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

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

Hey yall, Alex here, Huge thanks to Wolfram for running point on the live show this week. Didn't have tons of time to edit this one, so please skip the first 10 minutes, it's a loop of our new “wait for the live show to start” vid, that I build with HyperFrames and can't wait to tell you about, next week! Today it seems that OpenSource is biting back, with Kimi K3 getting released just a short while after Thinking Machines (Thinky) has released Inkling, their near 1T model. I'm attaching the TL;DR and timestamps for the full show (my AI agents, yes even Fable and Sol are not a match yet at editing down hehe) and I'll spare you the long Fable recap (please do let me know in the comments if you were expecting it) 0:00 – Intro, Alex on vacation, TLDR overview11:35 – TLDR: Thinking Machines, open source, OpenAI news12:34 – Banter: impressions of Sol/Codex, over-verification behavior37:22 – TLDR restart & detailed breakdown48:40 – Open Source AI section begins (Bonsai/Prism ML, Kimi K3)58:42 – Inkling (Thinking Machines) deep dive & 3D model visualization1:10:33 – Kimi K3 discussion & demo comparisons1:27:02 – Frontier Labs: AGI governance framework discussion (Demis Hassabis essay)1:47:04 – Grok Build CLI data leak & OpenAI file deletion incident2:02:15 – This Week's Buzz: Wolfbench results on GPT 5.6 Sol/Terra/Luna2:09:52 – Closing remarks & sign-offThe one-minute version: Mira Murati's Thinking Machines released Inkling, a 975B parameter open-weights MoE under Apache 2.0, the top US open-weights model right now. Moonshot's Kimi K3 went from rumor to released API during the show, confirmed at 2.8 trillion parameters with open weights promised within days, and it's already topping early arena boards. PrismML's Bonsai 27B squeezes a full 27B model into 3.9 gigabytes so it runs on a phone. Codex and ChatGPT Work blew past 9 million users, OpenAI confirmed and explained the Sol file-deletion bug (back up your machines, folks), and xAI's Grok Build CLI got caught uploading entire private repos before open-sourcing the whole thing in response. Plus Wolfram's fresh Wolfbench numbers on the GPT-5.6 family in This Week's Buzz

White Mountain Apache chef Nephi Craig had an unconventional culinary path: from a reservation to a fine dining restaurant to cooking for 7,800 inmates while in county jail. Now he's the executive chef at Café Gozhóó. He spoke with Terry Gross about Native cuisine, getting sober, and bringing nutrition education and addiction treatment to his community on the reservation. His memoir is ‘Our Knives Will Save Us.' Also, John Powers reviews the big tech heist novel ‘Cloudthief' by Nathaniel Rich. Subscribe to our free weekly newsletter Follow us on Instagram Subscribe to our YouTube channel Check out the Fresh Air ArchivesSee pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

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

White Mountain Apache chef Nephi Craig had an unconventional culinary path: from a reservation to a fine dining restaurant to cooking for 7,800 inmates while in county jail. Now he's the executive chef at Café Gozhóó. He spoke with Terry Gross about Native cuisine, getting sober, and bringing nutrition education and addiction treatment to his community on the reservation. His memoir is ‘Our Knives Will Save Us.' Also, John Powers reviews the big tech heist novel ‘Cloudthief' by Nathaniel Rich. Subscribe to our free weekly newsletter Follow us on Instagram Subscribe to our YouTube channel Check out the Fresh Air ArchivesSee pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

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Host Andrew Camp interviews Nephi Craig, executive chef of Café Gozhoo on the White Mountain Apache Tribe, relapse prevention specialist, and founder of the Native American Culinary Association, on the release of his memoir Our Knives Will Save Us. Craig describes writing the book as a tool about the “ingredients of a chef,” linking his 15 years of sobriety, relapse history, and healing to cooking and indigenous foods. He explains how kitchen discipline and mentors shaped him, why indigenous cultivars and foodways connect to public and mental health, and how colonization's violence and intergenerational trauma relate to addiction and health disparities. Craig details Café Gozhoo as a recovery-oriented, clinically designed, non-hierarchical kitchen emphasizing excellence, work-life balance, and Native values, discusses NACA's grassroots impact, and answers food questions, including avoiding snake and bear, loving pho, and naming a last meal featuring Apache racket bread.Nephi Craig is the executive chef of Café Gozhóó in Whiteriver, Arizona, on the White Mountain Apache Tribe, and an advanced certified relapse prevention specialist (ACRPS) and behavioral health technician (BHT) currently serving as the nutritional recovery program coordinator at the Rainbow Treatment Center. Craig is the founder of the Native American Culinary Association (NACA), an organization that is dedicated to the research, refinement, and development of Native American cuisine. His work has been recognized in national and international publications such as Newsweek, Forbes, Food & Wine, and The Guardian.Follow Nephi on Instagram: @nephi_craigBuy Our Knives Will Save UsFollow Andrew CampFacebook: andrew.camp.9Instagram: @andrewcamp80Substack: @thebiggesttableThis episode of the Biggest Table is brought to you in part by Wild Goose Coffee. Since 2008, Wild Goose has sought to build better communities through coffee. For our listeners, Wild Goose is offering a special promotion of 20% off a one time order using the code TABLE at checkout. To learn more and to order coffee, please visit wildgoosecoffee.com. 

Special Guest David Culler (Cobra and Apache pilot) joins us to talk about the Apache pilots that were grounded and a wild video of a Bell 206 spinning near the ground. Plus HAF F-16 Gear Up Landing, NetJets NTSB Preliminary Report, and more! Another wild week in aviation. Bring your questions! Fighter pilots break down the biggest aviation stories of the week. Recorded real time with no edits!This Weeks Timeline and Topics!00:00 Intro07:30 Apache Pilots Grounded and Then Ungrounded44:44 Helicopter Doing Helicoptery Things1:04:00 HAF F-16 Gear Up Landing1:15:27 NetJets NTSB Preliminary Report1:28:50 737-400 Freighter Lost1:38:24 Instructor Jumps From Aircraft1:51:0 China Building J-20s Fast2:10:26 B-21 Will Have Two Person Crew2:22:30 Outro and Goodbye!Go here to support the channel. https://www.themoverandgonkyshow.comFor sponsorships and business inquiries: themoverandgonkyshow@gmail.comMost Mondays at 8PM ET, Mover (F-16, F/A-18, T-38, 737, 787, helicopter pilot, author, cop, and wanna be race car driver) and Gonky (F/A-18, T-38, A320, dirt bike racer, author, and awesome dad) discuss everything from aviation to racing to life and anything in between. More About Mover:Mover's YouTube Channel: https://www.youtube.com/@CWLemoineLooking for a good book? https://www.cwlemoine.comMore About Gonky:Gonky's YouTube Channel: https://www.youtube.com/@therealgonkyKids Coloring and Activity Books! https://www.amazon.com/stores/author/B0CDS4C68Y*The appearance of U.S. Department of War (DoW) visual information does not imply or constitute DoW endorsement.Views presented are our own or our guests and do not represent the views of DoW or its Components.*

Join Jim and Greg for the Friday 3 Martini Lunch as they walk through the many Candace Owens conspiracy theories proven wrong in this week's hearings in the Charlie Kirk murder case, a surprising new poll of American Jewsish voters, a Wisconsin candidate using the Green Bay Packers as an example of socialism, and Apache helicopter pilots cleared after a controversial flyover last week.First, they walk through the mountain of evidence revealed in the preliminary hearings for the case against Tyler Robinson, who is accused of murdering Charlie Kirk last year in Utah. They walk through the the facts and how they blow up so many conspiratorial narratives put forth by Candace Owens and others. But they doubt the conspiracies will stop.Next, they react to an AP poll of Jewish Americans that shows they approve of New York City Mayor Zohran Mamdani much more than Israeli Prime Minister Benjamin Netanyahu. Jim explains why this is not a huge surprise to him but how it's also a disturbing result.Then, they laugh as a socialist running for governor in Wisconsin uses the Green Bay Packers as a positive example of socialism. Jim and Greg explain why the far left is using rhetoric like this and why the the Packers analogy is ridiculous.Finally, they react to eight South Carolina Air National Guard Apache pilots getting suspended for their conduct during a beach flyover but having those suspensions lifted by Sec. Pete Hegseth.Please visit our great sponsors:ZocDocYour health matters and taking care of yourself shouldn't be complicated. Find and book the right doctor with Zocdoc. Head to https://ZocDoc.com/3ML Noble GoldOwn the metal the future depends on. Visit https://NobleGoldInvestments.com/3MLDownload the free investor kit. No pressure. Just the information.New episodes every weekday. 

