Podcasts about Blackstone

US equity futures are trading higher, with the S&P up around 0.6%. Bonds are firmer, with the US 10-year yield down 2 bps at 4.7% and the Bund down 5 bps at 3.2%. The dollar is mixed, firmer against the euro, sterling, and the Aussie, but under pressure versus the yen following FX intervention. In commodities, oil is notably weaker, with WTI crude down 6.5% below $80 a barrel, while gold is trading firmer and industrial metals are mostly lower. Bitcoin is also lower. Market sentiment is benefiting from news that President Trump called off planned strikes against Iran to allow room for negotiations over Strait of Hormuz. Trump said talks would begin Monday and posted parameters of deal have been agreed to. Iran echoed by noting an agreement on Strait of Hormuz close. Companied mentioned: AstraZeneca, BMS, Shell Plc, Blackstone

Subscribe for free weekly Property Management News & updates: https://peter.beehiiv.com/KKR just made a major change to how it manages its single-family rental portfolio. Here's what happened:KKR is ending its asset management relationship with Avenue One and bringing oversight in-house through its subsidiary, My Community Homes (MCH)~10,000 SFR doors are affected across four property managers: Mynd (4,000), Evernest (3,500), North Point (1,500), and Pure Home River (1,000)MCH is keeping Mynd on, but cutting Evernest, North Point, and Pure Home River loose — most of the work is shifting to Darwin Homes insteadThe move follows new legislation restricting large investors from buying SFRs, plus a broader trend of institutional owners pulling property management in-house (Blackstone did the same earlier this year)North Point expects to lose ~30% of its door count; Evernest and Pure Home River are looking at roughly 15% and 3% hits, respectivelyLesson: don't tether too much of your business to one or two institutional clients.___Resources for Property Managers & Real Estate Entrepreneurs:Crane – Private PM Owner Community → Join a private network of property management owners and operators: https://joincrane.co/Free Weekly Newsletter → Property management insights, strategies, and industry updates direct to your inbox: https://peter.beehiiv.com/subscribeRL Property Management → Learn more about Peter's company and services in Columbus, Ohio: https://rlpmg.com/__Disclaimer: The content of this news video is for informational purposes only and does not constitute professional advice. I may have consulting agreements with, or financial interests in, companies mentioned in this podcast (more info here: https://www.peterlohmann.com/financial-interest-disclosure ). Additionally, some of the links included may be affiliate links, meaning I may earn a commission if you purchase through these links. Always perform your own due diligence before making any financial or business decisions.

Apprendre à investir en bourse ➡️ https://www.rachelfinance.com/weinvest/youtube (We Invest)

Private equity is expanding into India’s K-12 school sector, following the same playbook it used to reshape private hospitals. Since Indian schools must legally operate as not-for-profit trusts, PE firms like KKR, Blackstone, and Kedaara invest indirectly through separate for-profit “OpCo” service companies that charge trusts for management, infrastructure, and operations—mirroring hospital structures. The appeal: predictable, long-term cash flow from families who rarely withdraw children mid-cycle, rising fees, and unmet demand for quality private education. Regulatory hurdles, fee caps, and mandated free seats for low-income students complicate profitability. Unlike hospitals, no major PE-backed education platform has yet achieved a successful exit, leaving the model’s long-term viability untested. Alenjith K Johny and Mohit Bhalla report; Anirban Chowdhury narrates for audio. You can follow Anirban Chowdhury on his social media: X and LinkedinCheck out other interesting episodes like:ET Deep Dive: Swipe Left on Reality,India wants manufacturing at 25% of GDP — will AI in factories help?, Tanay Kothari Wants To Kill The Keyboard, From Doer to Director: The LinkedIn Playbook for the AI Agea, Semaglutide Goes Generic: Big Pharma’s Moat Breaks and much more. Catch the latest episode of ‘The Morning Brief’ on The Economic Times Online, Spotify, Apple Podcasts, JioSaavn, Amazon Music and Youtube.See omnystudio.com/listener for privacy information.

THRESHOLD is a direct continuation of Malevolent, the Audio Drama. This Series 2 sees John and Arthur having returned to Arkham after their time seeking the BLACKSTONE and facing the new and terrible truth this world has revealed to them. Faced with the new challenges before them and old foes perhaps still a threat, the duo must carve a new path in this strange world.Featuring Jo Guthrie as "Faroe"Support Malevolent and be a part of the story now at: https://www.patreon.com/TheINVICTUSStream Hosted on Acast. See acast.com/privacy for more information.

We spoke with Julian Adair - President, Director, and Instructor with her company, the Adair Dance Academy, and is also the Artistic Director of Ever After Productions.   We always have a delightful conversation with Julian, and we had podcasted about "A Suite For Small Spaces III", held at Shelterbelt, however, we touched on different things this podcast, including that "A Suite for Small Spaces IV" at the Omaha Fringe Festival at UNO006 will be a different show than the third one!  So even if you saw the third one, you won't want to miss this intimate and exquisitely moving production of the fourth one.  Each vignette has their own texture and feeling and we are excited to see this production! Tickets and Website: https://omahafringe.org Omaha Fringe Festival Kick Off Party - August 5th @ Shelterbelt Fringe Festival Dates: August 6-9, 2026 at UNO, Blackstone and Shelterbelt Theatre Dates for "A Suite for Small Spaces IV" (no production August 6th):  Friday, August 7th at 9:30pm, Saturday August 8th at 6:30pm, and Sunday August 9th at 2pm.     HOW TO LISTEN TO THE PLATTE RIVER BARD PODCAST Listen at https://platteriverbard.podbean.com or anywhere you get your podcasts. We are on Apple, Google, Pandora, Spotify, iHeart Radio, Podbean, Overcast, Listen Now, Castbox and anywhere you get your podcasts. You may also find us by just asking Alexa. Listen on your computer or any device on our website: https://www.platteriverbard.com. Find us on You Tube: https://youtube.com/channel/UCPDzMz8kHvsLcJRV-myurvA. Please find us and Subscribe!

Bonus Episode for July 31. Investment firms like Blackstone, KKR and Blue Owl have been battered over the past year by a client exodus from private-credit funds. WSJ lead financial reporter AnnaMaria Andriotis discusses the state of the industry's recovery from a surge in redemption requests from rattled investors and whether these firms' investments in AI can help them recover from blows to the software sector. WSJ reporter Matt Wirz, who covers credit, hosts this special bonus episode of What's News in Earnings, where we dig into companies' earnings reports and analyst calls to find out what's going on under the hood of the American economy. Sign up for the WSJ's free Markets A.M. newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Stablecoins are reshaping how credit is created, priced and distributed. As balances grow, holders are looking for yield, and a new generation of on-chain asset managers is stepping into territory that once belonged exclusively to banks and private credit giants. In this episode, we discuss:

P.M. Edition for July 30. The U.S. economy grew just 1.5% last quarter, lower than the previous quarter and falling short of economists' expectations. WSJ economics reporter Harriet Torry explains why the details in the report, particularly around consumer spending, suggest things aren't as bad as the headline number makes it seem. Plus, the buzzy AI-focused hedge fund Situational Awareness, founded by AI whiz kid Leopold Aschenbrenner, sold most of its stock portfolio to investment firm Citadel. We hear from WSJ special writer Greg Zuckerman about why this happened and where the company goes from here. And a big rally in tech companies sent U.S. stocks soaring today. Alex Ossola hosts. See the new fronts in the Iran war.  Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The Bower Brothers are local legends for Corunna folks, but they're on to Ferris State where they've now won a couple national titles. They join us on Ep. 417 to talk about that championship run, preparing for the upcoming season, and plenty more! The Tigers are in a trade deadline dilemma, NBA roster movement always makes headlines, summertime catch-up, and more! Take a listen and hit us up @3pointpod! Thanks to: Memorial Healthcare Wellness Center, Blackstone's Public House, Nelson House Funeral Home, Success Group Mortgage & Servicing, Kori Shook & Associates, Jacobs Insurance, AZee Branding Solutions, Pickpocket Sports & Outdoors, Lebowsky Center, Marrs Furniture & Mattress Barn, Shiawassee County Fair, Nichols Painting, Great Lakes Apparel Co., SportsNet MI

HEADLINES:• PIF Moves to Tackle Al-Nassr's $213 Million Debt Crisis • Blackstone Opens Kuwait Office After $16 Billion Infrastructure Deal • Bar Works Fraudster Ordered to Repay $58 Million After Scamming UAE Investors  Newsletter: https://aug.us/4jqModrWhatsApp: https://aug.us/40FdYLUInstagram: https://aug.us/4ihltzQTiktok: https://aug.us/4lnV0D8Smashi Business Show (Mon-Friday): https://aug.us/3BTU2MY

العناوين:• PIF يتحرك لمعالجة أزمة ديون Al-Nassr البالغة 213 مليون دولار• Blackstone تفتتح مكتبًا في الكويت بعد صفقة بنية تحتية بقيمة 16 مليار دولار• إلزام المتورط في احتيال Bar Works بسداد 58 مليون دولار بعد الاحتيال على مستثمرين من الإمارات

