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

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

Steve drops serious cash on an M5 Max MacBook Pro right as Apple's Rampocalypse price hikes hit, then immediately bricks his iPhone 14 Pro Max installing iOS 27 Beta 3. The Trio unpacks Apple pulling the liquid glass opt-out after its promised one year, and spins out increasingly unhinged ideas for what a foldable iPhone's split screen could actually be good for. They close out with post-WWDC side project pitches: Kotaro weighing a Retro Sparkle or Fav 10 revival, Aaron dreaming up the ultimate foldable app, and Steve making BentoFit updates with a photography app on his mind.## Chapters00:00 Introductions & Token Economics 10:11 Hardware Upgrades and the RAM Apocalypse 17:47 Bricking an iPhone Installing iOS 27 Beta 3 21:34 UIKit Updates & Reading the Folding Phone Tea Leaves 35:26 Exploring New App Ideas Post-WWDC 47:20 Wrap-Up & Dad Jokes 48:19 Tag ## Show Notes* Steve bit the bullet on a mid-tier, on sale M5 Max MacBook Pro (the best config Amazon had discounted) after Apple's Rampocalypse price hikes made waiting for the redesigned model a bad bet.* The Amazon Prime Day deal saved him around $850 versus buying the same config direct from Apple.* He's already seeing real speed gains in Lightroom, with AI denoise dropping from about ten seconds a photo to three to five.* Steve bricked his iPhone 14 Pro Max installing iOS 27 Beta 3 and had to DFU restore it from an iCloud backup.* iOS 27 removes the liquid glass opt-out entirely, exactly one year after Apple said it would, and it's ugly on unmigrated UIKit apps.* The Trio speculates Apple's foldable iPhone, rumored to run two screens with unusual aspect ratios, is driving the push to force UIKit and scene delegate updates.* They riff on absurd split screen app concepts for the foldable, from a permanent AI chat pane to a Tetris style game that dumps everything onto the bigger screen on unfold.* Kotaro is weighing a Retro Sparkle revival (his three second match three game) or a long overdue Fav 10 rebuild for the next side project.* Aaron wonders who could possibly afford a foldable iPhone that will probably cost as much as a MacBook.* Steve is making BentoFit theme manager updates and floats a photography app as a future project.## Links**Side Project Apps**Retro Sparkle: https://tomatoboy.co/retro | Fav 10: https://tomatoboy.co/fav10**Tools & Services Mentioned**Gas Town (Steve Yegge): https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16dd04 | GLM 5.2: https://z.ai/blog/glm-5.2**Bento Fit**Website: https://bentofit.app**PhillyCocoa:** https://phillycocoa.orgIntro music: "When I Hit the Floor", © 2021 Lorne Behrman. Used with permission of the artist.

After almost 250 episodes, Leo gives an update on what he's working on and what he's interested in. From passive timer apps, static site generation, to sub repos and RSS feeds.Related LinksWWDC 2026 & CelestraCelestraWWDC26: What's new in the Foundation Models frameworkWWDC26: Meet Core AIBushelswift-buildbrightdigit/swift-buildIntroducing swift-build (blog post)Swift.org Nightly ToolchainsAt LeastAt Leastbrightdigit/SundialKitbrightdigit/SundialKitStreambrightdigit.com Website Upgradebrightdigit.com repoJohnSundell/PublishJohnSundell/ShellOutJohnSundell/Inkswiftlang/swift-subprocessswiftlang/swift-markdownkabiroberai/node-swift (NodeSwift)Tailwind CSSgit-subrepoingydotnet/git-subrepoBen ScheirmanCommunity & OutroConsultation (ZCal)PatreonNewsletterDonny WalsSaleem Abdulrasool (@compnerd)Swift on WindowsRelated EpisodesActually Really Useful120% Likely with Cihat GündüzPlatforms State of the Union 2026 with Peter WithamWho's Wendy with Joannis OrlandosMilk Diary with Kaya ThomasDeconstructing Xcode with xTool with Kabir OberaiThe Great SwiftUI Migration - Part 2 with Ben ScheirmanThe Great SwiftUI Migration - Part 1 with Ben ScheirmanHacking with Ignite with Paul HudsonNow You Know What I'm Doing This SummerChapters(00:00) - WWDC 2026 and Celestra (01:35) - swift-build (02:23) - AtLeast (05:26) - brightdigit.com (05:45) - git-subrepo (06:47) - Join the Community WatchClick here to watch a video of this episode. TranscriptClick here to view the episode transcript. Support the Show ★ Support this podcast on Patreon ★  Thanks to our supporters: Thanks to our monthly supporters Steven Lipton  Welcome new supporters: Social MediaLinkedIn - @leogdionGitHub - @brightdigitGitHub - @leogdionMastodon - @leogdion@c.imYouTube - @brightdigitX - @leogdionX - @brightdigitCreditsMusic from https://filmmusic.io "Blippy Trance" by Kevin MacLeod (https://incompetech.com) License: CC BY (http://creativecommons.org/licenses/by/4.0/)

Benjamin and Chance react to the news from Bloomberg's Mark Gurman that Apple is accelerating the roadmap for the M7 series of Apple Silicon chips, somewhat at the expense of the as-yet-unreleased M6 line. Also, we break down what's new in visionOS 27 and do some summer Ask9to5Mac questions.  And in Happy Hour Plus, Benjamin and Chance pick their favorite grab-bag features from the iOS 27 WWDC cloud side. Subscribe at 9to5mac.com/join. Sponsored by Square: Get up to $200 off Square hardware when you sign up at square.com/go/happyhour. Sponsored by Shopify: All you need is the idea. Shopify handles the rest. Start your free trial at shopify.com/happyhour. Sponsored by Cash App: Download Cash App Today: https://click.cash.app/ui6m/i4d1b1x2 #CashAppPod

Transkrypcja:Transkrypcję tego odcinka znajdziesz tutaj. Mój gość stworzył aplikację, która jest dosłownie cyfrową, domową apteczką i robi niektóre rzeczy o wiele lepiej niż systemowe rozwiązania od Apple. #BoCzemuNie ? POBIERZ ODCINEK Partnerzy technologiczni: > iDream – Apple Premium Reseller, Apple Premium Service Provider > Pancernik – Akcesoria do telefonów i nie tylko Linki: Zadaj pytanie w odcinku lub zgłoś temat! Newsletter podcastu Myślisz o podcaście? Sprawdź warsztat „Poznaj podcasting” Sklep – lista oczekujących Gość: Tomasz Szuster Aplikacja mojApteczka Podcast Tomka Regulamin konkursu #451 – WWDC 2026 – o czym nie powiedziano? Bądźmy w kontakcie: X | Facebook | Instagram | kontakt@boczemunie.pl > Prowadzący: Krzysztof Kołacz Mam prośbę: Oceń ten podcast w Apple Podcasts oraz na Spotify i YouTube. Zostaw tyle gwiazdek, ile uznasz. Twoja opinia ma znaczenie! Zainteresowany współpracą? Pogadajmy. > Liczby znajdziesz na boczemunie.pl/partner/ Słuchaj, gdzie chcesz: YouTube | Apple Podcasts | Spotify | Overcast FM i przez RSS Dobrego odbioru! Bo czemu nie? Rozdziały: (00:00:00) PARTNERZY (00:00:27) INTRO (00:01:01) Wstępniak (00:02:21) Historia aplikacji „mojApteczka” (00:39:29) Co WWDC dało Tomkowi?

