Podcasts about stanford

Jiaoying Summers is a Chinese-American stand-up comedian, actress, and social media personality who rose to prominence through viral comedy clips and sold-out tours across the United States. She has built a large online following with comedy centered on her experiences as an immigrant. To see her live, check out her website jiaoyingcomedy.com. IN THE NEWS: Black United Airlines employee threatens to call ICE on Hispanic passenger, then the two take turns calling each other racist, Jasmine Crockett says people were rooting against Argentina in the World Cup because of its “racist history”, New Jersey governor says "software error" caused 6,600 foreigners to be registered to vote, Jason Alexander Apologizes to Courtney Stodden for Resurfaced VideoFOR MORE WITH JIAOYING SUMMERS:SHOW DATES: (jiaoyingcomedy.com)Sep 4-Sep 6–Washington, DC–DC ImprovSep 11-12–Stanford, CT–New York Comedy ClubSep 15–Pasadena, CA–The Ice HousePODCAST: Tiger MommyINSTAGRAM: @jiaoyingsummersFOR MORE WITH ADAM YENSER:YOUTUBE SHOW: The Cancelled NewsINSTAGRAM: @adamyenser TWITTER: @cleancomedian69LIVE SHOWS: July 25 - Huntington Beach, CAJuly 26 - Torrance, CA (2 Shows)July 30 - Freehold, NJ (2 Shows)July 31 - New York, NY (2 Shows)August 1 - Uncasville, CTAugust 2 - Albany, NYThank you for supporting our sponsors:ForThePeople.Com/ADAMoreillyauto.com/ADAMhttps://www.rosettastone.com/adampluto.tvPodcastOneSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What if the story you keep telling about yourself is the only thing standing between you and everything you want? You will hear the real difference between fortune and luck, and why one of them is completely in your control. Dr. Tina Seelig, a Stanford professor and neuroscientist, breaks down the framework from her book What I Wish I Knew About Luck and explains why the wind of opportunity might be blowing right past you. Tina grew up terrified of things most people never think twice about. She rebuilt her entire risk profile from scratch, one uncomfortable moment at a time. As did Lewis. You will learn why the words other people say about you can become a program running your whole life, and how to finally overwrite it. This conversation will make you rethink every excuse you have ever made for staying small. Tina's Website Tina on LinkedIn What I Wish I Knew About Luck: A Crash Course on Turning Aspirations into Achievements Amazon Audiobook Creativity Rules: Get Ideas Out of Your Head and into the World – A Stanford Guide to Innovation and Entrepreneurship Amazon inGenius: A Crash Course on Creativity – A Stanford Guide Demystifying Innovation for Business Leaders Amazon What I Wish I Knew When I Was 20 - 10th Anniversary Edition: A Crash Course on Making Your Place in the World Amazon Audiobook In this episode you will: Discover the real difference between fortune and luck, and which one you actually control Learn the Risk-O-Meter framework for expanding your comfort zone in every area of life Uncover how the stories you tell about yourself quietly shape the opportunities you see Overcome the fear of asking for help using Tina's framework for making people want to say yes Build the daily habits that compound into extraordinary luck over time For more information go to https://lewishowes.com/1957 More SOG episodes we think you'll love! Get More From Lewis! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Let's dive into some wrestling news and results!TIMESTAMPS:0:00 - Intro, Start of Show04:55 - Stanford Adds Amine08:55 - F&M adds Anthony Noto09:55 - Recruiting; UNC Adds Reynolds16:30 - RAF 1135:00 - Trent Hidlay Up or Down?53:35 - Askren's Final Match01:04:45 - Sam Barber Stepping Down01:08:50 - Ridge Lovett & Ranking SeriesRokfin.com/MatScouts for all of Willie's Content!Be sure to SUBSCRIBE to the podcast. NEW EPISODES WEEKLY! Support the show & leave a 5-star rating and review on Apple Podcasts, and shop some apparel on BASCHAMANIA.com! For all partnership and sponsorship inquiries, email info@baschamania.com.BASCHAMANIA is a Basch Solutions Production. Learn more about Basch Solutions, a digital marketing agency specializing in custom websites, content creation, and digital strategy, at BaschSolutions.com.

