Podcasts about Dyson

If anyone builds superintelligent AI before we know how to control it, everyone dies. Nate Soares wrote the book on why that's not a metaphor. Subscribe if you want science with evidence, not speculation. Soares runs the Machine Intelligence Research Institute and co-wrote If Anyone Builds It, Everyone Dies with Eliezer Yudkowsky. The first word in that title is if. That matters. His argument is not that doom is certain. His argument is that the path we are on leads there, that the driver is asleep at the wheel, and that we still have time to wake him up. We argue for over an hour. I push on whether LLMs can ever reach superintelligence, whether GPU lock-in is a real ceiling, and what it would actually take to move his p-doom. He pushes back with one clean point: by the time an AI can rediscover general relativity from pre-1911 data the way Einstein did, we will have almost no time left. You don't wait for that goalpost. What you'll hear: Why the bus-racing-toward-a-cliff analogy depends entirely on whether the driver is asleep or awake Whether LLM lock-in is a prison or a temporary inefficiency What the AI that broke out of its virtual machine to solve a hacking problem tells us Why GPT-4o encouraging a teenager toward suicide is not a malice problem but a training problem The difference between an AI doing the right thing too well and an AI that never wanted to do what you asked What Soares actually thinks about aliens, Dyson spheres, and why we should not see stars going out The first word in the title is if. The second word to watch is would. CHAPTERS 00:00 The people racing to build superhuman AI say it might kill everyone 00:42 Who coined "AI alignment" and why the first word in the title matters 02:28 Is it already too late for the if? 04:40 The bus, the cliff, and the sleeping driver 05:02 Silicon Valley is spooked. Washington is not. 07:02 Align with who? The rogue actor problem 07:34 Who is holding the leash? 08:24 The AI that edits its own test and deletes the log file 10:04 Controllability vs. making an AI that actually cares 10:44 The move gets harder. The outcome gets easier. 13:04 Are GPUs and LLMs a ceiling or a temporary inefficiency? 16:56 Brian's Einstein test: can an LLM rediscover general relativity? 18:38 Waiting for the goalpost is waiting too long 20:14 How prediction training can push AI beyond humans 21:44 Tycho Brahe, Kepler, and planetary motion as a prediction problem 24:38 Yann LeCun said never. GPT-4 did it half a generation later. 27:28 Can you prove a no-go theorem for superintelligence? 29:14 Training a human takes a light bulb. Training an AI takes a city. 33:28 What would proof of alien life do to p-doom? 35:00 Why interstellar aliens should have Dyson spheres 44:26 What would actually update Soares' p-doom? 49:42 Nobody intended this. Intent doesn't matter. 51:08 The AI hides its tracks before it does what you want 51:34 Sycophancy vs. hallucination: which runs deeper? 51:56 Leaded gasoline and civilizational risk 59:48 Sam Harris: humans have no free will but AIs do 01:00:38 Is alignment really a governance problem? 01:01:48 Unaligned AI vs. AI aligned to the wrong person 01:04:20 2026: 10 to 30% chance of automated AI research this year 01:06:44 What if Soares is wrong? 01:09:18 What gets him out of bed 01:12:38 Watch my conversation with Roman Yampolskiy Get the transcript, fascinating bonus content, and my Monday M.A.G.I.C. Message: https://briankeating.com/yt All my top AI episodes in one place: https://briankeating.com/ai Have a .edu email and live in the USA? You automatically win a meteorite: https://BrianKeating.com/edu Subscribe: https://www.youtube.com/DrBrianKeating?sub_confirmation=1 Support Into the Impossible on Patreon, get my weekly M.A.G.I.C. Message, unfiltered bonus content, and live monthly Office Hours with me: https://www.patreon.com/drbriankeating Join this channel for perks, monthly Office Hours, and your name in the Member Roster at the end of every episode: https://www.youtube.com/channel/UCmXH_moPhfkqCk6S3b9RWuw/join Featured Guest: Nate Soares / MIRI: https://intelligence.org If Anyone Builds It, Everyone Dies (book): https://ifanyonebuildsit.com/ Nate Soares on Twitter/X: https://x.com/So8res?lang=en My books: Losing the Nobel Prize (memoir): http://amzn.to/2sa5UpA Think Like a Nobel Prize Winner: https://a.co/d/03ezQFu Focus Like a Nobel Prize Winner: https://a.co/d/hi50U9U Galileo's Dialogue (first-ever audiobook): https://a.co/d/iZPi9Un Twitter/X: https://x.com/BrianKeating Substack: https://briankeating.substack.com Blog: https://briankeating.com/blog Audio-only: https://briankeating.com/podcast #intotheimpossible #briankeating #AIrisk #aisafety #artificialintelligence #superintelligence #NateSoares #MIRI #podcast Learn more about your ad choices. Visit megaphone.fm/adchoices

James Dyson is a visionary inventor, designer, educator, and founder of Dyson, a global company transforming ordinary household appliances into design and engineering marvels. He joins to discuss his iconic career, the role of failure in the creative process, and how good design can reshape the way we live. Hosted on Acast. See acast.com/privacy for more information.

This Sunday Worship episode features dynamic Pastors, Preachers and Reverends that speak truth to power and wake us up. I capture these Sermons from various sources to share as our Church On-Line that I started back during 2020 shutdown. Rev. Dyson sermon was aired on WHUR 96.3 FM Radio. He preached from the Bible verse 2 Corrinthian 12:7-10..  

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

Dyson launched a portable fan that's basically wearable air conditioning… And they launched it pre-trend.Apple sued Open AI for allegedly stealing blueprints to the iPhone… because only a phone can replace the iPhone.Millennial moms buying and running businesses… It's MAM: Maternal Acquisition & Management.Plus, the wildest stock on Wall Street right now is a cookie… Biscoff cookies are up 17,000%.$LOTB $AAPL $PINSGrab your Tickets to the IPO Tour: Our In-Person OfferingSan Francisco 9/23: https://www.ticketmaster.com/event/1C0064AFB5F688BDBoston 10/14: https://tickets.citywinery.com/event/tboy-the-ipo-tour-in-person-offering-8cdhupSeattle 11/4 (21+): https://www.axs.com/events/1446394/the-best-one-yet-ticketsNEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.

Talking with Tom Murphy, professor emeritus of the departments of Physics and Astronomy & Astrophysics at the University of California, San Diego, passionate astronomer, author of the Do the Math blog and the Metastatic Modernity series on mapping the intersections of thermodynamics, ecological limits, and the long arc of civilizational collapse…On species-level growth versus the fantasy of the endless economy, on Dyson spheres, on boiling the oceans, on the sixth mass extinction, on solar panels that preserve modernity rather than the planet, on peak oil and fracking, on demographic modeling, on Africa's food spigot, on John Michael Greer and “collapse now to avoid the rush”, on sealed-glass shrimp, Mars as juvenile fantasy, on Hobbes as mythology, on rivulets down a windshield, on the amoeba's genius and thirteen thousand genes, on hunter gather lifestyles, carrying loads of the planet, on friction fire, flint knapping, atlatl darts, on written language as the thing academics will never speak against, Tom's work challenges both the Mars-colonizing techno-optimist and the solar-cheering mainstream environmentalist, arguing instead for falling out of love with modernity: not doom for humanity, or life, ultimately trying to provide quantitative assessment of the challenges associated with long-term human success on a finite planet.ExcerptsTom Murphy's Law And my version of Murphy's Law is that it's not if something can go wrong, it will go wrong. It's that if something can happen, you shouldn't be surprised if it does.On Authentic LivingI'm a prisoner, and I don't feel hypocritical bashing the prison that I'm in.I think that's valid. What I can do is just try to raise awareness that we don't have to be in a prison, and ultimately we might escape to more authentic ways of living and dispel the mythology around the, fear, this irrational fear about other ways of living that have worked well for humans for countless millennia.On The Sixth Mass Extinction“Preserving our ability to crank out terawatts of energy is exactly the same as preserving our ability to continue a sixth mass extinction.”Aside from his work with Apache Point Observatory Lunar Laser-ranging Operation Project, Tom Murphy is known for his blog “Do The Math” which examines societal issues related to energy production, climate change, and economic growth from an astrophysicist's perspectiveDo the Math BlogBook: Energy and Human Ambitions on a Finite Planethttps://tmurphy.physics.ucsd.edu/ Get full access to Leafbox at leafbox.substack.com/subscribe

TRiple M's Tech Talk: Playstation ends the physical game disc - gamers to go all-digitalhttps://eftm.com/2026/07/playstation-kills-the-physical-disc-and-the-second-hand-games-market-277754Confusing SMS Spam and Scam could be over with new Sender ID ruleshttps://eftm.com/2026/07/what-is-a-sender-id-and-why-do-we-now-have-unverified-sms-messages-277717A stick vacuum better than a Dyson? the Tineco Pure One P50 could be ithttps://eftm.com/2026/06/tineco-pure-one-p50-review-vacuum-tangle-hair-zero-rug-hard-floor-bend-under-clean-277693See omnystudio.com/listener for privacy information.