The June 2026 update, preview Chuck's upcoming trip to MacStock, encouraging attendees to introduce themselves. The also outlines the last of the  NAB interviews, recaps participation in MacPaw's Flip the Script event during WWDC and announces the launch of the new MacVoices Merch Store. The update wraps by encouraging YouTube subscriptions and thanking Patreon supporters.  Show Notes: MacVoices on Patreon:http://patreon.com/macvoices Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Behind every new AI breakthrough lies a bigger question: who benefits, who loses, and what comes next?  In this conversation, Nathan and Scott explore some of the biggest debates shaping the future of artificial intelligence. They begin with Apple's WWDC announcements, discussing Siri's major upgrades and how on-device AI could make it a smarter and more personalized assistant. The discussion then shifts to Anthropic and its Claude models, including Fable, a safety-focused AI system that was ultimately shut down due to potential risks.   Nathan and Scott also examine changing narratives around AI and employment, questioning why industry leaders such as Sam Altman and Dario Amodei have recently shifted from warning about job losses to promoting job creation, especially as their companies prepare for IPOs. Finally, they tackle AI's environmental impact, highlighting the energy demands of data centers and considering whether future technologies, such as quantum computing, could provide sustainable solutions.  HIGHLIGHTS [02:44] WWDC and Siri Updates   [12:07] Anthropic and Claude Models   [22:20] Impact of AI on Jobs and IPOs  [30:00] Environmental Concerns and AI   Resources:  Connect with Nathan and Scott:  LinkedIn (Nathan): linkedin.com/in/nathanchappell/  LinkedIn (Scott): linkedin.com/in/scott-rosenkrans  Website: fundraising.ai/    Mentioned in the episode:   The Artificial Intelligence Show: podcast.smarterx.ai/  The AI Daily Brief: aidailybrief.ai/ 

The June 2026 update, preview Chuck's upcoming trip to MacStock, encouraging attendees to introduce themselves. The also outlines the last of the  NAB interviews, recaps participation in MacPaw's Flip the Script event during WWDC and announces the launch of the new MacVoices Merch Store. The update wraps by encouraging YouTube subscriptions and thanking Patreon supporters.  Show Notes: MacVoices on Patreon: http://patreon.com/macvoices Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

AI has been a constant in tech buzzword bingo for some time now, and the tide has very much changed from "how do we block this" to "how do we use it for the things that make sense". As the constraints have been loosened, and the token costs go up… how do we get a clear understanding of exactly what is being used in our environment, what the AI agents and harnesses are doing, and ensuring we are meeting the expectations of the people who are held accountable? Matt Vlasach is back to talk to us about AI Governance and how Jamf is tackling this in an authentically Apple way. Hosts: Tom Bridge - @tbridge@theinternet.social Marcus Ransom - @marcusransom Selina Ali - LinkedIn Guests: Matt Vlasach - LinkedIn Links: https://www.jamf.com/solutions/ai-governance/ Clankers: https://starwars.fandom.com/wiki/Clanker The Talk Show at WWDC: https://daringfireball.net/2026/06/the_talk_show_live_from_wwdc_2026 Sponsors: Iru Fleet Device Management Workbrew Watchman Monitoring If you're interested in sponsoring the Mac Admins Podcast, please email podcast@macadmins.org for more information. Get the latest about the Mac Admins Podcast, follow us on Twitter! We're @MacAdmPodcast! The Mac Admins Podcast has launched a Patreon Campaign! Our named patrons this month include Weldon Dodd, Damien Barrett, Justin Holt, Chad Swarthout, William Smith, Stephen Weinstein, Seb Nash, Dan McLaughlin, Joe Sfarra, Nate Cinal, Jon Brown, Dan Barker, Tim Perfitt, Ashley MacKinlay, Tobias Linder Philippe Daoust, AJ Potrebka, Adam Burg, & Hamlin Krewson  

Steve is back from a Royal Caribbean cruise to Bermuda just in time for the WWDC26 wrap-up, and Kotaro wastes no time YOLOing onto the macOS beta to demo Siri AI live. Things go sideways fast when Siri deletes Kotaro's Redfin emails instead of listing their subjects, sparking a wide-ranging conversation about what it actually means to ship AI features to everyday users. The Trio also maps out their WWDC-inspired side project plans for the year ahead.## Chapters00:08 Introductions 00:56 Side Quest: Steve's Cruise Adventures 13:23 Transitioning to AI and WWDC Discussions 17:23 WWDC26 Highlights 22:04 Kotaro Beta Tests macOS & Siri AI 24:17 Xcode & macOS UI Changes 27:10 Kotaro Tries Out Siri AI Live 31:26 Siri Deletes Kotaro's Emails! 41:04 Exploring Siri AI and User Experience 43:25 WWDC26 Insights and Future Projects 52:25 Wrap-Up & One More Thing... 52:46 Tag ## Show Notes- Steve returns from a 5-night Royal Caribbean cruise to Bermuda: escape rooms, cliff climbing, 17k daily steps, and the best lasagna of his life.- The Trio catches up on WWDC26 after Steve's cruise delay, covering Siri AI, SwiftUI improvements, and Swift Data's new results observer.- Kotaro has already YOLOd the macOS beta onto his laptop and shares first impressions of the more refined, less opinionated UI.- New Xcode hides your current branch but gains liquid glass segment controls and an AI assistant for identifying dead code.- Kotaro demos Siri AI live: it correctly locates the Rocky statue and renders a map widget, building some initial optimism about Apple's AI integration story.- Siri AI then accidentally deletes Kotaro's Redfin emails when he only asked it to list their subject lines.- Siri also fails the classic "how many Rs in Raspberry?" test on the local on-device model.- Steve worries that mainstream Siri AI shipping on devices like his dad's new MacBook Neo will create a new wave of family tech support nightmares.- Steve plans to add conversational health assistant features to BentoFit; Kotaro wants to vibe-code Fave10 using only Xcode AI tools and port Retro Sparkle to Godot.## Links**WWDC26**Videos: https://developer.apple.com/videos/wwdc2026/**One More Thing**AppJawn LLC: https://appjawn.com/Apps: Clipdish, Mio Vino, Minimalist Meditation Timer**PhillyCocoa:** https://phillycocoa.orgIntro music: "When I Hit the Floor", © 2021 Lorne Behrman. Used with permission of the artist.Music licensed through Soundstripe. Code: RLF9P8ZZ6MPKNOGX

This week, Will is joined by tech journalist Florence Ion, of PC Mag, Material Podcast, and Android Faithful to talk about what Google's been up to, the inevitable encroachment of Gemini into Android, and the shocking revelation that she uploaded her Livejournal archive to Gemini. It's a wide-ranging conversation about the state of tech, good and bad uses of AI, what it's like working for a long time in tech journalism, and a whole lot more.  Support the Pod! Contribute to the Tech Pod Patreon and get access to our booming Discord, a monthly bonus episode, your name in the credits, and other great benefits! You can support the show at: https://patreon.com/techpod

Ep 286 I asked Apple's senior watchOS team why the latest upgrade isn't coming to so many older models — and they told me "we make power and performance a priority" macOS 27 Golden Gate makes it clear when apps are sneakily running in background iOS 27 Adds Landscape Mode to More Apple Apps Ahead of 'iPhone Ultra' ninxsoft/Mist: A Mac utility that automatically downloads macOS Firmwares / Installers. What's new in Soulver 4? | Soulver for Mac, iPad & iPhone WWDC 2026: Emptying the notebook about AI, bug fixes, and more Stalman: One of the coolest in person demos at WWDC was LM Studio running massive local models on 4 daisy chained Mac Studios with a total of 2TB memory Bringing the latest Gemini models to Apple developers Claude support for Apple's Foundation Models framework | Claude Tim Cook Confirms Apple Will Raise Prices Due to Memory and Storage Costs Apple Just Increased Prices on MacBooks, iPads, and More Zahvalnice Snimano 28.6.2026. Uvodna muzika by Vladimir Tošić, stari sajt je ovde. Logotip by Aleksandra Ilić. Artwork epizode by Saša Montiljo, njegov kutak na Devianartu