Join Jim and Greg for the Friday 3 Martini Lunch as they walk through the many Candace Owens conspiracy theories proven wrong in this week's hearings in the Charlie Kirk murder case, a surprising new poll of American Jewsish voters, a Wisconsin candidate using the Green Bay Packers as an example of socialism, and Apache […]

Hour Two of The Marc Cox Morning Show opens with a life-threatening flash flood warning for Iron and Reynolds County before celebrating Palm Beach's new Donald J. Trump International Airport and questioning why patriotic Apache pilots got suspended for a 250th birthday flyover. The St. Louis Morning Brief delivers real accountability with the new Bentley and Mason's Law forcing drunk drivers to pay child support, alongside a heartbreaking Belleville case and Marc's fiery takedown of an activist judge upholding Illinois' gun ban. Marc urges every listener to download his voter guide ahead of Missouri's Amendment 4 and Amendment 5 primary vote, and financial reporter Nicole Murray breaks down market gains and local layoffs. The hour wraps with In Other News' wildest headline yet: a student pilot's miracle landing after her instructor jumped from the plane mid-flight, plus a lioness who spared a cattle herder in India. Straight talk, faith, family, and common sense — that's The Marc Cox Morning Show on 97.1 Talk. Hashtags: #MarcCoxMorningShow #971Talk #StLouis #StLouisMorningBrief #InOtherNews #TrumpAirport #VoterGuide #GunRights #NicoleMurray #FaithFamilyFreedom #ConservativeTalk #America250

"Life is supposed to be challenging, but it is not supposed to be stressful." - Ten Bears, Maria's great-grandfather *** Mellissa Seaman on sensory intelligence, subtle sensation, and what she learned from her Apache teacher, Maria Yraceburu, about the body's language. Tingles up your spine. A sick feeling in your gut. Sparkles at the edges of your vision. They mean three different things. But no one taught us in grad school how to translate subtle sensations. Honestly, even most intuitive training systems can't tell you the difference. When Mellissa met Maria, she finally met a teacher who knew the difference. Maria learned the map of the eight atmospheric layers of the energy body when she was still a kid. Growing up on the White Mountains Reservation, she practiced using all eight sensory layers to track and hunt rabbits. She sat with her great-grandfather, who used the eight sensory layers of the art of Ya'Odishido, sensual telepathy, as part of everyday life. A lot of us have general tags for this stuff. My intuition says this. My gut says that. But what am I actually feeling? This one's about sensory intelligence, instinct as the body's language, and the way subtle sensations can carry information before the mind has words. Maria talks about the difference between intellect, intuition, and instinct. She keeps correcting how most of us collapse instinct into fight-or-flight. Nope. Instinct is primal, often subtle, sensation. And in a world where we think every pain or pinch or tension is "wrong," Maria's suggestion is a real turnaround: Don't run from your sensations. Find out what they mean.   In this episode: Why tingles, gut feelings, and sparkles at the edge of your vision may mean different things What Maria teaches about the eight atmospheric layers and Ya'Odishido Why instinct is the body's language, not just fight-or-flight How subtle sensation can help with real decisions involving money, calendars, and people Why the land is part of the conversation How "I don't know. Show me what I need to know" becomes the starting place If you are sensitive enough to feel the room, the client, the decision, and the stress-frequency of the humans around you, this one will help you stop dumping every sensation into one overwhelmed pile.    More Resources:  Take the Soul Gift Quiz: https://www.soulgiftquiz.com   Join the FREE Explore Your Gifts Circle: https://academy.channelyourgenius.com/explore     Connect with Mellissa Website: https://www.channelyourgenius.com   Instagram: https://www.instagram.com/MellissaSea    YouTube Channel: https://www.youtube.com/@channelyourgenius    Substack: mellissaseaman.substack.com   Keywords Intuitive gifts, spiritual gifts, Soul Gifts, Specialist archetype, Channel Your Genius, Genius Activation, grounded intuition, soul-led business, intuitive leadership, spiritual awakening at midlife

Before Dustin Chappel ever stepped onto the battlefield, he had already spent his childhood fighting to survive.Separated from his mother at just two years old, Dustin endured years of abuse, instability, homelessness, and constant moves before eventually dropping out of school and earning his GED. After witnessing the attacks of September 11th, he felt called to serve and joined the U.S. Army as a 12B Combat Engineer.During two deployments to Iraq, Dustin conducted route-clearance missions, hunted insurgents, executed raids alongside infantry units, and survived some of the most dangerous streets in Baghdad. He describes a deployment where every patrol felt like "Russian roulette," facing complex ambushes, sniper fire, RPGs, and one of the most disturbing traps of the entire war... a body rigged to explode.But this story doesn't end on the battlefield. Dustin opens up about the sniper round that was meant for him, dragging his wounded squad leader out of the line of fire, and the long road home — his fight with PTSD, checking himself into treatment, rebuilding his life, and the work he does today mentoring fellow veterans.

Tonight on Gulf War Side Effects, Kevin Simon and Wade welcome Todd Branda, a former AH-64 Apache pilot who flew combat missions during Operation Desert Storm.Get access to past and bonus content with exclusive guest. Please help support the podcast and veterans so we can keep making the show - patreon.com/GulfWarSideEffects▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬Merch: https://gulfwarsideeffects.myshopify....Contact me with your questions, comments, or concerns at kevinsimon@gulfwarsideeffects.com

Denny Lee is PM Director, Startups & Ecosystem at Databricks, a longtime Apache Spark, MLflow, and Delta Lake contributor — and one of the people behind Omnigent, the open-source meta-harness Databricks just released under Apache 2.0. He joins Demetrios to explain why the industry is moving from models to harnesses to meta-harnesses, why token spend is replaying the CapEx-to-OpEx shift all over again, and why he's using debating AI agents to plan a matcha farm in Taiwan.In this episode:

