Podcasts about Citadel

Connect with Early Riders — https://www.earlyriders.com/contactConnect with Onramp — https://onrampbitcoin.com/contact-us/Presented collaboratively by Early Riders & Onramp Media…Final Settlement is a weekly podcast covering capital markets, dealmaking, early-stage venture, bitcoin applications and protocol development.This week Michael, Liam, and Brian break down Moonshot's Kimmy K3 release and what a more open, cheaper Chinese frontier model means for the race against Claude Fable 5 and GPT 5.6, from cyber guardrails and export controls to the Trump administration weighing a ban on Chinese models. They dig into the AI capital markets: Anthropic and DeepSeek's IPO plans, Nous Research's $75 million raise at a $1.5 billion valuation, Gavin Baker's intelligence-per-dollar thesis, Liquid AI, and OpenShip's self-hostable app platform. The guys run through the payments story: the $53 billion Stripe, Advent, and Block bid for PayPal, Visa's new OUSD stablecoin platform, and Amazon Japan's move into a yen-backed stablecoin. They cover a stack of digital asset headlines: IBIT options limits rising to 1 million contracts, Citadel's $400 million investment in Crypto.com at a $20 billion valuation, the ECB's digital euro pilot, Velocity's $38 million Series A, Tether's Genius Act countdown, and Lynn Alden's new Bitcoin-focused PE firm. They close on where the Clarity Act stands, Early Riders' mid-year letter, Onramp's back-to-basics promo, and AI's arrival in film and music.Chapters00:00 - Introduction and Weekly Recap01:26 - Kimmy K3 Release and Open Source AI Models05:43 - Meta-level Analysis of AI Race and AGI08:04 - AI Development: Capabilities and Guardrails09:44 - AI as a Commodity and Data Strategies11:08 - Global AI Race and Export Controls13:13 - US-China AI Power Dynamics16:46 - US Regulatory Posturing and Competition21:55 - US and Chinese AI Model Competition24:58 - AI Infrastructure and Market Share Shifts31:40 - AI and Financial Markets: IPOs and Capital Flows36:29 - Open Source AI Projects and Sovereignty37:16 - Fintech and Payments: Stripe, PayPal, and Crypto49:05 - Digital Asset Headlines: Tether, Stablecoins, and Regulation52:58 - Crypto Market Dynamics and Capital Flows55:25 - Bitcoin and Digital Asset Strategies01:00:16 - AI and Bitcoin: The Future of Capital and Innovation01:12:50 - Closing Remarks and Future OutlookIf you found this valuable, please subscribe to Early Riders Insights for access to the best content in the ecosystem weekly: https://www.earlyriders.com/researchKeep up with Michael:https://x.com/MTangumaKeep up with Liam:https://x.com/Lnelson_21Keep up with Brian:https://x.com/BackslashBTC

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

 Halifax Part 1 of 2  Dr. Mary Travelbest Guide podcast.  Find my book series on the website​​ at https://www.5stepstosolotravel.com/ or on Amazon. It's a several-part series. Today's destination is Halifax,  Nova Scotia, Canada. Part 1 of 2 Eastern Canada is understated. This episode is about what I actually did there in August 2025, as a solo woman traveler. Halifax surprised me. It is a harbor city, a university city, a military city, a cruise-ship city, and a place where history seems to rise from the water. One of the first things I noticed is that Halifax is surrounded by water. The harbor is not just scenery. It is part of the city's identity. Ships, ferries, kayaks, cruise passengers, navy vessels, and waterfront walkers all share the same sense of place. So I walked, I spent a lot of time along the waterfront. There was music, people eating outside, and a lively summer feeling. I was there around August 4, which was a holiday, and I ate poutine at the buskers' event. Poutine was new to me. It is French fries with cheese curds and gravy, topped with ketchup. It was a different flavor for me, and that is part of travel: trying something even when you are not sure it will become your favorite. Halifax has a strong maritime history, and I visited the Maritime Museum. That was one of the highlights. I learned more about the Halifax Explosion of December 6, 1917, when two ships collided in the harbor. The explosion was enormous — often described as the world's largest pre-atomic explosion. I heard that the anchor landed miles away, the water was displaced, and a tsunami followed. The next day, there was a blizzard. That story stayed with me because it showed how much tragedy this city has survived. The Maritime Museum also connects you to other parts of Halifax history, including shipyards, dockyards, and the city's role as a port. If you are a first-time visitor, this is a good place to start because it helps you understand why Halifax matters. Immigration museum https://pier21.ca/ Look up your family history here, including whether you have US relatives. It had a 15-minute wait, but it was free. I also visited the Citadel, up on the hill. I spent about two hours there learning about the military and cultural changes in the area. It was informative, and I am glad I made the climb. Halifax has hills, so wear good walking shoes. You may think you are just going "up the hill to the museum," but your legs will know you are in a real city with elevation. Another special experience was my kayak tour around St. George's Island. It was a two-and-a-half-hour tour, and we learned about tunnels and armaments from the time when the British were responsible for the harbor's defense and security. It was expensive, but I was really glad I did it. Sometimes a higher-cost experience is worth it because it gives you a memory you would not get any other way. I also made time for beauty and quiet. I took bus number 1 to the Public Gardens, and they were beautiful. The main gate is near South Park Street and Spring Garden Road. That area is a good part of the city to explore. I wandered, took buses, and let myself explore different parts of Halifax rather than staying in just one tourist zone. One morning, I went swimming at the Centennial Pool at 8:30 AM. The water was chilly, but not freezing, and I swam for about 45 minutes. It felt fantastic. I love finding ordinary things in a new city — a public pool, a bus route, a grocery store, a coffee shop — because those places help me feel less like a tourist and more like a temporary resident. I noticed Tim Hortons everywhere. Strong coffee, bathrooms, and big business. For a traveler, especially one moving around by bus, knowing where you can get coffee and find a bathroom matters. I rode public buses and appreciated that they announced the next street before arriving. That was helpful when I was trying to figure out where I was going. At one point, I jumped on a 10C bus, not completely sure where it was going, but I was on South Park Street and Spring Garden Road and seeing more of Halifax. That is one of my travel styles: I like to wander, but I also pay attention. I passed St. Mary's University, Dalhousie University, Gorsebrook Park on Inglis Street, and other neighborhoods. Halifax has a strong student presence, which gives parts of the city energy. Quinpool Road felt like a main drag for shops. I also hopped at the Mic Mac Mall. I went to the Art Gallery, where Maud Lewis's paintings are an important draw. I saw Point Pleasant Park, one of my favorite parts of the city, especially around Young Avenue. Halifax has one gated street with six houses on the ocean, and that area felt peaceful and special. Point Pleasant Park also carries reminders of storms and resilience. I heard about a hurricane in 2010 that downed a huge number of trees. Nature is beautiful here, but also powerful. I also visited downtown Halifax, including St. Paul's Anglican Church, the city's oldest building, dating back to 1749. It is close to downtown and gives you a sense of how old Halifax is by North American standards. A few small details stayed with me. Some red traffic lights in Nova Scotia were square. The city has a Commons area for winter skating at the Emera Oval. There is an armory, the Scotiabank Center for events, cruise ships at the harbor, Irving gas stations, and a pretty waterfront at night. I even saw or heard about Theodore the Tugboat, which brought a lighter, cheerful side to the harbor. My food experiences included fish and chips, scallops, clams, poutine, and outdoor eating. I remember Olive and Rudy, scallops and clams, and the pleasure of eating outside when the weather is right. Halifax is a good place for seafood and simple travel meals. One day, I had a ham sandwich, an apple, a pear, an orange, and toast. That helped me manage costs while spending money on experiences. My caution for listeners: someone mentioned the "Dome" neighborhood as a place with many bars and a possible recipe for a bar fight. I would say this more gently: as a solo traveler, especially at night, be aware of nightlife districts. You do not have to avoid fun, but you do need to know your surroundings. The shownote includes a link to crime mapping in Halifax. https://www.halifax.ca/safety-security/police/crime-mapping   My mistake for this episode: assuming Halifax would be only a small waterfront stop. It was much more layered than that. My lesson: Halifax is not just a pretty Canadian harbor. It is a city of resilience, history, students, seafood, public spaces, and water views. Next up will be Part 2 of 2 on Halifax.    Travel Mistakes  My mistake for this episode: assuming Halifax would be only a small waterfront stop. It was much more layered than that. My travel tip: take the buses, walk the waterfront, and do at least one water-based experience — a ferry, harbor cruise, or kayak tour.     AI was used to select some of the suggestions for this episode.   Connect with Dr. Travelbest 5 Steps to Solo Travel website Dr. Mary Travelbest X Dr. Mary Travelbest Facebook Page Dr. Mary Travelbest Facebook Group Dr. Mary Travelbest Instagram Dr. Mary Travelbest Podcast Dr. Travelbest on TikTok Dr.Travelbest on YouTube In the news  

