Podcasts about Waymo

The Tim Conway Jr Show Hour with Andy Riesmeyer Hour 3 (7.24) Andy is still impressed by how good Waymo’s self-driving cars really are — the first time he rode one in San Francisco, the vehicle pulled over and a remote voice came through the speakers because a passenger wasn’t wearing a seatbelt. It leaves us wondering if Waymos also use remote drivers the way some driverless fleets in Las Vegas do. Andy rants about AI’s effect on the brain: Google now pushes Gemini answers to the top of every search with zero context, and the real robot apocalypse isn’t Terminator-style robots — it’s us lazily handing over our autonomy. The flood of AI-generated slop online is only getting worse. Then it’s time for Andy’s favorite game, Solo to Solo (DJ Greasefire style), where he plays the isolated guitar solo from a classic track and listeners call in to guess the song and artist. First up is a retired pilot calling from LAX who still drives for Uber and admits to drinking on the job — maybe we should set him up with that earlier caller who doesn’t drink, claims she’s not boring, and has a cracking body. See omnystudio.com/listener for privacy information.

Honk honk! Who’s out there? It’s your favorite local form of transportation - Waymo! And today we met with the creative team who was inspired and talented enough to tell the groundbreaking story of Waymo in the cinematic format of film. The team gets out of pocket as they discuss bringing a tech eye to the entertainment industry, speak on the innovation of Waymo and parallels to innovation in Hollywood, and reveal what inspires them. So call up a Waymo, hook up your computer to the audio system, and listen in in the peace and quiet of the road. MERCH HERE! https://artistsonartistsonartistsonartists.com/shop This episode was filmed in the beautiful Dynasty Typewriter Theater, and tech-produced by Samuel Curtis. For live shows and events you can find more about them at dynastytypewriter.com. To learn more about the BTS of this episode and to find a world of challenges, games, inside scoop, and the Artists being themselves, subscribe to our Patreon! You won't be disappointed with what you find. Check out patreon.com/aoaoaoapod Artists on Artists on Artists on Artists is an improvised Hollywood roundtable podcast Created and Hosted by Kylie Brakeman, Jeremy Culhane, Angela Giarratana and Patrick McDonald. It is a production of Will Ferrell’s Big Money Players and iHeartMedia Podcasts. Executive Produced by Matt Apodaca and produced by Alexandra Dennis and Laservision Productions. Music By Gabriel Ponton, editing by Conner McCabe, and social media editing by Adam Keller. Thumbnails by Josh Fleury and logo design by Lucy Tomkiewicz. Hollywood's talking. Make sure you're listening. Subscribe to us on Apple Podcasts, Spotify, and Youtube! Please rate us five stars!See omnystudio.com/listener for privacy information.

We are completing our last round of summer tour as we speak. The shows are finished and all that's left to do is come home. You can imagine that after 8 days together, we've gathered some stories for you! THANKS SPONSORS -Get 25% off Cowboy Colostrum with code LT at https://cowboycolostrum.com/lt. Take control of your finances and cancel unwanted subscriptions with Rocket Money at https://rocketmoney.com/ladiestangents. Start your free trial today at https://shopify.com/ladies Try Nature's Sunshine supplements for you and the planet—go to https://naturessunshine.com and use code LADIES for 20% off your first order plus free shipping. WE'RE GOING ON TOUR - https://www.ladiesandtangents.com/live-show WE'RE ON PATREON - patreon.com/ladiesandtangents MERCH - https://ladiesandtangents.kingsroadmerch.com/ *NEW* SUBMIT YOUR STORIES - landtstories@gmail.com  FOLLOW ALONG WITH US ON SOCIAL MEDIA - @ladiesandtangents Learn more about your ad choices. Visit podcastchoices.com/adchoices

A mid-July Vision Cast loaded with accessible-tech wins, live-on-Zoom family updates, and a second helping of the Summer Song and Dance Festival. Hosted by Salvis with Donald, George, Preston, Phil, and Veronica on the panel - plus pre-recorded drop-ins from JC (calling in from Puerto Rico) and Stacey James with a high-energy launch promo for her brand-new Crazy Stacey Radio Network. The centerpiece of the night is Donald's blind-coder AI breakthrough: he walks the crew through his journey using ChatGPT to write actual C# code for the Microsoft .NET 8 framework, building his own custom audio recorder and a fully working MP3 player he's calling "MP3 DJ." It's a live case study for the "AI is finally lowering the barrier for non-programmer blind creators" trend - landing the same week the industry is buzzing over the Suno AI source-code leak that pulls back the curtain on how much AI music is trained on scraped YouTube audio.The Summer Song and Dance Festival keeps rolling with pre-submitted covers from the crew: JC on "America the Beautiful" and The Rolling Stones' "I Can't Get No Satisfaction," Rita's fan-favorite "Como La Flor" and "La Bamba," Veronica delivering James Taylor's "Fire and Rain," and Preston closing it out with Toby Keith's "I Love This Bar."The instant-classic bit of the night is "Shower in the Dark." Veronica sets it up telling the story of a sighted friend who lost power and immediately worried about how she'd shower. Veronica's dry reply - "I don't have to see to take a shower" - sends the crew into fits, and Salvis coins the phrase "Shower in the Dark. That sounds like a great song or even story," calling it back later alongside the running pizza-on-a-black-Waymo joke.Phil is back on the panel after fighting a 4th of July flu and previews Sunday's grand final of the FIFA World Cup 2026 - Spain vs. Argentina - the biggest match of the summer as the tournament wraps up its US/Mexico/Canada hosting run. George brings the crackle in JC's absence, catching up with the crew about the wild-swinging summer weather, quality time with his girlfriend, a shout-out to his Portland friend Taylor, ongoing Mac and screen-reader compatibility challenges facing blind creators in 2026, and yes, a busted toenail on the way into the show. He also relays a family update on Phil's behalf: Phil's mother is home from the hospital after a bout of pneumonia and the crew keeps her in their prayers.Preston rounds it out with a new patio bistro set, a booked DJ gig at a local crab and karaoke bar, his transit-advocacy video for the CTAA hitting Facebook and Instagram, plus plans to catch the new Twisters movie. JC's pre-recorded tropical postcard from Puerto Rico teases coquí, salsa, and street food stories in a future episode, and Stacey's high-energy audio drop announces the launch of her brand-new independent Crazy Stacey Radio Network. Warm shout-outs to Phil's mom recovering, baby Noah still home safe post-NICU, and a nod to Katie's birthday callback from the previous week close the show.Keep technology alive, let your talent shine.Recorded 2026-07-15. Hosted by Salvis on the VisionCast Network.Final note:Bear is a tentative schedule for crazy Stacy‘s new radio edition now posted on the vision cast email list.