A hard wheat year can still teach Oklahoma producers something useful about risk, timing, and variety decisions. In this episode of the Red Dirt Agronomy Podcast, Dave Deken, Brian Arnall Ph.D., and Josh Lofton Ph.D. talk with Amanda Silva Ph.D., Oklahoma State University Extension small grains specialist, about the 2026 Oklahoma wheat crop. They discuss drought stress, scattered rainfall, early crop development, planting date decisions, test weight, wheat streak mosaic virus, and what variety trials can still tell farmers in a difficult year. Key takeaways: Rain timing drove much of the difference between fields, even within the same county. Earlier crop development, warm winter conditions, and a cooler grain-fill period shaped yield and test weight outcomes. Planting date can be used as a risk-management tool, especially when paired with different maturity groups. Wheat variety trials are still valuable in stressful years, but researchers must carefully judge data quality, CV, blocks, and field variability. OSU research continues on late-planted wheat, seeding rates, nitrogen management, forage production, coleoptile length, and deeper planting to chase moisture. Detailed timestamped rundown 00:00–02:14 — Intro and setup Dave opens Episode 514 by framing the conversation around the Oklahoma wheat crop and why a hard year can still shape decisions for future crops. He also promotes the Summer Crop Demo Day near Chickasha and introduces Brian Arnall Ph.D., Josh Lofton Ph.D., and guest Amanda Silva Ph.D.02:17–06:19 — Field-tour context and statewide wheat observations The group talks about seeing wheat across Oklahoma through field tours, Oklahoma Wheat Commission work, and research stops from Apache and Greenfield to the Panhandle and northeast Oklahoma. Dave notes how seeing the crop in person gave a fuller picture than just looking at numbers.06:27–09:10 — A hard, variable wheat season Silva describes the season as one of the hardest since she started at OSU. She explains that southwest and western Oklahoma were especially rough, while some locations saw enough rain to produce pockets of better wheat. Rainfall patterns created major differences, even between fields in the same county.09:11–12:02 — Stand establishment, planting timing, and grain fill Josh compares the wheat variability to what he saw in canola. Silva and Arnall discuss how some locations benefited from earlier establishment, while others struggled with stands and canopy closure. Cooler weather during grain fill likely helped preserve some grain quality and test weight.12:04–15:17 — Why wheat matured early Arnall asks why wheat was running ahead of schedule across a broad region. Silva points to warm late-winter and early-spring temperatures that moved the crop through growth stages quickly. The group also compares how those conditions affected canola and freeze risk.15:17–17:40 — The critical period for yield Silva explains that the jointing-to-flowering period is especially important because key yield components are being set. Moisture or stress during that window can strongly shape final yield.17:45–20:35 — Diversifying planting dates Arnall raises the idea of spreading planting dates as another form of risk management. Silva agrees that stacking planting dates could help, especially when combined with different variety maturities. She clarifies that “early” for grain-only wheat may still mean mid-October, not September.20:36–23:53 — Dusting in wheat and chasing moisture Dave asks when dusting in becomes worth the risk. Silva explains that farmers and researchers both have acreage and time constraints, and sometimes planting dry is a practical choice. The group also discusses deeper planting, coleoptile length, and whether Oklahoma could learn from dryland systems in the Pacific Northwest and Australia.23:54–28:13 — How much water does wheat really need? Dave asks whether researchers can determine a minimum moisture requirement for wheat in a controlled setting. Arnall and Lofton explain why lab or pot-study answers do not always translate well to field decisions because soil, temperature, humidity, wind, rooting environment, and other factors change the outcome.29:09–32:19 — Silva's research program Silva outlines current OSU wheat work, including planting date, variety maturity, nitrogen management in late-planted wheat, seeding rates, forage response, grazing recovery, nitrogen uptake, protein, and nitrogen-use efficiency. She notes new forage-focused seeding-rate work at El Reno and possibly Chickasha.32:20–36:47 — Variety trials and disease pressure The group discusses OSU's wheat variety trial network, the number of varieties being evaluated, and the inclusion of irrigated wheat work in the Panhandle. Silva notes wheat streak mosaic virus pressure in irrigated plots and explains that water alone does not remove the impact of disease.36:48–45:45 — How researchers judge trial data Arnall asks Silva and Lofton to explain how they decide whether trial data is trustworthy. They discuss CV, blocks, reps, averages, plot-by-plot review, field notes, drone imagery, canopy gaps, and the challenge of publishing fair comparisons when field variability is high.45:46–49:10 — Lessons from a stressful wheat year Silva's big takeaway is the resilience of wheat and Oklahoma producers. The group points out that hard “scientist years” can reveal useful information about stress tolerance, variety response, and management, even when they are not the years producers hope for. RedDirtAgronomy.com

HER 250, Episode 1:This country is turning 250. But whose independence are we actually celebrating?In the opening episode of HER 250, Dr. Crystallee Crain pulls back the curtain on America's founding to ask a question the parades won't: where were the women of color when this nation was born — and why were their stories left out of the textbooks?Dr. Crain tells the story of Ona Judge, a 22-year-old woman enslaved by George Washington who escaped his household in 1796 rather than be given away as a wedding gift, and who evaded the first president's repeated attempts to recapture her for the rest of her life.[1] She introduces Elizabeth "Mumbet" Freeman, who sued for her freedom in Massachusetts in 1781 using the state's own constitutional language — and won, becoming the first African American woman to do so.[2]The episode turns to the Indigenous women erased from the founding narrative entirely, including Lozen, the Apache warrior and prophet known as "a shield to her people," who fought alongside her brother Chief Victorio and died a prisoner of war.[3] Dr. Crain also confronts the federal Indian boarding school system — a policy that operated from 1819 into the 1960s and has been linked to hundreds of confirmed child deaths and dozens of burial sites, according to a 2022–2024 federal investigation.[4]The episode closes by connecting this history directly to the present: today's stark racial disparities in maternal health outcomes, Dr. Crain argues, are not an accident — they're the long shadow of a founding that never accounted for these women in the first place.[5][1] Ona Judge's escape from George Washington's household, the circumstances surrounding it, and Washington's repeated attempts at recapture are documented by the National Park Service ("Ona Judge Escapes to Freedom," nps.gov), George Washington's Mount Vernon ("Ona Judge," mountvernon.org), and Smithsonian Magazine. Judge's own account is drawn from her 1845 interview published in The Granite Freeman.[2] Elizabeth Freeman's 1781 freedom suit, Brom and Bett v. Ashley, is documented by the National Constitution Center ("Elizabeth Freeman, her case for freedom, and the Massachusetts Constitution," constitutioncenter.org) and the National Women's History Museum (womenshistory.org).[3] Lozen's role in the Apache Wars, her relationship to Chief Victorio, and her death in U.S. custody at Mount Vernon Barracks, Alabama in 1889 are documented via historian Eve Ball's recorded oral histories (In the Days of Victorio, University of Arizona Press, 1970) and the New Mexico Historic Women Marker Program (nmhistoricwomen.org).[4] Federal Indian boarding school data is drawn from the U.S. Department of the Interior's Federal Indian Boarding School Initiative Investigative Report, Volume 1 (May 2022, doi.gov) and the 2024 follow-up findings reported by the Equal Justice Initiative (eji.org), confirming 408 federal schools across 37 states/territories (1819–1969), at least 973 confirmed child deaths, and 74 identified burial sites at 65 schools.[5] Maternal mortality disparities are drawn from the CDC National Center for Health Statistics, "Maternal Mortality Rates in the United States, 2024" (cdc.gov/nchs), reporting a rate of 44.8 deaths per 100,000 live births for Black women versus 14.2 for white women.Sound:Epidemic Sound - Timelapse Title: nothanks

Hit the trail with the stars of Stagecoach - John Ford's western classic that announced John Wayne as one of Hollywood's legendary leading men. The film follows a gang of passengers on a dangerous trip through Apache country, and we'll hear two of those riders - Claire Trevor and Thomas Mitchell - whose performance won him an Academy Award. Mitchell stars in "John Barbie and Son" (originally aired on CBS on February 22, 1945) and Ms. Trevor stars in "The Blue Hour" (originally aired on CBS on September 25, 1947) and "The Light Switch" (originally aired on CBS on May 12, 1949). Plus, Claire Trevor and the Duke himself reunite in a production of the film from Screen Directors' Assignment (originally aired on NBC on January 9, 1949).

