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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

A Cradle Catholic's Long Road Home Tim Francis grew up in New Carlisle, Ohio, in a faithful Catholic household — but by the time he reached college at Ohio State, the faith took a back seat to partying and eventually substance abuse. His journey into addiction in his early twenties set him on a dark path that would last years. The Mom Who Kept Praying While Tim was drifting, his mother Patricia Ann was praying — rosaries, Mass, Holy Hours, prayer journals, and letter campaigns. She was sending Tim cassette tapes of Scott Hahn's conversion story as early as 1988, even when he wasn't remotely interested. She never pushed, never gave up, and never stopped interceding. A Slow, Surprising Return Tim's path back to the Church wound through a megachurch Bible study, debates with Catholic apologists Tim Staples and Father Mitch Pacwa held in his own living room, and a stunning Fox documentary on a woman with the stigmata — a tape his mother sent him. Each thread, years apart, was quietly part of the same answer to the same prayers. The Book — and What Came From It Tim is the author of From the Crack House to God's House: The Power of a Mother's Prayer, a raw and honest account of his journey that he says will make you "hate me and love my mom." He also has a new book in the works: The Men Who Knew the Apostles, expected out within the month. A Message for Moms with Kids Away from the Church Tim's direct word to Catholic moms: don't stop praying. Use every tool available — including the stigmata documentary his mother sent him, available on his website — and ask the Holy Spirit to go before your children as they watch it. Learn more and find the stigmata video at ScienceTestFaith.com #CatholicWomenNow #TimFrancis #PowerOfPrayer #CatholicMom #PrayingMom #RosaryWorks #CatholicFaith #FromTheCrackHouseToGodsHouse #CatholicConversion #IowasCatholicRadio #CatholicSpeaker #MothersPrayer #CatholicTestimony #ComingHomeToCatholic #ScienceTestFaith Listen Live · Program Schedule · Our StationsLINKSYou can follow us on Facebook, Instagram, Youtube, Tiktok! More on our website.If you would like to support Iowa Catholic Radio you can donate Here! More from Iowa Catholic Radio:Sunday Dive with Katie PatrizioMan Up! with Joe StopulosCatholic Women Now with Chris Magruder and Julie NelsonThe Uncommon Good with Bo Bonner and Dr. Bud MarrBe Not Afraid with Fr. Fabian Moncada and Fr. Bruce RiebeBe Not Afraid en Español con el P. Fabián MoncadaMaking it Personal with Bishop William JoensenFaith and Family Finance with Gregory WaddleThe Great Men of the Bible with Joe Stopulos Liturgy & DevotionsThe Daily Gospel Reflection with Fr. Nick SmithThe Daily Mass from St. Francis of AssisiThe Daily Mass from St. Pius XThe Daily Mass from St. TheresaSunday Mass from the Basilica of Saint JohnWant to support your favorite show? Click Here Iowa Catholic Radio - Connecting People to Christ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Man kann es gut finden oder auch nicht, Fakt ist: Geht es nach den Hyperscalern Meta, Amazon, Google und Microsoft, dann wird AI ab etwa 2030 zu großen Teilen von Atomkraft angetrieben. Die AI Talk Hosts ⁠⁠⁠Jakob Steinschaden⁠⁠⁠ (Trending Topics, ⁠⁠⁠newsrooms⁠⁠⁠) und ⁠⁠⁠Clemens Wasner⁠⁠⁠ (⁠⁠⁠enliteAI⁠⁠⁠, ⁠⁠⁠AI Austria⁠⁠⁠) diskutieren im Podcast, warum das so ist - die Themen:⚡ Energiekrise der KI: Trainingsleistung verdoppelt sich alle sechs Monate – von GPT-3 mit unter 10 Megawatt bis zu künftigen Modellen mit einem Gigawatt und mehr

Inside INdiana Business Radio for the morning of June 4, 2025. The U.S. Department of Energy has canceled a $500 million grant for a carbon capture project at Heidelberg Materials' cement plant in Mitchell. Construction at the GM-Samsung EV battery plant in New Carlisle is ahead of schedule, with up to 4,000 workers expected onsite. Also: AES Indiana seeks approval for a two-phase rate hike, Notre Dame moves forward on a South Bend tech district, and Anderson University's former president joins a law firm. Get the latest business news from throughout the state at InsideINdianaBusiness.com.

Inside INdiana Business Radio for the afternoon of May 14, 2025. An Evansville company lands a strategic investment and is preparing for continued growth. Plus, another data center project could be coming to New Carlisle. Get the latest business news from throughout the state at InsideINdianaBusiness.com.

Investments, new projects powering northern Indiana Hundreds of new jobs and multiple projects are coming to the South Bend-Elkhart region. Bethany Hartley shares how the area is focusing on child care and housing to support the people coming into the area. City, university benefitting from renewed commitment Mayor James Mueller joined our Engage Indiana series panel this week and talked to us about the city's partnership with the University of Notre Dame and how the two are connecting. Amazon Web Services $11B data center construction underway The largest single investment in state history is coming to New Carlisle, which is located west of South Bend. Eniola shares insight on how AWS will fill 1,000 jobs and her perspective on the impact of this project for Northern Indiana. New film highlights the impact of organ donation The Heartland International Film Festival is happening this weekend, and one film highlights the stories of late race car driver Bryan Clauson and three other families who have been affected by organ donation. Elkhart investing in placemaking projects The City of Elkhart is seeing population growth and focusing on quality of life. We take a look at some projects in the works and how those project play into the city's talent attraction strategy.

The Marion County Prosecutor's office announced three charges on Thursday for dealing controlled substances that resulted in death. Governor Eric Holcomb believes New Carlisle's location helped attract an eleven billion dollar investment from Amazon. A federal court this week permanently struck down a state law that tried to ban people from telling minors about other states' abortion laws without parental consent. Family caregivers of medically complex children will soon no longer be able to provide attendant care. Pike Township Schools is asking voters to approve a tax increase in the Tuesday primary.

The Marion County Prosecutor's office announced three charges on Thursday for dealing controlled substances that resulted in death. Governor Eric Holcomb believes New Carlisle's location helped attract an eleven billion dollar investment from Amazon. A federal court this week permanently struck down a state law that tried to ban people from telling minors about other states' abortion laws without parental consent. Family caregivers of medically complex children will soon no longer be able to provide attendant care. Pike Township Schools is asking voters to approve a tax increase in the Tuesday primary. Want to go deeper on the stories you hear on WFYI News Now? Visit wfyi.org/news and follow us on social media to get comprehensive analysis and local news daily. Subscribe to WFYI News Now wherever you get your podcasts. Today's episode of WFYI News Now was produced by Abriana Herron, Drew Daudelin and Kendall Antron with support from News Director Sarah Neal-Estes.