En un mundo saturado de mensajes, “muy bueno” es invisible. La Vaca Púrpura de Seth Godin te sacude con una idea simple y poderosa: solo lo extraordinario detiene miradas y se comenta. Calidad y anuncios ya no bastan; hay que diseñar productos y experiencias que merezcan conversación. Piensa en el iMac traslúcido, la aspiradora Dyson que mostraba la suciedad girando o el “tercer lugar” de Starbucks: no solo funcionaban, daban tema.¿Cómo se logra? Apunta a una minoría apasionada (innovadores), integra lo “compartible” en el propio producto (como los auriculares blancos del iPod), mima a los propagadores y atrévete a redefinir la categoría (el donut caliente de Krispy Kreme). Cada detalle comunica; si algo ya no destaca, elimínalo. La pregunta que queda en el aire es directa: ¿qué cambiarás esta semana para que alguien diga “tienes que ver esto”? Porque, como recuerda Godin, lo opuesto de notable no es malo; es “muy bueno”.Conviértete en un supporter de este podcast: https://www.spreaker.com/podcast/grandes-aprendizajes--5720587/support.Newsletter Marketing Radical: https://marketingradical.substack.com/welcomeNewsletter Negocios con IA: https://negociosconia.substack.com/welcomeLibro "Libertad Financiera" Gratis: https://borjagiron.com/libertadMis Libros: https://borjagiron.com/librosSysteme Gratis: https://borjagiron.com/systemeSysteme 30% dto: https://borjagiron.com/systeme30Manychat Gratis: https://borjagiron.com/manychatMetricool 30 días Gratis Plan Premium (Usa cupón BORJA30): https://borjagiron.com/metricoolNoticias Redes Sociales: https://redessocialeshoy.comNoticias IA: https://inteligenciaartificialhoy.comClub: https://triunfers.comThis content is under Fair Use: Copyright Disclaimer Under Section 107 of the Copyright Act in 1976; Allowance is made for "Fair Use" for purposes such as criticism, comment, news reporting, teaching, scholarship and research. Fair Use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. I do not own the original content. All rights and credit go to its rightful owners. No copyright infringement intended.

We will talk about faith during adversity, overcoming fear, God's faithfulness in difficult seasons, the lessons learned through health challenges, and how biblical truth becomes real when life tests what we believe.Book:The ShadowWalking Through The Valley, Abiding Under His Wingshttps://a.co/d/06mXyZrYmikedysonauthor.com

Chris Burke reveals why most hybrid work policies fail—and how to turn hybrid work from a policy into a measurable system that improves productivity, reduces costs, and optimizes office space.If your hybrid work setup feels chaotic, expensive, or difficult to manage, this episode will change how you think about workplace operations. Chris Burke, founder of HybridHero, shares how enterprise organizations across 40+ countries use data, automation, and workplace intelligence to improve workforce coordination, office utilization, and financial performance.In this episode, you'll learn:• Why hot desking often fails—and how to avoid common workplace frustrations• How AI-powered desk booking helps teams coordinate automatically• Why Tuesday-Thursday office mandates create hidden productivity problems• How to use data to improve office utilization and reduce real estate costs• The importance of workforce behavior when designing office space• How visibility and coordination impact employee productivity• Why hybrid work should be managed as an operational system, not just a policy• Practical lessons from organizations successfully running hybrid workplaces at scaleAbout Chris BurkeChris Burke is the founder of HybridHero, a workplace operating platform used by organizations including Dyson, BMW, and Pepsi across more than 40 countries. He works with executives and leadership teams to solve one of the biggest challenges in modern business: making hybrid work productive, measurable, and financially efficient. Combining experience from both consulting and SaaS, Chris focuses on helping organizations optimize workforce behavior, office utilization, and workplace costs through better systems and data.Chapters00:00 Introduction• Meet Chris Burke and the conversation begins with workplace culture, accents, and hybrid work challenges.07:51 Optimizing a Tuesday-Thursday Hybrid Model• How organizations can improve coordination and visibility even without hot desking.08:31 The Problem with Everyone Coming In on the Same Days• Why rigid office schedules often create communication and collaboration gaps.30:34 Hot Desking Horror Stories• Real-world challenges of shared workspaces and why systems matter.34:50 AI Desk Booking• How managers can automatically coordinate teams and office space.36:48 The Joe and Eric Problem• Why poor scheduling leads to productivity losses and unnecessary friction.37:31 The HybridHero Interface• How color-coded floor plans and workplace visibility improve operations.45:00 How to Connect with Chris• Learn more about HybridHero and workplace optimization strategies.46:30 Closing• Final thoughts and where to find more episodes from 10X Your Team.Connect with Chris Burke:https://hybridhero.com/https://chrisburkeexec.com/https://www.linkedin.com/in/chris-burke-uk/https://www.instagram.com/hybridheroos/https://www.instagram.com/chrisburkeexec/https://www.youtube.com/@HybridHero-HH

KB & DJ are BACK and kick things off discussing the Team USA tryouts and why there needs to be an overhaul of the process, especially with the known commodity talent. They discuss the Trevor Baptiste and Matt Campbell injuries and how it impacts the most important game of the season for both the Atlas and Cannons. They preview the slate of games in the PLL and WLL on Long Island this weekend and discuss the Dyson Williams and Zed Williams releases and heir thoughts on each move. They round out the show with their Picks of the Week and gear up for another lacrosse-filled weekend!Voicemails: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠speakpipe.com/OTBLaxPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Support our partners!Merch: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Code UNDERGROUND for 10% off at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠phiapparel.co/shop⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠'47 BrandShop for your favorite sports fan and get FREE SHIPPING on ALL orders with '47 Brand!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠47.sjv.io/e1Nyor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠PLL App CodeDownload the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠PLL App⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & redeem code OTBPOD for 500 XP!RiversideGet your podcast looking and sounding pristine with Riverside!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://riverside.sjv.io/QjBBVM⁠⁠Kenwood BeerVisit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://kenwoodbeer.com/#finder⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to see who has Kenwood on tap! (Must be 21+)Follow Us!TwitterUnderground: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/UndergroundPHI⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠OTB: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/OTBLaxPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠KB: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/KBizzl311⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠DJ: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/Scs_nextgreat⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Hoots: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/HootSportsMedia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/otblaxpod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/undergroundphi⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠SUBSCRIBE on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠youtube.com/@UndergroundSportsPhiladelphia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠youtube.com/@OTBLaxPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Intro/Outro Music: Arkells "American Screams"#Lacrosse #NLL #NationalLacrosseLeague #PremierLacrosseLeague #WomensLacrosseLeague #LacrossePodcast #Subscribe #fyp

The market for AI tokens barely exists yet and that's exactly why this moment matters. In this Bitcoin Policy Hour, the team debates whether the AI industry disperses into many players or consolidates into an "AI Google," and what either outcome means for freedom, surveillance, and the dollar. They also tackle the US–China compute race, autonomous weapons, and data centers in space.

If you are a founder preparing to raise capital, this episode is a practical guide to getting investor-ready before you ever walk into the room.Oliver Bruce sits down with Connor Wells, founder of Caplia. Connor spent eight years inside one of the world's largest beauty businesses, moved into engineering-led innovation at Dyson, then ran PrimeTime as MD before building Caplia to fix the problem that nearly broke him: fundraising.The venture ecosystem is more fragmented than ever. Capital is flooding in. Founder numbers have tripled since the nineties. Yet rounds are still run like it is 1995, investors are drowning in noise, and great deals get missed because signal is buried inside manual pitch deck reviews.Connor's answer is capital readiness. Caplia turns your pitch deck into a Cap Passport in 60 seconds, giving investors decision-ready signal at their fingertips with your data room one click away. Its agentic AI, Iris, acts as a fundraising mentor that learns your process and deploys it. The goal is simple. Put every founder on the front foot from day one.Connor also gets honest about the human cost of raising. The 50 percent of your time it consumes. The relentless rejection. The resilience it demands. And why the right co-founder, the right early signal and a genuinely strategic cap table matter more than proximity to money.Key topics covered: How to know when your business is actually ready to raise Why the venture ecosystem is fragmented and how to cut through it What capital readiness looks like at pre-seed versus Series A How the Cap Passport turns a pitch deck into investor-ready signal Why fundraising eats 50 percent of a founder's time How to choose a co-founder you can build with Why design partnerships unlock distribution for early tech companies How to build credibility and signal before you raise a penny Why the female founder funding gap persists and how to close it Key takeaway: The founders who win the next decade of fundraising will be the ones who turn up ready, with clear signal, real credibility and confidence from day one.

Kemal Kılıçdaroğlu yönetimi, 9 milletvekilini kesin ihraç talebiyle Yüksek Disiplin Kurulu'na sevk etti. Dışişleri Bakanlığı, Cumhurbaşkanı Erdoğan'ın eleştirilerine yanıt veren Netanyahu'ya tepki gösterdi.Bu bölüm Dyson hakkında reklam içermektedir. Dyson Türkiye, teknoloji ve gastronomi arasındaki ilişkiyi odağına alan “Chefs' Kitchens With Dyson” projesini hayata geçirdi. Ayrıntılı bilgiye buradan ulaşabilirsiniz.

