Podcasts about Vint Cerf

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

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

From the sudden retirement of Internet pioneer Vint Cerf to the unstoppable advance of "apex agentic adversaries," get a front-row seat to the unfolding security revolution and its massive real-world stakes. Why Fable5's re-release has disappointed. Opera becomes the first browser to offer "Paste Protect." Microsoft BlueHammer exploit is "hammering" systems. Industry legend (TCP creator) Vint Cerf on AI. Chrome turns 150 with too many fixes to load. Google fails to sidestep a $4.67 billion EU fine. One last (we can hope) Chat Control vote next week. AirDrop & Android Quick Share are exploitable. How to bypass Claude's and ChatGPT's guardrails. My own Sunday spin with SpinRite. A legendary hacker uses AI on a widespread library Show Notes - https://www.grc.com/sn/SN-1086-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT cohesity.com/Resilience bitwarden.com/twit zscaler.com/security XBOW.com adaptivesecurity.com

What happens when intelligence is no longer exclusively human? In DisrupTV Episode 439, Vala Afshar and R "Ray" Wang are joined by internet pioneer Vint Cerf, Dr. David Bray, and decision scientist Cheryl Strauss Einhorn for a far-reaching conversation on agentic AI, governance, misinformation, autonomous systems, and the future of human judgment. Together, they explore: Why agentic AI changes the rules of accountability and governance The rise of digital labor and human + agent collaboration How synthetic media and misinformation are reshaping enterprise risk Why critical thinking may become the most important skill of the AI era The role of human judgment, values, and decision-making in a world increasingly shaped by intelligent systems How organizations must redesign, reskill, redeploy, and restructure for the future of work From autonomous vehicles and synthetic data to cognitive fitness and decision science, this episode explores what it truly means to lead in an era where AI can act, reason, and scale alongside humans. The conclusion: AI may accelerate intelligence, but human judgment remains the ultimate competitive edge.

“What I’m really interested in and fascinated about is that, as AI penetrates and spreads throughout the workplace and gets placed into or integrated into workflows, the first thing that happens is that people in the mix are going to have to learn how to use AI and learn why to use AI when they do.” –Jon Husband About Jon Husband Jon Husband is the Founder and Principal of Wirearchy, a creative research and experimentation laboratory exploring the crossroads of AI and networked workplaces and society. He works as a coach, consultant, speaker and writer, and has co-authored three books, including Wirearchy. Website: wirearchy.com LinkedIn Profile: Jon Husband What you will learn The origins and evolution of wirearchy as a response to traditional organizational hierarchies How AI integration is reshaping knowledge work, workflows, and tacit knowledge within organizations The persistence of Taylorist job evaluation and why traditional work design remains resistant to change The rise of the relational economy and the increasing value of human judgment, trust, and relationships beyond financial exchange New approaches and tools for surfacing and mapping intangible or non-financial value exchanges in organizations The concept of emergence and the need to foster conditions for positive outcomes in complex adaptive systems Challenges and opportunities as organizations shift from rigid, control-based management to adaptive, networked, feedback-driven models Why coaching, facilitation, and skills like listening and allowing for emergence will be critical in navigating AI-augmented workplaces Episode Resources Transcript Ross Dawson: Jon, it is wonderful to have you on the show. Jon: Thank you very much, Ross, it’s good to see you again. Ross Dawson: We’ve known of each other and each other’s work for a very, very long time now from, I suppose, the roots of—yeah, I suppose you can crudely say—the intersection of knowledge and networks. So, as I think many of us who have come from that background, we now are thinking about humans and their relative role to AI. Some people will know of your wirearchy and a lot of your work of the past; others will not. So I’d love to just start off with: what is the concept of wirearchy? And then, how is that morphing or evolving, or are you building on that in how you’re thinking now? We’ll dig in and explore that. Jon: Okay, well, I started paying attention to knowledge work and work in organizations and so on as I changed careers in my early 30s, moving from banking, where I was in management, into management consulting. I ended up working for a large global HR consulting firm that, amongst several others—all the major consulting firms that address organizational issues—have services where they do what’s called job evaluation. What job evaluation does is put a size or a measure or a weight to a job, which then basically places it on the organization chart. I spent quite a few years writing thousands of job descriptions and helping streamline workflows and so on and so forth. So, when the internet came along, I had always been an avid reader, and I suppose a wannabe futurist—a wannabe Ross Dawson, if you will. I was reading all sorts of books back then. Instead of dating, because I was single in my mid-30s, I was spending Friday nights reading books about organizations, like “The Living Company” by Arie de Geus, the Tofflers’ work, “Powershift,” certainly Peter Drucker’s work. There was one day—well, I was reading all of these books, and all of the books were about the coming Information Age. The Information Age had not arrived yet; this was roughly late ’80s, early ’90s. All of a sudden, we hit 1994. I’m sitting in London, and I was just told by my team leader in my consulting firm that I was going to be proposed as one of the next global partners. Three weeks later, I quit my job in the consulting firm because I had begun to feel very uneasy about the work I was doing. If I was made a partner, your job becomes basically selling larger projects to keep the younger consultants employed. I realized that I would be selling methods that I had come to not believe in anymore, and the reason for that is that all of the job evaluation methods sold by all the major consulting companies are all versions of generic Taylorism. They have semantic statements that you pick to figure out a level of a job on a number of different factors. This is one of the things I’ve talked and written quite a bit about in wirearchy: this generic Taylorism is still deeply at the core of most of the work of most organizations. It’s how the work is designed. There has been now, what, 15 or 20 years—how far back does Enterprise 2.0 go?—about collaboration and cooperation and better knowledge management and sharing and transfer of knowledge, and so on and so forth. If you know these semantic statements, which are burned into my brain from this method—the Hay method—you realize that no amount of talking about doing things differently is going to make much difference. It’s not going to change much. And the remuneration—the way people get paid—every single person in every single company, is tied to all of that. It’s tied to your job size, it’s tied to the compensation practice, it’s tied to your performance management, it’s tied to your career plans, if an organization is still doing career planning. Frankly, it has not been touched in 75 years now. Ross Dawson: Used to describe it as a job as a box. Jon: Well, sure, and that’s where that term “think outside the box” comes from. I wrote an article about this at one point in time—oh, I can’t remember the title, so it doesn’t matter—but about the semantic statements essentially becoming semantic straightjackets, because they put limits around what you do. They’re a graded level of permissions, basically, or amounts of influence and authority, and that’s the codified, official organizational chart. So anyway, I was working with this all the time, and I realized if I was going to be made a big-time partner, I’d have to be selling these tools all the time. The internet had come along, so I quit, and I didn’t know what to do after that. I had to move from the UK because I was on a work permit, had to go back to Canada. When I went back to Canada, all the companies I tried to approach to work as an independent consultant didn’t want to engage me, because all of the work I’d been doing in the UK was with really large multinationals, and according to them, too sophisticated for what they were doing in Vancouver. But at the same time, I was still reading all the time—reading Charles Handy’s work, reading Gerard Fairtlough’s work on heterarchy, and so on. I came to believe very strongly that the ongoing sharing of information—which we were starting even 20 years ago to build into constant, incessant flows of information carried via hyperlinks—was going to inevitably begin to affect, I’m going to use the word affect, the traditional top-down power of hierarchy. That comes from the “knowledge is power” by Francis Bacon kind of perspective. Now, that was 25 years ago. What we’ve seen since is, of course, what you know—one umbrella term I could apply to much of what’s going on outside of organizations is the “enshittification” of the web. The same thing applies in a lot of ways, I think, to people doing work, sitting behind screens in organizations. Now, a whole host of things have happened in the past 10 or 15 years: there were armies of developers sitting in office spaces, all of them with their headphones on behind screens coding. There were all sorts of people beginning to understand how to use the internet. There were many failed attempts at effective knowledge management because of the idea that it’s still just good search, find documents, retrieval, without really paying any attention to the connections between people and how they work together, and so on. Ross Dawson: So, the frame there is, I mean, obviously, moving—the wirearchy being an arche of the organization being essentially a network. Obviously, there’s more richness to that as you describe the organization as a network, as opposed to the rigid structures, which are still very much rampant. But fast-forwarding to today, what we’ve overlaid is, whilst the old rigid structure is in place, organizations are effectively a lot more loosened up by Enterprise 2.0 and other types of frames, and essentially more peer communication. Now AI is changing a fundamental role, now being, in many ways, a participant in those workflows, in the creation of value. So where does that take us today, in this humans-plus—essentially wirearchy—pulled into where AI plays a role within those networks? Jon: Well, it’s a fascinating question for which I don’t have an answer. I have some responses, I suppose. The notion of wirearchy came, as you pointed out, out of everybody being wired, everybody being networked—the organization as a network. What I’m really interested in and fascinated about is that, as AI penetrates and spreads throughout the workplace and gets placed into or integrated into workflows, the first thing that happens is that people in the mix are going to have to learn how to use AI and learn why to use AI when they do. Often, it’s very soft at the beginning because it’s reminders, or “did you want to do that,” or “do you want to say that,” and so on. Increasingly, the AI, I think, will have more and more coaching built into it. But what I’m interested in is how, as we learn from the mistakes that are made in integration, and also learn from the successes that are made from integration, is that going to decompose a knowledge worker’s work and eventually capture most of their tacit knowledge and ways of working to reduce the cost of doing that kind of work? Then, on a larger scale, what is the active decomposition of types of work through the influence and integration of AI? How is that going to change the fundamental assumptions about work design? My belief is that the work of Dave Snowden and others with respect to complex adaptive systems is what is going to become—and this is a poorly connected parallel or analogy—but I think something like the Cynefin framework, or a unified approach to complex adaptive systems, will become the Taylorism of the 21st century. In other words, there will come to be forms of patterns and models and actions that help you address certain kinds of conditions, because I think, especially with AI, work and outputs are going to become continuous flows. They are the push and the pull, or the dynamic flow of power and authority that is alluded to in the working definition of wirearchy, the working definition of wirearchy includes knowledge, trust, credibility, and a focus on results, each of which you could write a book about. But as general headings, they are what capture what’s in play, I believe. Ross Dawson: Yeah, no, I think absolutely still relevant today. Now, the point I was going to make was around, in complex adaptive systems, a really central concept is emergence— Jon: Yes. Ross Dawson: —where you are not planning or overlaying or dictating a structure; the structure and the value and how that’s created emerges. And to your point, a lot of the key aspect in that world is, how do you create the conditions for emergence of positive outcomes, as opposed to less positive outcomes? And that’s still, of course, arguably at least as much an art as a science, particularly when you’re looking at complex adaptive systems composed of not just many humans, but also AI, which are stochastic in nature. Jon: Yes, well, it’s a very, very good point. I think it relates to the paper I shared with you a couple of days ago about what the author is calling “weaving the web.” There is an enormous amount of human input and activity, combined with the AI, that doesn’t get measured and is not seen in our currently technocratic, generic Taylorist worldview. That’s not seen, not captured, and it arguably is the kind of human input, work, and knowledge that is going to make this whole new era operate fairly well. That’s this notion of exchanges of value. Once that code is cracked, in terms of how to understand it, surface it, see it, measure it, this is going to lead to more and more of what Nvidia’s Jensen Huang is doing with respect to tokenization. There are some people who say tokenization will become the replacement for money in some cases, or even many cases in another, let’s say, 10 years or so. It’s kind of hard to imagine, but if you come back to the paper that you and I first connected on—Alex Imas’s review of the structural changes to the economy—if you can see the logic of his argument, he says there’s going to be a lot more work, but it’s going to be relational economy work, which ties directly into value exchange and surfacing how that exchange of value operates, say, between two people at work, or a group and a person, or two groups, and so on. This notion of value exchange is going to ground a lot of the conceptual and abstract issues that we talk about when we talk about, you know, why is making effective collaboration so hard? Why is it hard to de-silo an organization? All of those kinds of things are going to, I believe, eventually be washed away in this continuous flow of information. So we have to look for new concepts and new ways to measure what’s being created, the value that’s being created. Ross Dawson: Well, that’s—I mean, this is really interesting. As long as you do not recall, in “Living Networks,” I was actually laying out a quite similar thesis around value creation and network structures, and I did quite a bit of work with Verna Allee on value networks. We ran some workshops together, and we’re essentially—a lot as laid out in the paper you described, and as you’re saying now—a lot of it is saying, how do you look at the non-financial or intangible exchanges of value, which sometimes are apparent and sometimes less apparent? There are all sorts of these structures where, as you say, there is an exchange of value. Sometimes it involves money, oftentimes it doesn’t. To understand the landscape, you do need to understand all of these non-financial structures. But are you suggesting that in this tokenization or other structures, there is a way then of being able to, I suppose, capture some of these non-financial values, which does imply there needs to be some kind of measurement, or at least a mutual agreement or assessment on what that value is? Jon: Yes, the paper that I sent you, and the tool that I’m interested in and think is important, is called VEMapper—Value Exchange Mapper—which has some sophisticated capabilities with respect to AI, mainly by calling the main AI engines into the conversation. There’s a process set out whereby, in a dialogue that’s captured both by recording and by typing, there’s a record of a conversation or a dialogue about value exchange. I’ve carried out a few of them. I recommend trying it, because it’s quite remarkable. You really just tell your story, but it surfaces the tacit knowledge often that you’ve put to work in the creation and exchange of the value. The tool is also quite sophisticated today in terms of its databases and other components. Please forgive me, I’m not a technologist, but it creates a data commons. You, as a participant in a value exchange using this tool, your data, your output, is yours and yours alone. You own it. There’s a notion of data ownership and privacy, and as you carry out more and more of this value exchange, the way it’s captured—and again, I don’t really know about this, but I do know about the structure of the semantic web—it captures triplets: subject, predicate, object, which then makes them readable, makes them discoverable in knowledge graphs and other ways. The tool also has a 3D knowledge graph. If you read that paper, it’s really following the logic, the reasoning, and the innovations that were introduced by Vint Cerf long ago in terms of how knowledge would work, whether there would be things like knowbots, which are agents, and so on. So it stores all of this, and then there’s a process whereby you enter into a dialogue. The AI coach helps you clarify, elaborate, and so on, and then you revisit this process. What this does is it builds and scaffolds trust between people and between groups or whomever is working on a problem. Ross Dawson: Back to a broader frame here. So, what you’re describing—this tool or other tools—has been able to, as you state, capture or make visible value exchange in various guises, with the potential to shift to where we are looking and understanding far beyond the exchanges of financial or overt products and services, and so on. But we’re also relating it to Alex Imas’s thesis that we are moving into a relational economy, where the value—what is scarce—is not AI churning away on reasoning; what is scarce is human relation and judgment. In a whole variety of exchange contexts, including in simple conversations or other knowledge exchange, they’ll be able to apply human expertise to people in situations and organizations. So perhaps, if we just marry those two, what do you see might happen if we move into both a relational economy with the potential to surface more of the nature of how value is exchanged? Jon: Wow, that’s quite a question. I think it’s one of those things where there’s likely to be a very large and durable polarity emerge. I think that the polarity is that there will be some people—probably younger, I’m guessing under 45-ish—that will take to the new environment like ducks to water. They’re already living it in many ways. Their work is much more precarious. They operate in networks that are often networks of support and help, and so on. I think the other end of the polarity is that there will be lots of people who are—I sent you another piece about a week ago called “Artificial Intelligence and Sleeping Humans,” which was about the fact that many of us are, whether we like it or not, not all that much awake when we’re walking around every day, particularly after we’ve been working for 10 or 15 or 20 years, and, you know, kids, busy life, and so on. As AI moves through the workplace, different industries, different natures of work, and brings up issues of relation and so on, I think that relational work will always be AI-aided and supported. I think there’s a significant possibility of something emerging that currently I’m calling AI psychosis. I think that it will disturb a lot of people. They’ll try to build habits or create habits, and they’ll be trained for this with organizations with respect to using AI, but I think it will feel very foreign to them. I think there’s been something—you probably have talked about this before somewhere; I seem to remember reading something from you—but there’s been about 25, 30, 40 years of what I’d call atomization and augmentation in the social fabric. I don’t think that the introduction of AI on a widespread basis throughout work and everything is going to help with that atomization very much. So I think that the longer-term, emergent impacts of AI—I don’t think they’re going to be about productivity and efficiency. They’re going to be up a level or two in terms of the discombobulation and ongoing anxiety that are created. That makes sense? Ross Dawson: Yeah, yes, it does. I think most people can relate to what you’re saying. So, you were just saying before we started the podcast, you’ve, in a way, come back to your work. You’ve been reinvigorated by seeing some interesting shifts in the world. So, what are the next years for you? What do you think we should be thinking about? What should we be focusing on? What should we be creating to enable, as much as possible, all of this to go in a positive direction? Jon: Again, a tough question. It’s so hard because these conditions are all swirling around us. But for me, 10 years—10 years, I’ll be in my early 80s. I don’t like to play golf. I like to swim, so I’ll probably still be swimming. I think we’ll see more and more evidence of the relational economy, with respect to wirearchy and my implication. I’m going, in about a week, to Cambridge to start a creative residency there that involves a number of components. I’ll meet people with the Digital Futures Institute at the University of Bristol, some people at Cambridge. What I’m going to be doing with this creative residency is paying attention to and learning about improvisational facilitation. I think what’s going to happen, what I’m seeing happen everywhere, is shifts in what will be brought to work around the integration of AI. I think the evolution of wirearchy, which implies a different kind of leadership and power, will mean there will just be more and more—how do I want to say it? What I’m noticing is that there’s an enormous amount of talk on LinkedIn and other places where people are wondering about similar things to what we’re talking about. They’re emphasizing the ability to listen, the ability to suspend judgment, the ability to allow the time and the space for emergence—a very, very different mindset than the predict, plan, execute, control, linear types of work. This will be more circular. Many of the elements are already there. We’ve already seen in the last 10 years: develop fast, push versions out fast, fail faster—sort of recursive feedback loops. We’ll all be operating in recursive feedback loops, probably forever more. Ross Dawson: That’s actually very central to my own beliefs. Jon: Yeah, and we just—we have to get used to it. There’s an example I like. It’s not specifically apt for this, but I think you’d probably relate to it. Living in Bondi and in Australia, I presume you’ve gone scuba diving more than once in your life. There’s a kind of dive called a drift dive. Do you know what a drift dive is? Ross Dawson: No. Jon: Okay, I participated in one once, and it was really fascinating. At certain places, there are coral reefs where, I guess because of the topography, the current moves past it quite quickly—more quickly than you can swim against or manage yourself in. So if you go on a drift dive, the dive masters take you out, drop you in somewhere. They know how fast the water is moving, they know how much air you have, they know where you’re going to come up, so they meet you when you come up. But while you’re in the drift dive, what you do is essentially drift along the coral reef, watching the reef vertically because you can’t really swim. I learned about that reading a book a long time ago called “The Horizontal Society” by a Yale Law professor. I can find the title and I’ll email it to you. He described that living in our media-saturated environment—and this was a long time ago—was like living in a drift dive. I think we’re all going to be living in a big drift dive for the next forever—well, certainly for the rest of my life. It’s really interesting to think about things in that way. It relates particularly poignantly to my quitting my job as a management consultant, where I learned all of the method with the generic Taylorism. Because if you go back 20 years ago, the assumption—I know you’ve done a lot of strategic planning with companies and organizations—the assumption was that the next thing, the next time, and we get the strategy right, this thing is going to be stable. This is how it’s going to operate. Ross Dawson: Yes, it’s a common fallacy. Jon: Yeah, exactly. That wasn’t the case 20 years ago, and I started realizing it, and it’s much less the case today than it was 10 years ago. So, you know, I guess it’s like, get used to it. Ross Dawson: Yeah. So where can people go to find out more about your work and what you’re doing, Jon? Jon: At the moment, just LinkedIn. I’m going to put up a new site. I keep—another interesting, fascinating little story. I’ll do it quickly. I was over in England about a month ago, and there’s a guy, a friend of mine, whose claim to fame is, I think he built the first website in the UK in 1994. His name is Felix Velarde, and he’s run a number of agencies and is on the board of directors of a number of digital agencies now, as he’s gotten older. When I visited him a couple days later, I said, “Okay, I want to build a new website. I want to develop a new website, and I have some ideas. But Felix, can you point me to—you know a lot of really talented people—to help me design my next website?” He said—we were on a Zoom like this—he said, “Hang on for a sec.” Started typing into Claude a pretty general statement of, “Give my friend Jon Husband—go scrape his website and blah, blah, blah, and give him an idea of what a good website would look like.” Enter. Wow. Wow, just wow. I started playing with it, and I can do all sorts of interesting things. I can take the wirearchy graphic, I can embed that as a semi-opaque in the back. Anyway, just astonished. I don’t have it up yet, but I will have a new website called wirearchy.com in, I don’t know, about a month or so. I’ll try to put up a couple of my key pieces, but it’s mainly just going to be a landing page. I’ve decided that I don’t have any answers for anything, but I have, you know, 40 years of knowledge about watching organizations morph and change. So I’m going to really just offer half-day and one-day master classes. I respond to all sorts of different situations with different methods, done a lot of facilitation. I think facilitators and coaches are going to be very happy in this new era. Coaching is really interesting. From what I’ve used—Claude, you know, a bit as a personal coach, haven’t tried the others—but I’m really impressed with what they’re going to be able to do, or already can do. Where coaching is going to become critical is at the higher levels, the top of the organization, because all of what we’ve been talking about—sensing, listening, allowing for emergence. The phrase I used to replace “command and control” was “champion and channel”: champion ideas, channel resources. See what happens. Does the node light up? Does the node wither? Does the node connect to other nodes, and so on. This is the world where I think we’re going to be living in, and coaches will be operating at the higher levels to help executives—who have typically been hard-charging and with mindsets they learned 20 or 30 or 40 years ago—helping them adapt, which will be critical. Ross Dawson: Absolutely. There are many people who, for a long time, have been following and applying your insights, Jon, so I’m sure they’ll all be glad to get the update from this podcast and also when your website’s back up. Thank you so much, Jon. Jon: Thank you, Ross. The post Jon Husband on wirearchy, web weaving, the relational economy, and drift diving (AC Ep41) appeared first on Humans + AI.

