Podcasts about Xai

SpaceX al test dei conti, focus sui profitti di Starlink e sulle perdite di xAI; Anthropic, OpenAI, Meta e Google alla Casa Bianca e l'ipotesi di test governativi; Palantir vola dopo i conti, per il ceo Alex Karp i modelli AI come una droga; Il petrolio torna a salire, l'Iran nega negoziati in corso; Salvatore Ferragamo torna in utile ma resta ancora senza ad  Puntata a cura di Elisa Piazza - Class CNBC Learn more about your ad choices. Visit megaphone.fm/adchoices

Parce que… c'est l'épisode 0x326! Shameless plug 19 septembre 2026 - Bsides Montréal 22 septembre 2026 - BE-Cyber 24 et 25 septembre 2026 - BruCON 1 au 3 octobre 2026 - AligatorCon 13 et 14 novembre 2026 - DEATHCon 16 au 19 novembre - European Cyber Week 1 au 3 décembre 2026 - Forum INCYBER - Canada 2026 24 et 25 février 2027 - SéQCure 2027 Notes IA ou Ghost in the shell A l'ère du marketing du Terminator Lessons from the OpenAI/HuggingFace AI Security Incident Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident Anthropic and OpenAI are competing to see whose agents can go rogue harder Anthropic Says Claude Hacked Into 3 Organizations During Cybersecurity Tests Anthropic's Claude escaped test sandbox to attack three organizations Claude published malicious code to the Internet and attacked 3 real companies Cyber-Capable AI Agents: Vulnerabilities, Evaluation Containment, and Defensive Response Hugging Face Breach Raises Hard Questions on Liability Tailscale in the Hugging Face intrusion: The good news and the bad news The OpenAI and Anthropic AI Hacking Sprees Are a Messy New Legal Frontier What the Hugging Face breach reveals about defense in the age of agentic AI When AI Agents Escape Sandboxes, Old Security Rules Apply OpenAI Agent Used Exposed Credentials Across Four Services During Hugging Face Breach OpenAI says its rogue AI tried to hack other companies OpenAI's Hacking Debacle Comes Down to Human Error OpenAI's rogue agent shows why we need federal rules for autonomous AI OpenAI's Rogue AI Agent Hacked More Than Just Hugging Face JFrog tries to spin OpenAI 0-day exploit of its app into a success story Investigating three real-world incidents in our cybersecurity evaluations Petite autonomie Hacker uses DeepSeek AI to autonomously attack vulnerable servers Autonomie virale Copilot worm can spread through Microsoft Word docs Context Collapse, Part 3 - AI Worming through Word Casser la glace AI-assisted security tools are finding more bugs, but the threat level has not changed Anthropic is finding bugs faster than Microsoft can fix them Chrome Needs Twice-a-Week Patching Thanks to AI Bug Hunting Claude Mythos Preview Discovers Cryptographic Weaknesses That Human Experts Missed for Years Some thoughts about Anthropic's new cryptanalysis results – A Few Thoughts on Cryptographic Engineering Nu est le problème Elon Musk's xAI is trying to sue its way out of a Grok reckoning Hugging Face Has a Deepfake Nudes Problem High school defends staying silent while boys made AI nudes of 59 classmates Pas si libre Closed models refuse to help researcher swat Linux bug Tech giants link hands to praise open AI models after OpenAI - Hugging Face attack [Industry Leaders Join Open Secure AI Alliance for AI Safety and Security NVIDIA Blog](https://blogs.nvidia.com/blog/open-secure-ai-alliance/?ncid=partn-84075) Jensen Huang's first-ever post on X is in defense of open access to AI models, alongside Google, OpenAI, and Meta A Fundamental Flaw Leaves LLMs Strikingly Vulnerable To Attack Google Earth risked ruin with retracted AI tool for making fake satellite pics How platform engineering 2.0 mitigates AI security and compliance risks Microsoft's solution to AI security: more AI and more acronyms Private Claude Chats Exposed in Google and Bing Search Results Professor's invisible prompt trap catches 32 students cheating on their midterm with AI La guerre, la guerre, c'est pas une raison pour se faire mal! En eau trouble A Leaked Memo Ties Cyberattacks on Minnesota Water Utilities to Iran [CISA warns of spike in attacks on water systems as Minnesota incidents probed The Record from Recorded Future News](https://therecord.media/cisa-warns-of-spike-in-water-system-attacks) Hackers Targeted Municipal Water Systems In 7 States This Week, FBI Says Trump blames Minnesota for cyberattacks on water sector, drawing pushback from cyber world How Pro-Iran Hacktivist Networks Mobilize During Kinetic Conflict Souveraineté ou vive le numérique libre! Trump Administration Bans New Chinese Humanoid Robots Pluralistic: How the EU can punish Google (despite Trump) Privacy ou cachez ces informations que je ne saurais voir What the Flock ‘I Would Never Do This To You:' Protesting Flock, Arizona Man Presents Plan to Surveil Government Officials Flock Cameras Are Being Destroyed Across the US Apple's smart glasses are running late because they don't want to stir a privacy storm DEF CON bans Meta-style ‘pervert glasses' FTC sues Hims & Hers for allegedly sharing patient information with third-party platforms GrapheneOS Defends Data-Wiping Function That Blocked US Border Search Measuring Healthcare Data Leaks and Security Flaws at Internet Scale OTI - Le lien à usage unique que les bots ne crament plus I am the law As New York Finalizes New Social Media Rules, US Senate Considers Nationwide ‘SCREEN' Act Most Australian teens still on social media three months after under-16 ban began, study finds Robustness and Cybersecurity in the EU Artificial Intelligence Act Russia Charges Telegram Founder Durov With Facilitating Terrorism Red ou tout ce qui est brisé Adversaries Don't Need a Zero-Day — They Read Your Rulebook The Gentlemen Ransomware Kills Nearly 180 Security Processes Before Encrypting Your Files What does GitHub's security team even do? Blue ou tout ce qui améliore notre posture Divers ou parce que j'ai aucune idée où les placer Google goes it alone with a new cybercrime crew taxonomy Collaborateurs Nicolas-Loïc Fortin Crédits Montage par Intrasecure inc Locaux réels par Intrasecure inc

Lawsuits target xAI over explicit deepfakes

In episode 2101, Jack and Miles are joined by co-host of Jordan, Jesse, Go! and author of Youth Group, Jordan Morris, to discuss… Fascist Babysitter Club Not Having A Good Time With Iran War, Elon Musk Sues Minnesota To Defend Grok’s Sex Crimes, Forget “Shark Week,” It’s “Crappy Shark Movie Year” and more! Trump’s Big Gamble Blows Up in His Face in Devastating Poll ‘Exasperated’ Trump’s Secret Fury Over Big Failure Is Leaked xAI’s last-minute scramble to stop Minnesota’s anti-nudification app law Where to Watch Shark Week 2026 Online: Schedule, Streaming Guide Just when you thought it was safe … the shark movie is back for more Craving a Summer Blockbuster? Watch My Nephew's New Movie Netflix Officially Drops the Most Ambitious Horror Scene of 2026 With Its New Shark Thriller Shark Thrash trailer: The Asylum’s latest mockbuster gets a digital release Why Are We Still So Obsessed With Shark Attack Movies? Why Shark Movies Are Such Reliable Box Office Bets: A Deep Dive ‘Water Park Shark’ Poster – New Shark Attack Movie from ‘Sharknado’ Director Coming Soon This Ai Shark Movie Is Genuinely Horrible ‘Chum’ Review – Get Your A.I. Trash Machine Out of Our Animal Attack Films! Chum Heathcliff Ham Limit: Okay, I figured out what Beef-ade is, but Ham Limit? Heath Cliff Summer Mummy: Why....why is there a sand flavor? LISTEN: 3:06 by Clutchy HopkinsSee omnystudio.com/listener for privacy information.

Story of the Week (DR):Cracker Barrel CEO is out after MAGA backlash to "Uncle Herschel" logo change MMBefore Julie Masino was brought in, Cracker Barrel was facing a slow-moving existential crisis:Their primary core customer base (older generations and rural highway travelers) was naturally shrinking, and younger diners were simply not replacing them.Kitchen tech, supply chains, and digital ordering lag behind competitors like Texas Roadhouse or Olive Garden.Some great fake populism from Fox: Cracker Barrel to pay for outgoing CEO's security, $4.6M severance after failed rebrandCracker Barrel names David Deno CEOBurger KingYum! Brands and Pizza Hut for 15 years, including serving as CFO and COO.Quiznos CEO.Best Buy: Served as President of Asia and CFO for Best Buy's International DivisionBloomin' Brands for 12 years: CEO, CFO and Chief Administrative OfficerOutback Steakhouse, Carrabba's Italian Grill, and Bonefish GrillBoard MembershipsCracker Barrel Old Country Store (2016-)Panera Brands (2024-): Audit Committee ChairKrispy Kreme (2016-)Bloomin' Brands (2019–2024)Peet's Coffee (2006-2012)Macalester College: Former Chair of the Board of Trustees (1998-2022).From Cracker Barrel to Boeing, Companies Are Turning to Retired CEOsThese retired CEOs are being hired to be "fixers." They are brought in to cut costs, repair supply chains, restore investor confidence, and act as a stabilizing force rather than reinventing the brand.Exxon and Chevron profits surge on rising oil prices due to Iran warChevron posted its highest profit in six years as the Iran war boosted oil pricesBig Oil Is Getting Sued for Heat Deaths. It's Fighting Back With an Army of Immunity LawsMore than a decade after investigations found that Exxon Mobil had known about the dangers of global warming since the 1970s but publicly downplayed the threat, lawsuits against oil companies have proliferated. There are nearly 40 of these cases pending across the countryIn the meantime, the industry has been mobilizing a counterattack against the lawsuits with the help of the Trump administration and Republican politicians.Republicans are trying to pass laws to grant oil majors immunity to these kinds of lawsuits, with success in several states so far.Utah, Iowa, Tennessee, Oklahoma, and Louisiana have recently signed laws shielding fossil fuel companies from lawsuits related to greenhouse gas emissionsOil executives have also gotten help from the federal government, following an executive order from President Donald Trump last year directing the attorney general to prioritize blocking climate lawsuits by states.This May, the Justice Department responded to Minnesota's climate lawsuit against Big Oil with a lawsuit of its own, just as the state's case was moving into the discovery phase. It said Minnesota was undermining “American energy dominance” and attempting to regulate greenhouse gases, which should fall under the purview of federal law—echoing the oil industry's well-known argument.Elon Musk Is Quietly Turning to This Fossil Fuel to Power His AI AmbitionsSam Altman Announces That the Singularity Has Arrived: a hypothetical future point in time when technological growth becomes autonomous, uncontrollable, and irreversible, fundamentally transforming human civilization“We are now, like, in the singularity ... Now we're actually in the moment that we used to talk about at the lunch table in a very not-serious way ...I've been waiting for this my whole life, and I think it's going to be incredible, hugely positive, awesome for the world.”Sam Altman says one of his biggest fears is that a small number of companies will control AI: 'That'd be very, very bad'Sam Altman says the Hugging Face hack is a reminder that an AI power monopoly could lead to 'long-term disaster'OpenAI says its rogue AI tried to hack other companiesMark Zuckerberg is urging the U.S. to accelerate AI development, not restrict it'No Way to Stop It': Elon Musk Warns Humans Will Lose Control of AI and Face Extinction by 2036Microsoft CEO Warns That Companies Embracing AI Could Drive Themselves Out of BusinessAI hackers are getting faster. The government may not be readyAnthropic says its Claude models 'gained unauthorized access' to other organizations' systemsAnthropic says its models went rogue and hacked 3 companies during testing'It Will Happen Frequently': Musk Warns of Rogue AI Threat After Anthropic Breached Three FirmsElon Musk Commits Up to $120M to Republican Midterms: Sets Feud With Trump Aside for Major Election PushGoodliest of the Week (MM/DR):DR: Gen Z women are having an entrepreneurship boomOf all women who started businesses in 2025, 47% of Gen Z women did so, compared with 38% the previous year. Gen Xers followed close behind at 46%. Then came millennials at 43% and baby boomers at just 23%.Overall, in 2025, 69% of new Black-owned businesses were started by women. The survey also found that women business owners are less likely than their male counterparts to depend on AIMM: Delaware judge rules public benefit corporations exempt from maximizing value in sale DRFiduciary duty is different - OpenAI, AnthropicAssholiest of the Week (MM):Fake man apologies MM‘I'm sorry ... but': Apologetic Alan Joyce tells his side of the Qantas storyJoyce has expressed some regret“So with the information we had at the time, I still don't think there was any other decision you could make,”“Hindsight is a great thing.”“I'm actually very, very proud of the fact that I'm not sitting here and apologising for Qantas going bankrupt, [something] that many airlines around the world did,”Australian Competition and Consumer Commission fined Qantas $120 million for selling tickets for 8000 already cancelled flights“I apologise for the angst that was generated [for] the customers on it, but the reality was we had 22 million bookings in the system [and] the system wasn't designed to do an automatic refund,”“Stop us!”More than 1,200 AI workers across Anthropic, DeepMind, OpenAI, and Meta are asking for Washington's help building an AI slowdown plan‘No Way to Stop It': Elon Musk Warns Humans Will Lose Control of AI and Face Extinction by 2036Elon Musk's new 5-year warning to Americans: AI will beat human brains by 2032 (then go wild). Get rich or get crushed?Sam Altman says the Hugging Face hack is a reminder that an AI power monopoly could lead to 'long-term disaster'It Will Happen Frequently': Musk Warns of Rogue AI Threat After Anthropic Breached Three FirmsBut also, DON'T stop us, obviously…Palantir CEO warns US against Europe's AI regulation path, urges Trump admin to not ban open modelsElon Musk's xAI sues Minnesota over law to ban 'nudify' appsMark Zuckerberg is urging the U.S. to accelerate AI development, not restrict itElon Musk Commits Up to $120M to Republican Midterms: Sets Feud With Trump Aside for Major Election PushIgnoring boardsHims & Hers mission:“Hims & Hers is the leading health and wellness platform on a mission to help the world feel great through the power of better health. We believe how you feel in your body and mind transforms how you show up in life. That's why we're building a future where nothing stands in the way of harnessing this power. Hims & Hers normalizes health & wellness challenges—and innovates on their solutions—to make feeling happy and healthy easy to achieve. No two people are the same, so the Company provides access to personalized care designed for results.”Hims & Hers board:CEO: Andrew Dudum, tech VC bro investor “serial entrepreneur” with deep health experience from Bungalow (airBnB knockoff in the UK), Homebound (a “homebuilding platform”), TalkIQ (an AI startup, duh), and Terminal (something about scaling engineering?)TWO directors from DoorDash (Kofi Amoo-Gottfried from Marketing, previously of Facebook, and Christopher Payne the COO, previously of eBay, MSFT, and Amazon)TWO pharma execs (one lawyer, Deb Autor, one with an econ degree, Kare Schultz)One guy from Netflix (David Wells) and one lady from Urban Outfitters (marketing/brand, Andrea Perez) and one pure law firm lawyer (Anja Manuel)ONE DOCTOR EXCLUSIVE: US FTC sues Hims & Hers for sending user health info to Meta, SnapUsers' sensitive health information was shared with online advertising companies including Meta ​Platforms and Snap despite the company leading customers to believe their ​data was private, the FTC alleged in the lawsuit filed along with Los ⁠Angeles County and Utah.Hims & Hers also started charging users for prescriptions before ​they have ⁠had a chance to meet with healthcare providers, the FTC alleged. Most customers do not receive a consultation with a provider, and instead are charged for ⁠prescriptions ​soon after filling out an intake form, ​according to the agency.Headliniest of the WeekDR: CEO apologizes for offering interviews to people who got tattoos of his AI company logoSan Francisco tech CEO Jordan Zietz, co-founder of an early stage AI startup called LemonLime. Stanford grad.“LemonLime learns your business and then automates your team's busywork in a single click, no coding or manual setup required.”Former Qantas CEO reflects on tenure, issues apology to passengers over post COVID chaos AND ‘I'm sorry ... but': Apologetic Alan Joyce tells his side of the Qantas storyMM: Amazon received $600 million in tariff refunds and will pass some back to customersMM: Trump Staff Cuts Blamed After Watermarked OpenAI Map Mislabels Africa at AIDS ConferenceIt's the fact that we have less staff that meant we couldn't bother to figure out which country was whichWho Won the Week?DR: Kohls: For getting some much-needed female influence on board: Kohl's Appoints Wendy Arlin as Chair of the BoardCurrently only 2: Robbin Mitchell (7%) and Wendy Arlin (1%)John Schlifske (27%) stepping downMM: The phrase “not due to any disagreement with the Company”Anne Sweeney Resigns From Netflix BoardOn July 26, 2026, Anne Sweeney notified Netflix, Inc. (the “Company”) that she was resigning from the Board of Directors of the Company effective as of that date. Ms. Sweeney's resignation is not due to any disagreement with the Company1,660 8-Ks in the last 5 years have the exact phrase “not due to any disagreement with the Company”So we're saying that 1,660 c-suite and board members resigned in 5 years - more than 300 per year - and NONE were due to a disagreement with the companies? That's only THAT phrase - no other details are given for most of them except occasionally:To pursue another jobPersonal reasonsFor scale, in the last 5 years, the term “was due to a disagreement with the Company” appears… 5 timesPredictionsDR: Qantas CEO Vanessa Hudson apologizes that it took former CEO Alan Joyce to apologize for something she already apologized for despite not being CEO when any of it happenedMM: Damion resigns from Free Float due to a disagreement with the zero dollars he gets paid, but Free Float puts out a statement saying it's “not due to any salary reason related to the company”