In today's bonus episode, Gastor and Shalewa talk about joy riding in a Waymo, humanoids joining the classroom as teachers, and the power of an old AC unit. PATREON LAUNCH! For all those that have asked how they can help support the pod - it's finally here! Thanks again to all the Troops and Correspondents who rock with us. Check it out - we'll have some exclusive content and fun perks, plus it really does help! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠patreon.com/WarReportPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Many Thanks to our Patreon Troops & Correspondents for helping us bring this show to life.Shouts to the Correspondents!Tanya WeimanFontayne WoodsMark OrellanaCrystall SchmidtB. EmmerichCharlene BankAskewCharlatan the FraudCynthia PongKen MogulSayDatAgain SayDatAgainLaKai DillStephanie GayleUncleJoeStylenoshCato from StonoJennifer PedersenMarcusSarah PiardAna MathambaJSKnoLooking to further support? Help our data storage/archiving needs here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.amazon.com/hz/wishlist/ls/23X55OW4CFU8Y?ref_=wl_share⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow The Team:Instagram@SilkyJumbo@GastorAlmonteTwitter:@SilkyJumbo@GastorAlmonteTheme music "Guns Go Cold" provided by Kno of Knomercyproductions Twitter: @Kno Instagram: @KnoMercyProductions

EMAIL US NEWS STORIES!TarpReportNewsStories@gmail.com⚫ JUMP AROUND0:00 - Thunder Down Under3:15 - Man Uses Penis To Start Fire15:40 - Horrible Boundaries25:30 - Waymo Drive By39:10 - Comedy Corner48:20 - Sam's Jokes⚫ FOLLOW SAM MILLER:https://www.sammillercomedy.com Youtube @sammillercomedian https://www.tiktok.com/@sammillercomedianhttps://www.facebook.com/makeolympialaughagainhttps://www.instagram.com/sammillercomedian⚫ FOLLOW JES ANDERSON:https://jesanderson.comYoutube @coachsmoach https://www.tiktok.com/@coachsmoachhttps://www.facebook.com/coachsmoachhttps://www.instagram.com/coachsmoach

We would love to hear your feedback!We react to a week of gig economy headlines that show how fast a normal shift can turn into a legal mess, a safety issue, or an app support disaster. We also debate what responsibility looks like when platforms, customers, and drivers all push risk onto someone else. • Amazon Flex routes running long and small pay adjustments • Uber terms of service changes and lawsuit funding disclosure • Passenger safety and the road rage Uber clip • Amazon delivery etiquette and when to hand off packages • Dog renting app debate and how it compares to Wag or Rover • Instacart NYC bonus pay and confusing adjustment screenshots • Roadie cancellations, support failures, and unpaid time • Waymo robotaxi chaos including vandalism, teens, and fireworks • DoorDash driver hit during delivery and what accountability means Support the showEverything Gig Economy Podcast Related: https://gigeconomyshow.com/Download the Audio Podcast: https://thegigeconomypodcast.buzzsprout.com Love the show? You now have the opportunity to support the show with some great rewards by becoming a Patron. Tier #2 we offer free merch, an Extra in-depth podcast per month, and an NSFW pre-show https://www.patreon.com/thegigeconpodcastOctopus is a mobile entertainment tablet for your riders. Earn 100.00 per month for having the tablet in your car! No cost for the driver!https://playoctopus.page.link/HD2FBKJzFqRR35YE9 Your car stinks, use this! https://bit.ly/Driftsents The Gig Economy Podcast Group Download Telegram 1st, then click on the link to join. https://t.me/joinchat/R42wUR2QGhCi2gBDTikTok: https://www.tiktok.com/@gigeconomypodcast?Subscribe on Youtube https://www.youtube.com/c...

The conflict between the U.S. and Iran is once again threatening the flow of oil through the Strait of Hormuz, raising new concerns about gas prices, diesel costs, and the risk of global supply shortages.Chuck Zodda and Mike Armstrong break down why the situation in the Middle East remains so difficult to resolve, how refinery shutdowns in Russia, China, and the Persian Gulf are tightening supplies of gasoline and diesel, and why the U.S. may have limited options short of a major escalation. They also discuss the quiet earnings week ahead, why Alphabet's AI spending and delayed Gemini rollout matter for investors, how Waymo could become a bigger part of Google's future, whether retail investors are really moving beyond the Magnificent Seven, and why the World Cup delivered a major boost for Boston bars and local economies.

Alex, Ed, and Kirsten sit down with George Kalligeros, CEO and co-founder of Aseon Labs, to explore the overlooked infrastructure required to scale autonomous vehicles and robotaxis. The discussion covers robotic vehicle servicing, decentralized charging, autonomous fleet maintenance, Waymo and Tesla operations, fleet economics, deadheading, EV charging networks, and the future of robotaxi deployment. George explains how Aseon's mobile robotic service pods could dramatically improve fleet utilization while reducing operating costs, paving the way for scalable autonomous transportation.

San Francisco Mayor Daniel Lurie wants the state to set higher standards for Waymo's robotaxis. For more, KCBS Radio News Anchor Steve Scott spoke with KCBS Insider Phil Matier.