This week's throwback guest is Cal Fussman. This was a very special interview for me, because Cal is one of the major reasons why I started podcasting in the first place. He made an appearance on Tim Ferriss' show, to which Tim talked him into starting his own show. As both of them are my podcasting inspirations, I knew this was going to be a good one! Cal is a New York Times Bestselling Author, Professional Speaker, Storytelling Coach, and host of “Big Questions” Cal was best friends with Larry King and shared breakfast with him every morning. He also traveled around the world for 10 years straight after booking a 1 way ticket to start a trip. He worked his way around the world, bus by bus where locals would invite him to their house to stay (more about this in the episode).Cal was a former writer for Esquire Magazine, where he interviewed a very impressive list, including: Muhammad Ali, Mikhail Gorbachev, Jeff Bezos, Richard Branson, Jimmy Carter, Robert DeNiro, Donald Trump, Al Pacino, Joe Biden, Larry King, Ted Kennedy, Tony Bennett, Barbara Walters, Bruce Springsteen, Dr. Michael DeBakey (father of open-heart surgery), Pele, Vint Cerf (co-creator of the Internet), George Clooney, Lauren Hutton (first super model) Leonardo DiCaprio, Dr. Dre, Walter Cronkite, Clint Eastwood, Mary Barra (General Motors CEO), legendary coaches John Wooden, Bobby Bowden and Mike Krzyzewski, Salman Rushdie, Tom Hanks, Shaquille O'Neal In this episode, we discussed:How A Good Question Can Get You To The Most Powerful Person In The WorldUkraine and Their Fight For A Free SocietyBuilding The Connection Bridge How Every Step back Is A Step Forward Rethinking Healthcare in America How To Tell Your StoryMuch More! Please enjoy this week's episode with Cal Fussman____________________________________________________________________________I am now in the early stages of writing my first book! In this book, I will be telling my story of getting into sales and the lessons I have learned so far, and intertwine stories, tips, and advice from the Top Sales Professionals In The World! As a first time author, I want to share these interviews with you all, and take you on this book writing journey with me! Like the show? Subscribe to the email: https://mailchi.mp/a71e58dacffb/welcome-to-the-20-podcast-community

YeePay is a leading payment service provider that delivers payment solutions for enterprises across industries, including airline & travel, new retail, fintech, administration & education, and cross-border transactions.Prior to founding YeePay, Chen held various roles at Oracle, John Deere Health Care, and AT&T Bell Labs, and served as a director at the Silicon Valley enterprise SVC Wireless. He also co-founded NetVan, a nonprofit promoting internet adoption in traditional industries, and advised China Central Television's documentary The Internet Age, where he interviewed leaders such as Elon Musk, Mark Zuckerberg, Peter Thiel, Reid Hoffman, Jerry Yang, Vint Cerf, and Kevin Kelly.In this episode, you will hear about: The entrepreneurial landscape in China in the early 2000s: challenges and opportunities of building a startup at that time.How YeePay evolved its business model as WeChat Pay and Alipay entered the market.Broader insights on Web3, cross-border transactions, globalization, and the growing role of AI in the future of the payment industry.

Vint is seen as one of the founding fathers of the Internet, and along with Robert Kahn, was award the ACM AM Turing Prize - the Nobel Prize of Computer Science - in 2004. Vint contributed to many areas in the creation of the Internet, including writing many RFCs (Requests For Comment) drafts, and in 1974 published the classic paper of "A Protocol for Packet Network Intercommunication" in the IEEE Transactions on Communications. This paper basically defined the IP and TCP protocols that would eventually be used to build the Internet. Along with the A.M. Turing Award, he received the National Medal of Technology from President Clinton in 1997, the Presidential Medal of Freedom from President George W Bush, and the Marconi Prize. Vint has Honorary Doctorates from over 27 universities, including ETHZ in Zurich, Yale University and the University of St Andrews. In 2012, he was induced into the Internet Hall of Fame, and, in 2023, he received the IEEE Medal of Honor for co-creating the Internet, and in sustained leadership in the creation of the Internet as critical infrastructure.

My guest today is Vinton G. Cerf, widely regarded as a “father of the Internet.” In the 1970s, Vint co-developed the TCP/IP protocols that define how data is formatted, transmitted, and received across devices. In essence, his work enabled networks to communicate, thus laying the foundation for the Internet as a unified global system. He has received honorary degrees and awards that include the National Medal of Technology, the Turing Award, the Presidential Medal of Freedom, the Marconi Prize, and membership in the National Academy of Engineering. He is currently Chief Internet Evangelist at Google.In this episode, Vint reflects on the Internet's path from ARPANET and TCP/IP to the scaling choices that made global connectivity possible. He explains why decentralization was key, and how fiber optics and data centers underwrote explosive growth. Vint also addresses today's policy anxieties (fragmentation, sovereignty walls, and fragile infrastructures…) before looking upward to the interplanetary Internet now linking spacecraft. Finally, we turn to AI: how LLMs are reshaping learning and software, and why the next leap may be systems that question us back. I hope you enjoy our discussion.You can follow me on X (@⁠ProfSchrepel⁠) and BlueSky (@⁠ProfSchrepel⁠).