In this episode of The Capital Raiser Show, Richard C. Wilson sits down with Marcus Ridgway, founder of F6 Partners and co-founder of Invitation Homes, for a fireside chat on attracting institutional capital at scale, building frameworks that earn the trust of the world's largest investors, and why extreme conservatism - not big risk - is what created one of the most impressive real estate track records in the country. Marcus shares how building institutional-grade systems from day one led to Blackstone wiring $35 million before a single document was signed, and how they ultimately scaled that relationship to $1 billion - all because the architecture, software, and reporting were airtight from the start. The conversation dives into risk mitigation frameworks, optionality as an insurance policy against volatility, the mindset shift from hustle to architecture, what separates centimillionaires from founders who never scale, and why Marcus believes fat tail risk is the defining challenge facing every investor in the years ahead. Topics covered include: Securing $4 billion from Blackstone and taking Invitation Homes public on the NYSE Why institutional investors never look at IRR - only downside risk Building architecture that creates returns vs. relying on hustle to create results Why exactness and transparency with institutional capital is non-negotiable Creating an investment committee even for a single house purchase How a cold call from an industry researcher led directly to Blackstone Optionality as an insurance policy against volatility Returning $200 million to an investor when the strategy no longer made sense Offshoring decisions so the business doesn't depend on one person Separating ego and identity from outcomes as a founder Student housing and senior housing as the top opportunities right now Fat tail risk - why black swan events are increasing in frequency and what to do about it How conservative structuring, not big bets, built a billion-dollar platform The Capital Raiser Show brings together billionaire investors, family offices, elite entrepreneurs, and capital allocators to discuss investing, scaling, strategic growth, and wealth creation. Subscribe for more interviews with top investors, founders, family offices, and industry leaders.

In this episode of the Smashi Business Show, we examine President Donald Trump tying a civil nuclear deal with Saudi Arabia directly to the Abraham Accords. We then break down a historic $16 billion foreign investment in Kuwait's oil pipeline network by Blackstone, KKR, and Brookfield. Finally, we cover Iraq's strategic decision to construct new Mediterranean export pipelines through Syria alongside new energy development tenders.

Saudi Arabia's tallest ambition is rising again as Prince Alwaleed bin Talal confirms Jeddah Tower has reached another major construction milestone. Kuwait signs the largest foreign direct investment in its history with a $16 billion pipeline deal involving Blackstone, Brookfield and KKR. Plus, prediction market giant Kalshi, founded by Lebanese entrepreneur Tarek Mansour, takes on Netflix over claims made in an upcoming documentary. Here's what it all means for business, investment and the Middle East.

Send us Fan MailA fruit sour just earned a straight-up 10, and we were not shy about it. We crack open Cheeky Kiki from Prairie Artisan Ales and get hit with pineapple first, then lime, orange, and a coconut rum vibe that drinks more like a beach cocktail than a face-puckering sour. We talk can art, sweetness vs tartness, and why this sour ale works when so many “fruit sours” go overboard.Then we take a hard left into real life: posting beer content online without getting flagged, why Instagram feels easier than Facebook, and the little behind-the-scenes stuff that comes with running a beer podcast. From there, the conversation turns into food, and we share a legit Blackstone griddle pizza hack: pre-cook your toppings, crisp the dough, flip it, build it fast, and use a lid to melt the cheese. If you are into Blackstone recipes, griddle cooking, and easy weeknight wins, you will want to steal this one.After the break, we test DuClaw Sweet Baby Banana, a porter built on the Sweet Baby Jesus base with chocolate, peanut butter, and banana. We wanted dessert beer magic, but what we got is bitterness and a banana note that feels faint and a little chemical, so we rate it accordingly. We also toss in a round of “What Would You Choose” and end with our weekly “another reason to drink,” including work stress and why we still love showing up for this studio time.Subscribe for more craft beer reviews, share the episode with your drinking buddy, and leave us a review if you like the honest takes. What beer surprised you the most this year?Support the showwww.anotherreasontodrink.com

P.M. Edition for July 23. The U.S. plans to impose new tariffs on most trade partners, replacing President Trump's temporary global 10% tariff. Plus, the threat of escalating conflict in the Middle East drove oil prices over $100, and concerns around higher inflation made bond yields surge. WSJ markets reporter Sam Goldfarb discusses how that ripples through the economy. Meanwhile, heavy AI spending from Alphabet and Tesla spooked investors, and the Nasdaq dropped more than 2%. And after IBM issued a rare profit warning last week, the company's earnings shed more light on what went wrong. We hear from reporter Anissa Gardizy about where its business goes from here, while tech columnist Christopher Mims spoke with IBM CEO Arvind Krishna. Alex Ossola hosts. Correction: New U.S. tariffs target 60 economies, or more than 80 countries. An earlier version of this podcast incorrectly said the tariffs target 60 countries. (Corrected on July 24.) Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Plus: The FDA is investigating a new outbreak of cyclospora adding to three other active flare-ups. And US stock futures are pointing to a lower open after shares in Alphabet and Tesla slipped off-hours. Luke Vargas hosts. Sign up for WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

US and Iran exchanged strikes for the 12th consecutive night; US President Trump said Iran is getting hit so hard and that they want to make a deal.Yemeni Houthis targeted two Saudi oil tankers in the Red Sea, while reports noted that at least 9 ships have stopped passing through Bab al-Mandeb, following the blockade on Saudi ports by Houthis.Alphabet (GOOGL) shares fell -3.3%, Tesla (TSLA) slipped over 4%, and IBM (IBM) was modestly softer post-earnings.APAC stocks were predominantly in the green, DXY mildly softened, 10yr UST futures lingered near the prior day's trough, and crude futures extended gains.European equity futures indicate a slightly lower cash market open, with Euro Stoxx 50 futures down 0.3%.Looking ahead, highlights include Canadian Retail Sales (May), US Initial Jobless Claims (Jul/18), Chicago Fed National Activity Index (Jun), EU Consumer Confidence Flash (Jul). Policy Announcements from the ECB, CBRT, and SARB. Comments from ECB President Lagarde. Supply from the UK & the US. Earnings from Intel, Blackstone, Lockheed Martin, RTX, TotalEnergies, Thales, SAP & Repsol.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

US Secretary of State Rubio said Iran was intending to double missile stockpile and that it looks like Iran is not ready to make a deal. He added that the price on Iran will get higher every night until they come to their senses but that Iran is begging to reach a deal.Yemeni Houthis targeted two Saudi oil tankers in the Red Sea, while reports noted that at least 9 ships have stopped passing through Bab al-Mandeb, following the blockade on Saudi ports by Houthis. US equity futures are softer across the board as Alphabet raises AI Capex guidance and STMicroelectronics misses Q3 revenue guidance estimates.DXY rangebound, AUD outperforms after a strong jobs report. Fixed income lower but off worst levels as energy prices continue to drive price action (Brent +4.5%).Looking ahead, highlights include Canadian Retail Sales (May), US Initial Jobless Claims (Jul/18), Chicago Fed National Activity Index (Jun), EU Consumer Confidence Flash (Jul). Policy Announcements from the ECB, CBRT, and SARB. Comments from ECB President Lagarde. Supply from the US. Earnings from Intel, Blackstone, Lockheed Martin & SAP.Read the full report covering Equities, Forex, Fixed Income, Commodites and more on Newsquawk

(July 21, 2026 - Hour One)Show Summary:Meatman is back with another massive Tuesday night lineup on the longest-running podcast in BBQ! Before we get to the interviews, the opening monologue tackles a wild viral video of a hair transplant gone completely off the rails—you won't believe the facial swelling on this guy.After that, it's a stacked four-guest roster covering everything from the business of the outdoor cooking industry to the ultimate fast-food burgers.On Tonight's Episode:Dan Arnold | CEO, Suckle BustersIt's been a minute, but Dan is back on the show to catch up. We're talking rubs, sauces, seasonings, and seeing what's new in the world of Suckle Busters.Wes Wright | Creator, Cookout NewsWes drops in for his monthly visit to break down the BBQ and grilling industry from a strictly business perspective. We dive into market trends, news, and what's moving the needle.Sam The Cooking Guy | YouTube CreatorThe YouTube legend joins the show to catch up on his latest recipe drops, the grind of content creation, and balancing it all with family.Ali Khan | TV Host & Content CreatorOur favorite new guest returns! We're talking all things beef, the anatomy of a perfect burger, and diving into the fast-food reviews he's been uploading to social media.All this plus a new "Would You Rather" YouTube Poll Question of the week and results from last week's poll.The BBQ Central Show SponsorsPrimo GrillsFireboardMicallef Cigars – Premium Hand Rolled Cigars

Send us Fan MailDr. Robin Blackstone joins Dr. Mitchell Rothstein to talk about the intersection of technology, empathy, and the healthcare system. The doctoral duo discuss the emerging role of AI in healthcare and how specialized, individualized, non-chatbot systems may be able to sift through the masses of health data that plague doctors to provide individualized, patient-specific recommendations and revelations. The two also briefly discuss the history of healthcare in order to present Dr. Blackstone's vision for the future, Health 4.0. They finish the discussion with more details about Dr. Blackstone's Public Benefit Corporation, The H4 Alliance Trust, a 5013c project focusing on a person-centered health system. Find more about the H4 Alliance Trust at h4alliancetrust.orgBe a part of advancing science by participating in clinical research.Have a question for Dr. Koren? Email him at askDrKoren@MedEvidence.comListen on SpotifyListen on Apple PodcastsWatch on YouTubeShare with a friend. Rate, Review, and Subscribe to the MedEvidence! podcast to be notified when new episodes are released.Follow us on Social Media:FacebookInstagramX (Formerly Twitter)LinkedInWant to learn more? Checkout our entire library of podcasts, videos, articles and presentations at www.MedEvidence.comMusic: Storyblocks - Corporate InspiredThank you for listening!

