilization has successfully navigated major economic shifts in the past: from hunter-gathering to farming, farming to feudalism, and feudalism to industrialism. I suspect that some new and stranger thing will be needed, and that it\u2019s something no one today has done a good job of envisioning. It could be as simple as a large universal basic income for everyone, although I suspect that will only be a small part of a solution. It could be a capitalist economy of AI systems, which then give out resources (huge amounts of them, since the overall economic pie will be gigantic) to humans based on some secondary economy of what the AI systems think makes sense to reward in humans (based on some judgment ultimately derived from human values). Perhaps the economy runs on Whuffie points. Or perhaps humans will continue to be economically valuable after all, in some way not anticipated by the usual economic models. All of these solutions have tons of possible problems, and it\u2019s not possible to know whether they will make sense without lots of iteration and experimentation. And as with some of the other challenges, we will likely have to fight to get a good outcome here: exploitative or dystopian directions are clearly also possible and have to be prevented. Much more could be written about these questions and I hope to do so at some later time.\n\nTaking stock\n\nThrough the varied topics above, I\u2019ve tried to lay out a vision of a world that is both plausible if everything goes right with AI, and much better than the world today. I don\u2019t know if this world is realistic, and even if it is, it will not be achieved without a huge amount of effort and struggle by many brave and dedicated people. Everyone (including AI companies!) will need to do their part both to prevent risks and to fully realize the benefits.\n\nBut it is a world worth fighting for. If all of this really does happen over 5 to 10 years\u2014the defeat of most diseases, the growth in biological and cognitive freedom, the lifting of billions of people out of poverty to share in the new technologies, a renaissance of liberal democracy and human rights\u2014I suspect everyone watching it will be surprised by the effect it has on them. I don\u2019t mean the experience of personally benefiting from all the new technologies, although that will certainly be amazing. I mean the experience of watching a long-held set of ideals materialize in front of us all at once. I think many will be literally moved to tears by it.\n\nThroughout writing this essay I noticed an interesting tension. In one sense the vision laid out here is extremely radical: it is not what almost anyone expects to happen in the next decade, and will likely strike many as an absurd fantasy. Some may not even consider it desirable; it embodies values and political choices that not everyone will agree with. But at the same time there is something blindingly obvious\u2014something overdetermined\u2014about it, as if many different attempts to envision a good world inevitably lead roughly here.\n\nIn Iain M. Banks\u2019 The Player of Games29, the protagonist\u2014a member of a society called the Culture, which is based on principles not unlike those I\u2019ve laid out here\u2014travels to a repressive, militaristic empire in which leadership is determined by competition in an intricate battle game. The game, however, is complex enough that a player\u2019s strategy within it tends to reflect their own political and philosophical outlook. The protagonist manages to defeat the emperor in the game, showing that his values (the Culture\u2019s values) represent a winning strategy even in a game designed by a society based on ruthless competition and survival of the fittest. A well-known post by Scott Alexander has the same thesis\u2014that competition is self-defeating and tends to lead to a society based on compassion and cooperation. The \u201carc of the moral universe\u201d is another similar concept.\n\nI think the Culture\u2019s values are a winning strategy because they\u2019re the sum of a million small decisions that have clear moral force and that tend to pull everyone together onto the same side. Basic human intuitions of fairness, cooperation, curiosity, and autonomy are hard to argue with, and are cumulative in a way that our more destructive impulses often aren\u2019t. It is easy to argue that children shouldn\u2019t die of disease if we can prevent it, and easy from there to argue that everyone\u2019s children deserve that right equally. From there it is not hard to argue that we should all band together and apply our intellects to achieve this outcome. Few disagree that people should be punished for attacking or hurting others unnecessarily, and from there it\u2019s not much of a leap to the idea that punishments should be consistent and systematic across people. It is similarly intuitive that people should have autonomy and responsibility over their own lives and choices. These simple intuitions, if taken to their logical conclusion, lead eventually to rule of law, democracy, and Enlightenment values. If not inevitably, then at least as a statistical tendency, this is where humanity was already headed. AI simply offers an opportunity to get us there more quickly\u2014to make the logic starker and the destination clearer.\n\nNevertheless, it is a thing of transcendent beauty. We have the opportunity to play some small role in making it real.\n\nThanks to Kevin Esvelt, Parag Mallick, Stuart Ritchie, Matt Yglesias, Erik Brynjolfsson, Jim McClave, Allan Dafoe, and many people at Anthropic for reviewing drafts of this essay.\n\nTo the winners of the 2024 Nobel prize in Chemistry, for showing us all the way.]]>\n  \n  \n    Peter Thiel is a kingmaker in the shadows\n    https://x.com/swaaanson/status/1883875322430685415/?s=12&rw_tt_thread=True\n    readwise:01jjn0qgn55zrx2ddfhqf61jtq\n    Mon, 27 Jan 2025 23:14:45 +0000\n    X (formerly Twitter)\n    \nPeter Thiel is a kingmaker in the shadows\nHe backed Trump in 2016 and now 7 of his ex-colleagues(JD Vance, David Sacks, Elon, Vivek) are running the US government\nOnce you understand how Thiel spots winners before anyone else, you'll build influential networks like no other\ud83e\uddf5\n\nPeter Thiel today is at the center of all talent in Trump's cabinet.\nHe has quietly built a Peter Thiel Cinematic Universe.\nThe kind of power that could transform the US government and Silicon Valley.\nBut how did Peter Thiel orchestrate this?\n\nThiel values substance over status.\nStatus and prestige are zero-sum games.In a world where real value can be created, substance and true knowers are the people to look for.\nTo assess winners before anyone else, he came up with 4 questions...Your browser does not support the video tag.\n\n1. \"Tell me something that's true that very few people agree with you on.\"\n- It's psychologically hard to disagree with the masses.\"Brilliant thinking is rare, but courage is in even shorter supply than genius.\"\n- Having a sound contrarian conviction requires being well-read.\n\nAll of the greats have bet their company on a contrarian belief:\nJobs and Gates: Computers will sit on desks, not warehouses.Elon: Self-driving and Electric is the future.Jensen: GPUs are the future, not CPUs.\n\nPeter's decision to hire David Sacks at PayPal is the perfect example of this.\nSacks walked into his interview, called their core product dumb, and walked out with a job.\n\n2. How successful are you going to be?\nThiel believes that only the most successful people have a definite view of the future.\nThose who have thought through their ambitions in detail are the ones who will answer the question most compellingly.Your browser does not support the video tag.\n\n3. Would you grab a beer with them?\nMany people think that working with others you don't like is a sacrifice required for doing business.\nBut you can choose who you work with.Look at Berkshire Hathaway.\nWarren has only partnered with people he liked, and it really worked.Your browser does not support the video tag.\n\n4. Do they have Zen-like opposites?\nExceptional people are living contradictions with a combination of unusual traits.\n- Stubborn and open-minded- Idiosyncratic yet work well in teams\nThiel calls this \"The Founders Paradox\" and I think it's his best idea.Your browser does not support the video tag.\n\nThiel's ability to identify exceptional people by focusing on the right things helps him build extraordinary teams.\nHe creates the conditions that enable them to do their life's work.\nAnd Peter does so by using a very peculiar system:Your browser does not support the video tag.\n\nTrump applied this within his own cabinet.\nHe made every person responsible for doing just one thing.\n\nMost entrepreneurs can only aspire to be as good as Peter at recruiting and enforcing focus.\nThis stops them from operating at a high level of leverage.\nWhile most founders operate at Level 2 or 3, Peter comfortably rests at 5. (maybe higher)\n\nIf you'd like to know at which delegation level you stand in a minute, take this quiz:\nathena.com/?utm_source=tw\u2026\n\nIf you found this thread valuable:\n1. Follow me @swaaanson for more threads on entrepreneurship and delegation.\n2. RT the first tweet\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Jonathan Swanson\n                    @swaaanson\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nPeter Thiel is a kingmaker in the shadows\nHe backed Trump in 2016 and now 7 of his ex-colleagues(JD Vance, David Sacks, Elon, Vivek) are running the US government\nOnce you understand how Thiel spots winners before anyone else, you'll build influential networks like no other\ud83e\uddf5\n            \n            \n\n                \n                    Posted Jan 27, 2025 at 1:50PM\n                \n            \n        \n\nBuilding Thumbtack to $1B+ taught me effective delegation is key to managing a 1,000+ team.\nDelegation is the scaling law of entrepreneurship.\nI believe this, practice this, and now building a company to empower everybody with this.\nathena.com/?utm_source=tw\u2026]]>\n    \nPeter Thiel is a kingmaker in the shadows\nHe backed Trump in 2016 and now 7 of his ex-colleagues(JD Vance, David Sacks, Elon, Vivek) are running the US government\nOnce you understand how Thiel spots winners before anyone else, you'll build influential networks like no other\ud83e\uddf5\n\nPeter Thiel today is at the center of all talent in Trump's cabinet.\nHe has quietly built a Peter Thiel Cinematic Universe.\nThe kind of power that could transform the US government and Silicon Valley.\nBut how did Peter Thiel orchestrate this?\n\nThiel values substance over status.\nStatus and prestige are zero-sum games.In a world where real value can be created, substance and true knowers are the people to look for.\nTo assess winners before anyone else, he came up with 4 questions...Your browser does not support the video tag.\n\n1. \"Tell me something that's true that very few people agree with you on.\"\n- It's psychologically hard to disagree with the masses.\"Brilliant thinking is rare, but courage is in even shorter supply than genius.\"\n- Having a sound contrarian conviction requires being well-read.\n\nAll of the greats have bet their company on a contrarian belief:\nJobs and Gates: Computers will sit on desks, not warehouses.Elon: Self-driving and Electric is the future.Jensen: GPUs are the future, not CPUs.\n\nPeter's decision to hire David Sacks at PayPal is the perfect example of this.\nSacks walked into his interview, called their core product dumb, and walked out with a job.\n\n2. How successful are you going to be?\nThiel believes that only the most successful people have a definite view of the future.\nThose who have thought through their ambitions in detail are the ones who will answer the question most compellingly.Your browser does not support the video tag.\n\n3. Would you grab a beer with them?\nMany people think that working with others you don't like is a sacrifice required for doing business.\nBut you can choose who you work with.Look at Berkshire Hathaway.\nWarren has only partnered with people he liked, and it really worked.Your browser does not support the video tag.\n\n4. Do they have Zen-like opposites?\nExceptional people are living contradictions with a combination of unusual traits.\n- Stubborn and open-minded- Idiosyncratic yet work well in teams\nThiel calls this \"The Founders Paradox\" and I think it's his best idea.Your browser does not support the video tag.\n\nThiel's ability to identify exceptional people by focusing on the right things helps him build extraordinary teams.\nHe creates the conditions that enable them to do their life's work.\nAnd Peter does so by using a very peculiar system:Your browser does not support the video tag.\n\nTrump applied this within his own cabinet.\nHe made every person responsible for doing just one thing.\n\nMost entrepreneurs can only aspire to be as good as Peter at recruiting and enforcing focus.\nThis stops them from operating at a high level of leverage.\nWhile most founders operate at Level 2 or 3, Peter comfortably rests at 5. (maybe higher)\n\nIf you'd like to know at which delegation level you stand in a minute, take this quiz:\nathena.com/?utm_source=tw\u2026\n\nIf you found this thread valuable:\n1. Follow me @swaaanson for more threads on entrepreneurship and delegation.\n2. RT the first tweet\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Jonathan Swanson\n                    @swaaanson\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nPeter Thiel is a kingmaker in the shadows\nHe backed Trump in 2016 and now 7 of his ex-colleagues(JD Vance, David Sacks, Elon, Vivek) are running the US government\nOnce you understand how Thiel spots winners before anyone else, you'll build influential networks like no other\ud83e\uddf5\n            \n            \n\n                \n                    Posted Jan 27, 2025 at 1:50PM\n                \n            \n        \n\nBuilding Thumbtack to $1B+ taught me effective delegation is key to managing a 1,000+ team.\nDelegation is the scaling law of entrepreneurship.\nI believe this, practice this, and now building a company to empower everybody with this.\nathena.com/?utm_source=tw\u2026]]>\n  \n  \n    this is incredible.\n    https://x.com/ehuanglu/status/1883530084902187302/?s=12&rw_tt_thread=True\n    readwise:01jjm16x4mt8nztbwztfzwhgyp\n    Mon, 27 Jan 2025 14:03:54 +0000\n    X (formerly Twitter)\n    \nthis is incredible..\nKling AI just dropped Elements, it lets you create ads for any product, with any actors, in any environment\nyou can even make actors say any slogan and.. you just need 4 images\nstep by step tutorial:Your browser does not support the video tag.\n\n1. Kling AI is an AI media hub, the best video generator on the market, you get free credits to try\nlimited time discount available now\ndiscount link:klingai.com/membership?kol\u2026Your browser does not support the video tag.\n\n2. Kling AI Elements (Must-Know)\nyou can upload up to 4 images to control your scene like character, product, background, clothing\nPrompt example: On the stage, a woman wearing a crystal crown walks and poses for the camera. She lifts the bag up to the cameraYour browser does not support the video tag.\n\n3. here are the images I used, you can try it out\n\n4. settings\n- Use Pro Mode for the best quality- Shorter durations often get better results- Choose the aspect ratio- Adjust the Generating Count to create multiple clips in one go\n\n5. lipsync\n- click \u2018Lip Sync\u2019 under the video you\u2019ve generated- upload your own voice file or type in your script- choose from various voice options, adjust the speech rate, and even add emotionsYour browser does not support the video tag.\n\nif you enjoyed reading this post,\nfollow @EHuanglu for more AI stuff.\nand support with like/repost the post below \ud83d\udc47\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    el.cine\n                    @EHuanglu\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nthis is incredible..\nKling AI just dropped Elements, it lets you create ads for any product, with any actors, in any environment\nyou can even make actors say any slogan and.. you just need 4 images\nstep by step tutorial:Your browser does not support the video tag.\n            \n            \n\n                \n                    Posted Jan 26, 2025 at 2:59PM\n                \n            \n        ]]>\n    \nthis is incredible..\nKling AI just dropped Elements, it lets you create ads for any product, with any actors, in any environment\nyou can even make actors say any slogan and.. you just need 4 images\nstep by step tutorial:Your browser does not support the video tag.\n\n1. Kling AI is an AI media hub, the best video generator on the market, you get free credits to try\nlimited time discount available now\ndiscount link:klingai.com/membership?kol\u2026Your browser does not support the video tag.\n\n2. Kling AI Elements (Must-Know)\nyou can upload up to 4 images to control your scene like character, product, background, clothing\nPrompt example: On the stage, a woman wearing a crystal crown walks and poses for the camera. She lifts the bag up to the cameraYour browser does not support the video tag.\n\n3. here are the images I used, you can try it out\n\n4. settings\n- Use Pro Mode for the best quality- Shorter durations often get better results- Choose the aspect ratio- Adjust the Generating Count to create multiple clips in one go\n\n5. lipsync\n- click \u2018Lip Sync\u2019 under the video you\u2019ve generated- upload your own voice file or type in your script- choose from various voice options, adjust the speech rate, and even add emotionsYour browser does not support the video tag.\n\nif you enjoyed reading this post,\nfollow @EHuanglu for more AI stuff.\nand support with like/repost the post below \ud83d\udc47\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    el.cine\n                    @EHuanglu\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nthis is incredible..\nKling AI just dropped Elements, it lets you create ads for any product, with any actors, in any environment\nyou can even make actors say any slogan and.. you just need 4 images\nstep by step tutorial:Your browser does not support the video tag.\n            \n            \n\n                \n                    Posted Jan 26, 2025 at 2:59PM\n                \n            \n        ]]>\n  \n  \n    Jevons paradox - Wikipedia\n    https://en.m.wikipedia.org/wiki/Jevons_paradox\n    readwise:01jjkwypr7h6s5ffccg2tt6gmx\n    Mon, 27 Jan 2025 12:49:31 +0000\n    wikipedia.org\n    \nCoal-burning factories in 19th-century Manchester, England. Improved technology allowed coal to fuel the Industrial Revolution, greatly increasing the consumption of coal.\n\nIn economics, the Jevons paradox (/\u02c8d\u0292\u025bv\u0259nz/; sometimes Jevons effect) occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the falling cost of use induces increases in demand enough that resource use is increased, rather than reduced.[1][2][3][4] Governments, both historical and modern, typically expect that energy efficiency gains will lower energy consumption, rather than expecting the Jevons paradox.[5]\n\nIn 1865, the English economist William Stanley Jevons observed that technological improvements that increased the efficiency of coal use led to the increased consumption of coal in a wide range of industries. He argued that, contrary to common intuition, technological progress could not be relied upon to reduce fuel consumption.[6][7]\n\nThe issue has been re-examined by modern economists studying consumption rebound effects from improved energy efficiency. In addition to reducing the amount needed for a given use, improved efficiency also lowers the relative cost of using a resource, which increases the quantity demanded. This may counteract (to some extent) the reduction in use from improved efficiency. Additionally, improved efficiency increases real incomes and accelerates economic growth, further increasing the demand for resources. The Jevons paradox occurs when the effect from increased demand predominates, and the improved efficiency results in a faster rate of resource utilization.[7]\n\nConsiderable debate exists about the size of the rebound in energy efficiency and the relevance of the Jevons paradox to energy conservation. Some dismiss the effect, while others worry that it may be self-defeating to pursue sustainability by increasing energy efficiency.[5] Some environmental economists have proposed that efficiency gains be coupled with conservation policies that keep the cost of use the same (or higher) to avoid the Jevons paradox.[8] Conservation policies that increase cost of use (such as cap and trade or green taxes) can be used to control the rebound effect.[9]\n\nHistory\n\n\nWilliam Stanley Jevons, after whom the effect is named\n\nThe Jevons paradox was first described by the English economist William Stanley Jevons in his 1865 book The Coal Question. Jevons observed that England's consumption of coal soared after James Watt introduced the Watt steam engine, which greatly improved the efficiency of the coal-fired steam engine from Thomas Newcomen's earlier design. Watt's innovations made coal a more cost-effective power source, leading to the increased use of the steam engine in a wide range of industries. This in turn increased total coal consumption, even as the amount of coal required for any particular application fell. Jevons argued that improvements in fuel efficiency tend to increase (rather than decrease) fuel use, writing: \"It is a confusion of ideas to suppose that the economical use of fuel is equivalent to diminished consumption. The very contrary is the truth.\"[6]\n\nAt that time, many in Britain worried that coal reserves were rapidly dwindling, but some experts opined that improving technology would reduce coal consumption. Jevons argued that this view was incorrect, as further increases in efficiency would tend to increase the use of coal. Hence, improving technology would tend to increase the rate at which England's coal deposits were being depleted, and could not be relied upon to solve the problem.[6][7]\n\nAlthough Jevons originally focused on coal, the concept has since been extended to other resources, e.g., water usage.[10] The Jevons paradox is also found in socio-hydrology, in the safe development paradox called the reservoir effect, where construction of a reservoir to reduce the risk of water shortage can instead exacerbate that risk, as increased water availability leads to more development and hence more water consumption.[11]\n\nCause\n\nMain article: Rebound effect (conservation)\n\n\nElastic Demand : A 20% increase in efficiency causes a 40% increase in travel. Fuel consumption increases and the Jevons paradox occurs. \n\n\nInelastic Demand : A 20% increase in efficiency causes a 10% increase in travel. The Jevons paradox does not occur. \n\nEconomists have observed that consumers tend to travel more when their cars are more fuel efficient, causing a 'rebound' in the demand for fuel.[12] An increase in the efficiency with which a resource (e.g. fuel) is used causes a decrease in the cost of using that resource when measured in terms of what it can achieve (e.g. travel). Generally speaking, a decrease in the cost (or price) of a good or service will increase the quantity demanded (the law of demand). With a lower cost for travel, consumers will travel more, increasing the demand for fuel. This increase in demand is known as the rebound effect, and it may or may not be large enough to offset the original drop in fuel use from the increased efficiency. The Jevons paradox occurs when the rebound effect is greater than 100%, exceeding the original efficiency gains.[7]\n\nThe size of the direct rebound effect is dependent on the price elasticity of demand for the good.[13] In a perfectly competitive market where fuel is the sole input used, if the price of fuel remains constant but efficiency is doubled, the effective price of travel would be halved (twice as much travel can be purchased). If in response, the amount of travel purchased more than doubles (i.e. demand is price elastic), then fuel consumption would increase, and the Jevons paradox would occur. If demand is price inelastic, the amount of travel purchased would less than double, and fuel consumption would decrease. However, goods and services generally use more than one type of input (e.g. fuel, labour, machinery), and other factors besides input cost may also affect price. These factors tend to reduce the rebound effect, making the Jevons paradox less likely to occur.[7]\n\nKhazzoom\u2013Brookes postulate\n\nMain article: Khazzoom\u2013Brookes postulate\n\nIn the 1980s, economists Daniel Khazzoom and Leonard Brookes revisited the Jevons paradox for the case of society's energy use. Brookes, then chief economist at the UK Atomic Energy Authority, argued that attempts to reduce energy consumption by increasing energy efficiency would simply raise demand for energy in the economy as a whole. Khazzoom focused on the narrower point that the potential for rebound was ignored in mandatory performance standards for domestic appliances being set by the California Energy Commission.[14][15]\n\nIn 1992, the economist Harry Saunders dubbed the hypothesis that improvements in energy efficiency work to increase (rather than decrease) energy consumption the Khazzoom\u2013Brookes postulate, and argued that the hypothesis is broadly supported by neoclassical growth theory (the mainstream economic theory of capital accumulation, technological progress and long-run economic growth). Saunders showed that the Khazzoom\u2013Brookes postulate occurs in the neoclassical growth model under a wide range of assumptions.[14][16]\n\nAccording to Saunders, increased energy efficiency tends to increase energy consumption by two means. First, increased energy efficiency makes the use of energy relatively cheaper, thus encouraging increased use (the direct rebound effect). Second, increased energy efficiency increases real incomes and leads to increased economic growth, which pulls up energy use for the whole economy. At the microeconomic level (looking at an individual market), even with the rebound effect, improvements in energy efficiency usually result in reduced energy consumption.[17] That is, the rebound effect is usually less than 100%. However, at the macroeconomic level, more efficient (and hence comparatively cheaper) energy leads to faster economic growth, which increases energy use throughout the economy. Saunders argued that taking into account both microeconomic and macroeconomic effects, the technological progress that improves energy efficiency will tend to increase overall energy use.[14]\n\nEnergy conservation policy\n\nSee also: Steady-state economy \u00a7 Resource decoupling and the rebound effect\n\nJevons warned that fuel efficiency gains tend to increase fuel use. However, this does not imply that improved fuel efficiency is worthless if the Jevons paradox occurs; higher fuel efficiency enables greater production and a higher material quality of life.[18] For example, a more efficient steam engine allowed the cheaper transport of goods and people that contributed to the Industrial Revolution. Nonetheless, if the Khazzoom\u2013Brookes postulate is correct, increased fuel efficiency, by itself, will not reduce the rate of depletion of fossil fuels.[14]\n\nThere is considerable debate about whether the Khazzoom-Brookes Postulate is correct, and of the relevance of the Jevons paradox to energy conservation policy. Most governments, environmentalists and NGOs pursue policies that improve efficiency, holding that these policies will lower resource consumption and reduce environmental problems. Others, including many environmental economists, doubt this 'efficiency strategy' towards sustainability, and worry that efficiency gains may in fact lead to higher production and consumption. They hold that for resource use to fall, efficiency gains should be coupled with other policies that limit resource use.[5][16][19] However, other environmental economists argue that, while the Jevons paradox may occur in some situations, the empirical evidence for its widespread applicability is limited.[20]\n\nThe Jevons paradox is sometimes used to argue that energy conservation efforts are futile, for example, that more efficient use of oil will lead to increased demand, and will not slow the arrival or the effects of peak oil. This argument is usually presented as a reason not to enact environmental policies or pursue fuel efficiency (e.g. if cars are more efficient, it will simply lead to more driving).[21][22] Several points have been raised against this argument. First, in the context of a mature market such as for oil in developed countries, the direct rebound effect is usually small, and so increased fuel efficiency usually reduces resource use, other conditions remaining constant.[12][17][23] Second, even if increased efficiency does not reduce the total amount of fuel used, there remain other benefits associated with improved efficiency. For example, increased fuel efficiency may mitigate the price increases, shortages and disruptions in the global economy associated with crude oil depletion.[24] Third, environmental economists have pointed out that fuel use will unambiguously decrease if increased efficiency is coupled with an intervention (e.g. a fuel tax) that keeps the cost of fuel use the same or higher.[8]\n\nThe Jevons paradox indicates that increased efficiency by itself may not reduce fuel use, and that sustainable energy policy must rely on other types of government interventions as well.[9] As the imposition of conservation standards or other government interventions that increase cost-of-use do not display the Jevons paradox, they can be used to control the rebound effect.[9] To ensure that efficiency-enhancing technological improvements reduce fuel use, efficiency gains can be paired with government intervention that reduces demand (e.g. green taxes, cap and trade, or higher emissions standards). The ecological economists Mathis Wackernagel and William Rees have suggested that any cost savings from efficiency gains be \"taxed away or otherwise removed from further economic circulation. Preferably they should be captured for reinvestment in natural capital rehabilitation.\"[8] By mitigating the economic effects of government interventions designed to promote ecologically sustainable activities, efficiency-improving technological progress may make the imposition of these interventions more palatable, and more likely to be implemented.[25][26][27]\n\nOther examples\n\nAgriculture\n\nIncreasing the yield of a crop, such as wheat, for a given area will reduce the area required to achieve the same total yield. However, increasing efficiency may make it more profitable to grow wheat and lead farmers to convert land to the production of wheat, thereby increasing land use instead.[28]\n\nAI, Large Language Models, and Semiconductors\n\nImprovements in AI model efficiency have demonstrated the Jevons paradox in the computing sector. When OpenAI introduced their advanced ChatGPT Pro model in 2024 at $200 per month, featuring 86% accuracy on competition math problems (compared to 78% for their standard model), the higher performance led to increased rather than decreased compute consumption. Despite the higher price point and improved efficiency, organizations began implementing AI automation more extensively, particularly in data science, programming, and case law analysis. This trend was evidenced by OpenRouter's data, which showed an increase from 8 billion to over 300 billion tokens per week in token consumption within a year. The improved efficiency of these models, rather than reducing overall compute usage, enabled new use cases like continuous-operation AI agents and automated workflows, leading to higher total semiconductor demand for companies like TSMC, Intel, and Samsung.[29]\n\nSee also\n\n\nAndy and Bill's law, new software will always consume any increase in computing power that new hardware can provide \nDiminishing returns \nDowns\u2013Thomson paradox, increasing road capacity can make traffic congestion worse \nTragedy of the commons, a phenomenon in which common resources to which access is not regulated tend to become depleted \nWirth's law, faster hardware can trigger the development of less-efficient software \nDutch Disease, strong revenue from a dominant sector renders other sectors uncompetitive and starves them \nAI boom, periods of increased investment and rapid advancement in artificial intelligence technology\n\nReferences\n\n \n^ Sorrell, Steve (2009). \"Exploring Jevons' Paradox\". Energy Efficiency and Sustainable Consumption: The Rebound Effect. London: Palgrave Macmillan. pp. 136\u2013164. ISBN 978-0-230-58310-8.  \n^ Bauer, Diana; Papp, Kathryn (18 March 2009). \"Book Review Perspectives: The Jevons Paradox and the Myth of Resource Efficiency Improvements\". Sustainability: Science, Practice, & Policy. 5 (1). doi:10.1080/15487733.2009.11908028.  \n^ York, Richard; McGee, Julius Alexander (2 January 2016). \"Understanding the Jevons paradox\". Environmental Sociology. 2 (1): 77\u201387. Bibcode:2016EnvSo...2...77Y. doi:10.1080/23251042.2015.1106060. S2CID 156762601.  \n^ York, Richard (2006). \"Ecological paradoxes: William Stanley Jevons and the paperless office\" (PDF). Human Ecology Review. 13 (2): 143\u2013147. Retrieved 2015-05-05.  \n^ a b c Alcott, Blake (July 2005). \"Jevons' paradox\". Ecological Economics. 54 (1): 9\u201321. Bibcode:2005EcoEc..54....9A. doi:10.1016/j.ecolecon.2005.03.020. hdl:1942/22574.  \n^ a b c Jevons, William Stanley (1866). \"VII\". The Coal Question (2nd ed.). London: Macmillan and Company. ISBN 978-1-78987-646-8. OCLC 464772008. Retrieved 2008-07-21.  \n^ a b c d e Alcott, Blake (2008). \"Historical Overview of the Jevons paradox in the Literature\". In JM Polimeni; K Mayumi; M Giampietro (eds.). The Jevons Paradox and the Myth of Resource Efficiency Improvements. Earthscan. pp. 7\u201378. ISBN 978-1-84407-462-4.  \n^ a b c Wackernagel, Mathis; Rees, William (1997). \"Perceptual and structural barriers to investing in natural capital: Economics from an ecological footprint perspective\". Ecological Economics. 20 (3): 3\u201324. Bibcode:1997EcoEc..20....3W. doi:10.1016/S0921-8009(96)00077-8.  \n^ a b c Freire-Gonz\u00e1lez, Jaume; Puig-Ventosa, Ignasi (2015). \"Energy Efficiency Policies and the Jevons Paradox\". International Journal of Energy Economics and Policy. 5 (1): 69\u201379. Retrieved 29 May 2015.  \n^ Dumont, A.; Mayor, B.; L\u00f3pez-Gunn, E. (2013). \"Is the Rebound Effect or Jevons Paradox a Useful Concept for Better Management of Water Resources? Insights from the Irrigation Modernisation Process in Spain\". Aquatic Procedia. 1: 64\u201376. Bibcode:2013AqPro...1...64D. doi:10.1016/j.aqpro.2013.07.006.  \n^ Di Baldassarre, Giuliano; Wanders, Niko; AghaKouchak, Amir; Kuil, Linda; Rangecroft, Sally; Veldkamp, Ted I. E.; Garcia, Margaret; van Oel, Pieter R.; Breinl, Korbinian; Van Loon, Anne F. (November 2018). \"Water shortages worsened by reservoir effects\". Nature Sustainability. 1 (11): 617\u2013622. Bibcode:2018NatSu...1..617D. doi:10.1038/s41893-018-0159-0. ISSN 2398-9629. S2CID 134508048.  \n^ a b Small, Kenneth A.; Kurt Van Dender (2005-09-21). \"The Effect of Improved Fuel Economy on Vehicle Miles Traveled: Estimating the Rebound Effect Using U.S. State Data, 1966\u20132001\". Policy and Economics. Retrieved 2010-09-01.  \n^ Chan, Nathan W.; Gillingham, Kenneth (1 March 2015). \"The Microeconomic Theory of the Rebound Effect and Its Welfare Implications\". Journal of the Association of Environmental and Resource Economists. 2 (1): 133\u2013159. doi:10.1086/680256. ISSN 2333-5955. S2CID 3681642.  \n^ a b c d Saunders, Harry D. (October 1992). \"The Khazzoom-Brookes Postulate and Neoclassical Growth\". The Energy Journal. 13 (4): 131\u2013148. doi:10.5547/ISSN0195-6574-EJ-Vol13-No4-7. JSTOR 41322471. S2CID 154484026.  \n^ Herring, Horace (19 July 1999). \"Does energy efficiency save energy? The debate and its consequences\". Applied Energy. 63 (3): 209\u2013226. Bibcode:1999ApEn...63..209H. doi:10.1016/S0306-2619(99)00030-6. ISSN 0306-2619.  \n^ a b Sorrell, Steve (April 2009). \"Jevons' Paradox revisited: The evidence for backfire from improved energy efficiency\". Energy Policy. 37 (4): 1456\u20131469. Bibcode:2009EnPol..37.1456S. doi:10.1016/j.enpol.2008.12.003.  \n^ a b Greening, Lorna; David L. Greene; Carmen Difiglio (2000). \"Energy efficiency and consumption\u2014the rebound effect\u2014a survey\". Energy Policy. 28 (6\u20137): 389\u2013401. Bibcode:2000EnPol..28..389A. doi:10.1016/S0301-4215(00)00021-5.  \n^ Ryan, Lisa; Campbell, Nina (2012). \"Spreading the net: the multiple benefits of energy efficiency improvements\". IEA Energy Papers. doi:10.1787/20792581. Retrieved 5 June 2015.  \n^ Owen, David (December 20, 2010). \"Annals of Environmentalism: The Efficiency Dilemma\". The New Yorker. pp. 78\u2013.  \n^ Gillingham, Kenneth; Kotchen, Matthew J.; Rapson, David S.; Wagner, Gernot (23 January 2013). \"Energy policy: The rebound effect is overplayed\". Nature. 493 (7433): 475\u2013476. Bibcode:2013Natur.493..475G. doi:10.1038/493475a. ISSN 0028-0836. PMID 23344343. S2CID 3220092.  \n^ Potter, Andrew (2007-02-13). \"Planet-friendly design? Bah, humbug\". Maclean's. 120 (5): 14. Archived from the original on 2007-12-14. Retrieved 2010-09-01.  \n^ Strassel, Kimberley A. (2001-05-17). \"Conservation Wastes Energy\". The Wall Street Journal. Archived from the original on 2005-11-13. Retrieved 2009-07-31.  \n^ Gottron, Frank (2001-07-30). \"Energy Efficiency and the Rebound Effect: Does Increasing Efficiency Decrease Demand?\" (PDF). National Council for Science and the Environment. Retrieved 2012-02-24.  \n^ Hirsch, R. L.; Bezdek, R.; and Wendling, R. (2006). \"Peaking of World Oil Production and Its Mitigation\". AIChE Journal. 52 (1): 2\u20138. Bibcode:2006AIChE..52....2H. doi:10.1002/aic.10747.  \n^ Laitner, John A.; De Canio, Stephen J.; Peters, Irene (2003). Incorporating Behavioural, Social, and Organizational Phenomena in the Assessment of Climate Change Mitigation Options. Advances in Global Change Research. Vol. 8. pp. 1\u201364. doi:10.1007/0-306-48160-X_1. ISBN 978-0-7923-6802-1. {{cite book}}: |journal= ignored (help)  \n^ Freire-Gonz\u00e1lez, Jaume (1 February 2021). \"Governing Jevons' Paradox: Policies and systemic alternatives to avoid the rebound effect\". Energy Research & Social Science. 72: 101893. Bibcode:2021ERSS...7201893F. doi:10.1016/j.erss.2020.101893. S2CID 234020339.  \n^ Siami, Navid; Winter, Ralph A. (1 September 2021). \"Jevons' paradox revisited: Implications for climate change\". Economics Letters. 206: 109955. doi:10.1016/j.econlet.2021.109955.  \n^ \"Drones, crops and Jevons' Paradox\". Centre for Society, Technology and Values. 2016-08-22. Retrieved 2022-05-12.  \n^ \"ChatGPT Pro, The Jevons Paradox & Investing in Semiconductors\". FinAI.uk. Retrieved 2025-01-18.  \n\nFurther reading\n\n\nJenkins, Jesse; Nordhaus, Ted; Shellenberger, Michael (February 17, 2011). Energy Emergence: Rebound and Backfire as Emergent Phenomena (Report). Oakland, CA: The Breakthrough Institute. Archived from the original on 25 May 2015. Retrieved 29 May 2015. \nLords Select Committee on Science and Technology (5 July 2005). \"3: The economics of energy efficiency\". Select Committee on Science and Technology Second Report (Report). Session 2005\u201306. London, UK: House of Lords. \nMichaels, Robert J. (July 6, 2012). Energy Efficiency and Climate Policy: The Rebound Dilemma (PDF) (Report). Washington, D.C.: Institute for Energy Research. Retrieved 5 June 2015.]]>\n    \nCoal-burning factories in 19th-century Manchester, England. Improved technology allowed coal to fuel the Industrial Revolution, greatly increasing the consumption of coal.\n\nIn economics, the Jevons paradox (/\u02c8d\u0292\u025bv\u0259nz/; sometimes Jevons effect) occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the falling cost of use induces increases in demand enough that resource use is increased, rather than reduced.[1][2][3][4] Governments, both historical and modern, typically expect that energy efficiency gains will lower energy consumption, rather than expecting the Jevons paradox.[5]\n\nIn 1865, the English economist William Stanley Jevons observed that technological improvements that increased the efficiency of coal use led to the increased consumption of coal in a wide range of industries. He argued that, contrary to common intuition, technological progress could not be relied upon to reduce fuel consumption.[6][7]\n\nThe issue has been re-examined by modern economists studying consumption rebound effects from improved energy efficiency. In addition to reducing the amount needed for a given use, improved efficiency also lowers the relative cost of using a resource, which increases the quantity demanded. This may counteract (to some extent) the reduction in use from improved efficiency. Additionally, improved efficiency increases real incomes and accelerates economic growth, further increasing the demand for resources. The Jevons paradox occurs when the effect from increased demand predominates, and the improved efficiency results in a faster rate of resource utilization.[7]\n\nConsiderable debate exists about the size of the rebound in energy efficiency and the relevance of the Jevons paradox to energy conservation. Some dismiss the effect, while others worry that it may be self-defeating to pursue sustainability by increasing energy efficiency.[5] Some environmental economists have proposed that efficiency gains be coupled with conservation policies that keep the cost of use the same (or higher) to avoid the Jevons paradox.[8] Conservation policies that increase cost of use (such as cap and trade or green taxes) can be used to control the rebound effect.[9]\n\nHistory\n\n\nWilliam Stanley Jevons, after whom the effect is named\n\nThe Jevons paradox was first described by the English economist William Stanley Jevons in his 1865 book The Coal Question. Jevons observed that England's consumption of coal soared after James Watt introduced the Watt steam engine, which greatly improved the efficiency of the coal-fired steam engine from Thomas Newcomen's earlier design. Watt's innovations made coal a more cost-effective power source, leading to the increased use of the steam engine in a wide range of industries. This in turn increased total coal consumption, even as the amount of coal required for any particular application fell. Jevons argued that improvements in fuel efficiency tend to increase (rather than decrease) fuel use, writing: \"It is a confusion of ideas to suppose that the economical use of fuel is equivalent to diminished consumption. The very contrary is the truth.\"[6]\n\nAt that time, many in Britain worried that coal reserves were rapidly dwindling, but some experts opined that improving technology would reduce coal consumption. Jevons argued that this view was incorrect, as further increases in efficiency would tend to increase the use of coal. Hence, improving technology would tend to increase the rate at which England's coal deposits were being depleted, and could not be relied upon to solve the problem.[6][7]\n\nAlthough Jevons originally focused on coal, the concept has since been extended to other resources, e.g., water usage.[10] The Jevons paradox is also found in socio-hydrology, in the safe development paradox called the reservoir effect, where construction of a reservoir to reduce the risk of water shortage can instead exacerbate that risk, as increased water availability leads to more development and hence more water consumption.[11]\n\nCause\n\nMain article: Rebound effect (conservation)\n\n\nElastic Demand : A 20% increase in efficiency causes a 40% increase in travel. Fuel consumption increases and the Jevons paradox occurs. \n\n\nInelastic Demand : A 20% increase in efficiency causes a 10% increase in travel. The Jevons paradox does not occur. \n\nEconomists have observed that consumers tend to travel more when their cars are more fuel efficient, causing a 'rebound' in the demand for fuel.[12] An increase in the efficiency with which a resource (e.g. fuel) is used causes a decrease in the cost of using that resource when measured in terms of what it can achieve (e.g. travel). Generally speaking, a decrease in the cost (or price) of a good or service will increase the quantity demanded (the law of demand). With a lower cost for travel, consumers will travel more, increasing the demand for fuel. This increase in demand is known as the rebound effect, and it may or may not be large enough to offset the original drop in fuel use from the increased efficiency. The Jevons paradox occurs when the rebound effect is greater than 100%, exceeding the original efficiency gains.[7]\n\nThe size of the direct rebound effect is dependent on the price elasticity of demand for the good.[13] In a perfectly competitive market where fuel is the sole input used, if the price of fuel remains constant but efficiency is doubled, the effective price of travel would be halved (twice as much travel can be purchased). If in response, the amount of travel purchased more than doubles (i.e. demand is price elastic), then fuel consumption would increase, and the Jevons paradox would occur. If demand is price inelastic, the amount of travel purchased would less than double, and fuel consumption would decrease. However, goods and services generally use more than one type of input (e.g. fuel, labour, machinery), and other factors besides input cost may also affect price. These factors tend to reduce the rebound effect, making the Jevons paradox less likely to occur.[7]\n\nKhazzoom\u2013Brookes postulate\n\nMain article: Khazzoom\u2013Brookes postulate\n\nIn the 1980s, economists Daniel Khazzoom and Leonard Brookes revisited the Jevons paradox for the case of society's energy use. Brookes, then chief economist at the UK Atomic Energy Authority, argued that attempts to reduce energy consumption by increasing energy efficiency would simply raise demand for energy in the economy as a whole. Khazzoom focused on the narrower point that the potential for rebound was ignored in mandatory performance standards for domestic appliances being set by the California Energy Commission.[14][15]\n\nIn 1992, the economist Harry Saunders dubbed the hypothesis that improvements in energy efficiency work to increase (rather than decrease) energy consumption the Khazzoom\u2013Brookes postulate, and argued that the hypothesis is broadly supported by neoclassical growth theory (the mainstream economic theory of capital accumulation, technological progress and long-run economic growth). Saunders showed that the Khazzoom\u2013Brookes postulate occurs in the neoclassical growth model under a wide range of assumptions.[14][16]\n\nAccording to Saunders, increased energy efficiency tends to increase energy consumption by two means. First, increased energy efficiency makes the use of energy relatively cheaper, thus encouraging increased use (the direct rebound effect). Second, increased energy efficiency increases real incomes and leads to increased economic growth, which pulls up energy use for the whole economy. At the microeconomic level (looking at an individual market), even with the rebound effect, improvements in energy efficiency usually result in reduced energy consumption.[17] That is, the rebound effect is usually less than 100%. However, at the macroeconomic level, more efficient (and hence comparatively cheaper) energy leads to faster economic growth, which increases energy use throughout the economy. Saunders argued that taking into account both microeconomic and macroeconomic effects, the technological progress that improves energy efficiency will tend to increase overall energy use.[14]\n\nEnergy conservation policy\n\nSee also: Steady-state economy \u00a7 Resource decoupling and the rebound effect\n\nJevons warned that fuel efficiency gains tend to increase fuel use. However, this does not imply that improved fuel efficiency is worthless if the Jevons paradox occurs; higher fuel efficiency enables greater production and a higher material quality of life.[18] For example, a more efficient steam engine allowed the cheaper transport of goods and people that contributed to the Industrial Revolution. Nonetheless, if the Khazzoom\u2013Brookes postulate is correct, increased fuel efficiency, by itself, will not reduce the rate of depletion of fossil fuels.[14]\n\nThere is considerable debate about whether the Khazzoom-Brookes Postulate is correct, and of the relevance of the Jevons paradox to energy conservation policy. Most governments, environmentalists and NGOs pursue policies that improve efficiency, holding that these policies will lower resource consumption and reduce environmental problems. Others, including many environmental economists, doubt this 'efficiency strategy' towards sustainability, and worry that efficiency gains may in fact lead to higher production and consumption. They hold that for resource use to fall, efficiency gains should be coupled with other policies that limit resource use.[5][16][19] However, other environmental economists argue that, while the Jevons paradox may occur in some situations, the empirical evidence for its widespread applicability is limited.[20]\n\nThe Jevons paradox is sometimes used to argue that energy conservation efforts are futile, for example, that more efficient use of oil will lead to increased demand, and will not slow the arrival or the effects of peak oil. This argument is usually presented as a reason not to enact environmental policies or pursue fuel efficiency (e.g. if cars are more efficient, it will simply lead to more driving).[21][22] Several points have been raised against this argument. First, in the context of a mature market such as for oil in developed countries, the direct rebound effect is usually small, and so increased fuel efficiency usually reduces resource use, other conditions remaining constant.[12][17][23] Second, even if increased efficiency does not reduce the total amount of fuel used, there remain other benefits associated with improved efficiency. For example, increased fuel efficiency may mitigate the price increases, shortages and disruptions in the global economy associated with crude oil depletion.[24] Third, environmental economists have pointed out that fuel use will unambiguously decrease if increased efficiency is coupled with an intervention (e.g. a fuel tax) that keeps the cost of fuel use the same or higher.[8]\n\nThe Jevons paradox indicates that increased efficiency by itself may not reduce fuel use, and that sustainable energy policy must rely on other types of government interventions as well.[9] As the imposition of conservation standards or other government interventions that increase cost-of-use do not display the Jevons paradox, they can be used to control the rebound effect.[9] To ensure that efficiency-enhancing technological improvements reduce fuel use, efficiency gains can be paired with government intervention that reduces demand (e.g. green taxes, cap and trade, or higher emissions standards). The ecological economists Mathis Wackernagel and William Rees have suggested that any cost savings from efficiency gains be \"taxed away or otherwise removed from further economic circulation. Preferably they should be captured for reinvestment in natural capital rehabilitation.\"[8] By mitigating the economic effects of government interventions designed to promote ecologically sustainable activities, efficiency-improving technological progress may make the imposition of these interventions more palatable, and more likely to be implemented.[25][26][27]\n\nOther examples\n\nAgriculture\n\nIncreasing the yield of a crop, such as wheat, for a given area will reduce the area required to achieve the same total yield. However, increasing efficiency may make it more profitable to grow wheat and lead farmers to convert land to the production of wheat, thereby increasing land use instead.[28]\n\nAI, Large Language Models, and Semiconductors\n\nImprovements in AI model efficiency have demonstrated the Jevons paradox in the computing sector. When OpenAI introduced their advanced ChatGPT Pro model in 2024 at $200 per month, featuring 86% accuracy on competition math problems (compared to 78% for their standard model), the higher performance led to increased rather than decreased compute consumption. Despite the higher price point and improved efficiency, organizations began implementing AI automation more extensively, particularly in data science, programming, and case law analysis. This trend was evidenced by OpenRouter's data, which showed an increase from 8 billion to over 300 billion tokens per week in token consumption within a year. The improved efficiency of these models, rather than reducing overall compute usage, enabled new use cases like continuous-operation AI agents and automated workflows, leading to higher total semiconductor demand for companies like TSMC, Intel, and Samsung.[29]\n\nSee also\n\n\nAndy and Bill's law, new software will always consume any increase in computing power that new hardware can provide \nDiminishing returns \nDowns\u2013Thomson paradox, increasing road capacity can make traffic congestion worse \nTragedy of the commons, a phenomenon in which common resources to which access is not regulated tend to become depleted \nWirth's law, faster hardware can trigger the development of less-efficient software \nDutch Disease, strong revenue from a dominant sector renders other sectors uncompetitive and starves them \nAI boom, periods of increased investment and rapid advancement in artificial intelligence technology\n\nReferences\n\n \n^ Sorrell, Steve (2009). \"Exploring Jevons' Paradox\". Energy Efficiency and Sustainable Consumption: The Rebound Effect. London: Palgrave Macmillan. pp. 136\u2013164. ISBN 978-0-230-58310-8.  \n^ Bauer, Diana; Papp, Kathryn (18 March 2009). \"Book Review Perspectives: The Jevons Paradox and the Myth of Resource Efficiency Improvements\". Sustainability: Science, Practice, & Policy. 5 (1). doi:10.1080/15487733.2009.11908028.  \n^ York, Richard; McGee, Julius Alexander (2 January 2016). \"Understanding the Jevons paradox\". Environmental Sociology. 2 (1): 77\u201387. Bibcode:2016EnvSo...2...77Y. doi:10.1080/23251042.2015.1106060. S2CID 156762601.  \n^ York, Richard (2006). \"Ecological paradoxes: William Stanley Jevons and the paperless office\" (PDF). Human Ecology Review. 13 (2): 143\u2013147. Retrieved 2015-05-05.  \n^ a b c Alcott, Blake (July 2005). \"Jevons' paradox\". Ecological Economics. 54 (1): 9\u201321. Bibcode:2005EcoEc..54....9A. doi:10.1016/j.ecolecon.2005.03.020. hdl:1942/22574.  \n^ a b c Jevons, William Stanley (1866). \"VII\". The Coal Question (2nd ed.). London: Macmillan and Company. ISBN 978-1-78987-646-8. OCLC 464772008. Retrieved 2008-07-21.  \n^ a b c d e Alcott, Blake (2008). \"Historical Overview of the Jevons paradox in the Literature\". In JM Polimeni; K Mayumi; M Giampietro (eds.). The Jevons Paradox and the Myth of Resource Efficiency Improvements. Earthscan. pp. 7\u201378. ISBN 978-1-84407-462-4.  \n^ a b c Wackernagel, Mathis; Rees, William (1997). \"Perceptual and structural barriers to investing in natural capital: Economics from an ecological footprint perspective\". Ecological Economics. 20 (3): 3\u201324. Bibcode:1997EcoEc..20....3W. doi:10.1016/S0921-8009(96)00077-8.  \n^ a b c Freire-Gonz\u00e1lez, Jaume; Puig-Ventosa, Ignasi (2015). \"Energy Efficiency Policies and the Jevons Paradox\". International Journal of Energy Economics and Policy. 5 (1): 69\u201379. Retrieved 29 May 2015.  \n^ Dumont, A.; Mayor, B.; L\u00f3pez-Gunn, E. (2013). \"Is the Rebound Effect or Jevons Paradox a Useful Concept for Better Management of Water Resources? Insights from the Irrigation Modernisation Process in Spain\". Aquatic Procedia. 1: 64\u201376. Bibcode:2013AqPro...1...64D. doi:10.1016/j.aqpro.2013.07.006.  \n^ Di Baldassarre, Giuliano; Wanders, Niko; AghaKouchak, Amir; Kuil, Linda; Rangecroft, Sally; Veldkamp, Ted I. E.; Garcia, Margaret; van Oel, Pieter R.; Breinl, Korbinian; Van Loon, Anne F. (November 2018). \"Water shortages worsened by reservoir effects\". Nature Sustainability. 1 (11): 617\u2013622. Bibcode:2018NatSu...1..617D. doi:10.1038/s41893-018-0159-0. ISSN 2398-9629. S2CID 134508048.  \n^ a b Small, Kenneth A.; Kurt Van Dender (2005-09-21). \"The Effect of Improved Fuel Economy on Vehicle Miles Traveled: Estimating the Rebound Effect Using U.S. State Data, 1966\u20132001\". Policy and Economics. Retrieved 2010-09-01.  \n^ Chan, Nathan W.; Gillingham, Kenneth (1 March 2015). \"The Microeconomic Theory of the Rebound Effect and Its Welfare Implications\". Journal of the Association of Environmental and Resource Economists. 2 (1): 133\u2013159. doi:10.1086/680256. ISSN 2333-5955. S2CID 3681642.  \n^ a b c d Saunders, Harry D. (October 1992). \"The Khazzoom-Brookes Postulate and Neoclassical Growth\". The Energy Journal. 13 (4): 131\u2013148. doi:10.5547/ISSN0195-6574-EJ-Vol13-No4-7. JSTOR 41322471. S2CID 154484026.  \n^ Herring, Horace (19 July 1999). \"Does energy efficiency save energy? The debate and its consequences\". Applied Energy. 63 (3): 209\u2013226. Bibcode:1999ApEn...63..209H. doi:10.1016/S0306-2619(99)00030-6. ISSN 0306-2619.  \n^ a b Sorrell, Steve (April 2009). \"Jevons' Paradox revisited: The evidence for backfire from improved energy efficiency\". Energy Policy. 37 (4): 1456\u20131469. Bibcode:2009EnPol..37.1456S. doi:10.1016/j.enpol.2008.12.003.  \n^ a b Greening, Lorna; David L. Greene; Carmen Difiglio (2000). \"Energy efficiency and consumption\u2014the rebound effect\u2014a survey\". Energy Policy. 28 (6\u20137): 389\u2013401. Bibcode:2000EnPol..28..389A. doi:10.1016/S0301-4215(00)00021-5.  \n^ Ryan, Lisa; Campbell, Nina (2012). \"Spreading the net: the multiple benefits of energy efficiency improvements\". IEA Energy Papers. doi:10.1787/20792581. Retrieved 5 June 2015.  \n^ Owen, David (December 20, 2010). \"Annals of Environmentalism: The Efficiency Dilemma\". The New Yorker. pp. 78\u2013.  \n^ Gillingham, Kenneth; Kotchen, Matthew J.; Rapson, David S.; Wagner, Gernot (23 January 2013). \"Energy policy: The rebound effect is overplayed\". Nature. 493 (7433): 475\u2013476. Bibcode:2013Natur.493..475G. doi:10.1038/493475a. ISSN 0028-0836. PMID 23344343. S2CID 3220092.  \n^ Potter, Andrew (2007-02-13). \"Planet-friendly design? Bah, humbug\". Maclean's. 120 (5): 14. Archived from the original on 2007-12-14. Retrieved 2010-09-01.  \n^ Strassel, Kimberley A. (2001-05-17). \"Conservation Wastes Energy\". The Wall Street Journal. Archived from the original on 2005-11-13. Retrieved 2009-07-31.  \n^ Gottron, Frank (2001-07-30). \"Energy Efficiency and the Rebound Effect: Does Increasing Efficiency Decrease Demand?\" (PDF). National Council for Science and the Environment. Retrieved 2012-02-24.  \n^ Hirsch, R. L.; Bezdek, R.; and Wendling, R. (2006). \"Peaking of World Oil Production and Its Mitigation\". AIChE Journal. 52 (1): 2\u20138. Bibcode:2006AIChE..52....2H. doi:10.1002/aic.10747.  \n^ Laitner, John A.; De Canio, Stephen J.; Peters, Irene (2003). Incorporating Behavioural, Social, and Organizational Phenomena in the Assessment of Climate Change Mitigation Options. Advances in Global Change Research. Vol. 8. pp. 1\u201364. doi:10.1007/0-306-48160-X_1. ISBN 978-0-7923-6802-1. {{cite book}}: |journal= ignored (help)  \n^ Freire-Gonz\u00e1lez, Jaume (1 February 2021). \"Governing Jevons' Paradox: Policies and systemic alternatives to avoid the rebound effect\". Energy Research & Social Science. 72: 101893. Bibcode:2021ERSS...7201893F. doi:10.1016/j.erss.2020.101893. S2CID 234020339.  \n^ Siami, Navid; Winter, Ralph A. (1 September 2021). \"Jevons' paradox revisited: Implications for climate change\". Economics Letters. 206: 109955. doi:10.1016/j.econlet.2021.109955.  \n^ \"Drones, crops and Jevons' Paradox\". Centre for Society, Technology and Values. 2016-08-22. Retrieved 2022-05-12.  \n^ \"ChatGPT Pro, The Jevons Paradox & Investing in Semiconductors\". FinAI.uk. Retrieved 2025-01-18.  \n\nFurther reading\n\n\nJenkins, Jesse; Nordhaus, Ted; Shellenberger, Michael (February 17, 2011). Energy Emergence: Rebound and Backfire as Emergent Phenomena (Report). Oakland, CA: The Breakthrough Institute. Archived from the original on 25 May 2015. Retrieved 29 May 2015. \nLords Select Committee on Science and Technology (5 July 2005). \"3: The economics of energy efficiency\". Select Committee on Science and Technology Second Report (Report). Session 2005\u201306. London, UK: House of Lords. \nMichaels, Robert J. (July 6, 2012). Energy Efficiency and Climate Policy: The Rebound Dilemma (PDF) (Report). Washington, D.C.: Institute for Energy Research. Retrieved 5 June 2015.]]>\n  \n  \n    Build anything with DeepSeek-R1, here's how...\n    https://x.com/JulianGoldieSEO/status/1883499097933680660/?s=09&t=-1IVfCncEUdAWLIyeW1KEA&rw_tt_thread=True\n    readwise:01jjk16380w4jbvf735ekb9zss\n    Mon, 27 Jan 2025 04:44:13 +0000\n    X (formerly Twitter)\n    \nBuild anything with DeepSeek-R1, here's how...Your browser does not support the video tag.\n\nWant the SOP? DM me.\nLike the content? Check this out:\n\ud83d\ude80 Book a FREE SEO strategy Session \ud83d\udc49 go.juliangoldie.com/strategy-sessi\u2026\n\ud83d\udd17 Free SEO Course \ud83d\udc49 go.juliangoldie.com/opt-in-3672?ut\u2026\n\ud83d\udcb0 Want more money, traffic and sales from SEO? Join the SEO Elite Circle \ud83d\udc49 go.juliangoldie.com/register?utm=t\u2026]]>\n    \nBuild anything with DeepSeek-R1, here's how...Your browser does not support the video tag.\n\nWant the SOP? DM me.\nLike the content? Check this out:\n\ud83d\ude80 Book a FREE SEO strategy Session \ud83d\udc49 go.juliangoldie.com/strategy-sessi\u2026\n\ud83d\udd17 Free SEO Course \ud83d\udc49 go.juliangoldie.com/opt-in-3672?ut\u2026\n\ud83d\udcb0 Want more money, traffic and sales from SEO? Join the SEO Elite Circle \ud83d\udc49 go.juliangoldie.com/register?utm=t\u2026]]>\n  \n  \n    \u00fe\u00ff[EXT] Represent Overview _December 2024\n    https://readwise.io/reader/document_raw_content/263554642\n    readwise:01jjb37gr5y3mekxpn0bgcyk38\n    Fri, 24 Jan 2025 02:46:03 +0000\n    readwise.io\n    \n\n\n73%\n\nOF CREATORS\nDO NOT HAVE REPRESENTATION\n\u2026.HOWEVER\n\n\nCREATORS NEED OPERATIONAL SUPPORT & GUIDANCE FROM TRUSTED EXPERTS\n\nT E\n\nPROBLEM\n\nWhat happens to the 73% of creators without representation?\n\n\n\nLow-balled / inequitable deals\n\nInconsistent deal \ufb02ow\n\nLack of strategy\n\nLack of mentorship\n\nLack of operational support\n\nStunted Growth\nThat\u2019s unacceptable for this saturated multi- billion dollar market.\n\nTHE\nSUSTAINABLE\nSOLUTION\n\nRepresent is a B2C2B subscription service featuring tech-enabled tools and an expert marketplace for professional development for creators.\nOur mission is to close the gap between access, information, and action for creators to realize their goals.\n\nOur vision is to build the most useful & largest global resource for creators to upskill their career unlocking wealth potential.\nCreators get the bene\ufb01ts of representation without the messy middle.\n\nIt\u2019s go time.\n\n\n\n\n1 in 4 American kids want to become an infiuencer\n\n200M Active Creators 66% are Part Time\n\n6% of early-stage\nCreators (<1 Yr Experience) have monetized to 10K+\n\nTradition commission structures can be costly\n\n80% of Creators enjoy their work\n\nNearly 25% of Creators earn $50K\n\n64% of Creators are women\n\n44% Creators say this is their families primary source of\n\nNOW\nIS\nTHE TIME\nWe are at the center of a cultural zeitgeist & career movement\n\nincome\n\nOUR\nBELIEF\n\nWhen we operationalize our social and creative capital, we can positively increase the wealth outcomes for ALL creators.\n\nMEET\nTHE\nFOUNDER\nCreator Economy Expert, Entrepreneur and Coach.\n\u201cI help creators increase their wealth outcomes & access the freedom they\ndeserve.\u201d\n- Tiffany  ardin\n\nFormer Talent Manager (fmr Violator Management & Independently)\n\nAward Winning Marketer & Leader - 20 Years Creator Economy Experience\n\nFacilitator, Presenter & Professor for NYU, AWS, Amazon, FFC, Billboard\n\nConference Speaker AdWeek, Social Media Week, AdAge, Adcolor, ROI Summit\nDeveloped campaigns with Fortune 500 clients like Victoria\u2019s Secret, Hulu, WeWork, Microsoft, and Rocket Mortgage\nDistributed millions in talent payments with her agency\n\nCreator Coach & Advocate B2B Creator with Hubspot, Sprout Social and more\n\nCommunity leader to Adcolor, Harlem\u2019s Fashion Row, Heal Haus, Soul 4 Soles, and Nashville Rep Theater\n\n\nMEET \nTHE TEAM\nOpalescent, Head of Product\n\nTBC, Head of Operations, Team & Product\n\nSophie Ash, Sr Manager, Marketplaces & Community\n\nTBC, Sr Manager, Marketing & Sales\n\nOUR\nECOSYSTEM\n\n \n\n\nFULL FUNNEL CREATOR MARKETING AGENCY\n\nCREATOR PLATFORM\n \n\n\nDynamic Marketplace of Experts\nUseful Tech Tools, Templates & Community\nCREATORS\nCreative Corporate Partnerships\nIn-House Creator Support Specialists\n\nOUR\nFLYWHEEL\n\n\nTHE\nPLATFORM\nCreators will sign up for a subscription and use the web-based app to get started & get paired with a creator support manager to assess their needs, connect them to tools, curate matches in the expert marketplace and suggest opportunities for them.\n\n\nTech Enabled Tools\n\nExpert Support Managers\n \n\n\nExpert Marketplace\n\nContract Readers Pricing Calculators Platform Assessments Analytic Guidance Business Templates\n\nTop Mid-Career & Executive Professionals, Experts, Mentors, and Coaches\nAccount Executives Creator Support Specialists Data Analysts\n\n\nCommunity\n\n\nCommunity Newsle\ue009ers Chat Room Partner Perks\nOpportunity Shares\n\n\nPRICING\n\n \n\n\nMEETING THE\n\nCREATOR DEMAND\n\n\u201cAm I pricing myself appropriately?\u201d\n- @christalluster IG: 474K\n\n\u201cHow can I get more quali\ufb01ed brand deals?\u201d - @reggiecouz\nIG: 2.8M\n\u201cIs this deal going to bite me later?\u201d\n- @rachelrodgers IG: 193K\n\n\u201cWho can I talk to about building merchandise from my brand?\u201d\n-@lidiasalzar\nIG: 222K TKTK: 460K\n\n\nOUR\nTARGET?\nPrimary:\n\n\n25-35 years old single woman with a full-time job in the city averaging 60K-75K per year\n\nSpends $200-500 per month on creator tools and subscriptions to support the growth of her social channels.\n\nHustles 20-30 hours of her time on building her creator business. On average she earns an extra $50K per year with brand deals and a\ue007iliate revenue.\n\nSecondary Customer:\n\nEnterprises o\ue007ering programming & relationship building e\ue007orts for their \u201ccreators cohorts/academies/funds\u201d\n\n\nOUR\n\nCOMPETITORS\n\n\nBUSINESS\nMODEL\n\nPRIMARY\nB2C SUBSCRIPTION MODEL\n\n\nMonthly Creator Subscriptions\n\nMonthly subscription for in\ufb02uencers/creators for access to tools and marketplace\n$79/mo - Basic\n$500/mo - Premium\nSECONDARY\nB2B RETAINER MODEL\n\n\nCorporate Partners\n\n\nRetainer fee for brands to receive curation services, proprietary cohort management\nTERTIARY\nB2B AFFILIATE MODEL\n\n\nBrand Affiliate Partners\n\nRepresent to earn a\ue007iliate revenue from brands that target creators for products, goods, services\n\n\nCurrent TAM is $250B\n\nTAM- SAM-\nSOM\n\nCreator Economy to\nGrow to $500B in 2027\n\n66%of 200M Creators\n25%\n\n1% of 132M Creators\nof 1.32M Creators that earn at least 50K\nSOM SWEET SPOT:\n330,000\nCreators/Users\n\nSource: In\ufb02uencer Marketing Hub & Goldman Sachs Intelligence\n\nTHE\n\nPaid Users\nAnnual Fee ($79/mo)\nTotal\n100\n$948\n94,800\n1,000\n$948\n948,000\n10,000\n$948\n9,480,000\n330,000 (SOM)\n$948\n$313,000,000\n\nREVENUE*\n\n**More Complete Financial Projections Available Upon Request\n\n\nSTART UP\nCOSTS\n\nProduct Development & Support              \u20ac200,000\nOperations            \u20ac200,000\n\nSalaries            \u20ac500,000\nMarketing\n\u20ac100,000\n\n\n\n\u20ac1,000,000\n\nT E\n\nASK\n\nWe are seeking angel investors and strategic partners for a \u20ac1M pre-seed round in a rolling close.\n\nWe are seeking check sizes starting at\n\u20ac25,000 for institutions and starting at\n\u20ac5,000 for individual investors.\n\nInvestors will receive a SAFE note upon agreement.\n\n\nLOOKING\nAHEAD\n 2024 \n\n 2025 \n\n\nMake Key Hires\n\n\nLaunch Beta\n 2023 \n\n\nInitiate Research Project\n\n\nDevelop Prototype\n\nProduct Market Fit\n\n\nStart Seed Round Raise\n\n\nBegin Creator Waitlist\n\n\nBegin Creator Education\n\n\nBegin Marketplace Waitlist\n\n\nProduct Build\n\n\nHire Ops\n\n\n\nGain Market Traction\n\n\nLaunch Marketing/PR Campaigns\n\n\nIterate & Grow\n\n\n\n\nJOIN US\nTiffany Hardin, Founder tiffany@represent.biz\n]]>\n    \n\n\n73%\n\nOF CREATORS\nDO NOT HAVE REPRESENTATION\n\u2026.HOWEVER\n\n\nCREATORS NEED OPERATIONAL SUPPORT & GUIDANCE FROM TRUSTED EXPERTS\n\nT E\n\nPROBLEM\n\nWhat happens to the 73% of creators without representation?\n\n\n\nLow-balled / inequitable deals\n\nInconsistent deal \ufb02ow\n\nLack of strategy\n\nLack of mentorship\n\nLack of operational support\n\nStunted Growth\nThat\u2019s unacceptable for this saturated multi- billion dollar market.\n\nTHE\nSUSTAINABLE\nSOLUTION\n\nRepresent is a B2C2B subscription service featuring tech-enabled tools and an expert marketplace for professional development for creators.\nOur mission is to close the gap between access, information, and action for creators to realize their goals.\n\nOur vision is to build the most useful & largest global resource for creators to upskill their career unlocking wealth potential.\nCreators get the bene\ufb01ts of representation without the messy middle.\n\nIt\u2019s go time.\n\n\n\n\n1 in 4 American kids want to become an infiuencer\n\n200M Active Creators 66% are Part Time\n\n6% of early-stage\nCreators (<1 Yr Experience) have monetized to 10K+\n\nTradition commission structures can be costly\n\n80% of Creators enjoy their work\n\nNearly 25% of Creators earn $50K\n\n64% of Creators are women\n\n44% Creators say this is their families primary source of\n\nNOW\nIS\nTHE TIME\nWe are at the center of a cultural zeitgeist & career movement\n\nincome\n\nOUR\nBELIEF\n\nWhen we operationalize our social and creative capital, we can positively increase the wealth outcomes for ALL creators.\n\nMEET\nTHE\nFOUNDER\nCreator Economy Expert, Entrepreneur and Coach.\n\u201cI help creators increase their wealth outcomes & access the freedom they\ndeserve.\u201d\n- Tiffany  ardin\n\nFormer Talent Manager (fmr Violator Management & Independently)\n\nAward Winning Marketer & Leader - 20 Years Creator Economy Experience\n\nFacilitator, Presenter & Professor for NYU, AWS, Amazon, FFC, Billboard\n\nConference Speaker AdWeek, Social Media Week, AdAge, Adcolor, ROI Summit\nDeveloped campaigns with Fortune 500 clients like Victoria\u2019s Secret, Hulu, WeWork, Microsoft, and Rocket Mortgage\nDistributed millions in talent payments with her agency\n\nCreator Coach & Advocate B2B Creator with Hubspot, Sprout Social and more\n\nCommunity leader to Adcolor, Harlem\u2019s Fashion Row, Heal Haus, Soul 4 Soles, and Nashville Rep Theater\n\n\nMEET \nTHE TEAM\nOpalescent, Head of Product\n\nTBC, Head of Operations, Team & Product\n\nSophie Ash, Sr Manager, Marketplaces & Community\n\nTBC, Sr Manager, Marketing & Sales\n\nOUR\nECOSYSTEM\n\n \n\n\nFULL FUNNEL CREATOR MARKETING AGENCY\n\nCREATOR PLATFORM\n \n\n\nDynamic Marketplace of Experts\nUseful Tech Tools, Templates & Community\nCREATORS\nCreative Corporate Partnerships\nIn-House Creator Support Specialists\n\nOUR\nFLYWHEEL\n\n\nTHE\nPLATFORM\nCreators will sign up for a subscription and use the web-based app to get started & get paired with a creator support manager to assess their needs, connect them to tools, curate matches in the expert marketplace and suggest opportunities for them.\n\n\nTech Enabled Tools\n\nExpert Support Managers\n \n\n\nExpert Marketplace\n\nContract Readers Pricing Calculators Platform Assessments Analytic Guidance Business Templates\n\nTop Mid-Career & Executive Professionals, Experts, Mentors, and Coaches\nAccount Executives Creator Support Specialists Data Analysts\n\n\nCommunity\n\n\nCommunity Newsle\ue009ers Chat Room Partner Perks\nOpportunity Shares\n\n\nPRICING\n\n \n\n\nMEETING THE\n\nCREATOR DEMAND\n\n\u201cAm I pricing myself appropriately?\u201d\n- @christalluster IG: 474K\n\n\u201cHow can I get more quali\ufb01ed brand deals?\u201d - @reggiecouz\nIG: 2.8M\n\u201cIs this deal going to bite me later?\u201d\n- @rachelrodgers IG: 193K\n\n\u201cWho can I talk to about building merchandise from my brand?\u201d\n-@lidiasalzar\nIG: 222K TKTK: 460K\n\n\nOUR\nTARGET?\nPrimary:\n\n\n25-35 years old single woman with a full-time job in the city averaging 60K-75K per year\n\nSpends $200-500 per month on creator tools and subscriptions to support the growth of her social channels.\n\nHustles 20-30 hours of her time on building her creator business. On average she earns an extra $50K per year with brand deals and a\ue007iliate revenue.\n\nSecondary Customer:\n\nEnterprises o\ue007ering programming & relationship building e\ue007orts for their \u201ccreators cohorts/academies/funds\u201d\n\n\nOUR\n\nCOMPETITORS\n\n\nBUSINESS\nMODEL\n\nPRIMARY\nB2C SUBSCRIPTION MODEL\n\n\nMonthly Creator Subscriptions\n\nMonthly subscription for in\ufb02uencers/creators for access to tools and marketplace\n$79/mo - Basic\n$500/mo - Premium\nSECONDARY\nB2B RETAINER MODEL\n\n\nCorporate Partners\n\n\nRetainer fee for brands to receive curation services, proprietary cohort management\nTERTIARY\nB2B AFFILIATE MODEL\n\n\nBrand Affiliate Partners\n\nRepresent to earn a\ue007iliate revenue from brands that target creators for products, goods, services\n\n\nCurrent TAM is $250B\n\nTAM- SAM-\nSOM\n\nCreator Economy to\nGrow to $500B in 2027\n\n66%of 200M Creators\n25%\n\n1% of 132M Creators\nof 1.32M Creators that earn at least 50K\nSOM SWEET SPOT:\n330,000\nCreators/Users\n\nSource: In\ufb02uencer Marketing Hub & Goldman Sachs Intelligence\n\nTHE\n\nPaid Users\nAnnual Fee ($79/mo)\nTotal\n100\n$948\n94,800\n1,000\n$948\n948,000\n10,000\n$948\n9,480,000\n330,000 (SOM)\n$948\n$313,000,000\n\nREVENUE*\n\n**More Complete Financial Projections Available Upon Request\n\n\nSTART UP\nCOSTS\n\nProduct Development & Support              \u20ac200,000\nOperations            \u20ac200,000\n\nSalaries            \u20ac500,000\nMarketing\n\u20ac100,000\n\n\n\n\u20ac1,000,000\n\nT E\n\nASK\n\nWe are seeking angel investors and strategic partners for a \u20ac1M pre-seed round in a rolling close.\n\nWe are seeking check sizes starting at\n\u20ac25,000 for institutions and starting at\n\u20ac5,000 for individual investors.\n\nInvestors will receive a SAFE note upon agreement.\n\n\nLOOKING\nAHEAD\n 2024 \n\n 2025 \n\n\nMake Key Hires\n\n\nLaunch Beta\n 2023 \n\n\nInitiate Research Project\n\n\nDevelop Prototype\n\nProduct Market Fit\n\n\nStart Seed Round Raise\n\n\nBegin Creator Waitlist\n\n\nBegin Creator Education\n\n\nBegin Marketplace Waitlist\n\n\nProduct Build\n\n\nHire Ops\n\n\n\nGain Market Traction\n\n\nLaunch Marketing/PR Campaigns\n\n\nIterate & Grow\n\n\n\n\nJOIN US\nTiffany Hardin, Founder tiffany@represent.biz\n]]>\n  \n  \n    ByteDance dropping an Apache 2.0 licensed 2B, 7B & 72B...\n    https://x.com/reach_vb/status/1882055572876656919/?s=12&rw_tt_thread=True\n    readwise:01jj8nxpws07rq26k5kdh1m2zb\n    Thu, 23 Jan 2025 04:15:00 +0000\n    X (formerly Twitter)\n    \nByteDance dropping an Apache 2.0 licensed 2B, 7B & 72B \"reasoning\" agent for computer use was not on my list for this year!! \ud83d\udca5\nBenchmarks look promising? How are the actual vibes?Your browser does not support the video tag.\n\ncheck them out here:\nhuggingface.co/bytedance-rese\u2026]]>\n    \nByteDance dropping an Apache 2.0 licensed 2B, 7B & 72B \"reasoning\" agent for computer use was not on my list for this year!! \ud83d\udca5\nBenchmarks look promising? How are the actual vibes?Your browser does not support the video tag.\n\ncheck them out here:\nhuggingface.co/bytedance-rese\u2026]]>\n  \n  \n    Decentralized AGI \u2665\ufe0f Eliza\n    https://x.com/punk3700/status/1882027728352002139/?rw_tt_thread=True\n    readwise:01jj7dbbyk3t4tngwv5kk8ppzb\n    Wed, 22 Jan 2025 16:25:56 +0000\n    X (formerly Twitter)\n    \nDecentralized AGI \u2665\ufe0f Eliza\nExcited to bring Decentralized DeepSeek-R1 to @ai16zdao Eliza agents.\nYour Eliza agents can now think and reason. Agents' thoughts and reasonings are all onchain-verifiable on @base. \nDeveloper guide: https://t.co/AFGNBSUmWS\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Eternal AI\n                    @CryptoEternalAI\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nDEVELOPER GUIDE\nLet's build a very different kind of Eliza agent. \n- Powerful DeepSeek-R1 by @deepseek_ai- Decentralized inference by @CryptoEternalAI- Agentic framework by @ai16zdao - Smart contracts on @base\nCode example below \ud83d\udd3d\n            \n            \n\n                \n                    Posted Jan 22, 2025 at 11:20AM\n                \n            \n        ]]>\n    \nDecentralized AGI \u2665\ufe0f Eliza\nExcited to bring Decentralized DeepSeek-R1 to @ai16zdao Eliza agents.\nYour Eliza agents can now think and reason. Agents' thoughts and reasonings are all onchain-verifiable on @base. \nDeveloper guide: https://t.co/AFGNBSUmWS\n        \n\n            \n\n                \n\n                    \n                \n                \n\n                    Eternal AI\n                    @CryptoEternalAI\n                \n                \n\n                    \n                        \n        \n\n\n        \n                    \n                \n            \n            \n\n            \nDEVELOPER GUIDE\nLet's build a very different kind of Eliza agent. \n- Powerful DeepSeek-R1 by @deepseek_ai- Decentralized inference by @CryptoEternalAI- Agentic framework by @ai16zdao - Smart contracts on @base\nCode example below \ud83d\udd3d\n            \n            \n\n                \n                    Posted Jan 22, 2025 at 11:20AM\n                \n            \n        ]]>\n  \n  \n    The next billion dollar companies are being built on Solana\n    https://x.com/solana/status/1881734577934524767/?rw_tt_thread=True\n    readwise:01jj53m7w63j9r60bpf1yj1cer\n    Tue, 21 Jan 2025 18:57:32 +0000\n    X (formerly Twitter)\n    \nThe next billion dollar companies are being built on Solana.\nIt\u2019s time to go founder mode \u2014 here are the resources you need to grow your crypto startup from 0 to 100 \ud83e\uddf5Your browser does not support the video tag.\n\nGlobal online Solana hackathons by @colosseum are the #1 source for talent discovery in crypto, with past winners going on to raise $650 million in funding.\n1,300 teams in 150 countries participated in the last hackathon \u2014 the largest in crypto.\n\nTechnically strong but need to scale your GTM and business ops?\nThe @heliuslabs Startup Launchpad and @0xMert_'s bald head has got you covered.\nAccelerate growth with 8 months of Helius infra, mentorship from Solana veterans, and access to battle-tested investors.Your browser does not support the video tag.\n\nA leading ecosystem-agnostic crypto accelerator is @alliancedao, with 3,000 yearly applicants. Its recent report showcased the growth of startups on Solana.\n18% of applicants for its H1\u201924 cohort built on Solana, up from 8% in H2\u201922.\nApply to their next cohort by Feb 26th.\n\nFounder looking to accelerate? Stay ready for the next rounds of applications for these programs:\n\u2192 @solanalabs\u2019 Incubator, with 3 months of support in NYC\u2192 @OrangeDAOxyz's Accelerator\u2192 @HackQuest_'s Solaris MCM Accelerator\n\nJoin crypto\u2019s talent layer and get involved with a local @superteam chapter.\nConnect with Solana-native builders around the world, share resources, and harden your startup by building in public \u2014 together.\nSuperteam members have collectively earned $9.5m GDP.\n\nNetwork and work with builders around the globe at Solana community coworking hubs, including:\n- Startup Villages hosted by @superteam divisions- @mtndao, the month-long build event in Salt Lake City- @formacity Solana Economic Zones- @shipyard_, a network of ecosystem workspaces- @SuperteamAE\u2019s Founders\u2019 Villas- @islandDAO_DL, a month-long coworking space following Breakpoint\n\nConnect with and ship alongside a globally distributed, curated community of Solana builders by joining the @luciddrakes Startup Society.\nTheir venture arm, Lucid Ventures, invests in and helps incubate Solana startups.\n\nHave technical talent who need to get up to speed on Solana? Check out:\n\u2192 @solanaturbine\u2019s dev incubator programs\u2192 @AckeeBlockchain\u2019s School of Solana bootcamps\u2192 @SolanaFndn\u2019s self-paced 20 hour developer bootcamp video series\n\nBuilding a crypto x AI startup? Solana has the tools you need to ship.\n@sendaifun\u2019s open source Solana Agent Kit features 15+ Solana protocol integrations.\n@ai16zdao's Eliza framework & @Crossmint\u2019s GOAT framework help create, deploy, and manage autonomous AI agents on Solana.\n\nWant to bootstrap distribution for your live product?\n1\ufe0f\u20e3 Find and partner with a Solana native content creator via @superteam\u2019s Solana-native creator database.\n\n2\ufe0f\u20e3 Raise rounds and bootstrap distribution with community support from investors who have skin in the game.\nCheck out @echodotxyz and @legiondotcc \u2014 Capital formation is quickly changing, and Solana users and founders are the best marketing.\n\nX hates links so we put them all here at the end.\nBookmark this \u2014 it\u2019s time to accelerate your startup on Solana \ud83e\udee1\nHelius Startup Launchpad \u2192 https://t.co/N8f6WiodwTColosseum Hackathons \u2192 https://t.co/M8zG8STniFAlliance Accelerator \u2192 https://t.co/b86cIxlUvkOrangeDAO Accelerator \u2192 https://t.co/FPvLdwk2jfHackquest MCM Accelerator \u2192 https://t.co/NMcscL07WZSolana Labs Incubator \u2192 https://t.co/pjsYs8do4NLucid Drakes Startup Society \u2192 https://t.co/DgbnvKsgZ3Solana Developer Bootcamp \u2192 https://t.co/miW35uGXUvTurbine Developer Incubator \u2192 https://t.co/D4wY4cXxxIAckee Developer School \u2192 https://t.co/BL6YJyOLPHSolana x AI resources \u2192 https://t.co/HtuOyT9bEcSuperteam Chapters \u2192 https://t.co/YqM58RHyNCSolana Creator Database \u2192 https://t.co/k0Oynoo8XGRaising on Echo \u2192 https://t.co/kgOGVHHgdgRaising on Legion \u2192 https://t.co/Vefzq9Zfm0]]>\n    \nThe next billion dollar companies are being built on Solana.\nIt\u2019s time to go founder mode \u2014 here are the resources you need to grow your crypto startup from 0 to 100 \ud83e\uddf5Your browser does not support the video tag.\n\nGlobal online Solana hackathons by @colosseum are the #1 source for talent discovery in crypto, with past winners going on to raise $650 million in funding.\n1,300 teams in 150 countries participated in the last hackathon \u2014 the largest in crypto.\n\nTechnically strong but need to scale your GTM and business ops?\nThe @heliuslabs Startup Launchpad and @0xMert_'s bald head has got you covered.\nAccelerate growth with 8 months of Helius infra, mentorship from Solana veterans, and access to battle-tested investors.Your browser does not support the video tag.\n\nA leading ecosystem-agnostic crypto accelerator is @alliancedao, with 3,000 yearly applicants. Its recent report showcased the growth of startups on Solana.\n18% of applicants for its H1\u201924 cohort built on Solana, up from 8% in H2\u201922.\nApply to their next cohort by Feb 26th.\n\nFounder looking to accelerate? Stay ready for the next rounds of applications for these programs:\n\u2192 @solanalabs\u2019 Incubator, with 3 months of support in NYC\u2192 @OrangeDAOxyz's Accelerator\u2192 @HackQuest_'s Solaris MCM Accelerator\n\nJoin crypto\u2019s talent layer and get involved with a local @superteam chapter.\nConnect with Solana-native builders around the world, share resources, and harden your startup by building in public \u2014 together.\nSuperteam members have collectively earned $9.5m GDP.\n\nNetwork and work with builders around the globe at Solana community coworking hubs, including:\n- Startup Villages hosted by @superteam divisions- @mtndao, the month-long build event in Salt Lake City- @formacity Solana Economic Zones- @shipyard_, a network of ecosystem workspaces- @SuperteamAE\u2019s Founders\u2019 Villas- @islandDAO_DL, a month-long coworking space following Breakpoint\n\nConnect with and ship alongside a globally distributed, curated community of Solana builders by joining the @luciddrakes Startup Society.\nTheir venture arm, Lucid Ventures, invests in and helps incubate Solana startups.\n\nHave technical talent who need to get up to speed on Solana? Check out:\n\u2192 @solanaturbine\u2019s dev incubator programs\u2192 @AckeeBlockchain\u2019s School of Solana bootcamps\u2192 @SolanaFndn\u2019s self-paced 20 hour developer bootcamp video series\n\nBuilding a crypto x AI startup? Solana has the tools you need to ship.\n@sendaifun\u2019s open source Solana Agent Kit features 15+ Solana protocol integrations.\n@ai16zdao's Eliza framework & @Crossmint\u2019s GOAT framework help create, deploy, and manage autonomous AI agents on Solana.\n\nWant to bootstrap distribution for your live product?\n1\ufe0f\u20e3 Find and partner with a Solana native content creator via @superteam\u2019s Solana-native creator database.\n\n2\ufe0f\u20e3 Raise rounds and bootstrap distribution with community support from investors who have skin in the game.\nCheck out @echodotxyz and @legiondotcc \u2014 Capital formation is quickly changing, and Solana users and founders are the best marketing.\n\nX hates links so we put them all here at the end.\nBookmark this \u2014 it\u2019s time to accelerate your startup on Solana \ud83e\udee1\nHelius Startup Launchpad \u2192 https://t.co/N8f6WiodwTColosseum Hackathons \u2192 https://t.co/M8zG8STniFAlliance Accelerator \u2192 https://t.co/b86cIxlUvkOrangeDAO Accelerator \u2192 https://t.co/FPvLdwk2jfHackquest MCM Accelerator \u2192 https://t.co/NMcscL07WZSolana Labs Incubator \u2192 https://t.co/pjsYs8do4NLucid Drakes Startup Society \u2192 https://t.co/DgbnvKsgZ3Solana Developer Bootcamp \u2192 https://t.co/miW35uGXUvTurbine Developer Incubator \u2192 https://t.co/D4wY4cXxxIAckee Developer School \u2192 https://t.co/BL6YJyOLPHSolana x AI resources \u2192 https://t.co/HtuOyT9bEcSuperteam Chapters \u2192 https://t.co/YqM58RHyNCSolana Creator Database \u2192 https://t.co/k0Oynoo8XGRaising on Echo \u2192 https://t.co/kgOGVHHgdgRaising on Legion \u2192 https://t.co/Vefzq9Zfm0]]>\n  \n  \n    I am rich and have no idea what to do with my life\n    https://vinay.sh/i-am-rich-and-have-no-idea-what-to-do-with-my-life/\n    readwise:01jhg0gmm78vnw5mph9fpjp3ya\n    Mon, 13 Jan 2025 14:19:05 +0000\n    vinay.sh\n    Life has been a haze this last year. After selling my company, I find myself in the totally un-relatable position of never having to work again. Everything feels like a side quest, but not in an inspiring way. I don\u2019t have the same base desires driving me to make money or gain status. I have infinite freedom, yet I don\u2019t know what to do with it, and, honestly, I\u2019m not the most optimistic about life.\n\nI know. This is a completely zeroth-world position to be in. The point of this post isn\u2019t to brag or gain sympathy. To be honest, I don\u2019t exactly know what the point of this post is. I tried to manufacture one, but I just felt like a phony. Then I recognized the irony of creating purpose out of a blog post when I don\u2019t currently have much conviction or purpose in life.\n\nSo I\u2019ll just go ahead and explain my current situation for my own selfish purposes. To push myself to be completely (and awkwardly) vulnerable to a blob of nameless strangers over the internet. No expectations of what comes out of it.\n\nGoing to the redwoods and giving up $60m\n\nLast March I had no idea what to do with my life. I knew that staying at the acquiring company was not it for me for the big company reasons you might suspect (lots of politics, things moved slowly, NPC coworkers, etc.), but I found it very hard to give up a $60m pay package. I had already made more money than I knew what to do with, but your mind does funny things when you start to consider numbers like this.\n\nSo I decided to go to the redwoods and figure it out.\n\nWithin 5 minutes of my first hike, the trees smiled at me and whispered their simple wisdom.\n\nWhat is the point of money if it not for freedom?\n\nWhat is your most scarce resource if not time?\n\nI would leave to do something. Anything. To be alive again. I had no idea. But I was hell bent on making sure everyone knew I had it all figured out. Out of ego. Out of fear of wading into the unknown. When you work on something that consumes your life for a decade, it\u2019s hard to let go of the certainty and purpose you\u2019ve grown accustomed to.\n\nRobotics, or my cringe \u201ctrying to be Elon\u201d phase\n\nThe immediate 2 weeks after leaving an intense 10-year journey, I did what any healthy person does and met with over 70 investors and founders in robotics. I had been learning about robotics for quite some time and was positive I wanted to throw myself into giving computers arms and legs. I had come up with all the tag lines to delude myself into thinking this was my \u201clife\u2019s calling\u201d. Everything had been \u201cleading to this exact point\u201d.\n\n\u201cThe world is going through a major labor shortage!\u201d\n\n\u201cWe must stay competitive against China!\u201d\n\n\u201cThe market for highly repetitive labor is multiple trillions of dollars.\u201d\n\nAt the end of the 2 weeks, I left feeling deflated and foolish. I didn\u2019t want to start a robotics company. The only thing that seemed interesting to me was humanoids. It started to dawn on me that what I actually wanted was to look like Elon, and that is incredibly cringe. It hurts to even type this out.\n\nBreaking up with my girlfriend and realizing I\u2019m very insecure\n\nAfter deciding to not start a robotics company, I found myself rudderless. No sense of direction. I traveled to many beautiful places with my loving and supportive (ex) girlfriend. This 6 month stretch could be several essays on its own, but the outcome of this period is that nothing seemed right.\n\nWe started getting into regular arguments, and I knew it wasn\u2019t on her. It was me. I was starting to come to terms with all the mounting insecurities I had stuffed down over the past several years. I didn\u2019t feel like I could work on them with her. So I broke things off after almost 2 years of unconditional love. It was extremely painful, but it was the right call. I needed to fully face myself.\n\nI have only started to realize that, when Loom was in its early innings, I felt very secure with my position in life, and lots of this stemmed from an extreme gratitude for the journey I was on. I was happy with everything as it was. The growth trajectory of the company was more than I could ever dream for. I was happy. I felt secure. It could all turn to shit the next day, and that would be ok.\n\nThen, as the company continued to skyrocket to new heights, I started to have growing expectations for myself, and others started to have growing expectations of me. When we went through our first round of layoffs, this company my ego was hitched to had suffered a massive blow, so I lost myself. This whole chapter of Loom has created a complex web of internalized insecurities I must now work hard to disentangle and free myself from.\n\n(If my ex is reading this. Thank you for everything. I am sorry I couldn\u2019t be what you needed me to be.)\n\nClimbing mountains in the Himalayas, remembering to do hard things\n\nAfter breaking up with my girlfriend, I did what any healthy person would do and decided to externalize my emotions by climbing a 6800m peak in the Himalayas with absolutely no mountaineering experience or training. In the earliest stages of trekking into the valley, before the altitude sickness, cold, and chronic bronchitis started to settle in, this seemed like the best idea in the world. It wasn\u2019t until every person I met along the way asked how long I had been training for, that it started to settle in how insane what I was doing was.\n\nNeedless to say, there were some rough patches. I got very hypoxic on one of my summits and had to repel down cliff faces while tripping out of my mind. In the end, I pushed through, completed both my planned summits, and got reacquainted with how important doing hard things is to me. It is the heart beat of my life, and I don\u2019t 100% understand why, but it probably has something to do with me having not the best childhood.\n\nWhen I got back home and regaled my friends with my mountain stories, one of my friends joked that I should work for Elon and Vivek at DOGE and help America get off its current crash to defaulting on its own debt. So I reached out to some people and got in. After 8 calls with people who all talked fast and sounded very autistic smart, I was added to a number of Signal groups and immediately put to work.\n\nWorking for DOGE for 4 weeks, remembering the power of urgency\n\nWithin 2 minutes of talking to the final interviewer for DOGE, he asked me if I wanted to join. I said \u201cyes\u201d. Then he said \u201ccool\u201d and I was in multiple Signal groups. I was immediately acquainted with the software, HR, and legal teams and went from 0 to 100 taking meetings and getting shit done. This was the day before Thanksgiving.\n\nThe next 4 weeks of my life consisted of 100s of calls recruiting the smartest people I\u2019ve ever talked to, working on various projects I\u2019m definitely not able to talk about, and learning how completely dysfunctional the government was. It was a blast.\n\nI learned about the power of urgency and having an undeniable mission. Not by reading it somewhere. By experiencing it. I came to realize how laughable my robotics stint had been in comparison. And I started to realize that, although the mission of DOGE is extremely important, it wasn\u2019t the most important thing I needed to focus on with urgency for myself. I needed to get back to ambiguity, focus on my insecurities, and be ok with that for a while. DOGE wasn\u2019t going to fix that.\n\nSo, after 4 intense and intoxicating weeks, I called off my plans to move to DC and embark on a journey to save our government with some of the smartest people I\u2019ve ever met. And I booked a 1-way ticket to Hawaii.\n\nStudying physics in the jungle, focusing on my insecurities\n\nSo now I\u2019m in Hawaii. I\u2019m learning physics. Why? The reason I tell myself is to build up my first principles foundation so I can start a company that manufactures real world things. It seems plausible, but I\u2019m learning to just accept that I am happy learning physics. That\u2019s the goal in and of itself. If it leads to nothing, that\u2019s ok. If this means I\u2019ll never do something as spectacular as Loom, so be it. It\u2019s been too long since I\u2019ve been completely raw and real with myself, so I\u2019m applying a healthy dose of humility to everything I say and do. It\u2019s the only thing that feels authentic.\n\nHowever, there are some questions left unanswered.\n\nWhy did I need to do the absolute most to reach this point?\n\nWhy couldn\u2019t I just leave Loom and say \u201cI don\u2019t know what I want to do next\u201d?\n\nWhy do I feel the need to only be on a journey if it\u2019s grand?\n\nWhat is wrong with being insignificant?\n\nWhy is letting people down so hard?\n\nI don\u2019t know. But I\u2019m going to find out.]]>\n    Life has been a haze this last year. After selling my company, I find myself in the totally un-relatable position of never having to work again. Everything feels like a side quest, but not in an inspiring way. I don\u2019t have the same base desires driving me to make money or gain status. I have infinite freedom, yet I don\u2019t know what to do with it, and, honestly, I\u2019m not the most optimistic about life.\n\nI know. This is a completely zeroth-world position to be in. The point of this post isn\u2019t to brag or gain sympathy. To be honest, I don\u2019t exactly know what the point of this post is. I tried to manufacture one, but I just felt like a phony. Then I recognized the irony of creating purpose out of a blog post when I don\u2019t currently have much conviction or purpose in life.\n\nSo I\u2019ll just go ahead and explain my current situation for my own selfish purposes. To push myself to be completely (and awkwardly) vulnerable to a blob of nameless strangers over the internet. No expectations of what comes out of it.\n\nGoing to the redwoods and giving up $60m\n\nLast March I had no idea what to do with my life. I knew that staying at the acquiring company was not it for me for the big company reasons you might suspect (lots of politics, things moved slowly, NPC coworkers, etc.), but I found it very hard to give up a $60m pay package. I had already made more money than I knew what to do with, but your mind does funny things when you start to consider numbers like this.\n\nSo I decided to go to the redwoods and figure it out.\n\nWithin 5 minutes of my first hike, the trees smiled at me and whispered their simple wisdom.\n\nWhat is the point of money if it not for freedom?\n\nWhat is your most scarce resource if not time?\n\nI would leave to do something. Anything. To be alive again. I had no idea. But I was hell bent on making sure everyone knew I had it all figured out. Out of ego. Out of fear of wading into the unknown. When you work on something that consumes your life for a decade, it\u2019s hard to let go of the certainty and purpose you\u2019ve grown accustomed to.\n\nRobotics, or my cringe \u201ctrying to be Elon\u201d phase\n\nThe immediate 2 weeks after leaving an intense 10-year journey, I did what any healthy person does and met with over 70 investors and founders in robotics. I had been learning about robotics for quite some time and was positive I wanted to throw myself into giving computers arms and legs. I had come up with all the tag lines to delude myself into thinking this was my \u201clife\u2019s calling\u201d. Everything had been \u201cleading to this exact point\u201d.\n\n\u201cThe world is going through a major labor shortage!\u201d\n\n\u201cWe must stay competitive against China!\u201d\n\n\u201cThe market for highly repetitive labor is multiple trillions of dollars.\u201d\n\nAt the end of the 2 weeks, I left feeling deflated and foolish. I didn\u2019t want to start a robotics company. The only thing that seemed interesting to me was humanoids. It started to dawn on me that what I actually wanted was to look like Elon, and that is incredibly cringe. It hurts to even type this out.\n\nBreaking up with my girlfriend and realizing I\u2019m very insecure\n\nAfter deciding to not start a robotics company, I found myself rudderless. No sense of direction. I traveled to many beautiful places with my loving and supportive (ex) girlfriend. This 6 month stretch could be several essays on its own, but the outcome of this period is that nothing seemed right.\n\nWe started getting into regular arguments, and I knew it wasn\u2019t on her. It was me. I was starting to come to terms with all the mounting insecurities I had stuffed down over the past several years. I didn\u2019t feel like I could work on them with her. So I broke things off after almost 2 years of unconditional love. It was extremely painful, but it was the right call. I needed to fully face myself.\n\nI have only started to realize that, when Loom was in its early innings, I felt very secure with my position in life, and lots of this stemmed from an extreme gratitude for the journey I was on. I was happy with everything as it was. The growth trajectory of the company was more than I could ever dream for. I was happy. I felt secure. It could all turn to shit the next day, and that would be ok.\n\nThen, as the company continued to skyrocket to new heights, I started to have growing expectations for myself, and others started to have growing expectations of me. When we went through our first round of layoffs, this company my ego was hitched to had suffered a massive blow, so I lost myself. This whole chapter of Loom has created a complex web of internalized insecurities I must now work hard to disentangle and free myself from.\n\n(If my ex is reading this. Thank you for everything. I am sorry I couldn\u2019t be what you needed me to be.)\n\nClimbing mountains in the Himalayas, remembering to do hard things\n\nAfter breaking up with my girlfriend, I did what any healthy person would do and decided to externalize my emotions by climbing a 6800m peak in the Himalayas with absolutely no mountaineering experience or training. In the earliest stages of trekking into the valley, before the altitude sickness, cold, and chronic bronchitis started to settle in, this seemed like the best idea in the world. It wasn\u2019t until every person I met along the way asked how long I had been training for, that it started to settle in how insane what I was doing was.\n\nNeedless to say, there were some rough patches. I got very hypoxic on one of my summits and had to repel down cliff faces while tripping out of my mind. In the end, I pushed through, completed both my planned summits, and got reacquainted with how important doing hard things is to me. It is the heart beat of my life, and I don\u2019t 100% understand why, but it probably has something to do with me having not the best childhood.\n\nWhen I got back home and regaled my friends with my mountain stories, one of my friends joked that I should work for Elon and Vivek at DOGE and help America get off its current crash to defaulting on its own debt. So I reached out to some people and got in. After 8 calls with people who all talked fast and sounded very autistic smart, I was added to a number of Signal groups and immediately put to work.\n\nWorking for DOGE for 4 weeks, remembering the power of urgency\n\nWithin 2 minutes of talking to the final interviewer for DOGE, he asked me if I wanted to join. I said \u201cyes\u201d. Then he said \u201ccool\u201d and I was in multiple Signal groups. I was immediately acquainted with the software, HR, and legal teams and went from 0 to 100 taking meetings and getting shit done. This was the day before Thanksgiving.\n\nThe next 4 weeks of my life consisted of 100s of calls recruiting the smartest people I\u2019ve ever talked to, working on various projects I\u2019m definitely not able to talk about, and learning how completely dysfunctional the government was. It was a blast.\n\nI learned about the power of urgency and having an undeniable mission. Not by reading it somewhere. By experiencing it. I came to realize how laughable my robotics stint had been in comparison. And I started to realize that, although the mission of DOGE is extremely important, it wasn\u2019t the most important thing I needed to focus on with urgency for myself. I needed to get back to ambiguity, focus on my insecurities, and be ok with that for a while. DOGE wasn\u2019t going to fix that.\n\nSo, after 4 intense and intoxicating weeks, I called off my plans to move to DC and embark on a journey to save our government with some of the smartest people I\u2019ve ever met. And I booked a 1-way ticket to Hawaii.\n\nStudying physics in the jungle, focusing on my insecurities\n\nSo now I\u2019m in Hawaii. I\u2019m learning physics. Why? The reason I tell myself is to build up my first principles foundation so I can start a company that manufactures real world things. It seems plausible, but I\u2019m learning to just accept that I am happy learning physics. That\u2019s the goal in and of itself. If it leads to nothing, that\u2019s ok. If this means I\u2019ll never do something as spectacular as Loom, so be it. It\u2019s been too long since I\u2019ve been completely raw and real with myself, so I\u2019m applying a healthy dose of humility to everything I say and do. It\u2019s the only thing that feels authentic.\n\nHowever, there are some questions left unanswered.\n\nWhy did I need to do the absolute most to reach this point?\n\nWhy couldn\u2019t I just leave Loom and say \u201cI don\u2019t know what I want to do next\u201d?\n\nWhy do I feel the need to only be on a journey if it\u2019s grand?\n\nWhat is wrong with being insignificant?\n\nWhy is letting people down so hard?\n\nI don\u2019t know. But I\u2019m going to find out.]]>\n  \n  \n    Reflections\n    https://blog.samaltman.com/reflections/\n    readwise:01jhec8gpg1rbg2mm597k21e51\n    Sun, 12 Jan 2025 23:05:53 +0000\n    Sam Altman\n    The second birthday of ChatGPT was only a little over a month ago, and now we have transitioned into the next paradigm of models that can do complex reasoning. New years get people in a reflective mood, and I wanted to share some personal thoughts about how it has gone so far, and some of the things I\u2019ve learned along the way.\n\nAs we get closer to AGI, it feels like an important time to look at the progress of our company. There is still so much to understand, still so much we don\u2019t know, and it\u2019s still so early. But we know a lot more than we did when we started.\n\nWe started OpenAI almost nine years ago because we believed that AGI was possible, and that it could be the most impactful technology in human history. We wanted to figure out how to build it and make it broadly beneficial; we were excited to try to make our mark on history. Our ambitions were extraordinarily high and so was our belief that the work might benefit society in an equally extraordinary way.\n\nAt the time, very few people cared, and if they did, it was mostly because they thought we had no chance of success.\n\nIn 2022, OpenAI was a quiet research lab working on something temporarily called \u201cChat With GPT-3.5\u201d. (We are much better at research than we are at naming things.) We had been watching people use the playground feature of our API and knew that developers were really enjoying talking to the model. We thought building a demo around that experience would show people something important about the future and help us make our models better and safer.\n\nWe ended up mercifully calling it ChatGPT instead, and launched it on November 30th of 2022.\n\nWe always knew, abstractly, that at some point we would hit a tipping point and the AI revolution would get kicked off. But we didn\u2019t know what the moment would be. To our surprise, it turned out to be this.\n\nThe launch of ChatGPT kicked off a growth curve like nothing we have ever seen\u2014in our company, our industry, and the world broadly. We are finally seeing some of the massive upside we have always hoped for from AI, and we can see how much more will come soon.\n\nIt hasn\u2019t been easy. The road hasn\u2019t been smooth and the right choices haven\u2019t been obvious.\n\nIn the last two years, we had to build an entire company, almost from scratch, around this new technology. There is no way to train people for this except by doing it, and when the technology category is completely new, there is no one at all who can tell you exactly how it should be done.\n\nBuilding up a company at such high velocity with so little training is a messy process. It\u2019s often two steps forward, one step back (and sometimes, one step forward and two steps back). Mistakes get corrected as you go along, but there aren\u2019t really any handbooks or guideposts when you\u2019re doing original work. Moving at speed in uncharted waters is an incredible experience, but it is also immensely stressful for all the players. Conflicts and misunderstanding abound.\n\nThese years have been the most rewarding, fun, best, interesting, exhausting, stressful, and\u2014particularly for the last two\u2014unpleasant years of my life so far. The overwhelming feeling is gratitude; I know that someday I\u2019ll be retired at our ranch watching the plants grow, a little bored, and will think back at how cool it was that I got to do the work I dreamed of since I was a little kid. I try to remember that on any given Friday, when seven things go badly wrong by 1 pm.\n\nA little over a year ago, on one particular Friday, the main thing that had gone wrong that day was that I got fired by surprise on a video call, and then right after we hung up the board published a blog post about it. I was in a hotel room in Las Vegas. It felt, to a degree that is almost impossible to explain, like a dream gone wrong.\n\nGetting fired in public with no warning kicked off a really crazy few hours, and a pretty crazy few days. The \u201cfog of war\u201d was the strangest part. None of us were able to get satisfactory answers about what had happened, or why.\n\nThe whole event was, in my opinion, a big failure of governance by well-meaning people, myself included. Looking back, I certainly wish I had done things differently, and I\u2019d like to believe I\u2019m a better, more thoughtful leader today than I was a year ago.\n\nI also learned the importance of a board with diverse viewpoints and broad experience in managing a complex set of challenges. Good governance requires a lot of trust and credibility. I appreciate the way so many people worked together to build a stronger system of governance for OpenAI that enables us to pursue our mission of ensuring that AGI benefits all of humanity.\n\nMy biggest takeaway is how much I have to be thankful for and how many people I owe gratitude towards: to everyone who works at OpenAI and has chosen to spend their time and effort going after this dream, to friends who helped us get through the crisis moments, to our partners and customers who supported us and entrusted us to enable their success, and to the people in my life who showed me how much they cared. [1]\n\nWe all got back to the work in a more cohesive and positive way and I\u2019m very proud of our focus since then. We have done what is easily some of our best research ever. We grew from about 100 million weekly active users to more than 300 million. Most of all, we have continued to put technology out into the world that people genuinely seem to love and that solves real problems.\n\nNine years ago, we really had no idea what we were eventually going to become; even now, we only sort of know. AI development has taken many twists and turns and we expect more in the future.