Tim Cook warned us it was coming, but still the price rises on most, although not all, Apple products is a blow if you were just about to order. Here's what's changed, and when it might change back. Plus we're now on developer beta 2 of the new OSes, and of course there's more news about the iPhone Fold.Contact your hosts:@williamgallagher_ on Threads@WGallagher on TwitterWilliam's 58keys on YouTubeWilliam Gallagher on emailWes on BlueskyWes Hilliard on emailWes's blog HillitechSponsored by:MasterClass: Get 15% off annual memberships at MasterClass.comNordStellar: Unlock your 10% discount at nordstellar.com/appleinsider with the coupon code nordappleinsider-10-NORDSTELLARLinks from the Show:Apple confirms big price hikes across Macs, iPads, and moreThe Apple Store is back online after being taken down briefly, and its return has brought with it some significant price increases across some of Apple's most popular products, including the MacBook Neo.Apple's home automation updates & new product releases will stretch into 2028Apple left Apple TV & HomePod out of WWDC and Siri AI is the culprittvOS 27 beta code backs up HomePod and Apple TV Siri AI rumorsNew supply chain source is sure iPhone Fold will launch in September 2026Folding iPhone hinge issues may have been worked out, rumored to ship in fallLeak claims iPhone Ultra 2 is already greenlit, but maybe not iPhone Air 3Second developer betas of iOS 27, macOS 27 are outNew in iOS 27 beta 2: Update an Apple TV in the Home app, Wallet InsightsCannes Lions 2026 Entertainment Person of the Year is Apple TV chiefApple Ring would dominate the fitness market, which is why it can't existGoogle's new payment policies are a preview of what could come to Apple platformsSupport the show:Support the show on Patreon or Apple Podcasts to get ad-free episodes every week, access to our private Discord channel, and early release of the show! We would also appreciate a 5-star rating and review in Apple PodcastsMore AppleInsider podcastsTune in to our HomeKit Insider podcast covering the latest news, products, apps and everything HomeKit related. Subscribe in Apple Podcasts, Overcast, or just search for HomeKit Insider wherever you get your podcasts.Subscribe and listen to our AppleInsider Daily podcast for the latest Apple news Monday through Friday. You can find it on Apple Podcasts, Overcast, or anywhere you listen to podcasts.Those interested in sponsoring the show can reach out to us at: advertising@appleinsider.com (00:00) - Intro (01:18) - Price increases (10:16) - Apple Home (13:18) - iPhone Fold (27:14) - Beta 2 (55:36) - Eddy Cue (01:04:45) - Google Play Commissions ★ Support this podcast on Patreon ★

Happy EOFY to all who celebrate! We get deep into WWDC for about 3 minutes. We create an app corner möbius strip! We accidentally transform the show into a whole new category! "You don't know what börek is!?" —Martin EOFY and the World Cup 00:00:00 EOFY

Software development has changed a lot. On today's episode, Joe Fabisevich talks about building with AI without falling into the trap of "work slop," why prompting is a communication skill, where Apple fits in, and Broadcast — his new Swift logging library for developers and AI agents.GuestBuild.msJoe Fabisevich :verified: (@mergesort@macaw.social) - Macaw-SocialJoe Fabisevich (@mergesort.me) — BlueskyGithub (@mergesort)https://www.threads.net/@mergesortfabisevi.chRelated LinksArtifacts | Fabisevi.chSupporting Markdown Search For LLMsAI (Without the Hype)WorkslopBeing A 1.5-10x Developermergesort/Broadcast: Simple and composable logging for Swift apps, servers, and coding agents.AtLeast — Passive Timer for Apple WatchMonthBar - Track your month's progressRelated Episodes120% Likely with Cihat GündüzPlatforms State of the Union 2026 with Peter WithamWho's Wendy with Joannis OrlandosActually Really UsefulPractical Year - Part 1 with Donny WalsPlinky with Joe FabisevichChatGPTovski with Kris SlazinskiChapters(00:00) - Work Slop (13:02) - Verifiable Tasks (25:51) - Building Agents (32:06) - Careers & Hiring (43:31) - Daily Setup (53:00) - WWDC 2026 (01:09:07) - AI Economics (01:20:33) - Broadcast Logging WatchClick here to watch a video of this episode. TranscriptClick here to view the episode transcript. Support the Show ★ Support this podcast on Patreon ★  Thanks to our supporters: Thanks to our monthly supporters Steven Lipton  Welcome new supporters: Social MediaLinkedIn - @leogdionGitHub - @brightdigitGitHub - @leogdionMastodon - @leogdion@c.imYouTube - @brightdigitX - @leogdionX - @brightdigitCreditsMusic from https://filmmusic.io "Blippy Trance" by Kevin MacLeod (https://incompetech.com) License: CC BY (http://creativecommons.org/licenses/by/4.0/)

Jason Snell returns to the show for a look back at WWDC 2026, and a look ahead to “Designed in California”, his and Myke Hurley's upcoming 50-episode Apple history podcast.

Paul had a blast at HellmouthCon! The boys talk about DubDub, and Paul is worried about his NAS. Drew gives an update on his local LLM setup and his never ending quest for more VRAM. Recorded 06/18/26 Show Links: Doug Jones Everything Apple Announced at WWDC 2026 in 10 Minutes SWE-Bench Opencode Qwen3-Coder-Next Gigabyte AMD Radeon AI PRO R9700 LM Studio llama.cpp AMD Radeon™ AI PRO Graphics Razer Core X V2 External Graphics Enclosure

On the Road to Macstock, we look forward to the presentation by David Ginsburg, who will look back on ten years of Apple change, reflecting on the move from Intel Macs and early Apple Watch days to Apple Silicon, AirDrop, Continuity, Vision Pro, and Apple Intelligence. Dave discusses how small ecosystem improvements reshape daily workflows, how enterprise experience informs his perspective, and how we got from there to here.  This edition of MacVoices is brought to you by our Patreon supporters. Get access to the MacVoices Slack and MacVoices After Dark by joining in at Patreon.com/macvoices. Show Notes: Chapters: 00:00 Opening and Road to MacStock introduction00:51 Introducing David Ginsburg01:18 David's MacStock presentation topic01:36 Ten years of Apple change and adaptation02:20 Putting Apple progress into perspective03:14 Living through Apple transitions as users04:17 Apple Silicon, AirDrop, Continuity, and Apple Watch04:52 Everyday ecosystem features used in production workflows06:04 iCloud, Apple Notes, and syncing across devices07:05 AI as part of the next wave of change07:53 Dave's enterprise perspective09:31 Growing professionally through Apple technology10:13 Vision Pro as a bridge to the future10:51 Apple Intelligence and another transition period11:53 WWDC timing and future perspective12:48 Apple Intelligence expectations13:46 Encouraging attendees to register14:12 MacStock as shared enthusiasm and learning15:03 Where to find David Ginsburg online16:11 Why first-time attendees quickly find community16:54 Closing credits and support information Links: Macstock Conferencehttp://macstockconference.comDave's Discount Code: intouch  Guests: David Ginsburg is the host of the weekly podcast In Touch With iOS where he discusses all things iOS, iPhone, iPad, Apple TV, Apple Watch, and related technologies. He is an IT professional supporting Mac, iOS and Windows users. Visit his YouTube channel at https://youtube.com/daveg65 and find and follow him on Twitter @daveg65 and on Mastodon at @daveg65@mastodon.cloud. Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Reflecting on WWDC's announcements