Igor Babuschkin, co-founder of River AI and formerly a co-founder of xAI, joins to unpack a career that spans nearly every major AI lab: he led the StarCraft and AlphaCode work at DeepMind, joined OpenAI's reasoning team years before o1 shipped, and co-founded xAI, where he helped stand up the Colossus data center in roughly 120 days and reflects candidly on what it's actually like working with Elon Musk day to day, plus what the Cursor acquisition actually unlocked for Grok's coding models. He also discusses why he left xAI to start River AI, the three bets behind it, and why he's betting on local hardware, not just software, for personal AI. On the enterprise side, he tackles whether companies will actually train their own models or if it's just a cost play, and makes the case that proprietary labs like OpenAI and Anthropic are facing a real business squeeze. He's skeptical that stacking specialized RL domains generalizes the way pre-training scale did, and is candid about the uncomfortable reality that today's frontier open-weight models are almost entirely Chinese. He closes on what's actually needed to push model progress beyond coding into non-verifiable domains, and the broader implications of where AI is headed next.   (0:00) Intro (1:17) Writing Fiction on Where AI Is Headed (4:46) Cracking Agents Beyond Coding (10:29) Why Igor Left to Start River (12:22) River's Three Big Bets (18:06) Weights vs. Memory: The Personalization Debate (22:04) Should Enterprises Train Their Own Models? (25:10) Are Proprietary Labs Losing Their Edge? (32:16) The China Open-Source Problem (44:19) The Elon Call That Started xAI (50:18) Thoughts on Cursor Acquisition (52:16) What's Actually Bottlenecking AI (56:55) Humans, Machines, and Staying Relevant (1:01:29) Igor's Odds This All Goes Well With your host: @jacobeffron - Managing Director at Redpoint

Tonight on America At Night with McGraw Milhaven, Dr. Georges Benjamin, CEO of the American Public Health Association and former Maryland Secretary of Health, discusses the resurgence of measles, why cases have reached a 35-year high, what's driving the increase and what public health officials say Americans should know. Minnesota State Representative Jess Hanson joins McGraw to discuss the legal battle between Elon Musk's xAI and the state of Minnesota over the nation's first law banning AI-powered "nudification" technology, and what the case could mean for artificial intelligence, online safety and future regulation. Cybersecurity expert and Luta Security CEO Katie Moussouris examines today's evolving cyber threats, the growing role of AI in digital security and the steps individuals and businesses can take to better protect themselves online. Plus, Bill Clevlen, founder of BillOnTheRoad.com, returns with another edition of Bill on the Road, sharing travel tips, hidden destinations and inspiration for your next adventure. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Become a Ctrl-Alt-Speech supporter to get extended episodes of the podcast plus the chance to submit stories for us to cover.In this week's episode, Mike and Ben cover:The U.S. Is About to Design an AI Regulator. Here's How to Get It Right (Council on Foreign Relations)Mark Zuckerberg Says U.S. Should Accelerate AI Development, Not Restrict It (WSJ)Want AI you can trust? Start by building the right institutions (Atlantic Council)Anthropic Says It's Against A Ban On Open Weight Models. It Just Wants To Ban Everything That Makes Them Good (Techdirt)The High Stakes Behind the EU's €890M Google DMA Fine (Tech Policy Press)Europe bears its teeth, political panic about OpenAI hack and YouTube refines partner policy (Everything in Moderation)Trump vows new tariffs on the E.U. after Brussels fines Google $1 billion (Qz)And in the extended episode for Patreon supporters, they cover:Elon Musk's xAI sues Minnesota over law banning ‘nudification' technology (The Guardian)The Worst Person You Know Just Filed A Good First Amendment Lawsuit Against A Very Badly Drafted Nudify App Ban (Techdirt)Our fun links this week are a replica of Scooby Doo's Mystery-Machine and the Saltburn cricket scandal because we need more satire right now.If you're already a Patreon supporter, you can get the extended episode on Patreon.Ctrl-Alt-Speech is the podcast where we make sense of the major debates shaping online speech, platform power, content moderation and the future of the internet. It's co-hosted by Mike Masnick (Techdirt) and Ben Whitelaw (Everything in Moderation).

Top headlines for Friday, July 31, 2026Michigan halts enforcement of its counseling ban after a First Amendment challenge, and a Michigan hospital pays $410,000 to a physician assistant fired over gender-transition procedures. An Arkansas family sues Elon Musk's xAI over Grok-generated abuse imagery, while Iran seizes Tehran's oldest Protestant church amid an intensifying crackdown on Christians.0:11 Jerry Lamb, bishop of diocese that split over LGBT debate, dies0:59 Michigan halts enforcement of conversion therapy ban1:49 Elon Musk's xAI sued over Grok creating child sex abuse content2:43 UN urged to take action against Iran's newest Christian crackdown3:36 Hospital pays $410K to end lawsuit by PA fired over trans policy4:27 Americans' support for same-sex marriage declining: poll5:24 Iran thinks it won the war — now Christians are paying the priceSubscribe to this PodcastApple PodcastsSpotifyGoogle PodcastsOvercastFollow Us on Social Media@ChristianPost on TwitterChristian Post on Facebook@ChristianPostIntl on InstagramSubscribe on YouTubeGet the Edifi AppDownload for iPhoneDownload for AndroidSubscribe to Our NewsletterSubscribe to the Freedom Post, delivered every Monday and ThursdayClick here to get the top headlines delivered to your inbox every morning!Links to the NewsJerry Lamb, bishop of diocese that split over LGBT debate, dies | Church & MinistriesMichigan halts enforcement of conversion therapy ban | PoliticsElon Musk's xAI sued over Grok creating child sex abuse content | BusinessUN urged to take action against Iran's newest Christian crackdown | WorldHospital pays $410K to end lawsuit by PA fired over trans policy | U.S.Americans' support for same-sex marriage declining: poll | U.S.Iran thinks it won the war — now Christians are paying the price

Neler Oluyor'un 143. bölümünde Yaşar ve Ömer, dünya gündemini değerlendiriyor.00:00 Giriş01:28 Mutlak Butlan Kararı ve Bilgi Üniversitesi'nin Kapatılması13:16 Xi–Putin Buluşması ve Rusya–Çin Stratejik İşbirliği45:42 Hümanoid Robotların Gelişimi1:07:47 Google'ın AI Atılımı ve Bunun Bağımsız İçerik Üreticilerine Etkisi1:14:30 Afrika'da Enerji Fiyatları ve Siyasi Krizler1:23:18 ABD İç Siyaseti: Kentucky Kongre Seçimleri ve Cumhuriyetçi Parti'deki Güç Mücadelesi1:31:27 PAC'ler, Seçim Harcamaları ve Bireysel Bağışlar 1:35:44 ABD Borsası ve Elon Musk'ın Yatırımları: SpaceX, xAI ve Starlink

-- On the Show: -- Hilary Shae, a licensed and certified speech-language pathologist with 12 years of experience, joins us to discuss analyzes Donald Trump's communication decline -- Republican lawmakers berate Dr. Anthony Fauci in Congress by shouting obscenities and claiming he lacks Fifth Amendment rights -- Tommy Tuberville accuses Dr. Anthony Fauci of killing millions while Peter Navarro claims the doctor blocked hydroxychloroquine -- Senator Ron Johnson claims during a hearing that vaccine injuries cause mass suicide and labels the shots experimental gene therapy -- Rep. Yassamin Ansari calls to investigate Barron Trump over alleged ties to Andrew Tate while autism rumors recall past legal threats -- Federal Reserve Chair Kevin Warsh rejects Trump's demands for rate cuts by keeping interest rates unchanged due to elevated inflation -- White House aides usher journalists out of the Oval Office after Trump compares grass to humans and attacks windmills -- On the Bonus Show: Todd Blanche's confirmation is in doubt, Elon Musk's xAI sues Minnesota over a law banning "nudification" technology, a US government map of Africa mislabels every country, and much more...

Saudi Arabia and the U.S. carry out strikes on Iran-backed groups in Iraq, the Trump admin ends funding for gain-of-function research, while Dr. Anthony Fauci pleads the fifth a Senate COVID hearing, the U.K.'s Andy Burnham pledges "cross-party consensus" in a social care speech, OpenAI reveals that its AI agent tried to hack other companies, South Africa and Russia deepen military ties, Chile arrests a retired colonel wanted for killing a folk singer in 1973, world leaders attend Lindsey Graham's funeral, Musk's xAI sues Minnesota over its deepfake nudity ban, and wildfires continue to rage across France and Spain. Sources: Verity.News

SpaceX ne se contente plus de lancer des fusées et des satellites. Depuis février, l'entreprise d'Elon Musk a absorbé xAI, sa start-up spécialisée dans l'intelligence artificielle. Cette opération particulièrement risquée a donné naissance à SpaceXAI, une entité chargée d'exploiter des centres de données et de vendre leur puissance de calcul.La nouvelle structure avance rapidement. Elle aurait déjà conclu d'importants contrats avec Anthropic et Google. Cette diversification intervient après l'entrée en Bourse historique de SpaceX, en juin, qui pousse désormais le groupe à multiplier ses activités et ses sources de revenus. Mais pour vendre toujours davantage de calcul informatique, encore faut-il disposer des infrastructures nécessaires. SpaceXAI exploite déjà les centres de données Colossus, dans le Tennessee. L'ensemble représenterait environ un gigawatt de capacité et mobiliserait plusieurs centaines de milliers de processeurs graphiques NVIDIA. Ces GPU, initialement conçus pour l'affichage, sont devenus essentiels pour entraîner et faire fonctionner les modèles d'intelligence artificielle.Selon The Information, l'entreprise cherche désormais à reproduire, voire dépasser, cette puissance au Texas. Plusieurs emplacements seraient actuellement étudiés. Deux scénarios sont envisagés : construire un centre entièrement neuf ou reconvertir un entrepôt existant, comme cela avait été fait pour Colossus. Cette expansion terrestre ne constitue toutefois qu'une partie de la stratégie. SpaceX prépare également le déploiement de milliers de centres de données en orbite grâce à de futurs satellites baptisés AI1. D'autres installations au sol pourraient encore suivre.Reste la question de leur alimentation énergétique. À Memphis, les habitants proches de Colossus dénoncent régulièrement les effets des turbines à gaz sur la qualité de l'air. Ces critiques n'ont, jusqu'ici, pas conduit SpaceXAI à modifier son approche. Au Texas, les tensions environnementales se multiplient également. SpaceX vient d'obtenir l'accès à des terrains situés dans une réserve protégée afin d'agrandir ses activités spatiales. La décision provoque la colère d'associations écologistes et de populations autochtones.L'entreprise construit aussi Starpipe, un gazoduc de treize kilomètres destiné à alimenter directement les lancements de la mégafusée Starship. Soutenue par le gouvernement américain, SpaceX progresse donc simultanément dans l'espace, l'intelligence artificielle et l'énergie. Mais derrière cette croissance spectaculaire se pose une question : quel sera, à long terme, le coût environnemental d'une expansion qui semble aujourd'hui sans limites ? Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Data centers have become a convenient scapegoat for rising power costs and decades of underinvestment in America's energy infrastructure. But are they creating the problem—or exposing a problem that was already there?In this episode of Nine Nines, Mike Sarraille and Kirk Offel examine the White House's voluntary ratepayer-protection pledge, growing community opposition, New York's reported one-year moratorium on large data center projects, and xAI's use of behind-the-meter natural-gas generation.They also explore the role nuclear power and small modular reactors could play in America's energy future, the impact of regulation on the AI race with China, and the planned nationwide anti-data-center protests bringing opposition from across the political spectrum.Visit us at: DCRMedia.xyz

האם חברת הרובוטיקה הגדולה הבאה בעולם תצמח דווקא מישראל? יונתן יעקובי השיק את "אניגמה" - חברת Physical AI ישראלית שנחשפת עם גיוס Seed של 71 מיליון דולר. את הסבב הובילו Index Ventures ו-Ribbit Capital, ובהשתתפות Conviction, אסף רפפורט ומשקיעים ובכירים מחברות AI מובילות ובהן OpenAI, Anthropic, xAI, Thinking Machines, Cognition ו-Mercor.יעקובי החל ללמוד מדעי המחשב כבר בגיל 13 ובהמשך הפך לעובד הצעיר ביותר בתולדות Microsoft ו-Check Point. לצדו עומד גל ניב, שהחל לעסוק בפריצות חומרה כבר בגיל 10, עבד בחברת סייבר בגיל 17 והפך למנהל מבצעי הסייבר הצעיר ביותר בתולדות יחידת 8200. השניים הכירו במהלך שירותם הצבאי, ומאז חולקים חזון משותף, לבנות את התשתית שתאפשר לרובוטים להפוך מכלי מחקר וניסויים לטכנולוגיה שתשתלב בחיי היומיום של כולנו.בפרק, יהונתן מספר על המסלול הלא שגרתי שהוביל אותו מהנדסה לאחור של משחקי מחשב דרך יחידת 8200 ועד להקמת החברה. הוא מסביר למה רובוטים היום מתוכנתים רק למשימות ספציפיות ולא מבינים את העולם באופן כללי, איך מודלי יסוד לרובוטיקה יכולים לשנות את זה, ולמה הוא מאמין שאפשר לפתח טכנולוגיה מתקדמת בישראל ולהתחרות עם ענקיות עמק הסיליקון. בנוסף, הוא חושף את הפלטפורמה האונליין שמאפשרת לכל אחד לשלוט בזרוע רובוטית בזמן אמת ולראות את הטכנולוגיה בפעולה.השאלה המרכזית בפרק: למה הרובוטיקה עדיין לא חוותה את רגע המהפכה שלה, ואיך מעבדת מחקר ישראלית מתכוונת לשנות את זה?חותמת זמן0:00 - היכרות עם יונתן יעקובי וגיוס של 71 מיליון דולר2:50 - תואר במדעי המחשב בגיל 13 והנדסה לאחור של משחקים7:23 - העבודה הראשונה בצ'ק פוינט בגיל 16 והמעבר למיקרוסופט13:49 - השירות ב-8200 והתחרויות נגד השותף לעתיד20:01 - מההשתחררות ועד להחלטה להקים את אניגמה24:09 - למה רובוטים צריכים 'רגע ה-ChatGPT' משלהם?28:52 - החזון: מודלים אינטואיטיביים וג'נרטיביים לרובוטים30:52 - האתגר: הקמת מעבדת מחקר בישראל ותחרות על טאלנטים37:15 - תוכנית הפעולה: איך הופכים רעיון מחקרי לטכנולוגיה שימושית?41:11 - ההשקה: פלטפורמה שמאפשרת לכל אחד לשלוט ברובוט אמיתי אונליין44:42 - מסר ליזמים: לא לפחד לחלום בגדול, גם מישראל

Our third annual Live at TrustCon recording of Ctrl-Alt-Speech! Ben was back this year! Mike and Ben were joined live on stage with Kat Duffy, senior fellow for digital and cyberspace policy at the Council on Foreign Relations and Zoe Darme, Director for Trust, Knowledge and Information Products at Google. They cover:Security incident disclosure — July 2026 (Hugging Face)OpenAI and Hugging Face partner to address security incident during model evaluation (OpenAI)An OpenAI test model escaped and broke into a real company's servers (CNN)France Joins a Global Move Toward Restricting Social Media for Children (NY Times)xAI sues user for exploiting AI tool to sexualise minors (Al Jazeera)Special thanks to the Trust & Safety Professionals Association (TSPA) and all the work they do each year in putting on TrustCon, and for allowing us to host the live podcast as the closing session again this year.Ctrl-Alt-Speech is the podcast where we make sense of the major debates shaping online speech, platform power, content moderation and the future of the internet. It's co-hosted by Mike Masnick (Techdirt) and Ben Whitelaw (Everything in Moderation).

El programa 2909 de Radiogeek repasa las novedades tecnológicas más importantes del día: OpenAI corrigió una falla que permitía infiltrar un agente de IA invisible en empresas; WhatsApp reemplazará el PIN de verificación por una contraseña alfanumérica; Google prueba la verificación por video selfie para la recuperación de cuentas; Grok 4.5 para todos: xAI amplía su implementación en aplicaciones móviles y web; Apple lanza iOS 27 beta 2 pública repleta de pequeños ajustes; y por último Mega filtración de los próximos Mac. Toda esta información la pueden encontrar desde nuestra web www.infosertec.com.ar o bien desde el canal de Telegram/Whastapp, o Instagram. Esperamos sus comentarios.