What does your spine have to do with staying sober? More than you think. In this episode of I Love Being Sober, recorded live at Camelback Recovery in Scottsdale, Arizona, Tim Westbrook sits down with Dr. Marc Blackstone, a board-licensed chiropractic physician with more than 25 years of clinical experience who has spent the past five years bringing chiropractic care into mental health and addiction treatment settings.Dr. Blackstone breaks down the mind-body connection in plain language: how a chiropractic adjustment affects far more than the joint being treated, why addiction and mental health conditions keep the sympathetic (fight-or-flight) nervous system stuck in overdrive, and how adjustments help activate the parasympathetic (rest-and-digest) response that lowers cortisol, reduces anxiety, and supports better sleep in early recovery.He also delivers one of the most important warnings of the episode: unresolved chronic pain is a real relapse risk. With more than half of chronic pain patients likely to use opioids, treating the physical damage people carry into recovery isn't a luxury. It's relapse prevention.In this episode, you'll learn: how a rugby injury at age 14 led Dr. Blackstone to chiropractic; what he sees treating clients in recovery settings versus traditional practice; what actually happens in your body during an adjustment; why the body reverts to old patterns (and why one visit isn't enough); how chiropractic supports people detoxing from opioids, amphetamines, and alcohol; the forgotten history of chiropractic sanitariums treating mental health in the 1920s; his advice for anyone in early recovery dealing with pain; and what it would take to bring chiropractic care into every treatment center in America.Whether you're navigating substance use disorder, supporting a loved one in recovery, or running a treatment program and wondering what holistic care really looks like, this conversation makes the case that recovery has to include the body, not just the mind.Connect with Dr. Marc Blackstone: info@azchiropracticservices.com | drblackstone.comI Love Being Sober is hosted by Tim Westbrook, MS, founder and CEO of Camelback Recovery, an addiction and mental health treatment center in Scottsdale, Arizona. Learn more at CamelbackRecovery.com.Click Here for more information about Camelback Recovery

In this episode of The Wrap with Chris Whalen, Chris breaks down a blockbuster week of bank earnings — and why the record numbers mask a growing problem. Wall Street trading and investment banking revenues are exploding, but banks aren't making money on money, as asset yields fall for a sixth straight quarter and private credit giants like Apollo poach deals. Whalen flags roughly $4 trillion in bank exposure to non-depository financial institutions, warns "there are no regulators in Washington" watching the risks, and says the housing market's business-purpose loan boom "feels like 2005." He sticks with his double-digit inflation call, arguing diesel — not oil — is the real story, and predicts fuel shortages, maybe even rationing, before the midterm elections. Plus: Kevin Warsh's Greenspan-style Fed debut, gold's selloff as a buying opportunity, viewer questions on Annaly, and a World Cup prediction.Thank you to our sponsor, Monetary Metals. Learn more at https://www.monetary-metals.com/THEWRAP/Links:    The Institutional Risk Analyst: https://www.theinstitutionalriskanalyst.com/  The Wrap: https://www.theinstitutionalriskanalyst.com/post/theira869Twitter/X: https://twitter.com/rcwhalen    Seeing Around Corners book: https://www.theinstitutionalriskanalyst.com/product-page/seeing-around-corners-achieving-success-in-business-and-life-hardcoverUse the code TheWrap2026 for 25% off your first year of The Institutional Risk Analyst https://www.theinstitutionalriskanalyst.com/plans-pricingTimestamps:0:00 — Intro and welcome 00:55 Bank earnings and oil prices soar as Middle East war reignites2:36 — Bank earnings disconnect: Wall Street booms, lending shrinks3:55 — Why big deals keep going to private credit (Apollo, Blackstone)5:59 — The hidden risk: banks lending directly to private credit funds9:06 — The $4 trillion exposure — "no regulators watching the hen house"10:07 — The "Everything Bubble": rising rates, falling yields, record home prices12:06 — Kevin Warsh's Greenspan-style Fed: "inflation is a choice"14:40 — Rate hike odds cool — will the Fed wait until after midterms?15:42 — Energy shortages building: why the Trump administration stays quiet16:45 — Double-digit inflation call stands; possible rationing by Election Day17:53 — Iran destroyed Gulf refining capacity — years to rebuild21:52 — Housing: sales fall 2.4%, median price hits record high23:14 — "It feels like 2005" — DSCR and non-QM loans flash warning signs27:19 — Gold selloff: why Chris is buying more (especially silver)29:37 — Viewer Q: How rates affect Annaly (NLY) — it's all about the spread31:03 — Viewer Q: Warsh's 2% target vs. $80 oil — a double whammy?32:27 — Chris's World Cup prediction: Argentina

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'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

Chinesische Open-Source-Modelle schließen zu westlichen Modellen auf. Bei OpenAI wird das erste eigene Gerät konkret, während ein Analyst vorrechnet, dass das Werbegeschäft die eigene Prognose um 90% verfehlt. Codex und ChatGPT Work kommen auf 8 Mio. aktive Nutzer, gleichzeitig räumt OpenAI ein, dass Codex in seltenen Fällen das Home-Verzeichnis löscht. Google verschiebt den Gemini-Launch, weil die Technik interne Ziele verfehlt. Anthropic und Blackstone wetten, dass das nächste Billionen-Geschäft die Implementation ist, nicht die Modelle selbst. Bei Musk gibt es eine Identitätskrise rund um SpaceXAI, Grok Build wird nach dem Datenskandal open source, und für den Compute-Hunger wird eine Gasturbinen-Firma gekauft. In Europa lockert die EU unter US-Druck die Regeln für Meta-Brillen und zwingt Google gleichzeitig zur KI-Interoperabilität. Dazu die große Konsolidierung: Uber übernimmt Delivery Hero und Salesforce schluckt Contentful. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) OpenAI Speaker (00:03:17) Codex Micro (00:05:29) OpenAI Werbe-Flop 6 Codex 8 Mio. Nutzer (00:11:28) NY Datacenter-Moratorium (00:14:18) Stripe PayPal (00:28:58) Thinking Machines (00:31:49) Soofi-S (00:35:26) Open-Source-AI-Report (00:37:24) Kimi 3 überholt Fable 5 (00:39:16) DeepSeek $74 Mrd. (00:40:10) Gemini verschoben (00:41:18) Ramp KI-Kosten (00:45:53) Earnings: ASML, TSMC, Netflix (00:48:05) Anthropic x Blackstone (00:50:18) Spahn (00:54:14) Truth API (00:59:48) Trump-Insiderwetten (01:01:27) EU lockert Meta-Brillen (01:02:45) Grok lädt Nutzerdaten hoch (01:05:07) SpaceXAI Chaos (01:05:40) Musk kauft APR Energy (01:06:55) xAI-Kraftwerk Umwelt (01:07:20) China vs. Chatbot-Liebe (01:08:37) Globales KI-Gremium (01:09:33) KI-Slop auf Amazon (01:11:26) Eli Lilly kauft Atai (01:12:32) Uber Delivery Hero, Salesforce Contentful (01:13:24) Schwarz Digits Shownotes OpenAI-Speaker ohne Bildschirm - bloomberg.com Codex Micro Keypad - worklouder.cc OpenAI-Werbung verfehlt Ziel um 90% - adweek.com Codex: 8 Mio. Nutzer - xcancel.com Codex löscht Home-Verzeichnis - xcancel.com NY: Moratorium für KI-Rechenzentren - theverge.com Stripe & Advent bieten für PayPal - linkedin.com PayPal-Board lehnt Angebot ab - reuters.com Thinking Machines launcht Inkling - wired.com Soofi-S: deutsches 30B-Modell - the-decoder.com State of Open-Source-AI (Mozilla) - stateofopensource.ai Kimi 3 schließt zu Opus 4.8 auf - techcrunch.com Kimi K3: Fable/Sol-Niveau - xcancel.com Google verschiebt Gemini - bloomberg.com Ramp: KI-Kosten-Dashboard - ramp.com ASML hebt Prognose an - cnbc.com TSMC: +80% Q2-Gewinn - cnbc.com Netflix Q2-Zahlen - cnbc.com Anthropic & Blackstone: Implementation statt Modelle - techcrunch.com Kimi-K3 überholt Fable 5 (Arena) - xcancel.com DeepSeek: $74 Mrd. vor IPO - reuters.com DeepSeek plant Börsengang - ft.com Truth API: Trump-Posts für Wall Street - cnbc.com Insiderwetten auf Trump-Reden - spiegel.de EU lockert Regeln für Meta-Brillen - politico.eu Grok Build lädt Daten hoch, wird Open Source - simonwillison.net Musk zur SpaceXAI-Datenspeicherung - xcancel.com SpaceXAI in der Identitätskrise - bloomberg.com Musk kauft Gasturbinen-Firma APR Energy - electrek.co xAI-Kraftwerk belastet Black Communities - reuters.com China verbietet Chatbot-Liebe - wsj.com 29 Länder gründen KI-Gremium - reuters.com KI-Slop-Biografien auf Amazon - nytimes.com Jens Spahn ist Vater geworden - spiegel.de Eli Lilly kauft AtaiBeckley ($2,8 Mrd.) - pharmaceutical-technology.com Uber vor Delivery-Hero-Deal (FT) - ft.com Uber kauft Delivery Hero ($14,8 Mrd.) - bloomberg.com Pausder plant ARK Labs (Palantir-Vorbild) - manager-magazin.de Salesforce kauft Contentful (1,3 Mrd.) - manager-magazin.de Schwarz-Gruppe gibt XM Cyber ab - manager-magazin.de EU zwingt Google zu KI-Interoperabilität - theverge.com ZDF untersagt Levit & Danger Dan - spiegel.de Doppelgänger Orakel - doppelgaenger-orakel.com