Hi, Curious Listener! Today, I have the story of the senseless murder of Grace Ross and the scumbag who blamed a "shadowy man" for making him kill her. Sources--  'It stopped being a regular day': Murder trial tells of when 6-year-old went missing (yahoo.com)  Boy accused of killing 6-year-old Grace Ross could be tried as adult (southbendtribune.com)  16-year-old faces lengthy sentence for murder and molestation of 6-year-old (wsbt.com)  GRAPHIC: New details released in the death of 6-year-old Grace Ross (wndu.com)  Judge sentences Anthony Hutchens as a juvenile for murder of Grace Ross (southbendtribune.com)  Trial over: Verdict expected Thursday in murder of 6-year-old girl (wsbt.com)  Boy accused of killing 6-year-old Grace Ross could be tried as adult (southbendtribune.com)  14-year-old boy facing murder, molestation charges in 6-year-old girl's death in St. Joseph County | wthr.com  New Carlisle residents come together to express love for 6-year-old found dead Friday (southbendtribune.com)  Anthony Hutchens loses appeal, will remain sentenced as adult in New Carlisle murder (wvpe.org) 

Aucune rénovation majeure n'a encore été effectuée à la maison d'enfance de René Lévesque, située à New Carlisle, en Gaspésie, depuis que Québec en a fait l'acquisition, en septembre 2021. Entrevue avec David Thibault, maire de New CarlislePour de l'information concernant l'utilisation de vos données personnelles - https://omnystudio.com/policies/listener/fr

Drive-Thru Pay It Forward Madness; Alec Baldwin Indicted Again; Idiots of the Week; Pauly Shore and Richard Simmons; Playboy Tell-All Book. It's Hot Hat Friday and tonight's beanie/toboggan/tuque/sock hat is provided by Bright Now Signs, in New Carlisle.

This week, multiple major stories with significant implications for the Indiana economy and we are covering it all on this week's show. In Fort Wayne, General Motors announced a $632 million investment in its truck plant there to support next-generation production of internal combustion engine trucks. The investment to secure the future for nearly 4,000 workers at the Allen County plant. Meanwhile, in St. Joseph County, a GM-Samsung SDI joint venture this week confirmed plans to invest $3.5 billion to build an Electric Vehicle battery plant with 1,700 jobs just east of New Carlisle...the latest in a series of major EV investments in Indiana. And in Indianapolis, a transformational day as Indiana University and Purdue University make it official, signing documents creating Indiana University Indianapolis and Purdue University in Indianapolis, a move expected to have a major impact on the two schools AND the state economy.

Steve Grzanich has the business news of the day with the Wintrust Business Minute. Indiana will be home to a new $3 billion electric vehicle battery plant. The plant will be located east of New Carlisle in St. Joseph County. That’s about 80 miles east of Chicago. The plant will create 1,700 manufacturing jobs. The […]

A guilty verdict Thursday in the case against a teenager charged as an adult in the murder and molestation of a 6 year old New Carlisle girl. Now 16 year old Anthony Hutchens was found guilty by the judge in a bench trial of killing little Grace Ross nearly two years ago. The case will be appealed in an attempt to get it placed back in juvenile court. Hutchens could serve decades in prison if the conviction stands. Five Memphis, Tennessee police officers involved in the violent arrest of Tyre Nichols have been charged and are currently in jail. Nichols died in the hospital from injuries allegedly received from the officers during a January 7th traffic stop. The officers, who are also black, all face second-degree murder and other charges. The alleged Half Moon Bay shooter in northern California admitted to killing seven people and injuring one other in a jailhouse media interview. Chunli Zhao complained of years of bullying and long hours working on a farm and said he believes he suffers from mental illness. He has also expressed remorse for the killings, according to the reporter who interviewed him. Notre Dame women's basketball downed Florida State at Purcell Pavilion last night, 70-to-47. The Irish men host Louisville tomorrow at noon. In the Big Ten, top ranked Purdue won at Michigan, 75-70. Michigan State over Iowa, 63-61. NBA: the Chicago Bulls lost at Charlotte, 111-96. The Detroit Pistons won at Brooklyn, 130-122. NFL Conference Championship games are on tap Sunday: San Francisco at Philadelphia at 3pm, Cincinnati at Kansas City at 6:30. Winners go to the Super Bowl. Notre Dame hockey hosts Wisconsin tonight and tomorrow at the Compton Family Ice Arena. 7:30 tonight, 6:00pm Saturday, both games on Z 94-3. NHL: the Chicago Blackhawks won at Calgary, 5-to-1. The Detroit Redwings won at Montreal, 4-to-3 in overtime.See omnystudio.com/listener for privacy information.

Mishawaka travels to New Carlisle to face New Prairie.

Steve Grzanich has the business news of the day with the Wintrust Business Minute. General Motors and LG Energy Solution are eyeing northwest Indiana for a $2 billion battery factory. Reuters reports the site is between Michigan City and South Bend in New Carlisle. Two distressed suburban hotels are being purchased by an Oklahoma real […]