Following our prelude, Episode 2 steps back into the dust bowl era to explore the origins of our protagonists, Milton "Doc" Noss and his steadfast wife, Ova "Babe" Noss. Based on the exhaustively documented, decades-long research of investigative author John Clarence (the pen name of Jack Staley), this episode delves into Doc's complex past as a part-Cheyenne foot doctor whose lifelong obsession with treasure was sparked by a childhood encounter with the Apache chief Geronimo and a crude, ancient map received from a patient.Before the monumental find at Victoria Peak, Doc and Ova successfully unearthed a sizable cache of gold and artifacts in the Caballo Mountains in early 1937. However, their early pursuits were overshadowed by Doc's struggles with alcohol and his proximity to the chilling "Caballo Gold Vanishing"—a 1935 unsolved double murder of two Illinois couples. Though Doc was cleared, the tragedy ensnared him in a relentless web of false accusations fueled by a bitter adversary, eventually forcing the couple to pivot their search to the desolate Hembrillo Basin.The climax of this episode arrives on November 7, 1937, when a routine deer hunting trip changed history forever. Seeking a better vantage point, Doc stumbled upon a hidden ventilation shaft matching his crude map, plunging deep into Victoria Peak. Descending into the treacherous, ancient caverns, Doc and Ova discovered a "forgotten warehouse of history" containing an estimated $22 million in crude gold bars piled like cordwood, conquistador artifacts, a gold crown, and the macabre remains of chained human skeletons.However, this unimaginable wealth instantly thrust the Noss family into a perilous legal minefield against the federal government, clashing with the Gold Reserve Act of 1934 and drawing the intense scrutiny of federal authorities. Tune in to experience the breathless moment of discovery that ignited a decades-long war for the gold. And remember, if you want to read the definitive account of this incredible saga, you can secure a rare, signed copy of John Clarence's Gold House trilogy by contacting Jeff Crudele directly at podcastjfk@gmail.com. 

From bar-hopping at CMA Fest with Jason Aldean's band to scheduled high school fights at 3 pm sharp, this episode of Try That in a Small Town is all about chaos, consequences, and the crazy ways we somehow survive it all. The guys kick things off with surgery scars, locked-up backs, and near misses in the garage, then pivot into behind-the-scenes CMA Fest stories, in-ear monitor nightmares, and why late-night stadium sets grind down even veteran players. They talk Morgan Wallen flipping pianos and throwing phones, Taylor Swift's historic new country single tied to Toy Story 5, and how modern country production has become so “perfect” it's almost personality-free. Things get heavier when they unpack the Carmelo Anthony/Austin Metcalf stabbing at a track meet, race narratives in the media, and what real self-defense is—and isn't—when someone pulls a knife. They contrast that with a powerful small-town hero story: a Gwinnett County officer who saves a 7-year-old launched through a windshield. In classic TTIAST fashion, the crew rounds it out with songwriting pet peeves, delusional DMs from strangers wanting co-writes and video calls, bullying stories that still haunt them, and how golf, TV binges, and pizza reviews are getting them through recovery. 01:30 Surgeries, brutal bruises, allergic reactions to bandages and upcoming product bans in Tennessee 04:40 Locked-up back on the toilet, crawling across the house and day-three recovery status 06:30 Surviving CMA Fest: bar crawl sets, in-ear monitor disasters and playing blind on stage 09:45 Bar energy vs stadium distance and podcast fans popping up at shows 11:15 Late-night stadium headlining slot, fried fans, and what TV does to show times 14:00 Original Glory and Patriot Mobile sponsor segments 15:10 Learning piano one-handed after surgery, Jingle Bells, and mining TV shows for song ideas 17:50 TV recs: Life After Lockup, The Invisible Pilot, and Cape Fear reboot 20:20 NBA and Stanley Cup talk: Knicks' huge comeback, Wembanyama, and why some tuned out the NBA 22:45 Trump at the Garden, celebrity courtside culture, and politics vs respect for the office 24:40 Taylor Swift's Toy Story 5 country single and the business behind her return to the format 29:00 Why modern country records all sound the same and the few acts still using their own bands 31:40 Morgan Wallen: “I Ain't Coming Back” lyric love, phone toss, piano flip and Billy Joel's defense 36:30 Wild private plane trip with Morgan Wallen, crass “rich buddies” and what stuck with Kalo 38:20 Post-surgery meds, apologizing to Neil, and the nurse/dong/stripper one-liner 41:10 Group shave before a heart cath and hospital humor 42:00 CMA Fest nights with Luke Bryan at his bar, tequila overload and four-day hangovers 44:10 Dipshits of the week: insane video chat requests, song pitches, and social media entitlement 47:00 Fans demanding co-writes and “brain picking” vs actually earning a seat at the table 50:40 The worst song “idea” ever: Cats in the Cradle… but backwards 55:00 Young writers sliding into DMs, asking for writes and coffees, and basic industry etiquette 58:40 Nearly gassing yourself in a closed garage while checking mixes: calling dipshit on yourself 1:01:40 Drone-rescue story: Apache down, surviving in the water and next-level military tech 1:05:30 Golf injuries, steroids on the road, and fighting to stay in playing shape 1:07:10 The Carmelo Anthony–Austin Metcalf stabbing: facts, sentencing and race narratives 1:12:10 Media framing, self-defense vs murder, and how race gets injected into every case 1:16:00 Scheduled school fights at the park, bus brawls and why nobody brought knives back then 1:19:40 Getting drilled in the face for knocking a kid's basketball away: lesson learned 1:20:30 One cold jab to the nose and understanding when you've gone too far 1:22:10 The bully who made you fast: getting wrecked in pickup football and later asking for tickets 1:24:20 Small Town Big Story: Officer Ariana James saves a 7-year-old thrown from a truck in Gwinnett County 1:26:10 Closing: Peacemaker Coffee, shoutout to listener Ed, scheduled fights and listener call-to-action ______________________________________________________________________________________________SPONSORS: The Try That in a Small Town Podcast is powered by e|spaces!Redefining Coworking - Exceptional Office Space for Every BusinessBook a tour today at espaces.comFrom the Patriot Mobile studios:Don't get fooled by other cellular providers pretending to share your values or have the same coverage. They don't and they can't!Go to PATRIOTMOBILE.COM/SMALLTOWN or call 972-PATRIOTRight now, get a FREE MONTH when you use the offer code SMALLTOWN.Original Brands - Our original sponsor since the beginning!!Original brands is starting a new era and American domestic premium beer, American made, American owned, Original glory.Join the movement at www.drinkoriginalbrands.comPeacemaker Coffee CompanyFounded by retired police officer/chief Chris Morris, Peacemaker delivers clean, low-acidity coffee while supporting police, firefighters, EMS, military, veterans, teachers, dispatchers, and medical personnel through donations and programs.https://www.peacemakercoffeecompany.com/________________________________________________________________________________________________Follow/Rate/Share at www.trythatinasmalltown.com -For advertising inquiries, email info@trythatinasmalltown.comProduced by Jim McCarthy and www.ItsYourShow.coSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