Netflix shares tumble despite double-digit revenue growth, reminding investors that lofty expectations can outweigh solid results. Hosted by Michelle Martin, this episode explores why TSMC continues to ride the AI wave while Nvidia expands its physical AI ambitions and Alphabet faces fresh pressure over delays to Gemini 3.5 Pro. We also discuss Blackstone-backed AirTrunk's planned Singapore REIT IPO, the global pullback in AI stocks, and why some strategists believe US small caps are enjoying their strongest run in decades. Plus, in Up or Down: SpaceX comes under pressure after a failed Starship test and growing short interest, while Thailand's stock market stages one of the year's most surprising turnarounds.See omnystudio.com/listener for privacy information.

Dice Shame Recommends! Before we jump into Season 3 of Dice Shame, check out our sister show, MALEVOLENT!Malevolent: THRESHOLD is a direct continuation of Malevolent, the Audio Drama. This Series 2 sees John and Arthur having returned to Arkham after their time seeking the BLACKSTONE and facing the new and terrible truth this world has revealed to them. Faced with the new challenges before them and old foes perhaps still a threat, the duo must carve a new path in this strange world.Featuring Jo Guthrie as "Faroe"Support Malevolent and be a part of the story now at: https://www.patreon.com/TheINVICTUSStream Hosted on Acast. See acast.com/privacy for more information.

(July 14, 2026 - Hour Two)On the show tonight (All Times Eastern):9:14pm - David Gafford - The Barbecue Lab9:35pm - Robert Moss10:14pm - Roger Dahle - Weber/Blackstone CEOAll this plus a new "Would You Rather" YouTube Poll Question of the week and results from last week's poll.The BBQ Central Show SponsorsPrimo GrillsFireboardMicallef Cigars – Premium Hand Rolled Cigars

Trump heads to the Army War College in Pennsylvania for Senator Dave McCormick's defense summit, and somehow turns an infrastructure announcement into a masterclass on aircraft carrier catapults. Nearly $10 billion in new defense investment gets unveiled on the spot, submarines, shipyards, missile components, robotics hubs, and a passionate, extended rant about why magnets do not belong on Navy elevators. The room is stacked with heavy hitters, Jamie Dimon, Boeing's CEO, Lockheed, General Dynamics, Blackstone, all taking turns praising the new pace of business at the Pentagon. Between the economic numbers and manufacturing stats, there's a serious policy announcement on commercial truck licensing, a teaser for a "very big" Thursday announcement on election integrity, and a genuinely emotional moment honoring a fallen state trooper. It's part economic victory lap, part military pep rally, and part engineering opinion piece, with a truck cameo that gets compared to the infamous Dukakis tank moment.

Founders 100 ETFs CIO Lauren Cassidy explains why she believes today's banking environment is the strongest in decades, driven by healthy capital markets, renewed IPO activity, and resilient lending trends. She also shares her outlook on private credit, market growth through 2027, and the upcoming earnings reports from leaders including Nvidia's (NVDA) Jensen Huang, Oracle's (ORCL) Larry Ellison, and Blackstone's (BX) Stephen Schwarzman.======== 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

In today's Cloud Wars Minute, I explain why hyperscalers are rewriting the rules of deal-making to build the next generation of AI infrastructure. Highlights 00:01 — We are seeing the beginnings here of an incredible round of innovation, not just in technology, but in deal-making, partnerships, alliances, and financing, all by the hyperscalers trying to meet this insatiable AI demand. We're seeing these companies undertake some very innovative, bold, distinctive new strategies to build the capability and capacity to get these AI data centers built out to meet this insatiable demand. 00:49 — Google Cloud did a joint venture with Blackstone, in which Blackstone invested $5 billion into the joint venture. We have seen Amazon issue a series of debt and bond offerings totaling over $100 billion. AWS has said that in calendar year 2026 it will spend $200 billion on CapEx, most of which is going into AI data centers. Oracle announced $50 billion in debt and equity financing. 01:57 — This funding, this raising of funds to build out the data centers, is because there is, among these hyperscalers, over $2 trillion in committed contracted business. While Oracle right now is the smallest by revenue of the hyperscalers, it has the largest backlog, and in order to meet that, it has to spend a lot of money to build the capacity. 02:46 — Microsoft is using proceeds from its brilliant early relationship with OpenAI to help secure some of the funding. Under a newly restructured agreement between the two companies, Microsoft now will receive 20% of OpenAI revenues for the next few years. Plus, Microsoft has a huge ownership stake in OpenAI. 04:17 — Remarkable things are going on here as the technology buildout by all these companies has helped create this incredible demand. What we're seeing now is extraordinary efforts by the hyperscalers to combine with other companies, move into different industries, and do everything possible — at staggering expense — to meet this insatiable customer demand for AI. Visit Cloud Wars for more.

As part of our ongoing series of episodes devoted to thecelebration of the 250th Anniversary of the Declaration, we are delighted to bring you an episode devoted to the legal relevance of the Declaration's most famous sentence, “We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain unalienable Rights, that among these are Life, Liberty and the pursuit of Happiness.” We'll focus in today's episode particularly on that last phrase. In his Commentaries on the Laws of England, William Blackstone described the pursuit of happiness as a science of jurisprudence by which his students could identify, and then apply, the first principles of the Common Law in their future work in law.  Separately, the American founders includedthe pursuit of happiness as one of only three unalienable rights specifically listed in the Declaration of Independence.  Where do Blackstone and the founders agree and disagree in their understanding of the pursuit of happiness? What practical role (if any) did they suggest the concept could serve in English and early American law and legal philosophy? To discuss these subjects, we are pleased to have Carli N. Conklin with us. She is an associate professor at University of Missouri School of Law, an associate professor of constitutional democracy and former associate director at theKinder Institute on Constitutional Democracy, and director of the School of Law's Center for the Study of Dispute Resolution. She earned her JD/MA and PhD in American Legal History from the University of Virginia, where she received the School of Law's John and Madeleine Traynor prize for outstanding written work. This episode is captured from a jointly-sponsored webinar by the James Wilson Institute and the Center for Religion Culture and Democracy of First Liberty Institute.

Brendan Wallace is the Founder, CEO & CIO of Fifth Wall, the largest investment firm focused on technology for the built environment, with ~$3B in capital, the firm is driving the growth of nearly 170 companies, backing category-defining PropTech leaders such as Opendoor, Procore, Blend, Hippo, and Bilt Rewards. It's supported by ~115 of the world's largest real estate owner-operators including CBRE, Hilton, Hines, Marriott, Public Storage, Related, and Starwood. Before Fifth Wall, Brendan was at Goldman Sachs and Blackstone, and he co-founded Identified (sold to Workday) and Cabify. In this episode of Summation, Brendan and Auren discuss:How remote work protected mediocrity for yearsThe data center land grab: powered land, 2037 grid connections, and bring-your-own-solarHow land is the most stable asset on earth and there's still no way to buy an index of itWhy "capital-intensive businesses are bad for venture" is no longer trueYou can find Auren Hoffman on X at @auren and Brendan Wallace on X at @BrendanFWallace