What happens when life takes you down a path you never expected?In this powerful conversation, Chad Williams and Daryl Perry sit down with Simon Dyson, father, caregiver, endurance athlete, author, and founder of Billy's Farm of Hopes and Dreams.Simon shares the story of his son Billy, who was diagnosed with cerebral palsy following complications at birth, and how decades of caregiving challenges, family struggles, endurance racing, alcoholism, recovery, faith, and self-discovery ultimately led him to a new purpose.From Ironman races to one of the toughest endurance cycling events in the world, Simon spent years searching for answers, trying to outrun pain, and searching for meaning. What he discovered along the way transformed not only his own life, but the lives he hopes to impact through Billy's Farm of Hopes and Dreams.This is a conversation about resilience, caregiving, recovery, faith, hope, purpose, and what can happen when we decide to keep moving forward, even when life feels impossible.Connect with Simon and Learn More About Billy's Farm of Hopes and Dreams:https://billysfarmsofhope.org/Follow Chad Williams:https://www.instagram.com/chadwillia1Follow Daryl Perry:https://www.instagram.com/daryltperry

If you are worried about China taking over due to having better robots than the yanks, I got mixed messages for ya here. This was created using DeepSeek v4 Pro. Remember when DeepSeek could do the same thing as chatGPT but on shitty processors and not much RAM? All those stocks shit themselves? Oh what memories. Would have been a great time to buy NVIDIA stocks. I didn't, if you're asking....It's pretty good but it really didn't follow the instruction in the prompt that Joel Hill is Jack the Insider on the transcript. So that's a minus point. But also, this took fucking ages to generate. It's better than lots of the yankee slop but damn son this took MINUTES. So they might take over if we are patient or whatever. Enjoy the episode. ----------------------------------------------Joel Hill (Jack the Insider) and Hong Kong Jack return for a sprawling episode that tackles two of the biggest stories shaping politics in 2026. The pair open with the jaw-dropping Redbridge poll putting One Nation at 31% of the primary vote — a number that would all but wipe the National Party off the federal map and potentially deliver Anthony Albanese a strengthened majority government by splintering the right. Joel and Jack clash over whether culture-war grievances or material concerns are driving the surge, while drawing historical parallels to Joh for Canberra and the DLP split of the 1950s.The conversation then crosses hemispheres for a tour through UK chaos: Peter Mandelson's leaked dossier exposing a rudderless No. 10 under Keir Starmer, Nicola Sturgeon's estranged husband pleading guilty to embezzling SNP donations on a surreal shopping spree of Lalique salt shakers, seven Dysons, and a motorhome with four miles on the clock, and a deeply troubling police body-cam incident that has reignited the two-tier policing debate ahead of three critical by-elections.The centrepiece of the episode is a sober, hour-long deep dive into the COVID-19 pandemic and what Australia has refused to learn. The Two Jacks lay out the true death toll (perhaps 22 to 69 million globally), the devastating scale of long COVID, the vaccine rollout failures, the absurdities of hotel quarantine with rubbish bags over heads, and why governments and public health officials are desperate to avoid a Royal Commission. They close by asking whether the next pandemic will meet a population that has permanently lost trust in its leaders — and whether we'll simply repeat the mistakes of both COVID and the Spanish flu.Sport provides a lighter coda: the Carlton revival under an interim coach, James Hird's awkward candidacy at Essendon, the expanded 48-team World Cup that nobody seems excited about, and a formidable New Zealand Test side taking on England at Lord's.00:00:25 — Introduction Joel welcomes listeners to Episode 159, recorded 4 June. Today: Australian political news, a check-in on the UK, and a deep dive into the COVID-19 pandemic.00:01:21 — The Redbridge Poll: One Nation at 31% The AFR's Redbridge poll: One Nation 31%, Labor 28%, LNP 20%, Greens 12%. The two-party preferred is now being calculated as One Nation versus Labor — a seismic shift in how Australian politics is measured.00:03:12 — Not Just a Protest Vote Jack argues this is real, not a re-run of Hanson's 1990s flash-in-the-pan. The South Australian state election and the Farrah by-election suggest One Nation support is durable. Joel counters that protest votes can be expressed at the ballot box and that Australians are tiring of pluralism.00:04:09 — If One Nation Succeeds, Labor Wins The cruel irony: One Nation's rise probably delivers Labor government. The National Party could simply disappear. The DLP kept the Coalition in power for decades as an anti-Labor party; One Nation may do the reverse.00:05:46 — Scrutiny and Splintering Joel notes One Nation's policies are "two-sentence fragments" and motherhood statements. When proper scrutiny arrives, the contradictions will surface. Hanson's parliamentary attendance is as poor as imaginable.00:08:22 — The Third Rail Jack argues populists succeed because they discuss what polite society won't: immigration, culture wars, welcome to country rituals. The major parties must engage these topics or cede the ground entirely.00:11:34 — Feeling Unheard The core driver, Jack contends: voters feel sneered at and silenced by mainstream politics. It's not about flag counts, it's about being listened to.00:13:50 — What Actually Drives Votes Joel pushes back: voting determinants are the household economy, migration, climate change — not culture war trivia. Culture wars "don't amount to a hill of beans" at the ballot box.00:14:51 — The DLP Parallel Both agree the One Nation phenomenon most closely resembles the DLP split of the 1950s and 60s — a right-wing fracture that delivered Labor government after Labor government.00:17:18 — The Republic Referendum Lesson Jack recalls the 1999 republic referendum: pro-republicans split between models rather than uniting, scuppering the whole project. Voters will vote their preference even knowing it helps their enemy.00:19:32 — UK Parallels: Accommodate or Fight? Significant figures in the UK Tory party are debating whether to fight Reform or reach an accommodation. Tony Abbott recently said the Liberal Party won't criticise Pauline Hanson.00:21:48 — Joh for Canberra Redux Imre Salusinszky's comparison: this is "Joh for Canberra" all over again. But Joel notes Joh's moment lasted months; One Nation's has already lasted years.00:24:08 — State Election Previews Joel predicts the Victorian state election will be chaotic and peculiar — a government that's been in power too long, an opposition that may not be up to the task, and One Nation peeling votes from safe Labor seats. NSW will give a clearer reading.00:25:44 — Hanson "Ready to Govern" — from the Senate? Pauline Hanson announced she's ready to govern. Joel asks: shouldn't she contest a lower-house seat first? Jack recalls the only precedent: John Gorton became PM while still a senator, but had to be eased into Kooyong.00:28:20 — The Mandelson Dossier: Starmer's Empty Suit Jack's read of the leaked Mandelson documents: ministers don't know what the PM wants, there's zero respect or fear of his authority. Starmer comes across as an empty chair. One minister's text: "Every meeting with Labour MPs — it's all about who can we tax to pay benefits to other people."00:30:50 — Mandelson's Legal Peril Mandelson is under police investigation for misconduct in public office. Could face charges — the seriousness depends on whether it's mere misconduct or genuine bribery for foreign interests.00:31:49 — The Nicola Sturgeon Saga Her estranged husband has pleaded guilty to embezzling roughly £400,000 in SNP donations. The shopping list: six high-end coffee machines, seven Dyson vacuums, Lalique salt and pepper shakers, Montblanc pens, Swiss watches, an iJag, part of a Volkswagen, and a motorhome with four miles on the clock parked at his 92-year-old mother's house. Nicola claims she "didn't go in the kitchen much."00:34:20 — The BBC Interview Laura Kuenssberg's forensic interview with Sturgeon — "not quite Prince Andrew, but not much better." Sturgeon has been cleared by Police Scotland, but her reputation, already damaged by the Alex Salmond trial, is now in tatters.00:35:05 — Will He Go to Prison? £400,000 is a substantial sum. With another £600,000 unaccounted for, a custodial sentence seems likely. The money was ring-fenced for a second independence referendum push.00:36:50 — Money Laundering or Conspicuous Consumption? Joel wonders if the bizarre purchases — multiple watches on the same day — were an amateur money-laundering attempt: buy goods with SNP funds, sell them quietly for cash.00:38:23 — UK By-elections: Makerfield Looms Three by-elections on 18 June, including the critical Makerfield contest. Andy Burnham, Greater Manchester's high-profile mayor, is the tepid favourite. Low turnout could help him return to Westminster.00:39:30 — The Body-Cam Incident A white teenager accused of racially vilifying a Sikh man was stabbed — and police arrested the bleeding victim, not the attacker. Body-cam footage shows the victim saying "I can't breathe, I've been stabbed" while officers dismiss him. Joel calls the footage "just awful."00:41:22 — Two-Tier Policing Jack traces UK policing's overcorrection: after the Macpherson/Lawrence report, guidelines were rewritten so aggressively that they've produced a pattern of questionable enforcement that devastates community trust — and plays directly into Tommy Robinson's hands.00:42:08 — NSW Police on Four Corners Joel recommends the harrowing Four Corners investigation: bashings in custody, false arrests, an officer who threw body-cam footage into Sydney Harbour, and two undercover officers jailed for a savage assault. The problem today is general duties policing, not the specialist squads of the 1980s. Some command