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Another splendiferous family episode this week as Dave and Derek talk Love Island betting odds to Waymo snitching on passengers! We also get into Jay-Z's concert security breach, Meg Thee Stallion, viral Waymo videos, and the meltdown in our comment section over some cowboy boots. Then, we talk why sports betting has officially taken over EVERYTHING, Love Island strategy, Waymo recording passengers... even during awkward moments, World Cup butter chicken wings in Jersey City, why Lizzo's new album is bad and where her career should go next. Plus: E-40 at SeaWorld, Uber loopholes, weird TikTok trends, and a bison launching a tourist into the air.DON'T FORGET TO LIKE, SHARE & SUBSCRIBE Watch “Gone in 60 Steps"! https://www.youtube.com/@GoneIn60Steps MERCH https://nnfa.creator-spring.com/ BONUS CONTENT https://www.patreon.com/c/ImDaveTemple?utm_medium=clipboard_copy&utm_source=copyLink -----------------Follow host Derek GainesIG https://www.instagram.com/thegreatboy/ YouTube https://www.youtube.com/channel/UCEQDlfXd3hPcpTkU8xHYBTg Follow host Dave TempleIG https://www.instagram.com/imdavetemple/ YouTube https://www.youtube.com/@DAT46Follow No Need for ApologiesIG https://www.instagram.com/nnfapodcast/ TT https://www.tiktok.com/@noneedforapologies FB https://www.facebook.com/noneedforapologies/Produced by Teona SashaIG https://www.instagram.com/teonasasha/TT https://www.tiktok.com/@teonasasha -----------------To advertise your product on our podcasts please email jimmy@gasdigitalmarketing.com with a brief description about your product and any shows you may be interested in advertising on.SEND US MAIL:GaS Digital StudiosAttn: NNFA151 1st Ave # 311New York, NY 10003"No Need for Apologies" - NEW Episodes every Saturday at 3PM/ET on YouTube-----------------⏱️CHAPTERS00:00 Intro00:45 Welcome to the Show06:33 Watching Argentina With TJ Miller12:22 Love Island Is Now a Gambling Sport15:03 Derek Finally Arrives24:06 Dave's Apology of the Week: Starting a Comment Race War29:11 Hanging With Indian Bros in Jersey City33:20 Derek's Apology to Himself35:54 Jay-Z Concert Security Disaster45:50 Waymo Snitches on Everyone49:24 E-40 Performs at SeaWorld56:00 Stud Strippers & Women-Only Uber Drivers01:01:00 The Nose Trumpet 01:02:58 Wide Pants Are Injuring People01:08:40 Lizzo's New Album Review01:16:30 Rap Inside Church01:28:00 Bison Launch01:30:00 OutroSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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

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

Apple has filed a lawsuit against OpenAI, alleging the AI startup stole trade secrets. The iPhone maker claimed that former Apple employees were asked to bring proprietary hardware to job interviews with OpenAI, and that the company tricked manufacturers into sharing Apple design secrets.Plus, New York state becomes the first to enact a data center moratorium, and Uber is lobbying to slow the roll of autonomous vehicles in Washington D.C. Marketplace's Meghan McCarty Carino spoke with Paresh Dave, senior writer at Wired, to learn more.Here's what we talked about: “The 6 wildest claims in Apple's lawsuit against OpenAI” from The Verge“OpenAI's First Device Will Be Movable, Screenless Speaker Built as AI Companion” from Bloomberg“New York becomes the first state to impose a data center moratorium” from Reuters“Uber's robotaxi lobbying effort puts it on a collision course with Waymo” from TechCrunch“Robotaxi Riders Are Falling Asleep, Sparking Frantic 911 Calls” from Bloomberg

Apple has filed a lawsuit against OpenAI, alleging the AI startup stole trade secrets. The iPhone maker claimed that former Apple employees were asked to bring proprietary hardware to job interviews with OpenAI, and that the company tricked manufacturers into sharing Apple design secrets.Plus, New York state becomes the first to enact a data center moratorium, and Uber is lobbying to slow the roll of autonomous vehicles in Washington D.C. Marketplace's Meghan McCarty Carino spoke with Paresh Dave, senior writer at Wired, to learn more.Here's what we talked about: “The 6 wildest claims in Apple's lawsuit against OpenAI” from The Verge“OpenAI's First Device Will Be Movable, Screenless Speaker Built as AI Companion” from Bloomberg“New York becomes the first state to impose a data center moratorium” from Reuters“Uber's robotaxi lobbying effort puts it on a collision course with Waymo” from TechCrunch“Robotaxi Riders Are Falling Asleep, Sparking Frantic 911 Calls” from Bloomberg

Eric Peters of ericpetersautos.com and David Knight take stock of the EV collapse — Ford losing $20,000 per F-150 Lightning sold, Lucid repeatedly threatening bankruptcy, and Waymo robotaxis bricking themselves across San Francisco on the Fourth of July — while Trump's big "tiny car" announcement turned out to be a $15,000 golf cart with a rope for a door that can't legally drive on any American road. Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

Eric Peters of ericpetersautos.com and David Knight take stock of the EV collapse — Ford losing $20,000 per F-150 Lightning sold, Lucid repeatedly threatening bankruptcy, and Waymo robotaxis bricking themselves across San Francisco on the Fourth of July — while Trump's big "tiny car" announcement turned out to be a $15,000 golf cart with a rope for a door that can't legally drive on any American road. Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

Fri, 17 Jul 2026 22:00:00 GMT http://relay.fm/material/576 http://relay.fm/material/576 Andy Ihnatko and Florence Ion OnePlus is done for in the U.S. and Europe, but why? Don't drunkenly hijack a Waymo to go around shooting water pellets. OnePlus is done for in the U.S. and Europe, but why? Don't drunkenly hijack a Waymo to go around shooting water pellets. clean 3801 OnePlus is done for in the U.S. and Europe, but why? Don't drunkenly hijack a Waymo to go around shooting water pellets. Links and Show Notes: Important Information Regarding OnePlus Operational Changes OnePlus Exiting the US Phone Market Is a Gut Punch for Android Fans It's not too late to get Pixel Care+ for your Pixel 9 or 10 Waymo called the cops Support

Fri, 17 Jul 2026 22:00:00 GMT http://relay.fm/material/576 http://relay.fm/material/576 Another Chance 576 Andy Ihnatko and Florence Ion OnePlus is done for in the U.S. and Europe, but why? Don't drunkenly hijack a Waymo to go around shooting water pellets. OnePlus is done for in the U.S. and Europe, but why? Don't drunkenly hijack a Waymo to go around shooting water pellets. clean 3801 OnePlus is done for in the U.S. and Europe, but why? Don't drunkenly hijack a Waymo to go around shooting water pellets. Links and Show Notes: Important Information Regarding OnePlus Operational Changes OnePlus Exiting the US Phone Market Is a Gut Punch for Android Fans It's not too late to get Pixel Care+ for your Pixel 9 or 10 Waymo called the cops Support Material

Melynda & Kenny Austin City Council & Mayor were presented with the city managers proposed budget Should Tyler Robinson's parents contribute financially to his case? Virginia school district is voting on mandating drug tests Waymo passenger trapped inside while vandals were smashing the windows to get inside See omnystudio.com/listener for privacy information.