Vint Cerf, widely recognized as one of the fathers of the Internet, is today’s special guest on Total Network Operations. He currently serves as Vice President and Chief Internet Evangelist at Google. His pioneering work began back in the 1960’s when he was involved in the ARPANET project. Alongside Bob Kahn, Vint co-invented the TCP/IP... Read more »

Vint Cerf, widely recognized as one of the fathers of the Internet, is today’s special guest on Total Network Operations. He currently serves as Vice President and Chief Internet Evangelist at Google. His pioneering work began back in the 1960’s when he was involved in the ARPANET project. Alongside Bob Kahn, Vint co-invented the TCP/IP... Read more »

This week's throwback guest is Cal Fussman. This was a very special interview for me, because Cal is one of the major reasons why I started podcasting in the first place. He made an appearance on Tim Ferriss' show, to which Tim talked him into starting his own show. As both of them are my podcasting inspirations, I knew this was going to be a good one! Cal is a New York Times Bestselling Author, Professional Speaker, Storytelling Coach, and host of “Big Questions” Cal was best friends with Larry King and shared breakfast with him every morning. He also traveled around the world for 10 years straight after booking a 1 way ticket to start a trip. He worked his way around the world, bus by bus where locals would invite him to their house to stay (more about this in the episode).Cal was a former writer for Esquire Magazine, where he interviewed a very impressive list, including: Muhammad Ali, Mikhail Gorbachev, Jeff Bezos, Richard Branson, Jimmy Carter, Robert DeNiro, Donald Trump, Al Pacino, Joe Biden, Larry King, Ted Kennedy, Tony Bennett, Barbara Walters, Bruce Springsteen, Dr. Michael DeBakey (father of open-heart surgery), Pele, Vint Cerf (co-creator of the Internet), George Clooney, Lauren Hutton (first super model) Leonardo DiCaprio, Dr. Dre, Walter Cronkite, Clint Eastwood, Mary Barra (General Motors CEO), legendary coaches John Wooden, Bobby Bowden and Mike Krzyzewski, Salman Rushdie, Tom Hanks, Shaquille O'Neal In this episode, we discussed:How A Good Question Can Get You To The Most Powerful Person In The WorldUkraine and Their Fight For A Free SocietyBuilding The Connection Bridge How Every Step back Is A Step Forward Rethinking Healthcare in America How To Tell Your StoryMuch More! Please enjoy this week's episode with Cal Fussman____________________________________________________________________________I am now in the early stages of writing my first book! In this book, I will be telling my story of getting into sales and the lessons I have learned so far, and intertwine stories, tips, and advice from the Top Sales Professionals In The World! As a first time author, I want to share these interviews with you all, and take you on this book writing journey with me! Like the show? Subscribe to the email: https://mailchi.mp/a71e58dacffb/welcome-to-the-20-podcast-communityI want your feedback!Reach out to 20percentpodcastquestions@gmail.com, or find me on LinkedIn.If you know anyone who would benefit from this show, share it along! If you know of anyone who would be great to interview, please drop me a line!Enjoy the show!

Episode 5 of the Board Director Series features Aliza Knox, bestselling author of "Don't Quit Your Day Job" and the tech executive who built APAC businesses for Google, Twitter, and Cloudflare. From Boston Consulting Group to becoming APAC IT Woman of the Year and the first female partner across Asia Pacific at BCG, Aliza's career demonstrates the power of curiosity-driven decision-making and strategic risk-taking. Aliza shares her unique career framework—Aliza 1.0 (consulting/finance), 2.0 (tech transformation), and 3.0 (portfolio career)—while revealing how personal interests in swimming, Asia, and the internet inadvertently shaped her professional trajectory. She discusses the "brave or foolish" decision to take significant title and salary cuts to enter tech, and how writing a simple email to Vint Cerf changed everything. Now in her portfolio phase as a board director and senior advisor, Aliza offers practical insights on staying relevant in rapidly changing industries, the importance of building a "personal board of directors," and why emotional feedback taught her to separate stress from authentic enthusiasm.   -----------------------   Inside My CEO Calendar: How I Led A Team of 5k+ Without Getting Pulled Back Into the Weeds A behind-the-scenes private podcast for senior female leaders and CEOs who don't need fluff—just sharper thinking, smarter moves, and more time for what matters. You don't have time for another 60-minute webinar. But you do have 15 minutes while you're driving into the office or grabbing your mid-day coffee. Listen here: https://www.bravefeminineleadership.com/BFL-Private-Podcast   ----------------------- Craving inspiration? I send an email each Sunday about leadership reflection, top tips to build an intentional & sustainable life and other things that have captured my attention and are too good not to share! Sign up here: https://www.bravefeminineleadership.com/leadershipinspiration   Loving the podcast? Leave us a short review. It takes less than 60 seconds & will inspire like-minded leaders to join the conversation!   Access Your Free Clarity Tool Between the endless to-do lists, competing priorities, and decisions piling up, it's easy to lose sight of what matters most. But here's the truth: you can't give more if you're running on empty. That's why we created Balance Your Brave—a free 15-minute diagnostic tool to help you regain control and clarity. In just 15 minutes, you will: ✅ Pinpoint energy drains holding you back. ✅ Identify where to focus for the biggest impact. ✅ Walk away feeling calmer and more confident in your next steps. Think of it as your personal roadmap to balance and alignment. ⬇️ Click here to access your free Balance Your Brave diagnostic tool. https://www.bravefeminineleadership.com/Balance-Your-Brave   Are we friends? Connect with Us. YouTube: https://www.youtube.com/@bravefeminineleadership Instagram: https://www.instagram.com/bravefeminineleadership LinkedIn: https://www.linkedin.com/company/brave-feminine-leadership

In this episode of The Broadband Bunch, host Brad Hine previews Fiber Connect 2025 with Richard Williams, President & CEO of Connect2 Communications, and Evann Freeman, VP of Government & Community Relations at EPB Chattanooga and Fiber Connect Conference Chair. They discuss what's new at this year's event—including 300+ speakers, expanded operator Light Talks, tribal broadband sessions, and the premiere of the Thought Waves documentary featuring internet pioneer Vint Cerf. Plus, get the inside scoop on the expo, Smart Home Open House, OpTIC Path rodeo, and can't-miss social events like karaoke night and the Glow Party.

This week on DisrupTV, we interviewed Vint Cerf, VP & Chief Internet Evangelist at Google, Dr. David Bray, Distinguished Chair of the Accelerator, Stimson Center & Principal/CEO, LDA Ventures Inc. and Irene Yam, author of Build a World-Class Customer Advisory Board: How To Create Deeper Relationships And Validate Strategies. Vint highlighted the internet's rapid growth, now used by 5.6 billion people, and its advancements in speed and technology, including AI and interplanetary connectivity. David emphasized the need for social norms and accountability in the digital age. Irene touched on the importance of customer advisory boards (CABs) for product development and the need for leaders to actively listen to customer feedback. DisrupTV is a weekly podcast with hosts R "Ray" Wang and Vala Afshar. The show airs live at 11:00 a.m. PT/ 2:00 p.m. ET every Friday. Brought to you by Constellation Executive Network: constellationr.com/CEN.

"The telephone, invented by Alexander Graham Bell, whose wife and mother were Deaf, and could not use the phone. It's Ironic!" Chief Internet Evangelist for Google Vint Cerf is widely recognised and applauded for being a pioneer in the invention of the internet, redefining not only connecting software and people on incredible scale but also accessibility and access worldwide.Vint, who is Hard of Hearing, speaks about how technology has transformed his and wife Sigrid's lives from communication to education and socialisation. The story of "listening" to E-Books as a person who is deaf is HILARIOUS! If you've ever wondered how people who are part of the Deaf & Hard of Hearing community understand accents, listen to music or even learn other languages? All will be revealed in this episode of ListenABLE! Watch the Full Episode on YouTube with Captions Here: https://youtu.be/skFkfaQUGAY BIG thank you to our friends at Remarkable Tech for helping make this interview happen! You can hear their fantastic interview focusing solely on Vint's intersection with technology here: https://www.remarkable.org/insights-podcast/vint-cerf---fathers-of-the-internet-and-accessible-technology Grab our first merch release at our website From Your Pocket https://fromyourpocket.com.au/work/listenable/merch Recorded, edited and produced by Angus' Podcast Company  https://fromyourpocket.com.au/See omnystudio.com/listener for privacy information.

In response to escalating gang violence and severe food shortages, a U.S. government-chartered flight from Cap Haitien brought 47 Americans to safety in Miami. This operation follows a series of evacuations and warnings of dire conditions in Haiti.With the arrival of spring, it's the perfect time to declutter your finances and address pressing financial matters. CBS News business analyst Jill Schlesinger offers expert advice on how to refresh and organize your financial life.In a heartfelt return to prime-time, Oprah Winfrey confronts the complex issues of obesity and the associated shame, sharing her personal journey with weight and discussing the impact of weight-loss drugs like Ozempic.The children of late Run D-M-C star DJ Jam Master Jay are speaking out for the first time since two men were convicted last month of murdering their father more than 20 years ago. CBS New York anchor Maurice DuBois spoke to them at "Scratch DJ Academy," which was co-founded by their father."CBS Mornings" co-host Tony Dokoupil sits down with three computer scientists who helped create the internet, Bob Kahn, Vint Cerf and Steve Crocker, to see what they think of their creation now, and what our digital future may hold.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we dive into the unexpected consequences of technological decisions, from Vint Cerf's IPv4 format leading to address scarcity and rising costs, to the pervasive challenges of identity fraud exacerbated by deepfake technology. We also shed light on the persistent issue of application performance tied to third-party scripts and unpack the looming Y2K38 problem, highlighting the need for forward-thinking in digital infrastructure and cybersecurity.Stay updated with new weekly episodes every Thursday – and don't forget to subscribe! For more behind-the-scenes content, follow us @justshiftleft on Facebook, Instagram, Twitter, and LinkedIn.

OpenAI and Microsoft are leaders in generative artificial intelligence (AI). OpenAI has built GPT-4, one of the world's most sophisticated large language models (LLMs) and Microsoft is injecting those algorithms into its products, from Word to Windows. At the World Economic Forum in Davos last week, Zanny Minton Beddoes, The Economist's editor-in-chief, interviewed Sam Altman and Satya Nadella, who run OpenAI and Microsoft respectively. They explained their vision for humanity's future with AI and addressed some thorny questions looming over the field, such as how AI that is better than humans at doing tasks might affect productivity and how to ensure that the technology doesn't pose existential risks to society.Host: Alok Jha, The Economist's science and technology editor. Contributors: Zanny Minton Beddoes, editor-in-chief of The Economist; Ludwig Siegele, The Economist's senior editor, AI initiatives; Sam Altman, chief executive of OpenAI; Satya Nadella, chief executive of Microsoft. If you subscribe to The Economist, you can watch the full interview on our website or app. Essential listening, from our archive:“Daniel Dennett on intelligence, both human and artificial”, December 27th 2023“Fei-Fei Li on how to really think about the future of AI”, November 22nd 2023“Mustafa Suleyman on how to prepare for the age of AI”, September 13th 2023“Vint Cerf on how to wisely regulate AI”, July 5th 2023“Is GPT-4 the dawn of true artificial intelligence?”, with Gary Marcus, March 22nd 2023Sign up for a free trial of Economist Podcasts+. If you're already a subscriber to The Economist, you'll have full access to all our shows as part of your subscription. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account. Hosted on Acast. See acast.com/privacy for more information.

OpenAI and Microsoft are leaders in generative artificial intelligence (AI). OpenAI has built GPT-4, one of the world's most sophisticated large language models (LLMs) and Microsoft is injecting those algorithms into its products, from Word to Windows. At the World Economic Forum in Davos last week, Zanny Minton Beddoes, The Economist's editor-in-chief, interviewed Sam Altman and Satya Nadella, who run OpenAI and Microsoft respectively. They explained their vision for humanity's future with AI and addressed some thorny questions looming over the field, such as how AI that is better than humans at doing tasks might affect productivity and how to ensure that the technology doesn't pose existential risks to society.Host: Alok Jha, The Economist's science and technology editor. Contributors: Zanny Minton Beddoes, editor-in-chief of The Economist; Ludwig Siegele, The Economist's senior editor, AI initiatives; Sam Altman, chief executive of OpenAI; Satya Nadella, chief executive of Microsoft. If you subscribe to The Economist, you can watch the full interview on our website or app. Essential listening, from our archive:“Daniel Dennett on intelligence, both human and artificial”, December 27th 2023“Fei-Fei Li on how to really think about the future of AI”, November 22nd 2023“Mustafa Suleyman on how to prepare for the age of AI”, September 13th 2023“Vint Cerf on how to wisely regulate AI”, July 5th 2023“Is GPT-4 the dawn of true artificial intelligence?”, with Gary Marcus, March 22nd 2023Sign up for a free trial of Economist Podcasts+. If you're already a subscriber to The Economist, you'll have full access to all our shows as part of your subscription. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account. Hosted on Acast. See acast.com/privacy for more information.

