Podcasts about sk hynix

Un ataque ejecutado por agentes de IA compromete la infraestructura de Hugging Face y deja una lección incómoda: en plena respuesta a incidentes, los modelos comerciales pueden negarse a analizar las pruebas. Además, Alibaba presenta Qwen 3.8 Max con 2,4 billones de parámetros; el Parlamento Europeo prepara una plataforma multimodelo para sus equipos; SK Hynix alerta de una escasez de memoria que podría empeorar en 2027; y científicos recrean polvo cósmico en el laboratorio para estudiar el origen de compuestos orgánicos.Puedes seguirnos en YouTube en https://youtube.com/olivernabani y puedes unirte al Discord Mashain en https://olivernabani.com/discord

Semiconductor stocks have plunged more than 20% from their recent highs, officially entering bear market territory after China's Moonshot launched its Kimi K3 model sparking fears of intensifying global competition. Amid rising concerns over stretched valuations, geopolitical risks, and a critical earnings week ahead – including reports from Alphabet, SK Hynix, and Tesla – markets stand at a crossroads. Mensur Pocinci, Head of Technical Analysis, explains why the long-term uptrend of semiconductors remains intact despite the sell-off and what this means for broader equity markets.(00:00) - Introduction: Lucija Caculovic, Product & Investment Content (00:38) - Markets wrap-up: Jan Bopp, Product & Investment Content (06:38) - Technical Analysis update: Mensur Pocinci, Head of Technical Analysis (09:13) - Closing remarks: Lucija Caculovic, Product & Investment Content Would you like to support this show? Please leave us a review and star rating on Apple Podcasts, Spotify or wherever you get your podcasts.

Depuis l'automne dernier, le prix de la mémoire vive ne grimpe plus : il s'envole. Les fabricants répètent que cette tension restera temporaire, le temps d'ouvrir de nouvelles usines. Mais une analyse de Bank of America, relayée le 12 juillet par le quotidien taïwanais Commercial Times, fragilise ce discours. Elle paraît alors que Samsung, SK Hynix et Micron sont visés en Californie par une plainte collective les accusant d'avoir organisé cette rareté.La Corée du Sud affiche ses ambitions. Le président Lee Jae-myung veut doubler les capacités nationales d'ici 2030, notamment grâce aux mégasites de Samsung à Gwangju et de SK Hynix dans le Jeolla. Bank of America estime qu'après déduction des anciennes lignes arrêtées pour modernisation, la capacité coréenne en wafers (les plaques de silicium servant à fabriquer les puces) progresserait de moins de 10 % par an.Un professionnel taïwanais affirme que SK Hynix ne mettrait en service qu'un sixième des ajouts prévus d'ici 2028. Construire une usine de semi-conducteurs exige du temps : cinq ans pour les fondations, trois à quatre années supplémentaires pour les salles blanches et les machines, puis près d'une décennie pour l'écosystème complet. Le patron de SK Hynix prévient d'ailleurs que 2027 sera la pire année de l'histoire du secteur. La plainte déposée le 25 juin accuse les trois groupes d'avoir profité du basculement vers la HBM, une mémoire empilée indispensable aux accélérateurs d'intelligence artificielle, pour réduire l'offre de DDR4 et de DDR5. Chaque bit de HBM mobilise environ trois fois plus de silicium qu'un bit de DDR5 : produire davantage pour l'IA signifie fabriquer moins pour le grand public.Les plaignants évoquent une hausse de la DRAM d'environ 700 % en quatre ans. Ils devront prouver une coordination, une procédure comparable ayant échoué en 2018. Le passé nourrit les soupçons : Samsung et Hynix avaient déjà été sanctionnés pour entente dans les années 2000. En France, un kit de 32 gigaoctets de DDR5-6000 est passé d'environ 75 euros à l'été 2025 à près de 300 euros en juin. Les projections annoncent encore deux fortes hausses successives, sans répit avant 2028. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

South Korea has the best performing stock market in the world for the second year running — and it's also in the middle of one of the worst bear markets on earth. The KOSPI is down around 27% from its June peak, more than 1.2 million retail accounts have been hit with margin calls, and hundreds of thousands of Korean investors have been wiped out entirely. But this isn't a story about meme stocks or worthless companies. Samsung Electronics and SK Hynix are enormously profitable businesses at the center of the global AI boom, and the traders buying them were right about the trend. In this video I look at how a national stock index became a two-stock bet on artificial intelligence, how single-stock leveraged ETFs turned ordinary volatility into a mechanical feedback loop, why Korea's retail "ants" took on so much leverage in the first place, and what Victor Haghani's famous biased-coin experiment tells us about how you can be completely right about a market and still lose everything.Patrick's Books:Statistics For The Trading Floor: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://amzn.to/3eerLA0⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Derivatives For The Trading Floor: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ https://amzn.to/3cjsyPF⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Corporate Finance: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://amzn.to/3fn3rvC ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ways To Support The Channel:Patreon: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/PatrickBoyleOnFinance⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Buy Me a Coffee: https://www.buymeacoffee.com/patrickboyle

