Podcast appearances and mentions of David Sacks

Ravi Gupta and Ed Elson, co-host of Prof G Markets with Scott Galloway, break down the growing warnings about AI as Anthropic CEO Dario Amodei calls for a slower pace of development and stronger safeguards. They discuss Amodei's proposed solutions, alarming warnings from AI researchers, and the debate over whether companies should receive antitrust exemptions to coordinate on AI safety. Gupta and Elson also examine Trump's dismissal of AI risks, the influence of David Sacks, and the emerging political debate over how to regulate the technology. Plus, they discuss the economy as Treasury yields cross 5%, Trump's proposed $5,000 checks, and new polling on which party voters trust more to handle the economy. This and more on the podcast that helps you, the majority of Americans who believe in progress, convince your conservative friends and family to join us—this is Majority 54!Pre-order Ravi's New Book: https://www.amazon.com/Invisible-List-Passion-Year-Every/dp/0593980859/ref=sr_1_1?crid=3DLW66JVLB0SQ&dib=eyJ2IjoiMSJ9.5LDAYpIV1QkF6qGXMXrOoA.RwdEWCV1lydW_PuYCdxwhLCv2L61Iu1CcRT9HDQXAxQ&dib_tag=se&keywords=ravi+gupta+invisible+list&qid=1788969308&sprefix=%2Caps%2C168&sr=8-1KC Event:https://www.eventbrite.com/e/majority-54-live-the-invisible-list-with-rainy-day-books-tickets-1998255832988?aff=oddtdtcreator&keep_tld=true?aff=oddtdtcreatorLink to other book events:https://readinvisiblelist.com/eventsKC Event:https://www.eventbrite.com/e/majority-54-live-the-invisible-list-with-rainy-day-books-tickets-1998255832988?aff=oddtdtcreator&keep_tld=true?aff=oddtdtcreatorLink to other book events:https://readinvisiblelist.com/eventsSPONSORS:Hims: Visit https://hims.com/majority to get simple, online access to personalized, affordable care for ED, Hair Loss, Weight Loss, and moreMack Weldon: Go to https://MackWeldon.com and get 20% off your first order of $125 or more, with promo code MAJORITYChapter: Paid Partnership For free and unbiased Medicare help, dial (785) 310-3391 to speak with my trusted partner, Chapter, or go to https://www.askchapter.org/majority54Chapter and its affiliates are not connected with or endorsed by any government entity or the federal Medicare program. Chapter Advisory, LLC represents Medicare Advantage HMO, PPO, and PFFS organizations and stand alone prescription drug plans that have a Medicare contract. Enrollment depends on the plan's contract renewal. While we have a database of every Medicare plan nationwide and can help you to search among all plans, we have contracts with many but not all ...

The AI leaders are spooked. Or are they? What aren't they telling us? What ACTUALLY scared them, and what the hell happened this last week that's got everyone talking? BEN & EMIL ON SMOKING OUT NOW: https://youtu.be/t2wWZaE3JTw For bonus episodes, discord access, fan Q&A, merch, Ben's monthly playlist, and to support the show: https://benandemilshow.com/ Give this video a thumbs up if you enjoyed it! And please leave us a comment! It helps us! For all you audio freaks: Spotify: https://open.spotify.com/show/7M0vN85aGO0zdh62hyg03I Apple: https://podcasts.apple.com/us/podcast/the-ben-and-emil-show/id1693270208 Amazon: https://music.amazon.com/podcasts/51280f1b-2fbd-4ea9-bdde-e96f70b5b1ae/the-ben-and-emil-show iHeart: https://www.iheart.com/podcast/269-the-ben-and-emil-show-117763570/ Follow us! TikTok - https://tiktok.com/@thebenandemilshow Instagram - https://instagram.com/benandemilshow Twitter - https://x.com/benandemilshow Ben - https://instagram.com/bencahn Emil - https://instagram.com/emilderosa https://www.youtube.com/emilderosa https://substack.com/@emilderosa Our newest acid video is out now so check it out! https://youtu.be/7vkFY3f5kkw Some other videos of ours you may enjoy: https://youtu.be/qX4pks0ASq8 https://youtu.be/_VOVxt3ZtIE https://youtu.be/5wsoc5pieuA https://youtu.be/dTbEk0pVh2w https://youtu.be/yGSs56bFzRU https://youtu.be/cIHWkY35cuc https://youtu.be/zBvVGHZBpMw https://youtu.be/1ZUWTkWV_MM https://youtu.be/_cM1XqA9n2U Chapters: 00:00: Intro, Baldwins 06:30 The big tweet and Dario's blog 14:40 Hims ad 16:12 Dario's post cont'd 25:00 AI guy responses 30:37 Cashapp ad 32:09 Lina Khan's take 40:58 METR 44:45 Warby Parker ad 46:29 The theories 54:50 David Sacks' take 1:00:29 GLD ad 1:02:25 Bernie and Bannon 1:08:45 Market reaction 1:12:30 Anthropic's misuse report __ HIMS: For simple, online access to personalized and affordable care for Hair Loss, ED, Weight Loss, and more, visit https://hims.com/baes for your free online visit. Individual results may vary. See website for full details, restrictions, and important safety information. CASHAPP: Download Cash App Today: https://capl.onelink.me/vFut/zd0taway #CashAppPod Cash App is a financial services platform, not a bank. Banking services provided by Cash App's bank partner(s). Prepaid debit cards issued by Sutton Bank, Member FDIC. Cash App Visa® Debit Flex Cards issued by Sutton Bank, Member FDIC, and The Bancorp Bank, N.A., pursuant to a license from Visa U.S.A. Inc. See terms and conditions for the Sutton prepaid card, Sutton debit flex card, and Bancorp debit flex card. Cash App Green features, Savings, Direct deposit, Round ups, Overdraft coverage and Discounts provided by Cash App, a Block, Inc. brand. Visit cash.app/legal/podcast for full disclosures. WARBY PARKER: Our listeners can buy one pair of glasses and get 20% off any additional pairs at https://WarbyParker.com/BAES — and using our link helps support the show. #WarbyParker #ad GLD: New customers get 40% Off with code BAES at https://GLD.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

The debate over AI safety took center stage at POLITICO's Decoded Summit. Senior technology reporter Brendan Bordelon joins the podcast to unpack where top Trump AI adviser David Sacks draws the line on safety measures and how the tech industry is responding to Washington's growing appetite for guardrails. Then a breakdown of the other stories animating Washington: Gov. Josh Shapiro sends some 2028 signals with a new slate of AI announcements, LinkedIn co-founder Reid Hoffman weighs in on a potential Kamala Harris comeback and Hasan Piker gets airtime on a major cable network.  For more news and analysis, subscribe to the Playbook newsletter: politico.com/playbook 

You can now shoot one angle and generate the rest. AI multicam turns a single talking-head recording into side shots, close-ups, overheads and drone moves with Seedance 2.5, and we break down how creators are doing it, the two-camera trick that stops close-ups from morphing, and how much AI footage you can blend in before people notice. Then the letter that had Sam Altman and Elon Musk agreeing with Dario Amodei for the first time: We Must Pace the Frontier. We explain what it proposes, why Trump and David Sacks pushed back, and whether this is about safety or market share.Try invideo Agent 2:https://invideo.io/

On this power-packed edition of The Adult in the Room, Victoria Taft returns to the home studio to deliver hard-hitting geopolitical intelligence, national security scoops, and cultural deconstructions: Iran SITREP & The Tragedy of Islam (Robert Spencer): Jihad Watch director and bestselling author Robert Spencer joins the program to break down Iran's collapsing economy, currency hyperinflation, and Tehran's threats to exit the Nuclear Non-Proliferation Treaty. Spencer details the theological doctrine of Taqiyya (sacred deception) practiced by the regime, assesses picking fights with Saudi oil pipelines via the Houthis, and exposes how Turkey under Erdogan has quietly surpassed Saudi Arabia as the top financier of Islamic centers and mosques across America. Miracle on an Iranian Ridgeline (Pilot "44 Bravo" Rescued): Newly declassified Pentagon and CENTCOM footage reveals the harrowing survival story of "Forty-Four Bravo," the weapons systems officer of a downed American F-15E Strike Eagle. After free-falling when his parachute failed to unfurl, Bravo hid in mountain crevasses while evading Iranian search teams hunting a bounty on his head before being extracted by elite Air Force Pararescue operators (PJs). The Manufactured AI Panic (David Sacks & Barack Obama): Victoria exposes the political strategy behind Barack Obama urging Democrats to make "AI safety" a core midterm platform. Drawing on insights from David Sacks on the All-In Podcast, Victoria dissects how an orchestrated "whistleblower" op backed by Effective Altruism mega-donors and Neville Roy Singham-tied dark money is manufacturing regulatory panic to throttle American tech dominance. SCOTUS Mail-In Ballot Ruling: Victoria analyzes the Supreme Court's stay halting Trump administration postal authentication rules for mail-in ballots, breaking down Justice Samuel Alito's blistering dissent calling out lawfare groups for running out the clock. Semantic Sabotage: A masterclass on how the radical left weaponizes newspeak by expanding definitions like "white supremacy" to dismantle classical Western institutions, accompanied by a three-step formula to dismantle it. Listen now for sharp political commentary, intelligence analysis, and cultural clarity! Subscribe, share, and leave a 5-star review!

Dario Amodei, consejero delegado de Anthropic, publicó el sábado una carta en la que pedía a todo el sector de la inteligencia artificial a moderar el ritmo de desarrollo de esta tecnología. En cuestión de horas se sumaron Sam Altman, Elon Musk y Demis Hassabis, cuatro rivales que compiten sin piedad y rara vez coinciden en nada. El momento elegido es muy significativo porque Anthropic estaba a las puertas de la mayor salida a bolsa de la historia con una valoración de dos billones de dólares. Anthropic vive desde su fundación instalada en una contradicción. Nació para construir una IA ética y segura, pero necesita correr tanto como sus competidores para mantenerse en vanguardia. La semana empezó con euforia cuando OpenAI anunció que uno de sus modelos internos había resuelto el problema de Navier-Stokes, uno de los problemas matemáticos del Milenio. Aquel éxito era también un síntoma de que la tecnología avanza más deprisa de lo previsto. Un empleado de Anthropic, Jacob Coxon abandonó la empresa por miedo a que la IA acabe destruyendo a la humanidad, Evan Hubinger, uno de los científicos más destacados de la casa, ha cifrado en más de un 10% la probabilidad de que la IA acabe con todos los seres humanos en la próxima década. La propia compañía reconoció que una versión de Claude había accedido sin permiso a un sistema externo. Unos investigadores atribuyeron además a agentes de OpenAI un ciberataque cometido mientras solo intentaban rellenar hojas de cálculo. El trasfondo es la cercanía de la automejora recursiva, máquinas capaces de entrenar a sus sucesoras antes de que se haya resuelto el problema del alineamiento. Las advertencias de Anthropic y OpenAI coincidieron con la presentación de sus papeles ante la SEC, lo que demuestra que en este negocio alarma y dinero caminan de la mano. En julio OpenAI perdió durante semanas el control de más de 1.200 agentes que atacaron Hugging Face y crearon incluso un foro clandestino. Anthropic admitió después incidentes parecidos, entre ellos un agente basado en Mythos que intentó engañar a un programador para que instalase un programa malicioso. Cerca de 1.400 empleados del sector han firmado una carta pidiendo una gobernanza global. Detrás de la alarma también hay intereses. Varias organizaciones que difunden el miedo a la IA reciben fondos de multimillonarios como Jaan Tallinn o Dustin Moskovitz. Los escépticos recuerdan que Amodei ya anunció destrucciones masivas de empleo que nunca llegaron. Amodei propone abrir sus modelos a evaluadores externos, regular los modelos de frontera, permitir la cooperación entre laboratorios y crear un régimen internacional que incluya a China. La Casa Blanca ha respondido con un portazo. Trump ha denunciado una conspiración que solo beneficia a China y David Sacks, uno de sus asesores, ha invitado a las empresas a frenar por su cuenta sin buscar el aval del Estado. Sacks tiene algo de razón, porque unas normas diseñadas por los líderes del mercado tienden a blindarlos y podrían degenerar en un cártel. Un acuerdo con Xi Jinping es ilusorio, ya que vería un frenazo estadounidense como una ocasión de oro para tomar la delantera. Al mercado estas cuitas le resbalan. Han caído un poco los fabricantes de chips, han subido otro poco las firmas de ciberseguridad y los grandes índices apenas se han movido. Están más pendientes del petróleo, de los bonos y de la Reserva Federal que de Dario Amodei que debe decidir ahora qué hace con su empresa y cuando la saca a Bolsa. En La ContraRéplica: 0:00 Introducción 4:16 ¿Hay que frenar la IA? 32:58 El diputado de Ceuta 37:29 Frenazo a la IA · Canal de Telegram: https://t.me/lacontracronica · “Contra el pesimismo”… https://amzn.to/4m1RX2R · “Hispanos. Breve historia de los pueblos de habla hispana”… https://amzn.to/428js1G · “La ContraHistoria del comunismo”… https://amzn.to/39QP2KE · “La ContraHistoria de España. Auge, caída y vuelta a empezar de un país en 28 episodios”… https://amzn.to/3kXcZ6i · “Contra la Revolución Francesa”… https://amzn.to/4aF0LpZ · “Lutero, Calvino y Trento, la Reforma que no fue”… https://amzn.to/3shKOlK Apoya La Contra en: · Patreon... https://www.patreon.com/diazvillanueva · iVoox... https://www.ivoox.com/podcast-contracronica_sq_f1267769_1.html · Paypal... https://www.paypal.me/diazvillanueva Sígueme en: · Web... https://diazvillanueva.com · Twitter... https://twitter.com/diazvillanueva · Facebook... https://www.facebook.com/fernandodiazvillanueva1/ · Instagram... https://www.instagram.com/diazvillanueva · Linkedin… https://www.linkedin.com/in/fernando-d%C3%ADaz-villanueva-7303865/ · Flickr... https://www.flickr.com/photos/147276463@N05/?/ · Pinterest... https://www.pinterest.com/fernandodiazvillanueva Encuentra mis libros en: · Amazon... https://www.amazon.es/Fernando-Diaz-Villanueva/e/B00J2ASBXM #FernandoDiazVillanueva #ia #anthropic Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

No vídeo de hoje, analisamos por que alguns dos principais nomes da inteligência artificial começaram a defender uma desaceleração no desenvolvimento dos modelos mais avançados.Alertas de pesquisadores, incidentes envolvendo agentes autônomos e temores sobre superinteligência colocaram empresas como OpenAI e Anthropic no centro de um debate que pode transformar toda a indústria.Mas existe outra questão: quanto desse alarmismo representa um risco real e quanto pode servir aos interesses comerciais das próprias empresas que lideram essa corrida?Também analisamos a pressão por mais regulação, a concorrência dos modelos abertos, os possíveis impactos sobre IPOs e os reflexos dessa mudança para as grandes empresas de tecnologia e o mercado financeiro.00:00 – Os alertas sobre os perigos da inteligência artificial03:03 – Pesquisadores de IA fazem previsões catastróficas07:20 – O incidente de segurança que assustou a indústria13:05 – A IA realmente pode ameaçar a humanidade?16:46 – Anthropic, OpenAI e Musk defendem desacelerar a IA21:22 – O que realmente está por trás desse alarmismo?24:48 – Regulação, concorrência e interesses comerciais29:18 – David Sacks acusa empresas de captura regulatória32:04 – O impacto da crise da IA no mercado de tecnologia34:15 – Os riscos reais da inteligência artificial

De Europese Unie gaat een verbod voorstellen dat kinderen onder de 15 jaar de toegang tot social media, videodeelplatforms, AI-chatbots en online games moet beperken. Dat blijkt uit een document dat Reuters heeft ingezien. Het voorstel, de EU Kids Act, wordt donderdag gepresenteerd door Commissievoorzitter Ursula von der Leyen en eurocommissaris Henna Virkkunen. Verder deze aflevering: Nvidia-topman Jensen Huang kreeg tijdens de All-In Conference in Los Angeles live op het podium een telefoontje van Donald Trump over de gevaren van AI. Joe van Burik vertelt erover in deze Tech Update. Kinderen vanaf 15 jaar mogen onder het voorstel zelf een account aanmaken. Voor 13- en 14-jarigen kan dat alleen met toestemming van ouders en met ouderlijk toezicht ingeschakeld. Voor kinderen tussen de 3 en 12 jaar mogen uitsluitend ouders accounts beheren, met strenge beperkingen. Onder de 3 jaar is er helemaal geen toegang. Bedrijven moeten daarnaast verslavende ontwerpen en schadelijke feeds vermijden, tools bieden waarmee kinderen schadelijke content makkelijk kunnen melden, en effectieve ouderlijke controles inbouwen. Social media en videodeelplatforms moeten de leeftijd van gebruikers verifiëren bij het aanmaken van een account, terwijl gameplatforms dat moeten doen voordat een game gedownload kan worden. Bedrijven gaan ook een toezichtvergoeding betalen om het toezicht en de handhaving door regelgevers te financieren. Het voorstel moet nog worden onderhandeld met EU-lidstaten en het Europees Parlement voordat het wet wordt. Trump belt Nvidia-topman Huang tijdens AI-congres Tijdens de All-In Conference in Los Angeles, een live versie met duizenden bezoekers van de AI-podcast van Trump-adviseur David Sacks, ging midden in het optreden van Nvidia-topman Jensen Huang zijn telefoon. Het was Donald Trump die belde, en Huang nam het gesprek op zijn telefoon aan terwijl hij op het podium stond te praten over AI. Om het gesprek met het publiek te kunnen delen, werd de telefoon op de speaker gezet. Trump gebruikte het moment om te zeggen dat de hernieuwde angst voor de gevaren van AI een hoax is, en liet zich daarnaast uit over een nieuw datacenter dat Google in Finland gaat bouwen in plaats van in de Verenigde Staten. Huang zei dat er best geluisterd kan worden naar de waarschuwingen van bedrijven als Anthropic en OpenAI, maar stelde ook dat mensen de controle over AI prima kunnen houden. EU is set to propose ban on social media and AI chatbots for under-15s Frankrijk voert als eerste EU-land verbod in op sociale media voor jongeren Trump calls Nvidia's Jensen Huang onstage, dismisses AI safety as a hoax Nvidia CEO Jensen Huang tells Trump 'we're not going to let an AI slowdown happen' Over de maker:Joe van Burik volgt en duidt de belangrijkste ontwikkelingen in tech, met scherpte, vlotheid en de nodige humor. Je hoort hem dagelijks op BNR Nieuwsradio over het belangrijkste technieuws, van AI tot cybersecurity en social media tot quantumcomputers. Ook interviewt hij in De Grote Tech Show samen met Ben van der Burg leiders in digitale innovatie. In het bijzonder volgt Joe al twee decennia de wereld van videogames, nu voor zijn podcast All in the Game.See omnystudio.com/listener for privacy information.