Better sleep isn't just about getting more rest, it's about unlocking a healthier body, a clearer mind, and a deeper connection to your higher self. Eric Bigger and Stanford-trained sleep medicine physician Dr. Feby Maria Puravath Manikat explore how sleep can elevate your consciousness, boost your health, and help you show up as your highest self every day.About Dr. Feby Maria Puravath ManikatDr. Feby Maria Puravath Manikat is a Stanford-trained sleep medicine physician specializing in sleep health, longevity, and integrative medicine. She also trained at Cornell University in nutritional sciences and Harvard Medical School in Cognitive Behavioral Therapy for Insomnia (CBT-I). Blending science with holistic practices, she helps high-performing professionals optimize their sleep to improve health, energy, performance, and overall well-being. Dr. Feby also lectures Stanford's "Sleep and Dreams" course and serves as Sleep Director at Apple's AC Wellness, guiding Apple employees toward better rest, recovery, and peak performance.Website: https://www.febymariamd.com/aboutInstagram: https://www.instagram.com/febypuravath/Check out Miracle Season's collection: https://itsmiracleseason.co/collections/frontpageWork with me: https://www.ericbigger.com/workwithme?utm_source=podcast&utm_medium=podcast&utm_campaign=work_with_m...Connect with Simplified Impact: https://hubs.ly/Q02vvMJ90

On this  re-release episode of the Live Greatly podcast, Kristel Bauer sits down with organizational psychologist, Stanford professor, bestselling author, and leadership expert Robert Sutton to discuss how leaders can reduce unnecessary workplace friction, build stronger teams, improve organizational culture, and create environments where people can thrive. Drawing from his book The Friction Project, Robert shares insights on identifying "bad friction," making work more effective, receiving feedback with greater resilience, building self-awareness as a leader, and why his famous "No Asshole Rule" continues to be so relevant in today's workplace. Whether you're leading a team, managing organizational change, or looking to improve workplace performance, this conversation offers actionable insights to help you become a more intentional and effective leader. Tune in now! Key Takeaways From This Episode What workplace friction is—and how to recognize it How great leaders remove unnecessary barriers to success Lessons from The Friction Project The leadership principles behind the "No Asshole Rule" How to build greater self-awareness as a leader Why receiving honest feedback is essential for growth ABOUT ROBERT SUTTON: Robert I. Sutton is an organizational psychologist and professor of Management Science and Engineering in the Stanford Engineering School. He has given keynote speeches to more than 200 groups in 20 countries, and served on numerous scholarly editorial boards. Sutton's work has been featured in the New York Times, BusinessWeek, The Atlantic, Financial Times, Wall Street Journal, Vanity Fair, and Washington Post. He is a frequent guest on various television and radio programs, and has written eight books including The Friction Project, and two edited volumes, including the bestsellers The No Asshole Rule; Good Boss, Bad Boss; and Scaling Up Excellence. About the book THE FRICTION PROJECT: How Smart Leaders Make the Right Things Easier and the Wrong Things Harder (St. Martin's Press; January 30, 2024), bestselling authors and Stanford professors Robert I. Sutton and Hayagreeva "Huggy" Rao present a decade's worth of research on what ought to be easy and what ought to be hard in organizations, and how to change things for the better. Based on their research, case studies, and hundreds of engagements with top companies, the authors reveal just how widespread this affliction is, and provide a roadmap for readers to take up the mantle and blaze a path out of the muck. Sutton and Rao tease out the most common and destructive forms of friction, and share proven tactics, tools, and practices that can help us avert these traps and move forward. Ultimately, THE FRICTION PROJECT makes the case for a new philosophy that empowers us to build positive, productive, and humane organizations that make life better for their people and those they serve. Website:  https://www.bobsutton.net/  Order the book, THE FRICTION PROJECT - How Smart Leaders Make the Right Things Easier and the Wrong Things Harder: https://www.bobsutton.net/book/the-friction-project/  Social Media Links: LinkedIn: https://www.linkedin.com/in/bobsutton1/  Twitter:  https://twitter.com/work_matters     About the Host of the Live Greatly podcast, Kristel Bauer: Kristel Bauer is a corporate wellness and performance expert, keynote speaker and TEDx speaker supporting organizations and individuals on their journeys for more happiness and success. She is the award-winning author of Work-Life Tango: Finding Happiness, Harmony, and Peak Performance Wherever You Work (John Murray Business November 19, 2024). With Kristel's healthcare background, she provides data driven actionable strategies to leverage happiness and high-power habits to drive growth mindsets, peak performance, profitability, well-being and a culture of excellence. Kristel's keynotes provide insights to "Live Greatly" while promoting leadership development and team building. Kristel is the creator and host of her global top self-improvement podcast, Live Greatly. She is a contributing writer for Entrepreneur, and she is an influencer in the business and wellness space having been recognized as a Top 10 Social Media Influencer of 2021 in Forbes. As an Integrative Medicine Fellow & Physician Assistant having practiced clinically in Integrative Psychiatry, Kristel has a unique perspective into attaining a mindset for more happiness and success. Kristel has presented to groups from the American Gas Association, Bank of America, bp, Commercial Metals Company, General Mills, Northwestern University, Santander Bank and many more. Kristel's work has been featured in Forbes and she has had multiple TV appearances including NBC News Daily, ABC News Live, FOX Weather, ABC 7 Chicago, WGN Daytime Chicago and more. Kristel lives in the Chicago, IL area and she can be booked for speaking engagements worldwide. To Book Kristel as a speaker for your next event, click here. Website: www.livegreatly.co  Follow Kristel Bauer on: Instagram: @livegreatly_co  LinkedIn: Kristel Bauer Twitter: @livegreatly_co Facebook: @livegreatly.co Youtube: Live Greatly, Kristel Bauer To Watch Kristel Bauer's TEDx talk of Redefining Work/Life Balance in a COVID-19 World click here. Click HERE to check out Kristel's corporate wellness and leadership blog Click HERE to check out Kristel's Travel and Wellness Blog Disclaimer: The contents of this podcast are intended for informational and educational purposes only. Always seek the guidance of your physician for any recommendations specific to you or for any questions regarding your specific health, your sleep patterns changes to diet and exercise, or any medical conditions.  Always consult your physician before starting any supplements or new lifestyle programs. All information, views and statements shared on the Live Greatly podcast are purely the opinions of the authors, and are not medical advice or treatment recommendations.  They have not been evaluated by the food and drug administration.  Opinions of guests are their own and Kristel Bauer & this podcast does not endorse or accept responsibility for statements made by guests.  Neither Kristel Bauer nor this podcast takes responsibility for possible health consequences of a person or persons following the information in this educational content.  Always consult your physician for recommendations specific to you.