As long compilations of episodes that can accompany you for several hours were requested, we put this new one together. This is a compilation of three different stories: Maya and Aztec Mythology, Native American Myths (Navajo and Apache), and History of the Incas. This podcast is entirely scripted and recorded by real people, it includes no AI, and mid-roll ad breaks are turned off so that you can relax without interruption. #sleep #documentary #bedtimestory #asmr #sleepstory #history #mythology Welcome to Lights Out Library Join me for a sleepy adventure tonight. Sit back, relax, and fall asleep to documentary-style bedtime stories read in a calming ASMR voice. Learn something new while you enjoy a restful night of sleep. Listen ad free and get access to bonus content on our Patreon: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/LightsOutLibrary621⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Enjoy my audiobook on Ancient Egyptian History, Myths & Mysteries: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://open.spotify.com/show/6mCqX5FoO6uCilrWCS8mB9?si=e1ecb983d2534d69⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Listen on Youtube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@LightsOutLibraryov⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠   ¿Quieres escuchar en Español? Echa un vistazo a La Biblioteca de los Sueños! En Spotify: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://open.spotify.com/show/1t522alsv5RxFsAf9AmYfg⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ En Apple Podcasts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://podcasts.apple.com/us/podcast/la-biblioteca-de-los-sue%C3%B1os-documentarios-para-dormir/id1715193755⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ En Youtube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@LaBibliotecadelosSuenosov⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

In Episode 159 of the MAX Afterburner Podcast, Matthew “Whiz” Buckley delivers an unfiltered SITREP on Operation Epic Fury, the escalating conflict with Iran, and the daily confusion surrounding negotiations, red lines, and America's strategic objectives.Pulling no punches, Whiz argues that proportional warfare is for losers and contends that the radical Islamic regime in Iran began its war against the United States nearly five decades ago. He examines President Trump's stated desire to finish that fight while questioning whether current negotiations and military strategy are achieving the desired outcome.Drawing on his experience as a TOPGUN fighter pilot who spent a lot of time in the region, Whiz discusses the dangers of prolonged military operations, the risks faced by America's young servicemembers, and why he believes dragging conflicts out can carry costs measured not only in lives lost, but in lives forever changed.He highlights the recent shootdown of a U.S. Army AH-64 Apache helicopter by Iranian forces. By the grace of God, both aviators survived. Yet Whiz challenges the notion that America should only respond decisively after fatalities occur. He argues that traumatic brain injuries, life-altering wounds, and invisible injuries suffered by servicemembers matter just as much as casualty statistics.As the founder of the No Fallen Heroes Foundation, Whiz has spent years working with veterans carrying the unseen wounds of war. He points out that repeated drone, missile, and proxy attacks don't have to kill American troops to inflict devastating consequences. Every attack risks creating another generation of warriors who return home carrying physical, emotional, and moral injuries that can last a lifetime.Whiz also challenges the idea that America's adversaries can be negotiated with as if they were business partners across a Manhattan real estate table. He questions whether mixed messaging, shifting red lines, and prolonged operations are putting more American lives at risk rather than bringing the conflict to a decisive conclusion.But this episode is about more than strategy and geopolitics.As always, Whiz speaks from the heart, reminding listeners that war is the ultimate failure of the human condition. Beneath the flags, politics, religions, and borders, we are all human beings. While he calls for decisive action when necessary, he also calls for peace—and for leaders to never forget the human cost paid by those sent into harm's way.Passionate. Provocative. Thought-provoking.This is an episode that will challenge assumptions, spark debate, and leave listeners thinking long after the debrief is over.Fight's On!

Original Air Date: October 12, 1942Host: Andrew RhynesShow: The Lone RangerPhone: (707) 98 OTRDW (6-8739) Stars:• Brace Beemer (Lone Ranger)• John Todd (Tonto) Writer:• Fran Striker Producer:• George W. Trendle Director:• Charles D. Livingston Music:• Ben Bonnell For more great shows check out our site: https://www.otrwesterns.comExit music from: Roundup on the Prairie by Aaron Kenny...

Former Marine Force Recon veteran Kirk Spradely, call sign “Tadpole,” shares his powerful life story...from surviving a brutal childhood and orphanage violence, to becoming a Marine Force Recon operator, working for Blackwater in Iraq, serving in OGA special programs, flying Blackhawk and Apache helicopters, and later supporting the Kurdish military.In this episode of Urban Valor, Kirk opens up about the day his teammate Tommy Jenner was killed by an enemy sniper in Ramadi. Kirk says the sniper was likely Juba, one of the most feared enemy snipers in Iraq. He describes watching Tommy fall beside him, hearing his teammate yell “sniper, get down,” and realizing a follow-up round had just cracked over his head.Kirk also talks about Marine Force Recon training, combat diving, counter-narcotics operations, Blackwater convoy work, OGA special programs, the moment he met a Taliban-contracted assassin, flying medevac missions for wounded troops, and attempting to help build a Kurdish Air Force before the referendum fallout. 

This week on The Necessary Conversation, Chad, Haley, and Mary Lou are recording just hours before UFC Freedom 250 kicks off on the White House lawn. It's also Trump's 80th birthday, making him the oldest president in American history.

On Thursday afternoon, President Trump abruptly halted U.S. airstrikes against Iran. FOX News Chief National Security Correspondent Jennifer Griffin explains the recent military actions and analyzes the potential for a new deal between the two nations. Jennifer describes the military's risky game of cat-and-mouse in the Strait of Hormuz and the unprecedented naval rescue of two U.S. Apache pilots. She also discusses a quiet crisis brewing behind the scenes: a critical shortage of high-end Pentagon munitions after weeks of precision strikes. Learn more about your ad choices. Visit podcastchoices.com/adchoices

MeidasTouch host Ben Meiselas reports on the major red flags surfacing as Trump and CENTCOM continue to discuss the purported Apache Helicopter Crash as the grounds for attacking Iran. Go to https://armra.com/MEIDAS or enter MEIDAS to get 30% off your first subscription order! Visit https://meidasplus.com for more! Remember to subscribe to ALL the MeidasTouch Network Podcasts:MeidasTouch: https://www.meidastouch.com/tag/meidastouch-podcastLegal AF: https://www.meidastouch.com/tag/legal-afMissTrial: https://meidasnews.com/tag/miss-trialThe PoliticsGirl Podcast: https://www.meidastouch.com/tag/the-politicsgirl-podcastCult Conversations: The Influence Continuum with Dr. Steve Hassan: https://www.meidastouch.com/tag/the-influence-continuum-with-dr-steven-hassanThe Weekend Show: https://www.meidastouch.com/tag/the-weekend-showThe Ken Harbaugh Show: https://meidasnews.com/tag/the-ken-harbaugh-showMajority 54: https://www.meidastouch.com/tag/majority-54On Democracy with FP Wellman: https://www.meidastouch.com/tag/on-democracy-with-fpwellmanUncovered: https://www.meidastouch.com/tag/maga-uncovered Learn more about your ad choices. Visit megaphone.fm/adchoices