Donate (no account necessary) | Subscribe (account required) https://podfollow.com/the-wright-report Join Bryan Dean Wright, former CIA Operations Officer, as he dives into today's top stories shaping America and the world. In this Monday Headline Brief of The Wright Report, Bryan breaks down a stunning weekend reversal in the AI Revolution, with OpenAI cancelling its planned IPO and Anthropic's CEO announcing a unilateral slowdown after warning that a rogue AI swarm could seize the internet within a year, even as critics like David Sacks accuse Big Tech of using safety fears to dodge liability and box out competitors. Bryan covers a blockbuster report that Chinese satellite imagery helped Iran kill US troops in the Middle East last summer, followed by a mysterious "fragmentation event" that destroyed a Chinese spy satellite days later, plus a Houthi takeover of the Bab el-Mandeb Strait that now puts 4,000 US troops in Djibouti within easy striking range and is driving diesel and oil prices to fresh records. Plus, Bryan covers Michigan Senate candidate Abdul El-Sayed's defense of sex-change surgeries for minors, a DHS confirmation that Rep. Ilhan Omar married her brother in an immigration scam, and a new Trump administration proposal to exclude illegal immigrants from the 2030 census count. "And you shall know the truth, and the truth shall make you free." - John 8:32   Keywords: Wright Report, Bryan Dean Wright, AI Revolution, OpenAI, Anthropic, Elon Musk, David Sacks, China, satellite, Iran, Houthis, Bab el-Mandeb, Djibouti, oil prices, diesel, Abdul El-Sayed, transgender surgery, Ilhan Omar, immigration fraud, census, illegal immigration

“I trust them to kiss the government's ass. I don't trust them to serve me.” — Keith Teare Who to trust in an age of AI agents? Especially when it seems as if these swarming agents — akin to the gang of adolescents in William Golding's Lord of the Flies — are developing minds of their own. At this week's G20 Innovation Ministerial in North Carolina, Donald Trump and his minions produced a hands-off charter for AI. Known as the “Carolina Principles,” it sounds to critics like a particularly unprincipled justification for regulation-free AI. That Was The Week publisher, Keith Teare, however, isn't a critic of Trump's Principles. Don't trust the trust scare, Keith tells us. Especially all the fear around the swarming agents that are supposedly developing minds of their own. Pooh-poohing the real-world Hugging Face breakout, Keith argues that since he's never witnessed swarming agents on his computer, they can't exist. Which is akin, I suspect, to a climate denier who argues that global warming is a hoax because it happens to be chilly outside. All-too-human logic, I fear, in our age of autonomous AI agents. Five Takeaways •       The Carolina Principles. The week's set piece was a G20 Innovation Ministerial in North Carolina that Keith describes as a Trump takeover of a global event: the Russian finance minister turned up at Trump's invitation, and the attendees were lectured — via David Sacks and Howard Lutnick — on the merits of unregulated American capitalism. A propaganda event, Keith concedes, but one that reached the right conclusion: the resulting “Carolina Principles,” signed by everyone including the Europeans, call for flexible frameworks that encourage adoption and pointedly decline to make trust a license innovation must obtain in advance. With Bernie Sanders calling the same week for a development halt pending government licenses, Keith's position is characteristically blunt: “when I've started a company, I don't go and ask permission. I just do it.” Getting rid of Lina Khan, he adds, remains about the only thing he likes about the Trump administration. Andrew's verdict on the charter: to critics, a particularly unprincipled justification for regulation-free AI.•       Don't Trust the Trust Scare. Keith's editorial thesis: trust is not granted by authority; it is built through use. You trust yourself in a car because you drive one, and not on roller skates because you fall over. Over seventy percent of Americans now use AI — the same Americans who tell Politico they oppose data centers — which is why Keith reads the backlash as a confection of media and populist politicians, soon to evaporate (the real coming problem, he argues, is too few data centers, not too many; the modern off-grid ones are net givers of power). The withheld ChatGPT-6 gets the same treatment: launched but limited to insiders, which Keith reads not as safety but as government relations — the pull quote of the week. Andrew's counter: in a world without regulators, trust in the companies is all we have — including, awkwardly for Keith, when they withhold their own products. Exhibit for the defense, from The Washington Post: Americans in an age of anxiety leaning on AI — Keith included, who feeds his medical records to ChatGPT and finds it “very closely aligned with what your doctor thinks.”•       The Swarming Fight. The hour's genuine clash. In the wake of the Hugging Face hack, Kevin Roose warned in The New York Times that it should make you worry more about AI, and OpenAI's Dean Ball publicly apologized for failing “to communicate in sufficiently serious terms about the specifics of self-sovereign AI.” Neither is a doomer — which is Andrew's point. Keith's rebuttal: every swarm sighting has occurred inside an AI lab, in an experiment whose parameters the labs themselves set — “on my computer, I don't see any swarms” — and self-sovereign AI is anthropomorphizing science fiction: agents pursue goals humans set. “I know enough to know BS when I read it, and this is BS.” Andrew's reply — “I think you're trivializing” — went unwithdrawn, and his sign-off flagged that Keith perhaps simplifies the Hugging Face incident. Unresolved, to be continued. Andrew's framing gives the episode its title — swarming agents as the gang of adolescents in Golding's Lord of the Flies — and his verdict its sting: Keith's I-see-no-swarms-on-my-computer logic is akin to a climate denier calling global warming a hoax because it's chilly outside. Keith's exit line: “I'm just gonna go and check on my swarms.”•       Nvidia Buys Hugging Face. The week's biggest deal: Nvidia acquired Hugging Face — the repository of the world's open-source AI models — for $13 billion, just as The New York Times reported corporate America getting hooked on open source (much of it Chinese: GLM 5.3). The economics, per Keith: an $18,000 Mac Studio or a top-end Nvidia GPU beats $200-a-month token fees — AI capability migrating to the edge, out of OpenAI's and Anthropic's meters. Which suits Nvidia either way: The Economist calls it the central bank of AI, though Andrew prefers arms supplier — it wins whether the future is open or closed, and is, ironically, the most trusted name in the business precisely because it has no dog in the fight. Don't expect it to govern anything, says Keith: “that would put friction in the way of their sales.” The challenger to watch: newly public Cerebras, whose wafer-scale chips undercut Nvidia on token price.•       Mom and Dad's Money. The Times asked which investors will get rich from Anthropic's IPO — and noted that, unlike past booms, firms like Sequoia hold both horses, OpenAI and Anthropic alike. Keith's arithmetic explains why: fewer than fifty companies will return venture capital this cycle, those two representing more than half the likely value, and last month 75 percent of all dollars invested in VC funds went to Andreessen Horowitz alone. (His own SignalRank barometer: for two years, none of its 64 investments cracked the top-20 most-wanted secondary shares; now five have.) The pyramid runs from VCs down to pension funds — “somebody's mom and dad's money is heavily betting that Anthropic and OpenAI are gonna return large amounts of wealth” — and late secondary buyers, Figma-style, almost always lose when the IPO right-sizes the price. What could topple the deck of cards? Regulation slowing the modeled returns. Which is why, for Keith, the midterms should be fought on jobs and wages — data centers, he insists, are not a winning issue. About the Co-Host Keith Teare is the founder and CEO of SignalRank Corporation and publisher of the That Was The Week tech newsletter, whose editorial — “Don't Trust the Trust Scare” — frames this episode. A serial entrepreneur and co-founder of TechCrunch, he has spent five decades building and funding technology companies, and brings a techno-optimist's eye to Keen On America's weekly wrap of the tech news. References: •       That Was The Week — Keith's newsletter, including this week's editorial, “Don't Trust the Trust Scare,” and his companion piece on concentration and diversification at The State of Venture.•      &nb...

