Podcasts about Palantir

The investigative journalist Lucas Amin reports on how the tech company Palantir won a £330m contract with the NHS … and what happened once its software was introduced. Help support our independent journalism at theguardian.com/infocus

────────────────────────────────────────[00:02:09]House Passes $1.5 Trillion NDAA With Israeli Military Merger — Only Seven Republicans Voted NoJosh Brechen, Tim Burchard, Eli Crane, Harriet Hageman, Anna Paulina Luna, Thomas Massey, and Chip Roy; no debate and no separate vote on the merger provision.────────────────────────────────────────[00:14:05]The NDAA Gives Israel an Executive Agent Inside the Pentagon With Precedent Authority Over US Defense OfficialsNo other US ally has this; the agent could overrule offices like the Defense Technology Security Administration; Kucinich: not a merger, a takeover.────────────────────────────────────────[00:20:57]Netanyahu Publicly Took Credit for the NDAA Provision — Puts Defense Department Above State DepartmentRuns through the whole government; anyone inside DOD who pushes back can be overruled; Massey: no debate, no vote, no representation.────────────────────────────────────────[00:46:08]23,380 American Jews Serve in the IDF vs. 15,000 in the US Army — Britain and Canada Show the Same PatternBritish Jews: 2,069 in IDF, 180 in British Army; Canadian Jews: 1,542 in IDF, 680 in Canadian; Israel commands 11.5x the loyalty of the UK and 14x that of Germany.────────────────────────────────────────[00:48:10]Ron Lauter, Head of World Jewish Congress and Kevin Warsh's Father-in-Law, Threatens to Destroy Any Anti-Zionist PoliticianHe pledged to fund opponents and demand FARA registration; FCC chair Brendan Carr's wife is an executive at Palantir.────────────────────────────────────────[01:10:50]Trump's Ultimatum: For Every Ship Shot at in the Strait, He Will Destroy One Bridge or Power PlantTargeting civilian infrastructure punitively is a war crime; he made no equivalent promise for every American life taken.────────────────────────────────────────[01:19:24]Trump Called the War a Skirmish and Bragged It Only Killed 18 US SoldiersHe claimed every soldier died saying they can't let Iran have a nuclear weapon; they were there because he ordered them; he had already claimed to destroy Iran's nuclear program.────────────────────────────────────────[01:45:36]The Oil Crack Spread Hit $70 a Barrel — All-Time Record; Prior to the War It Was $10-15Crack spread is refinery profit margin; at $70 it exceeds the pre-war price of crude itself; Goldman Sachs warns oil could reach $120.────────────────────────────────────────[01:55:22]Median Household Income Would Be $40,000 Higher Today If the US Had Stayed on the Gold StandardSteve Forbes: growth rates declined 33% since abandoning the standard; gold is the constant — when its price changes, the currency's value has changed.────────────────────────────────────────[01:56:07]Fed Chair Kevin Warsh Plans to Change the Inflation Yardstick to Hide Rising Prices From Trump30-year Treasury yield above 5% longer than any point since 2007; Shiller P/E in the low 40s vs. low 30s at the 1929 crash; interest payments approach $1 trillion per year. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

────────────────────────────────────────[00:02:09]House Passes $1.5 Trillion NDAA With Israeli Military Merger — Only Seven Republicans Voted NoJosh Brechen, Tim Burchard, Eli Crane, Harriet Hageman, Anna Paulina Luna, Thomas Massey, and Chip Roy; no debate and no separate vote on the merger provision.────────────────────────────────────────[00:14:05]The NDAA Gives Israel an Executive Agent Inside the Pentagon With Precedent Authority Over US Defense OfficialsNo other US ally has this; the agent could overrule offices like the Defense Technology Security Administration; Kucinich: not a merger, a takeover.────────────────────────────────────────[00:20:57]Netanyahu Publicly Took Credit for the NDAA Provision — Puts Defense Department Above State DepartmentRuns through the whole government; anyone inside DOD who pushes back can be overruled; Massey: no debate, no vote, no representation.────────────────────────────────────────[00:46:08]23,380 American Jews Serve in the IDF vs. 15,000 in the US Army — Britain and Canada Show the Same PatternBritish Jews: 2,069 in IDF, 180 in British Army; Canadian Jews: 1,542 in IDF, 680 in Canadian; Israel commands 11.5x the loyalty of the UK and 14x that of Germany.────────────────────────────────────────[00:48:10]Ron Lauter, Head of World Jewish Congress and Kevin Warsh's Father-in-Law, Threatens to Destroy Any Anti-Zionist PoliticianHe pledged to fund opponents and demand FARA registration; FCC chair Brendan Carr's wife is an executive at Palantir.────────────────────────────────────────[01:10:50]Trump's Ultimatum: For Every Ship Shot at in the Strait, He Will Destroy One Bridge or Power PlantTargeting civilian infrastructure punitively is a war crime; he made no equivalent promise for every American life taken.────────────────────────────────────────[01:19:24]Trump Called the War a Skirmish and Bragged It Only Killed 18 US SoldiersHe claimed every soldier died saying they can't let Iran have a nuclear weapon; they were there because he ordered them; he had already claimed to destroy Iran's nuclear program.────────────────────────────────────────[01:45:36]The Oil Crack Spread Hit $70 a Barrel — All-Time Record; Prior to the War It Was $10-15Crack spread is refinery profit margin; at $70 it exceeds the pre-war price of crude itself; Goldman Sachs warns oil could reach $120.────────────────────────────────────────[01:55:22]Median Household Income Would Be $40,000 Higher Today If the US Had Stayed on the Gold StandardSteve Forbes: growth rates declined 33% since abandoning the standard; gold is the constant — when its price changes, the currency's value has changed.────────────────────────────────────────[01:56:07]Fed Chair Kevin Warsh Plans to Change the Inflation Yardstick to Hide Rising Prices From Trump30-year Treasury yield above 5% longer than any point since 2007; Shiller P/E in the low 40s vs. low 30s at the 1929 crash; interest payments approach $1 trillion per year. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

What are we supposed to make of Palantir — a company whose software has helped organizations save lives, and end them? And what of CEO Alex Karp's warnings that AI could upend American democracy? Journalist Michael Steinberger spent six years reporting on Karp for his biography, The Philosopher in the Valley: Alex Karp, Palantir, and the Rise of the Surveillance State. He tells Oz that Alex Karp, the former progressive, is a provocateur who embraces the complexity of Palantir’s work and reputation. Additional Reading: The Philosopher in the Valley: Alex Karp, Palantir, and the Rise of the Surveillance State | Simon & Schuster See omnystudio.com/listener for privacy information.

Inside the growing U.S.–Israeli military partnership, AI surveillance technology, data centers, cybersecurity firms, and political lobbying are becoming increasingly connected. In this episode, investigative journalist and YouTube creator Tommy G discusses the proposed expansion of U.S.–Israel defense integration, the role of artificial intelligence and cyber warfare, Israeli settlements in the West Bank, surveillance companies such as Palantir and Flock Safety, and concerns about privacy, censorship, and government overreach. Tommy also explains why he expanded his reporting beyond crime and street documentaries to cover Gaza, Palestine, Israel, foreign influence in American politics, AIPAC campaign spending, AI-generated political propaganda, license-plate tracking, and the rapid growth of the surveillance state. Topics discussed include: • U.S.–Israel military and technology integration • AI surveillance and cyber warfare • Palantir, Flock Safety, and data privacy • Israeli cybersecurity companies and U.S. data centers • AIPAC lobbying and campaign spending • Gaza, Palestine, and West Bank settlements • Government surveillance and constitutional rights • Artificial intelligence in modern warfare • Free speech, censorship, and political influence • Whether public pressure can still change government policy This conversation contains strong opinions, allegations, and disputed claims from the participants. Viewers are encouraged to research the legislation, statistics, companies, and historical events discussed and reach their own conclusions. Go Support Tommy! YouTube: @TommyGMcGee Podcast: @thetommygshow IG: https://www.instagram.com/tommygmcgee/ Join The Patreon For Bonus Content! https://www.patreon.com/theconnectshow 00:00 Opening: Anti-Israel Sentiment & US-Israel Alliance 03:30 Concerns Over Merging US and Israeli Militaries 05:30 Spying, Surveillance Tech, and US Risks 08:00 Tommy G's Background: Hustle, Work Ethic, and YouTube 10:30 Why Talk About Politics and Current Events? 13:20 Facing Backlash and Threats for Speaking Out 15:30 Confronting Propaganda and Irreconcilable Bubbles 18:00 Defining Truth Amid the US-Israel Debate 21:30 Land Theft and Settlements in the West Bank 27:00 Historical Parallels: Land Theft and Modern Day Policies 30:00 Government Policies and Systemic Oppression 32:45 Why Americans Should Care About Palestine 35:00 Testing Surveillance State in Palestine & Its Spread 39:00 US Politics, Data Centers, & Israeli Tech Influence 43:30 Flock Cameras and Surveillance Concerns in the US 47:30 Government Overreach, Privacy, and Rights Erosion 51:00 Slippery Slope: Surveillance and Citizen Rights 54:00 Big Government, Corruption, and Propaganda 57:00 Hope, Pressure, and The Power of Social Change 59:00 Closing Remarks & Tommy G's Impact Learn more about your ad choices. Visit podcastchoices.com/adchoices