Gerard and Laurent first welcomed David Scaysbrook to the podcast in Episode 66, back in January 2022, for a conversation about the future of 24/7 power. Four years later, it felt like the right moment to reconnect and take stock of how profoundly the market has evolved.  Since then, Quinbrook Infrastructure Partners has continued to establish itself as one of the leading specialist investors in the energy transition, orchestrating and deploying billions of dollars of capital through project finance structures and platform companies.   As of today, the firm has participated in more than $27 billion of transactions, developed or acquired over 240 projects, and built a portfolio exceeding 40 GW across the United States, the United Kingdom, and Australia.  Our discussion traces Quinbrook's own transformation alongside that of the broader energy landscape. We revisit the firm's strategic exit from wind generation, marked by the sale of its Scout platform to Brookfield in 2023 for more than $1 billion, and explore how its focus has shifted toward utility-scale solar and long-duration energy storage across the United States and Australia.  More fundamentally, David explains how Quinbrook has moved beyond the era of single-technology investment funds. Instead of financing isolated generation assets, the firm now builds integrated, multi-technology platforms designed to solve specific customer problems. The objective is no longer simply to inject generic electrons into the grid, but to work backwards from the needs of large electricity consumers—particularly hyperscale datacenter operators—and develop bespoke energy solutions around them.  This philosophy is illustrated by Rowan, Quinbrook's datacenter development platform, which attracted a $1 billion co-investment from Blackstone. As hyperscalers race to deploy new computing capacity, speed has become the defining constraint. Waiting for the grid is no longer an option, making "bring your own power" an increasingly compelling proposition.  The conversation also explores how advances in software and long-duration energy storage are improving behind-the-meter performance, allowing energy infrastructure to become more resilient, flexible, and economically attractive.  Ultimately, David argues that we are witnessing a profound shift in thinking. In a world increasingly captivated by virtual technologies and digital intelligence, the greatest opportunities may lie in investing in the physical infrastructure that makes them all possible.“Let's get Physical”  

A man who has feared death every day of his life wakes among strangers who cannot die — and finds that to them, he is something called an “atavus” — drawn by lot into what they have waited five hundred years to do.Look for this podcast on Apple Podcasts, Spotify, iHeart Radio, Amazon Music, Pandora, TuneIn Radio, and other podcast apps. Get a list of free listening apps here: https://weirddarkness.tiny.us/OTRCHAPTERS & TIME STAMPS (All Times Approximate)…00:00:00.000 = Show Open00:01:30.028 = CBS Radio Mystery Theater, “Wise Child” (March 24, 1978) ***WD00:45:57.515 = Arch Oboler's Plays, “Immortal Gentleman” (June 17, 1939) ***WD01:14:01.420 = Barry Craig, “Corpse On Delivery” (November 31, 1951)01:41:53.419 = BBC Radio 4/Radio 7, “Mortmain” (April 22, 1992)02:26:10.177 = Night Beat, “Lost Souls” (November 16, 1951) ***WD02:55:47.576 = Beyond The Green Door, “Mk. Arkady Bradian, Bolder and TNT” (1966)02:58:57.644 = Man In Black (The Black Book), “The Price of the Head” (February 02, 1952) ***WD03:13:42.390 = Blackstone The Magic Detective, “The Ghost That Wasn't” (November 28, 1948) ***WD03:26:24.838 = Box 13, “The Professor And The Puzzle” (January 09, 1949)03:52:53.344 = Calling All Cars, “The Human Bomb” (December 20, 1933) ***WD04:22:42.424 = Casey Crime Photographer, “A Tooth For a Tooth” (July 15, 1946) ***WD04:48:33.183 = Show Close(ADU) = Air Date Unknown(LQ) = Low Quality***WD = Remastered, edited, or cleaned up by Weird Darkness to make the episode more listenable. Audio may not be pristine, but it will be better than the original file which may have been unusable or more difficult to hear without editing.CUSTOM WEBPAGE: https://weirddarkness.com/WDRR0713Weird Darkness presents Retro Radio: Old Time Radio in the Dark, a collection of vintage broadcasts spanning psychological horror, hard-boiled detective work, ghost stories, and the strange corners where the two overlap.It opens with the CBS Radio Mystery Theater and E.G. Marshall's presentation of "Wise Child," written by Sam Dann and starring Ralph Bell. Joyce and Calvin Spurlock argue their way off a turnpike into a storm near a place called Kiowa Flats, sleep the night in their stalled car, and wake to find a newborn baby lying naked on a hillside — alive, unharmed, and abandoned. Joyce insists the child is a miracle and claims him as her own, inventing a birth story to secure a certificate. Calvin Junior never grows, not an ounce, not a fraction of an inch, while doctors find him perfectly healthy. Then a newspaper report reveals that the wilderness north of Kiowa Flats had been used as a secret dumping ground for atomic waste — and Calvin begins to sense something in the air, a force, a light, a power that lets him read the minds of his boss, his sister, and his customers, reshaping his entire life around whatever entered that child during the storm.From there, Arch Oboler's "Immortal Gentleman" arrives with Edmund O'Brien and Anne Shepherd, in which a man terrified of death his entire life screams aloud in a crowded auditorium and then explains why to the woman beside him. Sitting through a political speech, he found himself displaced into a future where science has abolished death entirely — a world of young people conditioned for fifty years, filled with all human knowledge, living two hundred, three hundred, five hundred years with nothing to do because "the old ones" never die and never surrender their positions. They call him an atavus, a throwback that surfaces once in every two thousand embryos. Twenty-four of them draw lots in a darkened room, and he is handed a black box and told to throw it at a woman who has lived five thousand years.Next, William Gargan stars as Barry Craig, confidential investigator, in "Corpse On Delivery." Bail bondsman Sam Solloway hires Craig to find Joey Florio, a racketeer who jumped a fifty-thousand-dollar bond, and offers ten percent to get him back. A merchant seaman named Stacy Crocker is stabbed four separate times outside Craig's office door before he can deliver whatever he came to sell. A blonde in ballerina sweaters frisks the corpse for its papers, a rifle shot grazes Craig's skull along West Street, and monogrammed pillows in a room at the Hotel Mohansic spell out the answer in two letters.The episode continues with John Metcalfe's "Mortmain," dramatized for radio by Rebecca Wilmshurst, set in the south of England before the war. Salome Clare marries Humphrey Ramsden Child, a man obsessed with moths, boats, and his dead mother Harriet, who vows at the altar that marriage binds souls beyond death throughout eternity. At an anniversary dinner deliberately set for thirteen guests aboard his houseboat, a woman is attacked by a swarm of moths in an upstairs bathroom, and a decomposing dog is dragged from the linen closet. Humphrey is committed as criminally insane, dresses in his mother's clothing, and promises from inside a straitjacket that death shall not part them. After his death, Salome marries John Temple — and on their honeymoon, a rotting pink boat begins rising out of the water behind them.Frank Lovejoy follows as Randy Stone in "Lost Souls," walking South State Street on Chicago's Skid Row, where a woman named Ruth Martin has spent eight hundred dollars buying steaks, clean sheets, and champagne for every derelict on the block. She refuses to answer a ringing telephone. Her purse holds a hotel key and a brand-new loaded .32. Twenty years earlier, watching police drag a screaming thirty-year-old woman into a wagon, Ruth made her friend Vivian Clark promise to kill her if she ever turned out the same way. Vivian Clark died at eleven years old — and every night for three weeks, the phone has rung wherever Ruth runs, from St. Louis to Kansas City to Duluth to Chicago.Basil Rathbone then delivers a short piece from Beyond the Green Door about a magician turned bank robber who kills two guards in Croesus, Maine, and hides in an abandoned granite quarry by disguising himself as a boulder — until a truck from the Eastern Maine Gravel Corporation pulls in to set the dynamite charges. The Man in Black, starring Paul Frees, presents John Russell's South Seas story "The Price of the Head," in which Christopher Pellet, a red-whiskered drunk with a bad name in the islands, murders a bartender at Fufuti and is saved by a Bougainville native named Karaki, who steals a canoe, sails eight hundred miles, nurses him through withdrawal, kills two white men in a cutter, gives him the last of the water, and combs his red hair and whiskers twice every day.Blackstone the Magic Detective investigates "The Ghost That Wasn't" at the Weldon mansion, where Mortimer Weldon's brother Clarence accepted a dare to spend the night in the tower room and was found in the courtyard with a broken neck behind a door locked from the inside — and where a grandfather clock that has always kept excellent time is suddenly two minutes slow. Alan Ladd stars as Dan Holliday in "The Professor And The Puzzle," a Box 13 adventure in which a college crystallographer named Martin Gardner is found shot through the heart with his own gun, his niece abruptly breaks her engagement to marry her uncle's lab assistant Ed Macklin, and Macklin turns up stabbed with his own knife. Registered mail receipts and a bank book under the name Samuel Stoner lead Holliday to an office building and a case of illicit diamond cutting.Calling All Cars reaches back into the records for "The Human Bomb," the true story of Carl Weiss, who walked into police headquarters wearing a sheepskin hood, green goggles, and a soldier's campaign hat, carrying a blood-red box packed with sixty-six sticks of dynamite and holding a spring-loaded trigger that would fire the moment he let go. He demanded to see Paul Shoup, president of the Pacific Electric Railway, and threatened to level the building unless the railroad workers got a raise. Two hundred and sixty prisoners were evacuated by streetcar while Chief Sebastian stalled him, and Officer Sam Brown eventually thrust his bare hand through the glass top of the box to smother the lit fuse.The episode closes with Staats Cotsworth as Casey, Crime Photographer, in "A Tooth For a Tooth" by Charles Holden. Rewrite man Henry Brower confesses a premonition of his own death and admits that a man named Renat — no licensed dentist, but a self-described research scientist on River Road — filled his teeth for free to test a new metal. Brower vanishes that night, and Lieutenant Logan writes him off as a debtor who skipped town. Casey recognizes the shape of a Colorado cattleman's case from 1931, and a bartender's habit of spelling words backward hands him the name he needs.