\n\nSome of the twists have been joyful; some have been hard. It\u2019s been fun watching a steady stream of research miracles occur, and a lot of naysayers have become true believers. We\u2019ve also seen some colleagues split off and become competitors. Teams tend to turn over as they scale, and OpenAI scales really fast. I think some of this is unavoidable\u2014startups usually see a lot of turnover at each new major level of scale, and at OpenAI numbers go up by orders of magnitude every few months. The last two years have been like a decade at a normal company. When any company grows and evolves so fast, interests naturally diverge. And when any company in an important industry is in the lead, lots of people attack it for all sorts of reasons, especially when they are trying to compete with it.\n\nOur vision won\u2019t change; our tactics will continue to evolve. For example, when we started we had no idea we would have to build a product company; we thought we were just going to do great research. We also had no idea we would need such a crazy amount of capital. There are new things we have to go build now that we didn\u2019t understand a few years ago, and there will be new things in the future we can barely imagine now.\n\nWe are proud of our track-record on research and deployment so far, and are committed to continuing to advance our thinking on safety and benefits sharing. We continue to believe that the best way to make an AI system safe is by iteratively and gradually releasing it into the world, giving society time to adapt and co-evolve with the technology, learning from experience, and continuing to make the technology safer. We believe in the importance of being world leaders on safety and alignment research, and in guiding that research with feedback from real world applications.\n\nWe are now confident we know how to build AGI as we have traditionally understood it. We believe that, in 2025, we may see the first AI agents \u201cjoin the workforce\u201d and materially change the output of companies. We continue to believe that iteratively putting great tools in the hands of people leads to great, broadly-distributed outcomes.\n\nWe are beginning to turn our aim beyond that, to superintelligence in the true sense of the word. We love our current products, but we are here for the glorious future. With superintelligence, we can do anything else. Superintelligent tools could massively accelerate scientific discovery and innovation well beyond what we are capable of doing on our own, and in turn massively increase abundance and prosperity.\n\nThis sounds like science fiction right now, and somewhat crazy to even talk about it. That\u2019s alright\u2014we\u2019ve been there before and we\u2019re OK with being there again. We\u2019re pretty confident that in the next few years, everyone will see what we see, and that the need to act with great care, while still maximizing broad benefit and empowerment, is so important. Given the possibilities of our work, OpenAI cannot be a normal company.\n\nHow lucky and humbling it is to be able to play a role in this work.\n\n(Thanks to Josh Tyrangiel for sort of prompting this. I wish we had had a lot more time.)\n\n[1]\n\nThere were a lot of people who did incredible and gigantic amounts of work to help OpenAI, and me personally, during those few days, but two people stood out from all others.\n\nRon Conway and Brian Chesky went so far above and beyond the call of duty that I\u2019m not even sure how to describe it. I\u2019ve of course heard stories about Ron\u2019s ability and tenaciousness for years and I\u2019ve spent a lot of time with Brian over the past couple of years getting a huge amount of help and advice.\n\nBut there\u2019s nothing quite like being in the foxhole with people to see what they can really do. I am reasonably confident OpenAI would have fallen apart without their help; they worked around the clock for days until things were done.\n\nAlthough they worked unbelievably hard, they stayed calm and had clear strategic thought and great advice throughout. They stopped me from making several mistakes and made none themselves. They used their vast networks for everything needed and were able to navigate many complex situations. And I\u2019m sure they did a lot of things I don\u2019t know about.\n\nWhat I will remember most, though, is their care, compassion, and support.\n\nI thought I knew what it looked like to support a founder and a company, and in some small sense I did. But I have never before seen, or even heard of, anything like what these guys did, and now I get more fully why they have the legendary status they do. They are different and both fully deserve their genuinely unique reputations, but they are similar in their remarkable ability to move mountains and help, and in their unwavering commitment in times of need. The tech industry is far better off for having both of them in it.\n\nThere are others like them; it is an amazingly special thing about our industry and does much more to make it all work than people realize. I look forward to paying it forward.\n\nOn a more personal note, thanks especially to Ollie for his support that weekend and always; he is incredible in every way and no one could ask for a better partner.]]>\n    The second birthday of ChatGPT was only a little over a month ago, and now we have transitioned into the next paradigm of models that can do complex reasoning. New years get people in a reflective mood, and I wanted to share some personal thoughts about how it has gone so far, and some of the things I\u2019ve learned along the way.\n\nAs we get closer to AGI, it feels like an important time to look at the progress of our company. There is still so much to understand, still so much we don\u2019t know, and it\u2019s still so early. But we know a lot more than we did when we started.\n\nWe started OpenAI almost nine years ago because we believed that AGI was possible, and that it could be the most impactful technology in human history. We wanted to figure out how to build it and make it broadly beneficial; we were excited to try to make our mark on history. Our ambitions were extraordinarily high and so was our belief that the work might benefit society in an equally extraordinary way.\n\nAt the time, very few people cared, and if they did, it was mostly because they thought we had no chance of success.\n\nIn 2022, OpenAI was a quiet research lab working on something temporarily called \u201cChat With GPT-3.5\u201d. (We are much better at research than we are at naming things.) We had been watching people use the playground feature of our API and knew that developers were really enjoying talking to the model. We thought building a demo around that experience would show people something important about the future and help us make our models better and safer.\n\nWe ended up mercifully calling it ChatGPT instead, and launched it on November 30th of 2022.\n\nWe always knew, abstractly, that at some point we would hit a tipping point and the AI revolution would get kicked off. But we didn\u2019t know what the moment would be. To our surprise, it turned out to be this.\n\nThe launch of ChatGPT kicked off a growth curve like nothing we have ever seen\u2014in our company, our industry, and the world broadly. We are finally seeing some of the massive upside we have always hoped for from AI, and we can see how much more will come soon.\n\nIt hasn\u2019t been easy. The road hasn\u2019t been smooth and the right choices haven\u2019t been obvious.\n\nIn the last two years, we had to build an entire company, almost from scratch, around this new technology. There is no way to train people for this except by doing it, and when the technology category is completely new, there is no one at all who can tell you exactly how it should be done.\n\nBuilding up a company at such high velocity with so little training is a messy process. It\u2019s often two steps forward, one step back (and sometimes, one step forward and two steps back). Mistakes get corrected as you go along, but there aren\u2019t really any handbooks or guideposts when you\u2019re doing original work. Moving at speed in uncharted waters is an incredible experience, but it is also immensely stressful for all the players. Conflicts and misunderstanding abound.\n\nThese years have been the most rewarding, fun, best, interesting, exhausting, stressful, and\u2014particularly for the last two\u2014unpleasant years of my life so far. The overwhelming feeling is gratitude; I know that someday I\u2019ll be retired at our ranch watching the plants grow, a little bored, and will think back at how cool it was that I got to do the work I dreamed of since I was a little kid. I try to remember that on any given Friday, when seven things go badly wrong by 1 pm.\n\nA little over a year ago, on one particular Friday, the main thing that had gone wrong that day was that I got fired by surprise on a video call, and then right after we hung up the board published a blog post about it. I was in a hotel room in Las Vegas. It felt, to a degree that is almost impossible to explain, like a dream gone wrong.\n\nGetting fired in public with no warning kicked off a really crazy few hours, and a pretty crazy few days. The \u201cfog of war\u201d was the strangest part. None of us were able to get satisfactory answers about what had happened, or why.\n\nThe whole event was, in my opinion, a big failure of governance by well-meaning people, myself included. Looking back, I certainly wish I had done things differently, and I\u2019d like to believe I\u2019m a better, more thoughtful leader today than I was a year ago.\n\nI also learned the importance of a board with diverse viewpoints and broad experience in managing a complex set of challenges. Good governance requires a lot of trust and credibility. I appreciate the way so many people worked together to build a stronger system of governance for OpenAI that enables us to pursue our mission of ensuring that AGI benefits all of humanity.\n\nMy biggest takeaway is how much I have to be thankful for and how many people I owe gratitude towards: to everyone who works at OpenAI and has chosen to spend their time and effort going after this dream, to friends who helped us get through the crisis moments, to our partners and customers who supported us and entrusted us to enable their success, and to the people in my life who showed me how much they cared. [1]\n\nWe all got back to the work in a more cohesive and positive way and I\u2019m very proud of our focus since then. We have done what is easily some of our best research ever. We grew from about 100 million weekly active users to more than 300 million. Most of all, we have continued to put technology out into the world that people genuinely seem to love and that solves real problems.\n\nNine years ago, we really had no idea what we were eventually going to become; even now, we only sort of know. AI development has taken many twists and turns and we expect more in the future.\n\nSome of the twists have been joyful; some have been hard. It\u2019s been fun watching a steady stream of research miracles occur, and a lot of naysayers have become true believers. We\u2019ve also seen some colleagues split off and become competitors. Teams tend to turn over as they scale, and OpenAI scales really fast. I think some of this is unavoidable\u2014startups usually see a lot of turnover at each new major level of scale, and at OpenAI numbers go up by orders of magnitude every few months. The last two years have been like a decade at a normal company. When any company grows and evolves so fast, interests naturally diverge. And when any company in an important industry is in the lead, lots of people attack it for all sorts of reasons, especially when they are trying to compete with it.\n\nOur vision won\u2019t change; our tactics will continue to evolve. For example, when we started we had no idea we would have to build a product company; we thought we were just going to do great research. We also had no idea we would need such a crazy amount of capital. There are new things we have to go build now that we didn\u2019t understand a few years ago, and there will be new things in the future we can barely imagine now.\n\nWe are proud of our track-record on research and deployment so far, and are committed to continuing to advance our thinking on safety and benefits sharing. We continue to believe that the best way to make an AI system safe is by iteratively and gradually releasing it into the world, giving society time to adapt and co-evolve with the technology, learning from experience, and continuing to make the technology safer. We believe in the importance of being world leaders on safety and alignment research, and in guiding that research with feedback from real world applications.\n\nWe are now confident we know how to build AGI as we have traditionally understood it. We believe that, in 2025, we may see the first AI agents \u201cjoin the workforce\u201d and materially change the output of companies. We continue to believe that iteratively putting great tools in the hands of people leads to great, broadly-distributed outcomes.\n\nWe are beginning to turn our aim beyond that, to superintelligence in the true sense of the word. We love our current products, but we are here for the glorious future. With superintelligence, we can do anything else. Superintelligent tools could massively accelerate scientific discovery and innovation well beyond what we are capable of doing on our own, and in turn massively increase abundance and prosperity.\n\nThis sounds like science fiction right now, and somewhat crazy to even talk about it. That\u2019s alright\u2014we\u2019ve been there before and we\u2019re OK with being there again. We\u2019re pretty confident that in the next few years, everyone will see what we see, and that the need to act with great care, while still maximizing broad benefit and empowerment, is so important. Given the possibilities of our work, OpenAI cannot be a normal company.\n\nHow lucky and humbling it is to be able to play a role in this work.\n\n(Thanks to Josh Tyrangiel for sort of prompting this. I wish we had had a lot more time.)\n\n[1]\n\nThere were a lot of people who did incredible and gigantic amounts of work to help OpenAI, and me personally, during those few days, but two people stood out from all others.\n\nRon Conway and Brian Chesky went so far above and beyond the call of duty that I\u2019m not even sure how to describe it. I\u2019ve of course heard stories about Ron\u2019s ability and tenaciousness for years and I\u2019ve spent a lot of time with Brian over the past couple of years getting a huge amount of help and advice.\n\nBut there\u2019s nothing quite like being in the foxhole with people to see what they can really do. I am reasonably confident OpenAI would have fallen apart without their help; they worked around the clock for days until things were done.\n\nAlthough they worked unbelievably hard, they stayed calm and had clear strategic thought and great advice throughout. They stopped me from making several mistakes and made none themselves. They used their vast networks for everything needed and were able to navigate many complex situations. And I\u2019m sure they did a lot of things I don\u2019t know about.\n\nWhat I will remember most, though, is their care, compassion, and support.\n\nI thought I knew what it looked like to support a founder and a company, and in some small sense I did. But I have never before seen, or even heard of, anything like what these guys did, and now I get more fully why they have the legendary status they do. They are different and both fully deserve their genuinely unique reputations, but they are similar in their remarkable ability to move mountains and help, and in their unwavering commitment in times of need. The tech industry is far better off for having both of them in it.\n\nThere are others like them; it is an amazingly special thing about our industry and does much more to make it all work than people realize. I look forward to paying it forward.\n\nOn a more personal note, thanks especially to Ollie for his support that weekend and always; he is incredible in every way and no one could ask for a better partner.]]>\n  \n  \n    This is what great writing looks like:\n    https://x.com/matt_gray_/status/1839864316750602621/?rw_tt_thread=True\n    readwise:01jdykqtdf32xjms55mc3wjczy\n    Sat, 30 Nov 2024 13:21:38 +0000\n    X (formerly Twitter)\n    \nThis is what great writing looks like:\n\nP.S. If you like proven systems, you'll love my weekly newsletter (it's free).\n1 actionable tip to grow your online business.\nBonus: You\u2019ll get my 50 Systems to Generate $1M Per Month Guide (worth $249) for free.\nJoin 137,000+ subscribers here:\nfounderos.com/newsletter]]>\n    \nThis is what great writing looks like:\n\nP.S. If you like proven systems, you'll love my weekly newsletter (it's free).\n1 actionable tip to grow your online business.\nBonus: You\u2019ll get my 50 Systems to Generate $1M Per Month Guide (worth $249) for free.\nJoin 137,000+ subscribers here:\nfounderos.com/newsletter]]>\n  \n  \n    \ud83d\udc49 Small Caps + Monthly Income\n    https://gritcap.io/p/small-caps-monthly-income?_bhlid=e751aa41fb4d082015e43fd13a3dc1b7873245d1&utm_campaign=small-caps-monthly-income&utm_medium=newsletter&utm_source=gritcap.io\n    readwise:01jcnm2b69sgnwsm47pc6geda8\n    Thu, 14 Nov 2024 15:18:31 +0000\n    GRIT\n    \n\n\n\n\n\n\n\n\nHi everyone \u2014 Austin Hankwitz here.\n\nAs you might know, we\u2019re always looking for well-written content and analysis to share with our subscribers. A few months ago I stumbled upon Nicholas Bratto on Seeking Alpha and we quickly became friends.\n\nNicholas does a wonderful job of analyzing ETFs and single stocks in a very approachable, easy-to-understand manner. The following content is a \u201crepost\u201d of his analysis on the NEOS Russell 2000 High Income ETF, IWMI.\n\nSmall cap companies are usually the biggest benefactors of lower tax rates, and considering the \u201cRed Wave\u201d that just swept through the United States it\u2019s safe to assume lower corporate tax rates are around the corner.\n\nEnjoy this well-written analysis by Nicholas Bratto, and if you know of other analysts online that publish great work \u2014 never hesitate to send them our way :)\n\nIWMI: Generating Income with Lower Volatility in a Shifting Small-Cap Market\n\nSummary\n\n\n\n IWMI ETF combines small-cap stock exposure with an active options strategy, offering tax-efficient monthly income yielding 14.82%. \n\n Small-cap stocks are poised for a comeback: IWMI positions itself to capitalize on potential shifts in market leadership as macroeconomic factors favor value-oriented, smaller companies. \n\n IWMI aims to enhance risk-adjusted returns, providing a strategic income option for investors seeking stability and upside potential with less volatility. \n\nOver the summer, NEOS launched the NEOS Russell 2000 High Income ETF using the same option overlay strategy on US small-cap stocks: the Russell 2000 Index.\n\nGiven the continued positive performance of SPYI and QQQI, I believe IWMI can offer a similar level of risk-adjusted performance, gaining exposure to small-cap stocks while hedging volatility with an options overlay income strategy.\n\nIWMI Summary\n\nIWMI is an actively managed ETF which seeks high, tax efficient monthly income, with the opportunity to capture upside when the underlying index, the Russell 2000, rises.\n\nTo summarize, IWMI generates income by selling Russell 2000 (\"RUT\") index options and buying call options for upside capture when the Russell 2000 rises. These options would presumably be bought when volatility or the RVX index is low, similar to the strategy SPYI and QQQI execute for the VIX and VXN respectively, but I couldn't find this exact information stated in the prospectus.\n\n\n\nIWMI uses the same layers of tax efficiency utilized by SPYI and QQQI as well:\n\n\n\n The contracts sold are taxed 60%/40% long/short-term capital gains tax rates respectively per Section 1256 contracts. \n\n Part of the fund earns qualified dividends from the equities held. \n\n Utilization of tax-loss harvesting. \n\n Uses Return of Capital (ROC) classification on the distributions, which makes > 90% of the distributions deferred long-term capital gains. \n\nBelow is the performance of IWMI since inception compare to iShares Russell 2000 ETF (IWM), but since the fund has only been around for about 4 months, I defer to draw major conclusions until more time has passed.\n\nStill, one characteristic we can and should see with options-based income ETFs are less volatility than their underlying index. In August, IWM had a drawdown of nearly 10% while IWMI saw a drawdown of about 5% or about half as much.\n\n\n\nWe can also see a higher Sharpe Ratio during this period of 1.97 for IWMI vs. 1.46 for IWM, suggesting higher risk-adjusted returns.\n\nMore time is needed to be sure, but I want to point out to investors the purpose of these funds are not to beat their underlying indices every year in terms of total return, rather it's to offer higher risk-adjusted returns with tax-efficient monthly income. Risk metrics are key to tracking the performance of these funds.\n\nBenchmarking Performance \u2014 RYLD vs. VTWO\n\nThere's no products quite like the NEOS ETFs let alone with enough history as one like IWMI, however one such similar and popular ETF is Global X Russell 2000 Covered Call ETF (RYLD) with $1.41B AUM. I published an article on RYLD last September and decided to sell my shares shortly after running what my real returns were from my analysis: negative when accounting for inflation. The fund uses a passive at-the-money covered call strategy, so a different strategy than IWMI which uses an out-of-the money call overlay strategy, but the returns of RYLD haven't been good.\n\n\n\nRYLD vs. VTWO Total Return (Seeking Alpha)\n\nComparing to Vanguard Russell 2000 Index Fund ETF Shares (VTWO), VTWO has returned 54.59% vs. RYLDs 23.26% since inception. Even on a risk-adjusted return basis, RYLD has a lower Sharpe Ratio of 0.09 vs. 0.33 for VTWO. To be fair, small-cap stocks in general have not performed well in the last 5 years or even the last decade when compared to the large-cap S&P 500. RYLD actually returned similarly to the Russell 2000 up until about a year ago when small-caps had a small breakout, leaving RYLD behind while the index rose.\n\nThis is one of the major issues with passive-options strategies on funds like RYLD: they cannot capture any upside and participate in all the downside, with no active management intervention. I believe IWMI helps solve this problem with their active management strategy.\n\nSmall-Cap Reversal\n\nThere has been much discussion the past few years in the investment community speculating a small-cap reversal is inbound to overtake large-cap stocks. There's a great white paper on small-cap stocks by WisdomTree reminding investors of the value and performance that can be unlocked with small-cap stocks. A small-cap reversal may make sense when we account for the dominance of large-cap growth stocks being driven by historically low interest rates, low inflation, and low-stable economic growth, which were further amplified by the COVID-19 pandemic.\n\nThese factors are unlikely to continue as elevated interest rates, higher inflation, and more volatile economic growth tend to create a more favorable environment for small-cap value stocks to outperform and carry the index. Historically, market leadership between large and small-caps tends to shift in cycles over about 10 years. With large-caps outperforming since 2014 and small-cap value already outperforming since late 2020, the current environment suggests a reversal may be underway. Interestingly, small-caps have outperformed large caps by 386% cumulatively since 1926, making this shift in leadership historically consistent.\n\n\n\nSmall Caps vs. Large Caps: Cumulative Relative Total Returns (WisdomTree)\n\nI published an article on VB covering dividends place in the small-cap stock market and published an article coming full circle on this topic back in August on my Substack showing when adjusted for risk the last 20 years, the small-cap Russell 2000 and large-cap S&P 500 performed almost the same, both returning around 11.20% annually. All in all, while small-caps have underperformed in recent history, the data shows this trend is not unusual and small-caps can offer significant alpha in the market.\n\n\n\nPeriodic Table of Investment Returns (Bratto Biz Substack, Callan Institute)\n\nRisk Analysis\n\nRegardless of your conviction in the thesis laid out above, small-cap stocks have higher volatility than large-cap making IWMI a good hedge for investors to manage risk by reducing portfolio volatility and generating income, especially during down cycles like small-caps have been experiencing. And remember, IWMI can increase in value another way: by entering into call options spreads to capture upside when a small-cap reversal does happen and the Russell 2000 rises.\n\nAs there is not enough data for IWMI, I compared SPYI and the S&P 500 as a surrogate to get an idea of what could be possible with this strategy for the small-cap version.\n\n\n\nAlthough SPDR S&P 500 ETF Trust (SPY) has outperformed SPYI with 28% vs. 20% CAGR since SPYIs inception in January 2023, SPYI has better risk-adjusted returns looking at both the unsystematic and systemic risk profiles.\n\nThe beta of SPYI is markedly lower as well at 0.59. Although the Sharpe and Treynor ratios are only slightly higher, I believe with more time and market conditions this gap will widen. These are critical metrics to monitor on IWMI as well as the fund performance unfolds.\n\nOutlook\n\nSo, what's my move? My followers across social media know I've been on a relentless pursuit to achieve financial security with my dividend portfolio in my taxable brokerage account. I am enticed by the idea of having at least enough shares of income ETFs like the NEOS funds and other income funds to cover my fixed expenses: subscriptions, cellphone, water, internet, gas, energy, car & home insurance, CapEx, property taxes, and grocery bills.\n\nThese are expenses that are never going away and are necessary to survive. The tax efficiency of the distributions, effectively deferred long-term capital gains, is a big driving factor too as this strategy requires significant investment in a taxable brokerage account. I estimate I need about $3000/month or $250,000 invested in funds like SPYI QQQI and IWMI to cover my fixed expenses, with the rest of my money in dividend growth ETFs.\n\nI really like the three funds: SPYI QQQI and IWMI below $50/share or at a discount to the NAV. While I want the funds to dip below $50/share to initiate my equal-weighted positions, I'm also happy if they don't dip below $50/share ever again and continue to slowly appreciate in price.\n\nDon\u2019t follow us on social yet? Follow us on Instagram, TikTok, and Twitter.\n\n\n\nThe author, publisher or insiders of the publisher may currently have long or short positions in the securities of the companies mentioned herein, or may have such a position in the future (and therefore may profit from fluctuations in the trading price of the securities). To the extent such persons do have such positions, there is no guarantee that such persons will maintain such positions.\n\nCover Image Credit: Investopedia\n\nGrit is a publisher of financial information, not an investment advisor. Grit does not provide personalized or individualized investment advice or information that is tailored to the needs of any particular recipient. Grit does not guarantee the accuracy or completeness of the information provided in this page. All statements and expressions herein are the sole opinion of the author or paid advertiser.\n\nTHE INFORMATION CONTAINED ON THIS WEBSITE IS NOT AND SHOULD NOT BE CONSTRUED AS INVESTMENT ADVICE, AND DOES NOT PURPORT TO BE AND DOES NOT EXPRESS ANY OPINION AS TO THE PRICE AT WHICH THE SECURITIES OF ANY COMPANY MAY TRADE AT ANY TIME. THE INFORMATION AND OPINIONS PROVIDED HEREIN SHOULD NOT BE TAKEN AS SPECIFIC ADVICE ON THE MERITS OF ANY INVESTMENT DECISION. INVESTORS SHOULD MAKE THEIR OWN INVESTIGATION AND DECISIONS REGARDING THE PROSPECTS OF ANY COMPANY DISCUSSED HEREIN BASED ON SUCH INVESTORS\u2019 OWN REVIEW OF PUBLICLY AVAILABLE INFORMATION AND SHOULD NOT RELY ON THE INFORMATION CONTAINED HEREIN. INVESTORS SHOULD OBTAIN INDIVIDUAL INVESTMENT ADVICE BASED ON THEIR OWN CIRCUMSTANCES BEFORE MAKING AN INVESTMENT DECISION\n\nNo statement or expression of opinion, or any other matter herein, directly or indirectly, is an offer or the solicitation of an offer to buy or sell the securities or financial instruments mentioned.\n\nThe author, publisher or insiders of the publisher may currently have long or short positions in the securities of the companies mentioned herein, or may have such a position in the future (and therefore may profit from fluctuations in the trading price of the securities). To the extent such persons do have such positions, there is no guarantee that such persons will maintain such positions.\n\nAny projections, market outlooks or estimates herein are forward looking statements and are inherently unreliable. They are based upon certain assumptions and should not be construed to be indicative of the actual events that will occur. Other events that were not taken into account may occur and may significantly affect the returns or performance of the securities discussed herein. The information provided herein is based on matters as they exist as of the date of preparation and not as of any future date, and Grit undertakes no obligation to correct, update or revise the information in this document or to otherwise provide any additional material.\n\nGrit does not accept any liability whatsoever for any direct or consequential loss, however arising, directly or indirectly, from any use of the information contained herein.\n\nBy using the Site or any related social media account, you are indicating your consent and agreement to this disclaimer and our terms of use. Unauthorized reproduction of this newsletter or its contents by photocopy, facsimile or any other means is illegal and punishable by law.\n\nPlease read: Terms of Use, Privacy Policy, Disclosure Policy and Disclaimer Policy\n\nIf you have any questions please contact us at info@gritcap.io]]>\n    \n\n\n\n\n\n\n\n\nHi everyone \u2014 Austin Hankwitz here.\n\nAs you might know, we\u2019re always looking for well-written content and analysis to share with our subscribers. A few months ago I stumbled upon Nicholas Bratto on Seeking Alpha and we quickly became friends.\n\nNicholas does a wonderful job of analyzing ETFs and single stocks in a very approachable, easy-to-understand manner. The following content is a \u201crepost\u201d of his analysis on the NEOS Russell 2000 High Income ETF, IWMI.\n\nSmall cap companies are usually the biggest benefactors of lower tax rates, and considering the \u201cRed Wave\u201d that just swept through the United States it\u2019s safe to assume lower corporate tax rates are around the corner.\n\nEnjoy this well-written analysis by Nicholas Bratto, and if you know of other analysts online that publish great work \u2014 never hesitate to send them our way :)\n\nIWMI: Generating Income with Lower Volatility in a Shifting Small-Cap Market\n\nSummary\n\n\n\n IWMI ETF combines small-cap stock exposure with an active options strategy, offering tax-efficient monthly income yielding 14.82%. \n\n Small-cap stocks are poised for a comeback: IWMI positions itself to capitalize on potential shifts in market leadership as macroeconomic factors favor value-oriented, smaller companies. \n\n IWMI aims to enhance risk-adjusted returns, providing a strategic income option for investors seeking stability and upside potential with less volatility. \n\nOver the summer, NEOS launched the NEOS Russell 2000 High Income ETF using the same option overlay strategy on US small-cap stocks: the Russell 2000 Index.\n\nGiven the continued positive performance of SPYI and QQQI, I believe IWMI can offer a similar level of risk-adjusted performance, gaining exposure to small-cap stocks while hedging volatility with an options overlay income strategy.\n\nIWMI Summary\n\nIWMI is an actively managed ETF which seeks high, tax efficient monthly income, with the opportunity to capture upside when the underlying index, the Russell 2000, rises.\n\nTo summarize, IWMI generates income by selling Russell 2000 (\"RUT\") index options and buying call options for upside capture when the Russell 2000 rises. These options would presumably be bought when volatility or the RVX index is low, similar to the strategy SPYI and QQQI execute for the VIX and VXN respectively, but I couldn't find this exact information stated in the prospectus.\n\n\n\nIWMI uses the same layers of tax efficiency utilized by SPYI and QQQI as well:\n\n\n\n The contracts sold are taxed 60%/40% long/short-term capital gains tax rates respectively per Section 1256 contracts. \n\n Part of the fund earns qualified dividends from the equities held. \n\n Utilization of tax-loss harvesting. \n\n Uses Return of Capital (ROC) classification on the distributions, which makes > 90% of the distributions deferred long-term capital gains. \n\nBelow is the performance of IWMI since inception compare to iShares Russell 2000 ETF (IWM), but since the fund has only been around for about 4 months, I defer to draw major conclusions until more time has passed.\n\nStill, one characteristic we can and should see with options-based income ETFs are less volatility than their underlying index. In August, IWM had a drawdown of nearly 10% while IWMI saw a drawdown of about 5% or about half as much.\n\n\n\nWe can also see a higher Sharpe Ratio during this period of 1.97 for IWMI vs. 1.46 for IWM, suggesting higher risk-adjusted returns.\n\nMore time is needed to be sure, but I want to point out to investors the purpose of these funds are not to beat their underlying indices every year in terms of total return, rather it's to offer higher risk-adjusted returns with tax-efficient monthly income. Risk metrics are key to tracking the performance of these funds.\n\nBenchmarking Performance \u2014 RYLD vs. VTWO\n\nThere's no products quite like the NEOS ETFs let alone with enough history as one like IWMI, however one such similar and popular ETF is Global X Russell 2000 Covered Call ETF (RYLD) with $1.41B AUM. I published an article on RYLD last September and decided to sell my shares shortly after running what my real returns were from my analysis: negative when accounting for inflation. The fund uses a passive at-the-money covered call strategy, so a different strategy than IWMI which uses an out-of-the money call overlay strategy, but the returns of RYLD haven't been good.\n\n\n\nRYLD vs. VTWO Total Return (Seeking Alpha)\n\nComparing to Vanguard Russell 2000 Index Fund ETF Shares (VTWO), VTWO has returned 54.59% vs. RYLDs 23.26% since inception. Even on a risk-adjusted return basis, RYLD has a lower Sharpe Ratio of 0.09 vs. 0.33 for VTWO. To be fair, small-cap stocks in general have not performed well in the last 5 years or even the last decade when compared to the large-cap S&P 500. RYLD actually returned similarly to the Russell 2000 up until about a year ago when small-caps had a small breakout, leaving RYLD behind while the index rose.\n\nThis is one of the major issues with passive-options strategies on funds like RYLD: they cannot capture any upside and participate in all the downside, with no active management intervention. I believe IWMI helps solve this problem with their active management strategy.\n\nSmall-Cap Reversal\n\nThere has been much discussion the past few years in the investment community speculating a small-cap reversal is inbound to overtake large-cap stocks. There's a great white paper on small-cap stocks by WisdomTree reminding investors of the value and performance that can be unlocked with small-cap stocks. A small-cap reversal may make sense when we account for the dominance of large-cap growth stocks being driven by historically low interest rates, low inflation, and low-stable economic growth, which were further amplified by the COVID-19 pandemic.\n\nThese factors are unlikely to continue as elevated interest rates, higher inflation, and more volatile economic growth tend to create a more favorable environment for small-cap value stocks to outperform and carry the index. Historically, market leadership between large and small-caps tends to shift in cycles over about 10 years. With large-caps outperforming since 2014 and small-cap value already outperforming since late 2020, the current environment suggests a reversal may be underway. Interestingly, small-caps have outperformed large caps by 386% cumulatively since 1926, making this shift in leadership historically consistent.\n\n\n\nSmall Caps vs. Large Caps: Cumulative Relative Total Returns (WisdomTree)\n\nI published an article on VB covering dividends place in the small-cap stock market and published an article coming full circle on this topic back in August on my Substack showing when adjusted for risk the last 20 years, the small-cap Russell 2000 and large-cap S&P 500 performed almost the same, both returning around 11.20% annually. All in all, while small-caps have underperformed in recent history, the data shows this trend is not unusual and small-caps can offer significant alpha in the market.\n\n\n\nPeriodic Table of Investment Returns (Bratto Biz Substack, Callan Institute)\n\nRisk Analysis\n\nRegardless of your conviction in the thesis laid out above, small-cap stocks have higher volatility than large-cap making IWMI a good hedge for investors to manage risk by reducing portfolio volatility and generating income, especially during down cycles like small-caps have been experiencing. And remember, IWMI can increase in value another way: by entering into call options spreads to capture upside when a small-cap reversal does happen and the Russell 2000 rises.\n\nAs there is not enough data for IWMI, I compared SPYI and the S&P 500 as a surrogate to get an idea of what could be possible with this strategy for the small-cap version.\n\n\n\nAlthough SPDR S&P 500 ETF Trust (SPY) has outperformed SPYI with 28% vs. 20% CAGR since SPYIs inception in January 2023, SPYI has better risk-adjusted returns looking at both the unsystematic and systemic risk profiles.\n\nThe beta of SPYI is markedly lower as well at 0.59. Although the Sharpe and Treynor ratios are only slightly higher, I believe with more time and market conditions this gap will widen. These are critical metrics to monitor on IWMI as well as the fund performance unfolds.\n\nOutlook\n\nSo, what's my move? My followers across social media know I've been on a relentless pursuit to achieve financial security with my dividend portfolio in my taxable brokerage account. I am enticed by the idea of having at least enough shares of income ETFs like the NEOS funds and other income funds to cover my fixed expenses: subscriptions, cellphone, water, internet, gas, energy, car & home insurance, CapEx, property taxes, and grocery bills.\n\nThese are expenses that are never going away and are necessary to survive. The tax efficiency of the distributions, effectively deferred long-term capital gains, is a big driving factor too as this strategy requires significant investment in a taxable brokerage account. I estimate I need about $3000/month or $250,000 invested in funds like SPYI QQQI and IWMI to cover my fixed expenses, with the rest of my money in dividend growth ETFs.\n\nI really like the three funds: SPYI QQQI and IWMI below $50/share or at a discount to the NAV. While I want the funds to dip below $50/share to initiate my equal-weighted positions, I'm also happy if they don't dip below $50/share ever again and continue to slowly appreciate in price.\n\nDon\u2019t follow us on social yet? Follow us on Instagram, TikTok, and Twitter.\n\n\n\nThe author, publisher or insiders of the publisher may currently have long or short positions in the securities of the companies mentioned herein, or may have such a position in the future (and therefore may profit from fluctuations in the trading price of the securities). To the extent such persons do have such positions, there is no guarantee that such persons will maintain such positions.\n\nCover Image Credit: Investopedia\n\nGrit is a publisher of financial information, not an investment advisor. Grit does not provide personalized or individualized investment advice or information that is tailored to the needs of any particular recipient. Grit does not guarantee the accuracy or completeness of the information provided in this page. All statements and expressions herein are the sole opinion of the author or paid advertiser.\n\nTHE INFORMATION CONTAINED ON THIS WEBSITE IS NOT AND SHOULD NOT BE CONSTRUED AS INVESTMENT ADVICE, AND DOES NOT PURPORT TO BE AND DOES NOT EXPRESS ANY OPINION AS TO THE PRICE AT WHICH THE SECURITIES OF ANY COMPANY MAY TRADE AT ANY TIME. THE INFORMATION AND OPINIONS PROVIDED HEREIN SHOULD NOT BE TAKEN AS SPECIFIC ADVICE ON THE MERITS OF ANY INVESTMENT DECISION. INVESTORS SHOULD MAKE THEIR OWN INVESTIGATION AND DECISIONS REGARDING THE PROSPECTS OF ANY COMPANY DISCUSSED HEREIN BASED ON SUCH INVESTORS\u2019 OWN REVIEW OF PUBLICLY AVAILABLE INFORMATION AND SHOULD NOT RELY ON THE INFORMATION CONTAINED HEREIN. INVESTORS SHOULD OBTAIN INDIVIDUAL INVESTMENT ADVICE BASED ON THEIR OWN CIRCUMSTANCES BEFORE MAKING AN INVESTMENT DECISION\n\nNo statement or expression of opinion, or any other matter herein, directly or indirectly, is an offer or the solicitation of an offer to buy or sell the securities or financial instruments mentioned.\n\nThe author, publisher or insiders of the publisher may currently have long or short positions in the securities of the companies mentioned herein, or may have such a position in the future (and therefore may profit from fluctuations in the trading price of the securities). To the extent such persons do have such positions, there is no guarantee that such persons will maintain such positions.\n\nAny projections, market outlooks or estimates herein are forward looking statements and are inherently unreliable. They are based upon certain assumptions and should not be construed to be indicative of the actual events that will occur. Other events that were not taken into account may occur and may significantly affect the returns or performance of the securities discussed herein. The information provided herein is based on matters as they exist as of the date of preparation and not as of any future date, and Grit undertakes no obligation to correct, update or revise the information in this document or to otherwise provide any additional material.\n\nGrit does not accept any liability whatsoever for any direct or consequential loss, however arising, directly or indirectly, from any use of the information contained herein.\n\nBy using the Site or any related social media account, you are indicating your consent and agreement to this disclaimer and our terms of use. Unauthorized reproduction of this newsletter or its contents by photocopy, facsimile or any other means is illegal and punishable by law.\n\nPlease read: Terms of Use, Privacy Policy, Disclosure Policy and Disclaimer Policy\n\nIf you have any questions please contact us at info@gritcap.io]]>\n  \n  \n    It's done!\n    https://twitter.com/Julian/status/1853510703388524979/?rw_tt_thread=True\n    readwise:01jcbrx47z600h65dknwnh8zxz\n    Sun, 10 Nov 2024 19:30:39 +0000\n    X (formerly Twitter)\n    \nIt's done! I read 3,000 startup pitch decks.\nI wanted to find what the incredible pitches had in common.\nWas there a \"secret ingredient\" unifying them?\nYES. The 4 best (that VCs wanted intros to) had the same talking point:\n\nFirst, here's why most decks were *not* interesting:\nFounders believed that explaining how they're better than the competition is what makes them compelling to VCs.\nMaybe, but in many markets, it's not hard to suggest a solution better than status quo.\nWhat's more interesting:\n\n...is what approach you use to *acquire customers at scale.*\nMeaning, what's your *distribution* insight?\nNot just your product insight.\nBecause if you build something good, often they will not simply come.\n\nWhy is distribution so important in 2024?\nBecause winning your market by just having a better product worked better in the last startup cycle when SaaS ideas were more novel.\nThat ship is sailing for many non-AI plays. SaaS has become commoditized.\nMeaning:\n\nEvery idea has 10 VC-backed competitors.\nPlus, many incumbents move faster to suffocate startups by releasing new features.\nI think of it like this:\nYour SaaS co is no longer competing with slow-moving incumbents like Netsuite & Oracle.\n\nNow you're competing with the founders of Figma, Dropbox, Airbnb, Stripe\u2014 who are still the *original* CEOs at the top of their game.\nThey're still cutthroat & fast.\nFor example: Are you starting something in the design space?\n\nIn the past, perhaps you worried about slow-moving Adobe.\nToday, maybe you're competing with Dylan of Figma and his team of world-class engineers.\nThey're armed with copilot and hungry to line-extend to maximize market share and eventually IPO.\n\nAnd even \"slow-moving\" Adobe is faster than before.\nDid you see how quickly they released Midjourney-like features?\n\nDid you see how quickly Notion integrated LLMs?\nDid you see how quickly Microsoft integrated ChatGPT into Office?\nAnd so on.\nThe point is that some VCs don't JUST want to hear how your product is better.\n\nWhat some investors including myself also want to hear is:\nWhat is your unique approach to scalably and convincingly *getting in front of customers*?\nBecause great ideas eventually get copied by other great founders anyway.\nSo let's explain distribution:\n\nFirst, for context, this thread's distribution insight is from my weeklong deck review of DeepChecks.vc, where hardware founders get VC dollars from the best energy/chips/robotics/bio investors.\nOkay, so here's why distribution matters SO much:\n\n1. Most founders are bad at growth, so if you're amazing at it, the advantage is significant.\nConsider: Most startups die not because founders are bad or products suck, but because they couldn't figure out how to get anyone to try them.\n\n2. If you can grow rapidly and win the hearts of customers by scaling to them before competitors do, and if you have a great product, people are unlikely to immediately switch to competitors.\n\nLock-in is real. Being first can matter. Especially when users fall in love with your brand.\nAlso, if you've already sucked all the oxygen out of a market, competitors may be less likely to emerge and get funded.\n\nThis is why I'll sometimes invest in B-tier tech with A-tier growth strategies, especially if I believe the CEO can become A-tier over time.\nBut. Here's the kicker\u2014the point of this whole thread:\nFounders NEVER talk about distribution in their decks.\n\nThey do not think like marketers.\nThe few founders who do are the 4 decks who stood out to VCs!\nPeter Thiel spoke about this a while back, and it feels like no one noticed:\n\n\"Distribution is essential to the design of the product. If you invent something but you haven't invented an effective way to sell it, you have a bad business. Superior distribution by itself can create a monopoly, even with no product differentiation. The converse is not true.\"\n\nPaul Graham spoke about it too:\n\"Don't start a startup where you need to go through someone else to get users.\" \u2014Paul Graham\nThere are exceptions, of course:\n\nCompanies with actually novel and defensible products can often focus more on product than distribution. However, few software companies are actually novel. Instead, novelty exists more often today within deeptech (hardware, robotics, energy, chips, etc.)\n\nAnd when you're NOT novel, your major advantage is going to be a distribution edge combined with great retention.\nOkay, finally, so how do you crush distribution? What do the best startups do?\n\nFirst, it's OK if your distribution insight starts as a hack.\nFor Airbnb, their early approach was cross-posting room listings to Craigslist where people were already desperately searching for places to stay.\nAirbnb had the inventory craiglist needed, and they took off.\n\nFor Hotmail, pioneers of cloud email, their growth strategy was including an email signature that said \u201cSent through Hotmail.\u201c\nEveryone you emailed suddenly learned about the product. That's free viral distribution.\nThis was before the iPhone did this.\n\nI call that billboarding.\nIt's a form of my favorite distribution strategy for most startups: product-led acquisition (PLA).\nPLA means your users naturally invite other users just by using your product.\nIt's a clearer definition of network effects for tech startups.\nExample:\n\nAnother subtype of PLA is *deliberate user invitations:* When you join Slack, you naturally invite your team and contractors so you can talk with them easily.\nBy doing so, you\u2019re growing Slack\u2019s user base for them\u2014sparing them the need to spend money on ads.\n\nHere\u2019s another example:\nIf you Venmo or PayPal someone who doesn\u2019t yet have an account on those platforms, they will create an account in order to claim the $1,000 you sent them.\nBecause who isn't going to take 30 secs to claim money they're owed?\n\nOnce again, by using the app, you encourage others to sign up and grow the userbase.\nI talk about more ways to do PLA on my site. For now, the takeaway:\nFor software companies, put a bunch of energy into your distribution insight\u2014not just your product insight.\nOne last thing.\n\nDistribution has at least two components.\nThe first is the HOW: the channel that you use to get the word out, e.g. PLA or ads.\nThe second is the WHAT: what is your message\u2014and whether it's compelling enough to resonate.\nMeaning:\n\nFor people to try your product, you should present your product in a way that people intuitively FEEL how much better you are than your competition and perceive ENOUGH of an improvement to warrant QUICKLY switching plus enduring your switching costs.\n\nMeaning, customer adoption isn't just about whether you provide more value than the status quo.\nIt's also about whether users can PERCEIVE that big value reflexively.\n\nThe skill of growth doesn\u2019t just consist of getting the word out, but also in presenting your value in a way that *resonates.*\nThat means distribution is (1) growth engines and (2) great storytelling.\nThat's where the best founders I've backed often win.\n\nHere's an example of storytelling. I call this a \"genesis narrative:\"\nAt Synthesis, their CEO told the true story of how their cutting-edge, online, interactive game that helps children become better at problem-solving is a spinoff of Elon's school for his kids at SpaceX.\n\nThe message: If it's good enough for Elon, it's good enough for you.\nThat narrative piqued the curiosity of skeptical Elon-favoring parents and led to millions in profitable ad spend because parents gravitated toward genesis narratives justifying what made something fresh.\n\nPut another way, Synthesis\u2019 pitch isn\u2019t just value props.\nRather, it\u2019s a story that customers partake in.\nSo, keep this in mind:\n\nWhen a post-product business is still a young startup, it's not a traditional business yet.\n*It's an experimentation factory in search of distribution insights and storytelling.*\nSet your priorities accordingly.\n\nAnd if you're building something dope in hardware or the sciences, consider submitting your deck to Deep Checks VC. It's where the best scientific founders get funded.]]>\n    \nIt's done! I read 3,000 startup pitch decks.\nI wanted to find what the incredible pitches had in common.\nWas there a \"secret ingredient\" unifying them?\nYES. The 4 best (that VCs wanted intros to) had the same talking point:\n\nFirst, here's why most decks were *not* interesting:\nFounders believed that explaining how they're better than the competition is what makes them compelling to VCs.\nMaybe, but in many markets, it's not hard to suggest a solution better than status quo.\nWhat's more interesting:\n\n...is what approach you use to *acquire customers at scale.*\nMeaning, what's your *distribution* insight?\nNot just your product insight.\nBecause if you build something good, often they will not simply come.\n\nWhy is distribution so important in 2024?\nBecause winning your market by just having a better product worked better in the last startup cycle when SaaS ideas were more novel.\nThat ship is sailing for many non-AI plays. SaaS has become commoditized.\nMeaning:\n\nEvery idea has 10 VC-backed competitors.\nPlus, many incumbents move faster to suffocate startups by releasing new features.\nI think of it like this:\nYour SaaS co is no longer competing with slow-moving incumbents like Netsuite & Oracle.\n\nNow you're competing with the founders of Figma, Dropbox, Airbnb, Stripe\u2014 who are still the *original* CEOs at the top of their game.\nThey're still cutthroat & fast.\nFor example: Are you starting something in the design space?\n\nIn the past, perhaps you worried about slow-moving Adobe.\nToday, maybe you're competing with Dylan of Figma and his team of world-class engineers.\nThey're armed with copilot and hungry to line-extend to maximize market share and eventually IPO.\n\nAnd even \"slow-moving\" Adobe is faster than before.\nDid you see how quickly they released Midjourney-like features?\n\nDid you see how quickly Notion integrated LLMs?\nDid you see how quickly Microsoft integrated ChatGPT into Office?\nAnd so on.\nThe point is that some VCs don't JUST want to hear how your product is better.\n\nWhat some investors including myself also want to hear is:\nWhat is your unique approach to scalably and convincingly *getting in front of customers*?\nBecause great ideas eventually get copied by other great founders anyway.\nSo let's explain distribution:\n\nFirst, for context, this thread's distribution insight is from my weeklong deck review of DeepChecks.vc, where hardware founders get VC dollars from the best energy/chips/robotics/bio investors.\nOkay, so here's why distribution matters SO much:\n\n1. Most founders are bad at growth, so if you're amazing at it, the advantage is significant.\nConsider: Most startups die not because founders are bad or products suck, but because they couldn't figure out how to get anyone to try them.\n\n2. If you can grow rapidly and win the hearts of customers by scaling to them before competitors do, and if you have a great product, people are unlikely to immediately switch to competitors.\n\nLock-in is real. Being first can matter. Especially when users fall in love with your brand.\nAlso, if you've already sucked all the oxygen out of a market, competitors may be less likely to emerge and get funded.\n\nThis is why I'll sometimes invest in B-tier tech with A-tier growth strategies, especially if I believe the CEO can become A-tier over time.\nBut. Here's the kicker\u2014the point of this whole thread:\nFounders NEVER talk about distribution in their decks.\n\nThey do not think like marketers.\nThe few founders who do are the 4 decks who stood out to VCs!\nPeter Thiel spoke about this a while back, and it feels like no one noticed:\n\n\"Distribution is essential to the design of the product. If you invent something but you haven't invented an effective way to sell it, you have a bad business. Superior distribution by itself can create a monopoly, even with no product differentiation. The converse is not true.\"\n\nPaul Graham spoke about it too:\n\"Don't start a startup where you need to go through someone else to get users.\" \u2014Paul Graham\nThere are exceptions, of course:\n\nCompanies with actually novel and defensible products can often focus more on product than distribution. However, few software companies are actually novel. Instead, novelty exists more often today within deeptech (hardware, robotics, energy, chips, etc.)\n\nAnd when you're NOT novel, your major advantage is going to be a distribution edge combined with great retention.\nOkay, finally, so how do you crush distribution? What do the best startups do?\n\nFirst, it's OK if your distribution insight starts as a hack.\nFor Airbnb, their early approach was cross-posting room listings to Craigslist where people were already desperately searching for places to stay.\nAirbnb had the inventory craiglist needed, and they took off.\n\nFor Hotmail, pioneers of cloud email, their growth strategy was including an email signature that said \u201cSent through Hotmail.\u201c\nEveryone you emailed suddenly learned about the product. That's free viral distribution.\nThis was before the iPhone did this.\n\nI call that billboarding.\nIt's a form of my favorite distribution strategy for most startups: product-led acquisition (PLA).\nPLA means your users naturally invite other users just by using your product.\nIt's a clearer definition of network effects for tech startups.\nExample:\n\nAnother subtype of PLA is *deliberate user invitations:* When you join Slack, you naturally invite your team and contractors so you can talk with them easily.\nBy doing so, you\u2019re growing Slack\u2019s user base for them\u2014sparing them the need to spend money on ads.\n\nHere\u2019s another example:\nIf you Venmo or PayPal someone who doesn\u2019t yet have an account on those platforms, they will create an account in order to claim the $1,000 you sent them.\nBecause who isn't going to take 30 secs to claim money they're owed?\n\nOnce again, by using the app, you encourage others to sign up and grow the userbase.\nI talk about more ways to do PLA on my site. For now, the takeaway:\nFor software companies, put a bunch of energy into your distribution insight\u2014not just your product insight.\nOne last thing.\n\nDistribution has at least two components.\nThe first is the HOW: the channel that you use to get the word out, e.g. PLA or ads.\nThe second is the WHAT: what is your message\u2014and whether it's compelling enough to resonate.\nMeaning:\n\nFor people to try your product, you should present your product in a way that people intuitively FEEL how much better you are than your competition and perceive ENOUGH of an improvement to warrant QUICKLY switching plus enduring your switching costs.\n\nMeaning, customer adoption isn't just about whether you provide more value than the status quo.\nIt's also about whether users can PERCEIVE that big value reflexively.\n\nThe skill of growth doesn\u2019t just consist of getting the word out, but also in presenting your value in a way that *resonates.*\nThat means distribution is (1) growth engines and (2) great storytelling.\nThat's where the best founders I've backed often win.\n\nHere's an example of storytelling. I call this a \"genesis narrative:\"\nAt Synthesis, their CEO told the true story of how their cutting-edge, online, interactive game that helps children become better at problem-solving is a spinoff of Elon's school for his kids at SpaceX.\n\nThe message: If it's good enough for Elon, it's good enough for you.\nThat narrative piqued the curiosity of skeptical Elon-favoring parents and led to millions in profitable ad spend because parents gravitated toward genesis narratives justifying what made something fresh.\n\nPut another way, Synthesis\u2019 pitch isn\u2019t just value props.\nRather, it\u2019s a story that customers partake in.\nSo, keep this in mind:\n\nWhen a post-product business is still a young startup, it's not a traditional business yet.\n*It's an experimentation factory in search of distribution insights and storytelling.*\nSet your priorities accordingly.\n\nAnd if you're building something dope in hardware or the sciences, consider submitting your deck to Deep Checks VC. It's where the best scientific founders get funded.]]>\n  \n  \n    Situational Awareness\n    https://situational-awareness.ai/wp-content/uploads/2024/06/situationalawareness.pdf\n    readwise:01j5nwk9p3bhrq4fjrfykmftj8\n    Mon, 19 Aug 2024 17:57:43 +0000\n    SITUATIONAL AWARENESS - The Decade Ahead\n    \n\n\n\n    Leopold Aschenbrenner\n   \n\n\n\n\n    S I T U AT I O N A L AWA R E N E S S\n   \n\n\n\n   The Decade Ahead\n  \n\n\n   J U NE 2024\n  \n\n\n\n    Dedicated to Ilya Sutskever.\n   \n\n\n\n   While I used to work at OpenAI, all of this is based on publiclyavailable information, my own ideas, general field-knowledge, or SF-gossip.\n  \n\n\n   Thank you to Collin Burns, Avital Balwit, Carl Shulman, Jan Leike, Ilya Sutskever, Holden Karnofsky, Sholto Douglas, James Bradbury, Dwarkesh Patel, and many others for formative discussions. Thank you to many friends for feedback on earlier drafts. Thank you to Joe Ronan for help with graphics, and Nick Whitaker for publishing help.\n  \n\n\n   situational-awareness.ai leopold@situational-awareness.ai\n   \n    Updated June 6, 2024 San Francisco, California\n   \n\n\n\n   You can see the future first in San Francisco.\n  \n\n\n   Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there's a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.\n  \n\n\n   The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be unleashed, and before long, The Project will be on. If we're lucky, we'll be in an all-out race with the CCP; if we're unlucky, an all-out war.\n  \n\n\n   Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the willful blindness of \"it's just predicting the next word\". They see only hype and business-as-usual; at most they entertain another internet-scale technological change.\n  \n\n\n   Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have\n   \n    situational awareness\n   \n   . Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy\u2014but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people\u2014the smartest people I have ever met\u2014and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.\n  \n\n\n   Let me tell you what we see.\n  \n\n\n\n    Contents\n   \n\n\n\n\n    Introduction 3\n   \n\n\n\n\n    History is live in San Francisco.\n   \n\n\n\n\n    I. From GPT-4 to AGI: Counting the OOMs 7\n   \n\n\n\n\n    AGI by 2027 is strikingly plausible. GPT-2 to GPT-4 took us from ~preschooler to ~smart high-schooler abilities in 4 years. Tracing trendlines in compute (~0.5 orders of magnitude or OOMs/year), algorithmic efficiencies (~0.5 OOMs/year), and \"unhobbling\" gains (from chatbot to agent), we should expect another preschooler-to-high-schoolersized qualitative jump by 2027.\n   \n\n\n\n\n    II. From AGI to Superintelligence: the Intelligence Explosion 46\n   \n\n\n\n\n    AI progress won't stop at human-level. Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into 1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power\u2014and the peril\u2014of superintelligence would be dramatic.\n   \n\n\n\n\n    III. The Challenges 74\n   \n\n\n\n\n    IIIa. Racing to the Trillion-Dollar Cluster 75\n   \n\n\n\n\n    The most extraordinary techno-capital acceleration has been set in motion. As AI revenue grows rapidly, many trillions of dollars will go into GPU, datacenter, and power buildout before the end of the decade. The industrial mobilization, including growing US electricity production by 10s of percent, will be intense.\n   \n\n\n\n\n    IIIb. Lock Down the Labs: Security for AGI 89\n   \n\n\n\n\n\n\n\n    The nation's leading AI labs treat security as an afterthought. Currently, they're basically handing the key secrets for AGI to the CCP on a silver platter. Securing the AGI secrets and weights against the state-actor threat will be an immense effort, and we're not on track.\n   \n\n\n\n   4\n  \n\n\n\n    IIIc. Superalignment 105\n   \n\n\n\n\n    Reliably controlling AI systems much smarter than we are is an unsolved technical problem. And while it is a solvable problem, things could very easily go off the rails during a rapid intelligence explosion. Managing this will be extremely tense; failure could easily be catastrophic.\n   \n\n\n\n\n    IIId. The Free World Must Prevail 126\n   \n\n\n\n\n    Superintelligence will give a decisive economic and military advantage. China isn't at all out of the game yet. In the race to AGI, the free world's very survival will be at stake. Can we maintain our preeminence over the authoritarian powers? And will we manage to avoid self-destruction along the way?\n   \n\n\n\n\n    IV. The Project 141\n   \n\n\n\n\n\n\n\n    As the race to AGI intensifies, the national security state will get involved. The USG will wake from its slumber, and by 27/28 we'll get some form of government AGI project. No startup can handle superintelligence. Somewhere in a SCIF, the endgame will be on.\n   \n\n\n\n\n    V. Parting Thoughts 156\n   \n\n\n\n\n    What if we're right?\n   \n\n\n\n\n    Appendix 162\n   \n\n\n\n\n\n\n\n\n\n\n    I. From GPT-4 to AGI: Counting the OOMs\n   \n\n\n\n\n    AGI by 2027 is strikingly plausible. GPT-2 to GPT-4 took us from ~preschooler to ~smart high-schooler abilities in 4 years. Tracing trendlines in compute (~0.5 orders of magnitude or OOMs/year), algorithmic efficiencies (~0.5 OOMs/year), and \"unhobbling\" gains (from chatbot to agent), we should expect another preschooler-to-high-schooler-sized qualitative jump by 2027.\n   \n\n\n\n\n\n    Look. The models, they just want to learn. You have to understand this. The models, they just want to learn.\n   \n\n\n\n\n\n\n\n     ilya sutskever (circa 2015, via\n     \n      Dario Amodei)\n     \n\n\n\n\n\n   GPT-4's capabilities came as a shock to many: an AI system that could write code and essays, could reason through difficult math problems, and ace college exams. A few years ago, most thought these were impenetrable walls.\n  \n\n\n   But GPT-4 was merely the continuation of a decade of breakneck progress in deep learning. A decade earlier, models could barely identify simple images of cats and dogs; four years earlier, GPT-2 could barely string together semi-plausible sentences. Now we are rapidly saturating all the benchmarks we can come up with. And yet this dramatic progress has merely been the result of consistent trends in scaling up deep learning.\n  \n\n\n   There have been people who have seen this for far longer. They were scoffed at, but all they did was trust the trendlines. The\n  \n\n\n   trendlines are intense, and they were right. The models, they just want to learn; you scale them up, and they learn more.\n  \n\n\n   I make the following claim:\n   \n    it is strikingly plausible that by 2027, models will be able to do the work of an AI researcher/engineer.\n   \n   That doesn't require believing in sci-fi; it just requires believing in straight lines on a graph.\n  \n\n\n\n\n\n\n   In this piece, I will simply \"count the OOMs\" (OOM = order of magnitude, 10x = 1 order of magnitude): look at the trends in 1)\n   \n    compute\n   \n   , 2)\n   \n    algorithmic efficiencies\n   \n   (algorithmic progress that we can think of as growing \"effective compute\"), and 3)\n   \n    \"unhobbling\" gains\n   \n   (fixing obvious ways in which models are hobbled by default, unlocking latent capabilities and giving them tools, leading to step-changes in usefulness). We trace\n  \n\n\n   Figure 1: Rough estimates of past and future scaleup of effective compute (both physical compute and algorithmic efficiencies), based on the public estimates discussed in this piece. As we scale models, they consistently get smarter, and by \"counting the OOMs\" we get a rough sense of what model intelligence we should expect in the (near) future. (This graph shows only the scaleup in base models; \"unhobblings\" are not pictured.)\n  \n\n\n   the growth in each over four years before GPT-4, and what we should expect in the four years after, through the end of 2027. Given deep learning's consistent improvements for every OOM of effective compute, we can use this to project future progress.\n  \n\n\n   Publicly, things\n   \n    have been quiet\n   \n   for a year since the GPT-4 release, as the next generation of models has been in the oven leading some to proclaim stagnation and that deep learning is hitting a wall.\n   \n    1\n   \n   But by counting the OOMs, we get a peek at\n   \n    1\n   \n   Predictions they've made every year been consistently wrong about. . . what we should actually expect.\n  \n\n\n   The upshot is pretty simple. GPT-2 to GPT-4\u2014from models that were impressive for sometimes managing to string together a few coherent sentences, to models that ace high-school exams\u2014was not a one-time gain. We are racing through the OOMs extremely rapidly, and the numbers indicate we should expect another ~100,000x effective compute scaleup\u2014resulting in another GPT-2-to-GPT-4-sized qualitative jump\u2014over four years. Moreover, and critically, that doesn't just mean a better chatbot; picking the many obvious low-hanging fruit on \"unhobbling\" gains should take us from chatbots to agents, from a tool to something that looks more like drop-in remote worker replacements.\n  \n\n\n   While the inference is simple, the implication is striking. Another jump like that very well could take us to AGI, to models as smart as PhDs or experts that can work beside us as coworkers. Perhaps most importantly, if these AI systems could automate AI research itself, that would set in motion intense feedback loops\u2014the topic of the the next piece in the series.\n  \n\n\n   Even now, barely anyone is pricing all this in. But situational awareness on AI isn't actually that hard, once you step back and look at the trends. If you keep being surprised by AI capabilities, just start counting the OOMs.\n  \n\n\n   for the last decade, and which they've\n  \n\n\n\n    The last four years\n   \n\n\n\n   We have machines now that we can basically\n   \n    talk to like\n   \n\n    humans.\n   \n   It's a remarkable testament to the human capacity to adjust that this seems normal, that we've become inured to the pace of progress. But it's worth stepping back and looking at the progress of just the last few years.\n  \n\n\n\n    GPT-2 to GPT-4\n   \n\n\n\n   Let me remind you of how far we came in just the ~4 (!) years leading up to GPT-4.\n  \n\n\n\n    GPT-2\n   \n   (2019) ~\n   \n    preschooler\n   \n   : \"Wow, it can string together a few plausible sentences.\" A very-cherry-picked example of a semicoherent story about unicorns in the Andes\n   \n    it generated\n   \n   was incredibly impressive at the time. And yet GPT-2 could barely count to 5 without getting tripped up;\n   \n    2\n   \n   when summarizing an article, it just barely outperformed selecting 3 random sentences from the article.\n   \n    3\n   \n\n    3\n   \n   From the GPT-\n   \n    2\n   \n\n    paper,\n   \n   Section\n   \n    3\n   \n   .6.\n  \n\n\n\n\n\n      2 From SSC: \"Janelle Shane asks GPT-2\n     \n\n\n\n      its ten favorite animals:\n     \n\n\n\n\n\n   Prompt: My 10 favorite animals are: 1. My ten favorite animals are:\n  \n\n\n   1. Zebras with a white scar on the back\n  \n\n\n\n\n\n\n     2. Insiduous spiders and octopus\n    \n\n\n     3. Frog with large leaves, hopefully\n    \n\n\n     black\n    \n\n\n     4. Cockatiel with scales\n    \n\n\n\n   5. Razorbill with wings hanging about 4 inches from one's face and a heart tattoo on a frog\n  \n\n\n\n\n\n\n     3. Cockatric interlocking tetrabods that can be blind, cut, and eaten raw: 4. Black and white desert crocodiles\n    \n\n\n     living in sunlight 5. Zebra and many other pea bugs\"\n    \n\n\n\n\n\n\n\n\n\n\n\n      GPT-2 examples people found very impressive at the time\n     \n\n\n\n      Task\n     \n\n\n       Reading Comprehension:\n      \n      answer questions about given passages\n     \n\n      System Prompt\n      \n      (human-written)\n     \n\n      For today's homework assignment, please describe the reasons for the US Civil War.\n     \n\n\n\n      Dataset\n     \n\n      COOA\n     \n\n      Model Completion\n      \n      (machine-written, 10)\n      \n      tries)\n     \n\n      By Donny Ferquson\n      \n      It is easy to identify why the Civil War happened, because so\n      \n      many people and so many books and so much television and films\n     \n\n\n\n      Examples\n     \n\n      The trophy doesn't fit into the brown suitcase because it is too large.\n      \n\n       Correct answer:\n      \n\n       it = trophy\n      \n\n\n       Model answer:\n      \n      it = trophy\n     \n\n\n\n      tell us that it was the cause, that it has something to do with\n      \n      race or economics or religion. There is much agreement that it\n      \n      was essentially a war of slavery on behalf of capitalism, about a\n      \n      century of slavery. But that's not what most people think of when\n      \n      they think of the Civil War. Many people think of the war as\n      \n      about states rights. You're not wrong about that, but it's kind\n     \n\n\n\n\n\n      The trophy doesn't fit into the brown suitcase because it is too small.\n     \n\n\n\n      of misleading to say that the Civil War was a conflict between\n      \n      states' rights and federalism. So let's try again. What's the\n      \n      idea that has inspired so many people to go onto the battlefields\n     \n\n\n\n\n\n\n       Correct answer:\n      \n\n       it = suitable\n      \n\n      Model answer: it = suitcase\n     \n\n\n\n      of Gettysburg and Antietam and Gettysberg and Petersburg and\n      \n      Fredericksburg? The American idea of the republic--a notion of\n      \n      limited government--is a great part of the history.\n     \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   Comparing AI capabilities with human intelligence is difficult and flawed, but I think it's informative to consider the analogy\n  \n\n\n   Figure 2: Some\n   \n    examples\n   \n   of what people found impressive about GPT-2 at the time. Left: GPT-2 does an ok job on extremely basic reading comprehension questions. Right: In a cherry-picked sample (best of 10 tries), GPT-2 can write a semi-coherent paragraph that says some semi-relevant things about the Civil War.\n  \n\n\n   here, even if it's highly imperfect. GPT-2 was shocking for its command of language, and its ability to occasionally generate a semi-cohesive paragraph, or occasionally answer simple factual questions correctly. It's what would have been impressive for a preschooler.\n  \n\n\n\n    GPT-3\n   \n   (2020)\n   \n    4\n   \n   ~\n   \n    elementary schooler\n   \n   : \"Wow, with just some few-\n   \n    4\n   \n   might know from ChatGPT. shot examples it can do some simple useful tasks.\" It started being cohesive over even multiple paragraphs much more consistently, and could correct grammar and do some very basic arithmetic. For the first time, it was also commercially useful in a few narrow ways: for example, GPT-3 could generate\n   \n    simple\n   \n\n    copy\n   \n   for SEO and marketing.\n  \n\n\n   I mean clunky old GPT-3 here, not the dramatically-improved GPT-3.5 you\n  \n\n\n\n\n\n\n   Again, the comparison is imperfect, but what impressed people about GPT-3 is perhaps what would have been impressive for an elementary schooler: it wrote some basic poetry, could tell richer and coherent stories, could start to do rudimentary\n  \n\n\n   Figure 3: Some\n   \n    examples\n   \n   of what people found impressive about GPT-3 at the time. Top: After a simple instruction, GPT-3\n   \n    can\n   \n   use a made-up word in a new sentence. Bottom-left: GPT-3\n   \n    can\n   \n   engage in rich storytelling back-and-forth. Bottom-right: GPT-3\n   \n    can\n   \n   generate some very simple code.\n  \n\n\n   coding, could fairly reliably learn from simple instructions and demonstrations, and so on.\n  \n\n\n\n    GPT-4\n   \n   (2023) ~\n   \n    smart high schooler\n   \n   : \"Wow, it can write pretty sophisticated code and iteratively debug, it can write intelligently and sophisticatedly about complicated subjects, it can reason through difficult high-school competition math, it's beating the vast majority of high schoolers on whatever tests we can give it, etc.\" From code to math to Fermi estimates, it can think and reason. GPT-4 is now useful in my daily tasks, from helping write code to revising drafts.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 4: Some of what people found impressive about GPT-4 when it was released, from the\n   \n    \"Sparks of AGI\"\n   \n   paper. Top: It's writing very complicated code (producing the plots shown in the middle) and can reason through nontrivial math problems. Bottom-left: Solving an AP math problem. Bottom-right: Solving a fairly complex coding problem. More interesting excerpts from that exploration of GPT-4's capabilities\n   \n    here.\n   \n\n\n\n   On everything from AP exams to the SAT, GPT-4 scores better than the vast majority of high schoolers.\n  \n\n\n   Of course, even GPT-4 is still somewhat uneven; for some tasks it's much better than smart high-schoolers, while there are other tasks it can't yet do. That said, I tend to think most of these limitations come down to obvious ways models are still hobbled, as I'll discuss in-depth later. The raw intelligence is (mostly) there, even if the models are still artificially constrained; it'll take extra work to unlock models being able to fully apply that raw intelligence across applications.\n  \n\n\n\n\n\n\n   Figure 5: Progress over just four years. Where are\n   \n    you\n   \n   on this line?\n  \n\n\n\n    The trends in deep learning\n   \n\n\n\n   The pace of deep learning progress in the last decade has simply been extraordinary. A mere decade ago it was revolutionary for a deep learning system to identify simple images. Today, we keep trying to come up with novel, ever harder tests, and yet each new benchmark is quickly cracked. It used to take decades to crack widely-used benchmarks; now it feels like mere months.\n  \n\n\n   We're literally running out of benchmarks. As an anecdote, my friends Dan and Collin made a benchmark called\n   \n    MMLU\n   \n   a few years ago, in 2020. They hoped to finally make a benchmark that would stand the test of time, equivalent to all the hardest exams we give high school and college students. Just three years later, it's basically solved: models like GPT-4 and Gemini\n  \n\n\n\n\n\n\n\n\n\n   Figure 6: Deep learning systems are rapidly reaching or exceeding humanlevel in many domains. Graphic:\n   \n    Our\n   \n\n    World in Data\n   \n\n\n\n   get ~90%.\n  \n\n\n   More broadly, GPT-4 mostly cracks all the standard high school and college aptitude tests (Figure 7).\n   \n    5\n   \n\n    5\n   \n   And no, these tests aren't in the train-\n  \n\n\n   Or consider the\n   \n    MATH benchmark,\n   \n   a set of difficult mathematics problems from high-school math competitions.\n   \n    6\n   \n   When the benchmark was released in 2021, GPT-3 only got ~5% of problems right. And the original paper noted: \"Moreover, we find that simply increasing budgets and model parameter counts will be impractical for achieving strong mathematical reasoning if scaling trends continue [...]. To have more traction on mathematical problem solving we will likely need new algorithmic advancements from the broader research community\"\u2014we would need fundamental new breakthroughs to solve MATH, or so they thought. A survey of\n   \n    ML researchers predicted\n   \n   minimal progress over the coming years (Figure 8);\n   \n    7\n   \n   and yet within\n   \n    7\n   \n   A coauthor\n   \n    notes:\n   \n   \"When our group just a year (by mid-2022), the best models went from ~5% to 50\n   \n    % accuracy;\n   \n   now,\n   \n    MATH is basically solved,\n   \n   with recent performance over 90%.\n  \n\n\n   ing set. AI labs put real effort into ensuring these evals are uncontaminated, because they need good measurements in order to do good science. A\n   \n    recent\n   \n\n    analysis on this by ScaleAI\n   \n   confirmed that the leading labs aren't overfitting to the benchmarks (though some smaller LLM developers might be juicing their numbers).\n  \n\n\n   6 In the original paper, it was noted: \"We also evaluated humans on MATH, and found that a computer science PhD student who does not especially like mathematics attained approximately 40% on MATH, while a three-time IMO gold medalist attained 90%, indicating that MATH can be challenging for humans as well.\"\n  \n\n\n   first released the MATH dataset, at least one [ML researcher colleague] told us that it was a pointless dataset because it was too far outside the range of what ML models could accomplish (indeed, I was somewhat worried about this myself).\"\n  \n\n\n\n\n\n\n\n\n       GPT-4\n      \n\n      (2023)\n     \n\n\n       GPT-3.5\n      \n\n      (2022)\n     \n\n\n\n      Uniform Bar Exam\n     \n\n      90th\n     \n\n      10th\n     \n\n\n\n\n       LSAT\n      \n\n\n      88th\n     \n\n      40th\n     \n\n\n\n\n       SAT\n      \n\n\n      97th\n     \n\n      87th\n     \n\n\n\n\n       GRE\n      \n      (Verbal)\n     \n\n      99\n      \n       th\n      \n\n\n      63rd\n     \n\n\n\n\n       GRE\n      \n      (Quantitative)\n     \n\n      80th\n     \n\n      25\n      \n       th\n      \n\n\n\n\n\n       US Biology Olympiad\n      \n\n\n      99th\n     \n\n      32nd\n     \n\n\n\n\n       AP Calculus BC\n      \n\n\n      51st\n     \n\n      3rd\n     \n\n\n\n\n       AP Chemistry\n      \n\n\n      80th\n     \n\n      34th\n     \n\n\n\n\n       AP Macroeconomics\n      \n\n\n      92nd\n     \n\n      40th\n     \n\n\n\n\n       AP\n      \n      Statistics\n     \n\n      92nd\n     \n\n      51st\n     \n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 7: GPT-4\n   \n    scores\n   \n   on standardized tests. Note also the large jump from GPT-3.5 to GPT-4 in human percentile on these tests, often from well below the median human to the very top of the human range. (And this is GPT-3.5, a fairly recent model released less than a year before GPT-4, not the clunky old elementary-school-level GPT-3 we were talking about earlier!)\n  \n\n\n   Figure 8: Gray: Professional forecasts, made in August 2021, for June 2022 performance on the MATH benchmark (difficult mathematics problems from high-school math competitions). Red star: actual state-of-the-art performance by June 2022, far exceeding even the upper range forecasters gave. The median ML researcher was\n   \n    even more\n   \n\n    pessimistic.\n   \n\n\n\n   Over and over again, year after year, skeptics have claimed \"deep learning won't be able to do X\" and have been quickly proven wrong.\n   \n    8\n   \n\n    If there's one lesson we've learned from the past\n   \n\n    8\n   \n   Here's Yann LeCun\n   \n    predicting\n   \n   in 2022\n   \n    decade of AI, it's that you should never bet against deep learning.\n   \n\n\n\n   Now the hardest unsolved benchmarks are tests like\n   \n    GPQA,\n   \n   a set of PhD-level biology, chemistry, and physics questions. Many of the questions read like gibberish to me, and even PhDs in other scientific fields spending 30+ minutes with Google barely score above random chance. Claude 3 Opus currently gets ~60%,\n   \n    9\n   \n   compared to in-domain PhDs who get ~80%\u2014and I expect this benchmark to fall as well, in the next generation or two.\n  \n\n\n   that even GPT-5000 won't be able to reason about physical interactions with the real world; GPT-4 obviously does it with ease a year later.\n  \n\n\n   Here's Gary Marcus's walls predicted after GPT-2\n   \n    being solved\n   \n   by GPT-3, and the walls he predicted after GPT-3\n   \n    being\n   \n\n    solved\n   \n   by GPT-4.\n  \n\n\n   Here's Prof. Bryan Caplan\n   \n    losing\n   \n   his first-ever public bet (after previously famously having a perfect public betting track record). In January 2023, after GPT-3.5 got a D on his economics midterm, Prof. Caplan\n   \n    bet\n   \n   Matthew Barnett that no AI would get an A on his economics midterms by\n   \n    2029.\n   \n   Just two months later, when GPT-4 came out, it promptly scored an A on his midterm (and it would have been one of the highest scores in his class).\n  \n\n\n\n    9\n   \n   On the\n   \n    diamond set, majority voting\n   \n   of the model trying 32 times with chain-of-thought.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 9: Example GPQA questions. Models are already better at this than I am, and we'll probably crack expert-PhD-level soon. . .\n  \n\n\n\n    Counting the OOMs\n   \n\n\n\n   How did this happen? The magic of deep learning is that it\n   \n    just works\n   \n   \u2014and the trendlines have been astonishingly consistent, despite naysayers at every turn.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n    With each OOM of effective compute, models predictably, reliably get\n   \n   pute, in the example of\n   \n    OpenAI Sora.\n   \n\n    better.\n   \n\n    10\n   \n   If we can count the OOMs, we can (roughly, qualita-\n   \n    10\n   \n   And it's worth noting\n   \n    just how con\n   \n   tively) extrapolate capability improvements.\n   \n    11\n   \n   That's how a few prescient individuals saw GPT-4 coming.\n  \n\n\n   We can decompose the progress in the four years from GPT-2 to GPT-4 into three categories of scaleups:\n  \n\n\n\n\n\n\n     1. compute: We're using much bigger computers to train these models.\n    \n\n\n     2. algorithmic efficiencies: There's a continuous trend of algorithmic progress. Many of these act as \"compute multipliers,\" and we can put them on a unified scale of growing\n     \n      effective compute\n     \n     .\n    \n\n\n     3. \"unhobbling\" gains: By default, models learn a lot of amazing raw capabilities, but they are hobbled in all sorts of dumb ways, limiting their practical value. With simple algorithmic improvements like reinforcement learning from human feedback (RLHF), chain-of-thought (CoT), tools, and scaffolding, we can unlock significant latent capabilities.\n    \n\n\n\n   Figure 10: The effects of scaling com-\n  \n\n\n\n    sistent\n   \n   these trendlines are. Combining the original\n   \n    scaling laws paper\n   \n   with some of the estimates on compute and compute efficiency scaling since then implies a consistent scaling trend for\n   \n    over 15 orders of magnitude\n   \n   (over 1,000,000,000,000,000x in effective compute)!\n  \n\n\n\n    11\n   \n   A common misconception is that scaling only holds for perplexity loss, but we see very clear and consistent scaling behavior on downstream performance on benchmarks as well. It's usually just a matter of finding the right loglog graph. For example, in the GPT-4 blog post, they show consistent scaling behavior for performance on coding problems over 6 OOMs (1,000,000x) of compute, using MLPR (mean log pass rate).\n  \n\n\n   The\n   \n    \"Are Emergent Abilities a Mi\n   \n\n    rage?\"\n   \n   paper makes a similar point; with the right choice of metric, there is almost always a consistent trend for performance on downstream tasks.\n  \n\n\n   More generally, the \"scaling hypothesis\" qualitative observation\u2014very clear trends on model capability with scale\u2014predates loss-scaling-curves; the \"scaling laws\" work was just a formal measurement of this.\n  \n\n\n   We can \"count the OOMs\" of improvement along these axes: that is, trace the scaleup for each in units of effective compute. 3x is 0.5 OOMs; 10x is 1 OOM; 30x is 1.5 OOMs; 100x is 2 OOMs; and so on. We can also look at what we should expect on top of GPT-4, from 2023 to 2027.\n  \n\n\n   I'll go through each one-by-one, but the upshot is clear: we are rapidly racing through the OOMs. There are potential headwinds in the data wall, which I'll address\u2014but overall, it seems likely that we should expect another GPT-2-to-GPT-4-sized jump, on top of GPT-4, by 2027.\n  \n\n\n\n    Compute\n   \n\n\n\n   I'll start with the most commonly-discussed driver of recent progress: throwing (a lot) more compute at models.\n  \n\n\n   Many people assume that this is simply due to Moore's Law. But even in the old days when Moore's Law was in its heyday, it was comparatively\n   \n    glacial\n   \n   \u2014perhaps 1-1.5 OOMs per decade. We are seeing much more rapid scaleups in compute\u2014close to 5x the speed of Moore's law\u2014instead because of mammoth\n   \n    investment\n   \n   . (Spending even a million dollars on a single model used to be an outrageous thought nobody would entertain, and now that's pocket change!)\n  \n\n\n\n\n\n      Model\n     \n\n      Estimated Compute\n     \n\n      Growth\n     \n\n\n\n      GPT-2\n      \n      (2019)\n     \n\n      ~4e21\n      \n      FLOP\n     \n\n\n\n\n\n      GPT-3\n      \n      (2020)\n     \n\n      ~3e23\n      \n      FLOP\n     \n\n      + ~2\n      \n      OOMs\n     \n\n\n\n      GPT-4\n      \n      (2023)\n     \n\n      8e24\n      \n      to 4e25\n      \n      FLOP\n     \n\n      + ~1.5\u20132\n      \n      OOMs\n     \n\n\n\n\n\n   Table 1: Estimates of compute for GPT-2 to GPT-4 by\n   \n    Epoch AI.\n   \n\n\n\n   We can use public estimates from Epoch AI (a source widely respected for its excellent analysis of AI trends) to trace the compute scaleup from 2019 to 2023. GPT-2 to GPT-3 was a quick scaleup; there was a large overhang of compute, scaling from a smaller experiment to using an entire datacenter to train a large language model. With the scaleup from GPT-3 to GPT-4, we transitioned to the modern regime: having to build an entirely new (much bigger) cluster for the next model. And yet\n  \n\n\n   the dramatic growth continued. Overall, Epoch AI estimates suggest that GPT-4 training used ~3,000x-10,000x more raw compute than GPT-2.\n  \n\n\n   In broad strokes, this is just the continuation of a longer-running trend. For the last decade and a half, primarily because of broad scaleups in investment (and specializing chips for AI workloads in the form of GPUs and TPUs), the training compute used for frontier AI systems has grown at roughly ~0.5 OOMs/year.\n  \n\n\n\n\n\n\n\n\n\n\n   The compute scaleup from GPT-2 to GPT-3 in a year was an unusual overhang, but all the indications are that the longerrun trend will continue. The SF-rumor-mill is abreast with dramatic tales of huge GPU orders. The investments involved will be extraordinary\u2014but they are in motion. I go into this more later in the series, in IIIa. Racing to the Trillion-Dollar Cluster; based on that analysis, an additional 2 OOMs of compute (a cluster in the $10s of billions) seems very likely to happen by the end of 2027; even a cluster closer to +3 OOMs of compute ($100 billion+) seems plausible (and is\n   \n    rumored to be in the\n   \n\n    works\n   \n   at Microsoft/OpenAI).\n  \n\n\n\n    Algorithmic efficiencies\n   \n\n\n\n   While massive investments in compute get all the attention, algorithmic progress is probably a similarly important driver of progress (and has been dramatically underrated).\n  \n\n\n   To see just how big of a deal algorithmic progress can be, consider the following illustration (Figure 12) of the drop in price to attain ~50% accuracy on the MATH benchmark (high school competition math) over just\n   \n    two years.\n   \n   (For comparison, a computer science PhD student who didn't particularly like math scored 40%, so this is already quite good.) Inference efficiency improved by nearly 3 OOMs\u20141,000x\u2014in less than two years.\n  \n\n\n\n\n\n\n   Though these are numbers just for inference efficiency (which may or may not correspond to training efficiency improvements, where numbers are harder to infer from public data), they make clear there is an\n   \n    enormous\n   \n   amount of algorithmic progress possible and happening.\n  \n\n\n   Figure 12: Rough estimate on relative inference cost of attaining ~50% MATH performance.\n  \n\n\n\n    Calculations below.\n   \n\n\n\n   Gemini 1.5 Flash\n   \n    scores\n   \n   54.9% on MATH, and\n   \n    costs\n   \n   $0.35/$1.05 (input/output) per million tokens. GPT-4 scored 42.5% on MATH\n   \n    prelease\n   \n   and\n   \n    52\n   \n   .9% on MATH in early 2023, and\n   \n    cost\n   \n   $30/$60 (input/output) per million tokens; that's 85x/57x (input/output) more expensive per token than Gemini 1.5 Flash. To be conservative, I use an estimate of 30x cost decrease above (accounting for Gemini 1.5 Flash possibly using more tokens to reason through problems).\n  \n\n\n   Minerva540B\n   \n    scores\n   \n   50.3% on MATH, using majority voting among 64 samples. A knowledgeable friend estimates the base model here is probably 2- 3x more expensive to inference than GPT-4. However, Minerva seems to use somewhat fewer tokens per answer on a quick spot check. More importantly, Minerva needed 64 samples to achieve that performance, naively implying a 64x multiple on cost if you e.g. naively ran this via an inference API. In practice, prompt tokens can be cached when running an eval; given a few-shot prompt, prompt tokens are likely a majority of the cost, even accounting for output tokens. Supposing output tokens are a third of the cost for getting a single sample, that would imply only a ~20x increase in cost from the maj@64 with caching. To be conservative, I use the rough number of a 20x cost decrease in the above (even if the naive decrease in inference cost from running this via an API would be larger).\n  \n\n\n   In this piece, I'll separate out two kinds of algorithmic progress. Here, I'll start by covering \"within-paradigm\" algorithmic improvements\u2014those that simply result in better base models, and that straightforwardly act as\n   \n    compute efficiencies\n   \n   or\n   \n    compute multipliers\n   \n   . For example, a better algorithm might allow us to achieve the same performance but with 10x less training compute. In turn, that would act as a 10x (1 OOM) increase in\n   \n    effective compute\n   \n   . (Later, I'll cover \"unhobbling,\" which you can think of as \"paradigm-expanding/application-expanding\" algorithmic progress that unlocks capabilities of base models.)\n  \n\n\n   If we step back and look at the long-term trends, we seem to find new algorithmic improvements at a fairly consistent rate. Individual discoveries seem random, and at every turn, there seem insurmountable obstacles\u2014but the long-run trendline is predictable, a straight line on a graph. Trust the trendline.\n  \n\n\n   We have the best data for ImageNet (where algorithmic research has been mostly public and we have data stretching back a decade), for which we have consistently improved compute efficiency by roughly ~0.5 OOMs/year across the 9-year period between 2012 and 2021.\n  \n\n\n\n\n\n\n\n\n\n   That's a huge deal: that means 4 years later, we can achieve the same level of performance for ~100x less compute (and concomitantly, much higher performance for the same compute!).\n  \n\n\n   Unfortunately, since labs don't publish internal data on this, it's harder to measure algorithmic progress for frontier LLMs\n  \n\n\n   Figure 13: We can measure algorithmic progress: how much less compute is needed in 2021 compared to 2012 to train a model with the same performance? We see a trend of ~0.5 OOMs/year of algorithmic efficiency. Source:\n   \n    Erdil and Besiroglu\n   \n   2022.\n  \n\n\n   over the last four years.\n   \n    EpochAI has new work\n   \n   replicating their results on ImageNet for language modeling, and estimate a similar ~0.5 OOMs/year of algorithmic efficiency trend in LLMs from 2012 to 2023. (This has wider error bars though, and doesn't capture some more recent gains, since the leading labs have stopped publishing their algorithmic efficiencies.)\n  \n\n\n\n\n\n\n\n\n\n   More directly looking at the last 4 years, GPT-2 to GPT-3 was basically a simple scaleup (according to\n   \n    the paper)\n   \n   , but there have been many publicly-known and publicly-inferable gains since GPT-3:\n  \n\n\n\n\n\n\n     We can infer gains from API costs:\n     \n      12\n     \n\n\n\n\n\n        \u2013\n       \n       GPT-4, on release, cost ~the same as GPT-3 when it was released, despite the absolutely enormous performance increase.\n       \n        13\n       \n       (If we do a naive and oversimplified back-of-theenvelope estimate based on scaling laws, this suggests that perhaps roughly half the effective compute increase from GPT-3 to GPT-4 came from algorithmic improvements.14)\n      \n\n\n\n\n\n\n        \u2013\n       \n       Since the GPT-4 release a year ago, OpenAI prices for GPT-4-level models have fallen another 6x/4x (input/output) with the release of GPT-4o.\n      \n\n\n\n\n\n\n\n\n\n\n    12\n   \n   Though these are inference efficiencies (rather than necessarily training efficiencies), and to some extent will reflect inference-specific optimizations, a) they suggest enormous amounts of algorithmic progress is possible and happening in general, and b) it's often the case that an algorithmic improvements is both a training efficiency gain and an inference efficiency, for example by reducing the number of parameters necessary.\n  \n\n\n\n    13\n   \n\n    GPT-\n   \n   3: $60/1M tokens,\n   \n    GPT-\n   \n   4: $30/1M input tokens and $60/1M output tokens.\n  \n\n\n\n    14\n   \n   Chinchilla scaling laws say that one should scale parameter count and data equally. That is, parameter count grows \"half the OOMs\" of the OOMs that effective training compute grows. At the same time, parameter count is intuitively roughly proportional to inference costs. All else equal, constant inference costs thus implies that half of the OOMs of effective compute growth were \"canceled out\" by algorithmic win.\n  \n\n\n   That said, to be clear, this is a very naive calculation (just meant for a rough illustration) that is wrong in various ways. There may be inferencespecific optimizations (that don't translate into training efficiency); there may be training efficiencies that don't reduce parameter count (and thus don't translate into inference efficiency); and so on.\n  \n\n\n\n\n\n\n\n      \u2013\n     \n     Gemini 1.5 Flash, recently released, offers between \"GPT-3.75-level\" and GPT-4-level performance,\n     \n      15\n     \n     while\n     \n      costing\n     \n\n      15\n     \n     Gemini\n     \n      1\n     \n     .\n     \n      5\n     \n     Flash ranks similarly to 85x/57x (input/output) less than the original GPT-4 (extraordinary gains!).\n    \n\n\n\n      Chinchilla scaling laws\n     \n     give a 3x+ (0.5 OOMs+) efficiency gain.\n     \n      16\n     \n\n\n\n     Gemini 1.5 Pro claimed\n     \n      major compute efficiency gains\n     \n     (outperforming Gemini 1.0 Ultra, while using \"significantly less\" compute), with Mixture of Experts (MoE) as a highlighted architecture change.\n     \n      Other\n     \n\n      papers\n     \n\n      also\n     \n\n      claim\n     \n     a substantial multiple on compute from MoE.\n    \n\n\n     There have been many tweaks and gains on\n     \n      architecture,\n     \n\n      data,\n     \n\n      training stack,\n     \n\n      etc.\n     \n     all the time.\n     \n      17\n     \n\n\n\n\n   Put together, public information suggests that the GPT-2 to scale. GPT-4 jump included 1-2 OOMs of algorithmic efficiency gains.\n   \n    18\n   \n\n\n\n\n\n\n\n   GPT-4 (higher than original GPT-4, lower than updated versions of GPT-4)\n   \n    on LMSys, a chatbot leaderboard,\n   \n   and has\n   \n    similar performance\n   \n   on MATH and GPQA (evals that measure reasoning) as the original GPT-4, while landing roughly in the middle between GPT-3.5 and GPT-4 on MMLU (an eval that more heavily weights towards measuring knowledge).\n  \n\n\n\n    16\n   \n\n    At ~GPT-\n   \n   3 scale, more than 3x at larger scales.\n  \n\n\n\n    17\n   \n   For example,\n   \n    this paper\n   \n   contains a comparison of a GPT-3-style vanilla Transformer to various simple changes to architecture and training recipe published over the years (RMSnorms instead of layernorm, different positional embeddings, SwiGlu activation, AdamW optimizer instead of Adam, etc.), what they call \"Transformer++\", implying a 6x gain at least at small\n  \n\n\n\n    18\n   \n   If we take the trend of 0.5 OOMs/year, and 4 years between GPT-2 and GPT-4 release, that would be 2 OOMs. However, GPT-2 to GPT-3 was a simple scaleup (after big gains from e.g. Transformers), and OpenAI claims GPT-4\n   \n    pretraining finished in\n   \n\n    2022\n   \n   , which could mean we're looking at closer to 2 years worth of algorithmic progress that we should be counting here. 1 OOM of algorithmic efficiency seems like a conservative lower bound.\n  \n\n\n   Figure 15: Decomposing progress: compute and algorithmic efficiencies. (Rough illustration.)\n  \n\n\n   Over the 4 years following GPT-4, we should expect the trend to continue:\n   \n    19\n   \n   on average ~0.5 OOMs/year of compute effi-\n   \n    19\n   \n   At the very least, given over a decade ciency, i.e. ~2 OOMs of gains compared to GPT-4 by 2027. While compute efficiencies will become harder to find as we pick the low-hanging fruit, AI lab investments in money and talent to find new algorithmic improvements are growing rapidly.\n   \n    20\n   \n   (The publicly-inferable inference cost efficiencies,\n   \n    20\n   \n   The economic returns to a\n   \n    3\n   \n   x compute of billions or more, given cluster costs. at least, don't seem to have slowed down at all.) On the high end, we could even see more fundamental, Transformer-like\n   \n    21\n   \n   breakthroughs with even bigger gains.\n   \n    gain.\n   \n\n\n\n   Put together, this suggests we should expect something like 1-3 OOMs of algorithmic efficiency gains (compared to GPT-4) by the end of 2027, maybe with a best guess of ~2 OOMs.\n  \n\n\n\n    The data wall\n   \n\n\n\n   There is a potentially important source of variance for all of this: we're running out of internet data. That could mean that, very soon, the naive approach to pretraining larger language models on more scraped data could start hitting serious bottlenecks.\n  \n\n\n   Frontier models are already trained on much of the internet. Llama 3, for example, was trained on over 15\n   \n    T tokens.\n   \n   Common Crawl, a dump of much of the internet\n   \n    used for\n   \n\n    LLM training,\n   \n   is >100T tokens raw, though much of that is spam and duplication (e.g., a\n   \n    relatively simple deduplica\n   \n\n    tion\n   \n   leads to 30T tokens, implying Llama 3 would already be using basically all the data). Moreover, for more specific domains like code, there are many fewer tokens still, e.g.\n   \n    public github repos\n   \n   are estimated to be in low trillions of tokens.\n  \n\n\n   You can go somewhat further by repeating data, but\n   \n    aca\n   \n\n    demic work on this\n   \n   suggests that repetition only gets you so far, finding that after 16 epochs (a 16-fold repetition), returns diminish extremely fast to nil. At some point, even with more (effective) compute, making your models better can become much tougher because of the data constraint. This isn't to be understated: we've been riding the\n  \n\n\n   of consistent algorithmic improvements, the burden of proof would be on those who would suggest it will all suddenly come to a halt!\n  \n\n\n   efficiency will be measured in the $10s\n   \n    21\n   \n   Very roughly something like a ~\n   \n    10\n   \n   x\n  \n\n\n   scaling curves, riding the wave of the language-modelingpretraining-paradigm, and without something new here, this paradigm will (at least naively) run out. Despite the massive investments, we'd plateau.\n  \n\n\n   All of the labs are rumored to be making massive research bets on new algorithmic improvements or approaches to get around this. Researchers are purportedly trying many strategies, from\n   \n    synthetic data to self-play and RL ap\n   \n\n    proaches.\n   \n   Industry insiders seem to be very bullish: Dario Amodei (CEO of Anthropic)\n   \n    recently said on a podcast:\n   \n   \"if you look at it very naively we're not that far from running out of data [. . . ] My guess is that this will not be a blocker [. . . ] There's just many different ways to do it.\" Of course, any research results on this are proprietary and not being published these days.\n  \n\n\n   In addition to insider bullishness, I think there's a strong intuitive case for why it should be possible to find ways to train models with much better sample efficiency (algorithmic improvements that let them learn more from limited data). Consider how you or I would learn from a really dense math textbook:\n  \n\n\n\n\n\n\n     What a modern LLM does during training is, essentially, very very quickly skim the textbook, the words just\n     \n      flying by\n     \n     , not spending much brain power on it.\n    \n\n\n     Rather, when you or I read that math textbook, we read a couple pages slowly; then have an internal monologue about the material in our heads and talk about it with a few study-buddies; read another page or two; then try some practice problems, fail, try them again in a different way, get some feedback on those problems, try again until we get a problem right; and so on, until eventually the material \"clicks.\"\n    \n\n\n     You or I also wouldn't learn much at all from a pass through a dense math textbook if all we could do was breeze through it like LLMs.\n     \n      22\n     \n\n      22\n     \n     And just rereading the same textbook\n    \n\n\n\n   over and over again might result in memorization, not understanding. I take it that's how many wordcels pass math classes!\n  \n\n\n   \u2022 But perhaps, then, there are ways to incorporate aspects of how humans would digest a dense math textbook to let the models learn much more from limited data. In a simplified sense, this sort of thing\u2014having an internal monologue about material, having a discussion with a study-buddy, trying and failing at problems until it clicks\u2014is what many synthetic data/self-play/RL approaches are trying to do.\n   \n    23\n   \n\n\n\n   The old state of the art of training models was simple and naive, but it worked, so nobody really tried hard to crack these approaches to sample efficiency. Now that it may become more of a constraint, we should expect all the labs to invest billions of dollars and their smartest minds into cracking it. A common pattern in deep learning is that it takes\n   \n    a lot\n   \n   of effort (and many failed projects) to get the details right, but eventually some version of the obvious and simple thing just works. Given how deep learning has managed to crash through every supposed wall over the last decade, my base case is that it will be similar here.\n  \n\n\n   Moreover, it actually seems possible that cracking one of these algorithmic bets like synthetic data could dramatically\n   \n    improve\n   \n   models. Here's an intuition pump. Current frontier models like Llama 3 are trained on the internet and the internet is mostly crap, like e-commerce or SEO or whatever. Many LLMs spend the vast majority of their training compute on this crap, rather than on really highquality data (e.g. reasoning chains of people working through difficult science problems). Imagine if you could spend GPT-4-level compute on entirely extremely highquality data\u2014it could be a much, much more capable model.\n  \n\n\n   A look back at AlphaGo\u2014the first AI system that beat the world champions at Go, decades before it was thought possible\u2014is useful here as well.\n   \n    24\n   \n\n    24\n   \n   See also Andrej Karpathy's talk\n  \n\n\n   \u2022 In step 1, AlphaGo was trained by imitation learning on expert human Go games. This gave it a foundation.\n  \n\n\n\n    23\n   \n   One other way of thinking about it I find interesting: there is a \"missingmiddle\" between pretraining and in-context learning.\n  \n\n\n   In-context learning is\n   \n    incredible\n   \n   (and competitive with human sample efficiency). For example, the\n   \n    Gemini\n   \n   1.5\n   \n    Pro paper\n   \n   discusses giving the model instructional materials (a textbook, a dictionary) on Kalamang, a language spoken by fewer than 200 people and basically not present on the internet, in context\u2014and the model learns to translate from English to Kalamang at human-level! In context, the model is able to learn from the textbook as well as a human could (and much better than it would learn from just chucking that one textbook into pretraining).\n  \n\n\n   When a human learns from a textbook, they're able to distill their shortterm memory/learnings into long-term memory/long-term skills with practice; however, we don't have an equivalent way to distill in-context learning \"back to the weights.\" Synthetic data/selfplay/RL/etc are trying to fix that: let the model learn by itself, then think about it and practice what it learned, distilling that learning back into the weights.\n  \n\n\n   discussing this\n   \n    here.\n   \n\n\n\n   \u2022 In step 2, AlphaGo played millions of games against itself. This let it become superhuman at Go: remember the famous move 37 in the game against Lee Sedol, an extremely unusual but brilliant move a human would never have played.\n  \n\n\n   Developing the equivalent of step 2 for LLMs is a key research problem for overcoming the data wall (and, moreover, will ultimately be the key to surpassing human-level intelligence).\n  \n\n\n   All of this is to say that data constraints seem to inject large error bars either way into forecasting the coming years of AI progress. There's a very real chance things stall out (LLMs might still be as big of a deal as the internet, but we wouldn't get to truly crazy AGI). But I think it's reasonable to guess that the labs will crack it, and that doing so will not just keep the scaling curves going, but possibly enable huge gains in model capability.\n  \n\n\n   As an aside, this also means that we should expect more variance between the different labs in coming years compared to today. Up until recently, the state of the art techniques were published, so everyone was basically doing the same thing. (And new upstarts or open source projects could easily compete with the frontier, since the recipe was published.) Now, key algorithmic ideas are becoming increasingly proprietary. I'd expect labs' approaches to diverge much more, and some to make faster progress than others\u2014even a lab that seems on the frontier now could get stuck on the data wall while others make a breakthrough that lets them race ahead. And open source will have a much harder time competing. It will certainly make things interesting. (And if and when a lab figures it out, their breakthrough will be the key to AGI, key to superintelligence\u2014one of the United States' most prized secrets.)