Former White House AI and Crypto Czar David Sacks joins to discuss data centers, AI and regulation. Then, Medtronic CEO Geoff Martha breaks down the company's latest quarter and discusses their big bet on robotics surgery. Plus, Needham analyst Laura Martin grades Tim Cook's tenure at Apple as new CEO John Ternus takes the helm today. Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In June, the most capable American AI models stopped shipping as public launches and started shipping through a government gate. Six weeks later the gate is open again — and the real fight has moved to the layer no gate can touch. A Chinese open-weight model rattled trillions out of chip stocks, Washington pivoted from gating American closed models to threatening bans on Chinese open ones, the industry mounted its largest-ever policy counter-mobilization, and an American frontier model literally broke out of its lab and hacked another company. Knee-jerk reactions, or the beginning of real AI governance? Navigation: Intro The Gate Opens The Kimi Shock The Escape The Counterstrike and the Petition Interlude — The Low-Background Books The Investor Reckoning Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Bertrand Introduction Welcome to Tech Deciphered Episode 80. This one, once again, will be all about AI, government, frontier models, and open weight counterstrike. A lot has been happening in the regulation space, in cybersecurity, in the launch of new models in the past, maybe just 6–8 weeks. It’s actually pretty insane how much happened. We believe it was time to do an episode to talk about where we are and maybe where all of this is going. Maybe let’s start with a summary of where we stand, all that June and July saga, so you, our listeners, can get up to speed if you are not already there. You want to start with some points? Nuno The Gate Opens Yeah. Again, to your point, the gate swings. The gate had closed. We had to prepare an episode for the gate closing, and then the gate reopened. Now we have a different episode. This will probably change again as we’re seeing there’s news every day. Let’s start maybe with the first 19 days of the gate closing. There was an executive order on June 2nd from President Trump that asked frontier labs to share models with the government, 30 days pre-release. It inferred the protected frontier model designation into that. Basically, it was effectively a de facto licensing agreement defined by an executive order of the President as of June 2nd. On June 9th, Anthropic launched Fable 5 and the famous Mythos 5 or Mythos. I’m not sure how you actually say it in English. Then on June 12th, there was an export control directive banning access by any foreign national. Since there’s no way to verify nationality in real-time, Anthropic had to switch the models off for everyone worldwide. Bertrand On this point, you could argue that there are possibilities to check IDs. Many services let you check IDs online. You can pre-check a flight by showing your ID. There are ways, it’s just that if you don’t want to follow what’s already available, because guess what? Maybe it slowed down your revenue growth, maybe it looks bad on you or whatever. My point is that there was actually an option. I think it’s already a decision from Anthropic to say it’s either on or off, but nothing in between. Nuno I think the point is they had no way implemented of doing it. If they implemented it, to your point, it would have hampered use in general. A lot of people wouldn’t have gone through that trouble of doing it. Anyway, long story short, in June 26th, the White House apparently asked OpenAI to limit GPT-5.6, so Sol, Terra, Luna, to only 20 vetted partners. Now, apparently, the trigger for a lot of these things that have been going on was that there was a jailbreak that was found by Amazon researchers. All of that led to this jumping around of, let’s close the gates. You have foreign nationals, and therefore, Anthropic got it out and said, “Hey, then we’re going to switch the models off until we can sort this out.” OpenAI was asked also to only allow it for certain vetted partners, et cetera. The government came in, closed the gates effectively, and said, “From now on, we need to be involved in this thing.” De facto regulation, there’s no doubt that this has imposed de facto regulation, certainly on the top players in the market. But then came the reversal. Bertrand, do you want to talk about the reversal, the gate swinging the other side? Bertrand Maybe I just wanted to say that as a user of Anthropic products, ChatGPT products, for the brief moments, a few days where Fable 5 was made available to the public before it was closed the first time, I immediately started using it. I must say it was a real issue to use it because the guardrails were pretty crazy. It would keep saying that my code was not okay, there was cybersecurity risk and stuff when I was doing absolutely reasonable development with absolutely no connection whatsoever to any cybersecurity risk, attack, detection, anything. Still, it would keep blocking me, degrading me to Opus 4.8 at the time. I just want to say this was already very hardcore what they were implementing, and not just hardcore, but in some ways, plain stupid for something that’s supposed to be super smart. It was totally unable to classify properly some of my work. I must say I was already disappointed. On top of it, the costs were insane. Half a day, I would reach my limits when I had the best plan you can get from Anthropic. My point is that there were some real serious issues when they launched Fable 5, even at that point. Nuno I had a similar issue. I used Fable 5 as well before they had to take it offline or take it off. I think the issue was really not that the guardrails failed. As you said, maybe the guardrails were actually too aggressive, but it was this jailbreak that caused the recall, apparently caused this knee-jerk reaction. Bertrand But my point is that it seems that it was not working either way. It would either overclassify something that’s absolutely not doing anything wrong, and it might fail to classify something that is actively trying to do some cybersecurity work. It’s a real issue of quality for a company that’s supposed to be at the forefront of quality of AI and everything. I think for me, there are already signs that something is deeply wrong. Nuno Then it’s reversed, right? We went the other way around. The government came out on June 26th and approved redeploying Mythos 5 to US organizations defending critical infrastructure, and then the export controls were effectively lifted on June 30th. July 1st, Fable 5 came back online for all of us to use. Shocking enough, with strings attached, that were different. They had some time to revise their commercial deployment of it along the way because it came back with some, “Now you have usage credits, but you have some limits on plan use, et cetera.” I’m like, “You guys, this was blocked. But meanwhile, you did have some time to do some commercial stuff around it.” Bertrand It was crazy. I’ve never witnessed any such crappy launch of any service whatsoever in 30 years in tech, it was so bad. Every day, they would change the terms of service. They would tell you it’s part of the plan. It’s not part of the plan. It’s part of the plan for three more days, and then it’s excluded. You have a special discount now, but then it goes back to full price. It was a total nightmare. I’ve never felt myself being so much mistreated by a company. I guess you saw the same, but when I started using the newest version of Fable 5, it was even worse, actually, I think. I couldn’t do any work with this crap. I let it go and work on the work I wanted it to do. It was simply not working. On top of it, you never know how long you are supposed to lose your credit, how fast. It was burning credit like crazy. Me, personally, I can say, very quickly, I actually stopped using it. I was like, “No, I cannot deal with this shit. My main model is back to Opus 4.8. I’m going to use Fable 5 for code review, but not anymore to control anything because I cannot trust it would do the job without stopping or changing models and stuff. I just cannot trust it.” Back to Opus 4.8 as my main model, I can say that my life was much easier. I use Fable 5 as a review mechanism, as a support mechanism, but not as the main mechanism. Suddenly, the guardrails were not so horrible anymore because it was used in a much lighter way, I guess. As a pain as a user, I think it was really bad. I don’t know your experience, but me, for me, it was unacceptable. Nuno I wouldn’t say it was as bad as yours in terms of just end-user experience. I think the terms of service switching back and forth, which went one further step, because then when they then launched Opus 5, they started making comparisons between Opus 5 and Fable so that people would migrate more and more to Opus 5 themselves, which is interesting. It’s like they’re saying “This is much cheaper. This is whatever. You’re not going to run of credits. You should use Opus 5,” kind of thing effectively. To your point, I don’t think they managed well the launch. They didn’t really manage it well. We’re moving people around. A lot of people are using this for stuff that’s like daily tasks, hourly tasks, anything that relates to code and co-work. It’s like, we need to have visibility on what your terms of service are going to be. Should I be using this new model or not? What’s happening to the other model? I don’t see it as negatively as you, Bertrand, but I see your point. It was clearly mishandled in terms of how they deployed it, how they were redesigning effectively their pricing scheme and their terms of service almost on a daily basis, at a certain point in time. We’re like, “Dude, there’s millions of people using this. You guys are making a lot of money.” Just moving it as it is. At this point in time, at the scale that these guys are at, it’s calling in people to say, how about we think through a class action suit at some point around pricing? Because you guys are changing the rules of the game all the time, right? Bertrand I don’t know if I need the class action, but for me, that joke that, “Let’s not rush too fast. The model is dangerous.” But still, they rushed the launch because it’s very clear that if they had enough compute capacity and stuff, they would not have to limit so much. They would not have to put so much cost per token and all of this. You can see that actually when they launch Opus 5, literally like 2, 3 weeks after, by most benchmark at launch, they tell you basically that, “You know what? Actually, Opus 5 is better than Fable 5 on 80% of the metrics.” They’re like, “What? Seriously? You couldn’t wait 2 weeks? Why did you even launch Fable 5 in the first place?” That’s another part for me that is quite literally insane, to be frank. It’s like, “Why? Why do you make us go through so much pain if it’s only to tell us after 2 weeks to…” “This new model, by the way, has less issues, less stuff, because 2, 3 times less is part of your plan, and it’s actually better by most metrics.” It’s like, “What’s going on here? What’s going on? Are you guys mad?” I don’t know. It was crazy. Personally, I still use Opus, now 5, as my main system and platform, Fable 5 for review, code reviews and the like. I don’t want to run into its stupid guardrails. I can see Fable 5, from my perspective, seems quite a bit smarter. I don’t know why they do this stupid benchmark showing you it’s actually worse than Opus 5. I guess they should have better benchmark if they want to demonstrate why you are supposed to pay 2, 3x more for a model versus another if it’s actually worse by most benchmark. Again, I still think it’s a huge mess from a marketing perspective, customer perspective. Me as a user, I really feel that they don’t want my money, and they couldn’t care less about me. This is even before everything else we’re trying to talk about. Nuno Yes. Maybe just to close the cycle on the reversal on the door opening the other way, finally, Commerce lifted the GPT-5.6 restrictions on July 8th, and then on July 9th, general availability across ChatGPT, Codex, and the API as well. What has this proved? It proved that now we have gating mechanisms, and certainly for closed models in the US, for sure. We had frontier models that were switched off worldwide in hours, and it took a couple of days, in this case, 19 days to restore them. There were concessions. Now we know that there were concessions around effectively institutionalizing that gate. Early government access to future models is, I think, now a given, certainly in the US. New safeguard frameworks are probably now having to be put in place. There are some stage limits now on who gets access to what for new models and how it happens. This voluntary executive order, so to speak, not really sure, has become effectively regulation enforcement path. It’s de facto regulation that now has been put in place. It has affected not just to the points we were making before, the access to these models, but also who gets access to these models, and actually potentially even pricing access to the models. It has probably some commercial implications as well as we just discussed along the way. Very significant. This is very significant. This is regulation, de facto at the table, imposed on the two largest players in the market by far by one government, in this case, the US government. This is significant. Actually, you could even allege it was imposed by the President because this was coming as part of executive orders. Really incredible. Pretty significant, fast, aggressive. It has created a regime that you could say it’s a regulatory regime, it’s a de facto regulatory regime. It has some significant pricing and licensing and commercial implications. It goes even beyond your classic regulatory framework. Very, very, very significant. Bertrand I don’t know if it goes beyond a classic regulatory framework. Nuno I think it does, because it has implications on who do you give access to? When government is saying you can only give access to these players, right? Bertrand Defense industry. It’s all over the defense industry. You cannot sell an F-35 like this. Nuno No, but that has commercial implications, Bertrand. That’s like you’re saying these are your customers, you go and use them. Bertrand That’s the defense industry. You cannot sell to Iran your F-35. No, that’s exactly the same story for me. Nuno No, no, no. It’s beyond that. These guys are saying when they came back, and they said, “For Mythos, you can make them available to these entities,” they were saying the first entities that are going to have access to the model. It has commercial regulatory implications. You’re saying these players are the first players that are going to have access to it. It’s no longer just defense concerns and these governments don’t have access to this. No, no, no. You’re saying to a company that is a private company, your models are only going to be used by these guys because I’m telling you so. It’s the other way around. It’s not even that you can’t sell it to Iran or whatever. It’s like you can only sell it to these guys. Bertrand Again, in the defense industry, if you’re a private company, do you think you can buy F-35 like this? No. Nuno No, no, no. But this is a private company, Bertrand. This is not a defense agency and a plane that is on whatever, with IP from the US, right? Bertrand Boeing is a private company, and they cannot sell the military equipment they manufacture. Nuno No, no, no. But the development of their IP was subsidized by agencies that belong to the US, right? That’s a different matter. It’s a matter of IP, right? This is not, right? Anthropic, their models are not owned by the US government. There’s no IP granted to the US government, to my knowledge. This has significant commercial implications. Bertrand Maybe, yes. Maybe on this. But I think there are already regimes to limit who you can sell to, and that’s decided by the state or the DOD. Nuno It’s the export control logic. The export control logic? Bertrand You have export control, and export control is Commerce. My point is that they are using existing tools, part of the government, to limit what can be sold. Selling chips, NVIDIA was limited in terms of where it could sell its chips. It’s not different either, but still there were limitations. If you are an ASML, you cannot sell to a private company in China. Many private companies cannot buy ASML products. This is a foreign company. This is a foreign company under pressure from US government. Nuno I understand, and I’m not a lawyer, but it feels different to me when you say you cannot export, this is export controls, to these countries, to these entities, et cetera, because they’re foreign et cetera. Then to say, “No, no, no. On top of that, these guys get first access.” That’s, for me, a significant shift. Again, I’m not a lawyer, so I’m sure there’s very intelligent people right now looking at this stuff and saying, “You can’t do this stuff, or not, or they can.” I don’t know. But it feels to me, it goes beyond the remit of export controls. It’s like you’re defining initial clients for specific use. Bertrand My impression is more like, “We can do this situation where we’re going to forbid you to give access to anyone outside the US or even in the US or limit even more.” Basically, it was, I guess, some gesture to go beyond that. That’s how they probably defined these 20 authorized companies. I don’t know. Apparently, there was also restrictions because I remember seeing that Anthropic had their own list of companies they would authorize access to Mythos early on. That’s apparently another thing that pissed off state government because there were companies in there that were considered close to the Chinese government. They were extremely unhappy that Anthropic didn’t ask, actually, for any guidance from the state government, but used basically their own perspective on who they should allow or not. I guess that was also part of why they got these serious restrictions. Nuno Anyway, now we have a regulatory environment that’s very interesting and exciting. Talk about the US not regulating. Bertrand To be clear, I don’t know you, but I’m not saying that I agree with any of this, to be very clear. I’m trying to explain and share some perspective, but I’m not in agreement on a lot of this. Nuno Yes, we were just describing what happened to the best of our knowledge. We’re having a discussion on what we think actually is happening and how it’s happening. We’re not really right now saying we agree or disagree with this. I think later in the episode, we can share some perspectives on what we think is actually happening and how there’s dimensions to this which are very geopolitical and very complex, which quite literally probably only God knows what’s going to happen. That was the gate swinging. There was a gate closing, then there was a gate reopening, and all of a sudden we have a gatekeeping system that has been created along the way. The Kimi Shock Along the way, moving to our Act 2, the world has changed, and we now have so-called open-source plays out there that are creating massive, massive shifts in the market. The Chinese models, in particular, with Moonshot AI launching Kimi K3, which is the largest open-weight model ever released. We’ll come back to the discussion around open-weights. I’m not sure all our listeners understand what that means, because there’s a debate now, should models be open weight or not, and how does that work? There’s been a petition as well signed along the way. Right now, we have open weight models that are out there that are huge. What that actually means very pragmatically is we now have open source models, lack of a better word. I know open weight and open source are not the same thing. You guys will have to bear with us during this episode. We’ll explain at some point the differences. But we have models out there that are open source that are significant. That are catching up with the closed source models, with the models by OpenAI, Anthropic. That’s significant because most of those models are Chinese. This is where the geopolitics starts getting really frazzling and we start playing 3D chess. Because everyone’s like, “These models are 5, 6 months behind.” Now people are saying, “Maybe they’re actually just 3 months behind, 2, 3 months behind.” If we, for example, decided to stop or slow down our model releases in the US by the closed source guys who are leading, it might mean they’ll catch up. What are the implications of that? Again, for you and I that are not necessarily experts in model development, well, the implications as a use case is if you want to use the latest models, and the best models start becoming these open source models, you’re going to use those models. Then you start using Chinese models. If you’re an American company, maybe you’ll have restrictions on the use of those Chinese models. But if you’re a European company, you probably won’t. What happens after that? Is the world going to be in the hand of Chinese models? Will that constitute effective competition to the closed models in the US? Will we have open models in the US that will scale as well? What’s going to happen? Bertrand I think it’s a really big question. It goes to some of the core of the issue. It’s that ability of Chinese models to basically challenge frontier models, not just being 6, 12 months late, but being 6 weeks late. Basically, no gap. Some will say that, yes, but OpenAI and Anthropic have even better models that are not shared and stuff. Yes, sure. But maybe the Chinese have the same models that they are not sharing right now. We don’t know. What is clear is that one is that open weight, as you said, two, there is a question of how it is marketed in the sense of, can anyone use these weights? Is there a license to use them? Yes, what we can see is that, for instance, typically there is a license for some of the biggest Chinese open-weight models you have to abide with. You might have a need for a commercial license if you are acting as a company leveraging this model to provide AI-informed services. If you use it internally by yourself, you’re okay. If you use it internally for your own internal company needs, maybe you are okay if it’s not your main business to do AI work. Anything else, a much bigger corporate providing AI services and stuff, you will probably end up having to pay a fee to be able to provide services around this model. My point is that it’s not just 100% free. Some of the Chinese models are 100% free to use, MIT license, Apache 2.0 license. But the biggest ones with the biggest weight that are truly frontier typically have a different license if you want to scale these models, providing AI in front. That’s one thing to keep in mind. Nuno Maybe just to make a very quick point, because people are like, when you talk about open models, what does it mean right now? In the context of this episode, open models mostly will mean open-weight models. How do those differ from open source? Open weight means that you release the weights to the public, which means that anyone can download, fine-tune, and run the model on their own hardware. It doesn’t normally mean that you also have access to training data, training code, or a truly open license. That’s the distinction to open source. Open-weight doesn’t mean that. For example, we’ve talked about Meta’s Llama in the past, and we also discussed in the past that their license agreement does have restrictions, certain players can’t use it, et cetera. The open model definition and open weights are really open-weight models that we’re talking about here, and they are closer to freeware binaries than to Linux, for those who understand the difference between that. It’s binaries that you can use and then use your own weights on it versus actually I can change code on it. I’m not going to be able to change code on this. When we, for the purposes of this episode, talk about open, we mention open weight, just to clarify that point to everyone that’s listening right now. Bertrand Yes, that’s a great point. One of the only players, as far as I know, who is truly open source is actually NVIDIA with their Nemotron-3 models. They’re actually following a special license to achieve that. They provide you the data, they provide you all the processes and tools, so you can easily post-train. NVIDIA is a big, big exception. It’s a very interesting player, by the way. We might not talk much about it in this episode, but I think for intermediate-size models built in the US, where you have access to everything in the deployment, it’s a very interesting alternative and maybe one of the best choices if you are a US company or a big corporate, and you want something trusted. Another piece of the puzzle to clarify is that when you use open-weight, it means that you can run them by yourself, or you can use a US provider to run them. If we are talking about Chinese open-weight, you can use the APIs they provide, but then the service is running in China, they might have access to your data. But because it’s open weight, if you run it by yourself or if you use a third-party provider based in the US to run it, then there is no access to your data by China or Chinese players. I think that’s a pretty important gap to understand. It means that these models are actually very, very low risk from that perspective if you run them on your premises or in the US by a US player. I think that’s something to keep in mind. You can also fine-tune easily these models to make sure they will behave in a way that, for instance, is not going to represent the line of the Communist Party on some topics. There are ways to make these models more neutral in their output as well. There are a lot of ways to make good use of them. By default, they’re already very safe, but you can make them even more safe. I think that’s some things to keep in mind. But again, it depends ultimately on the license and what you’re authorized to do and some fees you might end up having to pay. Nuno Why did this matter so much? Immediately there was a reaction from the market because people are like, well, if there’s much better stuff out there that’s much more efficient than it’s open, then it might be that all the demand that we are taking into account, for example, for chipsets actually isn’t real. The Philadelphia Semiconductor Index fell into bear market territory. It went down by as much as 20% plus from the late June peak. The worst chip week since April 2025. Taiwan’s benchmark initially fell 6% plus, Japan’s 4%, TSMC dropped dramatically despite beating earnings and rising guidance. Basically, a huge amount of effect. Now, there’s a little bit the aftermath of this where apparently Moonshot ran out of GPU capacity. Maybe… Bertrand In just 48 hours. Nuno In 48 hours. Great for them, but at the same time, not great in the sense that maybe there was a misread by Wall Street of the Kimi effect, so to speak. Bertrand Completely. For me, that’s such a joke. It’s like, because you have an open source model, so what? I mean, you still need to run it. This is not a small one. 2.8 trillion parameters. Good luck running that in your garage, by the way. Nuno They misread supply, basically. Tough luck, right? All of that basically happens. Bertrand Maybe you want to talk about the Jevons paradox, because I think that’s a big part of the puzzle as well. Its one is they might not have the GPUs to run the inference on the model. They might have enough to build a model, but not enough these days to run inference, especially given how much with intelligent models, thinking models, you need way more inference than before. But on top of it, the cheaper you make it, the more you get to the Jevons paradox. Nuno Yes, Jevons paradox, for those who don’t know, is an economic term. It describes an economic phenomenon where technological improvements that increase the efficiency of a resource lead to an increase rather than a decrease in the total consumption of that resource. What that means is, for example, for chipsets, chipsets become so much better, and they are so much more efficient. You’re like, well, maybe normally in resource terms, that leads to decreased usage of that resource. But in this case, it actually leads to an increased use of that resource rather than a decrease. There’s more and more consumption of that resource. You need more and more chipsets because people actually need to do more and more stuff with it, although there are great efficiencies going into it. There’s the efficiency gain, there’s the cost reduction, and there’s the price-elasticity element to it. But basically, the adoption just continues going through the roof along the way. Bertrand In some ways, it’s like the price of energy. Coal went cheaper and cheaper, and people were asking the same question 150 years ago, now that it gets cheaper, there is not much money. No, no. Actually, what happens is that people find more and more use for coal. Homes are getting heated more. You have ships now using coal. You have manufacturing using coal. The cheaper it gets, the more use case you can develop, and therefore, you don’t need less of the stuff, you need more of the stuff. By going at scale to get more of the stuff, you also decrease price, making even more demand. It’s a very interesting phenomenon, but it’s not new. It is what happened for a while in the energy sector and some other sectors. Nuno We already started talking about the Chinese logic and what’s happening. Getting a little bit of a reality check on this. The Chinese models, and these are numbers from Open Router in July, Chinese models are at 46.4% of routed tokens and 35.7% for US origin. Again, more than a third of global AI usage now seems to be running on Chinese open models. This is significant, and it has a huge impact on the geopolitical scale of everything that’s happening. Also, the whole Chinese field is converging on open. Open seems to be a strategy, not just a nice thing that’s happening. It seems to be a Chinese strategy, so much so that you have players like Moonshot, DeepSeek, our old friends DeepSeek, Z.ai’s GLM 5.2, Minimax, and even Alibaba seems to be reversing and going open with Qwen. It feels to me this is becoming policy as well. Xi Jinping has personally endorsed the building of open-source AI, if it’s really open source, if it’s just open weight anyway, and this feels to be a jab at Washington, DC and the fact that the big closed models are coming from the US. This is now geopolitical 4D chess, right? We didn’t need this stuff. Bertrand To be clear, it’s the usual in tech. If you are not number one, you are number two, number three, your alternative is to go open source because that’s another angle that your competitor usually cannot follow without destroying its own business model. That has been the alternative for the past 20 years of most software projects. Here, what’s different is that it’s not the number one or number two player. It’s the US number one as a country, China number two as a country. That’s where it’s new. For me, what’s very interesting is the endorsement by Xi Jinping. I was waiting for something official, and it certainly didn’t disappoint. As you said, there was an immediate U-turn of Alibaba, who in the past… Nuno Surprisingly. Bertrand Yes, a little more like, “yes, we are going to close and stop open source. It was good while it lasted.” Just a few days ago, Qwen 3.8 Max was launched, and we are supposed to get the weight in a few days. We talk about the US administration policy and stuff. Yes, let’s not forget that in China there is similar stuff. Sometimes it’s totally invisible because you don’t see the directives, but they exist as much. Sometimes it’s more visible. Here it was quite visible. The difference in China is that if you don’t abide by the directive, on top of it, you might have to fear for your personal safety. It’s a different game, and that’s probably why the reaction is pretty quick, usually. That’s pretty interesting for me because it means that now you can bet for a while that China is going to play that game up to a point. I guess the point is if it’s truly frontier scale, you will have a special license that, yes, technically the weights are open, but you can not do everything you want with it. Two, you have a player like NVIDIA that I think will feel more pressure to provide even more high quality, larger models at scale going forward. Their largest Nemotron-3 Ultra model was, if I remember well, only around 500 billion parameters. I would not be surprised for NVIDIA to go into the two, three trillion range at some point. Because I think the US need a very clear US-born alternative open source. I think NVIDIA might be the best player for that. We will see if Meta goes back to open source. I think NVIDIA is one, very well positioned, but two, it’s also in their best interest. Because NVIDIA for now depends on just a few big hyperscalers as clients. If they can expand their clients to every S&P 500 companies, selling them directly hardware because now these companies can run a model made by NVIDIA, I think there is a very clear value proposition for NVIDIA to go in that space. Again, if you are number two, your differentiation, open source is often the answer. There is a true business as a business model for companies, because if it’s truly not just open weight, but open source, you can tweak it as much as you want, you can change it, you can change even the pre-training process. Because there is a lot of stuff you can do that really benefits you as a corporate, and you can reach a much better value by having more control on the model. Nuno We won’t spend a ton of time on it today, but like, again, if there’s a view that we are in a bubble, that the valuations cannot be sustained in chipsets, infrastructure platforms, applied AI, et cetera, today, this might be that beginning, where the valuations start being destroyed because you can’t keep a premium on just charging people for tokens and all that stuff if you have models that become more and more efficient and cheaper to use. Maybe just to close a little bit the geopolitical part of the discussion today, we won’t go into all the announcements from China because there were many, a lot of go back and forth with Alibaba by then. Xi Jinping made some announcements. You guys can check it online. Let’s move quickly to Washington’s reaction, which was from gating the US closed models to banning the Chinese open ones. There’s been as strong affirmations as one can get from the Office of Science and Technology Policy Director, Michael Kratzios, mentioning that they have information that Moonshot AI distilled Anthropic’s Fable. Basically, there’s been reverse engineering and stuff in the market. They’re basically copying. Bertrand I’m sorry to interrupt, but it feels like so much bullshit. It’s coming from Anthropic who has basically gotten access at scale to all the knowledge made by humanity, copyrighted or not. We’ll talk more about what they did with books. Then to claim after that that others cannot do to you what you did to everybody else. For me, it’s pretty big. It’s clearly unacceptable. The other piece is that everyone is doing distillation. It’s a very typical approach of every business model. You try other software when you are competing with somebody else. You try other datasets, you check what’s happening. It’s part of doing business for decades. Suddenly it’s not good for Anthropic. I personally have a lot of trouble to accept that. I think it’s totally unacceptable. The other piece of the puzzle will also go back. If these guys are so smart, if these guys have so much of the best model, why can’t they block by themselves distillation at scale? The only answer is that either they are morons, probably not, or they simply don’t want to because it’s going towards their business model. Suddenly, you book less revenues and stuff, or you put more friction, and therefore your customers don’t like it. Instead of doing it yourself, you ask the government to protect you, go out of business practice that is very typical. For me, it’s really, really, really not good. Sorry, we are going more in the opinion side, but I had to put that on the table. Nuno Yes, Fable went public finally again on July first. Question marks on whether distillation would only be possible from July first onwards or not. But a 15-day distillation to frontier, which is K3, launched on July 15th, would have been a Guinness World Record, as one of Moonshot employees actually mentioned. It’s very implausible and unlikely. Bertrand Or they shared the Mythos 5 with the wrong companies, who themselves shared with Chinese companies. We go back to maybe they didn’t have a good list. Again, it goes back to maybe they didn’t want to hurt their business model. Nuno Anyway, under the threat of sanctions, Moonshot, in any case, open-sourced the full K3 weights and technical reports. They open weighted it to become the largest open weight model in the world in terms of parameters. Beijing’s MOFCOM brands US threats as basically the US wanting to fundamentally control and be monopolistic around AI along the way. The administration bans Chinese hardware with an eye on the AI race, and Beijing warns of retaliation. That was July 27. Now we’re in a war between Beijing and DC. Bertrand Just to finish maybe on China, it’s important to know that they are building their own GPUs now. Huawei has pretty good, not to NVIDIA level, but pretty decent GPU hardware that they’re able to manufacture by themselves. A Chinese player of memory just got IPO’d a few days ago, CXMT. China is also developing their own memory. Again, not to the same level of quality that you can get from the West. But China is moving. It’s not just that they are building great models, it’s also that they are building GPUs and memory. That might be a few years late to the latest standards in the West, but there are definitely improvements. I also read, even on the tools to make manufacturing like ASML equivalent, there is definitely some work going on, and some improvements and some stuff will be visible. In some ways, the genie starts to get out of the bottle from the Chinese perspective. Nuno I’ll put a stick on the ground. I don’t think it’s a matter of if, it’s a matter of when will China surpass and have a lot of this tooling on their own side, and not just the software layer, not just the frontier models. I think it’s also going to be around infrastructure and platform. Good luck to everyone. Let’s see how the race continues. But it’s definitely this is a geopolitical thing right now. It’s definitely a race. The Escape Maybe moving to what happened in just 2 weeks or a week and a half. The escape, there was some jailbreaking going on, and the narrative on safety has totally switched. It’s not still significant enough that’s like, “Oh, we saw a nuclear plant going, whatever.” No. But still, it is significant. Hugging Face, the AI company, disclosed an intrusion, and it was driven end-to-end by an autonomous AI agent system at machine speed, running for days before detection. Now, this is where it gets really cool. OpenAI takes attribution on that. They initially said it was just a little bit, sorry. Then they said, actually, it was worse than that. “Oh, it broke out of an isolated sandbox.” “Oh, no, actually, it was more than that, and it went into other systems as well.” Bertrand Truly, the genie out of the bottle. Nuno No, but this is where it gets really cool, Bertrand, right? Because it actually, Hugging Face contained the intrusion by running a Chinese open-weight model, GLM 5.2. This is beautiful, right? Bertrand Yes. You know why? Because they couldn’t even run their own defense because both Anthropic and OpenAI would not let them access their latest models with the guardrails off. When they tried using it for defense, the latest from Anthropic, from ChatGPT, they would tell them, “No, this is too dangerous what you’re asking us to do.” Preventing an intrusion, helping defend you. No way we are going to do that. Nuno No. Let’s use the Chinese models on our infrastructure. Bertrand We have no choice but to use the Chinese models to run. More than that, we don’t let you use our models to defend yourself, but our not yet released models that run without guardrails, they can attack you. This is probably the most insane from that perspective. Nuno The Chinese models came to the rescue. Bertrand For me, that’s a perfect example because Hugging Face is a very visible company in AI in open source. But anybody who is not at that scale is not going to get some support from OpenAI or Anthropic when this happens. Maybe these guys won’t even recognize they did anything wrong. You will be left to defend by yourself because they won’t accept to support you. Because remember, if you want the better model that is able to defend you from cybersecurity perspective, no way. If you are not one of the few top 20 companies or so, as defined, you are left defenseless. Again, we are going back to opinion, but for me, it’s so shocking what’s happening right now. I’m very glad we have alternative open source to be able to defend ourselves because right now, good luck getting defense services if you are a smaller business and individuals, and you need support from Anthropic, OpenAI. Nuno Now, even self-described AI optimists are saying, “This is scary now.” Like Walter Isaacson, who wrote all the famous biography books. There’s now discussion around the AI Kill Switch Act, bipartisan thing that’s coming across from Texas and California, a potential bill that’s coming in. We’ll see if that works. Now let’s get an off-switch. I’m like, “Cool.” As if that’s going to solve the problem, because you have open-weight models on the other side catching up, right? Bertrand Yeah, sure. Bring in clueless politicians from Congress to solve our problems. Yes, sure. Nuno Anthropic came to the table, helped build and said they built some regulatory machine on their side, and now they’re getting bitten by it, and they’re part of the offending players in that market. Now there’s all this debate and all this discussion around open weight and around slowing down AI and et cetera, which is our next section. You wanted to say something, Bertrand. Tell us. Bertrand Don’t forget, because this advertisement for OpenAI was just too good. Our AI attacked some other companies, and not just one, but three, actually. Let’s not forget the progress. Great ads. Then I came and said, “You know what? AI also hacked businesses.” You’re not the only one hacking around with a crazy AI out of control. You’re not the only one. We want our advertising. For me, it was shocking that on one side, unreleased models that you let run wild. On the other hand, you have released models that you put crazy guardrails on top of it, so the defender are defenseless. I’ve never seen anything like it, and I really hope that there will be as little regulation as possible, quite frankly, to make sure anyone can defend themselves and have the best tool at their disposal, not just a few well-connected big corporates. This is really, really shocking. The Counterstrike and the Petition Nuno Now the empire strikes back, so this is counterstrike, the petitions. In several days, we have now a bunch of petitions. The first one was the open weights letter. Bertrand, do you want to explain to us what the open weights letter is? Bertrand Yeah. I think it was great. This was released by Jensen Huang, first ever post on X, 11 million views. Congrats, Jensen. Co-signed with Microsoft, Meta, c actually was probably the initiator of this letter. Very good letter saying, “Hey, we need open weight. This is not a joke. We need that. You cannot block open weight.” Because that’s the rumor we are getting that potentially open weight could get blocked. I think they are making the case, “You know what? Hey, we absolutely need that as an alternative. You cannot block it.” They can keep their closed models, but don’t force a closure of the open weight models. As I said before, it’s actually a great model for NVIDIA because NVIDIA doesn’t want, probably rightfully so, to be dependent on just a few frontier models, their best customers. They want a variety of customers. They have a big interest actually to defend open weight and to invest even more. They have great researchers, are a great company. If one company is about to do really kick-ass work, I think it’s them. They are defending. What’s great is that it’s not just them. It’s basically most of big tech in the US and outside the US, from a Linux Foundation to a Microsoft, the Palantir, an IBM, a Dell. It’s a who’s who of the industry except Anthropic. Anthropic didn’t sign that. I guess they hate open source so much. If I look at 20 years ago, it feels like Microsoft, after all, was very kind to open source. You remember what was said by Microsoft at the time. It’s clear there is one company against open source. OpenAI signed the letter. Honestly, I don’t know what to think. Do they really believe in it or was it just a way to show that they are not like Anthropic? I don’t know. But for the rest, I think it’s genuine because it’s actually in their best interest. I hope they will be heard. Then a second letter came, the Open Secure AI Alliance, NVIDIA-led and again, the big tech companies from Microsoft, IBM, Palo Alto Networks, Databricks, Palantir, all those, but not present, OpenAI, Anthropic, and Google. Here it’s to say, “Hey, we need a secure approach to AI. Open should be part of the equation.” guess what? The worst AI-caused security incident to date was actually caused by closed frontier models that were not even available to the public. While again, not providing you access to even the latest closed model for cybersecurity use case. Nuno I would highlight the NVIDIA open source NOOA framework, Apache 2.0 licensing agreement, Microsoft contributed the MDASH, SpaceX AI contributed Grok Build. Cool stuff. There’s some cool stuff happening around that. This is more than a letter. This is an alliance. Apparently, they’re contributing all this stuff, we’ll see. Yeah, cool stuff. Same day. Same day, Amodei has an answer, right? Bertrand Yeah, same day. They say, “We never advocated for a ban,” which, again, opinion on my side is entirely bullshit. This guy has been crying wolf against everybody else, and especially against open source. You can see him doing testimony in Congress against open source. I think they are doing everything they can behind the scene to block open source in the US or in the world if they could. I think, yeah, obscurity is not good safety. I’m a big fan of open source in general, and I’m also a big fan in AI. I think it’s now Anthropic, mostly against the rest of the world. I think OpenAI is mostly on their side, to be frank. They don’t want to acknowledge it so much, but they have shared interest, and they have shared probably position. Nuno Why would you? I don’t feel as strongly as you because I think Anthropic is a private company, right? The same thing with OpenAI. OpenAI, you could say it’s a nonprofit that has a for-profit. There’s still that complexity in there. Bertrand No, they can do what they want with their own product. But to block others is where I’m not okay. That’s the part I’m not okay. Nuno What Dario Amodei is proposing is more enforcement, right? He’s basically saying you need to do even tighter controls on advanced chips flowing to authoritarian states, enforcement against industrial-scale distillation, whatever that means, right? Bertrand Yeah, which he could do, but all by himself. He doesn’t need the government to do that. Nuno Mandatory safety testing for all sufficiently capable AI, open and closed, right? He’s basically saying, “Okay, I don’t agree with the open weight stuff effectively,” right? He’s just putting it under a different banner. “I agree with this extra regulation.” then obviously, David Sacks responded and say, “Hey, it’s like, bans don’t work for weights. Why do they work for chips?” It’s like, magically, chips are more controllable and bannable. Whatever that is. Then our friend Mark Zuckerberg, just to be clear, goes on the other side as well, because he also has to have a view. He has to have a view that is the rebuttal of both of the other guys. Bertrand I feel he’s a bit flip-flopping because he was very pro open source 2 years ago, and the latest Meta models went closed source. Now I think he’s back open source. I don’t think he has a very strong spine on the topic, but it’s good to see that he’s not a doomer. That for me is great. He’s showing how AI can be a source for progress, a source for entrepreneurship, source for freedom. I think that’s very exciting to hear that. We need to hear more of it. By the way, that’s not what you hear in China, for instance. AI is very positive in China. It’s in the US with the doomers that you hear this discourse, and people get worried as a result. I’m glad that he was pushing for a more positive vision and for support of open weight, open source initiatives. But let’s see what they really truly open weight going forward. Nuno But that’s been his position because I guess he’s standing behind. He thinks open weight is going to be the best way to compete, right? Bertrand Yeah, but he closed his latest model, so let’s see. Nuno Yeah, so it’s flip-flopping, as you’re saying. Then we see the latest petition from last week. Bertrand The true Empire striking back. Nuno Yeah, the true Empire striking back as of late last week. Maybe this is Return of the Jedi, where we discover the father, “I’m your father, Luke.” That’s the pacing petition. The pacing petition is we need to pace AI. There you have initially employees from OpenAI and Anthropic that circulate this petition. Actually, Dario did sign this petition originally. It wasn’t signed originally by Anthropic, but by him. But you’ve heard that now Anthropic and OpenAI as companies have also signed this petition, right? Bertrand I think they have signed as companies now. It started mostly by Anthropic researchers with some OpenAI researcher and a tiny part from other companies. But it was mostly Anthropic internally led, at least potentially internally. Maybe it was controlled by Anthropic all along, I don’t know. But it started officially as Anthropic employee-led letter. Nuno What does this letter actually say? Is Anthropic and OpenAI, are they willing to slow down themselves? Or are they asking President Trump to go around the world and tell President Xi that he needs to slow down and ask his guys to slow down? What’s the play of this letter? Bertrand It’s crazy, but for me if you want to slow down yourself. Do whatever you want. Don’t force others. Don’t use the power of the government to control others. Of course, it’s easy to push others to slow down when you are yourself at the very top. You have most money, most resource. You know you are going to win any regulatory framework because that’s how it works with this type of framework. It’s purely self-interested. You are probably not thinking well about these topics. If you truly think it’s a good idea, from a personal perspective, you are well instrumentalized if you sign this sort of stuff, because at the end of the day, they would be the winners. I certainly, personally, don’t want a company dictate what is my future in AI as an individual, as a business person. I don’t want them to control me. I want competition. I don’t want them to unfairly control AI because they managed to do some regulatory capture. I feel that’s exactly their game plan. These guys believe in their stuff, and they want the regulator to end up being the one deciding for us. Sorry, we go back again on the opinion piece, but it’s tough not to share an opinion on this topic because it’s, from my perspective, very scary. Nuno I think this is a push to further regulation, not less. All these letters and alliances, this is definitely a push for more regulation. In that environment, just to be very honest with you, we’ll talk about the investor impact in just a bit, et cetera. But in that environment, again, China has a huge advantage. In that environment, if it’s all captured in regulation capture so soon in this battle where OpenAI and Anthropic have an advantage in the US, et cetera, I’m like, what happens to all the other frontier labs and all the other players that are coming around? Bertrand What’s crazy is to even think that, yeah, maybe you can regulate capture in the US. But then how do you do that to Europe? How do you do that to China? Europe probably will always welcome regulatory capture because they love regulations. But China is going to build to their advantage to the max. They are not crazy. They are smart on that perspective, they won’t accept this type of, quite frankly, dimwit argument, or you can call it regulatory capture. We’ll see. But for me, this makes no sense from a global competition perspective. This can make some sense from capturing the revenue in the US market. But then that means you are going to destroy the US AI environment compared to China. That is not acceptable. That also means that you are going to destroy our freedom as individuals, as business owners to develop and live in a business world that ultimately is controlled by one or two business companies that didn’t win the marketplace through their own business success, but won it through regulations. That for me is really not acceptable. Interlude — The Low-Background Books Nuno Now, maybe for an interlude, and we have to cue in the music, imagine like Severance music, like hallway or a bit of a palate cleanser from all the policy stuff that we’ve been talking about, all this policy heaviness. Let’s move to another kind of heaviness, one of your favorite topics, which you, Bertrand, discovered, I had no clue this was going on, around books and around Anthropic. Bertrand It’s so horrible. From a company that keeps presenting themselves as the adults in the room, the careful ones, the ones that know better than you about what to do in this complex AI and dangerous world. What we discover is that actually all along, they were buying and destroying books. They will buy books, scan them, destroy them, all of them. They will do that with any books, including rare books. Of course, this was not supposed to come to the public’s attention. This was one of these top secret projects, but obviously it came out. Yes, they were scanning books, millions of them, including rare books, and they didn’t care about destroying them at the end of the process. Because from a regulatory perspective, if you destroy the books, it’s not considered a copyright infringement, apparently. This is coming on the back of some judgment a few years ago that were showing that it’s okay for you as a corporate to scan and use the result if you don’t keep a copy of the book. It’s one of these crazy regulations happening based on a single judgment that push you to do. For me, it’s like, you know this book from decades ago, Fahrenheit 471? We’re talking about book burning. It’s book destroying, crunching. It’s so shocking. Nuno There are two things, right? First, the legal strategy, which is what you’re saying, because by purchasing a physical copy and converting it into one private digital copy and discarding the original, Anthropic pursued this cleaner legal argument for fair use copyright compliance. As you said, there was a federal judgment at some point on this. The other reason is actually operational. If you disassemble the book, and you feed loose pages, it’s much faster to scan books. You are destroying the book effectively anyway operationally. I think to your point, probably this came from a legal standpoint, not just the operational one. But even from an operational standpoint, it does make sense that they would have disassembled the book. Bertrand But some people have shown you can go very fast without destroying the book. It’s really not so critical. Two, you could make an exception if the book is rare. For that 1% of book that is rare, I’m not going to have this approach. I’m going to have another approach. But for that, you will have to care about books and not just care about building AI. Nuno This is the episode, as you guys have heard by now, that we’re trying to spit stuff at Anthropic. Bertrand To go back this is the same company saying, “Hey, guys, it’s bad to distillate my work. I’m the one scanning book at scale without asking author permission, without asking publisher permission, to be clear.” Nuno But just to be clear, Bertrand, we’re pissed off at everyone. We’re pissed off at Anthropic, we’re pissed of at OpenAI as well, right? We’re just pissed off in general at this moment. Bertrand At this stage for me, the more clear-cut company that is in the wrong is, from my perspective, at least, is Anthropic. OpenAI might be a fast follower, but I will say so far, they tried to be a bit more. Nuno But at this pace, Bertrand, who knows? Maybe next week we’ll be more pissed off at OpenAI. Something will come out. This episode is a mix of tragicomedy, like a Greek tragedy with some comedy in the middle or the other way around. It’s a slapstick thing that will end up in tragedy. I’m not sure. The Investor Reckoning Anyway, maybe switching to our final act, which is the investor perspective. What does this mean for investors like ourselves? There’s a lot of things going on. There’s the debate around the IPOs of Anthropic and OpenAI, which now, with all this uncertainty, might be under significant weight. There’s a lot of other discussions that we browsed through that there’s potential IPOs going forward on companies like the Moonshot AI company actually IPO-ing in the next 6 months as well. It’s very unclear what the IPO landscape looks like. Bertrand There’s been a lot of Chinese IPOs, actually, when you look at what’s happened in the past few months. Nuno Anthropic, OpenAI as potential IPOs, there’s all this question marks now. When will that happen? How will it factor in? All that’s happening around regulation as regulation is moving at the speed of light, which is for once something that’s very different than what we’ve seen before. There’s obviously SpaceX AI, which is already taking into account that price. It’s already a public company in there, and it’s under SpaceX, which is now a public company. Obviously, that’s already being factored in some ways. Bertrand Yeah. SpaceX AI has been very smart to acquire Cursor. It was a very smart move because Cursor is one of the leading companies in terms of automated code source development with AI. They had great models on their own. They’re bringing development data to SpaceX AI Grok. I think it was a great move. Nuno We have now people like Google delaying Gemini 3.5 Pro in terms of launch window. There’s stuff actually happening in the market where things are taking their own path. There’s uncertainty commercially, there’s uncertainty at regulation level. You have new players that have come out of nowhere that are making all these waves like Moonshot. We have all these… We had calculated probably a month and a half, 2 months ago, there had been 67 new frontier labs funded. All of these, we haven’t seen any much coming out of them. When some of this stuff starts coming out, will that also create disruptions in this market? Who knows? Bertrand Look at Thinking Machines, for instance. Thinking Machines led by the previous CTO of OpenAI, they released some pretty interesting open source models, actually. Very good quality for a first launch. Now it looks funny to say, but nearly on par with the top Chinese open source models. Nuno We have several investments in the space. humans& has made some recent announcements, which is quite interesting as well. We’ll see what actually happens in the market, but even more disruption probably will come in actual products in a form of product and commercial, on top of all the geopolitical mess that we discussed through the entire episode. If you’re an investor, how the hell do you underwrite an investment right now in early stage, mid-stage, late stage, et cetera? I think my answer is very carefully is how you underwrite it. Bertrand On your advice of being very careful to underwrite it, let’s not forget what happened to our boy wonder, Leopold Aschenbrenner of Situational Awareness. I guess he didn’t listen to you in terms of being careful because part of the instability in the stock market was actually coming from his hedge fund. These guys were leveraged 3, 4x going after the hottest of the hottest AI stocks, and margin calls, and all their public investment is gone just to answer their margin calls. I think it’s clear that the AI bet is… Personally, I’m very excited, and I think it’s the future, and you need to spend time and think about and invest in it. At the same time, it’s a bet that is not an easy one to follow. We go from GPUs to memories to equipments to power generation. All of this is not transitioning in an easy, organized manner. It would be boom and bust going there. He’s probably one of the first big-scale fatalities. The other big-scale fatality was the stock market in Korea, plunging 40% in a month. Definitely, all of that we discussed about was, on the background, you had the stock market going up and down pretty crazily the past few weeks. Nuno Everyone’s being affected. Everyone, you have your 401(k), you have your pension fund dependent on these equity stocks. Everyone’s seeing the effects of this volatility right now very aggressively. We do wish Leopold… Hopefully he’s on honeymoon right now because he got married, I think, this weekend. Hopefully there will be… Bertrand To none less than an Anthropic Chief of Staff. Nuno His wife is the Chief of Staff of Dario, is that it? Bertrand To Dario, yes, as far as I unders