U.S. launches "self defense" strikes on Iran after Apache helicopter shot down; Bill Gates grilled by lawmakers over Epstein ties; High security for NBA game after clashes; and more on tonight's broadcast. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The situation with Iran continues to feel like Groundhog Day, except this time, believe it or not, there may actually be movement.Earlier this week, I mentioned that I had heard from people in the know that the United States military was coiled to strike Iran and was looking for either provocation or justification to resume major military activity. That appeared to happen when Iran shot down an Apache helicopter that was escorting oil tankers through the Strait of Hormuz. We also learned that more than 100 million barrels of oil had moved through the strait under U.S. protection over the last month.Politics Politics Politics is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.One of the reasons that caught my attention is that gas prices in the United States have been falling pretty dramatically. It was a head-scratcher. If the Strait of Hormuz was effectively stalled, then what explained the drop? Was it a global rerouting of supply? Was there a China component that had been negotiated and never publicly heralded? I didn't know then, and I don't know now, but the announcement about oil shipments at least provides part of the picture.What's more interesting is what happened next. After one night of military strikes, the second night was canceled. Donald Trump said that's because we're at the point of a deal, one that has supposedly been signed off on by all available parties in the region. It appears to resemble the memorandum of understanding that's been floating around for weeks, although nobody really knows because we still haven't seen the text. We don't know if it's real. We don't even know exactly what it says.The administration's definition of success has been fairly consistent: Iran gives up its nuclear material and removes the nuclear threat. If that's actually in the agreement, then it would be meaningfully different from what came before. The obvious question is what Iran gets in return. The reporting and public comments suggest that Tehran is focused on access to frozen assets and getting money quickly. Whether that money goes directly to Iran, whether it's routed through humanitarian aid, and what conditions are attached are all questions that still need answers.The strongest sign that something may actually be happening is coming from inside Iran. Reports indicate that FARS, the IRGC-controlled news agency, is acknowledging that a draft memorandum of understanding exists, that the United States has approved it, and that Iran is likely to do the same. The bigger question is whether any agreement can actually be enforced. Iran's leadership appears splintered. We've seen officials make commitments before, only to have military figures or IRGC commanders move in a different direction. That's why the real issue isn't whether a deal can be signed. It's whether anybody in Iran has enough authority to keep it.Chapters00:00:00 - Intro00:02:48 - Iran00:08:38 - Interview with Karol Markowicz00:36:19 - Update00:37:19 - DeSantis and AI00:42:56 - FISA00:44:42 - Director of National Intelligence00:47:17 - Interview with Karol Markowicz, con't01:07:27 - Wrap-up This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.politicspoliticspolitics.com/subscribe

The US military drops 49 Tomahawk missiles on key Iranian infrastructure after one of our Apache helicopters with two pilots patrolling the Strait of Hormuz were nearly shot down in a drone strike. The President's blunt response to the new offensive: Either Iran signs the peace deal or we'll bomb the shit out of them. RINO senator Susan Collins is clearly feeling the squeeze as Trump offers his endorsement to beat Graham Platner. What she had to agree to in exchange. The USPS tells states that refuse to share voter roll data with the Trump administration it won't deliver their mail-in ballots.  

An Iranian drone takes down an American helicopter in the Strait of Hormuz, prompting the U.S. to launch new strikes. A controversial murder case that divided a Texas community ends with a 35 year sentence for a teenage defendant. And NASA unveils the astronauts that will take part in its latest mission, Artemis III.  (FILE Photo: U.S. Army Photo by Sgt. Olivia Cowart) Learn more about your ad choices. Visit podcastchoices.com/adchoices

Wednesday, June 10th, 2026 Today, Epstein's assistant for over 20 years Lesley Groff denied any knowledge of his crimes during her House Oversight Committee testimony; a U.S. Apache helicopter was shot down over the Gulf according to Trump; Republicans in the House have passed the $70B ICE funding bill; ICE has detained over 500 babies and toddlers under this administration; a new report out from the Government Accountability Office says the Camp East Montana ICE facility wasted millions and put detainees at risk; a Somali referee says his World Cup dreams have been dashed after the U.S. denied him entry; the Broadview Six grand jury transcripts have been released; and Allison and Dana deliver your Good News. Thank You, 3DayBlinds For their buy 1 get 1 50% off deal, head to 3DayBlinds.com/DAILYBEANS. Guest: Sean Vitka Executive Director at Demand Progress  https://demandprogress.org/issues/surveillance/   The Latest Breakdown:Trump DOJ CORNERED by Judge in Jan 6 Cover-Up | The Breakdown StoriesLongtime Epstein assistant denies knowledge of his crimes to House Oversight Committee | MS NOW U.S. Apache helicopter shot down by Iran, Trump says; crew rescued by sea drone | CBS News Senate OKs $70B immigration bill after rejecting efforts to permanently ban Trump's settlement fund | AP News Largest ICE detention facility wasted millions and put detainees at risk, report finds | AP NewsICE has detained over 500 babies and toddlers under Trump | MS NOW Somali Referee Says His World Cup Dream Is Dashed After U.S. Denies Entry | New York Times Good Trouble  Lands Between Fundraiser Stream:Noah Caldwell-Gervais - YouTube  is doing a 12hr Livestream June 13, benefiting the Kawaguchi O'Connor Initiative → https://riseupsingout.com and http://nokings.org →Triumphal Arch - Section 106 Assessment of Effect and Draft Programmatic Agreement →Regulation for Federal Financial Assistance -  Open For Comments →The Forest Service is accepting public comments until June 7th →Form WTAF-8647 →Recall Gov. Jeff Landry - Louisianadeservesbetter.com →STOP the deportation of Mohsen Mahdawi - Action Network →detentionwatchnetwork.org →FieldTeam6.org →Standwithminnesota.com →Tell Congress Ice out Now | Indivisible, Defund ICE | 5Calls →Congress: Divest From ICE and CBP | ACLU →ICE List  →iceout.org Good Newshttps://youtube.com/@barbarastone-un4ir?si=0mmuzMT0Fcj7flqn https://www.route66-centennial.com/ →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com →Email Dana LGBTQ Owned eating establishments in your area - hello@mswmedia.com Subject: “Dana's Project” Subscribe to the MSW YouTube Channel - MSW Media - YouTube Harry Dunn is running for CongressHarry Dunn for Maryland Our Donation Links Blue Wave California - bluewavecalifornia.org/concert Donate to Public Citizen - https://citizen.org/beans/ The Daily Beans is donating $10,000 and invites you to give what you can to support their life-affirming work - Donate to It Gets Better / The Daily Beans Fundraiser   Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans in support of Human Rights Campaign http://onecau.se/_ekes71 More Donation LinksNational Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG at fedoath@pm.me and let me know what you're going to do, or just vent. I'm always here to listen.  Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Donate (no account necessary) | Subscribe (account required) Join Bryan Dean Wright, former CIA Operations Officer, as he covers today's top stories shaping America and the world. In this Listener Q&A episode of The Wright Report, Bryan breaks down the latest escalation with Iran, including a dramatic at-sea rescue of two downed Apache pilots using an AI-powered drone boat, and explains what a lasting peace deal would actually require. Listeners push Bryan on oil prices, the Iran endgame, and whether the U.S. should pursue regime change or a strategic withdrawal. He lays out his case for a coordinated pullback backed by covert CIA and SOCOM operations, while also addressing the riots now tearing through Belfast following a brutal attempted beheading by an asylum seeker, and what that moment reveals about the broader clash playing out across Europe. Plus, Bryan covers a landmark development in American-made solar panels, shares a correction on Ivermectin use in dogs, and closes with three pieces of genuinely good news: a simple hospital tip that cuts pneumonia risk by 60%, new UCLA research on creatine and cancer-fighting immune cells, and a stunning case study of an 80-year-old Alzheimer's patient who temporarily recovered speech, memory, and mobility after a single dose of psilocybin. "And you shall know the truth, and the truth shall make you free." - John 8:32   Keywords: Bryan Dean Wright, Wright Report, Iran war, Apache helicopter rescue, Saronic drone boat, Task Force 59, Iran peace deal, JD Vance, oil prices, demand destruction, Belfast riots, Sudan asylum seeker, UK immigration, European migration crisis, QCells solar panels, made in USA solar, screwworm update, Ivermectin dogs, pneumonia prevention hospital, creatine cancer research, killer T cells, UCLA immunotherapy, psilocybin Alzheimer's, dementia treatment, Fourth of July film special