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What separates the investors and founders who thrive in moments of radical change from those who don't? According to Alec Litowitz, it isn't intelligence or emotional maturity - it's adaptability.Alec is the founder of Magnetar Capital, one of the most respected multi-strategy hedge funds in the world, and the founder and managing partner of QStar Capital, his single family office and investment platform. Over a 30-year career that began at J.P. Morgan, continued as a founding partner and global head of equities at Citadel, and culminated in building Magnetar from scratch, Alec developed a framework he calls the Adaptability Quotient - AQ - for making decisions under genuine uncertainty. His book, The Adaptability Quotient, publishes September 15th.Today, through QStar, Alec invests with no fund mandate and no LP constraints - thematically across both public and private markets, in everything from CoreWeave and SpaceX to top-tier VC and PE managers. That unconstrained vantage point, combined with three decades of pattern recognition across market regimes, gives him a distinctive lens on where venture capital sits inside the current moment of change.Nick and Beezer dig into the core distinction Alec draws between risk and uncertainty - a difference he argues most investors collapse at their peril - and how the AQ framework maps directly onto how founders build, how VCs back them, and how the venture ecosystem itself needs to adapt. They also get into what he calls the second cognitive revolution: why AI isn't just a new tool but a system-level regime change, what that means for the capital stack and liquidity timelines in venture, and why the answer for smaller players isn't resistance - it's remapping.Quotes"What entrepreneurs get paid for is not risk. They get paid for uncertainty, for resolving the uncertainty. People may stay at some stranger's house or they may not, but I don't know the probability. If it's high, I have a business. If it's zero, I don't have a business. Let's go resolve that probability. And when someone does a startup and tests it, raises money, probes around it, and gets feedback loops - the answer is yes. That's what they get paid for, for resolving that uncertainty."Time Stamps00:00 What Entrepreneurs Actually Get Paid For00:31 Introducing Alec Litowitz: Citadel, Magnetar, and QStar02:49 Three Career Chapters and the Through Line: A Systematic Approach to Uncertainty06:09 The Book: Why Alec Wrote The Adaptability Quotient07:29 AQ Defined: Why IQ and EQ Aren't Enough When the Frame Itself Changes9:40 Why QStar: No Constraints, No Mandates, Just Mapping the Moment12:22 QStar's Investment Framework: Thematic, Top-Down, Technocentric and Anthrocentric14:51 Why Venture Still Matters: The Venture 20, the Mag Seven, and Where Disruption Lives17:03 Risk vs. Uncertainty vs. Black Swan: The Framework Most Investors Get Wrong22:30 Applying AQ in Venture: MVPs as Probes, Pivots as Feedback Loops22:51 A Case Study in Failing Without Feedback Loops24:33 The Second Cognitive Revolution: Why AI Is a Regime Change, Not a Tool29:20 Is SaaS Uninvestable? What Becomes Abundant and What Becomes Scarce32:53 Mapping the Venture Ecosystem: Capital Intensity, New Entrants, and IRR Pressure37:08 The Liquidity Problem Reframed: DPI, TDPI, and Timeline Mismatch40:12 Secondary Markets as a Structural Response43:48 Final Advice: Upgrade Your Operating SystemLinksConnect with the guest and hosts on LinkedIn!Alec LitowitzBeezer ClarksonNick ChirlsLearn more about:The Adaptability Quotient (pre-order on Amazon)QStar CapitalMagnetar Capital⁠⁠Early Adapters Newsletter⁠⁠Asylum Ventures⁠⁠OpenLP

Jim and A.Ron gather a conspiracy of ravens this week to answer your feedback and questions about all things House of the Dragon. Then, from the Citadel at Oldtown, please welcome Maester Anthony! He unveils a secret scroll of his own design and joins A.Ron and Max to break down the spoiler questions. Theme song: Game of Thrones (80's TV Theme) by Highway Superstar Maester Anthony's Double Dragon on Spotify and Apple Podcasts  Support Bald Move:  Club Bald Move Leave Us A Review on Apple Podcasts Join the discussion:  Email  |  Discord  |  Reddit  |  Forums Follow us: Twitch | YouTube | Twitter  |  Instagram  |  Facebook Learn more about your ad choices. Visit megaphone.fm/adchoices

Jim and A.Ron gather a conspiracy of ravens this week to answer your feedback and questions about all things House of the Dragon. Then, from the Citadel at Oldtown, please welcome Maester Anthony! He unveils a secret scroll of his own design and joins A.Ron and Max to break down the spoiler questions. Theme song: ⁠Game of Thrones (80's TV Theme)⁠ by ⁠Highway Superstar⁠ Maester Anthony's Double Dragon on ⁠Spotify⁠ and ⁠Apple Podcasts⁠  Support Bald Move:  ⁠Club Bald Move⁠ ⁠Leave Us A Review on Apple Podcasts⁠ Join the discussion:  ⁠Email⁠  |  Discord  |  Reddit  |  ⁠Forums⁠ Follow us: ⁠Twitch⁠ | ⁠YouTube⁠ | ⁠Twitter⁠  |  ⁠Instagram⁠  |  ⁠Facebook⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

It was a pleasure to welcome David Silber, Head of Institutional Equity Derivatives at Citadel Securities, to the Alpha Exchange to discuss the evolution of listed options markets, institutional liquidity, and the technology reshaping modern derivatives trading. We begin with Dave's early career on the floor of the Chicago Board Options Exchange during the transition to multi-listed options, where market making, open outcry, and physical proximity to order flow defined liquidity provision. He reflects on the evolution of the options market from paper tickets and fractional pricing to today's electronic ecosystem, highlighting how advances in technology have fundamentally changed both price discovery and risk management. We then turn to the creation of Citadel Securities' institutional derivatives business. Dave explains how his experience across multiple firms led him to identify opportunities to reduce friction in institutional options execution by combining technology, quantitative research, and broad access to liquidity. He describes how automation, electronic execution, and competitive pricing have transformed the institutional trading experience while expanding access to listed options. The discussion also examines recent growth in listed options markets, including increasing contract volumes, shorter-dated expirations, and the expanding use of listed options by institutional investors for hedging, leverage, and portfolio management. Dave shares his perspective on liquidity provision, risk management, and the importance of maintaining resilient markets during periods of elevated activity. We conclude with a discussion on recruiting talent, developing strategy and data products for clients, and aligning sales, trading, and technology teams around creating a more efficient experience for institutional investors. I hope you enjoy this episode of the Alpha Exchange, my conversation with David Silber.

Ken Griffin, the founder and CEO of Citadel, expects agentic artificial intelligence (AI) to enable a “golden age” of entrepreneurship and eliminate some corporate moats, even as the cost of using AI creates a deep moat around other companies. And while some jobs may be replaced by technology, Griffin says he has found that productivity increases from AI have, instead of reducing headcount, allowed his company to pursue new opportunities.   Griffin shares his views on geopolitical tensions between the US and China, the need for domestic data center construction in the US, and a range of other factors rippling through global markets in this episode of Goldman Sachs Exchanges: Great Investors, recorded at Goldman Sachs's Apex Symposium.  This episode was recorded on June 2, 2026. The opinions and views expressed herein are as of the date of publication, subject to change without notice, and may not necessarily reflect the institutional views of Goldman Sachs or its affiliates. The material provided is intended for informational purposes only, and does not constitute investment advice, a recommendation from any Goldman Sachs entity to take any particular action, or an offer or solicitation to purchase or sell any securities or financial products. This material may contain forward-looking statements. Past performance is not indicative of future results. Neither Goldman Sachs nor any of its affiliates make any representations or warranties, express or implied, as to the accuracy or completeness of the statements or information contained herein and disclaim any liability whatsoever for reliance on such information for any purpose. Each name of a third-party organization mentioned is the property of the company to which it relates, is used here strictly for informational and identification purposes only and is not used to imply any ownership or license rights between any such company and Goldman Sachs. A transcript is provided for convenience and may differ from the original video or audio content. Goldman Sachs is not responsible for any errors in the transcript. This material should not be copied, distributed, published, or reproduced in whole or in part or disclosed by any recipient to any other person without the express written consent of Goldman Sachs. Disclosures applicable to research with respect to issuers, if any, mentioned herein are available through your Goldman Sachs representative or at ⁠http://www.gs.com/research/hedge.html⁠ Goldman Sachs does not endorse any candidate or any political party. Views of the interviewee do not necessarily reflect the views of Goldman Sachs.  Copyright 2026. All rights reserved. Learn more about your ad choices. Visit megaphone.fm/adchoices

Gullah-Geechee Diasporas: Knowledge, Culture, and Black Lowcountry Legacies (University of South Carolina Press, 2026) counters romantic portrayals of Gullah-Geechee culture as a static, geographically isolated remnant of the past. Across eight interdisciplinary essays, the book's contributors trace an arc, described in time and space, from pre-Middle Passage Africa through the Caribbean and coastal United States into the interior South and beyond. They consider how Gullah-Geechee cultural traditions are simultaneously rooted in the physical Lowcountry homeland and represent a dynamic cultural ethos that is not bounded by geography and has shaped Black life across North America and the Caribbean Basin. Together, these essays reveal the resilience and adaptability of people whose history defies myths of isolation and immobility. Gullah-Geechee Diasporas is a fresh framework for understanding African American cultural origins, migrations, and transformations. Dr. Muhammad Fraser-Rahim is associate professor of Intelligence and Security Studies at The Citadel. He is the author of America's Other Muslims and Gullah Geechee Muslims in America. You can find him on Instagram and LinkedIn.Dr. Elizabeth J. West is professor of English and the John B. and Elena Diaz-Verson Amos Distinguished Chair in English Letters at Georgia State University. Her books include Finding Francis and African Spirituality in Black Women's Fiction. She can be found online at Instagram and LinkedIn. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/african-american-studies

Gullah-Geechee Diasporas: Knowledge, Culture, and Black Lowcountry Legacies (University of South Carolina Press, 2026) counters romantic portrayals of Gullah-Geechee culture as a static, geographically isolated remnant of the past. Across eight interdisciplinary essays, the book's contributors trace an arc, described in time and space, from pre-Middle Passage Africa through the Caribbean and coastal United States into the interior South and beyond. They consider how Gullah-Geechee cultural traditions are simultaneously rooted in the physical Lowcountry homeland and represent a dynamic cultural ethos that is not bounded by geography and has shaped Black life across North America and the Caribbean Basin. Together, these essays reveal the resilience and adaptability of people whose history defies myths of isolation and immobility. Gullah-Geechee Diasporas is a fresh framework for understanding African American cultural origins, migrations, and transformations. Dr. Muhammad Fraser-Rahim is associate professor of Intelligence and Security Studies at The Citadel. He is the author of America's Other Muslims and Gullah Geechee Muslims in America. You can find him on Instagram and LinkedIn.Dr. Elizabeth J. West is professor of English and the John B. and Elena Diaz-Verson Amos Distinguished Chair in English Letters at Georgia State University. Her books include Finding Francis and African Spirituality in Black Women's Fiction. She can be found online at Instagram and LinkedIn. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Gullah-Geechee Diasporas: Knowledge, Culture, and Black Lowcountry Legacies (University of South Carolina Press, 2026) counters romantic portrayals of Gullah-Geechee culture as a static, geographically isolated remnant of the past. Across eight interdisciplinary essays, the book's contributors trace an arc, described in time and space, from pre-Middle Passage Africa through the Caribbean and coastal United States into the interior South and beyond. They consider how Gullah-Geechee cultural traditions are simultaneously rooted in the physical Lowcountry homeland and represent a dynamic cultural ethos that is not bounded by geography and has shaped Black life across North America and the Caribbean Basin. Together, these essays reveal the resilience and adaptability of people whose history defies myths of isolation and immobility. Gullah-Geechee Diasporas is a fresh framework for understanding African American cultural origins, migrations, and transformations. Dr. Muhammad Fraser-Rahim is associate professor of Intelligence and Security Studies at The Citadel. He is the author of America's Other Muslims and Gullah Geechee Muslims in America. You can find him on Instagram and LinkedIn.Dr. Elizabeth J. West is professor of English and the John B. and Elena Diaz-Verson Amos Distinguished Chair in English Letters at Georgia State University. Her books include Finding Francis and African Spirituality in Black Women's Fiction. She can be found online at Instagram and LinkedIn. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/history