  What Does This Week’s Market Volatility Mean for Your Retirement Portfolio? By Tom Dupree, Founder, Dupree Financial Group Inflation cooled. The big banks beat expectations. And somehow, it was still a wild week in the market. If you’ve been watching your account balance bounce around and wondering whether any of it has anything to do with the actual value of what you own, here’s the short answer: usually not. Most of what moved the market this week wasn’t new information about businesses — it was leverage, technical trading, and forced selling. That distinction matters more for your retirement than almost anything else you’ll read this month, because it tells you when to act and when to simply hold on. This week’s episode of The Tom Dupree Show walked through four separate stories — cooling inflation, strong bank earnings, a leveraged-ETF blowup on the other side of the world, and a regulatory fight over how often companies should report earnings — that all point to the same lesson: know what you own, know why the price is moving, and don’t confuse someone else’s forced selling with your own emergency. Key Takeaways Inflation cooled to 3.5% year-over-year in June, but the Fed’s new chair has questioned whether the 2% target is even the right one — the ground rules for bonds and rate-sensitive investments could shift. Bank profits this quarter came mostly from paying less on deposits, not from a borrowing boom — a reminder that cash flow, not headlines, tells the real story. A leveraged single-stock ETF collapse in South Korea forced hundreds of thousands of retail accounts into liquidation — a case study in what daily-compounding leverage does to a portfolio. Semiconductor stocks have swung hard on technical signals, not fundamentals — which can create real opportunity for patient, long-term owners. A federal proposal to let companies report earnings twice a year instead of four times has reignited a real debate about transparency versus short-termism. Why Does the Market Feel So Unpredictable Right Now? If you’re 55, 65, or 75 and watching a retirement account that’s supposed to fund the next 30 or 40 years of your life, a week like this one is unsettling. The headlines contradict each other: inflation is cooling, but chip stocks are getting hammered one day and ripping higher the next. Banks are thriving, but somewhere on the other side of the world, hundreds of thousands of retail investors just lost their entire trading accounts overnight. It’s a lot to hold at once, and it’s reasonable to wonder whether any of it should change what you do with your own money. Here’s the honest answer: for most retirees holding a diversified, income-producing portfolio, almost none of it should. But understanding why requires pulling apart what actually happened this week — and separating the noise from the signal. What Actually Happened This Week — The Data Start with the good news. The Bureau of Labor Statistics reported that headline inflation cooled to 3.5% year-over-year in June, with core inflation (which strips out food and energy) coming in at 2.6% — both below what economists expected, and producer prices actually declined for the month. That’s a meaningfully better inflation picture than markets were braced for. But the Fed’s target isn’t necessarily fixed anymore. Kevin Warsh, who was sworn in as Federal Reserve chairman this spring, has openly questioned the assumptions behind the central bank’s longstanding 2% inflation goal and launched a broader review of how the Fed operates. For retirees who own bonds or rate-sensitive income investments, that’s not a footnote — it’s a reason to pay attention to what “the target” even means over the next few years, rather than assuming the old rules still apply. Meanwhile, bank earnings came in strong — but not for the reason most people assume. The lift came primarily from banks paying less to fund themselves (short-term deposit rates have fallen faster than the loans on their books have repriced), not from a fresh wave of borrowing. It’s a good environment for financial stocks, but it’s a funding-cost story more than a booming-economy story, and that distinction matters if you’re trying to judge whether the rally has legs. Then there’s the semiconductor sector, which has been the market’s most volatile corner. Taiwan Semiconductor, the company that manufactures the vast majority of the world’s advanced AI chips, reported June revenue up nearly 68% year-over-year, a genuinely extraordinary number driven by AI infrastructure demand. And yet chip stocks broadly have been whipping up and down for reasons that have very little to do with numbers like that one. A lot of that action is technical: when a stock breaks below a widely watched moving average, institutional trading algorithms are programmed to sell, regardless of what the underlying business is doing. That selling then triggers more selling. It looks like panic. It’s often just mechanics. The starkest illustration of what leverage does in a downturn came out of South Korea this month, where a wave of new single-stock leveraged ETFs tied to semiconductor giants Samsung and SK Hynix triggered margin calls on more than 1.2 million retail trading accounts, with roughly 320,000 to 360,000 of those accounts fully liquidated in a matter of days. These products were designed to move twice the daily price swing of a single stock — which sounds appealing on the way up and is devastating on the way down, because the losses compound daily rather than tracking the stock’s actual return over time. It’s an ocean away from Lexington, Kentucky, but the lesson travels: leverage doesn’t just add risk, it changes the math entirely. Finally, there’s a quieter but genuinely important story developing in Washington. The SEC has proposed letting public companies choose to report earnings twice a year instead of four times, a change championed by President Trump and SEC Chairman Paul Atkins as a way to reduce short-term pressure on management teams. The idea splits reasonable people: less frequent reporting could free executives to run their businesses for the next several years instead of the next ninety days, but it could also mean investors — including retirees who depend on knowing exactly what they own — get less information, less often. This week’s news cycle also included a primetime presidential address in which Trump alleged that newly declassified intelligence showed foreign interference — including from China — in the 2020 election, along with claims of voter registration fraud in Michigan. Election security officials, including the Cybersecurity and Infrastructure Security Agency, have said they’ve found no evidence that any votes were altered in past elections. Whatever your read on the speech, it fed into a broader theme running through the whole hour: how much can you trust the numbers an institution hands you, whether that’s a vote count or a government inflation report? It’s why we do our own research instead of relying solely on government statistics or Wall Street’s sell-side analysts, and it’s the same instinct that should guide how you evaluate any claim, official or otherwise. The Reframe: Manufactured Volatility vs. Real Risk Here’s the framework we come back to on nearly every episode of the show, and it’s the one thing we want you to take from this week’s news: there is a real difference between manufactured volatility and real risk, and confusing the two is one of the most expensive mistakes a retiree can make. Manufactured volatility is what happens when a stock’s price swings because of leverage unwinding, algorithmic trading around technical levels, or funds racing to exit ahead of a quarterly number — not because the underlying business got worse. The Korean ETF collapse is manufactured volatility in its purest form: a Samsung or SK Hynix shareholder holding actual shares, with no leverage, watched the same news and the same earnings power, just without the forced-selling spiral. Real risk is different. Real risk is a company losing its competitive position, cutting its dividend, or piling on debt it can’t service. Real risk should change what you own. Manufactured volatility, more often than not, should not. The trouble is that from the outside, both look identical on a stock chart. A share price falling 10% doesn’t come labeled “manufactured” or “real.” Telling the difference requires actually knowing the business you own — its cash flow, its dividend history, its balance sheet — well enough to judge whether this week’s headline changed anything about that story. That’s the diligence part of the job, and there’s no shortcut around it. How Should Retirement Investors Respond to This Kind of Volatility? At Dupree Financial Group, this is exactly why our approach centers on dividend-paying stocks and bonds rather than chasing whatever sector is moving fastest. When you own a company for the income it generates — not for a price target — a week of manufactured volatility becomes far less threatening, and sometimes it becomes an opportunity. When institutions are forced to sell a good company for reasons that have nothing to do with its fundamentals, the price drop that scares one investor is simply a better entry point for another. That’s not a guarantee of a favorable outcome — all investing involves risk, including the possible loss of principal — but it’s a fundamentally different posture than reacting to every headline. Seven Steps to Retirement-Proof Your Portfolio Against Manufactured Volatility Know what you own, line by line. Pull up your statement and be able to explain, in one sentence each, why you own every major holding. If you can’t, that’s the first thing to fix — not the market. Separate the headline from the business. Before reacting to a price move, ask whether anything actually changed about the company’s earnings, dividend, or balance sheet — or whether it’s a technical or leverage-driven move like the ones described above. Keep leveraged and single-stock ETFs out of retirement money entirely. These products are built for daily traders, not long-term holders. The Korean ETF collapse is a real-world example of what daily compounding leverage can do to an account in a matter of days. Read past the quarterly headline number. Whether or not the reporting-frequency rules change, judge a company on multi-year cash flow and dividend trends, not a single quarter’s beat or miss. Keep a watchlist of quality companies for when panic creates a discount. When forced selling knocks a good business down for reasons unrelated to its fundamentals, that’s the moment long-term investors get paid for their patience. Revisit your income plan, not just your account balance. A retirement portfolio’s job is to produce cash flow you can live on for 30 to 40 years. Judge a volatile week by whether your income stream held up — not by the number on the login screen. Get a second set of eyes on your portfolio. If you’re not sure whether what you own is built to withstand this kind of volatility, or whether you’re carrying more leverage or concentration risk than you realize, that’s exactly what a portfolio review is for. Frequently Asked Questions Is a leveraged ETF a good way to boost my retirement returns? No. Leveraged ETFs reset and compound daily, so their long-term return can diverge sharply from the underlying stock’s actual performance — including large losses even when the stock has technically risen over time. They’re built for short-term traders, not retirement accounts. Does cooling inflation mean the Fed will cut interest rates soon? Not necessarily. While June’s cooler CPI reading supports the case for rate cuts, the Fed’s new chairman has signaled openness to rethinking the central bank’s approach to its inflation target, adding real uncertainty to the timeline for any rate decisions. Why do stock prices swing so much when a company’s earnings didn’t change? Much of the day-to-day movement in popular stocks comes from technical trading, algorithmic strategies tied to chart levels, and leveraged funds being forced to buy or sell — not from new information about the business itself. That’s manufactured volatility, not real risk. What does the debate over quarterly earnings reports mean for individual investors? If the SEC’s proposal is adopted, some companies may report financial results only twice a year instead of four times. That could reduce short-term pressure on management, but it may also mean investors get less frequent, less detailed information about what they actually own. How do I know if my retirement portfolio is built to handle volatility? Start by confirming you can explain why you own every major holding and that none of your retirement money sits in leveraged or single-stock products. A complimentary portfolio review with a fee-only fiduciary advisor is the fastest way to get an honest, unbiased answer. The Bottom Line Weeks like this one will keep happening. Leverage will keep building up somewhere and unwinding somewhere else. Traders will keep reacting to chart levels instead of cash flow. What won’t change is the difference between a business that’s actually worth less than it was last week and a stock price that simply got caught in someone else’s forced selling. Learn to tell those two things apart, build your income around companies you understand, and a volatile week stops being a threat to your retirement — it starts being background noise, or even opportunity. Schedule a Complimentary Portfolio Review If you’re not sure whether your portfolio is built to take advantage of volatility like we saw this week — instead of getting knocked around by it — we’ll take a look. No charge. No pressure. Just an honest conversation about what you own and whether it’s working for you. Call: 859-233-0400  |  Visit: dupreefinancial.com You Might Also Like Catch up on past episodes of The Tom Dupree Show — our full podcast archive, updated every week. Meet the team at Dupree Financial Group — learn about our fee-only, fiduciary approach and the people behind it. [PLACEHOLDER — link to a prior show notes/blog post on dividend investing fundamentals once a confirmed URL is available] About the Author: Tom Dupree is the founder of Dupree Financial Group and host of The Tom Dupree Show, heard weekly across Central Kentucky radio and podcast. With 47 years in the investment business, starting in municipal bonds in 1978, Tom built DFG’s investment philosophy around one idea: retirement money should generate income you can see, not just a balance you hope holds up. Dupree Financial Group is an independent, fee-only fiduciary Registered Investment Advisor based in Lexington, Kentucky. REGULATORY DISCLAIMER: This material is for informational and educational purposes only and does not constitute investment, legal, or tax advice, nor is it a solicitation to buy or sell any security. All investing involves risk, including the possible loss of principal. Past performance of any market index or security is not indicative of future results. Dupree Financial Group is a fee-only fiduciary and does not receive commissions on any products or securities discussed. 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Mel Mattison joins Marty to dissect AI's impact on memory chips, the hyperscaler debt cycle, and the Fed's rate outlook under Chairman Warsh. The conversation swings from Korean memory stocks like Micron, Samsung and SK Hynix to macro themes such as fiscal deficits, debasement trades, gold, Bitcoin and the new “Trump accounts” tax vehicle. Listeners get a contrarian view on why AI demand may outlast hype, how free‑cash‑flow can erase debt fast, and what assets could dominate the market this decade. Mel on Twitter: https://x.com/MelMattison1 Mel's Book: https://www.melmattison.com/quoz Find the Home Mining Playbook here: https://www.tftc.io/home-mining-energy-playbook STACK SATS hat: https://tftcmerch.io/ Our newsletter: https://www.tftc.io/bitcoin-brief/ TFTC Elite (Ad-free & Discord): https://www.tftc.io/#/portal/signup/ Discord: https://discord.gg/yHGkvYxdqT Opportunity Cost Extension: https://www.opportunitycost.app/ Shoutout to our sponsors: Block: Cash App: For a limited time, new customers can get $21 added to their balance. Just use code TFTC10 when you sign up, and send at least $5 to a friend in the first two weeks. Terms apply. Bitcoin services by Block, Inc. See the Bitcoin disclosures at cash.app/legal/podcast. Square: Visit http://square.com/go/**tftc** for up to $200 off eligible Square hardware. Bitkey: Use code TFTC10 for 10% off the new Bitkey. Aven https://www.aven.com/bitcoin CrowdHealth https://www.joincrowdhealth.com/tftc Unchained https://unchained.com/tftc/ Salt of the Earth: https://drinksote.com/tftc Join the TFTC Movement: Main YT Channel https://www.youtube.com/c/TFTC21/videos Clips YT Channel https://www.youtube.com/channel/UCUQcW3jxfQfEUS8kqR5pJtQ Website https://tftc.io/ Newsletter tftc.io/bitcoin-brief/ Twitter https://twitter.com/tftc21 Instagram https://www.instagram.com/tftc.io/ Nostr https://primal.net/tftc Follow Marty Bent: Twitter https://twitter.com/martybent Nostr https://primal.net/martybent Newsletter https://tftc.io/martys-bent/ Podcast https://www.tftc.io/tag/podcasts/ Disclosure: Bitcoin services are provided by Block, Inc. Bitcoin services are not licensable activity in all U.S. states and territories, and not all services are available in all states. Bitkey is not available in New York. Block, Inc. operates in New York as Block of Delaware and is licensed to engage in virtual currency business activity by the New York State Department of Financial Services. Bitcoin is a non-deposit, non-bank product that is not FDIC insured and involves risk, including monetary loss. For additional information, see the Bitcoin disclosures: https://help.cash.app/btcdisclosures Get up to $200 off Square hardware when you sign up at http://square.com/go/tftc**!** #squarepartner. Offer expires December 31, 2026 at 11:59 pm PST. Offer for $40 off the cost of one Square Stand, $75 off the cost of one Square Terminal, $100 off the cost of one Square Handheld, or $200 off the cost of one Square Register, excluding applicable taxes. Limited to one discount per product type per seller account. Each code is limited to one redemption per account holder. Valid for new Square customers located in the US only. Offer not valid with guest checkout. Square reserves the right to modify, revoke or cancel the offer at any time. Offer cannot be combined with any other coupon. Void where prohibited, not redeemable for cash, and non-transferable. #squarepartner #blockpartner