\n  \n\n\n\n    Unhobbling\n   \n\n\n\n   Finally, the hardest to quantify\u2014but no less important\u2014category of improvements: what I'll call \"unhobbling.\"\n  \n\n\n   Imagine if when asked to solve a hard math problem, you had to instantly answer with the very first thing that came to mind. It seems obvious that you would have a hard time, except for the simplest problems. But until recently, that's how we had LLMs solve math problems. Instead, most of us work through the problem step-by-step on a scratchpad, and are able to solve much more difficult problems that way. \"Chain-of-thought\" prompting unlocked that for LLMs. Despite excellent raw capabilities, they were much worse at math than they could be because they were hobbled in an obvious way, and it took a small algorithmic tweak to unlock much greater capabilities.\n  \n\n\n   We've made huge strides in \"unhobbling\" models over the past few years. These are algorithmic improvements beyond just training better base models\u2014and often only use a fraction of pretraining compute\u2014that unleash model capabilities:\n  \n\n\n\n\n\n\n\n      Reinforcement learning from human feedback (RLHF)\n     \n     . Base models have incredible\n     \n      latent\n     \n     capabilities,\n     \n      25\n     \n     but they're raw and\n     \n      25\n     \n     That's the magic of unsupervised incredibly hard to work with. While the popular conception of RLHF is that it merely censors swear words, RLHF has been key to making models actually useful and commercially valuable (rather than making models predict random internet text, get them to actually apply their capabilities to try to answer your question!). This was the magic of ChatGPT\u2014well-done RLHF made models usable and useful to real people for the first time. The original\n     \n      InstructGPT\n     \n\n      paper\n     \n     has a great quantification of this: an RLHF'd small model was equivalent to a non-RLHF'd >100x larger model in terms of human rater preference.\n    \n\n\n\n      Chain of Thought (CoT)\n     \n     . As discussed.\n     \n      CoT started being\n     \n\n      widely used just\n     \n     2 years ago and can provide the equivalent of a >10x effective compute increase on math/reasoning problems.\n    \n\n\n\n      Scaffolding\n     \n     . Think of CoT++: rather than just asking a model\n    \n\n\n\n   learning, in some sense: to better predict the next token, to make perplexity go down, models learn incredibly rich internal representations, everything from\n   \n    (famously)\n   \n   sentiment to complex world models. But, out of the box, they're hobbled: they're using their incredible internal representations merely to predict the next token in random internet text, and rather than applying them in the best way to actually try to solve your problem.\n  \n\n\n   to solve a problem, have one model make a plan of attack, have another propose a bunch of possible solutions, have another critique it, and so on. For\n   \n    example,\n   \n   on HumanEval (coding problems), simple scaffolding enables GPT-3.5 to outperform un-scaffolded GPT-4. On SWE-Bench (a benchmark of solving real-world software engineering tasks), GPT-4 can only solve ~2% correctly, while with\n   \n    Devin's agent\n   \n\n    scaffolding\n   \n   it jumps to 14-23%. (Unlocking agency is only in its infancy though, as I'll discuss more later.)\n  \n\n\n\n\n\n\n\n      Tools:\n     \n     Imagine if humans weren't allowed to use calculators or computers. We're only at the beginning here, but Chat-GPT can now use a web browser, run some code, and so on.\n    \n\n\n\n      Context length\n     \n     . Models have gone from 2k token context (GPT-3) to 32k context (GPT-4 release) to 1M+ context (Gemini 1.5 Pro). This is a\n     \n      huge\n     \n     deal. A much smaller base model with, say, 100k tokens of relevant context can outperform a model that is much larger but only has, say, 4k relevant tokens of context\u2014more context is effectively a large compute efficiency gain.\n     \n      26\n     \n     More generally, context is key to unlock-\n     \n      26\n     \n     See Figure\n     \n      7\n     \n     from the\n     \n      updated Gem\n     \n     ing many applications of these models: for example, many coding applications require understanding large parts of a codebase in order to usefully contribute new code; or, if you're using a model to help you write a document at work, it really needs the context from lots of related internal docs and conversations. Gemini 1.5 Pro, with its 1M+ token context, was\n     \n      even able\n     \n     to learn a new language (a low-resource language not on the internet) from scratch, just by putting a dictionary and grammar reference materials in context!\n    \n\n\n\n      Posttraining improvements.\n     \n     The current GPT-4 has substantially improved compared to the original GPT-4 when released,\n     \n      according to John Schulman\n     \n     due to posttraining improvements that unlocked latent model capability: on\n     \n      reasoning evals\n     \n     it's made substantial gains (e.g., ~50% -> 72% on MATH, ~40% to ~50% on GPQA) and on the\n     \n      LMSys\n     \n\n      leaderboard,\n     \n     it's made nearly 100-point elo jump (comparable to the difference in elo between Claude 3 Haiku and the much larger Claude 3 Opus, models that have a ~50x\n     \n      price\n     \n\n      difference)\n     \n     .\n    \n\n\n\n   ini 1.5\n   \n    whitepaper,\n   \n   comparing perplexity vs. context for Gemini 1.5 Pro and Gemini 1.5 Flash (a much cheaper and presumably smaller model).\n  \n\n\n\n    A survey by Epoch AI\n   \n   of some of these techniques, like scaffolding, tool use, and so on, finds that techniques like this can typically result in effective compute gains of 5-30x on many benchmarks. METR (an organization that evaluates models) similarly found very large performance improvements on their set of agentic tasks, via unhobbling from the same GPT-4 base model: from 5% with just the base model, to 20% with the GPT-4 as posttrained on release, to nearly 40% today from better posttraining, tools, and agent scaffolding (Figure 16).\n  \n\n\n\n\n\n\n   Figure 16: Performance on METR's agentic tasks, over time via better unhobbling. Source:\n   \n    Model Evaluation\n   \n\n    and Threat Research\n   \n\n\n\n   While it's hard to put these on a unified effective compute scale with compute and algorithmic efficiencies, it's clear these are\n   \n    huge\n   \n   gains, at least on a roughly similar magnitude as the compute scaleup and algorithmic efficiencies. (It also highlights the central role of algorithmic progress: the ~0.5 OOMs/year of compute efficiencies, already significant, are only part of the story, and put together with unhobbling algorithmic progress overall is maybe even a majority of the gains on the current trend.)\n  \n\n\n   \"Unhobbling\" is a huge part of what actually enabled these models to become useful\u2014and I'd argue that much of what is holding back many commercial applications today is the need for further \"unhobbling\" of this sort. Indeed,\n   \n    models today are still incredibly hobbled\n   \n   ! For example:\n  \n\n\n   \u2022 They don't have long-term memory.\n  \n\n\n\n\n\n\n\n\n\n\n     They can't use a computer (they still only have very limited tools).\n    \n\n\n     They still mostly don't think before they speak. When you ask ChatGPT to write an essay, that's like expecting a human to write an essay via their initial stream-of-consciousness.\n     \n      27\n     \n\n      27\n     \n     People are\n     \n      working on this though.\n     \n\n\n\n     They can (mostly) only engage in short back-and-forth dialogues, rather than going away for a day or a week, thinking about a problem, researching different approaches, consulting other humans, and then writing you a longer report or pull request.\n    \n\n\n     They're mostly not personalized to you or your application (just a generic chatbot with a short prompt, rather than having all the relevant background on your company and your work).\n    \n\n\n\n   The possibilities here are enormous, and we're rapidly picking low-hanging fruit here. This is critical:\n   \n    it's completely wrong to just imagine \"GPT-6 ChatGPT.\"\n   \n   With continued unhobbling\n  \n\n\n\n\n\n   Figure 17: Decomposing progress: compute, algorithmic efficiencies, and unhobbling. (Rough illustration.)\n  \n\n\n   progress, the improvements will be step-changes compared to GPT-6 + RLHF. By 2027, rather than a chatbot, you're going to have something that looks more like an agent, like a coworker.\n  \n\n\n\n    From chatbot to agent-coworker\n   \n\n\n\n   What could ambitious unhobbling over the coming years look like? The way I think about it, there are three key ingredients:\n  \n\n\n   1. solving the \"onboarding problem\"\n  \n\n\n   GPT-4 has the raw smarts to do a decent chunk of many people's jobs, but it's sort of like a smart new hire that just showed up 5 minutes ago: it doesn't have any relevant context, hasn't read the company docs or Slack history or had conversations with members of the team, or spent any time understanding the company-internal codebase. A smart new hire isn't that useful 5 minutes after arriving\u2014but they are quite useful a month in! It seems like it should be possible, for example via very-long-context, to \"onboard\" models like we would a new human coworker. This alone would be a huge unlock.\n  \n\n\n   2. the test-time compute overhang (reasoning/error correction/system ii for longer-horizon problems)\n  \n\n\n   Right now, models can basically only do short tasks: you ask them a question, and they give you an answer. But that's extremely limiting. Most useful cognitive work humans do is longer horizon\u2014it doesn't just take 5 minutes, but hours, days, weeks, or months.\n  \n\n\n   A scientist that could only think about a difficult problem for 5 minutes couldn't make any scientific breakthroughs. A software engineer that could only write skeleton code for a single function when asked wouldn't be very useful software engineers are given a larger task, and they then go make a plan, understand relevant parts of the codebase or\n  \n\n\n   technical tools, write different modules and test them incrementally, debug errors, search over the space of possible solutions, and eventually submit a large pull request that's the culmination of weeks of work. And so on.\n  \n\n\n   In essence, there is a large\n   \n    test-time compute overhang.\n   \n   Think of each GPT-4 token as a word of internal monologue when you think about a problem. Each GPT-4 token is quite smart, but it can currently only really effectively use on the order of ~hundreds of tokens for chains of thought coherently (effectively as though you could only spend a few minutes of internal monologue/thinking on a problem or project).\n  \n\n\n\n    Number of tokens Equivalent to me working on something for. . .\n   \n   100s A few minutes ChatGPT (we are here) 1,000s Half an hour +1 OOMs test-time compute 10,000s Half a workday +2 OOMs 100,000s A workweek +3 OOMs Millions Multiple months +4 OOMs\n  \n\n\n   What if it could use millions of tokens to think about and work on really hard problems or bigger projects?\n  \n\n\n   Even if the \"per-token\" intelligence were the same, it'd be the difference between a smart person spending a\n   \n    few minutes\n   \n   vs. a\n   \n    few months\n   \n   on a problem. I don't know about you, but there's much, much, much more I am capable of in a few months vs. a few minutes. If we could unlock \"being able to think and work on something for monthsequivalent, rather than a few-minutes-equivalent\" for models, it would unlock an\n   \n    insane\n   \n   jump in capability. There's a huge overhang here, many OOMs worth.\n  \n\n\n   Right now, models can't do this yet. Even with recent advances in long-context, this longer context mostly only works for the consumption of tokens, not the production of tokens\u2014after a while, the model goes off the rails or gets stuck. It's not yet able to go away for a while to work on a\n  \n\n\n   Table 2: Assuming a human thinking at ~100 tokens/minute and working 40 hours/week, translating \"how long a model thinks\" in tokens to human-time on a given problem/project.\n  \n\n\n   problem or project on its own.\n   \n    28\n   \n\n    28\n   \n   Which makes sense\u2014why would\n  \n\n\n   But unlocking test-time compute might merely be a matter of relatively small \"unhobbling\" algorithmic wins. Perhaps a small amount of RL helps a model learn to error correct (\"hm, that doesn't look right, let me double check that\"), make plans, search over possible solutions, and so on. In a sense, the model already has most of the raw capabilities, it just needs to learn a few extra skills on top to put it all together.\n  \n\n\n   In essence, we just need to teach the model a sort of System II outer loop\n   \n    29\n   \n   that lets it reason through difficult, long-\n   \n    29\n   \n   System I vs. System II is a useful horizon projects.\n  \n\n\n   If we succeed at teaching this outer loop, instead of a short chatbot answer of a couple paragraphs, imagine a stream of millions of words (coming in more quickly than you can read them) as the model thinks through problems, uses tools, tries different approaches, does research, revises its work, coordinates with others, and completes big projects on its own.\n  \n\n\n\n    Trading off test-time and train-time compute in other ML domains.\n   \n   In other domains, like AI systems for board games, it's been demonstrated that you can use more test-time compute (also called inference-time compute) to substitute for training compute.\n  \n\n\n\n\n\n\n\n\n\n   it have learned the skills for longerhorizon reasoning and error correction? There's very little data on the internet in the form of \"my complete internal monologue, reasoning, all the relevant steps over the course of a month as I work on a project.\" Unlocking this capability will require a new kind of training, for it to learn these extra skills.\n  \n\n\n   Or as Gwern put it (private correspondence): \" 'Brain the size of a galaxy, and what do they ask me to do? Predict the misspelled answers on benchmarks!' Marvin the depressed neural network moaned.\"\n  \n\n\n   way of thinking about current capabilities of LLMs\u2014including their limitations and dumb mistakes\u2014and what might be possible with RL and unhobbling. Think of this way: when you are driving, most of the time you are on autopilot (system I, what models mostly do right now). But when you encounter a complex construction zone or novel intersection, you might ask your passenger-seat-companion to pause your conversation for a moment while you figure out\u2014actually think about\u2014what's going on and what to do. If you were forced to go about life with only system I (closer to models today), you'd have a lot of trouble. Creating the ability for system II reasoning loops is a central unlock.\n  \n\n\n   Figure 18:\n   \n    Jones (\n   \n   2021): A smaller model can do as well as a much larger model at the game of Hex if you give it more test-time compute (\"more time to think\"). In this domain, they find that one can spend ~1.2 OOMs more compute at test-time to get performance equivalent to a model with ~1 OOMs more training compute.\n  \n\n\n   If a similar relationship held in our case, if we could unlock +4 OOMs of test-time compute, that might be equivalent to +3 OOMs of pretraining compute, i.e. very roughly something like the jump between GPT-3 and GPT-4. (Solving this \"unhobbling\" would be equivalent to a huge OOM scaleup.)\n  \n\n\n   3. using a computer\n  \n\n\n   This is perhaps the most straightforward of the three. Chat-GPT right now is basically like a human that sits in an isolated box that you can text. While early unhobbling improvements teach models to use individual isolated tools, I expect that with multimodal models we will soon be able to do this in one fell swoop: we will simply enable models to use a computer like a human would.\n  \n\n\n   That means joining your Zoom calls, researching things online, messaging and emailing people, reading shared docs, using your apps and dev tooling, and so on. (Of course, for models to make the most use of this in longer-horizon loops, this will go hand-in-hand with unlocking test-time compute.)\n  \n\n\n   By the end of this, I expect us to get something that looks a lot like a\n   \n    drop-in remote worker\n   \n   . An agent that joins your company, is onboarded like a new human hire, messages you and colleagues on Slack and uses your softwares, makes pull requests, and that, given big projects, can do the model-equivalent of a human going away for weeks to independently complete the project. You'll probably need somewhat better base models than GPT-4 to unlock this, but possibly not even\n   \n    that\n   \n   much better\u2014a lot of juice is in fixing the clear and basic ways models are still hobbled.\n  \n\n\n   (A very early peek at what this might look like is\n   \n    Devin,\n   \n   an early prototype of unlocking the \"agency-overhang\"/\"testtime compute overhang\" on models on the path to creating a fully automated software engineer. I don't know how well Devin works in practice, and this demo is still very\n  \n\n\n   limited compared to what proper chatbot \u2192 agent unhobbling would yield, but it's a useful teaser of the sort of thing coming soon.)\n  \n\n\n   By the way, the centrality of unhobbling might lead to a somewhat interesting \"sonic boom\" effect in terms of commercial applications. Intermediate models between now and the dropin remote worker will require tons of schlep to change workflows and build infrastructure to integrate and derive economic value from. The drop-in remote worker will be dramatically easier to integrate\u2014just, well, drop them in to automate all the jobs that could be done remotely. It seems plausible that the schlep will take longer than the unhobbling, that is, by the time the drop-in remote worker is able to automate a large number of jobs, intermediate models won't yet have been fully harnessed and integrated\u2014so the jump in economic value generated could be somewhat discontinuous.\n  \n\n\n\n    The next four years\n   \n\n\n\n   Putting the numbers together, we should (roughly) expect another GPT-2-to-GPT-4-sized jump in the 4 years following GPT-4, by the end of 2027.\n  \n\n\n\n\n\n\n     GPT-2 to GPT-4 was roughly a 4.5\u20136 OOM base effective compute scaleup (physical compute and algorithmic efficiencies), plus major \"unhobbling\" gains (from base model to chatbot).\n    \n\n\n     In the subsequent 4 years, we should expect 3\u20136 OOMs of base effective compute scaleup (physical compute algorithmic efficiencies)\u2014with perhaps a best guess of ~5 OOMs\u2014plus step-changes in utility and applications unlocked by \"unhobbling\" (from chatbot to agent/drop-in remote worker).\n    \n\n\n\n   To put this in perspective, suppose GPT-4 training took 3 months.\n   \n    In 2027, a leading AI lab will be able to train a GPT-4 level model in a minute.\n   \n\n    30\n   \n   The OOM effective compute scaleup\n  \n\n\n\n    30\n   \n   On the best guess assumptions on physical compute and algorithmic efficiency scaleups described above, and simplifying parallelism considerations (in reality, it might look more like \"1440 (60*24) GPT-4-level models in a day\" or similar).\n  \n\n\n\n\n\n\n   Figure 19: Summary of the estimates on drivers of progress in the four years preceding GPT-4, and what we should expect in the four years following GPT-4.\n  \n\n\n   will be dramatic.\n  \n\n\n   Where will that take us?\n  \n\n\n\n\n\n\n   OOMs. GPT-2 to GPT-4 took us from ~preschooler to ~smart highschooler; from barely being able to output a few cohesive sentences to acing high-school exams and being a useful coding assistant. That was an insane jump. If\n   \n    this\n   \n   is the intelligence gap we'll cover once more, where will that take us?\n   \n    31\n   \n   We\n   \n    31\n   \n   Of course, any benchmark we have should not be surprised if that takes us very, very far. Likely, it will take us to models that can outperform PhDs and the best experts in a field.\n  \n\n\n   (One neat way to think about this is that the current trend of AI progress is proceeding at roughly 3x the pace of child development. Your 3x-speed-child just graduated high school; it'll be taking your job before you know it!)\n  \n\n\n   Again, critically, don't just imagine an incredibly smart Chat-GPT: unhobbling gains should mean that this looks more like a drop-in remote worker, an incredibly smart agent that can reason and plan and error-correct and knows everything about you and your company and can work on a problem indepen-\n  \n\n\n   Figure 20: Summary of counting the\n  \n\n\n   today will be saturated. But that's not saying much; it's mostly a reflection on the difficulty of making hard-enough benchmarks.\n  \n\n\n   dently for weeks.\n  \n\n\n   We are on course for AGI by 2027. These AI systems will basically be able to automate basically all cognitive jobs (think: all jobs that could be done remotely).\n  \n\n\n   To be clear\u2014the error bars are large. Progress could stall as we run out of data, if the algorithmic breakthroughs necessary to crash through the data wall prove harder than expected. Maybe unhobbling doesn't go as far, and we are stuck with merely expert chatbots, rather than expert coworkers. Perhaps the decade-long trendlines break, or scaling deep learning hits a wall for real this time. (Or an algorithmic breakthrough, even simple unhobbling that unleashes the test-time compute overhang, could be a paradigm-shift, accelerating things further and leading to AGI even earlier.)\n  \n\n\n   In any case, we are racing through the OOMs, and it requires no esoteric beliefs, merely trend extrapolation of straight lines, to take the possibility of AGI\u2014true AGI\u2014by 2027\n   \n    extremely\n   \n   seriously.\n  \n\n\n   It seems like many are in the game of downward-defining AGI these days, as just as really good chatbot or whatever. What I mean is an AI system that could fully automate my or my friends' job, that could fully do the work of an AI researcher or engineer. Perhaps some areas, like robotics, might take longer to figure out by default. And the societal rollout, e.g. in medical or legal professions, could easily be slowed by societal choices or regulation. But once models can automate AI research itself, that's enough\u2014enough to kick off intense feedback loops\u2014and we could very quickly make further progress, the automated AI engineers themselves solving all the remaining bottlenecks to fully automating everything. In particular, millions of automated researchers could very plausibly compress a decade of further algorithmic progress into a year or less. AGI will merely be a small taste of the superintelligence soon to follow. (More on that in the next chapter.)\n  \n\n\n   In any case, do not expect the vertiginous pace of progress to abate. The trendlines look innocent, but their implications are\n  \n\n\n   intense. As with every generation before them, every new generation of models will dumbfound most onlookers; they'll be incredulous when, very soon, models solve incredibly difficult science problems that would take PhDs days, when they're whizzing around your computer doing your job, when they're writing codebases with millions of lines of code from scratch, when every year or two the economic value generated by these models 10xs. Forget scifi, count the OOMs: it's what we should expect. AGI is no longer a distant fantasy. Scaling up simple deep learning techniques has just worked, the models just want to learn, and we're about to do another 100,000x+ by the end of 2027. It won't be long before they're smarter than us.\n  \n\n\n\n\n\n\n\n\n\n   Figure 21: GPT-4 is just the beginning where will we be four years later? Do not make the mistake of underestimating the rapid pace of deep learning progress (as illustrated by\n   \n    progress in\n   \n\n    GANs)\n   \n   .\n  \n\n\n\n    Addendum. Racing through the OOMs: It's this decade or bust\n   \n\n\n\n   I used to be more skeptical of short timelines to AGI. One reason is that it seemed unreasonable to privilege this decade, concentrating so much AGI-probability-mass on it (it seemed like a classic fallacy to think \"oh we're so special\"). I thought we should be uncertain about what it takes to get AGI, which should lead to a much more \"smeared-out\" probability distribution over when we might get AGI.\n  \n\n\n   However, I've changed my mind: critically, our uncertainty over what it takes to get AGI should be over\n   \n    OOMs\n   \n   (of effective compute), rather than over years.\n  \n\n\n   We're racing through the OOMs this decade. Even at its bygone heyday, Moore's law was only 1\u20131.5 OOMs/decade. I estimate that we will do ~5 OOMs in 4 years, and over ~10 this decade overall.\n  \n\n\n\n\n\n\n   Figure 22: Rough projections on effective compute scaleup. We've been racing through the OOMs this decade; after the early 2030s, we will face a slow slog.\n  \n\n\n   In essence, we're in the middle of a huge scaleup reaping one-time gains this decade, and progress through the OOMs will be multiples slower thereafter. If this scaleup doesn't get us to AGI in the next 5-10 years, it might be a\n  \n\n\n   long way out.\n  \n\n\n\n\n\n\n\n      Spending scaleup\n     \n     : Spending a million dollars on a model used to be outrageous; by the end of the decade, we will likely have $100B or $1T clusters. Going much higher than that will be hard; that's already basically the feasible limit (both in terms of what big business can afford, and even just as a fraction of GDP). Thereafter all we have is glacial 2%/year trend real GDP growth to increase this.\n    \n\n\n\n      Hardware gains\n     \n     : AI hardware has been improving much more quickly than Moore's law. That's because we've been specializing chips for AI workloads. For example, we've gone from CPUs to GPUs; adapted chips for Transformers; and we've gone down to much lower precision number formats, from fp64/fp32 for traditional supercomputing to fp8 on H100s. These are large gains, but by the end of the decade we'll likely have totallyspecialized AI-specific chips, without much further beyond-Moore's law gains possible.\n    \n\n\n\n      Algorithmic progress\n     \n     : In the coming decade, AI labs will invest tens of billions in algorithmic R&D, and all the smartest people in the world will be working on this; from tiny efficiencies to new paradigms, we'll be picking lots of the low-hanging fruit. We probably won't reach any sort of hard limit (though \"unhobblings\" are likely finite), but at the very least the pace of improvements should slow down, as the rapid growth (in $ and human capital investments) necessarily slows down (e.g., most of the smart STEM talent will already be working on AI). (That said, this is the most uncertain to predict, and the source of most of the uncertainty on the OOMs in the 2030s on the plot above.)\n    \n\n\n\n   Put together, this means we are racing through many more OOMs in the next decade than we might in multiple decades thereafter. Maybe it's enough\u2014and we get AGI soon\u2014or we might be in for a long, slow slog. You and I can reasonably disagree on the\n   \n    median\n   \n   time to AGI,\n  \n\n\n   depending on how hard we think achieving AGI will be but given how we're racing through the OOMs right now, certainly your\n   \n    modal\n   \n   AGI year should sometime later this decade or so.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 23: Matthew Barnett has a nice\n   \n    related visualization\n   \n   of this, considering just compute and biological bounds.\n  \n\n\n\n    II. From AGI to Superintelligence: the Intelligence Explosion\n   \n\n\n\n\n    AI progress won't stop at human-level. Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into 1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power\u2014and the peril\u2014of superintelligence would be dramatic.\n   \n\n\n\n\n\n    Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion,' and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.\n   \n\n\n\n\n\n\n\n     i. j. good (\n     \n      1965\n     \n     )\n    \n\n\n\n\n\n    The Bomb and The Super\n   \n\n\n\n   In the common imagination, the Cold War's terrors principally trace back to Los Alamos, with the invention of the atomic bomb. But The Bomb, alone, is perhaps overrated. Going from The Bomb to The Super\u2014hydrogen bombs\u2014was arguably just as important.\n  \n\n\n   In the Tokyo air raids, hundreds of bombers dropped thousands of tons of conventional bombs on the city. Later that year, Little Boy, dropped on Hiroshima, unleashed similar destructive power in a single device. But just 7 years later, Teller's hydrogen bomb multiplied yields\n   \n    a thousand-fold\n   \n   once again\u2014a single bomb with more explosive power than all of the bombs dropped in the entirety of WWII combined.\n  \n\n\n   The Bomb was a more efficient bombing campaign. The Super was a country-annihilating device.\n   \n    32\n   \n\n    32\n   \n   And much of the Cold War's per-\n  \n\n\n   So it will be with AGI and Superintelligence.\n  \n\n\n   AI progress won't stop at human-level. After initially learning from the best human games, AlphaGo started playing against itself\u2014and it quickly became superhuman, playing extremely creative and complex moves that a human would never have come up with.\n  \n\n\n   We discussed the path to AGI in the previous piece. Once we get AGI, we'll turn the crank one more time\u2014or two or three more times\u2014and AI systems will become superhuman\u2014vastly superhuman. They will become qualitatively smarter than you or I, much smarter, perhaps similar to how you or I are qualitatively smarter than an elementary schooler.\n  \n\n\n   The jump to superintelligence would be wild enough at the current rapid but continuous rate of AI progress (if we could make the jump to AGI in 4 years from GPT-4, what might another 4 or 8 years after that bring?). But it could be much faster than that, if AGI automates AI research itself.\n  \n\n\n   Once we get AGI, we won't just have one AGI. I'll walk through the numbers later, but: given inference GPU fleets by then, we'll likely be able to run\n   \n    many millions of them (perhaps 100 million human-equivalents, and soon after at 10x+ human speed)\n   \n   . Even if they can't yet walk around the office or make coffee, they will be able to do ML research on a computer. Rather than a few hundred researchers and engineers at a leading AI lab, we'd have more than 100,000x that\u2014furiously working on algorithmic breakthroughs, day and night. Yes, recursive self-improvement, but no sci-fi required;\n   \n    they would need only to accelerate the existing trendlines of algorithmic progress (currently at ~0.5 OOMs/year).\n   \n\n\n\n   Automated AI research could probably compress a humandecade of algorithmic progress into less than a year (and that seems conservative). That'd be 5+ OOMs, another GPT-2-to-\n  \n\n\n   versities (cf\n   \n    Daniel Ellsberg's book)\n   \n   stemmed from merely replacing Abombs with H-bombs, without adjusting nuclear policy and war plans to the massive capability increase.\n  \n\n\n\n\n\n\n   GPT-4-sized jump, on top of AGI\u2014a qualitative jump like that from a preschooler to a smart high schooler,\n   \n    on top\n   \n   of AI systems already as smart as expert AI researchers/engineers.\n  \n\n\n   There are several plausible bottlenecks\u2014including limited compute for experiments, complementarities with humans, and algorithmic progress becoming harder\u2014which I'll address, but none seem sufficient to definitively slow things down.\n  \n\n\n   Before we know it, we would have superintelligence on our hands\u2014AI systems\n   \n    vastly\n   \n   smarter than humans, capable of novel, creative, complicated behavior we couldn't even begin to understand\u2014perhaps even a small civilization of billions of them. Their power would be vast, too. Applying superin-\n  \n\n\n   Figure 24: Automated AI research could accelerate algorithmic progress, leading to 5+ OOMs of effective compute gains in a year. The AI systems we'd have by the end of an intelligence explosion would be vastly smarter than humans.\n  \n\n\n   telligence to R&D in other fields, explosive progress would broaden from just ML research; soon they'd solve robotics, make dramatic leaps across other fields of science and technology within years, and an industrial explosion would follow. Superintelligence would likely provide a decisive military advantage, and unfold untold powers of destruction. We will be faced with one of the most intense and volatile moments of human history.\n  \n\n\n\n    Automating AI research\n   \n\n\n\n\n    We don't need to automate everything\u2014just AI research.\n   \n   A common objection to transformative impacts of AGI is that it will be hard for AI to do everything. Look at robotics, for instance, doubters say; that will be a gnarly problem, even if AI is cognitively at the levels of PhDs. Or take automating biology R&D, which might require lots of physical lab-work and human experiments.\n  \n\n\n   But we don't need robotics\u2014we don't need many things\u2014for AI to automate AI research. The jobs of AI researchers and engineers at leading labs can be done fully virtually and don't run into real-world bottlenecks in the same way (though it will still be limited by compute, which I'll address later). And the job of an AI researcher is fairly straightforward, in the grand scheme of things: read ML literature and come up with new questions or ideas, implement experiments to test those ideas, interpret the results, and repeat. This all seems squarely in the domain where simple extrapolations of current AI capabilities could easily take us to or beyond the levels of the best humans by the end of 2027. 33\n  \n\n\n   and their labs' competitive edge. It's worth emphasizing just how straightforward and hacky some of the biggest machine learning breakthroughs of the last decade have been: \"oh, just add some normalization\" (LayerNorm/BatchNorm) or \"do f(x)+x instead of f(x)\" (residual connections)\" or \"fix an implementation bug\" (Kaplan \u2192 Chinchilla scaling laws). AI research can be automated. And automating AI research is all it takes to kick off extraordinary feedback loops.\n   \n    34\n   \n\n\n\n\n    33\n   \n   The job of an AI researcher is also a job that AI researchers at AI labs just, well, know really well\u2014so it'll be particularly intuitive to them to optimize models to be good at that job. And there will be huge incentives to do so to help them accelerate their research\n  \n\n\n\n    34\n   \n   This suggests an important point in terms of the sequencing of risks from AI, by the way. A common AI threat model people point to is AI systems developing novel bioweapons, and that posing catastrophic risk. But if AI research is more straightforward to automate than biology R&D, we might get an intelligence explosion before we get extreme AI biothreats. This matters, for example, with regard to whether we should expect \"bio warning shots\" in time before things get crazy on AI.\n  \n\n\n\n    We'd be able to run millions of copies (and soon at 10x+ human speed) of the automated AI researchers.\n   \n   Even by 2027, we should expect GPU fleets in the 10s of millions. Training clusters alone should be approaching ~3 OOMs larger, already putting us at 10 million+ A100-equivalents. Inference fleets should be much larger still. (More on all this in IIIa. Racing to the Trillion Dollar Cluster.)\n  \n\n\n   That would let us run many millions of copies of our automated AI researchers, perhaps 100 million human-researcherequivalents, running day and night. There's some assumptions that flow into the exact numbers, including that humans \"think\" at 100 tokens/minute (just a rough order of magnitude estimate, e.g. consider your internal monologue) and extrapolating historical trends and Chinchilla scaling laws on pertoken inference costs for frontier models remaining in the same ballpark.\n   \n    35\n   \n   We'd also want to reserve some of the GPUs for running experiments and training new models. Full calculation in a footnote.\n   \n    36\n   \n\n\n\n   Another way of thinking about it is that\n   \n    given inference fleets in 2027, we should be able to generate an entire internet's worth of tokens, every single day.\n   \n\n    37\n   \n   In any case, the exact numbers don't matter that much, beyond a simple plausibility demonstration.\n  \n\n\n\n    35\n   \n   As noted earlier, the GPT-4 API costs less today than GPT-3 when it was released\u2014this suggests that the trend of inference efficiency wins is fast enough to keep inference costs roughly constant even as models get much more powerful. Similarly, there have been huge inference cost wins in just the year since GPT-4 was released; for example,\n   \n    the current version of Gemini\n   \n   1.5 Pro outperforms the original GPT-4, while being roughly 10\n   \n    x cheaper.\n   \n\n\n\n   We can also ground this somewhat more by considering Chinchilla scaling laws. On Chinchilla scaling laws, model size\u2014and thus inference costs\u2014grow with the square root of training cost, i.e. half the OOMs of the OOM scaleup of effective compute. However, in the previous piece, I suggested that algorithmic efficiency was advancing at roughly the same pace as compute scaleup, i.e. it made up roughly half of the OOMs of effective compute scaleup. If these algorithmic wins also translate into inference efficiency, that means that the algorithmic efficiencies would compensate for the naive increase in inference cost.\n  \n\n\n   In practice, training compute efficiencies often, but not always, translate into inference efficiency wins. However, there are also separately many inference efficiency wins that are not training efficiency wins. So, at least in terms of the rough ballpark, assuming the $/token of frontier models stays roughly similar doesn't seem crazy.\n  \n\n\n   (Of course, they'll use more tokens, i.e. more test-time compute. But that's already part of the calculation here, by pricing human-equivalents as 100 tokens/minute.)\n  \n\n\n\n    36\n   \n   GPT4T\n   \n    is about\n   \n   $0.03/1K tokens. We supposed we would have 10s of millions of A100 equivalents, which cost ~$1 hour per GPU if A100-equivalents. If we used the API costs to translate GPUs into tokens generated, that implies 10s of millions GPUs * $1/GPU-hour * 33K tokens/$ = ~ one trillion tokens/ hour. Suppose a human does 100 tokens/min of thinking, that means a human-equivalent is 6,000 tokens/hour. One trillion tokens/hour divided by 6,000 tokens/human-hour = ~200 million human-equivalents i.e. as if running 200 million human researchers, day and night. (And even if we reserve half the GPUs for experiment compute, we get 100 million human-researcher-equivalents.)\n   \n    37\n   \n   The previous footnote estimated ~1T tokens/hour, i.e. 24T tokens a day. In the previous piece, I noted that a\n   \n    public deduplicated CommonCrawl\n   \n\n    had around\n   \n   30T tokens.\n  \n\n\n   Moreover, our automated AI researchers may soon be able to run at much faster than human-speed:\n  \n\n\n\n\n\n\n     By taking some inference penalties, we can trade off running fewer copies in exchange for running them at faster serial speed. (For example, we could go from ~5x human speed to ~100x human speed by \"only\" running 1 million copies of the automated researchers.38)\n    \n\n\n     More importantly, the first algorithmic innovation the automated AI researchers work on is getting a 10x or 100x speedup. Gemini 1.5 Flash is ~10x faster than the originallyreleased GPT-4,\n     \n      39\n     \n     merely a year later, while providing similar performance to the originally-released GPT-4 on reasoning benchmarks. If that's the algorithmic speedup a few hundred human researchers can find in a year, the automated AI researchers will be able to find similar wins very quickly.\n    \n\n\n\n\n    That is: expect 100 million automated researchers each working at 100x human speed not long after we begin to be able to automate AI research.\n   \n   They'll each be able to do a year's worth of work in a few days. The increase in research effort\u2014compared to a few hundred puny human researchers at a leading AI lab today, working at a puny 1x human speed\u2014will be extraordinary.\n  \n\n\n\n    This could easily dramatically accelerate existing trends of algorithmic progress, compressing a decade of advances into a year.\n   \n   We need not postulate anything totally novel for automated AI research to intensely speed up AI progress. Walking through the numbers in the previous piece, we saw that algorithmic progress has been a central driver of deep learning progress in the last decade; we noted a trendline of ~0.5 OOMs/year on algorithmic efficiencies alone, with additional large algorithmic gains from unhobbling on top. (I think the import of algorithmic progress has been underrated by many, and properly appreciating it is important for appreciating the possibility of an intelligence explosion.)\n  \n\n\n   Could our millions of automated AI researchers (soon working at 10x or 100x human speed) compress the algorithmic progress human researchers would have found in a decade into a year\n  \n\n\n\n    38\n   \n   Jacob Steinhardt estimates that k\u02c63 parallel copies of a model can be replaced with a single model that is k\u02c62 faster, given\n   \n    some math on inference\n   \n\n    tradeoffs\n   \n   with a tiling scheme (that theoretically works even for k of 100 or more). Suppose initial speeds were already ~5x human speed (based on, say, GPT-4 speed on release). Then, by taking this inference penalty (with k= ~5), we'd be able to run ~1 million automated AI researchers at ~100x human speed.\n  \n\n\n\n    39\n   \n   This\n   \n    source\n   \n   benchmarks throughput of Flash at ~6x GPT-4 Turbo, and GPT-4 Turbo was faster than original GPT-4. Latency is probably also roughly 10x faster.\n  \n\n\n   instead? That would be 5+ OOMs in a year.\n  \n\n\n   Don't just imagine 100 million junior software engineer interns here (we'll get those earlier, in the next couple years!). Real automated AI researchers be very smart\u2014and in addition to their raw quantitative advantage, automated AI researchers will have other enormous advantages over human researchers:\n  \n\n\n\n\n\n\n     They'll be able to read every single ML paper ever written, have been able to deeply think about every single previous experiment ever run at the lab, learn in parallel from each of their copies, and rapidly accumulate the equivalent of millennia of experience. They'll be able to develop far deeper intuitions about ML than any human.\n    \n\n\n     They'll be easily able to write millions of lines of complex code, keep the entire codebase in context, and spend humandecades (or more) checking and rechecking every line of code for bugs and optimizations. They'll be superbly competent at all parts of the job.\n    \n\n\n     You won't have to individually train up each automated AI researcher (indeed, training and onboarding 100 million new human hires would be difficult). Instead, you can just teach and onboard one of them\u2014and then make replicas. (And you won't have to worry about politicking, cultural acclimation, and so on, and they'll work with peak energy and focus day and night.)\n    \n\n\n     Vast numbers of automated AI researchers will be able to share context (perhaps even accessing each others' latent space and so on), enabling much more efficient collaboration and coordination compared to human researchers.\n    \n\n\n     And of course, however smart our initial automated AI researchers would be, we'd soon be able to make further OOM-jumps, producing even smarter models, even more capable at automated AI research.\n    \n\n\n\n   Imagine an automated Alec Radford\u2014\n   \n    imagine 100 million au-\n   \n\n\n\n\n    tomated Alec Radfords.\n   \n\n    40\n   \n   I think just about every researcher at\n   \n    40\n   \n   Alec Radford is an incredibly gifted OpenAI would agree that if they had 10 Alec Radfords, let alone 100 or 1,000 or 1 million running at 10x or 100x human speed, they could very quickly solve very many of their problems. Even with various other bottlenecks (more in a moment), compressing a decade of algorithmic progress into a year as a result seems very plausible. (A 10x acceleration from a million times more research effort, which seems conservative if anything.)\n  \n\n\n   That would be 5+ OOMs right there. 5 OOMs of algorithmic wins would be a similar scaleup to what produced the GPT-2-to-GPT-4 jump, a capability jump from ~a preschooler to ~a smart high schooler. Imagine such a qualitative jump\n   \n    on top of\n   \n   AGI,\n   \n    on top of\n   \n   Alec Radford.\n  \n\n\n   It's strikingly plausible we'd go from AGI to superintelligence very quickly, perhaps in 1 year.\n  \n\n\n\n    Possible bottlenecks\n   \n\n\n\n   While this basic story is surprisingly strong\u2014and is supported by\n   \n    thorough economic modeling work\u2014\n   \n   there are some real and plausible bottlenecks that will probably slow down an automated-AI-research intelligence explosion.\n  \n\n\n   I'll give a summary here, and then discuss these in more detail in the optional sections below for those interested:\n  \n\n\n   \u2022\n   \n    Limited compute\n   \n   : AI research doesn't just take good ideas, thinking, or math\u2014but running experiments to get empirical signal on your ideas. A million times more research effort via automated research labor won't mean a million times faster progress, because compute will still be limited\u2014and limited compute for experiments will be the bottleneck. Still, even if this won't be a 1,000,000x speedup, I find it hard to imagine that the automated AI researchers couldn't use the compute\n   \n    at least\n   \n   10x more effectively: they'll be able to get incredible ML intuition (having internalized the whole ML literature and every previous experiment every run!) and\n  \n\n\n   and prolific researcher/engineer at OpenAI, behind\n   \n    many of the most\n   \n\n    important advances,\n   \n   though he flies under the radar some.\n  \n\n\n   centuries-equivalent of thinking-time to figure out exactly the right experiment to run, configure it optimally, and get maximum value of information; they'll be able to spend centuries-equivalent of engineer-time before running even tiny experiments to avoid bugs and get them right on the first try; they can make tradeoffs to economize on compute by focusing on the biggest wins; and they'll be able to try tons of smaller-scale experiments (and given effective compute scaleups by then, \"smaller-scale\" means being able to train 100,000 GPT-4-level models in a year to try architecture breakthroughs). Some human researchers and engineers are able to produce 10x the progress as others, even with the same amount of compute\u2014and this should apply even moreso to automated AI researchers. I do think this is the most important bottleneck, and I address it in more depth below.\n  \n\n\n\n\n\n\n\n      Complementarities/long tail:\n     \n     A classic lesson from economics (cf Baumol's growth disease) is that if you can automate, say, 70% of something, you get some gains but quickly the remaining 30% become your bottleneck. For anything that falls short of full automation\u2014say, really good copilots\u2014human AI researchers would remain a major bottleneck, making the overall increase in the rate of algorithmic progress relatively small. Moreover, there's likely some long tail of capabilities required for automating AI research\u2014the last 10% of the job of an AI researcher might be particularly hard to automate. This could soften takeoff some, though my best guess is that this only delays things by a couple years. Perhaps 2026/27-models speed are the proto-automated-researcher, it takes another year or two for some final unhobbling, a somewhat better model, inference speedups, and working out kinks to get to full automation, and finally by 2028 we get the 10x acceleration (and superintelligence by the end of the decade).\n    \n\n\n\n      Inherent limits to algorithmic progress:\n     \n     Maybe another 5 OOMs of algorithmic efficiency will be fundamentally impossible? I doubt it. While there will definitely be upper limits,\n     \n      41\n     \n     if we got 5 OOMs in the last decade, we should\n     \n      41\n     \n\n      25\n     \n     OOMs of algorithmic progress on probably expect at least another decade's-worth of progress\n    \n\n\n\n   top of GPT-4, for example, are clearly impossible: that would imply it would be possible to train a GPT-4-level model with just a handful of FLOP.\n  \n\n\n   to be possible. More directly, current architectures and training algorithms are still very rudimentary, and it seems that much more efficient schemes should be possible. Biological reference classes also support dramatically more efficient algorithms being plausible.\n  \n\n\n\n\n\n\n\n      Ideas get harder to find, so the automated AI researchers will merely sustain, rather than accelerate, the current rate of progress:\n     \n     One objection is that although automated research would increase effective research effort a lot, ideas also get harder to find. That is, while it takes only a few hundred top researchers at a lab to sustain 0.5 OOMs/year today, as we exhaust the low-hanging fruit, it will take more and more effort to sustain that progress\u2014and so the 100 million automated researchers will be merely what's necessary to sustain progress. I think this basic model is correct, but the empirics don't add up: the magnitude of the increase in research effort\u2014a million-fold\u2014is way, way larger than the historical trends of the growth in research effort that's been necessary to sustain progress. In econ modeling terms, it's a bizarre \"knife-edge assumption\" to assume that the increase in research effort from automation will be\n     \n      just enough\n     \n     to keep progress constant.\n    \n\n\n\n      Ideas get harder to find and there are diminishing returns, so the intelligence explosion will quickly fizzle:\n     \n     Related to the above objection, even if the automated AI researchers lead to an initial burst of progress, whether rapid progress can be sustained depends on the shape of the diminishing returns curve to algorithmic progress. Again, my best read of the empirical evidence is that the exponents shake out in favor of explosive/accelerating progress. In any case, the sheer size of the one-time boost\u2014from 100s to 100s of millions of AI researchers\u2014probably overcomes diminishing returns here for at least a good number of OOMs of algorithmic progress, even though it of course can't be\n     \n      indefinitely\n     \n     selfsustaining.\n    \n\n\n\n   Overall, these factors may slow things down somewhat: the most extreme versions of intelligence explosion (say, overnight) seem implausible. And they may result in a somewhat longer\n  \n\n\n   runup (perhaps we need to wait an extra year or two from more sluggish, proto-automated researchers to the true automated Alec Radfords, before things kick off in full force). But they certainly don't rule out a very rapid intelligence explosion. A year\u2014or at most just a few years, but perhaps even just a few months\u2014in which we go from fully-automated AI researchers to vastly superhuman AI systems should be our mainline expectation.\n  \n\n\n\n    If you'd rather skip the in-depth discussions on the various bottlenecks below, click here to skip to the next section.\n   \n\n\n\n\n    Limited compute for experiments (optional, in more depth)\n   \n\n\n\n   The production function for algorithmic progress includes two complementary factors of production: research effort and experiment compute. The millions of automated AI researchers won't have any more compute to run their experiments on than human AI researchers; perhaps they'll just be sitting around waiting for their jobs to finish.\n  \n\n\n   This is probably the most important bottleneck to the intelligence explosion. Ultimately this is a quantitative question\u2014just how much of a bottleneck is it? On balance, I find it hard to believe that the 100 million Alec Radfords couldn't increase the marginal product of experiment compute by at least 10x (and thus, would still accelerate the pace of progress by 10x):\n  \n\n\n   \u2022\n   \n    There's a lot you can do with smaller amounts of compute.\n   \n   The way most AI research works is that you test things out at small scale\u2014and then extrapolate via scaling laws. (Many key historical breakthroughs required only a very small amount of compute, e.g.\n   \n    the original Transformer\n   \n   was trained on just 8 GPUs for a few days.) And note that with ~5 OOMs of baseline scaleup in the next four years, \"small scale\" will mean GPT-4 scale\u2014the automated AI researchers will be able to run 100,000 GPT-4 level experiments on their training cluster in a year, and tens of millions of GPT-3-level experiments. (That's a lot\n  \n\n\n   of potential-breakthrough new architectures they'll be able to test!)\n  \n\n\n\n\n\n\n\n      \u2013\n     \n     A lot of the compute goes into larger-scale validation of the final pretraining run\u2014making sure you are getting a high-enough degree of confidence on marginal efficiency wins for your annual headline product\u2014but if you're racing through the OOMs in the intelligence explosion, you could economize and just focus on the really big wins.\n    \n\n\n\n      \u2013\n     \n     As discussed in the previous piece, there are often\n     \n      enormous\n     \n     gains to be had from relatively low-compute \"unhobbling\" of models. These don't require big pretraining runs. It's highly plausible that that intelligence explosion starts off automated AI research e.g. discovering a way to do RL on top that gives us a couple OOMs via unhobbling wins (and then we're off to the races).\n    \n\n\n\n      \u2013\n     \n\n      As the automated AI researchers find efficiencies, that'll let them run more experiments.\n     \n     Recall the near-1000x cheaper inference in two years for equivalent-MATH performance, and the 10x general inference gains in the last year, discussed in the previous piece, from mere-human algorithmic progress. The first thing the automated AI researchers will do is quickly find similar gains, and in turn, that'll let them run 100x more experiments on e.g. new RL approaches. Or they'll be able to quickly make smaller models with similar performance in relevant domains (cf previous discussion of Gemini Flash, near-100x cheaper than GPT-4), which in turn will let them run many more experiments with these smaller models (again, imagine using these to try different RL schemes). There are probably other overhangs too, e.g. the automated AI researchers might be able to quickly develop much better distributed training schemes to utilize all the inference GPUs (probably at least 10x more compute right there). More generally, every OOM of training efficiency gains they find will give them an OOM\n    \n\n\n\n   more of effective compute to run experiments on.\n  \n\n\n\n\n\n\n\n      The automated AI researchers could be way more efficient.\n     \n     It's hard to understate how many fewer experiments you would have to run if you just got it right on the first try\u2014no gnarly bugs, being more selective about exactly what you are running, and so on. Imagine 1000 automated AI researchers spending a month-equivalent checking your code and getting the exact experiment right before you press go. I've asked some AI lab colleagues about this and they agreed: you should pretty easily be able to save 3x-10x of compute on most projects merely if you could avoid frivolous bugs, get things right on the first try, and only run high value-of-information experiments.\n    \n\n\n\n      The automated AI researchers could have way better intuitions.\n     \n\n\n\n\n\n        \u2013\n       \n       Recently, I was speaking to an intern at a frontier lab; they said that their dominant experience over the past few months was suggesting many experiments they wanted to run, and their supervisor (a senior researcher) saying they could already predict the result beforehand so there was no need. The senior researcher's years of random experiments messing around with models had honed their intuitions about what ideas would work\u2014or not. Similarly, it seems like our AI systems could easily get superhuman intuitions about ML experiments\u2014they will have read the entire machine learning literature, be able to learn from every other experiment result and deeply think about it, they could easily be trained to predict the outcome of millions of ML experiments, and so on. And maybe one of the first things they do is build up a strong basic science of \"predicting if this large scale experiment will be successful just after seeing the first 1% of training, or just after seeing the smaller scale version of this experiment\", and so on.\n      \n\n\n\n\n\n\n        \u2013\n       \n       Moreover, beyond really good intuitions about re-\n      \n\n\n\n\n\n   search directions,\n   \n    as Jason Wei has noted,\n   \n   there are incredible returns to having great intuitions on the dozens of hyperparameters and details of an experiment,. Jason calls this ability to get things right on the first try based on intuition \"yolo runs\". (Jason says, \"what I do know is that the people who can do this are surely 10-100x AI researchers.\")\n  \n\n\n   Compute bottlenecks will mean a million times more researchers won't translate into a million times faster research\u2014thus not an overnight intelligence explosion. But the automated AI researchers will have extraordinary advantages over human researchers, and so it seems hard to imagine that they couldn't also find a way to use the compute at least 10x more efficiently/effectively\u2014and so 10x the pace of algorithmic progress seems eminently plausible.\n  \n\n\n   I'll take a moment here to acknowledge perhaps the most compelling formulation of the counterargument I've heard, by my friend James Bradbury:\n   \n    if more ML research effort would so dramatically accelerate progress, why doesn't the current academic ML research community, numbering at least in the tens of thousands, contribute more to frontier lab progress?\n   \n   (Currently, it seems like lab-internal teams, of perhaps a thousand in total across labs, shoulder most of the load for frontier algorithmic progress.) His argument is that the reason is that algorithmic progress is compute-bottlenecked: the academics just don't have enough compute.\n  \n\n\n   Some responses:\n  \n\n\n\n\n\n\n     Quality-adjusted, I think academics are probably more in the thousands not tens of thousands (e.g., looking only at the top universities). This probably isn't substantially more than the labs combined. (And it's\n     \n      way\n     \n     less than the hundreds of millions of researchers we'd get from automated AI research.)\n    \n\n\n     Academics work on the wrong things. Up until very\n    \n\n\n\n   recently (and perhaps still today?), the vast majority of the academic ML community wasn't even working on large language models. In terms of strong academics in academia working on large language models, it might be meaningfully fewer than researchers at labs combined?\n  \n\n\n\n\n\n\n     Even when the academics do work on things like LLM pretraining, they simply don't have access to the stateof-the-art\u2014the large accumulated body of knowledge of tons of details on frontier model training inside labs. They don't know what problems are actually relevant, or can only contribute one-off results that nobody can really do anything with because their baselines were badly tuned (so nobody knows if their thing is actually an improvement).\n    \n\n\n     Academics are way worse than automated AI researchers: they can't work at 10x or 100x human speed, they can't read and internalize every ML paper ever written, they can't spend a decade checking every line of code, replicate themselves to avoid onboarding-bottlenecks, etc.\n    \n\n\n\n   Another countervailing example to the academics argument: GDM is rumored to have way more experiment compute than OpenAI, and yet it doesn't seem like GDM is massively outpacing OpenAI in terms of algorithmic progress.\n  \n\n\n   In general, I expect automated researchers will have a different style of research that plays to their strengths and aims to mitigate the compute bottleneck.\n   \n    I think it's reasonable to be uncertain how this plays out, but it's unreasonable to be confident it won't be doable for the models to get around the compute bottleneck just because it'd be hard for humans to do so.\n   \n\n\n\n   \u2022 For example, they could just spend a lot of effort early on building up a basic science of \"how to predict large scale results from smaller scale experiments\". And I expect there's a lot that they could do that humans can't do, e.g. maybe things more like \"predicting if this large scale experiment will be successful just after seeing the\n  \n\n\n   first 1% of training\". This seems pretty doable if you're a super strong automated researcher with very superhuman intuitions and this can save you a ton of compute.\n  \n\n\n   \u2022 When I imagine AI systems automating AI research, I see them as compute-bottlenecked but making up for it in large part by thinking e.g. 1000x more (and faster) than humans would, and thinking at a higher level of quality than humans (e.g. because of the superhuman ML intuitions from being trained to predict the result of millions of experiments). Unless they're just much worse at thinking than engineering, I think this can make up for a lot, and this would be qualitatively different from academics.\n  \n\n\n   (In addition to experiment compute, there's the additional bottleneck of eventually needing to run a big training run, something which currently takes months. But you can probably economize on those, doing only a handful during the year of intelligence explosion, taking bigger OOM leaps for each than labs currently do.\n   \n    42\n   \n   Or you could \"spend\" 1 out of the 5 OOMs of compute efficiency wins to do a training run in days rather than months.)\n  \n\n\n\n    Complementarities and long tails to 100% automation (optional, in more depth)\n   \n\n\n\n   The classic economist objection to AI automation speeding up economic growth is that different tasks are complementary: so, for example, automating 80% of what labor humans did in 1800 didn't lead to a growth explosion or mass unemployment, but the remaining 20% became what all humans did and remained the bottleneck. (See e.g. a model of this\n   \n    here.\n   \n   ).\n  \n\n\n   I think the economists'\n   \n    model\n   \n   here is correct. But a key point is that I'm only talking about one currently-small part of the economy, rather than the economy as a whole. People may well still be getting haircuts normally during this time\u2014robotics might not yet be worked out, AIs for every domain might not yet be worked out, the societal\n  \n\n\n\n    42\n   \n   Note that while I think this is likely, it's kind of scary: it means that rather than a fairly continuous series of big models, each somewhat better than the previous generation, downstream model intelligence might be more discrete/discontinuous. We might only do one or a couple of big runs during the intelligence explosion, banking multiple OOMs of algorithmic breakthroughs found at smaller scale for each.\n  \n\n\n   rollout might not yet be worked out, etc.\u2014but they\n   \n    will\n   \n   be able to do AI research. As discussed in the previous piece, I think the current course of AI progress is taking us to essentially drop-in remote workers as intelligent as the smartest humans; as discussed in this piece, the job of an AI researcher seems totally within the scope of what could be fully automated.\n  \n\n\n   Still, in practice, I do expect somewhat of a long tail to get to truly 100% automation even for the job of an AI researcher/engineer; for example, we might first get systems that function\n   \n    almost\n   \n   as an engineer replacement, but still need some amount of human supervision.\n  \n\n\n   In particular, I expect the level of AI capabilities to be somewhat uneven and peaky across domains: it might be a better coder than the best engineers while still having blindspots in some subset of tasks or skills; by the time it's human-level at whatever its worst at, it'll already be substantially superhuman at easier domains to train, like coding. (This is part of why I think they'll be able to use the compute more effectively than human researchers. By the time of 100% automation/the intelligence explosion starting, they'll already have huge advantages over humans in some domains. This will also have important implications for superalignment down the line, since it means that we'll have to align systems that are meaningfully superhuman in many domains in order to align even the first automated AI researchers.)\n  \n\n\n   But I wouldn't expect that phase to last more than a few years; given the pace of AI progress, I think it would likely just be a matter of some additional \"unhobbling\" (removing some obvious limitation of the models that prevented it from doing the last mile) or another generation of models to get all the way.\n  \n\n\n   Overall, this might soften takeoff some. Rather that 2027 AGI \u2192 2028 Superintelligence, it might look more like:\n  \n\n\n   \u2022 2026/27: Proto-automated-engineer, but blind spots in\n  \n\n\n   other areas. Speeds up work by 1.5x-2x already; progress begins gradually accelerating.\n  \n\n\n\n\n\n\n     2027/28: Proto-automated-researchers, can automate >90%. Some remaining human bottlenecks, and hiccups in coordinating a giant organization of automated researchers to be worked out, but this already speeds up progress by 3x+. This quickly does the remaining necessary \"unhobbling\" takes us the remainder of the way to 100% automation.\n    \n\n\n     2028/29: 10x+ pace of progress \u2192 superintelligence.\n    \n\n\n\n   That's still very fast. . .\n  \n\n\n\n    Fundamental limits to algorithmic progress (optional, in more depth)\n   \n\n\n\n   There's probably a real cap on how much algorithmic progress is physically possible. (For example, 25 OOMs of algorithm progress seems impossible, since that would imply being able to train a GPT-4 level system in less than ~10 FLOPs.43) But something like 5 OOMs seems very\n   \n    43\n   \n   Though you could get results that with current architecture! much in the realm of possibilities; again, that would just require another decade of trend algorithmic efficiencies (not even counting algorithmic gains from unhobbling).\n  \n\n\n   Intuitively, it very much doesn't seem like we have exhausted all the low-hanging fruit yet, given how simple the biggest breakthroughs are\u2014and how rudimentary and obviously hobbled current architectures and training techniques still seem to be. For example, I think it's pretty plausible that we'll bootstrap our way to AGI via AI systems that \"think out loud\" via chain-of-thought. But\n   \n    surely\n   \n   this isn't the most efficient way to do it,\n   \n    surely\n   \n   something that does this reasoning via internal states/recurrence/etc would be way more efficient. Or consider adaptive compute: Llama 3 still spends as much compute on predicting the \"and\" token as it does the answer to some complicated question, which seems clearly suboptimal. We're getting huge OOM algorithmic gains from even just small tweaks, while there are dozens of areas where much more effi-\n  \n\n\n   would take 25 more OOMs of hardware\n  \n\n\n   cient architectures and training procedures could likely be found.\n  \n\n\n   Biological references also suggest huge headroom. The human range of intelligence is very wide, for example, with only tiny tweaks to architecture. Humans have similar numbers of neurons as other animals, even though humans are much smarter than those animals. And current AI models are still many OOMs from the\n   \n    efficiency of\n   \n\n    a human brain;\n   \n   they can learn with a tiny fraction of the data (and thus tiny fraction of \"compute\") than AI models can, suggesting huge headroom for our algorithms and architecture.\n  \n\n\n\n    Ideas get harder to find and diminishing returns (optional, in more depth)\n   \n\n\n\n   As you pick the low-hanging fruit, ideas get harder to find. This is true in\n   \n    any domain of technological progress.\n   \n   Essentially, we see a straight line on a log-log curve: log(progress) is a function of log(cumulative research effort). Every OOM of further progress requires putting in more research effort than the last OOM.\n  \n\n\n   This leads to two objections to the intelligence explosion:\n  \n\n\n\n\n\n\n     1. Automated AI research will merely be what's necessary to sustain progress (rather than dramatically accelerating it).\n    \n\n\n     2. A purely-algorithmic intelligence explosion would not be sustained / would quickly fizzle out as algorithmic progress gets harder to find / you hit diminishing marginal returns.\n    \n\n\n\n   I spent a lot of time thinking about these sorts of models in a past life, when I was doing research in economics. (In particular,\n   \n    semi-endogenous growth theory\n   \n   is the standard model of technological progress, capturing these two competing dynamics of growing research effort and ideas getting harder to find.)\n  \n\n\n   In short, I think the underlying model behind these objections is sound, but how it shakes out is an empirical question\u2014and I think they get the empirics wrong.\n  \n\n\n   The key question is essentially: for every 10x of progress, does further progress become\n   \n    more\n   \n   or\n   \n    less\n   \n   than 10x harder? Napkin math (along the lines of how this is done in\n   \n    the\n   \n\n    economic literature)\n   \n   helps us bound this.\n  \n\n\n\n\n\n\n     Suppose we take the ~0.5 OOMs/year trend rate of algorithmic progress seriously; that implies a 100x of progress in 4 years.\n    \n\n\n     However, quality-adjusted headcount / research effort at a given leading AI lab has definitely grown by <100x in 4 years.\n     \n      Maybe\n     \n     it's increased 10x (from 10s to 100s of people working on relevant stuff at a given lab), but even that is unclear quality-adjusted.\n    \n\n\n     And yet, algorithmic progress seems to be sustained.\n    \n\n\n\n   Thus, in response to objection 1, we can note that the ~million-fold increase in research effort will simply be a much larger increase than what would merely be necessary to sustain progress. Maybe we'd need on the order of thousands of researchers working on relevant research at a lab in 4 years to sustain progress; the 100 million Alec Radfords would still be an\n   \n    enormous\n   \n   increase, and surely lead to massive acceleration. It's just a bizarre \"knife-edge\" assumption to think that automated research would be\n   \n    just enough\n   \n   to sustain the existing pace of progress. (And that's not even counting thinking at 10x human speed and all the other advantages the AI systems will have over human researchers.)\n  \n\n\n   In response to objection 2, we can note two things:\n  \n\n\n   \u2022 First, the mathematical condition noted above. Given that, based on our napkin math, quality-adjusted research effort needed to grow \u00ab100x while we did 100x of algorithmic progress, it pretty strongly seems that the\n  \n\n\n   shape of the returns curve shakes out in favor of selfsustaining progress.\n   \n    44\n   \n\n    44\n   \n\n    100\n   \n   x progress\n   \n    \u2192\n   \n\n    100\n   \n   x more auto-\n  \n\n\n   \u2022 Secondly, the returns curve doesn't even\n   \n    need\n   \n   to shake out in favor of a fully sustained chain reaction for us to get a bounded-but-many-OOM surge of algorithmic progress. Essentially, it doesn't need to be a \"growth effect\"; a large enough \"level effect\" would be enough. That is, a million-fold increase in research effort (combined with the many other advantages automated researchers would have over human researchers) would be such a large one-time boost that even if the chain reaction isn't fully self-sustaining, it could lead to a very sizeable (many OOMs) one-time gain.\n   \n    45\n   \n\n    45\n   \n   Analogously, in semi-endogenous\n  \n\n\n   On net, while obviously it won't be unbounded and I have a lot of uncertainty over just how far it'll go, I think something like a 5 OOM intelligence explosion purely from algorithmic gains / automated AI research seems highly plausible.\n  \n\n\n\n    Tom Davidson and Carl Shulman\n   \n   have also looked at the empirics of this in a growth-modeling framework and come to similar conclusions.\n   \n    Epoch AI has also done some\n   \n\n    recent work\n   \n   on the empirics, also coming to the conclusion that empirical returns to algorithmic R&D favors explosive growth, with a\n   \n    helpful writeup of the implications.\n   \n\n\n\n\n    The power of superintelligence\n   \n\n\n\n   Whether or not you agree with the strongest form of these arguments\u2014whether we get a <1 year intelligence explosion, or it takes a few years\u2014it is clear: we must confront the possibility of superintelligence.\n  \n\n\n   The AI systems we'll likely have\n   \n    by the end of this decade\n   \n   will be unimaginably powerful.\n  \n\n\n   \u2022 Of course, they'll be\n   \n    quantitatively\n   \n   superhuman. On our fleets\n  \n\n\n   mated research effort, but you, say, only needed 10x more research effort to keep it going and do the next 100x, so the returns are good enough for explosive progress to be sustained.\n  \n\n\n   economic growth theory, boosting science investment from 1% to 20% of GDP won't make growth rates higher forever\u2014eventually diminishing returns would lead things to return to the old growth rate\u2014but the \"level effect\" it would lead to would be so large as to dramatically speed up growth for decades.\n  \n\n\n   of 100s of millions of GPUs by the end of the decade, we'll be able to run a civilization of billions of them, and they will be able to \"think\" orders of magnitude faster than humans. They'll be able to quickly master any domain, write trillions of lines of code, read every research paper in every scientific field ever written (they'll be perfectly interdisciplinary!) and write new ones before you've gotten past the abstract of one, learn from the parallel experience of every one of its of copies, gain billions of human-equivalent years of experience with some new innovation in a matter of weeks, work 100% of the time with peak energy and focus and won't be slowed down by that one teammate who is lagging, and so on.\n  \n\n\n   \u2022 More importantly\u2014but harder to imagine\u2014they'll be\n   \n    qualitatively\n   \n   superhuman. As a narrow example of this, large-scale RL runs have been able to produce completely novel and creative behaviors beyond human understanding, such as the famous move 37\n   \n    in AlphaGo vs. Lee Sedol.\n   \n   Superintelligence will be like this across many domains. It'll find exploits in human code too subtle for any human to notice, and it'll generate code too complicated for any human to understand even if the model spent decades trying to explain it. Extremely difficult scientific and technological problems that a human would be stuck on for decades will seem just\n   \n    so obvious\n   \n   to them. We'll be like high-schoolers stuck on Newtonian physics while it's off exploring quantum mechanics.\n  \n\n\n   As an example of how\n   \n    wild\n   \n   this could be, look at some Youtube videos of video game speedruns, such as this one of\n   \n    beating\n   \n\n    Minecraft in\n   \n   20 seconds. (If you have no idea what's going on in this video, you're in good company; even most normal players of Minecraft have almost no clue what's going on.)\n  \n\n\n   Now imagine this applied to all domains of science, technology, and the economy. The error bars here, of course, are extremely large. Still,\n   \n    this is happening,\n   \n   and it's important to consider just how consequential this would be.\n  \n\n\n\n\n\n\n\n\n\n\n   In the intelligence explosion, explosive progress was initially only in the narrow domain of automated AI research. As we get superintelligence, and apply our billions of (now superintelligent) agents to R&D across many fields, I expect explosive progress to broaden:\n  \n\n\n\n\n\n\n\n      An AI capabilities explosion.\n     \n     Perhaps our initial AGIs had limitations that prevented them fully automating work in some other domains (rather than just in the AI research domain); automated AI research will quickly solve these, enabling automation of any and all cognitive work.\n    \n\n\n\n      Solve robotics.\n     \n     Superintelligence won't stay purely cognitive for long. Getting robotics to work well is primarily an ML algorithms problem (rather than a hardware problem), and our automated AI researchers will likely be able to solve it (more below!). Factories would go from human-run, to AIdirected using human physical labor, to soon being fully run by swarms of robots.\n    \n\n\n\n      Dramatically accelerate scientific and technological progress.\n     \n     Yes, Einstein alone couldn't develop neuroscience and build a semiconductor industry, but a billion superintelligent automated scientists, engineers, technologists, and robot\n    \n\n\n\n   technicians (with the robots moving at 10x or more human speed!)\n   \n    46\n   \n   would make extraordinary advances in many fields\n   \n    46\n   \n   The\n   \n    10\n   \n   x speed robots doing physical in the space of years. (Here's a nice\n   \n    short story\n   \n   visualizing what AI-driven R&D might look like.) The billion superintelligences would be able to compress the R&D effort humans researchers would have done in the next century into years. Imagine if the technological progress of the 20th century were compressed into less than a decade. We would have gone from flying being thought a mirage, to airplanes, to a man on the moon and ICBMs in a matter of years.\n   \n    This is what I expect the 2030s to look like across science and technology.\n   \n\n\n\n   \u2022\n   \n    An industrial and economic explosion.\n   \n   Extremely accelerated technological progress, combined with the ability to automate all human labor, could dramatically accelerate economic growth (think: self-replicating robot factories quickly covering all of the Nevada desert47). The increase in growth\n   \n    47\n   \n   Why isn't \"factorio-world\"\u2014build probably wouldn't just be from 2%/year to 2.5%/year; rather, this would be a fundamental shift in the growth regime, more comparable to the historical step-change from very slow growth to a couple percent a year with the industrial revolution. We could see economic growth rates of 30%/year and beyond, quite possibly multiple doublings a year. This follows fairly straightforwardly from economists'\n   \n    models\n   \n   of\n   \n    economic\n   \n\n    growth.\n   \n   To be sure, this may well be delayed by societal frictions; arcane regulation might ensure lawyers and doctors still need to be human, even if AI systems were much better at those jobs; surely sand will be thrown into the gears of rapidly expanding robo-factories as society resists the pace of change; and perhaps we'll want to retain human nannies; all of which would slow the growth of the overall GDP statistics. Still, in whatever domains we remove human-created barriers (e.g., competition might force us to do so for military production), we'd see an industrial explosion.\n  \n\n\n   R&D in the real world is the \"slow version\"; in reality the superintelligences will try to do as much R&D as possible in simulation, like\n   \n    AlphaFold\n   \n   or manufacturing\n   \n    \"digital\n   \n\n    twins\"\n   \n   .\n  \n\n\n   a factory, that produces more factories, producing even more factories, doubling factories until eventually your entire planet is quickly covered in factories\u2014possible today? Well, labor is constrained\u2014you can accumulate capital (factories, tools, etc.), but that runs into diminishing returns because it's constrained by a fixed labor force. With robots and AI systems being able to fully automate labor, that removes that constraint; robo-factories could produce more robo-factories in an ~unconstrained way, leading to an industrial explosion. See more economic growth models of this\n   \n    here.\n   \n\n\n\n\n\n\n      Growth mode\n     \n\n      Date began to\n      \n      dominate\n     \n\n      Doubling time of\n      \n      global economy\n      \n      (years)\n     \n\n\n\n      Hunting\n     \n\n      2,000,000\n      \n      B.C.\n     \n\n      230,000\n     \n\n\n\n      Farming\n     \n\n      4700\n      \n      B.C.\n     \n\n      860\n     \n\n\n\n      Science/commerce\n     \n\n      1730\n      \n      A.D.\n     \n\n      58\n     \n\n\n\n      Industry\n     \n\n      1903\n      \n      A.D.\n     \n\n      15\n     \n\n\n\n      Superintelligence?\n     \n\n      2030\n      \n      A.D.?\n     \n\n      ???\n     \n\n\n\n\n\n   Table 3: A shift in the growth regime is not unprecedented: as civilization went from hunting, to farming, to the blossoming of science and commerce, to industry, the pace of global economic growth accelerated. Superintelligence could kick off another shift in growth mode. Based on Robin Hanson's\n   \n    \"Long-run growth as a sequence of\n   \n\n    exponential modes\"\n   \n   .\n  \n\n\n\n\n\n\n\n      Provide a decisive and overwhelming military advantage.\n     \n     Even early cognitive superintelligence might be enough here; perhaps some superhuman hacking scheme can deactivate adversary militaries. In any case, military power and technological progress has been tightly linked historically, and with extraordinarily rapid technological progress will come concomitant military revolutions. The drone swarms and roboarmies will be a big deal, but they are just the beginning; we should expect completely new kinds of weapons, from novel WMDs to invulnerable laser-based missile defense to things we can't yet fathom. Compared to pre-superintelligence arsenals, it'll be like 21st century militaries fighting a 19th century brigade of horses and bayonets. (I discuss how superintelligence could lead to a decisive military advantage in a later piece.)\n    \n\n\n\n      Be able to overthrow the US government.\n     \n     Whoever controls superintelligence will quite possibly have enough power to seize control from pre-superintelligence forces. Even without robots, the small civilization of superintelligences would be able to hack any undefended military, election, television, etc. system, cunningly persuade generals and electorates, economically outcompete nation-states, design new synthetic bioweapons and then pay a human in bitcoin to synthesize it, and so on. In the\n     \n      early\n     \n     1500s, Cortes and about 500 Spaniards conquered the Aztec empire of several million; Pizarro and ~300 Spaniards conquered the Inca empire of several million; Alfonso and ~1000 Portuguese conquered the Indian Ocean. They didn't have god-like power, but the Old World's technological edge and an advantage in strate-\n    \n\n\n\n   gic and diplomatic cunning led to an utterly decisive advantage. Superintelligence might look similar.\n  \n\n\n\n\n\n\n\n    Robots.\n   \n   A common objection to claims like those here is that, even if AI can do cognitive tasks, robotics is lagging way behind and so will be a brake on any real-world impacts.\n  \n\n\n   I used to be sympathetic to this, but I've become convinced robots will not be a barrier. For years people claimed robots were a hardware problem\u2014but robot hardware is well on its way to being solved.\n  \n\n\n   Increasingly, it's clear that robots are an\n   \n    ML algorithms\n   \n   problem. LLMs had a much easier way to bootstrap: you had an entire internet to pretrain on. There's no similarly large dataset for robot actions, and so it requires more nifty approaches (e.g. using multimodal models as a base, then using synthetic data/simulation/clever RL) to train them.\n  \n\n\n   Figure 26: Explosive growth starts in the narrower domain of AI R&D; as we apply superintelligence to R&D in other fields, explosive growth will broaden.\n  \n\n\n   There's a ton of energy directed at solving this now. But even if we don't solve it before AGI, our hundreds of millions of AGIs/superintelligences will make\n   \n    amazing\n   \n   AI researchers (as is the central argument of this piece!), and it seems very likely that they'll figure out the ML to make amazing robots work.\n  \n\n\n   As such, while it's plausible that robots might cause a few years of delay (solving the ML problems, testing in the physical world in a way that is fundamentally slower than testing in simulation, ramping up initial robot production before the robots can build factories themselves, etc.)\u2014I don't think it'll be more than that.\n  \n\n\n   How all of this plays out over the 2030s is hard to predict (and a story for another time). But one thing, at least, is clear: we will be rapidly plunged into the most extreme situation humanity has ever faced.\n  \n\n\n   Human-level AI systems, AGI, would be highly consequential in their own right\u2014but in some sense, they would simply be a more efficient version of what we already know. But, very plausibly, within just a year, we would transition to much more alien systems, systems whose understanding and abilities whose raw power\u2014would exceed those even of humanity combined. There is a real possibility that we will lose control, as we are forced to hand off trust to AI systems during this rapid transition.\n  \n\n\n   More generally, everything will just start happening\n   \n    incredibly fast\n   \n   . And the world will start going insane. Suppose we had gone through the geopolitical fever-pitches and man-made perils of the 20th century in mere years; that is the sort of situation we should expect post-superintelligence. By the end of it, superintelligent AI systems will be running our military and economy. During all of this insanity, we'd have extremely scarce time to make the right decisions. The challenges will be immense. It will take everything we've got to make it through in one piece.\n  \n\n\n\n    The intelligence explosion and the immediate post-superintelligence period will be one of the most volatile, tense, dangerous, and wildest periods ever in human history.\n   \n\n\n\n   And by the end of the decade, we'll likely be in the midst of it.\n  \n\n\n   Confronting the possibility of an intelligence explosion the emergence of superintelligence\u2014often echoes the\n   \n    early\n   \n\n    debates\n   \n   around the possibility of a nuclear chain reaction and the atomic bomb it would enable. HG Wells predicted the atomic bomb in a 1914 novel. When Szilard first conceived of the idea of a chain reaction in 1933, he couldn't convince anyone of it; it was pure theory. Once fission was empirically discovered in 1938, Szilard freaked out again and argued strongly for secrecy, and a few people started to wake up to the possibility of a bomb. Einstein hadn't considered the possibility of a chain reaction, but when Szilard confronted him, he was quick to see the implications and willing to do anything that was needed to be done; he was willing to sound the alarm, and wasn't afraid of sounding foolish. But Fermi, Bohr, and most scientists thought the \"conservative\" thing was to play it down, rather than take seriously the extraordinary implications of the possibility of a bomb. Secrecy (to avoid sharing their advances with the Germans) and other all-out efforts seemed absurd to them. A chain reaction sounded too crazy. (Even when, as it turned out, a bomb was but half a decade from becoming reality.)\n  \n\n\n   We must once again confront the possibility of a chain reaction. Perhaps it sounds speculative to you. But among senior scientists at AI labs, many see a rapid intelligence explosion as strikingly plausible. They can\n   \n    see\n   \n   it. Superintelligence is possible.\n  \n\n\n\n    III. The Challenges\n   \n\n\n\n\n    IIIa. Racing to the Trillion-Dollar Cluster\n   \n\n\n\n\n    The most extraordinary techno-capital acceleration has been set in motion. As AI revenue grows rapidly, many trillions of dollars will go into GPU, datacenter, and power buildout before the end of the decade. The industrial mobilization, including growing US electricity production by 10s of percent, will be intense.\n   \n\n\n\n\n\n    You see, I told you it couldn't be done without turning the whole country into a factory. You have done just that.\n   \n\n\n\n\n\n\n\n     niels bohr (to Edward Teller, upon learning of the scale of the Manhattan Project in\n     \n      1944\n     \n     )\n    \n\n\n\n\n   The race to AGI won't just play out in code and behind laptops\u2014it'll be a race to mobilize America's industrial might. Unlike anything else we've recently seen come out of Silicon Valley, AI is a massive industrial process: each new model requires a giant new cluster, soon giant new power plants, and eventually giant new chip fabs. The investments involved are staggering. But behind the scenes, they are already in motion.\n  \n\n\n   In this chapter, I'll walk you through numbers to give you a sense of what this will mean:\n  \n\n\n   \u2022 As revenue from AI products grows rapidly\u2014plausibly hitting a $100B annual run rate for companies like Google or Microsoft by ~2026, with powerful but pre-AGI systems\u2014\n  \n\n\n\n\n\n\n   that will motivate ever-greater capital mobilization, and total AI investment could be north of $1T\n   \n    annually\n   \n   by 2027.\n  \n\n\n\n\n\n\n     We're on the path to individual training clusters costing $100s of billions by 2028\u2014clusters requiring power equivalent to a small/medium US state and more expensive than the International Space Station.\n    \n\n\n     By the end of the decade, we are headed to $1T+ individual training clusters, requiring power equivalent to >20% of US electricity production. Trillions of dollars of capex will churn out 100s of millions of GPUs per year overall.\n    \n\n\n\n   Nvidia shocked the world as its datacenter sales exploded from about $14\n   \n    B annualized\n   \n   to about $90\n   \n    B annualized\n   \n   in the last year. But that's still just the very beginning.\n  \n\n\n   Figure 27: The trillion-dollar cluster. Credit: DALLE.\n  \n\n\n\n    Training compute\n   \n\n\n\n   Earlier, we found a roughly ~0.5 OOMs48/year trend growth of\n   \n    48\n   \n   As mentioned earlier, OOM = ormagnitude AI training compute. If this trend were to continue for the rest of the decade, what would that mean for the largest training clusters?\n  \n\n\n   der of magnitude, 10x = 1 order of\n  \n\n\n\n\n\n      Year\n     \n\n      OOMs\n     \n\n      H100s\n      \n      equivalent\n     \n\n      Cost\n     \n\n      Power\n     \n\n      Power reference class\n     \n\n\n\n      2022\n     \n\n      ~GPT-4\n      \n      cluster\n     \n\n      ~10k\n     \n\n      ~$500M\n     \n\n      ~10\n      \n      MW\n     \n\n      ~10,000\n      \n      average homes\n     \n\n\n\n      ~2024\n     \n\n      +1\n      \n      OOM\n     \n\n      ~100k\n     \n\n      $billions\n     \n\n      ~100MW\n     \n\n      ~100,000\n      \n      homes\n     \n\n\n\n      ~2026\n     \n\n      +2\n      \n      OOMs\n     \n\n      ~1M\n     \n\n      $10s of bil\n      \n      lions\n     \n\n      ~1\n      \n      GW\n     \n\n      The Hoover Dam, or a\n      \n      large nuclear reactor\n     \n\n\n\n      ~2028\n     \n\n      +3\n      \n      OOMs\n     \n\n      ~10M\n     \n\n      $100s of\n      \n      billions\n     \n\n      ~10\n      \n      GW\n     \n\n      A small/medium US\n      \n      state\n     \n\n\n\n      ~2030\n     \n\n      +4\n      \n      OOMs\n     \n\n      ~100M\n     \n\n      $1T+\n     \n\n      ~100GW\n     \n\n      >20% of US electricity\n      \n      production\n     \n\n\n\n\n\n   This may seem hard to believe\u2014but it appears to be happening. Zuck\n   \n    bought\n   \n   350k H100s. Amazon bought a 1\n   \n    GW data\n   \n\n    center campus\n   \n   next to a nuclear power plant. Rumors\n   \n    suggest\n   \n   a 1GW, 1.4M H100-equivalent cluster (~2026-cluster) is being built in Kuwait. Media report that\n   \n    Microsoft and OpenAI are\n   \n\n    rumored to be working on a $\n   \n   100B cluster, slated for 2028 (a cost comparable to the\n   \n    International Space Station!\n   \n   ). And as each generation of models shocks the world, further acceleration may yet be in store.\n  \n\n\n   Perhaps the wildest part is that willingness-to-spend doesn't even seem to be the binding constraint at the moment, at least for training clusters. It's finding the infrastructure itself: \"Where do I find 10GW?\" (power for the $100B+, trend 2028 cluster) is a favorite topic of conversation in SF. What any compute guy is thinking about is securing power, land, permitting, and datacenter construction.\n   \n    49\n   \n   While it may take you a year\n   \n    49\n   \n   One key uncertainty is how disof waiting to get the GPUs, the lead times for these are much longer still.\n  \n\n\n   Table 4: Scaling the largest training clusters, rough back-of-the-envelope calculations. For details on the calculations, see Appendix.\n  \n\n\n   tributed training will be\u2014if instead of needing that amount of power in one location, we could spread it among 100 locations, it'd be a lot easier.\n  \n\n\n   The trillion-dollar cluster\u2014+4 OOMs from the GPT-4 cluster, the ~2030 training cluster on the current trend\u2014will be a truly extraordinary effort. The 100GW of power it'll require is equivalent to >20% of US electricity production; imagine not just a simple warehouse with GPUs, but hundreds of power plants. Perhaps it will take a national consortium.\n  \n\n\n   (Note that I think it's pretty likely we'll only need a ~$100B cluster, or less, for AGI. The $1T cluster might be what we'll train and run superintelligence on, or what we'll use for AGI if AGI is harder than expected. In any case, in a post-AGI world, having the most compute will probably still really matter.)\n  \n\n\n\n    Overall compute\n   \n\n\n\n   The above are just rough numbers for the largest training clusters. Overall investment is likely to be much larger still: a large fraction of GPUs will probably be be used for inference\n   \n    50\n   \n\n    50\n   \n   See, for example, Zuck\n   \n    here;\n   \n   only (GPUs to actually run the AI systems for products), and there could be multiple players with giant clusters in the race.\n  \n\n\n   My rough estimate is that 2024 will already feature $100B- $200B of AI investment:\n  \n\n\n\n\n\n\n     Nvidia datacenter revenue will hit a ~$25B/quarter run rate soon, i.e. ~$100B of capex flowing via Nvidia alone. But of course, Nvidia isn't the only player (Google's TPUs are great too!), and close to half of datacenter capex is on things other than the chips (site, building, cooling, power, etc.).\n     \n      51\n     \n\n      51\n     \n     For example, this\n     \n      total-cost-of-\n     \n\n\n\n     Big tech has been dramatically ramping their capex numbers: Microsoft and Google will likely do $50B+52, AWS and Meta $40B+, in capex this year. Not all of this is AI, but combined their capex will have grown $50B-$100B year-over-year because of the AI boom, and even then they are still cutting back on other capex to shift even more spending to AI. Moreover, other cloud providers, companies (e.g.,\n     \n      Tesla is\n     \n\n      spending $\n     \n     10B on AI this year), and nation-states are investing in AI as well.\n    \n\n\n\n   ~45k of his H100s are in his largest training clusters, the vast majority of his 350k H100s for inference. Meta likely has heavier inference needs than other players, who serve fewer customers so far, but as everyone else's AI products scale, I expect inference to become a strong majority of the GPUs.\n  \n\n\n\n    ownership analysis\n   \n   estimates that around 40% of a large cluster cost is the H100 GPUs itself, and another 13% goes to Nvidia for Infiniband networking. That said, excluding cost of capital in that calculation would mean the GPUs are about 50% of the cost, and with networking Nvidia gets a bit over 60% of the cost of the cluster.\n  \n\n\n\n    52\n   \n   And\n   \n    apparently,\n   \n   despite Microsoft growing capex by 79% compared to a year ago in a recent quarter, their AI cloud demand still exceeds supply!\n  \n\n\n\n\n\n\n\n\n\n\n   Figure 28: Quarterly Nvidia datacenter revenue. Plot by\n   \n    Thomas Woodside\n   \n\n\n\n   Figure 29: Big tech capex is growing extremely rapidly since ChatGPT unleashed the AI boom.\n   \n    Source.\n   \n\n\n\n   Let's play this forward. My best guess is overall compute investments will grow more slowly than the 3x/year largest training clusters, let's say 2x/year.\n   \n    53\n   \n\n    53\n   \n   A larger fraction of global GPU\n  \n\n\n   And these aren't just my idiosyncratic numbers.\n   \n    AMD fore\n   \n\n    casted\n   \n   a $400B AI accelerator market by 2027, implying $700B+ of total AI spending, pretty close to my numbers (and they are surely much less \"AGI-pilled\" than I am). Sam Altman is re-\n  \n\n\n   production will probably be going to the largest training cluster in the future than today, e.g. because of a consolidation to just a few leading labs, rather than many companies having frontier-model-scale clusters. Regarding power: Of course, not all of this will be in the US, but to give a reference class.\n  \n\n\n\n\n\n      Year\n     \n\n      Annual in\n      \n      vestment\n     \n\n      AI accelerator\n      \n      shipments (in\n      \n      H100s-equivalent)\n     \n\n      Power as % of US\n      \n      electricity produc\n      \n      tion\n     \n\n      Chips as % of current\n      \n      leading-edge TSMC\n      \n      wafer production\n     \n\n\n\n      2024\n     \n\n      ~$150B\n     \n\n      ~5-10M\n     \n\n      1-2%\n     \n\n      5-10%\n     \n\n\n\n      ~2026\n     \n\n      ~$500B\n     \n\n      ~10s of millions\n     \n\n      5%\n     \n\n      ~25%\n     \n\n\n\n      ~2028\n     \n\n      ~$2T\n     \n\n      ~100M\n     \n\n      20%\n     \n\n      ~100%\n     \n\n\n\n      ~2030\n     \n\n      ~$8T\n     \n\n      ~100s of millions\n     \n\n      100%\n     \n\n      4x current capacity\n     \n\n\n\n\n\n   ported to be in talks to raise funds for a project of\n   \n    \"up to $\n   \n   7T\" in capex to build out AI compute capacity (the number was widely mocked, but it seems less crazy if you run the numbers here. . . ). One way or another, this massive scaleup is happening.\n  \n\n\n\n    Will it be done? Can it be done?\n   \n\n\n\n   The scale of investment postulated here may seem fantastical. But both the demand-side and the supply-side seem like they could support the above trajectory. The economic returns justify the investment, the scale of expenditures is not unprecedented for a new general-purpose technology, and the industrial mobilization for power and chips is doable.\n  \n\n\n\n    AI revenue\n   \n\n\n\n   Companies will make large AI investments if they expect the economic returns to justify it.\n  \n\n\n   Reports suggest OpenAI was at a $1B revenue run rate in\n   \n    August\n   \n   2023, and a $2B revenue run rate in\n   \n    February\n   \n   2024. That's roughly a doubling every 6 months. If that trend holds, we should see a ~$10B annual run rate by late 2024/early 2025, even without pricing in a massive surge from any nextgeneration model. One estimate puts\n   \n    Microsoft\n   \n   at ~$5B of incremental AI revenue already.\n  \n\n\n   Table 5: Playing forward trends on total world AI investment. Rough back-ofthe-envelope calculation. For some further details on the calculations, see Appendix.\n  \n\n\n   So far, every 10x scaleup in AI investment seems to yield the necessary returns. GPT-3.5 unleashed the ChatGPT mania. The estimated $500M cost for the GPT-4 cluster would have been paid off by the reported billions of annual revenue for Microsoft and OpenAI (see above calculations), and a \"2024 class\" training cluster in the billions will easily pay off if Microsoft/OpenAI AI revenue continues on track to a $10B+ revenue run rate. The boom is investment-led: it takes time from a huge order of GPUs to build the clusters, build the models, and roll them out, and the clusters being planned today are many years out. But if the returns on the last GPU order keep materializing, investment will continue to skyrocket (and outpace revenue), plowing in even more capital in a bet that the next 10x will keep paying off.\n  \n\n\n   A key milestone for AI revenue that I like to think about is: when will a big tech company (Google, Microsoft, Meta, etc.) hit a $100B revenue run rate from AI (products and API)? These companies have on the order of $100B-$300B of revenue today; $100B would thus start representing a very substantial fraction of their business. Very naively extrapolating out the doubling every 6 months, supposing we hit a $10B revenue run rate in early 2025, suggests this would happen mid-2026.\n  \n\n\n   That may seem like a stretch, but it seems to me to require surprisingly little imagination to reach that milestone. For example, there are around 350\n   \n    million paid subscribers to Mi\n   \n\n    crosoft Office\u2014\n   \n   could you get a third of these to be willing to pay $100/month for an AI add-on? For an average worker, that's only a few hours a month of productivity gained; models powerful enough to make that justifiable seem very doable in the next couple years.\n   \n    54\n   \n\n\n\n   It's hard to understate the ensuing reverberations. This would make AI products the biggest revenue driver for America's largest corporations, and\n   \n    by far\n   \n   their biggest area of growth. Forecasts of overall revenue growth for these companies would skyrocket. Stock markets would follow; we might see our first $10T company soon thereafter. Big tech at this point would be willing to go all out, each investing many hundreds of billions (at least) into further AI scaleout. We probably see our first\n  \n\n\n\n    54\n   \n   A big uncertainty for me is what the lags are for the technology to diffuse and be adopted. I think it's plausible revenue is slowed because intermediate, pre-AGI models take a lot of \"schlep\" to properly integrate into company workflows; historically, it's taken a while to fully harvest the productivity gains from new general purpose technologies. This is where the \"sonic boom\" discussion earlier comes in: as we \"unhobble\" models and they start looking more like agents/dropin remote workers\" deploying them becomes much easier. Rather than having to completely remake some workflow to harvest a 25% productivity gain from a GPT-chatbot, instead you'll get models that you can onboard and work with as you would a new coworker (e.g., just directly substitute for an engineer, rather than needing to train up engineers to use some new tool). Or, in the extreme, and later on: you won't need to completely redesign a factory to work with some new tool, you'll just bring in the humanoid robots.\n  \n\n\n   That said, this may lead to some discontinuity in economic value and revenue generated, depending on how quickly we can \"unhobble\" models.\n  \n\n\n   many-hundred-billion dollar corporate bond sale then.\n   \n    55\n   \n\n    55\n   \n   What will happen to interest rates\n  \n\n\n   Beyond $100B, it gets harder to see the contours. But if we are truly on the path to AGI, the returns will be there. White-collar workers are paid tens of trillions of dollars in wages annually worldwide; a drop-in remote worker that automates even a fraction of white-collar/cognitive jobs (imagine, say, a truly automated AI coder) would pay for the trillion-dollar cluster. If nothing else, the national security import could well motivate a government project, bundling the nation's resources in the race to AGI (more later).\n  \n\n\n\n    Historical precedents\n   \n\n\n\n   $1T/year of total annual AI investment by 2027 seems outrageous. But it's worth taking a look at other historical reference classes:\n  \n\n\n\n\n\n\n     In their peak years of funding, the Manhattan and Apollo programs reached 0.4\n     \n      % of GDP,\n     \n     or ~$100 billion annually today (surprisingly small!). At $1T/year, AI investment would be about 3% of GDP.\n    \n\n\n     Between 1996\u20132001,\n     \n      telecoms invested\n     \n     nearly $1 trillion in today's dollars in building out internet infrastructure.\n    \n\n\n     From 1841 to 1850,\n     \n      private British railway investments to\n     \n\n      taled\n     \n     a cumulative ~40% of British GDP at the time. A similar fraction of\n     \n      US GDP\n     \n     would be equivalent to ~$11T over a decade.\n    \n\n\n\n      Many trillions\n     \n     are being spent on the green transition.\n    \n\n\n     Rapidly-growing economies often spend a high fraction of their GDP on investment; for example, China has spent more than 40\n     \n      % of its GDP on investment for two decades\n     \n     (equivalent to $11T\n     \n      annually\n     \n     given US GDP).\n    \n\n\n     In the historically most exigent national security circumstances wartime\u2014borrowing to finance the national effort has often comprised enormous fractions of GDP. During WWI, the\n    \n\n\n\n   will be interesting. . . see\n   \n    Tyler Cowen\n   \n\n    here;\n   \n\n    Chow, Mazlish and Halperin here.\n   \n\n\n\n\n    UK\n   \n   and\n   \n    France,\n   \n   and\n   \n    Germany\n   \n   borrowed over 100% of their GDPs while the\n   \n    US\n   \n   borrowed over 20%; during WWII, the\n   \n    UK\n   \n   and Japan borrowed over 100% of their GDPs while the\n   \n    US\n   \n   borrowed over 60% of GDP (equivalent to over $17T today).\n  \n\n\n   $1T/year of total AI investment by 2027 would be dramatic among the very largest capital buildouts ever\u2014but would not be unprecedented. And a trillion-dollar individual training cluster by the end of the decade seems on the table.\n   \n    56\n   \n\n    56\n   \n   And, farther out, but if AGI truly led\n  \n\n\n\n    Power\n   \n\n\n\n   Probably the single biggest constraint on the supply-side will be\n   \n    power.\n   \n   Already, at nearer-term scales (1GW/2026 and especially 10GW/2028), power has become the binding constraint: there simply isn't much spare capacity, and power contracts are usually long-term locked-in. And building, say, a new gigawatt-class nuclear power plant takes a decade. (I'll wonder when we'll start seeing things like tech companies buying\n   \n    aluminum smelting companies\n   \n   for their gigawatt-class power contracts.57)\n  \n\n\n\n\n\n\n   to substantial increases in economic growth, $10T+ annually would start being plausible\u2014the reference class being investment rates of countries during high-growth periods.\n  \n\n\n\n    57\n   \n   \"Since 2011, the Alouette Smelter uses 930 MW electricity at maximum production capacity.\"\n  \n\n\n   Figure 30: Comparing trends on total US electricity production to our back-of-the-envelope estimates on AI electricity demands.\n  \n\n\n   Total US electricity generation has\n   \n    barely grown\n   \n   5% in the last\n  \n\n\n\n    decade.\n   \n   Utilities are\n   \n    starting to get excited\n   \n   about AI\n   \n    (instead of\n   \n   2.6% growth over the next 5 years, they now estimate 4.7%!). But they're barely pricing in what's coming. The trillion-dollar, 100GW cluster alone would require ~20% of current US electricity generation in 6 years; together with large inference capacity, demand will be multiples higher.\n  \n\n\n   To most, this seems completely out of the question. Some are betting on Middle Eastern autocracies, who have been going around offering boundless power and giant clusters to get their rulers a seat at the AGI-table.\n  \n\n\n   But it's totally possible to do this in the United States: we have abundant natural gas.\n   \n    58\n   \n\n    58\n   \n   Thanks to\n   \n    Austin Vernon\n   \n   (private\n  \n\n\n\n\n\n\n     Powering a 10GW cluster would take only a few percent of US natural gas production and could be done rapidly.\n    \n\n\n     Even the 100GW cluster is surprisingly doable.\n     \n\n\n\n\n        \u2013\n       \n       Right now the Marcellus/Utica shale (around Pennsylvania) alone is\n       \n        producing\n       \n       around 36 billion cubic feet a day of gas; that would be enough to generate just under 150GW continuously with generators (and combined cycle power plants could output 250 GW due to their higher efficiency).\n      \n\n\n\n\n\n\n        \u2013\n       \n       It would take about ~1200\n       \n        new wells\n       \n       for the 100GW cluster.\n       \n        59\n       \n       Each rig can drill roughly 3 wells per month, so 40\n       \n        59\n       \n       New wells produce around\n       \n        0\n       \n       .\n       \n        01\n       \n       BCF per day. rigs (the current\n       \n        rig count\n       \n       in the Marcellus) could build up the production base for 100GW in less than a year.