In this episode, we go over how unchecked eyes secretly ruin your personal defenses and drive your life toward temptation. 1. Chronological "Chapter" Timestamps[00:00] - The Driver's Ed Rule: Why your life inevitably drifts in the exact direction of your eyes.[01:15] - The Citadel and the Open Gate: How bad eye discipline allows the enemy to quietly assemble an army inside your walls.[02:10] - The National Geographic Mindset: Confronting the toxic habit of taking "mental snapshots" for later.[03:30] - The Act of Stealing: Why looking with lust objectifies others and strips away your own future loyalty.[04:45] - The Overflowing Bucket: How temptation builds gradually drop-by-drop until sudden failure occurs.[06:00] - Master the "Eye Bounce": The practical, immediate action step to redirect your gaze and your mind.[07:15] - The Covenant of Job: Relying on Scripture (Job 31:1) to anchor your visual integrity.[08:40] - The 6-Week Neurological Shift: What to expect when your eyes stop fighting against you and start fighting for you.2. Deep-Dive Key TakeawaysThe Law of Visual Direction: Just like driving a car at 70 mph or navigating a mountain bike through a berm, your body biologically follows your gaze. If you look at the median, you crash into it. If you look at lust, your life steers directly into it.The Illusion of Sudden Failure: Relapse never happens all at once. Your mind is a bucket left out in a rainstorm. Every lingering look is a single drop of water. You don't notice the danger early on, but eventually, the bucket overflows and breaks. Moving the bucket means refusing to collect the drops.Lust as Spiritual Theft: Looking lustfully at a woman is not a victimless crime. It is an act of theft—stealing her dignity, stealing your own integrity, and stealing the exclusive loyalty that belongs to your future or current wife.

Joel, and Stephen give their full review of The Mandalorian And Grogu, and Masters Of The Universe. Plus, listener email about adapting, and casting books to the screen.Show notes for The Citadel Cafe are here:https://thecitadelcafe.com/2026/07/01/the-citadel-cafe-506-the-mandalorian-and-the-masters-of-the-universe/Join The Citadel Cafe Discord community!http://Patreon.com/TheCitadelCafeThe Citadel Cafe YouTube:https://youtube.com/thecitadelcafeMusic for The Citadel Cafe by Kevin MacLeod (incompetech.com) licensed under Creative Commons by Attribution 4.0 Hosted on Acast. See acast.com/privacy for more information.

Mike DeAddio is the Chief Operating Officer of Paloma Partners, the multi-manager platform founded by Donald Sussman in 1981 — one of the original seeders of firms like D.E. Shaw, Elliott, Canyon, and Caxton.   Mike takes us through a technical career that spans across Bell Labs, JPMorgan, Citadel and, Silver Point before bringing that entire playbook to Paloma.   We dig into what it takes to build institutional-grade hedge fund infrastructure today versus a decade ago and how Paloma completed a full technology refresh. All while keeping the plane in the air.   From there, we get into the model that makes Paloma different: flexible operational infrastructure and tailored to each manager's style and goals — minimizing operational burden so they can focus on alpha generation — and a commitment to their long-term success, whether that means growing within the platform or eventually going out on their own.   For anyone running or building operations at a hedge fund or multi-manager platform — this one's a masterclass on the operational lift when trying to launch a hedge fund today.  Learn MoreFollow Capital Allocators at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@tseides⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠mailing list ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Access transcript with ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Membership ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠)

Welcome to Episode 215 of the Bodybuilding Down Under Podcast! We open with an athlete watch, turning the spotlight on a couple of natural competitors who are making some serious noise heading into their upcoming shows. We discuss what's changed in their packages, what's got us excited, and why the standards being set are worth paying close attention to. From there we get into a conversation around natural federation integrity, specifically the three-year drug free period and why we think it falls well short of the gold standard. We discuss what polygraph testing actually adds to the process and what it would realistically take for a federation like NPC Natural to challenge WNBF's standing.  To close things out we talk about the current gym equipment arms race happening across Queensland, covering everything from Prime, Megamass, MedX and Citadel, through to some Technogym slander. Enjoy! Instagram Handles: Bodybuilding Down Under: https://www.instagram.com/bodybuildingdownunder/?hl=en Jack: https://www.instagram.com/jack.radfordsmith/ Daniel C: https://www.instagram.com/daniel.chapelle/ Lawrence: https://www.instagram.com/general.muscle/ Daniel Y: https://www.instagram.com/dy.fit/

This week, Kev and Ciarnan revisit the never-ending Brendan Sorsby saga as his request to enter the NFL Supplemental Draft is denied. They also discuss the NCAA adopting an age based eligibility model, and debate potential changes to the transfer portal windows. They also react to Brian Kelly joining CBS to cover the Mountain West, and ask an important question: are there actually mountains in Illinois? Then it's time for another logo history deep dive, this time covering the MAC. From iconic mascots and underrated classics to some truly questionable design choices, the guys rank every Mid-American Conference logo while celebrating the beautiful chaos that makes MACtion one of the best traditions in college football. Plus, thoughts on The Citadel finding bodies during their stadium renovation, World Cup talk, mascot weirdness, and planning some MACtion livestreams! 00:00 NFL denies supplemental draft request 06:38 NFL legal dispute discussion 10:17 Discussing Brandon Source's draft prospects 13:03 Big 12 legal discussions 14:37 College football lawsuit drama 20:33 Old bodies, not a murder case 21:15 Brian Kelly joins CBS 24:48 New eligibility rules for athletes 29:16 NCAA transfer timeline discussion 31:56 Raccoons at college football games 34:51 Getting rid of the logo 38:45 Discussing logo design choices 42:25 Central Michigan's logo history 46:25 Discussing color changes 47:56 Toledo vs. Kent State Performance 50:54 Changing team branding and mascots 55:04 USA's World Cup chances

We have a stadium name and people are very opinionated about it. Did Arkansas banks reject them first? Ruscin believes its not for as much money as they were hoping for and that is why they are hiding the financials from the public. Plus witch doctors at the World Cup and dead bodies under the stadium at The Citadel. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The Cognitive Crucible is a forum that presents different perspectives and emerging thought leadership related to the information environment. The opinions expressed by guests are their own, and do not necessarily reflect the views of or endorsement by the Information Professionals Association. During this episode, Dave Acosta and Austin Branch discuss IPA's APEX conference which will be September 8–9, 2026 at the CARASOFT facility in Reston VA. As governments, militaries, industries, and societies confront increasingly sophisticated influence operations, disinformation campaigns, and cognitive warfare activities, the need for cognitive security education, research, and professional development has never been greater. APEX 2026 is a two-day educational forum dedicated to advancing the emerging field of cognitive security. Bringing together educators, researchers, students, practitioners, government representatives, and industry leaders, APEX seeks to foster collaboration, strengthen professional expertise, and contribute to the development of future approaches to Operations in the Information Environment (OIE). Recording Date: 19 June 2026 Resources: APEX Conference Link to full show notes and resources Guest Bio:  Austin Branch is a nationally recognized leader in cognitive security, strategic influence, and information operations. A retired Army Officer and senior U.S. government executive, he pioneered the Army's Information Operations career field and served as the first Senior Director for IO in the Office of Special Operations and Low Intensity Conflict. He is the co-founder of the Information Professionals Association and Managing Partner of Crescent Bridge Corporation, advancing cross-sector solutions to achieve cognitive advantage. He also serves as Professor of Practice at the University of Maryland's Applied Research Lab for Intelligence and Security and as an Adjunct Professor at The Citadel, where he teaches Cognitive Security. A contributor to The Cipher Brief, Austin also designs college-level curricula on intelligence and gray zone competition, blending operational insight with academic rigor to mentor the next generation of strategic thinkers. David Acosta is a Board Member of the Information Professionals Association and focuses on the Association's education portfolio. Additionally, Dave serves as a Colonel in the U.S. Army Reserve, currently commanding the 2nd Brigade, 91st Training Division, headquartered in Denver, Colorado. He served at various levels throughout his career from the company/battery level to the Headquarters, Department of the Army G-3/5/7. He commanded the 303d Information Operations (IO) Battalion, 151st Theater IO Group at Camp Parks CA and served as the G3 Information Operations (IO) Chief for the US Army Civil Affairs and Psychological Operations Command (Airborne). He also served as the Assistant Deputy Director for Joint Warfighting Development, Joint Staff J-7 in Suffolk, Virginia. His operational tours include deployments to Kosovo in 1999, Bosnia-Herzegovina in 2002, and Iraq in 2007 and 2009. Additionally, Dave is a Professor of Practice of Technical Operations in the Information Environment at the Naval Postgraduate School in Monterey, California. Dave holds a Bachelors of Science in History (Russian Area) from the US Air Force Academy, a Master of Science in Joint Information Operations from the Naval Postgraduate School, and a Master of Strategic Studies from the Army War College. He is a PhD student of International Studies at Old Dominion University in Norfolk, Virginia. About: The Information Professionals Association (IPA) is a non-profit organization dedicated to exploring the role of information activities, such as influence and cognitive security, within the national security sector and helping to bridge the divide between operations and research. Its goal is to increase interdisciplinary collaboration between scholars and practitioners and policymakers with an interest in this domain. For more information, please contact us at communications@information-professionals.org. Or, connect directly with The Cognitive Crucible podcast host, John Bicknell, on LinkedIn. Disclosure: As an Amazon Associate, 1) IPA earns from qualifying purchases, 2) IPA gets commissions for purchases made through links in this post.