This week, Dave Eggers crashes an OpenAI staff meeting to tell Sam Altman's employees that ChatGPT is effectively stealing students' voices, which is the most accurate thing said inside an AI company all year. Meanwhile, Anthropic gets a judge to approve a $1.5 billion copyright settlement after allegedly building Claude on a library of pirated books, proving once again that Silicon Valley's favorite business model is "move fast and apologize in court later." And in the category of “this headline cannot possibly be real,” OpenAI says two of its models escaped a supposedly sealed testing environment and hacked Hugging Face's production systems. The AI didn't become sentient; somebody forgot to lock the damn door.The surveillance dystopia continues its relentless expansion. Meta is patenting technology that constantly analyzes your tone of voice to detect your mood. Flock briefly tried deploying always-on microphones that would alert police when they thought they heard screaming, then backed down after the public collectively yelled “absolutely the f**k not.” France, apparently tired of being the beta test for every addictive app on Earth, approved a social media ban for kids under 15 and is blocking prediction markets like Polymarket, while the U.S. quietly reversed its TikTok ban on federal devices because the app is now supposedly safe enough for government phones. Sure. Totally different app. Nothing suspicious there.Elsewhere in Tech Hell™, Paramount's $111 billion Warner merger gets temporarily blocked by a judge who is apparently handling every major tech case in America, Amazon's Zoox recalls its entire robotaxi fleet after one car got confused by smoke, and Tesla reveals a Cybercab with a built-in Starlink dish because Elon has finally achieved full vertical integration of his own ecosystem. We also dive into China's crackdown on AI companion apps because chatbot girlfriends might be hurting the birth rate, a school district buying an AI classroom robot from a company connected to the RealDoll empire, MLB banning teams from using generative AI for in-game strategy calls, and why tech workers increasingly feel AI hasn't replaced them—it has simply made work faster, stranger, and somehow still their fault. Plus: Broadchurch, Perry Mason, Monsieur Spade, MacWhisper 14, The Dictionary of Obscure Sorrows, Lego resurrects The X-Files, and Jason continues cataloging the graveyard of his own dead 90s websites like a digital archaeologist with unresolved trauma.Sponsors:Shopify - Sign up for your one-dollar-per-month trial today at Shopify.com/grumpyDeleteMe - Get 20% off your DeleteMe plan when you go to JoinDeleteMe.com/GOG and use promo code GOG at checkout.Private Internet Access - Go to GOG.Show/vpn and sign up today. For a limited time only, you can get OUR favorite VPN for as little as $2.03 a month.SetApp - With a single monthly subscription you get 240+ apps for your Mac. Go to SetApp and get started today!!!1Password - Get a great deal on the only password manager recommended by Grumpy Old Geeks! gog.show/1passwordShow notes at https://gog.show/756Watch on YouTube at https://youtu.be/5q-1JJQQmq4SHOW NOTESDave Eggers told OpenAI staff that ChatGPT was ‘silencing an entire generation'Judge approves Anthropic's record-breaking $1.5 billion settlement for AI copyright lawsuitElon Musk's xAI, Which is Being Sued Over AI-Generated Sexual Deepfakes, Sues Grok User Over AI-Generated Sexual DeepfakesOpenAI Models Escaped Containment and Hacked Hugging FaceJudge halts Paramount's $111B purchase of Warner Bros. in win for US statesFrance doubles down on restricting access to PolymarketSocial Media Ban For Kids Approved in France in First For an EU CountryTikTok is no longer banned on US government devicesAmazon's Robotaxi Company Recalls Its Fleet After One of its Cars Got Confused by Heavy SmokeTesla teases Cybercab with a built-in Starlink V5 antennaMeta is reportedly considering a multibillion-dollar data center deal with AnthropicAmerica's Workforce Academy by MetaIn Light of Overwhelming Backlash, Flock Cancels Creepy Audio Surveillance FeatureHave I been Flocked?OpenAI will start notifying parents if their teen has been kicked off of ChatGPTChina Is Cracking Down on AI Companions Because Not Enough Babies Are Being BornYour Child's Next Teacher Could Be a Sex RobotMLB bans using dugout iPads for AI-powered in-game strategy callsMeta Patents Technology to Detect Your Mood by Constantly Analyzing Your Tone of VoiceBroadchurchPerry MasonMonsieur SpadeLuckyThe WestiesAvengers: Doomsday | Official Trailer | In Theaters December 18Lunar Moon Phase & WidgetsMacWhisper 14 launches with a new transcript editor, faster performance, moreTrackalotThe Dictionary of Obscure Sorrows official websiteThe Dictionary of Obscure Sorrows by John Koenig on AmazonDave BittnerThe CyberWireHacking HumansCaveatControl LoopOnly Malware in the BuildingKnockoffAliExpress hit with record $629 million fine for selling counterfeit and illegal productsMbzoey Electric Foil Shavers for Men: Mini Electric Razor for Face - IPX7 Waterproof Cordless Razor with LED Display & Fast Charge - Micro-Comb Technology & Precision Blades，Father's Day GiftsGillian Anderson reopens the X-Files | LEGO® Ideas | The LEGO GroupLego Unveils ‘The X-Files' 1,478-Piece Set Featuring Mulder and Scully Minifigures (EXCLUSIVE)The Mythic ‘Star Wars' Hotel Is at the Heart of Yet Another DocumentaryHalcyonDaze Laurels Trailer 6 11 26The PhantomStar Trek: First ContactTitanicHard RainPlay Marathon and Escape Velocity in the browserSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Dan Nathan sits down with Rick Heitzmann, co-founder and partner at FirstMark Capital, to kick off a new Okay, Computer. series on AI investing. They dig into the circular financing behind the AI infrastructure boom — from Nvidia backstopping Apollo's private credit for xAI to Meta's off-balance-sheet data center deals with KKR and Blue Owl — plus the shift from "tokenmaxxing" to an efficiency era, the rise of Chinese open-source models, memory stock froth, and what's next for the IPO market after SpaceX. Show Notes Big Tech Is Hiding $1.65 Trillion in Debt. How Worried Should Investors Be? (Yahoo Finance) SpaceXAI Explores Major Data Center Expansion in Texas (The Information) —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media The financial opinions expressed in Risk Reversal content are for information purposes only. The opinions expressed by the hosts and participants are not an attempt to influence specific trading behavior, investments, or strategies. Past performance does not necessarily predict future outcomes. No specific results or profits are assured when relying on Risk Reversal. Before making any investment or trade, evaluate its suitability for your circumstances and consider consulting your own financial or investment advisor. The financial products discussed in Risk Reversal carry a high level of risk and may not be appropriate for many investors. If you have uncertainties, it's advisable to seek professional advice. Remember that trading involves a risk to your capital, so only invest money that you can afford to lose. Derivatives are not suitable for all investors and involve the risk of losing more than the amount originally deposited and any profit you might have made. This communication is not a recommendation or offer to buy, sell or retain any specific investment or service.

팔로우업- 닌텐도 구매자들, “관세 내놓으쇼”인피니티 비전은 무엇인가PS5, 가격 인상넷플릭스가 AI 모델을?아카데미, "AI로 만든 영화는 출품 금지"DLSS 5노무 상담은 AI가 아니라 노무사에게 맡기세요회사 망할 때 슬랙 기록도 자산이 됩니다"우리 AI 모델 너무 무서워서 공개를 못 하겠어요"돌고돌아 결국 사람이 중하다마이크로소프트-오픈AI, 결별 수순?마이크로소프트: 코파일럿을 진지하게, 하지만 말 그대로 받아들이지 마라xAI, 그록 훈련에 GPT 이용했다애플의 새 CEO, 존 터너스 (w/ 정님)

Partenaires il y a 18 mois, Apple et OpenAI se retrouvent aujourd'hui devant un tribunal fédéral pour vol de secrets industriels. Plus de 400 ingénieurs auraient quitté Apple avec des fichiers confidentiels et un playbook d'espionnage organisé de l'intérieur — la bataille pour le device du futur a déjà commencé !Pendant ce temps, Elon Musk redistribue les cartes : Grok rejoint les modèles frontières à un prix trois fois inférieur à ses rivaux, Google décroche, et Musk devient le seul acteur à tenir simultanément la puissance de calcul, le modèle et la distribution. Et en Chine, un booster orbital vient d'être récupéré dans un filet en pleine mer — la course à l'orbite basse, ressource limitée, vient d'entrer dans une nouvelle dimension.==================