Robin Kai, based in Munich, Germany, is a husband, dad, and writer on Medium and at ForMacUsers.com. He's built a simple, flexible system around Apple's built-in apps that actually fits real life: family, day job, and side projects.In this episode, Robin walks us through how he captures tasks without thinking about it, organizes them into a structure that doesn't require daily upkeep, and builds a custom "today" view that shows exactly what matters — without the noise.Topics covered:Why Robin left third-party apps like Remember the Milk and Wunderlist behindHis inbox-first capture method and weekly Friday reviewHow he uses folders (groups) in Reminders to separate work, side hustle, and familyThe "Your Day" and "Growth" smart list setup for a cleaner today viewMonth → Week → Priorities planning cadenceConnecting Reminders to Notes for project contextWhat Robin is most excited about from WWDC 2026: AI-powered Shortcuts and Safari improvementsTom's own journey from Evernote + OmniFocus to Craft tasksLinks from the show:Robin on Threads: https://www.threads.com/@robinsanahkaiForMacUsers.com: https://www.formacusers.com/Robin's Apple Reminders guide on Medium: https://medium.com/macoclock/apple-reminders-full-setup-deb28e755eb6?sk=21ab358dbf39f28ed90133d706fb7cf5Stories from Ukraine: The True Price of War: https://a.co/d/0gu6KDAlQuestion or Comment? Send us a Text Message!Support the showContact UsDrop us a line at feedback@basicafshow.comYou'll find Jeff at @reyespoint on Threads and reyespoint.bsky.social on BlueskyFind Tom at @tomanderson on ThreadsJoin Tom's newsletter, Apple Talk, for more Apple coverage and tips & tricks.Tom has a new YouTube channelShow artwork by the great Randall Martin DesignEnjoy Basic AF? Leave a review or rating!Review on Apple PodcastsRate on SpotifyRecommend in OvercastIntro Music: Psychokinetics - The ChosenApple MusicSpotifyTranscripts and some images are AI generated and may contain errors and general silliness.

Llegaron las betas de iOS 27 y analizamos el WWDC con tres grandes temas: nuevos controles parentales repensados desde cero, un "año Snow Leopard" enfocado en optimización y refinamiento de Liquid Glass, y el momento más esperado: el nuevo Apple Intelligence con un Siri que por fin hace lo que Apple prometió hace dos años. Y funciona desde el primer día.

The Cycling Tech Brief: the cycling tech that actually matters this week — and whether to update, wait, or ignore.Strava launches official MCP connector giving paid subscribers direct conversational access to their full training history via Anthropic's Claude — Monitor — if you're a paid Strava subscriber and want AI-assisted training analysis, the connector is live now and worth experimenting with; just know it's read-only and Claude-only for the moment.CPSC warns riders to immediately stop using Ridstar Q20 and Q20 Pro e-bikes — 11 fire incidents confirmed, manufacturer refuses recall — Don't buy — if you own a Ridstar Q20 or Q20 Pro, stop riding and charging it immediately, remove the battery, and contact your local household hazardous-waste program for disposal.Florida man sues Amazon and Chinese e-bike brand Bigniu after battery explodes during charging, causing severe burns and a residential fire — Monitor — if you own a Bigniu BG10 or any high-wattage moped-style 'e-bike' bought through Amazon without UL or equivalent certification, stop charging it unattended and check for any CPSC action.Garmin kicks off its biggest annual spring sale — deepest-ever discount on Fenix 8 Pro — while Apple's watchOS 27 (announced at WWDC) brings cycling power zone APIs and untethered Workout Buddy to the Apple Watch ecosystem — Monitor — if you've been waiting to buy a Fenix 8 Pro or Edge 1050, this is the window; for Apple Watch cyclists, wait for watchOS 27 public beta in July before committing to new workflows.TrainingPeaks-adjacent editorial debate: FTP vs. Critical Power — are coaches and platforms measuring the same physiological ceiling? — Monitor — no platform change to act on today; but if your training zones have felt off, ask your coach whether a CP test protocol would give you more accurate data than your current FTP estimate.Daily cycling intelligence from SEMIPRO CYCLING, produced with AI-assisted research, scripting, and synthetic voice.

Riley Hill and Tim Chaten discuss our experiences using beta 1 of iPadOS 27 and some thoughts about the announcements a week later. Early episodes are available by supporting the podcast at www.patreon.com/ipadpros. Early episodes are also now available in Apple Podcasts!Show notes are available at www.iPadPros.net. Feedback is welcomed at iPadProsPodcast@gmail.com.Links:- https://slatepad.org/2026/06/12/ipados-27-drops-support-for-the-legendary-2018-ipad-pro/- https://slatepad.org/2026/06/10/att-unlimited-day-pass-ipad/ Hosted on Acast. See acast.com/privacy for more information.

WWDC 2026 brought much more than AI hype. Get the recap on the overlooked updates to watchOS, CarPlay, iPadOS, and tvOS that could totally change how you use your Apple devices. Plus, Shortcuts just leveled up with powerful new triggers and AI-built automations! Siri AI waitlist and early impressions of New Siri WatchOS 27: Workout Buddy upgrades, Find My app, Siri app, & more iCloud+ adds AI feature limits and smarter home camera notifications CarPlay updates: video playback (when parked), audio scrubbing, wireless reliability iPadOS 27 changes driven by platform convergence and folding devices iPadOS improves multitasking, file transfers, and app name display in status bar tvOS updates: faster AirPlay, accessibility, podcast video support Shortcuts Corner: AI-powered shortcut creation and expanded automation triggers Hosts: Mikah Sargent and Rosemary Orchard Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today 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 Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

WWDC 2026 brought much more than AI hype. Get the recap on the overlooked updates to watchOS, CarPlay, iPadOS, and tvOS that could totally change how you use your Apple devices. Plus, Shortcuts just leveled up with powerful new triggers and AI-built automations! Siri AI waitlist and early impressions of New Siri WatchOS 27: Workout Buddy upgrades, Find My app, Siri app, & more iCloud+ adds AI feature limits and smarter home camera notifications CarPlay updates: video playback (when parked), audio scrubbing, wireless reliability iPadOS 27 changes driven by platform convergence and folding devices iPadOS improves multitasking, file transfers, and app name display in status bar tvOS updates: faster AirPlay, accessibility, podcast video support Shortcuts Corner: AI-powered shortcut creation and expanded automation triggers Hosts: Mikah Sargent and Rosemary Orchard Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today 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 Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

WWDC 2026 brought much more than AI hype. Get the recap on the overlooked updates to watchOS, CarPlay, iPadOS, and tvOS that could totally change how you use your Apple devices. Plus, Shortcuts just leveled up with powerful new triggers and AI-built automations! Siri AI waitlist and early impressions of New Siri WatchOS 27: Workout Buddy upgrades, Find My app, Siri app, & more iCloud+ adds AI feature limits and smarter home camera notifications CarPlay updates: video playback (when parked), audio scrubbing, wireless reliability iPadOS 27 changes driven by platform convergence and folding devices iPadOS improves multitasking, file transfers, and app name display in status bar tvOS updates: faster AirPlay, accessibility, podcast video support Shortcuts Corner: AI-powered shortcut creation and expanded automation triggers Hosts: Mikah Sargent and Rosemary Orchard Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today 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 Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

WWDC 2026 brought much more than AI hype. Get the recap on the overlooked updates to watchOS, CarPlay, iPadOS, and tvOS that could totally change how you use your Apple devices. Plus, Shortcuts just leveled up with powerful new triggers and AI-built automations! Siri AI waitlist and early impressions of New Siri WatchOS 27: Workout Buddy upgrades, Find My app, Siri app, & more iCloud+ adds AI feature limits and smarter home camera notifications CarPlay updates: video playback (when parked), audio scrubbing, wireless reliability iPadOS 27 changes driven by platform convergence and folding devices iPadOS improves multitasking, file transfers, and app name display in status bar tvOS updates: faster AirPlay, accessibility, podcast video support Shortcuts Corner: AI-powered shortcut creation and expanded automation triggers Hosts: Mikah Sargent and Rosemary Orchard Contact iOS Today at iOSToday@twit.tv. Download or subscribe to iOS Today at https://twit.tv/shows/ios-today 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 Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

