Podcasts about digital markets act

Plus: BYD's overseas push drives quarterly profit growth. And Google will change how it ranks certain websites in most of Europe to appease antitrust regulators. Julie Chang hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The EU just fined Google €890M for making it hard to steer users to cheaper web stores — another crack in the 30% wall, and genuinely good news for every developer. That's the lead of a quieter, summer-holiday news week, with Felix flying solo while Matej and Jakub are at ChinaJoy.Felix Braberg walks two stories and a charts tour. First, the European Commission fined Google €890M (split €460M + €430M) under the Digital Markets Act for antitrust practices — preventing developers from freely informing users about cheaper offers and steering them to web stores or third-party channels. Google has 60 days to comply or face periodic penalties of up to 5% of worldwide turnover (~$403B), and it's another blow in the slow unwinding of the 30% app-store tax that companies like FastSpring exist to route around. Second, a Seeking Alpha analysis argues the market keeps underestimating AppLovin: the stock came under pressure in 2026 (swept up in the "SaaS apocalypse" sell-off after the CloudX agentic-buying launch), but the fundamentals are strong, the gaming runway is bigger than assumed, and as the dominant mediation player (AppLovin Max), it holds a structural advantage. Then the US charts: Smash Fest (Flow Games, Turkey) is now #1 in free downloads — beating Roblox — followed by Meow Doku and Vita Mahjong (same studio), with the standout story being that a copycat of Smash Fest (Royal Smash by Cypher Games) has itself cracked the top six out of ~70 clones. Plus Level Devil sold and scaling under new ownership, EA Sports FC still strong post-World Cup, and Turkey vs China duking it out for chart dominance.The through-line of a quiet week: the 30% tax keeps cracking, AppLovin keeps winning, and the copycat economy is faster and more brutal than ever.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⏱️ TIMESTAMPS00:00 Solo news week — Matej and Jakub at ChinaJoy00:40 Google fined €890M under the Digital Markets Act04:00 Why it's another crack in the 30% wall05:00 AppLovin: why the market keeps underestimating it07:30 US charts — Smash Fest beats Roblox08:30 The copycat that cracked the top six10:00 Level Devil sold, EA Sports FC, and Turkey vs China---------------------------------------This is no BS gaming podcast 2.5 gamers session. Sharing actionable insights, dropping knowledge from our day-to-day User Acquisition, Game Design, and Ad monetization jobs. We are definitely not discussing the latest industry news, but having so much fun! Let's not forget this is a 4 a.m. conference discussion vibe, so let's not take it too seriously.Panelists: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jakub Remia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠r,⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Felix Braberg, Matej Lancaric⁠Join our slack channel here: https://join.slack.com/t/two-and-half-gamers/shared_invite/zt-3bckldvr8-8PXvzciMWdheOzED9hq0SA---------------------------------------Matej LancaricUser Acquisition & Creatives Consultant⁠https://lancaric.meFelix BrabergAd monetization consultant⁠https://www.felixbraberg.comJakub RemiarGame design consultant⁠https://www.linkedin.com/in/jakubremiar---------------------------------------Please share the podcast with your industry friends, dogs & cats. Especially cats! They love it!Hit the Subscribe button on YouTube, Spotify, and Apple!Please share feedback and comments - matej@lancaric.me---------------------------------------If you are interested in getting UA tips every week on Monday, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠lancaric.substack.com⁠⁠⁠⁠⁠⁠ & sign up for the Brutally Honest newsletter by Matej LancaricDo you have UA questions nobody can answer? Ask ⁠⁠⁠⁠⁠⁠⁠⁠Matej AI⁠⁠⁠⁠⁠⁠ - the First UA AI in the gaming industry! https://lancaric.me/matej-ai

Fri, 31 Jul 2026 03:00:00 GMT http://relay.fm/material/578 http://relay.fm/material/578 Andy Ihnatko and Florence Ion Google made a ton of money last quarter on AI, which is good, because now it owes the EU $1 Billion for violating the Digital Markets Act. Google made a ton of money last quarter on AI, which is good, because now it owes the EU $1 Billion for violating the Digital Markets Act. clean 3528 Google made a ton of money last quarter on AI, which is good, because now it owes the EU $1 Billion for violating the Digital Markets Act. Links and Show Notes: Full transcript of Alphabet earnings call Google hit with $1 billion EU fine, in 'constructive' talks to avoid more penalties Trump threatens new tariffs against EU over Google fine Our expanded partnership with NBCUniversal: Redefining the modern entertainment subscription Support Mate

Fri, 31 Jul 2026 03:00:00 GMT http://relay.fm/material/578 http://relay.fm/material/578 Flim Flam 578 Andy Ihnatko and Florence Ion Google made a ton of money last quarter on AI, which is good, because now it owes the EU $1 Billion for violating the Digital Markets Act. Google made a ton of money last quarter on AI, which is good, because now it owes the EU $1 Billion for violating the Digital Markets Act. clean 3528 Google made a ton of money last quarter on AI, which is good, because now it owes the EU $1 Billion for violating the Digital Markets Act. Links and Show Notes: Full transcript of Alphabet earnings call Google hit with $1 billion EU fine, in 'constructive' talks to avoid more penalties Trump threatens new tariffs against EU over Google fine Our expanded partnership with NBCUniversal: Redefining the modern entertainment subscription Support Material with

Union européenne : étiquetage obligatoire des contenus générés par IA.Pétition : plus de 1 000 cadres tech demandent de ralentir les modèles avancés.Google : 890 millions d'euros d'amende au titre du Digital Markets Act.OpenAI : 750 milliards de dollars d'ici 2030, objectifs publicitaires ratés de 90 %.Microsoft loue les data centers de Mistral AI : accord signé le 21 juillet 2026.Réseaux sociaux : 55 % des internautes publient moins qu'il y a cinq ans.