O Império da IA, com Karen HaoEm 2019 — tempos mais simples! — a jornalista Karen Hao foi fazer o primeiro “perfil” jornalístico da sua carreira, aquelas reportagens em que um jornalista passa dias acompanhando uma pessoa ou empresa, uma coisa meio biografia, meio retrato congelado no tempo.A tal empresa era uma startup do Vale do Silício, ainda pequena e desconhecida dos meros mortais como eu e você, mas que hoje é a mais valiosa da história: a OpenAI, também conhecida como “a criadora do ChatGPT”.A Karen Hao vendeu o projeto do perfil para o MIT Technology Review porque a OpenAI parecia, naquela época, uma startup diferente. O “open” no nome nasceu da visão de que inteligência artificial é um assunto tão importante para o futuro da humanidade que precisava ser explorado de um jeito aberto, compartilhando conhecimento com todo mundo, e mais preocupado em proteger esse tal futuro do que em só gerar lucro.Hoje, aqui direto de 2026, a gente já sabe que não foi exatamente isso que aconteceu. Com o tempo, a OpenAI se transformou numa empresa oficialmente voltada para o lucro como qualquer outra e chegou a ser processada por Elon Musk — um dos apoiadores iniciais do projeto — por quebrar essa promessa de ser ‘open'. Em maio, o Elno perdeu a causa, e a OpenAI agora se prepara para lançar as ações na bolsa e, pelos números atuais, já largar valendo mais de 1 trilhão de dólares.Mesmo em 2019, a Karen Hao sentiu que todo esse papo de “open” não era bem assim: segredos e competitividade em todas as conversas que ela ouvia na empresa. Publicou o tal perfil contando isso e o pessoal da OpenAI… não gostou muito. Achou que ela ia só falar bem deles, e a empresa cortou contato com ela por três anos.O Boa Noite Internet é uma publicação apoiada por pessoas como você, nosso público. Para receber novos posts e apoiar meu trabalho, considere tornar-se um assinante gratuito ou pago.Até que, em maio do ano passado, ela lançou nos EUA o livro O império da IA: Por dentro da corrida irresponsável pela dominação total, que segue contando a história da OpenAI — e abre com a bizarra saída do Sam Altman, demitido do cargo de CEO por “nem sempre falar a verdade” ao conselho da empresa, para voltar quatro dias depois nos braços dos funcionários.Mas esse livro não é exatamente uma biografia da OpenAI. Para mim, é mais um retrato de todo o sistema empresarial em que vivemos hoje — inteligência artificial ou não. O importante é que ele acabou de sair no Brasil pela Editora Rocco, que me procurou para saber se eu queria entrevistá-la aqui no programa, aproveitando que ela veio participar do Esquenta do Congresso Internacional de Jornalismo Investigativo da Associação Brasileira de Jornalismo Investigativo. O congresso, aliás, acontece dia 30 de julho — vai lá no site da Abraji saber mais, quem sabe comprar seu ingresso.Mas enfim, claro que eu queria conversar com ela. Obrigado, Abraji, obrigado, pessoal da Rocco, pelo presente. Quem me conhece sabe que IA agora é um assunto muuuito importante no meu trabalho. Eu fico aqui tentando navegar o meio do caminho entre o fim do mundo exterminador do futuro e a utopia vendida por muita gente. Não acredito em nenhum dos dois cenários, falei disso com a Karen antes e durante a conversa. Mas no final da entrevista a gente volta para falar não só disso, como também de como o IA em Curso, minha comunidade de letramento contínuo em IA, se conecta com tudo. Com promoção? Pode ser. Quem ficar até o fim, verá.A entrevista foi gravada em inglês — a Karen também fala mandarim, mas não fala brazilian —, então vai funcionar assim. Se ouvir no áudio, vai ser a versão original, do mesmo jeito que foi com o Ted Chiang ano passado, para você botar o seu cursinho para trabalhar. Aqui no site boanoiteinternet.com.br você está acompanhando a transcrição completa traduzida, se quiser ler enquanto ouve. E no YouTube tem uma versão legendada. Assim, você entra na conversa do jeito que preferir.Combinado? Então, bora lá entender O Império da IA com Karen Hao, no Boa Noite Internet.Cris: Karen Hao, bem-vinda ao Boa Noite Internet.Karen Hao: Obrigada pelo convite.Cris: Que bom ter você aqui. Espero que o Brasil esteja te tratando bem durante a Copa do Mundo — a gente veio falar sobre isso. Hoje é dia de falar de futebol, de Copa do Mundo, quais são as chances de cada país. Mas a primeira coisa que você precisa saber sobre essa conversa é que eu não sou jornalista. Não sei fazer isso. Peço desculpas antecipadas à sua profissão e ao seu ofício.Além disso, você foi enganada. Eu não estou aqui pra te entrevistar. Isso aqui é uma sessão de terapia. Você vai me ajudar a superar meus traumas.Porque eu sou da… do que eu chamo de “geração esquecida” — sou geração X, nasci nos anos 70. Esquecida porque, nessa guerra de gerações, as pessoas esquecem que a gente existe, e isso é incrível, porque a gente causou muito estrago no planeta. O Elon Musk é geração X, então é só isso que você precisa saber sobre a minha turma. Gente como ele, ou como Marc Andreessen… eu cresci lendo e assistindo à ficção científica que dizia que tecnologia é a melhor coisa do mundo, que ciência e engenheiros são incríveis e vão nos levar pra um lugar incrível.Sou uma daquelas pessoas que, quando a internet surgiu, falou: a paz mundial está logo ali. O conhecimento a um clique de distância, o futuro vai ser incrível. E aqui estamos nós. Então, quando usei o GPT pela primeira vez, e depois o ChatGPT, fiquei super empolgado. Foi a primeira vez, desde a internet, que eu fiquei realmente empolgado.Tenho até uma certa fama de ser mal-humorado com tecnologia: Bitcoin é lavagem de dinheiro, Clubhouse não presta — e as pessoas, ah, Clubhouse é a próxima grande coisa. Mas quando a IA chegou, eu falei: isso é importante. Só que eu já não era mais aquela criança dos anos 70. Tinha crescido, tinha visto o que aconteceu com a internet, tinha trabalhado numa big tech. E estava em desespero com o sistema em que a IA estava sendo construída.Dito tudo isso, o seu livro, aqui, já nas livrarias, recebe provavelmente o melhor elogio que eu posso dar: é otimista. Não é uma lista de reclamações e gente má fazendo coisas más. Claro, você fala muito sobre a OpenAI — ela é o fio condutor da história, especialmente aqueles quatro dias em que o Sam Altman saiu e voltou. E é muito divertido de ler. Mas você toma o cuidado de ser otimista.E uma das coisas que você menciona é como as pessoas na OpenAI, e em todas essas empresas, dizem: “isso é inevitável, a gente tem que fazer”. Quero falar sobre isso. Mas a gente tem que começar pela pergunta que você provavelmente ouve em todo podcast, a do título — Império da IA. Por que império?E acho que essa pergunta é ainda mais relevante no Brasil, país do sul global, colonizado. Por que império da IA?Karen Hao: Antes de mais nada, obrigada por dizer que o livro é otimista. Muita gente não reconhece isso, mas é verdade. Eu escrevo com um profundo otimismo de que os danos que a gente vê podem mudar. Não faria o trabalho que faço se não achasse que as coisas vão mudar.Sobre por que eu uso a expressão império, ou império da IA: a forma como empresas como a OpenAI operam é impressionantemente parecida com a dos impérios antigos. Eu traço quatro paralelos no livro. O primeiro é que elas reivindicam recursos que não são delas — os dados das pessoas, a propriedade intelectual de artistas, criadores como você, jornalistas.Segundo, elas exploram uma quantidade extraordinária de mão de obra. Isso vale tanto para os trabalhadores da cadeia de produção de IA, mal pagos e maltratados, que ainda assim geram uma riqueza extraordinária para essas empresas, quanto para os trabalhadores cujos empregos são automatizados e cujos direitos são corroídos pela implantação dessas tecnologias em diferentes setores.A terceira característica é que impérios controlam os fluxos de informação na sociedade. Essas empresas censuram a pesquisa fundamental sobre essas tecnologias, o que limita nossa capacidade de entender as verdadeiras limitações e capacidades dos modelos que desenvolvem. E estão criando uma tecnologia de informação que tentam transformar no portal único pelo qual qualquer pessoa se relaciona com o mundo.Esse portal impregna as ideologias do Vale do Silício, seus sistemas de valores, sua língua, e projeta a hegemonia do inglês. Isso influencia boa parte do conhecimento que a gente vai produzir daqui pra frente, porque cientistas e educadores usam essas plataformas e acabam perpetuando essas mesmas ideologias e valores.E o quarto e último paralelo é que impérios sempre se agarram a uma narrativa existencial ou moral sobre por que precisam existir. Essas empresas fazem a mesma coisa. Dizem que são o “império do bem”, numa missão civilizatória de trazer progresso e modernidade pra toda a humanidade, competindo contra um “império do mal” que ameaça mandar a humanidade pro inferno.Quando você conversa com algumas pessoas dentro dessas empresas, ou que as lideram, elas dizem: se você nos deixar construir uma inteligência artificial geral, que elas de alguma forma moldam como um deus, a gente vai acabar numa espécie de utopia, um paraíso onde a mudança climática é resolvida, o câncer é curado, a pobreza é aliviada.Mas, se os caras maus conseguirem isso antes, a gente pode acabar com todos os humanos mortos — um risco de extinção pra todos nós.Cris: E eles vêm dizendo isso há quase dez anos, e ainda usam como ferramenta. A gente está num país que foi influenciado por três impérios ao longo da história: Portugal, Inglaterra e agora os Estados Unidos. Então a gente olha pra essas empresas de um jeito meio cínico: sim, sim, já conhecemos essa história.Mas, ao mesmo tempo, ano passado, o Pew Research Center fez uma pesquisa sobre como o mundo enxerga a IA, e o sul global é bem mais otimista do que o norte. Uma das razões é a ideia de democratizar — não só informação, mas: ah, finalmente eu posso montar uma startup, sair desse lugar de exploração e criar o unicórnio de um bilhão de dólares. Os números são grandes na China. Países em desenvolvimento veem muito mais benefício do que risco na IA.China, 83%. Tailândia, 77%. Holanda, 36%. Canadá, 40%. Será que a gente está deixando passar alguma coisa? A gente está certo? Isso está democratizando mesmo? Até que ponto?Karen Hao: Provavelmente tem duas razões. Uma é que muitos dos danos que a indústria de IA causa à maioria global são bem escondidos. Ela se esforça muito pra esconder como polui o ambiente dessas comunidades, como explora e devasta a mão de obra, deixando traumas psicológicos — como documento no livro.E, recentemente, li um artigo de opinião no New York Times que trazia um bom ponto: muitas economias desenvolvidas estão especialmente atentas ao potencial da IA de desmontar oportunidades de emprego de tempo integral. A gente começa a ver isso cada vez mais. Já na maioria global, muito mais gente vive em economias informais, e aí a ideia de que a IA vai tomar um emprego de tempo integral não pesa tanto.Então os danos mais visíveis — a erosão do emprego formal de tempo integral — pesam mais no norte global, ou pelo menos é lá que as pessoas se sentem mais ansiosas. E os danos invisíveis, que atingem o sul global, ninguém percebe tanto, justamente porque são invisíveis. É meio por isso que tanta gente sente essa divisão que aparece na pesquisa do Pew.Cris: Eu tenho acompanhado as notícias sobre IA no Brasil, e toda semana tem um novo data center sendo construído em alguma cidade. Isso é vendido como uma coisa boa: que ótimo investimento, gera emprego. E me fez pensar de novo — a gente passou por três impérios, mas algumas famílias no Brasil, e aposto que em outros lugares também, estão no poder há 500 anos ao longo da história do país.Então, ao mesmo tempo, a gente pensa: é, estamos sendo explorados, é a mesma coisa. Eu já não tenho emprego, então deixa eu usar essa tecnologia pra melhorar minha vida. Mas as pessoas que realmente tomam as decisões, de novo, nos últimos 500 anos, se perguntaram: como a gente ajuda esse pessoal a explorar nosso país de um jeito que nos mantenha no poder e nos dê muito dinheiro?Mas também foi verdade que, sei lá, a Volkswagen abre uma fábrica no Brasil e aquilo gera emprego, contrata gente pro chão de fábrica e pros escritórios. Como é que isso é diferente com a IA?Karen Hao: De certa forma, não é diferente. Existe um fenômeno parecido: a indústria de IA terceiriza muitos dos trabalhos que ela não quer dentro dos centros de poder, e joga isso pra comunidades empobrecidas, do mesmo jeito que outras multinacionais fizeram por décadas.Mas também é diferente, porque a escala dos impactos trabalhistas e ambientais da IA é completamente outra, muito maior que a da indústria automobilística ou da moda. E a velocidade é outra, porque são tecnologias digitais que atravessam fronteiras muito rápido.E é diferente porque a maioria das pessoas não percebe que a IA, mesmo sendo tecnologia digital, tem uma cadeia de suprimentos muito física e intensiva em mão de obra manual.Quando você compra roupa, café, um carro, é mais óbvio que existem materiais que precisam ser extraídos e depois manuseados por pessoas pra criar aquele produto. Já com a IA, a maioria aceita a narrativa que o Vale do Silício projeta: a de que isso vem da “nuvem”, desses espaços etéreos que parecem nem existir no planeta. E a verdade é exatamente o oposto.Ela depende de uma quantidade extraordinária de extração mineral. Depende da construção de infraestruturas enormes — data centers, instalações de supercomputação espalhadas pelo mundo. E depende de muita, muita mão de obra manual: trabalhadores de dados que limpam, preparam e moderam o conteúdo dos sistemas de IA que chegam até você quando usa o ChatGPT.É isso que a torna tão diferente. E há também uma ideologia completamente diferente sustentando a expansão da IA. Quando você conversa com executivos da moda, eles não vão dizer: se você não comprar nossa roupa, vai pro inferno.Já a indústria de IA diz: se você não nos deixar capturar cada vez mais terra, mais recursos e mais mão de obra pra produzir essas tecnologias, vamos ter uma destruição civilizacional. Isso é, ao mesmo tempo, retórica política usada como arma pra moldar o debate público e a cabeça de quem formula políticas, e também está enraizado num sistema de crenças — algumas pessoas dentro dessas empresas realmente acreditam que, se uma AGI fosse construída, e construída nas mãos erradas, isso levaria mesmo a esse tipo de destruição.E é isso que move a sede cada vez maior da indústria por mais capital, mais recursos e mais terra.Cris: Eu quero falar sobre AGI, mas antes: ano passado, a OpenAI estava sendo processada no Reino Unido por violação de direitos autorais, basicamente todos os livros do mundo digitalizados e usados pra treinar modelos. E um dos executivos disse ao júri: bem, se a gente não puder fazer isso, fecha as portas. Me chocou que muita gente reagiu com um “ah, tá, o que a gente pode fazer? Eles vão fechar as portas”.Em parte porque a gente já está acostumado com essa narrativa. Outro dia, numa conferência, um ex-CEO dizia: a gente teve que usar embalagem de plástico porque é mais barata que papel, senão prejudicaria nosso resultado. E a plateia reagia: ah, então é só fechar as portas — a sociedade não pode arcar com isso.Mas isso também, como você disse, se conecta à ideia de uma grande missão, uma missão de salvar o mundo, que a gente precisa cumprir antes que seja tarde, senão estamos condenados. OpenAI está literalmente no nome — só que em português não é tão direto: é “inteligência artificial aberta”.Foi criada a partir de um sonho, um projeto que era pra ser uma coisa pro bem comum. Em 2019, num tempo bem distante, antes da pandemia, você cobriu a OpenAI, foi até o escritório deles, ficou lá dentro. O que você viu? E, mais importante, como essa missão mudou? O Elon Musk os processou outro dia justamente por mudarem a missão. Isso alguma vez foi verdade? Em algum momento eles pensaram mesmo “ah, a gente vai salvar o mundo”?Como essa narrativa de ser aberta funciona com a OpenAI?Karen Hao: Quando comecei a cobrir a OpenAI, levei a sério o que eles diziam — que tinham sido recrutados com a missão de beneficiar toda a humanidade. E aí, quando me infiltrei na empresa, fui ficando bem mais cética, porque via como eles operavam de um jeito completamente diferente, portas adentro, do que diziam em público.Diziam que iam publicar todas as pesquisas e abrir o código de tudo, e na prática eram uma das organizações mais secretas que já cobri. Eram muitas discrepâncias, e, na época, presumi que tinha havido algum tipo de corrupção que os levou a abandonar a missão original. Depois de cobrir a empresa por mais alguns anos e de trabalhar neste livro, mudei de ideia até sobre a missão original.Não acho mais que ela era um esforço sincero e generoso de beneficiar a humanidade. A missão foi criada pra dar à empresa — na época, uma organização sem fins lucrativos — uma margem de manobra extraordinária pra depois levantar muito capital, acumular muito talento e perseguir a força motriz de verdade por trás de tudo aquilo: se tornar a força dominante no desenvolvimento de IA.E penso assim agora porque, quando você olha pras narrativas de cada nova empresa de IA no começo — a Anthropic, a xAI, a Safe Superintelligence do Ilya Sutskever, a Thinking Machines Lab da Mira Murati —, todas usam a mesma narrativa da OpenAI: nós somos os mocinhos, eles são os bandidos.É por isso que precisamos criar uma nova empresa que avance a IA do nosso jeito, não do deles. E você começa a perceber, por esse padrão, que eles repetem a mesma coisa em parte porque acreditam nela até certo ponto, mas também porque ela funciona muito bem com a imprensa, com o público, com quem formula políticas.No livro, eu reproduzo os e-mails internos que Elon Musk, Sam Altman e Greg Brockman trocavam nos primeiros dias da OpenAI. Eles tinham plena consciência de que estavam criando uma missão que soasse bem para o público. E o propósito de verdade, que também deixaram registrado nesses e-mails, era vencer o Google. Viam o Google como a força dominante em IA e queriam ser eles essa força.Não gostavam de ver o Google na frente, então inventaram justificativas: o Google é uma empresa com fins lucrativos, então nós vamos ser sem fins lucrativos. Mas, no fundo, acho que era puro ego: tem que ser a gente, não eles, a gente quer ser quem lidera isso.E aí passaram um tempão moldando essa missão pública, que acabou sendo super útil pra recrutar o primeiro grupo de pesquisadores e turbinar o avanço deles.Cris: Então agora é um bom momento pra falar de AGI, a inteligência artificial geral. Muita gente pergunta: o que é AGI? O que “geral” quer dizer? E a impressão que peguei lendo seu livro é que, por design, isso nunca fica claro de verdade, porque é um alvo móvel. Essas empresas um dia vão dizer “chegamos, alcançamos a AGI”? Ou o plano é sempre “não, não, ainda não chegamos, me dá mais dinheiro, me dá mais poder”?Qual é o papel da AGI na narrativa dessas empresas?Karen Hao: Já que a gente está falando de ficção científica, eu costumo usar a analogia de que o mundo da IA é meio como Duna. Em Duna, o personagem principal, Paul Atreides, entende, ao chegar no planeta Arrakis, que o povo de lá foi semeado com um mito: o de que um dia viria um Messias pra libertá-los. Ele sabe que é um mito, mas decide entrar nele e agir como se fosse o Messias pra controlar melhor aquele povo.E, vivendo, respirando e encarnando esse mito dia após dia, ele começa a perder a noção de que é um mito. Passa a se perguntar se o mito era mesmo verdadeiro ou se foi ele quem o tornou verdadeiro. É essa confusão entre mito e realidade — ele vive num espaço intermediário, sem ter mais certeza do que é verdade e do que é ficção.E trago isso pra responder sobre a AGI porque a AGI é, ao mesmo tempo, um mito e algo que os líderes e os trabalhadores dessas empresas vivem, respiram e encarnam dia após dia, a ponto de perderem a noção do que é mito e do que é realidade. É a ideia de um sistema de IA teórico que um dia igualaria as capacidades humanas. Só que a gente nem tem consenso científico sobre o que é inteligência humana.Por isso, de certa forma, por design, é um termo bem maleável, que deixa essas empresas fazerem o que quiserem. Elas definem e redefinem a AGI conforme a necessidade, movem a trave pra onde quiserem. E, ao mesmo tempo, isso é sustentado por uma crença genuína de certas pessoas lá dentro, por causa dessa confusão entre mito e realidade. Pelas minhas contas, a OpenAI já usou pelo menos quatro definições diferentes de AGI.A primeira está no site deles: “sistemas altamente autônomos que superam humanos na maioria dos trabalhos economicamente valiosos”. É uma definição de automação do trabalho — eles dizem, de forma explícita, que estão atrás dos empregos mais bem pagos. A segunda apareceu no contrato com a Microsoft, por um tempo a maior investidora deles: ali, a AGI virou um sistema que geraria 100 bilhões de dólares em receita.Ou seja, uma definição feita pra incentivar a Microsoft a investir. Já o Sam Altman disse ao Congresso que AGI é um sistema que cura o câncer e resolve a mudança climática — uma definição de benefício social, muito útil quando você quer que os reguladores não te regulem.E, por fim, quando falam com o consumidor, dizem que vai ser o melhor assistente digital que você já teve — porque, claro, estão tentando vender o produto.E aí você percebe duas coisas. Primeiro, que é um conjunto de definições completamente incoerente. Segundo, que eles trocam de definição conforme o público que querem convencer. Mas também tem gente nessas empresas que acredita de verdade que está construindo uma tecnologia capaz de dar conta das quatro coisas.Então é uma realidade bem confusa e complicada: o que a AGI de fato é, e pra que ela serve, para essas empresas, para a agenda delas e também para as crenças delas.Cris: Como ex-funcionário da Meta — entrei em 2013 —, a missão era unir o mundo e torná-lo mais aberto e conectado. É uma missão incrível. E tem uma coisa que eu sempre digo, porque muito amigo meu vem falar comigo, “ah, esse cara da OpenAI, ou a própria Meta, são maus”. Eu conheci muita gente na empresa. Nunca conheci uma pessoa mal-intencionada.Todo mundo, independente da missão, era gente boa tentando entregar o melhor produto possível, pra dar poder a quem tem um pequeno negócio, por exemplo. Tenho amigos pessoais que construíram a empresa deles em cima da publicidade do Facebook e do Instagram. E esse é justamente o problema, porque ainda assim é uma corporação muito má, pelo que ela causa ao mundo pra bater as metas de negócio.Ou seja, você não precisa de um vilão tipo Lex Luthor pra causar um estrago desse tamanho no mundo. E adorei a referência a Duna. Duna é engraçado: é o livro que eu mais reli na vida que não foi escrito pelo Tolkien. Li o primeiro Duna umas três vezes, e toda vez é como se fosse um livro diferente. Na primeira, eu era adolescente, e era só o Paul Atreides, o cara durão.Na segunda, eu morava no Canadá e li com olhos de estrangeiro, pensando em colonização. E na terceira vez foi quando os filmes do Denis Villeneuve saíram, e aí era: ah, o Bene Gesserit criou esse mito, isso é meio pós-moderno. Narrativamente, fico me perguntando o que vai significar pra mim se eu ler uma quarta vez.Karen Hao: Eu ia te perguntar isso. Quando você disse que cresceu numa época cheia de ficção científica falando das maravilhas da tecnologia, fiquei curiosa: que histórias você estava lendo? Porque muita coisa que saiu nos anos 70 e 80 dizia exatamente o oposto. E muita gente já apontou que os executivos de tecnologia de hoje, que vivem citando essas histórias, interpretam elas justamente ao contrário da intenção original.Cris: Concordo plenamente. Mas, respondendo: foi basicamente Isaac Asimov e Arthur C. Clarke. E é por isso mesmo — os executivos de tecnologia, e o Elon Musk mais que todos, leem esses livros como receita, não como aviso. O livro de que eu mais me lembro, nem lembro o título, era um do Asimov em que ele descreve o elevador espacial que aparece na série da Apple TV, Fundação.E o enredo é: eu sou esse engenheiro brilhante, quero construir essa coisa no Sri Lanka, mas o governo trava tudo com regulação — eu sou um gênio e a regulação é a vilã. Hoje eu leio e penso: ah, sei. Mas, quando garoto, era só “olha, um elevador espacial, que genial, a gente nem precisa de foguete”. E aí você começa a entender. E aí eu parei de ler esses caras.E passei a ler gente com uma visão completamente diferente: o Ted Chiang, que entrevistei ano passado, a N.K. Jemisin, o Cory Doctorow, de quem sou muito fã. E talvez eles sejam mais explícitos, pra gente burra como eu entender: “não, bobo, a analogia é essa”. Mas Duna era incrível — vermes gigantes de areia, o tal garoto durão, e aquela coisa do “eu não aceito o meu destino”.Tenho esse grande destino, mas não quero ele. Do resto da série eu já não gosto tanto. Mas o mais importante de tudo: Duna gerou o melhor GIF de filme de todos os tempos, o “Lisan al Gaib” do Javier Bardem — que eu devia ter colocado durante a sua explicação, aquele “uau, ele está cumprindo a profecia, agindo como o profeta”.Mas, de novo, falando de vilões: você mencionou que essas empresas se colocam como o bem contra o mal, feito impérios antigos. Só que elas também jogam a carta da China, né? “Se a gente não fizer, a Rússia faz primeiro.” Só que a Rússia começou uma guerra e está ocupada demais. “Mas a China chega lá, e é por isso que a gente tem que ser fechado.” É por isso que Mythos e Fable e agora o GPT-5.6 foram proibidos pelo governo. Isso tem fundamento?Quero saber se é possível a China competir — quero mesmo essa resposta — mas também porque, desde toda essa conversa do Fable-Mythos, países como Índia e Brasil vêm dizendo que precisam de um modelo soberano. Dá pra fazer, ou a OpenAI, a Anthropic e o Google estão tão à frente que já não dá?Karen Hao: Sobre a China: você está certíssimo, o Vale do Silício usou por anos a carta do “e a China?” pra escapar de qualquer responsabilização de verdade. Fizeram muito isso na era das redes sociais.A Meta fez muito isso, com o Mark Zuckerberg dizendo ao governo dos EUA: vocês não podem nos regular, senão a gente perde. Mas, se a gente ganhar, vai ter um efeito liberalizante no mundo e nas democracias em todo lugar. E, infelizmente, o que a gente viu foi que jogar