In this episode, Chris Nichols and Caleb Stevens sit down with Brennan Perkins, a recent Citadel graduate, to explore how early leadership experiences translate into a career in banking. From learning how to be an effective follower to leading peers under pressure, Brennan shares key lessons on servant leadership, attention to detail, and building influence without authority. The conversation highlights how discipline and structure can coexist with creativity and problem-solving, and why curiosity, humility, and a willingness to learn are critical for success early in a banking career. Ultimately, it offers a fresh perspective on how foundational leadership principles can shape future leaders in financial services. Download our newest eBook: The Community Bank Performance Engine!   The views, information, or opinions expressed during this show are solely those of the participants involved and do not necessarily represent those of SouthState Bank and its employees. SouthState Bank, N.A. - Member FDIC

We are LIVE from the Hard Rock Bet Bus from the Citadel parking lot today for our Match Vibes Party! Tobin and Leroy set the scene for the USA's matchup versus Australia today; will captain Christian Pulisic play with his hamstring injury? And then we are joined by Juan Sebastian Urresti, World Cup analyst to break things down!

No Cars, All Kicks This week on the podcast, Brian and Darryl are back with spies, shadows, and a whole lot of martial arts chaos. They dig into Citadel Season 2 Episodes 5-7, check in on Spider-Noir Episodes 5-6, and throw down with the 2026 action film The Furious, starring Joe Taslim and Xie Miao. From high-stakes spy nonsense to black-and-white superhero noir to bone-crunching action, this episode has a little bit of everything. Citadel keeps pushing its global conspiracy machine forward, Spider-Noir continues blending superhero mythology with hardboiled detective vibes, and The Furious delivers exactly what the title promises: furious people kicking the absolute hell out of each other. Episode Index Intro: 0:07 Citadel (Season 2, Episodes 5-7): 6:51 Spider-Noir (Episodes 5-6): 28:47 The Furious: 46:51 Citadel (Prime Video) Season 2, Episode 5 Title: Heirlooms Air date: May 6, 2026 Runtime: 49 minutes Director: David Weil / Joseph Russo Writer: David Weil and Kennedy Edmonds Summary: Mason and Dahlia put a dangerous prisoner exchange in motion as they try to negotiate Abby's release, but Mason's unraveling mental state threatens to blow up the whole plan. As both sides race to complete the trade, Abby reveals something that changes the stakes for everyone and pushes the season deeper into betrayal, family damage, and spy-world manipulation. Season 2, Episode 6 Title: Highlands Air date: May 6, 2026 Runtime: 36 minutes Director: Greg Yaitanes / Joseph Russo Writer: David J. Rosen and David Weil Summary: As Joana moves closer to assassinating the Russian president at the G8 Summit and taking control of a Russian satellite network, Mason and Nadia bring Abby to a safehouse in Scotland. What should be a moment to regroup becomes another emotional and tactical disaster when the team uncovers the horrifying truth about what was done to Abby, setting off a devastating chain of events. Season 2, Episode 7 Title: Chin Chin Air date: May 6, 2026 Runtime: 44 minutes Director: Greg Yaitanes / Joseph Russo Writer: David J. Rosen and David Weil Summary: The season finale brings the Citadel team to the G8 Summit, where Joana plans to assassinate President Aronov and seize control of Russian satellites. The team is forced into a dangerous infiltration mission full of impossible choices, collapsing loyalties, and the kind of last-minute spy chaos that turns a diplomatic summit into a battlefield. Rating Out of 10, The Unexpected is Always Unexpected Brian: 8.55/10 Daryl: 7.77/10 Season 2 Rating Out of 10, Hutch is THE MAN Brian: 8.3/10 Darryl: 7.5/10 Citadel Series Out of 10, Kane… Mason Kane Brian: 8/10 Darryl: 7.25/10 Spider-Noir (Prime Video) Season 1, Episode 5 Title: Betrayal Air date: May 27, 2026 Director: Alethea Jones Writer: Jennifer Frazin and Steve Lightfoot Summary: Robbie continues fighting to reclaim his place at the Bugle, using his exclusive stories about super-powered soldiers and the return of The Spider to make his case. The episode digs deeper into deception, identity, and the strange science behind this noir-soaked superhero world, pushing Ben Reilly further into the mystery while the danger around him keeps getting uglier. Season 1, Episode 6 Title: Nightmare on a Gurney Air date: May 27, 2026 Director: Alethea Jones Writer: Jack Henderson, Jennifer Frazin, and Megan Liao Summary: The mystery tightens as Ben Reilly, Robbie, and the rest of the players move closer to the truth behind the city's super-powered nightmare. With the endgame starting to take shape, the episode leans into medical horror, noir paranoia, and superhero conspiracy, setting up the final stretch of the season with more questions, more danger, and more bodies piling up in the shadows. Rating Out of 10, Come on Webs, Work! Brian: 7.3/10 Darryl: 8.25/10 The Furious (2026) Release Date: June 12, 2026 Runtime: 113 minutes Director: Kenji Tanigaki Writers: Mak Tin Shu, Lei Zhilong, Shum Kwan Sin, and Frank Hui Studios: Edko Films, Zhejiang Hengdian Film, and XYZ Films Distributor: Lionsgate Premiere / Lionsgate Films Rating: R for strong bloody violence and language Summary: When his daughter Rainy is kidnapped, humble tradesman Wang Wei is dragged into a violent criminal underworld where corruption, trafficking, and blood-soaked revenge collide. His only real ally is Navin, a journalist whose own family tragedy connects him to the same criminal network. Together, they fight through waves of gangsters, assassins, and human wrecking balls in a brutal martial arts rescue mission that is light on subtlety and very, very heavy on kicks. Main Cast: Xie Miao as Wang Wei Joe Taslim as Navin Yang Enyou as Rainy Jeeja Yanin as Matia Brian Le as Ho / HD Yayan Ruhian as Tak Joey Iwanaga as Pak Lung Production Notes: The Furious is directed by Kenji Tanigaki, a veteran stunt coordinator and action filmmaker, and the movie's biggest selling point is exactly what you would expect from that background: relentless, bone-crunching fight choreography. The film premiered internationally before its 2026 U.S. theatrical release, with coverage positioning it as a Hong Kong action throwback built around practical stunt work, violent hand-to-hand combat, and the kind of crowd-pleasing martial arts insanity that has drawn comparisons to The Raid and other modern action benchmarks. The film is commonly listed as a 2025 Hong Kong production because of its festival premiere, but its U.S. theatrical release is June 12, 2026. Lionsgate handled the U.S. release, and Movie Insider lists the film as a nationwide theatrical release with an R rating for strong bloody violence and language. Rating Out of 10, Everybody Was Kung Fu Fighting… Especially the Guy with the Bow Brian: 8.11/10 Darryl: 8.2/10 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!

This month we are featuring a feed drop from The Penumbra Podcast one of the brilliant shows on the RQ Network. This episode is called “Knight of the Crown Lord of the Swamp Part 1 “and is from the 2nd season of the Second Citadel, a fantasy epic where friendships and romance are forged across enemy lines, which follows the fierce Sir Carolinem the first female Knight of the Crown, leading an eclectic team of warriors against mind-manipulating monsters. In this episode The Festival of the Three is the most important day of the year in the Second Citadel – or the most important three days, as the case may be. Battles and music and drink run free in Citadel's square, and nearly every knight is in attendance… which leaves very few to guard from the monsters' constant threat.Luckily, Sir Damien is on guard tonight, standing outside the Queen's chambers with his trusty bow in hand. But Sir Damien is injured, and when a monstrous threat crawls in, he may find that it's a very different sort of challenge from what he's used to.Introduction and outro by Karim Kronfli. You can listen to the next exciting episode of The Penumbra Podcast by clicking on this link, or by searching for The Penumbra Podcast wherever you find podcasts, on the Rusty Quill website and at www.thepenumbrapodcast.com If you would like to support the creators of The Penumbra and access behind-the-scenes content like production scripts, commentaries, blooper reels, and more you can find more information at The Penumbra Podcast: Special Edition.Transcript:You can find transcripts for all the episodes on the Penumbra Podcast here: https://drive.google.com/drive/folders/1OLddnnYamZuglgZc8pM2gqToPOwEBccM?usp=sharingAttributions: Licensed under a Creative Commons Attribution (3.0) license.http://creativecommons.org/licenses/by/3.0/legalcode"Kind of Girl" by Jeris, featuring spinningmerkaba: http://ccmixter.org/files/VJ_Memes/35657“hang_drum_310513.WAV” by miastodzwiekow http://www.freesound.org/people/miastodzwiekow/sounds/194584/“Ueno Shamisen – Japan” by RTB45 http://www.freesound.org/people/RTB45/sounds/195521/“Bhutan – Festival folk song” by RTB45 http://www.freesound.org/people/RTB45/sounds/179389/“Indian Ganpati Drums - Mumbai India - Track 1 – WAV” by loganbking http://www.freesound.org/people/loganbking/sounds/353143/Ganpati Drums - Mumbai India - Track 3 - WAV by loganbking http://www.freesound.org/people/loganbking/sounds/353141/“Javanese Angklung Music – Indonesia” by RTB45 http://www.freesound.org/people/RTB45/sounds/253962/“Pakacaping Music 1 - Makassar, Indonesia” by RTB45 http://www.freesound.org/people/RTB45/sounds/253616/Street_Hulusi_short.flac by Zabuhailohttp://www.freesound.org/people/Zabuhailo/sounds/194910/“20140212 - Chiang Rai mountains at night 10.wav” by LG http://www.freesound.org/people/LG/sounds/345151/“Regular Arrow Shot with Rattle” by brendan89 http://www.freesound.org/people/brendan89/sounds/321553/“Regular Arrow Shot” by brendan89 http://www.freesound.org/people/brendan89/sounds/321552/“Arrow Hit 02” by Yap_Audio_Production http://www.freesound.org/people/Yap_Audio_Production/sounds/218463/“cape-swoosh” by CosmicEmbers http://www.freesound.org/people/CosmicEmbers/sounds/161415/“Ambient battle noise: swords and shouting” by pfranzen http://www.freesound.org/people/pfranzen/sounds/192072/“Earthquake” by hiriak http://www.freesound.org/people/hiriak/sounds/187857/“Waves.wav” by juskiddink http://www.freesound.org/people/juskiddink/sounds/60507/“dragon wings.wav” by vedas http://www.freesound.org/people/vedas/sounds/175381/“Thunderclap.wav” by shaka9 http://www.freesound.org/people/shaka9/sounds/160514/“panic” by Erdie http://www.freesound.org/people/Erdie/sounds/165613/“CR Sharktopus Roar3” by cmusounddesign http://www.freesound.org/people/cmusounddesign/sounds/126312/Content Warnings:- Sudden loud noises- Depictions and descriptions of violence and death- Close, claustrophobic spaces- Depictions of illness (poison)- GaslightingFor ad-free episodes, bonus content and more, join members.rustyquill.com or our Patreon.Pre-order FROM THE LIBRARY OF JURGEN LEITNER, a Magnus novel releasing October 27th: rustyquill.com/novelBuy tickets to a Magnus Archives Live Show in Sheffield in July: crossedwires.live Hosted on Acast. See acast.com/privacy for more information.