John Gruber of Daring Fireball joins the MacBreak Weekly panel this week! A deep dive into Apple's new Siri following WWDC. Why Apple Intelligence & the new Siri is not coming to the EU initially later this year. And could the iPhone Ultra's launch be delayed this year? Private Cloud Compute Severely Limited for Third Party Devs. The future of Siri, or: why private inference isn't private enough. I tried Siri AI, and so far it actually works. How much Gemini is really inside Siri AI? The EU's DMA Folly. Reports of iPhone Ultra launch delays are 'false,' says leaker. Apple Vision Pro helped Disney re-engineer a classic EPCOT ride. Under-16 social media ban announced by UK government. Fox to Buy Roku Streaming Service in $25 Billion Deal. Picks of the Week Andy's Pick: Google Earth Flight Simulator for the Web John's Pick: Hovercraft Christina's Pick: Parachute Backup Hosts: Leo Laporte, Andy Ihnatko, and Christina Warren Guest: John Gruber 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 audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak hipebl.ai

John Gruber of Daring Fireball joins the MacBreak Weekly panel this week! A deep dive into Apple's new Siri following WWDC. Why Apple Intelligence & the new Siri are not coming to the EU initially later this year. And could the iPhone Ultra's launch be delayed this year? Private cloud compute severely limited for third party devs. The future of Siri, or: why private inference isn't private enough. I tried Siri AI, and so far it actually works. How much Gemini is really inside Siri AI? The EU's DMA Folly. Reports of iPhone Ultra launch delays are 'false,' says leaker. Apple Vision Pro helped Disney re-engineer a classic EPCOT ride. Under-16 social media ban announced by UK government. Fox to Buy Roku Streaming Service in $25 Billion Deal. Picks of the Week Andy's Pick: Google Earth Flight Simulator for the Web John's Pick: Hovercraft Christina's Pick: Parachute Backup Hosts: Leo Laporte, Andy Ihnatko, and Christina Warren Guest: John Gruber 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 audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak hipebl.ai

John Gruber of Daring Fireball joins the MacBreak Weekly panel this week! A deep dive into Apple's new Siri following WWDC. Why Apple Intelligence & the new Siri is not coming to the EU initially later this year. And could the iPhone Ultra's launch be delayed this year? Private Cloud Compute Severely Limited for Third Party Devs. The future of Siri, or: why private inference isn't private enough. I tried Siri AI, and so far it actually works. How much Gemini is really inside Siri AI? The EU's DMA Folly. Reports of iPhone Ultra launch delays are 'false,' says leaker. Apple Vision Pro helped Disney re-engineer a classic EPCOT ride. Under-16 social media ban announced by UK government. Fox to Buy Roku Streaming Service in $25 Billion Deal. Picks of the Week Andy's Pick: Google Earth Flight Simulator for the Web John's Pick: Hovercraft Christina's Pick: Parachute Backup Hosts: Leo Laporte, Andy Ihnatko, and Christina Warren Guest: John Gruber 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 audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zocdoc.com/macbreak hipebl.ai

Mon, 15 Jun 2026 17:15:00 GMT http://relay.fm/upgrade/622 http://relay.fm/upgrade/622 It's Doing It! 622 Jason Snell and Myke Hurley Back from WWDC, Jason and Myke have had more time to think about Apple's announcements--and to try many of them in beta releases. Siri AI impresses, we have Snow Leopard vibes, and much more. Back from WWDC, Jason and Myke have had more time to think about Apple's announcements--and to try many of them in beta releases. Siri AI impresses, we have Snow Leopard vibes, and much more. clean 6357 Back from WWDC, Jason and Myke have had more time to think about Apple's announcements--and to try many of them in beta releases. Siri AI impresses, we have Snow Leopard vibes, and much more. This episode of Upgrade is sponsored by: Sentry: Mobile crash reporting and app monitoring. New users get $100 in Sentry credits with code upgrade26. Decagon: The AI concierge for every customer. Get a personalized demo. ExpressVPN: High-Speed, Secure & Anonymous VPN Service. Links and Show Notes: Get Upgrade+. More content, no ads. Check out Upgrade merch! Submit Feedback Designed in California – Kickstarter Campaign Field Notes | Front Page Reporter's Notebook Mark Two – Studio Neat Sidekick Pocket – Cortex Brand macOS 27 will let you resize the iPhone Mirroring window - 9to5Mac Daring Fireball: Apple's Private Cloud Compute Is Severely Limited for Third-Party Developers WWDC 2026: Emptying the notebook about AI, bug fixes, and more – Six Colors That WWDC Glow – The Enthusiast All 264 Items on Apple's WWDC26 “Sweating the Details” Slide - TidBITS Mac OS X 10.6 Snow Leopard review | Macworld Daring Fireball: The Talk Show: Live From WWDC 2026 WWDC 2026: Between Seasons - MacStories Siri AI can do WAY more than you think – Ste

Finally catching up on the WWDC keynote and associated stories! - Sponsored by NordLayer: Get an exclusive offer - up to 22% off NordLayer yearly plans plus 10% on top with coupon code: macosken-10-NORDLAYER at nordlayer.com/macosken - Sponsored by Helix Sleep: Get 20% off Sitewide, 25% off Luxe Mattresses, and 30% off Elite Mattresses at helixsleep.com/macosken - Catch Ken on Mastodon - @macosken@mastodon.social - Send Ken an email: info@macosken.com - Chat with us on Patreon for as little as $1 a month. Support the show at Patreon.com/macosken

This week on Mac Geek Gab, you’re stacking up power moves from the jump. You’ll learn how to clean up messy lists in your favorite text editor, discover that any USB-C port on your MacBook can charge it, and find out why you should be charging your power bank from random ports instead of your iPhone or Mac. iPhones can now serve as Tailscale exit nodes — and that leads down a tangent where the guys dig deep into subnet routing so you understand exactly what that unlocks. You’ll also pick up how to save PDFs on iPhone when all you see is a print icon, how to use Apple Intelligence in Pages to reformat text as recipes, and how to clean up MacWhisper transcripts before anyone sees the raw chaos. Don’t Get Caught running Plex in Low Power Mode, either — there’s a fix for that. Dave also stumbled into a wild Fable moment when the AI found onto an unpublished API and decided to throttle itself back to Opus. Then the crew pivots to WWDC 2026 reactions, and there’s a lot to unpack. One big theme is refinement and stability: the new Liquid Glass slider is a visual treat, and Dave’s already running the beta without disaster. Apple Intelligence is getting a serious upgrade, with Siri becoming more contextually aware of what’s on your device, though the guys push back on where it still falls short compared to tools like Claude Cowork. Parental controls got a surprisingly large share of the spotlight for a developer conference, signaling Apple wants to own the conversation around kids and screen time — this leads to the interesting question of whether spouses can choose to hold each other accountable. Apple Vision Pro gets a Siri Orb and custom panoramas, and iOS 27 dev beta now includes a Recovery mode. Adam’s live from Nerdtacular 2026, and if you’re heading to Macstock, the discount code MACGEEKGAB saves you fifty bucks! 00:00:00 Mac Geek Gab 1146 for Monday, June 15th, 2026 00:03:35 June 15th: Take Your Cat to Work Day Pete lost his cat and she found her way home! MGG Monthly Giveaway – Win a license to SaneBox Quick Tips 00:00:01 Heidi-QT-Clean up messy lists with your favorite text editor 00:07:13 Dan DXZDB-QT-You can use your MacBook’s USB-C Ports to Charge it, too! AlDente 00:09:23 Chris-QT-1143-Charge your Power bank from random charging ports, not your iPhone or Mac 00:12:34 Dave (accidentally) ran into a Fable overstep! It had to throttle down to Opus after it found a company's unpublished API 00:15:03 Adam is at Nerdtacular 2026 Use the Mac Geek Gab app for the calendar Macstock MGG Discount Coupon: MACGEEKGAB 00:18:43 Phil-QT-Saving Documents as PDFs on iPhone When You Only See a Print Icon 00:20:42 Donald-QT-1145-iPhones can be used as Tailscale exit nodes 00:26:56 Tailscale Subnet Routing 00:29:19 Dom Bettinelli-QT-Clean Up your MacWhisper transcripts 00:30:44 Clif-QT-Use Apple Intelligence in Pages to Reformat as Recipes 00:31:50 QT-Low Power Mode vs. Plex on macOS Sponsors 00:36:38 SPONSOR: Decagon. Ready to transform your customer support? Decagon helps companies create personalized, concierge-style customer experiences with AI agents across chat, email, voice, and SMS. Go to https://decagon.ai/MGG to get a personalized demo and see what Decagon can do for your team. 00:38:16 SPONSOR: Shopify. In 2026, stop waiting and start selling with Shopify. Sign up for your one-dollar-per-month trial and start selling today at https://Shopify.com/MGG 00:39:57 SPONSOR: CleanMyMac. Get Tidy Today! Try 7 days free and use our code MACGEEK for 20% off at https://clnmy.com/MACGEEK WWDC Reactions 00:41:32 Operating Systems are focused on refinement Liquid Glass slider Dave's running the beta…successfully! 00:48:29 Apple Intelligence and Siri AI and Gemini and all of that “Profoundly more capable Assistant” Siri is aware of what's on my screen? 01:05:10 Where's the Siri equivalent of Claude Cowork? AI is Assistive Intelligence 01:13:11 WWDC Features Apple Vision Pro Siri Orb and Custom Panoramas 01:13:32 Parental Controls got a LOT of time…for a developer conference Apple wants to be a market leader here in solving this social problem Dave's question: Can my wife and I set up one another as accountability partners for screen time? 01:18:53 Richard-CSF-iOS27 Dev Beta has Recovery mode 01:21:00 MGG 1146 Outtro MGG Monthly Giveaway Bandwidth Provided by CacheFly Pilot Pete's Aviation Podcast: So There I Was (for Aviation Enthusiasts) The Debut Film Podcast – Adam's new podcast! Dave's Business Brain (for Entrepreneurs) and Gig Gab (for Working Musicians) Podcasts MGG Merch is Available! Mac Geek Gab iOS app Mac Geek Gab YouTube Page Mac Geek Gab Live Calendar This Week's MGG Premium Contributors MGG Apple Podcasts Reviews feedback@macgeekgab.com 224-888-GEEK Active MGG Sponsors and Coupon Codes List BackBeat Media Podcast Network