Tuesday, July 21, 2026 Today, a federal judge paused the merger of Paramount/Skydance and Warner Bros. Discovery pending litigation filed by state attorneys general; Troy Jackson has all but sewn up the nomination to replace Graham Platner on the ballot in Maine; Lindsey Graham's sister Darline Nardone will run for her dead brother's seat in the August 11th special primary election; the FBI not only subpoenaed New York Times journalists but members of their families as well; Marco Rubio claims that Cuba and Iran are funding Antifa; ICE shared Medicaid data with Palantir illegally; Trump PACs are paying tens of millions of dollars in legal bills for the president; Olympian Davey Hearn filed a motion to dismiss the reflecting pool charges against him arguing that the government destroyed exculpatory evidence; plus Allison delivers your Good News. Thank You, Smalls For a limited time, get 60% off your first order, plus free shipping and free treats for life, when you head to Smalls.com/DAILYBEANS The Daily Beans is proud to partner with Miles Taylor and our friends at DEFIANCE.org For a limited time, members of the Daily Beans community can receive a FREE 3-month full membership to DEFIANCE.org and gain access to one of the fastest-growing pro-democracy movements in America. Join here: https://www.defiance.org/beans Join The Daily Beans and give a gift today to ensure The Trevor Project can continue its crucial work in the face of continued challenges. Donate to The Trevor Project - Daily Beans Podcast The Latest Breakdown→ Epstein Survivor Recounts Meeting With Todd Blanche StoriesLindsey Graham's Sister, Darline Graham, Says She Will Run to Succeed Him | The New York Times Troy Jackson has effectively secured the Maine Senate Democratic nomination | POLITICO ICE shared Medicaid data it wasn't supposed to have with Palantir | NPR Rubio urges international counterterrorism crackdown on the far-left | ABC News Trump's PACs spend millions on legal bills as his personal court battles continue | MS NOW Trump Administration Sought Phone Records of Times Journalists and Their Relatives | The New York Times Trump administration should preserve Reflecting Pool evidence, judge says | News From The States Judge pauses Paramount-Warner merger | NBC NewsGood TroubleTriumphal Arch - Section 106 Assessment of Effect and Draft Programmatic Agreement Veterans and relatives see no place for Trump's arch near Arlington National Cemetery | NPR →Help save Texas from Ken Paxton! →Urge Democrats to Oppose and Stop Trump's Crypto Corruption | Indivisible Guide →Defiance.org/beans →Show up for our Libraries - action.ala.org →Stand With Minnesota →ICE List  →iceout.org Good Newsdana-goldbergs-southwest-funnyfest Oct 9 -Email Dana@DanaGoldberg.com for sponsorship informationTickets for Dana Goldberg: Outrageous - Sep 23 - Den Theater - Chicago  →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com →Email Dana LGBTQ Owned eating establishments in your area - hello@mswmedia.com Subject: “Dana's Project” Subscribe to the MSW YouTube Channel - MSW Media - YouTube Our Donation Links The Trevor Project - trevorproject.org/beans Blue Wave California - https://secure.actblue.com/donate/msw-bwc Donate to Public Citizen - https://citizen.org/beans/ Donate to It Gets Better / The Daily Beans Fundraiser Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans in support of Human Rights Campaign http://onecau.se/_ekes71National Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG - fedoath@pm.me Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The merging of big-technology with the CIA, and general intelligence community, alongside of social and mainstream media, is well-established in both fact and conspiracy lore. However, tracking down the origins of companies like Palantir, Axonius, OpenAI, ShieldAI, Flock Safety, etc., traces the origin of this system of total surveillance mostly to Israel, though countries like China play a role too - though they have worked heavily with Google. Many of the companies involved also derive their names from mythical realms and draw upon the inspiration of the all-seeing eye. Now that eye is infiltrating classrooms. Nvidia-backed Figure AI has been pushed by the White House directly, with its humanoid robot. Now the New York State Salamanca City Central School District is introducing Sally, a lifelike silicone teacher who will know students not by name but ID number. Sally is made by Reealbotix, which draws heavily from the language models of OpenAI, Meta and Google. Two are their hyper-realistic robots were given Hebrew names: Aria and David. Besides robotics, the U.S. has spent $30 billion to replace paper with digital devices in schools. This has reportedly led to a noticeable decline in cognitive ability among Gen Z. Although countries like Japan are famous for electronics, and have implemented similar policies in schools, Japanese students still outperform American students in most areas. Could this mean that perhaps the issue is far more related to effort and study than it is to technology? Then again, according to PISA (Programme for International Student Assessment), Japan had the lowest of all OECD (Organisation for Economic Co-operation and Development) countries for screen time. A study form the University of Tokyo also found that using paper strengthened brain activity more than screens, which has contributed to some schools taking a hybrid approach -- just like with gasoline and electric vehicles.*The is the FREE archive, which includes advertisements. If you want an ad-free experience, subscribe below.

Palantir, la empresa que proporciona a diferentes gobiernos sofware para vigilar y controlar a los ciudadanos, ha llegado a España. Lo ha hecho en secreto y sin hacer ruido...

In today's Cloud Wars Minute, I preview the coming wave of Q2 earnings while highlighting the extraordinary growth reshaping cloud computing. Highlights 00:03 — We're on the verge of having a lot of calendar Q2 financial results released, so just in advance of that, I wanted to offer a snapshot of where things stand now regarding the world's hottest cloud and AI vendors. Right now, we've got Palantir in the number one spot, Google Cloud number two, Oracle number three. 00:42 — I've also got a chart in there showing backlog, or RPO, which is future booked business that's fully contracted, fully committed, among the four hyperscalers that now totals over $2 trillion. But in the here and now, here's where it stands for the Cloud Wars Top 10 companies. Palantir is in the number one spot for Q1. 01:56 — We've got Microsoft with an enormous performance here: 29% growth and $54.5 billion in quarterly cloud revenue. AWS had a very strong quarter: 28% growth and $37.6 billion in revenue. Salesforce is in the number nine spot with 13% growth, while OpenAI remains an estimate because it is not yet publicly traded. 03:05 — You know, you see some of these numbers, and as I referred to a moment ago about the backlog numbers, which are truly just mind-bending, we become immune to being amazed by the size and the volume here. I do not throw around the phrase "the greatest growth market the world has ever known" lightly. 03:55 — The former applications companies are now racing to become agentic companies and data companies. Huge change and transformation within the Cloud Wars Top 10 is helping customers participate in, succeed in, and potentially thrive in the AI economy. I don't expect any massive changes in this lineup, but the growth numbers will be very interesting over the next few weeks. Visit Cloud Wars for more.

Se llama Alex Karp. Es el director ejecutivo de Palantir, la empresa de software militar y de vigilancia más relevante del mundo. Hijo de madre afroamericana, artista y activista por los derechos civiles, y de padre judío, pediatra, Alex Karp es una de las caras más visibles de Silicon Valey reorganizando la política del mundo. Xavi Orri y Mario Roehrich, editores de Página Intenacional, nos hablan de su vida antes de convertirse en quien proporciona herramientas de vigilancia a los Estados occidentales de mayor peso.

Polymarket isn't just a betting app — it might be the newest branch of the surveillance state. This week on Conspiracy Social Club, we break down journalist Whitney Webb's bombshell investigation tying Polymarket's origins to Palantir, Peter Thiel, DARPA's Information Awareness Office, and the Pentagon's decades-long obsession with predictive markets. We trace the lineage from John Poindexter's Iran-Contra-linked "Policy Analysis Market" all the way to today's prediction-market boom — plus the Zuckerberg and Bancor connections nobody's talking about. Then things get heated: Trump's claims of a massive Chinese data breach exposing 220 million voter profiles kicks off a full-blown 2020 election fight — FISA warrants, Carter Page, Thomas Massie's "Deep Throat" theory, election recounts in Arizona and Georgia, mail-in ballot security, and whether democracy itself is already broken. As always, it's not a debate without chaos — comment of the week, TRT talk, and way too many tangents. Get in the comments and let us know where you stand.

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

On the Record with Christian Briggs – Palantir's expanding role in artificial intelligence, digital identity, surveillance, and data analytics reshapes how governments and corporations make decisions. The investigation examines benefits in security, healthcare, logistics, and emergency response while confronting urgent concerns about privacy, transparency, accountability, civil liberties, and the future of digital governance worldwide...