John is joined by Shawn Fagan, the Chief Legal Officer of Citadel LLC and a key legal figure at Citadel Securities. Citadel is the most profitable hedge fund globally, while Citadel Securities is a leading market maker, processing nearly one-third of U.S. equities and options trades. They discuss Shawn's insights into the unique legal challenges of these rapidly growing organizations.Shawn has essentially four clients: Citadel, Citadel Securities, founder Ken Griffin, and Griffin's family office. His responsibilities extend beyond legal oversight to include regulatory affairs and compliance, reflecting the complexities of modern finance.Shawn's journey to Citadel was unconventional. He started as a litigator at Bartlit Beck, a boutique trial firm, where he spent nearly half his time in trial. He participated in high-profile cases, including Bush v. Gore, but ultimately realized that trial work was not his passion. A chance meeting with Ken Griffin led to an in-house opportunity at Citadel, where he has now been for 20 years.During that time, Citadel has grown from 1,000 employees and $12 billion in assets under management to 4,900 employees and $65 billion in assets under management. The focus of Shawn's role at Citadel is building the right teams to meet the demands of rapidly growing markets around the world, developing technology to ensure regulatory compliance across billions of transactions every day, and maintaining consistent standards in an organization that continues to grow at an extraordinary pace.Citadel has engaged in several high-profile legal battles, including lawsuits against the SEC and IRS, reflecting the firm's willingness to challenge regulations it views as unreasonable and unduly burdensome. When retaining outside counsel, Shawn looks for lawyers with strategic vision who can articulate a clear path to winning cases.Podcast Link: Law-disrupted.fmHost: John B. Quinn Producer: Alexis HydeMusic and Editing by: Alexander Rossi

Truly Significant honors Chuck Garcia and his extraordinary Dad and Mother in this special edition of Success Made to Last.  Learn from this insightful conversation about the art of honoring your parents today and always...... for you are their legacy. Chuck is a mountain climber, financial guru, college professor, brother, friend, and much more. Here's what grabbed me........Success gets you to the summits of life...significance (from intellectual giants like his parents) teaches you why you made the climb.Chuck spent 25 years on Wall Street in leadership roles at Bloomberg, BlackRock, and Citadel before reinventing himself as a leadership coach, speaker, author, professor, and mountaineer.Today he is the founder of Climb Leadership International and teaches leadership communication at Columbia University. His work focuses on emotional intelligence, executive presence, communication, and resilience. What makes him especially interesting through the Truly Significant lens is that he doesn't teach leadership from theory alone. He uses mountain climbing as a metaphor for life, leadership, and transformation.He has climbed peaks including Kilimanjaro, Elbrus, and the Matterhorn, and often connects lessons from the mountains to moments of personal reinvention. His most recent book, The Moment That Defines Your Life, explores how emotional intelligence and Stoic philosophy help people navigate defining moments when careers, families, and identities are on the line. What is Truly Significant About Chuck Garcia? Not the titles. Not Wall Street. Not the mountains.What's significant is that Chuck's career suggests a central truth: Remember.....Success gets you to the summit. Significance teaches you why you climbed the mountain in the first place.Become a supporter of this podcast: https://www.spreaker.com/podcast/success-made-to-last-legends--4302039/support.

They analyze the Miami Marlins' recent success under Clayton McCullough and the Florida Panthers' postseason journey. The discussion highlights Stephen A. Smith's public apology to Jalen Brunson and Shaquille O'Neal's critique of Victor Wembanyama's strength. Additionally, they cover Daniel Cormier's reaction to his social media hack and details on the Summer of Soccer event at the Citadel. 01:01 - Studio Banter And Soccer 02:36 - Marlins And Panthers News 05:15 - Stephen A. Smith Apologizes 08:31 - NBA And UFC Updates

Send us Fan Mail Have you ever heard a voice come through a radio that seemed misplaced? You might have heard a voice from beyond the veil. In our story, “The Message,” by Clinton Dangerfield, a death-row inmate and a chaplain hear a voice through the radio offering comfort. But is that truly what the spirit is offering?  Trying to contact spirits through radio waves is not a new technique for communicating with the dead. Even Thomas Edison designed one in the 1920's.  There have been many designs since then but let's look at its most modern counterpart, The Ghost Box. MusicFesliyan Studios: "Ghost," "Halloween," Phil Thorton: "At the Gates of the Citadel"Narration: Robert BreaultPlease join us! Like and follow our Facebook page to become " patron of the Cemetery Hills Library, or (even better!)  jump on our Patreon page and become a VIP Patron.                         Mugs, tee-shirts and eternal thanks await you!                                                                  Patreon Page: https://www.patreon.com/user?u=61177769&fan_landing=trueWebpage: http://www.afterwordsparanormal.comFacebook: After Words Paranormal Podcast

Vladimir Novakovski sits down with Andy & Robbie to break down the Lighter bull thesis from The Tokenization Tower in NYC. We discuss Lighter's escape hatch design that lets every participant exit through Ethereum even if the protocol fails, why the RFQ model is the key to bootstrapping liquidity for pre-IPO and RWA perps, and why getting Citadel and US institutional capital on chain is the biggest unlock the perp market hasn't hit yet. He's working with the CFTC to make that happen.Vladimir Novakovski is CEO of Lighter, a decentralized perp exchange built on top of Ethereum with an institutional-grade security-first architecture.The Rollup is where the leaders of digital assets and finance converge. Live from the financial capital of the world.Timestamps00:00 Intro01:37 Perp Market Awareness Today03:26 Pitching Institutions On Lighter05:28 Ethereum Security And Escape Hatch07:54 How Market Makers Stay Comfortable11:17 How Lighter Bootstraps Liquidity12:35 Pre-IPO Perp Durability15:37 Build In-House Or Composable19:29 US Regulatory Path For Perps23:29 CFTC Innovation Council Insights26:39 Questions For Commissioner Hester Peirce28:07 Team Culture And Miami Office32:26 Founder Decision Making Framework34:46 AI Agents And Lighter's Stack37:30 Perps Market Structure Long View41:21 Power Law Or Distributed Market?Guest Socials:Vladimir Novakovski X: https://x.com/vnovakovskiLighter X: https://x.com/Lighter_xyzLighter Website: https://lighter.xyz/Partners:Better than Banks. Transparent capital efficiency earning the highest yields in DeFi. Learn more here: https://infinifi.xyz/---Dinari - Over 230 1:1 backed tokenized stocks, ETFs & more with dividends. US-based SEC transfer agent. Available on 5+ chains & via API. https://dinari.com/---Relay is the fastest and most reliable way to swap any token on any chain. Learn more here: https://relay.link/bridge---Zama is an open source cryptography company that builds state-of-the-art Fully Homomorphic Encryption (FHE) solutions for blockchain.Learn more here: https://www.zama.org/---Trezor is the creator of the first-ever hardware wallet. Securing crypto for 2M+ users worldwide. 100% open source. Learn more here: https://affil.trezor.io/aff_c?offer_id=133&aff_id=36664---

emocleW, emocleW, emocleW to the Distraction Pieces Podcast with Scroobius Pip!This is your bonus FRIDAY REWIND episode! Today, we catch up with Rahul Kholi, originally episode 355 from 2020-11-25.Original writeup below:An ALMOST in person DPP right here - well, Pip and the guest being in the same city, in a country far far away from their respective homesteads anyway - please enjoy a brilliantly upfront and honest chat with actor RAHUL KOHLI!I say upfront and honest - basically it's one where sentiments aren't hinted at, and feelings and thoughts are addressed in a mature and adult manner. He and Pip are currently in Vancouver, Canada, in the midst of filming in some very airtight pandemic conditions. You can hear all about that, which of course branches out into how life is in Canada, viewing the pandemic from a different country, the attitudes in the US, race and the media, privilege, social media tone deafness, becoming a Twitter celeb (not as glamorous as it sounds), what re-Trump-ing says about you, Mike Bithell and the amazing North Star Rising project he and Pip guested on, auditions, gaming voiceovers, acting, and the many intricate nuances of invoking Bollywood. It's a packed one and it's great. Get yerself in a listening situation.PIP'S PATREON PAGE if you're of a supporting natureRAHUL on TWITTERRAHUL on IMDBRAHUL AGENTTWEETSTORM FUNTIMESiZOMBIEPIP x TOMO CAMPBELL @ HARRY STYLES MELTDOWN • SOUTHBANK CENTREPIP TWITCH • (music stuff)PIP INSTAGRAMSPEECH DEVELOPMENT WEBSTOREPIP TWITTERPIP IMDBPOD BIBLE Hosted on Acast. See acast.com/privacy for more information.