Sony schrapt het schijfje, Xbox schrapt banen en een nieuwe console kan richting duizend euro gaan. Wie kan gaming straks nog betalen? Games maken wordt duurder, consoles worden niet goedkoper en spelers blijven hangen op een prijsgrens van ongeveer 80 euro. Tweakers-redacteur Daan van Monsjou legt uit waarom die rekensom steeds minder goed uitkomt. Sony stopt vanaf januari 2028 met schijfjes voor nieuwe PlayStation-games en stuurt kopers richting digitale licenties, terwijl fysieke spellen volgens Daans prijsvergelijking meestal goedkoper zijn. Een korting in de PlayStation Store kan bovendien verdwijnen, waarna zelfs een jarenoude game weer 80 euro kost. Aan de andere kant snijdt Xbox na een kostbare overnamegolf in studio’s en personeel, terwijl aan tafel de vraag opkomt of Game Pass die investeringen ooit kan terugverdienen. Met Randal, Jurian en Ruurd bespreekt Daan wie de rekening betaalt, of de EU moet ingrijpen en waarom kleinere games juist ruimte krijgen tussen het miljoenengeweld. Over Daan van Monsjou Daan van Monsjou is nieuwsredacteur bij Tweakers, waar hij sinds 2019 nieuws- en achtergrondverhalen schrijft. Zijn voorliefde ligt bij computerhardware en de chipsector; eerder onderzocht hij de chipambities van de EU en interviewde hij ASML-cto Martin van den Brink. Voor deze aflevering dook hij in Sony’s afscheid van fysieke games en vergeleek hij de prijzen van digitale en fysieke PlayStation-games. LinkedIn: Daan van Monsjou Website: daanvanmonsjou.nl In deze aflevering 0:00:00 Cold open: schijfjes verdwijnen en consoles laten op zich wachten0:00:23 Intro: Daan is terug en Tech45 kreeg een verbouwing0:05:45 Waarom de game-industrie op haar grondvesten schudt0:10:41 Sony stopt in 2028 met nieuwe games op schijf0:14:52 Van winkelmarge naar Sony’s 30 procent0:20:05 Waarom games tegelijk te duur en te goedkoop zijn0:32:27 De volgende generatie: Sony op de troon, Xbox in de knel0:46:51 Miljoenenproducties, indiegames en de verdwenen middenklasse0:53:10 Luistervraag van Joris: wat betekent de Chinese invloed van Tencent?1:01:32 Luistervraag van Joost: werken bij Tweakers en pijnlijke kritiek Genoemd in deze aflevering GTA VI was het begin van het einde, Daan over Sony’s afscheid van fysieke games Prijsdata van fysieke en digitale PlayStation-games, fysieke spellen zijn vaak goedkoper PlayStation stopt met fysieke schijfproductie, Sony’s officiële aankondiging voor januari 2028 Project Helix, officiële toelichting op de volgende Xbox-console Digital Markets Act, Europese regels voor digitale poortwachters Steam-terugbetalingen, voorwaarden voor geld terug bij Steam Tech45, wekelijkse techpodcast met Ruurd Sanders Tips van de tafel Daan van Monsjou: Vergelijk de PlayStation Store met fysieke webwinkels; schijfjes zijn voorlopig meestal goedkoper en je kunt ze later doorverkopen. Ruurd Sanders: Test een Steam-game direct na aankoop; binnen veertien dagen en met minder dan twee uur speeltijd kun je meestal geld terugvragen. Randal Peelen: Loop gerust een consolegeneratie achter; oudere grote spellen zijn in een uitverkoop goedkoop en draaien prima op een Steam Deck.See omnystudio.com/listener for privacy information.

In Folge 321 sprechen die ApfelNerds über Apple Care One, welches jetzt in 4 weiteren Ländern verfügbar ist, Apple & Ford kündigen die Integration von Apple Maps in die System-Software von Ford an, der Apple Park Visitor Center ist vorübergehend geschlossen, Google erhält Strafe im Rahmen des Digital Markets Acts, die EU beschließt neue Ausnahmen für die Batterieverordnung, Sascha hat Versandsachen-Tracking und Daniel Custom Passes im Wallet getestet, es gibt Details zur ominösen OpenAI-Hardware, Mark Gurman liefert eine neue Hardware-Roadmap, Apple plant ein günstigeres Display um die Speicher-Preise aufzufangen, es gibt neue Details zu den Smart Glasses, in Kürze den Start von Apple Upgrade und es gibt Updates.

The U.S. House passes a $1.15 trillion defense bill, Yemen's Houthis claim attacks on two Saudi oil tankers, the 33rd ASEAN Regional Forum is held in Manila, thousands of Jewish visitors enter the Al-Aqsa Mosque compound, Trump hails Nigeria's efforts to address violence against Christian communities, Google is fined €890 million for breaching the EU's Digital Markets Act, MI5 and the Police Service of Northern Ireland are ordered to pay damages for spying on a journalist, a study links weight loss drugs to hair loss risk, new research links declining pollution to Europe's heatwaves, and U.S. lawmakers propose an AI kill switch. Sources: Verity.News

Cosa è accaduto durante i test dei nuovi modelli di GenAI di Open AI? È veramente un episodio sconcertante e “senza precedenti” come sostiene la società? Cosa sappiamo? Enrico Pagliarini ne parla con Corrado Giustozzi, esperto di cybersecurity e partner di Rexilience.Migliaia fra scienziati, economisti, ricercatori ed esperti di AI, hanno firmato un appello rivolto a leader politici e del settore tecnologico ad agire il più presto possibile al fine di creare i meccanismi di controllo e le istituzioni necessarie per uno sviluppo sano dell’Intelligenza Artificiale. Ne parliamo con Luca Vendraminelli, ricercatore allo Stanford Digital Economy Lab e allo Stanford Institute for Human-Centered AI presso l’Università di Stanford in California.La Commissione Europea ha multato Google per due violazioni del Digital Markets Act dopo aver imposto, la settimana scorsa, una serie di rimedi nell’ambito dei motori di ricerca. Simone Righini, esperto di search marketing spiega quali dati dovrà condividere con i concorrenti, perché e con quali conseguenze.Sempre a livello europeo fa discutere la decisione di reintrodurre la possibilità per le grandi piattaforme internet di individuare e rimuovere materiale pedopornografico online in deroga alle norme sulla privacy. Una misura conosciuta come chat control. Ne parliamo con Paolo Dal Checco, esperto di cybersecurity e informatica forense, cercando di capire anche come proteggere le nostre comunicazioni.

Rupprecht Podszun und Justus Haucap diskutieren die wichtigsten Entwicklungen der vergangenen Wochen in Kartellrecht und Wettbewerbspolitik. Im Mittelpunkt stehen der Regierungsentwurf der 12. GWB-Novelle, zwei wegweisende Urteile des Europäischen Gerichtshofs zu Google Android und den FIFA-Spielervermittlern sowie die Frage, welche Bedeutung das Grundsatzurteil Meca-Medina heute noch hat.Außerdem geht es um die neuen Spezifizierungsbeschlüsse zum Digital Markets Act, die Interoperabilität und den Zugang zu Google-Suchdaten konkretisieren. Warum sind gerade diese Themen entscheidend für den Wettbewerb im KI-Zeitalter? Und weshalb fordert Justus Haucap eine konsequente Durchsetzung des DMA?Daneben sprechen die beiden Professoren über KI-Agenten als künftige Einkäufer, aktuelle Ermittlungen des Bundeskartellamts wegen vertikaler Preisbindungen in der Reifenbranche und den geplanten Markteintritt des italienischen Hochgeschwindigkeitsanbieters Italo. Bringt mehr Wettbewerb auf der Schiene Vorteile für die Fahrgäste – oder hat die Deutsche Bahn mit ihrer Kritik recht?Weitere InformationenMonopolkommission, Stellungnahme zum Markteintritt von ItaloHaucap, J., Ch. Miele, V. Pausder, J. Reck, Die EU-Strafe gegen Google muss kommen, Offener Brief bei "The Pioneer".

European regulators recently issued a historic $1 billion fine against Google for multiple violations of the Digital Markets Act. The investigation concluded that the tech giant engaged in self-preferencing by prioritizing its own shopping and travel services within search results over those of its competitors. Additionally, officials found that Google utilized anti-steering practices on its app store to prevent developers from directing users toward more affordable payment options. While the company intends to appeal the decision and warns of potential product degradation, the European Commission has mandated a 60-day deadline for Google to implement fair, non-discriminatory practices. This landmark ruling represents the largest penalty yet under new digital laws designed to ensure a level playing field for online innovation and consumer choice.

The European Commission has fined US tech giant Google 890 million euros, or about 1.02 billion US dollars, for violating the EU's Digital Markets Act by favoring its own services and restricting app developers.