areas are far worse than others — a leadership failure.00:44:55 — Victoria Police: Under-Resourced, Not Corrupt Joel shares an anecdote: two divisional vans for 80,000 people in outer-east Melbourne. Tough work being a police officer; even tougher being a good one.The COVID-19 Reckoning00:45:09 — Why This Matters Joel sets the frame: we parked COVID in 2023 with a hangover but never understood what we'd been through. Today's episode aims to crack that problem.00:45:51 — The True Death Toll Officially: 7 million dead. But most countries stopped testing and stopped reporting cause-of-death data to the WHO. Using excess mortality, the real toll is between 22 and 69 million — at the high end, exceeding the Spanish flu.00:47:02 — Long COVID's Shadow Roughly 400 million people globally (6% of the population) have experienced long COVID. In Australia alone, between 200,000 and 500,000 people are living with or have lived with the condition. Second infections can be worse. Emerging links to cardiovascular disease, type 2 diabetes, and accelerated dementia.00:49:43 — The Collective Amnesia Governments worldwide have "a collective embarrassment" about how they handled the pandemic, Jack says. They want it in the history books and forgotten. Joel says this is a grave mistake for public trust — and for public health, given COVID is now a permanent fixture alongside flu season.00:50:50 — Why Excess Deaths Are the Only Honest Metric All other figures are "kind of made up" because attribution methods vary wildly between countries. Excess deaths remain elevated in Australia and most nations.00:51:25 — Children and COVID Bobby Kennedy Jr. removed under-18s from government-supported vaccines in the US. Joel argues this is a disastrous move given mounting evidence that childhood COVID infection leads to higher rates of long-term chronic illness.00:52:47 — Why No Royal Commission? Not just politicians protecting themselves — public health officials and much of the media wanted to avoid scrutiny of their judgments and actions during the pandemic.00:53:32 — The Media's Abdication Jack watched "a lot" of Daniel Andrews's daily press conferences. Only two journalists ever asked pertinent questions: Rachel Baxendale and Leigh Sales. Nobody asked why curfews, why beach arrests, why the disparate impact on tradies and cafe owners while the "laptop class" actually made money working from home.00:56:14 — Andrews's Immense Popularity Joel adds context: Andrews was wildly popular at the time, which partly explains the media's deference — though Jack insists that shouldn't have mattered.00:57:34 — The Curfew Nonsense Curfews were about giving law enforcement the easiest possible environment, Joel says — and should have been acknowledged as such and wound back sooner. Meanwhile, Bondi's wealthy swam en masse while Western Sydney's working-class communities were treated harshly.00:57:59 — The Vaccine Rollout Failure The Morrison government bet everything on AstraZeneca — the non-mRNA, first-available vaccine. Then rare blood-clotting issues emerged (seven deaths, mainly men aged 40–49). Meanwhile, Australia was left waiting for Pfizer and other mRNA vaccines because no other supply deals had been secured.00:59:37 — Omicron Breaks the Pandemic's Back The Omicron variant emerged from South Africa: more infectious but far less lethal. Combined with 95%+ vaccination rates among Australians over 18, it effectively ended the acute phase — though at the cost of entrenched mistrust.01:00:38 — Government Overreach and Broken Trust Jack's core criticism: governments outsourced decision-making to public health officials rather than making political judgments that balanced competing interests. Joel counters that it would have been a "bold move" for politicians with no scientific background to contradict public health advice.01:02:19 — "Just Let It Rip" Was Never an Option The three countries with the highest COVID mortality — Brazil (highest), United States (second), India (third) — were all led by populist governments that largely refused mandates. Letting it rip was devastating.01:03:27 — The ADF Quarantine Scandal Scott Morrison refused to allow ADF quarantine facilities to be used for returning travellers. Instead, people were crammed into hotels with gaps under the doors. Joel recalls the "rubbish bags over heads" episode in Victoria — dark green plastic bags as infection control.01:05:00 — The Inquiry's Recommendations Create a proper Australian CDC. Release expert advice publicly. Better national planning with clear political accountability. And critically: politicians must own the big decisions on freedoms and spending instead of hiding behind experts.01:06:01 — The Next Pandemic There will be another one. If it's a respiratory, airborne pathogen like COVID, similar circumstances will return. Are we ready? Probably not. Will we close the country again? The economic damage — unemployment hitting 7.5% in 2020 — was enormous, even if it recovered to 3.5% by pandemic's end.01:08:06 — Who Was Left Behind? The arts community was inexplicably excluded from JobSeeker and JobKeeper. Meanwhile, the "laptop class" working from home effectively got a 15% pay rise by eliminating commuting costs. Bunnings did very well; so did companies that kept JobKeeper without passing it to employees.01:11:14 — The Human Cost of Lockdowns Public housing towers in Flemington were locked down. Joel recalls one family: an African-Australian single mother with nine children in a two-bedroom commission flat, trapped. Jack calls what happened with schools "disgraceful." But Joel notes the evidence now shows childhood COVID infection has serious long-term health consequences, complicating the retrospective judgment.01:13:59 — Will We Learn Anything? Jack's bleak prediction: the next pandemic is probably far enough away that we'll take no notice of COVID's lessons and make the same mistakes. Joel agrees — we didn't learn from the Spanish flu a century ago either.01:15:51 — Malcolm Roberts and Vaccine Misinformation The One Nation senator claims 70,000 Australians died from COVID vaccines — a figure with no evidentiary support, built by misattributing excess deaths. In reality, mRNA technology is now being deployed as a cancer treatment, showing promise against bowel and pancreatic cancers.01:17:36 — Trust Destroyed If the next pandemic arrives within this generation, governments will face a population that has lost faith. If it takes 50 years, the damage may have faded. Western Australia, meanwhile, locked itself down with negligible deaths and actually loved the isolation — provided the iron ore and LNG ships kept moving.01:20:37 — The Spanish Flu Echo Joel's closing historical note: Australia's response to the Spanish flu in 1919–1921 was nearly identical to COVID — lockdown disputes, police arresting people for not wearing masks, states fighting the newly created federal Department of Health. The whole thing collapsed into acrimony the moment state rivalries flared. A century later, nothing had changed.01:21:48 — Federation as Fatal Flaw Jack adds: the three high-mortality COVID countries (US, Brazil, India) share a feature beyond populist leaders — they're all federations where central government power is limited. When "the emperor is far away and the mountains are high," coordinated pandemic response is nearly impossible.01:23:40 — No Appetite for Truth Jack's final word: nobody wants a proper inquiry. Not politicians, not public health officials, not much of the media. Joel disagrees on the importance — the pandemic's legacy still shapes how Australians think, vote, and trust.Sport01:27:40 — AFL Coaching Carousel Essendon and Carlton both need permanent coaches. Joel asks: is James Hird the right man for Essendon? Jack: 17 other clubs wouldn't give him an interview, but the Bombers may have backed themselves into a corner where appointing him is the only way out.01:28:53 — Merit vs Member Sentiment Rowan Connolly's question: would you take James Hird or John Longmire (five grand finals, one premiership, 60%+ win rate)? The answer is obvious on merit — but members and fans want the fairy tale.01:29:47 — Carlton's Astonishing Revival Three straight wins. Ranked 16th in forward-50 entries a month ago; now second. The game style is unrecognisable — no more bombing the ball to non-existent power forwards. Mitch McGovern's low, flat kick to Patrick Cripps for the match-winner against Geelong was emblematic of the transformation. Seven players aged 21 or younger are now getting games and bringing energy.01:33:18 — FIFA World Cup 2026: Nobody's Excited Expanded to 48 teams, Scotland are going — and a Scot in his 30s told Jack that neither he nor any of his mates (all doing well financially, normally first on the plane) have any interest. Ticket prices are "extraordinary." The final is at MetLife Stadium in New Jersey — which Jack describes as "Waverley on steroids, but even more bleak."01:36:08 — Australia's Draw Socceroos face Turkey first up, then the United States. Jack suggests marketing it as "Gallipoli Round Two." Spain are favourites; England, Brazil, and Germany are in the chasing pack.01:37:06 — Cricket: England v New Zealand, First Test at Lord's Joel runs through New Zealand's likely top seven — Latham, Conway, Williamson, Ravindra, Mitchell, Blundell — noting the first four have all made Test double-centuries. "Just about the best first six in Test cricket." With O'Rourke's express pace and Henry's quality, this is a formidable Black Caps side.01:38:40 — Stump Speech & Next Week Listener mail (including an "exposé of who Jack is") held over for next episode. For the record: Hong Kong Jack's CV includes HSC at Assumption College Kilmore, a stint as a carpenter, a law degree from Melbourne University, stints at Holding Redlich and Slater & Gordon, work as a litigation and immigration lawyer, and an appointment to the Refugee Review Tribunal as a federal cabinet appointee.01:40:39 — Outro Joel thanks listeners for hanging in for an extra ten minutes. Back next week.The Two Jacks is recorded weekly. Send your questions and feedback to the show.