Former national security adviser and cohost of Pod Save the World Ben Rhodes joins to discuss the conspiracy of an informal agreement between superpowers to stay out of each other's spheres. In this episode: (00:00) Intro (3:15) Spheres of influence (21:55) Marco Rubio running Venezuela? (29:11) Let's talk about drones (38:45) Ben Rhodes's top conspiracies (43:59) Tips for the paranoid (48:58) The death of Lindsey Graham (51:42) Terrorists and AI (54:20) Waymo calls police on teens (55:46) The MSG celebrity “risk” list (1:00:00) Zara's dangerous pants Hosts: Jason Concepcion and Tyler Parker Guest: Ben Rhodes Producers: Donnie Beacham and Justin Sayles Art direction: David Shoemaker Motion graphics and animations: Chris Calleton Engineering: Sarah Reddy Set design: Hannah Leiken and Jonathan Ratliff Additional support: Dae Shik Kim Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of KSL Brightside Afterparty, guest host Valerie Cameron from the KSL Movie Show joins us. On this episode, we discuss a beachgoer's real-life “Top Gun” experience. We have an update from Yellowstone about the Bison who attacked a man over the weekend. And Ethan sees a kindred spirit in a shirtless man who attacked a Waymo in downtown L.A.

In this episode of The Jess Larsen Show on Innovation & Leadership, Jess sits down with Lucas Ngoo, CEO of Cortex AI and co-founder of Carousell, the Southeast Asian marketplace that grew to a $1 billion valuation. Lucas explains why the next major leap in AI may not just be chatbots or software, but general-purpose robotics. While robot hardware is getting cheaper and more powerful, Lucas argues that the biggest bottleneck is still data: the real-world human and robot data needed to train machines to operate safely, precisely, and intelligently in everyday environments. Jess and Lucas dive into how Cortex AI is building the data infrastructure for robot brains, collecting human task data from industries like factories, retail, restaurants, hotels, and other real-world environments. They also explore why robots may follow a path similar to Waymo, starting with human supervision and gradually improving until autonomy becomes invisible and widespread. Lucas also shares the lessons he learned from building Carousell from three founders out of school into a billion-dollar company, including how to hire during rapid growth, survive startup chaos, raise capital, choose the right investors, and recognize technologies that are just becoming possible. This is a forward-looking conversation about robotics, AI, entrepreneurship, Silicon Valley ambition, and what it really takes to build the future before the rest of the world sees it coming. Learn more about your ad choices. Visit megaphone.fm/adchoices

Hollywood joins Joe Rose and the crew to break down the biggest headlines from around the sports and entertainment world. The guys discuss Wimbledon's disappointing ratings after several major stars were eliminated early, recap some of the biggest moments and winners from the ESPYs, and debate the push to make daylight saving time permanent. They also talk about Waymo's expansion into South Florida and a wild story involving passengers getting locked inside a self-driving car after causing trouble, sparking a conversation about the future of autonomous vehicles.

Hour 2 features a mix of ACC football talk, classic South Florida sports stories, and the latest headlines. Joe Rose is joined by Hollywood from ACC Media Days and Kim Bokamper in studio to discuss the possibility of the College Football Playoff expanding to 24 teams, Miami entering the season as the ACC favorite, and whether the Hurricanes can finally avoid the costly losses that have kept them from winning a conference title. The guys also discuss Bill Belichick's second season at North Carolina and compare his coaching style and personality to Nick Saban. The hour continues with Dave Hyde and Kim Bokamper sharing unforgettable stories from decades covering the Dolphins, including the challenges of covering losing teams, dealing with athletes upset over reporting, Nick Saban's awkward final days in Miami, old-school locker room moments, and Joe's own classic Marlins stories. Hollywood's Headlines wraps up the hour with discussion on Wimbledon ratings, the ESPYs, permanent daylight saving time, and Waymo's arrival in South Florida

In this C&C-less Packard 443 Episode, Tim drops a turd… off so our buddy Matt can start his next project while Mental hides from the Vegas sun. Really we talk to our buddy Paul, the creator of the Distilled Racing 41 Ford. What happens when a retired contractor decides that "good enough" isn't nearly crazy enough? Well, He Built the Ultimate LS-Swapped '41 Ford, and it became one of the most talked-about cars in the 24 Hours of Lemons paddock.... Now he's selling time in the driver's seat, and donating the money. This week on Everyone Racers, we're joined by Paul Dolan, builder of the legendary 1941 Ford Sedan that's become an icon of grassroots endurance racing. Powered by an LS V8 mounted an incredible 22.5 inches behind the front axle, this handcrafted machine has stunned racers, judges, and spectators everywhere it goes.But this episode isn't just about horsepower.Paul shares the incredible story of discovering endurance racing after retirement, designing and building this award-winning car from the ground up, learning the hard lessons of making an endurance racer survive, and finding the community that changed his life.Even better...For the 24 Hours of Lemons 20th Anniversary race at WeatherTech Raceway Laguna Seca, Paul is doing something almost unheard of.Instead of keeping the driver's seat for himself, he's offering seat time in the car to raise money for Lemons of Love, helping families affected by cancer. Every lap supports a cause far bigger than racing. Wanna be a part of it? Reach out to us, we'll put you in touch. Along the way we also dive into:

Support the pod and get so much extra content for $5/month at https://www.patreon.com/stiffsockspodBonus eps also available on Apple Podcasts! https://www.apple.co/socks

Trump plans prime-time speech on 2020 election allegations. The Battle for Hormuz: Trump Shifts Into Dangerous New Phase in Iran War. Trump’s plan to make daylight saving time permanent to get a vote in House. Parasite causing ‘explosive’ diarrhea surges nationwide, but King County cases remain at normal levels. You got the ‘explosive’ diarrhea parasite. Now what? // Robotaxi riders are falling asleep, sparking frantic 911 calls. Waymo car delivers misbehaving teen passengers to San Mateo police // John’s dreams of a teenage crime spree…