Discover the biggest announcements from WWDC 2026, including iOS 27 features, enhancements to Apple Home, Apple TV, and HomePod. This episode provides a comprehensive overview of new hardware and software updates, AI integrations, and home automation improvements that are shaping the future of smart living.Main Topics:New features and updates in iOS 27 and their implications for the Apple ecosystemEnhancements in Apple Home and Apple AI, including video analysis and device controlApple TV and HomePod updates, including faster performance and new capabilitiesHardware upgrades, discontinued models, and upcoming device expectationsExciting third-party integrations like Sonos shortcuts support, Eve Motion Blinds upgrades, and Philips Hue sports modeIn this episode:Apple announces support for video podcasts with chapters in iOS 27Faster device pairing, NFC reading, and Thread 1.4 support for enhanced connectivityIntroduction of new Apple Home widgets, energy monitoring, and Apple Intelligence for smarter automationSignificant improvements to Apple TV and HomePod with app launch speeds, Automix feature, and TV OS updatesDiscontinuation of older Apple TV models and speculation on upcoming hardware releasesSupport for Matter devices and enhanced camera features for security and video feedsNew third-party integrations including Sonos shortcut commands, Eve Motion Blinds upgrade kit, and Philips Hue's live sports modeInsights into the upcoming smart home landscape, Apple's hardware roadmap, and practical tips for usersSend me your smart home questions and recommendations with the hashtag #SmartHomeInsider. Tweet and follow your host at:@andrew_osu on Twitter@andrewohara941 on ThreadsEmail me hereSponsored by:Shopify: Sign up for a one-dollar-per-month trial period at shopify.com/homekit!CleanMyMac: Get Tidy Today! Try 7 days free and use my code SMARTHOME for 20% off at https://clnmy.com/SMARTHOMENordStellar: Get an exclusive offer: Unlock your 10% discount on NordStellar with the coupon code: SMARTHOMEINSIDER10  - Just mention it to NordStellar!Smart Home Insider YouTube ChannelSubscribe to the Smart Home Insider YouTube Channel and watch our episodes every week! Click here to subscribe.Links from the showtvOS 26 New Features videoSonos Shortcuts UpdateGovee Ice Make 2 ProHue Live Sports UpdateThose interested in sponsoring the show can reach out to us at: andrew@appleinsider.com

Sun, 14 Jun 2026 15:00:00 GMT http://relay.fm/mpu/853 http://relay.fm/mpu/853 Siri AI and WWDC 2026 853 David Sparks and Stephen Robles Stephen reports live from Apple Park on WWDC 2026: the post-keynote tech talk, Gemini partnership explained, and Siri AI that finally works. Plus shortcuts, photos AI, and more. Stephen reports live from Apple Park on WWDC 2026: the post-keynote tech talk, Gemini partnership explained, and Siri AI that finally works. Plus shortcuts, photos AI, and more. clean 4452 Stephen reports live from Apple Park on WWDC 2026: the post-keynote tech talk, Gemini partnership explained, and Siri AI that finally works. Plus shortcuts, photos AI, and more. This episode of Mac Power Users is sponsored by: Daylite: The only made-for-mac CRM solution. Start your free trial today. Workbrew: Deliver the software your team needs securely and at scale. Mercury Weather: Forecasts, beautifully done. Download now for free. Squarespace: Save 10% off your first purchase of a website or domain using code MPU. Links and Show Notes: Credits The Mac Power Users Stephen Robles David Sparks The Editor Jim Metzendorf The Fixer Kerry Provanzano More Power Users: Ad-free episodes with regular bonus segments Submit Feedback macOS Features Wall of Text — Basic Apple Guy Shortcuts Just Changed Forever - YouTube Apple unveils next generation of Apple Intelligence, Siri AI, and more - Apple Bridget Photo - Original Bridget Photo - Extended Bridget Photo - Clean Up UniFi Travel Router Stephen Robles Primary Technology iJustine John Gruber (Daring Fireball) Joanna Stern (WSJ) Nilay Patel (The Verge) Bridget Carey (CNET) Andrew O'Hara (AppleInsider) Federico Viticci (MacStories) Mike Hurley (Relay FM) LM Studio DEVONthink Bear Fastmail Perplexity changedetection.io Pushcut Data Jar MPU 852

Apple's Worldwide Developers Conference happened this week, and there was enough going on that we wanted to unpack the whole thing, primarily due to the company's uncharacteristic backpedaling on its... controversial Liquid Glass UI language, not to mention the unusual focus on CPU scheduling and numerous other performance refinements across the board in this year's OS updates, rather than the more typical long list of new features. It was enough to get us saying the words "Snow Leopard," which is always a good feeling. We also consider new broader parental controls, the apparently final state of Apple Intelligence and Siri AI features, and more. Support the Pod! Contribute to the Tech Pod Patreon and get access to our booming Discord, a monthly bonus episode, your name in the credits, and other great benefits! You can support the show at: https://patreon.com/techpod

This week is all about Apple WWDC! Marques, Andrew, and David go over everything new coming to your Siri. Including some improvements to Siri, new features for Siri, and believe it or not a whole new Siri! Oh yeah, and they talk about some of the new things coming to iOS, MacOS, and VisionOS too. Then they wrap it all up with some trivia. Enjoy! Links: Apple WWDC 26 keynote XBOX 25th anniversary edition Claude Fable This episode brought to you by: ChefIQ: https://chefiq.com/discount/WAVE Framer: https://www.framer.com/wave Zapier: https://www.zapier.com/wave Follow us on socials: Marques: https://twitter.com/MKBHD Andrew: https://www.instagram.com/andrew_manganelli/ David: https://www.instagram.com/davidimel/ Adam: https://www.instagram.com/parmesanpapi17/ Ellis: https://twitter.com/EllisRovin Rufus: https://www.instagram.com/rmullhaupt/ Waveform: Twitter: https://twitter.com/WVFRM Threads: https://www.threads.net/@waveformpodcast Instagram: https://www.instagram.com/waveformpodcast/ TikTok: https://www.tiktok.com/@waveformpodcast Join the Discord: https://discord.gg/mkbhd Intro/Outro music by 20syl: https://bit.ly/2S53xlC Waveform is part of the Vox Media Podcast Network. Learn more about your ad choices. Visit podcastchoices.com/adchoices