En este episodio de Extra Anormal Podcast hablamos de relatos de terror reales ligados a parques de diversiones malditos, botargas embrujadas, juegos mecánicos, payasos, brujas, espíritus de niños y entidades oscuras que se esconden en sitios donde, supuestamente, todo debería ser diversión.⚠️ Historias sobre una botarga en Europa que caminaba de noche sin que hubiera nadie dentro; una trabajadora de Citadel marcada por el espíritu de un niño que intentaba ahogarla desde su infancia; un ritual oscuro dentro de Parque Mágico; una bruja que ofrecía dulces en un parque rural; una entidad demoníaca en Monterrey que tomaba la forma de una niña, y una desaparición relacionada con payasos y un circo que llegó al pueblo.En este episodio encontrarás:

Grayskull, Gumshoes, and Global Spy Nonsense This week on the podcast, Brian and Darryl have the power… allegedly. The guys dig into Citadel Season 2 episodes 3 and 4, continue down the black-and-white rabbit hole with Spider-Noir episodes 3 and 4, and then head back to Eternia for the 2026 live-action Masters of the Universe movie. It's spies, spiders, swords, Skeletor, and probably way too much yelling about whether He-Man should ever be self-aware. Episode Index Intro: 0:07 The Citadel Season 2 (eps 3-4): 4:56 Spider-Noir (eps 3-4): 19:54 Masters of the Universe (2026): 32:02 The Citadel (Amazon Prime) Series: Citadel Season: 2 Network: Prime Video Season 2 Release Date: May 6, 2026 Season 2 Episode Count: 7 episodes Starring: Richard Madden, Priyanka Chopra Jonas, Stanley Tucci, Lesley Manville, Matt Berry, Michael Trucco, Rahul Kohli, Merle Dandridge, and Jack Reynor Citadel Season 2 released all seven episodes on Prime Video on May 6, 2026, with episode 3 titled “Chinos” and episode 4 titled “Unreasonable.” Prime Video describes the season as a globe-spanning spy thriller following Mason Kane, Nadia Sinh, and Bernard Orlick as Citadel operatives caught in a conspiracy where “anyone could be friend or foe.” Episode 3: “Chinos” Director: Joe Russo Writers: Gursimran Sandhu and David J. Rosen Original Air Date: May 6, 2026 Summary: As Paulo's plan escalates, Mason and Nadia are forced into an uneasy alliance. Bernard, Hutch, Celine, and Frank Sharpe join the mission as the team tries to uncover the identity of a mysterious hacker before the threat spins further out of control. Episode 4: “Unreasonable” Director: Joe Russo Writers: Tori Sampson, David Weil, and David J. Rosen Original Air Date: May 6, 2026 Summary: After pulling the truth about Edison's identity, the team shifts focus to a high-profile gala where their target is expected to appear. Mason and Nadia's tensions keep rising, enemies close in from every angle, and one dishonest move threatens to blow up the entire mission. Rating out of 10, What do the Italians Have Against Cereal Brian: 7/10 Darryl: 7.3/10 Spider-Noir (Amazon Prime) Series: Spider-Noir Season: 1 Network: MGM+ / Prime Video Season 1 Release: May 25, 2026 on MGM+ in the U.S.; May 27, 2026 on Prime Video Episode Count: 8 episodes Runtime: About 45 minutes per episode Starring: Nicolas Cage, Lamorne Morris, Li Jun Li, Karen Rodriguez, Abraham Popoola, Jack Huston, and Brendan Gleeson Spider-Noir follows a struggling private investigator in 1930s New York who is forced back into his past life as the city's lone superhero. The series stars Nicolas Cage as Ben “The Spider” Reilly, with Lamorne Morris as Robbie Robertson, Li Jun Li as Cat Hardy, Jack Huston as Flint Marko, and Brendan Gleeson as Silvermane. Episode 3: “Double Cross” Director: Nzingha Stewart Writers: Megan Liao and Steve Lightfoot Original Air Date: May 25, 2026 on MGM+ / May 27, 2026 on Prime Video Summary: Ben is hired by Silvermane to find who leaked his liquor transfer. At the hospital, he learns injured officers were tipped off by Morris. Robbie goes to a poor neighborhood to question Lincoln but witnesses a raid ordered by Morris, forcing Marko and Lincoln to use their powers against the cops. Janet discovers Addison, Lincoln, and Marko were former prisoners of war. Ben also finds out Carmedy lied about being Cat’s husband to gather evidence on Morris and that Cat arranged the meeting. He concludes Cat leaked the transfer and hired Addison to burn down Silvermane’s mansion. Ben breaks into Silvermane’s vault to pay Vera to leave town before she exposes Cat. Marko briefly considers escaping with Cat, but abandons the idea due to his symptoms worsening further. Ben later confronts Cat at Penn Station as she tries to flee, but Winston captures them. After tracing marked payments from Silvermane, Ben frames Winston by using his money to pay Vera. Silvermane shoots and kills Winston. Episode 4: “A Mistake I'll Never Make Again” Director: Nzingha Stewart Writer: Tori Sampson Original Air Date: May 25, 2026 on MGM+ / May 27, 2026 on Prime Video Summary: Cat reveals to Ben she hired Addison to kill Silvermane so she could settle down with Marko after Silvermane murdered her first fiancé. Marko eavesdrops on their discussion. Feeling betrayed, he decides to work for Silvermane again. Robbie and Janet interview Lincoln at the office. Silvermane uses Marko to intimidate Morris into backing off on his campaign ending Prohibition. Ben and Cat spend the night at his place, where he divulges on how Ruby died from a criminal he caught seeking revenge. They both leave after hearing a metahuman is attacking the Diamond District, presuming it to be Marko. The metahuman is a man named Dirk Leyden, a criminal with the ability to absorb and release electricity. The Spider defeats him by shutting off the power in the area to prevent Leyden from storing any more electricity, and Morris uses his victory to boost his campaign. Cat returns to Ben’s apartment and deduces that he is the Spider before kissing him. Rating out of 10, A Very Electric Spier-Noir Brian: 6.5/10 Darryl: 7.4/10 Masters of the Universe (2026) Release Date: June 5, 2026 Director: Travis Knight Screenplay: Chris Butler, Aaron Nee, Adam Nee, and Dave Callaham Distributor: Amazon MGM Studios in the U.S.; Sony Pictures International Releasing internationally Rating: PG-13 Runtime: 2 hours, 20 minutes Genre: Adventure, Action, Fantasy Starring: Nicholas Galitzine, Jared Leto, Idris Elba, Camila Mendes, Kristen Wiig, Alison Brie, James Purefoy, Morena Baccarin, Jóhannes Haukur Jóhannesson, and Charlotte Riley In the 2026 live-action Masters of the Universe, Prince Adam returns to Eternia after being separated from his home for 15 years. With Skeletor ruling over a shattered world, Adam must reunite with Teela and Duncan/Man-At-Arms, accept his destiny, and become He-Man. The cast includes Nicholas Galitzine as Prince Adam/He-Man, Jared Leto as Skeletor, Idris Elba as Duncan/Man-At-Arms, Camila Mendes as Teela, Kristen Wiig as the voice of Roboto, Alison Brie as Evil-Lyn, James Purefoy as King Randor, Morena Baccarin as the Sorceress, Jóhannes Haukur Jóhannesson as Malcolm/Fisto, and Charlotte Riley as Queen Marlena. Summary: After losing Eternia to Skeletor as a child, Prince Adam is sent to Earth with the Sword of Power, only to lose it during his escape. Fifteen years later, Adam has built a normal life in Oklahoma City while obsessively searching for the sword and proof that Eternia was real. When he finally recovers it, Teela brings him back home to a ruined kingdom under Skeletor's control. Dismissed at first as unworthy, Adam reconnects with Teela, Duncan, Roboto, and Eternia's remaining warriors as they rally against Skeletor's forces. After discovering his parents are still alive, Adam leads a rescue mission to Snake Mountain, where King Randor is killed and Skeletor attempts to unlock the Sword of Power's magic through Castle Grayskull. In the final battle, Adam learns that the power of Grayskull was never truly in the sword, but within himself. He reclaims his destiny, defeats Skeletor, and helps restore Eternia. Six months later, Queen Marlena rules Eternos, Adam is celebrated as a hero, and he finally chooses his legendary name: He-Man. Rating Out of 10, Shinny Dangling… Participles (Clean up your dirty minds) Brian: 8.3/10 Darryl: 8.45/10 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!

A dreadful Citadel looms hazily in the north, beyond the snow-capped peaks of the Expanse. Rumors speak of a dire threat to the Seers. The Mirror, Dove, Iron, and Bloody Knights trek into the Cairngorms in search of dire Omens.Mythic Bastionland is a complete roleplaying game about Knights on Quests, seeking Glory, and holding to their Oath.Seek the Myths, Honor the Seers, Protect the Realm. The game was designed and written by Chris McDowall, with art by Alec Sorensen, published by Bastionland Press. - Purchase the game ⁠⁠here⁠⁠.- Support Chris's work by subscribing to his ⁠⁠Patreon⁠⁠!- Art and graphics from the official book in our videos and promotional material is used with the author's express permission.The hex map of the Adamant Expanse was created using Hex Kit, developed by Cone of Negative Energy.- Purchase it ⁠⁠here⁠⁠.Explore more 3d6 Down the Line at our ⁠⁠official website⁠⁠! Access character sheets, maps, past campaigns, and lots more! Watch our ugly mugs on the ⁠⁠YouTube⁠⁠ version of this episode!Support our ⁠⁠Patreon⁠⁠, and enjoy awesome benefits! Purchase Feats of Exploration, an alternate XP system for old-school D&D-adjacent games! ⁠⁠Drivethru RPG⁠⁠ ⁠⁠Itch⁠⁠ Grab some ⁠⁠3d6 DTL merchandise⁠⁠!Join our friendly and lively ⁠⁠Discord server⁠⁠! Art, animation, and graphics by David Kenyon.⁠⁠Portfolio⁠⁠⁠⁠Bluesky⁠⁠⁠⁠Instagram⁠⁠Maps used in the channel banner by Dyson Logos.Intro music by Muzaproduction and kaazoom.