Der Halbleiterindex SOX verliert 20 Prozent in einem Monat, Speicherchip-Werte wie SK Hynix und Micron stürzen um bis zu 35 Prozent ab. Und das, obwohl ASML und TSMC sensationelle Zahlen vorlegen und Planungssicherheit bis 2030 versprechen. Die beiden Wirtschaftsjournalisten Dietmar Deffner und Holger Zschäpitz streiten über die große Tech-Rotation, dieses Mal mit vertauschten Rollen: Der Bär sieht mittelfristig Chancen im abgekühlten Chip-Sektor bei einem KGV von 17, der Bulle warnt vor einer nachhaltigen Korrektur nach dem Vorbild der Rüstungswerte. Außerdem: Stripe will PayPal für 60,50 Dollar je Aktie übernehmen, SpaceX verliert eine Billion Dollar an Marktkapitalisierung und Apple stößt Nvidia vom Thron des wertvollsten Unternehmens der Welt. Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte: https://linktr.ee/deffnerundzschaepitz DEFFNER & ZSCHÄPITZ sind wie das wahre Leben. Wie Optimist und Pessimist. Im wöchentlichen WELT-Podcast diskutieren und streiten die Journalisten Dietmar Deffner und Holger Zschäpitz über die wichtigen Wirtschaftsthemen des Alltags. Schreibt uns an: wirtschaftspodcast@welt.de Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutzerklärung: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

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

This week we let ChatGPT help pick the news stories (which seemed like a good idea at the time), and honestly, it kind of worked.We start with Russia reportedly having to buy gasoline after Ukrainian drone strikes hit their refinery capacity, which turns into a bigger conversation about energy markets, gasoline and diesel, and how cheap drones are completely changing the math of modern warfare.Then we get into Japan potentially pushing its giant pension funds to bring more money back home, the AI trade still running through SK Hynix and GPU demand, and the Fed now treating AI infrastructure spending as one of the things keeping inflation hotter than expected.So there is real market stuff in here.But also, this is Dan and me, so we also talk about a squirrel getting loose in a Meta office, a bear breaking into a shopping mall on a military base, Britain trying to survive heat waves with better refrigerators and tiny fans, Pepsi making a very questionable Wild Cherry post in India, AI reading ancient Roman scrolls, Pompeii, Pink Floyd, and whether Wendy's Biggie Bag is secretly one of the better recession trades on the board. Chapters00:00 — Hook, Intro, and Cold Open01:47 — Welcome Back to the China Shop02:30 — Letting ChatGPT Pick the News03:22 — Russia's Fuel Problem and Ukrainian Drone Strikes06:36 — EVs, Refinery Risk, and Energy Independence09:10 — A Squirrel Gets Loose at Meta14:28 — Japan's Pension Fund and Money Coming Home20:08 — The Alaska Mall Bear Story21:54 — SK Hynix, AI Chips, and Inflation Pressure25:24 — FedWatch, Rate Expectations, and No Cuts Yet27:38 — Britain's Heat Wave Economy32:49 — Scottsdale Will Pay for Your Lawn, Not Your Pool34:29 — Pepsi's Wild Cherry Problem38:33 — AI, Ancient Scrolls, and the Pompeii Detour42:28 — Wendy's, Biggie Bags, and Takeover Rumors48:38 — Jobs, Rent, and the Economy People Actually Feel50:30 — Chessferatu and Closing ThoughtsSubscribe, share, and join the trading conversations on Facebook, Twitter, LinkedIn and Discord!Sponsors and FriendsOur podcast is sponsored by Sue Maki at Fairway Independent Mortgage (MLS# 206048). Licensed in 38 states, if you need anything mortgage-related, reach out to her at SMaki@fairwaymc.com or give her a call at (520) 977-7904. Tell her 2 Bulls sent you to get the best rates available!If you are interested in signing up with TRADEPRO Academy, you can use our affiliate link here. We receive compensation for any purchases made when using this link, so it's a great way to support the show and learn at the same time! **Use code CHINASHOP15 to save 15%**To contact us, you can email us directly at bandoftraderspodcast@gmail.comIf you like our show, please let us know by rating and subscribing on your platform of choice!If you like our show and hate social media, then please tell all your friends!If you have no friends and hate social media and you just want to give us money for advertising to help you find more friends, then you can donate to support the show here!Dan:Dan co-founded 2 Bulls in a China Shop with Kyle when their shared passion for active trading ignited during the lockdowns. Their daily discussions about trades, interests, and the valuable lessons learned created the bedrock for what eventually evolved into both the 2 Bulls in a China Shop and Band of Traders podcasts.While navigating the complexities of trading, Dan infused humor into the shows with his self-deprecating wit and candid discussions about their trading experiences. This dynamic duo's chemistry became the catalyst for a podcast that resonated widely, capturing the attention of a diverse audience.Download ChessFeratuHalf-Cocked TalesAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Simeon Hyman of ProShares discusses the launch of the ProShares Ultra SK Hynix ETF (SKHU), which seeks to deliver twice the daily performance of SK Hynix (SKHY), a key player in the AI memory market. He explains how leveraged ETFs can provide enhanced exposure with less capital while addressing volatility concerns and highlighting the safeguards that support these products in the U.S. market.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

We dachten dat we alles al gezien hadden. Niet dus! Truth Social, het socialmediabedrijf van president Trump, gaat snellere toegang tot berichten van Trump verkopen. Dat betekent dat handelaren sneller informatie van de president kunnen verwerken dan concurrenten. Informatie die de koers van aandelen, maar ook de olieprijs vaak heeft beïnvloed. Zo bleek uit onderzoek al dat Trump minstens twintig bedrijven heeft gepromoot op Truth Social, net nadat hij er zelf een belang in had genomen. In sommige gevallen kondigde hij overheidsbeleid aan dat gunstig uit kon pakken voor die bedrijven. Het ging onder meer om autobouwer Tesla, chipmaker Nvidia en spijkerbroekenmerk American Eagle. Deze aflevering kijken we wat deze nieuwe dienst betekent voor de beurshandel. Het idee is dat flitshandelaren hiervan gebruik gaan maken, we zoeken uit of het Nederlandse Flowtraders hiervan gaat profiteren. Hebben we het ook uitgebreid over Netflix. Dat stelt teleur. De omzet en winst zijn de komende tijd minder dan waarop analisten en beleggers rekenden. Ze maken zich zorgen over de groei van de grootste streamer van de wereld. Die lijkt er nu wel echt uit. Ook komt Netflix met een opvallende stap: het wil minder vertellen over het kijkgedrag van hun klanten. Waardoor Netflix (weer) minder transparant wordt. Verder hoor je deze aflevering meer over ASML. Dat geeft bijna een miljard uit aan cadeaus voor het personeel. Ook komt Adyen voorbij. Moeten zij nu ook op overnamepad, nu hun grootste concurrent op overnamejacht is? En je hoort over Viaplay. Dat boekt voor het eerst in heel veel kwartalen weer eens winst! Te gast: Errol Keyner van de Vereniging van Effectenbezitters BNR Beurs is een journalistiek onafhankelijke productie, mede mogelijk gemaakt door Saxo. Over de makers: Jelle Maasbach is presentator van BNR Beurs en freelance financieel journalist. Zijn favoriete aandeel om over te praten is Disney, maar daar lijkt hij de enige in te zijn. Sinds de eerste uitzending van BNR Beurs is 'ie er bij. Maxim van Mil is presentator van BNR Beurs en journalist bij BNR, waar hij zich focust op de financiële markten en ontwikkelingen in de tech-wereld. Je krijgt hem het meest enthousiast als hij kan praten over ASML, of oer-Hollandse bedrijven zoals Ahold of ABN Amro. Jorik Simonides is presentator van BNR Beurs, economieredacteur en verslaggever bij BNR. Hij wordt er vooral blij van als het een keer níet over AI gaat. Je hoort hem ook in de BNR-podcast Moerdijk: dorp van de rekening. Milou Brand is presentator van BNR Beurs, freelance podcastmaker en columnist bij het Financieele Dagblad. Jochem Visser is presentator van BNR Beurs, maakt Beursnerd XL en is redacteur bij de podcast Onder Curatoren. Vraag hem naar obscure zaken op financiële markten en hij vertelt je waarom het eigenlijk nóg leuker is dan je al dacht. Over de podcast: Met BNR Beurs ga je altijd voorbereid de nieuwe beursdag in. We praten je in een kleine 25 minuten bij over alle laatste ontwikkelingen op de handelsvloer. We blijven niet alleen bij de AEX of Wall Street, maar vertellen je ook waar nog meer kansen liggen. En we houden het niet bij de cijfers, maar zoeken ook iedere dag voor je naar duiding van scherpe gasten en experts. Of je nu een ervaren belegger bent of net begint met je eerste stappen op de beurs, de podcast biedt waardevolle inzichten voor je beleggingsstrategie. Door de focus op zowel de korte termijn als de lange termijn, helpt BNR Beurs luisteraars om de ruis van de markt te scheiden van de essentie.See omnystudio.com/listener for privacy information.