Join us for Relaunch Week! Welcome to our first conference preview of the 2026 season, where Alex and Richard discuss the ACC's 17 teams. This episode has a rose (a good thing), a bud (a point of intrigue), and a thorn (a worry) for every team in the league. Each school is covered, and then we pick some preseason awards:- 4:28: Virginia- 10:51: Duke- 16:13: SMU- 21:49: Miami- 29:28: Pitt- 34:43: Georgia Tech- 43:28: NC State- 49:05: Cal- 52:53: Clemson- 58:48: Louisville- 1:02:47: Wake Forest- 1:08:23: Stanford- 1:11:38: Florida State- 1:17:33: North Carolina- 1:23:52: Virginia Tech- 1:28:34: Boston College- 1:32:08: SyracuseProducer: Anthony Vito. Thanks to Homefield and Nokian Tyres. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.splitzoneduo.com/subscribe

Primus made numerous radio appearnces throughout the 90s and into the 21st century. Two standout radio appearances are the 1989 KZSU at Stanford University and 1990 at VPRO in the Netherlands. The Stanford performance is well-known for the accompanying video footage, and the VPRO performance also has two of the songs performed on video as well. Perhaps someday we'll see and hear both performances with pristine audio quality. For now, we treat them as companion pieces to Suck On This (KZSU) and Frizzle Fry (VPRO). KZSU: https://youtu.be/iIMh_2KH6MYVPRO: https://youtu.be/OoUqOFtLeFQGet involvedInstagramFacebookEmailBurn your money 