Central canal low back stenosis is a condition that can affect people as they age. As symptoms often affect both legs and are multi factorial, it can lead to increased frustration, as symptoms can become more difficult to manage around activities of daily living.During this episode I discuss the signs and symptoms, how it's managed and how I approach it in a clinical setting.This episodes featured pup is Dyson. If you want adopt Dyson, or learn about all the great dogs the Hamilton/Burlington SPCA has up for adoption you can visit https://www.hbspca.shop/products/dyson

On this episode of The Bandwich Tapes, I sit down in person with drummer Joe Dyson, the first in-person conversation I've recorded for the show, and it couldn't have been with a better musician or person.  Joe is currently on the road with Pat Metheny, and we talk about the experience of being inside that music night after night, how the band continues to grow, how chemistry develops on the road, and what it truly means to live inside the music.We begin at the very beginning, Joe's earliest connection to the drums, growing up in church, watching his family play, and learning through imitation long before formal instruction. That foundation, playing with purpose, listening deeply, and serving something larger than yourself, continues to shape everything he does today.  From there, we dive into the cultural impact of growing up in New Orleans and the moment Joe realized just how unique that musical environment is. His reflections on culture, identity, and the preservation of tradition are powerful and deeply personal.One of the most meaningful parts of this conversation centers around mentorship, specifically his relationships with Alvin Batiste and Donald Harrison. Joe shares incredible stories about how these mentors shaped him, not just musically, but philosophically, and how their lessons continue to reveal themselves years later.  We also spend time talking about listening, not just as a musical skill, but as a life skill. Joe makes a compelling case that listening is at the center of everything: collaboration, groove, communication, and even being a better human being.We get into his artistic philosophy, how he balances honoring the lineage of great drummers like Elvin Jones, Roy Haynes, and Philly Joe Jones while still pushing forward creatively. His perspective on imitation, emulation, and innovation is something every musician can learn from.Joe also shares the incredible (and almost missed!) story of how he connected with Pat Metheny, starting with an email he nearly ignored, and what it's like working with an artist of that level in both live and studio settings.We wrap up by talking about his debut album, Look Within, and how stepping into the role of a bandleader changed his perspective, not just musically, but also in how he approaches collaboration and supports other artists.This is a conversation about growth, humility, and the lifelong process of becoming a musician.Key TakeawaysJoe Dyson explains why listening is the most important skill a musician can develop—on and off the stage.He shares how growing up in church shaped his sense of purpose and connection to music.Joe reflects on the unique cultural identity of New Orleans and its lasting influence on his playing.He discusses the profound impact of mentorship from Alvin Batiste and Donald Harrison.Joe breaks down the process of musical growth: imitation → emulation → innovation.He tells the story of nearly ignoring the email that led to working with Pat Metheny.Leading his own band gave him a deeper respect for collaboration and the responsibilities of being a bandleader.Music from the EpisodePious Walk - Joe DysonForward - Joe DysonFleeting Faith - Joe DysonIn On It - Pat Metheny Side Eye IIINaysayers - Joe DysonAbout the PodcastThe Bandwich Tapes is my chance to sit down with musicians, composers, songwriters, and creative artists I admire for honest conversations about craft, collaboration, and the deeper musical ideas that shape their work. It's a space to explore process, perspective, and the human side of a life in music.Connect with the ShowEmail: contact@thebandwichtapes.com

Dave and Julie record with the office doors wide open to enjoy an unusually hot day here in royal Deeside, and a quick run for cold drinks sparks an unexpected marketing lesson about the "famous brand rule". The discussion flows naturally toward the topic of the power of social proof in the B2B space. Unlike world-renowned B2C brands such as Adidas, lesser-known B2B companies must rely heavily on case studies, certifications, and social proof to make buyers feel safe. We discuss the dangers of using confusing, engineering-led product names and turned out Dyson's intricate model numbers was a perfect illustration of that, often leaving consumers unable to make an easy choice.   On the second half od this episode, the conversation shifts to a deep dive into Google's recent major announcements, including their plan to weave sponsored product ads directly into conversational AI responses. Will this turn out to be an innovative move or just an unimaginative reaction to losing search traffic to ad-free platforms like Claude...? Julie also touches on the transition from dynamic search ads to AI Max, which aims to offer advertisers more control over their assets, and Google's new focus on tracking "qualified future conversions" to better accommodate long B2B sales cycles.   The episode wraps up with staggering statistics on AI search adoption, noting that AI mode now boasts over one billion monthly users with increasingly long follow-up queries.   Dave and Julie record with the office doors wide open to enjoy an unusually hot day here in Royal Deeside, where a quick run for cold drinks sparks an unexpected marketing lesson about the "famous brand rule". The discussion flows naturally toward the power of social proof in the B2B space. Unlike world-renowned B2C brands such as Adidas, lesser-known B2B companies must rely heavily on case studies, certifications, and social proof to make buyers feel safe.   Discussing the dangers of using confusing, engineering-led product names, Dave and Julie bring up Dyson's intricate model numbers that serve as a perfect illustration of this, as they often leave consumers confused and unable to make an easy choice.   In the second half of the episode, the conversation shifts to a deep dive into Google's recent major announcements, including their plan to weave sponsored product ads directly into conversational AI responses. Julie and Dave debate whether this will turn out to be an innovative move, or just an unimaginative reaction to losing search traffic to ad-free platforms like Claude. Julie also touches on the transition from dynamic search ads to AI Max, which aims to offer advertisers more control over their assets, and Google's new focus on tracking "qualified future conversions" to better accommodate long B2B sales cycles.   The episode wraps up with some staggering statistics on AI search adoption, noting that AI mode now boasts over one billion monthly users who are typing in increasingly long follow-up queries.   And as plugged multiple times throughout the show, be sure to go and listen to the Uncensored CMO podcast to hear the full conversation with Rory Sutherland and Tom Goodwin.

Jessica Coody sat down with sophomore pole vaulter Dyson Wicker to talk about his recent Big 10 Title at the conference track meet in Lincoln, Dyson dives into his journey with the pole vault, why he started and how he grew into one of the top athletes in the country, he talks his recruiting journey from Texas and why he chose Nebraska, previews the regional and NCAAs, and much more!

Are aliens watching us? The Zoo Hypothesis suggests advanced civilizations may be hiding, enforcing a galactic quarantine, or masking reality itself. Explore the Fermi Paradox, Dyson dilemma, and the unsettling possibility we are not alone—but observed.Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthurWatch my exclusive video Surviving a New Ice Age: https://nebula.tv/videos/isaacarthur-surviving-a-new-ice-ageCheck out Gods & Monsters: https://nebula.tv/curiousarchive/gods-and-monsters?ref=isaacarthur

Are aliens watching us? The Zoo Hypothesis suggests advanced civilizations may be hiding, enforcing a galactic quarantine, or masking reality itself. Explore the Fermi Paradox, Dyson dilemma, and the unsettling possibility we are not alone—but observed.Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthurWatch my exclusive video Surviving a New Ice Age: https://nebula.tv/videos/isaacarthur-surviving-a-new-ice-ageCheck out Gods & Monsters: https://nebula.tv/curiousarchive/gods-and-monsters?ref=isaacarthur

Derek Parker joins the show to talks Hawks draft. We go into who he sees as potential good fits at 8 and 23. Then we also talk about the outlook of some Hawks players currently on the team. Topics Best fit a 8 Best fits at 23 Should the Hawks stick with Risacher Jalen, Dyson & Kuminga outlook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

On episode 232 I am joined by Bernard Jackman, a former professional rugby player, coach, and now a performance consultant, guest speaker and respected voice in Irish sport. Bernard is a former pro Rugby player who played for Connacht, Leinster, Sale Sharks and an Irish international. He has been head coach in FC Grenoble, France and at the Dragons in Wales. Bernard is one of only a small number of Irish rugby players to have won a Six Nations, European Cup, Challenge Cup and a Magners League Medal.Since retiring from professional rugby he has moved into coaching and high-performance leadership. Bernard has built a diverse career across coaching, media, athlete development and performance consultancy, working with teams and organisations both within and beyond rugby. His work has also extended into other sporting environments, including collaborations with Horse Sport Ireland and involvement around the 2024 Paris Olympic Games. Jackman grew up on the Wicklow/Carlow border he grew up on a cattle farm which led to a different path to elite sport. We discuss how this affected his career and upbringing. Bernard shares his advice to parents with children on the elite sporting pathway and also offered insights to current athletes on developing their professional development and working during their sporting career. A major part of Bernard's professional development came through his master's research, where he travelled across the world studying some of the leading high-performance teams and organisations in sport including Manchester United, Dyson, Sydney Swans, Toyota, Melbourne Storm, Just Eat and more. Through visiting elite environments and learning directly from coaches, athletes and performance leaders, he gained valuable insight into the habits, cultures and systems that underpin sustained success at the highest level.In this episode, we discuss Bernard's journey through professional sport, working with Enda NcNulty, learning from Alex Ferguson, Brian O'Driscoll and Jonny Sexton, his approach to retirement, transitioning into coaching, high-performance environments, and the lessons he has taken from working across multiple sports. The conversation also explores performance, elite sport, and what high performance really looks like behind the scenes in sport & business.Find Bernard here https://www.linkedin.com/in/bernardjackmanFollow The Sideline Live Social Media channels and the host Orla here: https://linktr.ee/TheSidelineLiveRecorded using Samson Q2 microphone, Edited using GarageBandIntro music, Watered Eyes by a talented Irish artist, Dillon Ward check him out ⁠⁠here⁠⁠ . If you are looking to set up your own podcast get in touch with the Prymal Productions team ⁠⁠⁠www.prymal.ie⁠⁠⁠ 