We're all starting to test Apple's newest software post-WWDC, and the most surprising thing has happened: Siri actually seems to be pretty good now. Nilay and David discuss how that happened, and what it means for the AI industry, and all of us, that Apple's voice assistant is finally useful. Then, we have some news about Bluesky, Threads, and YouTube that adds up to a big change in social networks, plus the Hype Desk, Brendan Carr, the Trump Phone, and a really great deal for iPad users Further reading: Apple announces Siri AI and its next generation of Apple Intelligence  I tried Siri AI, and so far it actually works  Apple's new Siri AI knows when to shut up  I'm relieved Siri AI isn't trying to be a health coach  You can just tell the Instagram algorithm what you want now  YouTube is introducing DMs (again)  Bluesky is getting ‘communities'  Anthropic releases its first Mythos-class model Claude Fable   Claude Fable won't answer basic biology questions  Anthropic apologizes for invisible Claude Fable guardrails  Microsoft restricts Claude Fable for employees over data retention concerns  YouTube is introducing DMs (again)  Bluesky is getting ‘communities'  iFixit Trump phone teardown confirms it's an HTC dupe Solar has overtaken coal in the US for the first time AT&T is launching $3 ‘unlimited' day passes for iPads Subscribe to The Verge for unlimited access to theverge.com, subscriber-exclusive newsletters, and our ad-free podcast feed.We love hearing from you! Email your questions and thoughts to vergecast@theverge.com or call us at 866-VERGE11. (Timestamps are approximate.) 00:00:00 Intro 00:03:00 New Siri is good 00:04:00 Search Index Breakthrough 00:08:00 Cloud vs On Device 00:11:00 Siri Upends AI Apps 00:20:00 Where Is The Computer 00:24:00 EU Interoperability Fight 00:31:00 Social News Lightning Trio 00:33:00 Mosseri Algorithm Control 00:35:00 Bluesky Communities 00:37:00 YouTube DMs Social Push 00:41:00 Bluesky Bets on Communities 00:50:00 Talking to Your Algorithm 00:51:00 AI Made-to-Order Instagram 00:54:00 Bespoke Apps Break Reality 01:01:00 Hype Desk 01:02:00 Social Reckoning Trailer Breakdown and Casting 01:14:00 CBS News Meltdown 01:17:00 Carr vs Newsrooms 01:20:00 SpaceX IPO Favors 01:24:00 Claude Fable Guardrails 01:30:00 Trump Phone Teardown 01:34:00 AT&T iPad Day Pass 01:36:00 Solar Beats Coal 01:38:00 Signoff Learn more about your ad choices. Visit podcastchoices.com/adchoices

This year at WWDC we had a ton of new updates for iOS 27! We'll discuss that at more in this all new episode of Same Brain with our guest host Joe Cirillo 0:00:00 - Intro0:27:25 - Who is Joe?2:51:01 - Justine wanted to be a programmer3:58:12 - Let's talk vibe coding6:51:26 - Snack break8:01:05 - The new Siri11:21:08 - Apple world knowledge12:22:29 - New AI camera features14:17:24 - New child protection features17:24:26 - New way to do shortcuts19:50:00 - Seeing WWDC for the first time24:00:23 - Justine's Pokopia addiction28:07:22 - Outro

Finally, we know everything about iOS 27, iPadOS 27, macOS Golden Gate, and more. Except there is still so much to find out, and especially now that we're diving into the betas on the AppleInsider Podcast.Contact your hosts:@williamgallagher_ on Threads@WGallagher on TwitterWilliam's 58keys on YouTubeWilliam Gallagher on emailWes on BlueskyWes Hilliard on emailWes's blog HillitechSponsored by:NordStellar: Unlock your 10% discount at nordstellar.com/appleinsider with the coupon code nordappleinsider-10-NORDSTELLARScribe: Book an enterprise demo at scribe.how/appleinsiderLinks from the Show:The last good morning: Celebrities help Tim Cook start WWDCAppleInsider at Apple Park before the WWDC 2026 keynoteRevamped parental controls are coming to iPhone, Mac, and MoreNew, more personal Siri AI is set to arrive in 2026Apple's new foundation models don't contain a drop of GeminiApple's expanded child safety features aren't going to protect kids from everythingLiquid Glass changes in macOS 27 are minorSpatial Reframe in iOS 27 is a neat trick that creates nightmare fuel right nowHands on with AirPods EQ settings in iOS 27Image Playground gets realistic AI image generation in iOS 27macOS Golden Gate menus revert to having no icons by each item, as it should bePretty trees and Local Lists: Apple Maps gets a big upgrade in iOS 27Expect more controllers & objects for Apple Vision Pro thanks to visionOS 27Hands on: iPadOS 27's shortcut builder creates automations from plain EnglishmacOS 27 'Golden Gate' delivers more Liquid Glass and updated SiriiOS 27 gets better Liquid Glass and more responsivenessLiquid Glass customization & better Apple Intelligence arrive with iPadOS 27Spatial computing & Apple Intelligence upgrades collide in visionOS 27Coaching, wellness features & AI make the biggest impact in watchOS 27tvOS 27 sneaks out with redesigned Podcasts app & AI subtitle generationApple Vision Pro's biggest problem isn't addressed in visionOS 27, but progress is progress  iOS 27 keeps iPhone 11 and newer compatibilitymacOS 27 compatibility list focuses entirely on Apple SiliconwatchOS 27 supported by just six Apple Watch modelsiPadOS 27 cuts off a few favorite iPad models For the first time in four years, tvOS cuts off some older Apple TV hardwareSupport the show:Support the show on Patreon or Apple Podcasts to get ad-free episodes every week, access to our private Discord channel, and early release of the show! We would also appreciate a 5-star rating and review in Apple PodcastsMore AppleInsider podcastsTune in to our HomeKit Insider podcast covering the latest news, products, apps and everything HomeKit related. Subscribe in Apple Podcasts, Overcast, or just search for HomeKit Insider wherever you get your podcasts.Subscribe and listen to our AppleInsider Daily podcast for the latest Apple news Monday through Friday. You can find it on Apple Podcasts, Overcast, or anywhere you listen to podcasts.Those interested in sponsoring the show can reach out to us at:...

Amanda Silberling of TechCrunch joins Mikah Sargent this week! Anthropic launches Fable 5, its newest AI model. The FCC seeks to end the use of burner phones in the US. And everything Apple unveiled at WWDC 2026. Amanda talks about Anthropic's newest AI model, Fable 5, its first consumer-accessible version of its powerful Mythos model. Mikah shares a story from 404 Media about the FCC's push to end anonymous "burner phones," raising significant concerns about the privacy implications for people who rely on them for legitimate reasons. And Dan Moren of SixColors joins the show to break down WWDC 2026's latest announcements, including a revamped AI-powered Siri and a privacy-first approach to its new intelligence features. Hosts: Mikah Sargent and Amanda Silberling Guest: Dan Moren 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: joindeleteme.com/twit promo code TWIT bitwarden.com/twit hipebl.ai

Now that we've had a couple of days to digest all the Siri AI updates, the new corner radii, and everything else Apple announced at its developer conference, we spend the episode answering all your most burning questions. What non-AI stuff are we excited about? How much catching up did Siri really do this week? And wait: what about the HomePod? Further reading: ⁠WWDC 2026: All the news from Apple's developers conference⁠ ⁠5 things I already love from the iOS 27 beta⁠ ⁠Subscribe to The Verge⁠ for unlimited access to ⁠theverge.com⁠, subscriber-exclusive newsletters, and our ⁠ad-free podcast feed⁠.We love hearing from you! Email your questions and thoughts to ⁠vergecast@theverge.com⁠ or call us at 866-VERGE11. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Recorded in front of a live audience at The California Theatre in San Jose on Tuesday 9 June 2026, special guests Joanna Stern and Nilay Patel join John Gruber to discuss Apple's announcements at WWDC 2026.