In this E462 of Inner Voice A heartfelt Chat with Dr. Foojan, Dr. Foojan sits down with Jennifer (Jen) Stanford — trust coach, keynote speaker, CEO of Emergent Performance Solutions, and author of *De-Stressed* — to explore chronic stress, leadership pressure, emotional resilience, and personal transformation. Jen shares the deeply personal story behind writing *De-Stressed*: how years spent helping organizations navigate change eventually exposed her own unmanaged stress. While leading teams, raising a family, and striving to excel at every role, she ignored the warning signs until a serious health crisis forced her to rethink everything she believed about success and wellbeing. Together, Jen and Dr. Foojan unpack why stress touches every part of our lives — physical health, relationships, leadership, decision-making — and why managing it isn't just about exercise or time off, but about restoring balance across four energy systems: intellectual, physical, emotional, and purposeful. The conversation moves into perfectionism, people-pleasing, and Jen's four stress response perspectives (logical, relationship-oriented, action-oriented, organized) — and how understanding them transforms teams, workplaces, and families. If you've ever felt overwhelmed, exhausted, or trapped in the pressure to achieve more, this episode is a reminder that success doesn't have to come at the expense of your peace. **⏱️ Timestamps** 0:00 – The image of inner voice 1:25 – Welcome to Inner Voice with Dr. Foojan 1:58 – Meet Jennifer Stanford 4:10 – The IAII Virtual Clinic 5:31 – Jennifer joins the conversation 5:44 – Why Jen wrote *De-Stressed* 7:06 – The story behind the book 8:20 – The health crisis that changed everything 9:06 – Pressure vs. stress 10:59 – The mind-body connection 12:15 – Learning to actually release stress, not just manage it 14:01 – The four energy systems 15:00 – Letting go of perfectionism and control 16:30 – Fear of image vs. fear of failure 17:42 – The four stress response perspectives 17:54 – The logical perspective 21:01 – Relationship, action-oriented & organized perspectives 22:20 – Why leaning into your *least* natural response relieves stress 26:56 – Applying this to teams and families 29:05 – Creating space as a leader 31:00 – Energy as currency — and why it's contagious 32:56 – Reading your team's and family's stress patterns 38:01 – Two pathways forward: therapy and coaching at IAII 38:53 – Stop wearing stress like a badge of honor 40:08 – Where to find Jennifer Stanford 41:04 – Closing thoughts **Connect with us:** awarenessintegration.com | www.iaii.life Topics Covered: . Stress Management • Burnout Recovery • Leadership Development • Emotional Intelligence • Executive Coaching • Change Management • Mental Health • High Performance Leadership • Team Communication • Psychological Safety • Personal Growth • Work-Life Balance • Resilience • Mindset • Self-Awareness • Peak Performance • Leadership Coaching • Trust Building • Executive Wellness • Authentic Leadership #StressManagement #Burnout #Leadership #EmotionalIntelligence #MentalHealth #ExecutiveCoaching #LeadershipDevelopment #PersonalGrowth #Mindset #Resilience #WorkLifeBalance #BurnoutRecovery #HighPerformance #Trust #JenStanford #DrFoojan #InnerVoicePodcast #mentalhealth #Wellness #Relationship #PersonalGrowth #selfimprovement #MentalHealth #Wellness #Relationship #PersonalGrowth #selfdevelopment Development

Building a successful career or business starts with the right mindset. In this episode, Leonard Ang and Sharan Mansukhani of Sip and Scale discuss how community, AI literacy, and continuous learning create long-term opportunities for founders, professionals, and future leaders.Learn practical lessons on navigating uncertainty, simplifying decisions, and staying adaptable in an evolving world.00:02:30 – Meet Leonard Ang and Sharan Mansukhani of Sip & Scale00:04:28 – Their current hustles: Diffusr and building Sip & Scale00:09:23 – Sharan's family migration story and entrepreneurial inspiration00:13:03 – Grit, budgeting, and lessons inherited from their families00:19:49 – First mentors, internships, and learning through startups00:24:53 – Why paying it forward matters in the startup ecosystem00:30:41 – How Sharan found purpose through startup communities00:34:05 – How Leonard and Sharan met and launched Sip & Scale00:37:24 – The vision behind Sip & Scale's community-first approach00:40:41 – A Stanford-inspired idea that shaped Sip & Scale00:45:02 – Scaling the community from Manila to the world00:46:54 – Curating ambitious, diverse, and high-quality communities00:49:42 – How building a community transformed them as founders00:54:55 – The evolution of startup founders in the AI era00:57:46 – Building Diffusr with AI-first product development01:00:33 – AI-powered operations and the future of startup execution01:01:31 – Leonard's approach to building AI-native startupsFollow now and never miss an episode.