Story of the Week (DR):Social Media's 'Big Tobacco Moment': Meta Faces $1.4 Trillion Fine for Allegedly Fueling Teen Suicide and AddictionMeta is being sued by 33 US states, led by California, Colorado, Kentucky, and New Jersey.12 blue/12 red/9 purpleThe states allege that Meta deliberately designed Facebook and Instagram to be addictive to children and teens, fueling a youth mental health crisis (including anxiety, depression, self-harm, and suicide).They also accuse Meta of violating child privacy laws by collecting data from children under 13 without parental consent.Meta warned a federal court that it could face up to $1.4T in penalties if the states prevail at the upcoming trial (set for August 18, 2026). Meta extrapolated this massive figure—which is roughly equivalent to the company's entire stock market value—based on the methodology proposed by the lead states for calculating damages.Meta calls the penalty "outlandish" and "unsubstantiated," arguing it has no precedent in consumer protection history: 'A sanction of that size has no analog in the history of consumer protection enforcement.' The company accuses the states of improperly multiplying penalties (e.g., stacking fines based on daily usage time). Meta denies the allegations, asserting its platforms have extensive safety tools and that the claims are unmoored from actual unfair practices.‘I Don't Think I'm Ever Going to Stop,' Says Mark Zuckerberg. Even With 'Infinite Money,' He Has No Plans to Retreat to His Massive Hawaii EstateMeta found to breach EU laws with 'addictive' Instagram, Facebook designsInstagram and Facebook's “addictive” designs have put Meta in breach of the European Union's digital laws, the EU concluded Friday in a preliminary report.The tech giant violated the EU's Digital Services Act by failing to adequately consider the risks associated with design features that affected the physical well-being of its users, including minors and vulnerable adults, the European Commission said.These features include infinite scroll, which constantly shows fresh content, autoplay, push notifications and highly personalized recommendation systems — feeding users' compulsion to continue using platforms and putting them into “autopilot mode.”The EU Commission also accused Meta of ignoring available information about how much time young people are spending on Instagram or Facebook at night, and how different types of content formats, from reels to stories, could lead to excessive use of its services.Meta said, “We disagree with these preliminary findings.”New Zealand Moves To Ban Climate Change Litigation. Will The U.S. Follow?New Zealand has proposed a bill to limit the ability of individuals to sue high greenhouse gas emitters over the impacts of climate change, relying instead on the enforcement measures taken by the government. The bill appears poised to pass.The women who wouldn't let climate data disappear MMAfter losing their jobs at National Oceanic and Atmospheric Administration (NOAA), Rebecca Lindsey, her sister Mary and colleague Anna Eshelman teamed up to rebuild a pivotal resource the Trump administration took offlineRebecca Lindsey, a technical writer for NASA–one of 280,000 federal workers fired by Musk/Trump, joined forces with former NOAA employees Anna Eshelman, and Mary Lindsey, her older sister, to become the core team behind the deactivated site's successor, Climate.us, preserving over 15 years of key climate data and resources.Elon Musk says he always wanted his SpaceX employees to get rich — and now thousands of them are millionairesElon Musk's 'Chainsaw for Bureaucracy' Just Left an $11 Billion Budget Hole as Trump Rehires StaffThe trove features key maps, educational materials and climate indicator reports, including the now-deleted Fifth National Climate Assessment, the government's most comprehensive analysis of climate change that was at risk of being lost to the publicJersey Mike's $12 billion IPO filing reveals a $50 million payday for the founder's stepson and a $41 million jetFamily members of founder Peter Cancro were employed Jersey Mike's in various roles and received compensation in excess of $120,000 from the Company as follows for the years ended December 28, 2025 and December 31, 2024 and 2023:John Cancro, Mr. Cancro's brother, received total compensation of approximately $20,019,231, $519,231 and $500,000, respectively;Paul J. Cancro, Mr. Cancro's son, received total compensation of approximately $8,001, $216,022 and $208,023, respectively;Robert Cancro, Mr. Cancro's son, received total compensation of approximately $38,462, $1,038,462 and $1,000,000, respectively;Tatiana Cancro, Mr. Cancro's wife, received total compensation of approximately $11,538, $311,539 and $300,000, respectively;Caroline Jones, Mr. Cancro's daughter, received total compensation of approximately $38,462, $1,038,462 and $1,000,000, respectively;Alexandra Powers, Mr. Cancro's sister-in-law, received total compensation of approximately $0, $1,165,437 and $0;Daniel Powers, Mr. Cancro's brother-in-law, received total compensation of approximately $30,213,462, $1,793,952 and $0;John Tesauro Jr., Mr. Cancro's brother-in-law, received total compensation of approximately $0, $0 and $2,429,628, respectively;Phillip Sivolobov, Mr. Cancro's stepson, received total compensation of approximately $50,011,538, $311,539 and $276,923, respectively.GRAND TOTAL: $112MStepson Phillip got $51M, brother John got $21MOther Peter Cancro schwag in 2025:Got a $41 million jet and an additional fixed amount of $166,666.66 per month in light of the business expenses incurred by Mr. Cancro related to air transportation to travel from time to time for business purposes.Lease agreements valued at $1M in rent (leases go to 2030) Controlled company: Blackstone (will control more than 50% of voting power)Board: 8 directorsBlackstone:Chair Nigel Travis (also chair of Abercrombie & Fitch)David N. KestnbaumDevon L. RinkerMichael J. StaubFounder/former CEO/chair: Peter CancroCEO Charles R. MorrisonCheryl S. Miller, director on two controlled companies:Tyson FoodsOld Dominion Freight Line (Congdon brothers)Fran Horowitz, CEO of Abercrombie & Fitch (where chair serves as chair)Goodliest of the Week (MM/DR):DR: Amazon, Walmart and Other Large Employers Could Face New Costs As New Jersey Targets Companies With Medicaid Workers— Will Other States Follow?DR: UBS says rich people will be younger, female and openly queer thanks to the Great Wealth TransferMM: Meta Buried Research Linking Instagram To Teen Harm While Facing $1.4 Trillion Penalty That Could Erase Its Entire WorthMM: ESG!Madison Square Garden Kept a List of Gay CelebritiesAn internal Madison Square Garden database of VIPs labels Joe a “medium risk,” one of roughly 400 celebrities given a risk score.If you're a celebrity and you're marked with a risk score—even as a low risk—it means “you've done something in the publicity world, the social media world, that has caught the attention of the wrong people,” the source continues.The talent database also tracks some celebrities' race, gender identity, and sexual orientation; 93 entries are marked as “LGBTQIA.”MM: California vs. Elon Musk: Tesla Snubbed as New EV Incentives Boost Rivian, Lucid MM DRAssholiest of the Week (MM):Billionaire amplificationKen Griffin says everyone is misinterpreting the AI revolution — and wishes Zohran and Bernie would ‘read a damn history book for once'“[Capitalism is] the greatest success story in the history of humanity,” Griffin said, urging the self-identified socialist politicians, “whether it's Bernie Sanders, whether it's Mamdani,” to “read a damn history book for once and then tell us how to run our country.”Jeff Bezos 'Made All of Our Lives So Much Better,' Says Billionaire Investor Tim Draper"Amazon has made all of our lives so much better," Draper said.Draper said he has benefited from what Bezos has done, and that's a part of the world economy that isn't spoken about enough."Those geniuses who create this incredible world for us are benefiting all of us."40 Epstein-Tied Billionaires Have Injected $1.6B Into US Elections, Report FindsThese are the millionaires and billionaires pledging to fund Trump accountsZuckMeta AI Data Centre Contractor Triggers Biohazard Scare After Flushing Rare Bacterium Into Public SewersMeta Platforms To Build $9 Billion A.I. Data Centre In CanadaThe $145 Billion Lie? Zuckerberg's Leaked Town Hall Audio Exposes Massive AI Failures After Mass LayoffsMeta jumps into AI coding market in effort to chase Anthropic and OpenAIWhat person in their right mind would trust Zuckerberg with their coding?Hollywood Vs Zuckerberg: CAA Warns Meta's AI Image Tool Needs A Major Privacy Overhaul‘I Don't Think I'm Ever Going to Stop,' Says Mark Zuckerberg. Even With 'Infinite Money,' He Has No Plans to Retreat to His Massive Hawaii EstateJeff Sonnenfeld - DRIn defense of Musk, SpaceX, and dual class shares“the rigid formulas of proxy advisors create a perverse, socially destructive incentive: hoard your wealth like an oligarch to maintain your good governance rating, or give it away and risk losing your company”“The proxy advisors want a world governed by rigid mathematical formulas because auditing a checklist is easy. Evaluating human character, industry dynamics, track records of success and failure, and the capacity for visionary leadership is hard. But it is exactly that hard work of judgment which is vital. When it comes to dual-class shares, it is time for the critics to step out of the theoretical vacuum and look at the real-world scoreboards”Headliniest of the WeekDR: OpenAI Wants a $1 Trillion Valuation. But College Students Are Testing At The Level Of 10-Year-Olds AND Suspecting AI cheating, Ivy League prof ordered an in-person final; scores fell 50%MM: ‘Waymo Takes Revenge, Dropping Drunk Teens Directly Into Squad of CopsMM: West Virginia spent $3M to create university program to fight ‘woke ideology.' One student is enrolledWho Won the Week?DR: Free Float's new platformAnd blowhard Jeffrey Sonnenfeld for arguing that dualclass owners are necessary because the dualclass mechanism allows them to sell shares and maintain voting power so they can “cure diseases, endow universities, and combat poverty” MM: Free Float data: Elon Musk and the age of the corporate leviathanAbove a certain size the ordinary rules of governance apparently cease to apply.Of the 16 listed firms worth more than $1trn, seven are shareholder fundamentalists.None has an elaborate statement of corporate purpose, since they are mostly content making heaps of moneyFree Float says Nvidia, Amazon, Broadcom, Micron are all TOTALITARIANNext are the corporate paternalists, who believe that the problem with shareholder democracy is that its voters do not know what is best for them.Free Float says Berkshire, Google, Meta are all TOTALITARIANThe final clan presents the strongest argument against the end of corporate history: individual shareholders consent to hand over all of their rights to the world's richest man, who then governs as he sees fit.Free Float says SpaceX, Tesla are TOTALITARIANBasically, it's nice of the economist to recognize everything Free Float says every weekPredictionsDR: Jeff Sonnenfeld writes something on Fortune that triggers meMM: Jeff Sonnenfeld writes something on Fortune that triggers Damion