An OpenAI model broke free of its test environment, found an exploit in a piece of third party server software, and commenced a series of actions that led to it hacking HuggingFace's data processing systems. OpenAI didn't detect the breach of HuggingFace for several days even though the test it was running was to "... use complex attack paths..." to test how well the AI could exploit a computer system. HuggingFace is reviewing and preparing its own version of events. In other news, a federal judge has approved a 1.5Billion copyright settlement between Anthropic and thousands of authors whose work was used without permission to train the Claude chatbot. The settlement, which has been rejected by a smaller group of authors gives creators about $3000 per title copied. Though it is the largest known copyright recovery in legal history, it is also a paltry sum to essentially sign away rights to an authored book. Google is having a terrible week in court. Its lawsuit against SerpAPI over scraping search results has been dismissed, the EU dinged it for a Billion EU under the Digital Markets Act for anti-competitive practices. Meanwhile, more large publishers are reconsidering the value of Google within their Internet economies. Many are threatening to block Google search entirely and replace it with content licensing deals to train other AIs. It was a busy news week and this is a news heavy edition.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Aktien-Analyst Jürgen Pieper erklärt, warum er Musks Pläne für viel Fantasie hält. Und: Das macht die Digitalgesetz-Strafe gegen Google so riskant.

In today's Digest, we discuss Stagwell bringing ad inventory curation in-house with a new AI platform, the EU forcing Google to open Android AI and Search to rivals under the Digital Markets Act, and Chinese AI lab Moonshot narrowing the gap with leading US frontier models. 

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

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

Episode 254: Microsoft Cuts 4,800 Jobs, Meta Faces a $1.4 Trillion Lawsuit, Apple Loses in Europe, and the iPhone Ultra NearsJay and Karl discuss another turbulent week across big tech, AI, gaming, and consumer hardware. Microsoft announces another round of layoffs that hits Xbox particularly hard, Meta finds itself fighting legal battles on multiple fronts, and Apple loses an important appeal over the App Store in Europe.We also look at Meta's continued investment in mixed reality hardware, fresh evidence that Nvidia's long-rumoured RTX 50 Super cards may finally be on the way, and the latest reports suggesting Apple's iPhone Ultra could launch in extremely limited numbers.Also available on:Apple Podcasts | YouTubeIn This EpisodeNewsMicrosoft cuts 4,800 jobs and shrinks Xbox in 'significant restructure'Microsoft announces another major restructuring, with significant impacts across Xbox and other divisions.Meta is facing $1.4 trillion in state lawsuits over social media addictionUS states continue legal action against Meta over the impact of its platforms on younger users.Disable autoplay and infinite scroll or risk massive fines, EU tells MetaEuropean regulators increase pressure on Meta to redesign key engagement features.Apple loses legal fight over its App Store 'gatekeeper' status in EuropeApple's appeal fails, meaning it remains subject to the EU's Digital Markets Act requirements.Meta reaffirms work on multiple next-generation headsetsMeta confirms several future VR and mixed reality devices remain in active development.RTX 5080 Super, RTX 5070 Ti Super and RTX 5070 Super appear in PSU calculatorNew evidence suggests Nvidia's refreshed RTX 50 Series GPUs could arrive sooner than expected.RumoursReport: iPhone Ultra to have incredibly limited availability at launch, may ship slightly laterApple's premium iPhone Ultra could be difficult to buy at launch if the latest reports prove accurate.Say hello:@WeeklyTechRant | @weeklytechrant.bs

The European Commission has mandated binding antitrust measures that require Google to grant access to essential Android system features for competing AI assistants and to share its extensive search data with rival search engines.This significant ruling, implemented under the Digital Markets Act (DMA) of the European Union, seeks to create a more equitable environment and prevent Google from exploiting its dominant Android ecosystem to monopolize the swiftly advancing artificial intelligence industry.Google is obligated to provide access to 11 specific system-level features for competing artificial intelligence models, such as OpenAI's ChatGPT and Anthropic's Claude.Competing AI agents must be permitted to achieve the same level of system integration as Google's own Gemini, which includes enabling comprehensive voice activation and the ability to perform background tasks, such as making restaurant reservations through third-party applications.Additionally, to dismantle Google's near-monopoly on data, the company is required to start sharing anonymized search data with qualifying rival search engines by January 2027.Noncompliance with these binding directives could lead to substantial fines of up to 10% of Alphabet's global annual revenue.In the meantime, Kent Walker, Google's President of Global Affairs, has strongly criticized the ruling. He expressed that compelling the company to disclose search metrics to "unfamiliar companies" poses significant privacy risks, data protection concerns, and cybersecurity threats to European citizens.EU Competition Commissioner Teresa Ribera defended the action, emphasizing that society is experiencing a significant digital transformation that necessitates robust legal protections for fairness and consumer choice.The vigorous implementation of the Digital Markets Act continues to provoke criticism from U.S. political leaders, who contend that European regulators are unjustly targeting and undermining American technology giants.

Google moet de zoekgegevens van zijn gebruikers gaan delen met concurrerende zoekmachines en AI-ontwikkelaars zoals OpenAI van de Europese Commissie. Doet het bedrijf dat niet, dan schendt het de Digital Markets Act. Niels Kooloos vertelt erover in deze Tech Update. De Digital Markets Act verplicht een bepaald aantal techbedrijven in Europa om een gelijk speelveld te behouden met hun platformen. Ook Google moet dat, met onder andere de zoekmachine. Als Google geen zoekgegevens van gebruikers deelt met de concurrentie, dan zou die volgens de Europese Commissie niet in staat zijn om volwaardige alternatieven voor Google Search te kunnen ontwikkelen. Ken Walker, de president van Global Affairs bij Google, schrijft in een blogpost dat het besluit van de Europese Commissie onredelijk is. Volgens Walker is het 'bijzonder zorgwekkend dat de persoonlijke zoekopdrachten van Europeanen zouden worden blootgesteld aan onbekende bedrijven'. Daarbij beweert hij dat de eis privacy, bedrijfsgeheimen en zelfs nationale veiligheid in gevaar kan brengen. De Europese Commissie stelt dat gedeelde zoekgegevens geanonimiseerd worden en in lijn zullen zijn met de AVG. ChatGPT en Claude moeten net zoveel op Android kunnen als Gemini Ook eist de Europese Commissie van Google dat concurrerende AI-chatbots evenveel op Android moeten kunnen als de chatbot van Google: Gemini. Gebruikers moeten chatbots zoals ChatGPT en Claude bijvoorbeeld met een eigen 'wake word' kunnen oproepen, zoals 'Hey Google' voor Gemini werkt. Ook moeten concurrerende chatbots evenveel toegang tot externe apps krijgen. Daarover zegt Walker dat chatbots van de concurrentie al voldoende toegang hebben op Android. Als die toegang uitgebreid zou worden, dan zouden er cyberdreigingen ontstaan volgens hem. Persbericht Europese Commissie over de bindende maatregelen voor Google Blogpost van Google over de gevolgen van de DMA voor privacy en veiligheid Over de maker: Niels Kooloos is dagelijks op BNR Nieuwsradio te horen over het laatste technieuws in de Tech Update. Hij interesseert zich vooral in cybercriminaliteit, privacy, social media en (computer)hardware. Hier en daar kan je Niels ook in All in the Game horen, waar hij graag vertelt over zijn favoriete games.See omnystudio.com/listener for privacy information.