Stewart Alsop sits down with investor and entrepreneur Adnan Hassan on the Crazy Wisdom Podcast to explore his thesis on creating a small state asset class, using evolutionary insights from asteroids, dinosaurs, and mycelium as a framework for understanding resilient systems. Hassan brings his background in Silicon Valley technology, New York and Washington finance, and sovereign funds—including senior leadership roles at the World Bank—to explain why 162 of the world's 200 states are actually small states with populations under 12 million, and why these distributed, autonomous entities might be best positioned to survive the coming global shocks from AI, currency disruption, and the wobbling international order. For more information about Hassan's work, visit www.sac-holding.com (SAC stands for Small State Asset Class), where you can find two-minute videos explaining his approach to building this new financial architecture.Timestamps00:00 Introduction and the asteroid, dinosaur, mycelium thesis as a framework for understanding evolutionary survival patterns across billions of years05:00 Global order institutions are wobbling while currency systems evolve and AI emerges, creating simultaneous shocks that favor adaptable networked systems over large centralized structures10:00 Small states defined as populations under 12 million represent 162 of 200 global economies, contradicting assumptions that most nations are large centralized powers15:00 States behave as selfish entities seeking regulatory control while individuals seek autonomy, creating tension as the Westphalian system undergoes fundamental transformation20:00 Cooperation versus competition in human systems, examining how KYC requirements and state surveillance are expanding globally including in America and Argentina25:00 Small states are most interested in rule-based global order because they need protection from larger powers, unlike powerful nations that prefer unconstrained action30:00 Of the twenty richest countries by per capita GDP, seventeen are small states, yet no small state asset class exists in financial markets35:00 Uncorrelated assets provide diversification protection for investors, while small states offer geographic distribution across Caribbean, Africa, Europe, Gulf, and Pacific regions40:00 Cross-border family business collaboration between small states will increase, leading to knowledge sharing and a proposed Davos for small states event45:00 The individual sits at the core of this framework, with AI enabling creative minds in small places to access world-class resources previously impossible50:00 Demonstration of accessible technology costing only ten dollars shows how AI removes barriers, allowing creativity to become the distinguishing factor for entrepreneurs globallyKey Insights1. Adnan Hassan presents a thesis grounded in billions of years of evolutionary data, arguing that systems which survive major shocks share common characteristics: they are autonomous, networked, cooperative, resilient, and lack single points of failure. He uses the asteroid strike that killed the dinosaurs as his central metaphor, noting that while massive dinosaurs went extinct, smaller organisms like mycelium, ants, bees, and marsupials survived because of their distributed and adaptable nature. Hassan believes we are currently experiencing a similar asteroid-level shock to our global systems through the simultaneous disruption of the rule-based global order, currency systems, and artificial intelligence, all happening at once over the next three to five years.2. Hassan identifies 162 out of 200 global states and economies as small states, defined as having populations under 12 million people. This number surprises most people, including sophisticated observers who typically guess around 60 or 70. Even more striking, 17 of the 20 richest countries by per capita GDP are small states, representing 85 percent of the wealthiest nations. These small states have disproportionate resources to deploy internationally and the greatest interest in maintaining a rule-based global order since they have the most to lose from chaos and cannot rely on size or military power for protection.3. The current global institutional framework established after World War Two, including the UN, IMF, World Bank, and WTO, is fundamentally wobbling and reaching the end of an era. Hassan argues that states are inherently selfish creatures addicted to regulatory sovereignty and control, but the systems designed to give these states structure and credibility are now failing. This represents the first major restructuring of the global order since the post-World War Two period, which itself followed 400 years of colonial systems. The transition period will be characterized by significant chaos and convulsions throughout the global system.4. Hassan advocates for creating a new small states asset class in financial markets, which does not currently exist despite small states representing the majority of countries and the wealthiest per capita economies. This asset class would provide large institutional investors like pension funds and sovereign wealth funds with globally diversified, potentially uncorrelated assets while simultaneously supporting political and economic structures that embody the evolutionary principles of survival through distributed, autonomous, networked cooperation. The small states asset class represents both sound evolutionary strategy and pragmatic investment opportunity.5. Technology without philosophy is efficiency without purpose, a concern Hassan raised as early as 1994 when he helped prototype the first electronic trading market on the internet. He witnessed the naive optimism of Silicon Valley technologists who believed simply throwing tools over the wall would create a better world, but this approach made both good and bad activities more efficient. Social media demonstrated this danger by efficiently creating disruption and loss of trust in political systems. Hassan warns that the same mistake is being made with AI, where powerful tools are being deployed without adequate philosophical framework or consideration of consequences.6. Small states and their leading families will find more common language and shared understanding with each other across geographic boundaries than with larger neighboring states. A family business in Montevideo has an easier conversation with counterparts in Singapore or New Zealand than with businesses in Sao Paulo because small state actors recognize each other's unique realities and circumstances. Hassan plans to create a Davos for small states in 2027 to facilitate this knowledge sharing among the mycelium colony, allowing different nodes to exchange innovations and strategies across the distributed global network of small state actors.7. The optimistic future involves unleashing individual creativity globally by giving people access to AI-enabled tools that provide world-class legal, financial, and consulting advice in their language of choice. The solopreneur can now become a conglomerate, with individuals no longer constrained by lack of access to execution machinery. Hassan envisions young people in places like Gabon, Swaziland, or Uruguay having the same access to sophisticated business infrastructure as those in traditional power centers, with the distinguishing factor being creativity of mind rather than geographic or institutional privilege. Small states can pivot faster on regulatory frameworks, sometimes achieving in a dinner meeting what takes large states three years of legislative, executive, and judicial wrangling.

Are AI companies becoming targets? Why is DeepSeek suddenly worth $52 billion? Is Mira Murati bringing OpenAI back to its original mission? And why has Oracle's massive AI investment led to a credit downgrade? On Hashtag Trending for Friday, July 17, 2026, host Jim Love covers four major developments shaping the future of artificial intelligence. The episode begins with growing security concerns across the AI industry. According to reporting from The Wall Street Journal, threats against AI executives are increasing, prompting companies including Palantir, Oracle, Salesforce, and Anthropic to dramatically expand executive protection. The story examines attacks and threats involving Anthropic and OpenAI CEO Sam Altman, along with growing concerns that fears over AI, jobs, copyright, the environment, and society are creating new risks for technology leaders. Next, Reuters reporting reveals that DeepSeek is now valued at approximately $52 billion. While far below the valuations of OpenAI or Anthropic, the real story is what billions in new funding could mean for China's AI ambitions. Jim explores how companies including Qwen, Kimi, and Zhipu AI could benefit if investors begin backing Chinese frontier AI models on a much larger scale. The third story looks at former OpenAI CTO Mira Murati, whose new company, Thinking Machines Lab, has released its first nearly one-trillion-parameter open-weight AI model. Jim explains why the announcement may represent a return to OpenAI's original philosophy of making powerful AI broadly available instead of concentrating control in a handful of technology giants. Finally, Oracle receives a rare credit downgrade from S&P Global, which says it underestimated the scale and financial risk of Oracle's AI investments. The rating agency also warns that Oracle's future has become heavily tied to OpenAI, making one of Silicon Valley's most conservative software companies one of its biggest AI risk-takers. If you enjoy thoughtful analysis of artificial intelligence, enterprise technology, cybersecurity, cloud computing, and digital transformation, subscribe to Hashtag Trending for new episodes every weekday. 00:00 Headlines And Intro 00:39 AI Executive Threats Rise 04:11 DeepSeek Funding Shockwave 07:04 Murati Open Weight Challenge 09:48 Oracle Credit Rating Hit 12:19 Wrap Up And Book Promo If you'd like a free Kindle copy of Jim Love's novel ELISA, watch through to the end for details. Keywords: AI news, artificial intelligence, OpenAI, Sam Altman, DeepSeek, Mira Murati, Thinking Machines Lab, Oracle, S&P Global, Anthropic, Palantir, Salesforce, AI security, executive protection, open-weight AI, frontier AI, Qwen, Kimi, Zhipu AI, enterprise AI, cloud computing, Hashtag Trending, Jim Love, technology news

This week, the AI clown car somehow shifted into another gear. Apple is suing OpenAI over alleged trade-secret theft, newspapers accuse ChatGPT of training on stolen journalism while asking a judge to sanction the company, Anthropic is out here marketing AI with what looks like a feature-length anxiety attack, and Meta managed to launch—and kill—a creepy AI photo feature in less time than it takes to binge The Bear. Meanwhile, AI Appreciation Day wants you to thank the machines, but we'd rather thank the people still creating actual art while the rest of Silicon Valley burns cash convincing us the next chatbot is definitely different this time.Outside the AI bubble, the rest of the tech industry isn't exactly inspiring confidence. Volkswagen is cutting back on its lineup, New York paused new AI data centers before the electrical grid hits its limit, Europe and the UK are getting serious about keeping kids off social media, and publishers are finally realizing maybe feeding Google's AI isn't the best business move after all. Add in surveillance companies sulking over lost police contracts, lawsuits claiming Meta let algorithms decide who gets fired, smart glasses disqualifying cyclists, and a new pile of orbital junk threatening the satellites we depend on, and it's another reminder that "move fast and break things" eventually leaves you ankle-deep in broken glass.Of course, we still made time for the important stuff: Project Hail Mary, Black Bag, the return of Middle-earth with The Hunt for Gollum and rumors that OpenAI's "revolutionary” gadget might just be a smart speaker with delusions of grandeur. Throw in digital piano repairs, anti-data-center lawn signs, AI trying to sell solar panels, too much stuff at Downtown Disney, and you get another week where reality out-satirizes satire itself. As always, never build your house in someone else's backyard, and maybe don't let the chatbot build it either.Sponsors:CleanMyMac - Get Tidy Today! Try 7 days free and use code OLDGEEKS for 20% off at clnmy.com/OLDGEEKSDeleteMe - Get 20% off your DeleteMe plan when you go to JoinDeleteMe.com/GOG and use promo code GOG at checkout.Private Internet Access - Go to GOG.Show/vpn and sign up today. For a limited time only, you can get OUR favorite VPN for as little as $2.03 a month.SetApp - With a single monthly subscription you get 240+ apps for your Mac. Go to SetApp and get started today!!!1Password - Get a great deal on the only password manager recommended by Grumpy Old Geeks! gog.show/1passwordShow notes at https://gog.show/755Watch on YouTube at https://youtu.be/Vv2W5OCBXR4SHOW NOTESVolkswagen will dramatically shrink its model lineup and factory footprintElon Musk Could Still Face Criminal Charges for Trying to Bribe Voters in WisconsinEurope takes step toward social media ban for kidsThe UK Is Planning a Social Media Curfew for 16- and 17-Year-OldsOnce Unimaginable, Publishers Are Preparing to Opt Out of Google SearchWhat are your plans for AI Appreciation Day?New Anthropic Ad Implies AI Could Kill Us AllThe Public Got So Mad at Meta's New AI Photo Tool That It's Scrapped AlreadyFlock Says ‘We Hope to Resume' Work With LAPD After Getting DroppedApple sues OpenAI over alleged trade secret theftApple F*cking Did It: One Month With Siri AIOpenAI faces sanctions bid as newspapers say ChatGPT was trained on stolen newsA Majority of Americans Now Support Seizing Wealth From AI IndustryNew York enacts first US ban on data center constructionAstronomers Found a Hidden Swarm of Space Junk Threatening Earth's Most Valuable OrbitLawsuit claims Meta's layoff decisions were made by AI, not humansJudge dismisses lawsuit accusing Apple of failing to stop CSAM on iCloudSmart Glasses Just Got a Pro Cyclist Nixed From a RaceProject Hail MaryGood Luck, Have Fun, Don't DieThe New ‘Lord of the Rings' Film Gets an Epic Filming AnnouncementBlack BagPhilips offers free replacements after update bricked smart lighting hubsWaze rolls out new AI features including Motorcycle and 'Less Chatty' modesThe OpenAI Mystery Device Will Reportedly Be Basically Just a Smart SpeakerPhoebe Gates' AI shopping app Phia reportedly claimed unearned affiliate sales through fake clicksThe End of Reading Is HereDave BittnerThe CyberWireHacking HumansCaveatControl LoopOnly Malware in the Building‘The Mandalorian and Grogu' Is Finally Coming HomeDave Kendall, Creator and Host of MTV's 120 Minutes, Has DiedSam Neill, Jurassic Park Star, Dies at 78The DishSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We are continuing our Lord of the Rings study with the Book III, Chs. 7-11.Purchase the entire course, including our recorded live meetings, here: Purchase CourseWatch the video of this episode and subscribe to my YouTube channel here: https://youtu.be/_XTGWHb0iDYBecome a patron of Mythic Mind at patreon.com/mythicmindListen to all THREE Mythic Mind podcasts:Mythic MindMythic Mind GamesMythic Mind Movies & Shows(or become a patron to get all three shows in one ad-free feed)Become a supporter of this podcast: https://www.spreaker.com/podcast/mythic-mind--5808321/support.