Vint Cerf is known for his pioneering work as one of the fathers of the internet. He now serves as the vice president and chief internet evangelist for Google where he furthers global policy development and accessibility of the internet. He shares his Brief But Spectacular take on the future of the internet. PBS NewsHour is supported by - https://www.pbs.org/newshour/about/funders

Vint Cerf is known for his pioneering work as one of the fathers of the internet. He now serves as the vice president and chief internet evangelist for Google where he furthers global policy development and accessibility of the internet. He shares his Brief But Spectacular take on the future of the internet. PBS NewsHour is supported by - https://www.pbs.org/newshour/about/funders

*Explore the Presidential Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence. Signed by President Biden on October 30th 2023, this directive stands as a landmark in the evolving landscape of AI, setting a precedent for future development, usage, and regulation.Our guest is Dr. David Bray, previously CIO of the Federal Communications Commision for four years, IT Chief for the Bioterrorism Preparedness and Response Program, Senior National Intelligence Service Executive, and an expert on AI governance and ethics.*In this episode, we examine the presidential order to:*⭕ Explain why it's a crucial step for the future of AI.⭕Unravel its significant impact on the business world, examining the immediate and long-term implications for industries navigating this new regulatory landscape.⭕Consider what the order did not cover and explain what is missing.As AI continues to redefine the boundaries of innovation and efficiency, understanding the framework set by this Executive Order is imperative for business leaders. This episode provide insightful perspectives, clarifying how businesses can adapt, comply, and excel in this new era of AI.Watch this discussion to bridge the gap between technological evolution and business strategy, with valuable insights for executives and decision-makers in the rapidly changing world of AI.*Dr. David A. Bray* is both a Distinguished Fellow and co-chair of the Alfred Lee Loomis Innovation Council at the non-partisan Henry L. Stimson Center. He is also a non-resident Distinguished Fellow with the Business Executives for National Security, and a CEO and transformation leader for different “under the radar” tech and data ventures seeking to get started in novel situations. He is Principal at LeadDoAdapt Ventures and has served in a variety of leadership roles in turbulent environments, including bioterrorism preparedness and response from 2000-2005. Dr. Bray previously was the Executive Director for a bipartisan National Commission on R&D, provided non-partisan leadership as a Senior Executive and CIO at the FCC for four years, worked with the U.S. Navy and Marines on improving organizational adaptability, and aided U.S. Special Operation Command's J5 Directorate on the challenges of countering disinformation online. He has received both the Joint Civilian Service Commendation Award and the National Intelligence Exceptional Achievement Medal. David accepted a leadership role in December 2019 to direct the successful bipartisan Commission on the Geopolitical Impacts of New Technologies and Data that included Senator Mark Warner, Senator Rob Portman, Rep. Suzan DelBene, and Rep. Michael McCaul. From 2017 to the start of 2020, David also served as Executive Director for the People-Centered Internet coalition Chaired by Internet co-originator Vint Cerf and was named a Senior Fellow with the Institute for Human-Machine Cognition starting in 2018. Business Insider named him one of the top “24 Americans Who Are Changing the World” under 40 and he was named a Young Global Leader by the World Economic Forum. For twelve different startups, he has served as President, CEO, Chief Strategy Officer, and Strategic Advisor roles.*Michael Krigsman* is an industry analyst and publisher of CXOTalk. For three decades, he has advised enterprise technology companies on market messaging and positioning strategy. He has written over 1,000 blogs on leadership and digital transformation and created almost 1,000 video interviews with the world's top business leaders on these topics. His work has been referenced in the media over 1,000 times and in over 50 books. He has presented and moderated panels at numerous industry events around the world.#cxotalk #enterpriseai #responsibleai #aiethics

In this episode, we have the honor of welcoming Vint Cerf, Vice President and Chief Internet Evangelist at Google.A true pioneer in the realm of technology and communication, Vint's contributions have fundamentally shaped the digital landscape we inhabit today.With a career spanning decades and a legacy that extends from his pioneering work on the creation of the Internet to his continued advocacy for innovation, Vint's insights offer a profound perspective on the evolution of technology and its impact on society. His experiences have been forged through a lifetime of exploration, invention, and a deep curiosity about the interconnected world we live in.Vint's Top 5 CliftonStrengths are: Futuristic, Input, Communication, Strategic and Analytical.For more interviews visit leadingwithstrengths.comTranscripts available upon request.

How can engineering become more inclusive for disabled and neurodivergent people? And what are the engineering innovations that might make the workplace more accessible in the future? Lara Suzuki and Vint Cerf share their experiences and insights.Larissa Suzuki is a computer scientist, inventor, Chartered Engineer, and entrepreneur, who works with Google, NASA, UCL and the Queen Elizabeth Prize for Engineering among many others. She's neurodivergent (Autism and ADHD).Vinton Cerf is considered one of the ‘fathers of the Internet', and has been inducted into the National Inventors Hall of Fame. In 2005, Cerf became Vice President and Chief Internet Evangelist for Google. He's hearing impaired.Follow @QEPrize on Twitter, Instagram, and Facebook for more info.New episodes - conversations about how to rebuild the world better - every other Friday. Hosted on Acast. See acast.com/privacy for more information.

In this episode, we have the honor of talking to one of the pioneers of the internet: Vint Cerf. He is not only the co-inventor of the TCP/IP protocols and the internet architecture, but also a visionary leader and a passionate advocate for digital inclusion and accessibility.He will tell us how he got interested in technology and software engineering, how he met and collaborated with Bob Kahn on creating the internet, and how he became an evangelist for bringing more people online. He will also share some of his challenges and achievements from his six-decade-long career, and his thoughts on the future of the internet. He will also give us some tips on how to deal with stress, burnout, and harmful behaviors onlineDon't miss this incredible and inspiring conversation with Vint Cerf.-"I'm smart enough to know that if you want to do anything big, you need to get help, preferably from people who are smarter than you are."-Vint's Links:LinkedInTwitterWikipediaCommunications of the ACM - Cerf's UpMarconi Society--Thanks for being an imposter - a part of the Imposter Syndrome Network (ISN)! We'd love it if you connected with us at the links below: The ISN LinkedIn group (community): https://www.linkedin.com/groups/14098596/ The ISN on Twitter: https://twitter.com/ImposterNetwork Zoë on Twitter: https://twitter.com/RoseSecOps Chris on Twitter: https://twitter.com/ChrisGrundemann Make it a great day.

This podcast is a commentary and does not contain any copyrighted material of the reference source. We strongly recommend accessing/buying the reference source at the same time. ■Reference Source https://www.ted.com/talks/diana_reiss_peter_gabriel_neil_gershenfeld_and_vint_cerf_the_interspecies_internet_an_idea_in_progress ■Post on this topic (You can get FREE learning materials!) https://englist.me/177-academic-words-reference-from-diana-reiss-peter-gabriel-neil-gershenfeld-and-vint-cerf-the-interspecies-internet-an-idea-in-progress-ted-talk/ ■Youtube Video https://youtu.be/uAVvzIAI8ws (All Words) https://youtu.be/Yk9u0-QkrWQ (Advanced Words) https://youtu.be/D9IQHT5pKi4 (Quick Look) ■Top Page for Further Materials https://englist.me/ ■SNS (Please follow!)

Almost 50 years ago, Vint Cerf and Bob Kahn designed TCP/IP, a set of rules enabling computers to connect and communicate with each other. It led to the creation of a vast global network: the internet. TCP/IP is how almost the entirety of the internet still sends and receives information. Vint Cerf is now 80 and serves as the chief internet evangelist and a vice president at Google. He is also the chairman of the Marconi Society, a group that promotes digital equity.Alok Jha, The Economist's science and technology editor, asks Vint to reflect on the state of the internet today and the lessons that should be learned for the next, disruptive technology: generative artificial intelligence. Vint Cerf explains how he thinks large language models can be regulated without stifling innovation—ie, more precisely based on their specific applications.For full access to The Economist's print, digital and audio editions subscribe at economist.com/podcastoffer and sign up for our weekly science newsletter at economist.com/simplyscience. Hosted on Acast. See acast.com/privacy for more information.

Almost 50 years ago, Vint Cerf and Bob Kahn designed TCP/IP, a set of rules enabling computers to connect and communicate with each other. It led to the creation of a vast global network: the internet. TCP/IP is how almost the entirety of the internet still sends and receives information. Vint Cerf is now 80 and serves as the chief internet evangelist and a vice president at Google. He is also the chairman of the Marconi Society, a group that promotes digital equity.Alok Jha, The Economist's science and technology editor, asks Vint to reflect on the state of the internet today and the lessons that should be learned for the next, disruptive technology: generative artificial intelligence. Vint Cerf explains how he thinks large language models can be regulated without stifling innovation—ie, more precisely based on their specific applications.For full access to The Economist's print, digital and audio editions subscribe at economist.com/podcastoffer and sign up for our weekly science newsletter at economist.com/simplyscience. Hosted on Acast. See acast.com/privacy for more information.