\n       \n        60\n       \n\n        60\n       \n       Each well produces ~\n       \n        20\n       \n       BCF over The Marcellus had a rig count of ~80 as recently as 2019 so it would not be taxing to add 40 rigs to build up the production base.\n       \n        61\n       \n\n\n\n\n\n\n\n        \u2013\n       \n       More generally, US natural gas production has more than time frame than\n       \n        10\n       \n       months.\n       \n        doubled in a decade;\n       \n       simply continuing that trend could power multiple trillion-dollar datacenters.\n       \n        62\n       \n\n        62\n       \n       A cubic foot of natural gas\n       \n        generates\n       \n\n\n\n\n\n\n\n        \u2013\n       \n       The harder part would be building enough generators / turbines; this wouldn't be trivial, but it seems doable with\n      \n\n\n\n\n\n   correspondence) for helping with these estimates.\n  \n\n\n\n\n\n   its lifetime, meaning two new wells a month would replace the depleted reserves. That is, it would need only one rig to maintain the production.\n   \n    61\n   \n   Though it would be more efficient to add less rigs and build up over a longer\n  \n\n\n\n    about\n   \n   0.13 kWh. Shale gas production\n   \n    was about\n   \n   ~70 billion cubic feet per day in the US in 2020. Suppose we doubled production again, and the extra capacity all went to compute clusters. That's 3322 TWh/year of electricity, or enough for almost 4 100GW clusters.\n  \n\n\n   about $100B of capex\n   \n    63\n   \n   for 100GW of natural gas power\n   \n    63\n   \n   The capex costs for natural gas power plants. Combined cycle plants can be built in about two years; the timeline for generators would be even shorter still.\n   \n    64\n   \n\n\n\n   The barriers to even trillions of dollars of datacenter buildout in the US are entirely self-made. Well-intentioned but rigid climate commitments (not just by the government, but green datacenter commitments by Microsoft, Google, Amazon, and so on) stand in the way of the obvious, fast solution. At the very least, even if we won't do natural gas, a broad deregulatory agenda would unlock the solar/batteries/SMR/geothermal megaprojects. Permitting, utility regulation, FERC regulation of\n   \n    transmission lines,\n   \n   and NEPA environmental review makes things that should take a few years take a decade or more. We don't have that kind of time.\n  \n\n\n   We're going to drive the AGI datacenters to the Middle East, under the thumb of brutal, capricious autocrats. I'd prefer clean energy too\u2014but this is simply too important for US national security. We will need a new level of determination to make this happen. The power constraint can, must, and will be solved.\n  \n\n\n\n    Chips\n   \n\n\n\n   While chips are usually what comes to mind when people think about AI-supply-constraints, they're likely a smaller constraint than power. Global production of AI chips is still a pretty small percent of TSMC-leading-edge production, likely less than 10%. There's a lot of room to grow via AI becoming a larger share of TSMC production.\n  \n\n\n   Indeed, 2024 production of AI chips (~5-10M H100-equivalents) would already be almost enough for the $100s of billion cluster (if they were all diverted to one cluster). From a pure logic fab standpoint ~100% of TSMC's output for a year could already support the trillion-dollar cluster (again if all the chips went to one datacenter).\n   \n    65\n   \n   Of course, not all of TSMC will be able to be diverted to AI, and not all of AI chip production for a year will be for one training cluster. Total AI chip demand (including\n  \n\n\n   plants\n   \n    seem to be\n   \n   under $1000 per kW, meaning the capex for 100GW of natural gas power plants would be about $100 billion.\n  \n\n\n\n    64\n   \n   Solar and batteries aren't a totally crazy alternative, but it does just seem rougher than natural gas. I did appreciate\n   \n    Casey Handmer's\n   \n\n    calculation\n   \n   of tiling the Earth in solar panels:\n  \n\n\n   \"With current GPUs, the global solar datacenter's compute is equivalent to ~150 billion humans, though if our computers can eventually match [human brain] efficiency, we could support more like 5 quadrillion AI souls.\"\n  \n\n\n\n    65\n   \n   This poses the interesting question of why power requirements are going up so much before chip fab production starts being really constrained. A simple answer is while datacenters run continuously at close to max power, most chips currently produced are idle a lot of the time. Currently, smartphones are close to half of leading chip demand, but use a lot less energy per wafer area (trading transistors for serial operations and energy efficiency) and have low utilization as smartphones are mostly idle. The AI revolution means working our transistors way harder, dedicating them all to constantly-running, high-performance AI datacenters instead of idle, batterypowered/energy-saving devices. HT Carl Shulman for this point.\n  \n\n\n   inference and multiple players) by 2030 will be a multiple of TSMC's current total leading-edge logic chip capacity, just for AI. TSMC\n   \n    ~doubled\n   \n\n    66\n   \n   in the past 5 years; they'd likely need to\n   \n    66\n   \n   (Using revenue as a proxy.) go ~at least twice as fast on their pace of expansion to meet AI chip demand. Massive new fab investments would be necessary.\n  \n\n\n   Even if raw logic fabs won't be the constraint, chip-on-waferon-substrate (CoWoS) advanced packaging (connecting chips to memory, also made by TSMC, Intel, and others) and HBM memory (for which demand\n   \n    is\n   \n\n    enormous)\n   \n   are already key bottlenecks for the current AI GPU scaleup; these are more specialized to AI, unlike the pure logic chips, so there's less pre-existing capacity. In the near term, these will be the primary constraint on churning out more GPUs, and these will be the huge constraints as AI scales. Still, these are comparatively \"easy\" to scale; it's been incredible watching TSMC literally build \"greenfield\" fabs (i.e. entirely new facilities from scratch) to massively scale up CoWoS production this year (and Nvidia is even starting to find\n   \n    CoWoS alternatives\n   \n   to work around the shortage).\n  \n\n\n   A new TSMC\n   \n    Gigafab\n   \n   (a\n   \n    technological marvel)\n   \n   costs around $20B in capex and produces 100k wafer-starts a month. For hundreds of millions of AI GPUs a year by the end of the decade, TSMC would need to build dozens of these\u2014as well as a huge buildout for memory, advanced packaging, networking, etc., which will be a major fraction of capex. It could add up to over $1T of capex. It will be intense, but doable. (Perhaps the biggest roadblock will not be feasibility, but TSMC not even trying\u2014TSMC does not yet seem AI-scaling-pilled! They think AI will \"only\" grow at a glacial 50\n   \n    % CAGR.\n   \n   )\n  \n\n\n   Recent USG efforts like the CHIPS Act have been trying to onshore more AI chip production to the US (as insurance in case of the Taiwan contingency). While onshoring more of AI chip production to the US would be nice, it's less critical than having the actual datacenter (on which the AGI lives) in the US. If having chip production abroad is like having uranium deposits abroad, having the AGI datacenter abroad is like having the literal nukes be built and stored abroad. Given the dysfunction\n  \n\n\n\n\n\n   and cost we've seen from building fabs in the US in practice, my guess is we should prioritize datacenters in the US while betting more heavily on democratic allies like Japan and South Korea for fab projects\u2014fab buildouts there\n   \n    seem much more\n   \n\n    functional.\n   \n\n\n\n\n    The Clusters of Democracy\n   \n\n\n\n   Before the decade is out, many trillions of dollars of compute clusters will have been built. The only question is whether they will be built in America. Some are rumored to be betting on building them elsewhere, especially in the Middle East. Do we really want the infrastructure for the Manhattan Project to be controlled by some capricious Middle Eastern dictatorship?\n  \n\n\n   The clusters that are being planned today may well be the clusters AGI and superintelligence are trained and run on, not just the \"cool-big-tech-product clusters.\" The national interest demands that these are built in America (or close democratic allies). Anything else creates an irreversible security risk: it\n   \n    risks the AGI weights getting stolen\n   \n\n    67\n   \n   (and perhaps be\n   \n    shipped\n   \n\n    67\n   \n   It's a lot easier to do side-channel ataccess!\n   \n    to China)\n   \n   ; it risks these dictatorships physically seizing the datacenters (to build and run AGI themselves) when the AGI race gets hot; or even if these threats are only wielded implicity, it puts AGI and superintelligence at unsavory dictator's whims. America sorely regretted her energy dependence on the Middle East in the 70s, and we worked so hard to get out from under their thumbs. We cannot make the same mistake again.\n  \n\n\n   The clusters can be built in the US, and we have to get our act together to make sure it happens in the US. American national security must come first, before the allure of free-flowing Middle Eastern cash, arcane regulation, or even, yes, admirable climate commitments. We face a real system competition can the requisite industrial mobilization only be done in \"topdown\" autocracies? If American business is unshackled, America can build like none other (at least in red states). Being willing to use natural gas, or at the very least a broad-based deregulatory agenda\u2014NEPA exemptions, fixing FERC and\n  \n\n\n   tacks to exfiltrate weights with physical\n  \n\n\n   transmission permitting at the federal level, overriding utility regulation, using federal authorities to unlock land and rights of way\u2014is a national security priority.\n  \n\n\n   In any case: the exponential is in full swing now.\n  \n\n\n   In the \"old days,\" when AGI was still a dirty word, some colleagues and I used to make theoretical economic models of what the path to AGI might look like. One feature of these models used to be a hypothetical \"AI wakeup\" moment, when the world started realizing how powerful these models could be and began rapidly ramping up their investments culminating in multiple % of GDP towards the largest training runs.\n  \n\n\n   It seemed far-off then, but that time has come. 2023\n   \n    was\n   \n   \"AI wakeup.\"\n   \n    68\n   \n   Behind the scenes, the most staggering techno-\n   \n    68\n   \n   I distinctly remember writing \"THE capital acceleration has been put into motion.\n  \n\n\n   Brace for the G-forces.\n  \n\n\n\n    (What all of this means for NVDA/TSM/etc I leave as an exercise for the reader. Hint: Those with situational awareness bought much lower than you, but it's still not even close to fully priced in.)\n   \n\n    69\n   \n\n    69\n   \n   Mainstream sell-side analysts seem\n  \n\n\n   TAKEOFF HAS STARTED\" on my whiteboard in March of 2023.\n  \n\n\n   to assume only 10-20% year-over-year growth in Nvidia revenue from CY24 to CY25, maybe $120B-$130B in CY25 (or at least did until very recently). Insane! It's been pretty obvious for a while that Nvidia is going to do over $200B of revenue in CY25.\n  \n\n\n\n    IIIb. Lock Down the Labs: Security for AGI\n   \n\n\n\n\n    The nation's leading AI labs treat security as an afterthought. Currently, they're basically handing the key secrets for AGI to the CCP on a silver platter. Securing the AGI secrets and weights against the state-actor threat will be an immense effort, and we're not on track.\n   \n\n\n\n\n\n    They met in the evening in Wigner's office. \"Szilard outlined the Columbia data,\" Wheeler reports, \"and the preliminary indications from it that at least two secondary neutrons emerge from each neutron-induced fission. Did this not mean that a nuclear explosive was certainly possible?\" Not necessarily, Bohr countered.\n   \n\n\n\n\n\n    \"We tried to convince him,\" Teller writes, \"that we should go ahead with fission research but we should not publish the results. We should keep the results secret, lest the Nazis learn of them and produce nuclear explosions first.\"\n   \n\n\n\n   \"Bohr insisted that we would never succeed in producing nuclear energy and he also insisted that secrecy must never be introduced into physics.\"\n  \n\n\n\n    The Making of the Atomic Bomb\n   \n   , p. 430\n  \n\n\n   On the current course, the leading Chinese AGI labs won't be in Beijing or Shanghai\u2014they'll be in San Francisco and London. In a few years, it will be clear that the AGI secrets are the United States' most important national defense secrets\u2014deserving treatment on par with B-21 bomber or Columbia-class submarine blueprints, let alone the proverbial\n  \n\n\n   \"nuclear secrets\"\u2014but today, we are treating them the way we would random SaaS software. At this rate, we're basically just handing superintelligence to the CCP.\n  \n\n\n   All the trillions we will invest, the mobilization of American industrial might, the efforts of our brightest minds\u2014none of that matters if China or others can simply steal the model\n   \n    weights\n   \n   (all a finished AI model is, all AGI will be, is a large file on a computer) or key\n   \n    algorithmic secrets\n   \n   (the key technical breakthroughs necessary to build AGI).\n  \n\n\n   America's leading AI labs self-proclaim to be building AGI: they believe that the technology they are building will, before the decade is out, be the most powerful weapon America has ever built. But they do not treat it as such. They measure their security efforts against \"random tech startups,\" not \"key national defense projects.\" As the AGI race intensifies\u2014as it becomes clear that superintelligence will be utterly decisive in international military competition\u2014we will have to face the full force of foreign espionage. Currently, labs are barely able to defend against scriptkiddies, let alone have \"North Koreaproof security,\" let alone be ready to face the Chinese Ministry of State Security bringing its full force to bear.\n  \n\n\n   And this won't just matter years in the future. Sure, who cares if GPT-4 weights are stolen\u2014what really matters in terms of weight security is that we can secure the AGI weights down the line, so we have a few years, you might say. (Though if we're building AGI in 2027, we really have to get moving!) But the AI labs are developing the\n   \n    algorithmic secrets\u2014\n   \n   the key technical breakthroughs, the blueprints so to speak\u2014for the AGI\n   \n    right now\n   \n   (in particular, the RL/self-play/synthetic data/etc \"next paradigm\" after LLMs to get past the data wall). AGI-level security for algorithmic secrets is necessary years before AGIlevel security for weights. These algorithmic breakthroughs will matter more than a 10x or 100x larger cluster in a few years\u2014this is a much bigger deal than export controls on compute, which the USG has been (presciently!) intensely pursuing. Right now, you needn't even mount a dramatic espionage operation to steal these secrets: just go to any SF party or look through the office windows.\n  \n\n\n   Our failure today will be irreversible soon: in the next 12-24 months, we will leak key AGI breakthroughs to the CCP. It will be the national security establishment's single greatest regret before the decade is out.\n  \n\n\n   The preservation of the free world against the authoritarian states is on the line\u2014and a healthy lead will be the necessary buffer that gives us margin to get AI safety right, too. The United States has an advantage in the AGI race. But we will give up this lead if we don't get serious about security very soon. Getting on this, now, is maybe even the single most important thing we need to do today to ensure AGI goes well.\n  \n\n\n\n    Underrate state actors at your peril\n   \n\n\n\n   Too many smart people underrate espionage.\n  \n\n\n   The capabilities of states and their intelligence agencies are extremely formidable. Even in normal, non-all-out-AGI-race times (and from the little we know publicly), nation-states (or less advanced actors) have been able to:\n  \n\n\n\n\n\n\n\n      Zero-click hack any desired iPhone and Mac\n     \n     with just a phone number,\n    \n\n\n     Infiltrate an\n     \n      airgapped atomic weapons program,\n     \n\n\n\n\n      Modify Google source code,\n     \n\n\n\n     Find\n     \n      dozens of zero-days\n     \n     a year that take\n     \n      on average of\n     \n     7\n     \n      years\n     \n     to detect,\n    \n\n\n     Spearfish\n     \n      major tech companies,\n     \n\n\n\n     Install\n     \n      keyloggers on employee devices,\n     \n\n\n\n     Insert\n     \n      trapdoors in encryption schemes,\n     \n\n\n\n     Steal information\n     \n      via electromagnetic emanations or vibra\n     \n\n      tion,\n     \n\n\n\n\n\n\n\n\n     Use\n     \n      just the noise from your computer\n     \n     to determine where you are on a video game map or\n     \n      steal a password,\n     \n\n\n\n     Gain direct access to sensitive systems like\n     \n      nuclear power\n     \n\n      plants,\n     \n\n\n\n     Exfiltrate 22\n     \n      million security clearance files\n     \n     from the USG,\n    \n\n\n     Expose the\n     \n      financial information of\n     \n     110 million customers by\n     \n      planting vulnerabilities in HVAC systems,\n     \n\n\n\n     Compromise\n     \n      computer hardware supply chains at large\n     \n\n      scale,\n     \n\n\n\n     Slip\n     \n      malicious code into updates to software dependencies\n     \n     used by top tech companies and the USG\n    \n\n\n     . . . let alone planting spies or seducing, cajoling, or threatening employees (which happens effectively at\n     \n      large scales,\n     \n     but is less public)\n    \n\n\n     . . . let alone special forces operations and similar (when things really get hot).\n    \n\n\n\n   For a further taste of what we're dealing with when facing down intelligence agencies, I highly recommend\n   \n    Inside the Aquarium\n   \n   , a book by a Soviet GRU (military intelligence) defector.\n   \n    70\n   \n\n\n\n   Already, China engages in widespread industrial espionage; the FBI director stated the PRC has a hacking operation greater than\n   \n    \"every major nation combined.\n   \n   \" And just a couple months ago, the Attorney General\n   \n    announced the arrest of a Chinese\n   \n\n    national\n   \n   who had stolen key AI code from Google to take back with him to the PRC (back in 2022/23, and probably just the tip of the iceberg).\n   \n    71\n   \n\n\n\n   But that's just the beginning. We must be prepared for our adversaries to \"wake up to AGI\" in the next few years. AI will become the #1 priority of every intelligence agency in the world. In that situation, they would be willing to employ extraordinary means and pay any cost to infiltrate the AI labs.\n  \n\n\n\n    70\n   \n   One spoiler, as a taste: on graduation from their ~spy academy, before being sent overseas, aspiring spies had to prove their skills domestically: they had to acquire secret information from a Soviet scientist. The penalty for revealing state secrets, of course, was death. That is: graduating from the ~spy academy meant picking a countryman to condemn to death. HT Ilya Sutskever for the book recommendation.\n  \n\n\n\n    71\n   \n   By the way, the indictment provides a great illustration of how easy it is to evade security at even Google, which likely has the best security of all the AI labs (given their ability to lean on Google's decades-long investment in security infrastructure). All it took to steal the code, without detection, was pasting code into Apple Notes, then exporting to pdf!\n  \n\n\n   \"DING exfiltrated these files by copying data from the Google source files into the Apple Notes application on his Google-issued MacBook laptop. DING then converted the Apple Notes into PDF files. and uploaded them from the Google network into DING Account 1. This method helped DING evade immediate detection.\" (From the\n   \n    indictment.\n   \n   )\n  \n\n\n   He only got caught because he did a bunch of other stupid things, like immediately start prominent startups in China which got people suspicious (and later even came back to the US).\n  \n\n\n\n    The threat model\n   \n\n\n\n   There are two key assets we must protect: model weights (especially as we get close to AGI, but which takes years of preparation and practice to get right) and algorithmic secrets (starting yesterday).\n  \n\n\n\n    Model weights\n   \n\n\n\n   An AI model is just a large file of numbers on a server. This can be stolen. All it takes an adversary to match your trillions of dollars and your smartest minds and your decades of work is to steal this file. (Imagine if the Nazis had gotten an exact duplicate of every atomic bomb made in Los Alamos.)\n  \n\n\n   If we can't keep model weights secure, we're just building AGI for the CCP (and, given the current trajectory of AI lab security, even North Korea).\n  \n\n\n   Even besides national competition, securing model weights is critical for preventing AI catastrophes as well. All of our handwringing and protective measures are for naught if a bad actor (say, a terrorist or rogue state) can just steal the model and do whatever they want with it, circumventing any safety layers. Whatever novel WMDs superintelligence could invent would rapidly proliferate to dozens of rogue states. Moreover, security is the first line of defense against uncontrolled or misaligned AI systems, too (how stupid would we feel if we failed to contain the rogue superintelligence because we didn't build and test it in an air-gapped cluster first?).\n  \n\n\n   Securing model weights doesn't matter that much right now: stealing GPT-4 without the underlying recipe doesn't do that much for the CCP. But it will\n   \n    really\n   \n   matter in a few years, once we have AGI, systems that are genuinely incredibly powerful.\n  \n\n\n\n    Perhaps the single scenario that most keeps me up at night is if China or another adversary is able to steal the automated-AI-researchermodel-weights on the cusp of an intelligence explosion.\n   \n   China could immediately use these to automate AI research themselves\n  \n\n\n   (even if they had previously been way behind)\u2014and launch their own intelligence explosion. That'd be all they need to automate AI research, and build superintelligence. Any lead the US had would vanish.\n  \n\n\n   Moreover, this would immediately put us in an existential race; any margin for ensuring superintelligence is safe would disappear. The CCP may well try to race through an intelligence explosion as fast as possible\u2014even months of lead on superintelligence could mean a decisive military advantage\u2014in the process skipping all the safety precautions any responsible US AGI effort would hope to take. We would also have to race through the intelligence explosion to avoid complete CCP dominance. Even if the US still manages to barely pull out ahead in the end, the loss of margin would mean having to run enormous risks on AI safety.\n  \n\n\n   We're miles away for sufficient security to protect weights today. Google DeepMind (perhaps the AI lab that has the best security of any of them, given Google infrastructure) at least straight-up admits this. Their\n   \n    Frontier Safety Framework\n   \n   outlines security levels 0, 1, 2, 3, and 4 (~1.5 being what you'd need to defend against well-resourced terrorist groups or cybercriminals, 3 being what you'd need to defend against the North Koreas of the world, and 4 being what you'd need to have even a shot of defending against priority efforts by the most capable state actors).\n   \n    72\n   \n   They admit to being at level 0 (only the most banal and basic measures). If we got AGI and superintelligence soon, we'd literally deliver it to terrorist groups and every crazy dictator out there!\n  \n\n\n   Critically, developing the infrastructure for weight security probably takes many years of lead times\u2014if we think AGI in ~3-4 years is a real possibility and we need state-proof weight security then, we need to be launching the crash effort\n   \n    now.\n   \n   Securing weights will require innovations in hardware and radically different cluster design; and security at this level can't be reached overnight, but requires cycles of iteration.\n  \n\n\n   If we fail to prepare in time, our situation will be dire. We will be on the cusp of superintelligence, but years away from the se-\n  \n\n\n\n    72\n   \n   Based off of their claimed correspondence of their security levels to\n   \n    RAND's\n   \n\n    weight security report's\n   \n   L1-L5\n  \n\n\n   curity necessary. Our choice will be to press ahead, but directly deliver superintelligence to the CCP\u2014with the existential race through the intelligence explosion that implies\u2014or wait until the security crash program is complete, risking losing our lead.\n  \n\n\n\n    Algorithmic secrets\n   \n\n\n\n   While people are starting to appreciate (though not necessarily implement) the need for weight security, arguably even more important right now\u2014and\n   \n    vastly\n   \n   underrated\u2014is securing algorithmic secrets.\n  \n\n\n   One way to think about this is that stealing the algorithmic secrets will be worth having a 10x or more larger cluster to the PRC:\n  \n\n\n\n\n\n\n     As discussed in Counting the OOMs, algorithmic progress is probably similarly as important as scaling up compute to AI progress. Given the baseline trend of ~0.5 OOMs of compute efficiency a year (+ additional algorithmic \"unhobbling\" gains on top), we should expect multiple OOMs-worth of algorithmic secrets between now and AGI. By default, I expect American labs to be years ahead; if they can defend their secrets, this could easily be worth 10x-100x compute.\n     \n\n\n\n\n        \u2013\n       \n       (Note that we're willing to incur American investors 100s of billions of dollars of costs by export controlling Nvidia chips\u2014perhaps a 3x increase in compute cost for Chinese labs\u2014but we're leaking 3x algorithmic secrets all over the place!)\n      \n\n\n\n\n     Maybe even more importantly,\n     \n      we may be developing the key paradigm breakthroughs for AGI right now.\n     \n     As discussed previously, simply scaling up current models will hit a wall: the data wall. Even with way more compute, it won't be possible to make a better model. The frontier AI labs are furiously at work at what comes next, from RL to synthetic data. They will probably figure out some crazy stuff essentially, the \"AlphaGo self-play\"-equivalent for general intelligence. Their inventions will be as key as the invention of the LLM paradigm originally was a number of years\n    \n\n\n\n   ago, and they will be the key to building systems that go far beyond human-level. We still have an opportunity to deny China these key algorithmic breakthroughs, without which they'd be stuck at the data wall. But without better security in the next 12-24 months, we may well irreversibly supply China with these key AGI breakthroughs.\n  \n\n\n   \u2022 It's easy to underrate how important an edge algorithmic secrets will be\u2014because up until ~a couple years ago, everything was published. The basic idea was out there: scale up Transformers on internet text. Many algorithmic details and efficiencies were out there: Chinchilla scaling laws, MoE, etc. Thus, open source models today are pretty good, and a bunch of companies have pretty good models (mostly depending on how much $$$ they raised and how big their clusters are). But this will likely change fairly dramatically in the next couple years. Basically all of frontier algorithmic progress happens at labs these days (academia is surprisingly irrelevant), and the leading labs have stopped publishing their advances. We should expect far more divergence ahead: between labs, between countries, and between the proprietary frontier and open source models. A few American labs will be way ahead\u2014a moat worth 10x, 100x, or more, way more than, say, 7nm vs. 3nm chips\u2014unless they instantly leak the algorithmic secrets.\n   \n    73\n   \n\n    73\n   \n   I sometimes joke that AI lab algo-\n  \n\n\n\n    Put simply, I think failing to protect algorithmic secrets is probably the most likely way in which China is able to stay competitive in the AGI race.\n   \n   (I discuss this more later.)\n  \n\n\n   It's hard to overstate how bad algorithmic secrets security is right now. Between the labs, there are thousands of people with access to the most important secrets; there is basically no background-checking, silo'ing, controls, basic infosec, etc. Things are stored on easily hackable SaaS services. People gabber at parties in SF. Anyone, with all the secrets in their head, could be offered $100M and recruited to a Chinese lab at any point.\n   \n    74\n   \n   You can . . . just look through office windows. And\n   \n    74\n   \n   Indeed, I've heard from friends so on. There are many articles, and rumors flying around SF, purporting to have extensive details of various lab algorithmic advances.\n  \n\n\n   rithmic advances are not shared with the American research community, but they are being shared with the Chinese research community!\n  \n\n\n   that ByteDance emailed basically every person who was on the Google Gemini paper to recruit them, offering them L8 (a very senior position, with presumably similarly high pay), and pitching them by saying they'd report directly to the CTO in America of ByteDance.\n  \n\n\n   AI lab security isn't much better than \"random startup security.\" Directly selling the AGI secrets to the CCP would at least be more honest.\n  \n\n\n\n\n    . . . Is this what we see at OpenAI or any other American AI lab? No. In fact, what we see is the opposite\u2014the security equivalent of swiss cheese. Chinese penetration of these labs would be trivially easy using any number of industrial espionage methods, such as simply bribing the cleaning crew to stick USB dongles into laptops. My own assumption is that all such American AI labs are fully penetrated and that China is getting nightly downloads of all American AI research and code RIGHT NOW. . .\n   \n\n\n\n\n\n\n\n\n\n       Marc Andreessen\n      \n\n\n\n\n\n\n   While it will be tough, I think these secrets are defensible. There are probably only dozens of people who truly \"need to know\" the key implementation details for a given algorithmic breakthrough at a given lab (even if a larger number need to know the basic high-level idea)\u2014you can vet, silo, and intensively monitor these people, in addition to radically upgraded infosec.\n  \n\n\n\n    What \"supersecurity\" will require\n   \n\n\n\n   There's a lot of low-hanging fruit on security at AI labs. Merely adopting best practices from, say, secretive hedge funds or Google-customer-data-level security, would put us in a much better position with respect to \"regular\" economic espionage from the CCP. Indeed, there are notable examples of private sector firms doing remarkably well at preserving secrets. Take quantitative trading firms (the Jane Streets of the world) for example. A number of people have told me that in an hour of conversation they could relay enough information to a competitor such that their firm's alpha would go to ~zero\u2014similar to how many key AI algorithmic secrets could be relayed in a short conversation\u2014and yet these firms manage to keep these secrets and retain their edge.\n  \n\n\n   While most of America's leading AI labs have refused to put the national interest first\u2014rejecting even basic security mea-\n  \n\n\n   sures in this tier, if they have any cost or require any prioritization of security\u2014picking this low-hanging fruit would be well within their abilities.\n  \n\n\n   But let's look out just a bit further. Once China begins to truly understand the import of AGI, we should expect the full force of their espionage efforts to come to bear; think billions of dollars invested, thousands of employees, and extreme measures (e.g., special operations strike teams) dedicated to infiltrating American AGI efforts. What will security for AGI and superintelligence require?\n  \n\n\n   In short,\n   \n    this will only be possible with government help\n   \n   . Microsoft, for example, is regularly hacked by state actors (e.g., Russian hackers recently\n   \n    stole Microsoft executives' emails,\n   \n   as well as\n   \n    government emails Microsoft hosts)\n   \n   . A high-level security expert working in the field estimated that even with a complete private crash course, China would still likely be able to exfiltrate the AGI weights if it was their #1 priority\u2014the only way to get this probability to the single digits would require, more or less, a government project.\n  \n\n\n   While the government does not have a perfect track record on security themselves, they're the only ones who have the infrastructure, know-how, and competencies to protect nationaldefense-level secrets. Basic stuff like the authority to subject employees to intense vetting; threaten imprisonment for leaking secrets; physical security for datacenters; and the vast know-how of places like the NSA and the people behind the security clearances (private companies simply don't have the expertise on state-actor attacks).\n  \n\n\n   I'm not one of the people behind the security clearances, so I can't give a proper accounting of what security for AGI will truly require. The best public resource on this is RAND's\n   \n    re\n   \n\n    port on weight security.\n   \n   To give a taste of what this state-actor proof security will actually mean:\n  \n\n\n   \u2022 Fully airgapped datacenters, with physical security on par with most secure military bases (cleared personnel, physical fortifications, onsite response team, extensive surveillance\n  \n\n\n   and extreme access control),\n  \n\n\n\n\n\n\n\n      \u2013\n     \n     And not just for training clusters\u2014inference clusters need the same intense security!\n     \n      75\n     \n\n      75\n     \n     Inference fleets will likely be much\n    \n\n\n     Novel technical advances on confidential compute / hardware encryption\n     \n      76\n     \n     and extreme scrutiny on the entire hardware supply chain,\n    \n\n\n     All research personnel working from a\n     \n      SCIF\n     \n     (Sensitive Compartmented Information Facility, pronounced \"skiff\", see\n     \n      this\n     \n\n      visualization)\n     \n     ,\n    \n\n\n     Extreme personnel vetting and security clearances (including regular employee integrity testing and the like), constant monitoring and substantially reduced freedoms to leave, and rigid information siloing.\n    \n\n\n     Strong internal controls, e.g. multi-key signoff to run any code.\n    \n\n\n     Strict limitations on any external dependencies, and satisfying general requirements of TS/SCI networks.\n    \n\n\n     Ongoing intense pen-testing by the NSA or similar.\n    \n\n\n     And so on. . .\n    \n\n\n\n   The giant AGI clusters are being mapped out, right now; the corresponding security effort must be too. If we are building AGI in just a few years, we have very little time.\n  \n\n\n   Still, this immense effort shouldn't lead to fatalism. The saving grace on security is that the CCP probably isn't fully AGIpilled yet, and so not yet investing in the most extreme efforts. American AI lab security \"only\" has to stay ahead of the curve compared to the intensity of Chinese espionage efforts. That means immediately upgrading security to stay ahead of \"more normal\" economic espionage (which we are far from resistant to, but private companies probably could be); and that means over the next couple years, as Chinese and other foreign espionage ramps up, rapidly upgrading to much more intense\n  \n\n\n   larger than training clusters, and there will be overwhelming pressure to use these inference clusters to run automated AI researchers during the intelligence explosion (and run billions of superintelligences more broadly in the immediate aftermath). The AGI/superintelligence weights could thus be exfiltrated from these clusters as well. (I worry that this is underrated, and inference clusters will be much less protected.)\n  \n\n\n\n    76\n   \n   But you can't rely only on this! Hardware encryption regularly gets\n   \n    side-channeled.\n   \n   Defense-in-depth is key, of course.\n  \n\n\n   measures in cooperation with the government.\n  \n\n\n   Some argue that strict security measures and their associated friction aren't worth it because they would slow down American AI labs too much. But I think that's mistaken:\n  \n\n\n\n\n\n\n     This is a tragedy of the commons problem. For a given lab's commercial interests, security measures that cause a 10% slowdown might be deleterious in competition with other labs. But the national interest is clearly better served if every lab were willing to accept the additional friction: American AI research is way ahead of Chinese and other foreign algorithmic progress, and America retaining 90%-speed algorithmic progress as our national edge is clearly better than retaining 0% as a national edge (with everything instantly stolen)!\n    \n\n\n     Moreover, ramping security now will be the\n     \n      less\n     \n     painful path in terms of research productivity in the long run. Eventually, inevitably, if only on the cusp of superintelligence, in the extraordinary arms race to come, the USG will realize the situation is unbearable and demand a security crackdown. It will be so much more painful, and cause much more of a slowdown, to have to implement extreme, state-actor-proof security measures from a standing start, rather than iteratively.\n    \n\n\n\n   Others argue that even if our secrets or weights leak, we will still manage to eke out\n   \n    just ahead\n   \n   by being faster in other ways (so we needn't worry about security measures). That, too, is mistaken, or at least running\n   \n    way\n   \n   too much risk:\n  \n\n\n   \u2022 As I discuss in a later piece, I think the CCP may well be able to brutely outbuild the US (a 100GW cluster will be much easier for them). More generally, China might not have the same caution slowing it down that the US will (both reasonable and unreasonable caution!). Even if stealing the algorithms or weights \"only\" puts them on par with the US model-wise, that might be enough for them to win the race to superintelligence.\n  \n\n\n\n\n\n\n     Moreover, even if the US squeaks out ahead in the end, the difference between a 1-2 year and 1-2 month lead will\n     \n      really\n     \n     matter for navigating the perils of superintelligence. A 1-2 year lead means at least a reasonable margin to get safety right, and to navigate the extremely volatile period around the intelligence explosion and post-superintelligence.\n     \n      77\n     \n     A\n     \n      77\n     \n     E.g., space to take an extra\n     \n      6\n     \n     months mere 1-2 month lead means a breakneck international arms race with extreme pressures, racing through the intelligence explosion, and no room at all to get safety right. It is that neck-and-neck, existential race in which we face the greatest risks of self-destruction.\n    \n\n\n     Don't forget about Russia, Iran, North Korea, and so on. Their hacking capabilities are no slouch. On the current course, we're freely sharing superintelligence with them too! Without much better security, we're proliferating what will be our most powerful weapon to a plethora of incredibly dangerous, reckless, and unpredictable actors.\n     \n      78\n     \n\n      78\n     \n     We try really hard to prevent nuclear\n    \n\n\n\n   during the intelligence explosion for alignment research to make sure superintelligence doesn't go awry, time to stabilize the situation after the invention of some novel WMDs by directing these systems to focus on defensive applications, or simply time for human decision-makers to make the right decisions given an extraordinarily rapid pace of technological change with the advent of superintelligence.\n  \n\n\n   proliferation to rogue states, even if we'd still be \"ahead\" on nuclear technology compared to their more limited arsenal, given the mayhem\n  \n\n\n   proliferation can cause.\n   \n    We are not on track\n   \n\n\n\n   When it first became clear to a few that an atomic bomb was possible, secrecy, too, was perhaps the most contentious issue. In 1939 and 1940, Leo Szilard became known \"throughout the American physics community as the leading apostle of secrecy in fission matters.\"\n   \n    79\n   \n   But he was rebuffed by most; secrecy was\n   \n    79\n   \n\n    The Making of the Atomic Bomb, p.\n    \n     509\n    \n\n   not at all something scientists were used to, and it ran counter to many of their basic instincts of open science. But it slowly became clear what had to be done: the military potential of this research was too great for it to simply be freely shared with the Nazis. And secrecy was finally imposed, just in time.\n  \n\n\n   In the fall of 1940, Fermi had finished new carbon absorption measurements on graphite, suggesting graphite was a viable moderator for a bomb. Szilard assaulted Fermi with yet another secrecy appeal. \"At this time Fermi really lost his temper; he really thought this was absurd,\" Szilard recounted. Luckily, further appeals were eventually successful, and Fermi reluctantly refrained from publishing his graphite results.\n  \n\n\n\n\n\n\n\n\n\n   Figure 31:\n   \n    Leo Szilard.\n   \n\n\n\n   At the same time, the German project had narrowed down on two possible moderator materials: graphite and heavy water. In\n   \n    early\n   \n   1941 at Heidelberg, Walther Bothe made an incorrect measurement on the absorption cross-section of graphite, and concluded that graphite would absorb too many neutrons to sustain a chain reaction. Since Fermi had kept his result secret, the Germans did not have Fermi's measurements to check against, and to correct the error.\n   \n    This was crucial: it left the German project to pursue heavy water instead\u2014a decisive wrong path that ultimately doomed the German nuclear weapons effort.\n   \n\n    80\n   \n\n    80\n   \n\n    The Making of the Atomic Bomb,\n   \n   p.\n   \n    507\n   \n\n\n\n   If not for that last-minute secrecy appeal, the German bomb project may have been a much more formidable competitor and history might have turned out very differently.\n  \n\n\n   There's a real mental dissonance on security at the leading AI labs. They full-throatedly claim to be building AGI this decade. They emphasize that American leadership on AGI will be decisive for US national security. They are reportedly planning 7\n   \n    T chip buildouts\n   \n   that only make sense if you\n   \n    really\n   \n   believe in AGI. And indeed, when you bring up security, they nod and acknowledge \"of course, we'll all be in a bunker\" and smirk.\n  \n\n\n   And yet the reality on security could not be more divorced from that. Whenever it comes time to make hard choices to prioritize security, startup attitudes and commercial interests prevail over the national interest. The national security advisor would have a mental breakdown if he understood the level of security at the nation's leading AI labs.\n  \n\n\n   There are secrets being developed right now, that can be used for every training run in the future and will be the key unlocks to AGI, that are protected by the security of a startup and will be worth hundreds of billions of dollars to the CCP.\n   \n    81\n   \n   The real-\n   \n    81\n   \n\n    100\n   \n   x+ compute efficiencies, when are being built. ity is that, a) in the next\n   \n    12\n   \n   -\n   \n    24\n   \n   months, we will develop the key algorithmic breakthroughs for AGI, and promptly leak them to the CCP, and b) we are not even on track for our weights to be secure against rogue actors like North Korea, let alone an\n  \n\n\n\n\n\n   clusters worth $10s or $100s of billions\n  \n\n\n   all-out effort by China, by the time we build AGI. \"Good security for a startup\" simply is not even close to good enough, and we have very little time before the egregious damage to the national security of the United States becomes irreversible.\n  \n\n\n   We're developing the most powerful weapon mankind has ever created. The algorithmic secrets we are developing, right now, are literally the nation's most important national defense secrets\u2014the secrets that will be at the foundation of the US and her allies' economic and military predominance by the end of the decade, the secrets that will determine whether we have the requisite lead to get AI safety right, the secrets that will determine the outcome of WWIII, the secrets that will determine the future of the free world. And yet AI lab security is probably worse than a random defense contractor making bolts.\n  \n\n\n   It's madness.\n  \n\n\n   Basically nothing else we do\u2014on national competition, and on AI safety\u2014will matter if we don't fix this, soon.\n  \n\n\n\n\n\n\n   Figure 32: A\n   \n    billboard\n   \n   at the Oak Ridge, Tennessee uranium enrichment facilities, 1943.\n  \n\n\n\n    IIIc. Superalignment\n   \n\n\n\n\n    Reliably controlling AI systems much smarter than we are is an unsolved technical problem. And while it is a solvable problem, things could very easily go off the rails during a rapid intelligence explosion. Managing this will be extremely tense; failure could easily be catastrophic.\n   \n\n\n\n\n\n    The old sorcerer Has finally gone away! Now the spirits he controls Shall obey my commands. . . . I shall work wonders too.\n    \n     . . .\n    \n    Sir, I'm in desperate straits!\n    \n     The spirits I summoned - I can't get rid of them.\n    \n\n\n\n\n\n\n\n\n     johann wolfgang von goethe \"The Sorcerer's Apprentice\"\n    \n\n\n\n\n   By this point, you have probably heard of the AI doomers. You might have been intrigued by their arguments, or you might have dismissed them off-hand. You're loath to read yet another doom-and-gloom meditation.\n  \n\n\n   I am not a doomer.\n   \n    82\n   \n   Misaligned superintelligence is probably not the biggest AI risk.\n   \n    83\n   \n   But I did spend the past year working on technical research on aligning AI systems as my day-job at OpenAI, working with Ilya and the\n   \n    Superalignment\n   \n\n\n\n\n    82\n   \n   As not-very-politely\n   \n    certified by the\n   \n\n    doomer-in-chief!\n   \n   At the very least, I would\n   \n    call myself a strong optimist\n   \n   that this problem is solvable. I have spent considerable energies debating the AI pessimists and strongly advocated against policies like an AI pause.\n   \n    83\n   \n   I'm most worried about\n   \n    things just being totally crazy\n   \n   around superintelligence, including things like novel WMDs, destructive wars, and unknown unknowns. Moreover, I think the arc of history counsels us to not underrate authoritarianism\u2014and superintelligence might allow authoritarians to dominate for billions of years.\n  \n\n\n   team. There is a very real technical problem: our current alignment techniques (methods to ensure we can reliably control, steer, and trust AI systems) won't scale to superhuman AI systems. What I want to do is explain what I see as the \"default\" plan for how we'll muddle through,\n   \n    84\n   \n   and why I'm optimistic.\n   \n    84\n   \n   As Tyler Cowen says, muddling\n   \n    While not enough people are on the ball\u2014\n   \n   we should have through is underrated! much more ambitious efforts to solve this problem!\u2014overall, we've gotten lucky with how deep learning has shaken out, there's a lot of empirical low-hanging fruit that will get us part of the way, and we'll have the advantage of millions of automated AI researchers to get us the rest of the way.\n  \n\n\n   But I also want to tell you why I'm worried. Most of all, ensuring alignment doesn't go awry will require extreme competence in managing the intelligence explosion. If we do rapidly transition from from AGI to superintelligence, we will face a situation where,\n   \n    in less than a year\n   \n   , we will go from recognizable human-level systems for which descendants of current alignment techniques will mostly work fine, to much more alien, vastly superhuman systems that pose a qualitatively different, fundamentally novel technical alignment problem; at the same time, going from systems where failure is low-stakes to extremely powerful systems where failure could be catastrophic; all while most of the world is probably going kind of crazy. It makes me pretty nervous.\n  \n\n\n   By the time the decade is out, we'll have billions of vastly superhuman AI agents running around. These superhuman AI agents will be capable of extremely complex and creative behavior; we will have no hope of following along. We'll be like first graders trying to supervise with multiple doctorates.\n  \n\n\n   In essence, we face a problem of handing off\n   \n    trust\n   \n   . By the end of the intelligence explosion, we won't have any hope of understanding what our billion superintelligences are doing (except as they might choose to explain to us, like they might to a child). And we don't yet have the technical ability to reliably guarantee even basic side constraints for these systems, like \"don't lie\" or \"follow the law\" or \"don't try to exfiltrate your server\".\n   \n    Reinforcement from human feedback\n   \n   (RLHF) works very well for adding such side constraints for current\n  \n\n\n\n\n\n   systems\u2014but RLHF relies on humans being able to understand and supervise AI behavior, which fundamentally won't scale to superhuman systems.\n  \n\n\n   Simply put, without a very concerted effort, we won't be able to guarantee that superintelligence won't go rogue (and this is acknowledged by many\n   \n    leaders\n   \n\n    in\n   \n\n    the\n   \n\n    field)\n   \n   . Yes, it may all be fine by default. But we simply don't know yet. Especially once future AI systems aren't just trained with imitation learning, but large-scale, long-horizon RL (reinforcement learning), they will acquire unpredictable behaviors of their own, shaped by a trial-and-error process (for example, they may learn to lie or seek power, simply because these are successful strategies in the real world!).\n  \n\n\n   The stakes will be high enough that hoping for the best simply isn't a good enough answer on alignment.\n  \n\n\n\n    The problem\n   \n\n\n\n\n    The superalignment problem\n   \n\n\n\n   We've been able to develop a very successful method for aligning (i.e., steering/controlling)\n   \n    current\n   \n   AI systems (AI systems dumber than us!): Reinforcement Learning from Human Feedback (RLHF). The idea behind RLHF is simple: the AI system tries stuff, humans rate whether its behavior was good or bad, and then reinforce good behaviors and penalize bad behaviors. That way, it learns to follow human preferences.\n  \n\n\n   Indeed, RLHF has been the key behind the success of ChatGPT and others.\n   \n    85\n   \n   Base models had lots of raw smarts but weren't applying these in a useful way by default; they usually just responded with a garbled mess resembling random internet text. Via RLHF, we can steer their behavior, instilling important basics like instruction-following and helpfulness. RLHF also allows us to bake in safety guardrails: for example, if a user asks me for bioweapon instructions, the model should probably refuse.\n   \n    86\n   \n\n\n\n\n    85\n   \n   Ironically, the safety guys made the biggest breakthrough for enabling AI's commercial success by inventing RLHF! Base models had lots of raw smarts but were unsteerable and thus unusable for most applications.\n  \n\n\n\n    86\n   \n   This highlights an important distinction: the\n   \n    technical ability\n   \n   to align (steer/control) a model is separate from a values question of\n   \n    what to align to.\n   \n   There have been many political controversies about the latter question. And while I agree with the opposition to some of the outgrowths here, that shouldn't distract from the basic technical problem. Yes, alignment techniques can be misused\u2014but we will need better alignment techniques to ensure even basic side constraints for future models, like follow instructions or follow the law. See also\n   \n    \"AI alignment is distinct\n   \n\n    from its near-term applications\"\n   \n   .\n  \n\n\n\n    The core technical problem of superalignment is simple: how do we control AI systems (much) smarter than us?\n   \n\n\n\n\n    RLHF will predictably break down as AI systems get smarter\n   \n   , and we will face fundamentally new and qualitatively different technical challenges. Imagine, for example, a superhuman AI system generating a million lines of code in a new programming language it invented. If you asked a human rater in an RLHF procedure, \"does this code contain any security backdoors?\" they simply wouldn't know. They wouldn't be able to rate the output as good or bad, safe or unsafe, and so we wouldn't be able to reinforce good behaviors and penalize bad behaviors with RLHF.\n  \n\n\n\n\n\n\n   scale to superintelligence. Even now, AI labs already\n   \n    need to pay expert software engi\n   \n\n    neers\n   \n   to give RLHF ratings for ChatGPT code\u2014the code current models can generate is already pretty advanced! Human labeler-pay has gone from a few dollars for MTurk labelers to\n  \n\n\n   Figure 33: Aligning AI systems via human supervision (as in RLHF) won't\n  \n\n\n   ~$100/hour for GPQA questions\n   \n    87\n   \n   in the last few years. In the\n   \n    87\n   \n   \"We estimate an average hourly (near) future, even the best human experts spending lots of time won't be good enough. We're starting to hit early versions of the superalignment problem in the real world now, and very soon this will be a major issue even just for practically deploying next-generation systems. It's clear we will need a successor to RLHF that scales to AI capabilities better than human-level, where human supervision breaks down. In some sense, the goal of superalignment research efforts is to repeat the success story of RLHF: make the basic research bets that will be necessary to steer and deploy AI systems a couple years down the line.\n  \n\n\n\n    What failure looks like\n   \n\n\n\n   People too often just picture a \"GPT-6 chatbot,\" informing their intuitions that surely these wouldn't be dangerously misaligned. As discussed previously in this series, the \"unhobbling\" trajectory points to agents, trained with RL, in the near future. I think Roger's graphic gets it right.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   payment of approximately $95 per hour,\" p.3 of the\n   \n    GPQA paper.\n   \n\n\n\n   Figure 34:\n   \n    Roger Grosse\n   \n   on the evolution of the alignment problem as systems become more advanced.\n  \n\n\n   One way to think of what we're trying to accomplish with alignment, from the safety perspective, is add\n   \n    side-constraints.\n   \n   Consider a future powerful \"base model\" that, in a second stage of training, we train with long-horizon RL to run a business and make money\n   \n    88\n   \n   (as a simplified example):\n   \n    88\n   \n   Very simplified, think of an AI system\n  \n\n\n\n\n\n\n     By default, it may well learn to lie, to commit fraud, to deceive, to hack, to seek power, and so on\u2014simply because these can be successful strategies to make money in the real world!\n     \n      89\n     \n\n      89\n     \n     What RL is doing is simply explor-\n    \n\n\n     What we want is to add side-constraints: don't lie, don't break the law, etc.\n    \n\n\n     But here we come back to the fundamental issue of aligning superhuman systems: we won't be able to understand what they are doing, and so we won't be able to notice and penalize bad behavior with RLHF.\n     \n      90\n     \n\n      90\n     \n     (or inference-time monitoring models\n    \n\n\n\n   If we can't add these side-constraints, it's not clear what will happen.\n   \n    Maybe\n   \n   we'll get lucky and things will be benign by default (for example, maybe we can get pretty far without the AI systems having long-horizon goals, or the undesirable behaviors will be minor). But it's also totally plausible they'll learn much more serious undesirable behaviors: they'll learn to lie, they'll learn to seek power, they'll learn to behave nicely when humans are looking and pursue more nefarious strategies when we aren't watching, and so on.\n  \n\n\n   The superalignment problem being unsolved means that we simply won't have the ability to ensure even these basic side constraints for these superintelligence systems, like \"\n   \n    will they reliably follow my instructions?\n   \n   \" or \"\n   \n    will they honestly answer my questions?\"\n   \n   or \"\n   \n    will they not deceive humans?\"\n   \n   . People often associate alignment with some complicated questions about human values, or jump to political controversies, but deciding on what behaviors and values to instill in the model, while important, is a separate problem. The primary problem is that for whatever you want to instill the model (including ensuring very basic things, like \"follow the law\"!) we don't yet know how to do that for the very powerful AI systems we are building very\n  \n\n\n   trying, via trial and error, to maximize money over a period of a year, and the final, trained AI model being the result of a selection process that selects for the AI systems that were most successful at maximizing money.\n  \n\n\n   ing strategies for succeeding at the objective. If a strategy works, it is reinforced in the model. So if lying, fraud, power-seeking, etc. (or patterns of thinking that could lead to these sorts of behaviors in at least some situations) work, these will also be reinforced in the model.\n  \n\n\n   trained with human supervision)\n  \n\n\n   soon.\n  \n\n\n   Again, the consequences of this aren't totally clear. What is clear is that superintelligence will have vast capabilities\u2014and so misbehavior could fairly easily be catastrophic. What's more, I expect that within a small number of years, these AI systems will be integrated in many critical systems, including military systems (failure to do so would mean complete dominance by adversaries). It sounds crazy, but remember when everyone was saying we wouldn't connect AI to the internet? The same will go for things like\n   \n    \"we'll make sure a human is\n   \n\n    always in the loop!\"\n   \n   \u2014as people say today.\n  \n\n\n   Alignment failures then might look like isolated incidents, say, an autonomous agent committing fraud, a model instance self-exfiltrating, an automated researcher falsifying an experimental result, or a drone swarm overstepping rules of engagement. But failures could also be much larger scale or more systematic\u2014in the extreme, failures could look more like a robot rebellion. We'll have summoned a fairly alien intelligence, one\n   \n    much\n   \n   smarter than us, one whose architecture and training process wasn't even designed by us but some supersmart previous generation of AI systems, one where we can't even begin to understand what they're doing, it'll be running our military, and its goals will have been learned by a naturalselection-esque process.\n  \n\n\n   Unless we solve alignment\u2014unless we figure out how to instill those side-constraints\u2014there's no particular reason to expect this small civilization of superintelligences will continue obeying human commands in the long run. It seems totally within the realm of possibilities that at some point they'll simply conspire to cut out the humans, whether suddenly or gradually.\n  \n\n\n\n    The intelligence explosion makes this all incredibly tense\n   \n\n\n\n   I am optimistic that superalignment is a solvable technical problem. Just like we developed RLHF, so we can develop the successor to RLHF for superhuman systems and do the science that gives us high confidence in our methods. If things continue to progress iteratively, if we insist on rigorous safety\n  \n\n\n   testing and so on, it should all be doable (and I'll discuss my current best-guess of how we'll muddle through more in a bit).\n  \n\n\n   What makes this incredibly hair-raising is the possibility of an intelligence explosion: that we might make the transition from roughly human-level systems to\n   \n    vastly\n   \n   superhuman systems extremely rapidly, perhaps in less than a year.\n  \n\n\n\n\n\n\n\n      AGI\n     \n\n      Superintelligence\n     \n\n\n\n\n       Required alignment\n      \n\n      technique\n     \n\n\n       RLHF++\n      \n\n\n      Novel, qualitatively different technical\n      \n      solutions\n     \n\n\n\n\n       Failures\n      \n\n\n      Low-stakes\n     \n\n      Catastrophic\n     \n\n\n\n\n       Architecture and\n      \n\n      algorithms\n     \n\n      Familiar, descendants of current\n      \n      systems, fairly benign safety\n      \n      properties\n     \n\n      Alien. Designed by previous-\n      \n      generation super-smart AI system\n     \n\n\n\n      Backdrop\n     \n\n      World is normal\n     \n\n      World is going crazy, extraordinary\n      \n      pressures\n     \n\n\n\n\n       Epistemic state\n      \n\n\n      We can understand what the systems\n      \n      are doing, how they work, and\n      \n      whether they're aligned.\n     \n\n      We have no ability to understand\n      \n      what's going on, how to tell if systems\n      \n      are still aligned and benign, what the\n      \n      systems are doing, and we are entirely\n      \n      reliant on trusting the AI systems.\n     \n\n\n\n\n\n      Transition in\n      \n       \\langle\n      \n      1 year?\n      \n      with very little time to get decisions right\n     \n\n\n\n\n\n\n\n\n   \u2022 We will extremely rapidly go from systems where RLHF works fine\u2014to systems where it will totally break down. This leaves us extremely little time to iteratively discover and\n  \n\n\n   Figure 35: The intelligence explosion makes superalignment incredibly hair-raising.\n  \n\n\n   address ways in which our current methods will fail.\n  \n\n\n\n\n\n\n     At the same time, we will extremely rapidly go from systems where failures are fairly low-stakes (ChatGPT said a bad word, so what)\u2014to extremely high-stakes (oops, the superintelligence self-exfiltrated from our cluster, now it's hacking the military). Rather than iteratively encountering increasingly more dangerous safety failures in the wild, the first notable safety failures we encounter might already be catastrophic.\n    \n\n\n     The superintelligence we get by the end of it will be\n     \n      vastly\n     \n     superhuman. We'll be entirely reliant on trusting these systems, and trusting what they're telling us is going on\u2014since we'll have no ability of our own to pierce through what exactly they're doing anymore.\n    \n\n\n     The superintelligence we get by the end of it could be quite\n     \n      alien\n     \n     . We'll have gone through a decade or more of ML advances during the intelligence explosion, meaning the architectures and training algorithms will be totally different (with potentially much riskier safety properties).\n     \n\n\n\n\n        \u2013\n       \n       One example that's very salient to me: we may well bootstrap our way to human-level or somewhat-superhuman AGI with systems that reason via chains of thoughts, i.e. via English tokens. This is\n       \n        extraordinarily\n       \n       helpful, because it means the models \"think out loud\" letting us catch malign behavior (e.g., if it's scheming against us). But\n       \n        surely\n       \n       having AI systems think in tokens is not the most efficient means to do it,\n       \n        surely\n       \n       there's something much better that does all of this thinking via internal states\u2014and so the model by the end of the intelligence explosion will almost certainly\n       \n        not\n       \n       think out loud, i.e. will have completely uninterpretable reasoning.\n      \n\n\n\n\n     This will be an incredibly volatile period, potentially with the backdrop of an international arms race, tons of pressure to go faster, wild new capabilities advances every week with basically no human-time to make good decisions, and so on. We'll face tons of ambiguous data and high-stakes decisions.\n    \n\n\n\n\n    \u2013\n   \n   Think: \"We caught the AI system doing some naughty things in a test, but we adjusted our procedure a little bit to hammer that out. Our automated AI researchers tell us the alignment metrics look good, but we don't really understand what's going on and don't fully trust them, and we don't have any strong scientific understanding that makes us confident this will continue to hold for another couple OOMs. So, we'll\n   \n    probably\n   \n   be fine? Also China just stole our weights and they're launching their own intelligence explosion, they're right on our heels.\"\n  \n\n\n\n    It just really seems like this could go off the rails.\n   \n   To be honest, it sounds terrifying.\n  \n\n\n   Yes, we will have AI systems to help us. Just like they'll automate capabilities research, we can use them to automate alignment research. That will be key, as I discuss below. But\u2014can you trust the AI systems? You weren't sure whether they were aligned in the first place\u2014are they actually being honest with you about their claims about alignment science? Will automated alignment research be able to keep up with automated capabilities research (for example, because automating alignment is harder, e.g. because there are less clear metrics we can trust compared to improving model capabilities, or there's a lot of pressure to go full-speed on capabilities progress because of the international race)? And AI won't be able to fully substitute for the still-human decision makers making good calls in this incredibly high-stakes situation.\n  \n\n\n\n    The default plan: how we can muddle through\n   \n\n\n\n   I think we can harvest wins across a number of empirical bets, which I'll describe below, to align somewhat-superhuman systems. Then, if we're confident we can trust these systems, we'll need to use these somewhat-superhuman systems to automate alignment research\u2014alongside the automation of AI research in general, during the intelligence explosion\u2014to figure out how to solve alignment to go the rest of the way.\n  \n\n\n\n    Aligning somewhat-superhuman models\n   \n\n\n\n   Aligning human-level systems won't be enough. Even the first systems that can do automated AI research, i.e. start the intelligence explosion, will likely already be substantially superhuman in many domains. This is because AI capabilities are likely to be somewhat spikey\u2014by the time AGI is human-level at whatever a human AI researcher/engineer is worst at, it'll be superhuman at many other things. For example, perhaps the ability for AI systems to effectively coordinate and plan lags behind, meaning that by the time the intelligence explosion is in full force they'll probably already be superhuman coders, submitting million-line pull requests in new programming languages they devised, and they'll be superhuman at math and ML.\n  \n\n\n   These early-intelligence-explosion-systems will start being quantitatively and qualitatively superhuman, at least in many domains. But they'll look much closer to the systems we have today in terms of architecture, and the intelligence gap we need to cover is much more manageable. (Perhaps if humans trying to align true superintelligence is like a first grader trying to supervise a PhD graduate, this is more like a smart high schooler trying to supervise a PhD graduate.)\n  \n\n\n   More generally, the more we can develop good science now, the more we'll be in a position to verify that things aren't going off the rails during the intelligence explosion. Even having good metrics we can trust for superalignment is surprisingly difficult\u2014but without reliable metrics during the intelligence explosion, we won't know whether pressing on is safe or not.\n  \n\n\n   Here are some of the main research bets I see for crossing the gap between human-level and somewhat-superhuman systems.\n  \n\n\n   evaluation is easier than generation. We get some of the way \"for free,\" because it's easier for us to evaluate outputs (especially for egregious misbehaviors) than it is to generate them ourselves. For example, it takes me months or years of hard work to write a paper, but only a couple hours to tell if a paper someone has written is any good (though perhaps longer\n  \n\n\n   to catch fraud). We'll have teams of expert humans spend a lot of time evaluating every RLHF example, and they'll be able to \"thumbs down\" a lot of misbehavior even if the AI system is somewhat smarter than them. That said, this will only take us so far (GPT-2 or even GPT-3 couldn't detect nefarious GPT-4 reliably, even though evaluation is easier than generation!)\n  \n\n\n   scalable oversight. We can use AI assistants to help humans supervise other AI systems\u2014the human-AI team being able to extend supervision farther than the human could alone. For example, imagine an AI system generates 1M lines of complex code. It's easier for a human to double-check that a given line of code has a bug if an AI assistant has pointed out that (say) line 394,894 looks fishy, than it is for a human to find that same bug from scratch. A model trained to critique the code written by another model could thus help humans supervise a system with narrowly superhuman coding abilities.\n  \n\n\n   Several scalable oversight strategies have been proposed, including\n   \n    debate,\n   \n\n    market-making,\n   \n\n    recursive reward modeling,\n   \n   and\n   \n    prover-verifier games,\n   \n   as well as simplified versions of those ideas lik\n   \n    ecritiques.\n   \n   Models are now strong enough that it's possible to\n   \n    empirically\n   \n\n    test\n   \n   these ideas, making direct progress on scalable oversight.\n  \n\n\n   I expect this to help a lot for the \"quantitatively\" superhuman part of the problem, such as the aforementioned million-lines of code example. But I am less optimistic that scalable oversight techniques can really help for the \"qualitatively\" superhuman part of the problem\u2014imagine the model invents quantum physics when you only understand Newtonian physics.\n  \n\n\n   generalization. Even with scalable oversight, we won't be able to supervise AI systems on really hard problems, problems beyond human comprehension. However, we can study: how will the AI systems\n   \n    generalize\n   \n   from human supervision on easy problems (that we do understand and can supervise) to behave on the hard problems (that we can't understand and can no longer supervise)? For example, perhaps supervising a model to be honest in simple cases generalizes benignly to\n  \n\n\n   the model just being honest in general, even in cases where it's doing extremely complicated things we don't understand.\n  \n\n\n   There's a lot of reasons to be optimistic here: part of the magic of deep learning is that it often generalizes in benign ways (for example, RLHF'ing with only labels on English examples also tends to produce good behavior when it's speaking French or Spanish, even if that wasn't part of the training). I'm fairly optimistic that there will both be pretty simple methods that help nudge the models' generalization in our favor, and that we can develop a strong scientific understanding that helps us predict when generalization will work and when it will fail. To a greater extent that for scalable oversight, the hope is that this will help with alignment even in the \"qualitatively\" superhuman case.\n  \n\n\n   Here's another way of thinking about this: if a superhuman model is misbehaving, say breaking the law, intuitively\n   \n    the model should already know\n   \n   that it's breaking the law. Moreover, \"is this breaking the law\" is probably a pretty natural concept to the model\u2014and it will be salient in the model's representation space. The question then is: can we \"summon\" this concept from the model with only weak supervision?\n  \n\n\n   I'm particularly partial to this direction (and perhaps biased), because I helped introduce this with some recent work with some colleagues at OpenAI. In particular, we studied an analogy to the problem of humans supervising superhuman systems can a\n   \n    small model\n   \n   align a\n   \n    larger (smarter) model\n   \n   ? We found that generalization does actually get you cross some (but certainly not all) of the intelligence gap between supervisor and supervisee, and that in simple settings there's a lot you can do to improve it.\n  \n\n\n   interpretability. One intuitively-attractive way we'd hope to verify and trust that our AI systems are aligned is if we could understand what they're thinking! For example, if we're worried that AI systems are deceiving us or conspiring against us, access to their internal reasoning should help us detect that.\n  \n\n\n   By default, modern AI systems are inscrutable black boxes.\n  \n\n\n\n\n\n\n   Yet it seems like we should be able to do amazing \"digital neuroscience\"\u2014after all, we have perfect access to model internals.\n  \n\n\n   There's a few different approaches here, going from \"most ambitious and 'cool' but will be very hard\" to \"hackier things that are easier and might just work\".\n  \n\n\n\n    Mechanistic interpretability.\n   \n   Try to fully reverse-engineer large neural networks from the ground up\u2014fully disentangle the inscrutable matrices, so to speak.\n  \n\n\n   Chris Olah's team at Anthropic has done\n   \n    much of the pio\n   \n\n    neering work\n   \n   on this, starting by understanding simple mechanisms in very small models. There's\n   \n    incredibly exciting progress\n   \n   happening recently, and I'm thrilled about the overall level of activity in this space.\n  \n\n\n   That said, I'm worried fully reverse-engineering superhuman AI systems will just be an intractable problem\u2014similar, to, say \"fully reverse engineering the human brain\"\u2014and I'd put this work mostly in the \"ambitious moonshot for AI safety\" rather than \"default plan for muddling through\" bucket.\n   \n    91\n   \n\n\n\n   (Neel Nanda's 200\n   \n    open problems in mechanistic interpretabil\n   \n\n    ity\n   \n   also gives a flavor of this kind of research.)\n  \n\n\n   Figure 36: A simple analogy for studying superalignment: instead of a human supervising a superhuman model, we can study a small model supervising a large model. For example, can we align GPT-4 with only GPT-2 supervision? Will that result in GPT-4 appropriately generalizing \"what GPT-2 meant\"? From\n   \n    Weak-to-strong generalization.\n   \n\n\n\n\n    91\n   \n   Moreover, even recent progress in mechanistic interpretability to \"disentangle the features\" of models with sparse autoencoders doesn't on its own solve the problem of how to deal with superhuman models. For one, the model might simply \"think\" in superhuman concepts you don't understand. Moreover, how do you know which feature is the one you want? You still don't have ground truth labels. For example, there might be tons of different features that look like the \"truth feature\" to you, one of which is \"what the model actually knows\" and the others being \"what would xyz human think\" or \"what do the human raters want me to think\" etc.\n  \n\n\n   Sparse autoencoders won't be enough on their own, but they will be a tool an incredibly helpful tool!\u2014that ultimately has to cash out in helping with things like the science of generalization.\n  \n\n\n\n    \"Top-down\" interpretability.\n   \n   If mechanistic interpretability tries to reverse engineer neural networks \"from the bottom up,\" other work takes a more targeted, \"top-down\" approach, trying to locate information in a model without full understanding of how it is processed.\n  \n\n\n   For example, we might try to build an \"AI lie detector\" by identifying the parts of the neural net that \"light up\" when an AI system is lying. This can be a lot more tractable (even if it gives less strong guarantees).\n  \n\n\n   Over the past couple of years, there's been a flurry of exciting work in this area.\n   \n    CCS\n   \n   is able to identify a \"truth direction\" in models with only unsupervised data.\n   \n    92\n   \n\n    ROME\n   \n   is able to\n   \n    92\n   \n   Essentially, needing only the conidentify the part of the model that knows the Eiffel Tower is in Paris\u2014and then directly edit the model's knowledge to place the Eiffel Tower in Rome.\n   \n    Representation Engineering\n   \n   and\n   \n    Inference-time Interventions\n   \n   demonstrate using top-down techniques to detect lying and hallucinations and surgically control model behavior on jailbreaking, power-seeking, fairness, truthfulness, and more. There's\n   \n    other creative work\n   \n   on lie detection that doesn't even require model internals.\n  \n\n\n   I'm increasingly bullish that top-down interpretability techniques will be a powerful tool\u2014i.e., we'll be able to build something like an \"AI lie detector\"93\u2014and without requiring funda-\n   \n    93\n   \n   I'm still worried about the scalability mental breakthroughs in understanding neural nets.\n  \n\n\n\n    Chain-of-thought interpretability.\n   \n   As mentioned earlier, I think it's quite plausible that we'll bootstrap our way to AGI with systems that \"think out loud\" via chains of thought. Even if it's not the most efficient algorithm in the limit (I'd be very surprised if superintelligence still used English-chain-of-thought, rather than thinking via some sort of recurrent internal states), we may well still benefit from this property for the first AGIs. This would be an incredible boon for interpretability: we'd have access to the AGI's \"internal monologue\"! That would make it relatively easy to detect egregious alignment failures.\n  \n\n\n   There's a ton of work to do here, however, if we wanted to rely on this. How do we ensure that the CoT remains\n   \n    legible\n   \n   ? (It\n  \n\n\n   sistency properties of truth, rather than strong/ground truth labels of true/false, which we won't have for superhuman systems.\n  \n\n\n   of a lot of these techniques to very superhuman models\u2014I think explicitly or implicitly they mostly rely on groundtruth labels, i.e. a supervisor smarter than the model, and/or favorable generalization.\n  \n\n\n   may simply drift from understandable English to unintelligible\n   \n    model-speak,\n   \n   depending on how we e.g. use RL to train models\u2014can we add some simple constraints to ensure it remains legible?) How do we ensure the CoT is\n   \n\n     faithful\n    \n\n   , i.e. actually reflects what models are thinking? (E.g, there's\n   \n    some\n   \n\n    work\n   \n   that shows in certain situations, models will just make up posthoc reasoning in their CoT that don't actually reflect their actual internal reasoning for an answer.)\n  \n\n\n   My best guess is that some simple measurement of legibility and faithfulness, and some simple hacks to preserve legibility and faithfulness longer, could go quite far. Yes, this won't work in some worlds, and it's a bit of a simple hack, but it's such low-hanging fruit; this direction is criminally underrated in my view.\n  \n\n\n   adversarial testing and measurements. Along the way, it's going to be critical to stress test the alignment of our systems at every step\u2014our goal should be to encounter every failure mode in the lab before we encounter it in the wild. This will require substantially advancing techniques for\n   \n    automated\n   \n\n    red-teaming.\n   \n   For example, if we deliberately plant backdoors or misalignments into models, would our safety training would have caught and gotten rid of them? (Early work suggests that\n   \n    \"sleeper agents\"\n   \n   can survive through safety training, for example.)\n  \n\n\n   More generally, it'll be critical to have good measurements of alignment. Does the model have the power to be misaligned? For example, does it have long-horizon goals, and what sorts of drives it is learning? And what are clear \"red lines\"? For example, a very intuitive bound might be \"model reasoning (chain of thoughts) always has to remain legible and faithful.\" (As Eric Schmidt\n   \n    says,\n   \n   the point at which AI agents can talk to each other in a language we can't understand, we should unplug the computers.) Another might be developing better measurements for whether models are being fully honest.\n  \n\n\n   The science of measuring alignment is still in its infancy; improving this will be critical for helping us make the right tradeoffs on risk during the intelligence explosion. Doing the science\n  \n\n\n   that lets us measure alignment and gives us an understanding of \"what evidence would be sufficient to assure us that the next OOM into superhuman territory is safe?\" is among the veryhighest priority work for alignment research today (beyond just work that tries to extend RLHF further to \"somewhatsuperhuman\" systems). See also\n   \n    this writeup of superalignment\n   \n\n\n\n\n    research directions\n   \n   for the Superalignment Fast Grants call-for-proposals.\n  \n\n\n\n    Automating alignment research\n   \n\n\n\n   Ultimately, we're going to need to automate alignment research. There's no way we'll manage to solve alignment for true superintelligence directly; covering that vast of an intelligence gap seems extremely challenging. Moreover, by the end of the intelligence explosion\u2014after 100 million automated AI researchers have furiously powered through a decade of ML progress\u2014I expect much more alien systems in terms of architecture and algorithms compared to current system (with potentially less benign properties, e.g. on legibility of CoT, generalization properties, or the severity of misalignment induced by training).\n  \n\n\n   But we also don't have to solve this problem just on our own. If we manage to align somewhat-superhuman systems enough to trust them, we'll be in an incredible position: we'll have millions of automated AI researchers, smarter than the best AI researchers, at our disposal. Leveraging these army of automated researchers properly to solve alignment for even-more superhuman systems will be decisive.\n  \n\n\n   (This applies more generally, by the way, for the full spectrum of AI risks, including misuse and so on. The best route perhaps the only route\u2014to AI safety in all of these cases, will involve properly leveraging early AGIs for safety; for example, we should put a bunch of them to work on automated research to improve security against foreign actors exfiltrating weights, others on shoring up defenses against worst-case bioattacks, and so on.)\n  \n\n\n   Getting automated alignment right during the intelligence explosion will be extraordinarily high-stakes: we'll be going through many years of AI advances in mere months, with little\n  \n\n\n   human-time to make the right decisions, and we'll start entering territory where alignment failures could be catastrophic. Labs should be willing to commit a large fraction of their compute to automated alignment research (vs. automated capabilities research) during the intelligence explosion, if necessary. We'll need strong guarantees that let us trust the automated alignment research being produced and much better measurements for misalignment than we have today to know whether we're still in the clear. For every OOM we want to ascend, we will need to have extremely high confidence in our alignment approaches for that next OOM.\n  \n\n\n   Most of all, getting this right will require an extreme degree of competence, seriousness, and willingness to make hard tradeoffs. Once we're approaching true superintelligence, the stakes get very real, and failure\u2014rogue AI\u2014could be catastrophic. There will be moments with ambiguous evidence, when metrics will superficially look ok, but there are some warning signs that hint at looming danger, and we mostly don't have a clue what's going on anymore. Navigating this situation responsibly will require making very costly tradeoffs. Eventually, the decision to greenlight the next generation of superintelligence will need to be taken as seriously as the decision to launch a military operation.\n  \n\n\n\n    Superdefense\n   \n\n\n\n   \"Getting alignment right\" should only be the first of many layers of defense during the intelligence explosion. Alignment will be hard; there\n   \n    will\n   \n   be failures along the way. If at all possible, we need to be in a position where alignment can fail\u2014but failure wouldn't be catastrophic. This could mean:\n  \n\n\n   \u2022\n   \n    Security.\n   \n   An airgapped cluster is the first layer of defense against superintelligence attempting to self-exfiltrate and doing damage in the real world. And that's only the beginning; we'll need much more extreme security against model selfexfiltration\n   \n    94\n   \n   across the board, from hardware encryption to\n   \n    94\n   \n   A model stealing its own weights, original datacenter. many-key signoff.\n   \n    95\n   \n   And once our AGIs can do automated\n  \n\n\n   to make copies of itself outside of the\n  \n\n\n\n    95\n   \n   protecting against humans fooled or persuaded by the AI to help it exfiltrate\n  \n\n\n   R&D, we should put them to work on further hardening security as well.\n  \n\n\n\n\n\n\n\n      Monitoring.\n     \n     If our AI systems are up to something fishy or malevolent\u2014or a rogue employee tries to use them for unauthorized activities\u2014we need to be able to catch it. However, this is not a trivial task: we will have millions of AGI instances running our cluster, executing complex code and so on. We will need advanced monitoring systems that leverage the models themselves, including monitoring model outputs, chains of thought, model-written code, server/network activity, and interactions with researchers/other humans; essentially, leveraging some AI systems to nark on other AI systems. Moreover, we'll want to develop and employ sophisticated\n     \n      \"control\" protocols,\n     \n     using less powerful but trusted models to protect against subversion from more powerful but less trusted models. This may require, for example, dedicating the same amount of compute to monitoring model instances as to compute for active model instances.\n    \n\n\n\n      Targeted capability limitations.\n     \n     As much as possible, we should try to limit the model's capabilities in targeted ways that reduce fallout from failure. A central example of this might be scrubbing everything related to biology and chemistry from model training (or using\n     \n      \"unlearning\"\n     \n     techniques); this helps cut off paths to catastrophic real world damage that occur via biological and chemical weapons\n    \n\n\n\n      Targeted training method restrictions.\n     \n     There are likely some ways of training models that are inherently riskier\u2014more likely to produce severe misalignments\u2014than others. For example, imitation learning seems relatively safe (hard to see how that would lead to models that have dangerous longterm internal goals), while we should avoid long-horizon outcome-based RL (which seems much more likely to lead to the model learning undesirable long-term goals) as long as possible. We should also avoid training against our interpretability methods and our monitoring setup (such that our models aren't simply trained to work around these). There might be additional desirable limitations, for example, maintaining legible and faithful chains of thought as long as\n    \n\n\n\n   possible. We should define these constraints ahead of time, maintain them as long as we can throughout the intelligence explosion, and only drop them if absolutely necessary.\n  \n\n\n   \u2022 And there's likely a lot more possible here.\n  \n\n\n   Will these be foolproof? Not at all. True superintelligence is likely able to get around most-any security scheme for example. Still, they buy us a lot more margin for error\u2014and we're going to need any margin we can get. We'll want to use that margin to get in a position where we have very high confidence in our alignment techniques, only relaxing \"superdefense\" measures (for example, deploying the superintelligence in nonairgapped environments) concomitant with our confidence.\n  \n\n\n   Things will get dicey again once we move to deploying these AI systems in less-controlled settings, for example in military applications. It's likely circumstances will force us to do this fairly quickly, but we should always try to buy as much margin for error as much as possible\u2014for example, rather than just directly deploying the superintelligences \"in the field\" for military purposes, using them to do R&D in a more isolated environment, and only deploying the specific technologies they invent (e.g., more limited autonomous weapons systems that we're more confident we can trust).\n  \n\n\n\n    Why I'm optimistic, and why I'm scared\n   \n\n\n\n   I'm incredibly bullish on the technical tractability of the superalignment problem. It feels like there's tons of low-hanging fruit everywhere in the field. More broadly, the empirical realities of deep learning have shaken out more in our favor compared to what some speculated 10 years ago. For example, deep learning\n   \n    generalizes\n   \n   surprisingly benignly in many situations: it often just \"does the thing we meant\" rather than picking up some abstruse malign behavior.\n   \n    96\n   \n   Moreover, while\n   \n    96\n   \n   Though, of course, while that may fully understanding model internals will be hard, at least for the initial AGIs we have a decent shot of interpretability\u2014we can get them to reason transparently via chains of thought, and\n  \n\n\n   apply to current models and perhaps human-level systems, we have to be careful about attempting to extrapolate evidence from current models to future vastly superhuman models.\n  \n\n\n   hacky techniques like representation engineering work surprisingly well as \"lie detectors\" or similar.\n  \n\n\n   I think there's a pretty reasonable shot that \"the default plan\" to align \"somewhat-superhuman\" systems will mostly work.\n   \n    97\n   \n\n    97\n   \n   To be clear, given the stakes, I think Of course, it's one thing to speak about a \"default plan\" in the abstract\u2014it's another if the team responsible for executing that plan is you and your 20 colleagues (much more stressful!).\n   \n    98\n   \n\n    98\n   \n   I'm reminded of Scott Aaronson's There's still an incredibly tiny number of people seriously working on solving this problem, maybe a few dozen serious researchers.\n   \n    Nobody's on the ball!\n   \n   There's so much interesting and productive ML research to do on this, and the gravity of the challenge demands a much more concerted effort than what we're currently putting forth.\n  \n\n\n   But that's just the first part of the plan\u2014what really keeps me up at night is the intelligence explosion. Aligning the first AGIs, the first somewhat-superhuman systems, is one thing. Vastly superhuman, alien superintelligence is a new ballgame, and it is a\n   \n    scary\n   \n   ballgame.\n  \n\n\n   The intelligence explosion will be more like running a war than launching a product. We're not on track for superdefense, for an airgapped cluster or any of that; I'm not sure we would even realize if a model self-exfiltrated. We're not on track for a sane chain of command to make any of these insanely high-stakes decisions, to insist on the very-high-confidence appropriate for superintelligence, to make the hard decisions to take extra time before launching the next training run to get safety right or dedicate a large majority of compute to alignment research, to recognize danger ahead and avert it rather than crashing right into it. Right now, no lab has demonstrated much of a willingness to make any costly tradeoffs to get safety right (we get lots of safety committees, yes, but those are pretty meaningless). By default, we'll probably stumble into the intelligence explosion and have gone through a few OOMs before people even realize what we've gotten into.\n  \n\n\n   We're counting way too much on luck here.\n  \n\n\n   \"muddling through\" is in some sense a terrible plan. But it might be all we've got.\n  \n\n\n\n    letter to his younger self:\n   \n\n\n\n   \"There's a company building an AI that fills giant rooms, eats a town's worth of electricity, and has recently gained an astounding ability to converse like people. It can write essays or poetry on any topic. It can ace collegelevel exams. It's daily gaining new capabilities that the engineers who tend to the AI can't even talk about in public yet. Those engineers do, however, sit in the company cafeteria and debate the meaning of what they're creating. What will it learn to do next week? Which jobs might it render obsolete? Should they slow down or stop, so as not to tickle the tail of the dragon? But wouldn't that mean someone else, probably someone with less scruples, would wake the dragon first? Is there an ethical obligation to tell the world more about this? Is there an obligation to tell it less?\n  \n\n\n   I am\u2014you are\u2014spending a year working at that company. My job your job\u2014is to develop a mathematical theory of how to prevent the AI and its successors from wreaking havoc. Where \"wreaking havoc\" could mean anything from turbocharging propaganda and academic cheating, to dispensing bioterrorism advice, to, yes, destroying the world.\"\n  \n\n\n\n    IIId. The Free World Must Prevail\n   \n\n\n\n\n    Superintelligence will give a decisive economic and military advantage. China isn't at all out of the game yet. In the race to AGI, the free world's very survival will be at stake. Can we maintain our preeminence over the authoritarian powers? And will we manage to avoid self-destruction along the way?\n   \n\n\n\n\n\n    The story of the human race is War. Except for brief and precarious interludes, there has never been peace in the world; and before history began, murderous strife was universal and unending.\n   \n\n\n\n   . . .\n  \n\n\n   Might not a bomb no bigger than an orange be found to possess a secret power to destroy a whole block of buildings \u2014 nay, to concentrate the force of a thousand tons of cordite and blast a township at a stroke?\n  \n\n\n\n\n    winston churchill \"Shall We All Commit Suicide?\" (1924)\n   \n\n\n\n   Superintelligence will be the most powerful technology and most powerful weapon\u2014-mankind has ever developed. It will give a decisive military advantage, perhaps comparable only with nuclear weapons. Authoritarians could use superintelligence for world conquest, and to enforce total control internally. Rogue states could use it to threaten annihilation. And though many count them out, once the CCP wakes up to AGI it has a clear path to being competitive (at least until and unless we drastically improve US AI lab security).\n  \n\n\n   Every month of lead will matter for safety too. We face the\n  \n\n\n   greatest risks if we are locked in a tight race, democratic allies and authoritarian competitors each racing through the alreadyprecarious intelligence explosion at breakneck pace\u2014forced to throw any caution by the wayside, fearing the other getting superintelligence first. Only if we preserve a healthy lead of democratic allies will we have the margin of error for navigating the extraordinarily volatile and dangerous period around the emergence of superintelligence. And only American leadership is a realistic path to developing a nonproliferation regime to avert the risks of self-destruction superintelligence will unfold.\n  \n\n\n   Our generation too easily takes for granted that we live in peace and freedom. And those who herald the age of AGI in SF too often ignore the elephant in the room: superintelligence is a matter of national security, and the United States must win.\n  \n\n\n\n    Whoever leads on superintelligence will have a decisive military advantage\n   \n\n\n\n   Superintelligence is not just any other technology\u2014hypersonic missiles, stealth, and so on\u2014where US and liberal democracies' leadership is highly desirable, but not strictly necessary. The military balance of power can be kept if the US falls behind on one or a couple such technologies; these technologies matter a great deal, but can be outweighed by advantages in other areas.\n  \n\n\n   The advent of superintelligence will put us in a situation unseen since the advent of the atomic era: those who have it will wield complete dominance over those who don't.\n  \n\n\n   I've previously discussed the vast power of superintelligence. It'll mean having billions of automated scientists and engineers and technicians, each much smarter than the smartest human scientists, furiously inventing new technologies, day and night. The acceleration in scientific and technological development will be extraordinary. As superintelligence is applied to R&D in military technology, we could quickly go through decades of military technological progress.\n  \n\n\n\n    The Gulf War, or: What a few-decades-worth of technological lead implies for military power\n   \n\n\n\n   The Gulf War provides a helpful illustration of how a 20- 30 year lead in military technology can be decisive. At the time, Iraq commanded the fourth-largest army in the world. In terms of\n   \n    numbers\n   \n   (troops, tanks, artillery), the US-led coalition barely matched (or was outmatched) by the Iraqis, all while the Iraqis had had ample time to entrench their defenses (a situation that would normally require a 3:1, or 5:1, advantage in military manpower to dislocate).\n  \n\n\n   But the US-led coalition\n   \n    obliterated\n   \n   the Iraqi army in a merely 100-hour ground war. Coalition dead\n   \n    numbered\n   \n   a mere 292, compared to 20k-50k Iraqi dead and hundreds of thousands of others wounded or captured. The Coalition lost a mere 31 tanks, compared to the destruction of over 3,000 Iraqi tanks.\n  \n\n\n   The difference in technology wasn't godlike or unfathomable, but it was utterly and completely decisive: guided and smart munitions, early versions of stealth, better sensors, better tank scopes (to see farther in the night and in dust storms), better fighter jets, an advantage in reconnaissance, and so on.\n  \n\n\n   (For a more recent example, recall Iran launching a massive attack of 300 missiles at Israel, \"99\n   \n    %\"\n   \n   of which were intercepted by superior Israel, US, and allied missile defense.)\n  \n\n\n   A lead of a year or two or three on superintelligence could mean as\n   \n    utterly decisive\n   \n   a military advantage as the US coalition had against Iraq in the Gulf War. A complete reshaping of the military balance of power will be on the line.\n  \n\n\n   Imagine if we had gone through the military technological developments of the 20th century in less than a decade. We'd have gone from horses and rifles and trenches, to modern tank armies, in a couple years; to armadas of supersonic fighter planes and nuclear weapons and ICBMs a couple years after\n  \n\n\n   that; to stealth and precision that can knock out an enemy before they even know you're there another couple years after that.\n  \n\n\n   That is the situation we will face with the advent of superintelligence: the military technological advances of a century compressed to less than a decade. We'll see superhuman hacking that can cripple much of an adversary's military force, roboarmies and autonomous drone swarms, but more importantly completely new paradigms we can't yet begin to imagine, and the inventions of new WMDs with thousandfold increases in destructive power (and new WMD defenses too, like impenetrable missile defense, that rapidly and repeatedly upend deterrence equilibria).\n  \n\n\n   And it wouldn't just be technological progress. As we solve robotics, labor will become fully automated, enabling a broader industrial and\n   \n    economic explosion,\n   \n   too. It is plausible growth rates could go into the 10s of percent a year; within at most a decade, the GDP of those with the lead would trounce those behind. Rapidly multiplying robot factories would mean not only a drastic technological edge, but also production capacity to dominate in pure materiel. Think millions of missile interceptors; billions of drones; and so on.\n  \n\n\n   Of course, we don't know the limits of science and the many frictions that could slow things down. But no godlike advances are necessary for a decisive military advantage. And a billion superintelligent scientists will be able to do\n   \n    a lot. It seems clear that within a matter of years, pre-superintelligence militaries would become hopelessly outclassed\n   \n   .\n  \n\n\n\n    The military advantage would be decisive even against nuclear deterrents\n   \n\n\n\n   To be even clearer: it seems likely the advantage conferred by superintelligence would be decisive enough even to preemptively take out an adversary's nuclear deterrent. Improved sensor networks and analysis could locate even the quietest current nuclear submarines (similarly for mobile missile launchers). Millions or billions of mouse-sized\n  \n\n\n   autonomous drones, with advances in stealth, could infiltrate behind enemy lines and then surreptitiously locate, sabotage, and decapitate the adversary's nuclear forces. Improved sensors, targeting, and so on could dramatically improve missile defense (similar to, say, the Iran vs. Israel example above); moreover, if there is an industrial explosion, robot factories could churn out thousands of interceptors for each opposing missile. And all of this is without even considering completely new scientific and technological paradigms (e.g.,\n   \n    remotely deactivating\n   \n   all the nukes).\n  \n\n\n   It would simply be no contest. And not just no contest in the nuclear sense of \"we could mutually destroy each other,\" but no contest in terms of being able to obliterate the military power of a rival without taking significant casualties. A couple years of lead on superintelligence would mean complete dominance.\n  \n\n\n   If there is a rapid intelligence explosion, it's plausible a lead of mere\n   \n    months\n   \n   could be decisive: months could mean the difference between roughly human-level AI systems and substantially superhuman AI systems. Perhaps possessing those initial superintelligences alone, even before being broadly deployed, would be enough for a decisive advantage, e.g. via superhuman hacking abilities that could shut down presuperintelligence militaries, more limited drone swarms that threaten instant death for every opposing leader, official, and their families, and advanced bioweapons developed with AlphaFold-style simulation that could target specific ethnic groups, e.g. anybody but Han Chinese (or simply withhold the cure from the adversary).\n  \n\n\n\n    China can be competitive\n   \n\n\n\n   Many seem complacent about China and AGI. The chip export controls have neutered them, and the leading AI labs are in the US and the UK\u2014so we don't have much to worry about, right? Chinese LLMs are\n   \n    fine\n   \n   \u2014they are definitely capable of training large models!\u2014but they are at best comparable to the\n  \n\n\n   second tier of US labs.\n   \n    99\n   \n   And even Chinese models are often\n   \n    99\n   \n   For example, Yi-Large\n   \n    seems to be\n   \n   mere ripoffs of American open source releases (for example, the Yi-34B architecture\n   \n    seems to have\n   \n   essentially the Llama2 architecture, with merely a\n   \n    few lines of code changed\n   \n   100). Chi-\n   \n    100\n   \n   Similarly, Qwen hugging face code nese deep learning\n   \n    used to be\n   \n   more important than it is today (for example\n   \n    Baidu published\n   \n   one of the first modern scaling law papers), and while China\n   \n    publishes more papers\n   \n   in AI than the US, they don't seem to have driven any of the key breakthroughs in recent years.\n  \n\n\n   That's all merely a prelude, however. If and when the CCP wakes up to AGI, we should expect extraordinary efforts on the part of the CCP to compete. And I think there's a pretty clear path for China to be in the game: outbuild the US and steal the algorithms.\n  \n\n\n   1. compute\n  \n\n\n\n    1a. Chips:\n   \n   China now seems to have demonstrated the ability to\n   \n    manufacture\n   \n   7nm chips. While going beyond 7nm will be difficult (requiring EUV), 7nm is enough! For reference, 7nm is what Nvidia A100s used. The indigenous Huawei Ascend 910B, based on the SMIC 7nm platform, seems to only be ~2-3x worse on performance/$ than an equivalent Nvidia chip would be.\n   \n    101\n   \n\n    101\n   \n   The Huawei Ascend\n   \n    910\n   \n   B seems to\n  \n\n\n   The\n   \n    yield\n   \n   of SMIC's 7nm production and the general maturity of Chinese abilities here is debated,\n   \n    102\n   \n   and a critical open question is in what quantities they could produce these 7nm chips.\n   \n    103\n   \n   Still, it seems like there's at least a very reasonable chance they'll be able to do this at large scale in a few years.\n  \n\n\n   Most of the gains in AI chips have come from improved chip design adapting them for AI use cases (and China likely already steals Nvidia chip designs from the Taiwan supply chain104). 7nm vs. 3nm or 2nm, and their general fab immaturity, probably makes things more expensive for China.\n   \n    105\n   \n   But that seems by no means fatal; you can make very good AI chips on top of a 7nm process. I wouldn't have high confidence at this point, for example, that they couldn't just spend a bit more and get ample compute for the $100B+ and trillion-dollar\n  \n\n\n   a GPT-4-class model on LMSys, but that's over a year after OpenAI released GPT-4.\n  \n\n\n   cites Mistral a lot, and it seems that Chinese LLM dependence on American open-source is an\n   \n    explicit worry\n   \n   that has made its way to the Chinese Premier.\n  \n\n\n\n    cost around\n   \n   120,000 yuan per card, or about $17k. This is\n   \n    produced on the\n   \n\n    SMIC\n   \n   7nm node, while performing similarly to an A100. H100s are maybe ~3x better than A100s, while costing somewhat more ($20-25k ASP), suggesting only a ~2-3x cost increase for equivalent AI GPU performance for China right now.\n  \n\n\n\n    102\n   \n   For example, they're still using Western HBM memory (which for some reason is not export controlled?), though\n   \n    CXMT is said to be sampling\n   \n\n    HBM\n   \n   next year.\n  \n\n\n\n    103\n   \n   Though, since they can still import other types of chips from the West, they could simply direct the entirety of their 7nm node to AI chips, making up for lower overall production.\n  \n\n\n\n    104\n   \n   Notably, even cybercriminals were able to\n   \n    hack Nvidia\n   \n   and get\n   \n    key GPU\n   \n\n    design\n   \n   secrets. Moreover,\n   \n    TPUv\n   \n   6\n   \n    designs were apparently among what\n   \n\n    was stolen\n   \n   by the recently-indicted Chinese national at Google.\n  \n\n\n\n    105\n   \n   For example, maybe these are 2x worse on perf/$ or perf/Watt. In turn, that also means to achieve the same overall datacenter performance, you need more power, and need more chips networked together, which also makes things more of a hassle.\n  \n\n\n   training clusters in a few years.\n   \n    106\n   \n\n    106\n   \n   Note that even\n   \n    3\n   \n   x more on chips\n  \n\n\n\n    1b. Outbuilding the US:\n   \n   The binding constraint on the largest training clusters won't be chips, but industrial mobilization perhaps most of all the 100GW of power for the trillion-dollar cluster. But if there's one thing China can do better than the US it's\n   \n    building stuff.\n   \n\n\n\n   In the last decade, China has roughly built as much new electricity capacity as\n   \n    the entire US capacity\n   \n   (while US capacity has remained basically flat). In the US, these things get stuck in environmental review, permitting, and regulation for a decade first. It thus seems quite plausible that China will be able to simply outbuild the US on the largest training clusters.\n  \n\n\n\n\n\n\n   would be much less than that in terms of increase in datacenter costs. Actual logic fab costs are <5% of Nvidia GPU cost, and even considering memory and CoWoS it's less than 20% of the Nvidia pricetag due to their margin. And even GPUs themselves tend to be only 50-60% of the cost of a datacenter. So 3x more expensive on the chip fab end might translate into much, much less than a 3x increase in overall cost. Even for 10x more expensive chips, it seems like China could stomach that without hugely increasing datacenter costs.\n  \n\n\n   Figure 37: The AI power buildout for 2030 seems much more doable for China than the US. Based on earlier estimates from IIIa. Racing to the Trillion-Dollar Cluster\n  \n\n\n   2. algorithms\n  \n\n\n   As discussed extensively in Counting the OOMs, scaling compute is only part of the story: algorithmic advances probably contribute at least half of AI progress. We're developing the key algorithmic breakthroughs for AGI\n   \n    right now\n   \n   (essentially the EUV of algorithms because of the data wall).\n  \n\n\n   By default, I expect Western labs to be well ahead; they have much of the key talent, and in recent years have developed all of the key breakthroughs. The size of the advantage may well be equivalent to a 10x (or even 100x) bigger cluster in a few years; this would provide the United States with a reasonably comfortable lead.