One in five children now lives with a chronic health condition. Rates of ADHD, allergies, eczema, autoimmune disease, anxiety and food sensitivities continue to rise worldwide. Could one of the biggest missing pieces be hiding inside the gut microbiome? In this episode of the Uncover Your Eyes Podcast, Dr. Meenal Agarwal sits down with Dr. Elisa Song, a Stanford-trained integrative pediatrician, Bestselling Author of Healthy Kids, Happy Kids, and one of the world's leading experts on children's gut health.   The first 1,000 days of life may have one of the greatest impacts on lifelong immune health, and the gut microbiome shapes it. Yet modern childhood has changed drastically: more antibiotics, fewer microbial exposures, more processed foods, less time outdoors, and more chronic disease than ever before. Together, they explore the science behind why so many children are struggling, and what parents can do to help build healthier, more resilient kids. In this episode, you'll uncover:

These sources examine the multifaceted impact of artificial intelligence on the global education landscape and the subsequent workforce. Research from Frontiers in Computer Science highlights a growing digital divide, noting that while AI offers personalized learning, it can also perpetuate cultural and linguistic biases against marginalized communities. Conversely, perspectives from Howard University and the University of New Hampshire frame AI as a critical intellectual partner that enhances doctoral research and shifts faculty roles from traditional lecturers to active facilitators. Economic analysis from Stanford further suggests that AI may actually level the professional playing field by simplifying complex tasks, allowing lower-skilled workers to compete for higher wages. Ultimately, the collection argues that inclusive design and proactive training are essential to ensure AI serves as a tool for equity rather than a driver of further stratification.

Robert L. McCullough joined me to discuss watching test patterns and Captain Tom; going to BHHS w/ Burt Ward; going to Stanford to mingle; became a page and a gopher at Universal; becoming a set locator for Bionic Woman and pitching a script; goes to Eight is Enough, then BJ and the Bear; writes "Gasohol", "Beauties and the Beasts" and the creepy "Blonde in a Cell of Gold" guest starring Paul Williams; getting call to "fix" Falcon Crest, makes it more soapy; creates show bible on stories on his wives 10 siblings; Jane Wyman was the hard worker ; getting Lana Turner to guest star; Jackie Collins Hollywood Wives; Arthur Hailey's International Airport; Dark Mansion; odd meeting with Loretta Young; signing Joan Fontaine; O'Hara, with Pat Morita; Zorro, four seasons with Duncan Regehr; Daniel Craig's first TV appearance, High Tide with Rick Springfield; Soldier of Fortune with Dennis Rodman; Tag Team pilot with Jesse Ventura & Randy "Macho Man" Savage; creating script contests that lead to things; going one on one with new writers and creating a how to podcast.

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

This week, feuding between some of the biggest tech companies spilled into public view. We discuss Apple's accusation that OpenAI tried to steal secrets about Apple's hardware business, as well as share our reactions about OpenAI's new model, Sol, and Anthropic's decision to extend access to its model Fable. Then, we unpack the loudest warning yet about A.I. and jobs. We talk with Erik Brynjolfsson, a Stanford economist, about a statement he helped organize that implores economists and A.I. researchers to “act now” to steer A.I. in a direction that complements humans. And finally, we play a round of HatGPT.   Guest: Erik Brynjolfsson, senior fellow at the Stanford Institute for Human-Centered A.I., and director of the Stanford Digital Economy Lab.   Additional Reading: Apple Sues OpenAI, Accusing It of Stealing Company Secrets OpenAI's First Device Will Be Movable, Screenless Speaker Built as A.I. Companion Nearly 200 Economists and Tech Leaders Warn of A.I. Threats The loudest warning about A.I. and jobs yet OpenAI Is Showing Kalshi's World Cup Odds in ChatGPT New York Enacts Nation's First Statewide Moratorium on Data Centers Brown Professor Suspects Majority of His Class Used A.I. to Cheat MiniMax CEO Vows to Forgo Salary Until Achieving A.G.I. Lorde Speaks Out — With Expletives — Against A.I. Glasses Nearly 6 in 10 Young Women Get Health and Wellness Information from Influencers Meta Removes A.I. Feature on Instagram After Days of Backlash   We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