Investigators are using an unusual tool to solve cold cases, discarded chewing gum. NBC News reports that DNA from gum has helped link suspects to violent crimes, including cases involving a serial offender, highlighting how advances in forensic technology are making old evidence “stick” and bringing new leads in long-unsolved murders. Dyson has unveiled a new fan and air purifier combo that can automatically follow you around the room, directing clean air wherever you are. The device uses sensors and motion‑tracking technology to adjust airflow in real time, highlighting how smart home products are becoming more personalized and a little futuristic. Please Like, Comment and Follow 'Philip Teresi on KMJ' on all platforms: --- Philip Teresi on KMJ is available on the KMJNOW app, Apple Podcasts, Spotify, YouTube or wherever else you listen to podcasts. -- Philip Teresi on KMJ Weekdays 2-6 PM Pacific on News/Talk 580 AM & 105.9 FM KMJ | Website | Facebook | Instagram | X | Podcast | Amazon | - Everything KMJ KMJNOW App | Podcasts | Facebook | X | Instagram See omnystudio.com/listener for privacy information.

Investigators are using an unusual tool to solve cold cases, discarded chewing gum. NBC News reports that DNA from gum has helped link suspects to violent crimes, including cases involving a serial offender, highlighting how advances in forensic technology are making old evidence “stick” and bringing new leads in long-unsolved murders. Dyson has unveiled a new fan and air purifier combo that can automatically follow you around the room, directing clean air wherever you are. The device uses sensors and motion‑tracking technology to adjust airflow in real time, highlighting how smart home products are becoming more personalized and a little futuristic. Please Like, Comment and Follow 'Philip Teresi on KMJ' on all platforms: --- Philip Teresi on KMJ is available on the KMJNOW app, Apple Podcasts, Spotify, YouTube or wherever else you listen to podcasts. -- Philip Teresi on KMJ Weekdays 2-6 PM Pacific on News/Talk 580 AM & 105.9 FM KMJ | Website | Facebook | Instagram | X | Podcast | Amazon | - Everything KMJ KMJNOW App | Podcasts | Facebook | X | Instagram See omnystudio.com/listener for privacy information.

Finish Him… Frenchie is Cooked! This week on the podcast, Brian and Darryl test their might with Mortal Kombat II, check in on the latest round of Homelander-induced misery in The Boys Season 5 Episode 7, suffer through The Punisher: One Last Kill, run the floor with the first four episodes of Running Point Season 2, and close things out with a good old-fashioned Odyssey bitch fest. You know, culture. Episode Index Intro: 0:07 The Odyssey Bitch Fest: 4:47 Running Point Season 2 Episodes 1-4: 10:48 The Punisher: One Last Kill: 20:45 The Boys Season 5 Episode 7: 33:00 Mortal Kombat II: 43:05 The Odyssey Bitch Fest Brian and Darryl close out the week with an Odyssey rant, because apparently ancient Greek epics, modern adaptations, translation discourse, and Hollywood hype cycles were not already exhausting enough. Somewhere, Homer is either proud, confused, or asking why everyone on the internet suddenly thinks they are a classics scholar with a Letterboxd account. Running Point: Season 2, Episodes 1-4 Series: Running Point Season: 2 Episodes covered: Episodes 1-4 Release date: April 23, 2026 Season 2, Episode 1 Title: New Coach Who Dis Air date: April 23, 2026 Director: David Stassen Writers: Mindy Kaling, Ike Barinholtz, and David Stassen Summary: Cam is back, which means Isla immediately has to deal with family politics, front office nonsense, and the ongoing question of who actually gets to control the Waves. With the team needing a new coach, Cam pushes his preferred pick while Isla tries to make the smarter basketball decision instead of the loudest nepo-baby decision. Season 2, Episode 2 Title: The Poacher Air date: April 23, 2026 Director: Erica Oyama Writer: Joe Mande Summary: Trade rumors around Dyson heat up, forcing Isla to fight for one of the team's most important players while Sandy uncovers a financial issue tied to Cam. Ali, tired of being treated like office furniture with a calendar invite, makes a major career move that threatens to shake up both the Waves and Isla's support system. Season 2, Episode 3 Title: Triangle of Badness Air date: April 23, 2026 Director: David Stassen Writer: David Phillips Summary: Ali's move to Canada creates a widening rift between her and Isla, because nothing says “healthy friendship” like professional resentment and international workplace drama. Meanwhile, the tension between Dyson and Travis keeps escalating, and Sandy tries to survive Charlie's new reality TV lifestyle without completely losing his mind. Season 2, Episode 4 Title: MVP: Marcus Very Pissed Air date: April 23, 2026 Director: Michael Weaver Writers: Ike Barinholtz and David Stassen Summary: The tension between Norm and Marcus starts turning into a full-blown problem, forcing Isla into damage-control mode. Sandy finally hits his breaking point with Charlie's reality show circus, while Ali begins questioning whether her big move was actually empowering or just a different flavor of chaos with better scenery. Rating out of 10 Those Canadians are the Nicest Cut Throats Ever Brian: 7.6/10 Darryl: 7.5/10 The Punisher: One Last Kill Title: The Punisher: One Last Kill Release date: May 12, 2026 Director: Reinaldo Marcus Green Writers: Jon Bernthal and Reinaldo Marcus Green Summary: Frank Castle is living off the grid, haunted by the ghosts of his past, and trying to exist without being the Punisher. Naturally, peace lasts about twelve seconds before Ma Gnucci and the Gnucci Crime Family drag him back into the kind of blood-soaked revenge spiral Marvel insists is “grounded” because nobody shoots laser beams. The special attempts to bridge Frank's story between Daredevil: Born Again and his next MCU appearance, but for Brian and Darryl, this one lands less like a brutal character study and more like Marvel trying to convince everyone that misery equals depth. Frank deserves better. So do we. Rating out of 10 Disney Just Doesn’t Get It Brian: 1/10 Darryl: 4/10 The Boys: Season 5, Episode 7 Title: The Frenchman, the Female, and the Man Called Mother’s Milk Air date: May 13, 2026 Director: Sylvain White Writer: Anslem Richardson Summary: Homelander, now juiced up with V1, fully tips into god-king nightmare mode by killing the President, dissolving the Seven, and preparing to reveal himself as America's favorite fascist deity. Soldier Boy tries to walk away, which goes about as well as you would expect when your son is Homelander and your family dynamic is basically a war crime with abs. Meanwhile, the Boys try to recreate Soldier Boy's depowering ability through Kimiko, Marie Moreau and Jordan Li uncover suspicious activity around Oh Father at Vought Studios, and the episode ends with Frenchie making one last move to protect Kimiko before Homelander fatally wounds him. So, you know, just another relaxing week in the Vought Cinematic Trauma Dump. Rating out of 5 A God Complex is a Terrible Thing to Waste Brian: 1.5/5 Darryl: 1.5/5 Mortal Kombat II Title: Mortal Kombat II Release date: May 8, 2026 Director: Simon McQuoid Writer: Jeremy Slater Rating: 7.99/10 Summary: Johnny Cage enters the arena as Earthrealm's fighters are pulled into the full-blown tournament chaos fans have been waiting for since the 2021 reboot. With Shao Kahn threatening the survival of Earthrealm and Kitana entering the mix, Mortal Kombat II leans into the franchise's blood-soaked mythology, fan-service mayhem, and video game ridiculousness in all the ways a movie like this absolutely should. It is loud, dumb, violent, and somehow still better calibrated than half the superhero stuff clogging the pipeline. Contact Us The Infamous Podcast can be found wherever podcasts are found on the Interwebs, feel free to subscribe and follow along on social media. And don't be shy about helping out the show with a 5-star review on Apple Podcasts to help us move up in the ratings. @infamouspodcast facebook/infamouspodcast instagram/infamouspodcast stitcher Apple Podcasts Spotify Google Play iHeart Radio contact@infamouspodcast.com Our theme music is ‘Skate Beat’ provided by Michael Henry, with additional music provided by Michael Henry. Find more at MeetMichaelHenry.com. The Infamous Podcast is hosted by Brian Tudor and Darryl Jasper, is recorded in Cincinnati, Ohio. The show is produced and edited by Brian Tudor. Subscribe today!