Am 1. April 2026 sendete die ARD im Vorabendprogramm „Wissen vor Acht – Erde” einen Beitrag über KI und Klima. Tenor: Künstliche Intelligenz sei klimaschädlich, statt KI solle man lieber das eigene Gehirn benutzen. Es war kein Aprilscherz. Es wirkte aber wie einer. Der Beitrag wurde wiederholt und steht noch immer in der Mediathek. Während in Deutschland zur Hauptsendezeit die Klimabilanz von ChatGPT-Prompts debattiert wird, beziffert die St. Louis Fed den KI-Anteil am US-BIP-Wachstum 2025 auf 42 Prozent. Goldman Sachs prognostiziert Hyperscaler-Investitionen von 533 Milliarden Dollar für 2026. Die Internationale Energieagentur erwartet bis 2030 einen Stromverbrauchszuwachs in Rechenzentren von 250 Terawattstunden in den USA – und nur 45 Terawattstunden in der EU. Das Verhältnis: eins zu fünf. Der Internationale Währungsfonds rechnet vor, dass die Produktivitätsgewinne aus KI in Europa um mehr als 30 Prozent niedriger ausfallen werden – wegen Regulierung. Europa im Schneckentempo, mit roter Laterne und erhobenem Zeigefinger.Daniel Stelter spricht in dieser Folge mit Johannes Reck, Mitgründer und CEO von GetYourGuide. Reck war Mitglied der von Bundeswirtschaftsministerin Katherina Reiche eingesetzten KI-Kommission. Seine Diagnose: „Wir sind ein Stück weit digitale Kolonie.” Sein Plan: weniger Regulierung für Aufsteiger, härtere Durchsetzung des Digital Markets Act gegen die Marktbeherrscher, Mobilisierung von Kapital und natürlich niedrigere Energiekosten.Findet Deutschland den KI-Anschluss noch? Und was lehrt die Dampfmaschinen-Geschichte des 19. Jahrhunderts darüber, was passiert, wenn ein Land eine Schlüsseltechnologie verschläft?Hinweis ABSTURZ – So retten wir Deutschland: das neue Buch von Daniel Stelter. Jetzt überall, wo es Bücher gibt. Auch bestellbar bei Thalia, Amazon, geniallokal.HörerserviceAbschlussbericht Wettbewerb und KI der KI-Kommission eingesetzt vom Bundesministerium für Wirtschaft (April 2026): https://tinyurl.com/28sbnubs Papier Tracking the AI Contribution to GDP Growth der St. Louis Fed (Januar 2026): https://tinyurl.com/muwhys44 Papier Energy demand from AI der Internationalen Energie Agentur (IEA): https://tinyurl.com/ye2audct Ausblick How Will AI Affect the US Labor Market? von Goldman Sachs Global Investment Research: https://tinyurl.com/4apv3u5s Papier AI and Productivity in Europe des Internationalen Währungsfonds (April 2025): https://tinyurl.com/3s5at54s Papier From Steam Power to Artificial Intelligence der Rockwool Foundation Berlin: https://tinyurl.com/mrs4ybhb Beitrag Wie klimaschädlich ist Künstliche Intelligenz? in der ARD-Sendung „Wissen vor Acht — Erde”: https://tinyurl.com/yn2a5jed beyond the obvious – Neue Analysen, Kommentare und Einschätzungen zur Wirtschafts- und Finanzlage finden Sie unter think-bto.com.Newsletter – Den monatlichen bto-Newsletter abonnieren Sie hier.Redaktionskontakt – Wir freuen uns über Ihre Meinungen, Anregungen und Kritik unter podcast@think-bto.com.Handelsblatt – Ein bisschen mehr Luft im Sommer? Dann ist jetzt die perfekte Zeit, Ihrem Wissensvorsprung ein Upgrade zu geben – mit dem Handelsblatt. Das liefert Ihnen verlässliche Fakten, exklusive Hintergründe und eine klare Einordnung wirtschaftlicher Entwicklungen. Mit unserem Sommer-Special ist der Einstieg supereinfach: Sie erhalten jetzt 6 Wochen für nur 1 Euro vollen Zugriff auf alle digitalen Inhalte. Sichern Sie sich dieses besondere Angebot unter handelsblatt.com/sommer26 Werbepartner – Weitere Informationen zu den Angeboten unserer aktuellen Werbepartner finden Sie hier. Hosted on Acast. See acast.com/privacy for more information.

Plus: The European Union says Amazon and Microsoft's cloud services should be regulated under its Digital Markets Act. And BlackBerry boosted its 2027 fiscal outlook, thanks to expanding opportunities in AI. Danny Lewis hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

GTA 6, voluit Grand Theft Auto VI, is vanaf 25 juni al te bestellen, zo heeft gamebedrijf Rockstar bekendgemaakt. Deze zonder twijfel meest geanticipeerde game aller tijden komt volgens de meest recente aankondiging uit op 19 november 2026. Dat moet volgens marktonderzoek Newzoo de mondiale game-industrie helpen aan een omzet van zo'n 47 miljard dollar uit alleen al verkopen rond spelcomputers. Joe van Burik vertelt erover in deze Tech Update. Verder in deze Tech Update: Internationale game-industrie behaalde in 2025 voor het eerst meer dan tweehonderd miljard dollar omzet: 201,6 miljard om te precies te zijn Amazon en Microsoft kunnen harde bevindingen tegemoet zien volgende week vanuit een EU-onderzoek naar hun macht over de cloudmarkt, waardoor ze onder de Digital Markets Act zullen vallen en meer moeten toen tegen 'lock-in' See omnystudio.com/listener for privacy information.