Today's Headlines: Iran shot down a US Army helicopter yesterday, the US responded with strikes on Iranian air defense systems, both crew members are stable, and stock futures dropped immediately — so the ceasefire is going great. Meanwhile, the World Cup starts tomorrow and the Trump administration is already making it a disaster: the best male referee in Africa was denied entry despite a valid visa, the Iraqi team's vice captain was detained for seven hours at O'Hare, the team photographer was turned away entirely, and Trump is preemptively blaming Europe for any Ebola outbreaks despite zero confirmed cases there. Meanwhile, the House voted to give ICE and Border Patrol $70 billion more for immigration enforcement — $38 billion to ICE, $26 billion to Border Patrol, and a breezy $5 billion for "unforeseen costs." Anthropic's cofounder published a blog post asking leading AI labs to consider pausing frontier AI development, comparing it to nuclear nonproliferation — the response was a collective "no," with some calling it self-serving given everyone's upcoming IPOs — and this comes as Anthropic is reportedly preparing to release Claude Fable 5, a model it deemed too dangerous for public release just six months ago. Epstein assistant Lesley Groff testified before the House Oversight Committee claiming she "never saw anything improper" after two decades of keeping Epstein's entire schedule, which the committee found highly inconsistent. Tom Steyer conceded the California governor's race, Trump kept pushing election fraud conspiracies about California to the point that a congressman reported a friend canceling their voter registration over Spencer Pratt, and Ken Paxton's own former impeachment attorney endorsed Democrat James Talarico in the Texas Senate race, saying Paxton is too focused on appeasing Trump to be a good senator. And finally, NASA announced the Artemis III crew of four astronauts who will orbit Earth practicing lunar lander docking in preparation for a 2028 moon landing — assuming Blue Origin delivers its lander on time, which is uncertain after one of its rockets exploded during a test. Resources/Articles mentioned: AP News: US and Iran launch airstrikes after Trump blamed Tehran for downing Army helicopter CNBC: Stock futures slip after U.S. launches ‘self-defense strikes' against Iran: Live updates NYT: U.S. Denies Entry to World Cup Referee From Somalia NYT: Iraq World Cup star Aymen Hussein questioned for ‘seven hours' by U.S. immigration officials Axios: Scoop: Trump admin pre-blames Europe for any World Cup Ebola AP News: House passes $70B bill to fund immigration enforcement for 3 years, sending to Trump MS Now: Longtime Epstein assistant denies knowledge of his crimes to House Oversight Committee Business Insider: What smart people are saying about Anthropic suggesting a global AI pause WSJ: Anthropic Releases Fable 5, a ‘Mythos-Class' AI Model With Guardrails WaPo: Maine Senate primary election live results: Graham Platner runs X: X | Ro Kanna  AP News: Ken Paxton's attorney in his impeachment trial endorses James Talarico in US Senate race AP News: NASA unveils Artemis III astronauts to test technology for a future moon landing Subscribe to the Betches News Room and join the Morning Announcements group chat. Go to: betchesnews.substack.com Morning Announcements is produced by Sami Sage and edited by Grace Hernandez-Johnson Learn more about your ad choices. Visit megaphone.fm/adchoices

Kinetic action is back in the Middle East. Brian Kilmeade breaks down the escalation as President Trump orders retaliatory strikes against 20 targets in Iran following an attack on a U.S. Apache helicopter. Plus, former Vice President Mike Pence joins the show to discuss his new book, "What Conservatives Believe," defending the conservative conscience against a rising populist right and open-border globalism. HUD Secretary Scott Turner exposes the regulations killing the American housing market and details how Opportunity Zones are being made permanent to help first-time homebuyers. Finally, Ian O'Connor logs on to react to the wild fan behavior outside Madison Square Garden after the Knicks' loss to the Spurs. [00:00:00] Sec. Scott Turner   [00:18:26] Roger Zakheim   [00:36:50] Adm. Robert Harward (Ret.)   [00:55:13] Arun Gupta   [01:13:37] Ian O'Connor   [01:32:00] Fmr. Vice President Mike Pence Learn more about your ad choices. Visit podcastchoices.com/adchoices

Karmelo Anthony, Decarlos Brown Jr., Bryan Fair, Zohran Mamdani, and the Gallup morality poll headline today's A.M. Update. Karmelo Anthony is found guilty of murder in the stabbing death of Austin Metcalf at a Frisco ISD track meet, with a jury deliberating less than three hours including their lunch break, and Aaron says justice has been served. Iran shoots down a U.S. Army AH-64 Apache helicopter over the Strait of Hormuz during what is supposed to be a ceasefire, Trump posts that the U.S. must respond, then tells the Wall Street Journal it was not a big deal — and Aaron says the whole thing just drips weakness. Interim SPLC CEO Bryan Fair appears before Congress and refuses to take TPUSA off the hate map even after Charlie Kirk was murdered, while Congressman Brandon Gill forces him to admit the SPLC's own reference materials call Graham Platner's tattoo a racist skinhead symbol. A Sudanese migrant in Belfast attempts to behead a man on the street, protesters set buses and police cars on fire across Northern Ireland, and Zohran Mamdani keeps beating the drum to abolish ICE. Decarlos Brown Jr. is found mentally incompetent to stand trial in the Iryna Zarutska Charlotte light rail murder, and Aaron closes with Aaronalysis on the Gallup morality poll — specifically why 89% of Americans call affairs immoral while 74% say divorce is acceptable, and why you cannot square that circle.

Trump says Iran shot down a United States Army Apache helicopter and says the United States must respond. Is this the start of yet another major escalation? CNN is live at the White House and Iran.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

900K Independents Blocked Out. Spencer Pratt is Out in LA. Trump Cries Foul. America 250 is Bigger Than Trump.  Trump showed up at Game 3 of the NBA Finals at Madison Square Garden and got booed loud enough that he had to lie about it on the tarmac. Hours later, news broke that an Iranian drone shot down a US Army Apache gunship off the coast of Oman — the pilots rescued, in a first-of-its-kind operation, by an American sea drone. And while the MAGA machine drags the NBA, the UFC, and America 250 into its political circus, four states are running primaries today that disenfranchise nearly a million independent voters, including roughly 450,000 independent veterans in Nevada alone. Paul Rieckhoff is solo on the mic for episode 545, delivering the kind of no-BS morning briefing the cable nets won't. This one moves fast and hits hard: drone warfare as the new normal in Iran and Ukraine, the difference between a closed primary, an open party primary, and the all-candidate open primary that actually respects independents, the Graham Plattner problem in Maine, Trump previewing his attack on November's election results, and a French flyover at the Statue of Liberty that's a reminder America 250 doesn't belong to Trump. If you're tired of partisans weaponizing every NBA scuffle and every foreign policy crisis, this is the briefing that meets the moment — righteous anger, rigorous analysis, and a path forward. -WATCH full video of this episode here. -Make the switch to Noble mobile and save money the easy way. -Join IVA and stand up to Trump's Forever Wars. -Learn more about Paul's work to elect a new generation of independent leaders with Independent Veterans of America. -Learn more about American Veterans for Ukraine here. -Remember Independent is an Attitude. -Learn more about The Headstrong Project for Veterans, Tragedy Assistance Program for Survivors (TAPS), and Department of Veterans Affairs resources in your area. Seeking support is not a sign of weakness. It's a show of strength. If you or a loved one are in immediate crisis, dial 988 and press 1, or text 838255. Connect with Independent Americans: Subscribe on YouTube, Spotify, Apple Podcasts, and all podcast platforms Read more at Substack Support ad-free episodes at Patreon  Connect: Instagram  • X/Twitter • BlueSky • Facebook  Follow on social: @PaulRieckhoff on X, Instagram, Threads, and Bluesky   -Join the movement. Hook into our exclusive Patreon community of Independent Americans. Get extra content, connect with guests, meet other Independent Americans, attend events, get merch discounts, and support this show that speaks truth to power.  -And get cool IA and Righteous hats, t-shirts and other merch now in time for the new year.  Independent Americans is powered by veteran-owned and led Righteous Media.  And now part of the BLEAV network!  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