It's been branded “the scariest company on the planet” and it is busy weaving itself into the fabric of Britain's NHS, defence establishment and beyond. Peter Thiel's Palantir has a terrible reputation – but do its products even work as billed? As MPs call for Palantir's £330m NHS contract to be scrapped and fears grow over Big Brother-style data sharing, we talk to Democracy for Sale founder Peter Geoghegan whose investigation into Palantir reveals a company that's a lot better at schmoozing than delivery – and how Peter Mandelson's lobbying firm helped land the NHS deal.How did a controversial US tech firm – whose AI powers military strikes in Gaza and Iran and ICE's immigration raids, and whose founder Peter Thiel thinks the NHS makes people sick – wheedle its way into Westminster? And what can we do about it? • Read about Peter and Lucas Amin's investigation on Democracy for Sale • Read the full 7,000 word investigation on the London Review of Books• Back us on Patreon – www.patreon.com/bunkercastWritten and presented by Group Editor Andrew Harrison. Producer: James Liddell. Audio production: Robin Leeburn. Managing Editor: Jacob Jarvis. Music: Kenny Dickinson. THE BUNKER is a Podmasters Production.www.podmasters.co.uk Hosted on Acast. See acast.com/privacy for more information.

Prototypes and demoware.That was Monumental two years ago, at their $25m Series A.Yesterday they announced a $32m Series B led by Khosla Ventures. In between, their robots laid the entire brickwork on 100 houses, plus canal walls and commercial buildings, as a subcontractor carrying full liability for the work.The day after the announcement, co-founder Salar al Khafaji sat down with us.In his words:"The Series A was basically still like an R&D round... we had some prototypes, we had some like demoware basically.""The Series B was raised off actual success."And the line that will start arguments:"Everyone is obsessed with speed. Speed doesn't really matter."A bricklaying robot company telling you speed doesn't matter. His reasoning is worth the listen on its own.Also in this one:> Why SAM and Hadrian X were too early, and what changed> Day zero to day one of a robot crew arriving on site> The economics vs a traditional bricklaying gang> UK going commercial, US pilots starting this year> Why the entire facade is next. Not in a decade, within a couple of years.

The Small Business Administration is ramping up its relationship with Palantir, announcing a “new phase” in its anti-fraud work with the data analytics and software giant. In a press release Tuesday, the SBA said it's formalizing and expanding its work with Palantir after signing a $300,000 contract in January for a fraud prevention pilot and bootcamp. That deal had a projected end date of April 4, but the agency said in the release that the “collaboration” with Palantir will now continue through “ongoing efforts to identify, investigate, and help prosecute fraud in pandemic-era small business relief programs.” The agency pointed specifically to its Paycheck Protection Program and COVID-19 Economic Injury Disaster Loan program as areas previously beset by fraud. SBA Administrator Kelly Loeffler said in a statement that the Palantir partnership “will strengthen our ability to expose fraudulent actors, support criminal enforcement actions, and recover stolen funds with advanced technology and artificial intelligence.” “No amount of fraud is acceptable — whether it is $10,000 or $10 million — which is why the SBA is deploying these tools to accelerate our work to surface wrongdoing and ensure those who cheated taxpayer-funded programs face consequences,” she added. The National Institutes of Health selected Kristen Honey, a longtime government data and technology official, to head up its coordination of public-private research partnerships. In a social media post, the Office of the National Coordinator for Health IT announced Honey as the inaugural official in the NIH role. As part of her duties, Honey will help “to build robust partnership models, reduce duplication, improve transparency, and move promising ideas from concept to execution with greater speed and consistency in collaboration with” ONC and across the department, per the post. The chief partnerships officer role is housed in the Office of the Director's Division of Program Coordination, Planning, and Strategic Initiatives, per the post. “The ‘wicked problems' that I run toward—complex, interdisciplinary challenges no one wants to own and that require cross-sector solutions—just got bigger. Joining NIH as Chief Partnerships Officer,” Honey said in a LinkedIn post. Honey has served in various HHS and White House roles over the past decade — including as HHS's chief data officer. Honey was initially installed as CDO after President Joe Biden's administration reorganization of its IT, data and artificial intelligence portfolio. Her time as CDO, however, appears to have ended after the Trump administration undid that reorganization in March, per her LinkedIn. Since then, she has listed her role as senior executive service. Currently, Arman Sharma, HHS's deputy chief AI officer, is listed as the agency's top data official on the CDO Council webpage. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

I just got back into the Land of the Free, and I have to tell you: it's a prison with a flag on it. Flock cameras on every corner. AI streetlights fitted with tech that can aim at your vehicle and listen to the conversation inside it. I went to the World Cup (no robot dogs yet, thankfully) but the cameras were everywhere, and nobody around me seemed to care. That's the part that should terrify you. Not the technology. The mindset. You just celebrated 250 years of “freedom” inside a surveillance grid your own culture built, because you dislike your neighbor more than you love your liberty. And understand what this machinery is for. The surveillance state is the ultimate weapon against competition, the lockdown mechanism of a rigged game. Politics is rigged. Finance is rigged. And the people who were going to protest it already did; with AI tracking, the rest are too scared to ever try again. They're building machines to follow the orders no human being would. So why don't I just despair? Because we already built the way out. That's why Crypto Vigilante exists… Watch on: Odysee | YouTube | X | Rumble | Bitchute | Vigilante.tv Blockchain is fairness as technology. We stopped trusting corruptible humans and started trusting mathematics. And that is exactly why Bitcoin was hijacked. The powers that be couldn't kill it, so they did something smarter: they convinced you it's a lottery ticket. A number-go-up token you buy on their exchanges and never use. The entire propaganda project has one goal: to keep you dumb, because Satoshi didn't give us a casino chip. He gave us a new internet: digital cash, a world computer, a place where you own your data and AI grows by market demand instead of by central planning. The antithesis of Palantir. And here's the black pill the maxis can't swallow: Bitcoin already scales on chain. Love him or hate him, Craig Wright's camp proved the thesis. BSV is pushing a million transactions per second and computing script on both sides of the UTXO model. They're training AI on chain. Meanwhile the Lightning Network, the thing you were told would save BTC, is dead. Its own whitepaper admitted it needed bigger blocks, and its senior devs keep walking out the door. Which brings us to August, when BTC's stalemate finally cracks in two: In early August, the Knots crew forks off with BIP 110: filter everything, change nothing, ten transactions per second forever. It's the end of the small-blocker experiment, going out with a whimper. August 21st brings the fork I'm actually cheering for: eCash (ECX), from Paul Sztorc and Layer 2 Labs. It uses Drivechains — BIP 300 and 301 — the sidechain technology Blockstream pitched to investors a decade ago and never delivered. Same 21 million coins, but now every philosophy gets its own room in the house. Want a big-blocker chain? Spin it up. Want optional privacy, with Zcash tech on ZSide? Move your coins there. Want scarcity harder than BTC? That exists too. Nobody forces one way of doing things, and no new shitcoins get minted along the way. It's the shitcoin killer, and it's the only lifeboat the BTC Titanic has. And while the forks race to scale Satoshi's vision, there's already a fair game running today: Monero. Private by default, immune to the surveillance grid, no permission needed. Most of our team became privacy enthusiasts the day the Bitcoin civil war started, and they've done just fine. Here's the real point, though. These networks are nothing without you. You are the most important node. The smarter you get, the smarter the network gets. So if I'm wrong, prove it, upgrade the software in your mind, and bring real arguments when you do. Because the psychologists are right: people under surveillance stop being themselves. The first act of resistance is to say it out loud. You live in the land of the surveilled. The second is to stop transacting like a prisoner. Peace, love, anarchy. Stay vigilant. Follow me on X @VamosVigilante Want to be on the pulse of crypto? Access our exclusive portfolio, insider reports, full archive of monthly newsletters, real-time market updates, buy/sell alerts, and private community chat and get instant access to the latest issue of our monthly newsletter… Subscribe now! FREE “Crypto 101” Video Training – Watch Our Millionaire Crypto Analyst Reveal the Exact Crypto Wallet Setup He Wished He Had When Starting Out: https://CryptoVigilante.io/crypto101TCV Summit: “What Matters Most in Crypto” | https://dollarvigilante.spiffy.co/checkout/what-matters-most Replay videos available! The Crypto Vigilante (Follow on All Socials) The post Land of the Surveilled appeared first on The Crypto Vigilante.

Palantir CTO Shyam Sankar says the Pentagon has accelerated defense tech adoption, speaking with Bloomberg News' Tyler Kendall on Bloomberg Open Interest at the 2026 Pennsylvania Defense & Innovation Summit. He also warned against turning away from AI innovation, saying doing so would be "as consequential a mistake as turning our back on the atom in the 70s."See omnystudio.com/listener for privacy information.