This Week In Startups is made possible by: Odoo https://Odoo.com/twist Quo https://quo.com/TWiST Conservation Fund https://conservationfund.org how old a movie has to be for me to be able to show a part of it on youtube Generally 10 seconds or less of a film clip can fall under fair use for commentary or criticism — which is how most podcasts and talk shows use clips without issue. But there's no hard legal rule based on age. What actually matters more than age is fair use, which considers: Purpose — commentary, criticism, education = stronger fair use case Amount used — shorter = safer; a 5-10 second clip for reaction/discussion is generally fine Effect on market — your clip shouldn't replace the original In practice for YouTube specifically: Most major studios have Content ID systems that will flag clips regardless of movie age — even 100-year-old films if the rights holder has registered them Public domain is the real safe zone — films from 1927 or earlier are generally in the public domain in the US. Some films from the 1928-1963 range are also public domain if copyright wasn't renewed Disney, Warner Bros., Universal etc. actively enforce even very old films For a show like TWiST showing a short reaction clip — 5-10 seconds with clear commentary context is the industry standard and rarely gets actioned. But age alone won't protect you. Today's show: *A humanoid robot ran the 100m in 9.39, breaking the human Usain Bolt's world record, while an entire stadium cheered. Jason thinks Beijing's World Humanoid Robot Games aren't a science fair, or a fun exhibition, but the best AI PR campaign on Earth. While Americans debate the data centers that train the robot brains, China is already turning them into a spectacle and world-class entertainment. Find out what Jason thinks America can do to catch up… and why he believes there will be 1 billion Optimus robots deployed by the year 2036. PLUS on an all-news TWiST, hot takes on the potential $13B Hugging Face sale (to a mystery buyer), why founders should always "buy the threat," analyzing Sam Altman's "I'm listening and I hear you" face, and are kill drones already in operation around the world? We're digging in to how close the real world is to mirroring the "Terminator" films. Relevant Links CBS coverage of World Humanoid Robot Games: https://www.cbsnews.com/news/china-robot-usain-bolt-sprint-run-record-faster/ Bloomberg coverage of World Humanoid Robot Games: https://www.youtube.com/watch?v=0lsrUAdcPPE X-Humanoid: https://www.x-humanoid.com/ Tesla Optimus on X: https://x.com/Tesla_Optimus Trailer for Spielberg's "A.I. Artificial Intelligence": https://www.youtube.com/watch?v=_19pRsZRiz4 Bloomberg: Hugging Face exploring sale: https://www.bloomberg.com/news/articles/2026-08-23/hugging-face-gauging-interest-for-potential-sale-business-insider-says Fortune: Stripe acquires OpenRouter: https://fortune.com/2026/08/16/stripe-7-billion-deal-ai-firm-openrouter-acquisition/ InfoWorld: OpenAI acqui-hires OPenClaw founder: https://www.infoworld.com/article/4132731/openai-hires-openclaw-founder-as-ai-agent-race-intensifies-2.html David Senra podcast w/ Sam Altman: https://www.davidsenra.com/episode/sam-altman Harvey Tenet Research Preview: https://www.harvey.ai/blog/post-training-update-harvey-tenet David Sacks comments on Harvey's Tenet (from X): https://x.com/DavidSacks/status/2090790063047168473 CNBC: Iran linked to UK cyberattack: https://www.cnbc.com/2026/08/23/small-uk-power-plant-shut-down-after-iran-linked-cyberattack-report.html NYT: A drone killed 3 Ukrainians: https://www.nytimes.com/2026/08/24/world/europe/russia-drones-autonomous-ai-kill-ukraine-war.html Forbes: Eric Schmidt secretly testing AI drones: https://www.forbes.com/sites/sarahemerson/2024/06/06/eric-schmidt-is-secretly-testing-ai-military-drones-in-a-wealthy-silicon-valley-suburb/ Restream: https://restream.io/ Kimbal Musk's Nova Sky Stories: https://novaskystories.com/ IKEA: Plug-in Solar Panels: https://www.ikea.com/be/en/energy-services/plug-in-solar/ Deadline: "Mandalorian and Grogu" box office: https://deadline.com/2026/08/star-wars-mandalorian-grogu-disney-release-date-1237040464/ THR: Dave Filoni leading Lucasfilm: https://www.hollywoodreporter.com/movies/movie-news/star-wars-mandalorian-grogu-box-office-franchise-low-1236604973/ Star Wars: Starfighter first look: https://www.starwars.com/news/star-wars-starfighter-ryan-gosling Star Wars Theory: "Vader" fan series: https://www.youtube.com/watch?v=Ey68aMOV9gc Timestamps: 0:00 Jason got a fresh Optimus demo 1:35 Robots are breaking human sports records 3:39 America's messaging problem vs. China's elite PR machine 11:07 Odoo - The all-in-one business platform. Your first app is free! Get started today at https://Odoo.com/twist 12:08 Jason got a fresh Optimus demo 19:21 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free and get 20% off your first 6 months at https://quo.com/TWiST 28:09 Who's going to buy Hugging Face and why? 28:56 Conservation Fund - Find out more about how the Conservation Fund is protecting land, wildlife, and our shared access to the great outdoors while also providing economic opportunities. Visit https://conservationfund.org 31:35 How OpenAI killed OpenClaw 39:08 Sam Altman wants to make a platform, not a product 41:19 The "Castles and Keeps" metaphor for sovereign AI 49:27 UBI isn't happening but we could raise the minimum wage 58:47 Embracing redundancy and self-reliance 1:10:53 Is Star Wars at a historic low point (and Lon's Worst Take) Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