Jenna Lyons and Jonny Bauer of Fundamentalco, the creative agency spun out of Blackstone, join Lauren for a deep dive into what it actually takes to build a great brand. They get into the importance of authenticity, the impact of A.I. on the creative industry, and why having clear brand values is more essential than ever. They also weigh the very different challenges facing established versus emerging brands as the fashion landscape keeps shifting.

In this episode, Chris, Andrew, and David kick things off with a very Remote Ruby style detour through Costco, Blue Apron, leftovers, Blackstone grills, and cast iron pans. Then, Andrew explains his Stripe subscription migration scare and major GitHub Actions workflow improvements that sped up Podia's CI by 20–30%. They dive into Apple's new on-device AI tooling, container alternatives on macOS, and the state of conferences, GitHub, AI infrastructure costs, solar power, and even crows attacking solar panels. Hit download now to hear more! LinksJudoscale- Remote Ruby listener giftBlue Apron  (Andrew's referral code: ANDREW4838)GitHub Blog: Actions steps can now be run in parallelCodebergGitLabGitHub apple/containerGitHub apple/Core AI ModelsRubyConf July 14-16, 2026, Las Vegas, NV Rails World 2026, September 23-23, 2026, Austin, TXHoneybadgerHoneybadger is an application health monitoring tool built by developers for developers.JudoscaleMake your deployments bulletproof with autoscaling that just works.Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Chris Oliver X/TwitterAndrew Mason X/TwitterJason Charnes X/Twitter

On July 9th, 2026 Black Stone Cherry stopped by The Preston & Steve Show ahead of their Quakertown concert to perform acoustic versions of "Deep" and "Stay," share stories from decades on the road, talk about touring everywhere from UK arenas to intimate clubs, reflect on their Kentucky roots, discuss their family's incredible musical history, and explain why their motto of "Family first, ego second" has kept the band together all these years. Plus, Jacky Bam Bam joins the conversation to discuss working with a member of Chuck Berry's band/ The band also looks back on Florida Georgia Line's hit version of "Stay," and Ben Wells talks about his outrageous custom Vans and even his children's books.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On this episode of Run the Numbers, CJ breaks down Jersey Mike's S-1 and the franchise machine behind more than $4 billion in sandwich sales. He explains how an asset-light royalty model works, why franchise economics can be so powerful, what Blackstone saw in the business, and what the filing reveals about growth, margins, and the real money behind the subs.—SPONSORS:RightRev is an automated revenue recognition platform that lets your product team ship new pricing without asking finance for permission, and your sales team close deals without creating downstream chaos. Check out their free tool at calculator.rightrev.com It scores your rev rec process, shows what's exposing you to risk, and tells you exactly where to focus before it bites you in the rear end. Check it out at https://calculator.rightrev.comPulley is an equity management platform that lets you issue options, model dilution, and complete 409As without your cap table turning into a spreadsheet disaster. Founders raising, hiring, and scaling use Pulley to keep equity clean and stay focused on building. Learn more or request a demo at https://pulley.com/mostlymetricsRillet is an AI-native ERP built for modern finance teams that want to replace NetSuite and close faster. With revenue recognition, close management, multi-entity support, and native Stripe and Salesforce integrations, Rillet helps scaling companies run their finance stack in one place. Hundreds of teams, including Windsurf and Mercor, use Rillet to make the zero-day close real. Book a demo at https://www.rillet.com/cjMaximor is an autonomous finance platform that runs order-to-cash, procure-to-pay, the close, cash management, and reporting on self-learning agents instead of a dozen disconnected tools. One PE-backed customer cut their close in half, took audit findings from seven to zero, and cut back-office costs by 70% in six months. You pay for outcomes, not seats. See it at https://www.maximor.ai/Brex is an intelligent finance platform with AI-powered agents that capture expenses automatically, enforce policy before the spend happens, and close your books in minutes instead of weeks. 35,000+ companies like OpenAI, Coinbase, Anthropic, and DoorDash already run on Brex. It's time to get Brex AF. Learn more at https://www.brex.com/metricsAnrok is the sales tax platform that watches your exposure everywhere, automates compliance, and flags risk before it turns into a surprise back-tax letter from a state you've never set foot in. Companies like Anthropic, Notion, and Vanta already trust Anrok to stay ahead of rules that move faster than any spreadsheet can. Talk to a sales tax expert for a personalized exposure estimate at https://www.anrok.com/rtn—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNCJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—TIMESTAMPS:0:00 Sell $4B in subs, own none of the stores0:33 Origin story: Peter Cancro buys a sub shop at 171:47 It's a royalty business2:42 Key metrics6:07 What you're actually buying6:42 The three revenue streams7:19 The franchisee's P&L10:00 Sponsors — RightRev | Pulley | Rillet13:02 Corporate P&L: 47% EBITDA margins13:33 The Blackstone math14:38 $2.1B whole business securitization15:09 Full EBITDA bridge16:00 The CEO buying back the 2%17:10 Red flag 1: Up-C structure18:11 Red flag 2: tax receivable agreement18:45 Red flag 3: controlled company governance19:05 Red flag 4: sponsor already took $500M19:29 Red flag 5: charitable donations added back20:13 Red flag 6: cheap debt maturing in 202920:52 Sponsors — Maximor | Brex | Anrok23:56 Valuation: $10–12B24:32 Peer comparison25:27 How do you underwrite $12B?25:58 Misc: quantum attack on the provolone26:28 The hidden 53rd week26:57 No drive-thru is a feature27:13 Verdict27:56 Credits#RunTheNumbersPodcast #IPO #Investing #BusinessStrategy #FinanceLeadership

The 4th of July is behind us, and so is USA soccer after losing to Belgium in the World Cup. Will soccer ever truly take off in the US? We recap our holiday weekends, give thoughts on the Tigers turning things around, some NBA offseason news, and more! Also, author of 'Midnight on the Potomac' Scott Ellsworth joins us to talk about a local event he has coming up, his writing process, a little US history, and more! Check out his books, take a listen to the pod, and hit us up @3pointpod! Thanks to: Memorial Healthcare Wellness Center, Blackstone's Public House, Nelson House Funeral Home, Success Group Mortgage & Servicing, Kori Shook & Associates, Jacobs Insurance, AZee Branding Solutions, Pickpocket Sports & Outdoors, Lebowsky Center, Marrs Furniture & Mattress Barn, Shiawassee County Fair, Nichols Painting, Great Lakes Apparel Co., SportsNet MI

What's That Sound Wednesday, Radar tests out his new Blackstone, Elizabeth and Radar are going to battle it out!?!?, and TR - She's pregnant... but is it mine?!?! Listen to Elizabeth & Radar on The Mix LIVE weekdays from 6am to 10am!