AGENDA: 00:00 – Apple SUES OpenAI: Did They Steal Apple's Biggest Secrets? 05:10 – Is OpenAI's $6BN Hardware Bet Already Dead? 12:50 – Zuckerberg Is Back: Meta Finally Takes On OpenAI 18:05 – The AI Spending Bubble Nobody Is Talking About 23:45 – Claude Is Coming for Designers, Product Managers & Figma 27:15 – Anthropic's $50BN Explosion: Have We Already Hit AI's TAM? 36:00 – The $26BN AI IPO Powering the Entire Industry 40:00 – Seed Investing Is Dead? Jason Calacanis Changes Strategy 57:00 – SaaS Is in Trouble: AI Is Accelerating Terminal Decay 01:15:00 – Why Greylock Said No to Billions of Extra Dollars  

In der heutigen Folge sprechen die Finanzjournalisten Nando Sommerfeldt und Holger Zschäpitz über neue Paypal-Fantasie, die unterschätzte Apple-Rallye und die Antwort auf die Frage: Kann ein Atommüll-Staatsfonds auch Rente? Außerdem geht es um Samsung Electronics, Micron Technology, IBM, SK Hynix, Alphabet, Meta Platforms, Amazon, Microsoft, Apple, PayPal Holdings, Block, Morgan Stanley, BlackRock, BASF, Volkswagen, BMW, Mercedes-Benz Group, Richemont, Kering, LVMH, Hermès, Burberry, TSMC, Netflix, ABB, Abbott Laboratories, GE Aerospace, Intuitive Surgical, UnitedHealth Group, Alcoa, United Airlines Holdings, BHP, ING Group, Smartbroker Holding, AMD, Broadcom, Nvidia, Viasat, AST SpaceMobile, Rocket Lab, Planet Labs, EchoStar, SpaceX, Amundi Global Luxury UCITS ETF (WKN: A2H564), Boreas S&P Absolute Luxury UCITS ETF (WKN: A412DN), iShares Core MSCI World UCITS ETF (WKN: A0RPWH), Xtrackers MSCI World UCITS ETF 1C (WKN: A1XB5U), SPDR MSCI ACWI ETF (WKN: A1JJTC), iShares Core MSCI EM IMI UCITS ETF (WKN: A111X9), VanEck Semiconductor UCITS ETF (WKN: A2QC5J), Amundi MSCI Semiconductors UCITS ETF (WKN: LYX018), VanEck Space Innovators UCITS ETF (WKN: A3DP9J), Global X Copper Miners UCITS ETF (WKN: A3C7FZ), Global X Silver Miners UCITS ETF (WKN: A3DC8R), VanEck Uranium and Nuclear Technologies ETF (WKN: A3D47K), iShares Global Clean Energy ETF (WKN: A0MW0M). Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Hier könnt ihr den AAA-Newsletter abonnieren: https://www.welt.de/newsletter/article232797673/Alles-auf-Aktien-Der-taegliche-Boersen-Newsletter-fuer-WELTplus-Abonnenten.html Und – ganz neu: AAA gibt es jetzt auch auf Instagram: https://www.instagram.com/alles_auf_aktien/ Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien *Anzeige: Eight Sleep: Der Pod 5 reguliert die Temperatur im Bett automatisch, trackt Schlaf- und Gesundheitswerte ohne Wearable und kann so zu besserem Schlaf beitragen. Mit dem Code ALLESAUFAKTIEN erhaltet ihr auf https://www.eightsleep.com/allesaufaktien bis zu 350 Euro Rabatt.* Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

The US has completed another round of strikes on various parts of Iran, targeting military capabilities; Tehran responded with its own attacks on Kuwait and Jordan.US President Trump stated Iran wants to meet, though warned that strikes would expand next week. Nonetheless, crude benchmarks take a breather following recent gains; Brent -0.6%.APAC stocks held a mostly negative bias, with the KOSPI (-6.4%) dragged by losses in Samsung Electronics (-8.6%) and SK Hynix (-11.9%). European equity futures are indicative of a slightly firmer open.DXY is flat and holds around 100.50; G10s are mixed against the USD.Looking ahead, highlights include UK GDP (May), Italian HICP Final (Jun), EZ Balance of Trade (May), US Retail Sales (Jun), Jobless Claims, Philly Fed Index (Jul), Pending Home Sales (Jun), Atlanta Fed GDP, SNB Minutes (Jul), Speakers including Fed's Logan & Schmid, Supply from Spain, France & UK.Earnings from Netflix, Alcoa, UnitedHealth, GE Aerospace, US Bancorp, Abbott, State Street & ABB.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