www.themidnighttrainpodcast.com  www.patreon.com/accidentaldads Belle Sorenson Gunness was initially born as Brynhild Paulsdatter Størseth; November 11, 1859, Selbu, Norway – April 28, 1908?, Lwas a Norwegian-Americ Standing six feet tall (183 cm) and weighing over 200 pounds (91 kg), she was a massive, physically strong woman.   Early years   Gunness' origins are a matter of some debate. Most of her biographers state that she was born on November 11, 1859, near the lake of Selbu, Sør-Trøndelag, Norway, and christened Brynhild Paulsdatter Størset. Her parents were Paul Pedersen Størset (a stonemason) and Berit Olsdatter. She was the youngest of their eight children. They lived at Størsetgjerdet, a very small cotter's farm in Innbygda, 60 km southeast of Trondheim, the largest city in central Norway (Trøndelag).   An Irish TV documentary by Anne Berit Vestby aired on September 4, 2006, tells a common, but the unverified story about Gunness' early life. The story holds that, in 1877, Gunness attended a country dance while pregnant. There she was attacked by a man who kicked her in the abdomen, causing her to miscarry the child. The man, who came from a wealthy family, was never prosecuted by the Norwegian authorities. According to people who knew her, her personality changed substantially. The man who attacked her died shortly afterward. His cause of death was said to be stomach cancer. Growing up in poverty, Gunness took to milking and herding cattle the following year on a large, wealthy farm and served there for three years to pay for a trip across the Atlantic.   Following the example of a sister, Nellie Larson, who had emigrated to America earlier, Gunness moved to the United States in 1881 and assumed a more American-style name. Initially, In Chicago, while living with her sister and brother-in-law, she worked as a domestic servant, then got a job at a butcher's shop cutting up animal carcasses until her first marriage in 1884.   First Victim   In 1884, Gunness married Mads Ditlev Anton Sorenson in Chicago, Illinois, where, two years later, they opened a candy store. The business was unsuccessful, and the shop mysteriously burned down within a year. They collected the insurance, which paid for another home.   Some researchers tend to believe that the marriage to Sorenson produced no offspring. However, Neighbors gossiped about the babies since Belle never appeared to be pregnant. Other investigators report that the couple had four children: Caroline, Axel, Myrtle, and Lucy. Caroline and Axel died in infancy, allegedly of acute colitis. The symptoms of acute colitis — nausea, fever, diarrhea, and lower abdominal pain and cramping — are also symptoms of many forms of poisoning. Caroline's and Axel's lives were reportedly insured, and the insurance company paid.   A May 7, 1908 article in The New York Times states that two children belonging to Gunness and her husband Mads Sorensen were interred in her plot in Forest Home cemetery.   On June 13, 1900, Gunness and her family were counted on the United States Census in Chicago. The census recorded her as the mother of four children; only two were living: Myrtle A., 3, and Lucy B., 1. An adopted 10-year-old girl, possibly identified as Morgan Couch but later known as Jennie Olsen, was also counted in the household.   Sorenson died on July 30, 1900, reportedly the only day on which two life insurance policies on him overlapped. Both policies were active simultaneously, as one would expire that day, and the other would begin. The first doctor to see him thought he was suffering from strychnine poisoning. However, the Sorensons' family doctor had been treating him for an enlarged heart, and he concluded that heart failure caused death. An autopsy was considered unnecessary because the death was not thought suspicious. Sorenson died of cerebral hemorrhage that day. Gunness explained he had come home with a headache, and she provided him with quinine powder for the pain; she later checked on him, and he was dead.   She applied for the insurance money the day after her husband's funeral. Sorenson's relatives claimed Gunness had poisoned her husband to collect on the insurance. Surviving records suggest that an inquest was ordered. It is unclear, however, whether that investigation actually occurred or Sorenson's body was ever exhumed to check for arsenic, as his relatives demanded. The insurance companies awarded her $8,500 (about $299,838.51 in today's dollars), with which she bought a pig farm on the outskirts of La Porte, Indiana.   Suspicion of murder   In 1901, Gunness purchased a house on McClung Road. It's been reported that both the boat and carriage houses burned to the ground shortly after she acquired the property.   As she was preparing to move from Chicago to LaPorte, she became re-acquainted with a recent widower, Peter Gunness, also Norwegian-born. They were married in LaPorte on April 1, 1902; just one week after the ceremony, Peter's infant daughter died (of uncertain causes) while alone in the house with Belle. In December 1902, Peter himself met with a "tragic accident.” According to Belle, he reached for his slippers next to the kitchen stove when he was scalded with brine. She later declared that part of a sausage-grinding machine fell from a high shelf, causing a fatal head injury. A year later, Peter's brother, Gust, took Peter's older daughter, Swanhilde, to Wisconsin. She is the only child to have survived living with Belle.   Her husband's death netted Gunness another $3,000 (some sources say $4,000). Local people refused to believe that her husband could be so clumsy; he had run a hog farm on the property and was known to be an experienced butcher; the district coroner reviewed the case and unequivocally announced that he had been murdered. He convened a coroner's jury to look into the matter. Meanwhile, Jennie Olsen, then 14, was overheard confessing to a classmate: "My mama killed my papa. She hit him with a meat cleaver and he died. Don't tell a soul."   Jennie was brought before the coroner's jury but denied having said anything. Gunness, meanwhile, convinced the coroner that she was innocent of any wrongdoing. She did not mention that she was pregnant, which would have inspired sympathy, but in May 1903, a baby boy, Phillip, joined the family. In late 1906 Belle told neighbors that her foster daughter, Jennie Olsen, had gone away to a Lutheran College in Los Angeles (some neighbors were informed that it was a finishing school for young ladies). Jennie's body would later be recovered, buried on her adoptive mother's property.   Between 1903 and 1906, Belle continued to run her farm. In 1907 Gunness employed a single farm hand, Ray Lamphere, to help with chores.   The Suitors   Around the same time, Gunness inserted the following advertisement in the matrimonial columns of all the Chicago daily newspapers and those of other large midwestern cities:   “Personal — comely widow who owns a large farm in one of the finest districts in La Porte County, Indiana, desires to make the acquaintance of a gentleman equally well provided, with view of joining fortunes. No replies by letter considered unless sender is willing to follow answer with personal visit. Triflers need not apply.”   Several middle-aged men of means responded to Gunness' ads. One of her ads was answered by a Wisconsin farmhand, Henry Gurholt. After traveling to La Porte, Gurholt wrote his family, saying that he liked the farm, was in good health, and requested that they send him seed potatoes. When they failed to hear from him, the family contacted Gunness. She told them Gurholt had gone off with horse traders to Chicago. She kept his trunk and fur overcoat.   Another one was John Moe, who arrived from Elbow Lake, Minnesota. He had brought more than $1,000 with him to pay off her mortgage, or so he told neighbors, whom Gunness introduced him to as her cousin. He disappeared from her farm within a week of his arrival.  Although no one ever saw Moe again, a carpenter who did occasional work for Gunness observed that Moe's trunk remained in her house, along with more than a dozen others.   Next came George Anderson from Tarkio, Missouri, who, like Peter Gunness and John Moe, was an immigrant from Norway.   During dinner with Anderson, she raised the issue of her mortgage. Anderson agreed that he would pay the debt off if they decided to get hitched. Late that night, Anderson awoke to see her standing over him, holding a burning, almost spent candle in her hand and with a strange, sinister expression on her face. Without uttering a word, she ran from the room. Anderson fled from the house, soon taking a train to Missouri.   The suitors kept coming, but none of them, except for Anderson, ever left the Gunness farm. By this time, she had begun ordering massive trunks to be delivered to her home. Hack driver Clyde Sturgis delivered many of these trunks to her from La Porte. He later remarked how the heavyset woman would lift these enormous trunks "like boxes of marshmallows,” tossing them onto her broad shoulders and carrying them into the house. She kept the shutters of her house closed day and night; farmers traveling past the dwelling at night saw her digging in the hog pen.   Ole B. Budsberg, an elderly widower from Iola, Wisconsin, showed up next. He was last seen alive at the La Porte Savings Bank on April 6, 1907, when he mortgaged his Wisconsin land, signing a deed and obtaining several thousand dollars in cash. Ole B. Budsberg's sons, Oscar and Mathew Budsberg, had no idea that their father had gone off to visit Gunness. When they finally discovered his destination, they wrote to her; she promptly responded, saying she had never seen their father.   Several other middle-aged men appeared and disappeared in brief visits to the Gunness farm throughout 1907. Then, in December 1907, Andrew Helgelien, a bachelor farmer from Aberdeen, South Dakota, wrote to her and Belle was all about it. The pair exchanged many letters until a letter came that overwhelmed Helgelien, written in Gunness' careful handwriting and dated January 13, 1908. This letter was later found at the Helgelien farm. It read:   “To the Dearest Friend in the World: No woman in the world is happier than I am. I know that you are now to come to me and be my own. I can tell from your letters that you are the man I want. It does not take one long to tell when to like a person, and you I like better than anyone in the world, I know. Think how we will enjoy each other's company. You, the sweetest man in the whole world. We will be all alone with each other. Can you conceive of anything nicer? I think of you constantly. When I hear your name mentioned, and this is when one of the dear children speaks of you, or I hear myself humming it with the words of an old love song, it is beautiful music to my ears. My heart beats in wild rapture for you, My Andrew, I love you. Come prepared to stay forever.”   Yikes….   In response to her letter, Helgelien flew to her side in January 1908. He arrived with a check for $2,900, the entire savings he had drawn from his local bank. A few days after Helgelien arrived, he and Gunness appeared at the Savings Bank in La Porte and deposited the check. Helgelien vanished a few days later, but Gunness appeared at the Savings Bank to make a $500 deposit and another deposit of $700 in the State Bank. At this time, she started to have problems with her farmhand, Ray Lamphere.   In March 1908, Gunness sent several letters to a farmer and horse dealer in Topeka, Kansas named Lon Townsend, inviting him to visit her; he decided to put off the visit until spring and thus did not see her before a fire at her farm. Gunness was also in correspondence with a man from Arkansas and sent him a letter dated May 4, 1908. He would have visited her, but didn't because of the fire at her farm. Gunness allegedly promised marriage to a suitor Bert Albert, which did not go through because of his lack of wealth.   Turning Point   The hired hand Ray Lamphere was deeply in love with Gunness; he performed any chore for her, no matter how gruesome. He became jealous of the many men who arrived to court his employer and began making scenes. She fired him on February 3, 1908. Shortly after dispensing with Lamphere, she presented herself at the La Porte courthouse. She declared that her former employee was not in his right mind and was a menace to the public. She somehow convinced local authorities to hold a sanity hearing. Lamphere was pronounced sane and released. Gunness was back a few days later to complain to the sheriff that Lamphere had visited her farm and argued with her. She contended that he threatened her family and had Lamphere arrested for trespassing.   Lamphere returned again and again to see her, but she told him to kick rocks each time. Lamphere made thinly disguised threats. Like on one occasion, he confided to farmer William Slater, "Helgelien won't bother me no more. We fixed him for keeps." Helgelien had long since disappeared from the area, or so it was believed. However, his brother, Asle Helgelien, was disturbed when Andrew failed to return home and he wrote to Belle in Indiana, asking her about his sibling's whereabouts. Gunness wrote back, telling Asle Helgelien that his brother was not at her farm and probably went to Norway to visit relatives. Asle Helgelien said he did not believe his brother would do that. He believed his brother was still in the La Porte area, the last place he was seen or heard from. Gunness, being the ballsy bitch she was, told him that if he wanted to come and look for his brother, she would help conduct a search, but she cautioned him that searching for missing persons was an expensive proposition. If she were to be involved in such a manhunt, she stated, Asle Helgelien should be prepared to pay her for her efforts. Asle Helgelien did come to La Porte, but not until May.   Ray Lamphere represented an unresolved danger to Belle, and now Asle Helgelien was making inquiries that could very well send her to the gallows. She told a lawyer in La Porte, M.E. Leliter, that she feared for her life and her children's. Ray Lamphere, she said, had threatened to kill her and burn her house down. She wanted to make out a will just in case Lamphere followed through with his threats. Leliter, the attorney, complied and drew up her will. She left her entire estate to her children and left Leliter's office. She went to one of the La Porte banks holding the mortgage for her property and, not suspiciously at all, paid it off. However, she did not go to the police to tell them about Lamphere's allegedly life-threatening conduct. The reason for this, most historical, true crime nerds agree, was that there hadn't been any threats; she was merely setting the stage for her own arson. Joe Maxson, who had been hired to replace Ray Lamphere in February 1908, awoke in the early hours of April 28, 1908, smelling smoke in his room on the second floor of the Gunness house. He opened the hall door to a shit load of flames. Maxson screamed Gunness' name and those of her children but got no response. He slammed the door and then, in his tighty whiteys, leaped from the second-story window of his room, barely surviving the fire that was closing in around him. He raced to town to get help, but by the time the old-fashioned hook and ladder firetruck arrived at the farm at early dawn, the farmhouse was a big ol' pile of smoking ruins. Four bodies were found inside the house. One of the bodies was that of a woman who could not immediately be identified as Gunness, since she had been decapitated. The head was never found. The bodies of her children were found still in their beds. County Sheriff Smutzer had somehow heard about Lamphere's alleged threats, so he took one look at the carnage and quickly went after the former handyman. Attorney Leliter came forward to recount his tale about Gunness' will and how she feared Lamphere would kill her and her family and, coincidentally, burn her house down.   