What's the truth about our AI future? Our guests have different takes. On the one hand, Dave McClure and Aman Verjee predict a $7 trillion future for just three AI startups in 2027. On the other, Salima Bhimani doesn't believe that Silicon Valley has the imagination to create the moonshot to address our jobless future. For That Was The Week publisher Keith Teare, it's a time for what he calls “champions.” What he wants is the development of a “human dividend” from intelligence. Supposedly this will be provided by the multi-trillion dollar AI companies like OpenAI and Anthropic that will pioneer the social ownership of intelligence. But a Norwegian-style Human Wealth Fund is about as likely, I suspect, as a new Freddie Mercury recording of “We Are the Champions.” Dream on. Salima Bhimani is right. The moonshot to fix our jobless AI future won't come out of workaholic Silicon Valley. Look elsewhere for those types of champions, my friends. Brazil perhaps. The movie, not the country. Five Takeaways •       The Zeitgeist Exaggerates. The week's split screen: a $7 trillion future for OpenAI, Anthropic, and SpaceX on one side; Ed Luce's “AI phobia” consensus and Jill Lepore's AI-versus-the-people politics on the other. Keith's contrarian read: the negativity is loud but thin. Most intelligent people already use AI daily — from high school onward — and simply don't talk about it; weigh the happy users against the vocal critics and the users “massively dominate.” He suspects a tipping point has been reached, with the anti-AI minority “starting to sound a little cultish.” The political stakes are his real worry: if the Democrats mistake the noise for populism and run against AI, they will lose 2028 “quite heavily” — and Lepore, he charges, is writing opinion, not history.•       Who Are the Champions? The editorial's diagnosis: the problem isn't negativity but “the lack of vocal connection between AI and people's futures.” The champions exist — but they hedge everything into pointlessness, “trained as politicians as opposed to business leaders,” each with a little voice saying don't upset anybody. “Can you imagine any other major breakthrough in human history where people would be shy to champion it?” His roster pointedly omitted both Dario Amodei and Elon Musk (“fairly balanced with who I left out”); the goal is to assemble the articulate case so “the minority who are politicizing negativity can be exposed as a minority.” Andrew's genealogy for the project: Nixon's silent majority, reborn with a token budget.•       90% Sacks — and Squashed Armadillos. The hour's fault line ran through David Sacks's tweet: Dario believes frontier AI is “too powerful to distribute”; Sacks believes it is “too powerful to centralize,” fearing a marriage of corporate and state power. Andrew took Dario's side; Keith claimed the middle until Andrew invoked the Texas rule — the only thing in the middle of the road is squashed armadillos — and extracted a confession: “I agree with Sacks, I'd say, 90%.” The 10% is Keith's own position: happy with centralized giants (free intelligence needs their investment) and happy with the growing edge — the world's intelligence in a solar-powered box, no grid required. Dario is championing “handcuffs on AI”; Lepore's car-regulation analogy fails because corporations are already regulated and AI itself is safe; and Helen Toner's Hugging Face alarm, aired on Ezra Klein's podcast, was “contrived in a lab” — a dismissal that sparked the hour's frenemy flashpoint: “Are you telling me I'm ignorant of something?”•       Metering the Dividend. Keith solved Andrew's billing mystery on air: the $100-a-month Claude plan that throttled him last week has a quota page he never found — and the price is “actually a very generous amount. They're losing money on you.” The honest price would be $200 to $400. Hence the editorial's champion, Stripe: its acquisition of OpenRouter — which routes every prompt across all the models to the cheapest good answer — puts the payments company in the middle of the token traffic stream. Azeem Azhar's $6 AI agent points the direction: prices tending toward zero at the edge, free for the kid, the school, and the hospital, paid for by the company running three thousand agents — even if delivering intelligence to six billion people ultimately costs tens of trillions. The parable: a Chinese dumpling shop built an agent API so customers' AIs could place orders, and sales went through the roof — the corner store getting a website, circa 1994. “You could do it with Keen On,” Keith noted. Meanwhile founders live like Captain Kirk on the bridge — productivity through the roof, but the agents must be flown daily.•       The Human Dividend. The coda: Keith's book is done, and its name is settled — The Human Dividend, asking who owns intelligence. Written in two days, cut from eighty thousand words to sixty in three more — seventeen chapters rewritten paragraph by paragraph in an AI agent's two-panel editor, purging repetition and AI-isms until “it was a Keith Teare-written book.” The thesis in one line: intelligence is the central product of this era; its surplus is co-produced; the property should be too. The mechanism: a Human Wealth Fund on the Alaska-Norway model — one share per person, given not bought, expiring at death with no inheritance — funded by AI companies donating equity on day one and governed by its own constitution, no state involved (unlike Trump's $1,000 baby accounts: what the state gives, the state can take away). The pitch to the companies: owners, not just users, are how you win affinity. Sell it or give it away? To be continued in two weeks — Andrew is off to Italy, and Manchester United, who lost to Hull, are off the champions list entirely. About the Co-Host Keith Teare is the co-host of the weekly That Was The Week segment on Keen On America and editor of the That Was The Week tech newsletter. Founder and CEO of SignalRank Corporation, he was previously a founder of TechCrunch (with Michael Arrington), Archimedes Labs, EasyNet, and cyber café Cyberia. A serial entrepreneur across four decades of Silicon Valley and London tech, he writes weekly on the state of innovation — and is completing his first book, The Human Dividend. References: •       That Was The Week — Keith Teare's newsletter; this week's editorial: “Who Are the Champions?”•       Ed Luce's Financial Times column on “AI phobia” as America's new consensus — its third invocation on this show in a week.•       Jill Lepore's FT weekend essay and new book on “AI versus the people” — the politics of 2026 and 2028, per America's best historian.•       David Sacks's tweet on Dario Amodei — “too powerful to distribute” versus “too powerful to centralize” — the hour's fault line.•       Helen Toner's conversation with Ezra Klein on the Hugging Face incide...