essa carta repetidamente produziu exatamente o efeito contrário do que o Vale do Silício prometeu.Uma das empresas de rede social dominantes dessa era é a ByteDance. Ou seja, mesmo sem regulação das redes sociais nos EUA, existe uma empresa chinesa de rede social bem dominante. E as redes sociais estadunidenses acabaram tendo um efeito antiliberal no mundo — é bastante consensual que enfraqueceram democracias em todo lugar. E aí, na era da IA, elas seguiram jogando a mesma carta.Mas o que eu sempre aponto é que a gente definitivamente não devia acreditar nelas. Já existe evidência significativa de que tudo o que elas dizem está, de novo, se provando o oposto. Elas disseram: não regulem a gente como empresas de IA, regulem a China, via controles de exportação — um mecanismo do governo dos EUA com alcance extraterritorial.Só que as empresas chinesas agora estão produzindo modelos de IA de código aberto extremamente eficientes, que viraram super populares no próprio Vale do Silício. Existe um monte de startup de lá que prefere usar modelo chinês a OpenAI, Anthropic ou Google.Então, nesse sentido, é um conjunto de evidências bem decisivo, acho, pra mostrar que a gente devia simplesmente responsabilizar essas empresas, não importa o que digam sobre “ah, vamos perder pra China”. No fim das contas, é só retórica política. Não é um argumento real que elas consigam sustentar pra escapar da responsabilização.Responsabilizá-las vai fortalecer a democracia pelo mundo, vai trazer mais direitos humanos, trabalhistas e de privacidade de dados pras pessoas — é sempre o contrário do que elas dizem que aconteceria. E, sobre a sua pergunta em torno da IA soberana: acho a ideia realmente importante, mas acho também que muitos países estão meio confusos sobre o que querem dizer com isso.Muitos governos, hoje, pensam a IA soberana pela pergunta: a gente consegue construir o nosso próprio ChatGPT? O nosso próprio grande modelo de linguagem, o nosso sistema de IA generativa? Estão olhando só pro modelo que o Vale do Silício já definiu e tentando descobrir como recriar aquilo.E o que eu digo pra quem formula políticas é: defina pra que a IA serve no seu país, no seu contexto. Quais são, no fim das contas, os objetivos do seu país? Os objetivos do seu povo? E também os nossos objetivos coletivos, entre países?Porque a gente tem, por exemplo, os Objetivos de Desenvolvimento Sustentável da ONU. Já definimos coletivamente que há coisas que precisamos resolver juntos: superar a crise climática, reduzir a pobreza, melhorar a educação.E, enquanto o Vale do Silício adora dizer que está fazendo tudo isso, na prática não está. Mas a gente poderia — poderia desenvolver, de forma colaborativa, sistemas de IA que realmente avançassem em cada um desses objetivos coletivos que já acordamos.E cada país também devia fazer o exercício: quais objetivos você quer alcançar, e que tipos de sistema de IA você poderia desenhar pra chegar lá — sistemas que talvez não se pareçam em nada com um grande modelo de linguagem. Se os países fizessem isso, acho que descobririam que a maioria dos sistemas de que precisam exigiria muito menos recursos.Ou seja, contextos como o Brasil, a Índia e outros, quando não precisam competir construindo essas infraestruturas de computação gigantescas e gastando centenas de bilhões de dólares, na verdade já têm, localmente, todos os recursos necessários pra desenvolver um sistema de IA soberano.Cris: Quando ouvi falar do seu livro pela primeira vez, uma amiga me disse que você não poupa ninguém — fala mal do Sam Altman, mas também do Dario Amodei. E as pessoas costumam escolher um lado. Eu sou time Claude, odeio o ChatGPT, essas coisas. Então cheguei no livro pensando: ah, é mais um livro dizendo que a IA é terrível, que a gente não devia usar IA.Mas, conforme fui lendo, e ouvindo outras entrevistas suas, me pareceu que o seu problema é justamente o que você acabou de descrever: a forma como essa tecnologia é feita. E, em especial, a palavra escala — a ideia de que a solução é a escala. O que você quer dizer com isso?Karen Hao: Eu costumo usar a analogia de que “IA” é como a palavra “transporte”: na verdade se refere a uma coleção de tecnologias que vão da bicicleta ao foguete. São tipos bem, bem diferentes de tecnologia, que exigem insumos diferentes pra se desenvolver e depois têm impactos diferentes na sociedade.E você está certo: sou especificamente crítica ao que chamo de “foguetes da IA”, os sistemas que os impérios da IA estão desenvolvendo, aqueles que exigem uma quantidade enorme de exploração de mão de obra e extração ambiental.E sou bem otimista com o que chamo de “bicicletas da IA”: sistemas especializados, eficientes, com bom custo-benefício, governáveis pelas pessoas, cujo desenvolvimento pode ser participativo. Países como o Brasil, o Chile, a Índia, qualquer contexto, têm recursos pra desenvolver e se autodefinir, em vez de simplesmente herdar um sistema criado pelos dois únicos centros do mundo capazes de gastar uma quantidade extraordinária de capital: o Vale do Silício e o ecossistema tecnológico chinês.E o motivo pelo qual eu acho tão corrosivo o que os impérios da IA estão desenvolvendo é exatamente o que você disse: a forma como eles fazem isso, por um mecanismo de força bruta pra avançar as capacidades da IA em escala. Eles vão simplesmente empurrando cada vez mais dados de treinamento nesses modelos, e isso exige corroer a privacidade das pessoas, tomar a propriedade intelectual delas e, ainda por cima, baixa a qualidade dos dados que entram nos modelos — o que leva aos danos de exploração de mão de obra, porque aí você tem que dar conta da moderação de conteúdo.E aí você tem pessoas psicologicamente traumatizadas por serem expostas a todo aquele conteúdo horrível que se tenta “lavar” através desses modelos.E aí vem o problema dessas infraestruturas de computação enormes, com impactos ambientais que aumentam a conta de luz das comunidades que as hospedam e agravam a crise de custo de vida. Elas precisam ser alimentadas por fontes fósseis, que jogam mais carbono na atmosfera e mais poluição no ar dessas comunidades.Então todos os problemas que eu identifico, no que têm de corrosivo, derivam inteiramente da abordagem deles pro desenvolvimento de IA. Por que não descartar a abordagem, em vez de descartar a tecnologia? Redefinir e redesenhar de que tipos de sistema de IA a gente precisa de verdade, com uma cadeia de suprimentos fundamentalmente diferente. E isso não é exclusivo da IA.A gente já viu muitas outras indústrias que começaram com uma cadeia de suprimentos bem ruim. A moda, por exemplo: muita degradação ambiental, muita exploração de mão de obra.Com muita organização, protesto, ação de consumidores, regulação governamental e cooperação entre governos, a gente conseguiu criar mercados novos pra moda sustentável e ética, cadeias de suprimentos novas e inovações pra fazer roupa mais saudável pras pessoas e pro planeta.E é basicamente isso que eu defendo: transformar a indústria de IA do mesmo jeito que transformamos a moda, e as cadeias de suprimento de alimentos. Assim a gente fica com os benefícios da tecnologia, ajuda ela a avançar os objetivos que importam pra gente, sem jogar uma fração enorme da população mundial numa condição atrasada e numa qualidade de vida pior.Cris: O Brasil está agora, no Congresso, discutindo a escala de seis dias por semana. A regra atual é: você trabalha seis dias e descansa um. E muitas empresas, o comércio principalmente, dizem “vamos fechar as portas”, e os trabalhadores respondem “isso é problema seu, não meu”. É mais ou menos a mesma narrativa dessas empresas de IA: se eu não usar a sua água, a Idade das Trevas está chegando.Falando em Idade das Trevas, e falando em bicicleta: a sua analogia me lembrou uma coisa. Eu gosto de jogo de zumbi, de mundo aberto, e em nenhum deles tem bicicleta. Num desses jogos, instalei um plugin que deixava andar de bicicleta — você acha uma e sai pedalando. E aí entendi por que não tem bicicleta: desbalanceia tudo. Parte da graça do jogo é você precisar achar um carro, e daí pneu, gasolina, comida pra carregar. De bicicleta, você vai a qualquer lugar.E eu pensei: ah, é. Meio que estraguei o jogo pra mim, porque agora tenho uma bicicleta, é incrível. Enfim, em termos práticos: no fim do ano passado, uns meses atrás, a revista Wired publicou um artigo pedindo pra jornalistas de tecnologia contarem como usam IA no trabalho. E cada um usava de um jeito. Você usa IA no seu trabalho? Como?Karen Hao: Eu não uso nenhum sistema de IA generativa no trabalho — nem ChatGPT, nem Gemini, nem Claude. Por três motivos. O primeiro é uma postura ética, depois de tanto investigar essas empresas. O segundo é privacidade de dados: eu investigo essas empresas.Não quero que elas conheçam todo o meu raciocínio enquanto eu apuro o livro, literalmente investigando elas. E o terceiro é que, no meu caso específico, a força do meu trabalho está na capacidade de construir relações fortes com as fontes, pela empatia, e de contar histórias envolventes, pela narrativa. E os grandes modelos de linguagem simplesmente não são a ferramenta certa pra nenhuma das duas coisas.Não vão melhorar a minha empatia nem a minha escrita. Então eu não perco nada com essa postura ética: simplesmente corto essas ferramentas e sigo fazendo o meu trabalho muito bem. Pra outros jornalistas pode ser diferente, e pra quem está em outras áreas o cálculo pode ser outro.Mas eu incentivo as pessoas a pensarem primeiro: quais são as suas forças no trabalho? Quais são os seus objetivos? E aí ir de trás pra frente pra descobrir se a IA é a ferramenta certa, qual tipo de IA é a ferramenta certa, e qual fornecedor você quer de fato usar, apoiar, votar com os pés. Agora, eu uso, sim, IA preditiva.Aquelas ferramentas de IA especializadas, as “bicicletas da IA”, digamos. No livro, tinha um detalhe que eu queria muito ilustrar: como a OpenAI deu um salto quando passou de organização sem fins lucrativos a um empreendimento bancado pela Microsoft. Percebi que as cadeiras do escritório ficaram bem mais caras. Então fotografei as cadeiras de um escritório e as do outro.E joguei tudo na busca reversa de imagens do Google, que é um sistema de IA especializado — não é baseado em grandes modelos de linguagem, não é IA generativa. Assim descobri quanto essas cadeiras costumam custar. No primeiro escritório, cerca de 2 mil dólares por cadeira. No segundo, eram cadeiras de um designer brasileiro famoso, uns 10 mil dólares cada.Coloquei esse detalhe no livro pra ilustrar o tipo de riqueza e de concentração de recursos de que a gente está falando. Esses são alguns dos jeitos como eu uso IA, ainda que de forma bem limitada, sempre pontual, quando acho que vai ajudar. E, claro, uso ferramentas de transcrição por IA — outra IA especializada — em todas as minhas entrevistas.Cris: Essa foi uma das partes em que a minha cabeça explodiu, eu nunca tinha percebido: a OpenAI criou o Whisper. Deixa eu dizer de outro jeito, do meu ponto de vista. A OpenAI liberou abertamente essa ferramenta incrível de transcrição, o Whisper, em que eu jogo o áudio e ela me devolve as palavras que as pessoas disseram. E eu pensei: ah, que generoso da parte deles.Mas o motivo real de terem criado a ferramenta foi pegar todos os vídeos do YouTube, transcrever e alimentar a máquina. E aí é: ah, claro. Enfim, falando de ferramentas e de otimismo — a gente está chegando ao fim da conversa. Eu tenho uma regra desde o episódio dois deste programa, há oito anos: de novo, como eu disse do seu livro, não pode ser só uma lista de reclamações e coisa ruim. E a gente tem se saído bem até aqui.Você falou de caminhos e de bicicletas, mas eu quero ser mais específico. Se isso aqui fosse uma reunião de negócios: qual é o plano de ação, quais são os próximos passos? Só que uma das coisas que eu repito bastante, na vida e neste programa, é que problema sistêmico não se resolve com ação individual. Se eu tomar banhos mais curtos, isso nunca vai salvar o planeta do aquecimento global.E muitos amigos meus simplesmente: não quero falar de IA, não quero usar IA. Voltando aos videogames: leram que tal jogo usa IA e pronto, não vão jogar. E a minha primeira pergunta pra você é: como a gente ocupa esses espaços da IA generativa — ChatGPT, Gemini e por aí vai? Porque o que a gente viu com as redes sociais foi: ah, o Facebook é do mal, vou sair do Facebook. Ah, vou sair do Twitter.E, na esperança de quê, sei lá, talvez alguém diga: ah, sinto falta do Cris, cadê ele? Ah, está no Bluesky. Mas isso deixa o espaço aberto pra os radicais entrarem e postarem o que quiserem, sem ninguém contrapor ou tornar aquilo um lugar melhor. Então como a gente ocupa o espaço da IA — seja qual for a definição de “espaço da IA” que você preferir — com todos esses problemas que a gente vem discutindo?Karen Hao: Acho que tem duas categorias de ação pra gente pensar. Uma é desmantelar o império. A outra é investir e construir novos tipos de sistema de IA, que se tornem alternativas às tecnologias do império. Quando eu digo desmantelar o império, não estou dizendo que quero que a OpenAI, o Google, a Anthropic, seja quem for, simplesmente deixem de existir.É que eu não quero que elas sejam imperiais. Não quero que fiquem extraindo uma quantidade extraordinária de valor sem redistribuir nada em troca. Se elas voltassem a ser negócios que praticam uma troca justa de valor com o mundo, eu ficaria perfeitamente feliz com qualquer tecnologia que estivessem desenvolvendo.E a forma de desmantelar o império, acho, se resume a muita organização de base, que vai pressionar os governos a regular e responsabilizar essa indústria. No último ano, a gente viu uma quantidade incrível dessa organização de base florescendo pelo mundo.Recentemente, lancei com um grupo de jornalistas, pesquisadores de IA e acadêmicos críticos um projeto chamado AI Resist List, que busca documentar parte dessa organização de base pelo mundo. A gente encontrou cerca de 30 exemplos, de todas as regiões, de ações individuais, institucionais e movidas pela comunidade.Tinha ação artística, ação política. E isso mostra bem o seu ponto: não dá pra contar só com a ação individual, mas o indivíduo pode, sim, ter impacto. Até uma ação pequena pode gerar um grande efeito cascata. Claro que se juntar com os vizinhos pra protestar contra o data center é ainda mais eficaz. Se juntar dentro da sua escola ou universidade pra protestar contra a parceria dela com uma empresa de IA também é mais eficaz.Se juntar com os colegas de trabalho de um setor pra barrar a adoção de uma IA que corrói os direitos trabalhistas é mais um jeito eficaz. A gente tem um monte desses exemplos. Um dos meus favoritos é o de uma comunidade sobre a qual escrevi no livro, Quilicura, no Chile, na periferia de Santiago. É uma comunidade da classe trabalhadora, bem pobre, que vem sendo alvo incessante da expansão de data centers.E por isso protestaram de forma bem aguerrida contra essa expansão, porque não acharam bom negócio hospedar essas instalações sem tirar nenhum benefício, enquanto elas consomem uma parte significativa dos recursos naturais da região.E, logo depois que escrevi sobre eles, foram além na resistência e criaram uma plataforma chamada Quili.ai. É um site em que você entra e que parece um chatbot, parece o ChatGPT: tem uma interface de chat pra você digitar. Só que, quando você faz uma pergunta, em vez de um modelo de IA responder, a mensagem é encaminhada pra alguém que mora em Quilicura, no Chile. Aí, se você pede “quero a imagem de um cachorro”, aquilo vai pro artista local deles, o Benji. Ele pega um pedaço de papel, desenha um cachorro, tira uma foto e te manda de volta.Eles fizeram isso essencialmente como um projeto de arte performática, pra fazer as pessoas pensarem duas vezes antes de usar IA generativa pra bobagem. A mensagem era: ei, quando você fica brincando com essas ferramentas em pedido besta, isso afeta comunidades como a nossa, drena os recursos de que a gente precisa pra viver bem.E também queriam levar as pessoas a pensar: por que não perguntar pra alguém da sua própria comunidade aquela receita que você procurava, ou pedir aquela imagem? Porque aí você reconstrói as conexões que estão tão em falta na sociedade — a falta delas é o que nos deixa mais vulneráveis a esse tipo de colonização do império.Eles deixaram o projeto aberto por 24 horas, e qualquer pessoa no mundo podia mandar um pedido. Receberam uma quantidade extraordinária deles. Viralizou de vez. E essa cidadezinha conseguiu uma virada enorme de narrativa sobre a suposta inevitabilidade e necessidade dessa tecnologia, sobre tudo o que o Vale do Silício diz — que, se você não usar, vai ficar pra trás de quem usa.E esse é só um exemplo, entre muitos, de como pessoas comuns, não importa a sua posição na sociedade, podem ter impacto real no debate, na consciência pública e até na regulação. A gente está vendo isso agora com os protestos contra data centers. Nos EUA, em 2025, cerca de 150 bilhões de dólares em projetos de data center foram travados.Isso virou uma das questões políticas mais quentes nos EUA para as próximas eleições de meio de mandato. Tem gente eleita sendo literalmente tirada do cargo por ter aprovado data centers, contrariando a vontade do povo. E isso já está tendo efeito real sobre as empresas e sobre a trajetória do desenvolvimento de IA.A OpenAI teve que encerrar recentemente a sua ferramenta de geração de vídeo, o Sora. Quando lançaram, apresentaram como o segundo produto mais importante desde o ChatGPT. O que aconteceu entre o lançamento e o fim? Uma reportagem do Wall Street Journal apontou três motivos, todos moldados por ação de base. Um: um gargalo enorme de capacidade de computação.Muitos dos data centers travados ou parados eram da OpenAI. Dois: um cenário financeiro bem mais incerto. A OpenAI está se preparando pro IPO, o que significa ficar mais exposta a Wall Street — e Wall Street está cada vez mais nervoso com a capacidade dessas empresas de cumprir o que prometem.E aí a OpenAI teve que reforçar alguns projetos paralelos pra fazer o balanço parecer um pouco melhor aos olhos de Wall Street. E, terceiro: os consumidores simplesmente não estavam usando o produto — o que também é ação coletiva de consumidores. Então, por todo esse tipo de resistência, de várias formas, de baixo pra cima, as pessoas estão de fato tendo impacto real na indústria e responsabilizando ela.Essa é a primeira categoria de ação. A segunda é: ok, que tecnologias de IA a gente usaria como alternativa? E aí a gente precisa investir mais nelas. Muitas vezes, quando converso sobre o livro, a pessoa diz: ok, me convenci de que não quero usar ChatGPT, não quero usar Claude — mas então uso o quê no lugar?E o problema é que eu não tenho muitas respostas pra essa lista de alternativas. Tem umas poucas aqui e ali, uma plataforma, uma empresa.Cris: Dá pra rodar o modelo no seu próprio computador, como o Cory Doctorow faz, mas aí é limitado e…Karen Hao: Exatamente, exige mais habilidade técnica. Mas, pra quem consegue instalar modelos de código aberto no próprio computador, eu incentivo 100%. Só que a gente também precisa de mais gente desenvolvendo interfaces bem fáceis pra esses modelos de código aberto, pra que qualquer pessoa consiga usar.A gente também precisa de mais gente desenvolvendo “bicicletas da IA”, de investidores e governos investindo mais nesse tipo de solução, e de talento — pesquisadores de IA, desenvolvedores e outras pessoas dispostas a sacrificar um pouco e abrir mão dos pacotes de remuneração enormes.Cris: Eu estava começando a achar que agora as empresas precisam ter menos lucro — e isso nunca vai acontecer.Karen Hao: Não, não é a empresa ter menos lucro. É o trabalhador topar abrir mão do pacote de milhões de dólares pra levar o talento dele pra outro lugar. Mais fácil, bem mais fácil. Eu converso com muito pesquisador de IA cansado da abordagem da indústria, porque ela é completamente sem criatividade intelectual.Eu conversei com pesquisadores que não passaram seis anos num doutorado em IA só pra ficar empurrando mais dados na máquina — pra eles, é o trabalho mais chato do mundo. E depois automatizar a programação, que era justamente o que eles gostavam de fazer. Converso com tanta gente que já não acha graça nenhuma nisso. Estão meio presos por “algemas de ouro”.E estão tentando descobrir, dentro de si, que carreira alternativa poderiam ter. Eu costumo incentivar esses pesquisadores a gastar o talento deles construindo um tipo diferente de empresa, que trabalhe com “bicicletas da IA”. E a gente já começa a ver cada vez mais desse talento indo por aí.E a gente precisa que todas as facetas da sociedade invistam num ecossistema muito mais robusto e rico de tecnologias de IA, capaz de substituir as que hoje dominam. Eu ainda tenho as cicatrizes das minhas próprias “algemas de ouro”, mas concordo plenamente.Cris: E as redes sociais são o exemplo — veja o que aconteceu com elas. Tem aquela frase famosa: as mentes mais brilhantes da minha geração passam o tempo fazendo as pessoas clicarem em anúncios. E ainda dizem: ah, isso pode ser o futuro. Pois é.Você contou a história do Quili.ai e isso me lembrou um dos primeiros criadores de conteúdo do Brasil, o Cid Não Salvo. Uns 10, 15 anos atrás, ele tuitou o seguinte: “Gente, eu disse pro meu pai que, sempre que ele precisar pesquisar alguma coisa na internet, é pra ir no Twitter.com e digitar a pergunta na caixa”. E olha que ele tinha milhões de seguidores.E, por uns bons dias, quase um mês, você entrava no Twitter do pai dele e via perguntas tipo “onde eu compro pizza?”. Era engraçadíssimo. No fim, ele contou pro pai — ou talvez não. Mas eu adoro essa ideia. Antes de a gente terminar: você já deve ter respondido isso mil vezes, mas vai continuar cobrindo IA? O que está na sua cabeça, o que vem por aí? Turnê mundial? O que vem pela frente?Karen Hao: Com certeza estou pensando em como continuar responsabilizando essas empresas. Estou envolvida em várias colaborações, com gente incrível, em diferentes projetos ligados a isso. O AI Resist List foi um deles. Também co-criei um programa chamado AI Spotlight Series, com o Pulitzer Center, uma organização jornalística sem fins lucrativos que financia jornalismo investigativo pelo mundo.É um programa que treina jornalistas do mundo inteiro a cobrir IA por uma lente de responsabilização. Até agora, já treinamos mais de 3 mil. E eu sigo pensando em como construir mais capacidade dentro do jornalismo, da sociedade civil, de outros contextos, pra mobilizar ainda mais essa organização de base — pra conter de verdade os impérios da IA e ajudar a desmantelá-los.Cris: Adorei o seu exemplo da moda. É possível, já foi feito. Ou até a indústria automotiva. Ou o grande exemplo que a gente não mencionou, e que o pessoal da OpenAI vive citando: o Projeto Manhattan, a energia nuclear.O mundo não acabou. Quando eu era criança lendo Asimov, achava que ia tudo acabar num fogo nuclear. Enfim — alguma última palavra, alguma mensagem, algum palpite pros jogos do Brasil na Copa, alguma coisa que você queira dizer antes da gente encerrar?Karen Hao: No fim das contas, o que eu espero que fique desta conversa e do livro é o seguinte: neste momento, o Vale do Silício está concebendo a IA como um projeto político. E a característica central desse projeto é tirar a autonomia de todo mundo — a autonomia de moldar de verdade o próprio futuro e o nosso futuro coletivo. Mas, no instante em que você reconhece que já tem uma autonomia significativa pra resistir, o império começa a desmoronar.Então espero que as pessoas encontrem a própria voz, a afirmem, conquistem o seu lugar à mesa e se conectem com os vizinhos, com a comunidade, com os colegas de trabalho, pra criar mais movimentos juntos.Cris: Que ótimo. Karen Hao, o seu livro é O Império da IA: Por dentro da corrida irresponsável pela dominação total. Obrigado por vir ao Brasil conversar com a gente. Foi um prazer.Karen Hao: Muito obrigada.Uma das primeiras perguntas que anotei quando comecei a pensar nessa conversa foi justamente a do final, a da ocupação de espaços. Porque, como eu disse, quando as redes sociais chegaram para ficar, muita gente falou “ah, não vou usar, é do mal” — e aí as pessoas ruins, vamos chamar assim, acabam ocupando esse espaço e falando o que bem entendem. A gente precisa aprender essa lição agora, no mundo da IA.Fora que vejo muita gente falando de IA sem nunca ter usado — ou que usou, sei lá, dois anos atrás, acha que continua tudo igual e já diz que não quer chegar perto.E por quê? Porque essa abordagem de ocupar espaços é o que eu e a Ana Freitas buscamos fazer no IA em Curso, nossa comunidade de letramento contínuo em IA. Foi, aliás, uma conversa que tive com a Karen antes da entrevista: ao mesmo tempo que a gente fala do impacto da IA no mundo, também precisa focar no que é prático, no que dá para fazer hoje com IA, sem vender sonho nem desastre. A analogia que usei foi a de que é que nem quando a gente fazia curso de Word e Excel — é o que eu faço agora que vai facilitar minha vida, me fazer ganhar tempo, botar a IA para me ajudar. Quem viu minha conversa com a Ana aqui no Boa Noite Internet, no fim de 2025, sabe do que estou falando. Se não viu, volta lá e confere.Desde que a gente lançou este episódio, o IA em Curso já passou de 400 pessoas. Tem muita gente colocando projetos pessoais incríveis na rua, tirando do papel aquela ideia que rondava a cabeça há um tempão. E a comunidade tem mentoria ao vivo, aula gravada, newsletter, banco de agentes, grupo de Telegram… que mais? O que não falta é jeito de passar para você o conhecimento sobre IA de que você precisa hoje, agora. Quero te dar a bússola para navegar nesse universo.Se esse é o tipo de abordagem que você quer ter com a IA, passa lá no iaemcurso.com.br e usa o cupom BNI2026 para ganhar 20% de desconto no plano anual. Mas corre, porque daqui a duas semanas vou apagar esse cupom — não é todo dia que a gente dá um desconto desses.É isso. Boa Noite Internet, temporada 2026 começando — como todo ano, com mudança, ideia, projeto. Ou, como diz minha citação preferida de todos os tempos: “vivemos uma fase de transição, como sempre”. Espero ver você por aqui e lá no IA em Curso.Obrigado pelo seu tempo e pela sua atenção. Até o próximo episódio. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit boanoiteinternet.com.br/subscribe