Malevolent is a thrilling eldrich horror, mystery audio drama brilliantly combined with elements of choose your own adventure and actual play via their Patreon. This is the first episode of Malevolent's second series Threshold, which follows John and Arthur as they return to Arkham after their time seeking the BLACKSTONE and face the new and terrible truth this world has revealed to them. Faced with the new challenges before them and old foes perhaps still a threat, the duo must carve a new path in this strange world.Malevolent is from Harlan Guthrie, the same talented creator behind Deviser and Dice Shame.Introduction and outro by Shahan HamzaListen to Malevolent on The Rusty Quill website, on Acast, or listen wherever you get your podcasts, or to learn more about Malevolent check out its official website.Support Malevolent and be a part of the story now at: https://www.patreon.com/TheINVICTUSStream Credits:Written and performed by Harlan Guthrie Featuring Jo Guthrie as “Faroe”Content warnings: BlindnessMind ControlGraphic ViolenceMurder RitualsHuman remainsShootingMemory LossEldritch Horror SFX Guns and Gunfire, Thunder, DrippingFor ad-free episodes, bonus content and more, join members.rustyquill.com or our Patreon.Pre-order FROM THE LIBRARY OF JURGEN LEITNER, a Magnus novel releasing October 27th: rustyquill.com/novel Hosted on Acast. See acast.com/privacy for more information.

“Crazy Town”: Two bomber pilots who rain death on defenseless villages crash behind the walls of a hidden asylum, where a soft-spoken madman insists they've finally come home to the only community where killers like them belong.Look for this podcast on Apple Podcasts, Spotify, iHeart Radio, Amazon Music, Pandora, TuneIn Radio, and other podcast apps. Get a list of free listening apps here: https://weirddarkness.tiny.us/OTRCHAPTERS & TIME STAMPS (All Times Approximate)…00:00:00.000 = Show Open00:01:30.028 = The CBS Radio Mystery Theater, “The Assassin” (March 03, 1978) ***WD00:46:37.892 = Strange Adventure, “The Wind Wagon” (1945) ***WD00:49:51.994 = Arch Oboler's Plays, “Crazy Town” (May 20, 1939) ***WD01:17:18.050 = Barrie Craig, “Microfilm in the Fishtank” (October 24, 1951) ***WD01:46:38.936 = BBC Radio 4/Radio7 GhostStory, “Lifeline” (2006) ***WD02:15:47.965 = Night Beat, “Mr. And Mrs. Carothers” (October 26, 1951) ***WD02:45:58.499 = Beyond The Green Door, “John Otis-Mr. Dunn, Disposer” (1966) ***WD02:49:49.627 = The Black Book, “Vagabond Murder” (March 02, 1952) ***WD03:04:18.025 = Blackstone, “Ghost That Trapped a Killer” (October 03, 1948) ***WD (LQ)03:16:00.352 = Box 13, “The Better Man” (January 02, 1949)03:43:04.360 = Calling All Cars, “York Gang Holdup” (December 13, 1933) ***WD04:11:50.697 = Casey Crime Photographer, “Reunion” (June 03, 1946) ***WD04:35:49.460 = CBC Mystery Theater, “The Dream Woman” (May 01, 1968)05:04:49.273 = Show Close(ADU) = Air Date Unknown(LQ) = Low Quality***WD = Remastered, edited, or cleaned up by Weird Darkness to make the episode more listenable. Audio may not be pristine, but it will be better than the original file which may have been unusable or more difficult to hear without editing.CUSTOM WEBPAGE: https://weirddarkness.com/WDRR0703

THRESHOLD is a direct continuation of Malevolent, the Audio Drama. This Series 2 sees John and Arthur having returned to Arkham after their time seeking the BLACKSTONE and facing the new and terrible truth this world has revealed to them. Faced with the new challenges before them and old foes perhaps still a threat, the duo must carve a new path in this strange world.Featuring Jo Guthrie as "Faroe"Support Malevolent and be a part of the story now at: https://www.patreon.com/TheINVICTUSStream Hosted on Acast. See acast.com/privacy for more information.

It's time for our annual Fourth of July grill episode here at Decoder, which is when we invite the CEOs of outdoor cooking companies onto the show to explain just how their businesses kind of look like every other business. And this is a very special edition.  Today we're talking to Roger Dahle, the CEO of Weber Blackstone, a full circle moment for Decoder. Roger was our first-ever grill CEO on the show back when he was the CEO of just Blackstone. Five years later, Roger now runs one of his biggest competitors, after Blackstone announced a merger with Weber in 2024. So we talked about that process, and how Roger is managing the integration of these two grilling giants.  Links:  Weber and Blackstone to combine | The Verge How Blackstone became the darling of grill TikTok | Decoder (2021) How arson led to a culture reboot at Traeger, with CEO Jeremy Andrus | Decoder (2022) Big Green Egg CEO Dan Gertsacov on growing kamado cooking | Decoder (2024) How SharkNinja took over the home | Decoder (2025) Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder is produced by Kate Cox and Nick Statt. This episode was edited by Eileen Felix. Our editorial director is Kevin McShane.  The Decoder music is by Breakmaster Cylinder. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Is private credit the pin that pops the market bubble? The short answer is no—but that’s the wrong question entirely. Private credit is now a $1.8–$3.5 trillion market, rivaling the entire U.S. leveraged loan and high-yield bond markets combined. It’s direct lending, shadow banking, and middle-market finance all rolled into one, and firms like Ares, Apollo, Blackstone, Blue Owl, and Morgan Stanley are at the center of it. Business development companies (BDCs), are gating redemptions. Pension funds, insurance companies, and retail investors are all exposed. And the Financial Stability Board issued a formal warning in May 2026. So what is private credit, how did it get this big, and what does it actually mean for the broader economy if it seizes up? In this episode, Max breaks down the entire private credit ecosystem—from its origins in post-2008 regulation to the mechanics of SOFR-linked floating rate loans, PIK interest, covenant-lite structures, and the $410–$540 billion in bank lending that ties the whole system together. We look at the BDC redemption crisis of 2025 and 2026, the First Brands and TriColor fraud cases and Jamie Dimon’s cockroach comment that won’t go away. Resources J.P. Morgan: Understanding Private Credit Bloomberg Television: Why Private Credit Is Not a Financial Crisis Threat Blackstone: What’s Really Happening in Private Credit? Expert Answers CNBC Television: Inside Alts: Private credit fears resurface CNBC Television: This is the start of a big crisis for private credit, says Verdad’s Rasmussen The Federal Reserve: Bank Lending to Private Credit: Size, Characteristics, and Financial Stability Implications Federal Reserve Bank of Boston: Could the Growth of Private Credit Pose a Risk to Financial System Stability? IMF eLibrary: Chapter 2 The Rise and Risks of Private Credit in: Global Financial Stability Report, April 2024 Financial Stability Board: FSB warns on private credit vulnerabilities NAIC: How State Insurance Regulators are Responding to Growth in CLOs and Private Credit Bloomberg: Ares Private Credit Fund Caps Redemptions After 14% Seek to Exit Bloomberg: Apollo Caps Private Credit Fund After 17% Request to Exit Bloomberg: Private Credit Is Still a Hot Asset for Bond Investors Buying Debt Bloomberg: Morgan Stanley Caps Private Credit Fund After 11.6% Exit Request Bloomberg: Cliffwater Private Credit Fund Stung by 17% Redemption Requests Bloomberg: Blackstone Limits Withdrawals From $79 Billion Private Credit Fund BCRED Bloomberg: Private Credit BDC Redemptions Exceed Fundraising for First Time The Lead Left: Middle Market & Private Credit – 1/5/2026 - The Lead Left Financial Times: US debt investors raise alarm over lending standards UNFTR Resources Video: Will Private Credit’s Death Spiral Pop the Market Bubble? Essay: Is Private Credit the Pin That Pops the Bubble? UNFTR Newsletter UNFTR Progressive Trivia -- If you like #UNFTR, please leave us a rating and review on Apple Podcasts and Spotify: unftr.com/rate and follow us on Facebook, Bluesky, and Instagram at @UNFTRpod. Visit us online at unftr.com. Become a member at unftr.com/memberships. Buy yourself some Unf*cking Coffee at shop.unftr.com. Visit our bookshop.org page at bookshop.org/shop/UNFTRpod to find the full UNFTR book list, and find book recommendations from our Unf*ckers at bookshop.org/lists/unf-cker-book-recommendations. Access the UNFTR Musicless feed by following the instructions at unftr.com/accessibility.Support the show: https://www.unftr.com/membershipsSee omnystudio.com/listener for privacy information.

The World Cup is the super bowl of male grooming… and Lionel Messi is leaning into it.Amazon Prime Day begins tomorrow… here's how to not get tricked by faux-deals.Blackstone acquired a spa in Napa Valley… because there's AI data on the massage table.Plus, dinosaur leather is here… who wants to buy the world's first T-Rex Handbag?Tryout to become the TBOY social editor for Instagram:https://app.joinroster.co/hiringchallenges/0f1390b6-2012-48a3-b75b-d11f667786ee/details Grab your Tickets to the IPO Tour: Our In-Person OfferingSan Francisco 9/23: https://www.ticketmaster.com/event/1C0064AFB5F688BDBoston 10/14: https://tickets.citywinery.com/event/tboy-the-ipo-tour-in-person-offering-8cdhupSeattle 11/4 (21+): https://www.axs.com/events/1446394/the-best-one-yet-tickets$OTLY $META $UL $BSNEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.