Go to https://surfshark.com/404Media to get 4 extra months of Surfshark VPN, with the reassurance of a 30-day money-back guarantee, or just use code 404MEDIA at checkout. That's https://surfshark.com/404Media. Our listeners can buy one pair of glasses and get 20% off any additional pairs at https://WarbyParker.com/404 — and using our link helps support the show. #WarbyParker #ad We start this week with Jason's story about the ChatGPT flyer pandemic. They're everywhere! Thank you to the readers and listeners who sent in their own examples. After the break, Sam tells us how Waymo snitched on kids and drove them to a group of waiting cops. In the subscribers-only section, Joseph explains why he bought a $3,000 suit that electrocutes your muscles. Yep. We Are Living in a ‘ChatGPT Flyer Pandemic' Cops Say Waymo Snitched on Teens for Allegedly Drinking and Shooting a Toy Gun I Bought the $3,000 Fitness Suit That Electrocutes You. I'm Sending It Back YouTube Version: https://youtu.be/Pc_uE7JF63k Subscribe at 404media.co Learn more about your ad choices. Visit megaphone.fm/adchoices

Today on the Woody and Wilcox Show: Soccer player takes home an interesting souvenir; Update on the explosive diarrhea parasite investigation; Pizza Hut brings back $3 personal pan pizza and a new line of clothing; Senegal's loss in World Cup blamed on team doctor; Woody Game Wednesday; Chelsea's son tips the cashier at the grocery store; Waymo problems: people falling asleep and forgetting to close the doors; And more!

Waymos—the autonomous, self-driving ride-hailing vehicles—are already cruising around D.C. with one big catch: under current D.C. law, there's still a human safety driver behind the wheel. But will D.C. ever allow Waymos to operate without a human driver? And more importantly, should it? The D.C. Council is considering a bill that could finally allow them to operate in the District, but not without a fight. Labor unions, disability advocates, tech companies, and business leaders all packed a marathon hearing to debate what the future of transportation in D.C. should look like—and who it should serve. Ben Brasch was there for many many hours. He joins me today to explain where the debate stands and what the future of AVs in D.C. could look like. Want some more DC news? Then make sure to sign up for our morning newsletter City Cast DC. You can text us or leave a voicemail at: (202) 642-2654. You can also become a member, with ad-free listening, for as little as $10 a month.  Learn more about the sponsors of this July 15th episode: DC Department of Behavioral Health Interested in advertising with City Cast? Find more info HERE.

Welcome to Show Me The Money Club live show with Sergio and Chris Tuesdays 6pm est/3pm pst.

Trump Memorializes Lindsey Graham, How To Flock The Flock Cams & A Getaway Driver Named Waymo Learn more about your ad choices. Visit megaphone.fm/adchoices

The Tim Conway Jr Show Hour 3 (7.13) A nasty SoCal heatwave is rolling in with sky-high humidity — we’re all sweating balls out here! Wildfires have sparked but firefighters are working hard on containment. Paris Hilton is back in the news as an advocate fighting to shut down the brutal Provo, Utah boarding school she attended as a teen, though we can’t help missing the old “Simple Life” Paris from the aughts. There’s a vegetation fire called the Zebra Fire burning in Azusa north of the 210, and don’t forget the shirtless nut in East Hollywood who jumped on a Waymo’s windshield, yelling at the sensors and ripping the car apart. In Boyle Heights, residents are dealing with an unbearable rotten stench, flies, and rodents thanks to the 85 million pounds of food rotting at the burned Linear Logistics warehouse, plus a burst water main leaving people without water nearby. On a slightly better note, two corpse flowers are about to bloom at the Huntington Library — those things only flower for 24–48 hours every few years and smell exactly as bad as the name suggests. In celebrity news, comedian Tom Segura and his wife Christina Pazsitzky announced they’re divorcing but will keep doing their podcast “Your Mom’s House” together (that should go smoothly!), while Brad Pitt’s kids Zahara and Maddox took out newspaper ads announcing they’re dropping “Pitt” and keeping “Jolie.”See omnystudio.com/listener for privacy information.

Trump travels with his poo. Updates on Taste of Italy. Florida cop uses ALPR to stalk woman in dangerous highway chase. A Waymo turns its teenage troublemaker riders into the police. Pickup artist Mystery has an AI girlfriend. And New York smashes solar goals.   https://www.newsweek.com/andrea-shaw-mom-says-vaccines-killed-twins-charged-murder-12172177     https://apnews.com/article/israel-gaza-palestinians-hamas-war-government-146f9a609580d4c8c42ab35fbe60d5b3    https://www.reddit.com/r/Albany/s/CwDqJHkCVW   https://www.404media.co/footage-shows-cop-stalking-woman-he-met-on-a-tv-set-after-surveilling-her-with-a-license-plate-reader/   https://www.wwnytv.com%2F2026%2F07%2F02%2Fnew-york-hits-solar-energy-milestone%2F    https://www.fastcompany.com/91570761/a-self-driving-waymo-just-reported-its-own-passengers-to-police    https://www.themirror.com/news/us-news/donald-trump-takes-lead-vladimir-1926930    https://www.themirror.com/entertainment/connor-murphy-death-gold-injection-1930934    https://www.reddit.com/r/Albany/s/9T1JYpl4e9    https://www.wired.com/story/pickup-artist-mystery-has-an-ai-girlfriend/    https://mondoweiss.net/2026/07/hamas-disbanded-its-government-in-gaza-but-israel-will-still-prevent-reconstruction-from-starting/   https://www.tiktok.com/@ifyouseethisdonttellme/video/7659484485909548302?_r=1&_t=ZP-97utB3VNrLS   https://youtu.be/bYPnNMg2R2w?is=d1nS37Us0KmlB7b_ 

Rideshare Rodeo Podcast (episode 596) July 13th, 2026 Uber just made a major move that could reshape the future of autonomous vehicles—and it may completely change the robotaxi race. In today's episode, we cover the biggest stories in autonomous driving, robotaxis, and delivery robotics: • Uber's brand-new autonomous vehicle strategy and what it means for the future of ride-hailing • Why Waymo is facing increasing criticism and negative press • A shocking incident where an Uber driver allegedly stabbed a passenger after a drop-off at Boston Logan Airport • Colorado moves closer to drone delivery as one city councilman voices support • A deep dive into Serve Robotics: robot cost, components, manufacturing, repair expenses, safety operators, networking, GPS systems, and how these delivery robots actually work If you're following the future of transportation, AI, autonomous vehicles, robotaxis, drone delivery, Tesla, Waymo, Uber, or robotics, this episode covers the biggest developments you need to know.