SpaceX  – Price almost $135 – full retracement. Earnings season in on –  here we go! Inflation – choppy. War back on! Straits Open? Or? New Diet? CYCLOSPORIASIS PLUS we are now on Spotify and Amazon Music/Podcasts! Click HERE for Show Notes and Links DHUnplugged is now streaming live - with listener chat. Click on link on the right sidebar. Love the Show? Then how about a Donation? PayPal.Donation.Button({ env:'production', hosted_button_id:'JJJHP2GDEJC7J', image: { src:'https://www.paypalobjects.com/en_US/i/btn/btn_donateCC_LG.gif', alt:'Donate with PayPal button', title:'PayPal - The safer, easier way to pay online!', } }).render('#donate-button'); Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter Warm-Up - CTP for SpaceX  - Price almost hit $135 yesterday - Earnings season 0 here we go! - Inflation - choppy - War back on! Straits Open? Or? New Diet? CYCLOSPORIASIS Markets - Inflation - Some Relief - IBM's Pre-Annnouncment - What does this say? - Bank earnings and an earnings cheat sheet - Some interesting chart data Health Update: Meniscus Repair next Thursday.... Today IBM stood for 'I Be Melting' as Big Blue turned into Big Blew Up... IBM: It's Been Murdered IBM: I Bought Misery IBM: Investment Board Malfunction Big Blue looked more like Deep Red today The only cloud around IBM today was hanging over the stock chart IBM investors got a free software update: Version 2.0 of disappointment. IBM'S AI FACE-PLANT - IBM shares plunged as much as 25%, putting the stock on pace for its worst session on record. - Preliminary revenue was $17.2 billion versus expectations near $17.9 billion. - Adjusted earnings were projected at $2.93 per share versus roughly $3.01 expected. - Management said customers redirected spending toward AI servers, memory and hardware while delaying software purchases. - The drop removed roughly 375 points from the price-weighted DJIA. - JCD and AH were both right and wrong for the weekly stock picks TRUTH? - President Trump says U.S. blockade will apply only to ships from Iranian ports; says Strait of Hormuz is open to all traffic except for Iran; says "Based on highly productive conversations with Middle East leadership, I have decided to replace the 20% United States reimbursement fee with trade and investment deals that the various Gulf States will be making into the United States" - Can never be proven - no real numbers here.... Clearly needed to walk back the 20% item - Hormuz still hobbled - best estimates are that the ships passing are 20% of pre-war levels INFLATION RELIEF - FOR NOW - June CPI rose 3.5% year over year, down from 4.2% in May and below the 3.8% consensus. - Core CPI held at 2.6%. - Falling gasoline and energy prices drove much of the improvement. - Traders sharply reduced expectations for a July Fed rate increase. - Treasury yields fell and the Nasdaq advanced. WALL STREET BANKS PRINT MONEY - JPMorgan posted $21.2 billion in net income, helped by special items. - Markets revenue rose 35% to $12.1 billion, including an 86% jump in equities revenue. - Bank of America earned $9.1 billion as equities trading revenue increased 70%. - Goldman Sachs reported earnings of $20.98 per share and a 23.5% annualized return on common equity. - Jamie Dimon described conditions as close to "as good as it gets." THE $26.5 BILLION AI-MEMORY IPO - $ GRAB - SK Hynix raised $26.5 billion through a Nasdaq ADR listing. - The offering priced at $149 and finished approximately 13% higher the day of the offering, but sunk the next. - Demand reportedly exceeded the available shares by more than seven times. - SK Hynix supplies high-bandwidth memory used in Nvidia-powered AI systems. - The listing gives U.S. investors direct access to one of the largest beneficiaries of AI infrastructure spending. - - Samsung is on tap to do the same thing... Some Interesting Charts Best Quarters Plus One Equal vs Cap-Weight OIL'S CEASEFIRE WHIPLASH - Brent crude jumped 5.2% to $78.02 a barrel after the U.S.-Iran ceasefire broke down. - WTI rose 4.4% to $73.52. - Markets repriced the risk of interrupted tanker traffic through the Strait of Hormuz. - Energy stocks gained while airlines and the broader market weakened. - Rising oil prices could quickly reverse the energy-related improvement seen in the June inflation report. APPLE SUES OPENAI - AI PARTNERS TURN RIVALS - Apple sued OpenAI and two former Apple employees on July 10, alleging coordinated theft of hardware trade secrets. - The defendants include OpenAI hardware chief Tang Tan and technical employee Chang Liu, both former Apple employees. - Apple claims confidential product designs and manufacturing information were taken to accelerate OpenAI's consumer-device program. - More than 400 former Apple employees reportedly now work at OpenAI, highlighting the scale of the talent migration between the companies. IPO AND MEGADEAL FEVER RETURNS - Global deals valued above $10 billion reached record levels during the first half of 2026. - Mega-deals represented approximately 43% of newly announced M&A volume. - Investment-banking revenue surged across JPMorgan, Bank of America and Goldman Sachs. - Large offerings from SpaceX and SK Hynix added momentum to underwriting activity. - The boom depends on high equity valuations, strong AI demand and large transactions continuing. BANKS BANKS BANKS JPMORGAN CHASE - RECORD PROFIT - Profit reached a record $16.9 billion, or $6.14 per share, versus $5.59 expected. - Managed revenue totaled $58 billion, with every major business reporting record revenue. - Markets revenue rose 35%, led by an 86% surge in equities trading. - Investment-banking revenue increased 30% to its highest level since 2021. - Jamie Dimon warned that geopolitical tensions, sticky inflation, fiscal deficits and elevated asset prices remain major risks. BANK OF AMERICA - TRADING RECORD - Net income rose 27% to $9.1 billion, or $1.21 per share, versus $1.13 expected. - Revenue increased 15% to $31.6 billion. - Sales and trading revenue jumped 33% to a record $7.1 billion; equities revenue rose 70%. - Investment-banking fees increased 50% to $2.1 billion. - Full-year net-interest-income growth is now expected near the upper end of the previous 6% to 8% range. GOLDMAN SACHS - DEAL BOOM - Profit reached $6.63 billion, or $20.98 per share, versus $14.48 expected. - Revenue totaled $20.3 billion. - Equities revenue surged 72% to a record $7.42 billion. - Fixed-income, currency and commodities revenue increased 32% to $4.59 billion. - Investment-banking fees jumped 55%, helping send Goldman shares to a record high. CITIGROUP - DECADE-HIGH REVENUE - Net income jumped 45% to $5.8 billion, or $3.15 per share, versus roughly $2.74 expected. - Revenue rose 14% to $24.8 billion, the bank's highest quarterly revenue in a decade. - Investment-banking revenue increased 44% to $1.55 billion. - Equities trading revenue rose 45%, while fixed-income trading increased 7%. - Return on tangible common equity reached 13%, matching the upper end of management's target range. WELLS FARGO - BACK ON OFFENSE - Net income rose 22% to $6.4 billion, or $2.00 per share. - Revenue reached $22.6 billion and topped expectations. - Investment-banking revenue increased 20%. - Markets revenue rose 24% as volatility boosted client activity. - Management said the removal of regulatory growth restrictions is allowing the bank to deploy capital and expand its balance sheet. Bank Returns Post Earnings (July 14, 2026) Bank Stocks Earnings Cheat Sheet - JULY 15 - ASML: Expected EPS around $7.92 on $10.25 billion revenue; bookings, EUV demand and updated AI-chip equipment guidance will matter most. - JULY 15 - JOHNSON & JOHNSON: Expected EPS around $2.86 on $25.02 billion revenue; watch pharmaceutical growth, medical-device demand and full-year guidance. - JULY 15 - MORGAN STANLEY: Expected EPS around $2.89 on $19.38 billion revenue; trading, investment banking and wealth-management inflows are the key numbers. - JULY 15 - BLACKROCK: Expected EPS around $12.59 on $6.80 billion revenue; assets under management, ETF flows and private-market fundraising will be in focus. - JULY 16 - TSMC: Expected EPS around $3.76-$3.77 on roughly $40 billion revenue; AI demand, gross margin and any increase to capital-spending guidance are critical. - JULY 16 - UNITEDHEALTH: Expected EPS around $4.84 on $110.8 billion revenue; medical-cost trends and the durability of full-year guidance are the main issues. - JULY 16 - GE AEROSPACE: Expected EPS around $1.85 on $11.8 billion revenue; engine deliveries, service revenue and supply-chain constraints will drive the reaction. - JULY 16 - NETFLIX: Expected EPS around $0.79 on $12.58 billion revenue; advertising growth, engagement and operating-margin guidance will matter more than subscribers. - JULY 17 - TRAVELERS: Expected EPS around $5.33 on roughly $11 billion revenue; catastrophe losses, insurance pricing and reserve development are the key swing factors. - JULY 17 - FIFTH THIRD: Expected EPS around $0.98 on $3.25 billion revenue; net-interest income, deposit costs and credit quality will be closely watched. WAYFAIR GOES PHYSICAL - Wayfair opened its second large-format store in Atlanta on March 31, following the 2024 debut of its 150,000-square-foot Wilmette, Illinois flagship. - The company is building a national store network, with Denver expected later in 2026 and Yonkers, Cincinnati and Princeton locations planned for 2027. - The stores combine furniture, decor, appliances and home-improvement products, giving customers a chance to test large purchases before ordering. - The strategy is a major reversal for an online-first retailer and is designed to increase brand awareness, reduce dependence on digital advertising and capture shoppers returning to physical stores. AI SOVEREIGN WEALTH FUND - PUBLIC OWNERSHIP DEBATE - Bernie Sanders introduced legislation requiring the largest AI companies to transfer 50% of their equity into a U.S. sovereign wealth fund. - The fund is projected by supporters to hold roughly $7 trillion and could finance annual public dividends and government services. - OpenAI has separately floated a much smaller proposal in which major AI companies would voluntarily contribute about 5% of their equity. - Supporters call it a way to share AI-created wealth; critics warn government ownership could discourage investment, distort regulation and reduce innovation. PSA  - That's what we do....CYCLOSPORIASIS OUTBREAK - CASES SURGE - Cyclosporiasis cases are rising across more than 30 states, with Michigan, Ohio and New York reporting particularly large increases. - The CDC reported at least 843 confirmed cases and 86 hospitalizations by July 9, but state totals and reporting delays suggest the real count is substantially higher. - Lettuce, salad greens and other fresh produce are being investigated, although officials have not identified a specific product, supplier or national recall. - The parasite causes prolonged or recurring watery diarrhea; washing produce may reduce risk, and persistent symptoms should prompt medical testing and treatment. HOW TO REDUCE CYCLOSPORIASIS RISK (FWIW) - Wash hands with soap before preparing food and after using the bathroom. - Rinse fresh fruits, vegetables and herbs thoroughly under running water; scrubbing helps but cannot guarantee removal. - Keep raw produce separate from unwashed items, dirty utensils and preparation surfaces. - When traveling in tropical or subtropical areas, use safe water and avoid raw produce you cannot peel yourself; routine chemical sanitizers may not kill Cyclospora. Love the Show? Then how about a Donation? PayPal.Donation.Button({ env: 'production', hosted_button_id: 'JJJHP2GDEJC7J', image: { src: 'https://www.paypalobjects.com/en_US/i/btn/btn_donateCC_LG.gif', alt: 'Donate with PayPal button', title: 'PayPal - The safer, easier way to pay online!' } }).render('#donate-button-2'); THE CLOSEST TO THE PIN for SpaceX (SPCX) Winners will be getting great stuff like the new "OFFICIAL" DHUnplugged Shirt!     FED AND CRYPTO LIMERICKS   See this week's stock picks HERE Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter

Este martes la acción de IBM se desplomó más de un 25% en una sola jornada. La masacre ha sido de tal calibre que ha superado incluso su anterior plusmarca, que se produjo el 19 de octubre de 1987, una fecha que ha pasado a la historia de la Bolsa como Lunes Negro. En aquel entonces IBM se hundió junto a todo el mercado, esta vez se ha hundido prácticamente sola. Unos 67.000 millones de dólares de capitalización se evaporaron en unas horas y sus directivos entraron en modo de máxima alerta . El detonante fue una simple carta. Arvind Krishna, consejero delegado de la empresa desde hace 6 años, adelantó a los inversores los resultados preliminares del segundo trimestre, algo que no estaba obligado a publicar hasta el 22 de julio, pero que decidió hacerlo una semana antes. Informaba de unos ingresos de 17.200 millones, ligeramente por encima de lo previsto, y un beneficio por acción ajustado de 2,93 dólares frente a los 3 que se esperaban. Nada especialmente llamativo de primeras, salvo por una frase concreta en la que Krishna reconocía que las cosas habían ido peor de lo previsto y de lo que él mismo había vaticinado hace solo unos meses. Krishna no hablaba de una empresa que esté perdiendo clientes, sino una empresa cuyos clientes gastan el dinero en otra cosa. Con la memoria disparada de precio, los directores de sistemas de otras empresas están priorizando la compra de memoria por encima de otros gastos de capital. Un contrato de software se puede aplazar al mes de octubre, un lote de módulos de memoria quizá ya no esté disponible o lo esté a un precio mucho mayor. El software se ha convertido así en la variable de ajuste. No se cancela su compra, se aplaza, pero el trimestre perdido está perdido para siempre. La prueba la encontramos en la cotización de empresas que se dedican a la fabricación de memoria. SK Hynix subió casi un 9% tras poner en producción su módulo HBM4 de 12 capas, Samsung y Kioxia ganaron un 6%, y ASML, que fabrica las máquinas que hacen chips, también subió. En definitiva, que cada dólar que no fue a una licencia de IBM se fue a un módulo de memoria. La cuestión es que, en contratos de software, IBM ha crecido un 5%, aproximadamente la la mitad de lo prometido. Pero lo problemático no es eso, sino que la venta de servidores se ha contraído un 7% cuando la propia compañía había previsto un 1%. IBM no tiene una crisis de costes, que podría arreglarse con un plan de ajuste, sino de demanda, algo que depende de terceros. No es, además, la primera sacudida bursátil que sufren este año. El 23 de febrero la acción cayó un 13% tras anunciar Anthropic que Claude Code podía mapear y documentar bases de código COBOL en pocas semanas. Ahí lo que peligra son las horas facturables en un negocio que aporta a IBM unos 5.000 millones cada trimestre. Otras empresas dedicadas a negocios parecidos como Workday, ServiceNow, Salesforce y Accenture también han bajado sin que ninguna de ellas publicase nota alguna. Es lo que los inversores han bautizado como “SaaSpocalipsis”, el apocalipsis de las empresas de software como servicio. IBM tiene el problema añadido de que su software va atado a su hardware. Si la tendencia persiste tendrán que tomar medidas serias, tanto como reinventarse de nuevo, algo que IBM ha hecho ya varias veces. En La ContraRéplica: 0:00 Introducción 3:57 El desplome de IBM 32:09 El cociente intelectual y las etnias 43:31 Propiedad de los videojuegos 47:53 Las consolas de Steam · Canal de Telegram: https://t.me/lacontracronica · “Contra el pesimismo”… https://amzn.to/4m1RX2R · “Hispanos. Breve historia de los pueblos de habla hispana”… https://amzn.to/428js1G · “La ContraHistoria del comunismo”… https://amzn.to/39QP2KE · “La ContraHistoria de España. Auge, caída y vuelta a empezar de un país en 28 episodios”… https://amzn.to/3kXcZ6i · “Contra la Revolución Francesa”… https://amzn.to/4aF0LpZ · “Lutero, Calvino y Trento, la Reforma que no fue”… https://amzn.to/3shKOlK Apoya La Contra en: · Patreon... https://www.patreon.com/diazvillanueva · iVoox... https://www.ivoox.com/podcast-contracronica_sq_f1267769_1.html · Paypal... https://www.paypal.me/diazvillanueva Sígueme en: · Web... https://diazvillanueva.com · Twitter... https://twitter.com/diazvillanueva · Facebook... https://www.facebook.com/fernandodiazvillanueva1/ · Instagram... https://www.instagram.com/diazvillanueva · Linkedin… https://www.linkedin.com/in/fernando-d%C3%ADaz-villanueva-7303865/ · Flickr... https://www.flickr.com/photos/147276463@N05/?/ · Pinterest... https://www.pinterest.com/fernandodiazvillanueva Encuentra mis libros en: · Amazon... https://www.amazon.es/Fernando-Diaz-Villanueva/e/B00J2ASBXM #FernandoDiazVillanueva #ibm #ia Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

Craig Bolanos, Co-founder and Wealth Advisor at VestGen Wealth Partners, joins John Williams to talk about the markets, President Trump's handling of the housing assistance bill and the gradual impact on housing inventory and borrowing costs. Craig and John also cover gas prices, Fed Chair Kevin Warsh, SK Hynix and SpaceX. https://serve.castfire.com/audio/8516200/8516200_2026-07-15-151700.64kmono.mp3

Craig Bolanos, Co-founder and Wealth Advisor at VestGen Wealth Partners, joins John Williams to talk about the markets, President Trump's handling of the housing assistance bill and the gradual impact on housing inventory and borrowing costs. Craig and John also cover gas prices, Fed Chair Kevin Warsh, SK Hynix and SpaceX. https://serve.castfire.com/audio/8516200/8516200_2026-07-15-151700.64kmono.mp3

US struck Iran overnight, Trump said they will do so again on Wednesday night. Adding, they will hit power plants and bridges next week unless Iran negotiates.IRGC targeted weapons/storage in Bahrain and Kuwait, US positions in Jordan and the Fifth Fleet Command HQ. Iran said it is a mistake to think military action will force them to talk.ASML (+3.7%) reported Q2 earnings that beat estimates while raising its FY guidance above analyst expectations. Additionally, the Co. announced a partnership with Intel (INTC) for high-volume production of Intel 18A logic products using High NA EUV.US equity futures are firmer across the board, with NQ supported by ASML and SK Hynix upside overnight.DXY and Fixed Income rangebound ahead of a busy speaker slate.Crude benchmarks eke out mild gains, with another round of US strikes tonight.Looking ahead, highlights include US PPI (Jun), BoC Policy Announcement (Jul), Fed Beige Book (Jul), Speakers including Fed's Williams, Musalem, Warsh & Cook, BoC Governor Macklem, BoE's Pill, Earnings from United Airlines, Johnson & Johnson, Morgan Stanley, PNC Financial Services, BNY Mellon.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

Craig Bolanos, Co-founder and Wealth Advisor at VestGen Wealth Partners, joins John Williams to talk about the markets, President Trump's handling of the housing assistance bill and the gradual impact on housing inventory and borrowing costs. Craig and John also cover gas prices, Fed Chair Kevin Warsh, SK Hynix and SpaceX. https://serve.castfire.com/audio/8516200/8516200_2026-07-15-151700.64kmono.mp3

Craig Bolanos, Co-founder and Wealth Advisor at VestGen Wealth Partners, joins John Williams to talk about the markets, President Trump's handling of the housing assistance bill and the gradual impact on housing inventory and borrowing costs. Craig and John also cover gas prices, Fed Chair Kevin Warsh, SK Hynix and SpaceX. https://serve.castfire.com/audio/8516200/8516200_2026-07-15-151700.64kmono.mp3

ASML heeft een extreem goed kwartaal achter de rug. De omzet steeg met 21 procent, de winst ging met 26 procent omhoog. Beide veel beter dan gedacht. Maar belangrijker, voor de tweede keer dit jaar gaat de omzetverwachting omhoog. Ook die verhoging was niet verwacht. Met al dat goede nieuws zou je denken: het aandeel gaat door het dak. Aanvankelijk leek het erop. Aan het begin van de beurshandel stond het aandeel zo'n 7 procent hoger, maar de koers zakte als een oude onderbroek. Deze aflevering kijken we waar dat pessimisme vandaan komt. Ook lopen we uitgebreid door de cijfers en de verwachtingen heen. Je hoort meer over het opschalen van de productie, over de orders en over de mogelijke aandelensplitsing. Gaat het ook over Stripe, de betaalverwerker. Dat is een Amerikaanse concurrent van Adyen die groeit door overnames. Nu willen ze de grootste overname uit hun geschiedenis doen: voor ruim 50 miljard het kwakkelende PayPal opkopen. Het lijkt een bedreiging voor Adyen, maar toch gaat dat aandeel opvallend goed op het nieuws. De Zuid-Koreaanse beurs komt ook langs. De beurs doet het dit jaar erg goed, maar heeft ook wat manische periodes. De koers schommelt nogal. Het gaat zo hard dat zelfs de president van het land ingrijpt! Te gast: Jordy Beuving van De Aandeelhouder BNR Beurs is een journalistiek onafhankelijke productie, mede mogelijk gemaakt door Saxo. Over de makers: Jelle Maasbach is presentator van BNR Beurs en freelance financieel journalist. Zijn favoriete aandeel om over te praten is Disney, maar daar lijkt hij de enige in te zijn. Sinds de eerste uitzending van BNR Beurs is 'ie er bij. Maxim van Mil is presentator van BNR Beurs en journalist bij BNR, waar hij zich focust op de financiële markten en ontwikkelingen in de tech-wereld. Je krijgt hem het meest enthousiast als hij kan praten over ASML, of oer-Hollandse bedrijven zoals Ahold of ABN Amro. Jorik Simonides is presentator van BNR Beurs, economieredacteur en verslaggever bij BNR. Hij wordt er vooral blij van als het een keer níet over AI gaat. Je hoort hem ook in de BNR-podcast Moerdijk: dorp van de rekening. Milou Brand is presentator van BNR Beurs, freelance podcastmaker en columnist bij het Financieele Dagblad. Jochem Visser is presentator van BNR Beurs, maakt Beursnerd XL en is redacteur bij de podcast Onder Curatoren. Vraag hem naar obscure zaken op financiële markten en hij vertelt je waarom het eigenlijk nóg leuker is dan je al dacht. Over de podcast: Met BNR Beurs ga je altijd voorbereid de nieuwe beursdag in. We praten je in een kleine 25 minuten bij over alle laatste ontwikkelingen op de handelsvloer. We blijven niet alleen bij de AEX of Wall Street, maar vertellen je ook waar nog meer kansen liggen. En we houden het niet bij de cijfers, maar zoeken ook iedere dag voor je naar duiding van scherpe gasten en experts. Of je nu een ervaren belegger bent of net begint met je eerste stappen op de beurs, de podcast biedt waardevolle inzichten voor je beleggingsstrategie. Door de focus op zowel de korte termijn als de lange termijn, helpt BNR Beurs luisteraars om de ruis van de markt te scheiden van de essentie.See omnystudio.com/listener for privacy information.