Episode 165 of A History of Rock Music in Five Hundred Songs looks at “Dark Stat” and the career of the Grateful Dead. This is a long one, even longer than the previous episode, but don't worry, that won't be the norm. There's a reason these two were much longer than average. Click the full post to read liner notes, links to more information, and a transcript of the episode. Patreon backers also have a twenty-minute bonus episode available, on "Codine" by the Charlatans. Errata I mispronounce Brent Mydland's name as Myland a couple of times, and in the introduction I say "Touch of Grey" came out in 1988 -- I later, correctly, say 1987. (I seem to have had a real problem with dates in the intro -- I also originally talked about "Blue Suede Shoes" being in 1954 before fixing it in the edit to be 1956) Resources No Mixcloud this week, as there are too many songs by the Grateful Dead, and Grayfolded runs to two hours. I referred to a lot of books for this episode, partly because almost everything about the Grateful Dead is written from a fannish perspective that already assumes background knowledge, rather than to provide that background knowledge. Of the various books I used, Dennis McNally's biography of the band and This Is All a Dream We Dreamed: An Oral History of the Grateful Dead by Blair Jackson and David Gans are probably most useful for the casually interested. Other books on the Dead I used included McNally's Jerry on Jerry, a collection of interviews with Garcia; Deal, Bill Kreutzmann's autobiography; The Grateful Dead FAQ by Tony Sclafani; So Many Roads by David Browne; Deadology by Howard F. Weiner; Fare Thee Well by Joel Selvin and Pamela Turley; and Skeleton Key: A Dictionary for Deadheads by David Shenk and Steve Silberman. Tom Wolfe's The Electric Kool-Aid Acid Test is the classic account of the Pranksters, though not always reliable. I reference Slaughterhouse Five a lot. As well as the novel itself, which everyone should read, I also read this rather excellent graphic novel adaptation, and The Writer's Crusade, a book about the writing of the novel. I also reference Ted Sturgeon's More Than Human. For background on the scene around Astounding Science Fiction which included Sturgeon, John W. Campbell, L. Ron Hubbard, and many other science fiction writers, I recommend Alec Nevala-Lee's Astounding. 1,000 True Fans can be read online, as can the essay on the Californian ideology, and John Perry Barlow's "Declaration of the Independence of Cyberspace". The best collection of Grateful Dead material is the box set The Golden Road, which contains all the albums released in Pigpen's lifetime along with a lot of bonus material, but which appears currently out of print. Live/Dead contains both the live version of "Dark Star" which made it well known and, as a CD bonus track, the original single version. And archive.org has more live recordings of the group than you can possibly ever listen to. Grayfolded can be bought from John Oswald's Bandcamp Patreon This podcast is brought to you by the generosity of my backers on Patreon. Why not join them? Transcript [Excerpt: Tuning from "Grayfolded", under the warnings Before we begin -- as we're tuning up, as it were, I should mention that this episode contains discussions of alcoholism, drug addiction, racism, nonconsensual drugging of other people, and deaths from drug abuse, suicide, and car accidents. As always, I try to deal with these subjects as carefully as possible, but if you find any of those things upsetting you may wish to read the transcript rather than listen to this episode, or skip it altogether. Also, I should note that the members of the Grateful Dead were much freer with their use of swearing in interviews than any other band we've covered so far, and that makes using quotes from them rather more difficult than with other bands, given the limitations of the rules imposed to stop the podcast being marked as adult. If I quote anything with a word I can't use here, I'll give a brief pause in the audio, and in the transcript I'll have the word in square brackets. [tuning ends] All this happened, more or less. In 1910, T. S. Eliot started work on "The Love Song of J. Alfred Prufrock", which at the time was deemed barely poetry, with one reviewer imagining Eliot saying "I'll just put down the first thing that comes into my head, and call it 'The Love Song of J. Alfred Prufrock.'" It is now considered one of the great classics of modernist literature. In 1969, Kurt Vonnegut wrote "Slaughterhouse-Five, or, The Children's Crusade: A Duty-Dance with Death", a book in which the protagonist, Billy Pilgrim, comes unstuck in time, and starts living a nonlinear life, hopping around between times reliving his experiences in the Second World War, and future experiences up to 1976 after being kidnapped by beings from the planet Tralfamadore. Or perhaps he has flashbacks and hallucinations after having a breakdown from PTSD. It is now considered one of the great classics of modernist literature or of science fiction, depending on how you look at it. In 1953, Theodore Sturgeon wrote More Than Human. It is now considered one of the great classics of science fiction. In 1950, L. Ron Hubbard wrote Dianetics: The Modern Science of Mental Health. It is now considered either a bad piece of science fiction or one of the great revelatory works of religious history, depending on how you look at it. In 1994, 1995, and 1996 the composer John Oswald released, first as two individual CDs and then as a double-CD, an album called Grayfolded, which the composer says in the liner notes he thinks of as existing in Tralfamadorian time. The Tralfamadorians in Vonnegut's novels don't see time as a linear thing with a beginning and end, but as a continuum that they can move between at will. When someone dies, they just think that at this particular point in time they're not doing so good, but at other points in time they're fine, so why focus on the bad time? In the book, when told of someone dying, the Tralfamadorians just say "so it goes". In between the first CD's release and the release of the double-CD version, Jerry Garcia died. From August 1942 through August 1995, Jerry Garcia was alive. So it goes. Shall we go, you and I? [Excerpt: The Grateful Dead, "Dark Star (Omni 3/30/94)"] "One principle has become clear. Since motives are so frequently found in combination, it is essential that the complex types be analyzed and arranged, with an eye kept single nevertheless to the master-theme under discussion. Collectors, both primary and subsidiary, have done such valiant service that the treasures at our command are amply sufficient for such studies, so extensive, indeed, that the task of going through them thoroughly has become too great for the unassisted student. It cannot be too strongly urged that a single theme in its various types and compounds must be made predominant in any useful comparative study. This is true when the sources and analogues of any literary work are treated; it is even truer when the bare motive is discussed. The Grateful Dead furnishes an apt illustration of the necessity of such handling. It appears in a variety of different combinations, almost never alone. Indeed, it is so widespread a tale, and its combinations are so various, that there is the utmost difficulty in determining just what may properly be regarded the original kernel of it, the simple theme to which other motives were joined. Various opinions, as we shall see, have been held with reference to this matter, most of them justified perhaps by the materials in the hands of the scholars holding them, but none quite adequate in view of later evidence." That's a quote from The Grateful Dead: The History of a Folk Story, by Gordon Hall Gerould, published in 1908. Kurt Vonnegut's novel Slaughterhouse-Five opens with a chapter about the process of writing the novel itself, and how difficult it was. He says "I would hate to tell you what this lousy little book cost me in money and anxiety and time. When I got home from the Second World War twenty-three years ago, I thought it would be easy for me to write about the destruction of Dresden, since all I would have to do would be to report what I had seen. And I thought, too, that it would be a masterpiece or at least make me a lot of money, since the subject was so big." This is an episode several of my listeners have been looking forward to, but it's one I've been dreading writing, because this is an episode -- I think the only one in the series -- where the format of the podcast simply *will not* work. Were the Grateful Dead not such an important band, I would skip this episode altogether, but they're a band that simply can't be ignored, and that's a real problem here. Because my intent, always, with this podcast, is to present the recordings of the artists in question, put them in context, and explain why they were important, what their music meant to its listeners. To put, as far as is possible, the positive case for why the music mattered *in the context of its time*. Not why it matters now, or why it matters to me, but why it matters *in its historical context*. Whether I like the music or not isn't the point. Whether it stands up now isn't the point. I play the music, explain what it was they were doing, why they were doing it, what people saw in it. If I do my job well, you come away listening to "Blue Suede Shoes" the way people heard it in 1956, or "Good Vibrations" the way people heard it in 1966, and understanding why people were so impressed by those records. That is simply *not possible* for the Grateful Dead. I can present a case for them as musicians, and hope to do so. I can explain the appeal as best I understand it, and talk about things I like in their music, and things I've noticed. But what I can't do is present their recordings the way they were received in the sixties and explain why they were popular. Because every other act I have covered or will cover in this podcast has been a *recording* act, and their success was based on records. They may also have been exceptional live performers, but James Brown or Ike and Tina Turner are remembered for great *records*, like "Papa's Got a Brand New Bag" or "River Deep, Mountain High". Their great moments were captured on vinyl, to be listened back to, and susceptible of analysis. That is not the case for the Grateful Dead, and what is worse *they explicitly said, publicly, on multiple occasions* that it is not possible for me to understand their art, and thus that it is not possible for me to explain it. The Grateful Dead did make studio records, some of them very good. But they always said, consistently, over a thirty year period, that their records didn't capture what they did, and that the only way -- the *only* way, they were very clear about this -- that one could actually understand and appreciate their music, was to see them live, and furthermore to see them live while on psychedelic drugs. [Excerpt: Grateful Dead crowd noise] I never saw the Grateful Dead live -- their last UK performance was a couple of years before I went to my first ever gig -- and I have never taken a psychedelic substance. So by the Grateful Dead's own criteria, it is literally impossible for me to understand or explain their music the way that it should be understood or explained. In a way I'm in a similar position to the one I was in with La Monte Young in the last episode, whose music it's mostly impossible to experience without being in his presence. This is one reason of several why I placed these two episodes back to back. Of course, there is a difference between Young and the Grateful Dead. The Grateful Dead allowed -- even encouraged -- the recording of their live performances. There are literally thousands of concert recordings in circulation, many of them of professional quality. I have listened to many of those, and I can hear what they were doing. I can tell you what *I* think is interesting about their music, and about their musicianship. And I think I can build up a good case for why they were important, and why they're interesting, and why those recordings are worth listening to. And I can certainly explain the cultural phenomenon that was the Grateful Dead. But just know that while I may have found *a* point, *an* explanation for why the Grateful Dead were important, by the band's own lights and those of their fans, no matter how good a job I do in this episode, I *cannot* get it right. And that is, in itself, enough of a reason for this episode to exist, and for me to try, even harder than I normally do, to get it right *anyway*. Because no matter how well I do my job this episode will stand as an example of why this series is called "*A* History", not *the* history. Because parts of the past are ephemeral. There are things about which it's true to say "You had to be there". I cannot know what it was like to have been an American the day Kennedy was shot, I cannot know what it was like to be alive when a man walked on the Moon. Those are things nobody my age or younger can ever experience. And since August the ninth, 1995, the experience of hearing the Grateful Dead's music the way they wanted it heard has been in that category. And that is by design. Jerry Garcia once said "if you work really hard as an artist, you may be able to build something they can't tear down, you know, after you're gone... What I want to do is I want it here. I want it now, in this lifetime. I want what I enjoy to last as long as I do and not last any longer. You know, I don't want something that ends up being as much a nuisance as it is a work of art, you know?" And there's another difficulty. There are only two points in time where it makes sense to do a podcast episode on the Grateful Dead -- late 1967 and early 1968, when the San Francisco scene they were part of was at its most culturally relevant, and 1988 when they had their only top ten hit and gained their largest audience. I can't realistically leave them out of the story until 1988, so it has to be 1968. But the songs they are most remembered for are those they wrote between 1970 and 1972, and those songs are influenced by artists and events we haven't yet covered in the podcast, who will be getting their own episodes in the future. I can't explain those things in this episode, because they need whole episodes of their own. I can't not explain them without leaving out important context for the Grateful Dead. So the best I can do is treat the story I'm telling as if it were in Tralfamadorian time. All of it's happening all at once, and some of it is happening in different episodes that haven't been recorded yet. The podcast as a whole travels linearly from 1938 through to 1999, but this episode is happening in 1968 and 1972 and 1988 and 1995 and other times, all at once. Sometimes I'll talk about things as if you're already familiar with them, but they haven't happened yet in the story. Feel free to come unstuck in time and revisit this time after episode 167, and 172, and 176, and 192, and experience it again. So this has to be an experimental episode. It may well be an experiment that you think fails. If so, the next episode is likely to be far more to your taste, and much shorter than this or the last episode, two episodes that between them have to create a scaffolding on which will hang much of the rest of this podcast's narrative. I've finished my Grateful Dead script now. The next one I write is going to be fun: [Excerpt: Grateful Dead, "Dark Star"] Infrastructure means everything. How we get from place to place, how we transport goods, information, and ourselves, makes a big difference in how society is structured, and in the music we hear. For many centuries, the prime means of long-distance transport was by water -- sailing ships on the ocean, canal boats and steamboats for inland navigation -- and so folk songs talked about the ship as both means of escape, means of making a living, and in some senses as a trap. You'd go out to sea for adventure, or to escape your problems, but you'd find that the sea itself brought its own problems. Because of this we have a long, long tradition of sea shanties which are known throughout the world: [Excerpt: A. L. Lloyd, "Off to Sea Once More"] But in the nineteenth century, the railway was invented and, at least as far as travel within a landmass goes, it replaced the steamboat in the popular imaginary. Now the railway was how you got from place to place, and how you moved freight from one place to another. The railway brought freedom, and was an opportunity for outlaws, whether train robbers or a romanticised version of the hobo hopping onto a freight train and making his way to new lands and new opportunity. It was the train that brought soldiers home from wars, and the train that allowed the Great Migration of Black people from the South to the industrial North. There would still be songs about the riverboats, about how ol' man river keeps rolling along and about the big river Johnny Cash sang about, but increasingly they would be songs of the past, not the present. The train quickly replaced the steamboat in the iconography of what we now think of as roots music -- blues, country, folk, and early jazz music. Sometimes this was very literal. Furry Lewis' "Kassie Jones" -- about a legendary train driver who would break the rules to make sure his train made the station on time, but who ended up sacrificing his own life to save his passengers in a train crash -- is based on "Alabamy Bound", which as we heard in the episode on "Stagger Lee", was about steamboats: [Excerpt: Furry Lewis, "Kassie Jones"] In the early episodes of this podcast we heard many, many, songs about the railway. Louis Jordan saying "take me right back to the track, Jack", Rosetta Tharpe singing about how "this train don't carry no gamblers", the trickster freight train driver driving on the "Rock Island Line", the mystery train sixteen coaches long, the train that kept-a-rollin' all night long, the Midnight Special which the prisoners wished would shine its ever-loving light on them, and the train coming past Folsom Prison whose whistle makes Johnny Cash hang his head and cry. But by the 1960s, that kind of song had started to dry up. It would happen on occasion -- "People Get Ready" by the Impressions is the most obvious example of the train metaphor in an important sixties record -- but by the late sixties the train was no longer a symbol of freedom but of the past. In 1969 Harry Nilsson sang about how "Nobody Cares About the Railroads Any More", and in 1968 the Kinks sang about "The Last of the Steam-Powered Trains". When in 1968 Merle Haggard sang about a freight train, it was as a memory, of a child with hopes that ended up thwarted by reality and his own nature: [Excerpt: Merle Haggard, "Mama Tried"] And the reason for this was that there had been another shift, a shift that had started in the forties and accelerated in the late fifties but had taken a little time to ripple through the culture. Now the train had been replaced in the popular imaginary by motorised transport. Instead of hopping on a train without paying, if you had no money in your pocket you'd have to hitch-hike all the way. Freedom now meant individuality. The ultimate in freedom was the biker -- the Hell's Angels who could go anywhere, unburdened by anything -- and instead of goods being moved by freight train, increasingly they were being moved by truck drivers. By the mid-seventies, truck drivers took a central place in American life, and the most romantic way to live life was to live it on the road. On The Road was also the title of a 1957 novel by Jack Kerouac, which was one of the first major signs of this cultural shift in America. Kerouac was writing about events in the late forties and early fifties, but his book was also a precursor of the sixties counterculture. He wrote the book on one continuous sheet of paper, as a stream of consciousness. Kerouac died in 1969 of an internal haemmorage brought on by too much alcohol consumption. So it goes. But the big key to this cultural shift was caused by the Federal-Aid Highway Act of 1956, a massive infrastructure spending bill that led to the construction of the modern American Interstate Highway system. This accelerated a program that had already started, of building much bigger, safer, faster roads. It also, as anyone who has read Robert Caro's The Power Broker knows, reinforced segregation and white flight. It did this both by making commuting into major cities from the suburbs easier -- thus allowing white people with more money to move further away from the cities and still work there -- and by bulldozing community spaces where Black people lived. More than a million people lost their homes and were forcibly moved, and orders of magnitude more lost their communities' parks and green spaces. And both as a result of deliberate actions and unconscious bigotry, the bulk of those affected were Black people -- who often found themselves, if they weren't forced to move, on one side of a ten-lane highway where the park used to be, with white people on the other side of the highway. The Federal-Aid Highway Act gave even more power to the unaccountable central planners like Robert Moses, the urban planner in New York who managed to become arguably the most powerful man in the city without ever getting elected, partly by slowly compromising away his early progressive ideals in the service of gaining more power. Of course, not every new highway was built through areas where poor Black people lived. Some were planned to go through richer areas for white people, just because you can't completely do away with geographical realities. For example one was planned to be built through part of San Francisco, a rich, white part. But the people who owned properties in that area had enough political power and clout to fight the development, and after nearly a decade of fighting it, the development was called off in late 1966. But over that time, many of the owners of the impressive buildings in the area had moved out, and they had no incentive to improve or maintain their properties while they were under threat of demolition, so many of them were rented out very cheaply. And when the beat community that Kerouac wrote about, many of whom had settled in San Francisco, grew too large and notorious for the area of the city they were in, North Beach, many of them moved to these cheap homes in a previously-exclusive area. The area known as Haight-Ashbury. [Excerpt: The Grateful Dead, "Grayfolded"] Stories all have their starts, even stories told in Tralfamadorian time, although sometimes those starts are shrouded in legend. For example, the story of Scientology's start has been told many times, with different people claiming to have heard L. Ron Hubbard talk about how writing was a mug's game, and if you wanted to make real money, you needed to get followers, start a religion. Either he said this over and over and over again, to many different science fiction writers, or most science fiction writers of his generation were liars. Of course, the definition of a writer is someone who tells lies for money, so who knows? One of the more plausible accounts of him saying that is given by Theodore Sturgeon. Sturgeon's account is more believable than most, because Sturgeon went on to be a supporter of Dianetics, the "new science" that Hubbard turned into his religion, for decades, even while telling the story. The story of the Grateful Dead probably starts as it ends, with Jerry Garcia. There are three things that everyone writing about the Dead says about Garcia's childhood, so we might as well say them here too. The first is that he was named by a music-loving father after Jerome Kern, the songwriter responsible for songs like "Ol' Man River" (though as Oscar Hammerstein's widow liked to point out, "Jerome Kern wrote dum-dum-dum-dum, *my husband* wrote 'Ol' Man River'" -- an important distinction we need to bear in mind when talking about songwriters who write music but not lyrics). The second is that when he was five years old that music-loving father drowned -- and Garcia would always say he had seen his father dying, though some sources claim this was a false memory. So it goes. And the third fact, which for some reason is always told after the second even though it comes before it chronologically, is that when he was four he lost two joints from his right middle finger. Garcia grew up a troubled teen, and in turn caused trouble for other people, but he also developed a few interests that would follow him through his life. He loved the fantastical, especially the fantastical macabre, and became an avid fan of horror and science fiction -- and through his love of old monster films he became enamoured with cinema more generally. Indeed, in 1983 he bought the film rights to Kurt Vonnegut's science fiction novel The Sirens of Titan, the first story in which the Tralfamadorians appear, and wrote a script based on it. He wanted to produce the film himself, with Francis Ford Coppola directing and Bill Murray starring, but most importantly for him he wanted to prevent anyone who didn't care about it from doing it badly. And in that he succeeded. As of 2023 there is no film of The Sirens of Titan. He loved to paint, and would continue that for the rest of his life, with one of his favourite subjects being Boris Karloff as the Frankenstein monster. And when he was eleven or twelve, he heard for the first time a record that was hugely influential to a whole generation of Californian musicians, even though it was a New York record -- "Gee" by the Crows: [Excerpt: The Crows, "Gee"] Garcia would say later "That was an important song. That was the first kind of, like where the voices had that kind of not-trained-singer voices, but tough-guy-on-the-street voice." That record introduced him to R&B, and soon he was listening to Chuck Berry and Bo Diddley, to Ray Charles, and to a record we've not talked about in the podcast but which was one of the great early doo-wop records, "WPLJ" by the Four Deuces: [Excerpt: The Four Deuces, "WPLJ"] Garcia said of that record "That was one of my anthem songs when I was in junior high school and high school and around there. That was one of those songs everybody knew. And that everybody sang. Everybody sang that street-corner favorite." Garcia moved around a lot as a child, and didn't have much time for school by his own account, but one of the few teachers he did respect was an art teacher when he was in North Beach, Walter Hedrick. Hedrick was also one of the earliest of the conceptual artists, and one of the most important figures in the San Francisco arts scene that would become known as the Beat Generation (or the Beatniks, which was originally a disparaging term). Hedrick was a painter and sculptor, but also organised happenings, and he had also been one of the prime movers in starting a series of poetry readings in San Francisco, the first one of which had involved Allen Ginsberg giving the first ever reading of "Howl" -- one of a small number of poems, along with Eliot's "Prufrock" and "The Waste Land" and possibly Pound's Cantos, which can be said to have changed twentieth-century literature. Garcia was fifteen when he got to know Hedrick, in 1957, and by then the Beat scene had already become almost a parody of itself, having become known to the public because of the publication of works like On the Road, and the major artists in the scene were already rejecting the label. By this point tourists were flocking to North Beach to see these beatniks they'd heard about on TV, and Hedrick was actually employed by one cafe to sit in the window wearing a beret, turtleneck, sandals, and beard, and draw and paint, to attract the tourists who flocked by the busload because they could see that there was a "genuine beatnik" in the cafe. Hedrick was, as well as a visual artist, a guitarist and banjo player who played in traditional jazz bands, and he would bring records in to class for his students to listen to, and Garcia particularly remembered him bringing in records by Big Bill Broonzy: [Excerpt: Big Bill Broonzy, "When Things Go Wrong (It Hurts Me Too)"] Garcia was already an avid fan of rock and roll music, but it was being inspired by Hedrick that led him to get his first guitar. Like his contemporary Paul McCartney around the same time, he was initially given the wrong instrument as a birthday present -- in Garcia's case his mother gave him an accordion -- but he soon persuaded her to swap it for an electric guitar he saw in a pawn shop. And like his other contemporary, John Lennon, Garcia initially tuned his instrument incorrectly. He said later "When I started playing the guitar, believe me, I didn't know anybody that played. I mean, I didn't know anybody that played the guitar. Nobody. They weren't around. There were no guitar teachers. You couldn't take lessons. There was nothing like that, you know? When I was a kid and I had my first electric guitar, I had it tuned wrong and learned how to play on it with it tuned wrong for about a year. And I was getting somewhere on it, you know… Finally, I met a guy that knew how to tune it right and showed me three chords, and it was like a revelation. You know what I mean? It was like somebody gave me the key to heaven." He joined a band, the Chords, which mostly played big band music, and his friend Gary Foster taught him some of the rudiments of playing the guitar -- things like how to use a capo to change keys. But he was always a rebellious kid, and soon found himself faced with a choice between joining the military or going to prison. He chose the former, and it was during his time in the Army that a friend, Ron Stevenson, introduced him to the music of Merle Travis, and to Travis-style guitar picking: [Excerpt: Merle Travis, "Nine-Pound Hammer"] Garcia had never encountered playing like that before, but he instantly recognised that Travis, and Chet Atkins who Stevenson also played for him, had been an influence on Scotty Moore. He started to realise that the music he'd listened to as a teenager was influenced by music that went further back. But Stevenson, as well as teaching Garcia some of the rudiments of Travis-picking, also indirectly led to Garcia getting discharged from the Army. Stevenson was not a well man, and became suicidal. Garcia decided it was more important to keep his friend company and make sure he didn't kill himself than it was to turn up for roll call, and as a result he got discharged himself on psychiatric grounds -- according to Garcia he told the Army psychiatrist "I was involved in stuff that was more important to me in the moment than the army was and that was the reason I was late" and the psychiatrist thought it was neurotic of Garcia to have his own set of values separate from that of the Army. After discharge, Garcia did various jobs, including working as a transcriptionist for Lenny Bruce, the comedian who was a huge influence on the counterculture. In one of the various attacks over the years by authoritarians on language, Bruce was repeatedly arrested for obscenity, and in 1961 he was arrested at a jazz club in North Beach. Sixty years ago, the parts of speech that were being criminalised weren't pronouns, but prepositions and verbs: [Excerpt: Lenny Bruce, "To is a Preposition, Come is a Verb"] That piece, indeed, was so controversial that when Frank Zappa quoted part of it in a song in 1968, the record label insisted on the relevant passage being played backwards so people couldn't hear such disgusting filth: [Excerpt: The Mothers of Invention, "Harry You're a Beast"] (Anyone familiar with that song will understand that the censored portion is possibly the least offensive part of the whole thing). Bruce was facing trial, and he needed transcripts of what he had said in his recordings to present in court. Incidentally, there seems to be some confusion over exactly which of Bruce's many obscenity trials Garcia became a transcriptionist for. Dennis McNally says in his biography of the band, published in 2002, that it was the most famous of them, in autumn 1964, but in a later book, Jerry on Jerry, a book of interviews of Garcia edited by McNally, McNally