Ian Cinnamon didn't set out to build a satellite company. After selling his first startup to Palantir, he became convinced the real bottleneck in space wasn't launch or payloads, but the spacecraft itself. While rockets were getting cheaper and payloads more capable, satellite buses were still being built like bespoke engineering projects. Apex's answer was simple in theory and incredibly difficult in practice: turn spacecraft into products. Four years later, Apex is building standardized satellite platforms for commercial and national security customers, with a product lineup that now spans missions from LEO to GEO. We get into whether the satellite bus market is genuinely supply constrained, if standardized spacecraft become commodities or durable technology platforms, and how Starship, proliferated constellations, and rising defense demand are reshaping the economics of spacecraft manufacturing. We also cover: Why Ian believes spacecraft should become products instead of bespoke engineering programs Whether the satellite bus market is actually underbuilt or heading toward oversupply How Apex thinks about manufacturing, vertical integration, and scaling production Why larger satellites may make more sense in a world of cheap launch The capital strategy behind building one of the industry's fastest-growing companies Check out Valley of Depth #045 on Apple, Spotify, or YouTube. • Chapters • 00:00 – Trailer 00:55 – New CEO of Apex 02:29 – The Apex origin story 05:39 – Partnering with Max Benassi 07:13 – Successes and drawbacks of Apex's first 6 months 08:50 – Apex's current product set 10:36 – Misconceptions about how much mass you need in orbit 12:08 – Is the plan to build larger and larger satellites indefinitely? 13:11 – State of the bus market today 14:52 – Domestically oversupplied, globally undersupplied 16:31 – Apex's biggest opportunities on the commercial and national security side 18:50 – When should a company utilize Apex vs. building their own bus in-house? 19:46 – Apex's moat 21:12 – Juggling the bespoke government customer 22:15 – What the primes having in-house buses says about the market 23:07 – Commoditization of the bus vs. owning the complete mission 26:01 – Apex partnerships 27:27 – How many satellites are you building at a $100B company? 28:10 – Apex's three $200M fundraising rounds 32:05 – Is there another fundraising round incoming? 33:04 – Where Apex needs to be to seriously consider going public 34:58 – The road to 200 satellites per year 35:46 – Who is Apex losing deals to the most? 37:39 – Apex vs. K2 40:27 – How the push for heavy launch will affect Apex 42:15 – Apex's ability to get to space if SpaceX fully cuts commercial launches 44:35 – Is York an under or overvalued business? 46:36 – What keeps Ian up at night? 50:10 – When is Apex launching their own constellation? 51:06 – The missions that Apex could enable 52:30 – Is Ian still excited about asteroid mining?   • Show notes • Apex's' website — https://www.apexspace.com/ Ian's' socials — https://x.com/IanCinnamon Mo's socials — https://x.com/itsmoislam Payload's socials — https://x.com/payloadspace / https://www.linkedin.com/company/payloadspace Ignition's socials — https://x.com/ignitionnuclear /  https://www.linkedin.com/company/ignition-nuclear/ Tectonic's socials — https://x.com/tectonicdefense / https://www.linkedin.com/company/tectonicdefense/ Valley of Depth archive — Listen: https://pod.payloadspace.com/   • About us • Valley of Depth is a podcast about the technologies that matter — and the people building them.  Brought to you by Arkaea Media, the team behind Payload (space), Ignition (nuclear energy), Decoding Bio (biotech) and Tectonic (defense tech), this show goes beyond headlines and hype. We talk to founders, investors, government officials, and military leaders shaping the future of national security and deep tech. From breakthrough science to strategic policy, we dive into the high-stakes decisions behind the world's hardest technologies. Payload: www.payloadspace.com Tectonic: www.tectonicdefense.com Ignition: www.ignition-news.com Decoding Bio: www.decodingbio.com

In Part Two of our special investigation into Palantir Technologies, On the Record with Christian Briggs takes listeners beyond the headlines and into the rapidly evolving world of artificial intelligence, digital identity, surveillance technology, and the global race to control information.Palantir is often portrayed as either the world's most powerful surveillance company or simply another enterprise software firm. The reality is far more complex—and potentially far more consequential. This episode explores what Palantir actually does, how its software is used by governments and Fortune 500 companies, and why its technology sits at the center of one of the most important debates of the 21st century.We examine the rise of digital identity systems, the explosion of data generated by modern society, and how advanced software platforms are helping organizations connect information that once existed in isolated databases. From hospitals and supply chains to military logistics and disaster response, the ability to transform massive amounts of information into real-time decisions is reshaping nearly every major institution.The episode also investigates automated license plate reader networks, the growing use of artificial intelligence inside government agencies, and the expanding ecosystem of cloud computing, cybersecurity, satellites, and advanced analytics that many experts believe will define the next generation of digital infrastructure. Along the way, we explore the promises these technologies offer—greater efficiency, stronger national security, improved public safety, and faster emergency response—as well as the difficult questions they raise about privacy, transparency, accountability, and civil liberties.Rather than relying on speculation or sensationalism, this documentary-style investigation separates established facts from interpretation, examining both the arguments of supporters and the concerns raised by critics. It asks whether society is adequately prepared for a future in which artificial intelligence increasingly assists with operational decisions, digital information becomes the foundation of modern governance, and software plays an ever-larger role in how governments and corporations understand the world around them.Whether you see these developments as the next great technological revolution or as a turning point that demands greater public oversight, one thing is becoming increasingly clear: the digital infrastructure of tomorrow is being built today.This is the conclusion to our two-part series on Palantir, artificial intelligence, and the technologies that are quietly reshaping the future of modern civilization.

AI is officially a national security issue and Washington is moving fast. The Bitcoin Policy Institute's Zack Cohen, Zack Shapiro, and Ken Egan break down Palantir and Nvidia's sovereign on-prem AI architecture, OpenAI's government-coordinated 5.6 rollout, and reports that Beijing may curb exports of China's top AI models. Then Zack Shapiro lays out his highest-conviction thesis: the biggest AI fortune won't be made by frontier labs, but by the people who help industry actually absorb the technology. Plus, a major CLARITY Act update as law enforcement opposition softens on Capitol Hill.

Louis Mosley is the UK head of Palantir, one of the world's most powerful – and controversial – technology companies. Its work with the NHS, the US government and western militaries has made it a lightning rod for criticism, with opponents accusing it of threatening privacy, enabling mass deportations and supporting military operations in Gaza. Louis therefore occupies an unusual position at the intersection of technology, politics and the British state.On the podcast, he explains what Palantir actually does, why fears over NHS data are misplaced and why scrapping its contract would be a ‘terrible mistake'. He tells Michael why technology companies should not overrule democratically elected governments, why Palantir is ‘ideological, not political' and why it believes in strengthening liberal democracies.They also discuss the coming AI revolution: why Britain is unusually well placed to benefit, how artificial intelligence could transform failing public services and why the ‘lanyard class' may have more to fear than frontline workers.Produced by Oscar Edmondson. Hosted on Acast. See acast.com/privacy for more information.

Flock cameras are all the new rage. We have finally forgotten or lost interest in smart meters, Stingray, Dirtbox, PRISM, etc. Flock Safety systems are being installed without consultation of the public, and sometimes reinstalled without permission from local authorities. Sometimes they're randomly placed. These cameras and sensors are supposed to keep communities safer, but what they ultimately do, even according to law-enforcement, is create a dragnet surveillance grid in local communities. They've already been used to fine and jail people for crimes that they did not commit. Perhaps the worst part, but not unlike Axonius, Palantir, Waze, ShieldAI, and so forth, is that the two primary investors are the Peter Thiel group and Andreessen Horowitz, a company directly rooted in Israel. Furthermore, resistance to these cameras being installed is being labeled terrorism. It's also not out of the realm of possibility that many of the cameras that have been cut down, have been removed by law-enforcement, community officials, or the company itself in order to paint the technology as a victim of ignorant and violent citizens.*The is the FREE archive, which includes advertisements. If you want an ad-free experience, subscribe below.

Wrap up your trading day for Tuesday, July 14, 2026, with Mark Longo on The Hot Options Report. It was a steady day on the tape, with the top 10 threshold landing just shy of the half-million contract mark at 497,000. Mark breaks down the social scans over at TheHotOptionsReport.com—highlighting what's trending up on X, including Luckin Coffee (LKNCY), Amkor Technology (AMKR), and a wild day for Carvana (CVNA). Then, we count down the top 10 most active equity options dominating the chains: Microsoft (MSFT): Paper leans toward selling the short-term 390 calls expiring Wednesday. Terawulf (WULF) & Oracle (ORCL): Massive action in WULF's August 25 calls, while Oracle hits a new 52-week low. Amazon (AMZN) & Micron (MU): Tech chips in as Amazon eyes the 250 strike and Micron rallies nearly 5% to flirt with par ($1,000). Intel (INTC) & Palantir (PLTR): Out-of-the-money lotto prints in Intel, and Palantir climbs the ranks to number 4. Apple (AAPL), Tesla (TSLA), & Nvidia (NVDA): The big dogs take center stage as Nvidia regains yesterday's losses, lighting up the Wednesday 210 calls. Find out where the smart money is leaning, which strikes are creating the most sweat equity, and how to scan the unusual activity for yourself at TheHotOptionsReport.com

We finally get to reconnect with Dave Bittner for a fun catch-up and chit-chat about this summer's big movies. Brian's kid discovers all of Star Wars at once.Dave BittnerThe CyberWireHacking HumansCaveatControl LoopOnly Malware in the BuildingKnockoff - Amazon Brand FilterBob Gurr: Living by DesignSupport the show at Patreon! - https://patreon.com/gogOther ways to support the show! - https://gog.show/donateJoin our Discord! - https://discord.gg/r4ZmSHBBuy some merch! - https://shop.gog.show/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

At the UN's Global Dialogue on AI Governance in Geneva, Nobel Peace Prize laureate Maria Ressa warned that artificial intelligence poses the threat of an "information Armageddon." Scholars of critical theory perceive that online culture reproduces a "cycle of epistemic injustice" by fostering "organized stupidity" that fuels extremism and authoritarianism. And the same technology now implements the grim material application of this degraded intellectual climate, with a UN Human Rights Council study especially accusing Palantir of being part of an "economy of genocide" through its enabling of Israel's AI-enhanced targeting in Gaza. Meanwhile, the pollution generated by the data centers that power AI is now "almost incomprehensible." Despite all this, UNESCO in Geneva glibly called for a "safe and inclusive AI that benefits all," and an openly boosteristic "AI for Good" confab was held alongside the Global Dialogue. The "anti-tech rebellion" against screens in school classrooms is a significant sign of hope, but the end of reading and death of literacy are already upon us. Moves toward greater regulation of AI are most significant as a catalyst for the conversation that needs to be had: how to launch an effective movement for abolition. In Episode 336 of the CounterVortex podcast, Bill Weinberg continues to make the case. Listen on SoundCloud or via Patreon. https://www.patreon.com/countervortex Production by Chris Rywalt We ask listeners to donate just $1 per weekly podcast via Patreon -- or $2 for our new special offer! We now have 60 subscribers. If you appreciate our work, please become Number 61!