Apple held its big WWDC 2026 keynote and introduced the new Siri AI for iOS 27, with sign-ups now available for the iOS 27 beta. However, Siri AI will be delayed in the EU for iOS and iPadOS 27. Liquid Glass has some opt-in options to roll back elements of the design. And Apple highlights its commitment to child safety with new child-safety features in its operating systems. WWDC 2026: Everything announced on Siri AI, iOS 27, Apple Intelligence and more. iOS 27 tidbits: share a phone number on two iPhones, independent alarm volume, faster AirPlay and more. OS overview - top OS features. Apple previews new child safety features. Introducing the third generation of Apple's foundation models. New dummy units give our closest look yet at the iPhone Fold. visionOS 27 features a new Thórsmörk Environment. Due to DMA, Siri AI delayed in EU for iOS 27 and iPadOS 27. No tech rule exemption for Apple, EU regulators say amid spat over Siri AI delay. Picks of the Week Leo's Pick: Optimized Pancakes Andy's Pick: PhotoRec Christina's Pick: Chipotlai Max Mikah's Pick: "The Chaos" (1922) by Gerard Nolst Trenité Hosts: Leo Laporte, Andy Ihnatko, and Christina Warren Guest: Mikah Sargent 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 audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: hipebl.ai helixsleep.com/macbreak

#862: Neal and Toby discuss the biggest news coming out of WWDC 2026, and why North Korea's economy is experiencing its strongest growth in years. Plus, Lavazza introduced a new single-serve coffee system that uses 100% coffee tabs with no plastic. Finally, why your co-worker might be listening to music tuned to 432 hertz. To learn more visit https://www.sage.com/morningbrew Subscribe to Morning Brew Daily for more of the news you need to start your day. Share the show with a friend, and leave us a review on your favorite podcast app. Listen to Morning Brew Daily Here:⁠ ⁠⁠https://www.swap.fm/l/mbd-note⁠⁠⁠  Watch Morning Brew Daily Here:⁠ ⁠⁠https://www.youtube.com/@MorningBrewDailyShow⁠ This is a paid advertisement. Today's episode of the Morning Brew Daily Show is brought to you by Sage — a trusted global provider and leader in accounting, financial, HR, and payroll technology for small and mid-sized businesses. The following commentary reflects general information about Sage and its products. Specific features, capabilities, and availability may vary by product, region, and customer requirements. To find out more, visit sage.com/morningbrew. Learn more about your ad choices. Visit megaphone.fm/adchoices

Apple's annual developer conference keynote was a strange one this year. The company breezed by its normal slew of operating system upgrades, and talked instead about helping people manage their relationships with their devices, and AI. Lots and lots of AI. On this post-keynote livestream, David Pierce, Hayden Field, and Jake Kastrenakes give their first takes on Siri AI, the Apple Intelligence features coming this fall, Apple's new Screen Time design, and everything else we liked and disliked from the keynote. Including the corner radii. Further reading: ⁠Apple WWDC 2026: The 7 biggest announcements⁠ Subscribe to The Verge for unlimited access to theverge.com, subscriber-exclusive newsletters, and our ad-free podcast feed.We love hearing from you! Email your questions and thoughts to vergecast@theverge.com or call us at 866-VERGE11. (Timestamps are approximate.) 00:00:00 Intro 00:03:00 Why This Keynote Felt Chaotic 00:05:00 AI Takes Center Stage 00:06:00 Apple Plays Catch Up 00:09:00 Privacy and Private Cloud 00:12:00 Useful Versus Creepy AI 00:18:00 Why Apple Went All In 00:25:00 New Siri Voice 00:33:00 Siri App Intents 00:37:00 Vibe Coding Shortcuts 00:39:00 Siri Goes Orb Mode 00:41:00 Too Many Siri Gestures 00:42:00 Apple Trust and Screen Time 00:46:00 Kids Safety and App Responsibility 00:50:00 App Store Dissonance and Regulation 00:52:00 OS 27 Device Cutoffs 00:59:00 Favorite Features and Liquid Glass 01:04:00 Dictation Confusion and Wrap Up Learn more about your ad choices. Visit podcastchoices.com/adchoices

An astronomical amount of money is being poured into AI and data centers as tech giants fight for dominance, but is this fueling the next big tech bubble or just the price of staying in the game? Get the panel's opinions on wild IPO valuations, global power grabs, Build 2026, NVIDIA GTC Taipei, and even successful YouTuber movies! SpaceX IPO to Be Largest Ever at $135 Share Price Utah residents sue officials over Kevin O'Leary data center plan When AI builds itself NVIDIA announces RTX Spark as 'the most efficient PC chip ever built' Major Homebuilder To Test Placing Mini Data Centers in Suburban Backyards Microsoft Build 2026: The 7 biggest announcements What to Expect at Apple's WWDC 2026: iOS 27, New Siri and AI Meta Silently Added Face-Recognition Code for Its Smart Glasses to Millions of Phones Trump Signs Executive Order Seeking Oversight of A.I. Models Trump: U.S. stake in AI giants "could be a beautiful thing" Cable lobby warns of chaos if FCC doesn't relax ban on foreign routers Google ordered to put clearer links in AI search and let UK publishers opt out AT&T and Verizon lose Supreme Court case over fines for selling location data YouTubers Win the Box Office, Goodbye Gatekeepers, The YouTube Bar YouTube overtakes Netflix in average daily viewing around the world Host: Leo Laporte Guests: Joey de Villa, Jeff Jarvis, and Fr. Robert Ballecer, SJ Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: expressvpn.com/twit ZipRecruiter.com/twit canary.tools/twit - use code: TWIT Melissa.com/twit helixsleep.com/twit

Tom, Sarah, Robb, and Nica Montford from SnobOS break down what just happened at WWDC.Starring Tom Merritt, Robb Dunewood, Sarah Lane, and Nica MontfordShow notes can be found here. Hosted on Acast. See acast.com/privacy for more information.

Next week is Apple's WWDC conference, but this week was all about Microsoft. But first, Andrew showed off his new DIY smartwatch to Marques and David. Then they go over the new announcements from Microsoft and NVIDIA including a new chip that might finally be some competition for the M-series chips. Allegedly. Maybe. Of course, we wrap it all up with trivia! Links: Fitbit Air mods Ollee watch Cam Shand - Ollee watch video 9to5Google - Opting out of AI overview in Google search Verge - Gemini Spark Microsoft - RTX spark Microsoft Surface Ultra Verge - Microsoft Project Solara Agent OS Newswire - Microsoft Banks Claude Code This episode brought to you by: ChefIQ: https://chefiq.com/discount/WAVE Shopify: https://www.shopify.com/wave Follow us on socials: Marques: https://twitter.com/MKBHD Andrew: https://www.instagram.com/andrew_manganelli/ David: https://www.instagram.com/davidimel/ Adam: https://www.instagram.com/parmesanpapi17/ Ellis: https://twitter.com/EllisRovin Waveform: Twitter: https://twitter.com/WVFRM Threads: https://www.threads.net/@waveformpodcast Instagram: https://www.instagram.com/waveformpodcast/ TikTok: https://www.tiktok.com/@waveformpodcast Join the Discord: https://discord.gg/mkbhd Intro/Outro music by 20syl: https://bit.ly/2S53xlC Waveform is part of the Vox Media Podcast Network. Learn more about your ad choices. Visit podcastchoices.com/adchoices