\n  \n\n\n   And yet, on the current course, we will completely surrender this advantage: as discussed extensively in the security section, the current state of security essentially makes it trivial for China to infiltrate American labs. And so, unless we lock down the labs very soon, I expect China to be able to simply steal the key algorithmic ingredients for AGI, and match US capabilities.\n   \n    107\n   \n\n    107\n   \n   Some argue that even if China stole\n  \n\n\n   (Even worse, if we don't improve security, there is an even more salient path for China to compete. They won't even need to train their own AGI: they'll just be able to steal the AGI weights directly. Once they've stolen a copy of the automated AI researcher, they'll be off to the races, and can launch their own intelligence explosion. If they're willing to apply less caution\u2014both good caution, and unreasonable regulation and delay\u2014than the US, they could race through the intelligence explosion more quickly, outrunning us to superintelligence.)\n  \n\n\n   To date, US tech companies have made a much bigger bet on AI and scaling than any Chinese efforts; consequently, we are well ahead. But counting out China now is a bit like counting out Google in the AI race when ChatGPT came out in late 2022. Google hadn't yet focused their efforts in an intense AI bet, and it looked as though OpenAI was far ahead\u2014but once Google woke up, a year and half later, they are putting up a very serious fight. China, too, has a clear path to putting up a very serious fight. If and when the CCP mobilizes in the race to AGI, the picture could start looking very different.\n  \n\n\n   Perhaps the Chinese government will be incompetent; perhaps they decide AI threatens the CCP and impose\n   \n    stifling regula\n   \n\n    tion.\n   \n   But I wouldn't count on it.\n  \n\n\n   these secrets, they wouldn't be able to compete because it requires tacit knowledge. I disagree. I think of this as having two layers. The bottom layer is the engineering prowess for large-scale training runs; these training runs can be hacky and delicate and requires tacit knowledge. But as I'll discuss later, Chinese AI efforts have shown themselves perfectly capable of training large-scale models, and I think they will have this tacit knowledge indigenously. The top layer is the algorithmic recipe\u2014things like model architecture, the right scaling laws, etc.\u2014that could be conveyed in a one-hour call. These compute multipliers are usually discrete changes, meaning the underlying tacit knowledge for large-scale training runs should transfer. I don't think \"tacit knowledge\" will be a decisive barrier for Chinese AGI efforts.\n  \n\n\n   I, for one, think we need to operate under the assumption that we will face a full-throated Chinese AGI effort. As every year we get dramatic leaps in AI capability, as we start seeing early automation of software engineers, as AI revenue explodes and we start seeing $10T valuations and trillion-dollar cluster buildouts, as a broader consensus starts to form that we are on the cusp of AGI\u2014the CCP will take note. Much as I expect these leaps to wake up the USG to AGI, I would expect it to wake up the CCP to AGI\u2014and to wake up to what being behind on AGI would mean for their national power.\n  \n\n\n   They will be a formidable adversary.\n  \n\n\n\n    The authoritarian peril\n   \n\n\n\n   A dictator who wields the power of superintelligence would command concentrated power unlike any we've ever seen. In addition to being able to impose their will on other countries, they could enshrine their rule internally. Millions of AIcontrolled robotic law enforcement agents could police their populace; mass surveillance would be hypercharged; dictatorloyal AIs could individually assess every citizen for dissent, with advanced near-perfect lie detection rooting out any disloyalty.\n  \n\n\n   Most importantly, the robotic military and police force could be wholly controlled by a single political leader, and programmed to be perfectly obedient\u2014no more risk of coups or popular rebellions.\n  \n\n\n   Whereas past dictatorships were never permanent, superintelligence could eliminate basically all historical threats to a dictator's rule and lock in their power (cf\n   \n    value lock-in)\n   \n   . If the CCP gets this power, they could enforce the Party's conception of \"truth\" totally and completely.\n  \n\n\n   To be clear, I don't just worry about dictators getting superintelligence because \"our values are better.\" I believe in freedom and democracy, strongly, because I don't know what the right values are. In the long arc of history,\n   \n    \"time has upset many\n   \n\n\n\n\n    fighting faiths.\n   \n   \" I believe we should\n   \n    place our faith in mech\n   \n\n    anisms of error correction,\n   \n   experimentation, competition, and adaption.\n  \n\n\n   Superintelligence will give those who wield it the power to crush opposition, dissent, and lock in their grand plan for humanity. It will be difficult for anyone to resist the terrible temptation to use this power. I hope, dearly, that we can instead rely on the wisdom of the Framers\u2014letting radically different values flourish, and preserving the raucous plurality that has defined the American experiment.\n  \n\n\n   At stake in the AGI race will not just be the advantage in some far-flung proxy war, but whether freedom and democracy can survive for the next century and beyond. The course of human history is as brutal as it is clear. Twice in the 20th century tyranny threatened the globe; we must be under no delusion that this threat is banished forever. For many of my young friends, freedom and democracy feel like a given\u2014but they are not. By far the most common political system in history is authoritarianism.\n   \n    108\n   \n\n    108\n   \n   Primarily monarchy.\n  \n\n\n   I genuinely do not know the intentions of the CCP and their authoritarian allies. But, as a reminder: the CCP is a regime founded on the\n   \n    continued worship\n   \n   of perhaps the\n   \n    greatest to\n   \n\n    talitarian mass-murderer\n   \n   in human history (\"with estimates ranging from 40 to 80 million victims due to starvation, persecution, prison labor, and mass executions\"); a regime that recently put a million Uyghurs in\n   \n    concentration camps\n   \n   and\n   \n    crushed\n   \n   a free Hong Kong; a regime that systematically practices mass surveillance for social control, both of the\n   \n    new\n   \n\n    fangled\n   \n   (tracking phones, DNA databases, facial recognition, and so on) and the\n   \n    old-fangled\n   \n   (recruiting an army of citizens to report on their neighbors) kind; a regime that ensures\n   \n    all\n   \n\n    text messages\n   \n   pass through a censor, and that goes so far to repress dissent as to\n   \n    pull families into police stations\n   \n   when their child overseas attends a protest; a regime that\n   \n    has cemented\n   \n   Xi Jinping as dictator-for-life; a regime that touts its aims to militarily crush and\n   \n    \"reeducate\"\n   \n   a free neighboring nation; a regime that\n   \n    explicitly seeks\n   \n   a China-centric world order.\n  \n\n\n\n\n\n\n    The free world must prevail over the authoritarian powers in this race.\n   \n   We owe our peace and freedom to American economic and military preeminence. Perhaps even empowered with superintelligence, the CCP will behave responsibly on the international stage, leaving each to their own. But the history of dictators of their ilk is not pretty. If America and her allies fail to win this race, we risk it all.\n  \n\n\n\n    Maintaining a healthy lead will be decisive for safety\n   \n\n\n\n   It is the cursed history of science and technology that as they have unfolded their wonders, they have also expanded the means of destruction: from sticks and stones, to swords and spears, rifles and cannons, machine guns and tanks, bombers and missiles, nuclear weapons. The \"destruction/$\" curve has consistently gone down as technology has advanced. We should expect the rapid technological progress post-superintelligence to follow this trend.\n  \n\n\n   Perhaps dramatic advances in biology will yield extraordinary new bioweapons, ones that spread silently, swiftly, before killing with perfect lethality on command (and that can be made extraordinarily cheaply, affordable even for terrorist groups). Perhaps new kinds of nuclear weapons enable the size of nuclear arsenals to increase by orders of magnitude, with new delivery mechanisms that are undetectable. Perhaps mosquito-sized drones, each carrying a deadly poison, could be targeted to kill every member of an opposing nation. It's hard to know what a century's worth of technological progress would yield\u2014but I am confident it would unfold appalling possibilities.\n  \n\n\n   Humanity barely evaded self-destruction during the Cold War. On the historical view, the greatest existential risk posed by AGI is that it will enable us to develop extraordinary new means of mass death. This time, these means could even proliferate to become accessible to rogue actors or terrorists (especially if, as on the current course, the superintelligence weights aren't sufficiently protected, and can be directly stolen by North Korea, Iran, and co.).\n  \n\n\n   North Korea already has a concerted bioweapons program: the US\n   \n    assesses\n   \n   that \"North Korea has a dedicated, national level offensive program\" to develop and produce bioweapons. It seems plausible that their primary constraint is how far their small circle of top scientists has been able to push the limits of (synthetic) biology. What happens when that constraint is removed, when they can use millions of superintelligences to accelerate their bioweapons R&D? For example, the US\n   \n    assesses\n   \n   that North Korea currently has \"limited ability\" to genetically engineer biological products\u2014what happens when that becomes unlimited? With what unholy new concoctions will they hold us hostage?\n  \n\n\n   Moreover, as discussed in the superalignment section, there will be extreme safety risks around and during the intelligence explosion\u2014we will be faced with novel technical challenges to ensure we can reliably trust and control superhuman AI systems. This very well may require us to slow down at some critical moments, say, delaying by 6 months in the middle of the intelligence explosion to get additional assurances on safety, or using a large fraction of compute on alignment research rather than capabilities progress.\n  \n\n\n   Some hope for some sort of international treaty on safety. This seems fanciful to me. The world where both the CCP and USG are AGI-pilled enough to take safety risk seriously is also the world in which both realize that international economic and military predominance is at stake, that being months behind on AGI could mean being permanently left behind. If the race is tight, any arms control equilibrium, at least in the early phase around superintelligence, seems extremely unstable. In short, \"breakout\" is too easy: the incentive (and the fear that others will act on this incentive) to race ahead with an intelligence explosion, to reach superintelligence and the decisive advantage, too great.\n   \n    109\n   \n   At the very least, the odds we get something good-enough here seem slim. (How have those climate treaties gone? That seems like a dramatically easier problem compared to this.)\n  \n\n\n   The main\u2014perhaps the only\u2014hope we have is that an alliance of democracies has a healthy lead over adversarial powers. The\n  \n\n\n\n    109\n   \n   Consider the following comparison of unstable vs. stable arms control equilibria. 1980s arms control during the Cold War reduced nuclear weapons substantially, but targeted a stable equilibrium. The US and the Soviet Union still had 1000s of nuclear weapons. MAD was assured, even if one of the actors tried a crash program to build more nukes; and a rogue nation could try to build some nukes of their own, but not fundamentally threaten the US or Soviet Union with overmatch.\n  \n\n\n   However, when disarmament is to very low levels of weapons or occurs amidst rapid technological change, the equilibrium is unstable. A rogue actor or treaty-breaker can easily start a crash program and threaten to totally overmatch the other players. Zero nukes wouldn't be a stable equilibrium; similarly,\n   \n    this paper\n   \n   has interesting historical case studies (such as post-WWI arms limitations and the Washington Naval Treaty) where disarmament in similarly dynamic situations destabilized, rather than stabilized.\n  \n\n\n   If mere months of lead on AGI would give an utterly decisive advantage, this makes stable disarmament on AI similarly difficult. A rogue upstart or a treaty-breaker could gain a huge edge by secretly starting a crash program; the temptation would be too great for any sort of arrangement to be stable.\n  \n\n\n   United States must lead, and use that lead to enforce safety norms on the rest of the world. That's the\n   \n    path we took with\n   \n\n    nukes,\n   \n   offering assistance on the peaceful uses of nuclear technology in exchange for an international nonproliferation regime (ultimately underwritten by American military power)\u2014and it's the only path that's been shown to work.\n  \n\n\n   Perhaps most importantly, a healthy lead gives us room to maneuver: the ability to \"cash in\" parts of the lead, if necessary, to get safety right, for example by devoting extra work to alignment during the intelligence explosion.\n  \n\n\n   The safety challenges of superintelligence would become\n   \n    extremely\n   \n   difficult to manage if you are in a neck-and-neck arms race. A 2 year vs. a 2 month lead could easily make all the difference. If we have only a 2 month lead, we have no margin at all for safety. In fear of the CCP's intelligence explosion, we'd almost certainly race, no holds barred, through our own intelligence explosion\u2014barreling towards AI systems vastly smarter than humans in months, without any ability to slow down to get key decisions right, with all the risks of superintelligence going awry that implies. We'd face an extremely volatile situation, as we and the CCP rapidly developed extraordinary new military technology that repeatedly destabilized deterrence. If our secrets and weights aren't locked down, it might even mean a range of other rogue states are close as well, each of them using superintelligence to furnish their own new arsenal of super-WMDs. Even if we barely managed to inch out ahead, it would likely be a pyrrhic victory; the existential struggle would have brought the world to the brink of total selfdestruction.\n  \n\n\n   Superintelligence looks very different if the democratic allies have a healthy lead, say 2 years.\n   \n    110\n   \n   That buys us the time nec-\n   \n    110\n   \n   Note that, given the already-rapid essary to navigate the unprecedented series of challenges we'll face around and after superintelligence, and to stabilize the situation.\n  \n\n\n   If and when it becomes clear that the US will decisively win,\n   \n    that's\n   \n   when we offer a deal to China and other adversaries. They'll know they won't win, and so they'll know their only\n  \n\n\n   pace of AI progress today, and the even-more-rapid pace we should expect in an intelligence explosion, and the broader technological explosion post-superintelligence, \"even\" a 2 year-lead would be a\n   \n    huge\n   \n   difference in capabilities in the post-superintelligence world.\n  \n\n\n   option is to come to the table; and we'd rather avoid a feverish standoff or last-ditch military attempts on their part to sabotage Western efforts. In exchange for guaranteeing noninterference in their affairs, and sharing the peaceful benefits of superintelligence, a regime of nonproliferation, safety norms, and a semblance of stability post-superintelligence can be born.\n  \n\n\n   In any case, as we go deeper into this struggle, we must not forget the threat of self-destruction. That we made it through the Cold War in one piece involved too much luck111\u2014and the\n   \n    111\n   \n   Daniel Ellsberg\n   \n    recounts this riv\n   \n   destruction could be a thousandfold more potent than what we faced then. A healthy lead by an American-led coalition of democracies\u2014and a solemn exercise of this leadership to stabilize whatever volatile situation we find ourselves in\u2014is probably the safest path to navigating past this precipice. But in the heat of the AGI race, we better not screw it up.\n  \n\n\n\n    Superintelligence is a matter of national security\n   \n\n\n\n   It is clear: AGI is an existential challenge for the national security of the United States. It's time to start treating it as such.\n  \n\n\n   Slowly, the USG is starting to move. The export controls on American chips are a huge deal, and were an incredibly prescient move at the time. But we have to get serious across the board.\n  \n\n\n   The US\n   \n    has\n   \n   a lead. We just have to keep it. And we're screwing that up right now. Most of all, we must rapidly and radically lock down the AI labs, before we leak key AGI breakthroughs in the next 12-24 months (or the AGI weights themselves). We must build the compute clusters in the US, not in dictatorships that offer easy money. And yes, American AI labs have a duty to work with the intelligence community and the military. America's lead on AGI won't secure peace and freedom by just building the best AI girlfriend apps. It's not pretty\u2014but we must build AI for American defense.\n  \n\n\n\n    etingly,\n   \n   as one of the nuclear war planners at RAND and in the national security apparatus at the time.\n  \n\n\n   We are already on course for the most combustive international situation in decades. Putin is on the march in Eastern Europe. The Middle East is on fire. The CCP views taking Taiwan as its destiny. Now add in the race to AGI. Add in a century's worth of technological breakthroughs compressed into years post-superintelligence. It will be the one of most unstable international situations ever seen\u2014and at least initially, the incentives for first-strikes will be tremendous.\n   \n    112\n   \n\n    112\n   \n   Everyone will be racing to their own\n  \n\n\n   There's already an eerie convergence of AGI timelines (~2027?) and Taiwan watchers' Taiwan invasion timelines\n   \n    (China ready\n   \n\n    to invade Taiwan by\n   \n   2027?)\u2014a convergence that will surely only heighten as the world wakes up to AGI. (Imagine if in 1960, the vast majority of the world's uranium deposits were somehow concentrated in Berlin!) It seems to me that there is a real chance that the AGI endgame plays out with the backdrop of world war. Then all bets are off.\n  \n\n\n   superintelligences, and there will be a limited window before someone ahead will have irreversibly pulled away. There will be a big incentive to try to disable the enemy superintelligence clusters before they've gained a sufficient physical advantage (e.g., using superintelligence to develop impenetrable missile defense or drone swarms) that leaves everyone else permanently in the dust.\n  \n\n\n\n    IV. The Project\n   \n\n\n\n\n    As the race to AGI intensifies, the national security state will get involved. The USG will wake from its slumber, and by 27/28 we'll get some form of government AGI project. No startup can handle superintelligence. Somewhere in a SCIF, the endgame will be on.\n   \n\n\n\n\n\n    We must be curious to learn how such a set of objects\u2014hundreds of power plants, thousands of bombs, tens of thousands of people massed in national establishments\u2014can be traced back to a few people sitting at laboratory benches discussing the peculiar behavior of one type of atom.\n   \n\n\n\n\n\n\n\n     spencer r. weart\n    \n\n\n\n\n   Many plans for \"AI governance\" are put forth these days, from licensing frontier AI systems to safety standards to a public cloud with a few hundred million in compute for academics. These seem well-intentioned\u2014but to me, it seems like they are making a category error.\n  \n\n\n\n    I find it an insane proposition that the US government will let a random SF startup develop superintelligence\n   \n   . Imagine if we had developed atomic bombs by letting Uber just improvise.\n  \n\n\n   Superintelligence\u2014AI systems\n   \n    much\n   \n   smarter than humans will have vast power, from developing novel weaponry to driving an explosion in economic growth. Superintelligence will be\n  \n\n\n   the locus of international competition; a lead of months potentially decisive in military conflict.\n  \n\n\n   It is a delusion of those who have unconsciously internalized our brief respite from history that this will not summon more primordial forces. Like many scientists before us, the great minds of San Francisco hope that they can control the destiny of the demon they are birthing. Right now, they still can; for they are among the few with situational awareness, who understand what they are building. But in the next few years, the world will wake up. So too will the national security state. History will make a triumphant return.\n  \n\n\n   As in many times before\u2014Covid, WWII\u2014it will seem as though the United States is asleep at the wheel\u2014before, all at once, the government shifts into gear in the most extraordinary fashion. There will be a moment\u2014in just a few years, just a couple more \"2023-level\" leaps in model capabilities and AI discourse where it will be clear: we are on the cusp of AGI, and superintelligence shortly thereafter. While there's a lot of flux in the exact mechanics, one way or another, the USG will be at the helm; the leading labs will (\"voluntarily\") merge; Congress will appropriate trillions for chips and power; a coalition of democracies formed.\n  \n\n\n   Startups are great for many things\u2014but a startup on its own is simply not equipped for being in charge of the United States' most important national defense project. We will need government involvement to have even a hope of defending against the all-out espionage threat we will face; the private AI efforts might as well be directly delivering superintelligence to the CCP. We will need the government to ensure even a semblance of a sane chain of command; you can't have random CEOs (or random nonprofit boards) with the nuclear button. We will need the government to manage the severe safety challenges of superintelligence, to manage the fog of war of the intelligence explosion. We will need the government to deploy superintelligence to defend against whatever extreme threats unfold, to make it through the extraordinarily volatile and destabilized international situation that will follow. We will need the government to mobilize a democratic coalition to win the race with\n  \n\n\n   authoritarian powers, and forge (and enforce) a nonproliferation regime for the rest of the world. I wish it weren't this way\u2014but we will need the government. (Yes, regardless of the Administration.)\n  \n\n\n   In any case, my main claim is not normative, but descriptive. In a few years, The Project will be on.\n  \n\n\n\n    The path to The Project\n   \n\n\n\n   A turn-of-events seared into my memory is late February to mid-March of 2020. In those last weeks of February and early days of March, I was in utter despair: it seemed clear that we were on the covid-exponential: a plague was about to sweep the country, the collapse of our hospitals was imminent\u2014and yet almost nobody took it seriously. The Mayor of New York was still dismissing Covid-fears as racism and encouraging people to go to Broadway shows. All I could do was buy masks and short the market.\n  \n\n\n   And yet within just a few weeks, the entire country shut down and Congress had appropriated trillions of dollars (literally >10% of GDP). Seeing where the exponential might go ahead of time was too hard, but when the threat got close enough, existential enough, extraordinary forces were unleashed. The response was late, crude, blunt\u2014but it came, and it was dramatic.\n  \n\n\n   The next few years in AI will feel similar. We're in the midgame now. 2023 was already a wild shift. AGI went from a fringe topic you'd be hesitant to associate with, to the subject of major Senate hearings and summits of world leaders. Given how early we are still, the level of USG engagement has been impressive to me. A couple more \"2023\"s, and the Overton window will be blown completely open.\n  \n\n\n   As we race through the OOMs, the leaps will continue. By 2025/2026 or so I expect the next truly shocking step-changes; AI will drive $100B+ annual revenues for big tech companies and outcompete PhDs in raw problem-solving smarts. Much as\n  \n\n\n   the Covid stock-market collapse made many take Covid seriously, we'll have $10T companies and the AI mania will be everywhere. If that's not enough, by 2027/28, we'll have models trained on the $100B+ cluster; full-fledged AI agents/drop-in remote workers will start to widely automate software engineering and other cognitive jobs. Each year, the acceleration will feel dizzying.\n  \n\n\n   While many don't yet see the possibility of AGI, eventually a consensus will form. Some, like Szilard, saw the possibility of an atomic bomb much earlier than others. Their alarm was not well-received initially; the possibility of a bomb was dismissed as remote (or at least, it was felt that the conservative and proper thing was to play down the possibility). Szilard's fervent secrecy appeals were mocked and ignored. But many scientists, initially skeptical, started realizing a bomb was possible as more and more empirical results came in. Once a majority of scientists came to believe we were on the cusp of a bomb, the government, in turn, saw the national security exigency as too great\u2014and the Manhattan Project got underway.\n  \n\n\n   As the OOMs go from theoretical extrapolation to (extraordinary) empirical reality, gradually, a consensus will form, too, among the leading scientists and executives and government officials: we are on the cusp, on the cusp of AGI, on the cusp of an intelligence explosion, on the cusp of superintelligence. And somewhere along here, we'll get the first genuinely terrifying demonstrations of AI: perhaps the oft-discussed \"helping novices make bioweapons,\" or autonomously hacking critical systems, or something else entirely. It will become clear: this technology will be an utterly decisive military technology. Even if we're lucky enough to not be in a major war, it seems likely that the CCP will have taken notice and launched a formidable AGI effort. Perhaps the eventual (inevitable) discovery of the CCP's infiltration of America's leading AI labs will cause a big stir.\n  \n\n\n   Somewhere around 26/27 or so, the mood in Washington will become somber. People will start to viscerally feel what is happening; they will be\n   \n    scared\n   \n   . From the halls of the Pentagon to the backroom Congressional briefings will ring the obvious\n  \n\n\n   question, the question on everybody's minds: do we need an AGI Manhattan Project? Slowly at first, then all at once, it will become clear: this is happening, things are going to get\n   \n    wild\n   \n   , this is the most important challenge for the national security of the United States since the invention of the atomic bomb. In one form or another, the national security state will get very heavily involved. The Project will be the necessary, indeed the only plausible, response.\n  \n\n\n   Of course, this is an extremely abbreviated account\u2014a lot depends on when and how consensus forms, key warning shots, and so on. DC is infamously dysfunctional. As with Covid, and even the Manhattan Project, the government will be incredibly late and hamfisted.\n   \n    After\n   \n   Einstein's letter to the President in 1939 (drafted by Szilard), an Advisory Committee on Uranium was formed. But officials were incompetent, and not much happened initially. For example, Fermi only got $6k (about $135k in today's dollars) to support his research, and even that was not given easily and only received after months of waiting. Szilard believed that the project was\n   \n    delayed for\n   \n\n    at least a year\n   \n   by the short-sightedness and sluggishness of the authorities. In March 1941, the British government finally concluded a bomb was inevitable. The US committee initially entirely ignored this British report for months\u2014until finally in December 1941, a full-scale atomic bomb effort was launched.\n  \n\n\n   There are many ways this could be operationalized in practice. To be clear, this doesn't need to look like literal nationalization, with AI lab researchers now employed by the military or whatever (though it might!).\n   \n    113\n   \n   Rather, I expect a more suave\n   \n    113\n   \n   Note that while private companies orchestration. The relationship with the DoD might look like the relationship the DoD has with Boeing or Lockheed Martin. Perhaps via defense contracting or similar, a joint venture between the major cloud compute providers, AI labs, and the government is established, making it functionally a project of the national security state. Much like the AI labs \"voluntarily\" made commitments to the White House in 2023, Western labs might more-or-less \"voluntarily\" agree to merge in the national effort. And likely Congress will have to be involved, given the trillions of investment involved, and for checks-and-balances.\n   \n    114\n   \n\n    114\n   \n   Congress\u2014even the Vice President!\u2014 How all these details shake out is a story for another day.\n  \n\n\n   help develop components for nuclear weapons, they are never allowed to possess a completed and assembled nuclear weapon. In comparison, the mainline version of the \"AGI government project\" I am putting forward here is unprecedentedly privatized, for the WMD reference class.\n  \n\n\n   didn't know about the Manhattan Project. We probably shouldn't repeat that here; I'd even suggest that key officials for The Project require Senate confirmation.\n  \n\n\n   But by late 26/27/28 it will be underway. The core AGI research team (a few hundred researchers) will move to a secure location; the trillion-dollar cluster will be built in record-speed; The Project will be on.\n  \n\n\n\n    Why The Project is the only way\n   \n\n\n\n   I am under no illusions about the government. Governments face all sorts of limitations and poor incentives. I am a big believer in the American private sector, and would almost never advocate for heavy government involvement in technology or industry.\n  \n\n\n   I used to apply this same framework to AGI\u2014until I joined an AI lab. AI labs are very good at some things: they've been able to take AI from an academic science project to the commercial big stage, in a way only a startup can. But ultimately, AI labs are still startups. We simply shouldn't expect startups to be equipped to handle superintelligence.\n  \n\n\n   There are no good options here\u2014but I don't see another way. When a technology becomes this important for national security, we will need the USG.\n  \n\n\n\n    Superintelligence will be the United States' most important national defense project\n   \n\n\n\n   I've discussed the power of superintelligence in previous pieces. Within years, superintelligence would completely shake up the military balance of power. By the early 2030s, the entirety of the US arsenal (like it or not, the bedrock of global peace and security) will probably be obsolete. It will not just be a matter of modernization, but a wholesale replacement.\n  \n\n\n   Simply put, it will become clear that the development of AGI will fall in a category more like nukes than the internet. Yes, of course it'll be dual-use\u2014but nuclear technology was dualuse too. The civilian applications will have their time. But in\n  \n\n\n   the fog of the AGI endgame, for better or for worse, national security will be the primary backdrop.\n  \n\n\n   We will need to completely reshape US forces, within a matter of years, in the face of rapid technological change\u2014or risk being completely outmatched by adversaries who do. Perhaps most of all, the initial priority will be to deploy superintelligence for defensive applications, to develop countermeasures to survive untold new threats: adversaries with superhuman hacking capabilities, new classes of stealthy drone swarms that could execute a preemptive strike on our nuclear deterrent, the proliferation of advances in synthetic biology that can be weaponized, turbulent international (and national) power struggles, and rogue superintelligence projects.\n  \n\n\n   Whether nominally private or not, the AGI project will need to be,\n   \n    will be,\n   \n   integrally a defense project, and it will require extremely close cooperation with the national security state.\n  \n\n\n\n    A sane chain of command for superintelligence\n   \n\n\n\n   The power\u2014and the challenges\u2014of superintelligence will fall into a very different reference class than anything else we're used to seeing from tech companies. It seems pretty clear: this should not be under the unilateral command of a random CEO. Indeed, in the private-labs-developing-superintelligence world, it's quite plausible individual CEOs would have the power\n   \n    to literally coup the US government\n   \n   .\n   \n    115\n   \n   Imagine if Elon Musk\n   \n    115\n   \n   It wouldn't even require cooperhad final command of the nuclear arsenal.\n   \n    116\n   \n   (Or if a random nonprofit board could decide to seize control of the nuclear arsenal.)\n  \n\n\n   It is perhaps obvious, but: as a society, we've decided democratic governments should control the military;\n   \n    117\n   \n   superin-\n   \n    117\n   \n   In fact, the government having telligence will be, at least at first, the most powerful military weapon. The radical proposal is not The Project; the radical proposal is taking a bet on private AI CEOs wielding military power and becoming benevolent dictators.\n  \n\n\n   (Indeed, in the private AI lab world, it would likely be even worse than random CEOs with the nuclear button\u2014part of AI\n  \n\n\n   ation from AI lab employees at this point, since they'll have been mostly automated by this point.\n   \n    116\n   \n   And as Sam Altman once said, every year we get closer to AGI everybody will gain +10 crazy points.\n  \n\n\n   the biggest guns was an enormous\n   \n    civilizational achievement!\n   \n   Rather than medieval-like fights of all against all, we would sort out disagreements via courts, pluralistic institutions, and so on.\n  \n\n\n   labs' abysmal security is their utter lack of internal controls. That is, random AI lab employees (with zero vetting) could go rogue unnoticed.)\n  \n\n\n   We will need a sane chain of command\u2014along with all the other processes and safeguards that necessarily come with responsibly wielding what will be comparable to a WMD\u2014and it'll require the government to do so. In some sense, this is simply a Burkean argument: the institutions, constitutions, laws, courts, checks and balances, norms and common dedication to the liberal democratic order (e.g., generals refusing to follow illegal orders), and so on that check the power of the government have withstood the test of hundreds of years. Special AI lab governance structures, meanwhile, collapsed the first time they were tested. The US military could already kill basically every civilian in the United States, or seize power, if it wanted to\u2014and the way we keep government power over nuclear weapons in check is not through lots of private companies with their own nuclear arsenals. There's only one chain of command and set of institutions that has proven itself up to this task.\n  \n\n\n   Again, perhaps you are a true libertarian and disagree normatively (let Elon Musk and Sam Altman command their own nuclear arsenals!).\n   \n    118\n   \n   But once it becomes clear that superintel-\n   \n    118\n   \n   Or perhaps you say, just open-source ligence is a principal matter of national security, I'm sure this is how the men and women in DC will look at it.\n  \n\n\n\n    The civilian uses of superintelligence\n   \n\n\n\n   Of course, that doesn't mean the civilian applications of superintelligence will be reserved for the government.\n  \n\n\n\n\n\n\n     The nuclear chain reaction was first harnessed as a government project\u2014and nuclear weapons permanently reserved for the government\u2014but civilian nuclear energy flourished as private projects (in the 60s and 70s, before environmentalists shut it down).\n    \n\n\n     Boeing made the B-29 (the most expensive defense R&D project during WWII, more expensive than the Manhat-\n    \n\n\n\n   everything. The issue with simply open sourcing everything is that it's not a happy world of a thousand flowers blooming in the US, but a world in which the CCP has free access to US-developed superintelligence, and can outbuild (and apply less caution/regulation) and take over the world. And the other issue, of course, is the proliferation of super-WMDs to every rogue state and terrorist group in the world. I don't think it'll end well. It's a bit like how having no government at all is more likely to lead to tyranny (or destruction) than freedom.\n  \n\n\n   In any case, people overrate the importance of open-source as we get closer to AGI. Given cluster costs escalating to hundreds of billions, and key algorithmic secrets now being proprietary rather than published as they were a couple years ago, it'll be 2-3 or so leading players, rather than some happy community of decentralized coders building AGI.\n  \n\n\n   I do think a different variant of open source will continue to play an important role: models that lag a couple years behind being open sourced, helping the benefits of the technology diffuse broadly.\n  \n\n\n   tan Project) and the B-47 and B-52 long-range bombers in partnership with the military\u2014before using that technology for the Boeing 707, the commercial plane that ushered in the jet era. And today, while Boeing can only sell stealth fighter jets to the government, it can freely develop and sell civilian jets privately.\n  \n\n\n   \u2022 And so it went for radar, satellites, rockets, gene technology, WWII factories, and so on.\n  \n\n\n   The initial development of superintelligence will be dominated by the national security exigency to survive and stabilize an incredibly volatile period. And the military uses of superintelligence will remain reserved for the government, and safety norms will be enforced. But once the initial peril has passed, the natural path is for the companies involved in the national consortium (and others) to privately pursue civilian applications.\n  \n\n\n   Even in worlds with The Project, a private, pluralistic, market-based, flourishing ecosystem of civilian applications of superintelligence will have its day.\n  \n\n\n\n    Security\n   \n\n\n\n   I've gone on about this at length in a previous piece in the series. On the current course, we may as well give up on having any American AGI effort; China can promptly steal all the algorithmic breakthroughs and the model weights (literally a copy of superintelligence) directly. It's not even clear we'll get to \"North Korea-proof\" security for superintelligence on the current course. In the private-startups-developing-AGI-world, superintelligence would proliferate to dozens of rogue states. It's simply untenable.\n  \n\n\n   If we're going to be at all serious about this, we obviously need to lock this stuff down. Most private companies have failed to take this seriously. But in any case, if we are to eventually face the full force of Chinese espionage (e.g., stealing the weights being the MSS's #1 priority), it's probably impossible for a private company to get good enough security. It will require\n  \n\n\n   extensive cooperation from the US intelligence community at that point to sufficiently secure AGI. This will involve invasive restrictions on AI labs and on the core team of AGI researchers, from extreme vetting to constant monitoring to working from a SCIF to reduced freedom to leave; and it will require infrastructure only the government can provide, ultimately including the physical security of the AGI datacenters themselves.\n  \n\n\n   In some sense, security alone is sufficient to necessitate the government project\u2014both the free world's preeminence and AI safety are doomed if we can't lock this stuff down. (In fact, I think it's fairly likely to be a major factor in the ultimate trigger: once the Chinese infiltration of the AGI labs becomes clear, every Senator and Congressperson and national security official will. . . have a strong opinion on the matter.)\n  \n\n\n\n    Safety\n   \n\n\n\n   Simply put: there are a lot of ways for us to mess this up from ensuring we can reliably control and trust the billions of superintelligent agents that will soon be in charge of our economy and military (the superalignment problem), to controlling the risks of misuse of new means of mass destruction.\n  \n\n\n   Some AI labs claim to be committed to safety: acknowledging that what they are building, if gone awry, could cause catastrophe and promising that they will do what is necessary when the time comes. I do not know if we can trust their promise enough to stake the lives of every American on it. More importantly, so far, they have not demonstrated the competence, trustworthiness, or seriousness necessary for what they themselves acknowledge they are building.\n  \n\n\n   At core, they are startups, with all the usual commercial incentives. Competition could push all of them to simply race through the intelligence explosion, and there will at least be some actors that will be willing to throw safety by the wayside. In particular, we may want to \"spend some of our lead\" to have time to solve safety challenges, but Western labs will need to coordinate to do so. (And of course, private labs will have already had their AGI weights stolen, so their safety pre-\n  \n\n\n   cautions won't even matter; we'll be at the mercy of the CCP's and North Korea's safety precautions.)\n  \n\n\n   One answer is regulation. That may be appropriate in worlds in which AI develops more slowly, but I fear that regulation simply won't be up to the nature of the challenge of the intelligence explosion. What's necessary will be less like spending a few years doing careful evaluations and pushing some safety standards through a bureaucracy.\n   \n    It'll be more like fighting a war\n   \n   .\n  \n\n\n   We'll face an insane year in which the situation is shifting extremely rapidly every week, in which hard calls based on ambiguous data will be life-or-death, in which the solutions\u2014even the problems themselves\u2014won't be close to fully clear ahead of time but come down to competence in a \"fog of war,\" which will involve insane tradeoffs like \"some of our alignment measurements are looking ambiguous, we don't really understand what's going on anymore, it might be fine but there's some warning signs that the next generation of superintelligence might go awry, should we delay the next training run by 3 months to get more confidence on safety\u2014but oh no, the latest intelligence reports indicate China stole our weights and is racing ahead on their own intelligence explosion, what should we do?\".\n  \n\n\n   I'm not confident that a government project would be competent in dealing with this\u2014but the \"superintelligence developed by startups\" alternative seems much closer to \"praying for the best\" than commonly recognized. We'll need a chain of command that can bring to the table the seriousness that making these difficult tradeoffs will require.\n  \n\n\n\n    Stabilizing the international situation\n   \n\n\n\n   The intelligence explosion and its immediate aftermath will bring forth one of the most volatile and tense situations mankind has ever faced. Our generation is not used to this. But in this initial period, the task at hand will not be to build cool products. It will be to somehow, desperately, make it through this period.\n  \n\n\n   We'll need the government project to win the race against the\n  \n\n\n   authoritarian powers\u2014and to give us the clear lead and breathing room necessary to navigate the perils of this situation. We might as well give up if we can't prevent the instant theft of superintelligence model weights. We will want to bundle Western efforts: bring together our best scientists, use every GPU we can find, and ensure the trillions of dollars of cluster buildouts happen in the United States. We will need to protect the datacenters against adversary sabotage, or outright attack.\n  \n\n\n   Perhaps, most of all, it will take American leadership to develop and if necessary, enforce\u2014a nonproliferation regime. We'll need to subvert Russia, North Korea, Iran, and terrorist groups from using their own superintelligence to develop technology and weaponry that would let them hold the world hostage. We'll need to use superintelligence to harden the security of our critical infrastructure, military, and government to defend against extreme new hacking capabilities. We'll need to use superintelligence to stabilize the offense/defense balance of advances in biology or similar. We'll need to develop tools to safely control superintelligence, and to shut down rogue superintelligences that come out of others' uncareful projects.AI systems and robots will be moving at 10-100x+ human speed; everything will start happening extremely quickly. We need to be ready to handle whatever other six-sigma upheavals and concomitant threats\u2014come out of compressing a century's worth of technological progress into a few years.\n  \n\n\n   At least in this initial period, we will be faced with the most extraordinary national security exigency. Perhaps, nobody is up for this task. But of the options we have, The Project is the only sane one.\n  \n\n\n\n    The Project is inevitable; whether it's good is not\n   \n\n\n\n   Ultimately, my main claim here is descriptive: whether we like it or not, superintelligence won't look like an SF startup, and in some way will be primarily in the domain of national security. I've brought up The Project a lot to my San Francisco friends in the past year. Perhaps what's surprised me most is\n  \n\n\n   how surprised most people are about the idea. They simply haven't considered the possibility. But once they consider it, most agree that it seems obvious. If we are at all right about what we think we are building,\n   \n    of course,\n   \n   by the end this will be (in some form) a government project. If a lab developed literal superintelligence tomorrow,\n   \n    of course\n   \n   the Feds would step in.\n  \n\n\n   One important free variable is not\n   \n    if\n   \n   but\n   \n    when\n   \n   . Does the government not realize what's happening until we're in the middle of an intelligence explosion\u2014or will it realize a couple years beforehand? If the government project is inevitable, earlier seems better. We'll dearly need those couple years to do the security crash program, to get the key officials up to speed and prepared, to build a functioning merged lab, and so on. It'll be far more chaotic if the government only steps in at the very end (and the secrets and weights will have already been stolen).\n  \n\n\n   Another important free variable is the international coalition we can rally: both a tighter alliance of democracies for developing superintelligence, and a broader benefit-sharing offer made to the rest of the world.\n  \n\n\n\n\n\n\n     The former might look like the\n     \n      Quebec Agreement:\n     \n     a secret pact between Churchill and Roosevelt to pool their resources to develop nuclear weapons, while not using them against each other or against others without mutual consent. We'll want to bring in the UK (Deepmind), East Asian allies like Japan and South Korea (chip supply chain), and NATO/other core democratic allies (broader industrial base). A united effort will have more resources, talent, and control the whole supply chain; enable close coordination on safety, national security, and military challenges; and provide helpful checks and balances on wielding the power of superintelligence.\n    \n\n\n     The latter might look like\n     \n      Atoms for Peace,\n     \n     the\n     \n      IAEA,\n     \n     and the\n     \n      NPT.\n     \n     We should offer to share the peaceful benefits of superintelligence with a broader group of countries (including non-democracies), and commit to not offensively using superintelligence against them. In exchange, they refrain from pursuing their own superintelligence projects, make\n    \n\n\n\n   safety commitments on the deployment of AI systems, and accept restrictions on dual-use applications. The hope is that this offer reduces the incentives for arms races and proliferation, and brings a broad coalition under a US-led umbrella for the post-superintelligence world order.\n  \n\n\n   Perhaps the most important free variable is simply whether the inevitable government project will be competent. How will it be organized? How can we get this done? How will the checks and balances work, and what does a sane chain of command look like? Scarcely any attention has gone into figuring this out.\n   \n    119\n   \n   Almost all other AI lab and AI governance politicking is\n   \n    119\n   \n   To my Progress Studies brethren: you a sideshow. This is the ballgame.\n  \n\n\n   should think about this, this will be the culmination of your intellectual project! You spend all this time studying American government research institutions, their decline over the last half-century, and what it would take to make them effective again. Tell me: how will we make The Project effective?\n  \n\n\n\n    The endgame\n   \n\n\n\n   And so by 27/28, the endgame will be on. By 28/29 the intelligence explosion will be underway; by 2030, we will have summoned superintelligence, in all its power and might.\n  \n\n\n   Whoever they put in charge of The Project is going to have a hell of a task: to build AGI, and to build it fast; to put the American economy on wartime footing to make hundreds of millions of GPUs; to lock it all down, weed out the spies, and fend off all-out attacks by the CCP; to somehow manage a hundred million AGIs furiously automating AI research, making a decade's leaps in a year, and soon producing AI systems\n   \n    vastly\n   \n   smarter than the smartest humans; to somehow keep things together enough that this doesn't go off the rails and produce rogue superintelligence that tries to seize control from its human overseers; to use those superintelligences to develop whatever new technologies will be necessary to stabilize the situation and stay ahead of adversaries, rapidly remaking US forces to integrate those; all while navigating what will likely be the tensest international situation ever seen. They better be good, I'll say that.\n  \n\n\n   For those of us who get the call to come along for the ride, it'll be . . . stressful. But it will be our duty to serve the free\n  \n\n\n\n\n\n\n   Figure 38: Oppenheimer and Groves.\n  \n\n\n   world\u2014and all of humanity. If we make it through and get to look back on those years, it will be the most important thing we ever did. And while whatever secure facility they find probably won't have the pleasantries of today's ridiculouslyovercomped-AI-researcher-lifestyle, it won't be so bad. SF already feels like a peculiar AI-researcher-college-town; probably this won't be so different. It'll be the same weirdly-small circle sweating the scaling curves during the day and hanging out over the weekend, kibitzing over AGI and the lab-politics-ofthe-day.\n  \n\n\n   Except, well\u2014the stakes will be all too real.\n  \n\n\n   See you in the desert, friends.\n  \n\n\n\n\n\n\n   Figure 39: Reunion of atomic scientists on the fourth anniversary of the first controlled nuclear fission reaction at UChicago.\n  \n\n\n\n    V. Parting Thoughts\n   \n\n\n\n\n    What if we're right?\n   \n\n\n\n   I remember the spring of 1941 to this day. I realized then that a nuclear bomb was not only possible \u2014 it was inevitable. Sooner or later these ideas could not be peculiar to us. Everybody would think about them before long, and some country would put them into action. . . .\n  \n\n\n   And there was nobody to talk to about it, I had many sleepless nights. But I did realize how very very serious it could be. And I had then to start taking sleeping pills. It was the only remedy, I've never stopped since then. It's 28 years, and I don't think I've missed a single night in all those 28 years.\n  \n\n\n   james chadwich (Physics Nobel Laureate and author of the 1941 British government report on the inevitability of an atomic bomb, which finally spurred the Manhattan Project into action)\n  \n\n\n   Before the decade is out, we will have built superintelligence. That is what most of this series has been about. For most people I talk to in SF, that's where the screen goes black. But the decade after\u2014the 2030s\u2014will be at least as eventful. By the end of it, the world will have been utterly, unrecognizably transformed. A new world order will have been forged. But alas\u2014that's a story for another time.\n  \n\n\n   We must come to a close, for now. Let me make a few final remarks.\n  \n\n\n\n    AGI realism\n   \n\n\n\n   This is all much to contemplate\u2014and many cannot. \"Deep learning is hitting a wall!\" they proclaim, every year. It's just another tech boom, the pundits say confidently. But even among those at the SF-epicenter, the discourse has become polarized between two fundamentally unserious rallying cries.\n  \n\n\n   On the one end there are the doomers. They have been obsessing over AGI for many years; I give them a lot of credit for their prescience. But their thinking has become ossified, untethered from the empirical realities of deep learning, their proposals naive and unworkable, and they fail to engage with the very real authoritarian threat. Rabid claims of 99% odds of doom, calls to indefinitely pause AI\u2014they are clearly not the way.\n  \n\n\n   On the other end are the e/accs. Narrowly, they have some good points: AI progress must continue. But beneath their shallow Twitter shitposting, they are a sham; dilettantes who just want to build their wrapper startups rather than stare AGI in the face. They claim to be ardent defenders of American freedom, but can't resist the siren song of unsavory dictators' cash. In truth, they are real stagnationists. In their attempt to deny the risks, they deny AGI; essentially, all we'll get is cool chatbots, which surely aren't dangerous. (That's some underwhelming accelerationism in my book.)\n  \n\n\n   But as I see it, the smartest people in the space have converged on a different perspective, a third way, one I will dub\n   \n    AGI Realism.\n   \n   The core tenets are simple:\n  \n\n\n   1.\n   \n    Superintelligence is a matter of national security.\n   \n   We are rapidly building machines smarter than the smartest humans. This is not another cool Silicon Valley boom; this isn't some random community of coders writing an innocent open source software package; this isn't fun and games. Superintelligence is going to be\n   \n    wild\n   \n   ; it will be the most powerful weapon mankind has ever built. And for any of us involved, it'll be the most important thing we ever do.\n  \n\n\n\n\n\n\n     2.\n     \n      America must lead.\n     \n     The torch of liberty will not survive Xi getting AGI first. (And, realistically, American leadership is the only path to safe AGI, too.) That means we can't simply \"pause\"; it means we need to rapidly scale up US power production to build the AGI clusters in the US. But it also means amateur startup security delivering the nuclear secrets to the CCP won't cut it anymore, and it means the core AGI infrastructure must be controlled by America, not some dictator in the Middle East. American AI labs must put the national interest first.\n    \n\n\n     3.\n     \n      We need to not screw it up.\n     \n     Recognizing the power of superintelligence also means recognizing its peril. There are very real safety risks; very real risks this all goes awry\u2014whether it be because mankind uses the destructive power brought forth for our mutual annihilation, or because, yes, the alien species we're summoning is one we cannot yet fully control. These are manageable\u2014but improvising won't cut it. Navigating these perils will require good people bringing a level of seriousness to the table that has not yet been offered.\n    \n\n\n\n   As the acceleration intensifies, I only expect the discourse to get more shrill. But my greatest hope is that there will be those who feel the weight of what is coming, and take it as a solemn call to duty.\n  \n\n\n\n    What if we're right?\n   \n\n\n\n   At this point, you may think that I and all the other SF-folk are totally crazy. But consider, just for a moment:\n   \n    what if they're right?\n   \n   These are the people who invented and built this technology; they think AGI will be developed this decade; and, though there's a fairly wide spectrum, many of them take very seriously the possibility that the road to superintelligence will play out as I've described in this series.\n  \n\n\n   Almost certainly I've gotten important parts of the story wrong; if reality turns out to be anywhere near this crazy, the error bars will be very large. Moreover, as I said at the outset, I think there's a wide range of possibilities. But I think it is impor-\n  \n\n\n   tant to be concrete. And in this series I've laid out what I currently believe is the single most likely scenario for the rest of the decade\u2014the rest of\n   \n    this\n   \n   decade.\n  \n\n\n   Because\u2014it's starting to feel real,\n   \n    very\n   \n   real. A few years ago, at least for me, I took these ideas seriously\u2014but they were abstract, quarantined in models and probability estimates. Now it feels extremely visceral. I can\n   \n    see\n   \n   it. I can\n   \n    see\n   \n   how AGI will be built. It's no longer about estimates of human brain size and hypotheticals and theoretical extrapolations and all that\u2014I can basically tell you the cluster AGI will be trained on and when it will be built, the rough combination of algorithms we'll use, the unsolved problems and the path to solving them, the list of people that will matter. I can\n   \n    see\n   \n   it. It is extremely visceral. Sure, going all-in leveraged long Nvidia in early 2023 has been great and all, but the burdens of history are heavy. I would not choose this.\n  \n\n\n   But the scariest realization is that\n   \n    there is no crack team coming to handle this\n   \n   . As a kid you have this glorified view of the world, that when things get real there are the heroic scientists, the uber-competent military men, the calm leaders who are on it, who will save the day. It is not so. The world is incredibly small; when the facade comes off, it's usually just a few folks behind the scenes who are the live players, who are desperately trying to keep things from falling apart.\n  \n\n\n   Right now, there's perhaps a few hundred people in the world who realize what's about to hit us, who understand just how crazy things are about to get, who have situational awareness. I probably either personally know or am one degree of separation from everyone who could plausibly run The Project. The few folks behind the scenes who are desperately trying to keep things from falling apart are you and your buddies and their buddies. That's it. That's all there is.\n  \n\n\n   Someday it will be out of our hands. But right now, at least for the next few years of midgame, the fate of the world rests on these people.\n  \n\n\n   Will the free world prevail?\n  \n\n\n   Will we tame superintelligence, or will it tame us?\n  \n\n\n   Will humanity skirt self-destruction once more?\n  \n\n\n   The stakes are no less.\n  \n\n\n   These are great and honorable people. But they are just people. Soon, the AIs will be running the world, but we're in for one last rodeo. May their final stewardship bring honor to mankind.\n  \n\n\n\n\n\n\n    Appendix\n   \n\n\n\n\n    Some additional details on compute back-of-the-envelope calculcations\n   \n\n\n\n\n    Training compute\n   \n\n\n\n\n    Year.\n   \n   The OpenAI GPT-4\n   \n    tech report\n   \n   stated that GPT-4 finished training in August 2022. Thereafter we play forward the rough 0.5 OOMs/year trend.\n  \n\n\n\n    H100s-equivalent.\n   \n\n    Semianalysis,\n   \n\n    JP Morgan,\n   \n   and others estimate GPT-4 was trained on 25k A100s, and H100s are 2-3x the performance of A100s.\n  \n\n\n\n    Cost.\n   \n   Often people cite numbers like \"$100M for GPT-4 training,\" using just the rental cost of the GPUs (i.e., something like \"how much would it cost to rent this size cluster for 3 months of training\"). But that's a mistake. What matters is something more like ~the actual cost to build the cluster. If you want one of the largest clusters in the world, you can't just rent it for 3 months! And moreover, you need the compute for more than just the flagship training run: there will be lots of derisking experiments, failed runs, other models, etc.\n  \n\n\n   To approximate the GPT-4 cluster cost:\n  \n\n\n   \u2022 The\n   \n    public\n   \n\n    estimates\n   \n   suggest the GPT-4 cluster being around 25k A100s.\n  \n\n\n\n\n\n\n     Assuming $1/A100-hour for 2-3 years gives roughly a $500M cost.\n    \n\n\n     Alternatively, you can estimate it as $25k cost per H100, 10k H100s-equivalent, and Nvidia GPUs being around half the cost of a cluster (the rest being power, the physical datacenter, cooling, networking, maintenance personnel, etc.). (For example, this\n     \n      total-cost-of-ownership analysis\n     \n     estimates that around 40% of a large cluster cost is the H100 GPUs itself, and another 13% goes to Nvidia for Infiniband networking. That said, excluding cost of capital in that calculation would mean the GPUs are about 50% of the cost, and with networking Nvidia gets a bit over 60% of the cost of the cluster.)\n    \n\n\n\n   FLOP/$ is improving somewhat for each Nvidia generation, but not a ton. E.g., the H100 -> B100 is likely something like 1.5x FLOP/$: B100s are effectively two H100s stapled together, but retailing for <2x the cost. But the B100 was somewhat of an exception. They are surprisingly cheap, likely because Nvidia\n   \n    wants to crush competition.\n   \n   By contrast, A100s -> H100s weren't much of a FLOP/$ improvement (2x better chip without fp8, roughly 2x the cost), maybe 1.5x if we count fp8 improvements\u2014and that was for a two-year generation.\n  \n\n\n   While I think there are some tailwinds to further FLOP/$ improvements from margin compression, GPUs might also get more expensive as they become massively constrained. Gains from AI chip specialization will continue, but it's not clear to me there will still be game-changing technical improvements to FLOP/$ coming, given chips are already pretty specialized for AI (e.g. specialized for Transformers, and already at fp8/fp4 precision), Moore's Law is glacial these days, and\n   \n    other bottle\n   \n\n    neck components like memory and interconnect\n   \n   are improving more slowly. If you look at\n   \n    Epoch's data,\n   \n   there seems to be less than a 10x in FLOP/$ over the past decade for top ML GPUs, and for the aforementioned reasons if anything I'd expect this to slow down.\n  \n\n\n   Something like a 35%/year improvement in FLOP/$ would give us the 1T cost for the +4 OOM cluster. Maybe FLOP/$ improves faster, but also datacenter capex is going to get more\n  \n\n\n   expensive\u2014simply because you'll need to actually build new power, doing a lot of capex up front, rather than just renting existing depreciated power plants.\n  \n\n\n   These are just very rough numbers anyway. It would be very much within error bars if e.g. the 1T cluster can be done more efficiently and actually yields more like +4.5 OOMs on compute.\n  \n\n\n\n    Cost.\n   \n   An H100 is 700W, but there's a bunch of datacenter power you need (cooling, networking, storage); Semianalysis\n   \n    estimates\n   \n   ~1,400W per H100.\n  \n\n\n   There are some gains to be had on FLOP/Watt, though once we've exhausted the gains from AI chip specialization (see previous footnote), e.g. gone down to the lowest possible precision, these seem somewhat limited (mostly just chip process improvements, which are slow). That said, as power becomes more of a constraint (and thus a larger fraction of costs), chip designs might specialize to more power-efficiency at the costs of FLOPs. Still, there is still the power demand for cooling, networking, storage, and so on (which in the H100 numbers above was already roughly half the power demand).\n  \n\n\n   For these back of the envelope numbers, let's work with 1kW per H100-equivalent here; again these are just rough back-ofthe-envelope calculations. (And if there were an unexpected FLOP/Watt breakthrough, I'd expect the same power expenditure, just bigger OOM compute gains.)\n  \n\n\n\n    Power reference classes.\n   \n   A 10GW cluster run continuously for a year is 87.6 TWh. By comparison, Oregon\n   \n    consumes\n   \n   about 27 TWh of electricity annually, Washington state\n   \n    consumes\n   \n   about 92 TWh annually.\n  \n\n\n   A 100GW cluster run continuously for a year is 876 TWh, while total annual US electricity production is about 4,250 TWh.\n  \n\n\n\n    Click here to return back to the \"training compute\" table.\n   \n\n\n\n\n    Overall compute\n   \n\n\n\n\n    H100-equivalents this year.\n   \n   I estimate Nvidia is going to ship on the order of 5M datacenter GPUs in 2024. A minority of those are B100s, which we'll count as 2x+ H100s. Then there's the other AI chips: TPUs, Trainium, Meta's custom silicon, AMD GPUs, etc.\n  \n\n\n\n    TSMC Capacity.\n   \n   TSMC has capacity for over 150k 5\n   \n    nm\n   \n   wafers per month, is ramping to 100k 3\n   \n    nm wafers\n   \n   per month, and likely another 150\n   \n    k or so\n   \n   7nm wafers per month; let's call it 400k wafers per month in total.\n  \n\n\n   Let's say roughly 35 H100\n   \n    s per wafer\n   \n   (H100s are made on 5nm). At 5-10 million H100-equivalents in 2024, that's 150k-300k wafers per year for annual AI chip production in 2024.\n  \n\n\n   Depending on where in that range and whether we want to count 7nm production, that's about 3-10% of annual leadingedge wafer production.\n  \n\n\n\n    Click here to return back to the \"overall compute\" table.\n   \n\n]]>\n    \n\n\n\n    Leopold Aschenbrenner\n   \n\n\n\n\n    S I T U AT I O N A L AWA R E N E S S\n   \n\n\n\n   The Decade Ahead\n  \n\n\n   J U NE 2024\n  \n\n\n\n    Dedicated to Ilya Sutskever.\n   \n\n\n\n   While I used to work at OpenAI, all of this is based on publiclyavailable information, my own ideas, general field-knowledge, or SF-gossip.\n  \n\n\n   Thank you to Collin Burns, Avital Balwit, Carl Shulman, Jan Leike, Ilya Sutskever, Holden Karnofsky, Sholto Douglas, James Bradbury, Dwarkesh Patel, and many others for formative discussions. Thank you to many friends for feedback on earlier drafts. Thank you to Joe Ronan for help with graphics, and Nick Whitaker for publishing help.\n  \n\n\n   situational-awareness.ai leopold@situational-awareness.ai\n   \n    Updated June 6, 2024 San Francisco, California\n   \n\n\n\n   You can see the future first in San Francisco.\n  \n\n\n   Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there's a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.\n  \n\n\n   The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be unleashed, and before long, The Project will be on. If we're lucky, we'll be in an all-out race with the CCP; if we're unlucky, an all-out war.\n  \n\n\n   Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the willful blindness of \"it's just predicting the next word\". They see only hype and business-as-usual; at most they entertain another internet-scale technological change.\n  \n\n\n   Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have\n   \n    situational awareness\n   \n   . Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy\u2014but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people\u2014the smartest people I have ever met\u2014and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.\n  \n\n\n   Let me tell you what we see.\n  \n\n\n\n    Contents\n   \n\n\n\n\n    Introduction 3\n   \n\n\n\n\n    History is live in San Francisco.\n   \n\n\n\n\n    I. From GPT-4 to AGI: Counting the OOMs 7\n   \n\n\n\n\n    AGI by 2027 is strikingly plausible. GPT-2 to GPT-4 took us from ~preschooler to ~smart high-schooler abilities in 4 years. Tracing trendlines in compute (~0.5 orders of magnitude or OOMs/year), algorithmic efficiencies (~0.5 OOMs/year), and \"unhobbling\" gains (from chatbot to agent), we should expect another preschooler-to-high-schoolersized qualitative jump by 2027.\n   \n\n\n\n\n    II. From AGI to Superintelligence: the Intelligence Explosion 46\n   \n\n\n\n\n    AI progress won't stop at human-level. Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into 1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power\u2014and the peril\u2014of superintelligence would be dramatic.\n   \n\n\n\n\n    III. The Challenges 74\n   \n\n\n\n\n    IIIa. Racing to the Trillion-Dollar Cluster 75\n   \n\n\n\n\n    The most extraordinary techno-capital acceleration has been set in motion. As AI revenue grows rapidly, many trillions of dollars will go into GPU, datacenter, and power buildout before the end of the decade. The industrial mobilization, including growing US electricity production by 10s of percent, will be intense.\n   \n\n\n\n\n    IIIb. Lock Down the Labs: Security for AGI 89\n   \n\n\n\n\n\n\n\n    The nation's leading AI labs treat security as an afterthought. Currently, they're basically handing the key secrets for AGI to the CCP on a silver platter. Securing the AGI secrets and weights against the state-actor threat will be an immense effort, and we're not on track.\n   \n\n\n\n   4\n  \n\n\n\n    IIIc. Superalignment 105\n   \n\n\n\n\n    Reliably controlling AI systems much smarter than we are is an unsolved technical problem. And while it is a solvable problem, things could very easily go off the rails during a rapid intelligence explosion. Managing this will be extremely tense; failure could easily be catastrophic.\n   \n\n\n\n\n    IIId. The Free World Must Prevail 126\n   \n\n\n\n\n    Superintelligence will give a decisive economic and military advantage. China isn't at all out of the game yet. In the race to AGI, the free world's very survival will be at stake. Can we maintain our preeminence over the authoritarian powers? And will we manage to avoid self-destruction along the way?\n   \n\n\n\n\n    IV. The Project 141\n   \n\n\n\n\n\n\n\n    As the race to AGI intensifies, the national security state will get involved. The USG will wake from its slumber, and by 27/28 we'll get some form of government AGI project. No startup can handle superintelligence. Somewhere in a SCIF, the endgame will be on.\n   \n\n\n\n\n    V. Parting Thoughts 156\n   \n\n\n\n\n    What if we're right?\n   \n\n\n\n\n    Appendix 162\n   \n\n\n\n\n\n\n\n\n\n\n    I. From GPT-4 to AGI: Counting the OOMs\n   \n\n\n\n\n    AGI by 2027 is strikingly plausible. GPT-2 to GPT-4 took us from ~preschooler to ~smart high-schooler abilities in 4 years. Tracing trendlines in compute (~0.5 orders of magnitude or OOMs/year), algorithmic efficiencies (~0.5 OOMs/year), and \"unhobbling\" gains (from chatbot to agent), we should expect another preschooler-to-high-schooler-sized qualitative jump by 2027.\n   \n\n\n\n\n\n    Look. The models, they just want to learn. You have to understand this. The models, they just want to learn.\n   \n\n\n\n\n\n\n\n     ilya sutskever (circa 2015, via\n     \n      Dario Amodei)\n     \n\n\n\n\n\n   GPT-4's capabilities came as a shock to many: an AI system that could write code and essays, could reason through difficult math problems, and ace college exams. A few years ago, most thought these were impenetrable walls.\n  \n\n\n   But GPT-4 was merely the continuation of a decade of breakneck progress in deep learning. A decade earlier, models could barely identify simple images of cats and dogs; four years earlier, GPT-2 could barely string together semi-plausible sentences. Now we are rapidly saturating all the benchmarks we can come up with. And yet this dramatic progress has merely been the result of consistent trends in scaling up deep learning.\n  \n\n\n   There have been people who have seen this for far longer. They were scoffed at, but all they did was trust the trendlines. The\n  \n\n\n   trendlines are intense, and they were right. The models, they just want to learn; you scale them up, and they learn more.\n  \n\n\n   I make the following claim:\n   \n    it is strikingly plausible that by 2027, models will be able to do the work of an AI researcher/engineer.\n   \n   That doesn't require believing in sci-fi; it just requires believing in straight lines on a graph.\n  \n\n\n\n\n\n\n   In this piece, I will simply \"count the OOMs\" (OOM = order of magnitude, 10x = 1 order of magnitude): look at the trends in 1)\n   \n    compute\n   \n   , 2)\n   \n    algorithmic efficiencies\n   \n   (algorithmic progress that we can think of as growing \"effective compute\"), and 3)\n   \n    \"unhobbling\" gains\n   \n   (fixing obvious ways in which models are hobbled by default, unlocking latent capabilities and giving them tools, leading to step-changes in usefulness). We trace\n  \n\n\n   Figure 1: Rough estimates of past and future scaleup of effective compute (both physical compute and algorithmic efficiencies), based on the public estimates discussed in this piece. As we scale models, they consistently get smarter, and by \"counting the OOMs\" we get a rough sense of what model intelligence we should expect in the (near) future. (This graph shows only the scaleup in base models; \"unhobblings\" are not pictured.)\n  \n\n\n   the growth in each over four years before GPT-4, and what we should expect in the four years after, through the end of 2027. Given deep learning's consistent improvements for every OOM of effective compute, we can use this to project future progress.\n  \n\n\n   Publicly, things\n   \n    have been quiet\n   \n   for a year since the GPT-4 release, as the next generation of models has been in the oven leading some to proclaim stagnation and that deep learning is hitting a wall.\n   \n    1\n   \n   But by counting the OOMs, we get a peek at\n   \n    1\n   \n   Predictions they've made every year been consistently wrong about. . . what we should actually expect.\n  \n\n\n   The upshot is pretty simple. GPT-2 to GPT-4\u2014from models that were impressive for sometimes managing to string together a few coherent sentences, to models that ace high-school exams\u2014was not a one-time gain. We are racing through the OOMs extremely rapidly, and the numbers indicate we should expect another ~100,000x effective compute scaleup\u2014resulting in another GPT-2-to-GPT-4-sized qualitative jump\u2014over four years. Moreover, and critically, that doesn't just mean a better chatbot; picking the many obvious low-hanging fruit on \"unhobbling\" gains should take us from chatbots to agents, from a tool to something that looks more like drop-in remote worker replacements.\n  \n\n\n   While the inference is simple, the implication is striking. Another jump like that very well could take us to AGI, to models as smart as PhDs or experts that can work beside us as coworkers. Perhaps most importantly, if these AI systems could automate AI research itself, that would set in motion intense feedback loops\u2014the topic of the the next piece in the series.\n  \n\n\n   Even now, barely anyone is pricing all this in. But situational awareness on AI isn't actually that hard, once you step back and look at the trends. If you keep being surprised by AI capabilities, just start counting the OOMs.\n  \n\n\n   for the last decade, and which they've\n  \n\n\n\n    The last four years\n   \n\n\n\n   We have machines now that we can basically\n   \n    talk to like\n   \n\n    humans.\n   \n   It's a remarkable testament to the human capacity to adjust that this seems normal, that we've become inured to the pace of progress. But it's worth stepping back and looking at the progress of just the last few years.\n  \n\n\n\n    GPT-2 to GPT-4\n   \n\n\n\n   Let me remind you of how far we came in just the ~4 (!) years leading up to GPT-4.\n  \n\n\n\n    GPT-2\n   \n   (2019) ~\n   \n    preschooler\n   \n   : \"Wow, it can string together a few plausible sentences.\" A very-cherry-picked example of a semicoherent story about unicorns in the Andes\n   \n    it generated\n   \n   was incredibly impressive at the time. And yet GPT-2 could barely count to 5 without getting tripped up;\n   \n    2\n   \n   when summarizing an article, it just barely outperformed selecting 3 random sentences from the article.\n   \n    3\n   \n\n    3\n   \n   From the GPT-\n   \n    2\n   \n\n    paper,\n   \n   Section\n   \n    3\n   \n   .6.\n  \n\n\n\n\n\n      2 From SSC: \"Janelle Shane asks GPT-2\n     \n\n\n\n      its ten favorite animals:\n     \n\n\n\n\n\n   Prompt: My 10 favorite animals are: 1. My ten favorite animals are:\n  \n\n\n   1. Zebras with a white scar on the back\n  \n\n\n\n\n\n\n     2. Insiduous spiders and octopus\n    \n\n\n     3. Frog with large leaves, hopefully\n    \n\n\n     black\n    \n\n\n     4. Cockatiel with scales\n    \n\n\n\n   5. Razorbill with wings hanging about 4 inches from one's face and a heart tattoo on a frog\n  \n\n\n\n\n\n\n     3. Cockatric interlocking tetrabods that can be blind, cut, and eaten raw: 4. Black and white desert crocodiles\n    \n\n\n     living in sunlight 5. Zebra and many other pea bugs\"\n    \n\n\n\n\n\n\n\n\n\n\n\n      GPT-2 examples people found very impressive at the time\n     \n\n\n\n      Task\n     \n\n\n       Reading Comprehension:\n      \n      answer questions about given passages\n     \n\n      System Prompt\n      \n      (human-written)\n     \n\n      For today's homework assignment, please describe the reasons for the US Civil War.\n     \n\n\n\n      Dataset\n     \n\n      COOA\n     \n\n      Model Completion\n      \n      (machine-written, 10)\n      \n      tries)\n     \n\n      By Donny Ferquson\n      \n      It is easy to identify why the Civil War happened, because so\n      \n      many people and so many books and so much television and films\n     \n\n\n\n      Examples\n     \n\n      The trophy doesn't fit into the brown suitcase because it is too large.\n      \n\n       Correct answer:\n      \n\n       it = trophy\n      \n\n\n       Model answer:\n      \n      it = trophy\n     \n\n\n\n      tell us that it was the cause, that it has something to do with\n      \n      race or economics or religion. There is much agreement that it\n      \n      was essentially a war of slavery on behalf of capitalism, about a\n      \n      century of slavery. But that's not what most people think of when\n      \n      they think of the Civil War. Many people think of the war as\n      \n      about states rights. You're not wrong about that, but it's kind\n     \n\n\n\n\n\n      The trophy doesn't fit into the brown suitcase because it is too small.\n     \n\n\n\n      of misleading to say that the Civil War was a conflict between\n      \n      states' rights and federalism. So let's try again. What's the\n      \n      idea that has inspired so many people to go onto the battlefields\n     \n\n\n\n\n\n\n       Correct answer:\n      \n\n       it = suitable\n      \n\n      Model answer: it = suitcase\n     \n\n\n\n      of Gettysburg and Antietam and Gettysberg and Petersburg and\n      \n      Fredericksburg? The American idea of the republic--a notion of\n      \n      limited government--is a great part of the history.\n     \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   Comparing AI capabilities with human intelligence is difficult and flawed, but I think it's informative to consider the analogy\n  \n\n\n   Figure 2: Some\n   \n    examples\n   \n   of what people found impressive about GPT-2 at the time. Left: GPT-2 does an ok job on extremely basic reading comprehension questions. Right: In a cherry-picked sample (best of 10 tries), GPT-2 can write a semi-coherent paragraph that says some semi-relevant things about the Civil War.\n  \n\n\n   here, even if it's highly imperfect. GPT-2 was shocking for its command of language, and its ability to occasionally generate a semi-cohesive paragraph, or occasionally answer simple factual questions correctly. It's what would have been impressive for a preschooler.\n  \n\n\n\n    GPT-3\n   \n   (2020)\n   \n    4\n   \n   ~\n   \n    elementary schooler\n   \n   : \"Wow, with just some few-\n   \n    4\n   \n   might know from ChatGPT. shot examples it can do some simple useful tasks.\" It started being cohesive over even multiple paragraphs much more consistently, and could correct grammar and do some very basic arithmetic. For the first time, it was also commercially useful in a few narrow ways: for example, GPT-3 could generate\n   \n    simple\n   \n\n    copy\n   \n   for SEO and marketing.\n  \n\n\n   I mean clunky old GPT-3 here, not the dramatically-improved GPT-3.5 you\n  \n\n\n\n\n\n\n   Again, the comparison is imperfect, but what impressed people about GPT-3 is perhaps what would have been impressive for an elementary schooler: it wrote some basic poetry, could tell richer and coherent stories, could start to do rudimentary\n  \n\n\n   Figure 3: Some\n   \n    examples\n   \n   of what people found impressive about GPT-3 at the time. Top: After a simple instruction, GPT-3\n   \n    can\n   \n   use a made-up word in a new sentence. Bottom-left: GPT-3\n   \n    can\n   \n   engage in rich storytelling back-and-forth. Bottom-right: GPT-3\n   \n    can\n   \n   generate some very simple code.\n  \n\n\n   coding, could fairly reliably learn from simple instructions and demonstrations, and so on.\n  \n\n\n\n    GPT-4\n   \n   (2023) ~\n   \n    smart high schooler\n   \n   : \"Wow, it can write pretty sophisticated code and iteratively debug, it can write intelligently and sophisticatedly about complicated subjects, it can reason through difficult high-school competition math, it's beating the vast majority of high schoolers on whatever tests we can give it, etc.\" From code to math to Fermi estimates, it can think and reason. GPT-4 is now useful in my daily tasks, from helping write code to revising drafts.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 4: Some of what people found impressive about GPT-4 when it was released, from the\n   \n    \"Sparks of AGI\"\n   \n   paper. Top: It's writing very complicated code (producing the plots shown in the middle) and can reason through nontrivial math problems. Bottom-left: Solving an AP math problem. Bottom-right: Solving a fairly complex coding problem. More interesting excerpts from that exploration of GPT-4's capabilities\n   \n    here.\n   \n\n\n\n   On everything from AP exams to the SAT, GPT-4 scores better than the vast majority of high schoolers.\n  \n\n\n   Of course, even GPT-4 is still somewhat uneven; for some tasks it's much better than smart high-schoolers, while there are other tasks it can't yet do. That said, I tend to think most of these limitations come down to obvious ways models are still hobbled, as I'll discuss in-depth later. The raw intelligence is (mostly) there, even if the models are still artificially constrained; it'll take extra work to unlock models being able to fully apply that raw intelligence across applications.\n  \n\n\n\n\n\n\n   Figure 5: Progress over just four years. Where are\n   \n    you\n   \n   on this line?\n  \n\n\n\n    The trends in deep learning\n   \n\n\n\n   The pace of deep learning progress in the last decade has simply been extraordinary. A mere decade ago it was revolutionary for a deep learning system to identify simple images. Today, we keep trying to come up with novel, ever harder tests, and yet each new benchmark is quickly cracked. It used to take decades to crack widely-used benchmarks; now it feels like mere months.\n  \n\n\n   We're literally running out of benchmarks. As an anecdote, my friends Dan and Collin made a benchmark called\n   \n    MMLU\n   \n   a few years ago, in 2020. They hoped to finally make a benchmark that would stand the test of time, equivalent to all the hardest exams we give high school and college students. Just three years later, it's basically solved: models like GPT-4 and Gemini\n  \n\n\n\n\n\n\n\n\n\n   Figure 6: Deep learning systems are rapidly reaching or exceeding humanlevel in many domains. Graphic:\n   \n    Our\n   \n\n    World in Data\n   \n\n\n\n   get ~90%.\n  \n\n\n   More broadly, GPT-4 mostly cracks all the standard high school and college aptitude tests (Figure 7).\n   \n    5\n   \n\n    5\n   \n   And no, these tests aren't in the train-\n  \n\n\n   Or consider the\n   \n    MATH benchmark,\n   \n   a set of difficult mathematics problems from high-school math competitions.\n   \n    6\n   \n   When the benchmark was released in 2021, GPT-3 only got ~5% of problems right. And the original paper noted: \"Moreover, we find that simply increasing budgets and model parameter counts will be impractical for achieving strong mathematical reasoning if scaling trends continue [...]. To have more traction on mathematical problem solving we will likely need new algorithmic advancements from the broader research community\"\u2014we would need fundamental new breakthroughs to solve MATH, or so they thought. A survey of\n   \n    ML researchers predicted\n   \n   minimal progress over the coming years (Figure 8);\n   \n    7\n   \n   and yet within\n   \n    7\n   \n   A coauthor\n   \n    notes:\n   \n   \"When our group just a year (by mid-2022), the best models went from ~5% to 50\n   \n    % accuracy;\n   \n   now,\n   \n    MATH is basically solved,\n   \n   with recent performance over 90%.\n  \n\n\n   ing set. AI labs put real effort into ensuring these evals are uncontaminated, because they need good measurements in order to do good science. A\n   \n    recent\n   \n\n    analysis on this by ScaleAI\n   \n   confirmed that the leading labs aren't overfitting to the benchmarks (though some smaller LLM developers might be juicing their numbers).\n  \n\n\n   6 In the original paper, it was noted: \"We also evaluated humans on MATH, and found that a computer science PhD student who does not especially like mathematics attained approximately 40% on MATH, while a three-time IMO gold medalist attained 90%, indicating that MATH can be challenging for humans as well.\"\n  \n\n\n   first released the MATH dataset, at least one [ML researcher colleague] told us that it was a pointless dataset because it was too far outside the range of what ML models could accomplish (indeed, I was somewhat worried about this myself).\"\n  \n\n\n\n\n\n\n\n\n       GPT-4\n      \n\n      (2023)\n     \n\n\n       GPT-3.5\n      \n\n      (2022)\n     \n\n\n\n      Uniform Bar Exam\n     \n\n      90th\n     \n\n      10th\n     \n\n\n\n\n       LSAT\n      \n\n\n      88th\n     \n\n      40th\n     \n\n\n\n\n       SAT\n      \n\n\n      97th\n     \n\n      87th\n     \n\n\n\n\n       GRE\n      \n      (Verbal)\n     \n\n      99\n      \n       th\n      \n\n\n      63rd\n     \n\n\n\n\n       GRE\n      \n      (Quantitative)\n     \n\n      80th\n     \n\n      25\n      \n       th\n      \n\n\n\n\n\n       US Biology Olympiad\n      \n\n\n      99th\n     \n\n      32nd\n     \n\n\n\n\n       AP Calculus BC\n      \n\n\n      51st\n     \n\n      3rd\n     \n\n\n\n\n       AP Chemistry\n      \n\n\n      80th\n     \n\n      34th\n     \n\n\n\n\n       AP Macroeconomics\n      \n\n\n      92nd\n     \n\n      40th\n     \n\n\n\n\n       AP\n      \n      Statistics\n     \n\n      92nd\n     \n\n      51st\n     \n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 7: GPT-4\n   \n    scores\n   \n   on standardized tests. Note also the large jump from GPT-3.5 to GPT-4 in human percentile on these tests, often from well below the median human to the very top of the human range. (And this is GPT-3.5, a fairly recent model released less than a year before GPT-4, not the clunky old elementary-school-level GPT-3 we were talking about earlier!)\n  \n\n\n   Figure 8: Gray: Professional forecasts, made in August 2021, for June 2022 performance on the MATH benchmark (difficult mathematics problems from high-school math competitions). Red star: actual state-of-the-art performance by June 2022, far exceeding even the upper range forecasters gave. The median ML researcher was\n   \n    even more\n   \n\n    pessimistic.\n   \n\n\n\n   Over and over again, year after year, skeptics have claimed \"deep learning won't be able to do X\" and have been quickly proven wrong.\n   \n    8\n   \n\n    If there's one lesson we've learned from the past\n   \n\n    8\n   \n   Here's Yann LeCun\n   \n    predicting\n   \n   in 2022\n   \n    decade of AI, it's that you should never bet against deep learning.\n   \n\n\n\n   Now the hardest unsolved benchmarks are tests like\n   \n    GPQA,\n   \n   a set of PhD-level biology, chemistry, and physics questions. Many of the questions read like gibberish to me, and even PhDs in other scientific fields spending 30+ minutes with Google barely score above random chance. Claude 3 Opus currently gets ~60%,\n   \n    9\n   \n   compared to in-domain PhDs who get ~80%\u2014and I expect this benchmark to fall as well, in the next generation or two.\n  \n\n\n   that even GPT-5000 won't be able to reason about physical interactions with the real world; GPT-4 obviously does it with ease a year later.\n  \n\n\n   Here's Gary Marcus's walls predicted after GPT-2\n   \n    being solved\n   \n   by GPT-3, and the walls he predicted after GPT-3\n   \n    being\n   \n\n    solved\n   \n   by GPT-4.\n  \n\n\n   Here's Prof. Bryan Caplan\n   \n    losing\n   \n   his first-ever public bet (after previously famously having a perfect public betting track record). In January 2023, after GPT-3.5 got a D on his economics midterm, Prof. Caplan\n   \n    bet\n   \n   Matthew Barnett that no AI would get an A on his economics midterms by\n   \n    2029.\n   \n   Just two months later, when GPT-4 came out, it promptly scored an A on his midterm (and it would have been one of the highest scores in his class).\n  \n\n\n\n    9\n   \n   On the\n   \n    diamond set, majority voting\n   \n   of the model trying 32 times with chain-of-thought.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 9: Example GPQA questions. Models are already better at this than I am, and we'll probably crack expert-PhD-level soon. . .\n  \n\n\n\n    Counting the OOMs\n   \n\n\n\n   How did this happen? The magic of deep learning is that it\n   \n    just works\n   \n   \u2014and the trendlines have been astonishingly consistent, despite naysayers at every turn.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n    With each OOM of effective compute, models predictably, reliably get\n   \n   pute, in the example of\n   \n    OpenAI Sora.\n   \n\n    better.\n   \n\n    10\n   \n   If we can count the OOMs, we can (roughly, qualita-\n   \n    10\n   \n   And it's worth noting\n   \n    just how con\n   \n   tively) extrapolate capability improvements.\n   \n    11\n   \n   That's how a few prescient individuals saw GPT-4 coming.\n  \n\n\n   We can decompose the progress in the four years from GPT-2 to GPT-4 into three categories of scaleups:\n  \n\n\n\n\n\n\n     1. compute: We're using much bigger computers to train these models.\n    \n\n\n     2. algorithmic efficiencies: There's a continuous trend of algorithmic progress. Many of these act as \"compute multipliers,\" and we can put them on a unified scale of growing\n     \n      effective compute\n     \n     .\n    \n\n\n     3. \"unhobbling\" gains: By default, models learn a lot of amazing raw capabilities, but they are hobbled in all sorts of dumb ways, limiting their practical value. With simple algorithmic improvements like reinforcement learning from human feedback (RLHF), chain-of-thought (CoT), tools, and scaffolding, we can unlock significant latent capabilities.\n    \n\n\n\n   Figure 10: The effects of scaling com-\n  \n\n\n\n    sistent\n   \n   these trendlines are. Combining the original\n   \n    scaling laws paper\n   \n   with some of the estimates on compute and compute efficiency scaling since then implies a consistent scaling trend for\n   \n    over 15 orders of magnitude\n   \n   (over 1,000,000,000,000,000x in effective compute)!\n  \n\n\n\n    11\n   \n   A common misconception is that scaling only holds for perplexity loss, but we see very clear and consistent scaling behavior on downstream performance on benchmarks as well. It's usually just a matter of finding the right loglog graph. For example, in the GPT-4 blog post, they show consistent scaling behavior for performance on coding problems over 6 OOMs (1,000,000x) of compute, using MLPR (mean log pass rate).\n  \n\n\n   The\n   \n    \"Are Emergent Abilities a Mi\n   \n\n    rage?\"\n   \n   paper makes a similar point; with the right choice of metric, there is almost always a consistent trend for performance on downstream tasks.\n  \n\n\n   More generally, the \"scaling hypothesis\" qualitative observation\u2014very clear trends on model capability with scale\u2014predates loss-scaling-curves; the \"scaling laws\" work was just a formal measurement of this.\n  \n\n\n   We can \"count the OOMs\" of improvement along these axes: that is, trace the scaleup for each in units of effective compute. 3x is 0.5 OOMs; 10x is 1 OOM; 30x is 1.5 OOMs; 100x is 2 OOMs; and so on. We can also look at what we should expect on top of GPT-4, from 2023 to 2027.\n  \n\n\n   I'll go through each one-by-one, but the upshot is clear: we are rapidly racing through the OOMs. There are potential headwinds in the data wall, which I'll address\u2014but overall, it seems likely that we should expect another GPT-2-to-GPT-4-sized jump, on top of GPT-4, by 2027.\n  \n\n\n\n    Compute\n   \n\n\n\n   I'll start with the most commonly-discussed driver of recent progress: throwing (a lot) more compute at models.\n  \n\n\n   Many people assume that this is simply due to Moore's Law. But even in the old days when Moore's Law was in its heyday, it was comparatively\n   \n    glacial\n   \n   \u2014perhaps 1-1.5 OOMs per decade. We are seeing much more rapid scaleups in compute\u2014close to 5x the speed of Moore's law\u2014instead because of mammoth\n   \n    investment\n   \n   . (Spending even a million dollars on a single model used to be an outrageous thought nobody would entertain, and now that's pocket change!)\n  \n\n\n\n\n\n      Model\n     \n\n      Estimated Compute\n     \n\n      Growth\n     \n\n\n\n      GPT-2\n      \n      (2019)\n     \n\n      ~4e21\n      \n      FLOP\n     \n\n\n\n\n\n      GPT-3\n      \n      (2020)\n     \n\n      ~3e23\n      \n      FLOP\n     \n\n      + ~2\n      \n      OOMs\n     \n\n\n\n      GPT-4\n      \n      (2023)\n     \n\n      8e24\n      \n      to 4e25\n      \n      FLOP\n     \n\n      + ~1.5\u20132\n      \n      OOMs\n     \n\n\n\n\n\n   Table 1: Estimates of compute for GPT-2 to GPT-4 by\n   \n    Epoch AI.\n   \n\n\n\n   We can use public estimates from Epoch AI (a source widely respected for its excellent analysis of AI trends) to trace the compute scaleup from 2019 to 2023. GPT-2 to GPT-3 was a quick scaleup; there was a large overhang of compute, scaling from a smaller experiment to using an entire datacenter to train a large language model. With the scaleup from GPT-3 to GPT-4, we transitioned to the modern regime: having to build an entirely new (much bigger) cluster for the next model. And yet\n  \n\n\n   the dramatic growth continued. Overall, Epoch AI estimates suggest that GPT-4 training used ~3,000x-10,000x more raw compute than GPT-2.\n  \n\n\n   In broad strokes, this is just the continuation of a longer-running trend. For the last decade and a half, primarily because of broad scaleups in investment (and specializing chips for AI workloads in the form of GPUs and TPUs), the training compute used for frontier AI systems has grown at roughly ~0.5 OOMs/year.\n  \n\n\n\n\n\n\n\n\n\n\n   The compute scaleup from GPT-2 to GPT-3 in a year was an unusual overhang, but all the indications are that the longerrun trend will continue. The SF-rumor-mill is abreast with dramatic tales of huge GPU orders. The investments involved will be extraordinary\u2014but they are in motion. I go into this more later in the series, in IIIa. Racing to the Trillion-Dollar Cluster; based on that analysis, an additional 2 OOMs of compute (a cluster in the $10s of billions) seems very likely to happen by the end of 2027; even a cluster closer to +3 OOMs of compute ($100 billion+) seems plausible (and is\n   \n    rumored to be in the\n   \n\n    works\n   \n   at Microsoft/OpenAI).\n  \n\n\n\n    Algorithmic efficiencies\n   \n\n\n\n   While massive investments in compute get all the attention, algorithmic progress is probably a similarly important driver of progress (and has been dramatically underrated).\n  \n\n\n   To see just how big of a deal algorithmic progress can be, consider the following illustration (Figure 12) of the drop in price to attain ~50% accuracy on the MATH benchmark (high school competition math) over just\n   \n    two years.\n   \n   (For comparison, a computer science PhD student who didn't particularly like math scored 40%, so this is already quite good.) Inference efficiency improved by nearly 3 OOMs\u20141,000x\u2014in less than two years.\n  \n\n\n\n\n\n\n   Though these are numbers just for inference efficiency (which may or may not correspond to training efficiency improvements, where numbers are harder to infer from public data), they make clear there is an\n   \n    enormous\n   \n   amount of algorithmic progress possible and happening.\n  \n\n\n   Figure 12: Rough estimate on relative inference cost of attaining ~50% MATH performance.\n  \n\n\n\n    Calculations below.\n   \n\n\n\n   Gemini 1.5 Flash\n   \n    scores\n   \n   54.9% on MATH, and\n   \n    costs\n   \n   $0.35/$1.05 (input/output) per million tokens. GPT-4 scored 42.5% on MATH\n   \n    prelease\n   \n   and\n   \n    52\n   \n   .9% on MATH in early 2023, and\n   \n    cost\n   \n   $30/$60 (input/output) per million tokens; that's 85x/57x (input/output) more expensive per token than Gemini 1.5 Flash. To be conservative, I use an estimate of 30x cost decrease above (accounting for Gemini 1.5 Flash possibly using more tokens to reason through problems).\n  \n\n\n   Minerva540B\n   \n    scores\n   \n   50.3% on MATH, using majority voting among 64 samples. A knowledgeable friend estimates the base model here is probably 2- 3x more expensive to inference than GPT-4. However, Minerva seems to use somewhat fewer tokens per answer on a quick spot check. More importantly, Minerva needed 64 samples to achieve that performance, naively implying a 64x multiple on cost if you e.g. naively ran this via an inference API. In practice, prompt tokens can be cached when running an eval; given a few-shot prompt, prompt tokens are likely a majority of the cost, even accounting for output tokens. Supposing output tokens are a third of the cost for getting a single sample, that would imply only a ~20x increase in cost from the maj@64 with caching. To be conservative, I use the rough number of a 20x cost decrease in the above (even if the naive decrease in inference cost from running this via an API would be larger).\n  \n\n\n   In this piece, I'll separate out two kinds of algorithmic progress. Here, I'll start by covering \"within-paradigm\" algorithmic improvements\u2014those that simply result in better base models, and that straightforwardly act as\n   \n    compute efficiencies\n   \n   or\n   \n    compute multipliers\n   \n   . For example, a better algorithm might allow us to achieve the same performance but with 10x less training compute. In turn, that would act as a 10x (1 OOM) increase in\n   \n    effective compute\n   \n   . (Later, I'll cover \"unhobbling,\" which you can think of as \"paradigm-expanding/application-expanding\" algorithmic progress that unlocks capabilities of base models.)\n  \n\n\n   If we step back and look at the long-term trends, we seem to find new algorithmic improvements at a fairly consistent rate. Individual discoveries seem random, and at every turn, there seem insurmountable obstacles\u2014but the long-run trendline is predictable, a straight line on a graph. Trust the trendline.\n  \n\n\n   We have the best data for ImageNet (where algorithmic research has been mostly public and we have data stretching back a decade), for which we have consistently improved compute efficiency by roughly ~0.5 OOMs/year across the 9-year period between 2012 and 2021.\n  \n\n\n\n\n\n\n\n\n\n   That's a huge deal: that means 4 years later, we can achieve the same level of performance for ~100x less compute (and concomitantly, much higher performance for the same compute!).\n  \n\n\n   Unfortunately, since labs don't publish internal data on this, it's harder to measure algorithmic progress for frontier LLMs\n  \n\n\n   Figure 13: We can measure algorithmic progress: how much less compute is needed in 2021 compared to 2012 to train a model with the same performance? We see a trend of ~0.5 OOMs/year of algorithmic efficiency. Source:\n   \n    Erdil and Besiroglu\n   \n   2022.\n  \n\n\n   over the last four years.\n   \n    EpochAI has new work\n   \n   replicating their results on ImageNet for language modeling, and estimate a similar ~0.5 OOMs/year of algorithmic efficiency trend in LLMs from 2012 to 2023. (This has wider error bars though, and doesn't capture some more recent gains, since the leading labs have stopped publishing their algorithmic efficiencies.)\n  \n\n\n\n\n\n\n\n\n\n   More directly looking at the last 4 years, GPT-2 to GPT-3 was basically a simple scaleup (according to\n   \n    the paper)\n   \n   , but there have been many publicly-known and publicly-inferable gains since GPT-3:\n  \n\n\n\n\n\n\n     We can infer gains from API costs:\n     \n      12\n     \n\n\n\n\n\n        \u2013\n       \n       GPT-4, on release, cost ~the same as GPT-3 when it was released, despite the absolutely enormous performance increase.\n       \n        13\n       \n       (If we do a naive and oversimplified back-of-theenvelope estimate based on scaling laws, this suggests that perhaps roughly half the effective compute increase from GPT-3 to GPT-4 came from algorithmic improvements.14)\n      \n\n\n\n\n\n\n        \u2013\n       \n       Since the GPT-4 release a year ago, OpenAI prices for GPT-4-level models have fallen another 6x/4x (input/output) with the release of GPT-4o.\n      \n\n\n\n\n\n\n\n\n\n\n    12\n   \n   Though these are inference efficiencies (rather than necessarily training efficiencies), and to some extent will reflect inference-specific optimizations, a) they suggest enormous amounts of algorithmic progress is possible and happening in general, and b) it's often the case that an algorithmic improvements is both a training efficiency gain and an inference efficiency, for example by reducing the number of parameters necessary.\n  \n\n\n\n    13\n   \n\n    GPT-\n   \n   3: $60/1M tokens,\n   \n    GPT-\n   \n   4: $30/1M input tokens and $60/1M output tokens.\n  \n\n\n\n    14\n   \n   Chinchilla scaling laws say that one should scale parameter count and data equally. That is, parameter count grows \"half the OOMs\" of the OOMs that effective training compute grows. At the same time, parameter count is intuitively roughly proportional to inference costs. All else equal, constant inference costs thus implies that half of the OOMs of effective compute growth were \"canceled out\" by algorithmic win.\n  \n\n\n   That said, to be clear, this is a very naive calculation (just meant for a rough illustration) that is wrong in various ways. There may be inferencespecific optimizations (that don't translate into training efficiency); there may be training efficiencies that don't reduce parameter count (and thus don't translate into inference efficiency); and so on.\n  \n\n\n\n\n\n\n\n      \u2013\n     \n     Gemini 1.5 Flash, recently released, offers between \"GPT-3.75-level\" and GPT-4-level performance,\n     \n      15\n     \n     while\n     \n      costing\n     \n\n      15\n     \n     Gemini\n     \n      1\n     \n     .\n     \n      5\n     \n     Flash ranks similarly to 85x/57x (input/output) less than the original GPT-4 (extraordinary gains!).\n    \n\n\n\n      Chinchilla scaling laws\n     \n     give a 3x+ (0.5 OOMs+) efficiency gain.\n     \n      16\n     \n\n\n\n     Gemini 1.5 Pro claimed\n     \n      major compute efficiency gains\n     \n     (outperforming Gemini 1.0 Ultra, while using \"significantly less\" compute), with Mixture of Experts (MoE) as a highlighted architecture change.\n     \n      Other\n     \n\n      papers\n     \n\n      also\n     \n\n      claim\n     \n     a substantial multiple on compute from MoE.\n    \n\n\n     There have been many tweaks and gains on\n     \n      architecture,\n     \n\n      data,\n     \n\n      training stack,\n     \n\n      etc.\n     \n     all the time.\n     \n      17\n     \n\n\n\n\n   Put together, public information suggests that the GPT-2 to scale. GPT-4 jump included 1-2 OOMs of algorithmic efficiency gains.\n   \n    18\n   \n\n\n\n\n\n\n\n   GPT-4 (higher than original GPT-4, lower than updated versions of GPT-4)\n   \n    on LMSys, a chatbot leaderboard,\n   \n   and has\n   \n    similar performance\n   \n   on MATH and GPQA (evals that measure reasoning) as the original GPT-4, while landing roughly in the middle between GPT-3.5 and GPT-4 on MMLU (an eval that more heavily weights towards measuring knowledge).\n  \n\n\n\n    16\n   \n\n    At ~GPT-\n   \n   3 scale, more than 3x at larger scales.\n  \n\n\n\n    17\n   \n   For example,\n   \n    this paper\n   \n   contains a comparison of a GPT-3-style vanilla Transformer to various simple changes to architecture and training recipe published over the years (RMSnorms instead of layernorm, different positional embeddings, SwiGlu activation, AdamW optimizer instead of Adam, etc.), what they call \"Transformer++\", implying a 6x gain at least at small\n  \n\n\n\n    18\n   \n   If we take the trend of 0.5 OOMs/year, and 4 years between GPT-2 and GPT-4 release, that would be 2 OOMs. However, GPT-2 to GPT-3 was a simple scaleup (after big gains from e.g. Transformers), and OpenAI claims GPT-4\n   \n    pretraining finished in\n   \n\n    2022\n   \n   , which could mean we're looking at closer to 2 years worth of algorithmic progress that we should be counting here. 1 OOM of algorithmic efficiency seems like a conservative lower bound.\n  \n\n\n   Figure 15: Decomposing progress: compute and algorithmic efficiencies. (Rough illustration.)\n  \n\n\n   Over the 4 years following GPT-4, we should expect the trend to continue:\n   \n    19\n   \n   on average ~0.5 OOMs/year of compute effi-\n   \n    19\n   \n   At the very least, given over a decade ciency, i.e. ~2 OOMs of gains compared to GPT-4 by 2027. While compute efficiencies will become harder to find as we pick the low-hanging fruit, AI lab investments in money and talent to find new algorithmic improvements are growing rapidly.\n   \n    20\n   \n   (The publicly-inferable inference cost efficiencies,\n   \n    20\n   \n   The economic returns to a\n   \n    3\n   \n   x compute of billions or more, given cluster costs. at least, don't seem to have slowed down at all.) On the high end, we could even see more fundamental, Transformer-like\n   \n    21\n   \n   breakthroughs with even bigger gains.\n   \n    gain.\n   \n\n\n\n   Put together, this suggests we should expect something like 1-3 OOMs of algorithmic efficiency gains (compared to GPT-4) by the end of 2027, maybe with a best guess of ~2 OOMs.\n  \n\n\n\n    The data wall\n   \n\n\n\n   There is a potentially important source of variance for all of this: we're running out of internet data. That could mean that, very soon, the naive approach to pretraining larger language models on more scraped data could start hitting serious bottlenecks.\n  \n\n\n   Frontier models are already trained on much of the internet. Llama 3, for example, was trained on over 15\n   \n    T tokens.\n   \n   Common Crawl, a dump of much of the internet\n   \n    used for\n   \n\n    LLM training,\n   \n   is >100T tokens raw, though much of that is spam and duplication (e.g., a\n   \n    relatively simple deduplica\n   \n\n    tion\n   \n   leads to 30T tokens, implying Llama 3 would already be using basically all the data). Moreover, for more specific domains like code, there are many fewer tokens still, e.g.\n   \n    public github repos\n   \n   are estimated to be in low trillions of tokens.\n  \n\n\n   You can go somewhat further by repeating data, but\n   \n    aca\n   \n\n    demic work on this\n   \n   suggests that repetition only gets you so far, finding that after 16 epochs (a 16-fold repetition), returns diminish extremely fast to nil. At some point, even with more (effective) compute, making your models better can become much tougher because of the data constraint. This isn't to be understated: we've been riding the\n  \n\n\n   of consistent algorithmic improvements, the burden of proof would be on those who would suggest it will all suddenly come to a halt!\n  \n\n\n   efficiency will be measured in the $10s\n   \n    21\n   \n   Very roughly something like a ~\n   \n    10\n   \n   x\n  \n\n\n   scaling curves, riding the wave of the language-modelingpretraining-paradigm, and without something new here, this paradigm will (at least naively) run out. Despite the massive investments, we'd plateau.\n  \n\n\n   All of the labs are rumored to be making massive research bets on new algorithmic improvements or approaches to get around this. Researchers are purportedly trying many strategies, from\n   \n    synthetic data to self-play and RL ap\n   \n\n    proaches.