Los programas que crea Palantir para gobiernos y servicios de inteligencia de todo el mundo se han convertido en la herramienta que usan para vigilar inmigrantes y disidentes. Se trata de una suerte de Gran Hermano que ha llegado a colaborar en el bombardeo de Gaza y en el uso que efectúa la CIA para controlar a millones de ciudadanos. La polémica empresa creada por Peter Thiel acaba de llegar a España, en donde han sido señalada por Moncloa, pero antes había llegado a conseguir dos contratos oficiales que por valor de casi 20 millones de Euros.

Tras desvelarnos la llegada de la empresa Palantir -el auténtico Gran Hermano- a España, Fernando Rueda nos cuenta la apasionante historia de un agente de la CIA que estafó a la propia CIA.

Tim discusses the concerning trend known as 'Teen Takeovers', like the one that shut down Newport Beach on the 4th of July, and how a company like Palantir may step in to help. Tim also talks about Netanyahu calling Turkey a new enemy and saying Iran "definitely" has chemical weapons. Become a Friend Of The Show https://bit.ly/BecomeAFriendOfTheShow and get access to weekly bonus audio episodes of the podcast!Live Dates

Ben Lorica sits down with Evangelos Simoudis to unpack why open-weights models are closing the gap with frontier labs and pushing enterprises toward “corporate AI sovereignty.” They then apply an attenuation-funnel lens to AI coding tools — more code, but far less shipped software and usage growth — before turning to “neoconsulting,” the outcomes-based services model reshaping Accenture, Palantir, and the big Indian IT firms.Subscribe to the Gradient Flow Newsletter

#高雄 正義站&黃線捷運計劃，平面車位3房全新完工 實品屋預約鑑賞中。正義站通勤南科，未來捷運串連衛武營、Lalaport。正義公園，風景入門廳 。陽明國中自由學區07-7801988 洽澄清路227號 https://sofm.pse.is/9b848h －－－－以上為 SoundOn 動態廣告－－－－ 行政院規劃投入2100億元推動無人載具發展，目標5年內籌獲21 萬架無人機、艇，且以在地供應鏈為核心。不過，台灣國內相關產業目前是否具備這種規模的產能？產業生態足以支撐長期發展嗎？中科院過去在飛彈研發上表現不俗，但為何說中科院在無人機發展上不應繼續「全包獨佔」？那麼中科院未來可以扮演何種角色？攻擊無人機類型多樣，技術需求不同，台灣民間廠商如何建立有效的驗測機制，真正形成自主維修與迭代創新的能力？台灣無人機民間企業為何常落入「投入越深、死得越快」的失血困境？當前無人機技術以「週」為單位進行更新，傳統耗時3到5年的軍事採購流程是否已流於官僚？美國可以快速培育出Anduril、Palantir這些新型國防科技企業．關鍵在於政府願意扮演「第一個客戶」承擔創新風險，台灣政府敢嗎？政黨惡鬥下的台灣能做到嗎？隨著地緣政治加劇、資安意識提高，國際供應鏈正在「去紅」，美國推動Blue UAS計畫，有意將台灣納入美軍無人機供應鏈，台灣政府能如何幫助本土廠商剔除紅色供應鏈、打進國際軍工市場？精彩訪談內容，請鎖定@華視三國演議！ 本集來賓：#周宇平 #矢板明夫 主持人：#汪浩 以上言論不代表本台立場 #無人載具 #國防自主 #中科院 #藍天法案 電視播出時間

JOIN PATREON FOR EARLY UNCENSORED EPISODE RELEASES: https://www.patreon.com/JulianDorey CLIPPERS DISCORD: https://discord.gg/8QmWEKJ3BT (***TIMESTAMPS in Description Below) ~ Fat Electrician and Veteran w/ a Sign are both veterans and YouTube creators. They have their own channels and multiple podcasts including "Unsubscribe Podcast" & "Underwhelming Podcast." FAT ELECTRICIAN's LINKS: - YT:  https://www.youtube.com/@the_fat_electrician - POD:  https://www.youtube.com/@unsubscribepodcast - IG: https://www.instagram.com/the_fat_electrician/?hl=en VETERAN w/ A SIGN's LINKS: - IG: https://www.instagram.com/veteranwithasign/?hl=en - POD:  https://www.youtube.com/@UnderwhelmingPodcast FOLLOW JULIAN DOREY INSTAGRAM (Podcast): https://www.instagram.com/juliandoreypodcast/ INSTAGRAM (Personal): https://www.instagram.com/julianddorey/ X: https://twitter.com/julianddorey JULIAN YT CHANNELS - SUBSCRIBE to Julian Dorey Clips YT: https://www.youtube.com/@juliandoreyclips - SUBSCRIBE to Julian Dorey Daily YT: https://www.youtube.com/@JulianDoreyDaily - SUBSCRIBE to Best of JDP: https://www.youtube.com/@bestofJDP ****TIMESTAMPS**** 0:00 - Live podcasting and military transition 11:23 - Aldi, Poisoned American food & politics 26:19 - Agriculture, Iowa cancer & NJ Pumping Gas Argument 42:02 - AI, Thiel & skilled trades 53:18 - Trades, YouTube & corporate inefficiency 1:02:50 - Social security & opioid crisis 1:13:10 - Boomers, democracy flaws, voting barriers 1:22:56 - Voting tests and civil service 1:33:00 - Poverty, 9/11 & joining military 1:42:02 - Afghanistan deployment & Marja invasion 1:54:00 - Combat losses & supportive wives 2:07:55 - Marrying your high school sweetheart 2:08:57 - Logan Weston: The Fighting Preacher 2:23:08 - Merrill Marauders & bayonet charges 2:24:40 - Military history & political wars 2:43:35 - Afghanistan withdrawal & veteran healing 2:58:20 - Meeting online & veteran PTSD 3:08:18 - Systemic abuse & Afghan reality 3:26:49 - Fat Electrician & VWAS's Work CREDITS: - Host, Editor & Producer: Julian Dorey - COO, Producer & Editor: Alessi Allaman - https://www.youtube.com/@UCyLKzv5fKxGmVQg3cMJJzyQ - In-Studio Producer: Joey Deef Julian Dorey Podcast Episode 446 - Fat Electrician & Veteran w/ a Sign Music by Artlist.io Learn more about your ad choices. Visit podcastchoices.com/adchoices

For our cultural predictions roundup back in January, the musician and technologist Trevor McFedries predicted that 2026 was going to be a really good year—professionally speaking—for people with good taste. The jury's still out, but it's definitely turning into a big year for talking about taste. And for the first time in history, the tech world seems to be leading the charge, from engineers penning essays about how “personal taste” is the new moat, to startups promising us more aesthetically discerning AI, to the Palantir chore coat and tech billionaires sitting front row at Fashion Week.To make sense of why taste has become such a Silicon Valley buzzword—and what that tells us about the changing meaning and role of taste more broadly–we brought on Drew Austin, a writer and urban planner who runs the excellent Substack, Kneeling Bus, where he recently penned a piece called “Tastecore and the Enclosure of the Commons.” We discuss Drew's research on the tech world's changing relationship to fashion in the post-pandemic era, the growing epidemic of “tasteslop,” and how the current discourse frames taste as something less about personal distinction and more about gaining a competitive edge. Plus, we tap Pierre Bourdieu to try to parse the evolving function of taste in society over time—and what the tech industry's taste obsession can tell us about the shifting landscape of class and class antagonism.Follow Drew at Kneeling Bus on Substack.Read Drew on taste:“Tastecore and the enclosure of the commons”“Worn out: Tech elites' supposed indifference to fashion is a contempt for the commons” (Real Life)“Here comes a regular: Taste is obsolete & gatekeeping is code for what the internet took from us”“Bots in the beerlight: Sometimes embodiment is all you've really got”“Lo-fi beats for studying: How to push more through the human attention bottleneck”Additional references:“Taste is Eating Silicon Valley” by Anu Atluru (Working Theories)“Personal Taste is the Moat” by Wang Cong“Tasteslop: Notes on technological anxiety” by Emily Segal (Nemesis) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit theculturejournalist.substack.com/subscribe

In this episode of Business Brain, Shannon Jean and Dave Hamilton kick off Casual FridAI with a $10,000 surprise. Dave got an unsolicited email about a domain he’d owned for 21 years and never used — exactly the kind of message he’d normally ignore. This time he fed it to Claude, treated AI as a confidential collaborator, and worked through how to value a domain with zero cash flow and how to play the negotiation. He came in high at $15K, settled at $10K through escrow, and netted every dollar. The takeaway for you: stop using AI just to do the work and start using it to think alongside you. That everyday, back-and-forth collaboration mode is where the real money hides. From there, the guys dig into why the AI industry feels flat-out insane. Palantir’s Alex Karp argues enterprises are paying to feed frontier models their own IP, only to get outcompeted by the very tools they’re training — you can’t rent intelligence from the same place that rents it to your competitors. Where does that leave you? Betting on on-device AI and owning your software instead of renting it. If you’re still paying for a CRM a year from now, you may be throwing money away, because there’s never been a better time to build your own. Put these moves to work and you’ll be living the Charmed Life. 00:00:00 Business Brain – The Entrepreneurs' Podcast #769 for Casual FridAI, July 10, 2026 July 10th: National Piña Colada Day 00:01:03 I made ten grand by surprise Escrow.com 00:10:38 SPONSOR: Shopify: Stop waiting for permission to build something. Your next revenue stream starts free at Shopify.com/BusinessBrain. 00:12:03 SPONSOR: Bitdefender. Keep your small business safe with Bitdefender Ultimate Small Business Security. Save 30% when you go to https://bitdefender.com/BRAIN 00:13:37 Plantir CEO Alex Karp says AI Industry is Effing Insane You can't rent intelligence from the same place that rents it to your competitors FileMaker and AI Business Brain 769 Outtro This Episode's Big Takeway: There's never been a better time to own and build your own business software Check out Business Brain Blueprints Tell Your Friends! Business Blueprints Review Business Brain Subscribe to the show feedback@businessbrain.show Call/Text: (567) 274-6977 X/Twitter: @ShannonJean & @DaveHamilton, & @BizBrainShow LinkedIn: Shannon Jean, Dave Hamilton, & Business Brain Facebook: Dave Hamilton, Shannon Jean, & Business Brain The post FridAI – Free $10K + AI Insanity. Business Brain 769 appeared first on Business Brain - The Entrepreneurs' Podcast.