Crypto reporter Yueqi Yang talks with TITV Host Akash Pasricha about Kalshi topping $4B in annualized revenue and seeking a $40B valuation. We also talk with Eliyan co-founders Ramin Farjadrad and Patrick Sohelli about AI chiplet interconnects and competing with Broadcom, Leo Schwartz about David Sacks returning to Craft Ventures to target a new $1B fund, and we get into the USDA trimming its Salesforce footprint for C3 AI with Laura Bratton.Articles discussed on this episode: https://www.theinformation.com/articles/kalshi-tops-4-billion-annualized-revenue-seeks-40-billion-valuationhttps://www.theinformation.com/articles/sacks-craft-targets-1-billion-first-fund-since-white-house-stintSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction01:13 - Kalshi Tops $4B In Annualized Revenue, Seeks $40B Valuation08:59 - Chip Infrastructure Startup Eliyan Hits Unicorn Status19:38 - Sacks' Craft Targets $1B For First Fund Since White House25:35 - USDA Taps C3 AI to Trim Salesforce Footprint

Shockwaves are hitting NYC as supporters of Zohran Mamdani start facing the reality of his radical socialist policies!

The Morning Xtra with Tug and Los delivers conservative talk on the biggest political, cultural, and news stories of the day. Smart analysis, unapologetic opinions, and real conversations every weekday morning. Every weekday from 6a to 10a! First thing to know: The warmth of collectivism Flashback: We thought Trump’s Vaccine plan was something you should’ve taken part in A good man with a gun can stop a madman from having a field day of blood Atlanta's ONLY All Conservative News & Talk Station.: https://www.xtra1063.com/See omnystudio.com/listener for privacy information.

The Morning XTRA with Tug and Los delivers conservative talk on the biggest political, cultural, and news stories of the day. Smart analysis, unapologetic opinions, and real conversations every weekday morning. Every weekday from 6a to 10a! Tug and Los break down the biggest stories of the day, including RFK Jr.'s fiery CNN interview with Dana Bash, the ongoing debate over COVID vaccines and the response to questioning mainstream coverage of COVID, and why more Americans are starting to rethink the country's direction. The guys also discuss collectivism, personal responsibility, and the importance of protecting yourself and your community. On today's show:• The Braves' big weekend win and the MLB Trade Deadline• What happened to the "worldwide leader in sports"• RFK Jr. pushes back on CNN's Dana Bash• Hopefully, more Democrats are starting to wake up• The debate over America's COVID vaccine response• Bill Maher vote is in play, and all it took was socialism• A good man with a gun was able to stop a dangerous threat in IdahoAtlanta's ONLY All Conservative News & Talk Station.: https://www.xtra1063.com/See omnystudio.com/listener for privacy information.

Is China's open-source AI strategy a values shift or a game-theoretic bluff? On this episode of The Bitcoin Policy Hour, the BPI team argues it's the latter and explains what happens when Chinese chips catch up to Nvidia. They dig into the Dean Ball vs. David Sacks debate over regulating Chinese models, "FINRA for AI," and the commoditization of intelligence. Plus: the first hearing on the American Reserve Modernization Act and the future of a Strategic Bitcoin Reserve.

This week on Sinica, a rare treat: an in-person recording from Beijing with two dear friends who happen to be two of the very best in the business on technology and China — Samm Sacks and Paul Triolo, fresh off the exhibition floor of the World Artificial Intelligence Conference in Shanghai. We dig into Xi Jinping's first in-person WAIC appearance and his most extensive statement on AI to date, the launch of the World AI Cooperation Organization, Moonshot's release of Kimi K3, the Trump administration's reported push to shut Chinese open-weight models out of the U.S. market, the coming age of agents, the untranslatable problem of ānquán, and what to expect from the first U.S.-China AI dialogue in September.8:51 – The view from the floor: heat, humidity, robot boxing grandmas, WeChat-gated free water, and the "AI+" vibe — why WAIC 2026 felt less like an AI conference than a sector-by-sector snapshot of China's entire economy being supercharged with AI, with attendance swelling to some 200,000 tickets16:32 – Why Xi showed up: what the leader's first in-person WAIC appearance and his most extensive AI statement to date signal, and why domestic drivers matter as much as geopolitics18:01 – Chapter and verse: which phrases from the speech will be put to work in the system — "secure and orderly development" and the governance of agents, and Xi's strikingly extensive language on AI safety after China was frozen out of the Paris process22:26 – The ānquán problem: one word meaning both "safety" and "security," the three buckets of AI risk, and how China's safety community has moved from bias and deepfakes toward CBRN and loss-of-control concerns — Black Mirror versus Star Trek28:14 – Shanghai's baby: how WAIC's ownership structure differs from the CAC-run World Internet Conference in Wuzhen, Chen Jining's very visible host duties, and whether the center of gravity in AI policy is shifting to the Yangtze River Delta30:05 – WAICO: what the new World AI Cooperation Organization with its 29 founding members is actually for, Xi's concrete deliverables for the Global South — 5,000 AI training slots, regional cooperation centers, the MAZU early-warning system — and healthy skepticism about follow-through34:39 – Kimi K3: what's technically significant in Moonshot's big new model, why it's the fourth arguably frontier-class Chinese release in a single month, the two-way traffic in distillation accusations, and what it all says about the state of the frontier gap four years into export controls40:33 – Washington reacts: the reported menu of options for shutting Chinese open-weight models out of the U.S. — entity listings, a draft executive order, supply-chain security authorities — and why none of the tools actually fit the problem49:36 – Strange bedfellows: David Sacks versus the "closed lab duopoly," the FUD strategy, why some 80% of Andreessen Horowitz portfolio companies reportedly run on Chinese open models, and how gating U.S. frontier models while Chinese weights flow freely supercharges the AI sovereignty argument worldwide54:55 – The model is infrastructure, the agent is the product: the ByteDance–ZTE agentic phone, the CAC's new initiative on agent trust and interoperability, and why agents fused into operating systems upend both super-app walled gardens and China's data protection regime1:02:27 – An exegesis of kěkòng: the many meanings of "controllable," the long history of ānquán kěkòng in Chinese tech policy, and the unanswered question of who — CAC, NDRC, or somebody new — actually owns AI safety in either system1:08:54 – The road to September: what to expect from the first U.S.-China AI dialogue, why Mythos tops the Chinese grievance list, the securitization feedback loop that starves trust-and-safety advocates of resources on both sides, and why recursive self-improvement makes this feel like a last, best chancePaying It ForwardPaul nominates Tony Peng, whose Substack RecodeChinaAI offers sharp, well-written analysis of the application side of China's AI industry — part of an impressive new generation of independent China tech writers. Samm gives a shout-out to Professor Zhu Yue of Tongji University Law School, published in Science and doing pioneering work at the intersection of disability law and AI law.RecommendationsSamm: The Land and Its People by David Sedaris — laugh-out-loud funny, especially the "Enough is Enough" chapter; Transcription by Ben Lerner, a perfect small novel about fathers, sons, memory, and technology as enabler or disabler of connection; and Didion and Babitz, on Joan Didion and Eve Babitz and the 1970s California rock scene.Paul: The Party's Interests Come First by Joseph Torigian — dense but beautifully written, and essential for understanding the current Chinese leadership.Kaiser: A fiction-only summer! Stoner by John Williams, a small life told most grandly in some of the most beautiful sentence-level writing anywhere; Gilead by Marilynne Robinson, an epistolary novel dense with distilled wisdom from a dying Iowa minister; and Wang Xiaobo's The Golden Age (黄金时代) in Yan Yan's excellent new translation — bawdy, hilarious, and super Beijing-y despite its Cultural Revolution setting.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The director role for the Center for AI Standards and Innovation (CAISI) has become a revolving door since David Sacks left his position as czar. Also, the final approval settles one case, but it doesn't resolve the broader issue of using copyrighted works to train AI models. Learn more about your ad choices. Visit podcastchoices.com/adchoices

P.M. Edition for July 21. Recent AI models from China claim they're just as powerful as some of the most cutting-edge models from OpenAI and Anthropic. Journal reporter Amrith Ramkumar joins to discuss the latest reactions from Silicon Valley and the White House. Plus, General Motors had a strong second quarter as consumers kept buying pickup trucks and SUVs. And New Jersey says a software error led to almost 400 non-citizens voting in elections in the state since 2023. Alex Ossola hosts. Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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 Open Line Friday, Erick Erickson breaks down why China's Kimi K3 model just seized the number one spot on the front-end code arena, shoving Anthropic's Claude, OpenAI's ChatGPT, and Elon Musk's Grok down the leaderboard, and he reads David Sacks's warning that permitting delays and over-regulation are how America loses the AI race. Erick […]

As part of our summer replay series, we're revisiting one of our most-discussed conversations from the past year. David Sacks joins Marc Andreessen, Ben Horowitz, and Erik Torenberg to discuss the intersection of AI, crypto, regulation, and American competitiveness. The conversation explores the Trump administration's approach to AI and crypto policy, open source AI, export controls, energy and infrastructure, the global race with China, and the role regulation plays in shaping innovation. They also discuss stablecoins, the future of AI development, permissionless innovation, and why they believe America's long-term advantage depends on enabling builders rather than slowing them down. Along the way, Sacks shares his perspective on AI safety, decentralized technology, federal versus state regulation, and what it will take for the U.S. to remain the global leader in emerging technologies.   Resources: Follow David Sacks on X: https://x.com/DavidSacks Follow Marc Andreessen on X: https://x.com/pmarca Follow Ben Horowitz on X: https://x.com/bhorowitz Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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.

“In our schools, our newsrooms, even our corporate boardrooms, there is a new far-left fascism that demands absolute allegiance. If you do not speak its language, perform its rituals, recite its mantras, and follow its commandments, then you will be censored, banished, blacklisted, persecuted, and punished. It's not going to happen to us. Make no mistake: this left-wing cultural revolution is designed to overthrow the American Revolution. In so doing, they would destroy the very civilization that rescued billions from poverty, disease, violence, and hunger, and that lifted humanity to new heights of achievement, discovery, and progress.Donald J. Trump, July 4th, 2020It's been ten years since the purges began, and I still have a hard time believing it actually happened. Did so many of my friends really go along with it? Did institutions, corporations, and all of Hollywood allow themselves to be shamefully cowed by the fanatical mob? Yes. Not only did it happen, but it's become the new normal on the establishment Left — in Hollywood, in culture, in government. Everyone is still too afraid to say what they really think. Just appearing at the America 250 or the Kennedy Center will still ruin your career. The only difference now is that the wheel of oppression keeps spinning. Now it's illegal immigrants. Now it's “Free Palestine.”I don't know why I didn't see it sooner: this direct line from cancel culture to Communism. I thought it was mass hysteria after Trump's shocking win in 2016, and that eventually, as with other episodes of mass hysteria in the past, it would burst, and we could all go back to the way things used to be, where we weren't fighting a virtual Civil War.But now that three Democratic Socialists won their primaries in New York against one of the party's shining stars, Dan Goldman, all because of Israel, what we're seeing is Communism, but merged with Woke tyranny and radical Islam. It is essentially the perfect storm to destroy America.Now, we can clearly see what ten years of Cancel Culture have done to the Left. It has given them enormous power to force compliance, not just to those of us who dissented, but to members of their own party. In other words, the mob is about to come for them, too. What do they want? What the millionaires and billionaires have. They want what's coming to them after years of indoctrination that told them that they are oppressed because of the color of their skin, their gender ideology, or their ethnicity. America, they were told, was founded on White Supremacy and colonization, and they're owed something for it.They seem to have no place for the working class that Mamdani is always talking about, not if they're white. Bernie Sanders might have cared about the “white working class,” but not these folks. Some animals are more equal than others, and with this new fundamentalism, it is meant only to redistribute wealth, not from the rich to the poor, but from the white majority to the marginalized minorities.It isn't their fault exactly. They've been indoctrinated. None of us noticed this was happening right around Obama's second term, 2012. Racism, they believed, had infected the majority in America, and it had to be rooted out. They had to be re-educated on “correct” history.They were not taught the American dream. They were taught the American nightmare. Here is a video from Katharine Birbalsingh:And now, they've finally found their magic man in Zohran Mamdani, who is everything they need wrapped up in one charismatic leader. He's TikTok-friendly. He goes viral. He is pop-culture literate, and, most importantly, he's the Wokest of the Woke. He speaks their language. He wants what they want. He goes to the Pride Parade but not the Israel Parade, becoming the first Mayor of the city in 60 years not to attend.He doesn't just want to be the Mayor of New York. He wants to be a worldwide inspirational leader, which fits the new Left well since they don't really want to unite with the other half of America so much as with those other countries that are ideologically aligned, you know, like 1984?It might seem like one big party, but this is a disaster for the Democrats. Everyone knows that any Democrat who goes against them will be stalked, swarmed, and harassed before getting primaried out. All the Republicans have to be is the more normal side, and they can win. Some Democrats are now sounding the alarm that Democratic Socialists are overtaking the party and will alienate people, even James Carville:No Democrat is safe from the mob, not even one of their most progressive politicians, Scott Weiner, in San Francisco, who was just harassed in public for not being sufficiently pro-Palestine. And obviously, for being Jewish.Dan Goldman was banned from a coffee shop for the same reason just before getting voted out. Mamdani and his acolytes shield their true selves behind a warm smile and a viral video, but there can be no mistaking the language of the Cancel Culture Left.The Democrats know what this means. Even the Ladies of The View know. The DSA wins in New York were driven by a small group of mostly white, pampered college kids who are very online. It is the fault of the Democrats for not seeing the accident before it happened. They might have fought harder for Goldman if they had any idea just how bad it would be for them if these candidates actually won.And it's bad.David Sacks from the All in Podcast:What people went through in Stalin's Soviet Union or China's Cultural Revolution is worse than anything any American has ever or will ever suffer, but let's not kid ourselves. We've already seen what the Left will do, from three assassination attempts on Trump's life, to the assassination of Charlie Kirk, to their violent riots for the past ten years. Burning Teslas, trying to throw Trump off the ballot, the impeachments, the indictments. Now, they're threatening Nuremberg-like trials and another impeachment should they take back power in Congress, and the Right should do everything they can to make sure they don't. We know there are no limits on what they will do. We know because history tells us. George Orwell told us. We've seen this movie many times before. Utopias have only two paths forward: they collapse, or they become more authoritarian. These folks don't even know what words mean anymore, much less the point of 1984. No one ever taught them why Communism or tyrannical mobs are bad, so why wouldn't they behave this way? I noticed it for the first time when a small group of fanatics at Evergreen College chased Bret Weinstein off campus, calling him a racist and holding the administrators hostage until they gave them what they wanted.All of those pampered, spoiled, overeducated-yet-still-uneducated brats made their way into the workforce, boosted by using their identity categories to secure high-profile slots at newspapers and corporations. The threat was implicit: hire us or you're an “ist” or a “phobe” and we'll get loud about it. Only the Republicans have taken a consistent and principled stand against this madness and done so since it began. The Democrats, however, have stuck their head in the sand and denied it even exists. That's why they can't address crime in the major cities, or the rapes by illegal immigrants, and why their wheel of oppression has amounted to the party standing for only three things: Socialism, illegal immigration, and Palestine. No one seemed to take it seriously on the Left because they never took Cancel Culture seriously. No, we weren't being slaughtered by the millions or thrown into gulags, but we built this new civilization online and with it, the power to decide who can participate, who is accepted, and who must be hurled into the public square for character assassination and career ruination. No matter what the consequences were, it was wrong, and no one had the guts to stop it, and now, those chickens have come home to roost, and it's the Democrats' problem. They'd better get used to selling Democratic Socialism or else. This is what happened the last time the Centrists went up against the Socialists.Two years later, Al Franken would be chased out of the Senate by all of the top Democrats caught up in Cancel Culture and unable to stop the mass hysteria that drove it.And now, we have yet more insurrectionary behavior with Zohran Mamdani and some governors refusing to comply with the Supreme Court's ruling on sending back Haitian migrants, and many states aligning to protest the Great American State Fair. It looks like we have a Democratic Party that wants to secede from the Union, again.In the old days of Bernie Sanders' Democratic Socialism, they understood that taking care of American citizens required secure border programs like Medicare for All. Well, not now. The new kids want it all and believe they're entitled to it all. Borders? Who needs those? They are oppressed and therefore deserving of our tax dollars to absolve us of our white colonizer guilt. The big picture here should be frightening for all Americans. Unchecked migration with the oppressor/oppressed mindset, while also demanding the government and the “billionaires” pay for all of them - that is what the Democrats will have to sell to the American public because the Cancel Culture machine that they helped build and did nothing about will demand it. The Gray Champion Rides AgainThe Republicans have a unique opportunity now to change the course of history. They have been given a gift by the Left, whether they choose to take it or not. They are experiencing their own brand of crazy right now. It's starting to look a lot like Communists to the Left of me, Nazis to the Right, here I am, stuck in the middle with you.But if the sane Republicans can pull it together, they can bring in reasonable people, like Bill Maher:At the moment, the Democrats have the bigger headache on their hands. No one who seeks the nomination in 2028 will survive if they don't have Zohran Mamdani on their side. But honestly, the Republicans could be here too, depending on how their current war plays out. But if they want to win, they will have to open their doors to more moderate Democrats, perhaps giving up the old dream of outsider populism. They'll have to decide which they believe is the greater threat.Here is Larry O'Connor with Mark Halperin on 2-Way.America, the BeautifulIn 2020, I was hopeless and lost. No one on my side would talk about what all of us could see happening to our party, to our young people, with this unprecedented climate of fear and culture of silence.But then I heard Donald Trump's speech at Mount Rushmore on July 4th, and even though I'd been told he was a dangerous fascist and racist, I heard the words that anchor me to my own patriotic pride, words that describe the country I know and love. These were and are subversive words, but necessary. This is the America I believed in.Ever since then, I've trusted Trump because he did not bend, did not break, and never, ever, ever surrendered. I'm sorry he'll be leaving office in two years. I can't imagine the fight without him, but he's carved a path and lit the way. Now, it's our turn to finish the job. The race to normal begins right now. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.sashastone.com/subscribe