Lamphere reeeeeally didn't help his own cause. The moment Sheriff Smutzer confronted him and before the lawman uttered a word, Lamphere exclaimed, "Did Widow Gunness and the kids get out all right?" He was then told about the fire, but he denied having anything to do with it, claiming that he was not near the farm when the blaze occurred. A young lil dude, John Solyem, was brought forward. He said he was watching the Gunness place and saw Lamphere running down the road from the Gunness house just before the structure erupted in flames. Lamphere snorted to the boy: "You wouldn't look me in the eye and say that!"   "Yes, I will,” replied Solyem. "You found me hiding behind the bushes and you told me you'd kill me if I didn't get out of there." Lamphere was arrested and charged with murder and arson. Then scores of investigators, sheriff's deputies, coroner's men, and many volunteers began to search the ruins for evidence.   The headless woman's body was a massive concern to La Porte residents. C. Christofferson, a neighboring farmer, looked at the charred remains of this body and said that it was not the remains of Belle Gunness. As did another farmer, L. Nicholson, and so did Mrs. Austin Cutler, an old friend of Gunness. More of Gunness' old friends, Mrs. May Olander and Mr. Sigward Olsen, arrived from Chicago. They examined the remains of the headless woman and said it was't Belle Gunness.   Doctors then measured the remains and, making allowances for the body's missing neck and head, stated the corpse was that of a woman who stood five feet three inches tall and weighed no more than 150 pounds. Friends and neighbors, as well as the La Porte dressmakers who made her dresses and other garments, swore that Gunness was taller than 5'8" and weighed between 180 and 200 pounds. Remember, she was a large woman who could toss around clothing trunks like they were frisbees. Detailed measurements of the body were compared with those on file with several La Porte stores where she purchased her apparel.   When the two sets of measurements were compared, the authorities concluded that the headless woman could not possibly have been Belle Gunness, even when the ravages of the fire on the body were considered. (The flesh was severely burned but intact). Moreover, Dr. J. Meyers examined the internal organs of the dead woman. He sent the stomach contents of the victims to a pathologist in Chicago, who reported months later that the organs contained lethal doses of (dun dun dunnnn)...strychnine. Gunness' dentist, Dr. Ira P. Norton, said that if the teeth/dental work of the headless corpse had been located, he could definitely ascertain if it was, for sure, Belle Gunness. Enter Louis "Klondike" Schultz, a former miner, who was hired to build a sluice and begin sifting the debris (as more bodies were unearthed, the sluice was used to isolate human remains on a larger scale). What the flying FUCK is a sluice you may be asking your obviously intelligent self. Well, it's a sliding gate or other devices for controlling the flow of water, especially one in a locked gate. On May 19, 1908, a piece of bridgework was found consisting of two human, canine teeth, their roots still attached, porcelain teeth and gold crown work in between. Norton, her dentists, identified them as work done for Gunness. As a result, Coroner Charles Mack officially concluded that the adult female body discovered in the burned debris was Belle Gunness. Even though NOTHING ELSE LINES UP.   Asle Helgelien arrived in La Porte and told Sheriff Smutzer that he believed his brother had met with foul play at Gunness' hands. Then, the new farmhand, Joe Maxson came forward with information that could not be ignored: He told the Sheriff that Gunness had ordered him to bring loads of dirt by wheelbarrow to a large area surrounded by a high wire fence where the hogs were fed. Maxson said that there were many deep depressions in the ground that had been covered by dirt. These filled-in holes, Gunness had told Maxson, were nothing but garbage. She wanted the ground made level, so he filled in the depressions.   Sheriff Smutzer took a dozen men back to the farm and began to dig. On May 3, 1908, the diggers unearthed the body of Belle's stepdaughter, Jennie Olson (who vanished in December 1906). Then they found the small bodies of two unidentified children. Subsequently, the body of Andrew Helgelien was unearthed (his overcoat was found to be worn by Ray Lamphere). As days progressed and the gruesome work continued, one body after another was discovered in Gunness' hog pen:    So, let's run through these poor, unfortunate souls.   Ole B. Budsberg of Iola, Wisconsin, (vanished May 1907);   Thomas Lindboe, who had left Chicago and had gone to work as a hired man for Gunness three years earlier;   Henry Gurholdt of Scandinavia, Wisconsin, who had gone to wed her a year earlier, taking $1,500 to her; a watch corresponding to one belonging to Gurholdt was found with a body;   Olaf Svenherud, from Chicago;   John Moe of Elbow Lake, Minnesota; his watch was found in Lamphere's possession;   Olaf Lindbloom, age 35 from Wisconsin.   Reports of other possible victims began to come in:   William Mingay, a coachman of New York City, who had left that city on April 1, 1904;   Herman Konitzer of Chicago who disappeared in January 1906;   Charles Edman of New Carlisle, Indiana;   George Berry of Tuscola, Illinois;   Christie Hilkven of Dovre, Barron County, Wisconsin, who sold his farm and came to La Porte in 1906;   Chares Neiburg, a 28-year-old Scandinavian immigrant who lived in Philadelphia, told friends that he was going to visit Gunness in June 1906 and never came back — he had been working for a saloon keeper and took $500 with him;   John H. McJunkin of Coraopolis (near Pittsburgh) left his wife in December 1906 after corresponding with a La Porte woman;   Olaf Jensen, a Norwegian immigrant of Carroll, Indiana, wrote his relatives in 1906 he was going to marry a wealthy widow at La Porte;   Henry Bizge of La Porte who disappeared June 1906 and his hired man named Edward Canary of Pink Lake Ill who also vanished 1906;   Bert Chase of Mishawaka, Indiana sold his butcher shop and told friends of a wealthy widow and that he was going to look her up; his brother received a telegram supposedly from Aberdeen, South Dakota claiming Bert had been killed in a train wreck; his brother investigated and found the telegram was fictitious;   Tonnes Peterson Lien of Rushford, Minnesota, is alleged to have disappeared April 2, 1907;   A gold ring marked "S.B. May 28, 1907" was found in the ruins;   A hired man named George Bradley of Tuscola, Illinois is alleged to have gone to La Porte to meet a widow and three children in October 1907;   T.J. Tiefland of Minneapolis is alleged to have come to see Gunness in 1907;   Frank Riedinger a farmer of Waukesha, Wisconsin, came to Indiana in 1907 to marry and never returned;   Emil Tell, a Swede from Kansas City, Missouri, is alleged to have gone in 1907 to La Porte;   Lee Porter of Bartonville, Oklahoma separated from his wife and told his brother he was going to marry a wealthy widow at La Porte;   John E. Hunter left Duquesne, Pennsylvania, on November 25, 1907 after telling his daughters he was going to marry a wealthy widow in Northern Indiana.   Two other Pennsylvanians — George Williams of Wapawallopen and Ludwig Stoll of Mount Yeager — also left their homes to marry in the West.   Abraham Phillips, a railway man of Burlington, West Virginia, left in the winter of 1907 to go to Northern Indiana and marry a rich widow — a railway watch was found in the debris of the house.   Benjamin Carling of Chicago, Illinois, was last seen by his wife in 1907 after telling her that he was going to La Porte to secure an investment with a wealthy widow; he brought $1,000 from an insurance company and borrowed money from several investors as well; in June 1908 his widow was able to identify his remains from La Porte's Pauper's cemetery by the contour of his skull and three missing teeth; $1000 at that time is approximately $31,522.45 today.   Aug. Gunderson of Green Lake, Wisconsin;   Ole Oleson of Battle Creek, Michigan;   Lindner Nikkelsen of Huron, South Dakota;   Andrew Anderson of Lawrence, Kansas;   Johann Sorensen of St. Joseph, Missouri;   A possible victim was a man named Hinkley;   Reported unnamed victims were:   a daughter of Mrs. H. Whitzer of Toledo, Ohio, who had attended Indiana University near La Porte in 1902;   an unknown man and woman are alleged to have disappeared in September 1906, the same night Jennie Olson went missing. Gunness claimed they were a Los Angeles "professor" and his wife who had taken Jennie to California;   a brother of Miss Jennie Graham of Waukesha, Wisconsin, who had left her to marry a rich widow in La Porte but vanished;   a hired man from Ohio age 50 name unknown is alleged to have disappeared and Gunness became the "heir" to his horse and buggy;   an unnamed man from Montana told people at a resort he was going to sell Gunness his horse and buggy, which were found with several other horses and buggies at the farm.   Most of the remains found on the property could not be identified. Because of the crude recovery methods, the number of individuals unearthed on the Gunness farm is unknown but is believed to be approximately twelve. On May 19, 1908, the remains of approximately seven unknown victims were buried in two coffins in unmarked graves in the pauper's section of LaPorte's Pine Lake Cemetery. Andrew Helgelien and Jennie Olson are buried in La Porte's Patton Cemetery, near Peter Gunness.   So, here's the even MORE fucked up part… if it's possible.   Ray Lamphere was arrested on May 22, 1908, and tried for murder and arson. He denied the charges of arson and murder that were filed against him. His defense hinged on the assertion that the body was not that of that big ol' girl, Belle Gunness.   Lamphere's lawyer, Wirt Worden, developed evidence that contradicted Norton's identification of the teeth and bridgework. A local jeweler testified that though the gold in the bridgework had emerged from the fire almost undamaged, the fierce heat of the fire had melted the gold plating on several watches and items of gold jewelry. Local doctors replicated the fire conditions by attaching a similar dental bridgework to a human jawbone and placing it in a blacksmith's forge. The natural teeth crumbled and disintegrated; the porcelain teeth came out pocked and pitted, and the gold parts melted (both the artificial elements were damaged to a greater degree than those in the bridgework offered as evidence of Gunness' identity). The hired hand Joe Maxson and another man also testified that they'd seen "Klondike" Schultz take the bridgework out of his pocket and plant it just before it was "discovered.” Lamphere was found guilty of arson but acquitted of murder. On November 26, 1908, he was sentenced to 20 years in State Prison (in Michigan City). He died of tuberculosis the next year on December 30, 1909.   On January 14, 1910, the Rev. E. A. Schell came forward with a confession that Lamphere was said to have made to him while the clergyman was comforting the dying man. In it, Lamphere revealed Gunness' crimes and swore that she was still alive. Lamphere had stated to the Reverend Schell and a fellow convict, Harry Meyers, shortly before his death that he had not murdered anyone but had helped Gunness bury many of her victims. When a victim arrived, she made him comfortable, charming him and cooking a large meal. She then drugged his coffee, and when the man was all fucked up, she split his head with a meat chopper. Sometimes she would simply wait for the suitor to go to bed and then enter the bedroom by candlelight and chloroform the hapless sap. A powerful woman, Gunness would then carry the body to the basement, place it on a table, and dissect it. She then bundled the remains and buried these in the hog pen and on the grounds around the house. Thanks to her second husband's instruction, Peter Gunness, the butcher, Belle had become an expert at dissection. To save time, she sometimes poisoned her victims' coffee with strychnine. (Um… the first husband) She also varied her disposal methods, sometimes dumping the corpse into the hog-scalding vat and covering the remains with quicklime. Lamphere even stated that if Belle was overly tired after murdering one of her victims, she merely chopped up the remains and, in the middle of the night, stepped into her hog pen and fed the remains to the hogs.   Lamphere also cleared up the mysterious question of the headless female corpse found in Gunness's home's smoking remains. Gunness had lured this woman from Chicago on the pretense of hiring her as a housekeeper only days before she decided to make her permanent escape from La Porte. Gunness, according to Lamphere, had drugged the woman, then bashed in her head and decapitated the body, taking the head, which had weights tied to it, to a swamp where she threw it into deep water. Then, she chloroformed her children, smothered them to death, and dragged their small bodies, along with the headless corpse, to the basement.   She dressed the female corpse in her old clothing, and removed her false teeth, placing these beside the headless corpse to assure it being identified as Belle Gunness. She then torched the house and fled. Lamphere had helped her, he admitted, but she didn't take off by the road where he waited for her after the fire had been set. She had betrayed her one-time partner in crime in the end by cutting across open fields and then disappearing into the woods. Some accounts suggest that Lamphere admitted that he took her to Stillwell (a town about nine miles from La Porte) and saw her off on a train to Chicago.   Lamphere said that Gunness was a rich woman, that she had murdered 42 men by his count, and maybe more, and had taken amounts from them ranging from $1,000 to $32,000. She had allegedly accumulated more than $250,000 through her murder schemes over the years—a considerable fortune for those days (about 10 million dollars, today). She had a small amount remaining in one of her savings accounts, but local banks later admitted that she had withdrawn most of her money shortly before the fire. Gunness withdrawing most of her money suggested that she was planning to evade the law. Gunness was, for several decades, allegedly seen or sighted in cities and towns throughout the United States. Friends, acquaintances, and amateur detectives apparently spotted her on the streets of Chicago, San Francisco, New York, and Los Angeles. As late as 1931, Gunness was reported alive and living in a Mississippi town, where she supposedly owned a great deal of property and lived the life of a respected woman. Sheriff Smutzer, for more than 20 years, received an average of two reports a month. She became part of American criminal folklore, a female Sasquatch, if you will.   Gunness's three children's bodies were found in the home's wreckage, but the headless adult female corpse found with them was never positively identified. Gunness' true fate is unknown; La Porte residents were divided between believing that Lamphere killed her and that she had faked her own death. In 1931, a woman known as "Esther Carlson" was arrested in Los Angeles for poisoning August Lindstrom for money. Two people who had known Gunness claimed to recognize her from photographs, but the identification was never proved. Carlson died while awaiting trial.   So, what the fuck happened to “Hell's Belle”??   The body believed to be that of Belle Gunness was buried next to her first husband at Forest Home Cemetery in Forest Park, Illinois.   On November 5, 2007, with the permission of descendants of Belle's sister, the headless body was exhumed from Gunness' grave in Forest Home Cemetery by a team of forensic anthropologists and graduate students from the University of Indianapolis to learn her true identity. It was initially hoped that a sealed envelope flap on a letter found at the victim's farm would contain enough DNA to be compared to that of the body. Unfortunately, there was not enough DNA, so efforts continue to find a reliable source for comparison purposes, including the disinterment of other bodies and contact with known living relatives.   As far as we know… Belle Gunness, the wicked Norwegian bitch… got away with So. Many. Murders… including her own.   Movies   https://deluxevideoonline.org/our-tens-list-faked-deaths-in-movies/