Rod and Karen banter about adult stranger danger, Jay-Z vs Twitter Activists, the Oscar Meyer Weiner car, seeing a WAYMO in the wild, smart glasses, Karen is jealous of Rod’s t-shirt game on walk and heat exchange. Then they discuss McConnell says a fall lead to hospital stay, Boosie Badass Scammed for a pardon, Lindsay Graham’s death being investigated, Trump fires Election Assistance Commission members ahead of midterms, Black Folks Business™, man threatens police over his dogs, man kidnaps woman and takes her to Olive Garden, man uses penis to start a fire and sword ratchetness. Patreon: https://www.patreon.com/theblackguywhotips Twitter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@rodimusprime⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@SayDatAgain⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@TBGWT⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@TheBlackGuyWhoTips⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Email: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠theblackguywhotips@gmail.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Blog: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.theblackguywhotips.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Teepublic Store⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠- https://the-black-guy-who-tips-podcast.dashery.com/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Amazon Wishlist⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – https://www.amazon.com/hz/wishlist/ls/1PDD9JUQUNVY5?ref_=wl_share ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Crowdcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ – https://www.crowdcast.io/theblackguywhotips Voicemail: ‪(980) 500-9034Go Premium: https://www.theblackguywhotips.com/premium/See omnystudio.com/listener for privacy information.

Apple is suing OpenAI for allegedly stealing trade secrets, sparking a heated debate about AI, hardware ambitions, and Silicon Valley's shifting alliances. Leo, Wesley, Lou, and Patrick tackle what Apple's legal gambit could mean for OpenAI's IPO and the future of AI development. Apple Sues OpenAI for Trade Secret Theft in Blockbuster Case Apple's OpenAI lawsuit highlights broader tensions Microsoft says the world is changing faster than it can keep up as it guts commercial, Xbox teams Claude Fable 5 promotional access Meta says four states want $1.4 trillion in penalties at August youth-safety trial Meta Removes A.I. Feature on Instagram After Days of Backlash Meta tests 'super sensing' AI glasses that can capture every moment Meta Ordered by E.U. to Alter 'Addictive Design' of Instagram and Facebook The backlash against Sony ditching PlayStation discs is not slowing down Colibrì proof-of-concept gains frontier-level 1.5-TB AI model — novel approach runs on only 25GB of RAM and shows promise for local AI setups Waymo called the cops on teen riders, raising privacy concerns Waymo says some of its robotaxis ran out of power during San Francisco's July 4 gridlock and had to be towed Zombie 'who owns Unix?' lawsuit comes alive again Copy That Floppy! - Copy That Floppy! Host: Leo Laporte Guests: Wesley Faulkner, Louis Maresca, and Patrick Beja Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech 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 joindeleteme.com/twit-biz NetSuite.AI/TWIT zscaler.com/security bitwarden.com/twit ZipRecruiter.com/twit

Geoff Woo is the co-founder and managing partner of Anti Fund and a co-founder of Ketone-IQ and Archive. In this conversation, we break down choke points and information asymmetry — how smart money hunts for bottlenecks in AI, semiconductors, tungsten, and power. We also cover defense tech, humanoid robots, biohacking, Trump's aura in the Oval Office, and where bitcoin fits into Geoff's portfolio after 13 years of holding.======================Need liquidity without selling your crypto? Take out a Figure Crypto-Backed Loan, allowing you to borrow against your BTC, ETH, or SOL with 12-month terms, 8.91% interest rates, and no prepayment penalties. Or check out Democratized Prime (https://figuremarkets.co/pomp) and earn ~9% APY on real world assets, paid hourly. Unlock your crypto's potential today at Figure! https://figuremarkets.co/pomp Figure Lending LLC dba Figure (NMLS 1717824). Loans subject to approval. Crypto collateral may be liquidated. Terms apply - see full disclosures at figure.com/disclosures/======================This episode is brought to you by mogul ( https://www.mogul.club/pomp ). Deloitte estimates that $4 trillion of real estate will move onto the blockchain over the next decade. Through tokenized residential real estate, mogul gives investors access to professionally managed properties with targeted yields, monthly rent payouts, and potential tax benefits — all without the headaches of being a landlord. Learn more and claim a special offer at https://www.mogul.club/pomp See important disclosures at disclaimer.mogul.club.======================Arch Public is an agentic trading platform that automates the buying and selling of your preferred crypto strategies. Sign up today at https://www.archpublic.com and start your automated trading strategy for free. No catch. No hidden fees. Just smarter trading.======================0:00 - Intro1:00 - Why VCs are hunting for choke points in every industry4:45 - Can OpenAI & Anthropic crush every AI startup?13:40 - How Geoff uses AI daily & the tungsten choke point17:43 - Investing across public & private markets25:48 - The memory trade, CapEx & the power/fusion bet33:07 - How top investors like Peter Thiel play every trend at once35:03 - Inside Anti Fund's defense thesis39:50 - AI, robots & the ethics of force45:15 - The Waymo & teenagers story52:18 - Facial recognition & the end of privacy54:44 - Neuralink vs ultrasound brain-computer interfaces57:05 - Biohacking, sleep & the future of longevity1:06:33 - Gambling, hustle culture & internet fame1:22:20 - Geoff's honest take on bitcoin1:26:19 - Where to find Anti Fund

Thousands of people thought a movie set was a giant homeless encampment. Should we be expecting more movies to film in the city thanks to Mayor Lurie? Vinnie isn't digging the weird weather. Waymo is dealing with teenaged youth - just like the rest of us. Harrison Ford is kinda jacked at 84, but is he still a heart throb? Let's share our first celebrity crushes!

Hour 1: Happy Monday! Nothing at all confusing is going on here! Let's get to know “other” Sarah. Seattle Sarah? Nickname ideas are welcome. What's the best baseball stadium in the country? Taylor Swift and Travis Kelce got married! Have they made it to their honeymoon yet? Actor Sam Neil has passed away unexpectedly. The World Cup is getting fun! Lunchtime games all week for those in the Bay. Hour 2: JK Simmons and Tom Holland have never met. Is that weird? Considering they're in multiple movies together… is that weird? The live action ‘Moana' was #1 this weekend at the box office, but was it still a bomb? Vinnie learned how to use AI this weekend, and he's telling us all about it. Beyonce surprises a crowd at Jay-Z's show. It was a full family affair with Blue Ivy on piano. Then, Jay-Z's Sunday night show was delayed hours because of security concerns. Here's what we know. Hour 3: Thousands of people thought a movie set was a giant homeless encampment. Should we be expecting more movies to film in the city thanks to Mayor Lurie? Vinnie isn't digging the weird weather. Waymo is dealing with teenaged youth - just like the rest of us. Harrison Ford is kinda jacked at 84, but is he still a heart throb? Let's share our first celebrity crushes! Hour 4: The Grateful Dead is alive and well - here's what's next for the community in San Francisco. AKA free shows this fall! Americans reach a new level of delusion: 1 in 4 people think they could score a world cup goal. Vinnie has an update for us on his sweets. Do Taylor and Travis have a new family member? The Strokes have major beef with Jay-Z - thanks to Sarah!