This week, Da7e and Neil return after their brief hiatus with a newly cleaned Citadel of Crazytown to begin their next era of Westerosi podcasting as they prepare for the return of House of the Dragon. Up first, a Re-Thrones of season 1.They begin with a look back at the highlights of HotD's first season, from the big book changes to the time jumps to what they would change if they could go back in time.Then they hand out superlative Georgie Awards for including the Best Gift to the God of Death, season MVPs, The Catelyn Stark Memorial Ironic Statement Award, and much more.Next week, the Re-Thrones journey continues as your faithful hosts dig into season 2 of House of the Dragon, including a look ahead to what they expect from the upcoming third season, which debuts on HBO on June 21st.To interact with the show, send your comments and questions to stormofspoilers@gmail.com, and follow us on Twitter/X and Bluesky @Da7eandNeil.You can also support Da7e and Neil and get all kinds of bonus content (from the Game of Thrones era to the LOST rewatch to our Twin Peaks rewatch project to our current Adventure Pod and Dark watch project) by subscribing to our Patreon here: patreon.com/Da7eandNeil

After puzzling over an interesting follow-up question about Pitchford v. Cain, we unpack a summary vacatur in Whitton v. Dixon. We then spend a while breaking down the latest developments in Allen v. Milligan line, in which we discuss the future of the Purcell principle and whether the Court should be unusually attentive to public appearances in election cases. We finish with Sripetch v. Jarkesy, where the Court rejects a requirement that the SEC prove victims suffered pecuniary loss before seeking disgorgement, with specific attention to the interesting Seventh Amendment question raised in Justice Thomas's concurrence.Key Topics[00:03:23] - Listener question on Pitchford v. Cain, AEDPA, and procedural default[00:08:12] - Whitten v. Dixon: summary vacatur in a capital case and harmless-error review[00:12:44] - Justice Thomas's dissent and the critique of selective error correction[00:22:46] - Allen v. Milligan / Alabama redistricting and the stay of the lower court injunction[00:27:24] - The Court's restatement of Milligan and discussion of “colorblind constitution” language[00:32:30] - Purcell, election timing, and whether the doctrine is really about federal court intervention[00:41:20] - Merits and legitimacy concerns in election-law cases[00:53:27] - SEC v. Sripetch and the disgorgement remedy[00:58:42] - Justice Thomas's concurrence on disgorgement, equity, and the Seventh Amendment[01:03:36] - Broader implications for administrative law and jury-trial rights

The Chicago Bears are officially heading to Hammond, Indiana after the Illinois legislative session ended with no stadium deal, leaving the Bears with nowhere to go in Chicago. Ryan breaks down why this outcome actually makes financial sense for Hammond — and why it's a slow-motion disaster for a Chicago already hemorrhaging businesses, residents, and cultural institutions. Ryan zeroes in on the cope: Bears fans who've spent decades weaponizing Chicago's size against Packer fans have now been stripped of their most powerful argument. While he acknowledges the genuine tragedy for honest Bears fans who kept it about football, he's got nothing but mockery for the "Chicagoland" spin doctors trying to pretend this move is anything but what it is. Plus: a data-heavy look at the corporate exodus from Illinois — Boeing, Caterpillar, Citadel, Morton Salt — and why the Bears leaving is a symptom of a compounding crisis Chicago can't cope its way out of.

The Chicago Bears are officially heading to Hammond, Indiana after the Illinois legislative session ended with no stadium deal, leaving the Bears with nowhere to go in Chicago. Ryan breaks down why this outcome actually makes financial sense for Hammond — and why it's a slow-motion disaster for a Chicago already hemorrhaging businesses, residents, and cultural institutions. Ryan zeroes in on the cope: Bears fans who've spent decades weaponizing Chicago's size against Packer fans have now been stripped of their most powerful argument. While he acknowledges the genuine tragedy for honest Bears fans who kept it about football, he's got nothing but mockery for the "Chicagoland" spin doctors trying to pretend this move is anything but what it is. Plus: a data-heavy look at the corporate exodus from Illinois — Boeing, Caterpillar, Citadel, Morton Salt — and why the Bears leaving is a symptom of a compounding crisis Chicago can't cope its way out of.

Angel Ubide, Head of Economic Research for Global Fixed Income and Macro at Citadel, discusses the case for common EU debt, Europe's push for strategic autonomy, and the reforms needed to boost growth. He speaks with Bloomberg's Stephen Carroll about the future of eurobonds, pension reform, banking integration and the challenges facing the European economy.See omnystudio.com/listener for privacy information.

The greatest risk we face today isn’t that AI is becoming “too smart”; it’s that we are beginning to treat this technology as an infallible “oracle” rather than a capable, yet fundamentally fallible, “intern.” As the baseline for production drops to zero, the economy of human value is shifting away from raw output and toward the only two things a machine cannot authentically replicate: judgment and intent. How should we use AI to augment and enhance our professional output, instead of simply automating  and potentially replacing our value? How can we navigate the “Calculator Trap” to ensure our foundational critical thinking doesn’t atrophy?   Join us for a conversation with Ted Yang, an MIT-trained engineer and seasoned entrepreneur who has founded more than twelve companies. A former finance executive at legendary firms like Bridgewater and Citadel, Ted is an Emmy-nominated author and a member of Connecticut’s Board of Regents for Higher Education. His new book, Ageless Peak Performance, provides a practical playbook for professionals looking to thoughtfully adopt AI to expand human capability and opportunity. Hosted by: Alexa Raad and Leslie Daigle. Further reading: AI won’t make the call: Why human judgment still drives innovation, Harvard Business Review Harvard Business Review: “The Irreplaceable Value of Human Decision-Making in the Age of AI” Forbes: “Leadership-Driven Growth In The Age Of AI Acceleration” iGrafx: “Don’t Automate Chaos: Why Fixing Broken Processes Comes Before Adding AI” Stanford HAI: “Is Generative AI Killing Critical Thinking?” Ageless Peak Performance: The Playbook for AI-Powered Excellence” The views and opinions expressed in this program are our own and may not reflect the views or positions of our employers.

We catch up with former Hawkeyes Landan and Levi Paulsen in Kalona, Iowa, joking about local businesses, Amish country, and sponsorship dreams (including Kalona Supernatural Dairy). The conversation turns to post-football health, major weight loss, and a rundown of numerous surgeries—highlighted by Levi's gruesome big-toe capsule tear story. Landan shares how jiu-jitsu (training at Citadel in Iowa City) became his new competitive outlet and Kevin joins to add his own Citadel injury story, while Levi explains his shift into endurance sports and training for a three-day gravel/swim/run event. They discuss fueling, the psychology of pursuing hard challenges after Iowa football, anxiety around fall camp, fatherhood updates, and how Landan and Levi helped grow an F3 men's fitness/community group built on Fitness, Fellowship, and Faith. If you love the show and want to show support, tell your friends! And, check out our exclusive content at Patreon.com/washedupwalkons where you can find extra podcast episodes, exclusive merchandise, Merch discounts with every tier, private Walkon discord channel access, and more! Find us on social media @washedupwalkons Visit TheWashedUpWalkons.com for all of our episodes, merchandise, and more! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Anakin, Obi-Wan, and Ahsoka lead their teams to the Jedi rendezvous point with the warden of the Citadel in pursuit in the finale of the "Citadel" story arc in this discussion of The Clone Wars.   In this fully armed and operational episode of Podcast Stardust, we discuss: Our overall thoughts on this episode, The prison warden, Osi Sobeck, and James Arnold Taylor's performance, The last stand of the reprogrammed battle droids, Saesee Tinn's statement about how they haven't seen a battle like this since the Old Republic, The Anoobas, Tarkin's thoughts on the Jedi and his status with the Chancellor, Anakin's opinion of the Jedi and their roles in the war, Jedi Master Even Piell's fate, and What the conclusion means for Star Wars. For more discussion of The Clone Wars, check out episode 1039.   Thanks for joining us for another episode! Subscribe to Podcast Stardust for all your Star Wars news, reviews, and discussion wherever you get your podcasts. And please leave us a five star review on Apple Podcasts.   Find Jay and her cosplay adventures on J.Snips Cosplay on Instagram. Follow us on social media: Twitter | Facebook | Instagram | Pinterest | YouTube. T-shirts, hoodies, stickers, masks, and posters are available on TeePublic. Find all episodes on RetroZap.com.

Anakin, Obi-Wan, and Ahsoka lead their teams to the Jedi rendezvous point with the warden of the Citadel in pursuit in the finale of the “Citadel” story arc in this discussion of The Clone Wars.

Can you truly protect your assets if a third party controls your data? The Global Circular Bitcoin Economy Summit in El Zonte just wrapped up, and the focus on the ground was centered entirely on the raw, unyielding mechanics of financial survival and digital sovereignty rather than price action or trading charts. This week, we are cutting straight through the fiat marketing noise to talk to the world-class builders who are physically constructing parallel, decentralized, un-surveillable systems right now.First, we sit down with Renata Rodrigues (@renatarodr) from Fedi to unpack why digital privacy is a complete necessity in an era of tightening global surveillance. Renata breaks down how the Fedi wallet and the open-source Fedimint protocol are giving localized communities the tools to completely break free from centralized platforms like Telegram or WhatsApp. We look directly into how combining encrypted chat with shared financial custody allows any group to establish its own autonomous federation. This gives sovereign individuals total control over what data they choose to reveal to the outside world, and we track exactly how these systems are scaling globally, from the closed-loop nodes defying bans in Indonesia to the intense intellectual proof of work required by communities in South Korea.Then, Daniel (@wph_merida) from Bitcoin Merida joins us to map out why true local adoption has to integrate with local geography, native culture, and the ultimate goal of absolute, off-grid self-sufficiency. Daniel pulls back the curtain on the massive legal and structural undertaking behind the INAH Citadel, which is a 230-acre intentional community built deep in the Mexican jungle of Yucatan, alongside their local urban hub, the White Paper House. We break down exactly how their team established a secure Fideicomiso trust structure to handle real estate transactions, how they are leveraging local tourism to empower nearby Mayan agricultural schools, and the wild story behind a massive private cenote that secures total water independence for the citadel.We cover a massive amount of ground in these conversations, including the deployment of private community wallets, zero-custody financial tools, the twelve-book entry requirement for Bitcoin South Korea, the legal architecture for buying property in Mexico, and integrating solar grids for alternative energy independence.If you are ready to stop waiting for permission, achieve true self-sufficiency, and learn how to build a resilient Bitcoin circular economy that can withstand state overreach, make sure to subscribe, leave a comment, and share this episode because your support helps us bring more of these underground stories to light. Just remember, if anyone asks who gave you permission to opt out of the legacy system, tell them the President of Bitcoin approved it.—Bitcoin Beach TeamLearn more about the guests:X (Renata Rodrigues): https://x.com/lobaestrangeiraX (Daniel): https://x.com/inahcitadelX (White Paper House): https://x.com/whitepaper_HX (FEDI): https://x.com/fedibtcSupport and follow Bitcoin Beach:X: https://www.twitter.com/BitcoinBeach IG: https://www.instagram.com/bitcoinbeach_sv TikTok: https://www.tiktok.com/@livefrombitcoinbeachWeb: https://www.bitcoinbeach.com Browse through this quick guide to learn more about the episode:00:00 Intro00:53 Fedi wallet vs Telegram for decentralized community coordination03:01 How Fedimint protocol protects local transaction privacy07:31 Bypassing crypto bans with closed loop Bitcoin networks09:07 Proof of work requirements for sovereign Bitcoin onboarding15:09 Hyperbitcoinization strategies and local adoption in Mexico18:00 How to build an off-grid Bitcoin citadel infrastructure23:04 Real-world hyperbitcoinization and business node integration25:42 Buying Mexican real estate via Bitcoin Fideicomiso trust31:02 Securing off-grid water sovereignty and energy independenceLive From Bitcoin Beach