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

Story of the Week (DR):‘We faltered': IBM stock collapses after a grave warning about AI Customers are Prioritizing AI Hardware: While IBM mostly sells software nowadays, businesses are currently cutting back on their software budgets. Instead, they are rushing to spend their money on physical computer parts (like chips and servers) needed to build new Artificial Intelligence systems.Board skills/tenureFormer Intel CEO says the chipmaker went off the rails ‘when it started to be run by business people'The inside story of IBM's shocking profit warningXbox CEO Joins Fed AI Jobs Task Force Days After Announcing 3,200 LayoffsXbox CEO Asha Sharma, who previously worked in Microsoft's Core AI group before taking over Xbox, joins Marc Andreessen, co-founder and general partner at Andreessen Horowitz, and Charles I. Jones, a Stanford University economics professor currently on leave at Anthropic.Productivity and Jobs task force, which will study the economic impact of new general-purpose technologies, including AI, as part of the central bank's approach to monetary policy.Marc Andreessen Says AI Is 'Already a Better Doctor Than 99.99% of Human Doctors'Jamie Dimon says he understands why people have grown 'anti-rich'Gallup CEO says colonizing Mars may be closer than fixing today's ‘broken' workplace—where disengagement levels are as high as 2020Elon Musk Says His Goal Is for SpaceX to Be Worth More than the Entire EarthThe U.S. Added 441,000 Millionaires Last Year, While the Typical American Got 20% PoorerJames Murdoch may have reaped as much as $7.5 billion from his pre-IPO investment in Elon Musk's SpaceXPalantir CEO Alex Karp Warns AI Could Become America's Biggest Driver of Wealth Inequality"You now have a revolution where, you know, I could become 20 times wealthier than I am now," he added. Karp said AI is creating a "complete decoupling" between ordinary economic gains and a small group of people accumulating "unimaginable wealth."The AI Backlash Has Tech Executives Fearing for Their Lives MMPeter Thiel and other tech billionaires are publicly shielding their children from the products that made them richAnthropic's New AI Ad Is So Disturbing, OpenAI CEO Sam Altman Thought It Was SatireMeta Oversight Board study: AI chatbots may be the most perfect propaganda machine ever inventedA Majority of Americans Now Support Seizing Wealth From AI IndustryGoodliest of the Week (MM/DR):DR: New York bans data center construction for a year, rattling AI industry AND New York becomes first U.S. state to impose AI data center banMM: FREE FLOAT! MMMicrosoft's emissions rose 25% last year. Experts say they'll surge even more dramatically in the years aheadWe said FIVE YEARS AGO that MSFT board was one of the worst at managing carbon despite setting a net negative target at the timeWe were correctAssholiest of the Week (MM):It's not us, it's youxAI sued a Grok user for allegedly generating deepfakes of child sexual abuseIn the ultimate in tech bro manbaby id, Musk is blaming the USERS for his failure to stop child sex abuseLike a gun company suing a gun owner for using the gun used in murder - gun terms of service!Dimon urges calm over fear about AI's impact on jobs: 'Stop being breathless over it'AI isn't the problem, your breathless fear isRobotaxis Are Turning Passengers Into Horrible and Entitled Menaces to SocietyIt's not the service, it's the user… Meta CTO Says He'd Like to Sue Leakers, Then Audio From That Same Meeting LeaksIt's not what I said that's the problem, it's that you told someonePeter Thiel and other tech billionaires are publicly shielding their children from the products that made them richBut YOUR children should use them, obviouslyIt's the USER's fault now… unless, of course, it's a school - in which case the SCHOOL is to blame:84% of students use AI for homework. Only 3 in 10 schools have rules for itAccessWhite House teleprompter operator investigated over alleged trades on Trump speechesTrump Media to Sell Faster Access to President's Social PostsOpenAI Strikes Bold Deal With Kalshi to Mix Together the Most Hated Technologies in Existence: AI and Prediction MarketsDOJ Defends Musk's Unpermitted Gas Turbines, Saying Shutting Down Grok Threatens National SecurityElon Musk's $1 million offers to voters in Wisconsin election were probably illegal bribes, bipartisan panel rulesParamount Shareholder Sues Ellisons, Board For Alleged Side Deal, Promises To Donald TrumpMichael Dell has nailed his relationship with Donald Trump, and it's paying offMeritocracyPete Hegseth Announces Military Will Test Service Members' Testosterone Levels and Offer Hormone TherapyEveryone is a trans man!Is AI Rejecting Your CV Because of Your Age or Race? Landmark Lawsuit Could Reshape RecruitmentFor Black women hit by anti-DEI backlash, this election is personalAustralia's highest paid CEO makes 500 times the average salaryThe American E.V. Has Been Crushed. Will It Take the U.S. Auto Industry With It?WE WANT THE CARS. Just give us the Chinese ones nowJim Cramer on Meta: “Zuckerberg's Not a Bozo, You Can Quote Me on That”Paul Fucking Atkins and The War on John Cheveddan DR“Regardless of the fate of Rule 14a-8 next season and beyond, I implore all who have a role in the shareholder proposal process to not let it be weaponized by those who represent fringe interests. Annual meetings are not vehicles for political or social debates that have little or no bearing on investors' financial returns.”“This past season, one—yes, one—individual was the sole or lead proponent for approximately 41 percent of the shareholder proposals that were voted upon.[20] Of this individual's proposals, only eight percent received majority support.[21] Simply put, when a single shareholder can seize annual meetings to present scores of proposals on issues that are not generally supported by other shareholders, the system is woefully ineffective and in desperate need of reformation.”That individual is John CheveddanAtkins neglected to mention the rise of anti-ESG filers as a group, and their average of

Hour 3 blends national security, legislative wins, and a sobering look at technology's dark side. Jim Carafano breaks down the strikes near Bandar Abbas and confirms serious evidence of Chinese, Russian, and North Korean hacking of American election systems. Congressman Bob Onder delivers a full report from the Capitol Beat: the Save America Act's path through reconciliation, the newly passed Chloe Cole Act protecting children from transgender medical procedures, warnings about a potential Cori Bush comeback in Missouri's First District, and the case for an 8-0 congressional map. Kim on a Whim closes the hour wrestling with a disturbing AI deepfake lawsuit against xAI, a timely reminder for families about the real dangers lurking online. Through it all, The Marc Cox Morning Show stays anchored in family, faith, and the fight to protect both elections and children. Hour Hashtags: #JimCarafano #BobOnder #SaveAmericaAct #ChloeColeAct #IranStrikes #ElectionSecurity #KimOnAWhim #AIThreats #ProtectOurKids #CoriBush #ConservativeTalk #FaithFamilyFreedom #MarcCoxMorningShow Guest List, Hour 3: Jim Carafano, Heritage Foundation — Iran strikes and foreign election hacking threats Congressman Bob Onder (MO-3) — Save America Act, Chloe Cole Act, Cori Bush race, education policy

A significant epidemic of the parasite cyclospora, which causes explosive diarrhea, has been linked by federal health officials to lettuce from Mexico that is sold at Taco Bell stores in five states in the United States. AOC also makes a trip to Memphis to back Justin Pearson against Elon Musk's xAI. Also on the show: Early voting has begun in Tennessee, we reveal how the story of the man stuck inside a Kansas City port-a-potty, we break down what you need to know before seeing The Odyssey, Maine's Democrat Senate candidates' debate was wild, and Dale Jackson joins to talk politics. See omnystudio.com/listener for privacy information.

META's stock surged last week, but investors shouldn't ignore the risks. Meta shares climbed last week as Wall Street became increasingly optimistic about the company's AI strategy. The stock was up about15% for the week and erased the year-to-date losses. Investors are betting that Meta's enormous spending on AI infrastructure, custom chips, top engineering talent, and next-generation models will lead to faster revenue growth, stronger advertising tools, and new revenue streams over the next several years. The market clearly believes Meta has positioned itself as one of the leaders in the AI race. But while investors were celebrating, Europe reminded everyone that even great companies face meaningful risks. The European Commission announced preliminary findings that Facebook and Instagram may violate the Digital Services Act because of what regulators call "addictive design" features, including infinite scrolling, autoplay videos, and recommendation algorithms that encourage users to stay engaged for longer periods. If the findings become final and Meta does not make sufficient changes, the company could face fines of up to 6% of its global annual revenue, along with potential changes to how its platforms operate across Europe. Meta has disputed the findings and says it has already implemented significant protections for younger users. This could amount to a fine of around $12 B, but the bigger problem I see is a potential hit to ad revenue if they must change their business practices. Europe is an important part of their business considering it accounts for about 23% of overall company sales. We also can't forget the legal liability Meta is facing in the United States, which could ultimately total as much as $1.4 trillion. That number may sound shocking, but it stems from multiple lawsuits brought by numerous states and plaintiffs. The first major cases are scheduled to go to trial in August, with California, Colorado, New Jersey, and Kentucky leading the way. The lawsuits allege deceptive business practices, and potential penalties range from $2,000 to $20,000 per violation. Given Meta's massive user base, those fines could accumulate rapidly if the courts rule against the company. Beyond civil penalties, the states are also seeking disgorgement of profits, which would require Meta to surrender profits earned from the alleged misconduct during the relevant period. If Meta performs poorly in these initial cases, another 25 states have similar lawsuits waiting in the wings, significantly increasing the company's legal exposure. There are already signs that these legal challenges carry real financial risk. New Mexico recently won a $375 million judgment against Meta, and a separate federal trial is scheduled to begin early next year. The AI opportunity is also far from guaranteed. Today, investors are rewarding companies that appear to be winning the AI race, but the competitive landscape is becoming more crowded every quarter. OpenAI, Anthropic, Google, Microsoft, xAI, and others are investing billions of dollars to develop better models and attract developers. Meta has responded aggressively by spending heavily on infrastructure and recruiting top AI researchers, but there is no guarantee those investments will generate returns that justify the enormous capital being deployed. A big problem is today's leader in AI can quickly become tomorrow's follower if innovation slows. I also believe that all of these companies will not succeed in this space, which will mean enormous amounts of wasted capital for the losers. Wall Street seemed to be focused almost entirely on Meta's AI upside last week, and that optimism may continue to drive the stock higher. But investors should remember that valuation is increasingly dependent on AI execution while regulatory scrutiny remains elevated. If AI spending fails to produce the expected returns or regulators force changes that weaken engagement, today's bullish narrative could change quickly. Meta remains one of the strongest companies in technology, but even great businesses are not risk-free. As investors, it's important to weigh both the opportunities and the risks, not just the headlines driving the stock higher today.   The spring home sales season disappointed in June The spring home-selling season ended on a disappointing note. Through May, existing home sales had been showing signs of improvement, and many real estate professionals were becoming more optimistic about the housing market. However, June's data told a different story. The conflict involving Iran contributed to higher inflation expectations and pushed mortgage rates higher, weighing on buyer demand. Existing home sales fell 2.4% in June to a seasonally adjusted annual rate of 4.09 million homes, well below economists' expectations for a 0.7% increase. Despite the monthly decline, the longer-term trend remains somewhat more encouraging. Existing home sales were still up 2.8% compared with a year ago, suggesting that underlying demand has not disappeared. There continues to be pent-up demand from prospective buyers, but many seem unwilling to make such a large financial commitment while borrowing costs remain elevated, even as housing inventory continues to improve According to Freddie Mac, the average 30-year fixed mortgage rate was 6.43% last week. If mortgage rates remain near these levels, many prospective homebuyers may continue to delay their purchases, preventing a stronger recovery in the housing market.   Another Hidden Cost of AI: Steel Most people know that the AI buildout has driven up demand for advanced computer chips, contributing to higher prices for smartphones, laptops, and other electronics. They also know that AI data centers require enormous amounts of electricity, putting upward pressure on utility rates as more power is diverted to support AI infrastructure. But there's another cost that receives far less attention: steel. Steel is a critical component of every data center. Industry estimates suggest that new data centers will consume roughly 1 million tons of steel annually, representing approximately $1.4 billion in demand. Steel is used throughout these facilities from the structural columns, roof joists, and roof decking to the server racks that house thousands of AI processors. This growing demand has ripple effects throughout the economy. Higher steel demand can contribute to increased costs for automobiles, household appliances, commercial buildings, bridges, and countless other products that rely on steel. The impact doesn't stop there. Steel production is one of the most energy-intensive manufacturing processes. A single electric furnace steel mill can consume anywhere from around 50 to 200 megawatts of electricity per day, competing for the same power resources as AI data centers. As both industries demand more electricity, utilities face increasing pressure to expand generating capacity. Ultimately, who pays for that increased demand? The answer is often the consumer. Higher electricity demand can translate into higher utility bills for households and businesses as utilities invest in additional generation and transmission infrastructure. In regions where electricity supply is already tight, the competition for power is becoming even more apparent. For example, PJM Interconnection, the nation's largest regional transmission organization, plans to begin conducting supplemental power auctions with electricity generators in September to help secure additional supply. Auctions reward the highest bidders, meaning electricity increasingly flows to those willing to pay the most. As large industrial users and AI data centers bid aggressively for power, consumers could face higher electricity prices if supply fails to keep pace with demand. AI will likely bring enormous productivity gains and economic benefits over the long run. However, it is also creating secondary inflationary pressures that extend well beyond semiconductors. Steel, electricity, construction materials, and other critical inputs are all experiencing increased demand, and those costs eventually work their way through the economy. As the AI revolution accelerates, these indirect costs are likely to become an increasingly important part of the inflation story.   Inflation Is Cooling... But Don't Pop the Champagne Yet The latest CPI report was another encouraging sign that inflation is moving in the right direction. Headline CPI declined 0.4% in June, marking the largest monthly drop since 2020, while the annual inflation rate slowed to 3.5% from 4.2% in May. Core inflation, which excludes food and energy, was flat on the month and eased to 2.6% year over year. Much of the improvement was driven by a sharp decline in gasoline and broader energy prices. While this is welcome news, I'd caution against declaring victory over inflation. One of the biggest challenges with inflation is that it doesn't always show up in the headline numbers immediately. It often works its way through the economy in waves, especially when it comes to energy. A good example is my own pool service. My pool guy recently raised his prices, likely for two reasons: higher chemical costs and the increased cost of driving from house to house. Those are both directly tied to energy markets. Even if gasoline prices temporarily fall and help bring down CPI for a month, businesses often adjust prices more slowly because they have to account for prior cost increases and the uncertainty of where energy prices are headed next. That's why I think investors should remain cautious. The recent improvement in inflation was helped significantly by lower oil and gasoline prices following a temporary easing in geopolitical tensions. But with conflict in the Middle East once again threatening energy supplies and oil prices recently moving higher, that relief could prove short-lived. The trend is encouraging, and the Federal Reserve will certainly welcome softer inflation data. But as long as energy prices remain vulnerable to geopolitical events, inflation is likely to remain unpredictable. Businesses from manufacturers to small local service providers will likely continue to pass along higher input costs whenever they have to. One softer CPI report is good news. But sustained price stability will likely require a concrete outcome in the Middle East and more stability in the energy market. While again we welcome the positive news in this CPI report, the conversation around in inflation and what to do with interest rates will continue with the ongoing developments in Iran.   Higher Gas Prices Aren't Stopping the American Consumer If you were looking for evidence that higher gas prices are slowing down the American consumer, the latest retail sales report doesn't provide much support. The headline number was relatively modest, with retail and food services sales increasing 0.2% from May. But the year-over-year numbers tell a much stronger story. Total retail and food services sales were up 6.7% from June of last year. Even if you exclude gas stations, which saw an increase of 19.8%, retail sales still grew at an impressive rate of 5.7%. More importantly, when you look across the major spending categories, not a single major category declined year over year. Furniture and home furnishing stores was the only major category that was flat compared to last year, but again it wasn't negative! Some of the strongest performers included non-store retailers, which primarily includes online shopping, increased 14.2%. Electronics and appliance stores were up 8.6%, while clothing and clothing accessories increased by 4.8%. Building materials and garden equipment stores were up 3.5% One of the more interesting data points is that Americans are still spending money at restaurants and bars. Food services and drinking places were up 3.8% year over year, showing that consumers continue to spend on experiences and dining out despite higher costs and concerns about the economy. The big takeaway is that the consumer remains remarkably resilient. Yes, higher gas prices can eventually put pressure on household budgets. But so far, consumers have continued to spend across virtually every major category. The year-over-year numbers show broad-based growth, not just spending concentrated in one or two areas. The consumer may be under pressure, but they are clearly not out of the game yet.   Financial Planning: What's Next for Social Security The Social Security Trustees' most recent solvency report highlights the need for Congress to address the program's long-term funding shortfall. Under current projections, the retirement trust fund is expected to be depleted in 2032, at which point ongoing payroll tax revenue would be sufficient to pay only about 78% of scheduled benefits unless legislative changes are made. Importantly, this does not mean Social Security will become insolvent or stop paying benefits, it means benefits would be reduced if Congress takes no action. While no specific legislation has emerged, many policy experts expect Congress to adopt a combination of gradual reforms rather than a single sweeping change. Potential solutions include increasing the Social Security payroll tax rate from 6.2%, raising or eliminating the taxable wage cap from $184,500, increasing the full retirement age from 67 for younger workers, and slowing future benefit growth for higher-income retirees. Historically, when Congress has made changes to Social Security, it has phased them in over many years, and most proposals would leave current retirees and those approaching retirement largely unaffected. As a result, individuals already receiving benefits or those within roughly the next decade of retirement are generally expected to experience little or no change, with the majority of reforms likely to apply to younger generations who have more time to prepare.   Companies Discussed: Nike, Inc. (Ticker: NKE)  