\n   \n   Industry insiders seem to be very bullish: Dario Amodei (CEO of Anthropic)\n   \n    recently said on a podcast:\n   \n   \"if you look at it very naively we're not that far from running out of data [. . . ] My guess is that this will not be a blocker [. . . ] There's just many different ways to do it.\" Of course, any research results on this are proprietary and not being published these days.\n  \n\n\n   In addition to insider bullishness, I think there's a strong intuitive case for why it should be possible to find ways to train models with much better sample efficiency (algorithmic improvements that let them learn more from limited data). Consider how you or I would learn from a really dense math textbook:\n  \n\n\n\n\n\n\n     What a modern LLM does during training is, essentially, very very quickly skim the textbook, the words just\n     \n      flying by\n     \n     , not spending much brain power on it.\n    \n\n\n     Rather, when you or I read that math textbook, we read a couple pages slowly; then have an internal monologue about the material in our heads and talk about it with a few study-buddies; read another page or two; then try some practice problems, fail, try them again in a different way, get some feedback on those problems, try again until we get a problem right; and so on, until eventually the material \"clicks.\"\n    \n\n\n     You or I also wouldn't learn much at all from a pass through a dense math textbook if all we could do was breeze through it like LLMs.\n     \n      22\n     \n\n      22\n     \n     And just rereading the same textbook\n    \n\n\n\n   over and over again might result in memorization, not understanding. I take it that's how many wordcels pass math classes!\n  \n\n\n   \u2022 But perhaps, then, there are ways to incorporate aspects of how humans would digest a dense math textbook to let the models learn much more from limited data. In a simplified sense, this sort of thing\u2014having an internal monologue about material, having a discussion with a study-buddy, trying and failing at problems until it clicks\u2014is what many synthetic data/self-play/RL approaches are trying to do.\n   \n    23\n   \n\n\n\n   The old state of the art of training models was simple and naive, but it worked, so nobody really tried hard to crack these approaches to sample efficiency. Now that it may become more of a constraint, we should expect all the labs to invest billions of dollars and their smartest minds into cracking it. A common pattern in deep learning is that it takes\n   \n    a lot\n   \n   of effort (and many failed projects) to get the details right, but eventually some version of the obvious and simple thing just works. Given how deep learning has managed to crash through every supposed wall over the last decade, my base case is that it will be similar here.\n  \n\n\n   Moreover, it actually seems possible that cracking one of these algorithmic bets like synthetic data could dramatically\n   \n    improve\n   \n   models. Here's an intuition pump. Current frontier models like Llama 3 are trained on the internet and the internet is mostly crap, like e-commerce or SEO or whatever. Many LLMs spend the vast majority of their training compute on this crap, rather than on really highquality data (e.g. reasoning chains of people working through difficult science problems). Imagine if you could spend GPT-4-level compute on entirely extremely highquality data\u2014it could be a much, much more capable model.\n  \n\n\n   A look back at AlphaGo\u2014the first AI system that beat the world champions at Go, decades before it was thought possible\u2014is useful here as well.\n   \n    24\n   \n\n    24\n   \n   See also Andrej Karpathy's talk\n  \n\n\n   \u2022 In step 1, AlphaGo was trained by imitation learning on expert human Go games. This gave it a foundation.\n  \n\n\n\n    23\n   \n   One other way of thinking about it I find interesting: there is a \"missingmiddle\" between pretraining and in-context learning.\n  \n\n\n   In-context learning is\n   \n    incredible\n   \n   (and competitive with human sample efficiency). For example, the\n   \n    Gemini\n   \n   1.5\n   \n    Pro paper\n   \n   discusses giving the model instructional materials (a textbook, a dictionary) on Kalamang, a language spoken by fewer than 200 people and basically not present on the internet, in context\u2014and the model learns to translate from English to Kalamang at human-level! In context, the model is able to learn from the textbook as well as a human could (and much better than it would learn from just chucking that one textbook into pretraining).\n  \n\n\n   When a human learns from a textbook, they're able to distill their shortterm memory/learnings into long-term memory/long-term skills with practice; however, we don't have an equivalent way to distill in-context learning \"back to the weights.\" Synthetic data/selfplay/RL/etc are trying to fix that: let the model learn by itself, then think about it and practice what it learned, distilling that learning back into the weights.\n  \n\n\n   discussing this\n   \n    here.\n   \n\n\n\n   \u2022 In step 2, AlphaGo played millions of games against itself. This let it become superhuman at Go: remember the famous move 37 in the game against Lee Sedol, an extremely unusual but brilliant move a human would never have played.\n  \n\n\n   Developing the equivalent of step 2 for LLMs is a key research problem for overcoming the data wall (and, moreover, will ultimately be the key to surpassing human-level intelligence).\n  \n\n\n   All of this is to say that data constraints seem to inject large error bars either way into forecasting the coming years of AI progress. There's a very real chance things stall out (LLMs might still be as big of a deal as the internet, but we wouldn't get to truly crazy AGI). But I think it's reasonable to guess that the labs will crack it, and that doing so will not just keep the scaling curves going, but possibly enable huge gains in model capability.\n  \n\n\n   As an aside, this also means that we should expect more variance between the different labs in coming years compared to today. Up until recently, the state of the art techniques were published, so everyone was basically doing the same thing. (And new upstarts or open source projects could easily compete with the frontier, since the recipe was published.) Now, key algorithmic ideas are becoming increasingly proprietary. I'd expect labs' approaches to diverge much more, and some to make faster progress than others\u2014even a lab that seems on the frontier now could get stuck on the data wall while others make a breakthrough that lets them race ahead. And open source will have a much harder time competing. It will certainly make things interesting. (And if and when a lab figures it out, their breakthrough will be the key to AGI, key to superintelligence\u2014one of the United States' most prized secrets.)\n  \n\n\n\n    Unhobbling\n   \n\n\n\n   Finally, the hardest to quantify\u2014but no less important\u2014category of improvements: what I'll call \"unhobbling.\"\n  \n\n\n   Imagine if when asked to solve a hard math problem, you had to instantly answer with the very first thing that came to mind. It seems obvious that you would have a hard time, except for the simplest problems. But until recently, that's how we had LLMs solve math problems. Instead, most of us work through the problem step-by-step on a scratchpad, and are able to solve much more difficult problems that way. \"Chain-of-thought\" prompting unlocked that for LLMs. Despite excellent raw capabilities, they were much worse at math than they could be because they were hobbled in an obvious way, and it took a small algorithmic tweak to unlock much greater capabilities.\n  \n\n\n   We've made huge strides in \"unhobbling\" models over the past few years. These are algorithmic improvements beyond just training better base models\u2014and often only use a fraction of pretraining compute\u2014that unleash model capabilities:\n  \n\n\n\n\n\n\n\n      Reinforcement learning from human feedback (RLHF)\n     \n     . Base models have incredible\n     \n      latent\n     \n     capabilities,\n     \n      25\n     \n     but they're raw and\n     \n      25\n     \n     That's the magic of unsupervised incredibly hard to work with. While the popular conception of RLHF is that it merely censors swear words, RLHF has been key to making models actually useful and commercially valuable (rather than making models predict random internet text, get them to actually apply their capabilities to try to answer your question!). This was the magic of ChatGPT\u2014well-done RLHF made models usable and useful to real people for the first time. The original\n     \n      InstructGPT\n     \n\n      paper\n     \n     has a great quantification of this: an RLHF'd small model was equivalent to a non-RLHF'd >100x larger model in terms of human rater preference.\n    \n\n\n\n      Chain of Thought (CoT)\n     \n     . As discussed.\n     \n      CoT started being\n     \n\n      widely used just\n     \n     2 years ago and can provide the equivalent of a >10x effective compute increase on math/reasoning problems.\n    \n\n\n\n      Scaffolding\n     \n     . Think of CoT++: rather than just asking a model\n    \n\n\n\n   learning, in some sense: to better predict the next token, to make perplexity go down, models learn incredibly rich internal representations, everything from\n   \n    (famously)\n   \n   sentiment to complex world models. But, out of the box, they're hobbled: they're using their incredible internal representations merely to predict the next token in random internet text, and rather than applying them in the best way to actually try to solve your problem.\n  \n\n\n   to solve a problem, have one model make a plan of attack, have another propose a bunch of possible solutions, have another critique it, and so on. For\n   \n    example,\n   \n   on HumanEval (coding problems), simple scaffolding enables GPT-3.5 to outperform un-scaffolded GPT-4. On SWE-Bench (a benchmark of solving real-world software engineering tasks), GPT-4 can only solve ~2% correctly, while with\n   \n    Devin's agent\n   \n\n    scaffolding\n   \n   it jumps to 14-23%. (Unlocking agency is only in its infancy though, as I'll discuss more later.)\n  \n\n\n\n\n\n\n\n      Tools:\n     \n     Imagine if humans weren't allowed to use calculators or computers. We're only at the beginning here, but Chat-GPT can now use a web browser, run some code, and so on.\n    \n\n\n\n      Context length\n     \n     . Models have gone from 2k token context (GPT-3) to 32k context (GPT-4 release) to 1M+ context (Gemini 1.5 Pro). This is a\n     \n      huge\n     \n     deal. A much smaller base model with, say, 100k tokens of relevant context can outperform a model that is much larger but only has, say, 4k relevant tokens of context\u2014more context is effectively a large compute efficiency gain.\n     \n      26\n     \n     More generally, context is key to unlock-\n     \n      26\n     \n     See Figure\n     \n      7\n     \n     from the\n     \n      updated Gem\n     \n     ing many applications of these models: for example, many coding applications require understanding large parts of a codebase in order to usefully contribute new code; or, if you're using a model to help you write a document at work, it really needs the context from lots of related internal docs and conversations. Gemini 1.5 Pro, with its 1M+ token context, was\n     \n      even able\n     \n     to learn a new language (a low-resource language not on the internet) from scratch, just by putting a dictionary and grammar reference materials in context!\n    \n\n\n\n      Posttraining improvements.\n     \n     The current GPT-4 has substantially improved compared to the original GPT-4 when released,\n     \n      according to John Schulman\n     \n     due to posttraining improvements that unlocked latent model capability: on\n     \n      reasoning evals\n     \n     it's made substantial gains (e.g., ~50% -> 72% on MATH, ~40% to ~50% on GPQA) and on the\n     \n      LMSys\n     \n\n      leaderboard,\n     \n     it's made nearly 100-point elo jump (comparable to the difference in elo between Claude 3 Haiku and the much larger Claude 3 Opus, models that have a ~50x\n     \n      price\n     \n\n      difference)\n     \n     .\n    \n\n\n\n   ini 1.5\n   \n    whitepaper,\n   \n   comparing perplexity vs. context for Gemini 1.5 Pro and Gemini 1.5 Flash (a much cheaper and presumably smaller model).\n  \n\n\n\n    A survey by Epoch AI\n   \n   of some of these techniques, like scaffolding, tool use, and so on, finds that techniques like this can typically result in effective compute gains of 5-30x on many benchmarks. METR (an organization that evaluates models) similarly found very large performance improvements on their set of agentic tasks, via unhobbling from the same GPT-4 base model: from 5% with just the base model, to 20% with the GPT-4 as posttrained on release, to nearly 40% today from better posttraining, tools, and agent scaffolding (Figure 16).\n  \n\n\n\n\n\n\n   Figure 16: Performance on METR's agentic tasks, over time via better unhobbling. Source:\n   \n    Model Evaluation\n   \n\n    and Threat Research\n   \n\n\n\n   While it's hard to put these on a unified effective compute scale with compute and algorithmic efficiencies, it's clear these are\n   \n    huge\n   \n   gains, at least on a roughly similar magnitude as the compute scaleup and algorithmic efficiencies. (It also highlights the central role of algorithmic progress: the ~0.5 OOMs/year of compute efficiencies, already significant, are only part of the story, and put together with unhobbling algorithmic progress overall is maybe even a majority of the gains on the current trend.)\n  \n\n\n   \"Unhobbling\" is a huge part of what actually enabled these models to become useful\u2014and I'd argue that much of what is holding back many commercial applications today is the need for further \"unhobbling\" of this sort. Indeed,\n   \n    models today are still incredibly hobbled\n   \n   ! For example:\n  \n\n\n   \u2022 They don't have long-term memory.\n  \n\n\n\n\n\n\n\n\n\n\n     They can't use a computer (they still only have very limited tools).\n    \n\n\n     They still mostly don't think before they speak. When you ask ChatGPT to write an essay, that's like expecting a human to write an essay via their initial stream-of-consciousness.\n     \n      27\n     \n\n      27\n     \n     People are\n     \n      working on this though.\n     \n\n\n\n     They can (mostly) only engage in short back-and-forth dialogues, rather than going away for a day or a week, thinking about a problem, researching different approaches, consulting other humans, and then writing you a longer report or pull request.\n    \n\n\n     They're mostly not personalized to you or your application (just a generic chatbot with a short prompt, rather than having all the relevant background on your company and your work).\n    \n\n\n\n   The possibilities here are enormous, and we're rapidly picking low-hanging fruit here. This is critical:\n   \n    it's completely wrong to just imagine \"GPT-6 ChatGPT.\"\n   \n   With continued unhobbling\n  \n\n\n\n\n\n   Figure 17: Decomposing progress: compute, algorithmic efficiencies, and unhobbling. (Rough illustration.)\n  \n\n\n   progress, the improvements will be step-changes compared to GPT-6 + RLHF. By 2027, rather than a chatbot, you're going to have something that looks more like an agent, like a coworker.\n  \n\n\n\n    From chatbot to agent-coworker\n   \n\n\n\n   What could ambitious unhobbling over the coming years look like? The way I think about it, there are three key ingredients:\n  \n\n\n   1. solving the \"onboarding problem\"\n  \n\n\n   GPT-4 has the raw smarts to do a decent chunk of many people's jobs, but it's sort of like a smart new hire that just showed up 5 minutes ago: it doesn't have any relevant context, hasn't read the company docs or Slack history or had conversations with members of the team, or spent any time understanding the company-internal codebase. A smart new hire isn't that useful 5 minutes after arriving\u2014but they are quite useful a month in! It seems like it should be possible, for example via very-long-context, to \"onboard\" models like we would a new human coworker. This alone would be a huge unlock.\n  \n\n\n   2. the test-time compute overhang (reasoning/error correction/system ii for longer-horizon problems)\n  \n\n\n   Right now, models can basically only do short tasks: you ask them a question, and they give you an answer. But that's extremely limiting. Most useful cognitive work humans do is longer horizon\u2014it doesn't just take 5 minutes, but hours, days, weeks, or months.\n  \n\n\n   A scientist that could only think about a difficult problem for 5 minutes couldn't make any scientific breakthroughs. A software engineer that could only write skeleton code for a single function when asked wouldn't be very useful software engineers are given a larger task, and they then go make a plan, understand relevant parts of the codebase or\n  \n\n\n   technical tools, write different modules and test them incrementally, debug errors, search over the space of possible solutions, and eventually submit a large pull request that's the culmination of weeks of work. And so on.\n  \n\n\n   In essence, there is a large\n   \n    test-time compute overhang.\n   \n   Think of each GPT-4 token as a word of internal monologue when you think about a problem. Each GPT-4 token is quite smart, but it can currently only really effectively use on the order of ~hundreds of tokens for chains of thought coherently (effectively as though you could only spend a few minutes of internal monologue/thinking on a problem or project).\n  \n\n\n\n    Number of tokens Equivalent to me working on something for. . .\n   \n   100s A few minutes ChatGPT (we are here) 1,000s Half an hour +1 OOMs test-time compute 10,000s Half a workday +2 OOMs 100,000s A workweek +3 OOMs Millions Multiple months +4 OOMs\n  \n\n\n   What if it could use millions of tokens to think about and work on really hard problems or bigger projects?\n  \n\n\n   Even if the \"per-token\" intelligence were the same, it'd be the difference between a smart person spending a\n   \n    few minutes\n   \n   vs. a\n   \n    few months\n   \n   on a problem. I don't know about you, but there's much, much, much more I am capable of in a few months vs. a few minutes. If we could unlock \"being able to think and work on something for monthsequivalent, rather than a few-minutes-equivalent\" for models, it would unlock an\n   \n    insane\n   \n   jump in capability. There's a huge overhang here, many OOMs worth.\n  \n\n\n   Right now, models can't do this yet. Even with recent advances in long-context, this longer context mostly only works for the consumption of tokens, not the production of tokens\u2014after a while, the model goes off the rails or gets stuck. It's not yet able to go away for a while to work on a\n  \n\n\n   Table 2: Assuming a human thinking at ~100 tokens/minute and working 40 hours/week, translating \"how long a model thinks\" in tokens to human-time on a given problem/project.\n  \n\n\n   problem or project on its own.\n   \n    28\n   \n\n    28\n   \n   Which makes sense\u2014why would\n  \n\n\n   But unlocking test-time compute might merely be a matter of relatively small \"unhobbling\" algorithmic wins. Perhaps a small amount of RL helps a model learn to error correct (\"hm, that doesn't look right, let me double check that\"), make plans, search over possible solutions, and so on. In a sense, the model already has most of the raw capabilities, it just needs to learn a few extra skills on top to put it all together.\n  \n\n\n   In essence, we just need to teach the model a sort of System II outer loop\n   \n    29\n   \n   that lets it reason through difficult, long-\n   \n    29\n   \n   System I vs. System II is a useful horizon projects.\n  \n\n\n   If we succeed at teaching this outer loop, instead of a short chatbot answer of a couple paragraphs, imagine a stream of millions of words (coming in more quickly than you can read them) as the model thinks through problems, uses tools, tries different approaches, does research, revises its work, coordinates with others, and completes big projects on its own.\n  \n\n\n\n    Trading off test-time and train-time compute in other ML domains.\n   \n   In other domains, like AI systems for board games, it's been demonstrated that you can use more test-time compute (also called inference-time compute) to substitute for training compute.\n  \n\n\n\n\n\n\n\n\n\n   it have learned the skills for longerhorizon reasoning and error correction? There's very little data on the internet in the form of \"my complete internal monologue, reasoning, all the relevant steps over the course of a month as I work on a project.\" Unlocking this capability will require a new kind of training, for it to learn these extra skills.\n  \n\n\n   Or as Gwern put it (private correspondence): \" 'Brain the size of a galaxy, and what do they ask me to do? Predict the misspelled answers on benchmarks!' Marvin the depressed neural network moaned.\"\n  \n\n\n   way of thinking about current capabilities of LLMs\u2014including their limitations and dumb mistakes\u2014and what might be possible with RL and unhobbling. Think of this way: when you are driving, most of the time you are on autopilot (system I, what models mostly do right now). But when you encounter a complex construction zone or novel intersection, you might ask your passenger-seat-companion to pause your conversation for a moment while you figure out\u2014actually think about\u2014what's going on and what to do. If you were forced to go about life with only system I (closer to models today), you'd have a lot of trouble. Creating the ability for system II reasoning loops is a central unlock.\n  \n\n\n   Figure 18:\n   \n    Jones (\n   \n   2021): A smaller model can do as well as a much larger model at the game of Hex if you give it more test-time compute (\"more time to think\"). In this domain, they find that one can spend ~1.2 OOMs more compute at test-time to get performance equivalent to a model with ~1 OOMs more training compute.\n  \n\n\n   If a similar relationship held in our case, if we could unlock +4 OOMs of test-time compute, that might be equivalent to +3 OOMs of pretraining compute, i.e. very roughly something like the jump between GPT-3 and GPT-4. (Solving this \"unhobbling\" would be equivalent to a huge OOM scaleup.)\n  \n\n\n   3. using a computer\n  \n\n\n   This is perhaps the most straightforward of the three. Chat-GPT right now is basically like a human that sits in an isolated box that you can text. While early unhobbling improvements teach models to use individual isolated tools, I expect that with multimodal models we will soon be able to do this in one fell swoop: we will simply enable models to use a computer like a human would.\n  \n\n\n   That means joining your Zoom calls, researching things online, messaging and emailing people, reading shared docs, using your apps and dev tooling, and so on. (Of course, for models to make the most use of this in longer-horizon loops, this will go hand-in-hand with unlocking test-time compute.)\n  \n\n\n   By the end of this, I expect us to get something that looks a lot like a\n   \n    drop-in remote worker\n   \n   . An agent that joins your company, is onboarded like a new human hire, messages you and colleagues on Slack and uses your softwares, makes pull requests, and that, given big projects, can do the model-equivalent of a human going away for weeks to independently complete the project. You'll probably need somewhat better base models than GPT-4 to unlock this, but possibly not even\n   \n    that\n   \n   much better\u2014a lot of juice is in fixing the clear and basic ways models are still hobbled.\n  \n\n\n   (A very early peek at what this might look like is\n   \n    Devin,\n   \n   an early prototype of unlocking the \"agency-overhang\"/\"testtime compute overhang\" on models on the path to creating a fully automated software engineer. I don't know how well Devin works in practice, and this demo is still very\n  \n\n\n   limited compared to what proper chatbot \u2192 agent unhobbling would yield, but it's a useful teaser of the sort of thing coming soon.)\n  \n\n\n   By the way, the centrality of unhobbling might lead to a somewhat interesting \"sonic boom\" effect in terms of commercial applications. Intermediate models between now and the dropin remote worker will require tons of schlep to change workflows and build infrastructure to integrate and derive economic value from. The drop-in remote worker will be dramatically easier to integrate\u2014just, well, drop them in to automate all the jobs that could be done remotely. It seems plausible that the schlep will take longer than the unhobbling, that is, by the time the drop-in remote worker is able to automate a large number of jobs, intermediate models won't yet have been fully harnessed and integrated\u2014so the jump in economic value generated could be somewhat discontinuous.\n  \n\n\n\n    The next four years\n   \n\n\n\n   Putting the numbers together, we should (roughly) expect another GPT-2-to-GPT-4-sized jump in the 4 years following GPT-4, by the end of 2027.\n  \n\n\n\n\n\n\n     GPT-2 to GPT-4 was roughly a 4.5\u20136 OOM base effective compute scaleup (physical compute and algorithmic efficiencies), plus major \"unhobbling\" gains (from base model to chatbot).\n    \n\n\n     In the subsequent 4 years, we should expect 3\u20136 OOMs of base effective compute scaleup (physical compute algorithmic efficiencies)\u2014with perhaps a best guess of ~5 OOMs\u2014plus step-changes in utility and applications unlocked by \"unhobbling\" (from chatbot to agent/drop-in remote worker).\n    \n\n\n\n   To put this in perspective, suppose GPT-4 training took 3 months.\n   \n    In 2027, a leading AI lab will be able to train a GPT-4 level model in a minute.\n   \n\n    30\n   \n   The OOM effective compute scaleup\n  \n\n\n\n    30\n   \n   On the best guess assumptions on physical compute and algorithmic efficiency scaleups described above, and simplifying parallelism considerations (in reality, it might look more like \"1440 (60*24) GPT-4-level models in a day\" or similar).\n  \n\n\n\n\n\n\n   Figure 19: Summary of the estimates on drivers of progress in the four years preceding GPT-4, and what we should expect in the four years following GPT-4.\n  \n\n\n   will be dramatic.\n  \n\n\n   Where will that take us?\n  \n\n\n\n\n\n\n   OOMs. GPT-2 to GPT-4 took us from ~preschooler to ~smart highschooler; from barely being able to output a few cohesive sentences to acing high-school exams and being a useful coding assistant. That was an insane jump. If\n   \n    this\n   \n   is the intelligence gap we'll cover once more, where will that take us?\n   \n    31\n   \n   We\n   \n    31\n   \n   Of course, any benchmark we have should not be surprised if that takes us very, very far. Likely, it will take us to models that can outperform PhDs and the best experts in a field.\n  \n\n\n   (One neat way to think about this is that the current trend of AI progress is proceeding at roughly 3x the pace of child development. Your 3x-speed-child just graduated high school; it'll be taking your job before you know it!)\n  \n\n\n   Again, critically, don't just imagine an incredibly smart Chat-GPT: unhobbling gains should mean that this looks more like a drop-in remote worker, an incredibly smart agent that can reason and plan and error-correct and knows everything about you and your company and can work on a problem indepen-\n  \n\n\n   Figure 20: Summary of counting the\n  \n\n\n   today will be saturated. But that's not saying much; it's mostly a reflection on the difficulty of making hard-enough benchmarks.\n  \n\n\n   dently for weeks.\n  \n\n\n   We are on course for AGI by 2027. These AI systems will basically be able to automate basically all cognitive jobs (think: all jobs that could be done remotely).\n  \n\n\n   To be clear\u2014the error bars are large. Progress could stall as we run out of data, if the algorithmic breakthroughs necessary to crash through the data wall prove harder than expected. Maybe unhobbling doesn't go as far, and we are stuck with merely expert chatbots, rather than expert coworkers. Perhaps the decade-long trendlines break, or scaling deep learning hits a wall for real this time. (Or an algorithmic breakthrough, even simple unhobbling that unleashes the test-time compute overhang, could be a paradigm-shift, accelerating things further and leading to AGI even earlier.)\n  \n\n\n   In any case, we are racing through the OOMs, and it requires no esoteric beliefs, merely trend extrapolation of straight lines, to take the possibility of AGI\u2014true AGI\u2014by 2027\n   \n    extremely\n   \n   seriously.\n  \n\n\n   It seems like many are in the game of downward-defining AGI these days, as just as really good chatbot or whatever. What I mean is an AI system that could fully automate my or my friends' job, that could fully do the work of an AI researcher or engineer. Perhaps some areas, like robotics, might take longer to figure out by default. And the societal rollout, e.g. in medical or legal professions, could easily be slowed by societal choices or regulation. But once models can automate AI research itself, that's enough\u2014enough to kick off intense feedback loops\u2014and we could very quickly make further progress, the automated AI engineers themselves solving all the remaining bottlenecks to fully automating everything. In particular, millions of automated researchers could very plausibly compress a decade of further algorithmic progress into a year or less. AGI will merely be a small taste of the superintelligence soon to follow. (More on that in the next chapter.)\n  \n\n\n   In any case, do not expect the vertiginous pace of progress to abate. The trendlines look innocent, but their implications are\n  \n\n\n   intense. As with every generation before them, every new generation of models will dumbfound most onlookers; they'll be incredulous when, very soon, models solve incredibly difficult science problems that would take PhDs days, when they're whizzing around your computer doing your job, when they're writing codebases with millions of lines of code from scratch, when every year or two the economic value generated by these models 10xs. Forget scifi, count the OOMs: it's what we should expect. AGI is no longer a distant fantasy. Scaling up simple deep learning techniques has just worked, the models just want to learn, and we're about to do another 100,000x+ by the end of 2027. It won't be long before they're smarter than us.\n  \n\n\n\n\n\n\n\n\n\n   Figure 21: GPT-4 is just the beginning where will we be four years later? Do not make the mistake of underestimating the rapid pace of deep learning progress (as illustrated by\n   \n    progress in\n   \n\n    GANs)\n   \n   .\n  \n\n\n\n    Addendum. Racing through the OOMs: It's this decade or bust\n   \n\n\n\n   I used to be more skeptical of short timelines to AGI. One reason is that it seemed unreasonable to privilege this decade, concentrating so much AGI-probability-mass on it (it seemed like a classic fallacy to think \"oh we're so special\"). I thought we should be uncertain about what it takes to get AGI, which should lead to a much more \"smeared-out\" probability distribution over when we might get AGI.\n  \n\n\n   However, I've changed my mind: critically, our uncertainty over what it takes to get AGI should be over\n   \n    OOMs\n   \n   (of effective compute), rather than over years.\n  \n\n\n   We're racing through the OOMs this decade. Even at its bygone heyday, Moore's law was only 1\u20131.5 OOMs/decade. I estimate that we will do ~5 OOMs in 4 years, and over ~10 this decade overall.\n  \n\n\n\n\n\n\n   Figure 22: Rough projections on effective compute scaleup. We've been racing through the OOMs this decade; after the early 2030s, we will face a slow slog.\n  \n\n\n   In essence, we're in the middle of a huge scaleup reaping one-time gains this decade, and progress through the OOMs will be multiples slower thereafter. If this scaleup doesn't get us to AGI in the next 5-10 years, it might be a\n  \n\n\n   long way out.\n  \n\n\n\n\n\n\n\n      Spending scaleup\n     \n     : Spending a million dollars on a model used to be outrageous; by the end of the decade, we will likely have $100B or $1T clusters. Going much higher than that will be hard; that's already basically the feasible limit (both in terms of what big business can afford, and even just as a fraction of GDP). Thereafter all we have is glacial 2%/year trend real GDP growth to increase this.\n    \n\n\n\n      Hardware gains\n     \n     : AI hardware has been improving much more quickly than Moore's law. That's because we've been specializing chips for AI workloads. For example, we've gone from CPUs to GPUs; adapted chips for Transformers; and we've gone down to much lower precision number formats, from fp64/fp32 for traditional supercomputing to fp8 on H100s. These are large gains, but by the end of the decade we'll likely have totallyspecialized AI-specific chips, without much further beyond-Moore's law gains possible.\n    \n\n\n\n      Algorithmic progress\n     \n     : In the coming decade, AI labs will invest tens of billions in algorithmic R&D, and all the smartest people in the world will be working on this; from tiny efficiencies to new paradigms, we'll be picking lots of the low-hanging fruit. We probably won't reach any sort of hard limit (though \"unhobblings\" are likely finite), but at the very least the pace of improvements should slow down, as the rapid growth (in $ and human capital investments) necessarily slows down (e.g., most of the smart STEM talent will already be working on AI). (That said, this is the most uncertain to predict, and the source of most of the uncertainty on the OOMs in the 2030s on the plot above.)\n    \n\n\n\n   Put together, this means we are racing through many more OOMs in the next decade than we might in multiple decades thereafter. Maybe it's enough\u2014and we get AGI soon\u2014or we might be in for a long, slow slog. You and I can reasonably disagree on the\n   \n    median\n   \n   time to AGI,\n  \n\n\n   depending on how hard we think achieving AGI will be but given how we're racing through the OOMs right now, certainly your\n   \n    modal\n   \n   AGI year should sometime later this decade or so.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   Figure 23: Matthew Barnett has a nice\n   \n    related visualization\n   \n   of this, considering just compute and biological bounds.\n  \n\n\n\n    II. From AGI to Superintelligence: the Intelligence Explosion\n   \n\n\n\n\n    AI progress won't stop at human-level. Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into 1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power\u2014and the peril\u2014of superintelligence would be dramatic.\n   \n\n\n\n\n\n    Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion,' and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.\n   \n\n\n\n\n\n\n\n     i. j. good (\n     \n      1965\n     \n     )\n    \n\n\n\n\n\n    The Bomb and The Super\n   \n\n\n\n   In the common imagination, the Cold War's terrors principally trace back to Los Alamos, with the invention of the atomic bomb. But The Bomb, alone, is perhaps overrated. Going from The Bomb to The Super\u2014hydrogen bombs\u2014was arguably just as important.\n  \n\n\n   In the Tokyo air raids, hundreds of bombers dropped thousands of tons of conventional bombs on the city. Later that year, Little Boy, dropped on Hiroshima, unleashed similar destructive power in a single device. But just 7 years later, Teller's hydrogen bomb multiplied yields\n   \n    a thousand-fold\n   \n   once again\u2014a single bomb with more explosive power than all of the bombs dropped in the entirety of WWII combined.\n  \n\n\n   The Bomb was a more efficient bombing campaign. The Super was a country-annihilating device.\n   \n    32\n   \n\n    32\n   \n   And much of the Cold War's per-\n  \n\n\n   So it will be with AGI and Superintelligence.\n  \n\n\n   AI progress won't stop at human-level. After initially learning from the best human games, AlphaGo started playing against itself\u2014and it quickly became superhuman, playing extremely creative and complex moves that a human would never have come up with.\n  \n\n\n   We discussed the path to AGI in the previous piece. Once we get AGI, we'll turn the crank one more time\u2014or two or three more times\u2014and AI systems will become superhuman\u2014vastly superhuman. They will become qualitatively smarter than you or I, much smarter, perhaps similar to how you or I are qualitatively smarter than an elementary schooler.\n  \n\n\n   The jump to superintelligence would be wild enough at the current rapid but continuous rate of AI progress (if we could make the jump to AGI in 4 years from GPT-4, what might another 4 or 8 years after that bring?). But it could be much faster than that, if AGI automates AI research itself.\n  \n\n\n   Once we get AGI, we won't just have one AGI. I'll walk through the numbers later, but: given inference GPU fleets by then, we'll likely be able to run\n   \n    many millions of them (perhaps 100 million human-equivalents, and soon after at 10x+ human speed)\n   \n   . Even if they can't yet walk around the office or make coffee, they will be able to do ML research on a computer. Rather than a few hundred researchers and engineers at a leading AI lab, we'd have more than 100,000x that\u2014furiously working on algorithmic breakthroughs, day and night. Yes, recursive self-improvement, but no sci-fi required;\n   \n    they would need only to accelerate the existing trendlines of algorithmic progress (currently at ~0.5 OOMs/year).\n   \n\n\n\n   Automated AI research could probably compress a humandecade of algorithmic progress into less than a year (and that seems conservative). That'd be 5+ OOMs, another GPT-2-to-\n  \n\n\n   versities (cf\n   \n    Daniel Ellsberg's book)\n   \n   stemmed from merely replacing Abombs with H-bombs, without adjusting nuclear policy and war plans to the massive capability increase.\n  \n\n\n\n\n\n\n   GPT-4-sized jump, on top of AGI\u2014a qualitative jump like that from a preschooler to a smart high schooler,\n   \n    on top\n   \n   of AI systems already as smart as expert AI researchers/engineers.\n  \n\n\n   There are several plausible bottlenecks\u2014including limited compute for experiments, complementarities with humans, and algorithmic progress becoming harder\u2014which I'll address, but none seem sufficient to definitively slow things down.\n  \n\n\n   Before we know it, we would have superintelligence on our hands\u2014AI systems\n   \n    vastly\n   \n   smarter than humans, capable of novel, creative, complicated behavior we couldn't even begin to understand\u2014perhaps even a small civilization of billions of them. Their power would be vast, too. Applying superin-\n  \n\n\n   Figure 24: Automated AI research could accelerate algorithmic progress, leading to 5+ OOMs of effective compute gains in a year. The AI systems we'd have by the end of an intelligence explosion would be vastly smarter than humans.\n  \n\n\n   telligence to R&D in other fields, explosive progress would broaden from just ML research; soon they'd solve robotics, make dramatic leaps across other fields of science and technology within years, and an industrial explosion would follow. Superintelligence would likely provide a decisive military advantage, and unfold untold powers of destruction. We will be faced with one of the most intense and volatile moments of human history.\n  \n\n\n\n    Automating AI research\n   \n\n\n\n\n    We don't need to automate everything\u2014just AI research.\n   \n   A common objection to transformative impacts of AGI is that it will be hard for AI to do everything. Look at robotics, for instance, doubters say; that will be a gnarly problem, even if AI is cognitively at the levels of PhDs. Or take automating biology R&D, which might require lots of physical lab-work and human experiments.\n  \n\n\n   But we don't need robotics\u2014we don't need many things\u2014for AI to automate AI research. The jobs of AI researchers and engineers at leading labs can be done fully virtually and don't run into real-world bottlenecks in the same way (though it will still be limited by compute, which I'll address later). And the job of an AI researcher is fairly straightforward, in the grand scheme of things: read ML literature and come up with new questions or ideas, implement experiments to test those ideas, interpret the results, and repeat. This all seems squarely in the domain where simple extrapolations of current AI capabilities could easily take us to or beyond the levels of the best humans by the end of 2027. 33\n  \n\n\n   and their labs' competitive edge. It's worth emphasizing just how straightforward and hacky some of the biggest machine learning breakthroughs of the last decade have been: \"oh, just add some normalization\" (LayerNorm/BatchNorm) or \"do f(x)+x instead of f(x)\" (residual connections)\" or \"fix an implementation bug\" (Kaplan \u2192 Chinchilla scaling laws). AI research can be automated. And automating AI research is all it takes to kick off extraordinary feedback loops.\n   \n    34\n   \n\n\n\n\n    33\n   \n   The job of an AI researcher is also a job that AI researchers at AI labs just, well, know really well\u2014so it'll be particularly intuitive to them to optimize models to be good at that job. And there will be huge incentives to do so to help them accelerate their research\n  \n\n\n\n    34\n   \n   This suggests an important point in terms of the sequencing of risks from AI, by the way. A common AI threat model people point to is AI systems developing novel bioweapons, and that posing catastrophic risk. But if AI research is more straightforward to automate than biology R&D, we might get an intelligence explosion before we get extreme AI biothreats. This matters, for example, with regard to whether we should expect \"bio warning shots\" in time before things get crazy on AI.\n  \n\n\n\n    We'd be able to run millions of copies (and soon at 10x+ human speed) of the automated AI researchers.\n   \n   Even by 2027, we should expect GPU fleets in the 10s of millions. Training clusters alone should be approaching ~3 OOMs larger, already putting us at 10 million+ A100-equivalents. Inference fleets should be much larger still. (More on all this in IIIa. Racing to the Trillion Dollar Cluster.)\n  \n\n\n   That would let us run many millions of copies of our automated AI researchers, perhaps 100 million human-researcherequivalents, running day and night. There's some assumptions that flow into the exact numbers, including that humans \"think\" at 100 tokens/minute (just a rough order of magnitude estimate, e.g. consider your internal monologue) and extrapolating historical trends and Chinchilla scaling laws on pertoken inference costs for frontier models remaining in the same ballpark.\n   \n    35\n   \n   We'd also want to reserve some of the GPUs for running experiments and training new models. Full calculation in a footnote.\n   \n    36\n   \n\n\n\n   Another way of thinking about it is that\n   \n    given inference fleets in 2027, we should be able to generate an entire internet's worth of tokens, every single day.\n   \n\n    37\n   \n   In any case, the exact numbers don't matter that much, beyond a simple plausibility demonstration.\n  \n\n\n\n    35\n   \n   As noted earlier, the GPT-4 API costs less today than GPT-3 when it was released\u2014this suggests that the trend of inference efficiency wins is fast enough to keep inference costs roughly constant even as models get much more powerful. Similarly, there have been huge inference cost wins in just the year since GPT-4 was released; for example,\n   \n    the current version of Gemini\n   \n   1.5 Pro outperforms the original GPT-4, while being roughly 10\n   \n    x cheaper.\n   \n\n\n\n   We can also ground this somewhat more by considering Chinchilla scaling laws. On Chinchilla scaling laws, model size\u2014and thus inference costs\u2014grow with the square root of training cost, i.e. half the OOMs of the OOM scaleup of effective compute. However, in the previous piece, I suggested that algorithmic efficiency was advancing at roughly the same pace as compute scaleup, i.e. it made up roughly half of the OOMs of effective compute scaleup. If these algorithmic wins also translate into inference efficiency, that means that the algorithmic efficiencies would compensate for the naive increase in inference cost.\n  \n\n\n   In practice, training compute efficiencies often, but not always, translate into inference efficiency wins. However, there are also separately many inference efficiency wins that are not training efficiency wins. So, at least in terms of the rough ballpark, assuming the $/token of frontier models stays roughly similar doesn't seem crazy.\n  \n\n\n   (Of course, they'll use more tokens, i.e. more test-time compute. But that's already part of the calculation here, by pricing human-equivalents as 100 tokens/minute.)\n  \n\n\n\n    36\n   \n   GPT4T\n   \n    is about\n   \n   $0.03/1K tokens. We supposed we would have 10s of millions of A100 equivalents, which cost ~$1 hour per GPU if A100-equivalents. If we used the API costs to translate GPUs into tokens generated, that implies 10s of millions GPUs * $1/GPU-hour * 33K tokens/$ = ~ one trillion tokens/ hour. Suppose a human does 100 tokens/min of thinking, that means a human-equivalent is 6,000 tokens/hour. One trillion tokens/hour divided by 6,000 tokens/human-hour = ~200 million human-equivalents i.e. as if running 200 million human researchers, day and night. (And even if we reserve half the GPUs for experiment compute, we get 100 million human-researcher-equivalents.)\n   \n    37\n   \n   The previous footnote estimated ~1T tokens/hour, i.e. 24T tokens a day. In the previous piece, I noted that a\n   \n    public deduplicated CommonCrawl\n   \n\n    had around\n   \n   30T tokens.\n  \n\n\n   Moreover, our automated AI researchers may soon be able to run at much faster than human-speed:\n  \n\n\n\n\n\n\n     By taking some inference penalties, we can trade off running fewer copies in exchange for running them at faster serial speed. (For example, we could go from ~5x human speed to ~100x human speed by \"only\" running 1 million copies of the automated researchers.38)\n    \n\n\n     More importantly, the first algorithmic innovation the automated AI researchers work on is getting a 10x or 100x speedup. Gemini 1.5 Flash is ~10x faster than the originallyreleased GPT-4,\n     \n      39\n     \n     merely a year later, while providing similar performance to the originally-released GPT-4 on reasoning benchmarks. If that's the algorithmic speedup a few hundred human researchers can find in a year, the automated AI researchers will be able to find similar wins very quickly.\n    \n\n\n\n\n    That is: expect 100 million automated researchers each working at 100x human speed not long after we begin to be able to automate AI research.\n   \n   They'll each be able to do a year's worth of work in a few days. The increase in research effort\u2014compared to a few hundred puny human researchers at a leading AI lab today, working at a puny 1x human speed\u2014will be extraordinary.\n  \n\n\n\n    This could easily dramatically accelerate existing trends of algorithmic progress, compressing a decade of advances into a year.\n   \n   We need not postulate anything totally novel for automated AI research to intensely speed up AI progress. Walking through the numbers in the previous piece, we saw that algorithmic progress has been a central driver of deep learning progress in the last decade; we noted a trendline of ~0.5 OOMs/year on algorithmic efficiencies alone, with additional large algorithmic gains from unhobbling on top. (I think the import of algorithmic progress has been underrated by many, and properly appreciating it is important for appreciating the possibility of an intelligence explosion.)\n  \n\n\n   Could our millions of automated AI researchers (soon working at 10x or 100x human speed) compress the algorithmic progress human researchers would have found in a decade into a year\n  \n\n\n\n    38\n   \n   Jacob Steinhardt estimates that k\u02c63 parallel copies of a model can be replaced with a single model that is k\u02c62 faster, given\n   \n    some math on inference\n   \n\n    tradeoffs\n   \n   with a tiling scheme (that theoretically works even for k of 100 or more). Suppose initial speeds were already ~5x human speed (based on, say, GPT-4 speed on release). Then, by taking this inference penalty (with k= ~5), we'd be able to run ~1 million automated AI researchers at ~100x human speed.\n  \n\n\n\n    39\n   \n   This\n   \n    source\n   \n   benchmarks throughput of Flash at ~6x GPT-4 Turbo, and GPT-4 Turbo was faster than original GPT-4. Latency is probably also roughly 10x faster.\n  \n\n\n   instead? That would be 5+ OOMs in a year.\n  \n\n\n   Don't just imagine 100 million junior software engineer interns here (we'll get those earlier, in the next couple years!). Real automated AI researchers be very smart\u2014and in addition to their raw quantitative advantage, automated AI researchers will have other enormous advantages over human researchers:\n  \n\n\n\n\n\n\n     They'll be able to read every single ML paper ever written, have been able to deeply think about every single previous experiment ever run at the lab, learn in parallel from each of their copies, and rapidly accumulate the equivalent of millennia of experience. They'll be able to develop far deeper intuitions about ML than any human.\n    \n\n\n     They'll be easily able to write millions of lines of complex code, keep the entire codebase in context, and spend humandecades (or more) checking and rechecking every line of code for bugs and optimizations. They'll be superbly competent at all parts of the job.\n    \n\n\n     You won't have to individually train up each automated AI researcher (indeed, training and onboarding 100 million new human hires would be difficult). Instead, you can just teach and onboard one of them\u2014and then make replicas. (And you won't have to worry about politicking, cultural acclimation, and so on, and they'll work with peak energy and focus day and night.)\n    \n\n\n     Vast numbers of automated AI researchers will be able to share context (perhaps even accessing each others' latent space and so on), enabling much more efficient collaboration and coordination compared to human researchers.\n    \n\n\n     And of course, however smart our initial automated AI researchers would be, we'd soon be able to make further OOM-jumps, producing even smarter models, even more capable at automated AI research.\n    \n\n\n\n   Imagine an automated Alec Radford\u2014\n   \n    imagine 100 million au-\n   \n\n\n\n\n    tomated Alec Radfords.\n   \n\n    40\n   \n   I think just about every researcher at\n   \n    40\n   \n   Alec Radford is an incredibly gifted OpenAI would agree that if they had 10 Alec Radfords, let alone 100 or 1,000 or 1 million running at 10x or 100x human speed, they could very quickly solve very many of their problems. Even with various other bottlenecks (more in a moment), compressing a decade of algorithmic progress into a year as a result seems very plausible. (A 10x acceleration from a million times more research effort, which seems conservative if anything.)\n  \n\n\n   That would be 5+ OOMs right there. 5 OOMs of algorithmic wins would be a similar scaleup to what produced the GPT-2-to-GPT-4 jump, a capability jump from ~a preschooler to ~a smart high schooler. Imagine such a qualitative jump\n   \n    on top of\n   \n   AGI,\n   \n    on top of\n   \n   Alec Radford.\n  \n\n\n   It's strikingly plausible we'd go from AGI to superintelligence very quickly, perhaps in 1 year.\n  \n\n\n\n    Possible bottlenecks\n   \n\n\n\n   While this basic story is surprisingly strong\u2014and is supported by\n   \n    thorough economic modeling work\u2014\n   \n   there are some real and plausible bottlenecks that will probably slow down an automated-AI-research intelligence explosion.\n  \n\n\n   I'll give a summary here, and then discuss these in more detail in the optional sections below for those interested:\n  \n\n\n   \u2022\n   \n    Limited compute\n   \n   : AI research doesn't just take good ideas, thinking, or math\u2014but running experiments to get empirical signal on your ideas. A million times more research effort via automated research labor won't mean a million times faster progress, because compute will still be limited\u2014and limited compute for experiments will be the bottleneck. Still, even if this won't be a 1,000,000x speedup, I find it hard to imagine that the automated AI researchers couldn't use the compute\n   \n    at least\n   \n   10x more effectively: they'll be able to get incredible ML intuition (having internalized the whole ML literature and every previous experiment every run!) and\n  \n\n\n   and prolific researcher/engineer at OpenAI, behind\n   \n    many of the most\n   \n\n    important advances,\n   \n   though he flies under the radar some.\n  \n\n\n   centuries-equivalent of thinking-time to figure out exactly the right experiment to run, configure it optimally, and get maximum value of information; they'll be able to spend centuries-equivalent of engineer-time before running even tiny experiments to avoid bugs and get them right on the first try; they can make tradeoffs to economize on compute by focusing on the biggest wins; and they'll be able to try tons of smaller-scale experiments (and given effective compute scaleups by then, \"smaller-scale\" means being able to train 100,000 GPT-4-level models in a year to try architecture breakthroughs). Some human researchers and engineers are able to produce 10x the progress as others, even with the same amount of compute\u2014and this should apply even moreso to automated AI researchers. I do think this is the most important bottleneck, and I address it in more depth below.\n  \n\n\n\n\n\n\n\n      Complementarities/long tail:\n     \n     A classic lesson from economics (cf Baumol's growth disease) is that if you can automate, say, 70% of something, you get some gains but quickly the remaining 30% become your bottleneck. For anything that falls short of full automation\u2014say, really good copilots\u2014human AI researchers would remain a major bottleneck, making the overall increase in the rate of algorithmic progress relatively small. Moreover, there's likely some long tail of capabilities required for automating AI research\u2014the last 10% of the job of an AI researcher might be particularly hard to automate. This could soften takeoff some, though my best guess is that this only delays things by a couple years. Perhaps 2026/27-models speed are the proto-automated-researcher, it takes another year or two for some final unhobbling, a somewhat better model, inference speedups, and working out kinks to get to full automation, and finally by 2028 we get the 10x acceleration (and superintelligence by the end of the decade).\n    \n\n\n\n      Inherent limits to algorithmic progress:\n     \n     Maybe another 5 OOMs of algorithmic efficiency will be fundamentally impossible? I doubt it. While there will definitely be upper limits,\n     \n      41\n     \n     if we got 5 OOMs in the last decade, we should\n     \n      41\n     \n\n      25\n     \n     OOMs of algorithmic progress on probably expect at least another decade's-worth of progress\n    \n\n\n\n   top of GPT-4, for example, are clearly impossible: that would imply it would be possible to train a GPT-4-level model with just a handful of FLOP.\n  \n\n\n   to be possible. More directly, current architectures and training algorithms are still very rudimentary, and it seems that much more efficient schemes should be possible. Biological reference classes also support dramatically more efficient algorithms being plausible.\n  \n\n\n\n\n\n\n\n      Ideas get harder to find, so the automated AI researchers will merely sustain, rather than accelerate, the current rate of progress:\n     \n     One objection is that although automated research would increase effective research effort a lot, ideas also get harder to find. That is, while it takes only a few hundred top researchers at a lab to sustain 0.5 OOMs/year today, as we exhaust the low-hanging fruit, it will take more and more effort to sustain that progress\u2014and so the 100 million automated researchers will be merely what's necessary to sustain progress. I think this basic model is correct, but the empirics don't add up: the magnitude of the increase in research effort\u2014a million-fold\u2014is way, way larger than the historical trends of the growth in research effort that's been necessary to sustain progress. In econ modeling terms, it's a bizarre \"knife-edge assumption\" to assume that the increase in research effort from automation will be\n     \n      just enough\n     \n     to keep progress constant.\n    \n\n\n\n      Ideas get harder to find and there are diminishing returns, so the intelligence explosion will quickly fizzle:\n     \n     Related to the above objection, even if the automated AI researchers lead to an initial burst of progress, whether rapid progress can be sustained depends on the shape of the diminishing returns curve to algorithmic progress. Again, my best read of the empirical evidence is that the exponents shake out in favor of explosive/accelerating progress. In any case, the sheer size of the one-time boost\u2014from 100s to 100s of millions of AI researchers\u2014probably overcomes diminishing returns here for at least a good number of OOMs of algorithmic progress, even though it of course can't be\n     \n      indefinitely\n     \n     selfsustaining.\n    \n\n\n\n   Overall, these factors may slow things down somewhat: the most extreme versions of intelligence explosion (say, overnight) seem implausible. And they may result in a somewhat longer\n  \n\n\n   runup (perhaps we need to wait an extra year or two from more sluggish, proto-automated researchers to the true automated Alec Radfords, before things kick off in full force). But they certainly don't rule out a very rapid intelligence explosion. A year\u2014or at most just a few years, but perhaps even just a few months\u2014in which we go from fully-automated AI researchers to vastly superhuman AI systems should be our mainline expectation.\n  \n\n\n\n    If you'd rather skip the in-depth discussions on the various bottlenecks below, click here to skip to the next section.\n   \n\n\n\n\n    Limited compute for experiments (optional, in more depth)\n   \n\n\n\n   The production function for algorithmic progress includes two complementary factors of production: research effort and experiment compute. The millions of automated AI researchers won't have any more compute to run their experiments on than human AI researchers; perhaps they'll just be sitting around waiting for their jobs to finish.\n  \n\n\n   This is probably the most important bottleneck to the intelligence explosion. Ultimately this is a quantitative question\u2014just how much of a bottleneck is it? On balance, I find it hard to believe that the 100 million Alec Radfords couldn't increase the marginal product of experiment compute by at least 10x (and thus, would still accelerate the pace of progress by 10x):\n  \n\n\n   \u2022\n   \n    There's a lot you can do with smaller amounts of compute.\n   \n   The way most AI research works is that you test things out at small scale\u2014and then extrapolate via scaling laws. (Many key historical breakthroughs required only a very small amount of compute, e.g.\n   \n    the original Transformer\n   \n   was trained on just 8 GPUs for a few days.) And note that with ~5 OOMs of baseline scaleup in the next four years, \"small scale\" will mean GPT-4 scale\u2014the automated AI researchers will be able to run 100,000 GPT-4 level experiments on their training cluster in a year, and tens of millions of GPT-3-level experiments. (That's a lot\n  \n\n\n   of potential-breakthrough new architectures they'll be able to test!)\n  \n\n\n\n\n\n\n\n      \u2013\n     \n     A lot of the compute goes into larger-scale validation of the final pretraining run\u2014making sure you are getting a high-enough degree of confidence on marginal efficiency wins for your annual headline product\u2014but if you're racing through the OOMs in the intelligence explosion, you could economize and just focus on the really big wins.\n    \n\n\n\n      \u2013\n     \n     As discussed in the previous piece, there are often\n     \n      enormous\n     \n     gains to be had from relatively low-compute \"unhobbling\" of models. These don't require big pretraining runs. It's highly plausible that that intelligence explosion starts off automated AI research e.g. discovering a way to do RL on top that gives us a couple OOMs via unhobbling wins (and then we're off to the races).\n    \n\n\n\n      \u2013\n     \n\n      As the automated AI researchers find efficiencies, that'll let them run more experiments.\n     \n     Recall the near-1000x cheaper inference in two years for equivalent-MATH performance, and the 10x general inference gains in the last year, discussed in the previous piece, from mere-human algorithmic progress. The first thing the automated AI researchers will do is quickly find similar gains, and in turn, that'll let them run 100x more experiments on e.g. new RL approaches. Or they'll be able to quickly make smaller models with similar performance in relevant domains (cf previous discussion of Gemini Flash, near-100x cheaper than GPT-4), which in turn will let them run many more experiments with these smaller models (again, imagine using these to try different RL schemes). There are probably other overhangs too, e.g. the automated AI researchers might be able to quickly develop much better distributed training schemes to utilize all the inference GPUs (probably at least 10x more compute right there). More generally, every OOM of training efficiency gains they find will give them an OOM\n    \n\n\n\n   more of effective compute to run experiments on.\n  \n\n\n\n\n\n\n\n      The automated AI researchers could be way more efficient.\n     \n     It's hard to understate how many fewer experiments you would have to run if you just got it right on the first try\u2014no gnarly bugs, being more selective about exactly what you are running, and so on. Imagine 1000 automated AI researchers spending a month-equivalent checking your code and getting the exact experiment right before you press go. I've asked some AI lab colleagues about this and they agreed: you should pretty easily be able to save 3x-10x of compute on most projects merely if you could avoid frivolous bugs, get things right on the first try, and only run high value-of-information experiments.\n    \n\n\n\n      The automated AI researchers could have way better intuitions.\n     \n\n\n\n\n\n        \u2013\n       \n       Recently, I was speaking to an intern at a frontier lab; they said that their dominant experience over the past few months was suggesting many experiments they wanted to run, and their supervisor (a senior researcher) saying they could already predict the result beforehand so there was no need. The senior researcher's years of random experiments messing around with models had honed their intuitions about what ideas would work\u2014or not. Similarly, it seems like our AI systems could easily get superhuman intuitions about ML experiments\u2014they will have read the entire machine learning literature, be able to learn from every other experiment result and deeply think about it, they could easily be trained to predict the outcome of millions of ML experiments, and so on. And maybe one of the first things they do is build up a strong basic science of \"predicting if this large scale experiment will be successful just after seeing the first 1% of training, or just after seeing the smaller scale version of this experiment\", and so on.\n      \n\n\n\n\n\n\n        \u2013\n       \n       Moreover, beyond really good intuitions about re-\n      \n\n\n\n\n\n   search directions,\n   \n    as Jason Wei has noted,\n   \n   there are incredible returns to having great intuitions on the dozens of hyperparameters and details of an experiment,. Jason calls this ability to get things right on the first try based on intuition \"yolo runs\". (Jason says, \"what I do know is that the people who can do this are surely 10-100x AI researchers.\")\n  \n\n\n   Compute bottlenecks will mean a million times more researchers won't translate into a million times faster research\u2014thus not an overnight intelligence explosion. But the automated AI researchers will have extraordinary advantages over human researchers, and so it seems hard to imagine that they couldn't also find a way to use the compute at least 10x more efficiently/effectively\u2014and so 10x the pace of algorithmic progress seems eminently plausible.\n  \n\n\n   I'll take a moment here to acknowledge perhaps the most compelling formulation of the counterargument I've heard, by my friend James Bradbury:\n   \n    if more ML research effort would so dramatically accelerate progress, why doesn't the current academic ML research community, numbering at least in the tens of thousands, contribute more to frontier lab progress?\n   \n   (Currently, it seems like lab-internal teams, of perhaps a thousand in total across labs, shoulder most of the load for frontier algorithmic progress.) His argument is that the reason is that algorithmic progress is compute-bottlenecked: the academics just don't have enough compute.\n  \n\n\n   Some responses:\n  \n\n\n\n\n\n\n     Quality-adjusted, I think academics are probably more in the thousands not tens of thousands (e.g., looking only at the top universities). This probably isn't substantially more than the labs combined. (And it's\n     \n      way\n     \n     less than the hundreds of millions of researchers we'd get from automated AI research.)\n    \n\n\n     Academics work on the wrong things. Up until very\n    \n\n\n\n   recently (and perhaps still today?), the vast majority of the academic ML community wasn't even working on large language models. In terms of strong academics in academia working on large language models, it might be meaningfully fewer than researchers at labs combined?\n  \n\n\n\n\n\n\n     Even when the academics do work on things like LLM pretraining, they simply don't have access to the stateof-the-art\u2014the large accumulated body of knowledge of tons of details on frontier model training inside labs. They don't know what problems are actually relevant, or can only contribute one-off results that nobody can really do anything with because their baselines were badly tuned (so nobody knows if their thing is actually an improvement).\n    \n\n\n     Academics are way worse than automated AI researchers: they can't work at 10x or 100x human speed, they can't read and internalize every ML paper ever written, they can't spend a decade checking every line of code, replicate themselves to avoid onboarding-bottlenecks, etc.\n    \n\n\n\n   Another countervailing example to the academics argument: GDM is rumored to have way more experiment compute than OpenAI, and yet it doesn't seem like GDM is massively outpacing OpenAI in terms of algorithmic progress.\n  \n\n\n   In general, I expect automated researchers will have a different style of research that plays to their strengths and aims to mitigate the compute bottleneck.\n   \n    I think it's reasonable to be uncertain how this plays out, but it's unreasonable to be confident it won't be doable for the models to get around the compute bottleneck just because it'd be hard for humans to do so.\n   \n\n\n\n   \u2022 For example, they could just spend a lot of effort early on building up a basic science of \"how to predict large scale results from smaller scale experiments\". And I expect there's a lot that they could do that humans can't do, e.g. maybe things more like \"predicting if this large scale experiment will be successful just after seeing the\n  \n\n\n   first 1% of training\". This seems pretty doable if you're a super strong automated researcher with very superhuman intuitions and this can save you a ton of compute.\n  \n\n\n   \u2022 When I imagine AI systems automating AI research, I see them as compute-bottlenecked but making up for it in large part by thinking e.g. 1000x more (and faster) than humans would, and thinking at a higher level of quality than humans (e.g. because of the superhuman ML intuitions from being trained to predict the result of millions of experiments). Unless they're just much worse at thinking than engineering, I think this can make up for a lot, and this would be qualitatively different from academics.\n  \n\n\n   (In addition to experiment compute, there's the additional bottleneck of eventually needing to run a big training run, something which currently takes months. But you can probably economize on those, doing only a handful during the year of intelligence explosion, taking bigger OOM leaps for each than labs currently do.\n   \n    42\n   \n   Or you could \"spend\" 1 out of the 5 OOMs of compute efficiency wins to do a training run in days rather than months.)\n  \n\n\n\n    Complementarities and long tails to 100% automation (optional, in more depth)\n   \n\n\n\n   The classic economist objection to AI automation speeding up economic growth is that different tasks are complementary: so, for example, automating 80% of what labor humans did in 1800 didn't lead to a growth explosion or mass unemployment, but the remaining 20% became what all humans did and remained the bottleneck. (See e.g. a model of this\n   \n    here.\n   \n   ).\n  \n\n\n   I think the economists'\n   \n    model\n   \n   here is correct. But a key point is that I'm only talking about one currently-small part of the economy, rather than the economy as a whole. People may well still be getting haircuts normally during this time\u2014robotics might not yet be worked out, AIs for every domain might not yet be worked out, the societal\n  \n\n\n\n    42\n   \n   Note that while I think this is likely, it's kind of scary: it means that rather than a fairly continuous series of big models, each somewhat better than the previous generation, downstream model intelligence might be more discrete/discontinuous. We might only do one or a couple of big runs during the intelligence explosion, banking multiple OOMs of algorithmic breakthroughs found at smaller scale for each.\n  \n\n\n   rollout might not yet be worked out, etc.\u2014but they\n   \n    will\n   \n   be able to do AI research. As discussed in the previous piece, I think the current course of AI progress is taking us to essentially drop-in remote workers as intelligent as the smartest humans; as discussed in this piece, the job of an AI researcher seems totally within the scope of what could be fully automated.\n  \n\n\n   Still, in practice, I do expect somewhat of a long tail to get to truly 100% automation even for the job of an AI researcher/engineer; for example, we might first get systems that function\n   \n    almost\n   \n   as an engineer replacement, but still need some amount of human supervision.\n  \n\n\n   In particular, I expect the level of AI capabilities to be somewhat uneven and peaky across domains: it might be a better coder than the best engineers while still having blindspots in some subset of tasks or skills; by the time it's human-level at whatever its worst at, it'll already be substantially superhuman at easier domains to train, like coding. (This is part of why I think they'll be able to use the compute more effectively than human researchers. By the time of 100% automation/the intelligence explosion starting, they'll already have huge advantages over humans in some domains. This will also have important implications for superalignment down the line, since it means that we'll have to align systems that are meaningfully superhuman in many domains in order to align even the first automated AI researchers.)\n  \n\n\n   But I wouldn't expect that phase to last more than a few years; given the pace of AI progress, I think it would likely just be a matter of some additional \"unhobbling\" (removing some obvious limitation of the models that prevented it from doing the last mile) or another generation of models to get all the way.\n  \n\n\n   Overall, this might soften takeoff some. Rather that 2027 AGI \u2192 2028 Superintelligence, it might look more like:\n  \n\n\n   \u2022 2026/27: Proto-automated-engineer, but blind spots in\n  \n\n\n   other areas. Speeds up work by 1.5x-2x already; progress begins gradually accelerating.\n  \n\n\n\n\n\n\n     2027/28: Proto-automated-researchers, can automate >90%. Some remaining human bottlenecks, and hiccups in coordinating a giant organization of automated researchers to be worked out, but this already speeds up progress by 3x+. This quickly does the remaining necessary \"unhobbling\" takes us the remainder of the way to 100% automation.\n    \n\n\n     2028/29: 10x+ pace of progress \u2192 superintelligence.\n    \n\n\n\n   That's still very fast. . .\n  \n\n\n\n    Fundamental limits to algorithmic progress (optional, in more depth)\n   \n\n\n\n   There's probably a real cap on how much algorithmic progress is physically possible. (For example, 25 OOMs of algorithm progress seems impossible, since that would imply being able to train a GPT-4 level system in less than ~10 FLOPs.43) But something like 5 OOMs seems very\n   \n    43\n   \n   Though you could get results that with current architecture! much in the realm of possibilities; again, that would just require another decade of trend algorithmic efficiencies (not even counting algorithmic gains from unhobbling).\n  \n\n\n   Intuitively, it very much doesn't seem like we have exhausted all the low-hanging fruit yet, given how simple the biggest breakthroughs are\u2014and how rudimentary and obviously hobbled current architectures and training techniques still seem to be. For example, I think it's pretty plausible that we'll bootstrap our way to AGI via AI systems that \"think out loud\" via chain-of-thought. But\n   \n    surely\n   \n   this isn't the most efficient way to do it,\n   \n    surely\n   \n   something that does this reasoning via internal states/recurrence/etc would be way more efficient. Or consider adaptive compute: Llama 3 still spends as much compute on predicting the \"and\" token as it does the answer to some complicated question, which seems clearly suboptimal. We're getting huge OOM algorithmic gains from even just small tweaks, while there are dozens of areas where much more effi-\n  \n\n\n   would take 25 more OOMs of hardware\n  \n\n\n   cient architectures and training procedures could likely be found.\n  \n\n\n   Biological references also suggest huge headroom. The human range of intelligence is very wide, for example, with only tiny tweaks to architecture. Humans have similar numbers of neurons as other animals, even though humans are much smarter than those animals. And current AI models are still many OOMs from the\n   \n    efficiency of\n   \n\n    a human brain;\n   \n   they can learn with a tiny fraction of the data (and thus tiny fraction of \"compute\") than AI models can, suggesting huge headroom for our algorithms and architecture.\n  \n\n\n\n    Ideas get harder to find and diminishing returns (optional, in more depth)\n   \n\n\n\n   As you pick the low-hanging fruit, ideas get harder to find. This is true in\n   \n    any domain of technological progress.\n   \n   Essentially, we see a straight line on a log-log curve: log(progress) is a function of log(cumulative research effort). Every OOM of further progress requires putting in more research effort than the last OOM.\n  \n\n\n   This leads to two objections to the intelligence explosion:\n  \n\n\n\n\n\n\n     1. Automated AI research will merely be what's necessary to sustain progress (rather than dramatically accelerating it).\n    \n\n\n     2. A purely-algorithmic intelligence explosion would not be sustained / would quickly fizzle out as algorithmic progress gets harder to find / you hit diminishing marginal returns.\n    \n\n\n\n   I spent a lot of time thinking about these sorts of models in a past life, when I was doing research in economics. (In particular,\n   \n    semi-endogenous growth theory\n   \n   is the standard model of technological progress, capturing these two competing dynamics of growing research effort and ideas getting harder to find.)\n  \n\n\n   In short, I think the underlying model behind these objections is sound, but how it shakes out is an empirical question\u2014and I think they get the empirics wrong.\n  \n\n\n   The key question is essentially: for every 10x of progress, does further progress become\n   \n    more\n   \n   or\n   \n    less\n   \n   than 10x harder? Napkin math (along the lines of how this is done in\n   \n    the\n   \n\n    economic literature)\n   \n   helps us bound this.\n  \n\n\n\n\n\n\n     Suppose we take the ~0.5 OOMs/year trend rate of algorithmic progress seriously; that implies a 100x of progress in 4 years.\n    \n\n\n     However, quality-adjusted headcount / research effort at a given leading AI lab has definitely grown by <100x in 4 years.\n     \n      Maybe\n     \n     it's increased 10x (from 10s to 100s of people working on relevant stuff at a given lab), but even that is unclear quality-adjusted.\n    \n\n\n     And yet, algorithmic progress seems to be sustained.\n    \n\n\n\n   Thus, in response to objection 1, we can note that the ~million-fold increase in research effort will simply be a much larger increase than what would merely be necessary to sustain progress. Maybe we'd need on the order of thousands of researchers working on relevant research at a lab in 4 years to sustain progress; the 100 million Alec Radfords would still be an\n   \n    enormous\n   \n   increase, and surely lead to massive acceleration. It's just a bizarre \"knife-edge\" assumption to think that automated research would be\n   \n    just enough\n   \n   to sustain the existing pace of progress. (And that's not even counting thinking at 10x human speed and all the other advantages the AI systems will have over human researchers.)\n  \n\n\n   In response to objection 2, we can note two things:\n  \n\n\n   \u2022 First, the mathematical condition noted above. Given that, based on our napkin math, quality-adjusted research effort needed to grow \u00ab100x while we did 100x of algorithmic progress, it pretty strongly seems that the\n  \n\n\n   shape of the returns curve shakes out in favor of selfsustaining progress.\n   \n    44\n   \n\n    44\n   \n\n    100\n   \n   x progress\n   \n    \u2192\n   \n\n    100\n   \n   x more auto-\n  \n\n\n   \u2022 Secondly, the returns curve doesn't even\n   \n    need\n   \n   to shake out in favor of a fully sustained chain reaction for us to get a bounded-but-many-OOM surge of algorithmic progress. Essentially, it doesn't need to be a \"growth effect\"; a large enough \"level effect\" would be enough. That is, a million-fold increase in research effort (combined with the many other advantages automated researchers would have over human researchers) would be such a large one-time boost that even if the chain reaction isn't fully self-sustaining, it could lead to a very sizeable (many OOMs) one-time gain.\n   \n    45\n   \n\n    45\n   \n   Analogously, in semi-endogenous\n  \n\n\n   On net, while obviously it won't be unbounded and I have a lot of uncertainty over just how far it'll go, I think something like a 5 OOM intelligence explosion purely from algorithmic gains / automated AI research seems highly plausible.\n  \n\n\n\n    Tom Davidson and Carl Shulman\n   \n   have also looked at the empirics of this in a growth-modeling framework and come to similar conclusions.\n   \n    Epoch AI has also done some\n   \n\n    recent work\n   \n   on the empirics, also coming to the conclusion that empirical returns to algorithmic R&D favors explosive growth, with a\n   \n    helpful writeup of the implications.\n   \n\n\n\n\n    The power of superintelligence\n   \n\n\n\n   Whether or not you agree with the strongest form of these arguments\u2014whether we get a <1 year intelligence explosion, or it takes a few years\u2014it is clear: we must confront the possibility of superintelligence.\n  \n\n\n   The AI systems we'll likely have\n   \n    by the end of this decade\n   \n   will be unimaginably powerful.\n  \n\n\n   \u2022 Of course, they'll be\n   \n    quantitatively\n   \n   superhuman. On our fleets\n  \n\n\n   mated research effort, but you, say, only needed 10x more research effort to keep it going and do the next 100x, so the returns are good enough for explosive progress to be sustained.\n  \n\n\n   economic growth theory, boosting science investment from 1% to 20% of GDP won't make growth rates higher forever\u2014eventually diminishing returns would lead things to return to the old growth rate\u2014but the \"level effect\" it would lead to would be so large as to dramatically speed up growth for decades.\n  \n\n\n   of 100s of millions of GPUs by the end of the decade, we'll be able to run a civilization of billions of them, and they will be able to \"think\" orders of magnitude faster than humans. They'll be able to quickly master any domain, write trillions of lines of code, read every research paper in every scientific field ever written (they'll be perfectly interdisciplinary!) and write new ones before you've gotten past the abstract of one, learn from the parallel experience of every one of its of copies, gain billions of human-equivalent years of experience with some new innovation in a matter of weeks, work 100% of the time with peak energy and focus and won't be slowed down by that one teammate who is lagging, and so on.\n  \n\n\n   \u2022 More importantly\u2014but harder to imagine\u2014they'll be\n   \n    qualitatively\n   \n   superhuman. As a narrow example of this, large-scale RL runs have been able to produce completely novel and creative behaviors beyond human understanding, such as the famous move 37\n   \n    in AlphaGo vs. Lee Sedol.\n   \n   Superintelligence will be like this across many domains. It'll find exploits in human code too subtle for any human to notice, and it'll generate code too complicated for any human to understand even if the model spent decades trying to explain it. Extremely difficult scientific and technological problems that a human would be stuck on for decades will seem just\n   \n    so obvious\n   \n   to them. We'll be like high-schoolers stuck on Newtonian physics while it's off exploring quantum mechanics.\n  \n\n\n   As an example of how\n   \n    wild\n   \n   this could be, look at some Youtube videos of video game speedruns, such as this one of\n   \n    beating\n   \n\n    Minecraft in\n   \n   20 seconds. (If you have no idea what's going on in this video, you're in good company; even most normal players of Minecraft have almost no clue what's going on.)\n  \n\n\n   Now imagine this applied to all domains of science, technology, and the economy. The error bars here, of course, are extremely large. Still,\n   \n    this is happening,\n   \n   and it's important to consider just how consequential this would be.\n  \n\n\n\n\n\n\n\n\n\n\n   In the intelligence explosion, explosive progress was initially only in the narrow domain of automated AI research. As we get superintelligence, and apply our billions of (now superintelligent) agents to R&D across many fields, I expect explosive progress to broaden:\n  \n\n\n\n\n\n\n\n      An AI capabilities explosion.\n     \n     Perhaps our initial AGIs had limitations that prevented them fully automating work in some other domains (rather than just in the AI research domain); automated AI research will quickly solve these, enabling automation of any and all cognitive work.\n    \n\n\n\n      Solve robotics.\n     \n     Superintelligence won't stay purely cognitive for long. Getting robotics to work well is primarily an ML algorithms problem (rather than a hardware problem), and our automated AI researchers will likely be able to solve it (more below!). Factories would go from human-run, to AIdirected using human physical labor, to soon being fully run by swarms of robots.\n    \n\n\n\n      Dramatically accelerate scientific and technological progress.\n     \n     Yes, Einstein alone couldn't develop neuroscience and build a semiconductor industry, but a billion superintelligent automated scientists, engineers, technologists, and robot\n    \n\n\n\n   technicians (with the robots moving at 10x or more human speed!)\n   \n    46\n   \n   would make extraordinary advances in many fields\n   \n    46\n   \n   The\n   \n    10\n   \n   x speed robots doing physical in the space of years. (Here's a nice\n   \n    short story\n   \n   visualizing what AI-driven R&D might look like.) The billion superintelligences would be able to compress the R&D effort humans researchers would have done in the next century into years. Imagine if the technological progress of the 20th century were compressed into less than a decade. We would have gone from flying being thought a mirage, to airplanes, to a man on the moon and ICBMs in a matter of years.\n   \n    This is what I expect the 2030s to look like across science and technology.\n   \n\n\n\n   \u2022\n   \n    An industrial and economic explosion.\n   \n   Extremely accelerated technological progress, combined with the ability to automate all human labor, could dramatically accelerate economic growth (think: self-replicating robot factories quickly covering all of the Nevada desert47). The increase in growth\n   \n    47\n   \n   Why isn't \"factorio-world\"\u2014build probably wouldn't just be from 2%/year to 2.5%/year; rather, this would be a fundamental shift in the growth regime, more comparable to the historical step-change from very slow growth to a couple percent a year with the industrial revolution. We could see economic growth rates of 30%/year and beyond, quite possibly multiple doublings a year. This follows fairly straightforwardly from economists'\n   \n    models\n   \n   of\n   \n    economic\n   \n\n    growth.\n   \n   To be sure, this may well be delayed by societal frictions; arcane regulation might ensure lawyers and doctors still need to be human, even if AI systems were much better at those jobs; surely sand will be thrown into the gears of rapidly expanding robo-factories as society resists the pace of change; and perhaps we'll want to retain human nannies; all of which would slow the growth of the overall GDP statistics. Still, in whatever domains we remove human-created barriers (e.g., competition might force us to do so for military production), we'd see an industrial explosion.\n  \n\n\n   R&D in the real world is the \"slow version\"; in reality the superintelligences will try to do as much R&D as possible in simulation, like\n   \n    AlphaFold\n   \n   or manufacturing\n   \n    \"digital\n   \n\n    twins\"\n   \n   .\n  \n\n\n   a factory, that produces more factories, producing even more factories, doubling factories until eventually your entire planet is quickly covered in factories\u2014possible today? Well, labor is constrained\u2014you can accumulate capital (factories, tools, etc.), but that runs into diminishing returns because it's constrained by a fixed labor force. With robots and AI systems being able to fully automate labor, that removes that constraint; robo-factories could produce more robo-factories in an ~unconstrained way, leading to an industrial explosion. See more economic growth models of this\n   \n    here.\n   \n\n\n\n\n\n\n      Growth mode\n     \n\n      Date began to\n      \n      dominate\n     \n\n      Doubling time of\n      \n      global economy\n      \n      (years)\n     \n\n\n\n      Hunting\n     \n\n      2,000,000\n      \n      B.C.\n     \n\n      230,000\n     \n\n\n\n      Farming\n     \n\n      4700\n      \n      B.C.\n     \n\n      860\n     \n\n\n\n      Science/commerce\n     \n\n      1730\n      \n      A.D.\n     \n\n      58\n     \n\n\n\n      Industry\n     \n\n      1903\n      \n      A.D.\n     \n\n      15\n     \n\n\n\n      Superintelligence?\n     \n\n      2030\n      \n      A.D.?\n     \n\n      ???\n     \n\n\n\n\n\n   Table 3: A shift in the growth regime is not unprecedented: as civilization went from hunting, to farming, to the blossoming of science and commerce, to industry, the pace of global economic growth accelerated. Superintelligence could kick off another shift in growth mode. Based on Robin Hanson's\n   \n    \"Long-run growth as a sequence of\n   \n\n    exponential modes\"\n   \n   .\n  \n\n\n\n\n\n\n\n      Provide a decisive and overwhelming military advantage.\n     \n     Even early cognitive superintelligence might be enough here; perhaps some superhuman hacking scheme can deactivate adversary militaries. In any case, military power and technological progress has been tightly linked historically, and with extraordinarily rapid technological progress will come concomitant military revolutions. The drone swarms and roboarmies will be a big deal, but they are just the beginning; we should expect completely new kinds of weapons, from novel WMDs to invulnerable laser-based missile defense to things we can't yet fathom. Compared to pre-superintelligence arsenals, it'll be like 21st century militaries fighting a 19th century brigade of horses and bayonets. (I discuss how superintelligence could lead to a decisive military advantage in a later piece.)\n    \n\n\n\n      Be able to overthrow the US government.\n     \n     Whoever controls superintelligence will quite possibly have enough power to seize control from pre-superintelligence forces. Even without robots, the small civilization of superintelligences would be able to hack any undefended military, election, television, etc. system, cunningly persuade generals and electorates, economically outcompete nation-states, design new synthetic bioweapons and then pay a human in bitcoin to synthesize it, and so on. In the\n     \n      early\n     \n     1500s, Cortes and about 500 Spaniards conquered the Aztec empire of several million; Pizarro and ~300 Spaniards conquered the Inca empire of several million; Alfonso and ~1000 Portuguese conquered the Indian Ocean. They didn't have god-like power, but the Old World's technological edge and an advantage in strate-\n    \n\n\n\n   gic and diplomatic cunning led to an utterly decisive advantage. Superintelligence might look similar.\n  \n\n\n\n\n\n\n\n    Robots.\n   \n   A common objection to claims like those here is that, even if AI can do cognitive tasks, robotics is lagging way behind and so will be a brake on any real-world impacts.\n  \n\n\n   I used to be sympathetic to this, but I've become convinced robots will not be a barrier. For years people claimed robots were a hardware problem\u2014but robot hardware is well on its way to being solved.\n  \n\n\n   Increasingly, it's clear that robots are an\n   \n    ML algorithms\n   \n   problem. LLMs had a much easier way to bootstrap: you had an entire internet to pretrain on. There's no similarly large dataset for robot actions, and so it requires more nifty approaches (e.g. using multimodal models as a base, then using synthetic data/simulation/clever RL) to train them.\n  \n\n\n   Figure 26: Explosive growth starts in the narrower domain of AI R&D; as we apply superintelligence to R&D in other fields, explosive growth will broaden.\n  \n\n\n   There's a ton of energy directed at solving this now. But even if we don't solve it before AGI, our hundreds of millions of AGIs/superintelligences will make\n   \n    amazing\n   \n   AI researchers (as is the central argument of this piece!), and it seems very likely that they'll figure out the ML to make amazing robots work.\n  \n\n\n   As such, while it's plausible that robots might cause a few years of delay (solving the ML problems, testing in the physical world in a way that is fundamentally slower than testing in simulation, ramping up initial robot production before the robots can build factories themselves, etc.)\u2014I don't think it'll be more than that.\n  \n\n\n   How all of this plays out over the 2030s is hard to predict (and a story for another time). But one thing, at least, is clear: we will be rapidly plunged into the most extreme situation humanity has ever faced.\n  \n\n\n   Human-level AI systems, AGI, would be highly consequential in their own right\u2014but in some sense, they would simply be a more efficient version of what we already know. But, very plausibly, within just a year, we would transition to much more alien systems, systems whose understanding and abilities whose raw power\u2014would exceed those even of humanity combined. There is a real possibility that we will lose control, as we are forced to hand off trust to AI systems during this rapid transition.\n  \n\n\n   More generally, everything will just start happening\n   \n    incredibly fast\n   \n   . And the world will start going insane. Suppose we had gone through the geopolitical fever-pitches and man-made perils of the 20th century in mere years; that is the sort of situation we should expect post-superintelligence. By the end of it, superintelligent AI systems will be running our military and economy. During all of this insanity, we'd have extremely scarce time to make the right decisions. The challenges will be immense. It will take everything we've got to make it through in one piece.\n  \n\n\n\n    The intelligence explosion and the immediate post-superintelligence period will be one of the most volatile, tense, dangerous, and wildest periods ever in human history.\n   \n\n\n\n   And by the end of the decade, we'll likely be in the midst of it.\n  \n\n\n   Confronting the possibility of an intelligence explosion the emergence of superintelligence\u2014often echoes the\n   \n    early\n   \n\n    debates\n   \n   around the possibility of a nuclear chain reaction and the atomic bomb it would enable. HG Wells predicted the atomic bomb in a 1914 novel. When Szilard first conceived of the idea of a chain reaction in 1933, he couldn't convince anyone of it; it was pure theory. Once fission was empirically discovered in 1938, Szilard freaked out again and argued strongly for secrecy, and a few people started to wake up to the possibility of a bomb. Einstein hadn't considered the possibility of a chain reaction, but when Szilard confronted him, he was quick to see the implications and willing to do anything that was needed to be done; he was willing to sound the alarm, and wasn't afraid of sounding foolish. But Fermi, Bohr, and most scientists thought the \"conservative\" thing was to play it down, rather than take seriously the extraordinary implications of the possibility of a bomb. Secrecy (to avoid sharing their advances with the Germans) and other all-out efforts seemed absurd to them. A chain reaction sounded too crazy. (Even when, as it turned out, a bomb was but half a decade from becoming reality.)\n  \n\n\n   We must once again confront the possibility of a chain reaction. Perhaps it sounds speculative to you. But among senior scientists at AI labs, many see a rapid intelligence explosion as strikingly plausible. They can\n   \n    see\n   \n   it. Superintelligence is possible.\n  \n\n\n\n    III. The Challenges\n   \n\n\n\n\n    IIIa. Racing to the Trillion-Dollar Cluster\n   \n\n\n\n\n    The most extraordinary techno-capital acceleration has been set in motion. As AI revenue grows rapidly, many trillions of dollars will go into GPU, datacenter, and power buildout before the end of the decade. The industrial mobilization, including growing US electricity production by 10s of percent, will be intense.\n   \n\n\n\n\n\n    You see, I told you it couldn't be done without turning the whole country into a factory. You have done just that.\n   \n\n\n\n\n\n\n\n     niels bohr (to Edward Teller, upon learning of the scale of the Manhattan Project in\n     \n      1944\n     \n     )\n    \n\n\n\n\n   The race to AGI won't just play out in code and behind laptops\u2014it'll be a race to mobilize America's industrial might. Unlike anything else we've recently seen come out of Silicon Valley, AI is a massive industrial process: each new model requires a giant new cluster, soon giant new power plants, and eventually giant new chip fabs. The investments involved are staggering. But behind the scenes, they are already in motion.\n  \n\n\n   In this chapter, I'll walk you through numbers to give you a sense of what this will mean:\n  \n\n\n   \u2022 As revenue from AI products grows rapidly\u2014plausibly hitting a $100B annual run rate for companies like Google or Microsoft by ~2026, with powerful but pre-AGI systems\u2014\n  \n\n\n\n\n\n\n   that will motivate ever-greater capital mobilization, and total AI investment could be north of $1T\n   \n    annually\n   \n   by 2027.\n  \n\n\n\n\n\n\n     We're on the path to individual training clusters costing $100s of billions by 2028\u2014clusters requiring power equivalent to a small/medium US state and more expensive than the International Space Station.\n    \n\n\n     By the end of the decade, we are headed to $1T+ individual training clusters, requiring power equivalent to >20% of US electricity production. Trillions of dollars of capex will churn out 100s of millions of GPUs per year overall.\n    \n\n\n\n   Nvidia shocked the world as its datacenter sales exploded from about $14\n   \n    B annualized\n   \n   to about $90\n   \n    B annualized\n   \n   in the last year. But that's still just the very beginning.\n  \n\n\n   Figure 27: The trillion-dollar cluster. Credit: DALLE.\n  \n\n\n\n    Training compute\n   \n\n\n\n   Earlier, we found a roughly ~0.5 OOMs48/year trend growth of\n   \n    48\n   \n   As mentioned earlier, OOM = ormagnitude AI training compute. If this trend were to continue for the rest of the decade, what would that mean for the largest training clusters?\n  \n\n\n   der of magnitude, 10x = 1 order of\n  \n\n\n\n\n\n      Year\n     \n\n      OOMs\n     \n\n      H100s\n      \n      equivalent\n     \n\n      Cost\n     \n\n      Power\n     \n\n      Power reference class\n     \n\n\n\n      2022\n     \n\n      ~GPT-4\n      \n      cluster\n     \n\n      ~10k\n     \n\n      ~$500M\n     \n\n      ~10\n      \n      MW\n     \n\n      ~10,000\n      \n      average homes\n     \n\n\n\n      ~2024\n     \n\n      +1\n      \n      OOM\n     \n\n      ~100k\n     \n\n      $billions\n     \n\n      ~100MW\n     \n\n      ~100,000\n      \n      homes\n     \n\n\n\n      ~2026\n     \n\n      +2\n      \n      OOMs\n     \n\n      ~1M\n     \n\n      $10s of bil\n      \n      lions\n     \n\n      ~1\n      \n      GW\n     \n\n      The Hoover Dam, or a\n      \n      large nuclear reactor\n     \n\n\n\n      ~2028\n     \n\n      +3\n      \n      OOMs\n     \n\n      ~10M\n     \n\n      $100s of\n      \n      billions\n     \n\n      ~10\n      \n      GW\n     \n\n      A small/medium US\n      \n      state\n     \n\n\n\n      ~2030\n     \n\n      +4\n      \n      OOMs\n     \n\n      ~100M\n     \n\n      $1T+\n     \n\n      ~100GW\n     \n\n      >20% of US electricity\n      \n      production\n     \n\n\n\n\n\n   This may seem hard to believe\u2014but it appears to be happening. Zuck\n   \n    bought\n   \n   350k H100s. Amazon bought a 1\n   \n    GW data\n   \n\n    center campus\n   \n   next to a nuclear power plant. Rumors\n   \n    suggest\n   \n   a 1GW, 1.4M H100-equivalent cluster (~2026-cluster) is being built in Kuwait. Media report that\n   \n    Microsoft and OpenAI are\n   \n\n    rumored to be working on a $\n   \n   100B cluster, slated for 2028 (a cost comparable to the\n   \n    International Space Station!\n   \n   ). And as each generation of models shocks the world, further acceleration may yet be in store.\n  \n\n\n   Perhaps the wildest part is that willingness-to-spend doesn't even seem to be the binding constraint at the moment, at least for training clusters. It's finding the infrastructure itself: \"Where do I find 10GW?\" (power for the $100B+, trend 2028 cluster) is a favorite topic of conversation in SF. What any compute guy is thinking about is securing power, land, permitting, and datacenter construction.\n   \n    49\n   \n   While it may take you a year\n   \n    49\n   \n   One key uncertainty is how disof waiting to get the GPUs, the lead times for these are much longer still.\n  \n\n\n   Table 4: Scaling the largest training clusters, rough back-of-the-envelope calculations. For details on the calculations, see Appendix.\n  \n\n\n   tributed training will be\u2014if instead of needing that amount of power in one location, we could spread it among 100 locations, it'd be a lot easier.\n  \n\n\n   The trillion-dollar cluster\u2014+4 OOMs from the GPT-4 cluster, the ~2030 training cluster on the current trend\u2014will be a truly extraordinary effort. The 100GW of power it'll require is equivalent to >20% of US electricity production; imagine not just a simple warehouse with GPUs, but hundreds of power plants. Perhaps it will take a national consortium.\n  \n\n\n   (Note that I think it's pretty likely we'll only need a ~$100B cluster, or less, for AGI. The $1T cluster might be what we'll train and run superintelligence on, or what we'll use for AGI if AGI is harder than expected. In any case, in a post-AGI world, having the most compute will probably still really matter.)\n  \n\n\n\n    Overall compute\n   \n\n\n\n   The above are just rough numbers for the largest training clusters. Overall investment is likely to be much larger still: a large fraction of GPUs will probably be be used for inference\n   \n    50\n   \n\n    50\n   \n   See, for example, Zuck\n   \n    here;\n   \n   only (GPUs to actually run the AI systems for products), and there could be multiple players with giant clusters in the race.\n  \n\n\n   My rough estimate is that 2024 will already feature $100B- $200B of AI investment:\n  \n\n\n\n\n\n\n     Nvidia datacenter revenue will hit a ~$25B/quarter run rate soon, i.e. ~$100B of capex flowing via Nvidia alone. But of course, Nvidia isn't the only player (Google's TPUs are great too!), and close to half of datacenter capex is on things other than the chips (site, building, cooling, power, etc.).\n     \n      51\n     \n\n      51\n     \n     For example, this\n     \n      total-cost-of-\n     \n\n\n\n     Big tech has been dramatically ramping their capex numbers: Microsoft and Google will likely do $50B+52, AWS and Meta $40B+, in capex this year. Not all of this is AI, but combined their capex will have grown $50B-$100B year-over-year because of the AI boom, and even then they are still cutting back on other capex to shift even more spending to AI. Moreover, other cloud providers, companies (e.g.,\n     \n      Tesla is\n     \n\n      spending $\n     \n     10B on AI this year), and nation-states are investing in AI as well.\n    \n\n\n\n   ~45k of his H100s are in his largest training clusters, the vast majority of his 350k H100s for inference. Meta likely has heavier inference needs than other players, who serve fewer customers so far, but as everyone else's AI products scale, I expect inference to become a strong majority of the GPUs.\n  \n\n\n\n    ownership analysis\n   \n   estimates that around 40% of a large cluster cost is the H100 GPUs itself, and another 13% goes to Nvidia for Infiniband networking. That said, excluding cost of capital in that calculation would mean the GPUs are about 50% of the cost, and with networking Nvidia gets a bit over 60% of the cost of the cluster.\n  \n\n\n\n    52\n   \n   And\n   \n    apparently,\n   \n   despite Microsoft growing capex by 79% compared to a year ago in a recent quarter, their AI cloud demand still exceeds supply!\n  \n\n\n\n\n\n\n\n\n\n\n   Figure 28: Quarterly Nvidia datacenter revenue. Plot by\n   \n    Thomas Woodside\n   \n\n\n\n   Figure 29: Big tech capex is growing extremely rapidly since ChatGPT unleashed the AI boom.\n   \n    Source.\n   \n\n\n\n   Let's play this forward. My best guess is overall compute investments will grow more slowly than the 3x/year largest training clusters, let's say 2x/year.\n   \n    53\n   \n\n    53\n   \n   A larger fraction of global GPU\n  \n\n\n   And these aren't just my idiosyncratic numbers.\n   \n    AMD fore\n   \n\n    casted\n   \n   a $400B AI accelerator market by 2027, implying $700B+ of total AI spending, pretty close to my numbers (and they are surely much less \"AGI-pilled\" than I am). Sam Altman is re-\n  \n\n\n   production will probably be going to the largest training cluster in the future than today, e.g. because of a consolidation to just a few leading labs, rather than many companies having frontier-model-scale clusters. Regarding power: Of course, not all of this will be in the US, but to give a reference class.\n  \n\n\n\n\n\n      Year\n     \n\n      Annual in\n      \n      vestment\n     \n\n      AI accelerator\n      \n      shipments (in\n      \n      H100s-equivalent)\n     \n\n      Power as % of US\n      \n      electricity produc\n      \n      tion\n     \n\n      Chips as % of current\n      \n      leading-edge TSMC\n      \n      wafer production\n     \n\n\n\n      2024\n     \n\n      ~$150B\n     \n\n      ~5-10M\n     \n\n      1-2%\n     \n\n      5-10%\n     \n\n\n\n      ~2026\n     \n\n      ~$500B\n     \n\n      ~10s of millions\n     \n\n      5%\n     \n\n      ~25%\n     \n\n\n\n      ~2028\n     \n\n      ~$2T\n     \n\n      ~100M\n     \n\n      20%\n     \n\n      ~100%\n     \n\n\n\n      ~2030\n     \n\n      ~$8T\n     \n\n      ~100s of millions\n     \n\n      100%\n     \n\n      4x current capacity\n     \n\n\n\n\n\n   ported to be in talks to raise funds for a project of\n   \n    \"up to $\n   \n   7T\" in capex to build out AI compute capacity (the number was widely mocked, but it seems less crazy if you run the numbers here. . . ). One way or another, this massive scaleup is happening.\n  \n\n\n\n    Will it be done? Can it be done?\n   \n\n\n\n   The scale of investment postulated here may seem fantastical. But both the demand-side and the supply-side seem like they could support the above trajectory. The economic returns justify the investment, the scale of expenditures is not unprecedented for a new general-purpose technology, and the industrial mobilization for power and chips is doable.\n  \n\n\n\n    AI revenue\n   \n\n\n\n   Companies will make large AI investments if they expect the economic returns to justify it.\n  \n\n\n   Reports suggest OpenAI was at a $1B revenue run rate in\n   \n    August\n   \n   2023, and a $2B revenue run rate in\n   \n    February\n   \n   2024. That's roughly a doubling every 6 months. If that trend holds, we should see a ~$10B annual run rate by late 2024/early 2025, even without pricing in a massive surge from any nextgeneration model. One estimate puts\n   \n    Microsoft\n   \n   at ~$5B of incremental AI revenue already.\n  \n\n\n   Table 5: Playing forward trends on total world AI investment. Rough back-ofthe-envelope calculation. For some further details on the calculations, see Appendix.\n  \n\n\n   So far, every 10x scaleup in AI investment seems to yield the necessary returns. GPT-3.5 unleashed the ChatGPT mania. The estimated $500M cost for the GPT-4 cluster would have been paid off by the reported billions of annual revenue for Microsoft and OpenAI (see above calculations), and a \"2024 class\" training cluster in the billions will easily pay off if Microsoft/OpenAI AI revenue continues on track to a $10B+ revenue run rate. The boom is investment-led: it takes time from a huge order of GPUs to build the clusters, build the models, and roll them out, and the clusters being planned today are many years out. But if the returns on the last GPU order keep materializing, investment will continue to skyrocket (and outpace revenue), plowing in even more capital in a bet that the next 10x will keep paying off.\n  \n\n\n   A key milestone for AI revenue that I like to think about is: when will a big tech company (Google, Microsoft, Meta, etc.) hit a $100B revenue run rate from AI (products and API)? These companies have on the order of $100B-$300B of revenue today; $100B would thus start representing a very substantial fraction of their business. Very naively extrapolating out the doubling every 6 months, supposing we hit a $10B revenue run rate in early 2025, suggests this would happen mid-2026.\n  \n\n\n   That may seem like a stretch, but it seems to me to require surprisingly little imagination to reach that milestone. For example, there are around 350\n   \n    million paid subscribers to Mi\n   \n\n    crosoft Office\u2014\n   \n   could you get a third of these to be willing to pay $100/month for an AI add-on? For an average worker, that's only a few hours a month of productivity gained; models powerful enough to make that justifiable seem very doable in the next couple years.\n   \n    54\n   \n\n\n\n   It's hard to understate the ensuing reverberations. This would make AI products the biggest revenue driver for America's largest corporations, and\n   \n    by far\n   \n   their biggest area of growth. Forecasts of overall revenue growth for these companies would skyrocket. Stock markets would follow; we might see our first $10T company soon thereafter. Big tech at this point would be willing to go all out, each investing many hundreds of billions (at least) into further AI scaleout. We probably see our first\n  \n\n\n\n    54\n   \n   A big uncertainty for me is what the lags are for the technology to diffuse and be adopted. I think it's plausible revenue is slowed because intermediate, pre-AGI models take a lot of \"schlep\" to properly integrate into company workflows; historically, it's taken a while to fully harvest the productivity gains from new general purpose technologies. This is where the \"sonic boom\" discussion earlier comes in: as we \"unhobble\" models and they start looking more like agents/dropin remote workers\" deploying them becomes much easier. Rather than having to completely remake some workflow to harvest a 25% productivity gain from a GPT-chatbot, instead you'll get models that you can onboard and work with as you would a new coworker (e.g., just directly substitute for an engineer, rather than needing to train up engineers to use some new tool). Or, in the extreme, and later on: you won't need to completely redesign a factory to work with some new tool, you'll just bring in the humanoid robots.