This week, the world finally discovers what we've been saying for years: Gen X wasn't forgotten—we were quietly keeping the entire damn machine running. New Census numbers show America's 45-to-64 crowd is shrinking fast, which means the people who know where all the bodies are buried (and why you never reboot that one production server) are disappearing without a replacement bench. Meanwhile, Meta continues its speedrun toward becoming history's most aggressively unlikeable company, staring down a potential $1.4 trillion lawsuit over social media addiction while simultaneously launching AI features that happily remix your Instagram photos unless you remember to opt out of Zuckerberg's latest privacy experiment. Because nothing says "we've learned our lesson" quite like doubling down.The AI circus somehow gets even weirder. Illinois actually passed meaningful AI safety legislation—an event so rare it qualifies as science fiction—while Sam Altman reportedly floated the idea of AI companies handing the U.S. government an ownership stake. Anthropic published another paper that's already inspiring breathless declarations that Claude is "thinking," because apparently matrix multiplication now counts as an inner monologue. Cloudflare finally decided websites shouldn't have to give away their content for free to AI crawlers, researchers discovered AI agents could consume enough electricity to make Google Search look like a bicycle generator, and Amazon's Mechanical Turk is being replaced by the very AI it spent two decades secretly training. Progress: where everyone works harder, gets paid less, and the power grid cries.Elsewhere in Tech Hell™, Waymo robotaxis turned San Francisco traffic into an even bigger parking lot, Google lost another multibillion-dollar antitrust appeal in Europe, the FCC found fresh ways to make internet bills less transparent, and Midjourney is demanding Hollywood explain its own AI habits in court. We also dig into a disturbing lawsuit involving Grok-generated abuse imagery and what it says about AI guardrails, explain how to stop Meta from feeding your Instagram into its latest AI experiments, discuss why tech workers increasingly feel AI isn't replacing them so much as making them miserable faster, and close things out with the usual Media Candy, Apps & Doodads, and library recommendations to help you survive another week inside the techno-dystopian fever dream we apparently call "the future."Sponsors:Private Internet Access - Go to GOG.Show/vpn and sign up today. For a limited time only, you can get OUR favorite VPN for as little as $2.03 a month.SetApp - With a single monthly subscription you get 240+ apps for your Mac. Go to SetApp and get started today!!!1Password - Get a great deal on the only password manager recommended by Grumpy Old Geeks! gog.show/1passwordShow notes at https://gog.show/754Watch on YouTube at https://youtu.be/xnhzMxu1JNASHOW NOTESAmerica's missing middle: The shrinking 45-64 populationMeta is facing $1.4 trillion in state lawsuits over social media addictionMeta just launched a new AI generator, Muse Image, and users are already pushing back over use of their photosIllinois Drops the Hammer on AI CompaniesOpenAI reportedly wants all AI companies to give the US government a stake in their businessesLawsuit: Man used Grok to make 7K sex images of stepdaughter, then shot himselfMidjourney wants the Hollywood studios that sued it to show the court how they use AIAnthropic Releases Paper About Claude's Mental ‘Workspace.' Don't Read It UncriticallyCloudflare will filter out web crawlers that serve AI companiesWhen It Comes to Energy Use, AI Agents Could Make Chatbots Look Like Pocket CalculatorsAmazon's ‘Artificial Artificial Intelligence' Is Being Eaten by AIDrivers Trapped for Hours in Hopeless Gridlock as Waymos Brick on Major HolidayGoogle loses final appeal over $4.7 billion EU Android antitrust fineFCC to end Biden-era rule that forces ISPs to list all their feesGetty Images is canceling its $3.7 billion Shutterstock merger due to UK restrictionsFootage Shows Cop Stalking Woman He Met on a TV Set After Surveilling Her With a License Plate ReaderMeta says it will disable the camera on its glasses if you tamper with the recording LEDMeta tests ‘super sensing' AI glasses that can capture every momentHow tech workers are feeling in 2026: a workforce splitting in twoSiloSugarDune: Part Three | Official TrailerAI golem Tilly Norwood is reportedly 'starring' in a feature-length movieLuckyNormalHow to claim a WhatsApp usernameHow to Stop Meta AI From Processing Your Instagram ContentGold Rush (First Contact) by Peter CawdronSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Here at The Remnant, we strive to cover pressing issues that matter. Not content with copying and pasting other folk's reporting, we go straight to the sources ourselves to bring their words to your ears. Today, we're taking a deep dive into one of the topics that matters most to our nation, and to the world: the Annapolis Cup Croquet Match. You think we're kidding, but we're not.  But don't worry—if bombs, bullets, and dead ayatollahs are more your thing, we've got you covered too. School of War podcast host Aaron MacLean joins Jonah Goldberg to discuss, in addition to croquet, what happened in Iran, isolationism, sovereigntism, Machiavelli, Chris Donahue, Palantir, Pentagon purges, failures in the Middle East, warrior culture, careerism, and the lessons our adversaries are taking away from Iran.  Show Notes: —School of War Podcast —Aaron's last Remnant appearance  —School of War episode on chimps The Remnant is a production of ⁠The Dispatch⁠, a digital media company covering politics, policy, and culture from a nonpartisan perspective. To access all of The Dispatch's offerings—including the Saturday Ruminant, audio versions of all our articles and newsletters, and Jonah's twice-weekly G-File—⁠click here⁠. Instructions on how to set up your members-only feed can be found here, and if you'd like to remove all ads from your podcast experience, consider becoming a premium Dispatch member ⁠by clicking here⁠.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Dan Nathan and Guy Adami open the podcast by framing the day's key market story as sharp weakness and heightened volatility in memory, chips, and semi equipment, citing rapid reversals in names like Micron and Applied Materials and opaque guidance from Samsung. They discuss whether the AI build-out is increasingly debt-funded—highlighting Amazon and Oracle debt issuance and private credit deals—and reference a “Groundbreaker” piece shared by Jim Chanos arguing investors miss second-derivative slowdowns and that AI resembles a credit-driven real estate cycle more like 2008 than 2000's patient equity bubble. They note a rotation bounce into software (Microsoft, Palantir, Salesforce, Adobe, ServiceNow) but question sustainability, and debate SpaceX's fast-tracked inclusion in the Nasdaq 100 after its IPO, the stock's poor trading, possible broader IPO implications, and an upcoming insider share unlock —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media The financial opinions expressed in Risk Reversal content are for information purposes only. The opinions expressed by the hosts and participants are not an attempt to influence specific trading behavior, investments, or strategies. Past performance does not necessarily predict future outcomes. No specific results or profits are assured when relying on Risk Reversal. Before making any investment or trade, evaluate its suitability for your circumstances and consider consulting your own financial or investment advisor. The financial products discussed in Risk Reversal carry a high level of risk and may not be appropriate for many investors. If you have uncertainties, it's advisable to seek professional advice. Remember that trading involves a risk to your capital, so only invest money that you can afford to lose. Derivatives are not suitable for all investors and involve the risk of losing more than the amount originally deposited and any profit you might have made. This communication is not a recommendation or offer to buy, sell or retain any specific investment or service.

Les labos d'IA que vous financez scannent vos marchés pour mieux vous concurrencer ensuite. Ce n'est plus une théorie : Palantir, Anthropic, OpenAI — les preuves s'accumulent, et personne n'ose encore le dire officiellement.

Alex Karp went on CNBC to talk about Palantir's new Nvidia initiative, but what came out was much bigger than a partnership announcement. In this episode, Chris and Saied break down what Palantir actually does, why Gotham, Foundry, Apollo, and AIP matter, and why Karp believes the next phase of AI is not consumer chatbots — it is controlled, sovereign, mission-critical AI inside governments, militaries, banks, hospitals, factories, and critical infrastructure. The conversation becomes a larger debate over whether AI labs like OpenAI and Anthropic have oversold the dream, whether enterprises are wasting money on token economics, and whether corporate America fears its proprietary data, IP, and “alpha” are being absorbed by model providers. This is not just a Palantir episode. It is a conversation about who controls the future of AI: private labs, public governments, or the companies building the operating layer between them.