This week (8/12 & 8/14) on ART ON THE AIR we feature New Carlisle's quaint, artisan shop, Feeny's Homegoods, with its owner Marcy Kauffman. Next we discuss the Nature in the Arts events offered by the Shirley Heinze Land Trust with Willow Walsh. Our spotlight is on Lubeznik's Art Festival with Janet Bloch happening Saturday and Sunday August 20 and 21. Tune in on Friday at 11am for our hour long conversation with our special guests or listen on the web at WVLP.org Listen to past ART ON THE AIR shows at brech.com/aota. Rebroadcast on WVLP - Monday at 5pm and Sunday (8/14) on 7pm on Lakeshore Public Radio 89.1FM or lakeshorepublicradio.org/programs/art-air Please have your friends send show feedback to Lakeshore at: radiofeedback@lakeshorepublicmedia.org Send your questions about our show to AOTA@brech.com LIKE us on Facebook.com/artonthairwvlp to keep up to date about art issues in the Region. New and encore episodes also heard as podcasts on: anchor, NPR ONE, Spotify Tune IN, Amazon Music, Apple and Google Podcasts, plus many other podcast platforms. Larry A Brechner & Ester Golden hosts of ART ON THE AIR.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Ron Spears has been playing guitar since he was 15.  He took a little break after he got married and built his French Wine import business.  In 2010, he got his old Martin repaired and began playing again with purpose.  He now teaches guitar and practices 2-3 hours a day.  He currently play jazz with as a duo and with a big band out of New Carlisle, IN.  Welcome back to Ron (he was on episode 22).