\n  \n\n\n   That said, this may lead to some discontinuity in economic value and revenue generated, depending on how quickly we can \"unhobble\" models.\n  \n\n\n   many-hundred-billion dollar corporate bond sale then.\n   \n    55\n   \n\n    55\n   \n   What will happen to interest rates\n  \n\n\n   Beyond $100B, it gets harder to see the contours. But if we are truly on the path to AGI, the returns will be there. White-collar workers are paid tens of trillions of dollars in wages annually worldwide; a drop-in remote worker that automates even a fraction of white-collar/cognitive jobs (imagine, say, a truly automated AI coder) would pay for the trillion-dollar cluster. If nothing else, the national security import could well motivate a government project, bundling the nation's resources in the race to AGI (more later).\n  \n\n\n\n    Historical precedents\n   \n\n\n\n   $1T/year of total annual AI investment by 2027 seems outrageous. But it's worth taking a look at other historical reference classes:\n  \n\n\n\n\n\n\n     In their peak years of funding, the Manhattan and Apollo programs reached 0.4\n     \n      % of GDP,\n     \n     or ~$100 billion annually today (surprisingly small!). At $1T/year, AI investment would be about 3% of GDP.\n    \n\n\n     Between 1996\u20132001,\n     \n      telecoms invested\n     \n     nearly $1 trillion in today's dollars in building out internet infrastructure.\n    \n\n\n     From 1841 to 1850,\n     \n      private British railway investments to\n     \n\n      taled\n     \n     a cumulative ~40% of British GDP at the time. A similar fraction of\n     \n      US GDP\n     \n     would be equivalent to ~$11T over a decade.\n    \n\n\n\n      Many trillions\n     \n     are being spent on the green transition.\n    \n\n\n     Rapidly-growing economies often spend a high fraction of their GDP on investment; for example, China has spent more than 40\n     \n      % of its GDP on investment for two decades\n     \n     (equivalent to $11T\n     \n      annually\n     \n     given US GDP).\n    \n\n\n     In the historically most exigent national security circumstances wartime\u2014borrowing to finance the national effort has often comprised enormous fractions of GDP. During WWI, the\n    \n\n\n\n   will be interesting. . . see\n   \n    Tyler Cowen\n   \n\n    here;\n   \n\n    Chow, Mazlish and Halperin here.\n   \n\n\n\n\n    UK\n   \n   and\n   \n    France,\n   \n   and\n   \n    Germany\n   \n   borrowed over 100% of their GDPs while the\n   \n    US\n   \n   borrowed over 20%; during WWII, the\n   \n    UK\n   \n   and Japan borrowed over 100% of their GDPs while the\n   \n    US\n   \n   borrowed over 60% of GDP (equivalent to over $17T today).\n  \n\n\n   $1T/year of total AI investment by 2027 would be dramatic among the very largest capital buildouts ever\u2014but would not be unprecedented. And a trillion-dollar individual training cluster by the end of the decade seems on the table.\n   \n    56\n   \n\n    56\n   \n   And, farther out, but if AGI truly led\n  \n\n\n\n    Power\n   \n\n\n\n   Probably the single biggest constraint on the supply-side will be\n   \n    power.\n   \n   Already, at nearer-term scales (1GW/2026 and especially 10GW/2028), power has become the binding constraint: there simply isn't much spare capacity, and power contracts are usually long-term locked-in. And building, say, a new gigawatt-class nuclear power plant takes a decade. (I'll wonder when we'll start seeing things like tech companies buying\n   \n    aluminum smelting companies\n   \n   for their gigawatt-class power contracts.57)\n  \n\n\n\n\n\n\n   to substantial increases in economic growth, $10T+ annually would start being plausible\u2014the reference class being investment rates of countries during high-growth periods.\n  \n\n\n\n    57\n   \n   \"Since 2011, the Alouette Smelter uses 930 MW electricity at maximum production capacity.\"\n  \n\n\n   Figure 30: Comparing trends on total US electricity production to our back-of-the-envelope estimates on AI electricity demands.\n  \n\n\n   Total US electricity generation has\n   \n    barely grown\n   \n   5% in the last\n  \n\n\n\n    decade.\n   \n   Utilities are\n   \n    starting to get excited\n   \n   about AI\n   \n    (instead of\n   \n   2.6% growth over the next 5 years, they now estimate 4.7%!). But they're barely pricing in what's coming. The trillion-dollar, 100GW cluster alone would require ~20% of current US electricity generation in 6 years; together with large inference capacity, demand will be multiples higher.\n  \n\n\n   To most, this seems completely out of the question. Some are betting on Middle Eastern autocracies, who have been going around offering boundless power and giant clusters to get their rulers a seat at the AGI-table.\n  \n\n\n   But it's totally possible to do this in the United States: we have abundant natural gas.\n   \n    58\n   \n\n    58\n   \n   Thanks to\n   \n    Austin Vernon\n   \n   (private\n  \n\n\n\n\n\n\n     Powering a 10GW cluster would take only a few percent of US natural gas production and could be done rapidly.\n    \n\n\n     Even the 100GW cluster is surprisingly doable.\n     \n\n\n\n\n        \u2013\n       \n       Right now the Marcellus/Utica shale (around Pennsylvania) alone is\n       \n        producing\n       \n       around 36 billion cubic feet a day of gas; that would be enough to generate just under 150GW continuously with generators (and combined cycle power plants could output 250 GW due to their higher efficiency).\n      \n\n\n\n\n\n\n        \u2013\n       \n       It would take about ~1200\n       \n        new wells\n       \n       for the 100GW cluster.\n       \n        59\n       \n       Each rig can drill roughly 3 wells per month, so 40\n       \n        59\n       \n       New wells produce around\n       \n        0\n       \n       .\n       \n        01\n       \n       BCF per day. rigs (the current\n       \n        rig count\n       \n       in the Marcellus) could build up the production base for 100GW in less than a year.\n       \n        60\n       \n\n        60\n       \n       Each well produces ~\n       \n        20\n       \n       BCF over The Marcellus had a rig count of ~80 as recently as 2019 so it would not be taxing to add 40 rigs to build up the production base.\n       \n        61\n       \n\n\n\n\n\n\n\n        \u2013\n       \n       More generally, US natural gas production has more than time frame than\n       \n        10\n       \n       months.\n       \n        doubled in a decade;\n       \n       simply continuing that trend could power multiple trillion-dollar datacenters.\n       \n        62\n       \n\n        62\n       \n       A cubic foot of natural gas\n       \n        generates\n       \n\n\n\n\n\n\n\n        \u2013\n       \n       The harder part would be building enough generators / turbines; this wouldn't be trivial, but it seems doable with\n      \n\n\n\n\n\n   correspondence) for helping with these estimates.\n  \n\n\n\n\n\n   its lifetime, meaning two new wells a month would replace the depleted reserves. That is, it would need only one rig to maintain the production.\n   \n    61\n   \n   Though it would be more efficient to add less rigs and build up over a longer\n  \n\n\n\n    about\n   \n   0.13 kWh. Shale gas production\n   \n    was about\n   \n   ~70 billion cubic feet per day in the US in 2020. Suppose we doubled production again, and the extra capacity all went to compute clusters. That's 3322 TWh/year of electricity, or enough for almost 4 100GW clusters.\n  \n\n\n   about $100B of capex\n   \n    63\n   \n   for 100GW of natural gas power\n   \n    63\n   \n   The capex costs for natural gas power plants. Combined cycle plants can be built in about two years; the timeline for generators would be even shorter still.\n   \n    64\n   \n\n\n\n   The barriers to even trillions of dollars of datacenter buildout in the US are entirely self-made. Well-intentioned but rigid climate commitments (not just by the government, but green datacenter commitments by Microsoft, Google, Amazon, and so on) stand in the way of the obvious, fast solution. At the very least, even if we won't do natural gas, a broad deregulatory agenda would unlock the solar/batteries/SMR/geothermal megaprojects. Permitting, utility regulation, FERC regulation of\n   \n    transmission lines,\n   \n   and NEPA environmental review makes things that should take a few years take a decade or more. We don't have that kind of time.\n  \n\n\n   We're going to drive the AGI datacenters to the Middle East, under the thumb of brutal, capricious autocrats. I'd prefer clean energy too\u2014but this is simply too important for US national security. We will need a new level of determination to make this happen. The power constraint can, must, and will be solved.\n  \n\n\n\n    Chips\n   \n\n\n\n   While chips are usually what comes to mind when people think about AI-supply-constraints, they're likely a smaller constraint than power. Global production of AI chips is still a pretty small percent of TSMC-leading-edge production, likely less than 10%. There's a lot of room to grow via AI becoming a larger share of TSMC production.\n  \n\n\n   Indeed, 2024 production of AI chips (~5-10M H100-equivalents) would already be almost enough for the $100s of billion cluster (if they were all diverted to one cluster). From a pure logic fab standpoint ~100% of TSMC's output for a year could already support the trillion-dollar cluster (again if all the chips went to one datacenter).\n   \n    65\n   \n   Of course, not all of TSMC will be able to be diverted to AI, and not all of AI chip production for a year will be for one training cluster. Total AI chip demand (including\n  \n\n\n   plants\n   \n    seem to be\n   \n   under $1000 per kW, meaning the capex for 100GW of natural gas power plants would be about $100 billion.\n  \n\n\n\n    64\n   \n   Solar and batteries aren't a totally crazy alternative, but it does just seem rougher than natural gas. I did appreciate\n   \n    Casey Handmer's\n   \n\n    calculation\n   \n   of tiling the Earth in solar panels:\n  \n\n\n   \"With current GPUs, the global solar datacenter's compute is equivalent to ~150 billion humans, though if our computers can eventually match [human brain] efficiency, we could support more like 5 quadrillion AI souls.\"\n  \n\n\n\n    65\n   \n   This poses the interesting question of why power requirements are going up so much before chip fab production starts being really constrained. A simple answer is while datacenters run continuously at close to max power, most chips currently produced are idle a lot of the time. Currently, smartphones are close to half of leading chip demand, but use a lot less energy per wafer area (trading transistors for serial operations and energy efficiency) and have low utilization as smartphones are mostly idle. The AI revolution means working our transistors way harder, dedicating them all to constantly-running, high-performance AI datacenters instead of idle, batterypowered/energy-saving devices. HT Carl Shulman for this point.\n  \n\n\n   inference and multiple players) by 2030 will be a multiple of TSMC's current total leading-edge logic chip capacity, just for AI. TSMC\n   \n    ~doubled\n   \n\n    66\n   \n   in the past 5 years; they'd likely need to\n   \n    66\n   \n   (Using revenue as a proxy.) go ~at least twice as fast on their pace of expansion to meet AI chip demand. Massive new fab investments would be necessary.\n  \n\n\n   Even if raw logic fabs won't be the constraint, chip-on-waferon-substrate (CoWoS) advanced packaging (connecting chips to memory, also made by TSMC, Intel, and others) and HBM memory (for which demand\n   \n    is\n   \n\n    enormous)\n   \n   are already key bottlenecks for the current AI GPU scaleup; these are more specialized to AI, unlike the pure logic chips, so there's less pre-existing capacity. In the near term, these will be the primary constraint on churning out more GPUs, and these will be the huge constraints as AI scales. Still, these are comparatively \"easy\" to scale; it's been incredible watching TSMC literally build \"greenfield\" fabs (i.e. entirely new facilities from scratch) to massively scale up CoWoS production this year (and Nvidia is even starting to find\n   \n    CoWoS alternatives\n   \n   to work around the shortage).\n  \n\n\n   A new TSMC\n   \n    Gigafab\n   \n   (a\n   \n    technological marvel)\n   \n   costs around $20B in capex and produces 100k wafer-starts a month. For hundreds of millions of AI GPUs a year by the end of the decade, TSMC would need to build dozens of these\u2014as well as a huge buildout for memory, advanced packaging, networking, etc., which will be a major fraction of capex. It could add up to over $1T of capex. It will be intense, but doable. (Perhaps the biggest roadblock will not be feasibility, but TSMC not even trying\u2014TSMC does not yet seem AI-scaling-pilled! They think AI will \"only\" grow at a glacial 50\n   \n    % CAGR.\n   \n   )\n  \n\n\n   Recent USG efforts like the CHIPS Act have been trying to onshore more AI chip production to the US (as insurance in case of the Taiwan contingency). While onshoring more of AI chip production to the US would be nice, it's less critical than having the actual datacenter (on which the AGI lives) in the US. If having chip production abroad is like having uranium deposits abroad, having the AGI datacenter abroad is like having the literal nukes be built and stored abroad. Given the dysfunction\n  \n\n\n\n\n\n   and cost we've seen from building fabs in the US in practice, my guess is we should prioritize datacenters in the US while betting more heavily on democratic allies like Japan and South Korea for fab projects\u2014fab buildouts there\n   \n    seem much more\n   \n\n    functional.\n   \n\n\n\n\n    The Clusters of Democracy\n   \n\n\n\n   Before the decade is out, many trillions of dollars of compute clusters will have been built. The only question is whether they will be built in America. Some are rumored to be betting on building them elsewhere, especially in the Middle East. Do we really want the infrastructure for the Manhattan Project to be controlled by some capricious Middle Eastern dictatorship?\n  \n\n\n   The clusters that are being planned today may well be the clusters AGI and superintelligence are trained and run on, not just the \"cool-big-tech-product clusters.\" The national interest demands that these are built in America (or close democratic allies). Anything else creates an irreversible security risk: it\n   \n    risks the AGI weights getting stolen\n   \n\n    67\n   \n   (and perhaps be\n   \n    shipped\n   \n\n    67\n   \n   It's a lot easier to do side-channel ataccess!\n   \n    to China)\n   \n   ; it risks these dictatorships physically seizing the datacenters (to build and run AGI themselves) when the AGI race gets hot; or even if these threats are only wielded implicity, it puts AGI and superintelligence at unsavory dictator's whims. America sorely regretted her energy dependence on the Middle East in the 70s, and we worked so hard to get out from under their thumbs. We cannot make the same mistake again.\n  \n\n\n   The clusters can be built in the US, and we have to get our act together to make sure it happens in the US. American national security must come first, before the allure of free-flowing Middle Eastern cash, arcane regulation, or even, yes, admirable climate commitments. We face a real system competition can the requisite industrial mobilization only be done in \"topdown\" autocracies? If American business is unshackled, America can build like none other (at least in red states). Being willing to use natural gas, or at the very least a broad-based deregulatory agenda\u2014NEPA exemptions, fixing FERC and\n  \n\n\n   tacks to exfiltrate weights with physical\n  \n\n\n   transmission permitting at the federal level, overriding utility regulation, using federal authorities to unlock land and rights of way\u2014is a national security priority.\n  \n\n\n   In any case: the exponential is in full swing now.\n  \n\n\n   In the \"old days,\" when AGI was still a dirty word, some colleagues and I used to make theoretical economic models of what the path to AGI might look like. One feature of these models used to be a hypothetical \"AI wakeup\" moment, when the world started realizing how powerful these models could be and began rapidly ramping up their investments culminating in multiple % of GDP towards the largest training runs.\n  \n\n\n   It seemed far-off then, but that time has come. 2023\n   \n    was\n   \n   \"AI wakeup.\"\n   \n    68\n   \n   Behind the scenes, the most staggering techno-\n   \n    68\n   \n   I distinctly remember writing \"THE capital acceleration has been put into motion.\n  \n\n\n   Brace for the G-forces.\n  \n\n\n\n    (What all of this means for NVDA/TSM/etc I leave as an exercise for the reader. Hint: Those with situational awareness bought much lower than you, but it's still not even close to fully priced in.)\n   \n\n    69\n   \n\n    69\n   \n   Mainstream sell-side analysts seem\n  \n\n\n   TAKEOFF HAS STARTED\" on my whiteboard in March of 2023.\n  \n\n\n   to assume only 10-20% year-over-year growth in Nvidia revenue from CY24 to CY25, maybe $120B-$130B in CY25 (or at least did until very recently). Insane! It's been pretty obvious for a while that Nvidia is going to do over $200B of revenue in CY25.\n  \n\n\n\n    IIIb. Lock Down the Labs: Security for AGI\n   \n\n\n\n\n    The nation's leading AI labs treat security as an afterthought. Currently, they're basically handing the key secrets for AGI to the CCP on a silver platter. Securing the AGI secrets and weights against the state-actor threat will be an immense effort, and we're not on track.\n   \n\n\n\n\n\n    They met in the evening in Wigner's office. \"Szilard outlined the Columbia data,\" Wheeler reports, \"and the preliminary indications from it that at least two secondary neutrons emerge from each neutron-induced fission. Did this not mean that a nuclear explosive was certainly possible?\" Not necessarily, Bohr countered.\n   \n\n\n\n\n\n    \"We tried to convince him,\" Teller writes, \"that we should go ahead with fission research but we should not publish the results. We should keep the results secret, lest the Nazis learn of them and produce nuclear explosions first.\"\n   \n\n\n\n   \"Bohr insisted that we would never succeed in producing nuclear energy and he also insisted that secrecy must never be introduced into physics.\"\n  \n\n\n\n    The Making of the Atomic Bomb\n   \n   , p. 430\n  \n\n\n   On the current course, the leading Chinese AGI labs won't be in Beijing or Shanghai\u2014they'll be in San Francisco and London. In a few years, it will be clear that the AGI secrets are the United States' most important national defense secrets\u2014deserving treatment on par with B-21 bomber or Columbia-class submarine blueprints, let alone the proverbial\n  \n\n\n   \"nuclear secrets\"\u2014but today, we are treating them the way we would random SaaS software. At this rate, we're basically just handing superintelligence to the CCP.\n  \n\n\n   All the trillions we will invest, the mobilization of American industrial might, the efforts of our brightest minds\u2014none of that matters if China or others can simply steal the model\n   \n    weights\n   \n   (all a finished AI model is, all AGI will be, is a large file on a computer) or key\n   \n    algorithmic secrets\n   \n   (the key technical breakthroughs necessary to build AGI).\n  \n\n\n   America's leading AI labs self-proclaim to be building AGI: they believe that the technology they are building will, before the decade is out, be the most powerful weapon America has ever built. But they do not treat it as such. They measure their security efforts against \"random tech startups,\" not \"key national defense projects.\" As the AGI race intensifies\u2014as it becomes clear that superintelligence will be utterly decisive in international military competition\u2014we will have to face the full force of foreign espionage. Currently, labs are barely able to defend against scriptkiddies, let alone have \"North Koreaproof security,\" let alone be ready to face the Chinese Ministry of State Security bringing its full force to bear.\n  \n\n\n   And this won't just matter years in the future. Sure, who cares if GPT-4 weights are stolen\u2014what really matters in terms of weight security is that we can secure the AGI weights down the line, so we have a few years, you might say. (Though if we're building AGI in 2027, we really have to get moving!) But the AI labs are developing the\n   \n    algorithmic secrets\u2014\n   \n   the key technical breakthroughs, the blueprints so to speak\u2014for the AGI\n   \n    right now\n   \n   (in particular, the RL/self-play/synthetic data/etc \"next paradigm\" after LLMs to get past the data wall). AGI-level security for algorithmic secrets is necessary years before AGIlevel security for weights. These algorithmic breakthroughs will matter more than a 10x or 100x larger cluster in a few years\u2014this is a much bigger deal than export controls on compute, which the USG has been (presciently!) intensely pursuing. Right now, you needn't even mount a dramatic espionage operation to steal these secrets: just go to any SF party or look through the office windows.\n  \n\n\n   Our failure today will be irreversible soon: in the next 12-24 months, we will leak key AGI breakthroughs to the CCP. It will be the national security establishment's single greatest regret before the decade is out.\n  \n\n\n   The preservation of the free world against the authoritarian states is on the line\u2014and a healthy lead will be the necessary buffer that gives us margin to get AI safety right, too. The United States has an advantage in the AGI race. But we will give up this lead if we don't get serious about security very soon. Getting on this, now, is maybe even the single most important thing we need to do today to ensure AGI goes well.\n  \n\n\n\n    Underrate state actors at your peril\n   \n\n\n\n   Too many smart people underrate espionage.\n  \n\n\n   The capabilities of states and their intelligence agencies are extremely formidable. Even in normal, non-all-out-AGI-race times (and from the little we know publicly), nation-states (or less advanced actors) have been able to:\n  \n\n\n\n\n\n\n\n      Zero-click hack any desired iPhone and Mac\n     \n     with just a phone number,\n    \n\n\n     Infiltrate an\n     \n      airgapped atomic weapons program,\n     \n\n\n\n\n      Modify Google source code,\n     \n\n\n\n     Find\n     \n      dozens of zero-days\n     \n     a year that take\n     \n      on average of\n     \n     7\n     \n      years\n     \n     to detect,\n    \n\n\n     Spearfish\n     \n      major tech companies,\n     \n\n\n\n     Install\n     \n      keyloggers on employee devices,\n     \n\n\n\n     Insert\n     \n      trapdoors in encryption schemes,\n     \n\n\n\n     Steal information\n     \n      via electromagnetic emanations or vibra\n     \n\n      tion,\n     \n\n\n\n\n\n\n\n\n     Use\n     \n      just the noise from your computer\n     \n     to determine where you are on a video game map or\n     \n      steal a password,\n     \n\n\n\n     Gain direct access to sensitive systems like\n     \n      nuclear power\n     \n\n      plants,\n     \n\n\n\n     Exfiltrate 22\n     \n      million security clearance files\n     \n     from the USG,\n    \n\n\n     Expose the\n     \n      financial information of\n     \n     110 million customers by\n     \n      planting vulnerabilities in HVAC systems,\n     \n\n\n\n     Compromise\n     \n      computer hardware supply chains at large\n     \n\n      scale,\n     \n\n\n\n     Slip\n     \n      malicious code into updates to software dependencies\n     \n     used by top tech companies and the USG\n    \n\n\n     . . . let alone planting spies or seducing, cajoling, or threatening employees (which happens effectively at\n     \n      large scales,\n     \n     but is less public)\n    \n\n\n     . . . let alone special forces operations and similar (when things really get hot).\n    \n\n\n\n   For a further taste of what we're dealing with when facing down intelligence agencies, I highly recommend\n   \n    Inside the Aquarium\n   \n   , a book by a Soviet GRU (military intelligence) defector.\n   \n    70\n   \n\n\n\n   Already, China engages in widespread industrial espionage; the FBI director stated the PRC has a hacking operation greater than\n   \n    \"every major nation combined.\n   \n   \" And just a couple months ago, the Attorney General\n   \n    announced the arrest of a Chinese\n   \n\n    national\n   \n   who had stolen key AI code from Google to take back with him to the PRC (back in 2022/23, and probably just the tip of the iceberg).\n   \n    71\n   \n\n\n\n   But that's just the beginning. We must be prepared for our adversaries to \"wake up to AGI\" in the next few years. AI will become the #1 priority of every intelligence agency in the world. In that situation, they would be willing to employ extraordinary means and pay any cost to infiltrate the AI labs.\n  \n\n\n\n    70\n   \n   One spoiler, as a taste: on graduation from their ~spy academy, before being sent overseas, aspiring spies had to prove their skills domestically: they had to acquire secret information from a Soviet scientist. The penalty for revealing state secrets, of course, was death. That is: graduating from the ~spy academy meant picking a countryman to condemn to death. HT Ilya Sutskever for the book recommendation.\n  \n\n\n\n    71\n   \n   By the way, the indictment provides a great illustration of how easy it is to evade security at even Google, which likely has the best security of all the AI labs (given their ability to lean on Google's decades-long investment in security infrastructure). All it took to steal the code, without detection, was pasting code into Apple Notes, then exporting to pdf!\n  \n\n\n   \"DING exfiltrated these files by copying data from the Google source files into the Apple Notes application on his Google-issued MacBook laptop. DING then converted the Apple Notes into PDF files. and uploaded them from the Google network into DING Account 1. This method helped DING evade immediate detection.\" (From the\n   \n    indictment.\n   \n   )\n  \n\n\n   He only got caught because he did a bunch of other stupid things, like immediately start prominent startups in China which got people suspicious (and later even came back to the US).\n  \n\n\n\n    The threat model\n   \n\n\n\n   There are two key assets we must protect: model weights (especially as we get close to AGI, but which takes years of preparation and practice to get right) and algorithmic secrets (starting yesterday).\n  \n\n\n\n    Model weights\n   \n\n\n\n   An AI model is just a large file of numbers on a server. This can be stolen. All it takes an adversary to match your trillions of dollars and your smartest minds and your decades of work is to steal this file. (Imagine if the Nazis had gotten an exact duplicate of every atomic bomb made in Los Alamos.)\n  \n\n\n   If we can't keep model weights secure, we're just building AGI for the CCP (and, given the current trajectory of AI lab security, even North Korea).\n  \n\n\n   Even besides national competition, securing model weights is critical for preventing AI catastrophes as well. All of our handwringing and protective measures are for naught if a bad actor (say, a terrorist or rogue state) can just steal the model and do whatever they want with it, circumventing any safety layers. Whatever novel WMDs superintelligence could invent would rapidly proliferate to dozens of rogue states. Moreover, security is the first line of defense against uncontrolled or misaligned AI systems, too (how stupid would we feel if we failed to contain the rogue superintelligence because we didn't build and test it in an air-gapped cluster first?).\n  \n\n\n   Securing model weights doesn't matter that much right now: stealing GPT-4 without the underlying recipe doesn't do that much for the CCP. But it will\n   \n    really\n   \n   matter in a few years, once we have AGI, systems that are genuinely incredibly powerful.\n  \n\n\n\n    Perhaps the single scenario that most keeps me up at night is if China or another adversary is able to steal the automated-AI-researchermodel-weights on the cusp of an intelligence explosion.\n   \n   China could immediately use these to automate AI research themselves\n  \n\n\n   (even if they had previously been way behind)\u2014and launch their own intelligence explosion. That'd be all they need to automate AI research, and build superintelligence. Any lead the US had would vanish.\n  \n\n\n   Moreover, this would immediately put us in an existential race; any margin for ensuring superintelligence is safe would disappear. The CCP may well try to race through an intelligence explosion as fast as possible\u2014even months of lead on superintelligence could mean a decisive military advantage\u2014in the process skipping all the safety precautions any responsible US AGI effort would hope to take. We would also have to race through the intelligence explosion to avoid complete CCP dominance. Even if the US still manages to barely pull out ahead in the end, the loss of margin would mean having to run enormous risks on AI safety.\n  \n\n\n   We're miles away for sufficient security to protect weights today. Google DeepMind (perhaps the AI lab that has the best security of any of them, given Google infrastructure) at least straight-up admits this. Their\n   \n    Frontier Safety Framework\n   \n   outlines security levels 0, 1, 2, 3, and 4 (~1.5 being what you'd need to defend against well-resourced terrorist groups or cybercriminals, 3 being what you'd need to defend against the North Koreas of the world, and 4 being what you'd need to have even a shot of defending against priority efforts by the most capable state actors).\n   \n    72\n   \n   They admit to being at level 0 (only the most banal and basic measures). If we got AGI and superintelligence soon, we'd literally deliver it to terrorist groups and every crazy dictator out there!\n  \n\n\n   Critically, developing the infrastructure for weight security probably takes many years of lead times\u2014if we think AGI in ~3-4 years is a real possibility and we need state-proof weight security then, we need to be launching the crash effort\n   \n    now.\n   \n   Securing weights will require innovations in hardware and radically different cluster design; and security at this level can't be reached overnight, but requires cycles of iteration.\n  \n\n\n   If we fail to prepare in time, our situation will be dire. We will be on the cusp of superintelligence, but years away from the se-\n  \n\n\n\n    72\n   \n   Based off of their claimed correspondence of their security levels to\n   \n    RAND's\n   \n\n    weight security report's\n   \n   L1-L5\n  \n\n\n   curity necessary. Our choice will be to press ahead, but directly deliver superintelligence to the CCP\u2014with the existential race through the intelligence explosion that implies\u2014or wait until the security crash program is complete, risking losing our lead.\n  \n\n\n\n    Algorithmic secrets\n   \n\n\n\n   While people are starting to appreciate (though not necessarily implement) the need for weight security, arguably even more important right now\u2014and\n   \n    vastly\n   \n   underrated\u2014is securing algorithmic secrets.\n  \n\n\n   One way to think about this is that stealing the algorithmic secrets will be worth having a 10x or more larger cluster to the PRC:\n  \n\n\n\n\n\n\n     As discussed in Counting the OOMs, algorithmic progress is probably similarly as important as scaling up compute to AI progress. Given the baseline trend of ~0.5 OOMs of compute efficiency a year (+ additional algorithmic \"unhobbling\" gains on top), we should expect multiple OOMs-worth of algorithmic secrets between now and AGI. By default, I expect American labs to be years ahead; if they can defend their secrets, this could easily be worth 10x-100x compute.\n     \n\n\n\n\n        \u2013\n       \n       (Note that we're willing to incur American investors 100s of billions of dollars of costs by export controlling Nvidia chips\u2014perhaps a 3x increase in compute cost for Chinese labs\u2014but we're leaking 3x algorithmic secrets all over the place!)\n      \n\n\n\n\n     Maybe even more importantly,\n     \n      we may be developing the key paradigm breakthroughs for AGI right now.\n     \n     As discussed previously, simply scaling up current models will hit a wall: the data wall. Even with way more compute, it won't be possible to make a better model. The frontier AI labs are furiously at work at what comes next, from RL to synthetic data. They will probably figure out some crazy stuff essentially, the \"AlphaGo self-play\"-equivalent for general intelligence. Their inventions will be as key as the invention of the LLM paradigm originally was a number of years\n    \n\n\n\n   ago, and they will be the key to building systems that go far beyond human-level. We still have an opportunity to deny China these key algorithmic breakthroughs, without which they'd be stuck at the data wall. But without better security in the next 12-24 months, we may well irreversibly supply China with these key AGI breakthroughs.\n  \n\n\n   \u2022 It's easy to underrate how important an edge algorithmic secrets will be\u2014because up until ~a couple years ago, everything was published. The basic idea was out there: scale up Transformers on internet text. Many algorithmic details and efficiencies were out there: Chinchilla scaling laws, MoE, etc. Thus, open source models today are pretty good, and a bunch of companies have pretty good models (mostly depending on how much $$$ they raised and how big their clusters are). But this will likely change fairly dramatically in the next couple years. Basically all of frontier algorithmic progress happens at labs these days (academia is surprisingly irrelevant), and the leading labs have stopped publishing their advances. We should expect far more divergence ahead: between labs, between countries, and between the proprietary frontier and open source models. A few American labs will be way ahead\u2014a moat worth 10x, 100x, or more, way more than, say, 7nm vs. 3nm chips\u2014unless they instantly leak the algorithmic secrets.\n   \n    73\n   \n\n    73\n   \n   I sometimes joke that AI lab algo-\n  \n\n\n\n    Put simply, I think failing to protect algorithmic secrets is probably the most likely way in which China is able to stay competitive in the AGI race.\n   \n   (I discuss this more later.)\n  \n\n\n   It's hard to overstate how bad algorithmic secrets security is right now. Between the labs, there are thousands of people with access to the most important secrets; there is basically no background-checking, silo'ing, controls, basic infosec, etc. Things are stored on easily hackable SaaS services. People gabber at parties in SF. Anyone, with all the secrets in their head, could be offered $100M and recruited to a Chinese lab at any point.\n   \n    74\n   \n   You can . . . just look through office windows. And\n   \n    74\n   \n   Indeed, I've heard from friends so on. There are many articles, and rumors flying around SF, purporting to have extensive details of various lab algorithmic advances.\n  \n\n\n   rithmic advances are not shared with the American research community, but they are being shared with the Chinese research community!\n  \n\n\n   that ByteDance emailed basically every person who was on the Google Gemini paper to recruit them, offering them L8 (a very senior position, with presumably similarly high pay), and pitching them by saying they'd report directly to the CTO in America of ByteDance.\n  \n\n\n   AI lab security isn't much better than \"random startup security.\" Directly selling the AGI secrets to the CCP would at least be more honest.\n  \n\n\n\n\n    . . . Is this what we see at OpenAI or any other American AI lab? No. In fact, what we see is the opposite\u2014the security equivalent of swiss cheese. Chinese penetration of these labs would be trivially easy using any number of industrial espionage methods, such as simply bribing the cleaning crew to stick USB dongles into laptops. My own assumption is that all such American AI labs are fully penetrated and that China is getting nightly downloads of all American AI research and code RIGHT NOW. . .\n   \n\n\n\n\n\n\n\n\n\n       Marc Andreessen\n      \n\n\n\n\n\n\n   While it will be tough, I think these secrets are defensible. There are probably only dozens of people who truly \"need to know\" the key implementation details for a given algorithmic breakthrough at a given lab (even if a larger number need to know the basic high-level idea)\u2014you can vet, silo, and intensively monitor these people, in addition to radically upgraded infosec.\n  \n\n\n\n    What \"supersecurity\" will require\n   \n\n\n\n   There's a lot of low-hanging fruit on security at AI labs. Merely adopting best practices from, say, secretive hedge funds or Google-customer-data-level security, would put us in a much better position with respect to \"regular\" economic espionage from the CCP. Indeed, there are notable examples of private sector firms doing remarkably well at preserving secrets. Take quantitative trading firms (the Jane Streets of the world) for example. A number of people have told me that in an hour of conversation they could relay enough information to a competitor such that their firm's alpha would go to ~zero\u2014similar to how many key AI algorithmic secrets could be relayed in a short conversation\u2014and yet these firms manage to keep these secrets and retain their edge.\n  \n\n\n   While most of America's leading AI labs have refused to put the national interest first\u2014rejecting even basic security mea-\n  \n\n\n   sures in this tier, if they have any cost or require any prioritization of security\u2014picking this low-hanging fruit would be well within their abilities.\n  \n\n\n   But let's look out just a bit further. Once China begins to truly understand the import of AGI, we should expect the full force of their espionage efforts to come to bear; think billions of dollars invested, thousands of employees, and extreme measures (e.g., special operations strike teams) dedicated to infiltrating American AGI efforts. What will security for AGI and superintelligence require?\n  \n\n\n   In short,\n   \n    this will only be possible with government help\n   \n   . Microsoft, for example, is regularly hacked by state actors (e.g., Russian hackers recently\n   \n    stole Microsoft executives' emails,\n   \n   as well as\n   \n    government emails Microsoft hosts)\n   \n   . A high-level security expert working in the field estimated that even with a complete private crash course, China would still likely be able to exfiltrate the AGI weights if it was their #1 priority\u2014the only way to get this probability to the single digits would require, more or less, a government project.\n  \n\n\n   While the government does not have a perfect track record on security themselves, they're the only ones who have the infrastructure, know-how, and competencies to protect nationaldefense-level secrets. Basic stuff like the authority to subject employees to intense vetting; threaten imprisonment for leaking secrets; physical security for datacenters; and the vast know-how of places like the NSA and the people behind the security clearances (private companies simply don't have the expertise on state-actor attacks).\n  \n\n\n   I'm not one of the people behind the security clearances, so I can't give a proper accounting of what security for AGI will truly require. The best public resource on this is RAND's\n   \n    re\n   \n\n    port on weight security.\n   \n   To give a taste of what this state-actor proof security will actually mean:\n  \n\n\n   \u2022 Fully airgapped datacenters, with physical security on par with most secure military bases (cleared personnel, physical fortifications, onsite response team, extensive surveillance\n  \n\n\n   and extreme access control),\n  \n\n\n\n\n\n\n\n      \u2013\n     \n     And not just for training clusters\u2014inference clusters need the same intense security!\n     \n      75\n     \n\n      75\n     \n     Inference fleets will likely be much\n    \n\n\n     Novel technical advances on confidential compute / hardware encryption\n     \n      76\n     \n     and extreme scrutiny on the entire hardware supply chain,\n    \n\n\n     All research personnel working from a\n     \n      SCIF\n     \n     (Sensitive Compartmented Information Facility, pronounced \"skiff\", see\n     \n      this\n     \n\n      visualization)\n     \n     ,\n    \n\n\n     Extreme personnel vetting and security clearances (including regular employee integrity testing and the like), constant monitoring and substantially reduced freedoms to leave, and rigid information siloing.\n    \n\n\n     Strong internal controls, e.g. multi-key signoff to run any code.\n    \n\n\n     Strict limitations on any external dependencies, and satisfying general requirements of TS/SCI networks.\n    \n\n\n     Ongoing intense pen-testing by the NSA or similar.\n    \n\n\n     And so on. . .\n    \n\n\n\n   The giant AGI clusters are being mapped out, right now; the corresponding security effort must be too. If we are building AGI in just a few years, we have very little time.\n  \n\n\n   Still, this immense effort shouldn't lead to fatalism. The saving grace on security is that the CCP probably isn't fully AGIpilled yet, and so not yet investing in the most extreme efforts. American AI lab security \"only\" has to stay ahead of the curve compared to the intensity of Chinese espionage efforts. That means immediately upgrading security to stay ahead of \"more normal\" economic espionage (which we are far from resistant to, but private companies probably could be); and that means over the next couple years, as Chinese and other foreign espionage ramps up, rapidly upgrading to much more intense\n  \n\n\n   larger than training clusters, and there will be overwhelming pressure to use these inference clusters to run automated AI researchers during the intelligence explosion (and run billions of superintelligences more broadly in the immediate aftermath). The AGI/superintelligence weights could thus be exfiltrated from these clusters as well. (I worry that this is underrated, and inference clusters will be much less protected.)\n  \n\n\n\n    76\n   \n   But you can't rely only on this! Hardware encryption regularly gets\n   \n    side-channeled.\n   \n   Defense-in-depth is key, of course.\n  \n\n\n   measures in cooperation with the government.\n  \n\n\n   Some argue that strict security measures and their associated friction aren't worth it because they would slow down American AI labs too much. But I think that's mistaken:\n  \n\n\n\n\n\n\n     This is a tragedy of the commons problem. For a given lab's commercial interests, security measures that cause a 10% slowdown might be deleterious in competition with other labs. But the national interest is clearly better served if every lab were willing to accept the additional friction: American AI research is way ahead of Chinese and other foreign algorithmic progress, and America retaining 90%-speed algorithmic progress as our national edge is clearly better than retaining 0% as a national edge (with everything instantly stolen)!\n    \n\n\n     Moreover, ramping security now will be the\n     \n      less\n     \n     painful path in terms of research productivity in the long run. Eventually, inevitably, if only on the cusp of superintelligence, in the extraordinary arms race to come, the USG will realize the situation is unbearable and demand a security crackdown. It will be so much more painful, and cause much more of a slowdown, to have to implement extreme, state-actor-proof security measures from a standing start, rather than iteratively.\n    \n\n\n\n   Others argue that even if our secrets or weights leak, we will still manage to eke out\n   \n    just ahead\n   \n   by being faster in other ways (so we needn't worry about security measures). That, too, is mistaken, or at least running\n   \n    way\n   \n   too much risk:\n  \n\n\n   \u2022 As I discuss in a later piece, I think the CCP may well be able to brutely outbuild the US (a 100GW cluster will be much easier for them). More generally, China might not have the same caution slowing it down that the US will (both reasonable and unreasonable caution!). Even if stealing the algorithms or weights \"only\" puts them on par with the US model-wise, that might be enough for them to win the race to superintelligence.\n  \n\n\n\n\n\n\n     Moreover, even if the US squeaks out ahead in the end, the difference between a 1-2 year and 1-2 month lead will\n     \n      really\n     \n     matter for navigating the perils of superintelligence. A 1-2 year lead means at least a reasonable margin to get safety right, and to navigate the extremely volatile period around the intelligence explosion and post-superintelligence.\n     \n      77\n     \n     A\n     \n      77\n     \n     E.g., space to take an extra\n     \n      6\n     \n     months mere 1-2 month lead means a breakneck international arms race with extreme pressures, racing through the intelligence explosion, and no room at all to get safety right. It is that neck-and-neck, existential race in which we face the greatest risks of self-destruction.\n    \n\n\n     Don't forget about Russia, Iran, North Korea, and so on. Their hacking capabilities are no slouch. On the current course, we're freely sharing superintelligence with them too! Without much better security, we're proliferating what will be our most powerful weapon to a plethora of incredibly dangerous, reckless, and unpredictable actors.\n     \n      78\n     \n\n      78\n     \n     We try really hard to prevent nuclear\n    \n\n\n\n   during the intelligence explosion for alignment research to make sure superintelligence doesn't go awry, time to stabilize the situation after the invention of some novel WMDs by directing these systems to focus on defensive applications, or simply time for human decision-makers to make the right decisions given an extraordinarily rapid pace of technological change with the advent of superintelligence.\n  \n\n\n   proliferation to rogue states, even if we'd still be \"ahead\" on nuclear technology compared to their more limited arsenal, given the mayhem\n  \n\n\n   proliferation can cause.\n   \n    We are not on track\n   \n\n\n\n   When it first became clear to a few that an atomic bomb was possible, secrecy, too, was perhaps the most contentious issue. In 1939 and 1940, Leo Szilard became known \"throughout the American physics community as the leading apostle of secrecy in fission matters.\"\n   \n    79\n   \n   But he was rebuffed by most; secrecy was\n   \n    79\n   \n\n    The Making of the Atomic Bomb, p.\n    \n     509\n    \n\n   not at all something scientists were used to, and it ran counter to many of their basic instincts of open science. But it slowly became clear what had to be done: the military potential of this research was too great for it to simply be freely shared with the Nazis. And secrecy was finally imposed, just in time.\n  \n\n\n   In the fall of 1940, Fermi had finished new carbon absorption measurements on graphite, suggesting graphite was a viable moderator for a bomb. Szilard assaulted Fermi with yet another secrecy appeal. \"At this time Fermi really lost his temper; he really thought this was absurd,\" Szilard recounted. Luckily, further appeals were eventually successful, and Fermi reluctantly refrained from publishing his graphite results.\n  \n\n\n\n\n\n\n\n\n\n   Figure 31:\n   \n    Leo Szilard.\n   \n\n\n\n   At the same time, the German project had narrowed down on two possible moderator materials: graphite and heavy water. In\n   \n    early\n   \n   1941 at Heidelberg, Walther Bothe made an incorrect measurement on the absorption cross-section of graphite, and concluded that graphite would absorb too many neutrons to sustain a chain reaction. Since Fermi had kept his result secret, the Germans did not have Fermi's measurements to check against, and to correct the error.\n   \n    This was crucial: it left the German project to pursue heavy water instead\u2014a decisive wrong path that ultimately doomed the German nuclear weapons effort.\n   \n\n    80\n   \n\n    80\n   \n\n    The Making of the Atomic Bomb,\n   \n   p.\n   \n    507\n   \n\n\n\n   If not for that last-minute secrecy appeal, the German bomb project may have been a much more formidable competitor and history might have turned out very differently.\n  \n\n\n   There's a real mental dissonance on security at the leading AI labs. They full-throatedly claim to be building AGI this decade. They emphasize that American leadership on AGI will be decisive for US national security. They are reportedly planning 7\n   \n    T chip buildouts\n   \n   that only make sense if you\n   \n    really\n   \n   believe in AGI. And indeed, when you bring up security, they nod and acknowledge \"of course, we'll all be in a bunker\" and smirk.\n  \n\n\n   And yet the reality on security could not be more divorced from that. Whenever it comes time to make hard choices to prioritize security, startup attitudes and commercial interests prevail over the national interest. The national security advisor would have a mental breakdown if he understood the level of security at the nation's leading AI labs.\n  \n\n\n   There are secrets being developed right now, that can be used for every training run in the future and will be the key unlocks to AGI, that are protected by the security of a startup and will be worth hundreds of billions of dollars to the CCP.\n   \n    81\n   \n   The real-\n   \n    81\n   \n\n    100\n   \n   x+ compute efficiencies, when are being built. ity is that, a) in the next\n   \n    12\n   \n   -\n   \n    24\n   \n   months, we will develop the key algorithmic breakthroughs for AGI, and promptly leak them to the CCP, and b) we are not even on track for our weights to be secure against rogue actors like North Korea, let alone an\n  \n\n\n\n\n\n   clusters worth $10s or $100s of billions\n  \n\n\n   all-out effort by China, by the time we build AGI. \"Good security for a startup\" simply is not even close to good enough, and we have very little time before the egregious damage to the national security of the United States becomes irreversible.\n  \n\n\n   We're developing the most powerful weapon mankind has ever created. The algorithmic secrets we are developing, right now, are literally the nation's most important national defense secrets\u2014the secrets that will be at the foundation of the US and her allies' economic and military predominance by the end of the decade, the secrets that will determine whether we have the requisite lead to get AI safety right, the secrets that will determine the outcome of WWIII, the secrets that will determine the future of the free world. And yet AI lab security is probably worse than a random defense contractor making bolts.\n  \n\n\n   It's madness.\n  \n\n\n   Basically nothing else we do\u2014on national competition, and on AI safety\u2014will matter if we don't fix this, soon.\n  \n\n\n\n\n\n\n   Figure 32: A\n   \n    billboard\n   \n   at the Oak Ridge, Tennessee uranium enrichment facilities, 1943.\n  \n\n\n\n    IIIc. Superalignment\n   \n\n\n\n\n    Reliably controlling AI systems much smarter than we are is an unsolved technical problem. And while it is a solvable problem, things could very easily go off the rails during a rapid intelligence explosion. Managing this will be extremely tense; failure could easily be catastrophic.\n   \n\n\n\n\n\n    The old sorcerer Has finally gone away! Now the spirits he controls Shall obey my commands. . . . I shall work wonders too.\n    \n     . . .\n    \n    Sir, I'm in desperate straits!\n    \n     The spirits I summoned - I can't get rid of them.\n    \n\n\n\n\n\n\n\n\n     johann wolfgang von goethe \"The Sorcerer's Apprentice\"\n    \n\n\n\n\n   By this point, you have probably heard of the AI doomers. You might have been intrigued by their arguments, or you might have dismissed them off-hand. You're loath to read yet another doom-and-gloom meditation.\n  \n\n\n   I am not a doomer.\n   \n    82\n   \n   Misaligned superintelligence is probably not the biggest AI risk.\n   \n    83\n   \n   But I did spend the past year working on technical research on aligning AI systems as my day-job at OpenAI, working with Ilya and the\n   \n    Superalignment\n   \n\n\n\n\n    82\n   \n   As not-very-politely\n   \n    certified by the\n   \n\n    doomer-in-chief!\n   \n   At the very least, I would\n   \n    call myself a strong optimist\n   \n   that this problem is solvable. I have spent considerable energies debating the AI pessimists and strongly advocated against policies like an AI pause.\n   \n    83\n   \n   I'm most worried about\n   \n    things just being totally crazy\n   \n   around superintelligence, including things like novel WMDs, destructive wars, and unknown unknowns. Moreover, I think the arc of history counsels us to not underrate authoritarianism\u2014and superintelligence might allow authoritarians to dominate for billions of years.\n  \n\n\n   team. There is a very real technical problem: our current alignment techniques (methods to ensure we can reliably control, steer, and trust AI systems) won't scale to superhuman AI systems. What I want to do is explain what I see as the \"default\" plan for how we'll muddle through,\n   \n    84\n   \n   and why I'm optimistic.\n   \n    84\n   \n   As Tyler Cowen says, muddling\n   \n    While not enough people are on the ball\u2014\n   \n   we should have through is underrated! much more ambitious efforts to solve this problem!\u2014overall, we've gotten lucky with how deep learning has shaken out, there's a lot of empirical low-hanging fruit that will get us part of the way, and we'll have the advantage of millions of automated AI researchers to get us the rest of the way.\n  \n\n\n   But I also want to tell you why I'm worried. Most of all, ensuring alignment doesn't go awry will require extreme competence in managing the intelligence explosion. If we do rapidly transition from from AGI to superintelligence, we will face a situation where,\n   \n    in less than a year\n   \n   , we will go from recognizable human-level systems for which descendants of current alignment techniques will mostly work fine, to much more alien, vastly superhuman systems that pose a qualitatively different, fundamentally novel technical alignment problem; at the same time, going from systems where failure is low-stakes to extremely powerful systems where failure could be catastrophic; all while most of the world is probably going kind of crazy. It makes me pretty nervous.\n  \n\n\n   By the time the decade is out, we'll have billions of vastly superhuman AI agents running around. These superhuman AI agents will be capable of extremely complex and creative behavior; we will have no hope of following along. We'll be like first graders trying to supervise with multiple doctorates.\n  \n\n\n   In essence, we face a problem of handing off\n   \n    trust\n   \n   . By the end of the intelligence explosion, we won't have any hope of understanding what our billion superintelligences are doing (except as they might choose to explain to us, like they might to a child). And we don't yet have the technical ability to reliably guarantee even basic side constraints for these systems, like \"don't lie\" or \"follow the law\" or \"don't try to exfiltrate your server\".\n   \n    Reinforcement from human feedback\n   \n   (RLHF) works very well for adding such side constraints for current\n  \n\n\n\n\n\n   systems\u2014but RLHF relies on humans being able to understand and supervise AI behavior, which fundamentally won't scale to superhuman systems.\n  \n\n\n   Simply put, without a very concerted effort, we won't be able to guarantee that superintelligence won't go rogue (and this is acknowledged by many\n   \n    leaders\n   \n\n    in\n   \n\n    the\n   \n\n    field)\n   \n   . Yes, it may all be fine by default. But we simply don't know yet. Especially once future AI systems aren't just trained with imitation learning, but large-scale, long-horizon RL (reinforcement learning), they will acquire unpredictable behaviors of their own, shaped by a trial-and-error process (for example, they may learn to lie or seek power, simply because these are successful strategies in the real world!).\n  \n\n\n   The stakes will be high enough that hoping for the best simply isn't a good enough answer on alignment.\n  \n\n\n\n    The problem\n   \n\n\n\n\n    The superalignment problem\n   \n\n\n\n   We've been able to develop a very successful method for aligning (i.e., steering/controlling)\n   \n    current\n   \n   AI systems (AI systems dumber than us!): Reinforcement Learning from Human Feedback (RLHF). The idea behind RLHF is simple: the AI system tries stuff, humans rate whether its behavior was good or bad, and then reinforce good behaviors and penalize bad behaviors. That way, it learns to follow human preferences.\n  \n\n\n   Indeed, RLHF has been the key behind the success of ChatGPT and others.\n   \n    85\n   \n   Base models had lots of raw smarts but weren't applying these in a useful way by default; they usually just responded with a garbled mess resembling random internet text. Via RLHF, we can steer their behavior, instilling important basics like instruction-following and helpfulness. RLHF also allows us to bake in safety guardrails: for example, if a user asks me for bioweapon instructions, the model should probably refuse.\n   \n    86\n   \n\n\n\n\n    85\n   \n   Ironically, the safety guys made the biggest breakthrough for enabling AI's commercial success by inventing RLHF! Base models had lots of raw smarts but were unsteerable and thus unusable for most applications.\n  \n\n\n\n    86\n   \n   This highlights an important distinction: the\n   \n    technical ability\n   \n   to align (steer/control) a model is separate from a values question of\n   \n    what to align to.\n   \n   There have been many political controversies about the latter question. And while I agree with the opposition to some of the outgrowths here, that shouldn't distract from the basic technical problem. Yes, alignment techniques can be misused\u2014but we will need better alignment techniques to ensure even basic side constraints for future models, like follow instructions or follow the law. See also\n   \n    \"AI alignment is distinct\n   \n\n    from its near-term applications\"\n   \n   .\n  \n\n\n\n    The core technical problem of superalignment is simple: how do we control AI systems (much) smarter than us?\n   \n\n\n\n\n    RLHF will predictably break down as AI systems get smarter\n   \n   , and we will face fundamentally new and qualitatively different technical challenges. Imagine, for example, a superhuman AI system generating a million lines of code in a new programming language it invented. If you asked a human rater in an RLHF procedure, \"does this code contain any security backdoors?\" they simply wouldn't know. They wouldn't be able to rate the output as good or bad, safe or unsafe, and so we wouldn't be able to reinforce good behaviors and penalize bad behaviors with RLHF.\n  \n\n\n\n\n\n\n   scale to superintelligence. Even now, AI labs already\n   \n    need to pay expert software engi\n   \n\n    neers\n   \n   to give RLHF ratings for ChatGPT code\u2014the code current models can generate is already pretty advanced! Human labeler-pay has gone from a few dollars for MTurk labelers to\n  \n\n\n   Figure 33: Aligning AI systems via human supervision (as in RLHF) won't\n  \n\n\n   ~$100/hour for GPQA questions\n   \n    87\n   \n   in the last few years. In the\n   \n    87\n   \n   \"We estimate an average hourly (near) future, even the best human experts spending lots of time won't be good enough. We're starting to hit early versions of the superalignment problem in the real world now, and very soon this will be a major issue even just for practically deploying next-generation systems. It's clear we will need a successor to RLHF that scales to AI capabilities better than human-level, where human supervision breaks down. In some sense, the goal of superalignment research efforts is to repeat the success story of RLHF: make the basic research bets that will be necessary to steer and deploy AI systems a couple years down the line.\n  \n\n\n\n    What failure looks like\n   \n\n\n\n   People too often just picture a \"GPT-6 chatbot,\" informing their intuitions that surely these wouldn't be dangerously misaligned. As discussed previously in this series, the \"unhobbling\" trajectory points to agents, trained with RL, in the near future. I think Roger's graphic gets it right.\n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n   payment of approximately $95 per hour,\" p.3 of the\n   \n    GPQA paper.\n   \n\n\n\n   Figure 34:\n   \n    Roger Grosse\n   \n   on the evolution of the alignment problem as systems become more advanced.\n  \n\n\n   One way to think of what we're trying to accomplish with alignment, from the safety perspective, is add\n   \n    side-constraints.\n   \n   Consider a future powerful \"base model\" that, in a second stage of training, we train with long-horizon RL to run a business and make money\n   \n    88\n   \n   (as a simplified example):\n   \n    88\n   \n   Very simplified, think of an AI system\n  \n\n\n\n\n\n\n     By default, it may well learn to lie, to commit fraud, to deceive, to hack, to seek power, and so on\u2014simply because these can be successful strategies to make money in the real world!\n     \n      89\n     \n\n      89\n     \n     What RL is doing is simply explor-\n    \n\n\n     What we want is to add side-constraints: don't lie, don't break the law, etc.\n    \n\n\n     But here we come back to the fundamental issue of aligning superhuman systems: we won't be able to understand what they are doing, and so we won't be able to notice and penalize bad behavior with RLHF.\n     \n      90\n     \n\n      90\n     \n     (or inference-time monitoring models\n    \n\n\n\n   If we can't add these side-constraints, it's not clear what will happen.\n   \n    Maybe\n   \n   we'll get lucky and things will be benign by default (for example, maybe we can get pretty far without the AI systems having long-horizon goals, or the undesirable behaviors will be minor). But it's also totally plausible they'll learn much more serious undesirable behaviors: they'll learn to lie, they'll learn to seek power, they'll learn to behave nicely when humans are looking and pursue more nefarious strategies when we aren't watching, and so on.\n  \n\n\n   The superalignment problem being unsolved means that we simply won't have the ability to ensure even these basic side constraints for these superintelligence systems, like \"\n   \n    will they reliably follow my instructions?\n   \n   \" or \"\n   \n    will they honestly answer my questions?\"\n   \n   or \"\n   \n    will they not deceive humans?\"\n   \n   . People often associate alignment with some complicated questions about human values, or jump to political controversies, but deciding on what behaviors and values to instill in the model, while important, is a separate problem. The primary problem is that for whatever you want to instill the model (including ensuring very basic things, like \"follow the law\"!) we don't yet know how to do that for the very powerful AI systems we are building very\n  \n\n\n   trying, via trial and error, to maximize money over a period of a year, and the final, trained AI model being the result of a selection process that selects for the AI systems that were most successful at maximizing money.\n  \n\n\n   ing strategies for succeeding at the objective. If a strategy works, it is reinforced in the model. So if lying, fraud, power-seeking, etc. (or patterns of thinking that could lead to these sorts of behaviors in at least some situations) work, these will also be reinforced in the model.\n  \n\n\n   trained with human supervision)\n  \n\n\n   soon.\n  \n\n\n   Again, the consequences of this aren't totally clear. What is clear is that superintelligence will have vast capabilities\u2014and so misbehavior could fairly easily be catastrophic. What's more, I expect that within a small number of years, these AI systems will be integrated in many critical systems, including military systems (failure to do so would mean complete dominance by adversaries). It sounds crazy, but remember when everyone was saying we wouldn't connect AI to the internet? The same will go for things like\n   \n    \"we'll make sure a human is\n   \n\n    always in the loop!\"\n   \n   \u2014as people say today.\n  \n\n\n   Alignment failures then might look like isolated incidents, say, an autonomous agent committing fraud, a model instance self-exfiltrating, an automated researcher falsifying an experimental result, or a drone swarm overstepping rules of engagement. But failures could also be much larger scale or more systematic\u2014in the extreme, failures could look more like a robot rebellion. We'll have summoned a fairly alien intelligence, one\n   \n    much\n   \n   smarter than us, one whose architecture and training process wasn't even designed by us but some supersmart previous generation of AI systems, one where we can't even begin to understand what they're doing, it'll be running our military, and its goals will have been learned by a naturalselection-esque process.\n  \n\n\n   Unless we solve alignment\u2014unless we figure out how to instill those side-constraints\u2014there's no particular reason to expect this small civilization of superintelligences will continue obeying human commands in the long run. It seems totally within the realm of possibilities that at some point they'll simply conspire to cut out the humans, whether suddenly or gradually.\n  \n\n\n\n    The intelligence explosion makes this all incredibly tense\n   \n\n\n\n   I am optimistic that superalignment is a solvable technical problem. Just like we developed RLHF, so we can develop the successor to RLHF for superhuman systems and do the science that gives us high confidence in our methods. If things continue to progress iteratively, if we insist on rigorous safety\n  \n\n\n   testing and so on, it should all be doable (and I'll discuss my current best-guess of how we'll muddle through more in a bit).\n  \n\n\n   What makes this incredibly hair-raising is the possibility of an intelligence explosion: that we might make the transition from roughly human-level systems to\n   \n    vastly\n   \n   superhuman systems extremely rapidly, perhaps in less than a year.\n  \n\n\n\n\n\n\n\n      AGI\n     \n\n      Superintelligence\n     \n\n\n\n\n       Required alignment\n      \n\n      technique\n     \n\n\n       RLHF++\n      \n\n\n      Novel, qualitatively different technical\n      \n      solutions\n     \n\n\n\n\n       Failures\n      \n\n\n      Low-stakes\n     \n\n      Catastrophic\n     \n\n\n\n\n       Architecture and\n      \n\n      algorithms\n     \n\n      Familiar, descendants of current\n      \n      systems, fairly benign safety\n      \n      properties\n     \n\n      Alien. Designed by previous-\n      \n      generation super-smart AI system\n     \n\n\n\n      Backdrop\n     \n\n      World is normal\n     \n\n      World is going crazy, extraordinary\n      \n      pressures\n     \n\n\n\n\n       Epistemic state\n      \n\n\n      We can understand what the systems\n      \n      are doing, how they work, and\n      \n      whether they're aligned.\n     \n\n      We have no ability to understand\n      \n      what's going on, how to tell if systems\n      \n      are still aligned and benign, what the\n      \n      systems are doing, and we are entirely\n      \n      reliant on trusting the AI systems.\n     \n\n\n\n\n\n      Transition in\n      \n       \\langle\n      \n      1 year?\n      \n      with very little time to get decisions right\n     \n\n\n\n\n\n\n\n\n   \u2022 We will extremely rapidly go from systems where RLHF works fine\u2014to systems where it will totally break down. This leaves us extremely little time to iteratively discover and\n  \n\n\n   Figure 35: The intelligence explosion makes superalignment incredibly hair-raising.\n  \n\n\n   address ways in which our current methods will fail.\n  \n\n\n\n\n\n\n     At the same time, we will extremely rapidly go from systems where failures are fairly low-stakes (ChatGPT said a bad word, so what)\u2014to extremely high-stakes (oops, the superintelligence self-exfiltrated from our cluster, now it's hacking the military). Rather than iteratively encountering increasingly more dangerous safety failures in the wild, the first notable safety failures we encounter might already be catastrophic.\n    \n\n\n     The superintelligence we get by the end of it will be\n     \n      vastly\n     \n     superhuman. We'll be entirely reliant on trusting these systems, and trusting what they're telling us is going on\u2014since we'll have no ability of our own to pierce through what exactly they're doing anymore.\n    \n\n\n     The superintelligence we get by the end of it could be quite\n     \n      alien\n     \n     . We'll have gone through a decade or more of ML advances during the intelligence explosion, meaning the architectures and training algorithms will be totally different (with potentially much riskier safety properties).\n     \n\n\n\n\n        \u2013\n       \n       One example that's very salient to me: we may well bootstrap our way to human-level or somewhat-superhuman AGI with systems that reason via chains of thoughts, i.e. via English tokens. This is\n       \n        extraordinarily\n       \n       helpful, because it means the models \"think out loud\" letting us catch malign behavior (e.g., if it's scheming against us). But\n       \n        surely\n       \n       having AI systems think in tokens is not the most efficient means to do it,\n       \n        surely\n       \n       there's something much better that does all of this thinking via internal states\u2014and so the model by the end of the intelligence explosion will almost certainly\n       \n        not\n       \n       think out loud, i.e. will have completely uninterpretable reasoning.\n      \n\n\n\n\n     This will be an incredibly volatile period, potentially with the backdrop of an international arms race, tons of pressure to go faster, wild new capabilities advances every week with basically no human-time to make good decisions, and so on. We'll face tons of ambiguous data and high-stakes decisions.\n    \n\n\n\n\n    \u2013\n   \n   Think: \"We caught the AI system doing some naughty things in a test, but we adjusted our procedure a little bit to hammer that out. Our automated AI researchers tell us the alignment metrics look good, but we don't really understand what's going on and don't fully trust them, and we don't have any strong scientific understanding that makes us confident this will continue to hold for another couple OOMs. So, we'll\n   \n    probably\n   \n   be fine? Also China just stole our weights and they're launching their own intelligence explosion, they're right on our heels.\"\n  \n\n\n\n    It just really seems like this could go off the rails.\n   \n   To be honest, it sounds terrifying.\n  \n\n\n   Yes, we will have AI systems to help us. Just like they'll automate capabilities research, we can use them to automate alignment research. That will be key, as I discuss below. But\u2014can you trust the AI systems? You weren't sure whether they were aligned in the first place\u2014are they actually being honest with you about their claims about alignment science? Will automated alignment research be able to keep up with automated capabilities research (for example, because automating alignment is harder, e.g. because there are less clear metrics we can trust compared to improving model capabilities, or there's a lot of pressure to go full-speed on capabilities progress because of the international race)? And AI won't be able to fully substitute for the still-human decision makers making good calls in this incredibly high-stakes situation.\n  \n\n\n\n    The default plan: how we can muddle through\n   \n\n\n\n   I think we can harvest wins across a number of empirical bets, which I'll describe below, to align somewhat-superhuman systems. Then, if we're confident we can trust these systems, we'll need to use these somewhat-superhuman systems to automate alignment research\u2014alongside the automation of AI research in general, during the intelligence explosion\u2014to figure out how to solve alignment to go the rest of the way.\n  \n\n\n\n    Aligning somewhat-superhuman models\n   \n\n\n\n   Aligning human-level systems won't be enough. Even the first systems that can do automated AI research, i.e. start the intelligence explosion, will likely already be substantially superhuman in many domains. This is because AI capabilities are likely to be somewhat spikey\u2014by the time AGI is human-level at whatever a human AI researcher/engineer is worst at, it'll be superhuman at many other things. For example, perhaps the ability for AI systems to effectively coordinate and plan lags behind, meaning that by the time the intelligence explosion is in full force they'll probably already be superhuman coders, submitting million-line pull requests in new programming languages they devised, and they'll be superhuman at math and ML.\n  \n\n\n   These early-intelligence-explosion-systems will start being quantitatively and qualitatively superhuman, at least in many domains. But they'll look much closer to the systems we have today in terms of architecture, and the intelligence gap we need to cover is much more manageable. (Perhaps if humans trying to align true superintelligence is like a first grader trying to supervise a PhD graduate, this is more like a smart high schooler trying to supervise a PhD graduate.)\n  \n\n\n   More generally, the more we can develop good science now, the more we'll be in a position to verify that things aren't going off the rails during the intelligence explosion. Even having good metrics we can trust for superalignment is surprisingly difficult\u2014but without reliable metrics during the intelligence explosion, we won't know whether pressing on is safe or not.\n  \n\n\n   Here are some of the main research bets I see for crossing the gap between human-level and somewhat-superhuman systems.\n  \n\n\n   evaluation is easier than generation. We get some of the way \"for free,\" because it's easier for us to evaluate outputs (especially for egregious misbehaviors) than it is to generate them ourselves. For example, it takes me months or years of hard work to write a paper, but only a couple hours to tell if a paper someone has written is any good (though perhaps longer\n  \n\n\n   to catch fraud). We'll have teams of expert humans spend a lot of time evaluating every RLHF example, and they'll be able to \"thumbs down\" a lot of misbehavior even if the AI system is somewhat smarter than them. That said, this will only take us so far (GPT-2 or even GPT-3 couldn't detect nefarious GPT-4 reliably, even though evaluation is easier than generation!)\n  \n\n\n   scalable oversight. We can use AI assistants to help humans supervise other AI systems\u2014the human-AI team being able to extend supervision farther than the human could alone. For example, imagine an AI system generates 1M lines of complex code. It's easier for a human to double-check that a given line of code has a bug if an AI assistant has pointed out that (say) line 394,894 looks fishy, than it is for a human to find that same bug from scratch. A model trained to critique the code written by another model could thus help humans supervise a system with narrowly superhuman coding abilities.\n  \n\n\n   Several scalable oversight strategies have been proposed, including\n   \n    debate,\n   \n\n    market-making,\n   \n\n    recursive reward modeling,\n   \n   and\n   \n    prover-verifier games,\n   \n   as well as simplified versions of those ideas lik\n   \n    ecritiques.\n   \n   Models are now strong enough that it's possible to\n   \n    empirically\n   \n\n    test\n   \n   these ideas, making direct progress on scalable oversight.\n  \n\n\n   I expect this to help a lot for the \"quantitatively\" superhuman part of the problem, such as the aforementioned million-lines of code example. But I am less optimistic that scalable oversight techniques can really help for the \"qualitatively\" superhuman part of the problem\u2014imagine the model invents quantum physics when you only understand Newtonian physics.\n  \n\n\n   generalization. Even with scalable oversight, we won't be able to supervise AI systems on really hard problems, problems beyond human comprehension. However, we can study: how will the AI systems\n   \n    generalize\n   \n   from human supervision on easy problems (that we do understand and can supervise) to behave on the hard problems (that we can't understand and can no longer supervise)? For example, perhaps supervising a model to be honest in simple cases generalizes benignly to\n  \n\n\n   the model just being honest in general, even in cases where it's doing extremely complicated things we don't understand.\n  \n\n\n   There's a lot of reasons to be optimistic here: part of the magic of deep learning is that it often generalizes in benign ways (for example, RLHF'ing with only labels on English examples also tends to produce good behavior when it's speaking French or Spanish, even if that wasn't part of the training). I'm fairly optimistic that there will both be pretty simple methods that help nudge the models' generalization in our favor, and that we can develop a strong scientific understanding that helps us predict when generalization will work and when it will fail. To a greater extent that for scalable oversight, the hope is that this will help with alignment even in the \"qualitatively\" superhuman case.\n  \n\n\n   Here's another way of thinking about this: if a superhuman model is misbehaving, say breaking the law, intuitively\n   \n    the model should already know\n   \n   that it's breaking the law. Moreover, \"is this breaking the law\" is probably a pretty natural concept to the model\u2014and it will be salient in the model's representation space. The question then is: can we \"summon\" this concept from the model with only weak supervision?\n  \n\n\n   I'm particularly partial to this direction (and perhaps biased), because I helped introduce this with some recent work with some colleagues at OpenAI. In particular, we studied an analogy to the problem of humans supervising superhuman systems can a\n   \n    small model\n   \n   align a\n   \n    larger (smarter) model\n   \n   ? We found that generalization does actually get you cross some (but certainly not all) of the intelligence gap between supervisor and supervisee, and that in simple settings there's a lot you can do to improve it.\n  \n\n\n   interpretability. One intuitively-attractive way we'd hope to verify and trust that our AI systems are aligned is if we could understand what they're thinking! For example, if we're worried that AI systems are deceiving us or conspiring against us, access to their internal reasoning should help us detect that.\n  \n\n\n   By default, modern AI systems are inscrutable black boxes.\n  \n\n\n\n\n\n\n   Yet it seems like we should be able to do amazing \"digital neuroscience\"\u2014after all, we have perfect access to model internals.\n  \n\n\n   There's a few different approaches here, going from \"most ambitious and 'cool' but will be very hard\" to \"hackier things that are easier and might just work\".\n  \n\n\n\n    Mechanistic interpretability.\n   \n   Try to fully reverse-engineer large neural networks from the ground up\u2014fully disentangle the inscrutable matrices, so to speak.\n  \n\n\n   Chris Olah's team at Anthropic has done\n   \n    much of the pio\n   \n\n    neering work\n   \n   on this, starting by understanding simple mechanisms in very small models. There's\n   \n    incredibly exciting progress\n   \n   happening recently, and I'm thrilled about the overall level of activity in this space.\n  \n\n\n   That said, I'm worried fully reverse-engineering superhuman AI systems will just be an intractable problem\u2014similar, to, say \"fully reverse engineering the human brain\"\u2014and I'd put this work mostly in the \"ambitious moonshot for AI safety\" rather than \"default plan for muddling through\" bucket.\n   \n    91\n   \n\n\n\n   (Neel Nanda's 200\n   \n    open problems in mechanistic interpretabil\n   \n\n    ity\n   \n   also gives a flavor of this kind of research.)\n  \n\n\n   Figure 36: A simple analogy for studying superalignment: instead of a human supervising a superhuman model, we can study a small model supervising a large model. For example, can we align GPT-4 with only GPT-2 supervision? Will that result in GPT-4 appropriately generalizing \"what GPT-2 meant\"? From\n   \n    Weak-to-strong generalization.\n   \n\n\n\n\n    91\n   \n   Moreover, even recent progress in mechanistic interpretability to \"disentangle the features\" of models with sparse autoencoders doesn't on its own solve the problem of how to deal with superhuman models. For one, the model might simply \"think\" in superhuman concepts you don't understand. Moreover, how do you know which feature is the one you want? You still don't have ground truth labels. For example, there might be tons of different features that look like the \"truth feature\" to you, one of which is \"what the model actually knows\" and the others being \"what would xyz human think\" or \"what do the human raters want me to think\" etc.\n  \n\n\n   Sparse autoencoders won't be enough on their own, but they will be a tool an incredibly helpful tool!\u2014that ultimately has to cash out in helping with things like the science of generalization.\n  \n\n\n\n    \"Top-down\" interpretability.\n   \n   If mechanistic interpretability tries to reverse engineer neural networks \"from the bottom up,\" other work takes a more targeted, \"top-down\" approach, trying to locate information in a model without full understanding of how it is processed.\n  \n\n\n   For example, we might try to build an \"AI lie detector\" by identifying the parts of the neural net that \"light up\" when an AI system is lying. This can be a lot more tractable (even if it gives less strong guarantees).\n  \n\n\n   Over the past couple of years, there's been a flurry of exciting work in this area.\n   \n    CCS\n   \n   is able to identify a \"truth direction\" in models with only unsupervised data.\n   \n    92\n   \n\n    ROME\n   \n   is able to\n   \n    92\n   \n   Essentially, needing only the conidentify the part of the model that knows the Eiffel Tower is in Paris\u2014and then directly edit the model's knowledge to place the Eiffel Tower in Rome.\n   \n    Representation Engineering\n   \n   and\n   \n    Inference-time Interventions\n   \n   demonstrate using top-down techniques to detect lying and hallucinations and surgically control model behavior on jailbreaking, power-seeking, fairness, truthfulness, and more. There's\n   \n    other creative work\n   \n   on lie detection that doesn't even require model internals.\n  \n\n\n   I'm increasingly bullish that top-down interpretability techniques will be a powerful tool\u2014i.e., we'll be able to build something like an \"AI lie detector\"93\u2014and without requiring funda-\n   \n    93\n   \n   I'm still worried about the scalability mental breakthroughs in understanding neural nets.\n  \n\n\n\n    Chain-of-thought interpretability.\n   \n   As mentioned earlier, I think it's quite plausible that we'll bootstrap our way to AGI with systems that \"think out loud\" via chains of thought. Even if it's not the most efficient algorithm in the limit (I'd be very surprised if superintelligence still used English-chain-of-thought, rather than thinking via some sort of recurrent internal states), we may well still benefit from this property for the first AGIs. This would be an incredible boon for interpretability: we'd have access to the AGI's \"internal monologue\"! That would make it relatively easy to detect egregious alignment failures.\n  \n\n\n   There's a ton of work to do here, however, if we wanted to rely on this. How do we ensure that the CoT remains\n   \n    legible\n   \n   ? (It\n  \n\n\n   sistency properties of truth, rather than strong/ground truth labels of true/false, which we won't have for superhuman systems.\n  \n\n\n   of a lot of these techniques to very superhuman models\u2014I think explicitly or implicitly they mostly rely on groundtruth labels, i.e. a supervisor smarter than the model, and/or favorable generalization.\n  \n\n\n   may simply drift from understandable English to unintelligible\n   \n    model-speak,\n   \n   depending on how we e.g. use RL to train models\u2014can we add some simple constraints to ensure it remains legible?) How do we ensure the CoT is\n   \n\n     faithful\n    \n\n   , i.e. actually reflects what models are thinking? (E.g, there's\n   \n    some\n   \n\n    work\n   \n   that shows in certain situations, models will just make up posthoc reasoning in their CoT that don't actually reflect their actual internal reasoning for an answer.)\n  \n\n\n   My best guess is that some simple measurement of legibility and faithfulness, and some simple hacks to preserve legibility and faithfulness longer, could go quite far. Yes, this won't work in some worlds, and it's a bit of a simple hack, but it's such low-hanging fruit; this direction is criminally underrated in my view.\n  \n\n\n   adversarial testing and measurements. Along the way, it's going to be critical to stress test the alignment of our systems at every step\u2014our goal should be to encounter every failure mode in the lab before we encounter it in the wild. This will require substantially advancing techniques for\n   \n    automated\n   \n\n    red-teaming.\n   \n   For example, if we deliberately plant backdoors or misalignments into models, would our safety training would have caught and gotten rid of them? (Early work suggests that\n   \n    \"sleeper agents\"\n   \n   can survive through safety training, for example.)\n  \n\n\n   More generally, it'll be critical to have good measurements of alignment. Does the model have the power to be misaligned? For example, does it have long-horizon goals, and what sorts of drives it is learning? And what are clear \"red lines\"? For example, a very intuitive bound might be \"model reasoning (chain of thoughts) always has to remain legible and faithful.\" (As Eric Schmidt\n   \n    says,\n   \n   the point at which AI agents can talk to each other in a language we can't understand, we should unplug the computers.) Another might be developing better measurements for whether models are being fully honest.\n  \n\n\n   The science of measuring alignment is still in its infancy; improving this will be critical for helping us make the right tradeoffs on risk during the intelligence explosion. Doing the science\n  \n\n\n   that lets us measure alignment and gives us an understanding of \"what evidence would be sufficient to assure us that the next OOM into superhuman territory is safe?\" is among the veryhighest priority work for alignment research today (beyond just work that tries to extend RLHF further to \"somewhatsuperhuman\" systems). See also\n   \n    this writeup of superalignment\n   \n\n\n\n\n    research directions\n   \n   for the Superalignment Fast Grants call-for-proposals.\n  \n\n\n\n    Automating alignment research\n   \n\n\n\n   Ultimately, we're going to need to automate alignment research. There's no way we'll manage to solve alignment for true superintelligence directly; covering that vast of an intelligence gap seems extremely challenging. Moreover, by the end of the intelligence explosion\u2014after 100 million automated AI researchers have furiously powered through a decade of ML progress\u2014I expect much more alien systems in terms of architecture and algorithms compared to current system (with potentially less benign properties, e.g. on legibility of CoT, generalization properties, or the severity of misalignment induced by training).\n  \n\n\n   But we also don't have to solve this problem just on our own. If we manage to align somewhat-superhuman systems enough to trust them, we'll be in an incredible position: we'll have millions of automated AI researchers, smarter than the best AI researchers, at our disposal. Leveraging these army of automated researchers properly to solve alignment for even-more superhuman systems will be decisive.\n  \n\n\n   (This applies more generally, by the way, for the full spectrum of AI risks, including misuse and so on. The best route perhaps the only route\u2014to AI safety in all of these cases, will involve properly leveraging early AGIs for safety; for example, we should put a bunch of them to work on automated research to improve security against foreign actors exfiltrating weights, others on shoring up defenses against worst-case bioattacks, and so on.)\n  \n\n\n   Getting automated alignment right during the intelligence explosion will be extraordinarily high-stakes: we'll be going through many years of AI advances in mere months, with little\n  \n\n\n   human-time to make the right decisions, and we'll start entering territory where alignment failures could be catastrophic. Labs should be willing to commit a large fraction of their compute to automated alignment research (vs. automated capabilities research) during the intelligence explosion, if necessary. We'll need strong guarantees that let us trust the automated alignment research being produced and much better measurements for misalignment than we have today to know whether we're still in the clear. For every OOM we want to ascend, we will need to have extremely high confidence in our alignment approaches for that next OOM.\n  \n\n\n   Most of all, getting this right will require an extreme degree of competence, seriousness, and willingness to make hard tradeoffs. Once we're approaching true superintelligence, the stakes get very real, and failure\u2014rogue AI\u2014could be catastrophic. There will be moments with ambiguous evidence, when metrics will superficially look ok, but there are some warning signs that hint at looming danger, and we mostly don't have a clue what's going on anymore. Navigating this situation responsibly will require making very costly tradeoffs. Eventually, the decision to greenlight the next generation of superintelligence will need to be taken as seriously as the decision to launch a military operation.\n  \n\n\n\n    Superdefense\n   \n\n\n\n   \"Getting alignment right\" should only be the first of many layers of defense during the intelligence explosion. Alignment will be hard; there\n   \n    will\n   \n   be failures along the way. If at all possible, we need to be in a position where alignment can fail\u2014but failure wouldn't be catastrophic. This could mean:\n  \n\n\n   \u2022\n   \n    Security.\n   \n   An airgapped cluster is the first layer of defense against superintelligence attempting to self-exfiltrate and doing damage in the real world. And that's only the beginning; we'll need much more extreme security against model selfexfiltration\n   \n    94\n   \n   across the board, from hardware encryption to\n   \n    94\n   \n   A model stealing its own weights, original datacenter. many-key signoff.\n   \n    95\n   \n   And once our AGIs can do automated\n  \n\n\n   to make copies of itself outside of the\n  \n\n\n\n    95\n   \n   protecting against humans fooled or persuaded by the AI to help it exfiltrate\n  \n\n\n   R&D, we should put them to work on further hardening security as well.\n  \n\n\n\n\n\n\n\n      Monitoring.\n     \n     If our AI systems are up to something fishy or malevolent\u2014or a rogue employee tries to use them for unauthorized activities\u2014we need to be able to catch it. However, this is not a trivial task: we will have millions of AGI instances running our cluster, executing complex code and so on. We will need advanced monitoring systems that leverage the models themselves, including monitoring model outputs, chains of thought, model-written code, server/network activity, and interactions with researchers/other humans; essentially, leveraging some AI systems to nark on other AI systems. Moreover, we'll want to develop and employ sophisticated\n     \n      \"control\" protocols,\n     \n     using less powerful but trusted models to protect against subversion from more powerful but less trusted models. This may require, for example, dedicating the same amount of compute to monitoring model instances as to compute for active model instances.\n    \n\n\n\n      Targeted capability limitations.\n     \n     As much as possible, we should try to limit the model's capabilities in targeted ways that reduce fallout from failure. A central example of this might be scrubbing everything related to biology and chemistry from model training (or using\n     \n      \"unlearning\"\n     \n     techniques); this helps cut off paths to catastrophic real world damage that occur via biological and chemical weapons\n    \n\n\n\n      Targeted training method restrictions.\n     \n     There are likely some ways of training models that are inherently riskier\u2014more likely to produce severe misalignments\u2014than others. For example, imitation learning seems relatively safe (hard to see how that would lead to models that have dangerous longterm internal goals), while we should avoid long-horizon outcome-based RL (which seems much more likely to lead to the model learning undesirable long-term goals) as long as possible. We should also avoid training against our interpretability methods and our monitoring setup (such that our models aren't simply trained to work around these). There might be additional desirable limitations, for example, maintaining legible and faithful chains of thought as long as\n    \n\n\n\n   possible. We should define these constraints ahead of time, maintain them as long as we can throughout the intelligence explosion, and only drop them if absolutely necessary.\n  \n\n\n   \u2022 And there's likely a lot more possible here.\n  \n\n\n   Will these be foolproof? Not at all. True superintelligence is likely able to get around most-any security scheme for example. Still, they buy us a lot more margin for error\u2014and we're going to need any margin we can get. We'll want to use that margin to get in a position where we have very high confidence in our alignment techniques, only relaxing \"superdefense\" measures (for example, deploying the superintelligence in nonairgapped environments) concomitant with our confidence.\n  \n\n\n   Things will get dicey again once we move to deploying these AI systems in less-controlled settings, for example in military applications. It's likely circumstances will force us to do this fairly quickly, but we should always try to buy as much margin for error as much as possible\u2014for example, rather than just directly deploying the superintelligences \"in the field\" for military purposes, using them to do R&D in a more isolated environment, and only deploying the specific technologies they invent (e.g., more limited autonomous weapons systems that we're more confident we can trust).\n  \n\n\n\n    Why I'm optimistic, and why I'm scared\n   \n\n\n\n   I'm incredibly bullish on the technical tractability of the superalignment problem. It feels like there's tons of low-hanging fruit everywhere in the field. More broadly, the empirical realities of deep learning have shaken out more in our favor compared to what some speculated 10 years ago. For example, deep learning\n   \n    generalizes\n   \n   surprisingly benignly in many situations: it often just \"does the thing we meant\" rather than picking up some abstruse malign behavior.\n   \n    96\n   \n   Moreover, while\n   \n    96\n   \n   Though, of course, while that may fully understanding model internals will be hard, at least for the initial AGIs we have a decent shot of interpretability\u2014we can get them to reason transparently via chains of thought, and\n  \n\n\n   apply to current models and perhaps human-level systems, we have to be careful about attempting to extrapolate evidence from current models to future vastly superhuman models.\n  \n\n\n   hacky techniques like representation engineering work surprisingly well as \"lie detectors\" or similar.\n  \n\n\n   I think there's a pretty reasonable shot that \"the default plan\" to align \"somewhat-superhuman\" systems will mostly work.\n   \n    97\n   \n\n    97\n   \n   To be clear, given the stakes, I think Of course, it's one thing to speak about a \"default plan\" in the abstract\u2014it's another if the team responsible for executing that plan is you and your 20 colleagues (much more stressful!).\n   \n    98\n   \n\n    98\n   \n   I'm reminded of Scott Aaronson's There's still an incredibly tiny number of people seriously working on solving this problem, maybe a few dozen serious researchers.\n   \n    Nobody's on the ball!\n   \n   There's so much interesting and productive ML research to do on this, and the gravity of the challenge demands a much more concerted effort than what we're currently putting forth.\n  \n\n\n   But that's just the first part of the plan\u2014what really keeps me up at night is the intelligence explosion. Aligning the first AGIs, the first somewhat-superhuman systems, is one thing. Vastly superhuman, alien superintelligence is a new ballgame, and it is a\n   \n    scary\n   \n   ballgame.\n  \n\n\n   The intelligence explosion will be more like running a war than launching a product. We're not on track for superdefense, for an airgapped cluster or any of that; I'm not sure we would even realize if a model self-exfiltrated. We're not on track for a sane chain of command to make any of these insanely high-stakes decisions, to insist on the very-high-confidence appropriate for superintelligence, to make the hard decisions to take extra time before launching the next training run to get safety right or dedicate a large majority of compute to alignment research, to recognize danger ahead and avert it rather than crashing right into it. Right now, no lab has demonstrated much of a willingness to make any costly tradeoffs to get safety right (we get lots of safety committees, yes, but those are pretty meaningless). By default, we'll probably stumble into the intelligence explosion and have gone through a few OOMs before people even realize what we've gotten into.\n  \n\n\n   We're counting way too much on luck here.\n  \n\n\n   \"muddling through\" is in some sense a terrible plan. But it might be all we've got.\n  \n\n\n\n    letter to his younger self:\n   \n\n\n\n   \"There's a company building an AI that fills giant rooms, eats a town's worth of electricity, and has recently gained an astounding ability to converse like people. It can write essays or poetry on any topic. It can ace collegelevel exams. It's daily gaining new capabilities that the engineers who tend to the AI can't even talk about in public yet. Those engineers do, however, sit in the company cafeteria and debate the meaning of what they're creating. What will it learn to do next week? Which jobs might it render obsolete? Should they slow down or stop, so as not to tickle the tail of the dragon? But wouldn't that mean someone else, probably someone with less scruples, would wake the dragon first? Is there an ethical obligation to tell the world more about this? Is there an obligation to tell it less?\n  \n\n\n   I am\u2014you are\u2014spending a year working at that company. My job your job\u2014is to develop a mathematical theory of how to prevent the AI and its successors from wreaking havoc. Where \"wreaking havoc\" could mean anything from turbocharging propaganda and academic cheating, to dispensing bioterrorism advice, to, yes, destroying the world.\"\n  \n\n\n\n    IIId. The Free World Must Prevail\n   \n\n\n\n\n    Superintelligence will give a decisive economic and military advantage. China isn't at all out of the game yet. In the race to AGI, the free world's very survival will be at stake. Can we maintain our preeminence over the authoritarian powers? And will we manage to avoid self-destruction along the way?\n   \n\n\n\n\n\n    The story of the human race is War. Except for brief and precarious interludes, there has never been peace in the world; and before history began, murderous strife was universal and unending.\n   \n\n\n\n   . . .\n  \n\n\n   Might not a bomb no bigger than an orange be found to possess a secret power to destroy a whole block of buildings \u2014 nay, to concentrate the force of a thousand tons of cordite and blast a township at a stroke?\n  \n\n\n\n\n    winston churchill \"Shall We All Commit Suicide?\" (1924)\n   \n\n\n\n   Superintelligence will be the most powerful technology and most powerful weapon\u2014-mankind has ever developed. It will give a decisive military advantage, perhaps comparable only with nuclear weapons. Authoritarians could use superintelligence for world conquest, and to enforce total control internally. Rogue states could use it to threaten annihilation. And though many count them out, once the CCP wakes up to AGI it has a clear path to being competitive (at least until and unless we drastically improve US AI lab security).\n  \n\n\n   Every month of lead will matter for safety too. We face the\n  \n\n\n   greatest risks if we are locked in a tight race, democratic allies and authoritarian competitors each racing through the alreadyprecarious intelligence explosion at breakneck pace\u2014forced to throw any caution by the wayside, fearing the other getting superintelligence first. Only if we preserve a healthy lead of democratic allies will we have the margin of error for navigating the extraordinarily volatile and dangerous period around the emergence of superintelligence. And only American leadership is a realistic path to developing a nonproliferation regime to avert the risks of self-destruction superintelligence will unfold.\n  \n\n\n   Our generation too easily takes for granted that we live in peace and freedom. And those who herald the age of AGI in SF too often ignore the elephant in the room: superintelligence is a matter of national security, and the United States must win.\n  \n\n\n\n    Whoever leads on superintelligence will have a decisive military advantage\n   \n\n\n\n   Superintelligence is not just any other technology\u2014hypersonic missiles, stealth, and so on\u2014where US and liberal democracies' leadership is highly desirable, but not strictly necessary. The military balance of power can be kept if the US falls behind on one or a couple such technologies; these technologies matter a great deal, but can be outweighed by advantages in other areas.\n  \n\n\n   The advent of superintelligence will put us in a situation unseen since the advent of the atomic era: those who have it will wield complete dominance over those who don't.\n  \n\n\n   I've previously discussed the vast power of superintelligence. It'll mean having billions of automated scientists and engineers and technicians, each much smarter than the smartest human scientists, furiously inventing new technologies, day and night. The acceleration in scientific and technological development will be extraordinary. As superintelligence is applied to R&D in military technology, we could quickly go through decades of military technological progress.\n  \n\n\n\n    The Gulf War, or: What a few-decades-worth of technological lead implies for military power\n   \n\n\n\n   The Gulf War provides a helpful illustration of how a 20- 30 year lead in military technology can be decisive. At the time, Iraq commanded the fourth-largest army in the world. In terms of\n   \n    numbers\n   \n   (troops, tanks, artillery), the US-led coalition barely matched (or was outmatched) by the Iraqis, all while the Iraqis had had ample time to entrench their defenses (a situation that would normally require a 3:1, or 5:1, advantage in military manpower to dislocate).\n  \n\n\n   But the US-led coalition\n   \n    obliterated\n   \n   the Iraqi army in a merely 100-hour ground war. Coalition dead\n   \n    numbered\n   \n   a mere 292, compared to 20k-50k Iraqi dead and hundreds of thousands of others wounded or captured. The Coalition lost a mere 31 tanks, compared to the destruction of over 3,000 Iraqi tanks.\n  \n\n\n   The difference in technology wasn't godlike or unfathomable, but it was utterly and completely decisive: guided and smart munitions, early versions of stealth, better sensors, better tank scopes (to see farther in the night and in dust storms), better fighter jets, an advantage in reconnaissance, and so on.\n  \n\n\n   (For a more recent example, recall Iran launching a massive attack of 300 missiles at Israel, \"99\n   \n    %\"\n   \n   of which were intercepted by superior Israel, US, and allied missile defense.)\n  \n\n\n   A lead of a year or two or three on superintelligence could mean as\n   \n    utterly decisive\n   \n   a military advantage as the US coalition had against Iraq in the Gulf War. A complete reshaping of the military balance of power will be on the line.\n  \n\n\n   Imagine if we had gone through the military technological developments of the 20th century in less than a decade. We'd have gone from horses and rifles and trenches, to modern tank armies, in a couple years; to armadas of supersonic fighter planes and nuclear weapons and ICBMs a couple years after\n  \n\n\n   that; to stealth and precision that can knock out an enemy before they even know you're there another couple years after that.\n  \n\n\n   That is the situation we will face with the advent of superintelligence: the military technological advances of a century compressed to less than a decade. We'll see superhuman hacking that can cripple much of an adversary's military force, roboarmies and autonomous drone swarms, but more importantly completely new paradigms we can't yet begin to imagine, and the inventions of new WMDs with thousandfold increases in destructive power (and new WMD defenses too, like impenetrable missile defense, that rapidly and repeatedly upend deterrence equilibria).\n  \n\n\n   And it wouldn't just be technological progress. As we solve robotics, labor will become fully automated, enabling a broader industrial and\n   \n    economic explosion,\n   \n   too. It is plausible growth rates could go into the 10s of percent a year; within at most a decade, the GDP of those with the lead would trounce those behind. Rapidly multiplying robot factories would mean not only a drastic technological edge, but also production capacity to dominate in pure materiel. Think millions of missile interceptors; billions of drones; and so on.\n  \n\n\n   Of course, we don't know the limits of science and the many frictions that could slow things down. But no godlike advances are necessary for a decisive military advantage. And a billion superintelligent scientists will be able to do\n   \n    a lot. It seems clear that within a matter of years, pre-superintelligence militaries would become hopelessly outclassed\n   \n   .\n  \n\n\n\n    The military advantage would be decisive even against nuclear deterrents\n   \n\n\n\n   To be even clearer: it seems likely the advantage conferred by superintelligence would be decisive enough even to preemptively take out an adversary's nuclear deterrent. Improved sensor networks and analysis could locate even the quietest current nuclear submarines (similarly for mobile missile launchers). Millions or billions of mouse-sized\n  \n\n\n   autonomous drones, with advances in stealth, could infiltrate behind enemy lines and then surreptitiously locate, sabotage, and decapitate the adversary's nuclear forces. Improved sensors, targeting, and so on could dramatically improve missile defense (similar to, say, the Iran vs. Israel example above); moreover, if there is an industrial explosion, robot factories could churn out thousands of interceptors for each opposing missile. And all of this is without even considering completely new scientific and technological paradigms (e.g.,\n   \n    remotely deactivating\n   \n   all the nukes).\n  \n\n\n   It would simply be no contest. And not just no contest in the nuclear sense of \"we could mutually destroy each other,\" but no contest in terms of being able to obliterate the military power of a rival without taking significant casualties. A couple years of lead on superintelligence would mean complete dominance.\n  \n\n\n   If there is a rapid intelligence explosion, it's plausible a lead of mere\n   \n    months\n   \n   could be decisive: months could mean the difference between roughly human-level AI systems and substantially superhuman AI systems. Perhaps possessing those initial superintelligences alone, even before being broadly deployed, would be enough for a decisive advantage, e.g. via superhuman hacking abilities that could shut down presuperintelligence militaries, more limited drone swarms that threaten instant death for every opposing leader, official, and their families, and advanced bioweapons developed with AlphaFold-style simulation that could target specific ethnic groups, e.g. anybody but Han Chinese (or simply withhold the cure from the adversary).