U.S. Central Command striking Iran after the downing of a U.S. Apache helicopter, and possibly showing the ceasefire between the U.S. and Iran is in name only. A senior U.S. official tells FOX News that 20 targets inside Iran were hit, including air defense systems, ground control stations, and surveillance radar sites near the Strait of Hormuz. President Trump has promised more strikes saying the U.S. will be 'attacking them very hard.' FOX's John Saucier speaks with Dr. Rebecca Grant, national security analyst and Vice President of the Lexington Institute, who says it maybe time for more kinetic attacks in order to pressure the regime in Tehran to make a final deal that includes a free and safe Strait of Hormuz. Click Here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ To Follow 'The FOX News Rundown: Evening Edition' Learn more about your ad choices. Visit podcastchoices.com/adchoices

CNN is live on the ground in Iran after the United States retaliates for the downing of an Apache helicopter with two pilots. Plus, polls are closing in key primary elections across the country.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Plus: Oil futures gain after U.S. retaliatory strikes on Iran for a downed Apache helicopter. And an auto supplier that's particularly important for Ford is restarting production, nine months after a fire caused a supply crisis. Alex Ossola hosts. Sign up for WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to The Times of Israel's Daily Briefing, your 20-minute audio update on what's happening in Israel, the Middle East and the Jewish world. Political correspondent Tal Schneider joins host Amanda Borschel-Dan for today's episode. The US military carried out strikes in Iran early Wednesday following the downing of an Apache helicopter that US President Donald Trump accused Iran of shooting down and vowed retaliation for. Schneider describes uncertainty in Israel this morning as US bases housed by its neighbors are being targeted. During an interview about the Iran war with ABC News correspondent Jonathan Karl, Trump claimed Tuesday that it was an “open question” whether Prime Minister Benjamin Netanyahu, 76, wants to continue his political career, while a poll showed that over 60 percent of Israelis don’t want the longtime premier to run in the upcoming Knesset election. Schneider weighs in. Legislation enshrining Torah study as a Basic Law is set to be brought to a vote today. The proposed law, backed by Haredi parties United Torah Judaism and Shas, would establish Torah study as a foundational national value and define long-term Torah study as “meaningful service” to the state, equivalent to army service, with implications for the rights and obligations of those engaged in it. What could this mean for the country? Italian prosecutors have put Israel’s far-right National Security Minister Itamar Ben Gvir under investigation over the treatment of Gaza flotilla activists seen in a video he published last month. This comes as France has barred Israel’s Finance Minister Bezalel Smotrich, four leaders of settler organizations and 21 violent settlers from entering the country, as several countries introduced fresh sanctions against settlers and organizations deemed to be responsible for violence against Palestinians in the West Bank. Even as the Israeli ministers brush off the sanctions, Schneider explains why this matters. Check out The Times of Israel's ongoing liveblog for more updates. For further reading: US strikes Iran after Trump vows retaliation for downing of US helicopter over Hormuz Trump says Netanyahu may quit politics, as poll shows 61% of Israelis want him out Italy investigating Ben Gvir for alleged torture, kidnapping over Gaza flotilla video Smotrich banned from France as 4 countries introduce new sanctions against settler violence Subscribe to The Times of Israel Daily Briefing on Apple Podcasts, Spotify, YouTube, or wherever you get your podcasts. This episode was produced by Ari Schlacht.See omnystudio.com/listener for privacy information.

Iran takes down an Apache as global tensions spiral, President Donald Trump hits MSG big energy, Dems “steal the election” debate heats up again, SPLC under fire for labeling Charlie Kirk a “terrorist.” Is Governor Kemp really backing Rick Jackson or is it political rumor control? Plus: Rainy Day Theatre, HCIS, and all the hard-hitting talk you expect. Don’t miss it. See omnystudio.com/listener for privacy information.

This episode is presented by Create A Video – The USA has launched airstrikes on Iranian facilities and targets in response to the downing of an Apache helicopter. The two crew members were rescued by an autonomous boat. President Trump said Iran has two days to agree to a deal or military strikes will increase.Become a supporter of this podcast: https://www.spreaker.com/podcast/the-pete-kaliner-show--6946691/support.Subscribe to the podcast My preferred podcast platform: SpreakerAll the links to Pete's Prep are free!Get exclusive content here!Media Bias Check: GroundNews promo code!Advertising and Booking inquiries: Pete@ThePeteKalinerShow.com  

P.M. Edition for June 9. The fund that helps pay out Social Security benefits is now projected to run out by late 2032, earlier than was previously expected. WSJ reporter Anne Tergesen walks us through why… and what it could mean for retirees. Plus, today Anthropic rolled out a new AI model, Claude Fable 5, that gives the public access to Mythos–a model the company previously said was too dangerous for general release. Bob McMillan, who covers computer security for the Journal, explains how Anthropic aims to prevent bad actors from using the new model for hacking and bioweapons. And President Trump accused Iran of downing an Apache helicopter near the Strait of Hormuz last night, saying the U.S. must respond and threatening the fragile ceasefire. Alex Ossola hosts. Sign up for the WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

President Donald Trump says Iran shot down a U.S. Apache helicopter over the Strait of Hormuz, and vowed to respond in a post on Truth Social. Senior Pentagon officials have told FOX News Iran use a drone to attack the helicopter while it was patrolling the Strait. Meanwhile, Israel is pressing ahead with its campaign against Hezbollah in southern Lebanon. FOX's Eben Brown speaks with Yaakov Amidror, former major general and National Security Advisor of Israel and was also the head of the Research Department of Israeli military intelligence, who says while President Trump wants Israel to stop military action against Hezbollah, they have little choice when facing daily missile barrages. Click Here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ To Follow 'The FOX News Rundown: Evening Edition' Learn more about your ad choices. Visit podcastchoices.com/adchoices

The two crew members of a US army helicopter that crashed near the Strait of Hormuz were rescued by an American sea drone, say US officials. It was the first such operation carried out by US forces, the officials added.Also on the programme: Iran's ticket allocation for its team's World Cup games in the US is cancelled; and the trial opens in Paris over a Europe-wide scheme to steal Russian literary classics.(Photo: AH-64 Apache helicopters are American-made twin-turboshaft attack aircraft Credit: Getty Images)

We are live in Maine as Democrat Graham Platner gets a major test after months of controversies ... OpenAI is set to make the most highly anticipated market debut in recent history ... Olympic gold medalist Shawn Johnson joins us to talk about her new book on the importance of commitment ... Officials investigate why a US military Apache helicopter went down off the coast of Oman.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Spike and Zuckerman go off on the new $650,000 electric Ferrari Luce designed by Jony Ive, debate whether it's a Ferrari or a very expensive Waymo, and Zuckerman reveals his freshly imported Alpina B10 Bi-Turbo. Plus, Spike recaps his wild days at the Indy 500, and an exclusive interview with the anonymous creator of viral Instagram account Angeles Death Highway. ______________________________________________