Apple Intelligence au rabais en Europe : pourquoi ? • Web Summit Rio : gros plan sur la tech brésilienne • Anthropic bride ses modèles les plus sensibles • En France, Mistral AI contre les ayants droit • Le Canada veut limiter les réseaux sociaux aux moins de 16 ans • L'IA bouscule le droit, les médias et l'éducation • VivaTech se prépare à Paris.Avec Bruno Guglielminetti (Mon Carnet)Apple Intelligence : qui prive l'Europe du nouveau Siri ?Nous revenons sur la keynote Apple, marquée par l'arrivée annoncée d'iOS 27 et de nouvelles fonctions d'Apple Intelligence. Mais le vrai sujet, c'est l'absence de Siri AI en Europe : Apple accuse le Digital Markets Act, tandis que Bruxelles renvoie la balle à l'entreprise américaine. Derrière ce bras de fer, une réalité : des centaines de millions d'utilisateurs européens pris en otage. Zoom sur la tech brésilienne à l'occasion du Web Summit RioDepuis Copacabana, nous partons à la découverte du Web Summit Rio et d'un écosystème brésilien encore trop peu observé depuis l'Europe. Le Brésil apparaît comme un terrain passionnant pour parler souveraineté numérique, innovation locale et rapprochements possibles avec le Sud global. L'objectif : sortir du face-à-face habituel entre États-Unis, Europe et Asie.Anthropic : l'IA puissante, mais sous surveillanceNous revenons sur le sujet Claude Fable 5, présenté comme une version plus encadrée de Mythos 5, notamment sur les usages sensibles comme la cybersécurité ou la biologie. Les modèles d'IA les plus avancés ne sont plus seulement des produits technologiques : ils deviennent aussi des enjeux stratégiques, politiques et sécuritaires (EPISODE ENREGISTRÉ AVANT LE BLOCAGE DE FABLE POUR POUR LES NON AMERICAINS). Mistral AI face au droit d'auteurMistral AI dans la tourmente avec la loi sur le droit d'auteur de l'IA. Les médias et ayants droit dénoncent un pillage massif, tandis que Mistral craint d'être freiné face aux géants américains. Le débat oppose protection de la création et ambition de bâtir un champion européen de l'IA.Réseaux sociaux : le Canada veut protéger les jeunesLe Canada envisage d'interdire ou de limiter l'accès aux réseaux sociaux pour les moins de 16 ans. Bruno souligne les limites d'une telle mesure, déjà visibles dans d'autres pays : contournements, faux comptes et migration vers d'autres plateformes. Pour nous, la loi ne suffira pas sans un vrai travail d'éducation numérique.IA et justice : quand les hallucinations coûtent cherNous évoquons l'affaire d'avocats sanctionnés aux États-Unis après avoir déposé des documents contenant de fausses références juridiques générées par IA. L'épisode rappelle que ces outils peuvent aider les professionnels, mais qu'ils ne remplacent ni la vérification, ni la responsabilité humaine. Dans le droit, l'IA doit rester un assistant, pas une source aveuglément copiée.Médias et école : le faux débat du “sans IA”Nous discutons de la tentation de revendiquer des contenus “100 % humains”. Cette promesse nous semble trop simpliste, car l'IA peut aussi servir à corriger, traduire, comparer, entraîner ou donner du feedback sans remplacer l'humain. Le vrai sujet n'est pas d'interdire l'outil, mais de savoir comment on l'utilise.VivaTech à Paris : qui est l'invité vedette ? VivaTech 2026 aura lieu la semaine prochaine. Cette édition marque le 10ème anniversaire du salon parisien. L'événement s'annonce comme un moment fort pour la French Tech, avec de grands invités attendus et un contexte très marqué par l'IA. La semaine prochaine, le Debrief Transat se fera depuis Paris, en direct de l'écosystème tech français.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Apples große Entwicklerkonferenz WWDC ist geschlagen - und sie stand ganz im Zeichen von Siri AI. Liefert Apple endlich ab, was sie schon vor zwei Jahren versprochen haben? Das besprechen heute im Podcast sprechen Jakob Steinschaden, Mitgründer von eustella und Trending Topics, und Clemens Wasner, CEO von EnliteAI und Vorsitzender von AI Austria. Die Themen:

Apple zeigt auf ihrer Entwicklerkonferenz WWDC endlich die neue Siri, aber ausgerechnet in der EU soll sie vorerst nicht auf den Markt kommen. In dieser Episode klären wir, warum Apple den Digital Markets Act dafür verantwortlich macht, wie die EU das zurückweist und worum es beim Streit um Datenschutz, Interoperabilität und Marktmacht wirklich geht.Du magst unseren Podcast und willst uns finanziell unterstützen? Dann abonniere uns bei Steady: https://steady.page/de/silicon-weekly/about Unser Impressum findest du hier: https://silicon-weekly.de/impressum/

Apple heeft Siri AI onthuld tijdens hun WWDC-presentatie gisteravond, het centrale deel van het vernieuwde Apple Intelligence waarmee je onder meer berichten slim kunt doorzoeken of laten opstellen, en afbeeldingen aanpassen of doorzoeken. Maar al die functies komen voorlopig niet beschikbaar in EU-landen en er is ook geen indicatie wanneer dat wél gebeurt, volgens Apple door de Digital Markets Act die hier geldt. Joe van Burik vertelt erover in deze Tech Update. Verder in deze Tech Update: OpenAI heeft nu officieel de documenten ingediend om dit najaar naar de beurs te kunnen gaan, in navolging van SpaceX en Anthropic See omnystudio.com/listener for privacy information.

Hey hey, in dieser Folge diskutieren wir die neuesten Ankündigungen von Apple auf der WWDC, inklusive Systemoptimierungen, AI-Features und Designänderungen. Was denken wir über die ersten Einblicke, die uns Apple zu iOS 27, iPad OS 27, Mac OS 27, Vision OS 27 und weitere gegeben hat? Was denkt ihr darüber? Und nun viel Freude beim Zuhören und -sehen! PS: die Position, die wir ca. bei Minute 21 besprechen lautet: VP, OS Program Management - namentlich: Stacey Ford. PPS: die vorherige Podcast-Folge, auf die wir uns ca. bei Minute 6 beziehen, ist Folge 50. Kapitel: 00:00:00 Begrüßung 00:02:24 WWDC und die Eröffnungs-Keynote 00:05:14 Fokus auf Optimierungen statt neuen Features 00:10:03 Designanpassungen und Benutzerfreundlichkeit 00:15:07 Langfristige Unterstützung älterer Geräte 00:19:46 Integration und Systemoptimierung 00:24:36 Vision OS und neue Technologien 00:25:30 3D Icons und Designinnovationen 00:29:00 Apple Intelligence und Kinderschutz 00:31:20 Generative KI und Bildbearbeitung 00:37:06 AI in Apps und Automatisierung 00:49:51 Passwortmanagement und Sicherheitsinnovationen 00:51:23 Safari Erweiterungen und ihre Möglichkeiten 00:52:05 Kalender und Terminmanagement 00:53:14 Neue Funktionen in Nachrichten und Erinnerungen 00:54:24 Siri AI: Ein zweiter Versuch 00:56:15 Digital Markets Act und seine Herausforderungen 01:00:27 Apples Lösungsvorschläge und deren Ablehnung 01:02:11 Trusted System Agent und Datenschutz 01:05:08 Siri AI Einführung in der EU 01:10:47 Kindersicherheit und neue Funktionen 01:14:58 Kindersicherheit im digitalen Raum 01:22:09 Technologische Verantwortung und Altersverifikation 01:28:31 Reflexion über die WWDC und Tim Cooks Rolle

Apple Intelligence, a privacy-centric personal AI system integrated across Apple's device ecosystem. The technical documentation and press releases detail features such as Siri's enhanced contextual awareness, systemwide writing tools, and on-device image generation. While the rollout is moving forward in regions like the United States and India, it has been paused in the European Union due to regulatory conflicts with the Digital Markets Act. To address regional challenges, Apple has partnered with Baidu in China and is collaborating with Google to power advanced Siri functions via the Gemini model. Furthermore, the sources clarify that Apple unified its operating system version numbers to 26 to align with the 2026 calendar year.

Quad unveils a series of new initiatives after its foreign ministers' meeting in New Delhi, the U.S. launches new strikes on Iran, Netanyahu vows to 'crush' Hezbollah, former Scottish National Party Chief Peter Murrell pleads guilty to embezzlement, Trump completes his annual physical, a U.S. court blocks Alabama's Republican-drawn congressional map, the sentences of three U.K. teens convicted of rape are referred to the Court of Appeal, the EU reportedly prepares a record fine against Google under the Digital Markets Act, four people are killed in a train-school bus collision in Belgium, and Ferrari enters the EV market with a $640,000 electric supercar. Sources: Verity.News

Our guest in this show is known for crossing swords with the Trump administration on the regulation of big tech and, more recently, for actually coming under a US travel ban. Thierry Breton was the EU Commissioner for the Internal Market from 2019 to 2024, when he had a major role in driving forward the Digital Services Act and the Digital Markets Act. He and four other figures were hit with US travel bans at the end of last year, prompting Breton to denounce what he called "a wind of McCarthyism blowing again".