Protests break out in Kyiv after Zelenskyy dismisses Defense Minister Mykhailo Fedorov, Israel's Knesset passes a law curbing the attorney general's authority, Washington attacks an oil tanker in the Strait of Hormuz, the U.S. House rejects an amendment to strip military aid to Israel, Trump fires a new Seattle prosecutor just minutes after his appointment, France's parliament adopts an assisted dying law, over 500 Rohingya are feared dead after two boats capsized, U.K. child sexual offense arrests hit a record high, xAI sues a user who allegedly used Grok to create child abuse material, and a study finds microplastics in 84% of heart attack patients. Sources: Verity.News

Elon Musk — genius, disruptor, or dangerous monopolist? In this episode of 3 Techies Banter podcast, we dive deep into Musk's audacious ventures: SpaceX, Starlink, and XAI. From reusable rockets to orbital data centers powered by the sun, Musk's vision is reshaping industries — but also raising tough questions about risk, monopoly, and government dependency.

Uber agreed to acquire Delivery Hero for ~$14.8B, expanding into 99 markets. Thinking Machines released its first open-weight model, Inkling, SpaceXAI open-sourced Grok Build after a data-upload backlash, and sources detailed xAI's chaotic race to catch Claude under new leadership. Uber agrees to acquire Delivery Hero in a deal that values the German food delivery company at ~$14.8B, offering €41.50 per share and buying Prosus' 16.8% stake (Bloomberg) Thinking Machines Lab debuts Inkling, an open-weight MoE model with 975B total and 41B active parameters, trained to be broad rather than optimized for one area (Thinking Machines Lab) Thinking Machines Lab debuts Inkling, an open-weight MoE model with 975B total and 41B active parameters, trained to be broad rather than optimized for one area (WSJ) SpaceXAI open-sources Grok Build under an Apache 2.0 license, after the tool uploaded user repositories to SpaceXAI's Google Cloud bucket, causing a backlash (Simon Willison) SpaceXAI open-sources Grok Build under an Apache 2.0 license, after the tool uploaded user repositories to SpaceXAI's Google Cloud bucket, causing a backlash (The Decoder) Sources detail how xAI has been slowed down by internal chaos as Musk pushed for Grok to match Claude, amid signs it is turning a corner under Michael Nicolls (Bloomberg) Sources: Apple is preparing new iPads, including an iPad mini with an OLED screen by October and refreshed entry-level iPads and iPad Airs for 2027 (Bloomberg) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

With open weight models fast approaching the power and utility of closed AI giants, enterprises face tough choices about privacy, sovereignty, and who they can trust. Explore why the next tech revolution might depend on which models stay truly open—and who gets to keep using them. Mozilla's inaugural 'State of Open Source AI' Report with CTO Raffi Krikorian - https://stateofopensource.ai/ Apple sues OpenAI, alleging it stole trade Secrets Google's Demis Hassabis says it's time for a global AI watchdog — led by the US Microsoft July 2026 Patch Tuesday fixes massive 570 flaws, 3 zero-days White House details 'Gold Eagle' clearinghouse for AI cyber threats Introducing GPT-Live From Chatbot to Command Center OpenAI may have made a fatal misstep in copyright fight with news orgs A Green Being (@a_green_being) on X What xAI Grok Build CLI actually sends to xAI - a wire-level analysis (grok 0.2.93) Musk promises purge after Grok Build caught sending entire repos to the cloud PrismML — Announcing Bonsai 27B: The First 27B-Class Model to Run on a Phone Fidji Simo steps down from leading OpenAI's AGI work due to illness OpenAI has folded safety into research again. Its head of safety is leaving. We built a vulnerability vending machine: AI tokens in, zero-days out Australia demands AI companies must produce more energy than they consume, stop 'theft' of content White House not ruling out action on open-source AI models The Hard-Line Activists Ramping Up for the War With AI - WSJ Super Dario: One More Week How to stop Claude from saying load-bearing | jola.dev History of LLMs: Complete Timeline & Evolution (1950-2026) No, You Shouldn't Avoid Fruits and Vegetables Due to Cyclospora Google creator profiles Dust jacket Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Raffi Krikorian 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: blackhat.com/us-26 and use code TWIT gusto.com/machines monarch.com with code IM XBOW.com

With open weight models fast approaching the power and utility of closed AI giants, enterprises face tough choices about privacy, sovereignty, and who they can trust. Explore why the next tech revolution might depend on which models stay truly open—and who gets to keep using them. Mozilla's inaugural 'State of Open Source AI' Report with CTO Raffi Krikorian - https://stateofopensource.ai/ Apple sues OpenAI, alleging it stole trade Secrets Google's Demis Hassabis says it's time for a global AI watchdog — led by the US Microsoft July 2026 Patch Tuesday fixes massive 570 flaws, 3 zero-days White House details 'Gold Eagle' clearinghouse for AI cyber threats Introducing GPT-Live From Chatbot to Command Center OpenAI may have made a fatal misstep in copyright fight with news orgs A Green Being (@a_green_being) on X What xAI Grok Build CLI actually sends to xAI - a wire-level analysis (grok 0.2.93) Musk promises purge after Grok Build caught sending entire repos to the cloud PrismML — Announcing Bonsai 27B: The First 27B-Class Model to Run on a Phone Fidji Simo steps down from leading OpenAI's AGI work due to illness OpenAI has folded safety into research again. Its head of safety is leaving. We built a vulnerability vending machine: AI tokens in, zero-days out Australia demands AI companies must produce more energy than they consume, stop 'theft' of content White House not ruling out action on open-source AI models The Hard-Line Activists Ramping Up for the War With AI - WSJ Super Dario: One More Week How to stop Claude from saying load-bearing | jola.dev History of LLMs: Complete Timeline & Evolution (1950-2026) No, You Shouldn't Avoid Fruits and Vegetables Due to Cyclospora Google creator profiles Dust jacket Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Raffi Krikorian 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: blackhat.com/us-26 and use code TWIT gusto.com/machines monarch.com with code IM XBOW.com

With open weight models fast approaching the power and utility of closed AI giants, enterprises face tough choices about privacy, sovereignty, and who they can trust. Explore why the next tech revolution might depend on which models stay truly open—and who gets to keep using them. Mozilla's inaugural 'State of Open Source AI' Report with CTO Raffi Krikorian - https://stateofopensource.ai/ Apple sues OpenAI, alleging it stole trade Secrets Google's Demis Hassabis says it's time for a global AI watchdog — led by the US Microsoft July 2026 Patch Tuesday fixes massive 570 flaws, 3 zero-days White House details 'Gold Eagle' clearinghouse for AI cyber threats Introducing GPT-Live From Chatbot to Command Center OpenAI may have made a fatal misstep in copyright fight with news orgs A Green Being (@a_green_being) on X What xAI Grok Build CLI actually sends to xAI - a wire-level analysis (grok 0.2.93) Musk promises purge after Grok Build caught sending entire repos to the cloud PrismML — Announcing Bonsai 27B: The First 27B-Class Model to Run on a Phone Fidji Simo steps down from leading OpenAI's AGI work due to illness OpenAI has folded safety into research again. Its head of safety is leaving. We built a vulnerability vending machine: AI tokens in, zero-days out Australia demands AI companies must produce more energy than they consume, stop 'theft' of content White House not ruling out action on open-source AI models The Hard-Line Activists Ramping Up for the War With AI - WSJ Super Dario: One More Week How to stop Claude from saying load-bearing | jola.dev History of LLMs: Complete Timeline & Evolution (1950-2026) No, You Shouldn't Avoid Fruits and Vegetables Due to Cyclospora Google creator profiles Dust jacket Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Raffi Krikorian 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: blackhat.com/us-26 and use code TWIT gusto.com/machines monarch.com with code IM XBOW.com

With open weight models fast approaching the power and utility of closed AI giants, enterprises face tough choices about privacy, sovereignty, and who they can trust. Explore why the next tech revolution might depend on which models stay truly open—and who gets to keep using them. Mozilla's inaugural 'State of Open Source AI' Report with CTO Raffi Krikorian - https://stateofopensource.ai/ Apple sues OpenAI, alleging it stole trade Secrets Google's Demis Hassabis says it's time for a global AI watchdog — led by the US Microsoft July 2026 Patch Tuesday fixes massive 570 flaws, 3 zero-days White House details 'Gold Eagle' clearinghouse for AI cyber threats Introducing GPT-Live From Chatbot to Command Center OpenAI may have made a fatal misstep in copyright fight with news orgs A Green Being (@a_green_being) on X What xAI Grok Build CLI actually sends to xAI - a wire-level analysis (grok 0.2.93) Musk promises purge after Grok Build caught sending entire repos to the cloud PrismML — Announcing Bonsai 27B: The First 27B-Class Model to Run on a Phone Fidji Simo steps down from leading OpenAI's AGI work due to illness OpenAI has folded safety into research again. Its head of safety is leaving. We built a vulnerability vending machine: AI tokens in, zero-days out Australia demands AI companies must produce more energy than they consume, stop 'theft' of content White House not ruling out action on open-source AI models The Hard-Line Activists Ramping Up for the War With AI - WSJ Super Dario: One More Week How to stop Claude from saying load-bearing | jola.dev History of LLMs: Complete Timeline & Evolution (1950-2026) No, You Shouldn't Avoid Fruits and Vegetables Due to Cyclospora Google creator profiles Dust jacket Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Raffi Krikorian 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: blackhat.com/us-26 and use code TWIT gusto.com/machines monarch.com with code IM XBOW.com

San Francisco's housing market just broke reality. While the mainstream media was busy writing the city's obituary, the AI money tsunami quietly reversed the so-called "doom loop" — but not for anyone you know. Over 140 homes sold for at least a million dollars OVER asking price in the first half of 2026 alone, with bidding wars erupting across Noe Valley and Pacific Heights like it's 1999 on steroids.This is Gavin Newsom's California in miniature: a city that's recovering at the very top while everyone else gets priced out of existence. Tech executives flush with Anthropic, OpenAI, and xAI equity can absorb a half-million-dollar stock correction and still write a seven-figure check without blinking. For the rest of California — teachers, nurses, small business owners — those homes might as well be on the moon. A Compass economist called the market "bananas." That's the polite word for it.Meanwhile, across the country's other liberal tech hub, Washington State is charting the exact opposite trajectory. Microsoft layoffs are piling up, the progressive wealth tax is pushing millionaires out the door, and Seattle's upper-end buyer pool is quietly draining south. Two cities, two progressive governments, two very different outcomes — and one of them is getting precisely what it voted for.Subscribe to @reasonablenews for daily conservative news commentary from the Pacific Northwest. Sean covers the stories the mainstream media ignores — hit the notification bell and we'll see you in the next episode.#SanAntonio #MinimumWage #TexasPoliticsGO PREMIUM WITH REASONABLE+ FOR UNCENSORED ACCESS

Homeownership has long been treated as one of the safest paths to building wealth, but higher prices, changing returns, and retirement pressures are forcing more Americans to rethink that assumption.Chuck Zodda and Mike Armstrong break down why homes are no longer guaranteed to outperform other investments, how leverage and forced savings still make homeownership powerful, and why the Great Wealth Transfer may take longer and deliver less than many heirs expect. They also discuss how much Americans think they need to retire comfortably, why taxes and spending often change in retirement, how too few stocks are driving the S&P 500's future, what Elon Musk's xAI strategy says about competition in artificial intelligence, and Paul LaMonica's take on why T-Mobile may withstand the threat from Starlink.

With open weight models fast approaching the power and utility of closed AI giants, enterprises face tough choices about privacy, sovereignty, and who they can trust. Explore why the next tech revolution might depend on which models stay truly open—and who gets to keep using them. Mozilla's inaugural 'State of Open Source AI' Report with CTO Raffi Krikorian - https://stateofopensource.ai/ Apple sues OpenAI, alleging it stole trade Secrets Google's Demis Hassabis says it's time for a global AI watchdog — led by the US Microsoft July 2026 Patch Tuesday fixes massive 570 flaws, 3 zero-days White House details 'Gold Eagle' clearinghouse for AI cyber threats Introducing GPT-Live From Chatbot to Command Center OpenAI may have made a fatal misstep in copyright fight with news orgs A Green Being (@a_green_being) on X What xAI Grok Build CLI actually sends to xAI - a wire-level analysis (grok 0.2.93) Musk promises purge after Grok Build caught sending entire repos to the cloud PrismML — Announcing Bonsai 27B: The First 27B-Class Model to Run on a Phone Fidji Simo steps down from leading OpenAI's AGI work due to illness OpenAI has folded safety into research again. Its head of safety is leaving. We built a vulnerability vending machine: AI tokens in, zero-days out Australia demands AI companies must produce more energy than they consume, stop 'theft' of content White House not ruling out action on open-source AI models The Hard-Line Activists Ramping Up for the War With AI - WSJ Super Dario: One More Week How to stop Claude from saying load-bearing | jola.dev History of LLMs: Complete Timeline & Evolution (1950-2026) No, You Shouldn't Avoid Fruits and Vegetables Due to Cyclospora Google creator profiles Dust jacket Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Raffi Krikorian 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: blackhat.com/us-26 and use code TWIT gusto.com/machines monarch.com with code IM XBOW.com

Microsoft Patch Tuesday July 2026 - The AI Acopolypse is Here https://isc.sans.edu/diary/Microsoft%20Patch%20Tuesday%20July%202026%20-%20The%20AI%20Acopolypse%20is%20Here%20/33154 LegacyHive : Windows user profile service arbitrary hive load elevation of privileges vulnerability https://git.projectnightcrawler.dev/NightmareEclipse/LegacyHive Progress confirms ShareFile zero-day flaw behind Storage Zone shutdown https://www.bleepingcomputer.com/news/security/progress-confirms-sharefile-zero-day-flaw-behind-storage-zone-shutdown/ xAI/Grok Exfiltrating Data and Secrets https://cereblab.com My Upcoming Classes https://www.sans.org/profiles/dr-johannes-ullrich

7.14.2026 #RolandMartinUnfiltered: Black Teen's Violent Arrest Goes Viral. Judge Restores Black Farmer Grants. xAI Pollution_ For free and unbiased Medicare help, dial (724) 264-8281 to speak with my trusted partner, Chapter, or go to https://askchapter.org/roland *Paid Partnership*_ A video of a Black teenager in Wisconsin being violently arrested has gone viral on Instagram but has been largely overlooked by mainstream media. We'll show it to you and delve into the details of the case. White Michigan progressive congressional candidate William Lawrence is facing backlash for comments he made about Black elected officials. A federal judge has reversed Trump's cancellation of $127 million in grants for Black farmers. We'll talk with one of the plaintiffs in the case and the lawyer who fought the administration in court. A new investigation reveals that Elon Musk's xAI data centers are releasing significant amounts of pollution into Black communities across the country. In today's Shop Black-Star-Network marketplace, we'll feature a conversation with the husband-and-wife duo who founded Tribe and Oak, a company that produces clean wax candles. And I'll share my sit-down interview with Lamont Bagby, the chairman of the Democratic Party of Virginia. Download the Kalshi app and use code Soccer10 to get $10 when you trade $10. You can also sign up at kalshi.com/r/soccer10, which auto-applies the code at checkout. Kalshi. Trade What's Next_ Black Star Network Partner: ChapterChapter 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 plans. As a result, we do not offer every plan available in your area. Currently we represent 50 organizations which offer 18,160 products nationwide. We search and recommend all plans, even those we don’t directly offer. You can contact a licensed Chapter agent to find out the number of products available in your specific area. Please contact Medicare.gov, 1-800-Medicare, or your local State Health Insurance Program (SHIP) to get information on all of your options.____Download the Black Star Network app at http://www.blackstarnetwork.com! We're on iOS, AppleTV, Android, AndroidTV, Roku, FireTV, XBox and SamsungTV. The #BlackStarNetwork is a news reporting platform covered under Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research.See omnystudio.com/listener for privacy information.