This Week In Startups is made possible by: Quo https://quo.com/TWiST PayPal Open https://paypalopen.com Northwest Registered Agent https://northwestregisteredagent.com/twist Today's show: *Jason spent $11 building out PodMeme, an AI tool that tracks down the best segments from top podcasts about a specific topic, then stitches them together into a single stream. His post laying out how he did it, featuring a simple screenshot of the product, got all the way to 1.1M views in just a few days. It's a simple fact: builders love to see what other people are building, and growing your new project "in public," sharing your journey on social media, is a great way to develop buzz around your product before it even exists. Today's guest Thibault "Tibo" Louis-Lucas walks us through how he grew products like Tweet Hunter and Taplio on his social media account, using social media buzz and a focus on tools for creators to very quickly expand to over $1M ARR. PLUS why Apple would only sue OpenAI if they knew they had them dead to rights… why Uber and Waymo are fighting over DC robotaxis… Jason's response to the public backlash against surveillance startup Flock Safety… and the guys remember iconic New Zealand actor Sam Neill. Guest: Tibo Louis-Lucas on X: https://x.com/tibo_maker Revid.ai: https://www.revid.ai/ Tweet Hunter: https://tweethunter.io/ Taplio: https://taplio.com/ Relevant Links: Lemlist: https://www.lemlist.com/ GRIN influencer marketing: https://grin.co/ TechCrunch: "Apple Sues OpenAI": https://techcrunch.com/2026/07/10/apple-sues-openai-over-alleged-trade-secret-theft/ We Must Act Now statement: https://www.wemustactnow.ai/ TechCrunch: "Uber's Robotaxi Lobbying Effort": https://techcrunch.com/2026/07/13/ubers-robotaxi-lobbying-effort-has-put-it-on-a-collision-course-with-waymo/ DC Autonomous Vehicle Deployment Authorization Amendment of 2026: https://www.billtrack50.com/billdetail/2003462 DoorDash: Meet Dot: https://about.doordash.com/en-us/dot Flock Safety: https://www.flocksafety.com/ DeFlock: https://deflock.org/ Gigazine: Flock accuses Deflock of being a "terrorist org": https://gigazine.net/gsc_news/en/20260209-flock-ceo-deflock/#gsc.tab=0 Unifi AI Security Systems: https://ui.com/physical-security Jason's PodMeme post: https://x.com/Jason/status/2076231055443440105 Jason responds to Justine Bateman: https://x.com/Jason/status/2076326740050206959 NYT Sam Neill obituary: https://www.nytimes.com/2026/07/13/movies/sam-neill-dead.html "Possession" trailer: https://www.youtube.com/watch?v=aLXW-oVbTxE FanEdit: https://fanedit.org/forums/news-publisher/ "Manhunter" trailer: https://www.youtube.com/watch?v=cLqHlg2fAnE HBO "The Man Will Burn" trailer: https://www.youtube.com/watch?v=kRhUYPtp6Ao Timestamps: 0:00 There's no air conditioning in Paris 7:27 Tibo Maker's "ship 1 product a week" challenge 9:24 The power of building products in public 10:59 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free at https://quo.com/TWiST 12:04 Excitement for JCal's "PodMeme" set-up 15:40 Compounding an audience and enlisting influencers 19:13 Your follower count is not important any more 20:59 PayPal - Built for payments, growth, and agentic. Paypal Open, built for all business. Visit https://paypalopen.com to get started 22:28 How Tibo got banned on LinkedIn twice 28:48 Apple sues OpenAI 30:59 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at https://northwestregisteredagent.com/twist 38:44 How OpenAI should have handled the New York Times 45:10 DC's new robotaxi bill 52:06 Managing the AV and delivery-bot transition 53:23 Economists warn of AI job displacement 1:07:00 How Jason would fix Flock's messaging 1:17:26 Remembering Sam Neill 1:23:05 Lon's Dream AI edit 1:26:35 HBO's Burning Man docuseries   Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com  

Apple is suing OpenAI for allegedly stealing trade secrets, sparking a heated debate about AI, hardware ambitions, and Silicon Valley's shifting alliances. Leo, Wesley, Lou, and Patrick tackle what Apple's legal gambit could mean for OpenAI's IPO and the future of AI development. Apple Sues OpenAI for Trade Secret Theft in Blockbuster Case Apple's OpenAI lawsuit highlights broader tensions Microsoft says the world is changing faster than it can keep up as it guts commercial, Xbox teams Claude Fable 5 promotional access Meta says four states want $1.4 trillion in penalties at August youth-safety trial Meta Removes A.I. Feature on Instagram After Days of Backlash Meta tests 'super sensing' AI glasses that can capture every moment Meta Ordered by E.U. to Alter 'Addictive Design' of Instagram and Facebook The backlash against Sony ditching PlayStation discs is not slowing down Colibrì proof-of-concept gains frontier-level 1.5-TB AI model — novel approach runs on only 25GB of RAM and shows promise for local AI setups Waymo called the cops on teen riders, raising privacy concerns Waymo says some of its robotaxis ran out of power during San Francisco's July 4 gridlock and had to be towed Zombie 'who owns Unix?' lawsuit comes alive again Copy That Floppy! - Copy That Floppy! Host: Leo Laporte Guests: Wesley Faulkner, Louis Maresca, and Patrick Beja Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech 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 joindeleteme.com/twit-biz NetSuite.AI/TWIT zscaler.com/security bitwarden.com/twit ZipRecruiter.com/twit