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Today's podcast guest Justin Powell talks about founding Huntington Billboards in the middle of the 2009 great recession and growing the company to 1,800 displays over 13 years. Some of the highlights. How did you enter the out of home business? Justin Powell, Founder and President, Huntington Outdoor I graduated from college.  I was 20 years old...  I made a big list.  I called it my new venture checklist.  Everything from restaurants...to insurance companies, on and on and on...my cousin and uncle actually came to me and said Justin there's this billboard down on 75.  That seems like a fair business.  Why don't you buy that.  It was an on-premise sign and I couldn't purchase it for off-premise advertising but that got me thinking... Talk about your first location I found my first location in this town of New Carlisle and very dear landowners who are friends to this day...It was 8' by 20' and a 2 pole structure and cost three times more than it should have and then I spent the next two months knocking on doors trying to rent it. Small Signs I tie everything back to numbers...We are going to build the minimum size sign to derive the best returns.  A log of times an 8' by 20' sign will do just as fine as a 12' by 24' if the location is close enough to the road and the visibility is good. How do you find winning locations? CISD.  We desire to build billboards on curves.  That's the C.  On intersections.  That's the I.  And then the S is speed.  Lower speed.  If we can get billboards along roads that are 25 mph or 30 mph...And then the last one is Demand...As we install locations we have a weathervane as to what the market can bear and where we have demand... Growing Pains About the time I got to about 70 billboards my occupancy rate was atrocious...It was 40% or something.  It was absolutely awful because I was doing everything.  I would have nice clothes on and talk to an advertiser and then I would change out of my nice clothes in the car and change into climbing gear and change out a vinyl and then I would chop down trees.  I would do land leasing.  I would do everything.   My little sister at that time - Jena was 17.  She looked at me and said "Hey Justin, why don't you let me take over sales.  And I'm like yeah sure.  She became a partner in the business.  And then my brother, he was 16.  He came to me and he said, Justin, I think I can build these things for you.  Let me do that...On that foundation we continued to build and build and build.  We got to about 500 billboards and my sister Jena got elected as State Representative...So we hired a General Manager at that point...things have transitioned a bit. Digital Billboards We had not done digital until the end of 2020.  We had some really good locations that needed to be converted...End of 2020 we built our first two signs.  We learned a lot from them.  And then in 2021 - last year- we put in 22. Whose automated platforms are you connected to. Vistar, Blip.  Blip to me is fascinating.  It's a very fascinating platform...Whether it's Blip or any of the other services that we use, it's like one ad or two ads for a day and they're paying you $20, or $50 or $100.  It's where our industry needs to go...It's found money.  It's money we never would have gotten.  I think about movie releases...it's reminder advertising... Whose signs We use Formetco.  Formetco has done a very good job for us.  They look nice and have been very reliable.  Formetco seems to know what they are doing...All of the nightmares I thought we would have...we haven't had. Please enable JavaScript in your browser to complete this form.Never miss a Billboard Insider article. Join 3,240 subscribers who receive our daily stories for free by sending us your name and email using the form below. *FirstLastEmail *Submit Paid Advertisement