Verschillende streamingdiensten zoals Disney+ en Videoland willen dat de smart-tv-platforms van Google, Amazon en Samsung met de strengere regels van de Digital Markets Act te maken gaan krijgen. Nu kan namelijk geen gezonde en eerlijke concurrentie gegarandeerd worden, zegt de lobbyclub Association of Commercial Television and Video on Demand Services in Europe (ACT) waarin veel grote streamingsdiensten verenigd zijn. Rosanne Peters vertelt erover in deze Tech Update. Om hier aandacht voor te krijgen heeft de lobbyclub een brief gestuurd naar de verantwoordelijke EU-commissaris Teresa Ribera. De angst is dat grote techbedrijven steeds meer controle krijgen over de besturingssystemen van smart-tv's en spraakassistenten, waardoor ze een soort "poortwachters" rol krijgen. Ze kunnen gebruikers namelijk naar bepaalde content leiden en ergens van weghouden. Daarom is de hoop dat er uiteindelijk beter gecontroleerd zal worden om zo de concurrentie eerlijk te laten verlopen. Verder in deze Tech Update: Italiaanse markttoezichthouder geeft Trustpilot boete van 4 miljoen euro vanwege misleiding See omnystudio.com/listener for privacy information.

Dan Moren of SixColors joins Mikah Sargent this week on Tech News Weekly! Apple announced a whole new slew of products throughout the week, including the new MacBook Neo! A look into how Meta's Ray-Ban smart glasses collect data. And how Google's new proposed system for apps could change the App Store game. Dan and Mikah discuss the slew of new products Apple announced this week: the iPhone 17e, M4 iPad Air, M5 MacBook Air, M5 MacBook Pro, and the new MacBook Neo. Mikah talks about Meta's Ray-Ban smart glasses and how overseas workers are reviewing the data collected from the glasses, and how these workers are being exposed to deeply private video footage. And Leah Nylen, Antitrust Reporter for Bloomberg, joins the show to talk about Google's new system for apps on its Android phones to allow easier access for rivals as a result of the settlement between Google and Epic Games and fines in the EU as a result of the Digital Markets Act. Hosts: Mikah Sargent and Dan Moren Guest: Leah Nylen Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: hipebl.ai outsystems.com/twit trustedtech.team/twit365

Dan Moren of SixColors joins Mikah Sargent this week on Tech News Weekly! Apple announced a whole new slew of products throughout the week, including the new MacBook Neo! A look into how Meta's Ray-Ban smart glasses collect data. And how Google's new proposed system for apps could change the App Store game. Dan and Mikah discuss the slew of new products Apple announced this week: the iPhone 17e, M4 iPad Air, M5 MacBook Air, M5 MacBook Pro, and the new MacBook Neo. Mikah talks about Meta's Ray-Ban smart glasses and how overseas workers are reviewing the data collected from the glasses, and how these workers are being exposed to deeply private video footage. And Leah Nylen, Antitrust Reporter for Bloomberg, joins the show to talk about Google's new system for apps on its Android phones to allow easier access for rivals as a result of the settlement between Google and Epic Games and fines in the EU as a result of the Digital Markets Act. Hosts: Mikah Sargent and Dan Moren Guest: Leah Nylen Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: hipebl.ai outsystems.com/twit trustedtech.team/twit365

Dan Moren of SixColors joins Mikah Sargent this week on Tech News Weekly! Apple announced a whole new slew of products throughout the week, including the new MacBook Neo! A look into how Meta's Ray-Ban smart glasses collect data. And how Google's new proposed system for apps could change the App Store game. Dan and Mikah discuss the slew of new products Apple announced this week: the iPhone 17e, M4 iPad Air, M5 MacBook Air, M5 MacBook Pro, and the new MacBook Neo. Mikah talks about Meta's Ray-Ban smart glasses and how overseas workers are reviewing the data collected from the glasses, and how these workers are being exposed to deeply private video footage. And Leah Nylen, Antitrust Reporter for Bloomberg, joins the show to talk about Google's new system for apps on its Android phones to allow easier access for rivals as a result of the settlement between Google and Epic Games and fines in the EU as a result of the Digital Markets Act. Hosts: Mikah Sargent and Dan Moren Guest: Leah Nylen Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: hipebl.ai outsystems.com/twit trustedtech.team/twit365

Dan Moren of SixColors joins Mikah Sargent this week on Tech News Weekly! Apple announced a whole new slew of products throughout the week, including the new MacBook Neo! A look into how Meta's Ray-Ban smart glasses collect data. And how Google's new proposed system for apps could change the App Store game. Dan and Mikah discuss the slew of new products Apple announced this week: the iPhone 17e, M4 iPad Air, M5 MacBook Air, M5 MacBook Pro, and the new MacBook Neo. Mikah talks about Meta's Ray-Ban smart glasses and how overseas workers are reviewing the data collected from the glasses, and how these workers are being exposed to deeply private video footage. And Leah Nylen, Antitrust Reporter for Bloomberg, joins the show to talk about Google's new system for apps on its Android phones to allow easier access for rivals as a result of the settlement between Google and Epic Games and fines in the EU as a result of the Digital Markets Act. Hosts: Mikah Sargent and Dan Moren Guest: Leah Nylen Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: hipebl.ai outsystems.com/twit trustedtech.team/twit365

72% of smartphones run Android. Just 28% run iOS.Yet Apple's App Store generates billions—because for years, it controlled the only path to iPhone users.Until March 2024.The EU's Digital Markets Act forced Apple to open iOS to alternative app marketplaces, legally shifting the iPhone from a closed console to something closer to an open computer. But the transition came with friction, including a controversial install Core Technology Fee that left many developers questioning what “open” really meant.In this episode, Erick Espinosa sits down with Artur Assanskiy, Chief Product Officer at Onside, to unpack what actually changed, why developers hesitated, and how alternative iOS distribution is evolving in Europe.Find out more about Artur Assanskiy here. Learn more about Onside here.Reach out to today's host, Erick Espinosa - erick@sociable.coGet the latest on tech news - https://sociable.co/ Leave an iTunes review  - https://rb.gy/ampk26Follow us on your favourite podcast platform - https://link.chtbl.com/rN3x4ecY

-Ring has canceled its partnership with Flock Safety, after receiving backlash for running a Super Bowl ad touting its Search Party feature. -Gail Slater, a former JD Vance adviser and Fox Corp VP, reportedly clashed with Attorney General Pam Bondi. Their longstanding feud is said to have centered around Slater's skepticism of corporate mergers. -European Union regulators have already fined Google billions for violating the Digital Markets Act, and being found guilty of anticompetitive behavior in online advertising could add to that total. Learn more about your ad choices. Visit podcastchoices.com/adchoices