Apple is suing OpenAI for allegedly stealing trade secrets, sparking a heated debate about AI, hardware ambitions, and Silicon Valley's shifting alliances. Leo, Wesley, Lou, and Patrick tackle what Apple's legal gambit could mean for OpenAI's IPO and the future of AI development. Apple Sues OpenAI for Trade Secret Theft in Blockbuster Case Apple's OpenAI lawsuit highlights broader tensions Microsoft says the world is changing faster than it can keep up as it guts commercial, Xbox teams Claude Fable 5 promotional access Meta says four states want $1.4 trillion in penalties at August youth-safety trial Meta Removes A.I. Feature on Instagram After Days of Backlash Meta tests 'super sensing' AI glasses that can capture every moment Meta Ordered by E.U. to Alter 'Addictive Design' of Instagram and Facebook The backlash against Sony ditching PlayStation discs is not slowing down Colibrì proof-of-concept gains frontier-level 1.5-TB AI model — novel approach runs on only 25GB of RAM and shows promise for local AI setups Waymo called the cops on teen riders, raising privacy concerns Waymo says some of its robotaxis ran out of power during San Francisco's July 4 gridlock and had to be towed Zombie 'who owns Unix?' lawsuit comes alive again Copy That Floppy! - Copy That Floppy! Host: Leo Laporte Guests: Wesley Faulkner, Louis Maresca, and Patrick Beja Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech 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 joindeleteme.com/twit-biz NetSuite.AI/TWIT zscaler.com/security bitwarden.com/twit ZipRecruiter.com/twit

Apple is suing OpenAI for allegedly stealing trade secrets, sparking a heated debate about AI, hardware ambitions, and Silicon Valley's shifting alliances. Leo, Wesley, Lou, and Patrick tackle what Apple's legal gambit could mean for OpenAI's IPO and the future of AI development. Apple Sues OpenAI for Trade Secret Theft in Blockbuster Case Apple's OpenAI lawsuit highlights broader tensions Microsoft says the world is changing faster than it can keep up as it guts commercial, Xbox teams Claude Fable 5 promotional access Meta says four states want $1.4 trillion in penalties at August youth-safety trial Meta Removes A.I. Feature on Instagram After Days of Backlash Meta tests 'super sensing' AI glasses that can capture every moment Meta Ordered by E.U. to Alter 'Addictive Design' of Instagram and Facebook The backlash against Sony ditching PlayStation discs is not slowing down Colibrì proof-of-concept gains frontier-level 1.5-TB AI model — novel approach runs on only 25GB of RAM and shows promise for local AI setups Waymo called the cops on teen riders, raising privacy concerns Waymo says some of its robotaxis ran out of power during San Francisco's July 4 gridlock and had to be towed Zombie 'who owns Unix?' lawsuit comes alive again Copy That Floppy! - Copy That Floppy! Host: Leo Laporte Guests: Wesley Faulkner, Louis Maresca, and Patrick Beja Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech 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 joindeleteme.com/twit-biz NetSuite.AI/TWIT zscaler.com/security bitwarden.com/twit ZipRecruiter.com/twit

Love Island USA has defied every negative trend in TV… Thanks to “The Campfire Effect.”Waymo snitched on teens for drinking in the back seat… Because the car's getting camera-fied.Zuck's latest AI move for Instagram… is turning your photos into AI ads, opting you in by default (and not paying you).Plus, the hottest new investment you can make… is old Ikea furniture: $300 today, $3K tomorrow.$GOOG $META $IKEAGrab your Tickets to the IPO Tour: Our In-Person OfferingSan Francisco 9/23: https://www.ticketmaster.com/event/1C0064AFB5F688BDBoston 10/14: https://tickets.citywinery.com/event/tboy-the-ipo-tour-in-person-offering-8cdhupSeattle 11/4 (21+): https://www.axs.com/events/1446394/the-best-one-yet-ticketsNEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.

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

Kevin Clancy, better known as KFC, is one of the original voices of Barstool Sports and former host of KFC Radio. In this conversation, we break down how technology and AI are quietly reshaping everyday life — from self-driving cars, surveillance camera, Neuralink, humanoid robots, and AI catching medical mistakes doctors missed. We also get into the affordability crisis facing younger generations, the wild early days of Barstool, and why scarce assets like bitcoin and gold still matter in a world of abundance.=======================This episode is brought to you by TikTok for Business. If you run a company, your next wave of customers may already be on TikTok. With more than 200 million monthly active users in the U.S. and 51% unique reach, TikTok gives brands access to audiences they can't reach anywhere else. Learn how to turn that reach into growth at TikTok for Business ( https://anthonypompliano.splashthat.com/ )=======================Bitget is the world's largest Universal Exchange (UEX), serving over 125 million users with access to over 2M+ crypto tokens, and TradFi markets. Bitget's Stocks 2.0 brings 500 major equities and ETFs (like Tesla and NVIDIA) directly to your portfolio. Enjoy 1:1 mapping, deep liquidity, and USDT dividend payouts with ultra-low 0.04% fees. Upgrade your portfolio on Bitget.com today!=======================Arch Public is an agentic trading platform that automates the buying and selling of your preferred crypto strategies. Sign up today at https://www.archpublic.com and start your automated trading strategy for free. No catch. No hidden fees. Just smarter trading.=======================0:00 - Intro0:59 - Waymo "arrests" teens: the self-driving surveillance case5:03 - Flock cameras, Ring cameras & the rise of constant surveillance12:07 - Youth sports & the money behind it19:10 - Body cams, cop shootings & the truth technology reveals23:49 - The affordability crisis: housing, salaries & the American dream33:56 - Kevin's path from Deloitte to Barstool36:50 - Algorithms, authenticity & the death of discovery in podcasting45:00 - AI catching what doctors missed & the rise of humanoid robots53:08 - Neuralink, brain implants & joining the hive mind1:00:46 - Psychedelics, ignorance as bliss & wanting to unplug1:04:21 - The 2022 crash & envying the simple life1:08:16 - Barstool's origin story1:14:42 - Private equity, scarcity & the bitcoin "crazy uncle portfolio"

Episode 1993 - brought to you by our incredible sponsors: Ultra Pouches - Don't sleep on @ultrapouches. New customers get 15% Off with code HARDFACTOR at takeultra.com!  Better Help - Don't let stigma stand in the way of support. Start therapy with BetterHelp. Sign up and get 10% off at BetterHelp.com/HARDFACTOR. 00:00:00 Timestamps 00:00:43 NBA Jam riffing 00:08:34 Graham Platner and the condoms 00:31:27 Ford Fires Veteran Truck Builder Over Alleged Theft of One (1) Breakroom Cookie 00:39:46 Waymo turns bad teens into the police For more head over to patreon.com/hardfactor for weekly bonus episodes and most importantly HAGFD! Learn more about your ad choices. Visit megaphone.fm/adchoices