talks about it being when Garcia was nineteen, which would mean it was Bruce's first trial, in 1961. We can put this down to the fact that many of the people involved, not least Garcia, lived in Tralfamadorian time, and were rather hazy on dates, but I'm placing the story here rather than in 1964 because it seems to make more sense that Garcia would be involved in a trial based on an incident in San Francisco than one in New York. Garcia got the job, even though he couldn't type, because by this point he'd spent so long listening to recordings of old folk and country music that he was used to transcribing indecipherable accents, and often, as Garcia would tell it, Bruce would mumble very fast and condense multiple syllables into one. Garcia was particularly impressed by Bruce's ability to improvise but talk in entire paragraphs, and he compared his use of language to bebop. Another thing that was starting to impress Garcia, and which he also compared to bebop, was bluegrass: [Excerpt: Bill Monroe, "Fire on the Mountain"] Bluegrass is a music that is often considered very traditional, because it's based on traditional songs and uses acoustic instruments, but in fact it was a terribly *modern* music, and largely a postwar creation of a single band -- Bill Monroe and his Blue Grass Boys. And Garcia was right when he said it was "white bebop" -- though he did say "The only thing it doesn't have is the harmonic richness of bebop. You know what I mean? That's what it's missing, but it has everything else." Both bebop and bluegrass evolved after the second world war, though they were informed by music from before it, and both prized the ability to improvise, and technical excellence. Both are musics that involved playing *fast*, in an ensemble, and being able to respond quickly to the other musicians. Both musics were also intensely rhythmic, a response to a faster paced, more stressful world. They were both part of the general change in the arts towards immediacy that we looked at in the last episode with the creation first of expressionism and then of pop art. Bluegrass didn't go into the harmonic explorations that modern jazz did, but it was absolutely as modern as anything Charlie Parker was doing, and came from the same impulses. It was tradition and innovation, the past and the future simultaneously. Bill Monroe, Jackson Pollock, Charlie Parker, Jack Kerouac, and Lenny Bruce were all in their own ways responding to the same cultural moment, and it was that which Garcia was responding to. But he didn't become able to play bluegrass until after a tragedy which shaped his life even more than his father's death had. Garcia had been to a party and was in a car with his friends Lee Adams, Paul Speegle, and Alan Trist. Adams was driving at ninety miles an hour when they hit a tight curve and crashed. Garcia, Adams, and Trist were all severely injured but survived. Speegle died. So it goes. This tragedy changed Garcia's attitudes totally. Of all his friends, Speegle was the one who was most serious about his art, and who treated it as something to work on. Garcia had always been someone who fundamentally didn't want to work or take any responsibility for anything. And he remained that way -- except for his music. Speegle's death changed Garcia's attitude to that, totally. If his friend wasn't going to be able to practice his own art any more, Garcia would practice his, in tribute to him. He resolved to become a virtuoso on guitar and banjo. His girlfriend of the time later said “I don't know if you've spent time with someone rehearsing ‘Foggy Mountain Breakdown' on a banjo for eight hours, but Jerry practiced endlessly. He really wanted to excel and be the best. He had tremendous personal ambition in the musical arena, and he wanted to master whatever he set out to explore. Then he would set another sight for himself. And practice another eight hours a day of new licks.” But of course, you can't make ensemble music on your own: [Excerpt: Jerry Garcia and Bob Hunter, "Oh Mary Don't You Weep" (including end)] "Evelyn said, “What is it called when a person needs a … person … when you want to be touched and the … two are like one thing and there isn't anything else at all anywhere?” Alicia, who had read books, thought about it. “Love,” she said at length." That's from More Than Human, by Theodore Sturgeon, a book I'll be quoting a few more times as the story goes on. Robert Hunter, like Garcia, was just out of the military -- in his case, the National Guard -- and he came into Garcia's life just after Paul Speegle had left it. Garcia and Alan Trist met Hunter ten days after the accident, and the three men started hanging out together, Trist and Hunter writing while Garcia played music. Garcia and Hunter both bonded over their shared love for the beats, and for traditional music, and the two formed a duo, Bob and Jerry, which performed together a handful of times. They started playing together, in fact, after Hunter picked up a guitar and started playing a song and halfway through Garcia took it off him and finished the song himself. The two of them learned songs from the Harry Smith Anthology -- Garcia was completely apolitical, and only once voted in his life, for Lyndon Johnson in 1964 to keep Goldwater out, and regretted even doing that, and so he didn't learn any of the more political material people like Pete Seeger, Phil Ochs, and Bob Dylan were doing at the time -- but their duo only lasted a short time because Hunter wasn't an especially good guitarist. Hunter would, though, continue to jam with Garcia and other friends, sometimes playing mandolin, while Garcia played solo gigs and with other musicians as well, playing and moving round the Bay Area and performing with whoever he could: [Excerpt: Jerry Garcia, "Railroad Bill"] "Bleshing, that was Janie's word. She said Baby told it to her. She said it meant everyone all together being something, even if they all did different things. Two arms, two legs, one body, one head, all working together, although a head can't walk and arms can't think. Lone said maybe it was a mixture of “blending” and “meshing,” but I don't think he believed that himself. It was a lot more than that." That's from More Than Human In 1961, Garcia and Hunter met another young musician, but one who was interested in a very different type of music. Phil Lesh was a serious student of modern classical music, a classically-trained violinist and trumpeter whose interest was solidly in the experimental and whose attitude can be summed up by a story that's always told about him meeting his close friend Tom Constanten for the first time. Lesh had been talking with someone about serialism, and Constanten had interrupted, saying "Music stopped being created in 1750 but it started again in 1950". Lesh just stuck out his hand, recognising a kindred spirit. Lesh and Constanten were both students of Luciano Berio, the experimental composer who created compositions for magnetic tape: [Excerpt: Luciano Berio, "Momenti"] Berio had been one of the founders of the Studio di fonologia musicale di Radio Milano, a studio for producing contemporary electronic music where John Cage had worked for a time, and he had also worked with the electronic music pioneer Karlheinz Stockhausen. Lesh would later remember being very impressed when Berio brought a tape into the classroom -- the actual multitrack tape for Stockhausen's revolutionary piece Gesang Der Juenglinge: [Excerpt: Karlheinz Stockhausen, "Gesang Der Juenglinge"] Lesh at first had been distrustful of Garcia -- Garcia was charismatic and had followers, and Lesh never liked people like that. But he was impressed by Garcia's playing, and soon realised that the two men, despite their very different musical interests, had a lot in common. Lesh was interested in the technology of music as well as in performing and composing it, and so when he wasn't studying he helped out by engineering at the university's radio station. Lesh was impressed by Garcia's playing, and suggested to the presenter of the station's folk show, the Midnight Special, that Garcia be a guest. Garcia was so good that he ended up getting an entire solo show to himself, where normally the show would feature multiple acts. Lesh and Constanten soon moved away from the Bay Area to Las Vegas, but both would be back -- in Constanten's case he would form an experimental group in San Francisco with their fellow student Steve Reich, and that group (though not with Constanten performing) would later premiere Terry Riley's In C, a piece influenced by La Monte Young and often considered one of the great masterpieces of minimalist music. By early 1962 Garcia and Hunter had formed a bluegrass band, with Garcia on guitar and banjo and Hunter on mandolin, and a rotating cast of other musicians including Ken Frankel, who played banjo and fiddle. They performed under different names, including the Tub Thumpers, the Hart Valley Drifters, and the Sleepy Valley Hog Stompers, and played a mixture of bluegrass and old-time music -- and were very careful about the distinction: [Excerpt: The Hart Valley Drifters, "Cripple Creek"] In 1993, the Republican political activist John Perry Barlow was invited to talk to the CIA about the possibilities open to them with what was then called the Information Superhighway. He later wrote, in part "They told me they'd brought Steve Jobs in a few weeks before to indoctrinate them in modern information management. And they were delighted when I returned later, bringing with me a platoon of Internet gurus, including Esther Dyson, Mitch Kapor, Tony Rutkowski, and Vint Cerf. They sealed us into an electronically impenetrable room to discuss the radical possibility that a good first step in lifting their blackout would be for the CIA to put up a Web site... We told them that information exchange was a barter system, and that to receive, one must also be willing to share. This was an alien notion to them. They weren't even willing to share information among themselves, much less the world." 1962 brought a new experience for Robert Hunter. Hunter had been recruited into taking part in psychological tests at Stanford University, which in the sixties and seventies was one of the preeminent universities for psychological experiments. As part of this, Hunter was given $140 to attend the VA hospital (where a janitor named Ken Kesey, who had himself taken part in a similar set of experiments a couple of years earlier, worked a day job while he was working on his first novel) for four weeks on the run, and take different psychedelic drugs each time, starting with LSD, so his reactions could be observed. (It was later revealed that these experiments were part of a CIA project called MKUltra, designed to investigate the possibility of using psychedelic drugs for mind control, blackmail, and torture. Hunter was quite lucky in that he was told what was going to happen to him and paid for his time. Other subjects included the unlucky customers of brothels the CIA set up as fronts -- they dosed the customers' drinks and observed them through two-way mirrors. Some of their experimental subjects died by suicide as a result of their experiences. So it goes. ) Hunter was interested in taking LSD after reading Aldous Huxley's writings about psychedelic substances, and he brought his typewriter along to the experiment. During the first test, he wrote a six-page text, a short excerpt from which is now widely quoted, reading in part "Sit back picture yourself swooping up a shell of purple with foam crests of crystal drops soft nigh they fall unto the sea of morning creep-very-softly mist ... and then sort of cascade tinkley-bell-like (must I take you by the hand, ever so slowly type) and then conglomerate suddenly into a peal of silver vibrant uncomprehendingly, blood singingly, joyously resounding bells" Hunter's experience led to everyone in their social circle wanting to try LSD, and soon they'd all come to the same conclusion -- this was something special. But Garcia needed money -- he'd got his girlfriend pregnant, and they'd married (this would be the first of several marriages in Garcia's life, and I won't be covering them all -- at Garcia's funeral, his second wife, Carolyn, said Garcia always called her the love of his life, and his first wife and his early-sixties girlfriend who he proposed to again in the nineties both simultaneously said "He said that to me!"). So he started teaching guitar at a music shop in Palo Alto. Hunter had no time for Garcia's incipient domesticity and thought that his wife was trying to make him live a conventional life, and the two drifted apart somewhat, though they'd still play together occasionally. Through working at the music store, Garcia got to know the manager, Troy Weidenheimer, who had a rock and roll band called the Zodiacs. Garcia joined the band on bass, despite that not being his instrument. He later said "Troy was a lot of fun, but I wasn't good enough a musician then to have been able to deal with it. I was out of my idiom, really, 'cause when I played with Troy I was playing electric bass, you know. I never was a good bass player. Sometimes I was playing in the wrong key and didn't even [fuckin'] know it. I couldn't hear that low, after playing banjo, you know, and going to electric...But Troy taught me the principle of, hey, you know, just stomp your foot and get on it. He was great. A great one for the instant arrangement, you know. And he was also fearless for that thing of get your friends to do it." Garcia's tenure in the Zodiacs didn't last long, nor did this experiment with rock and roll, but two other members of the Zodiacs will be notable later in the story -- the harmonica player, an old friend of Garcia's named Ron McKernan, who would soon gain the nickname Pig Pen after the Peanuts character, and the drummer, Bill Kreutzmann: [Excerpt: The Grateful Dead, "Drums/Space (Skull & Bones version)"] Kreutzmann said of the Zodiacs "Jerry was the hired bass player and I was the hired drummer. I only remember playing that one gig with them, but I was in way over my head. I always did that. I always played things that were really hard and it didn't matter. I just went for it." Garcia and Kreutzmann didn't really get to know each other then, but Garcia did get to know someone else who would soon be very important in his life. Bob Weir was from a very different background than Garcia, though both had the shared experience of long bouts of chronic illness as children. He had grown up in a very wealthy family, and had always been well-liked, but he was what we would now call neurodivergent -- reading books about the band he talks about being dyslexic but clearly has other undiagnosed neurodivergences, which often go along with dyslexia -- and as a result he was deemed to have behavioural problems which led to him getting expelled from pre-school and kicked out of the cub scouts. He was never academically gifted, thanks to his dyslexia, but he was always enthusiastic about music -- to a fault. He learned to play boogie piano but played so loudly and so often his parents sold the piano. He had a trumpet, but the neighbours complained about him playing it outside. Finally he switched to the guitar, an instrument with which it is of course impossible to make too loud a noise. The first song he learned was the Kingston Trio's version of an old sea shanty, "The Wreck of the John B": [Excerpt: The Kingston Trio, "The Wreck of the John B"] He was sent off to a private school in Colorado for teenagers with behavioural issues, and there he met the boy who would become his lifelong friend, John Perry Barlow. Unfortunately the two troublemakers got on with each other *so* well that after their first year they were told that it was too disruptive having both of them at the school, and only one could stay there the next year. Barlow stayed and Weir moved back to the Bay Area. By this point, Weir was getting more interested in folk music that went beyond the commercial folk of the Kingston Trio. As he said later "There was something in there that was ringing my bells. What I had grown up thinking of as hillbilly music, it started to have some depth for me, and I could start to hear the music in it. Suddenly, it wasn't just a bunch of ignorant hillbillies playing what they could. There was some depth and expertise and stuff like that to aspire to.” He moved from school to school but one thing that stayed with him was his love of playing guitar, and he started taking lessons from Troy Weidenheimer, but he got most of his education going to folk clubs and hootenannies. He regularly went to the Tangent, a club where Garcia played, but Garcia's bluegrass banjo playing was far too rigorous for a free spirit like Weir to emulate, and instead he started trying to copy one of the guitarists who was a regular there, Jorma Kaukonnen. On New Year's Eve 1963 Weir was out walking with his friends Bob Matthews and Rich Macauley, and they passed the music shop where Garcia was a teacher, and heard him playing his banjo. They knocked and asked if they could come in -- they all knew Garcia a little, and Bob Matthews was one of his students, having become interested in playing banjo after hearing the theme tune to the Beverly Hillbillies, played by the bluegrass greats Flatt and Scruggs: [Excerpt: Flatt and Scruggs, "The Beverly Hillbillies"] Garcia at first told these kids, several years younger than him, that they couldn't come in -- he was waiting for his students to show up. But Weir said “Jerry, listen, it's seven-thirty on New Year's Eve, and I don't think you're going to be seeing your students tonight.” Garcia realised the wisdom of this, and invited the teenagers in to jam with him. At the time, there was a bit of a renaissance in jug bands, as we talked about back in the episode on the Lovin' Spoonful. This was a form of music that had grown up in the 1920s, and was similar and related to skiffle and coffee-pot bands -- jug bands would tend to have a mixture of portable string instruments like guitars and banjos, harmonicas, and people using improvised instruments, particularly blowing into a jug. The most popular of these bands had been Gus Cannon's Jug Stompers, led by banjo player Gus Cannon and with harmonica player Noah Lewis: [Excerpt: Gus Cannon's Jug Stompers, "Viola Lee Blues"] With the folk revival, Cannon's work had become well-known again. The Rooftop Singers, a Kingston Trio style folk group, had had a hit with his song "Walk Right In" in 1963, and as a result of that success Cannon had even signed a record contract with Stax -- Stax's first album ever, a month before Booker T and the MGs' first album, was in fact the eighty-year-old Cannon playing his banjo and singing his old songs. The rediscovery of Cannon had started a craze for jug bands, and the most popular of the new jug bands was Jim Kweskin's Jug Band, which did a mixture of old songs like "You're a Viper" and more recent material redone in the old style. Weir, Matthews, and Macauley had been to see the Kweskin band the night before, and had been very impressed, especially by their singer Maria D'Amato -- who would later marry her bandmate Geoff Muldaur and take his name -- and her performance of Leiber and Stoller's "I'm a Woman": [Excerpt: Jim Kweskin's Jug Band, "I'm a Woman"] Matthews suggested that they form their own jug band, and Garcia eagerly agreed -- though Matthews found himself rapidly moving from banjo to washboard to kazoo to second kazoo before realising he was surplus to requirements. Robert Hunter was similarly an early member but claimed he "didn't have the embouchure" to play the jug, and was soon also out. He moved to LA and started studying Scientology -- later claiming that he wanted science-fictional magic powers, which L. Ron Hubbard's new religion certainly offered. The group took the name Mother McRee's Uptown Jug Champions -- apparently they varied the spelling every time they played -- and had a rotating membership that at one time or another included about twenty different people, but tended always to have Garcia on banjo, Weir on jug and later guitar, and Garcia's friend Pig Pen on harmonica: [Excerpt: Mother McRee's Uptown Jug Champions, "On the Road Again"] The group played quite regularly in early 1964, but Garcia's first love was still bluegrass, and he was trying to build an audience with his bluegrass band, The Black Mountain Boys. But bluegrass was very unpopular in the Bay Area, where it was simultaneously thought of as unsophisticated -- as "hillbilly music" -- and as elitist, because it required actual instrumental ability, which wasn't in any great supply in the amateur folk scene. But instrumental ability was something Garcia definitely had, as at this point he was still practising eight hours a day, every day, and it shows on the recordings of the Black Mountain Boys: [Excerpt: The Black Mountain Boys, "Rosa Lee McFall"] By the summer, Bob Weir was also working at the music shop, and so Garcia let Weir take over his students while he and the Black Mountain Boys' guitarist Sandy Rothman went on a road trip to see as many bluegrass musicians as they could and to audition for Bill Monroe himself. As it happened, Garcia found himself too shy to audition for Monroe, but Rothman later ended up playing with Monroe's Blue Grass Boys. On his return to the Bay Area, Garcia resumed playing with the Uptown Jug Champions, but Pig Pen started pestering him to do something different. While both men had overlapping tastes in music and a love for the blues, Garcia's tastes had always been towards the country end of the spectrum while Pig Pen's were towards R&B. And while the Uptown Jug Champions were all a bit disdainful of the Beatles at first -- apart from Bob Weir, the youngest of the group, who thought they were interesting -- Pig Pen had become enamoured of another British band who were just starting to make it big: [Excerpt: The Rolling Stones, "Not Fade Away"] 29) Garcia liked the first Rolling Stones album too, and he eventually took Pig Pen's point -- the stuff that the Rolling Stones were doing, covers of Slim Harpo and Buddy Holly, was not a million miles away from the material they were doing as Mother McRee's Uptown Jug Champions. Pig Pen could play a little electric organ, Bob had been fooling around with the electric guitars in the music shop. Why not give it a go? The stuff bands like the Rolling Stones were doing wasn't that different from the electric blues that Pig Pen liked, and they'd all seen A Hard Day's Night -- they could carry on playing with banjos, jugs, and kazoos and have the respect of a handful of folkies, or they could get electric instruments and potentially have screaming girls and millions of dollars, while playing the same songs. This was a convincing argument, especially when Dana Morgan Jr, the son of the owner of the music shop, told them they could have free electric instruments if they let him join on bass. Morgan wasn't that great on bass, but what the hell, free instruments. Pig Pen had the best voice and stage presence, so he became the frontman of the new group, singing most of the leads, though Jerry and Bob would both sing a few songs, and playing harmonica and organ. Weir was on rhythm guitar, and Garcia was the lead guitarist and obvious leader of the group. They just needed a drummer, and handily Bill Kreutzmann, who had played with Garcia and Pig Pen in the Zodiacs, was also now teaching music at the music shop. Not only that, but about three weeks before they decided to go electric, Kreutzmann had seen the Uptown Jug Champions performing and been astonished by Garcia's musicianship and charisma, and said to himself "Man, I'm gonna follow that guy forever!" The new group named themselves the Warlocks, and started rehearsing in earnest. Around this time, Garcia also finally managed to get some of the LSD that his friend Robert Hunter had been so enthusiastic about three years earlier, and it was a life-changing experience for him. In particular, he credited LSD with making him comfortable being a less disciplined player -- as a bluegrass player he'd had to be frighteningly precise, but now he was playing rock and needed to loosen up. A few days after taking LSD for the first time, Garcia also heard some of Bob Dylan's new material, and realised that the folk singer he'd had little time for with his preachy politics was now making electric music that owed a lot more to the Beat culture Garcia considered himself part of: [Excerpt: Bob Dylan, "Subterranean Homesick Blues"] Another person who was hugely affected by hearing that was Phil Lesh, who later said "I couldn't believe that was Bob Dylan on AM radio, with an electric band. It changed my whole consciousness: if something like that could happen, the sky was the limit." Up to that point, Lesh had been focused entirely on his avant-garde music, working with friends like Steve Reich to push music forward, inspired by people like John Cage and La Monte Young, but now he realised there was music of value in the rock world. He'd quickly started going to rock gigs, seeing the Rolling Stones and the Byrds, and then he took acid and went to see his friend Garcia's new electric band play their third ever gig. He was blown away, and very quickly it was decided that Lesh would be the group's new bass player -- though everyone involved tells a different story as to who made the decision and how it came about, and accounts also vary as to whether Dana Morgan took his sacking gracefully and let his erstwhile bandmates keep their instruments, or whether they had to scrounge up some new ones. Lesh had never played bass before, but he was a talented multi-instrumentalist with a deep understanding of music and an ability to compose and improvise, and the repertoire the Warlocks were playing in the early days was mostly three-chord material that doesn't take much rehearsal -- though it was apparently beyond the abilities of poor Dana Morgan, who apparently had to be told note-by-note what to play by Garcia, and learn it by rote. Garcia told Lesh what notes the strings of a bass were tuned to, told him to borrow a guitar and practice, and within two weeks he was on stage with the Warlocks: [Excerpt: The Grateful Dead, “Grayfolded"] In September 1995, just weeks after Jerry Garcia's death, an article was published in Mute magazine identifying a cultural trend that had shaped the nineties, and would as it turned out shape at least the next thirty years. It's titled "The Californian Ideology", though it may be better titled "The Bay Area Ideology", and it identifies a worldview that had grown up in Silicon Valley, based around the ideas of the hippie movement, of right-wing libertarianism, of science fiction authors, and of Marshall McLuhan. It starts "There is an emerging global orthodoxy concerning the relation between society, technology and politics. We have called this orthodoxy `the Californian Ideology' in honour of the state where it originated. By naturalising and giving a technological proof to a libertarian political philosophy, and therefore foreclosing on alternative futures, the Californian Ideologues are able to assert that social and political debates about the future have now become meaningless. The California Ideology is a mix of cybernetics, free market economics, and counter-culture libertarianism and is promulgated by magazines such as WIRED and MONDO 2000 and preached in the books of Stewart Brand, Kevin Kelly and others. The new faith has been embraced by computer nerds, slacker students, 30-something capitalists, hip academics, futurist bureaucrats and even the President of the USA himself. As usual, Europeans have not been slow to copy the latest fashion from America. While a recent EU report recommended adopting the Californian free enterprise model to build the 'infobahn', cutting-edge artists and academics have been championing the 'post-human' philosophy developed by the West Coast's Extropian cult. With no obvious opponents, the global dominance of the Californian ideology appears to be complete." [Excerpt: Grayfolded] The Warlocks' first gig with Phil Lesh on bass was on June the 18th 1965, at a club called Frenchy's with a teenage clientele. Lesh thought his playing had been wooden and it wasn't a good gig, and apparently the management of Frenchy's agreed -- they were meant to play a second night there, but turned up to be told they'd been replaced by a band with an accordion and clarinet. But by September the group had managed to get themselves a residency at a small bar named the In Room, and playing there every night made them cohere. They were at this point playing the kind of sets that bar bands everywhere play to this day, though at the time the songs they were playing, like "Gloria" by Them and "In the Midnight Hour", were the most contemporary of hits. Another song that they introduced into their repertoire was "Do You Believe in Magic" by the Lovin' Spoonful, another band which had grown up out of former jug band musicians. As well as playing their own sets, they were also the house band at The In Room and as such had to back various touring artists who were the headline acts. The first act they had to back up was Cornell Gunter's version of the Coasters. Gunter had brought his own guitarist along as musical director, and for the first show Weir sat in the audience watching the show and learning the parts, staring intently at this musical director's playing. After seeing that, Weir's playing was changed, because he also picked up how the guitarist was guiding the band while playing, the small cues that a musical director will use to steer the musicians in the right direction. Weir started doing these things himself when he was singing lead -- Pig Pen was the frontman but everyone except Bill sang sometimes -- and the group soon found that rather than Garcia being the sole leader, now whoever was the lead singer for the song was the de facto conductor as well. By this point, the Bay Area was getting almost overrun with people forming electric guitar bands, as every major urban area in America was. Some of the bands were even having hits already -- We Five had had a number three hit with "You Were On My Mind", a song which had originally been performed by the folk duo Ian and Sylvia: [Excerpt: We Five, "You Were On My Mind"] Although the band that was most highly regarded on the scene, the Charlatans, was having problems with the various record companies they tried to get signed to, and didn't end up making a record until 1969. If tracks like "Number One" had been released in 1965 when they were recorded, the history of the San Francisco music scene may have taken a very different turn: [Excerpt: The Charlatans, "Number One"] Bands like Jefferson Airplane, the Great Society, and Big Brother and the Holding Company were also forming, and Autumn Records was having a run of success with records by the Beau Brummels, whose records were produced by Autumn's in-house A&R man, Sly Stone: [Excerpt: The Beau Brummels, "Laugh Laugh"] The Warlocks were somewhat cut off from this, playing in a dive bar whose clientele was mostly depressed alcoholics. But the fact that they were playing every night for an audience that didn't care much gave them freedom, and they used that freedom to improvise. Both Lesh and Garcia were big fans of John Coltrane, and they started to take lessons from his style of playing. When the group played "Gloria" or "Midnight Hour" or whatever, they started to extend the songs and give themselves long instrumental passages for soloing. Garcia's playing wasn't influenced *harmonically* by Coltrane -- in fact Garcia was always a rather harmonically simple player. He'd tend to play lead lines either in Mixolydian mode, which is one of the most standard modes in rock, pop, blues, and jazz, or he'd play the notes of the chord that was being played, so if the band were playing a G chord his lead would emphasise the notes G, B, and D. But what he was influenced by was Coltrane's tendency to improvise in long, complex, phrases that made up a single thought -- Coltrane was thinking musically in paragraphs, rather than sentences, and Garcia started to try the same kind of th