AI isn't just changing jobs — it's changing the risk/reward calculus of building companies, as new data shows solo business formation and revenue growth accelerating in AI-exposed sectors. NLW explores why startups, student founders, and one-person companies may be the clearest early signal of how AI is reshaping work. In the headlines: Palantir's Alex Karp makes the case for open-weight models in government, Nvidia backstops neocloud demand, and Tesla imposes token spending limits.Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠kpmg.com/us/Sophisticated⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Hyperagent - Hire a fleet of always-on agents. New users get $1,000 in inference. ⁠⁠⁠⁠hyperagent.com/aidailybrief⁠⁠⁠⁠Retool - Secure your vibecoded apps. New enterprise customers get up to $10,000 in AI credits per year. retool.com/aidaily Rackspace Technology- One accountable partner to build, operate and run your full enterprise AI stack ⁠⁠⁠⁠https://www.rackspace.com/⁠⁠⁠⁠Section - Section turns AI investment into workforce transformation and ROI - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.sectionai.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Scrunch - The AI customer experience platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://scrunch.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

Pratap Chatterjee, executive director of CorpWatch, joins us to discuss their latest report, MAGA Inc., which identifies the Crypto Czars, the Tech Titans and the Prison Profiteers who have bankrolled and benefited the most from Donald Trump's corrupt regime. Then, Ralph welcomes Elliot Negin, executive editor of Money Trail to talk about how Donald Trump is trying to turn Washington DC into a monument to himself.Pratap Chatterjee is an investigative journalist, producer and executive director of CorpWatch, an organization that works to promote environmental, social and human rights by holding multinational corporations accountable for their actions. He is the author of several books, including Verax: The True History of Whistleblowers, Drone Warfare, and Mass Surveillance, Halliburton's Army, and Iraq Inc.: A Profitable Occupation.Palantir is really critical to understanding how the surveillance state works, especially in identifying people to deport and locations and people to kill in Trump's new wars overseas, such as in Iran…Palantir's data analytical capabilities are actually extremely simplistic and terrible. But when it comes to looking for an easy solution, that's what Palantir offers. And they've been able to offer this to the Trump administration—to have them speed up their political plans such as deportation, such as waging war against Iran by giving them easy answers.Pratap ChatterjeeThe biggest company behind the cryptocurrency used by criminals and drug dealers and gun traffickers has come out of the shadows, into the light, thanks specifically to the credibility offered by the Trump administration. And so this is really a sea change.Pratap ChatterjeeElliott Negin, executive editor of the Substack newsletter Money Trail, is an award-winning writer, illustrator and publication designer. Prior to co-founding Money Trail in February 2025, he was the managing editor of American Journalism Review, editor and art director of Public Citizen and Nuclear Times magazines, a news editor at NPR, and a regular contributor to HuffPost and the Union of Concerned Scientists' Equation. His freelance articles have appeared in The Atlantic, Common Dreams, The Hill, L.A. Progressive, The Nation, Scientific American, the Washington Post and other publications.It turns out that there is a government-owned ballroom less than a mile from the White House that would serve the purposes of a state dinner, which is one of the only events that you would need a ballroom for. If Trump builds a ballroom, it will not be used probably 360 days out of the year… To have a building that big that's going to be sitting empty for all that time makes no sense whatsoever.Elliott NeginRight now, the cost of this ballroom has been escalating… And half of it's supposed to be covered by taxpayers. Give credit to Public Citizen. It did a report that found out that more than half the donors that were identified as donating to the project when it was pegged at $400 million (including Amazon, Lockheed Martin, Palantir) have gained contracts with the federal government worth more than $50 billion in the last six months. That's a hell of a return on investment.Elliott NeginNews 7/3/26* Our top stories this week are the Colorado primaries. First, DSA-backed insurgent Melat Kiros successfully ousted 29-year incumbent Democratic Congresswoman Diana DeGette in the state's first congressional district, winning in a surprise blowout of over 13 points. Kiros, a 29-year old Tigrayan-American lawyer and PhD student, was fired from Sidley Austin – a “biglaw” firm in 2023, after she “posted an open letter defending students protesting Israel's war in Gaza from charges of antisemitism,” per Colorado Newsline. Axios reports many House Democrats, speaking anonymously, have bemoaned DeGette's loss, with one accusing Kiros of trafficking in “performative politics,” but Usamah Andrabi, spokesperson for Justice Democrats, one of the main groups that backed Kiros, put it simply when he said “If DeGette didn't deserve a primary, Denverites wouldn't have elected Melat” by double digits.* Also in Colorado, state Attorney General Phil Weiser easily defeated Senator Michael Bennet in the primary to succeed Jared Polis as Governor. While Weiser did run to Bennet's left, the real victory for progressives is that Bennet finishing out his own term means the Colorado Democratic establishment won't be able to appoint someone – likely a centrist member of the House – to replace him, per Axios. Meanwhile, John Hickenlooper, a Colorado Democratic institution won his primary as well, fending off a challenge from his left by state Senator Julie Gonzales. However, Gonzales came within 6 points of Hickenlooper, according to Colorado Public Radio, a tantalizingly close margin. Moreover, not only has Hickenlooper vowed that this would be his final Senate term, many are speculating that Bennet himself won't run when his term ends in 2028. That is all to say, it is possible we have not seen the last of Ms. Gonzales.* Speaking of Gonzales, much has been made of the fact that she “softly” distanced herself from DSA as she launched her primary campaign, per Colorado Pols. Perhaps maintaining that organizational relationship would not have resulted in her victory, but the stunning successes of DSA-backed candidates – including Melat Kiros in Colorado – speaks to the group's impressive organizational muscle. In fact, the group can boast of winning yet another seat in the New York State Assembly, with Maurice “Mo” Brown declaring victory against longtime incumbent Assemblyman Bill Magnarelli in the 129th Assembly District. Magnarelli held the seat for 30 years. Brown won by just over 100 votes after all the absentee and affidavit votes were tallied, according to Syracuse.com. With Brown's victory, DSA will send 16 members to Albany next session, nearly doubling its presence across both chambers of the state legislature.* More impressive than the electoral victories however is the fact that DSA members in office are delivering on their campaign promises. Most notably, in New York City, Mayor Zohran Mamdani has successfully forced a vote through the Rent Guidelines Board to enact a rent freeze for the Big Apple's 1 million rent-stabilized apartments, Time reports. These units make up a whopping 27% of the city's housing stock and house around 2 million people. Mamdani's predecessor, the corporate-friendly Democrat Eric Adams, pushed through rent hikes via the guidelines board, raising the rent by 12.6% over the course of his term in office. Mamdani called this the “relief that working people across our city deserve.” This move has, predictably, drawn the ire of landlords and their industry representatives, but there is no denying that the people of New York City voted for Mamdani in large part for this exact policy and he delivered.* In Congress, another socialist – Alexandria Ocasio-Cortez – is fighting for key amendments to the must-pass National Defense Authorization Act. These run the gamut from prohibiting the transfer of weapons to countries hampering the delivery of humanitarian aid, such as Israel, to demanding that the Secretary of Defense conduct declassification reviews or release unclassified reports on American assistance to the dictatorship in Brazil and the coup in Chile, barring Pentagon funds from being used to enforce sanctions on Cuba, and many more. As the scope of national legislation has narrowed in recent decades, amendments to massive flagship funding bills like the NDAA have become a primary means of getting legislation through the gridlock. It is very encouraging to see AOC take advantage of this mechanism to force votes on these issues.* Of course, the centrists will not simply cede power to the left without a fight. Yahoo reports 13 Democratic House members and candidates have signed onto what they are calling the “Promise to America,” consisting mainly of vague commitments to principles like “Growth, Competition, and Broad Prosperity,” or “Safety, Security, and Human Dignity.” They have also stepped up their rhetoric, saying “there's going to be a war” between themselves and the new crop of progressive and DSA lawmakers, per Fox News. Of course, this all makes one wonder whether the Democrats would be in this position at all if they were this confrontational with the Republicans instead of their own voter base.* Another emerging theater of combat between the center and the left is the Congressional Hispanic Caucus. The CHC is led by the lame duck New York Congressman Adriano Espaillat, who was defeated in his primary by Darializa Avila Chevalier. Both Espaillat and Avila Chevalier – or DAC as she has come to be known – are Dominican, despite Espaillat's last-minute smear campaign calling her Haitian, and she plans to join the CHC once she takes her seat in the House. Yet, POLITICO reports the CHC is divided about admitting DAC. While no member is going so far as to say outright that she should not be admitted, many, such as CHC Whip Sylvia Garcia of Texas, are saying things like if DAC is “aligned with all our priorities and all our legislative programs, we would welcome her.” Of course this raises the question of if she is not, would they still welcome her. The all-Democratic CHC has previously barred the entry of Republican Hispanic Congressman Carlos Curbelo of Florida and the Congressional Black Caucus barred Espaillat himself from joining after a feud between him and former Congressman Charles Rangel. In addition to DAC's accession, the CHC will also have to decide on a new leader with Espaillat gone. The Vice-Chair, Darren Soto of Florida, may lose reelection due to redistricting in Florida, leaving the seat up for grabs.* In more Florida-related news, on June 25th Florida Governor Ron DeSantis formally announced the closure of “Alligator Alcatraz” the immigrant detention facility much hyped in the early days of the second Trump administration. While DeSantis claims that the facility had simply “fulfilled the role it was designed to serve,” there is an alternate story being told in the native community. Native News Online has published a statement by Judith LeBlanc (Caddo), executive director of Native Organizers Alliance, which highlights that the facility was constructed and operated “in violation of the sovereign rights of the Miccosukee Tribe, who took the government to court for illegally constructing the center without their consultation or consent,” and hailed the closure as “a victory for human rights and Tribal Sovereignty.” The statement further decried “The administration's violent crackdown on migrant communities” as “an affront to all we stand for as Native peoples.”* Turning further south, the Guardian is out with a chilling story concerning the death of Monika Silva Koniuszek, a Polish anti-corruption activist, who was supposedly investigating self-dealing within the ruling Noboa family of Ecuador. According to her colleagues, Silva Koniuszek was investigating “Noboa Trading, the fruit conglomerate belonging to the family of the rightwing president, Daniel Noboa.” Specifically, they said she had been pursuing allegations that “several tonnes of cocaine had been seized in Noboa Trading banana containers,” and that “high-ranking Ecuadorian judicial officials were stalling the investigations.” Additionally, “Shortly before she was killed, she told friends that she had delivered a dossier of allegations to the US embassy in Quito.” Koniuszek was found dead with a noose around her neck, and Ecuador's interior minister announced that she had died by suicide even before the autopsy results were released. Once those results came out, they contradicted this claim, finding that her cause of death was “a blow to the head and strangulation.”* Finally, in neighboring Colombia, leftist candidate Ivan Cepeda, who lost the recent presidential election, has called on the people of that country to engage in mass civil disobedience, according to Jorge Bastidas, a Colombian Congressman and member of Cepeda's party. Specifically, Cepeda is demanding that the Colombian people not recognize the presidency of Abelardo de la Espriella unless and until he meets certain demands, including renouncing his U.S. nationality, disproving claims that he is a CIA collaborator, and vowing not to persecute and extradite his political opponents including outgoing President Gustavo Petro. Cepeda has stressed that this mass action, if pursued, will be peaceful.This has been Francesco DeSantis, with In Case You Haven't Heard. Get full access to Ralph Nader Radio Hour at www.ralphnaderradiohour.com/subscribe