Today's podcast guest Justin Powell talks about founding Huntington Billboards in the middle of the 2009 great recession and growing the company to 1,800 displays over 13 years. Some of the highlights. How did you enter the out of home business? Justin Powell, Founder and President, Huntington Outdoor I graduated from college.  I was 20 years old...  I made a big list.  I called it my new venture checklist.  Everything from restaurants...to insurance companies, on and on and on...my cousin and uncle actually came to me and said Justin there's this billboard down on 75.  That seems like a fair business.  Why don't you buy that.  It was an on-premise sign and I couldn't purchase it for off-premise advertising but that got me thinking... Talk about your first location I found my first location in this town of New Carlisle and very dear landowners who are friends to this day...It was 8' by 20' and a 2 pole structure and cost three times more than it should have and then I spent the next two months knocking on doors trying to rent it. Small Signs I tie everything back to numbers...We are going to build the minimum size sign to derive the best returns.  A log of times an 8' by 20' sign will do just as fine as a 12' by 24' if the location is close enough to the road and the visibility is good. How do you find winning locations? CISD.  We desire to build billboards on curves.  That's the C.  On intersections.  That's the I.  And then the S is speed.  Lower speed.  If we can get billboards along roads that are 25 mph or 30 mph...And then the last one is Demand...As we install locations we have a weathervane as to what the market can bear and where we have demand... Growing Pains About the time I got to about 70 billboards my occupancy rate was atrocious...It was 40% or something.  It was absolutely awful because I was doing everything.  I would have nice clothes on and talk to an advertiser and then I would change out of my nice clothes in the car and change into climbing gear and change out a vinyl and then I would chop down trees.  I would do land leasing.  I would do everything.   My little sister at that time - Jena was 17.  She looked at me and said "Hey Justin, why don't you let me take over sales.  And I'm like yeah sure.  She became a partner in the business.  And then my brother, he was 16.  He came to me and he said, Justin, I think I can build these things for you.  Let me do that...On that foundation we continued to build and build and build.  We got to about 500 billboards and my sister Jena got elected as State Representative...So we hired a General Manager at that point...things have transitioned a bit. Digital Billboards We had not done digital until the end of 2020.  We had some really good locations that needed to be converted...End of 2020 we built our first two signs.  We learned a lot from them.  And then in 2021 - last year- we put in 22. Whose automated platforms are you connected to. Vistar, Blip.  Blip to me is fascinating.  It's a very fascinating platform...Whether it's Blip or any of the other services that we use, it's like one ad or two ads for a day and they're paying you $20, or $50 or $100.  It's where our industry needs to go...It's found money.  It's money we never would have gotten.  I think about movie releases...it's reminder advertising... Whose signs We use Formetco.  Formetco has done a very good job for us.  They look nice and have been very reliable.  Formetco seems to know what they are doing...All of the nightmares I thought we would have...we haven't had. Please enable JavaScript in your browser to complete this form.Never miss a Billboard Insider article. Join 3,152 subscribers who receive our daily stories for free by sending us your name and email using the form below. *FirstLastEmail *Submit Paid Advertisement