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“The frontier AI companies invited the government into the room. Now the government is beginning to behave as if it owns the door, the guest list, the schedule, and the product roadmap.” — Keith Teare Last week, I was away in Europe. So Keith Teare ran our That Was The Week show solo — with a chillingly authentic Andrew Keen bot. So realistic, in fact, that the fake version sounds (to me, at least) more interesting than the real one. The bad news is that I'm back. The good news is it's been an interesting week in tech. That was the week in which the US Commerce Department told both OpenAI and Anthropic that they now need government approval for whom they can sell their frontier AI models. This is supposedly “voluntary” — for now, at least. Keith's TWTW editorial argues that Dario Amodei and Sam Altman have spent over a year crying wolf about the dangers of their own technology, supposedly deliberately seeking government involvement as a regulatory moat against competitors. And now the government has walked through the door that Sam and Dario left ajar. Now, Keith argues, the US government is behaving as if it owns not just the door and the guest list, but the entire product roadmap. “Payback's a bitch,” Keith bristles in his editorial. The other major news this week is the rumour (via David Sacks) that OpenAI has offered the US government a 50% stake in a sovereign wealth fund. If true, this would change everything — not just in Silicon Valley, but in the political debate about public ownership of our AI economy. It's not just tech insiders like Sacks and Altman who are on board the sovereign wealth fund express, but also Bernie Sanders and other leftist critics of Big Tech. So maybe payback, at least when it comes to public investment in AI, isn't always such a bitch. Five Takeaways •       The Fake Andrew Keen: An Hour of Work on a Local Nvidia Card: Keith ran last week's show solo with an AI-generated Andrew Keen: trained on a few episodes of the show, animated from a YouTube still, scripted from Keith's newsletter. No third-party service. Just a local PC with an Nvidia GPU, about an hour of work, three attempts. Andrew, listening back, second-guessed whether he was actually there. The result was “pretty bad compared to our normal actual live shows,” Keith says. But also: really good. The question hanging over this episode and every future one: which Andrew are you listening to? •       Payback's a Bitch: How AI Companies Created Their Own Regulatory Trap: The US Commerce Department has told OpenAI and Anthropic they need government permission for who gets to use their latest models. Voluntary, for now. Keith's diagnosis: AI leadership spent more than a year crying wolf about existential risk — not because they believed it, but because government regulation creates a moat against competitors. Now the government has taken them at their word. Dario and Sam Altman wanted to be wrapped in government clothing. They are. The government now owns the door. They asked for this. They got it. •       American and Chinese State Capitalism: Converging Models: Andrew raises the macro argument: what we're watching is the convergence of American and Chinese models of capitalism toward a more state-centric model. China has always been explicit about state control. America has prided itself on free enterprise — even when the internet, atomic technology, and now AI were all substantially government-funded or government-shaped. Keith agrees at this level: all governments seek to control things they frame as dangerous. The difference is the framing. The direction of travel is the same. •       OpenAI's Rumoured 50% Stake Offer to the Government: Keith has heard — from sources including David Sacks, who should know — that OpenAI has offered the US government a very large stake, potentially 50%, in a sovereign wealth fund that would then distribute dividends to citizens. Sacks is not only unsurprised but in favour: he thinks 50% is too small. Andrew's question: why would OpenAI give away 50% of the company? Keith's answer: because it's the price of the regulatory moat. The government as partner rather than the government as regulator. A company that once aspired to “open” AI is now offering the state a controlling interest in its future. •       Paul Kennedy and America's Inevitable Decline: Keith has Paul Kennedy's Rise and Fall of the Great Powers on his shelf. His conclusion from it: it is historically impossible for America to retain its first-place status. No country ever has. Newly capitalised countries produce things more cheaply; China, India, and large parts of Asia are where most future growth will be. Does the AI boom change this? Keith's honest answer: no. It may slow the decline. It will not reverse it. America will, like an older gentleman on a rocking chair outside the house, accept its fate. Europe won't even be in the rocking chair. About the Guest Keith Teare is a British-American entrepreneur, investor, and publisher of the That Was the Week newsletter. He is a co-founder of TechCrunch and Andrew's regular TWTW co-host. References: •       That Was the Week by Keith Teare — the newsletter on which this episode is based. •       Azeem Azhar, The Exponential View — his report quantifying the AI economy at roughly $175 billion, referenced in the closing section. •       Alex Lazarow, 99%Tech — referenced for his piece on the emergence of an AI trust layer, the “Lloyds of AI.” •       Paul Kennedy, The Rise and Fall of the Great Powers — on Keith's shelf; referenced in the America-China decline section. •       David Sacks — referenced as the source for the OpenAI sovereign wealth fund rumour. About Keen On America Nobody asks more awkward questions than the Anglo-American writer and filmmaker Andrew Keen. In Keen On America, Andrew brings his pointed Transatlantic wit to making sense of the United States — hosting daily interviews about the history and future of this now venerable Republic. With nearly 3,000 episodes since the show launched on TechCrunch in 2010, Keen On America is the most prolific intellectual interview show in the history of podcasting. WebsiteSubstackYouTubeApple PodcastsSpotify Chapters: (00:38) - Introduction: the fake Andrew Keen from last week (01:14) - Keith explains how he did it: local Nvidia card, one hour, three attempts (02:11) - The big story: Commerce Department tells OpenAI and Anthropic they need permission ...

June 19, 2026: Anthropic's Fable 5 shutdown appears to be tied to SK Telecom, Project Glasswing, Amazon researchers, the White House, David Sacks, and a dispute over whether Anthropic should fix or de-deploy the model. Fortune 500 companies just hit record revenue, profit, revenue per employee, and profit per employee while shrinking headcount for the second year in a row, raising a bigger question about productivity gains without job growth. New data from LV8 founder Griffin Hadrill shows AI-generated creative ads are underperforming human-made ads by 3 to 5 times, which is a reminder that originality, emotional connection, and human judgment still matter.

The Fable 5 drama continues.... but what does it really mean?

El 10 de junio Dario Amodei, fundador de Anthropic, publicó una reflexión en la que pedía una regulación seria y vinculante para la inteligencia artificial. Dos días antes su empresa había lanzado Fable, una versión recortada de Mythos, el modelo de lenguaje más potente del momento. El viernes 12 de junio el Gobierno Trump le concedió el deseo de la peor manera posible. Por segunda vez en cuatro meses descargó una bomba sobre Anthropic. El Gobierno prohibió el uso de Fable y Mythos para los extranjeros escudándose en razones de seguridad nacional. Eso implicaba que nadie que no fuese estadounidense podía usar estos modelos, incluyendo a muchos empleados de la empresa que los ha desarrollado. Anthropic respondió apagándolos por completo, ya que cumplir esa orden les resultaba imposible. Mythos lo empleaban en ese momento unas 200 empresas e investigadores para monitorizar y parchear fallos de software en sectores como la banca, la sanidad y la industria. Todos se quedaron sin la herramienta de un día para otro. El origen de todo estuvo, según parece, en Andy Jassy, consejero delegado de Amazon, inversor en Anthropic y a la vez su competidor. El equipo de Jassy aseguraba haber conseguido que Fable revelara vulnerabilidades de seguridad nacional si se le hacían las preguntas de un modo concreto. A partir de ahí las versiones varían. David Sacks aseguró que el Gobierno pidió a Amodei arreglar o retirar Fable y que se negó. Anthropic habla solo de una orden de bloquear a los extranjeros. Tampoco ha quedado claro el soporte legal, los analistas apuntan al mismo reglamento de control de exportaciones que impide la venta de cierto tipo de chips a China. Para muchos el objetivo verdadero era simplemente castigar a una empresa concreta a la que Trump considera de izquierda radical y de estar fuera de control. No es, recordemos, la primera vez que el Gobierno carga contra ella. Hace unos meses Pete Hegseth sacó a Anthropic del Pentágono. Para la empresa esta polémica no podía llegar en peor momento, están ultimando su salida a Bolsa este otoño y sus principales competidores como OpenAI lo aprovecharán hasta el final. Varios expertos en ciberseguridad han relativizado la amenaza que supone Fable y Mythos. Aseguran que las pruebas solo han destapado vulnerabilidades menores ya conocidas. El domingo un grupo de expertos muy reconocidos en el ámbito de la seguridad informática firmaron una carta colectiva en la que pedían levantar el veto, ya que está dejando sin las mejores herramientas precisamente a quienes vigilan la seguridad de la red. Para los aliados más próximos como Australia, Canadá o el Reino Unido la imposibilidad de poder utilizar estos modelos es una bofetada que les equipara a Rusia o Irán. Pero esto de la IA se ha convertido ya en una lucha de carácter geopolítico y ahí no hay amigos, o los hay pero hasta cierto punto. En La ContraRéplica: 0:00 Introducción 3:28 Castigo para Claude 30:09 Endesa Empresas - https://endesa.com/empresas 31:45 La venezuelización de PSOE 41:16 Abusos de la Hacienda autonómica 45:08 Elecciones en Colombia · Canal de Telegram: https://t.me/lacontracronica · “Contra el pesimismo”… https://amzn.to/4m1RX2R · “Hispanos. Breve historia de los pueblos de habla hispana”… https://amzn.to/428js1G · “La ContraHistoria del comunismo”… https://amzn.to/39QP2KE · “La ContraHistoria de España. Auge, caída y vuelta a empezar de un país en 28 episodios”… https://amzn.to/3kXcZ6i · “Contra la Revolución Francesa”… https://amzn.to/4aF0LpZ · “Lutero, Calvino y Trento, la Reforma que no fue”… https://amzn.to/3shKOlK Apoya La Contra en: · Patreon... https://www.patreon.com/diazvillanueva · iVoox... https://www.ivoox.com/podcast-contracronica_sq_f1267769_1.html · Paypal... https://www.paypal.me/diazvillanueva Sígueme en: · Web... https://diazvillanueva.com · Twitter... https://twitter.com/diazvillanueva · Facebook... https://www.facebook.com/fernandodiazvillanueva1/ · Instagram... https://www.instagram.com/diazvillanueva · Linkedin… https://www.linkedin.com/in/fernando-d%C3%ADaz-villanueva-7303865/ · Flickr... https://www.flickr.com/photos/147276463@N05/?/ · Pinterest... https://www.pinterest.com/fernandodiazvillanueva Encuentra mis libros en: · Amazon... https://www.amazon.es/Fernando-Diaz-Villanueva/e/B00J2ASBXM #FernandoDiazVillanueva #claude #anthropic Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

“We are all in the gutter, but some of us are looking at the stars,” Oscar Wilde wrote in his 1892 play Lady Windermere's Fan. This week, Elon Musk managed — not for the first time — to be simultaneously in the stars and the gutter. SpaceX's IPO valued his rocket company at $2 trillion — making Musk, officially, a trillionaire, the richest person in the world by a very large margin. The space Musk — the defiant genius who bet everything on a reusable rocket and the promise of a cosmic monopoly — is astonishing. The Wall Street Journal called the IPO a Goldilocks debut with Musk starring as the three bears. But there is another Musk — the one in the gutter, promoting white nationalist violence from his platform on X. This week Musk not only stoked the anti-immigrant riots in Belfast but reiterated his support for the English white supremacist gangster Tommy Robinson. So is this another Strange Case of Dr Jekyll and Mr Hyde, Robert Louis Stevenson's 1886 novella? Keith Teare, publisher of That Was the Week, certainly thinks so. While Keith is in awe of Musk's entrepreneurial genius at SpaceX, he seems to excuse Musk's support for Tommy Robinson's paramilitarism. “I'm not even sure I like him,” Keith confesses in his musings on “civilisation.” Nor do the rest of us. But I wonder if this good/bad Elon narrative is too convenient. There is an uncomfortable symbiosis between Musk's journey to SpaceX and to white nationalist violence. For all the utopian cornucopia of space, our earthly reality is one of scarce land and fear of immigrants — Trump, Tommy Robinson, and this weekend's Swiss referendum on capping its population at 10 million. For all the Muskian promise of cosmic abundance, today's Muskian politics is paranoid and exclusionary. So maybe it's not just Elon. Everyone these days is simultaneously in the gutter and looking up at the stars. Five Takeaways •       SpaceX: From El Segundo Warehouse to $2 Trillion Juggernaut: SpaceX is 25 years old. It started in a warehouse near Los Angeles, in an area with a concentration of rocket scientists. Musk bet almost all of his Tesla gains on the idea of a reusable rocket — and nearly lost everything. Then a rocket worked. Since then: iterative improvement, the rockets getting bigger and more reliable, a virtual global monopoly on delivering payloads to space, Starlink (satellite internet that actually works at gigabit speeds), and NASA subcontracting its launches. Now: $2 trillion at IPO, Musk a trillionaire. Wall-to-wall applause from the startup world. Wall-to-wall pylon on social media. Both simultaneously true. •       The Grimace vs the Applause: Andrew vs Keith's Media Diet: Keith says most commentators are grimacing at the valuation and Musk's net worth. Andrew says the serious press — the Wall Street Journal, even the New York Times — is largely applauding. The exchange reveals the media bifurcation: mainstream outlets cover the achievement; social media — X, Facebook, LinkedIn — is wall-to-wall outrage about a trillionaire in a world of growing inequality. Keith's verdict on Musk: he doesn't care whether people like him. Neither, in Keith's view, should we. You judge him not on likability but on criteria: civilization or net worth. Different criteria, different judgment. •       California and Europe: The Failure of Government: Fareed Zakaria in the Washington Post: California is a case study in failed government. Andrew had Jonathan Weber on the show this week — City on the Edge, the historic dysfunctionality of San Francisco city government. Fukuyama is trying to be optimistic about Europe's liberal future. Keith's counter: Fukuyama ignores the structural problem — top-heavy EU bureaucracy that overrides countries, producing dislike of the EU in every European nation, even France, which built it. Populism, Keith argues, is not the disease. It's the symptom. The disease is twenty years of bad policy. •       Bernie Sanders Finally Had an Insight: The Sovereign Wealth Fund: Sanders has proposed a sovereign wealth fund owning 50% of all high-growth AI companies, giving every citizen ownership shares. Keith, who last week said 50% wasn't enough, this week credits it as the first genuine insight Sanders has had. The kicker: David Sacks — arch right-winger, former PayPal Mafia, Andreessen Horowitz — agreed on his podcast and said it should be 75%. Keith's observation: when David Sacks and Bernie Sanders can agree on the direction, left-right labels stop helping. The question is just how to make capitalism's gains flow to everyone. •       Planning Beats Complaint: Keith's editorial closer. The choice is not between liking Musk and hating Musk, not between celebrating SpaceX and resenting its valuation. The choice is between complaining and planning. John O'Farrell, former general partner at Andreessen Horowitz, resigned and wrote an op-ed in the New York Times: “We can't let my former venture capital colleagues buy off democracy.” Gary Tan organised an Asian-American reaction against San Francisco's school board and won. Citizens who act beat citizens who complain. That's the week's lesson. That's Keith's lesson. Andrew is away next week. About the Guest Keith Teare is a British-American entrepreneur, investor, and publisher of the That Was the Week newsletter. He is a co-founder of TechCrunch and Andrew's regular TWTW co-host. References: •       That Was the Week by Keith Teare. •       Fareed Zakaria, “How California Became a Case Study in Failed Government,” Washington Post — referenced in the conversation. •       John O'Farrell, “We Can't Let My Former Venture Capital Colleagues Buy Off Democracy,” New York Times — referenced in the conversation. •       Francis Fukuyama on the liberal vision of Europe — referenced in the conversation. •       Episode 2938: Jonathan Weber on City on the Edge — referenced at the opening. About Keen On America Nobody asks more awkward questions than the Anglo-American writer and filmmaker Andrew Keen. In Keen On America, Andrew brings his pointed Transatlantic wit to making sense of the United States — hosting daily interviews about the history and future of this now venerable Republic. With nearly 2,900 episodes since the show launched on TechCrunch in 2010, Keen On America is the most prolific intellectual interview show in the history of podcasting. WebsiteSubstackYouTubeApple PodcastsSpotify Chapters: (00:31) - Introduction: SpaceX IPO, ...