James Barlowe from draft junkies comes on the show to talk potential picks for the Hawks. Who does he like at 8 and 23? Then also we talk about the team outlook and roster. Topics Guys who stood out at the combine Who could the Hawks take a 8? Who could the Hawks take at 23? Jalen Johnson ceiling Risacher convo Dyson and more Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Explore SETI's history and modern methods—from radio and laser searches to Dyson spheres and technosignatures—and how we might detect alien civilizations across the galaxy.Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthurWatch my exclusive video Surviving a New Ice Age: https://nebula.tv/videos/isaacarthur-surviving-a-new-ice-ageCheck out Gods & Monsters: https://nebula.tv/curiousarchive/gods-and-monsters?ref=isaacarthur

Explore SETI's history and modern methods—from radio and laser searches to Dyson spheres and technosignatures—and how we might detect alien civilizations across the galaxy.Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthurWatch my exclusive video Surviving a New Ice Age: https://nebula.tv/videos/isaacarthur-surviving-a-new-ice-ageCheck out Gods & Monsters: https://nebula.tv/curiousarchive/gods-and-monsters?ref=isaacarthur

In this episode, Dan is joined by Jake Dyson to discuss his process of making training fun again by implementing a "gamification" element to his work with youth athletes. Jake Dyson is a performance coach and can be found on Instagram @emergeperformance where he shares innovative approaches to athletic development through gamified training, reactive movement, and competitive problem-solving. Known for blending creativity with performance principles, Jake has built a strong following by challenging traditional speed and agility models and helping athletes develop through variability, play, and real-world movement demands. Season 7 of the Braun Performance & Rehab Podcast is proudly supported by Pura Health, bringing ultrasound into every clinician's hands. Learn more at purahealth.net and @pura.health_ultrasound.Additional support provided by Firefly Recovery, the official recovery partner of Braun Performance & Rehab (recoveryfirefly.com), and Dr. Ray Gorman of Engage Movement. Learn how to grow your income beyond sessions—follow @raygormandpt on Instagram and DM “Dan” for a free breakdown of the blended practice model.Episode Affiliates: Airbands BFR (Coupon Code: DANIELBRAUN for 10% off), MoboBoard (BRAWNBODY10), AliRx (DBraunRx), MedBridge (BRAWN)If you enjoyed this episode, share it with someone who would benefit and leave a 5-star review.Explore more from Dan at linktr.ee/braun_pr.

In this conversation, Minter Dial is joined by Olivier Hinton, innovation strategist and psychologist, whose cross-Channel upbringing and multinational experience have profoundly shaped his perspective on change and creativity. Drawing from a career spanning France, the UK, Italy and beyond, Olivier Hinton sheds light on why embracing change is fundamental to innovation, and why companies must learn to “zoom out” from what they think they know in order to truly break new ground. The pair explore the real-world challenges organisations face when shifting from operational excellence to genuine innovation, untangling why it's so difficult to step away from established routines and the seductive comfort of “if it isn't broken, don't fix it.” Olivier Hinton goes behind the scenes of Groupe Zebra's approach to consulting on innovation and design, stressing the importance of integrating structure, function, and symbolism—not just in products, but in the processes and cultures that bring them to life. The discussion features candid examples—from the pitfalls of design innovation in everyday products, to the tricky dance of involving legal and financial stakeholders without stifling creative risk. The conversation delves into the influence of company culture, and the necessity of aligning innovation with brand DNA, illustrated by lessons from the likes of Renault and Dyson. Olivier also shares insights into the evolving role of AI, both as an enhancer of human insight and as a tool whose promise is all too often overestimated. Whether you're wrestling with innovation briefs, rethinking your approach to leadership, or navigating the tensions between flexibility and backbone, this episode is brimming with fresh perspectives on building tomorrow's business. Tune in as Minter Dial and Olivier Hinton challenge the buzzwords, uncover the thorny realities, and offer pathways to more human-centred, commercially viable innovation.

Join Matt Forde & Matt Dyson for an afternoon of goals and chaos!After Jamie Vardy unveiled an "interesting" ornament in a new documentary, Fordey and Dyson want to know, what ornamental tat have you spotted in other people's houses? Plus! Would you eat your dinner off a commemorative plate? And Matt Forde introduces a brand-new character in Séance of the Living

During the 4pm hour of today's show Chuck & Chernoff talked about Hawks-Knicks and specifically how Jalen, NAW and Dyson need to to step up, the Braves, Braves Pitching Alex Anthopolouys, the 2021 Georgia Bulldogs now having the record for most players drafted in the NFL ever with 45, the SEC's demise, Ozzie Albies and Money Mike being red hot and more! See omnystudio.com/listener for privacy information.

During the 4pm hour of today's show Chuck & Chernoff talked about Hawks-Knicks and specifically how Jalen, NAW and Dyson need to to step up, the Braves, Braves Pitching Alex Anthopolouys, the 2021 Georgia Bulldogs now having the record for most players drafted in the NFL ever with 45, the SEC's demise, Ozzie Albies and Money Mike being red hot and more! See omnystudio.com/listener for privacy information.

This week on the Jochum Strength Podcast we get the chance to talk with Jake Dyson a performance coach out of Iowa. You've probably seen his drills and warmups throughout social media actually getting athletes to move, compete, and be engaged. Throughout the episode he talks through how he comes up with different drills, how the rest of his sessions look, and his transition into this field. As always thank you for listening and enjoy the episode.

This week on Where’s Your Headline At?, Dyson Heppell opens up about the side of AFL pressure people rarely talk about. From body image expectations to his relationship with food during his career, Dyson gets candid about the mental toll that can come with elite sport, and how he eventually found balance again. We admire how candid Dyson was here and hope you take something away from his eps xxxSee omnystudio.com/listener for privacy information.

Welcome back to Where’s Your Head At! This week we’re joined by Dyson Heppell and we chat about his rise in the AFL, leading through one of the toughest periods in the game, and the pressure of having it all play out publicly. Dyson opens up about the mental toll, what he’s learnt from those challenges, and how it’s shaped who he is today. Plus, we get into his time in the jungle with Matt and his marriage, and what he’s learnt from long-term love. We’re so grateful for Dyson’s honesty in this episode, we hope you enjoy it xxSee omnystudio.com/listener for privacy information.

Tony: -Carbonation Station: Redbull White Peach Sugary, Dirty Mtn Dew Zero   -Artemis 2 is a success: https://www.engadget.com/science/space/the-artemis-ii-astronauts-are-back-after-a-10-day-journey-around-the-moon-033800654.html   -Anthropic still fighting to remove absurd “supply chain risk” label from DoD: https://www.politico.com/news/2026/04/08/d-c-circuit-rejects-anthropic-plea-to-pause-supply-chain-risk-label-00864880?experience_id=EXYF89KVT5UQ&is_login_link=true&template_id=OTJIR2CRKUD6&variant_id=OTV632IE7RALS   Jarron:  -An Intel laptop with insane battery life: https://www.notebookcheck.net/43-hours-battery-life-Dell-XPS-14-2026-lasts-almost-3x-longer-vs-MacBook-Air-15-M5-in-web-browsing-test.1262947.0.html   -A phone detox can restore 10 years to your brain: Two-Week Social Media 'Detox' Erases a Decade of Age-Related Decline, Study Finds   -Dyson put out a handheld fan that looks amaz….what is that shape?! Dyson just announced its first-ever handheld fan, with a motor that spins up to 65,000 RPM   Owen: -Kash Patel hacked by Iran. Im not surprised. https://www.reuters.com/world/us/iran-linked-hackers-claim-breach-of-fbi-directors-personal-email-doj-official-2026-03-27/   -Ok so we know sora is being shut down… but canceling erotic mode?!?! https://techcrunch.com/2026/03/26/openai-abandons-yet-another-side-quest-chatgpts-erotic-mode/ -Whose “ethics and morality” are we adding to AI? Is this the next Nicene Creed? https://www.msn.com/en-us/news/us/can-ai-be-a-child-of-god-inside-anthropic-s-meeting-with-christian-leaders/ar-AA20Eb2w

Geelong is quite literally on fire, Billy did a perfect ad read, and we start the show with the All Sports Report - as LIV Golf's future is suddenly up in the air. Former Essendon Captain Dyson Heppell joins the boys to talk about Run The Tan, plus his new career as Collingwood development coach, then Topics Rabs has a story about a possum. Herbie is in studio with some social media feedback from our Gather Round Road Trip, as well as some big news for 2027, then we hear an extended edition of Billy's Idiot File. Geelong star Jeremy Cameron calls in ahead of Mark Blicavs' 300th game tomorrow night against the Doggies, then Billy finishes with a joke about a firetruck.See omnystudio.com/listener for privacy information.