Is the AI trade entering a new phase?In this week's episode of Market Open, Reda and Russell unpack another eventful week for markets. They discuss SK Hynix's record-breaking US listing, why some investors are starting to question whether AI stocks have run too far, and what the latest moves in memory chips could mean for the companies building the next generation of AI.In this episode:Why AI investors may need to rethink the winnersSK Hynix's blockbuster US listingThe growing pressure on hyperscalers ahead of earningsWhat higher oil prices could mean for inflationThe key market risks to watch this weekTry Finimize Pro

Software stocks falling on the back of International Business Machines releasing a bleak earnings warning, causing the stock to lose a fourth of its value. The traders break down what the plummet means for the broader software market and why the fall could be a buying opportunity. Then, the June CPI results coming in softer than expected, cooling from  months-long upward moves. Former Dallas Fed president Richard Fisher gives his thoughts on what the reversal means for Fed policy and why he isn't saying goodbye to inflation yet. Plus, bank earnings season kicking off with Goldman Sachs soaring but Citigroup sinking, the latest on the Iran blockade, what's next for SK Hynix. Fast Money Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Carl Quintanilla, Jim Cramer and David Faber covered all of the bases on a busy day for the markets: IBM shares plunge on weaker-than-expected preliminary Q2 results; Five of the nation's six largest banks post quarterly beats to kick off earnings season; June CPI comes in tamer than expected ahead of Kevin Warsh's first Capitol Hill testimony as Fed Chairman; SK Hynix rebounds from Monday's sell-off. Also in focus: JPMorgan Chase CEO Jamie Dimon's earnings call message about the market and AI; Apple gets downgraded to the equivalent of a "sell" rating; An exclusive with Paramount's lead outside counsel defending the company's merger with Warner Bros. Discovery — after twelve state attorneys general filed a lawsuit to block it.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Andrew, Ben, and Tom discuss June CPI falling to 3.5% and core CPI to 2.6% both below expectations with the biggest month-over-month drop since May 2020, Trump proposing a 20% fee on Strait of Hormuz cargo and reinstating the blockade sending WTI to $80 and Brent to $87, Chris Waller's hawkish pivot as Warsh builds Fed credibility, IBM's 19% drop after warning on the quarter as clients reprioritized CapEx toward memory and cybersecurity, HCA's 6% drop on ACA payer mix, Samsung exploring a US ADR listing after SK Hynix's blockbuster $26.5B raise, SLB and Liberty Energy pushing into data center power, improving NFIB and Fastenal readings, and a very strong bank earnings kickoff with BAC investment banking fees up 50%.Join our live YouTube stream Monday through Friday at 8:30 AM EST:http://www.youtube.com/@TheMorningMarketBriefingPlease see disclosures:https://www.narwhal.com/disclosure

In this episode of The Circuit, Ben and Jay dive into SK Hynix's ambitious US stock listing, discussing how the AI-driven memory boom and a need for deeper capital pools prompted the move, while speculating if companies like MediaTek might follow suit. The hosts also explore the fierce competition among frontier AI models, noting that enterprise evaluation is shifting toward token efficiency for knowledge work and emphasizing the growing importance of AI orchestration layers and data ownership. Additionally, they break down Wall Street's harsh reaction to ON Semiconductor's acquisition of Synaptics, attributing the stock drop to a lack of clear corporate messaging regarding both sprawling businesses. Finally, the duo analyzes the rumors surrounding Nvidia's product roadmaps, concluding that while minor delays won't impact Nvidia's overall revenue given the massive compute demand, these shifts can trigger significant market volatility for the smaller optical and supply chain players dependent on those exact timelines.

A cooler inflation report gave investors some relief, but renewed pressure from oil prices and AI-driven spending is still shaping the market outlook.Mike Armstrong and Marc Fandetti break down the latest CPI report, why falling energy prices helped pull prices lower in June, and why the Fed is still unlikely to declare victory on inflation. They also discuss strong earnings from major banks, IBM's sharp warning as customers shift spending toward AI chips and servers, whether recent productivity gains are really coming from AI, why younger investors are taking bigger risks in speculative markets, how data center owners are trying to cash in on the AI boom, and why Samsung may follow SK Hynix with a U.S. listing.

Earnings season is underway as the major banks begin reporting. JPMorgan Chase (JPM) falls as CEO Jamie Dimon warns that economic risks are “shifting below the surface,” while Goldman Sachs (GS) posts a significant revenue beat and Bank of America (BAC) reports stronger trading revenue.In tech, chip stocks move higher following Monday's selloff in SK Hynix, while IBM plummets after releasing preliminary second-quarter earnings. Alex Coffey breaks down the biggest market moves and earnings takeaways.======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

Tech volatility took markets by storm with IBM Corp.'s (IBM) massive selling action and SK Hynix's (SKHY) substantial rally. Big banks also posted new record highs following earnings. Marley Kayden carries investors through the top stories of the trading session. ======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

Erst Pip Klöckner, jetzt Frank Thelen: Bei Deffner & Zschäpitz gibt der Antipode des Vorwochen-Gasts sein DuZ-Debüt. Beim Reform-Sommer fällt sein Urteil vernichtend aus, die Beschlüsse seien ein Zusammengemische, insgesamt katastrophal. Zschäpitz stimmt zu, Deffner verteidigt das Paket als größten Reformschritt seit der Agenda 2010. Dazu: Eine Quanten-Computer-Aktie aus Finnland, Trumps Wegzoll in der Straße von Hormuz, die KI-Rotation und die Frage, ob SK Hynix das Top der Speicherchip-Rally markiert. Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte: https://linktr.ee/deffnerundzschaepitz DEFFNER & ZSCHÄPITZ sind wie das wahre Leben. Wie Optimist und Pessimist. Im wöchentlichen WELT-Podcast diskutieren und streiten die Journalisten Dietmar Deffner und Holger Zschäpitz über die wichtigen Wirtschaftsthemen des Alltags. Schreibt uns an: wirtschaftspodcast@welt.de Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutzerklärung: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

Plus: Meta nearly doubles its planned investment in Louisiana data center project. And Intel will ramp up spending on expanded manufacturing in Ireland. Imani Moise hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

Treasury rates soaring to kick off the week, trading near highs not seen since the start of the Iran war. The traders break down the trend and what it means for bank earnings starting tomorrow. Then, Dow Jones Energy chief oil analyst Denton Cinquegrana gives his take on future oil prices and whether consumers can expect gas prices to fall back down to their June levels. Plus, Apple trading at record highs but SK Hynix hitting all-time lows, and SpaceX orbiting its initial offering price. Fast Money Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Plus: AI jitters weigh heavy on Nasdaq. And Paramount shares jump after a coalition of 12 states filed a lawsuit to block its acquisition of Warner Bros. Discovery. Alexis Moore hosts. Sign up for WSJ's free What's News newsletter. An artificial-intelligence tool assisted in the making of this episode by creating summaries that were based on Wall Street Journal reporting and reviewed and adapted by an editor. Learn more about your ad choices. Visit megaphone.fm/adchoices

Plus: The latest Journal survey of economists suggests high inflation is here to stay. And China greenlights Shein's Hong Kong IPO. Daniel Bach hosts. Sign up for WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

After the death of Senator Lindsey Graham (R-SC), former Congressman Patrick McHenry (R-NC) discusses Sen. Graham's legacy and the future of both the Republican and Democratic parties.  Shares of SK Hynix fell over 15% in Seoul on Monday after its impressive Friday debut of US-traded shares on the Nasdaq. Semafor's Rohan Goswami is reporting that friends and advisers of Paramount CEO David Ellison are pushing him to consider relocating the company out of California. Goswami discusses the state's role in Paramount's $110B takeover of Warner Bros. Discovery and the likelihood that the company will start fresh somewhere new. Plus, Apple is suing OpenAI, and Elon Musk and Sam Altman are taking shots at each other on X.    Emily Wilkins - 02:32 Patrick McHenry - 16:51 Rohan Goswami - 33:52   In this episode: Joe Kernen, @JoeSquawk Becky Quick, @BeckyQuick Andrew Ross Sorkin, @andrewrsorkin Emily Wilkins, @emrwilkins Katie Kramer, @Kramer_Katie Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Carl Quintanilla, Jim Cramer and David Faber kicked off a new week with the AI trade: Shares of SK Hynix tumbled 15% for its worst-ever day in the South Korean markets. The stock also fell sharply on Wall Street after surging 13% Friday in its U.S. trading debut — and dragged down memory names including Micron and Sandisk. The anchors reacted to the Sam Altman-Elon Musk's social media spat in wake of Apple's lawsuit against OpenAI. Also in focus: Oil prices jump on U.S.-Iran tensions, SpaceX shares fall closer to their $135 IPO price, Cramer on the non-tech names worthy of your attention, Disney's live-action "Moana" stumbles, Meta and data centers, American Express upgraded, "Faber Report" on State AGs vs. Paramount-WBD deal.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

MRKT Matrix - Monday, July 13th Stocks drop after Trump reimposes Strait of Hormuz blockade, SK Hynix leads chip stocks lower (CNBC) Wall Street Banks Set to Pull In Almost $39 Billion From Trading (Bloomberg) Think the S&P 500 Looks Cheap? Read the Fine Print (WSJ) Top Federal Reserve official warns ‘hot' inflation could trigger rate rise (FT) Businesses brace for years of inflation as new costs pile up (The Washington Post) K Hynix plunges after Nasdaq debut as memory chip euphoria cools (Reuters) Companies turn to Chinese AI models to cut costs (FT) --- Subscribe to our newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://riskreversal.substack.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ MRKT Matrix by RiskReversal Media is a daily AI powered podcast bringing you the top stories moving financial markets Story curation by RiskReversal, scripts by Perplexity Pro, voice by ElevenLabs