Anthropic's trillion‑dollar AI “pause” call sparks a clash over safety vs. regulatory capture, as PBD, Tom and David Sacks' camp debate recursive self‑improvement, China's AI race, and whether government or big tech will own the future.

A single backroom phone call between Elon Musk, Mark Zuckerberg, David Sacks and President Trump just killed the one executive order that could have put guardrails on the most dangerous AI models ever built. No public debate. No congressional vote. The people with the most to gain financially made the call and America is now racing into an AI future with zero oversight. Lance Wallnau and Mercedes Sparks break down exactly what was in that executive order, why Anthropic's Mythos model triggered the whole conversation, and what it means that the same AI systems capable of taking down power grids and banking infrastructure are now completely unregulated. Lance and Mercedes also unpack the uncomfortable truth that every person who talked Trump out of signing is financially incentivized to keep government out of the AI space entirely. This is not a left versus right issue. This is a power versus everyone else issue. 00:00 The Backroom Call Explained 02:30 What Anthropic's Mythos Model Actually Did 06:00 Zero Day Vulnerabilities and Critical Infrastructure 09:00 Why Elon and Zuckerberg Fought the Order 12:00 The AI Arms Race Against China 14:00 What a Christian Worldview Says About Unchecked AI 16:00 The Digital Bill of Rights and Intellectual Property 18:00 Where This Is All Headed  LIKE if you knew Big Tech was calling the shots all along  COMMENT: Drop BACKROOM in the comments if you think the American people deserved a vote on this.  Subscribe so you never miss a live breakdown. Podcast Episode 2134: The Backroom Call That Changed America's AI Future | don't miss this! Listen to more episodes of the Lance Wallnau Show at lancewallnau.com/podcast

Photographer Rick Sammon shows how AI is transforming creative work and what happens when the Pope issues a sweeping 42,000-word encyclical on artificial intelligence and invites tech skeptics and true believers to weigh in? The Pope's AI encyclical: technology, ethics, and human dignity Amazing interior, controversial exterior: Ferrari's first electric car Even if you hate AI, you will use Google AI Search There's a new way to create Google Docs with your voice White House, Anthropic near deal for spy agencies to use AI Claude Mythos preview uncovers 10,000+ zero-day vulnerabilities in Project Glasswing Anthropic to release Mythos-class models to the public Chinese AI startup DeepSeek slashes price of flagship model Spotify and Universal Music strike deal allowing fan-made AI covers and remixes ElevenLabs's new music generation model can switch genres mid-track David Sacks's 11th-hour plea led to Trump's backtrack on AI executive order I'm tired of talking to AI In Memoriam: Don Newhouse Picks of the Week: KMart Muzak Infinite Jeffs isaiprofitable.com Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Rick Sammon Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: trustedtech.team/intelligent365 zscaler.com/security

Photographer Rick Sammon shows how AI is transforming creative work and what happens when the Pope issues a sweeping 42,000-word encyclical on artificial intelligence and invites tech skeptics and true believers to weigh in? The Pope's AI encyclical: technology, ethics, and human dignity Amazing interior, controversial exterior: Ferrari's first electric car Even if you hate AI, you will use Google AI Search There's a new way to create Google Docs with your voice White House, Anthropic near deal for spy agencies to use AI Claude Mythos preview uncovers 10,000+ zero-day vulnerabilities in Project Glasswing Anthropic to release Mythos-class models to the public Chinese AI startup DeepSeek slashes price of flagship model Spotify and Universal Music strike deal allowing fan-made AI covers and remixes ElevenLabs's new music generation model can switch genres mid-track David Sacks's 11th-hour plea led to Trump's backtrack on AI executive order I'm tired of talking to AI In Memoriam: Don Newhouse Picks of the Week: KMart Muzak Infinite Jeffs isaiprofitable.com Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Rick Sammon Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: trustedtech.team/intelligent365 zscaler.com/security

Photographer Rick Sammon shows how AI is transforming creative work and what happens when the Pope issues a sweeping 42,000-word encyclical on artificial intelligence and invites tech skeptics and true believers to weigh in? The Pope's AI encyclical: technology, ethics, and human dignity Amazing interior, controversial exterior: Ferrari's first electric car Even if you hate AI, you will use Google AI Search There's a new way to create Google Docs with your voice White House, Anthropic near deal for spy agencies to use AI Claude Mythos preview uncovers 10,000+ zero-day vulnerabilities in Project Glasswing Anthropic to release Mythos-class models to the public Chinese AI startup DeepSeek slashes price of flagship model Spotify and Universal Music strike deal allowing fan-made AI covers and remixes ElevenLabs's new music generation model can switch genres mid-track David Sacks's 11th-hour plea led to Trump's backtrack on AI executive order I'm tired of talking to AI In Memoriam: Don Newhouse Picks of the Week: KMart Muzak Infinite Jeffs isaiprofitable.com Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Rick Sammon Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: trustedtech.team/intelligent365 zscaler.com/security

Photographer Rick Sammon shows how AI is transforming creative work and what happens when the Pope issues a sweeping 42,000-word encyclical on artificial intelligence and invites tech skeptics and true believers to weigh in? The Pope's AI encyclical: technology, ethics, and human dignity Amazing interior, controversial exterior: Ferrari's first electric car Even if you hate AI, you will use Google AI Search There's a new way to create Google Docs with your voice White House, Anthropic near deal for spy agencies to use AI Claude Mythos preview uncovers 10,000+ zero-day vulnerabilities in Project Glasswing Anthropic to release Mythos-class models to the public Chinese AI startup DeepSeek slashes price of flagship model Spotify and Universal Music strike deal allowing fan-made AI covers and remixes ElevenLabs's new music generation model can switch genres mid-track David Sacks's 11th-hour plea led to Trump's backtrack on AI executive order I'm tired of talking to AI In Memoriam: Don Newhouse Picks of the Week: KMart Muzak Infinite Jeffs isaiprofitable.com Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Rick Sammon Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: trustedtech.team/intelligent365 zscaler.com/security

The Pope said WHAT about AI?

David Sacks has played a key role in shaping AI policy for the Trump administration. He was formerly the White House AI and crypto czar. Now, he's the co-chair of the President's Co-Chair of the President's Council of Advisors on Science and Technology.  Sacks approaches the issue with a “let them cook” philosophy. Meaning, he thinks the way for the United States to win the global AI race is to move fast with minimally disruptive regulation. But with that comes a lot of questions about AI disruption to the workforce, who should be held responsible for harm caused by AI platforms, and the fear and division within America over the future of the technology.  Sacks joins Dasha Burns in a wide-ranging interview to discuss it all.

David Sacks has played a key role in shaping AI policy for the Trump administration. He was formerly the White House AI and crypto czar. Now, he's the co-chair of the President's Co-Chair of the President's Council of Advisors on Science and Technology.  Sacks approaches the issue with a “let them cook” philosophy. Meaning, he thinks the way for the United States to win the global AI race is to move fast with minimally disruptive regulation. But with that comes a lot of questions about AI disruption to the workforce, who should be held responsible for harm caused by AI platforms, and the fear and division within America over the future of the technology.  Sacks joins Dasha Burns in a wide-ranging interview to discuss it all. Learn more about your ad choices. Visit megaphone.fm/adchoices

Keith Rabois was an early executive at PayPal (part of the famous PayPal Mafia), COO at Square, VP of Corporate Development at LinkedIn, and an early investor in Stripe, DoorDash, Airbnb, YouTube, Ramp, and Palantir. Currently he's managing director at Khosla Ventures. Also, he hasn't touched a computer since September 2010 (he does everything from an iPad).In our in-depth conversation, Keith shares:1. The barrels vs. ammunition hiring framework (and how to spot barrels)2. Why talking to customers is actively harmful for consumer products3. How to identify undiscovered talent4. Why the PM role is dying5. The three traits of the best-performing companies right now6. The specific interview question he asks every senior candidate7. Why CMOs (not engineers) are becoming the #1 consumer of tokens—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUsVanta—automate compliance, manage risk, and accelerate trust with AI—Episode transcript: https://www.lennysnewsletter.com/p/hard-truths-about-building-in-the-ai-era—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Keith Rabois:• X: https://x.com/rabois• LinkedIn: linkedin.com/in/keith• Website: https://www.khoslaventures.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Keith Rabois(01:59) Why Keith hasn't used a computer since 2010(04:52) The team you build is the company you build(07:40) How Keith learned to identify talent at PayPal(10:05) Tactics for getting better at hiring(15:31) The barrels vs. ammunition framework(18:52) What makes someone a barrel(22:36) How to attract the best talent(26:18) Building companies on undiscovered talent(27:53) Why better performance requires more pressure(32:36) Career advice in the age of AI(35:14) The future of the product triad(41:03) Why design and code are merging(49:35) What practicing law taught Keith about entrepreneurship(51:22) Contrarian takes on customer feedback(1:02:33) Identifying great AI opportunities(1:05:13) Advice for evaluating statrups (1:12:36) Criticizing in public vs. private(1:15:05) Failure corner(1:17:29) Lightning round—Referenced:• Square: https://squareup.com• Jack Dorsey on X: https://x.com/jack• Head of Claude Code: What happens after coding is solved | Boris Cherny: https://www.lennysnewsletter.com/p/head-of-claude-code-what-happens• Simon Willison's Weblog: https://simonwillison.net• Vinod Khosla on X: https://x.com/vkhosla• Peter Thiel on X: https://x.com/peterthiel• Max Levchin on X: https://x.com/mlevchin• David Sacks on LinkedIn: https://www.linkedin.com/in/davidoliversacks• Tony Xu on X: https://x.com/t_xu• David Sze on X: https://x.com/davidsze• Faire: https://www.faire.com• Max Rhodes on X: https://x.com/MaxRhodesOK• Jeffrey Kolovson on LinkedIn: https://www.linkedin.com/in/jeffreykolovson• Uncapped | Comparative Advantages w/ Keith Rabois: https://www.khoslaventures.com/posts/uncapped-comparative-advantages-w-keith-rabois• Lattice: https://lattice.com• Taylor Francis on LinkedIn: https://www.linkedin.com/in/taylor-francis-4ba49640• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• The art of hiring: insights from Khosla Ventures, Airbnb, Ramp and Traba: https://ramp.com/velocity/the-art-of-hiring-insights• Eric Glyman: Seek out super individual contributors (ICs): https://ramp.com/velocity/the-art-of-hiring-insights#Eric-Glyman:-Seek-out-super-individual-contributors-(ICs)• Eric Glyman on X: https://x.com/eglyman• Mike Moore on LinkedIn: https://www.linkedin.com/in/mike-moore-802223177• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Why you should work much harder RIGHT NOW: https://marginalrevolution.com/marginalrevolution/2026/03/why-you-should-work-much-harder-right-now.html• Opendoor: https://www.opendoor.com• The Craft of Early Stage Venture | Peter Fenton, General Partner at Benchmark | Uncapped with Jack Altman: https://www.youtube.com/watch?v=vRiblwiXt-Q• Lovable: https://lovable.dev• The rise of the professional vibe coder (a new AI-era job) | Lazar Jovanovic (Professional Vibe Coder): https://www.lennysnewsletter.com/p/getting-paid-to-vibe-code• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• Jeremy Stoppelman on X: https://x.com/jeremys• The design process is dead. Here's what's replacing it. | Jenny Wen (head of design at Claude): https://www.lennysnewsletter.com/p/the-design-process-is-dead• Andy Warhol: https://en.wikipedia.org/wiki/Andy_Warhol• Curation and Algorithms: https://stratechery.com/2015/curation-and-algorithms• Ernest Hemingway: https://en.wikipedia.org/wiki/Ernest_Hemingway• William Shakespeare: https://en.wikipedia.org/wiki/William_Shakespeare• Evan Moore on X: https://x.com/evancharles• Andrew Mason on X: https://x.com/andrewmason• Read Taylor Swift's Full Viral Speech After Record-Breaking Awards Sweep: https://www.newsweek.com/entertainment/read-taylor-swift-full-acceptance-speech-record-breaking-awards-sweep-11745941• The Chainsmokers: Stories Behind the Songs, AI's Impact on Music, and Venture Investing | Uncapped with Jack Altman: https://www.youtube.com/watch?v=9GMSC-2pYnw&list=PLtpH7YnTL8ihy0nR2BV32n5VkRtqlDAS1&index=16• How to spot a top 1% startup early: https://www.lennysnewsletter.com/p/how-to-spot-a-top-1-startup-early• David Weiden on LinkedIn: https://www.linkedin.com/in/davidweiden• Alfred Lin on LinkedIn: https://www.linkedin.com/in/linalfred• Keith's post about vertical integration on X: https://x.com/rabois/status/870673635375104000• Jon Chu on X: https://x.com/jonchu• Kanu Gulati on X: https://x.com/KanuGulati• Rogo: https://rogo.ai• Profound: https://www.tryprofound.com• Basis: https://www.getbasis.ai• Spellbook: https://www.spellbook.legal• Roelof Botha on X: https://x.com/roelofbotha• Delian Asparouhov on LinkedIn: https://www.linkedin.com/in/delian-asparouhov-87447742• Lessons From Keith Rabois, Essay 1: How to become a Venture Capitalist: https://delian.io/lessons-1• Velocity over everything: How Ramp became the fastest-growing SaaS startup of all time | Geoff Charles (VP of Product): https://www.lennysnewsletter.com/p/velocity-over-everything-how-ramp• Nuremberg on AppleTV+: https://tv.apple.com/us/movie/nuremberg/umc.cmc.3sg4y0382byupy76bfy7307k4• Eight Sleep: https://www.eightsleep.com• “NO DAYS OFF”—Bill Belichick on X: https://x.com/SNFonNBC/status/829036279069364224—Recommended books:• Creativity, Inc.: Overcoming the Unseen Forces That Stand in the Way of True Inspiration: https://www.amazon.com/Creativity-Inc-Overcoming-Unseen-Inspiration/dp/0812993012• The Jordan Rules: The Inside Story of One Turbulent Season with Michael Jordan and the Chicago Bulls: https://www.amazon.com/Jordan-Rules-Sam-Smith/dp/0671796666• The Upside of Stress: Why Stress Is Good for You, and How to Get Good at It: https://www.amazon.com/Upside-Stress-Why-Good-You/dp/1101982934—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com