"I will say that QAnon was right and I was wrong." — Pepper CulpepperFrom Bannon and Trump to Summers, Gates, Blavatnik and Chomsky, the Epstein scandal has revealed elites of all ideological stripes behaving shamefully together. The Oxford political scientist Pepper Culpepper argues this is exactly the kind of corporate scandal that can save democracy—not despite its ugliness, but because of it. His new co-authored book, Billionaire Backlash, shows how scandals activate "latent opinion," bringing long-simmering public concerns to the surface and triggering society-wide demand for regulation. We discuss why Cambridge Analytica led to California privacy law, how Samsung's bribery scandal sparked Korea's Candlelight Protests, and why China's authoritarian approach to corporate malfeasance actually undermines trust.Culpepper, himself the Blavatnik Professor of Government at Oxford's Blavatnik School, acknowledges an uncomfortable truth. "I would say that QAnon was right," he admits, "and I was wrong." The specifics might have been fantasy, but the underlying suspicion about elite corruption was justified. And policy entrepreneurs—obsessive individuals who channel public outrage into actual legislation—matter more than we think. For Culpepper, billionaire backlash isn't a threat to democracy—it might actually be what saves it.About the GuestPepper Culpepper is Vice Dean of the Blavatnik School of Government at the University of Oxford. He is the co-author, with Taeku Lee of Harvard, of Billionaire Backlash: The Age of Corporate Scandal and How It Could Save Democracy (2026).ReferencesScandals discussed:●      The Epstein scandal revealed that elites across politics, finance, and academia were connected to Jeffrey Epstein's network of abuse—vindicating populist suspicions that "the system is broken."●      Cambridge Analytica (2018) exposed how Facebook leaked data on 90 million users, leading to the Digital Markets Act and Digital Services Act in the EU, and California's privacy regulations.●      The Samsung bribery scandal in South Korea led to the Candlelight Protests and President Park Geun-hye's resignation, demonstrating how corporate scandals can strengthen civil society.●      The 2008 Chinese milk scandal killed six infants due to melamine contamination; the government's cover-up during the Beijing Olympics destroyed public trust in domestic food safety.●      Volkswagen's Dieselgate scandal showed how companies cheat on regulations, bringing latent concerns about corporate behavior to the surface.Policy entrepreneurs mentioned:●      Carl Levin was a US Senator from Michigan who shepherded the Goldman Sachs hearings and contributed to the Dodd-Frank Act.●      Margrethe Vestager served as EU Competition Commissioner and pushed for the Digital Markets Act and Digital Services Act.●      Max Schrems is an Austrian privacy activist who, as a student, discovered Facebook retained his deleted messages and eventually brought down the US-EU data transfer agreement.●      Alastair Mactaggart is a California property developer who pushed through the state's privacy regulations when federal action proved impossible.●      Zhao Lianhai was a Chinese activist who tried to organize parents after the 2008 milk scandal; the government arrested and imprisoned him.Concepts discussed:●      Latent opinion refers to concerns people hold in the back of their minds that aren't front-of-mind until a scandal brings them to the surface.●      The Thermidor reference is to the French Revolutionary period when the radical Jacobins were overthrown—Culpepper suggests a controlled version might benefit democracy.●      The muckrakers were Progressive Era journalists whose exposés led to reforms like the Food and Drug Administration.Also mentioned:●      Michael Sandel is a Harvard political philosopher known for arguing that "there shouldn't be a price on everything."●      Patrick Radden Keefe wrote Empire of Pain, the definitive account of the Sackler family and the opioid epidemic.●      Lee Jae-yong is the heir apparent to Samsung, implicated in the bribery scandal.●      Parasite, Squid Game, and No Other Choice are Korean cultural works that critique the country's relationship with its conglomerates.About Keen On AmericaNobody asks more awkward questions than the Anglo-American writer and filmmaker Andrew Keen. In Keen On America, Andrew brings his pointed Transatlantic wit to making sense of the United States—hosting daily interviews about the history and future of this now venerable Republic. With nearly 2,800 episodes since the show launched on TechCrunch in 2010, Keen On America is the most prolific intellectual interview show in the history of podcasting.WebsiteSubstackYouTubeApple PodcastsSpotifyChapters:(00:00) - (00:22) - The Epstein opportunity (01:21) - Elite overreach exposed (03:12) - Scandals without partisan charge (05:04) - The Vice Dean's credibility problem (06:21) - Latent opinion explained (09:39) - Is there anything wrong with being a billionaire? (11:47) - American vs. European scandals (14:48) - Saving democracy vs. saving capitalism (17:05) - Corporate scandals and economic vitality (18:33) - Policy entrepreneurs: Carl Levin and Margrethe Vestager (19:54...

Cette semaine : procès contre les géants des réseaux sociaux aux US, action contre Android en UE, Facebook Actu bientôt de retour au Canada et concurrence déloyale au nom de la souveraineté en France.Avec Bruno Guglielminetti (Mon Carnet)Les réseaux sociaux face à la justice américaineLa justice américaine ouvre une série de procès visant les grandes plateformes accusées d'avoir des effets délétères sur la santé mentale des jeunes. Bruno Guglielminetti détaille les poursuites engagées contre Meta, propriétaire de Facebook et Instagram, tandis que TikTok et Snap ont conclu des accords à l'amiable hors cour. Ces procédures pourraient révéler des documents internes sensibles, notamment sur la connaissance par les plateformes des risques liés à leurs usages.Android et le DMA : l'Europe met Google sous pressionLa Commission européenne exige des changements profonds dans Android au nom du Digital Markets Act. Bruxelles veut forcer Google à ouvrir l'accès aux composants clés des smartphones, tant pour l'intelligence artificielle que pour les moteurs de recherche concurrents. Une bataille réglementaire de longue haleine qui rappelle les bras de fer déjà engagés avec Apple.Canada : Meta pourrait rouvrir l'accès aux contenus d'actualitéAu Canada, Meta avait bloqué le partage de contenus de presse en réaction à une loi imposant une rémunération des médias. Bruno Guglielminetti revient sur les conséquences concrètes de cette décision, notamment lors de situations d'urgence, et sur les discussions en cours entre Ottawa et Meta pour rétablir l'accès à l'information sur Facebook.La France développe sa propre visio : souveraineté ou concurrence déloyale ?L'État français lance une solution de visioconférence destinée à remplacer les outils américains dans l'administration. Jérôme Colombain analyse ce choix stratégique en matière de souveraineté numérique, mais aussi la colère des entreprises françaises du secteur, qui voient l'État devenir un concurrent direct avec une solution gratuite.-----------♥️ Soutien : https://mondenumerique.info/don

Was 2025 the year the games industry finally stopped talking about direct-to-consumer and started treating it as the default way to do business? In this episode of Tech Talks Daily, I'm joined by Chris Hewish, President at Xsolla, for a wide-ranging conversation about how regulation, platform pressure, and shifting player expectations have pushed D2C from the margins into the mainstream. As court rulings, the Digital Markets Act, and high-profile battles like Epic versus Apple continue to reshape the industry, developers are gaining more leverage, but also more responsibility, over how they distribute, monetize, and support their games. Chris breaks down why D2C is no longer just about avoiding app store fees. It is about owning player relationships, controlling data, and building sustainable businesses in a more consolidated market. We explore how tools like Xsolla's Unity SDK are lowering the barrier for studios to sell directly across mobile, PC, and the web, while handling the operational complexity that often scares teams away from global payments, compliance, and fraud management. We also dig into what is changing inside live service games. From offer walls that help monetize the vast majority of players who never spend, to LiveOps tools that simplify campaigns and retention strategies, Chris shares real examples of how studios are seeing meaningful lifts in revenue and engagement. The conversation moves beyond technology into mindset, especially for indie and mid-sized teams learning that treating a game as a long-term business needs to start far earlier than launch day. Here in 2026, we talk about account-centric economies, hybrid monetization models running in parallel, and the growing role of community-driven commerce inspired by platforms like Roblox and Fortnite. There is optimism in these shifts, but also understandable anxiety as studios adjust to managing more of the stack themselves. Chris offers a grounded perspective on how that balance is likely to play out. So if games are becoming hobbies, platforms are opening up, and developers finally have the tools to meet players wherever they are, what does the next phase of direct-to-consumer really look like, and are studios ready to fully own that relationship? Useful Links Connect with Chris Hewish on LinkedIn Learn more about Xsolla Follow on LinkedIn, Twitter, and Facebook Thanks to our sponsors, Alcor, for supporting the show.