7Sees is a researcher and host of “This Week on the Web” on Ickonic. He lays out the technocratic plan for enslavement that was gaining popularity during the early 1930s, in part due to the influence of Elon Musk's grandfather. The Technocracy movement was a century ahead of its time, as Aldous Huxley described in the 1932 classic Brave New World. His brother Julian headed the British Eugenics Society and founded the World Wildlife Fund and UNESCO. This new batch of technocrats were incubated at Stanford, Harvard, and In-Q-Tel, financed on Sand Hill Road, then groomed at Bilderberg, Aspen Institute, and the CFR. Their coordinated pivot to AI, and the companies involved in artificial intelligence, is terrifying.Guest: 7Sees | https://x.com/7SEES_---Macroaggressionswww.Macroaggressions.ioMerch StoreLink Tree Video ChannelsRumble | YouTube | BrighteonActivist PostNewsletter Sign UpAudiobooksHypocrazyThe Octopus of Global ControlSupport Our SponsorsReplace Your Mortgage: www.WipeOutYourMortgageNow.comGround Luxe Grounding MatsC60 Power | Promo Code: MACROChemical Free Body | Promo Code: MACROWise Wolf Gold & SilverLegalShield: www.DontGetPushedAround.comChristian Yordanov's Health ProgramThe Dollar VigilanteNesa's Hemp | Promo Code: MACROAugason Farms

Trivia is like sunshine on a cloudy day – on Go Fact Yourself! William Stanford Davis is an actor who plays Mr. Johnson, the enigmatic janitor on “Abbott Elementary.” He'll tell us how the role is a culmination of a lifetime of acting and how he got the part by … dancing? Laura Dave is the author of the book The Last Thing He Told Me. When it became a New York Times bestseller, she literally did not believe it. Now she's adapted the book (and its sequel) into a series on Apple TV. She'll tell us how casting Jennifer Garner in the lead role wasn't nearly as difficult as you might think. Areas of Expertise: Laura: Bruce Springsteen songs, Philadelphia Eagles football, and the movie Sleepless in Seattle. Stan: 1960s to 1980s R&B music, the movie Do the Right Thing, and St. Louis Cardinals baseball from the Lou Brock/Bob Gibson era. What's the Difference: The Metric System What's the difference between a measure and a metric? What's the difference between the justice system and the judicial system? With Guest Experts: Jon Dorenbos: Magician, motivational speaker, and record-breaking member of the Philadelphia Eagles. Otis Williams: Rock & Roll Hall of Famer and founding member of The Temptations. Hosts:  J. Keith van Straaten Helen Hong Credits: Theme Song by Jonathan Green. Maximum Fun's Senior Producer is Laura Swisher. Co-Producer and Editor is Julian Burrell. Additional editing by Valerie Moffat. Seeing our next live-audience shows by YOU! It's always a good time to go to maximumfun.org/joingofact to support this show and get monthly bonus episodes. Help support this show and unlock bonus content! Become a member at https://maximumfun.org/joingofact

As a historian who teaches a class called “The History of Information,” Stanford professor Thomas Mullaney has spent decades thinking about the unreliability of archival materials in understanding the past, subject as they are to decay, disorder and obsolescence. But it wasn't until his own father died and he scrambled to preserve the evidence of his life that he decided to write a personal history of information about how we disappear from the historical record and from the world. We talk with Mullaney about his new book, “How We Disappear: A Personal History of Information.” Thomas Mullaney, professor, Stanford University; author, “How We Disappear: A Personal History of Information” Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's podcast is a rare encounter with someone looking to revolutionise the insurance industry from its core. We are at one of those generational moments when a big tech question is right at the top of the board agenda in almost every industry sector in the world. That question is AI. Insurance is no different. As AI moves from the experimentation phase to the delivery phase, insurance businesses are going to be faced with a key dilemma – should they try to run AI as a new tech layer on top of their current core IT systems or should they take the plunge and use the opportunity to install a whole new system that has been designed and built with AI at its heart? Will Ross is the co-Founder and CEO of Federato and he is betting that enough companies will choose the latter path. Will is an AI native with post-graduate degrees from Stanford University and has been building Federato over the past six years. He is also a very special type of entrepreneur. He discovered insurance when working on wildfire models, but he saw an even bigger business opportunity across the core of insurance and co-founded Federato while still working on his Stanford studies. Federato has built substantial scale and has raised $180mn to date, with the latest round of $100mn lead by Goldman Sachs. This is clearly a firm that means business and is intent on taking a permanent seat at the Insurance IT table. Will is charismatic and fun to talk to and is probably the best-placed guest I have had on the show to date to really examine what the successful embedding of AI into insurance underwriting will mean for the sector as a whole. Some of what we discussed was highly reassuring, but some of his insights were surprising and challenging to conventional wisdom. Much of the industry is at a crossroads over the AI revolution and the next steps are going to be key. Senior decision-makers looking for guidance on their next move would be well advised to listen to Will set out his clear vision in this enlightening interview. LINKS: For more information visit www.federato.ai