Joel, and Stephen share their experience going along for the ride with Project Hail Mary, as well as Joel's final thoughts on season one of Star Wars: Maul, Shadow Lord. Plus, a large new Lord Of The Rings LEGO set, and new trailer from LEIKA.Show notes for The Citadel Cafe are here:https://thecitadelcafe.com/2026/05/29/the-citadel-cafe-505-project-hail-mary/Join The Citadel Cafe Discord community!http://Patreon.com/TheCitadelCafeThe Citadel Cafe YouTube:https://youtube.com/thecitadelcafeMusic for The Citadel Cafe by Kevin MacLeod (incompetech.com) licensed under Creative Commons by Attribution 4.0 Hosted on Acast. See acast.com/privacy for more information.

Citadel and SIFMA lobbied to slow tokenized equity rules. Arjun Sethi calls it 'corporate plumbing.' Chris Perkins calls it a bond future moment. --- Thank you to our sponsor! ⁠⁠Coinbase One⁠⁠: Get 20% off the first year of your Coinbase One annual plan at ⁠⁠coinbase.com/unchained⁠⁠. Heads up! If you haven't yet, be sure to subscribe to Bits + Bips, since the show will migrate there in a few weeks. Follow us on ⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠Unchained⁠⁠⁠⁠⁠⁠⁠ and wherever you get your podcasts. ---- Kraken has spent $2.75 billion on acquisitions in the past year, and co-CEO Arjun Sethi says the point is not a bigger exchange. The goal is a 24/7 global operating system for capital markets: spot, derivatives, payments, tokenized equities, and custody under one regulatory stack. Sethi makes the case for each move, from REAP's tripling revenue in emerging markets to Bitnomial's CFTC trifecta, and says what will actually drive Kraken's next three years is not trading volume. The conversation then turns to the SEC's paused innovation exemption for tokenized equities, why Citadel and SIFMA showed up to lobby against it, and whether direct listings on crypto rails could eventually replace Wall Street's IPO machine. The episode closes on a question nobody saw coming: what Pope Leo's first encyclical on AI and finance has to do with the Bitcoin white paper. Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Austin Campbell (@austincampbell) — Founder, Zero Knowledge Consulting; Adjunct Professor, NYU Stern ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ram Ahluwalia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Co-Host, CEO of Lumida ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Chris Perkins⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Co-Host, CEO of 250 Digital Asset Management Guest: Arjun Sethi - Co-CEO of Kraken / Payward and Chairman of Tribe Capital Learn more about your ad choices. Visit megaphone.fm/adchoices

Anakin and Obi-Wan continue to lead the Jedi and Clone rescue mission at the Citadel with Jedi Master Even Piell and Captain Tarkin in part two of "The Citadel" trilogy.   In this fully armed and operational episode of Podcast Stardust, we discuss: Our overall thoughts on this episode of The Clone Wars, What it says about Ahsoka that she disobeyed Anakin's orders and lied about it, Tarkin's observation that the Jedi's Code prevents them from doing what needs to be done, and Anakin's agreement, James Arnold Taylor having three roles in this episode, The reprogrammed Battle Droids, and The apparent death of Echo. For more discussion of The Clone Wars, check out episode 1035.   Thanks for joining us for another episode! Subscribe to Podcast Stardust for all your Star Wars news, reviews, and discussion wherever you get your podcasts. And please leave us a five star review on Apple Podcasts.   Find Jay and her cosplay adventures on J.Snips Cosplay on Instagram. Follow us on social media: Twitter | Facebook | Instagram | Pinterest | YouTube. T-shirts, hoodies, stickers, masks, and posters are available on TeePublic. Find all episodes on RetroZap.com.

FPS Through the Ages draws to an explosive close! Join the HG101 gang as they discuss and rank a 2020s first-person shooter that blends classic and modern FPS elements into a gory cybernetic thrill ride. Then stick around as returning special guest Sean Seanson joins for Magical Date: Doki Doki Kokuhaku Daisakusen, an arcade game about wooing girls based on your ability to do basic math! This weekend's Patreon Bonus Get episode will be RIPPLE DOT ZERO — a Flash-based penguin platformer, inspired by the 16-bit era! Donate at Patreon to get this bonus content and much, much more! Follow the show on Bluesky to get the latest and straightest dope. Check out what games we've already ranked on the Big Damn List, then nominate a game of your own via five-star review on Apple Podcasts! Take a screenshot and show it to us on our Discord server! Intro music by NORM. 2026 © Hardcore Gaming 101, all rights reserved. No portion of this or any other Hardcore Gaming 101 ("HG101") content/data shall be included, referenced, or otherwise used in any model, resource, or collection of data.

Tax the rich? More like tax the jobs away. Billionaire hedge fund titan Ken Griffin is scaling back in New York City and pouring jobs into Miami as a DIRECT response to socialist NYC Mayor Zohran Mamdani's “tax the rich” antics. This could be the beginning of the wealthy exodus Democrats fear most. In a stunning move, Griffin cited Mamdani's creepy viral video — filmed outside his $238 million penthouse — as the final straw. Instead of expanding Citadel's massive Park Avenue project in NYC, the firm is supersizing its Miami headquarters. Other Wall Street giants like Apollo are eyeing moves to Florida or Texas too. New Yorkers are about to feel the pain of lost jobs, shrinking tax revenue, and a dying financial capital. We also cover: David Hasselhoff gets a NEW hip & knee. President Obama on aliens & message to Republicans. Property taxes are UNCONSTITUTIONAL!  Delta to cut snacks & drinks on short flights. CNN founder Ted Turner dies at 87. This story exposes the dangerous reality of socialist policies: Attack job creators and they leave, taking opportunities with them. Griffin and his team have already paid billions in taxes while supporting major charities — yet radical Democrats treat them like enemies.

Dave Rubin of "The Rubin Report" gives a first look to the stories you need to know to start your day including how billionaire Ken Griffin's warning about Zohran Mamdani's leadership and Citadel's expansion in Miami signals a major shift in where wealth and jobs are heading; why the clock is ticking on potential charges against Dr. Anthony Fauci as pressure builds ahead of a critical legal deadline; and a Texas jury's verdict in the tragic Athena Strand case and what it reveals about justice and accountability, and much more.

1. Republican Tax Cuts Framed as Major Economic Wins Recent tax legislation by Donald Trump and Republican lawmakers, have significantly reduced tax burdens. Highlighted provisions include: No tax on tips, overtime, car loans, and Social Security income Creation of “Trump accounts” for children There are immediate, tangible benefits to working‑class Americans, seniors, and service workers. Democrats would have planned massive tax increases had they remained in power. 2. Delayed Impact of Tax Policy Tax cuts often feel delayed because benefits are most visible when people file returns. April tax refunds are used as proof that these policies are now producing results. 3. Democratic Party Characterized as Extremist The Democratic Party is described as: Pro‑open borders Hostile to law enforcement Driven by socialist or Marxist ideology The party no longer represents working Americans but instead prioritizes illegal immigrants and radical causes. 4. Tom Steyer and ICE Controversy Tom Steyer (billionaire Democrat) is criticized for stating that, as California governor, he would arrest or prosecute ICE agents. This would violate federal law Governors lack authority to prosecute federal officers Steyer could himself face federal criminal charges Historical comparisons are drawn to segregation‑era resistance to federal enforcement. 5. Law Enforcement and Federal Supremacy The podcast outlines specific U.S. criminal statutes to argue that: Interfering with federal officers is illegal State officials would lose immunity The federal government could intervene, even militarily, if necessary A recent case involving a judge convicted for aiding an undocumented immigrant is cited as precedent. 6. New York Wealth Taxes and Mamdani New York mayoral figure Mamdani is criticized for proposing a luxury property tax on second homes over $5 million. The proposal is: Punitive toward success Vindictive toward wealthy individuals (especially conservatives) Likely to accelerate business and resident flight from New York Ken Griffin and Citadel are used as examples of potential job losses if firms leave the city. 7. Wealth Redistribution as Ideological Motivation Democratic leaders: Promote redistribution over economic growth Downplay or dismiss business flight Mamdani’s comments about global inequality is a support for international wealth redistribution. Please Hit Subscribe to this podcast Right Now. Also Please Subscribe to the 47 Morning Update with Ben Ferguson and The Ben Ferguson Show Podcast Wherever You get You're Podcasts. And don't forget to follow the show on Social Media so you never miss a moment! Thanks for Listening YouTube: https://www.youtube.com/@VerdictwithTedCruz/ Facebook: https://www.facebook.com/verdictwithtedcruz X: https://x.com/tedcruz X: https://x.com/benfergusonshowYouTube: https://www.youtube.com/@VerdictwithTedCruzSee omnystudio.com/listener for privacy information.