Apex Fintech Solutions provides the tools and services that enable hundreds of clients to launch, scale, and support digital investing for tens of millions of end investors. The company provides essential infrastructure and a comprehensive ecosystem of cloud-based products to enable and streamline trading, wealth management, cost basis, tax reporting, and, through its subsidiary Apex Clearing™, custody and clearing. LEARN MORE: https://apexfintechsolutions.com/?utm_source=Risk+Reversal&utm_medium=Podcast&utm_campaign=701PJ00000fnXhaYAE SUBSCRIBE to our newsletter: http://riskreversal.substack.com/ Dan Nathan & Guy Adami break down the top market headlines and bring you stock market trade ideas for Monday, July 13th. Show Notes Businesses brace for years of inflation as new costs pile up (Washington Post) The Noble Update (Substack) Companies turn to Chinese AI models to cut costs (FT) -- Learn more about FactSet: https://www.factset.com/lp/mrkt-callFollow us on Twitter @MRKTCallFollow @GuyAdami on TwitterFollow @CarterBWorth on TwitterFollow us on Instagram @RiskReversalMediaLike us on Facebook @RiskReversalWatch all of our videos on YouTube Learn more about your ad choices. Visit megaphone.fm/adchoices

The FCC will crack down on an action camera from DJI, but NOT on a plan to flood the Earth with light pollution from space mirrors. OpenAI keeps digging deeper into lawsuits, and now Apple is taking them to court. AI data centers are SURGING in power use, but a few areas are pushing back. SK Hynix expects the RAM crisis will get worse next year, as Samsung posts higher profit guidance after breaking records this year. Chinese courts allow for heirs to inherit game accounts. NVIDIA wants us to remember how much we used to like them, and thinks trading cards will win us back. And we have to chat about this FCC filing for the new Tensor G6 going into the Pixel 11. Let's get our tech week started off RIGHT! -- Show Notes and Links https://somegadgetguy.com/b/4ej Support Talking Tech with SomeGadgetGuy by contributing to their tip jar: https://tips.pinecast.com/jar/talking-tech-with-somegadgetgu Find out more at https://talking-tech-with-somegadgetgu.pinecast.co This podcast is powered by Pinecast. Try Pinecast for free, forever, no credit card required. If you decide to upgrade, use coupon code r-c117ce for 40% off for 4 months, and support Talking Tech with SomeGadgetGuy.

Andy Stewart, co-chief executive officer at Argosy Real Estate Partners, says that housing affordability issues that have made headlines are real and persistent, but there are some solutions over time, coming from building smaller homes, changes in interest rates and in public policies like the new affordability legislation that became law on Friday. It also means there are big opportunities in the single-family build-to-rent market and more, and those opportunities should be persistent and long-term. Stewart also talks about issues in data center construction — and whether the opportunity is moving too fast — and the continuing evolution of commercial real estate, where he sees "a generational buying opportunity" for patient, long-term investors. Vijay Marolia, chief investment officer at Regal Point Capital, says the record domestic IPO for SK Hynix last week and ASML Holdings on Wednesday, should remind investors to balance big numbers with appropriate caution, because the profit potential comes with white-hot volatility. He also looks at how financial and banking stocks could be in for a rough earnings cycle when they start reporting results this week, with their numbers reflecting how right or wrong they were in anticipating how the Federal Reserve and new chairman Kevin Warsh would respond to economic conditions. Plus, he also looks at housing affordability and how new legislation may impact the picture. David Trainer, founder and president at New Constructs, looks at current earnings trends and sees some ugly misses coming during the second quarter, not because companies are sandbagging earnings expectations, but because they're not as solid as the Street believes. He says a number of those stocks — and he singled out Fidelity National Information Services — are headed for trouble when the street figures things out after seeing an earnings miss.

Trump declared the Iran ceasefire "over" at a NATO summit, triggering a broad market selloff across crypto, stocks, and futures. ~This episode is sponsored by iTrust Capital~ iTrustCapital | Get $100 Funding Reward + No Monthly Fees when you sign up using our custom link! ➜ https://bit.ly/iTrustPaul 00:10 Sponsor: iTrust Capital 01:00 This week 01:45 Final drop 02:45 Straight of Hormuz under siege 03:45 Trump: We'll prob take over the Straight 04:40 Back to normal by December? 05:15 Oil reserves vs price 06:40 Mohamed El-Rian: Markets don't believe this  08:30 Yields rising 08:45 Mohamed El-Rian: Middle East impact on tech and yields 11:10 Rate Hike odds 12:30 SK Hynix collapse 13:10 SpaceX new lows 14:00 Saylor sells to buy? 14:30 8-week outflow ending? 15:00 ETH vs BTC 15:40 BMNR 4.8% 16:15 Tom Lee: What would break your crypto thesis? 17:20 45-50K bottom? #Crypto #Bitcoin #ethereum ~Macro Risks Surging

It's Indicators of the Week (now on YouTube!). On today's episode: You could've septupled your money if you invested in this scalding-hot South Korean memory chip stock; nearly half of all adults under 30 are moving back in with the ‘rents; and a new democracy is born … in Connecticut.  Fact checking by Julia Ritchey and Corey Bridges. Your Next Listen — Why Americans don't want to move for jobs anymore (Encore)Connect with The Indicator — Sign up for The Indicator's brand new newsletter — Find our socials, YouTube and more! — For sponsor-free episodes, subscribe to NPR+ See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

A.M. Edition for July 10. The South Korean chip-making giant raised more than $26 billion in the largest share sale by a non-U.S. company. Plus, the EU says Meta failed to protect Instagram and Facebook users from harm caused by addictive apps. And WSJ Middle East correspondent Anat Peled details how Israel learned of a new Iranian plot to kill President Trump. Daniel Bach hosts. Sign up for the WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

P.M. Edition for July 10. Apple's lawsuit also names one of OpenAI's top executives, a former Apple employee. Plus, Israeli intelligence about a possible plot to kill President Trump made U.S. officials concerned about a lack of defensive capabilities on the new Air Force One. The success of films like “Backrooms” and “Obsession” means Hollywood is combing sites like YouTube and Reddit for the next big horror hit. WSJ entertainment reporter Ben Fritz discusses who's making money from that and what risks there are for film studios. And South Korean chipmaker SK Hynix pops in its U.S. market debut. Alex Ossola hosts. A 'Mansion Tax' Complicated the Housing Crisis. Could a Federal Bill Fix It?  Sign up for the WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

#886: SK Hynix is slated to begin public trading on the Nasdaq as a company that has seen its stock pop more than sevenfold in due to the AI memory chip crunch. The NYC Midtown building partial-collapse scare has given pause to investors who thought it was supposed to be a boom-time for the office-to-residential revolution. Stock of the Week: Arts & crafts store Michaels is seeing success under private equity owner Apollo thanks to the demise of its competitors. Dog of the Week: Reading literacy in the US is sadly low. Finally, Claude launches its own version of “Wrapped.”  Get 10% off using MORNINGBREW10 at https://altrarunning.com/morningbrew Get tickets for our trivia tournament! https://caveat.nyc/events/the-morning-brew-trivia-tournament-2026-07-30  Grab tickets to our Performance Revue show! https://www.morningbrew.com/events/brew-performance-revue-2026?utm_campaign=performance_revue_2026&utm_source=mbd Subscribe to Morning Brew Daily for more of the news you need to start your day. Share the show with a friend, and leave us a review on your favorite podcast app. Listen to Morning Brew Daily Here:⁠ ⁠⁠https://www.swap.fm/l/mbd-note⁠⁠⁠  Watch Morning Brew Daily Here:⁠ ⁠⁠https://www.youtube.com/@MorningBrewDailyShow⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Plus: Circle gets federal approval to launch a crypto-focused bank. And China successfully launched a reusable rocket. Julie Chang hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

OpenAI broadly released GPT-5.6 and launched ChatGPT Work, targeting Anthropic. Fidji Simo stepped down from OpenAI citing health, the EU found Meta's "addictive design" violates the DSA, Polymarket sought margin trading approval, and SK Hynix debuted on Nasdaq raising $26.5B. OpenAI broadly releases GPT-5.6, and launches ChatGPT Work, an AI agent that can gather context across apps and files to create documents, on macOS and Windows (Axios) OpenAI broadly releases GPT-5.6, and launches ChatGPT Work, an AI agent that can gather context across apps and files to create documents, on macOS and Windows (TechCrunch) Fidji Simo, OpenAI's CEO of AGI Deployment, says she will step down and become a part-time adviser after her medical condition worsened; Simo joined in August (WSJ) In preliminary findings, the EU Commission said Facebook's and Instagram's "addictive design" violates the DSA, telling Meta to make changes or risk hefty fines (NYT) Filing: Polymarket is seeking CFTC approval to offer margin trading in the US, a move that would let users bet on events with less capital upfront (Bloomberg) SK Hynix raises $26.5B in the largest ever US market debut by a foreign company, selling 177.9M ADRs for $149 each; the sale was more than 7x oversubscribed (Bloomberg) SK Hynix raises $26.5B in the largest ever US market debut by a foreign company, selling 177.9M ADRs for $149 each; the sale was more than 7x oversubscribed (CNBC) Xreal launches $299 A01 Plus AR glasses, weighing just 62 grams and featuring 1080p micro OLED panels with a 120Hz refresh rate and a 50-degree field of view (The Verge) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

SK Hynix begins trading on the Nasdaq in the second largest U.S. listing ever, raising over $26 billion and closing 13% above opening price. Tech strategist and analyst Dan Ives breaks down where the South Korean tech giant is heading next and what the IPO means for the memory market. Then, big banks heading into another strong earnings season next week. The traders lay out why Wall Street is expecting good results, and whether the results are sustainable long-term. Plus, Apple trading near record highs, Delta shares slipping despite its earnings report soaring above expectations, and Meta's best week since 2024.   Fast Money Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.