Picture of the Week. Google & Passkeys. TP-Link routers DO auto-update. US Marshals Service: Where's the backup?? T-Mobile keeps getting breached. Chrome: No more LOCK icon. Apple's new "Rapid Security Response" system. Elon Musk, making friends wherever he goes... A quick Mastodon aside. Here come the fake AI-generated "news" sites. Russia to replace "American" TCP/IP with "Russian Internet". Vint Serf's 3 mistakes. Detecting Unwanted Location Trackers. Show Notes: https://www.grc.com/sn/SN-922-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to this show at https://twit.tv/shows/security-now. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can submit a question to Security Now! at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Sponsor: kolide.com/securitynow

Picture of the Week. Google & Passkeys. TP-Link routers DO auto-update. US Marshals Service: Where's the backup?? T-Mobile keeps getting breached. Chrome: No more LOCK icon. Apple's new "Rapid Security Response" system. Elon Musk, making friends wherever he goes... A quick Mastodon aside. Here come the fake AI-generated "news" sites. Russia to replace "American" TCP/IP with "Russian Internet". Vint Serf's 3 mistakes. Detecting Unwanted Location Trackers. Show Notes: https://www.grc.com/sn/SN-922-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to this show at https://twit.tv/shows/security-now. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can submit a question to Security Now! at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Sponsor: kolide.com/securitynow