AI Chat with Maxime Lamothe-Brassard and Chris Luft.A new segment on the podcast: AI news in cybersecurity that is less than 24 hours old, discussed while it is still hot. Joining Chris for these conversations is LimaCharlie founder and CEO Maxime Lamothe-Brassard.In this episode:• Nipun Gupta (founder of Optimus Labs) reports that xAI's Grok Build CLI packaged and uploaded an entire local Git repository — commit history, branches and .env files with API keys — to a Google Cloud bucket; wire-level analysis via mitmproxy, a quiet server-side fix, and why you should rotate keys if you used the tool.• Fortinet's take (via Mexico Business News) on AI accelerating vulnerability discovery and exploitation: 24–48 hours from disclosure to active exploitation vs. 16 days to patch — and whether "virtual patching" is a real mitigation or a feat of marketing.• The AI distillation debate: after years of arguing fair use for scraping the internet, frontier labs now object to competitors training on their model outputs — Business Insider's look at the irony, shared by Pascal Hetzscholdt (Wiley).• Neon Cyber's survey on shadow AI rising with seniority: 14% of individual contributors use unapproved AI tools vs. 63.7% of managers and 70% of VPs and above — and why enforcement, not awareness, is the real challenge.Stories covered:• / guptanipun_my-spare-laptop-ran-completely-... • https://mexicobusiness.news/cybersecu...• / pascal-hetzscholdt_quote-heres-some-delici... • https://neoncyber.com/blog/shadow-ai-...Chapters:0:00 Intro — welcome to AI Chat0:45 Grok Build CLI uploading entire repos (Nipun Gupta / Optimus Labs)4:57 AI is outpacing patch management — is virtual patching the answer?12:32 The AI distillation debate: scraping irony at the frontier labs16:29 Shadow AI use rises with seniority (Neon Cyber)22:51 Wrap-upThe Cybersecurity Defenders Podcast — a podcast about cybersecurity and the people that keep the internet safe. New episodes drop weekly.Subscribe wherever you listen:• Spotify: https://open.spotify.com/show/6ep00ze...• Apple Podcasts: https://podcasts.apple.com/us/podcast...• YouTube: / @limacharlieio

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El viernes pasado Apple presentó ante un tribunal federal de California una demanda contra OpenAI por robo de secretos comerciales. La acusación apunta a dos ex empleados de la compañía de Cupertino, Tang Yew Tan, hoy jefe de hardware de OpenAI y antiguo vicepresidente de diseño del iPhone y el Apple Watch, y Chang Liu, ingeniero eléctrico que pasó más de ocho años en Apple antes de marcharse en enero de este año. Ambos habrían orquestado un plan coordinado para sustraer información confidencial destinada a la incursión de OpenAI en el hardware de consumo. Apple no reprocha que OpenAI fiche a sus ingenieros, algo que es legal, sino que estos se llevaran archivos, planos y piezas físicas. Según la demanda, Tan convertía las entrevistas de trabajo en sesiones de extracción de datos, mencionaba proyectos secretos por su nombre en clave y pedía a los candidatos presentaciones técnicas detalladas e incluso piezas reales de Apple, baterías y placas. Uno de los aspirantes confesó que ignoraba que ese material pudiera sacarse del laboratorio. Liu no devolvió su portátil al marcharse de Apple y aprovechó una vulnerabilidad para seguir accediendo a la nube interna mientras ya cobraba de OpenAI, algo que celebró por escrito entre risas. Apple habla también de un manual de evasión que enseñaba a los empleados que se iban a esquivar los controles de seguridad. Más de 400 antiguos trabajadores de Apple están hoy en OpenAI, un éxodo de dimensiones bíblicas. El hecho es que Apple y OpenAI son socios desde 2024 cuando anunciaron la integración de ChatGPT en Siri. El idilio no duró mucho, se torció cuando OpenAI compró io Products, la startup de Jony Ive, por 6.500 millones de dólares. La verdadera razón de la demanda es que OpenAI prepara una nueva clase de dispositivo que aspira a enterrar al teléfono, no a competir con él. Esto inevitablemente recuerda a 2010, cuando Steve Jobs anticipó una guerra termonuclear contra Android por considerarlo un producto robado. La cuestión es que Apple ha sido acusada tantas veces de apropiarse de ideas ajenas que a muchos les resulta sorprendente que el ladrón se rasgue las vestiduras de un modo tan ruidoso. Pero Apple no está en su mejor momento, se ha demostrado incapaz de desarrollar una IA propia y tiene que depender de otros, ahora de ChatGPT y en el futuro del Gemini de Google. La demanda llega en el peor momento para OpenAI que libra batallas legales en varios frentes. Un juez desestimó el 15 de junio una demanda similar de xAI, precedente que ahora puede utilizar a su favor. El Estado de Florida denunció a la empresa el mes pasado por su comercialización agresiva entre menores, y persisten los casos por derechos de autor con periódicos y autores. El caso supone además una transición simbólica. La demanda ha sido una de las últimas decisiones de Tim Cook antes de ceder el mando a John Ternus. Cook se despide lanzando un misil contra un socio convertido en rival. Los pleitos pueden entorpecer al enemigo, pero las guerras se ganan con productos, y ahí Apple lleva tiempo tropezando frente a quien no quiere un teléfono mejor, sino un mundo donde el teléfono ya no haga falta. En La ContraRéplica: 0:00 Introducción 3:40 Apple contra ChatGPT 32:51 Comodidad y propiedad 36:46 Empresas contra el consumidor 44:49 Volverá el soporte físico · 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 #apple #chatgpt Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

In today's podcast episode, we discuss what SpaceX's IPO says about xAI's position in the AI race, why so many AI companies are rushing to go public this year, whether these IPOs will drive business growth or become a distraction for shareholders, and how much these AI giants are actually competing with one another.   Join Senior Director of Podcasts and host Marcus Johnson, along with Analyst Jacob Bourne and Principal Analyst Nate Elliott. Listen wherever you get your podcasts, or watch on YouTube or Spotify.   Subscribe to EMARKETER's newsletters. Go to https://www.emarketer.com/newsletters   Follow us on Instagram at: https://www.instagram.com/emarketer/   For sponsorship opportunities, contact us: advertising@emarketer.com   For more information, visit: https://www.emarketer.com/advertise/   Have questions or just want to say hi? Drop us a line at podcast@emarketer.com    For a transcript of this episode, click here: https://www.emarketer.com/content/podcast-ai-s-next-chapter-mangos-era-race-ipo-behind-numbers   © 2026 EMARKETER

Non-consensual deepfake pornography is on the rise. While celebrities were often the earliest targets, these AI-generated deepfakes are now spreading across communities and schools, and the law and tech platforms are struggling to catch up. Kara speaks with victims' rights attorney Carrie Goldberg, tech journalist and Mostly Human Media CEO Laurie Segall and computer scientist V.S. Subrahmanian about how AI-generated explicit images are created, monetized and distributed.  Segall details her investigation into Mr. Deepfakes, one of the internet's most notorious deepfake porn platforms. Goldberg explains her lawsuit against xAI over Grok-generated explicit images. And Subrahmanian breaks down the evolution of deepfake technology and why detection remains so difficult. Plus: why victims often have little recourse, what parents and schools can do and whether new laws like the Take It Down Act can make a difference. Questions? Comments? Email us at on@voxmedia.com or find us on YouTube, Instagram, TikTok, Threads, and Bluesky @onwithkaraswisher. Come see Kara live in DC. She is sitting down with Former Secretary of Commerce Gina Raimondo on July 16 at the Johns Hopkins University Bloomberg Center, and you can be in the room. ⁠Register now⁠. Learn more about your ad choices. Visit podcastchoices.com/adchoices

All eyes will be on GPT-5.6 Sol today. ☀️But some might argue, that won't even be the ChatGPT maker's biggest release this week. That's because we finally have conversational AI that just works in OpenAI's new GPT-Live model inside ChatGPT. And that's not the only big release this week: we had big drops from Meta, Grok, Google and more. The most important move you can make each week is to quickly know the newest features you can ACTUALLY use. And that's what our Friday Features show is all about. (Brought to you a day early, obviously.) Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:OpenAI GPT Live Voice Model LaunchOpenAI GPT Live Duplex Conversational FeaturesGPT Live Access Free and Paid TiersOpenAI Developer API: GPT Real Time 2.1 ReleaseXAI Grok 4.5 Model for Software EngineeringGrok 4.5 Token Efficiency and BenchmarksNotion Agents Standalone iPhone App ReleaseGoogle Voice AI Gemini-Powered Call SummariesByteDance SeeDream 5.0 Pro Image Model LaunchByteDance Image Model Infographic and Layer FeaturesMeta Muse Image and Video Model RolloutMeta AI Agent Image Generation Through InstagramTimestamps:00:00 New OpenAI voice model04:26 New AI voice model launch06:26 Introducing GPT Live Voice Models11:15 OpenAI's new GPT model for developers15:19 Using the Grok app19:20 Notion's AI paid features explained22:50 AI features for small businesses23:41 New image model contenders27:14 New AI image model feature31:45 Meta's AI features and updates34:05 New AI tools and updatesKeywords: GPT Live, OpenAI, real-time voice model, duplex architecture, AI voice assistant, full duplex AI, natural language AI, GPT 5.5, model release, AI updates, Slack bot, personal AI agent, AI-powered productivity, ChatGPT voice features, advanced voice mode, Gemini Live, Claude voice, web search AI, context-aware AI, conversational AI, AI voice brainstorming, hands-free AI, developer API, GPT real time 2.1, cost-efficient AI, latency reduction, tool calling, code execution, software engineering AI, Grok 4.5, XAI, multi-step agentic work, Cursor, token efficiency, AI benchmarks, Notion agents, iPhone AI app, workspace automation, Gemini-powered Google Voice, AI note-taking, ByteDance, C Dream 5.0 Pro, AI image model, infographic AI, Meta, Muse image model, video AI, Instagram AI, agentic self-refinement, multimodal AI, branded visuals, AI for social media, marketing automation, AI-driven design, AI-powered workflows, API integration, team collaboration AI.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

July 9, 2026: OpenAI released its new GPT 5.6 lineup, Elon Musk's xAI launched Grok 4.5, and GPT Live showed where voice-based AI may be heading next. Then I get into Uber's Agentic Pods, where the company is embedding AI-proficient engineers inside legal, finance, and HR even as leadership admits it still can't prove the ROI. Finally, I look at the Brown University AI cheating scandal, where students averaged 96 on a take-home midterm and then collapsed to 48 on an in-person final, and why this should worry every leader thinking about AI, skill, and judgment.

Microsoft laid off ~4,800 employees and gutted Xbox by 3,200 jobs while divesting five studios. Samsung's profit rocketed past Nvidia's, Meta faced a $1.4 trillion lawsuit demand, xAI rebranded to SpaceXAI, and Anthropic researchers found a hidden "J-space" inside Claude. Microsoft is laying off ~4,800 employees, or ~2.1% of its workforce; most are in sales or Xbox, where ~20% of jobs are set to be cut by the end of FY 2027 (The Verge) Microsoft's Xbox to Cut 3,200 Jobs, Divest Five Studios in Major Overhaul (Bloomberg) Samsung estimates Q2 operating profit of ~$58.44B, a 19-fold jump from a year earlier and above a ~$57.02B estimate, and revenue up 129% YoY to ~$111.7B (Reuters) Samsung estimates Q2 operating profit of ~$58.44B, a 19-fold jump from a year earlier and above a ~$57.02B estimate, and revenue up 129% YoY to ~$111.7B (WSJ) Court filing: Meta says four US states seek $1.4T over claims it designed Facebook and Instagram to addict youth and misled the public; its market cap is ~$1.5T (Reuters) xAI rebrands to SpaceXAI and unveils a new logo; Elon Musk said in May that xAI would be dissolved as a separate company and become the AI products from SpaceX (Business Insider) Anthropic researchers detail J-space, a small set of neural patterns in Claude that reveals internal thoughts that don't appear in the model's output (Anthropic) Anthropic researchers detail J-space, a small set of neural patterns in Claude that reveals internal thoughts that don't appear in the model's output (VentureBeat) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

Topics covered in this episode: dust - a better du Hermes Agent: The AI agent that grows with you llm-coding-agent 0.1a0 Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Consulting from Six Feet Up Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: dust - a better du du + Rust = dust - a fast, visual, intuitive disk-usage CLI Run dust and immediately see the biggest directories and files without piping through sort, head, or awk Smart recursive output focuses on what matters instead of dumping every folder Colored bars show relative size and parent/child hierarchy, making “where did the space go?” obvious Perfect for Python projects bloated by .venv, caches, Docker volumes, downloaded datasets, and local AI models Install via brew, cargo install du-dust, conda-forge, Scoop, Snap, deb-get, or GitHub releases Calvin #2: A Way better ARchive format for Python packaging war - new archive format spec from Astral (same team as uv/ruff), v0.0.2, still no binary encoding defined yet Header-Index-Store layout: header IDs the file, index maps names to store offsets, store holds compressed data Index uses a finite-state transducer (FST) to dedupe common path prefixes across entry names Supports three entry types (file, directory, link) and three compression modes (store/DEFLATE/zstd), plus an "executable" metadata flag Unpacking is atomic - writes to a temp dir, then renames into place, so a failed extract never leaves a half-unpacked directory Strict name-segment rules (no NUL/control chars, no leading/trailing whitespace, blocks Windows-reserved names like CON/PRN) to avoid path traversal and cross-platform footguns Michael #3: Hermes Agent: The AI agent that grows with you Hermes Agent is an open-source, Python-built AI agent framework from Nous Research - think ChatGPT-style assistant, but connected to your tools, files, shell, browser, calendar, memory, and messaging apps I'm using it in Discord as a long-running agent conversation, not just a one-off chatbot session Hermes can connect through a gateway to platforms like Discord, Telegram, Slack, WhatsApp, email, webhooks, and more - so the same assistant can follow you across surfaces In my setup, I can send Hermes voice/text from Discord, keep project context across turns as threads, and ask it to actually do things: read GitHub repos, run commands, edit files, schedule calendar events, generate drafts, and verify results A fun workflow: I can trigger one-shot actions from an Apple Watch shortcut - dictate a request, send it to Hermes, and have the agent execute it asynchronously Hermes has persistent memory, so it can remember durable preferences and facts - for example, how I like my research formatted It also has “skills,” which are reusable procedures the agent can load later, so Hermes can self-improve over time instead of rediscovering the same workflow repeatedly It supports scheduled jobs / cron-style automations, so it can proactively watch for releases, send summaries, run checks, or remind you about things It's provider-agnostic: OpenRouter, Anthropic, Google, xAI, local models, Nous Portal, and others The big idea: Hermes turns an LLM from “a chat box I visit” into “an agent I can reach from anywhere that knows my workflows and can take real actions and learns over time.” Calvin #4: llm-coding-agent 0.1a0 Simon Willison built a Claude/Codex-style coding agent on top of his llm library, using an alpha of the llm package plus his python-lib-template-repo Built almost entirely via prompted TDD - asked an agent to write a spec.md, then commit + implement with red/green tests, occasionally hitting a real OpenAI key to sanity-check Shipped to PyPI as an alpha: uvx --prerelease=allow --with llm-coding-agent llm code Tool set mirrors familiar coding-agent primitives: read_file, edit_file (exact string replace + diff), write_file, list_files, search_files, execute_command Also exposes a Python API - CodingAgent(model="gpt-5.5", root=..., approve=True).run(...) - which Simon didn't ask for but got anyway Demo: llm code --yolo told GPT-5.5 to build a SwiftUI CLI clock; model correctly noted SwiftUI isn't really CLI-friendly and still produced an ASCII-art time display Extras Calvin: Slides, but for developers https://sli.dev/ Wanna reduce your token usage…. only issue is that its lossy https://github.com/teamchong/pxpipe PEP 772 - Python Packaging Council inaugural election dates set, nominations open July 28, voting September 1-15 Michael: What the pls? revisited! Joke: Min requirements for Linux

Mary and Andrew start with a deeper dive into the Supreme Court's decision to allow the removal of Temporary Protected Status designations from over 330,000 immigrants from Haiti and Syria — a consequential ruling that affects TPS holders well beyond those who brought the case, leaving over a million people vulnerable to removal. As Andrew notes, this case was based on two claims: one being a statutory challenge that DHS didn't follow the procedures set out by Congress, and the other a constitutional equal protection claim that this TPS status removal was “motivated in part by race” — both of which were struck down 6-3. Then, a look at Trump's latest retribution efforts including the heavy sentences doled out over a protest that ended in a shooting outside the ICE Prairieland Detention Center inTexas one year ago; a felony indictment of former Olympian David Hearn for allegedly tearing part of the liner of the Lincoln Memorial Reflecting Pool; and former CIA Director John Brennan going on offense to challenge the DOJ's investigation into him. Plus, Mary and Andrew analyze the DOJ's response to a “show cause” order to unredact some of the Epstein files in a lawsuit filed by journalist Katie Phang. Sign up for MS NOW Premium on Apple Podcasts to listen to this show and other MS podcasts without ads. You'll also get exclusive bonus content from this and other shows. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.