\n  \n\n\n\n    China can be competitive\n   \n\n\n\n   Many seem complacent about China and AGI. The chip export controls have neutered them, and the leading AI labs are in the US and the UK\u2014so we don't have much to worry about, right? Chinese LLMs are\n   \n    fine\n   \n   \u2014they are definitely capable of training large models!\u2014but they are at best comparable to the\n  \n\n\n   second tier of US labs.\n   \n    99\n   \n   And even Chinese models are often\n   \n    99\n   \n   For example, Yi-Large\n   \n    seems to be\n   \n   mere ripoffs of American open source releases (for example, the Yi-34B architecture\n   \n    seems to have\n   \n   essentially the Llama2 architecture, with merely a\n   \n    few lines of code changed\n   \n   100). Chi-\n   \n    100\n   \n   Similarly, Qwen hugging face code nese deep learning\n   \n    used to be\n   \n   more important than it is today (for example\n   \n    Baidu published\n   \n   one of the first modern scaling law papers), and while China\n   \n    publishes more papers\n   \n   in AI than the US, they don't seem to have driven any of the key breakthroughs in recent years.\n  \n\n\n   That's all merely a prelude, however. If and when the CCP wakes up to AGI, we should expect extraordinary efforts on the part of the CCP to compete. And I think there's a pretty clear path for China to be in the game: outbuild the US and steal the algorithms.\n  \n\n\n   1. compute\n  \n\n\n\n    1a. Chips:\n   \n   China now seems to have demonstrated the ability to\n   \n    manufacture\n   \n   7nm chips. While going beyond 7nm will be difficult (requiring EUV), 7nm is enough! For reference, 7nm is what Nvidia A100s used. The indigenous Huawei Ascend 910B, based on the SMIC 7nm platform, seems to only be ~2-3x worse on performance/$ than an equivalent Nvidia chip would be.\n   \n    101\n   \n\n    101\n   \n   The Huawei Ascend\n   \n    910\n   \n   B seems to\n  \n\n\n   The\n   \n    yield\n   \n   of SMIC's 7nm production and the general maturity of Chinese abilities here is debated,\n   \n    102\n   \n   and a critical open question is in what quantities they could produce these 7nm chips.\n   \n    103\n   \n   Still, it seems like there's at least a very reasonable chance they'll be able to do this at large scale in a few years.\n  \n\n\n   Most of the gains in AI chips have come from improved chip design adapting them for AI use cases (and China likely already steals Nvidia chip designs from the Taiwan supply chain104). 7nm vs. 3nm or 2nm, and their general fab immaturity, probably makes things more expensive for China.\n   \n    105\n   \n   But that seems by no means fatal; you can make very good AI chips on top of a 7nm process. I wouldn't have high confidence at this point, for example, that they couldn't just spend a bit more and get ample compute for the $100B+ and trillion-dollar\n  \n\n\n   a GPT-4-class model on LMSys, but that's over a year after OpenAI released GPT-4.\n  \n\n\n   cites Mistral a lot, and it seems that Chinese LLM dependence on American open-source is an\n   \n    explicit worry\n   \n   that has made its way to the Chinese Premier.\n  \n\n\n\n    cost around\n   \n   120,000 yuan per card, or about $17k. This is\n   \n    produced on the\n   \n\n    SMIC\n   \n   7nm node, while performing similarly to an A100. H100s are maybe ~3x better than A100s, while costing somewhat more ($20-25k ASP), suggesting only a ~2-3x cost increase for equivalent AI GPU performance for China right now.\n  \n\n\n\n    102\n   \n   For example, they're still using Western HBM memory (which for some reason is not export controlled?), though\n   \n    CXMT is said to be sampling\n   \n\n    HBM\n   \n   next year.\n  \n\n\n\n    103\n   \n   Though, since they can still import other types of chips from the West, they could simply direct the entirety of their 7nm node to AI chips, making up for lower overall production.\n  \n\n\n\n    104\n   \n   Notably, even cybercriminals were able to\n   \n    hack Nvidia\n   \n   and get\n   \n    key GPU\n   \n\n    design\n   \n   secrets. Moreover,\n   \n    TPUv\n   \n   6\n   \n    designs were apparently among what\n   \n\n    was stolen\n   \n   by the recently-indicted Chinese national at Google.\n  \n\n\n\n    105\n   \n   For example, maybe these are 2x worse on perf/$ or perf/Watt. In turn, that also means to achieve the same overall datacenter performance, you need more power, and need more chips networked together, which also makes things more of a hassle.\n  \n\n\n   training clusters in a few years.\n   \n    106\n   \n\n    106\n   \n   Note that even\n   \n    3\n   \n   x more on chips\n  \n\n\n\n    1b. Outbuilding the US:\n   \n   The binding constraint on the largest training clusters won't be chips, but industrial mobilization perhaps most of all the 100GW of power for the trillion-dollar cluster. But if there's one thing China can do better than the US it's\n   \n    building stuff.\n   \n\n\n\n   In the last decade, China has roughly built as much new electricity capacity as\n   \n    the entire US capacity\n   \n   (while US capacity has remained basically flat). In the US, these things get stuck in environmental review, permitting, and regulation for a decade first. It thus seems quite plausible that China will be able to simply outbuild the US on the largest training clusters.\n  \n\n\n\n\n\n\n   would be much less than that in terms of increase in datacenter costs. Actual logic fab costs are <5% of Nvidia GPU cost, and even considering memory and CoWoS it's less than 20% of the Nvidia pricetag due to their margin. And even GPUs themselves tend to be only 50-60% of the cost of a datacenter. So 3x more expensive on the chip fab end might translate into much, much less than a 3x increase in overall cost. Even for 10x more expensive chips, it seems like China could stomach that without hugely increasing datacenter costs.\n  \n\n\n   Figure 37: The AI power buildout for 2030 seems much more doable for China than the US. Based on earlier estimates from IIIa. Racing to the Trillion-Dollar Cluster\n  \n\n\n   2. algorithms\n  \n\n\n   As discussed extensively in Counting the OOMs, scaling compute is only part of the story: algorithmic advances probably contribute at least half of AI progress. We're developing the key algorithmic breakthroughs for AGI\n   \n    right now\n   \n   (essentially the EUV of algorithms because of the data wall).\n  \n\n\n   By default, I expect Western labs to be well ahead; they have much of the key talent, and in recent years have developed all of the key breakthroughs. The size of the advantage may well be equivalent to a 10x (or even 100x) bigger cluster in a few years; this would provide the United States with a reasonably comfortable lead.\n  \n\n\n   And yet, on the current course, we will completely surrender this advantage: as discussed extensively in the security section, the current state of security essentially makes it trivial for China to infiltrate American labs. And so, unless we lock down the labs very soon, I expect China to be able to simply steal the key algorithmic ingredients for AGI, and match US capabilities.\n   \n    107\n   \n\n    107\n   \n   Some argue that even if China stole\n  \n\n\n   (Even worse, if we don't improve security, there is an even more salient path for China to compete. They won't even need to train their own AGI: they'll just be able to steal the AGI weights directly. Once they've stolen a copy of the automated AI researcher, they'll be off to the races, and can launch their own intelligence explosion. If they're willing to apply less caution\u2014both good caution, and unreasonable regulation and delay\u2014than the US, they could race through the intelligence explosion more quickly, outrunning us to superintelligence.)\n  \n\n\n   To date, US tech companies have made a much bigger bet on AI and scaling than any Chinese efforts; consequently, we are well ahead. But counting out China now is a bit like counting out Google in the AI race when ChatGPT came out in late 2022. Google hadn't yet focused their efforts in an intense AI bet, and it looked as though OpenAI was far ahead\u2014but once Google woke up, a year and half later, they are putting up a very serious fight. China, too, has a clear path to putting up a very serious fight. If and when the CCP mobilizes in the race to AGI, the picture could start looking very different.\n  \n\n\n   Perhaps the Chinese government will be incompetent; perhaps they decide AI threatens the CCP and impose\n   \n    stifling regula\n   \n\n    tion.\n   \n   But I wouldn't count on it.\n  \n\n\n   these secrets, they wouldn't be able to compete because it requires tacit knowledge. I disagree. I think of this as having two layers. The bottom layer is the engineering prowess for large-scale training runs; these training runs can be hacky and delicate and requires tacit knowledge. But as I'll discuss later, Chinese AI efforts have shown themselves perfectly capable of training large-scale models, and I think they will have this tacit knowledge indigenously. The top layer is the algorithmic recipe\u2014things like model architecture, the right scaling laws, etc.\u2014that could be conveyed in a one-hour call. These compute multipliers are usually discrete changes, meaning the underlying tacit knowledge for large-scale training runs should transfer. I don't think \"tacit knowledge\" will be a decisive barrier for Chinese AGI efforts.\n  \n\n\n   I, for one, think we need to operate under the assumption that we will face a full-throated Chinese AGI effort. As every year we get dramatic leaps in AI capability, as we start seeing early automation of software engineers, as AI revenue explodes and we start seeing $10T valuations and trillion-dollar cluster buildouts, as a broader consensus starts to form that we are on the cusp of AGI\u2014the CCP will take note. Much as I expect these leaps to wake up the USG to AGI, I would expect it to wake up the CCP to AGI\u2014and to wake up to what being behind on AGI would mean for their national power.\n  \n\n\n   They will be a formidable adversary.\n  \n\n\n\n    The authoritarian peril\n   \n\n\n\n   A dictator who wields the power of superintelligence would command concentrated power unlike any we've ever seen. In addition to being able to impose their will on other countries, they could enshrine their rule internally. Millions of AIcontrolled robotic law enforcement agents could police their populace; mass surveillance would be hypercharged; dictatorloyal AIs could individually assess every citizen for dissent, with advanced near-perfect lie detection rooting out any disloyalty.\n  \n\n\n   Most importantly, the robotic military and police force could be wholly controlled by a single political leader, and programmed to be perfectly obedient\u2014no more risk of coups or popular rebellions.\n  \n\n\n   Whereas past dictatorships were never permanent, superintelligence could eliminate basically all historical threats to a dictator's rule and lock in their power (cf\n   \n    value lock-in)\n   \n   . If the CCP gets this power, they could enforce the Party's conception of \"truth\" totally and completely.\n  \n\n\n   To be clear, I don't just worry about dictators getting superintelligence because \"our values are better.\" I believe in freedom and democracy, strongly, because I don't know what the right values are. In the long arc of history,\n   \n    \"time has upset many\n   \n\n\n\n\n    fighting faiths.\n   \n   \" I believe we should\n   \n    place our faith in mech\n   \n\n    anisms of error correction,\n   \n   experimentation, competition, and adaption.\n  \n\n\n   Superintelligence will give those who wield it the power to crush opposition, dissent, and lock in their grand plan for humanity. It will be difficult for anyone to resist the terrible temptation to use this power. I hope, dearly, that we can instead rely on the wisdom of the Framers\u2014letting radically different values flourish, and preserving the raucous plurality that has defined the American experiment.\n  \n\n\n   At stake in the AGI race will not just be the advantage in some far-flung proxy war, but whether freedom and democracy can survive for the next century and beyond. The course of human history is as brutal as it is clear. Twice in the 20th century tyranny threatened the globe; we must be under no delusion that this threat is banished forever. For many of my young friends, freedom and democracy feel like a given\u2014but they are not. By far the most common political system in history is authoritarianism.\n   \n    108\n   \n\n    108\n   \n   Primarily monarchy.\n  \n\n\n   I genuinely do not know the intentions of the CCP and their authoritarian allies. But, as a reminder: the CCP is a regime founded on the\n   \n    continued worship\n   \n   of perhaps the\n   \n    greatest to\n   \n\n    talitarian mass-murderer\n   \n   in human history (\"with estimates ranging from 40 to 80 million victims due to starvation, persecution, prison labor, and mass executions\"); a regime that recently put a million Uyghurs in\n   \n    concentration camps\n   \n   and\n   \n    crushed\n   \n   a free Hong Kong; a regime that systematically practices mass surveillance for social control, both of the\n   \n    new\n   \n\n    fangled\n   \n   (tracking phones, DNA databases, facial recognition, and so on) and the\n   \n    old-fangled\n   \n   (recruiting an army of citizens to report on their neighbors) kind; a regime that ensures\n   \n    all\n   \n\n    text messages\n   \n   pass through a censor, and that goes so far to repress dissent as to\n   \n    pull families into police stations\n   \n   when their child overseas attends a protest; a regime that\n   \n    has cemented\n   \n   Xi Jinping as dictator-for-life; a regime that touts its aims to militarily crush and\n   \n    \"reeducate\"\n   \n   a free neighboring nation; a regime that\n   \n    explicitly seeks\n   \n   a China-centric world order.\n  \n\n\n\n\n\n\n    The free world must prevail over the authoritarian powers in this race.\n   \n   We owe our peace and freedom to American economic and military preeminence. Perhaps even empowered with superintelligence, the CCP will behave responsibly on the international stage, leaving each to their own. But the history of dictators of their ilk is not pretty. If America and her allies fail to win this race, we risk it all.\n  \n\n\n\n    Maintaining a healthy lead will be decisive for safety\n   \n\n\n\n   It is the cursed history of science and technology that as they have unfolded their wonders, they have also expanded the means of destruction: from sticks and stones, to swords and spears, rifles and cannons, machine guns and tanks, bombers and missiles, nuclear weapons. The \"destruction/$\" curve has consistently gone down as technology has advanced. We should expect the rapid technological progress post-superintelligence to follow this trend.\n  \n\n\n   Perhaps dramatic advances in biology will yield extraordinary new bioweapons, ones that spread silently, swiftly, before killing with perfect lethality on command (and that can be made extraordinarily cheaply, affordable even for terrorist groups). Perhaps new kinds of nuclear weapons enable the size of nuclear arsenals to increase by orders of magnitude, with new delivery mechanisms that are undetectable. Perhaps mosquito-sized drones, each carrying a deadly poison, could be targeted to kill every member of an opposing nation. It's hard to know what a century's worth of technological progress would yield\u2014but I am confident it would unfold appalling possibilities.\n  \n\n\n   Humanity barely evaded self-destruction during the Cold War. On the historical view, the greatest existential risk posed by AGI is that it will enable us to develop extraordinary new means of mass death. This time, these means could even proliferate to become accessible to rogue actors or terrorists (especially if, as on the current course, the superintelligence weights aren't sufficiently protected, and can be directly stolen by North Korea, Iran, and co.).\n  \n\n\n   North Korea already has a concerted bioweapons program: the US\n   \n    assesses\n   \n   that \"North Korea has a dedicated, national level offensive program\" to develop and produce bioweapons. It seems plausible that their primary constraint is how far their small circle of top scientists has been able to push the limits of (synthetic) biology. What happens when that constraint is removed, when they can use millions of superintelligences to accelerate their bioweapons R&D? For example, the US\n   \n    assesses\n   \n   that North Korea currently has \"limited ability\" to genetically engineer biological products\u2014what happens when that becomes unlimited? With what unholy new concoctions will they hold us hostage?\n  \n\n\n   Moreover, as discussed in the superalignment section, there will be extreme safety risks around and during the intelligence explosion\u2014we will be faced with novel technical challenges to ensure we can reliably trust and control superhuman AI systems. This very well may require us to slow down at some critical moments, say, delaying by 6 months in the middle of the intelligence explosion to get additional assurances on safety, or using a large fraction of compute on alignment research rather than capabilities progress.\n  \n\n\n   Some hope for some sort of international treaty on safety. This seems fanciful to me. The world where both the CCP and USG are AGI-pilled enough to take safety risk seriously is also the world in which both realize that international economic and military predominance is at stake, that being months behind on AGI could mean being permanently left behind. If the race is tight, any arms control equilibrium, at least in the early phase around superintelligence, seems extremely unstable. In short, \"breakout\" is too easy: the incentive (and the fear that others will act on this incentive) to race ahead with an intelligence explosion, to reach superintelligence and the decisive advantage, too great.\n   \n    109\n   \n   At the very least, the odds we get something good-enough here seem slim. (How have those climate treaties gone? That seems like a dramatically easier problem compared to this.)\n  \n\n\n   The main\u2014perhaps the only\u2014hope we have is that an alliance of democracies has a healthy lead over adversarial powers. The\n  \n\n\n\n    109\n   \n   Consider the following comparison of unstable vs. stable arms control equilibria. 1980s arms control during the Cold War reduced nuclear weapons substantially, but targeted a stable equilibrium. The US and the Soviet Union still had 1000s of nuclear weapons. MAD was assured, even if one of the actors tried a crash program to build more nukes; and a rogue nation could try to build some nukes of their own, but not fundamentally threaten the US or Soviet Union with overmatch.\n  \n\n\n   However, when disarmament is to very low levels of weapons or occurs amidst rapid technological change, the equilibrium is unstable. A rogue actor or treaty-breaker can easily start a crash program and threaten to totally overmatch the other players. Zero nukes wouldn't be a stable equilibrium; similarly,\n   \n    this paper\n   \n   has interesting historical case studies (such as post-WWI arms limitations and the Washington Naval Treaty) where disarmament in similarly dynamic situations destabilized, rather than stabilized.\n  \n\n\n   If mere months of lead on AGI would give an utterly decisive advantage, this makes stable disarmament on AI similarly difficult. A rogue upstart or a treaty-breaker could gain a huge edge by secretly starting a crash program; the temptation would be too great for any sort of arrangement to be stable.\n  \n\n\n   United States must lead, and use that lead to enforce safety norms on the rest of the world. That's the\n   \n    path we took with\n   \n\n    nukes,\n   \n   offering assistance on the peaceful uses of nuclear technology in exchange for an international nonproliferation regime (ultimately underwritten by American military power)\u2014and it's the only path that's been shown to work.\n  \n\n\n   Perhaps most importantly, a healthy lead gives us room to maneuver: the ability to \"cash in\" parts of the lead, if necessary, to get safety right, for example by devoting extra work to alignment during the intelligence explosion.\n  \n\n\n   The safety challenges of superintelligence would become\n   \n    extremely\n   \n   difficult to manage if you are in a neck-and-neck arms race. A 2 year vs. a 2 month lead could easily make all the difference. If we have only a 2 month lead, we have no margin at all for safety. In fear of the CCP's intelligence explosion, we'd almost certainly race, no holds barred, through our own intelligence explosion\u2014barreling towards AI systems vastly smarter than humans in months, without any ability to slow down to get key decisions right, with all the risks of superintelligence going awry that implies. We'd face an extremely volatile situation, as we and the CCP rapidly developed extraordinary new military technology that repeatedly destabilized deterrence. If our secrets and weights aren't locked down, it might even mean a range of other rogue states are close as well, each of them using superintelligence to furnish their own new arsenal of super-WMDs. Even if we barely managed to inch out ahead, it would likely be a pyrrhic victory; the existential struggle would have brought the world to the brink of total selfdestruction.\n  \n\n\n   Superintelligence looks very different if the democratic allies have a healthy lead, say 2 years.\n   \n    110\n   \n   That buys us the time nec-\n   \n    110\n   \n   Note that, given the already-rapid essary to navigate the unprecedented series of challenges we'll face around and after superintelligence, and to stabilize the situation.\n  \n\n\n   If and when it becomes clear that the US will decisively win,\n   \n    that's\n   \n   when we offer a deal to China and other adversaries. They'll know they won't win, and so they'll know their only\n  \n\n\n   pace of AI progress today, and the even-more-rapid pace we should expect in an intelligence explosion, and the broader technological explosion post-superintelligence, \"even\" a 2 year-lead would be a\n   \n    huge\n   \n   difference in capabilities in the post-superintelligence world.\n  \n\n\n   option is to come to the table; and we'd rather avoid a feverish standoff or last-ditch military attempts on their part to sabotage Western efforts. In exchange for guaranteeing noninterference in their affairs, and sharing the peaceful benefits of superintelligence, a regime of nonproliferation, safety norms, and a semblance of stability post-superintelligence can be born.\n  \n\n\n   In any case, as we go deeper into this struggle, we must not forget the threat of self-destruction. That we made it through the Cold War in one piece involved too much luck111\u2014and the\n   \n    111\n   \n   Daniel Ellsberg\n   \n    recounts this riv\n   \n   destruction could be a thousandfold more potent than what we faced then. A healthy lead by an American-led coalition of democracies\u2014and a solemn exercise of this leadership to stabilize whatever volatile situation we find ourselves in\u2014is probably the safest path to navigating past this precipice. But in the heat of the AGI race, we better not screw it up.\n  \n\n\n\n    Superintelligence is a matter of national security\n   \n\n\n\n   It is clear: AGI is an existential challenge for the national security of the United States. It's time to start treating it as such.\n  \n\n\n   Slowly, the USG is starting to move. The export controls on American chips are a huge deal, and were an incredibly prescient move at the time. But we have to get serious across the board.\n  \n\n\n   The US\n   \n    has\n   \n   a lead. We just have to keep it. And we're screwing that up right now. Most of all, we must rapidly and radically lock down the AI labs, before we leak key AGI breakthroughs in the next 12-24 months (or the AGI weights themselves). We must build the compute clusters in the US, not in dictatorships that offer easy money. And yes, American AI labs have a duty to work with the intelligence community and the military. America's lead on AGI won't secure peace and freedom by just building the best AI girlfriend apps. It's not pretty\u2014but we must build AI for American defense.\n  \n\n\n\n    etingly,\n   \n   as one of the nuclear war planners at RAND and in the national security apparatus at the time.\n  \n\n\n   We are already on course for the most combustive international situation in decades. Putin is on the march in Eastern Europe. The Middle East is on fire. The CCP views taking Taiwan as its destiny. Now add in the race to AGI. Add in a century's worth of technological breakthroughs compressed into years post-superintelligence. It will be the one of most unstable international situations ever seen\u2014and at least initially, the incentives for first-strikes will be tremendous.\n   \n    112\n   \n\n    112\n   \n   Everyone will be racing to their own\n  \n\n\n   There's already an eerie convergence of AGI timelines (~2027?) and Taiwan watchers' Taiwan invasion timelines\n   \n    (China ready\n   \n\n    to invade Taiwan by\n   \n   2027?)\u2014a convergence that will surely only heighten as the world wakes up to AGI. (Imagine if in 1960, the vast majority of the world's uranium deposits were somehow concentrated in Berlin!) It seems to me that there is a real chance that the AGI endgame plays out with the backdrop of world war. Then all bets are off.\n  \n\n\n   superintelligences, and there will be a limited window before someone ahead will have irreversibly pulled away. There will be a big incentive to try to disable the enemy superintelligence clusters before they've gained a sufficient physical advantage (e.g., using superintelligence to develop impenetrable missile defense or drone swarms) that leaves everyone else permanently in the dust.\n  \n\n\n\n    IV. The Project\n   \n\n\n\n\n    As the race to AGI intensifies, the national security state will get involved. The USG will wake from its slumber, and by 27/28 we'll get some form of government AGI project. No startup can handle superintelligence. Somewhere in a SCIF, the endgame will be on.\n   \n\n\n\n\n\n    We must be curious to learn how such a set of objects\u2014hundreds of power plants, thousands of bombs, tens of thousands of people massed in national establishments\u2014can be traced back to a few people sitting at laboratory benches discussing the peculiar behavior of one type of atom.\n   \n\n\n\n\n\n\n\n     spencer r. weart\n    \n\n\n\n\n   Many plans for \"AI governance\" are put forth these days, from licensing frontier AI systems to safety standards to a public cloud with a few hundred million in compute for academics. These seem well-intentioned\u2014but to me, it seems like they are making a category error.\n  \n\n\n\n    I find it an insane proposition that the US government will let a random SF startup develop superintelligence\n   \n   . Imagine if we had developed atomic bombs by letting Uber just improvise.\n  \n\n\n   Superintelligence\u2014AI systems\n   \n    much\n   \n   smarter than humans will have vast power, from developing novel weaponry to driving an explosion in economic growth. Superintelligence will be\n  \n\n\n   the locus of international competition; a lead of months potentially decisive in military conflict.\n  \n\n\n   It is a delusion of those who have unconsciously internalized our brief respite from history that this will not summon more primordial forces. Like many scientists before us, the great minds of San Francisco hope that they can control the destiny of the demon they are birthing. Right now, they still can; for they are among the few with situational awareness, who understand what they are building. But in the next few years, the world will wake up. So too will the national security state. History will make a triumphant return.\n  \n\n\n   As in many times before\u2014Covid, WWII\u2014it will seem as though the United States is asleep at the wheel\u2014before, all at once, the government shifts into gear in the most extraordinary fashion. There will be a moment\u2014in just a few years, just a couple more \"2023-level\" leaps in model capabilities and AI discourse where it will be clear: we are on the cusp of AGI, and superintelligence shortly thereafter. While there's a lot of flux in the exact mechanics, one way or another, the USG will be at the helm; the leading labs will (\"voluntarily\") merge; Congress will appropriate trillions for chips and power; a coalition of democracies formed.\n  \n\n\n   Startups are great for many things\u2014but a startup on its own is simply not equipped for being in charge of the United States' most important national defense project. We will need government involvement to have even a hope of defending against the all-out espionage threat we will face; the private AI efforts might as well be directly delivering superintelligence to the CCP. We will need the government to ensure even a semblance of a sane chain of command; you can't have random CEOs (or random nonprofit boards) with the nuclear button. We will need the government to manage the severe safety challenges of superintelligence, to manage the fog of war of the intelligence explosion. We will need the government to deploy superintelligence to defend against whatever extreme threats unfold, to make it through the extraordinarily volatile and destabilized international situation that will follow. We will need the government to mobilize a democratic coalition to win the race with\n  \n\n\n   authoritarian powers, and forge (and enforce) a nonproliferation regime for the rest of the world. I wish it weren't this way\u2014but we will need the government. (Yes, regardless of the Administration.)\n  \n\n\n   In any case, my main claim is not normative, but descriptive. In a few years, The Project will be on.\n  \n\n\n\n    The path to The Project\n   \n\n\n\n   A turn-of-events seared into my memory is late February to mid-March of 2020. In those last weeks of February and early days of March, I was in utter despair: it seemed clear that we were on the covid-exponential: a plague was about to sweep the country, the collapse of our hospitals was imminent\u2014and yet almost nobody took it seriously. The Mayor of New York was still dismissing Covid-fears as racism and encouraging people to go to Broadway shows. All I could do was buy masks and short the market.\n  \n\n\n   And yet within just a few weeks, the entire country shut down and Congress had appropriated trillions of dollars (literally >10% of GDP). Seeing where the exponential might go ahead of time was too hard, but when the threat got close enough, existential enough, extraordinary forces were unleashed. The response was late, crude, blunt\u2014but it came, and it was dramatic.\n  \n\n\n   The next few years in AI will feel similar. We're in the midgame now. 2023 was already a wild shift. AGI went from a fringe topic you'd be hesitant to associate with, to the subject of major Senate hearings and summits of world leaders. Given how early we are still, the level of USG engagement has been impressive to me. A couple more \"2023\"s, and the Overton window will be blown completely open.\n  \n\n\n   As we race through the OOMs, the leaps will continue. By 2025/2026 or so I expect the next truly shocking step-changes; AI will drive $100B+ annual revenues for big tech companies and outcompete PhDs in raw problem-solving smarts. Much as\n  \n\n\n   the Covid stock-market collapse made many take Covid seriously, we'll have $10T companies and the AI mania will be everywhere. If that's not enough, by 2027/28, we'll have models trained on the $100B+ cluster; full-fledged AI agents/drop-in remote workers will start to widely automate software engineering and other cognitive jobs. Each year, the acceleration will feel dizzying.\n  \n\n\n   While many don't yet see the possibility of AGI, eventually a consensus will form. Some, like Szilard, saw the possibility of an atomic bomb much earlier than others. Their alarm was not well-received initially; the possibility of a bomb was dismissed as remote (or at least, it was felt that the conservative and proper thing was to play down the possibility). Szilard's fervent secrecy appeals were mocked and ignored. But many scientists, initially skeptical, started realizing a bomb was possible as more and more empirical results came in. Once a majority of scientists came to believe we were on the cusp of a bomb, the government, in turn, saw the national security exigency as too great\u2014and the Manhattan Project got underway.\n  \n\n\n   As the OOMs go from theoretical extrapolation to (extraordinary) empirical reality, gradually, a consensus will form, too, among the leading scientists and executives and government officials: we are on the cusp, on the cusp of AGI, on the cusp of an intelligence explosion, on the cusp of superintelligence. And somewhere along here, we'll get the first genuinely terrifying demonstrations of AI: perhaps the oft-discussed \"helping novices make bioweapons,\" or autonomously hacking critical systems, or something else entirely. It will become clear: this technology will be an utterly decisive military technology. Even if we're lucky enough to not be in a major war, it seems likely that the CCP will have taken notice and launched a formidable AGI effort. Perhaps the eventual (inevitable) discovery of the CCP's infiltration of America's leading AI labs will cause a big stir.\n  \n\n\n   Somewhere around 26/27 or so, the mood in Washington will become somber. People will start to viscerally feel what is happening; they will be\n   \n    scared\n   \n   . From the halls of the Pentagon to the backroom Congressional briefings will ring the obvious\n  \n\n\n   question, the question on everybody's minds: do we need an AGI Manhattan Project? Slowly at first, then all at once, it will become clear: this is happening, things are going to get\n   \n    wild\n   \n   , this is the most important challenge for the national security of the United States since the invention of the atomic bomb. In one form or another, the national security state will get very heavily involved. The Project will be the necessary, indeed the only plausible, response.\n  \n\n\n   Of course, this is an extremely abbreviated account\u2014a lot depends on when and how consensus forms, key warning shots, and so on. DC is infamously dysfunctional. As with Covid, and even the Manhattan Project, the government will be incredibly late and hamfisted.\n   \n    After\n   \n   Einstein's letter to the President in 1939 (drafted by Szilard), an Advisory Committee on Uranium was formed. But officials were incompetent, and not much happened initially. For example, Fermi only got $6k (about $135k in today's dollars) to support his research, and even that was not given easily and only received after months of waiting. Szilard believed that the project was\n   \n    delayed for\n   \n\n    at least a year\n   \n   by the short-sightedness and sluggishness of the authorities. In March 1941, the British government finally concluded a bomb was inevitable. The US committee initially entirely ignored this British report for months\u2014until finally in December 1941, a full-scale atomic bomb effort was launched.\n  \n\n\n   There are many ways this could be operationalized in practice. To be clear, this doesn't need to look like literal nationalization, with AI lab researchers now employed by the military or whatever (though it might!).\n   \n    113\n   \n   Rather, I expect a more suave\n   \n    113\n   \n   Note that while private companies orchestration. The relationship with the DoD might look like the relationship the DoD has with Boeing or Lockheed Martin. Perhaps via defense contracting or similar, a joint venture between the major cloud compute providers, AI labs, and the government is established, making it functionally a project of the national security state. Much like the AI labs \"voluntarily\" made commitments to the White House in 2023, Western labs might more-or-less \"voluntarily\" agree to merge in the national effort. And likely Congress will have to be involved, given the trillions of investment involved, and for checks-and-balances.\n   \n    114\n   \n\n    114\n   \n   Congress\u2014even the Vice President!\u2014 How all these details shake out is a story for another day.\n  \n\n\n   help develop components for nuclear weapons, they are never allowed to possess a completed and assembled nuclear weapon. In comparison, the mainline version of the \"AGI government project\" I am putting forward here is unprecedentedly privatized, for the WMD reference class.\n  \n\n\n   didn't know about the Manhattan Project. We probably shouldn't repeat that here; I'd even suggest that key officials for The Project require Senate confirmation.\n  \n\n\n   But by late 26/27/28 it will be underway. The core AGI research team (a few hundred researchers) will move to a secure location; the trillion-dollar cluster will be built in record-speed; The Project will be on.\n  \n\n\n\n    Why The Project is the only way\n   \n\n\n\n   I am under no illusions about the government. Governments face all sorts of limitations and poor incentives. I am a big believer in the American private sector, and would almost never advocate for heavy government involvement in technology or industry.\n  \n\n\n   I used to apply this same framework to AGI\u2014until I joined an AI lab. AI labs are very good at some things: they've been able to take AI from an academic science project to the commercial big stage, in a way only a startup can. But ultimately, AI labs are still startups. We simply shouldn't expect startups to be equipped to handle superintelligence.\n  \n\n\n   There are no good options here\u2014but I don't see another way. When a technology becomes this important for national security, we will need the USG.\n  \n\n\n\n    Superintelligence will be the United States' most important national defense project\n   \n\n\n\n   I've discussed the power of superintelligence in previous pieces. Within years, superintelligence would completely shake up the military balance of power. By the early 2030s, the entirety of the US arsenal (like it or not, the bedrock of global peace and security) will probably be obsolete. It will not just be a matter of modernization, but a wholesale replacement.\n  \n\n\n   Simply put, it will become clear that the development of AGI will fall in a category more like nukes than the internet. Yes, of course it'll be dual-use\u2014but nuclear technology was dualuse too. The civilian applications will have their time. But in\n  \n\n\n   the fog of the AGI endgame, for better or for worse, national security will be the primary backdrop.\n  \n\n\n   We will need to completely reshape US forces, within a matter of years, in the face of rapid technological change\u2014or risk being completely outmatched by adversaries who do. Perhaps most of all, the initial priority will be to deploy superintelligence for defensive applications, to develop countermeasures to survive untold new threats: adversaries with superhuman hacking capabilities, new classes of stealthy drone swarms that could execute a preemptive strike on our nuclear deterrent, the proliferation of advances in synthetic biology that can be weaponized, turbulent international (and national) power struggles, and rogue superintelligence projects.\n  \n\n\n   Whether nominally private or not, the AGI project will need to be,\n   \n    will be,\n   \n   integrally a defense project, and it will require extremely close cooperation with the national security state.\n  \n\n\n\n    A sane chain of command for superintelligence\n   \n\n\n\n   The power\u2014and the challenges\u2014of superintelligence will fall into a very different reference class than anything else we're used to seeing from tech companies. It seems pretty clear: this should not be under the unilateral command of a random CEO. Indeed, in the private-labs-developing-superintelligence world, it's quite plausible individual CEOs would have the power\n   \n    to literally coup the US government\n   \n   .\n   \n    115\n   \n   Imagine if Elon Musk\n   \n    115\n   \n   It wouldn't even require cooperhad final command of the nuclear arsenal.\n   \n    116\n   \n   (Or if a random nonprofit board could decide to seize control of the nuclear arsenal.)\n  \n\n\n   It is perhaps obvious, but: as a society, we've decided democratic governments should control the military;\n   \n    117\n   \n   superin-\n   \n    117\n   \n   In fact, the government having telligence will be, at least at first, the most powerful military weapon. The radical proposal is not The Project; the radical proposal is taking a bet on private AI CEOs wielding military power and becoming benevolent dictators.\n  \n\n\n   (Indeed, in the private AI lab world, it would likely be even worse than random CEOs with the nuclear button\u2014part of AI\n  \n\n\n   ation from AI lab employees at this point, since they'll have been mostly automated by this point.\n   \n    116\n   \n   And as Sam Altman once said, every year we get closer to AGI everybody will gain +10 crazy points.\n  \n\n\n   the biggest guns was an enormous\n   \n    civilizational achievement!\n   \n   Rather than medieval-like fights of all against all, we would sort out disagreements via courts, pluralistic institutions, and so on.\n  \n\n\n   labs' abysmal security is their utter lack of internal controls. That is, random AI lab employees (with zero vetting) could go rogue unnoticed.)\n  \n\n\n   We will need a sane chain of command\u2014along with all the other processes and safeguards that necessarily come with responsibly wielding what will be comparable to a WMD\u2014and it'll require the government to do so. In some sense, this is simply a Burkean argument: the institutions, constitutions, laws, courts, checks and balances, norms and common dedication to the liberal democratic order (e.g., generals refusing to follow illegal orders), and so on that check the power of the government have withstood the test of hundreds of years. Special AI lab governance structures, meanwhile, collapsed the first time they were tested. The US military could already kill basically every civilian in the United States, or seize power, if it wanted to\u2014and the way we keep government power over nuclear weapons in check is not through lots of private companies with their own nuclear arsenals. There's only one chain of command and set of institutions that has proven itself up to this task.\n  \n\n\n   Again, perhaps you are a true libertarian and disagree normatively (let Elon Musk and Sam Altman command their own nuclear arsenals!).\n   \n    118\n   \n   But once it becomes clear that superintel-\n   \n    118\n   \n   Or perhaps you say, just open-source ligence is a principal matter of national security, I'm sure this is how the men and women in DC will look at it.\n  \n\n\n\n    The civilian uses of superintelligence\n   \n\n\n\n   Of course, that doesn't mean the civilian applications of superintelligence will be reserved for the government.\n  \n\n\n\n\n\n\n     The nuclear chain reaction was first harnessed as a government project\u2014and nuclear weapons permanently reserved for the government\u2014but civilian nuclear energy flourished as private projects (in the 60s and 70s, before environmentalists shut it down).\n    \n\n\n     Boeing made the B-29 (the most expensive defense R&D project during WWII, more expensive than the Manhat-\n    \n\n\n\n   everything. The issue with simply open sourcing everything is that it's not a happy world of a thousand flowers blooming in the US, but a world in which the CCP has free access to US-developed superintelligence, and can outbuild (and apply less caution/regulation) and take over the world. And the other issue, of course, is the proliferation of super-WMDs to every rogue state and terrorist group in the world. I don't think it'll end well. It's a bit like how having no government at all is more likely to lead to tyranny (or destruction) than freedom.\n  \n\n\n   In any case, people overrate the importance of open-source as we get closer to AGI. Given cluster costs escalating to hundreds of billions, and key algorithmic secrets now being proprietary rather than published as they were a couple years ago, it'll be 2-3 or so leading players, rather than some happy community of decentralized coders building AGI.\n  \n\n\n   I do think a different variant of open source will continue to play an important role: models that lag a couple years behind being open sourced, helping the benefits of the technology diffuse broadly.\n  \n\n\n   tan Project) and the B-47 and B-52 long-range bombers in partnership with the military\u2014before using that technology for the Boeing 707, the commercial plane that ushered in the jet era. And today, while Boeing can only sell stealth fighter jets to the government, it can freely develop and sell civilian jets privately.\n  \n\n\n   \u2022 And so it went for radar, satellites, rockets, gene technology, WWII factories, and so on.\n  \n\n\n   The initial development of superintelligence will be dominated by the national security exigency to survive and stabilize an incredibly volatile period. And the military uses of superintelligence will remain reserved for the government, and safety norms will be enforced. But once the initial peril has passed, the natural path is for the companies involved in the national consortium (and others) to privately pursue civilian applications.\n  \n\n\n   Even in worlds with The Project, a private, pluralistic, market-based, flourishing ecosystem of civilian applications of superintelligence will have its day.\n  \n\n\n\n    Security\n   \n\n\n\n   I've gone on about this at length in a previous piece in the series. On the current course, we may as well give up on having any American AGI effort; China can promptly steal all the algorithmic breakthroughs and the model weights (literally a copy of superintelligence) directly. It's not even clear we'll get to \"North Korea-proof\" security for superintelligence on the current course. In the private-startups-developing-AGI-world, superintelligence would proliferate to dozens of rogue states. It's simply untenable.\n  \n\n\n   If we're going to be at all serious about this, we obviously need to lock this stuff down. Most private companies have failed to take this seriously. But in any case, if we are to eventually face the full force of Chinese espionage (e.g., stealing the weights being the MSS's #1 priority), it's probably impossible for a private company to get good enough security. It will require\n  \n\n\n   extensive cooperation from the US intelligence community at that point to sufficiently secure AGI. This will involve invasive restrictions on AI labs and on the core team of AGI researchers, from extreme vetting to constant monitoring to working from a SCIF to reduced freedom to leave; and it will require infrastructure only the government can provide, ultimately including the physical security of the AGI datacenters themselves.\n  \n\n\n   In some sense, security alone is sufficient to necessitate the government project\u2014both the free world's preeminence and AI safety are doomed if we can't lock this stuff down. (In fact, I think it's fairly likely to be a major factor in the ultimate trigger: once the Chinese infiltration of the AGI labs becomes clear, every Senator and Congressperson and national security official will. . . have a strong opinion on the matter.)\n  \n\n\n\n    Safety\n   \n\n\n\n   Simply put: there are a lot of ways for us to mess this up from ensuring we can reliably control and trust the billions of superintelligent agents that will soon be in charge of our economy and military (the superalignment problem), to controlling the risks of misuse of new means of mass destruction.\n  \n\n\n   Some AI labs claim to be committed to safety: acknowledging that what they are building, if gone awry, could cause catastrophe and promising that they will do what is necessary when the time comes. I do not know if we can trust their promise enough to stake the lives of every American on it. More importantly, so far, they have not demonstrated the competence, trustworthiness, or seriousness necessary for what they themselves acknowledge they are building.\n  \n\n\n   At core, they are startups, with all the usual commercial incentives. Competition could push all of them to simply race through the intelligence explosion, and there will at least be some actors that will be willing to throw safety by the wayside. In particular, we may want to \"spend some of our lead\" to have time to solve safety challenges, but Western labs will need to coordinate to do so. (And of course, private labs will have already had their AGI weights stolen, so their safety pre-\n  \n\n\n   cautions won't even matter; we'll be at the mercy of the CCP's and North Korea's safety precautions.)\n  \n\n\n   One answer is regulation. That may be appropriate in worlds in which AI develops more slowly, but I fear that regulation simply won't be up to the nature of the challenge of the intelligence explosion. What's necessary will be less like spending a few years doing careful evaluations and pushing some safety standards through a bureaucracy.\n   \n    It'll be more like fighting a war\n   \n   .\n  \n\n\n   We'll face an insane year in which the situation is shifting extremely rapidly every week, in which hard calls based on ambiguous data will be life-or-death, in which the solutions\u2014even the problems themselves\u2014won't be close to fully clear ahead of time but come down to competence in a \"fog of war,\" which will involve insane tradeoffs like \"some of our alignment measurements are looking ambiguous, we don't really understand what's going on anymore, it might be fine but there's some warning signs that the next generation of superintelligence might go awry, should we delay the next training run by 3 months to get more confidence on safety\u2014but oh no, the latest intelligence reports indicate China stole our weights and is racing ahead on their own intelligence explosion, what should we do?\".\n  \n\n\n   I'm not confident that a government project would be competent in dealing with this\u2014but the \"superintelligence developed by startups\" alternative seems much closer to \"praying for the best\" than commonly recognized. We'll need a chain of command that can bring to the table the seriousness that making these difficult tradeoffs will require.\n  \n\n\n\n    Stabilizing the international situation\n   \n\n\n\n   The intelligence explosion and its immediate aftermath will bring forth one of the most volatile and tense situations mankind has ever faced. Our generation is not used to this. But in this initial period, the task at hand will not be to build cool products. It will be to somehow, desperately, make it through this period.\n  \n\n\n   We'll need the government project to win the race against the\n  \n\n\n   authoritarian powers\u2014and to give us the clear lead and breathing room necessary to navigate the perils of this situation. We might as well give up if we can't prevent the instant theft of superintelligence model weights. We will want to bundle Western efforts: bring together our best scientists, use every GPU we can find, and ensure the trillions of dollars of cluster buildouts happen in the United States. We will need to protect the datacenters against adversary sabotage, or outright attack.\n  \n\n\n   Perhaps, most of all, it will take American leadership to develop and if necessary, enforce\u2014a nonproliferation regime. We'll need to subvert Russia, North Korea, Iran, and terrorist groups from using their own superintelligence to develop technology and weaponry that would let them hold the world hostage. We'll need to use superintelligence to harden the security of our critical infrastructure, military, and government to defend against extreme new hacking capabilities. We'll need to use superintelligence to stabilize the offense/defense balance of advances in biology or similar. We'll need to develop tools to safely control superintelligence, and to shut down rogue superintelligences that come out of others' uncareful projects.AI systems and robots will be moving at 10-100x+ human speed; everything will start happening extremely quickly. We need to be ready to handle whatever other six-sigma upheavals and concomitant threats\u2014come out of compressing a century's worth of technological progress into a few years.\n  \n\n\n   At least in this initial period, we will be faced with the most extraordinary national security exigency. Perhaps, nobody is up for this task. But of the options we have, The Project is the only sane one.\n  \n\n\n\n    The Project is inevitable; whether it's good is not\n   \n\n\n\n   Ultimately, my main claim here is descriptive: whether we like it or not, superintelligence won't look like an SF startup, and in some way will be primarily in the domain of national security. I've brought up The Project a lot to my San Francisco friends in the past year. Perhaps what's surprised me most is\n  \n\n\n   how surprised most people are about the idea. They simply haven't considered the possibility. But once they consider it, most agree that it seems obvious. If we are at all right about what we think we are building,\n   \n    of course,\n   \n   by the end this will be (in some form) a government project. If a lab developed literal superintelligence tomorrow,\n   \n    of course\n   \n   the Feds would step in.\n  \n\n\n   One important free variable is not\n   \n    if\n   \n   but\n   \n    when\n   \n   . Does the government not realize what's happening until we're in the middle of an intelligence explosion\u2014or will it realize a couple years beforehand? If the government project is inevitable, earlier seems better. We'll dearly need those couple years to do the security crash program, to get the key officials up to speed and prepared, to build a functioning merged lab, and so on. It'll be far more chaotic if the government only steps in at the very end (and the secrets and weights will have already been stolen).\n  \n\n\n   Another important free variable is the international coalition we can rally: both a tighter alliance of democracies for developing superintelligence, and a broader benefit-sharing offer made to the rest of the world.\n  \n\n\n\n\n\n\n     The former might look like the\n     \n      Quebec Agreement:\n     \n     a secret pact between Churchill and Roosevelt to pool their resources to develop nuclear weapons, while not using them against each other or against others without mutual consent. We'll want to bring in the UK (Deepmind), East Asian allies like Japan and South Korea (chip supply chain), and NATO/other core democratic allies (broader industrial base). A united effort will have more resources, talent, and control the whole supply chain; enable close coordination on safety, national security, and military challenges; and provide helpful checks and balances on wielding the power of superintelligence.\n    \n\n\n     The latter might look like\n     \n      Atoms for Peace,\n     \n     the\n     \n      IAEA,\n     \n     and the\n     \n      NPT.\n     \n     We should offer to share the peaceful benefits of superintelligence with a broader group of countries (including non-democracies), and commit to not offensively using superintelligence against them. In exchange, they refrain from pursuing their own superintelligence projects, make\n    \n\n\n\n   safety commitments on the deployment of AI systems, and accept restrictions on dual-use applications. The hope is that this offer reduces the incentives for arms races and proliferation, and brings a broad coalition under a US-led umbrella for the post-superintelligence world order.\n  \n\n\n   Perhaps the most important free variable is simply whether the inevitable government project will be competent. How will it be organized? How can we get this done? How will the checks and balances work, and what does a sane chain of command look like? Scarcely any attention has gone into figuring this out.\n   \n    119\n   \n   Almost all other AI lab and AI governance politicking is\n   \n    119\n   \n   To my Progress Studies brethren: you a sideshow. This is the ballgame.\n  \n\n\n   should think about this, this will be the culmination of your intellectual project! You spend all this time studying American government research institutions, their decline over the last half-century, and what it would take to make them effective again. Tell me: how will we make The Project effective?\n  \n\n\n\n    The endgame\n   \n\n\n\n   And so by 27/28, the endgame will be on. By 28/29 the intelligence explosion will be underway; by 2030, we will have summoned superintelligence, in all its power and might.\n  \n\n\n   Whoever they put in charge of The Project is going to have a hell of a task: to build AGI, and to build it fast; to put the American economy on wartime footing to make hundreds of millions of GPUs; to lock it all down, weed out the spies, and fend off all-out attacks by the CCP; to somehow manage a hundred million AGIs furiously automating AI research, making a decade's leaps in a year, and soon producing AI systems\n   \n    vastly\n   \n   smarter than the smartest humans; to somehow keep things together enough that this doesn't go off the rails and produce rogue superintelligence that tries to seize control from its human overseers; to use those superintelligences to develop whatever new technologies will be necessary to stabilize the situation and stay ahead of adversaries, rapidly remaking US forces to integrate those; all while navigating what will likely be the tensest international situation ever seen. They better be good, I'll say that.\n  \n\n\n   For those of us who get the call to come along for the ride, it'll be . . . stressful. But it will be our duty to serve the free\n  \n\n\n\n\n\n\n   Figure 38: Oppenheimer and Groves.\n  \n\n\n   world\u2014and all of humanity. If we make it through and get to look back on those years, it will be the most important thing we ever did. And while whatever secure facility they find probably won't have the pleasantries of today's ridiculouslyovercomped-AI-researcher-lifestyle, it won't be so bad. SF already feels like a peculiar AI-researcher-college-town; probably this won't be so different. It'll be the same weirdly-small circle sweating the scaling curves during the day and hanging out over the weekend, kibitzing over AGI and the lab-politics-ofthe-day.\n  \n\n\n   Except, well\u2014the stakes will be all too real.\n  \n\n\n   See you in the desert, friends.\n  \n\n\n\n\n\n\n   Figure 39: Reunion of atomic scientists on the fourth anniversary of the first controlled nuclear fission reaction at UChicago.\n  \n\n\n\n    V. Parting Thoughts\n   \n\n\n\n\n    What if we're right?\n   \n\n\n\n   I remember the spring of 1941 to this day. I realized then that a nuclear bomb was not only possible \u2014 it was inevitable. Sooner or later these ideas could not be peculiar to us. Everybody would think about them before long, and some country would put them into action. . . .\n  \n\n\n   And there was nobody to talk to about it, I had many sleepless nights. But I did realize how very very serious it could be. And I had then to start taking sleeping pills. It was the only remedy, I've never stopped since then. It's 28 years, and I don't think I've missed a single night in all those 28 years.\n  \n\n\n   james chadwich (Physics Nobel Laureate and author of the 1941 British government report on the inevitability of an atomic bomb, which finally spurred the Manhattan Project into action)\n  \n\n\n   Before the decade is out, we will have built superintelligence. That is what most of this series has been about. For most people I talk to in SF, that's where the screen goes black. But the decade after\u2014the 2030s\u2014will be at least as eventful. By the end of it, the world will have been utterly, unrecognizably transformed. A new world order will have been forged. But alas\u2014that's a story for another time.\n  \n\n\n   We must come to a close, for now. Let me make a few final remarks.\n  \n\n\n\n    AGI realism\n   \n\n\n\n   This is all much to contemplate\u2014and many cannot. \"Deep learning is hitting a wall!\" they proclaim, every year. It's just another tech boom, the pundits say confidently. But even among those at the SF-epicenter, the discourse has become polarized between two fundamentally unserious rallying cries.\n  \n\n\n   On the one end there are the doomers. They have been obsessing over AGI for many years; I give them a lot of credit for their prescience. But their thinking has become ossified, untethered from the empirical realities of deep learning, their proposals naive and unworkable, and they fail to engage with the very real authoritarian threat. Rabid claims of 99% odds of doom, calls to indefinitely pause AI\u2014they are clearly not the way.\n  \n\n\n   On the other end are the e/accs. Narrowly, they have some good points: AI progress must continue. But beneath their shallow Twitter shitposting, they are a sham; dilettantes who just want to build their wrapper startups rather than stare AGI in the face. They claim to be ardent defenders of American freedom, but can't resist the siren song of unsavory dictators' cash. In truth, they are real stagnationists. In their attempt to deny the risks, they deny AGI; essentially, all we'll get is cool chatbots, which surely aren't dangerous. (That's some underwhelming accelerationism in my book.)\n  \n\n\n   But as I see it, the smartest people in the space have converged on a different perspective, a third way, one I will dub\n   \n    AGI Realism.\n   \n   The core tenets are simple:\n  \n\n\n   1.\n   \n    Superintelligence is a matter of national security.\n   \n   We are rapidly building machines smarter than the smartest humans. This is not another cool Silicon Valley boom; this isn't some random community of coders writing an innocent open source software package; this isn't fun and games. Superintelligence is going to be\n   \n    wild\n   \n   ; it will be the most powerful weapon mankind has ever built. And for any of us involved, it'll be the most important thing we ever do.\n  \n\n\n\n\n\n\n     2.\n     \n      America must lead.\n     \n     The torch of liberty will not survive Xi getting AGI first. (And, realistically, American leadership is the only path to safe AGI, too.) That means we can't simply \"pause\"; it means we need to rapidly scale up US power production to build the AGI clusters in the US. But it also means amateur startup security delivering the nuclear secrets to the CCP won't cut it anymore, and it means the core AGI infrastructure must be controlled by America, not some dictator in the Middle East. American AI labs must put the national interest first.\n    \n\n\n     3.\n     \n      We need to not screw it up.\n     \n     Recognizing the power of superintelligence also means recognizing its peril. There are very real safety risks; very real risks this all goes awry\u2014whether it be because mankind uses the destructive power brought forth for our mutual annihilation, or because, yes, the alien species we're summoning is one we cannot yet fully control. These are manageable\u2014but improvising won't cut it. Navigating these perils will require good people bringing a level of seriousness to the table that has not yet been offered.\n    \n\n\n\n   As the acceleration intensifies, I only expect the discourse to get more shrill. But my greatest hope is that there will be those who feel the weight of what is coming, and take it as a solemn call to duty.\n  \n\n\n\n    What if we're right?\n   \n\n\n\n   At this point, you may think that I and all the other SF-folk are totally crazy. But consider, just for a moment:\n   \n    what if they're right?\n   \n   These are the people who invented and built this technology; they think AGI will be developed this decade; and, though there's a fairly wide spectrum, many of them take very seriously the possibility that the road to superintelligence will play out as I've described in this series.\n  \n\n\n   Almost certainly I've gotten important parts of the story wrong; if reality turns out to be anywhere near this crazy, the error bars will be very large. Moreover, as I said at the outset, I think there's a wide range of possibilities. But I think it is impor-\n  \n\n\n   tant to be concrete. And in this series I've laid out what I currently believe is the single most likely scenario for the rest of the decade\u2014the rest of\n   \n    this\n   \n   decade.\n  \n\n\n   Because\u2014it's starting to feel real,\n   \n    very\n   \n   real. A few years ago, at least for me, I took these ideas seriously\u2014but they were abstract, quarantined in models and probability estimates. Now it feels extremely visceral. I can\n   \n    see\n   \n   it. I can\n   \n    see\n   \n   how AGI will be built. It's no longer about estimates of human brain size and hypotheticals and theoretical extrapolations and all that\u2014I can basically tell you the cluster AGI will be trained on and when it will be built, the rough combination of algorithms we'll use, the unsolved problems and the path to solving them, the list of people that will matter. I can\n   \n    see\n   \n   it. It is extremely visceral. Sure, going all-in leveraged long Nvidia in early 2023 has been great and all, but the burdens of history are heavy. I would not choose this.\n  \n\n\n   But the scariest realization is that\n   \n    there is no crack team coming to handle this\n   \n   . As a kid you have this glorified view of the world, that when things get real there are the heroic scientists, the uber-competent military men, the calm leaders who are on it, who will save the day. It is not so. The world is incredibly small; when the facade comes off, it's usually just a few folks behind the scenes who are the live players, who are desperately trying to keep things from falling apart.\n  \n\n\n   Right now, there's perhaps a few hundred people in the world who realize what's about to hit us, who understand just how crazy things are about to get, who have situational awareness. I probably either personally know or am one degree of separation from everyone who could plausibly run The Project. The few folks behind the scenes who are desperately trying to keep things from falling apart are you and your buddies and their buddies. That's it. That's all there is.\n  \n\n\n   Someday it will be out of our hands. But right now, at least for the next few years of midgame, the fate of the world rests on these people.\n  \n\n\n   Will the free world prevail?\n  \n\n\n   Will we tame superintelligence, or will it tame us?\n  \n\n\n   Will humanity skirt self-destruction once more?\n  \n\n\n   The stakes are no less.\n  \n\n\n   These are great and honorable people. But they are just people. Soon, the AIs will be running the world, but we're in for one last rodeo. May their final stewardship bring honor to mankind.\n  \n\n\n\n\n\n\n    Appendix\n   \n\n\n\n\n    Some additional details on compute back-of-the-envelope calculcations\n   \n\n\n\n\n    Training compute\n   \n\n\n\n\n    Year.\n   \n   The OpenAI GPT-4\n   \n    tech report\n   \n   stated that GPT-4 finished training in August 2022. Thereafter we play forward the rough 0.5 OOMs/year trend.\n  \n\n\n\n    H100s-equivalent.\n   \n\n    Semianalysis,\n   \n\n    JP Morgan,\n   \n   and others estimate GPT-4 was trained on 25k A100s, and H100s are 2-3x the performance of A100s.\n  \n\n\n\n    Cost.\n   \n   Often people cite numbers like \"$100M for GPT-4 training,\" using just the rental cost of the GPUs (i.e., something like \"how much would it cost to rent this size cluster for 3 months of training\"). But that's a mistake. What matters is something more like ~the actual cost to build the cluster. If you want one of the largest clusters in the world, you can't just rent it for 3 months! And moreover, you need the compute for more than just the flagship training run: there will be lots of derisking experiments, failed runs, other models, etc.\n  \n\n\n   To approximate the GPT-4 cluster cost:\n  \n\n\n   \u2022 The\n   \n    public\n   \n\n    estimates\n   \n   suggest the GPT-4 cluster being around 25k A100s.\n  \n\n\n\n\n\n\n     Assuming $1/A100-hour for 2-3 years gives roughly a $500M cost.\n    \n\n\n     Alternatively, you can estimate it as $25k cost per H100, 10k H100s-equivalent, and Nvidia GPUs being around half the cost of a cluster (the rest being power, the physical datacenter, cooling, networking, maintenance personnel, etc.). (For example, this\n     \n      total-cost-of-ownership analysis\n     \n     estimates that around 40% of a large cluster cost is the H100 GPUs itself, and another 13% goes to Nvidia for Infiniband networking. That said, excluding cost of capital in that calculation would mean the GPUs are about 50% of the cost, and with networking Nvidia gets a bit over 60% of the cost of the cluster.)\n    \n\n\n\n   FLOP/$ is improving somewhat for each Nvidia generation, but not a ton. E.g., the H100 -> B100 is likely something like 1.5x FLOP/$: B100s are effectively two H100s stapled together, but retailing for <2x the cost. But the B100 was somewhat of an exception. They are surprisingly cheap, likely because Nvidia\n   \n    wants to crush competition.\n   \n   By contrast, A100s -> H100s weren't much of a FLOP/$ improvement (2x better chip without fp8, roughly 2x the cost), maybe 1.5x if we count fp8 improvements\u2014and that was for a two-year generation.\n  \n\n\n   While I think there are some tailwinds to further FLOP/$ improvements from margin compression, GPUs might also get more expensive as they become massively constrained. Gains from AI chip specialization will continue, but it's not clear to me there will still be game-changing technical improvements to FLOP/$ coming, given chips are already pretty specialized for AI (e.g. specialized for Transformers, and already at fp8/fp4 precision), Moore's Law is glacial these days, and\n   \n    other bottle\n   \n\n    neck components like memory and interconnect\n   \n   are improving more slowly. If you look at\n   \n    Epoch's data,\n   \n   there seems to be less than a 10x in FLOP/$ over the past decade for top ML GPUs, and for the aforementioned reasons if anything I'd expect this to slow down.\n  \n\n\n   Something like a 35%/year improvement in FLOP/$ would give us the 1T cost for the +4 OOM cluster. Maybe FLOP/$ improves faster, but also datacenter capex is going to get more\n  \n\n\n   expensive\u2014simply because you'll need to actually build new power, doing a lot of capex up front, rather than just renting existing depreciated power plants.\n  \n\n\n   These are just very rough numbers anyway. It would be very much within error bars if e.g. the 1T cluster can be done more efficiently and actually yields more like +4.5 OOMs on compute.\n  \n\n\n\n    Cost.\n   \n   An H100 is 700W, but there's a bunch of datacenter power you need (cooling, networking, storage); Semianalysis\n   \n    estimates\n   \n   ~1,400W per H100.\n  \n\n\n   There are some gains to be had on FLOP/Watt, though once we've exhausted the gains from AI chip specialization (see previous footnote), e.g. gone down to the lowest possible precision, these seem somewhat limited (mostly just chip process improvements, which are slow). That said, as power becomes more of a constraint (and thus a larger fraction of costs), chip designs might specialize to more power-efficiency at the costs of FLOPs. Still, there is still the power demand for cooling, networking, storage, and so on (which in the H100 numbers above was already roughly half the power demand).\n  \n\n\n   For these back of the envelope numbers, let's work with 1kW per H100-equivalent here; again these are just rough back-ofthe-envelope calculations. (And if there were an unexpected FLOP/Watt breakthrough, I'd expect the same power expenditure, just bigger OOM compute gains.)\n  \n\n\n\n    Power reference classes.\n   \n   A 10GW cluster run continuously for a year is 87.6 TWh. By comparison, Oregon\n   \n    consumes\n   \n   about 27 TWh of electricity annually, Washington state\n   \n    consumes\n   \n   about 92 TWh annually.\n  \n\n\n   A 100GW cluster run continuously for a year is 876 TWh, while total annual US electricity production is about 4,250 TWh.\n  \n\n\n\n    Click here to return back to the \"training compute\" table.\n   \n\n\n\n\n    Overall compute\n   \n\n\n\n\n    H100-equivalents this year.\n   \n   I estimate Nvidia is going to ship on the order of 5M datacenter GPUs in 2024. A minority of those are B100s, which we'll count as 2x+ H100s. Then there's the other AI chips: TPUs, Trainium, Meta's custom silicon, AMD GPUs, etc.\n  \n\n\n\n    TSMC Capacity.\n   \n   TSMC has capacity for over 150k 5\n   \n    nm\n   \n   wafers per month, is ramping to 100k 3\n   \n    nm wafers\n   \n   per month, and likely another 150\n   \n    k or so\n   \n   7nm wafers per month; let's call it 400k wafers per month in total.\n  \n\n\n   Let's say roughly 35 H100\n   \n    s per wafer\n   \n   (H100s are made on 5nm). At 5-10 million H100-equivalents in 2024, that's 150k-300k wafers per year for annual AI chip production in 2024.\n  \n\n\n   Depending on where in that range and whether we want to count 7nm production, that's about 3-10% of annual leadingedge wafer production.\n  \n\n\n\n    Click here to return back to the \"overall compute\" table.\n   \n\n]]>\n  \n  \n    Social\n    https://www.optispan.life/\n    readwise:01j5nwhnbm900rg55jcen2skjg\n    Mon, 19 Aug 2024 17:56:49 +0000\n    Optispan\n    \n\nOUR MISSION\n\nTo help people stay healthy for the longest time possible\n\nThree core ideas underpin the concept of healthspan optimization:\n\n\n\nA discrete set of biological processes drives much of aging and age-related disease \n\nThese processes are malleable \n\nModifying these processes can delay or prevent age-related diseases and conditions\n\n\n\nBIOLOGY OF AGING\n\nWhy should you care about healthspan?\n\nOur goal is to recover the Lost Decade. The Lost Decade is the 10 or so years that many people spend suffering from poor health and/or disability, often due to a lack of preventative care and poor life choices.\n\nOur stretch goal is to achieve the Longevity Dividend, which refers to not just the recovery of the Lost Decade, but an additional lifespan increase beyond this threshold.\n\n\n\nA BETTER WAY\n\nMedicine today is disease care based on 19th century principles\n\nOptispan\u2019s core focus lies in promoting longevity and healthspan optimization through proactive health measures, rather than in waiting for chronic conditions to manifest. We are creating a science-based and friction-free longevity medicine toolkit to realize this vision.\n\nIN OUR TOOLKIT\n\n\n\nProviders are key\n\nBaseline / Risk profile / Lifestyle\n\nBiological age testing\n\nPersonalized intervention plans\n\nRepeated measurements\n\nHealthspan optimization\n\n\n\n\n\nOptimize-Me\n\nJoin the Optispan movement and embrace the power of geroscience and preventative medicine to help you become an advocate for your own health and wellbeing. Together, we can redefine what it means to age gracefully, breaking the barriers that limit our potential and reimagining the possibilities of a vibrant, healthy life.]]>\n    \n\nOUR MISSION\n\nTo help people stay healthy for the longest time possible\n\nThree core ideas underpin the concept of healthspan optimization:\n\n\n\nA discrete set of biological processes drives much of aging and age-related disease \n\nThese processes are malleable \n\nModifying these processes can delay or prevent age-related diseases and conditions\n\n\n\nBIOLOGY OF AGING\n\nWhy should you care about healthspan?\n\nOur goal is to recover the Lost Decade. The Lost Decade is the 10 or so years that many people spend suffering from poor health and/or disability, often due to a lack of preventative care and poor life choices.\n\nOur stretch goal is to achieve the Longevity Dividend, which refers to not just the recovery of the Lost Decade, but an additional lifespan increase beyond this threshold.\n\n\n\nA BETTER WAY\n\nMedicine today is disease care based on 19th century principles\n\nOptispan\u2019s core focus lies in promoting longevity and healthspan optimization through proactive health measures, rather than in waiting for chronic conditions to manifest. We are creating a science-based and friction-free longevity medicine toolkit to realize this vision.\n\nIN OUR TOOLKIT\n\n\n\nProviders are key\n\nBaseline / Risk profile / Lifestyle\n\nBiological age testing\n\nPersonalized intervention plans\n\nRepeated measurements\n\nHealthspan optimization\n\n\n\n\n\nOptimize-Me\n\nJoin the Optispan movement and embrace the power of geroscience and preventative medicine to help you become an advocate for your own health and wellbeing. Together, we can redefine what it means to age gracefully, breaking the barriers that limit our potential and reimagining the possibilities of a vibrant, healthy life.]]>\n  \n  \n    CoinMarketCap Posts on CoinMarketCap\n    https://coinmarketcap.com/community/post/335064824/\n    readwise:01hvyptf38kkgfwzyz9a4ja0w9\n    Sat, 20 Apr 2024 21:32:58 +0000\n    coinmarketcap.com\n    Cryptos: 2.4M+\n\nExchanges: 753\n\nMarket Cap:\n\n$2.39T\n\n1.93%\n\n24h Vol:\n\n$65.19B\n\n41.24%\n\nDominance: BTC: 53.4% ETH: 15.9%\n\nETH Gas:\n\n8 Gwei\n\n\nAPI\n\n\n\n\nCryptocurrencies\n\nCryptocurrencies\n\nRankingCategoriesGlobal ChartsHistorical SnapshotsBitcoin ETFs\n\nLeaderboards\n\nTrendingRecently AddedGainers & LosersMost Visited\n\nNFT\n\nOverall NFT StatsTop CollectionsUpcoming Sales\n\nOn Chain Data\n\nDex PairsChain RankingHot DEX Pairs\n\nExchanges\n\nSpotDerivativesDEX\n\nCommunity\n\nFeedsTopicsLivesArticles\n\nProducts\n\nPRODUCTS\n\nConverterCMC Labs\nTelegram Bot\nAdvertise\nCrypto API\nSite Widgets\n\nCAMPAIGNS\n\nAirdropsDiamond RewardsLearn & Earn\n\n\nCALENDARS\n\nICO CalendarEvents Calendar\n\nLearn\n\nNewsAcademy\nResearch\nVideos\nGlossary\n\n\nHalving\n\n\n\n\n\n\n\n\nSearch\n\n/\n\nUse CoinMarketCap APP\n\nGet a better and more comprehensive user experience\n\n\n\n\nCryptos: 2.4M+\n\nExchanges: 753\n\nMarket Cap:\n\n$2.39T\n\n1.93%\n\n24h Vol:\n\n$65.19B\n\n41.24%\n\nDominance: BTC: 53.4% ETH: 15.9%\n\nETH Gas:\n\n8 Gwei\n\n\n\nFeed\nTopics\nLivesNew\nArticles\nNotifications\nMy Page\nMore\n\nHomeCommunityPost Detail\n\nCoinMarketCap\n\nPost detail\n\n\n\n\nCoinMarketCap\n\n\n\n\n@CoinMarketCap\n\nSingularityNET, Fetch and Ocean are merging their tokens to create a decentralized artificial superintelligence alliance. Get to know every detail about it by joining this breaking #CMCLive. Set your reminder below! \ud83d\udc47\n\nFETAGIXOCEAN\n\n\ud83d\udea8 SingularityNET, Fetch AI & Ocean Token Merge\n\n\nMarch 27, 2024 at 8:21 AM\n\n\n336\n\n\n970\n\n\n78\n\n\n64\n\n\n51\n\n\n32\n\n\n47\n\n\n52.9K\n\n\n55\n\n\n32\n\n\n1.5K\n\n\n\n\nGuest\n\nType your response here\n\n\n\nBullish\n\n\nBearish\n\nComments (55)\n\nReposts (32)\n\nMost relevant\n\nfelixcepeda8@felixcepeda8_d95mp6\u00b7 Mar 28\n\n\nBearish\n\nReplying to @CoinMarketCap\n\nthis merge is dumb and shouldn\u2019t happen we don\u2019t need a new token!!!\n\n\n47\n\n\n0\n\n\n0\n\n\n47\n\n\ncaptd.@cappy\u00b7 Mar 27\n\nReplying to @CoinMarketCap\n\nI think the superintelligence alliance missed something about $ORAI\n\n\n84\n\n\n1\n\n\n5\n\n\n3\n\n\n0\n\n\n1\n\n\n93\n\n\nfelixcepeda8@felixcepeda8_d95mp6\u00b7 Mar 27\n\n\nBearish\n\nReplying to @CoinMarketCap\n\nso what\u2019s going to happen with my agix tokens because I\u2019m not converting them to anything\n\n\n41\n\n\n6\n\n\n2\n\n\n0\n\n\n0\n\n\n49\n\n\nnavas3@vceppvmrnwuu\u00b7 Apr 3\n\nReplying to @CoinMarketCap\n\nhey\n\n\n0\n\n\n0\n\n\n0\n\n\nnavas3@vceppvmrnwuu\u00b7 Apr 3\n\nReplying to @CoinMarketCap\n\nhi\n\n\n2\n\n\n1\n\n\n0\n\n\n2\n\n\nCoinMarketCap\n\n@CoinMarketCap\n\n74Following12145022Followers\n\nUpcoming Lives\n\nSee More\n\nCoinMarketCap\nAliceCrypto\nGabriel Zani\n\n\ud83c\udf99\ufe0f Weekly Crypto Forecast\n\n\n10:00, Apr 22892 going\n\nSet Reminder\n\n\nThe Moon\nDavinci Jeremie\n\n\ud83c\udf99\ufe0f Carl from the Moon & DaVinci\n\n\n10:00, Apr 23464 going\n\nSet Reminder\n\n\ud83d\udd25 Trending Topics\n\n\n1#BitcoinHalving2#CMCLive3#Runes4#TON5#Token2049\n\nTrending Tokens\n\n\n1$HEXHEX2$WIFdogwifhat3$JTOJito4$WZRDBitcoin Wizards5$POPCATPopcat\n\nRecommended Accounts\n\n\n\nCMC News\n\n\n\n\n@CMC_News\n\n\n\n_Check\u0271ate \ud83d\udfe0\ud83d\udd11\u26a1\u2622\ufe0f\ud83d\udee2\n\n\n\n\n@_Checkmatey_\n\n\n\nCMC DexScan Bot\n\n\n\n\n@cmcdexscanbot\n\nDisclaimer: The data and information contained therein are provided by a third party and CoinMarketCap does not create such data. See full terms\n\nhere]]>\n    Cryptos: 2.4M+\n\nExchanges: 753\n\nMarket Cap:\n\n$2.39T\n\n1.93%\n\n24h Vol:\n\n$65.19B\n\n41.24%\n\nDominance: BTC: 53.4% ETH: 15.9%\n\nETH Gas:\n\n8 Gwei\n\n\nAPI\n\n\n\n\nCryptocurrencies\n\nCryptocurrencies\n\nRankingCategoriesGlobal ChartsHistorical SnapshotsBitcoin ETFs\n\nLeaderboards\n\nTrendingRecently AddedGainers & LosersMost Visited\n\nNFT\n\nOverall NFT StatsTop CollectionsUpcoming Sales\n\nOn Chain Data\n\nDex PairsChain RankingHot DEX Pairs\n\nExchanges\n\nSpotDerivativesDEX\n\nCommunity\n\nFeedsTopicsLivesArticles\n\nProducts\n\nPRODUCTS\n\nConverterCMC Labs\nTelegram Bot\nAdvertise\nCrypto API\nSite Widgets\n\nCAMPAIGNS\n\nAirdropsDiamond RewardsLearn & Earn\n\n\nCALENDARS\n\nICO CalendarEvents Calendar\n\nLearn\n\nNewsAcademy\nResearch\nVideos\nGlossary\n\n\nHalving\n\n\n\n\n\n\n\n\nSearch\n\n/\n\nUse CoinMarketCap APP\n\nGet a better and more comprehensive user experience\n\n\n\n\nCryptos: 2.4M+\n\nExchanges: 753\n\nMarket Cap:\n\n$2.39T\n\n1.93%\n\n24h Vol:\n\n$65.19B\n\n41.24%\n\nDominance: BTC: 53.4% ETH: 15.9%\n\nETH Gas:\n\n8 Gwei\n\n\n\nFeed\nTopics\nLivesNew\nArticles\nNotifications\nMy Page\nMore\n\nHomeCommunityPost Detail\n\nCoinMarketCap\n\nPost detail\n\n\n\n\nCoinMarketCap\n\n\n\n\n@CoinMarketCap\n\nSingularityNET, Fetch and Ocean are merging their tokens to create a decentralized artificial superintelligence alliance. Get to know every detail about it by joining this breaking #CMCLive. Set your reminder below! \ud83d\udc47\n\nFETAGIXOCEAN\n\n\ud83d\udea8 SingularityNET, Fetch AI & Ocean Token Merge\n\n\nMarch 27, 2024 at 8:21 AM\n\n\n336\n\n\n970\n\n\n78\n\n\n64\n\n\n51\n\n\n32\n\n\n47\n\n\n52.9K\n\n\n55\n\n\n32\n\n\n1.5K\n\n\n\n\nGuest\n\nType your response here\n\n\n\nBullish\n\n\nBearish\n\nComments (55)\n\nReposts (32)\n\nMost relevant\n\nfelixcepeda8@felixcepeda8_d95mp6\u00b7 Mar 28\n\n\nBearish\n\nReplying to @CoinMarketCap\n\nthis merge is dumb and shouldn\u2019t happen we don\u2019t need a new token!!!\n\n\n47\n\n\n0\n\n\n0\n\n\n47\n\n\ncaptd.@cappy\u00b7 Mar 27\n\nReplying to @CoinMarketCap\n\nI think the superintelligence alliance missed something about $ORAI\n\n\n84\n\n\n1\n\n\n5\n\n\n3\n\n\n0\n\n\n1\n\n\n93\n\n\nfelixcepeda8@felixcepeda8_d95mp6\u00b7 Mar 27\n\n\nBearish\n\nReplying to @CoinMarketCap\n\nso what\u2019s going to happen with my agix tokens because I\u2019m not converting them to anything\n\n\n41\n\n\n6\n\n\n2\n\n\n0\n\n\n0\n\n\n49\n\n\nnavas3@vceppvmrnwuu\u00b7 Apr 3\n\nReplying to @CoinMarketCap\n\nhey\n\n\n0\n\n\n0\n\n\n0\n\n\nnavas3@vceppvmrnwuu\u00b7 Apr 3\n\nReplying to @CoinMarketCap\n\nhi\n\n\n2\n\n\n1\n\n\n0\n\n\n2\n\n\nCoinMarketCap\n\n@CoinMarketCap\n\n74Following12145022Followers\n\nUpcoming Lives\n\nSee More\n\nCoinMarketCap\nAliceCrypto\nGabriel Zani\n\n\ud83c\udf99\ufe0f Weekly Crypto Forecast\n\n\n10:00, Apr 22892 going\n\nSet Reminder\n\n\nThe Moon\nDavinci Jeremie\n\n\ud83c\udf99\ufe0f Carl from the Moon & DaVinci\n\n\n10:00, Apr 23464 going\n\nSet Reminder\n\n\ud83d\udd25 Trending Topics\n\n\n1#BitcoinHalving2#CMCLive3#Runes4#TON5#Token2049\n\nTrending Tokens\n\n\n1$HEXHEX2$WIFdogwifhat3$JTOJito4$WZRDBitcoin Wizards5$POPCATPopcat\n\nRecommended Accounts\n\n\n\nCMC News\n\n\n\n\n@CMC_News\n\n\n\n_Check\u0271ate \ud83d\udfe0\ud83d\udd11\u26a1\u2622\ufe0f\ud83d\udee2\n\n\n\n\n@_Checkmatey_\n\n\n\nCMC DexScan Bot\n\n\n\n\n@cmcdexscanbot\n\nDisclaimer: The data and information contained therein are provided by a third party and CoinMarketCap does not create such data. See full terms\n\nhere]]>\n  \n  \n    Sufficient Decentralization for Social Networks\n    https://www.varunsrinivasan.com/2022/01/11/sufficient-decentralization-for-social-networks\n    readwise:01htmfs4z77mtqsa0kxfdckncw\n    Thu, 04 Apr 2024 12:01:49 +0000\n    Varun Srinivasan\n    Every year, centralized social networks place more restrictions on what users and developers can do. They seem to believe that limiting choices is the path to a healthy network, while the opposite is probably true. A decentralized social network can challenge this hypothesis by making two powerful promises that centralized networks cannot. They can guarantee that users own a direct relationship with their audience and that developers can always build apps on the network.\n\nCentralized social networks closely control their users\u2019 ability to reach their audience. They highlight some posts and suppress others to increase page views and ad revenue. But reliably reaching an audience is valuable to users and not just in a post-and-get-paid kind of way. For example, Elon Musk\u2019s Twitter following makes it easy for his companies to raise billions from the public. When people discover that companies are restricting access for their own benefit, they are understandably frustrated. They\u2019re even more upset when they realize that companies control their identity and can kick them off the network with no recourse.\n\nNetworks have also had a contentious relationship with developers, who brought in millions of early users. Developers built alternate clients, invented UI paradigms, and even launched billion-dollar gaming companies. But as they grew, the networks realized that they didn\u2019t need developers anymore. Most users were locked in and wouldn\u2019t leave because they\u2019d lose part of their audience. Developer APIs became a liability that reduced revenue and increased complexity, and were limited or turned off completely. Now, only people who had political power within the company could experiment with new ideas.\n\nA decentralized social networking protocol could change this dynamic by ensuring open access to the network. Companies can still make money by offering services, as Gmail does with email and Github does with Git. But decentralizing access ensures that they can\u2019t be monopolistic and ignore users. It creates a market-based approach where the best ideas can compete on equal footing.\n\nSufficient decentralization\n\nA social network achieves sufficient decentralization if two users can find each other and communicate, even if the rest of the network wants to prevent it. This implies that users can always reach their audience, which can only be true if developers can build many clients on the network. If only one client existed, it could stop users from communicating. Achieving this only requires three decentralized features: the ability to claim a unique username, post messages under that name, and read messages from any valid name.\n\nOf course, social networks do more than send messages. For starters, they organize them into a threaded feed, send push notifications, and recommend new users to follow. These features aren\u2019t easy to decentralize, and the list of things that people want will grow faster than the ability to decentralize them. But these features don\u2019t compromise sufficient decentralization, so clients can build them in a centralized way. Email takes a similar approach, where sending messages is part of the protocol, but clients must develop their own spam filters.\n\nSome believe that decentralization requires the entire social network to be on a blockchain. This is unnecessary and even undesirable. Social networks generate petabytes of data every year, which can be very expensive to store on-chain. Blockchains also make it difficult to delete data forever, which is a desirable feature for users. A network design that leverages on-chain systems to decentralize ownership while using off-chain systems for a better user experience is a better path to building social networks.\n\nWe\u2019ve spilled a lot of ink over decentralizing social networks, but most users are still on centralized ones. Why hasn\u2019t this changed already? There are three challenging problems with decentralizing social networks that have slowed adoption: scaling networks, decentralizing the name registry, and building novel social primitives. But for the first time, there are practical solutions for all three problems.\n\nScaling Networks\n\nSocial networks are a series of messages passed between users through a centralized server. An easy way to decrease centralization is to remove the need for a centralized server. Users could choose any server they like to store their messages and sign each one with a public/private key pair1. The public key becomes a unique identifier for the user, and the messages are tamper-proof.\n\n\n\nUsing a social network in a decentralized way should be free and straightforward, but this is difficult in practice. Users want their messages available to all followers, which requires an always on-server in the cloud. A reasonable expectation is that self-hosting will be as complex and expensive as running your own website. But we can\u2019t onboard billions of people by asking everyone to run a server.\n\nThis is where managed hosts come in. These companies host users\u2019 social data, like Gmail and Outlook host email. Managed hosts can offer features that would be impractical for users to run at scale, like a content moderation system. They can provide better user experiences, and we should expect most people to use them instead of running their own server\n\n\n\nA common argument against managed hosts is that they can centralize the network. For instance, popular providers could band together and charge users more for certain messages. Such actions are negative-sum over the long term because they incentivize developers to make new managed hosts and users switch to them. Protocols like email and cryptocurrencies made changing providers easy from day one, which in turn made collusion rare and short-lived.\n\nDecentralizing The Name Registry\n\nA user\u2019s followers need to find the correct host to send and receive messages. A name registry can help map every user\u2019s unique public key to a host URL and a memorable, unique username like @alice. A follower can ask the registry for @alice\u2019s host and receive the correct URL. A decentralized registry that only allows Alice to change this URL protects them against malicious hosts. If a host stops serving their messages, they can modify the registry to point to a new host, and their followers will switch to the new location.\n\nDecentralizing a name registry is difficult, and earlier attempts made difficult tradeoffs. ActivityPub doesn\u2019t provide a way to use a managed host without compromising decentralization. Secure Scuttlebutt allows decentralization but doesn\u2019t allow unique and memorable names, which makes identifying people harder. Keybase implements a registry but in a centralized way.\n\nHowever, smart contracts have finally made decentralized registries possible. Users can make a transaction to a smart contract on a blockchain that performs the functions of a decentralized registry. The contract ensures that only that user can change the URL, and the blockchain provides conflict resolution if two people try to register the same name simultaneously. ENS and Unstoppable Domains have implemented similar systems on Ethereum.\n\n\n\nThe registry is the only part of the network that needs to be synchronized on a blockchain. All other actions can securely happen off-chain by signing them with the key pair. If you receive a message that claims to be from @alice, you can ask the registry for @alice\u2019s public key and verify that the signature came from @alice\u2019s private key.\n\nNovel Social Primitives\n\nUsers don\u2019t just want a decentralized version of an existing social network. What users really want from a new social network is status or entertainment, along with the benefits that decentralization offers. Any new network must offer a compelling way to achieve both, or it will face an uphill battle to get off the ground.\n\nBlockchains have created novel ways to gain status. Being an early user, token holder, or voter confers status on people. Social networks for blockchain users can make it easy for people to generate proofs of such activity. The network could then offer features like token-gated communities, verified badges for NFT holders, and anonymous polls for token holders. The best on-chain systems are also highly composable, so a social feature designed for a standard like ERC-721 automatically works with every new token added to the network.\n\nSuccessful social networks are usually built around a new communication primitive. Facebook had the wall, Twitter had the 140-character tweet and Snapchat had the ephemeral message. The idea maze of things you can do with decentralized identities, blockchains and zk-proofs is large, weird and interesting enough that there are probably many primitives waiting to be discovered. Decentralized social networks should explore this as a way to attract users. Offering a product experience that doesn\u2019t yet exist is far more compelling than a clone of an existing network.\n\nConclusion\n\nCentralized social networks influence every aspect of our lives, and their shortcomings are painfully clear. Improvements in cryptography and blockchains have provided workable solutions to achieve sufficient decentralization. We have a reasonable way to build a decentralized name registry, a hybrid off-chain/on-chain architecture to scale the network, and interesting new social primitives to build on. More importantly, people are unhappy with the status quo and want something better. If you\u2019re an ambitious builder who wants to change the world, this is a great problem space to start working on.]]>\n    Every year, centralized social networks place more restrictions on what users and developers can do. They seem to believe that limiting choices is the path to a healthy network, while the opposite is probably true. A decentralized social network can challenge this hypothesis by making two powerful promises that centralized networks cannot. They can guarantee that users own a direct relationship with their audience and that developers can always build apps on the network.\n\nCentralized social networks closely control their users\u2019 ability to reach their audience. They highlight some posts and suppress others to increase page views and ad revenue. But reliably reaching an audience is valuable to users and not just in a post-and-get-paid kind of way. For example, Elon Musk\u2019s Twitter following makes it easy for his companies to raise billions from the public. When people discover that companies are restricting access for their own benefit, they are understandably frustrated. They\u2019re even more upset when they realize that companies control their identity and can kick them off the network with no recourse.\n\nNetworks have also had a contentious relationship with developers, who brought in millions of early users. Developers built alternate clients, invented UI paradigms, and even launched billion-dollar gaming companies. But as they grew, the networks realized that they didn\u2019t need developers anymore. Most users were locked in and wouldn\u2019t leave because they\u2019d lose part of their audience. Developer APIs became a liability that reduced revenue and increased complexity, and were limited or turned off completely. Now, only people who had political power within the company could experiment with new ideas.\n\nA decentralized social networking protocol could change this dynamic by ensuring open access to the network. Companies can still make money by offering services, as Gmail does with email and Github does with Git. But decentralizing access ensures that they can\u2019t be monopolistic and ignore users. It creates a market-based approach where the best ideas can compete on equal footing.\n\nSufficient decentralization\n\nA social network achieves sufficient decentralization if two users can find each other and communicate, even if the rest of the network wants to prevent it. This implies that users can always reach their audience, which can only be true if developers can build many clients on the network. If only one client existed, it could stop users from communicating. Achieving this only requires three decentralized features: the ability to claim a unique username, post messages under that name, and read messages from any valid name.\n\nOf course, social networks do more than send messages. For starters, they organize them into a threaded feed, send push notifications, and recommend new users to follow. These features aren\u2019t easy to decentralize, and the list of things that people want will grow faster than the ability to decentralize them. But these features don\u2019t compromise sufficient decentralization, so clients can build them in a centralized way. Email takes a similar approach, where sending messages is part of the protocol, but clients must develop their own spam filters.\n\nSome believe that decentralization requires the entire social network to be on a blockchain. This is unnecessary and even undesirable. Social networks generate petabytes of data every year, which can be very expensive to store on-chain. Blockchains also make it difficult to delete data forever, which is a desirable feature for users. A network design that leverages on-chain systems to decentralize ownership while using off-chain systems for a better user experience is a better path to building social networks.\n\nWe\u2019ve spilled a lot of ink over decentralizing social networks, but most users are still on centralized ones. Why hasn\u2019t this changed already? There are three challenging problems with decentralizing social networks that have slowed adoption: scaling networks, decentralizing the name registry, and building novel social primitives. But for the first time, there are practical solutions for all three problems.\n\nScaling Networks\n\nSocial networks are a series of messages passed between users through a centralized server. An easy way to decrease centralization is to remove the need for a centralized server. Users could choose any server they like to store their messages and sign each one with a public/private key pair1. The public key becomes a unique identifier for the user, and the messages are tamper-proof.\n\n\n\nUsing a social network in a decentralized way should be free and straightforward, but this is difficult in practice. Users want their messages available to all followers, which requires an always on-server in the cloud. A reasonable expectation is that self-hosting will be as complex and expensive as running your own website. But we can\u2019t onboard billions of people by asking everyone to run a server.\n\nThis is where managed hosts come in. These companies host users\u2019 social data, like Gmail and Outlook host email. Managed hosts can offer features that would be impractical for users to run at scale, like a content moderation system. They can provide better user experiences, and we should expect most people to use them instead of running their own server\n\n\n\nA common argument against managed hosts is that they can centralize the network. For instance, popular providers could band together and charge users more for certain messages. Such actions are negative-sum over the long term because they incentivize developers to make new managed hosts and users switch to them. Protocols like email and cryptocurrencies made changing providers easy from day one, which in turn made collusion rare and short-lived.\n\nDecentralizing The Name Registry\n\nA user\u2019s followers need to find the correct host to send and receive messages. A name registry can help map every user\u2019s unique public key to a host URL and a memorable, unique username like @alice. A follower can ask the registry for @alice\u2019s host and receive the correct URL. A decentralized registry that only allows Alice to change this URL protects them against malicious hosts. If a host stops serving their messages, they can modify the registry to point to a new host, and their followers will switch to the new location.\n\nDecentralizing a name registry is difficult, and earlier attempts made difficult tradeoffs. ActivityPub doesn\u2019t provide a way to use a managed host without compromising decentralization. Secure Scuttlebutt allows decentralization but doesn\u2019t allow unique and memorable names, which makes identifying people harder. Keybase implements a registry but in a centralized way.\n\nHowever, smart contracts have finally made decentralized registries possible. Users can make a transaction to a smart contract on a blockchain that performs the functions of a decentralized registry. The contract ensures that only that user can change the URL, and the blockchain provides conflict resolution if two people try to register the same name simultaneously. ENS and Unstoppable Domains have implemented similar systems on Ethereum.\n\n\n\nThe registry is the only part of the network that needs to be synchronized on a blockchain. All other actions can securely happen off-chain by signing them with the key pair. If you receive a message that claims to be from @alice, you can ask the registry for @alice\u2019s public key and verify that the signature came from @alice\u2019s private key.\n\nNovel Social Primitives\n\nUsers don\u2019t just want a decentralized version of an existing social network. What users really want from a new social network is status or entertainment, along with the benefits that decentralization offers. Any new network must offer a compelling way to achieve both, or it will face an uphill battle to get off the ground.\n\nBlockchains have created novel ways to gain status. Being an early user, token holder, or voter confers status on people. Social networks for blockchain users can make it easy for people to generate proofs of such activity. The network could then offer features like token-gated communities, verified badges for NFT holders, and anonymous polls for token holders. The best on-chain systems are also highly composable, so a social feature designed for a standard like ERC-721 automatically works with every new token added to the network.\n\nSuccessful social networks are usually built around a new communication primitive. Facebook had the wall, Twitter had the 140-character tweet and Snapchat had the ephemeral message. The idea maze of things you can do with decentralized identities, blockchains and zk-proofs is large, weird and interesting enough that there are probably many primitives waiting to be discovered. Decentralized social networks should explore this as a way to attract users. Offering a product experience that doesn\u2019t yet exist is far more compelling than a clone of an existing network.\n\nConclusion\n\nCentralized social networks influence every aspect of our lives, and their shortcomings are painfully clear. Improvements in cryptography and blockchains have provided workable solutions to achieve sufficient decentralization. We have a reasonable way to build a decentralized name registry, a hybrid off-chain/on-chain architecture to scale the network, and interesting new social primitives to build on. More importantly, people are unhappy with the status quo and want something better. If you\u2019re an ambitious builder who wants to change the world, this is a great problem space to start working on.]]>\n  \n  \n    N.Y.C. to L.A. to N.Y.C. to L.A., Ad Infinitum | The New Yorker\n    https://www.newyorker.com/magazine/2016/02/01/n-y-c-to-l-a-to-n-y-c-to-l-a-ad-infinitum\n    readwise:01hscy6dq5ez88bn63nrj6edz0\n    Wed, 20 Mar 2024 03:24:06 +0000\n    The New Yorker\n    \nIllustration by Walter Green\n\nWhen I realized that New York was a cesspit filled with the viscera of broken dreams, I decided that the time had come for me to move to beautiful, sunny Los Angeles.\n\nWhen I arrived in L.A. and realized that it was creatively dead, had a withered husk for a soul, and considered ombr\u00e9 the height of culture, I took the first plane back to New York.\n\nOf course, my plane landed in a sea of overstressed, overworked rat kings fornicating with cockroaches and three of my exes. So I bought a used Prius and drove cross-country straight to L.A., because in L.A. people go on hikes.\n\nOn my first hike in L.A., I had to talk to someone who\u2019d never read Joan Didion and who\u2019d had\u2014get this\u2014plastic surgery. Before he could say \u201cjuice cleanse,\u201d I had ridden a fixed-gear bicycle right back to the Big Apple.\n\nMy bike wouldn\u2019t fit in my two-inch-wide urine-soaked apartment in Sunset Park, so I found someone to take over my lease and I rode a Segway all the way to Hollywood, eating local fruits and reciting positive affirmations as I rolled merrily along.\n\nAt my first party in Los Angeles, I heard the word \u201cagent\u201d more than fifteen thousand times. (I tried to keep a tally, but my fingers started bleeding, so I stopped.) People went on \u201cgenerals\u201d and never returned. I knew I needed to get back to where the real people were, the people of substance and letters, who understood the Struggle.\n\nSome content could not be imported from the original document. View content \u2197 \n\nSo I took the secret subway train that goes from L.A. to New York. It was O.K. until 3:30 P.M., when a gang of youths attacked me, emotionally. Somehow I arrived in one piece, but it was the middle of winter, so I sat alone in my apartment until spring. During that time, my hair fell out and my skin fell off.\n\nI hitchhiked to L.A. at the first opportunity. When I arrived, the people were sun-kissed and the rampant depression was barely noticeable compared with New York. You can hide all manner of mental illness with a solid tan and veneers. I hopped in my car, got on the 405, and headed to the beach. I was stuck in traffic for six years.\n\nBy the time I got back to New York, I was very old. I was twenty-seven. I was too old for the constant partying I assumed people did. I was too old to keep pretending I\u2019d read all the articles and listened to all the bands. Pretending to like things was a young person\u2019s game. I just needed a change.\n\nAnd L.A., city of vapid angels, provided that change. No one cared if I\u2019d read anything or listened to anything, or whether I even had eyes or ears, as long as I didn\u2019t get the part of Surprised Waitress No. 2 over them. Everything was fine until all the yoga made my bones dissolve.\n\nSkinless and boneless, I jiggled back to New York, but everyone kept making me feel so ashamed of being a blob. I threw on my comfiest sweatpants, poured what was left of me into a Vitamix, and shipped myself to L.A.\n\nHalfway between New York and L.A., I imploded. I am so much happier now. \u2666]]>\n    \nIllustration by Walter Green\n\nWhen I realized that New York was a cesspit filled with the viscera of broken dreams, I decided that the time had come for me to move to beautiful, sunny Los Angeles.\n\nWhen I arrived in L.A. and realized that it was creatively dead, had a withered husk for a soul, and considered ombr\u00e9 the height of culture, I took the first plane back to New York.\n\nOf course, my plane landed in a sea of overstressed, overworked rat kings fornicating with cockroaches and three of my exes. So I bought a used Prius and drove cross-country straight to L.A., because in L.A. people go on hikes.\n\nOn my first hike in L.A., I had to talk to someone who\u2019d never read Joan Didion and who\u2019d had\u2014get this\u2014plastic surgery. Before he could say \u201cjuice cleanse,\u201d I had ridden a fixed-gear bicycle right back to the Big Apple.\n\nMy bike wouldn\u2019t fit in my two-inch-wide urine-soaked apartment in Sunset Park, so I found someone to take over my lease and I rode a Segway all the way to Hollywood, eating local fruits and reciting positive affirmations as I rolled merrily along.\n\nAt my first party in Los Angeles, I heard the word \u201cagent\u201d more than fifteen thousand times. (I tried to keep a tally, but my fingers started bleeding, so I stopped.) People went on \u201cgenerals\u201d and never returned. I knew I needed to get back to where the real people were, the people of substance and letters, who understood the Struggle.\n\nSome content could not be imported from the original document. View content \u2197 \n\nSo I took the secret subway train that goes from L.A. to New York. It was O.K. until 3:30 P.M., when a gang of youths attacked me, emotionally. Somehow I arrived in one piece, but it was the middle of winter, so I sat alone in my apartment until spring. During that time, my hair fell out and my skin fell off.\n\nI hitchhiked to L.A. at the first opportunity. When I arrived, the people were sun-kissed and the rampant depression was barely noticeable compared with New York. You can hide all manner of mental illness with a solid tan and veneers. I hopped in my car, got on the 405, and headed to the beach. I was stuck in traffic for six years.\n\nBy the time I got back to New York, I was very old. I was twenty-seven. I was too old for the constant partying I assumed people did. I was too old to keep pretending I\u2019d read all the articles and listened to all the bands. Pretending to like things was a young person\u2019s game. I just needed a change.\n\nAnd L.A., city of vapid angels, provided that change. No one cared if I\u2019d read anything or listened to anything, or whether I even had eyes or ears, as long as I didn\u2019t get the part of Surprised Waitress No. 2 over them. Everything was fine until all the yoga made my bones dissolve.\n\nSkinless and boneless, I jiggled back to New York, but everyone kept making me feel so ashamed of being a blob. I threw on my comfiest sweatpants, poured what was left of me into a Vitamix, and shipped myself to L.A.\n\nHalfway between New York and L.A., I imploded. I am so much happier now. \u2666]]>\n  \n\n\n", "creation_timestamp": "2026-07-25T18:32:18.071958Z"}