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Host Dan Wilson is joined by Drew Bowman, Sales & Marketing Manager and Co-Owner of Bowman-Landes Free Range Turkey Farm in New Carlisle, Ohio - a 4th generation farm.

In today's episode of SOUND OFF, we asked how our listeners think the county, cities, and schools should spend the millions of dollars they received from the American Rescue Plan. Infrastructure? Recovery programs? Better pay for employees? Air filtration for public buildings? Here are the ARP allocations for the county entities: LaPorte County: $21,310,000 Michigan City: $16,549,045 City of LaPorte: $11,476,496 Westville: $1,200,000 New Carlisle: $436,578 North Liberty: $399,067 Kingsford Heights: $288,829 Wanatah: $209,224 Town of Pines: $143,998 Beverly Shores: $124,826 LaCrosse: $107,321 Michiana Shores: $61,892 Kingsbury: $49,805 Pottawattamie Park: $46,679 La Porte County districts are estimated to receive: Michigan City Area Schools: $21,267,438.76 La Porte Community Schools: $8,793,342.06 New Prairie United Schools: $3,089,587.45 MSD of New Durham Township: $846,812.48 South Central Community Schools: $523,309.46 Tri-Township Consolidated Schools: $408,589.11 CREDITS: Nate Loucks (Host), Dennis Siddall (Producer), Jeff Wuggazer (Editor) SOUND OFF is a community conversation show that airs every Monday and Friday on 96.7 the Eagle in LaPorte County, Indiana. SOUND OFF is a Spoon River Media production.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Join Film Maker, Sybil Drew for back story about her documentary about the industrial development of the Indiana Enterprise Center near New Carlisle and the persistent, well-organized community who continue to fight for protection of green space and environmental quality of life.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Sermon by Pastor Larry Marvel at Colonial Baptist Church in New Carlisle, Ohio.

Have you considered running for public office in your city government? Mayor Ethan Reynolds is Ohio's youngest mayor in history and he has excellent insight for you. If you have thought about allowing your faith to lead you into an elected role in your school board, city council, or perhaps even mayor, you do not want to miss the opportunity to hear from an expert. It takes great faith to lead a city and Ethan Reynolds will give you insight on how his faith has inspired his leadership as the former mayor of New Carlisle. Learn about Ethan Reynolds in his bio.

Vos animateurs vous invitent cette semaine à l'Espace René-Lévesque qui permet de découvrir sur la route des vacances cet été un politicien attachant qui au moment de devenir premier ministre du Québec, en 1976, croyait pouvoir faire accepter aux Québécois le rêve de l'indépendance assortie d'une alliance économique avec le reste du Canada, la fameuse « souveraineté-association ». Regardez Tam-Tam Canada du vendredi 13 juillet 2018 - 36:41 Voici nos archives sur le même sujet René Lévesque maintenant sur la route des vacances des Canadiens Cet été, si la route des vacances vous mène à New Carlisle, un petit village de la magnifique région de la Gaspésie, dans l'est du Québec, vous pourrez pour la toute première fois découvrir le nouvel Espace René-Lévesque. Trois ex-premiers ministres réunis 30 ans après la mort de René Lévesque Trois anciens premiers ministres de la province du Québec, tous d'ex-dirigeants du Parti Québécois comme l'a été René Lévesque de 1968 à 1985 rendent hommage à l'ancien premier ministre René Lévesque décédé en 1987. Les célébrités de RCI: René Lévesque, le journaliste À 22 ans, en 1944, il est embauché par la Voice of America qui l'envoie en Europe, alors que sévit la Seconde Guerre mondiale. En 1946, le service international de Radio-Canada (RCI) l'engage à son tour. Comprendre les motivations profondes des séparatistes québécois Qu'est-ce qui motive tant de Québécois à toujours souhaiter l'indépendance de leur province du reste du Canada. Les raisons varient certes beaucoup, mais on peut dire qu'elles relèvent généralement de quelques grands sentiments. Grande histoire de la petite animosité entre francophones et anglophones au Canada Le débat sur l'indépendance du Québec et les confrontations entre les anglophones et les francophones au Canada semblent s'être grandement estompés depuis les référendums sur la séparation en 1980 et en 1995. Voici notre meilleure offre cette semaine Les Québécois, rois des observations d'ovnis au Canada en 2017 On leur donne aujourd'hui le nom plus scientifique et sérieux de phénomènes aérospatiaux mystérieux (PAM) et les Québécois se sont avérés les champions de leur observation au pays selon le rapport publié par Ufology Research, qui indique qu'il y a eu 1101 observations – une moyenne de trois par jour – faites au Canada en 2017. L'amitié, antidote à l'horreur L'expérience de la torture, de la guerre et d'autres formes de violence organisée entraîne une rupture profonde des liens humains. C'est que croit le Centre canadien pour les victimes de torture (le Centre) qui a mis en oeuvre un programme pour aider les victimes de torture physique ou psychologique à se faire des amis. Femi Kuti : un vrai régal au Festival Nuits d'Afrique Le 32e festival international Nuits d'Afrique bat son plein à Montréal depuis deux jours. Parmi les artistes de grande renommée présents à ce rendez-vous culturel, le prince Diabate du Mali, Noubi du Sénégal, mais aussi et surtout Femi Kuti du Nigeria.

A tribute to my late grandfather, Lester Clark, 89 years young who passed earlier today in New Carlisle, OH. This man has made a major impact on my life and I talk about sensing his death from 2,400 miles away. I play a lot of songs that I love that help me through difficult times and I DO NOT OWN the rights to them, nor am I profiting from their inclusion. I have no intention of making money of their work. Let's all try to do our best and love each other. www.meandparanormalyou.comwww.ryansingercomedy.com818-839-0593 Mindline

Brittany Lee Moffitt is a professional vocalist, songwriter, and performer from the small town of New Carlisle, Indiana. Brittany moved to Chicago in 2005 to study music at Columbia College. During that time, Brittany was offered an opportunity to represent the music department as a participating singer/songwriter in the 2009 International Summer Music Camp, held by kraut-rock pioneer, drummer, and instructor Udo Dahmen at Popakademie School of Music in Mannheim, Germany.