Picture of the Week. Google & Passkeys. TP-Link routers DO auto-update. US Marshals Service: Where's the backup?? T-Mobile keeps getting breached. Chrome: No more LOCK icon. Apple's new "Rapid Security Response" system. Elon Musk, making friends wherever he goes... A quick Mastodon aside. Here come the fake AI-generated "news" sites. Russia to replace "American" TCP/IP with "Russian Internet". Vint Serf's 3 mistakes. Detecting Unwanted Location Trackers. Show Notes: https://www.grc.com/sn/SN-922-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to this show at https://twit.tv/shows/security-now. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can submit a question to Security Now! at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Sponsor: kolide.com/securitynow

Picture of the Week. Google & Passkeys. TP-Link routers DO auto-update. US Marshals Service: Where's the backup?? T-Mobile keeps getting breached. Chrome: No more LOCK icon. Apple's new "Rapid Security Response" system. Elon Musk, making friends wherever he goes... A quick Mastodon aside. Here come the fake AI-generated "news" sites. Russia to replace "American" TCP/IP with "Russian Internet". Vint Serf's 3 mistakes. Detecting Unwanted Location Trackers. Show Notes: https://www.grc.com/sn/SN-922-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to this show at https://twit.tv/shows/security-now. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can submit a question to Security Now! at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Sponsor: kolide.com/securitynow

Bugün 21.yy'a dönüyoruz. Bir yandan İnterneti katman katman inşa ederken, bir yandan da güvenlik boyutundaki kedi-fare oyunlarına bakacağız. Bölüm bittiğinde TCP/IP, DNS, VPN, TOR gibi kısaltmalardan artık korkmayacaksınız.Tüm kaynaklar ve referanslar aşağıda. Hepinize ve Patreonculara teşekkürler..Bu podcast, Cambly hakkında reklam içerir.Cambly'nin %60 indirimden 6fular koduyla yararlanmak için aşağıdaki linke tıklayın.https://cambly.biz/6fularCambly Kids'in %60 indiriminden 6fularkids koduyla yararlanmak için ise aşağıdaki linke tıklayın.https://cambly.biz/6fularkidsBölümler:(00:05) Telgraf: İlk standardın sebebi.(02:32) IP: Sanal posta.(03:30) VPN: Geoblocking'i nasıl önlüyor.(05:07) IP yasakları: Neden işe yaramaz.(06:40) CDN: İçerik dağıtım ağları.(07:35) NAT: Adres israfı ve anonimlik(11:47) DNS: Daha kolay sansür.(14:43) Port: Sanal bağlantı noktaları.(16:00) TCP: İnternetin Ulaştırma Bakanlığı.(17:40) Vint Cerf: İnternetin babası.(19:20) Servis sağlayıcının ekonomik çıkarı(20:30) Son katman: Uygulama.(22:15) DPI: Derin Paket Analizi maceralarım.(25:30) VPN güvenlik sağlar mı?(29:15) TOR: Kimse beni görmesin.(30:40) Gelecek bölüm için 3 soru.(32:33) Patreon teşekkürleri..Kaynaklar:Video: What's TCP/IPYazı: Where did all the IPs go?Video: Cerf and Kahn: Inventors of the InternetYazı: China DNS interceptionYazı: Configure DoHSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In the third episode of this mini-series on the Future of Technology, we will hear from Vint Cerf, Vice President & Chief Internet Evangelist at GOOGLE, and widely known as one of the “Fathers of the Internet,” and Alexandre Blais, Professor & Scientific Director of the Quantum Institute at UNIVERSITÉ DE SHERBROOKE. Vint and Alexandre will walk us through the challenges and opportunities that Quantum Learning presents. They will define Quantum Learning and explore: how can its development impact society as a whole? What are the challenges of making Quantum Machine Learning (QML) a reality? Vinton G. Cerf, Vice President & Chief Internet Evangelist, GOOGLEIn this role, he is responsible for identifying new enabling technologies to support the development of advanced, Internet-based products and services from Google. He is also an active public face for Google in the Internet world.Widely known as one of the “Fathers of the Internet,” Cerf is the co-designer of the TCP/IP protocols and the architecture of the Internet. In December 1997, President Clinton presented the U.S. National Medal of Technology to Cerf and his colleague, Robert E. Kahn, for founding and developing the Internet. Kahn and Cerf were named the recipients of the ACM Alan M. Turing award in 2004 for their work on the Internet protocols. In November 2005, President George Bush awarded Cerf and Kahn the Presidential Medal of Freedom for their work. The medal is the highest civilian award given by the United States to its citizens. In April 2008, Cerf and Kahn received the prestigious Japan Prize.Cerf is a recipient of numerous awards and commendations in connection with his work on the Internet.Cerf holds a Bachelor of Science degree in Mathematics from Stanford University and Master of Science and Ph.D. degrees in Computer Science from UCLA.Prof. Alexandre Blais, Physics Professor & Scientific Director of the Quantum Institute, UNIVERSITÉ DE SHERBROOKEAlexandre Blais is a professor of physics at the Université de Sherbrooke and Scientific Director of the Institut quantique at the same institution. His research focusses on superconducting quantum circuits for quantum information processing and microwave quantum optics. After completing a PhD at the Université de Sherbrooke in 2002, he was a postdoc at Yale University from 2003 to 2005 where he participated in the development of circuit quantum electrodynamics, a leading quantum computer architecture. Since then, his theoretical work as continued to have an impact in academic and industrial laboratories worldwide. Alexandre is a Fellow of the American Physical Society, a Guggenheim Fellow of the John Simon Guggenheim Memorial Foundation, a member of CIFAR's Quantum Information Science program and of the College of the Royal Society of Canada. His research contributions have earned him a number of academic awards, including NSERC's Doctoral Prize, NSERC's Steacie Prize, the Canadian Association of Physicists' Herzberg and Brockhouse Medals, the Prix Urgel-Archambault from the Association francophone pour le savoir, the Rutherford Memorial Medal of the Royal Society of Canada,  as well as a teaching award from the Université de Sherbrooke.Thanks for listening! Please be sure to check us out at www.eaccny.com or email membership@eaccny.com to learn more!

1. HOY… Elon Musk y la oleada de tweets en la sección 'Para ti' de Twitter: ¿Qué está sucediendo?"2. Además… "Apple vs. Hackers: ¡La Batalla por la Seguridad de los Dispositivos!3. Y también… Vint Cerf, el padre del internet, advierte sobre el riesgo de invertir en chatbots de AI.4. Y para terminar…: El departamento de Defensa sin infraestructura para controlar el uso seguro de smartphones en el trabajoTodo esto y más en el podcast del día de hoy…Yo soy LuisGyG, y sin más preámbulos… comenzamos.

Today's fourth Christmas guest editor this year is Sir Jeremy Fleming, director of GCHQ, the UK's largest but probably least known intelligence agency. Hear highlights from his programme which centres on the theme of data and trust, including how we all share our own personal information and how intelligence agencies across the world handle that data. Guests include Avril Haines, the United States director of national intelligence, Vint Cerf, one of the founding fathers of the internet, and multiple Olympic champion Sir Ben Ainslie, who discusses the use of data in his sport of sailing.

Thanks to the internet, today's world is more connected than ever. Communication is as simple as sending an email, home goods can be ordered to your door at the press of a button, and online communities have brought us closer together.   But it wasn't always that way. It took many years, extensive research, and brilliant leaders behind it's creation. Vint Cerf, one of the “Fathers of the Internet” helped to connect the first nodes that made the modern internet possible. For his achievements, Vint has been awarded the National Medal of Technology, the Turing Award, and the Presidential Medal of Freedom, among many more honors.   Today on Celebrations Chatter, Vint shares forward his insights on how the internet became what it is today, and where the ever-evolving technology is going.   New podcast episodes released weekly on Thursday. Follow along with the links below: Sign up for the Celebrations Chatter Newsletter: https://celebrationschatter.beehiiv.com/    Subscribe to Celebrations Chatter on YouTube: https://www.youtube.com/@celebrationschatter  Follow @CelebrationsChatter on Instagram: https://www.instagram.com/celebrationschatter/    Follow @CelebrationsChatter on Threads: https://www.threads.net/@celebrationschatter  Listen to more episodes of Celebrations Chatter on Apple Podcasts:  https://podcasts.apple.com/us/podcast/celebrations-chatter-with-jim-mccann/id1616689192    Listen to more episodes of Celebrations Chatter on Spotify: https://open.spotify.com/episode/5Yxfvb4qHGCwR5IgAmgCQX?si=ipuQC3-ATbKyqIk6RtPb-A    Listen to more episodes of Celebrations Chatter on Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5saWJzeW4uY29tLzQwMzU0MS9yc3M?sa=X&ved=0CAMQ4aUDahcKEwio9KT_xJuBAxUAAAAAHQAAAAAQNg  Visit 1-800-Flowers.com: https://www.1800flowers.com/    Visit the 1-800-Flowers.com YouTube Channel: https://www.youtube.com/@1800flowers  Follow Jim McCann on LinkedIn: https://www.linkedin.com/in/jim1800flowers/  Follow Jim McCann on X / Twitter: https://twitter.com/jim1800flowers (@Jim1800Flowers)

In this episode of Partnering Leadership, Mahan Tavakoli speaks with Gary Bolles, chair for the Future of Work for Singularity University, co-founder of eParachute.com, and author of The Next Rules of Work. Gary Bolles shares how his father's career advice book What Color Is Your Parachute impacted his early life and how he has gone through continual reinvention while guiding leaders through ongoing disruption. Gary Bolles also shares insights from his book The Next Rules of Work. Some highlights:- How Gary Bolles father's book What Color Is Your Parachute impacted his life- The ‘leader's dilemma,' how it manifests in times of disruptive change, and how to overcome it- Gary Bolles on how to foster a growth mindset within an organization- Embracing change and promoting diversity in organizations- What flex skills are and their importance in the future of work- Gary Bolles on the future of leadership and work- A framework for leaders in leading their teams and organizations forward Mentioned:-Richard Nelson Bolles, Gary Bolles' father and author of What Color Is Your Parachute?-Jeffrey S. Moore, university teacher, and researcher-John Hagel, author-Carol Dweck, psychologist and author-Sidney Fine, professor, and author-Vint Cerf, developer and internet pioneer-Esther Wojcicki, author of Moonshots in Education-The Five Temptations of a CEO by Patrick Lencioni Connect with Gary Bolles:The Next Rules of Work on AmazonGary Bolles' WebsiteFuture of Work on Singularity Hub WebsiteeParachute WebsiteGary Bolles on LinkedInGary Bolles on Twitter Connect with Mahan Tavakoli:MahanTavakoli.com More information and resources available at the Partnering Leadership Podcast website: PartneringLeadership.com