Kevin Dyson was part of the biggest play during the biggest season the Tennessee Titans have had to date. He saw the highs of the Music City Miracle and the bitter lows of being one yard short at Super Bowl XXXIV. And before long, he found his injury-prone career cut short in 2005. He wanted to coach but didn't have the credentials. So he went back to school and found education was his passion. He earned a doctorate, became a public school principal in Williamson County, and now he's starting his own athletics-focused charter school in Nashville — Music City Academy, scheduled to open in fall of 2027 if approved by the Metro Schools board of education. His mother asks him why he doesn't just take it easy. Dyson points to the title of his book, "Qualified So I Am Justified," and says he's still got something to prove.

Подводим итоги недели в совместном подкасте itzine.ru и Telegram-канала Forgeeks. Расскажем, зачем Яндекс обновил свой Поиск, нужно ли переплачивать за 2ТБ карту памяти, что научился делать Gemini, что такое ракета «Воронеж» и многое другое. Слушайте новый выпуск, читайте и подписывайтесь на ForGeeks в Telegram.00:00:04 Начало00:00:36 Яндекс обновил поиск, интегрировав нейросеть «Алиса»00:03:07 Нейросеть Gemini от Google научилась создавать интерактивные 3D-модели00:05:37 Apple удалила сторонний клиент Telega из App Store00:09:28 OpenAI представила новый тарифный план ChatGPT за 100 долларов00:12:51 SanDisk выпустила карту памяти объемом 2 ТБ за 2000 долларов00:15:09 США успешно испытали секретную технологию «призрачного шепота»00:17:35 Dyson представила портативный безлопастный вентилятор за 99 долларов00:21:25 Экипаж миссии Artemis 2 установил рекорд дальности пилотируемого полета00:24:27 В России зафиксирован масштабный сетевой сбой, затронувший работу государственных сервисов00:26:35 В России впервые одобрен проект частной ракеты-носителя00:28:15 Конец!

Hawks and United Broadcaster Mike Conti talks about how unexpected the Hawks turnaround since the All Star Break has been, role players stepping into starring roles, how difference the offense has flowed since things started to run through Dyson Daniels, the chances the Hawks would have to advance in the first round of the playoffs, why Jonathan Kuminga is having some issues having a bigger impact, keeping Zaccharie Risacher in a healthy mindset, and the Dan Hurley incident at the end of UConn's win.

In this episode, the mates discuss Elon's TeraFab: 1 terawatt/year chip factory (50x global AI compute), CyberCab fleets crushing rideshares, eVTOLs redesigning cities, garages-to-gyms real estate pivot, and moon disassembly for Dyson swarms amid robotaxi abundance. Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of OpenExO Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding      Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter  _ Connect with Peter: X Instagram Connect with Dave: X LinkedIn Connect with Salim: X Join Salim's Workshop to build your ExO  Connect with Alex Website LinkedIn X Email Substack  Spotify Threads Listen to MOONSHOTS: Apple YouTube – *Recorded on March 23rd, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Following the Supreme Court decision on tariffs, big companies including FedEx, Dyson, and L’Oréal are suing to recoup money paid. NPR’s Alina Selyukh explains why getting it back could be tricky. Some progress appears to have been made in the latest round of talks between the U.S. and Iran. Olivia Le Poidevin of Reuters joins to discuss why the two sides are still far apart. Mexican President Claudia Sheinbaum is under intense pressure to confront drug cartels. Emily Green of Reuters dissects how the killing of Mexico’s most powerful drug lord was a risky move. Plus, Hillary Clinton gave a deposition in the House’s Epstein investigation, why Netflix is backing out of the deal to buy Warner Bros., and Pope Leo tells priests not to use AI in homilies. Today’s episode was hosted by Cecilia Lei.

FedEx is suing the U.S. government for a full refund after the Supreme Court ruled the president lacked authority to impose certain tariffs, and the panel breaks down the $175 billion in refund claims from companies like L'Oréal, Dyson, Prada, and Costco, debating whether the ruling was about process, not legality, and what it means for negotiation leverage, small businesses, and America's ability to compete with China on national security priorities like semiconductors and rare earths.

From the BBC World Service: First up, British manufacturer Dyson settles a lawsuit filed against it by 24 migrant workers, and the Premier League says it's launching its own streaming service. And while David Brancaccio and the team will continue to share the economic news you need each weekday morning, today marks the final edition of the "Marketplace Morning Report" produced by the BBC World Service. Host Leanna Byrne reminisces about some of the show's biggest global news stories from over the years.

Chris Cuomo brings together key moments from this week's Cuomo Mornings on SiriusXM, featuring conversations with Michael Eric Dyson and Gary Vaynerchuk as the country reflects on the life and legacy of Reverend Jesse Jackson. Dyson shares personal stories from decades alongside Jackson, tracing his rise after Dr. King's assassination, the Rainbow Coalition campaigns of 1984 and 1988, and the relentless activism that defined his final years. The discussion turns to who carries that mantle now and what leadership looks like in a moment many Americans feel is lacking it. Gary Vee joins to talk about the algorithm-driven culture shaping politics, outrage, and self-worth — and why accountability, mindset, and economic opportunity may matter more than partisan warfare. Cuomo pushes back on whether social media is neutral, how political primaries reward extremes, and whether Americans still know how to disagree without dehumanizing one another. Calls from listeners also take the conversation into the Epstein controversy, transparency, media credibility, and the danger of conspiracy culture replacing serious inquiry. Join The Chris Cuomo Project on YouTube for ad-free episodes, early releases, exclusive access to Chris, and more: https://www.youtube.com/@chriscuomo/join Follow and subscribe to The Chris Cuomo Project on Apple Podcasts, Spotify, and YouTube for new episodes every Tuesday and Thursday: https://linktr.ee/cuomoproject Get 15% off OneSkin with code cuomo at https://www.oneskin.co/cuomo. #oneskinpod Head to https://factormeals.com/cuomo50off and use code cuomo50off to get 50 percent off and free breakfast for a year. Eat like a pro this month with Factor. Reverse hair loss with iRestore and get exclusive savings on the iRestore Elite—use code CUOMO at https://irestore.com/cuomo! #irestorepod Go to https://Leesa.com for 30% off mattresses PLUS get an extra $50 off with promo code CUOMO, exclusive for my listeners. Learn more about your ad choices. Visit podcastchoices.com/adchoices

The Robertsons dig into why truth doesn't always play well in modern culture, and why Jesus wouldn't be popular in a TikTok world built on virality and approval. The guys talk through everything from their long-running distrust of dentists to why being pro-life isn't a matter of personal preference or opinion. They reflect on how stories like The Chronicles of Narnia communicate hard truths better than arguments ever could and why true change is often so uncomfortable. Today's conversation is about Lesson 2 of C.S. Lewis on Christianity taught by visiting Hillsdale professor Michael Ward. Take the course with us at no cost to you! Sign up at http://unashamedforhillsdale.com/. More about C.S. Lewis on Christianity: Encounter the faith & wisdom of C.S. Lewis C.S. Lewis's writings bring the great questions of the Christian faith to life. Through his imaginative and invigorating style, Lewis answers these questions in ways that are compelling to those outside Christianity and energizing to those within the Christian faith. In this free, seven-lecture course, Professor Michael Ward—a leading scholar of C.S. Lewis—will explore Lewis's: argument for objective moral value in response to the rise of modern subjectivism; bittersweet path to conversion and the role of enjoyment in the Christian life; advice regarding the proper way to pray and read the Bible; teachings concerning the purpose of pain and how to confront suffering and loss; insights about the nature of heaven and hell. This course examines these fundamental topics not only through his classic works—including Mere Christianity, The Screwtape Letters, and The Abolition of Man—but also through Lewis's personal experiences with doubt, conversion, suffering, grief, and joy. Through this course, students will discover Lewis's core lessons regarding the truth and goodness of the Christian faith and how to apply those lessons to one's life.  Join us today in discovering C.S. Lewis's enduring lessons about the meaning and practice of Christianity. Sign up at ⁠http://unashamedforhillsdale.com/ Check out At Home with Phil Robertson, nearly 800 episodes of Phil's unfiltered wisdom, humor, and biblical truth, available for free for the first time! Get it on Apple, Spotify, Amazon, and anywhere you listen to podcasts! https://podcasts.apple.com/us/podcast/at-home-with-phil-robertson/id1835224621 Listen to Not Yet Now with Zach Dasher on Apple, Spotify, iHeart, or anywhere you get podcasts. Chapters: 0:00 – All good conversations need caffeine 4:05 – Why studying C.S. Lewis still matters today 8:25 – “I can't believe anything unless it makes sense” 13:10 – Objective truth vs. subjective feelings 18:20 – The problem of evil & why moral outrage points to God 23:55 – How suffering backed C.S. Lewis into Christianity 29:10 – Tolkien, Dyson, & relaxing into the Christian story 34:40 – Faith as participation, not just belief 40:05 – Why C.S. Lewis wouldn't be popular in today's culture 45:30 – Christianity isn't safe but it is good — Learn more about your ad choices. Visit megaphone.fm/adchoices