Intel has reportedly approached Apple about investing in the company. Some of Apple's new features will be delayed in the EU due to the Digital Markets Act. A study showcases a dramatic rise in fraudulent mobile apps on both iOS and Android. And Apple is working on its own ChatGPT-style chatbot app, which is being tested internally by employees. Intel is seeking an investment from Apple as part of its comeback bid. Apple warns of more feature delays in Europe. New study shows 'massive spike' in fraudulent apps powered by AI. Apple releases iOS 26.0.1 with fixes for Wi-Fi, Cellular, and camera issues on iPhone 17 models. Apple releases macOS Tahoe 26.0.1 with M3 Ultra bug fix. Apple working on all-new operating system. New iPad Pro with M5 chip leaked in unboxing video. Two new Apple displays nearing mass production, may launch this year. Apple's ChatGPT-style chatbot app deserves a public release. Apple researchers develop SimpleFold, a lightweight AI for protein folding prediction. Jessica Chastain 'not aligned' with Apple's decision to delay series about hate groups. Why did Apple get cold feet about 'Savant'? Tigers-Red Sox clash on Apple TV+ will feature live game footage on new iPhone 17 Pro. College football keeps picking iPad over Surface as fourth conference joins team Apple. Now available: Adobe Premiere on iPhone brings pro-quality video editing to creators. FCC mistakenly leaks confidential iPhone 16e schematics. Apple responds to iPhone 17 Pro scratch and durability concerns. Meet the new light of Jony Ive's life. Why Ford's CEO doesn't love Apple CarPlay Ultra. Picks of the Week Jason's Picks: Relay for St. Jude Alex's Pick: Vertical Heart Set Insert Tool Andy's Pick: UGREEN Phone Stand Leo's Pick: Nomat Goods Horween Leather Folio for iPhone 17 Pro Max Hosts: Leo Laporte, Alex Lindsay, Andy Ihnatko, and Jason Snell Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: threatlocker.com/twit pantheon.io

Intel has reportedly approached Apple about investing in the company. Some of Apple's new features will be delayed in the EU due to the Digital Markets Act. A study showcases a dramatic rise in fraudulent mobile apps on both iOS and Android. And Apple is working on its own ChatGPT-style chatbot app, which is being tested internally by employees. Intel is seeking an investment from Apple as part of its comeback bid. Apple warns of more feature delays in Europe. New study shows 'massive spike' in fraudulent apps powered by AI. Apple releases iOS 26.0.1 with fixes for Wi-Fi, Cellular, and camera issues on iPhone 17 models. Apple releases macOS Tahoe 26.0.1 with M3 Ultra bug fix. Apple working on all-new operating system. New iPad Pro with M5 chip leaked in unboxing video. Two new Apple displays nearing mass production, may launch this year. Apple's ChatGPT-style chatbot app deserves a public release. Apple researchers develop SimpleFold, a lightweight AI for protein folding prediction. Jessica Chastain 'not aligned' with Apple's decision to delay series about hate groups. Why did Apple get cold feet about 'Savant'? Tigers-Red Sox clash on Apple TV+ will feature live game footage on new iPhone 17 Pro. College football keeps picking iPad over Surface as fourth conference joins team Apple. Now available: Adobe Premiere on iPhone brings pro-quality video editing to creators. FCC mistakenly leaks confidential iPhone 16e schematics. Apple responds to iPhone 17 Pro scratch and durability concerns. Meet the new light of Jony Ive's life. Why Ford's CEO doesn't love Apple CarPlay Ultra. Picks of the Week Jason's Picks: Relay for St. Jude Alex's Pick: Vertical Heart Set Insert Tool Andy's Pick: UGREEN Phone Stand Leo's Pick: Nomat Goods Horween Leather Folio for iPhone 17 Pro Max Hosts: Leo Laporte, Alex Lindsay, Andy Ihnatko, and Jason Snell Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: threatlocker.com/twit pantheon.io

Intel has reportedly approached Apple about investing in the company. Some of Apple's new features will be delayed in the EU due to the Digital Markets Act. A study showcases a dramatic rise in fraudulent mobile apps on both iOS and Android. And Apple is working on its own ChatGPT-style chatbot app, which is being tested internally by employees. Intel is seeking an investment from Apple as part of its comeback bid. Apple warns of more feature delays in Europe. New study shows 'massive spike' in fraudulent apps powered by AI. Apple releases iOS 26.0.1 with fixes for Wi-Fi, Cellular, and camera issues on iPhone 17 models. Apple releases macOS Tahoe 26.0.1 with M3 Ultra bug fix. Apple working on all-new operating system. New iPad Pro with M5 chip leaked in unboxing video. Two new Apple displays nearing mass production, may launch this year. Apple's ChatGPT-style chatbot app deserves a public release. Apple researchers develop SimpleFold, a lightweight AI for protein folding prediction. Jessica Chastain 'not aligned' with Apple's decision to delay series about hate groups. Why did Apple get cold feet about 'Savant'? Tigers-Red Sox clash on Apple TV+ will feature live game footage on new iPhone 17 Pro. College football keeps picking iPad over Surface as fourth conference joins team Apple. Now available: Adobe Premiere on iPhone brings pro-quality video editing to creators. FCC mistakenly leaks confidential iPhone 16e schematics. Apple responds to iPhone 17 Pro scratch and durability concerns. Meet the new light of Jony Ive's life. Why Ford's CEO doesn't love Apple CarPlay Ultra. Picks of the Week Jason's Picks: Relay for St. Jude Alex's Pick: Vertical Heart Set Insert Tool Andy's Pick: UGREEN Phone Stand Leo's Pick: Nomat Goods Horween Leather Folio for iPhone 17 Pro Max Hosts: Leo Laporte, Alex Lindsay, Andy Ihnatko, and Jason Snell Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: threatlocker.com/twit pantheon.io

From the BBC World Service: Apple has called for the European Union's antitrust watchdogs to scrap some of its tech regulations, which it says lead to a worse experience for users. It's not the first time Apple has voiced its opposition to Europe's Digital Markets Act. We hear more. Plus, China has — for the first time — set a target for reducing carbon emissions. And, a Dutch village famous for its windmills is planning to charge visitors to see them.

From the BBC World Service: Apple has called for the European Union's antitrust watchdogs to scrap some of its tech regulations, which it says lead to a worse experience for users. It's not the first time Apple has voiced its opposition to Europe's Digital Markets Act. We hear more. Plus, China has — for the first time — set a target for reducing carbon emissions. And, a Dutch village famous for its windmills is planning to charge visitors to see them.