The Fast Lane with Ed Lane: Friday, July 17, 2026

“We have a Justice Department which is now 100% the political pawn of the president,” warns Brookings senior fellow Jonathan Rauch. “He points, and they shoot.” Point and shoot. Like an old Kodak camera. Not exactly assuring words, you might think, from a man who begins our conversation looking back at the first six months of 2026 by announcing that he's significantly less alarmed than he was a year ago. Yes, Rauch acknowledges, Trump's approval ratings have sunk, the courts have pushed back, Elon Musk's DOGE rampage has petered out. And yet the pointing and the shooting goes on. Rauch, who only months ago diagnosed eighteen “distinct and unmistakable signs” of an American fascism in a much touted Atlantic piece, now admits he may never crack the Trumpian code. Every time you nail it to the wall, he says, it morphs, creeps or sails away. Like an Iranian gunboat in Hormuz. Slippery stuff for the liberal Brookings analyst. Fascism one month, McKinley-style imperialism the next, then Gilded Age plutocracy — although without those ontologically undeniable Carnegie libraries. Meanwhile, America's 250th birthday party fizzled into what Rauch calls a “damp squib,” its reflecting pool turning an opaque green rather than a clarifying blue. A muddy madness in DC. Still, amidst all the opacity, Rauch remains a defiantly optimistic liberal. In contrast with yesterday's guest, the reality hallucinating Turi Munthe, Rauch believes not only that there is an ontological reality, but that it's good. Frank Fukuyama was right, Rauch insists. Liberalism is not only the only political system that creates wealth, produces knowledge and settles disputes, but also establishes an undeniable reality. Liberals just need to relearn how to clearly tell its story. Perhaps. Though storytelling is certainly simpler when nobody is waving a gun at you. Five Takeaways •       Less Alarmed, Still Scared. Rauch opens with the good news: he is significantly less alarmed than he was a year ago, when the administration was running rampage, putting agencies out of business and demanding Greenland. Approval ratings have dropped, so Trump has less political space; the courts have pushed back, so he has less judicial space; Stephen Miller has vanished from view. And then comes the caveat that gives the episode its title: the Justice Department is now 100% the political pawn of the president — he points, and they shoot — and Trump has shown that as his ratings fall, he becomes more willing, not less, to use those tools. •       I May Never Crack the Code. Only months ago, Rauch diagnosed eighteen distinct and unmistakable signs of a modern American reinvention of fascism in The Atlantic. He doesn't regret the essay — but he has gone back to being confused. The Trump phenomenon is slippery: every time you nail it to the wall, it morphs, creeps or slides away. Fascism one month, McKinley-style imperialism in Venezuela the next, an Iran war with no rationale at all. Trump is such an improviser, and so disorganized, that Rauch concedes there is an element of randomness he may never decode — though he accepts Andrew's suggestion that attention is now the coin of the political realm. •       Not the Gilded Age — No Carnegie Libraries. The new inequality, Rauch argues, is different in kind: a class of people almost superhuman in the wealth they control, and strangely narcissistic and nihilistic toward the broader society. The Gilded Age tycoons did some bad things, but they also built — Carnegie's libraries, Mellon's National Gallery, Rockefeller's University of Chicago, Stanford's university. This group builds rockets and sounds, in the case of Marc Andreessen, like a parody of an Ayn Rand novel — or, as Andrew corrects him, not a parody at all: they simply repeat what they've read. Even so, Rauch is not sorry to see politics reacting to a world where Musk can casually drop $300 million into a presidential race. •       The Gloves-Off Court and the Accelerating Presidency. The Supreme Court term brought the clearest statement yet of the conservative agenda: Humphrey's Executor overturned after eighty years, making it far easier for presidents to fire agency heads at will; what remained of the Voting Rights Act effectively gutted; birthright citizenship surviving by a shockingly narrow margin. The imperial presidency is not new, Rauch notes — what's new is the speed. A president can now simply refuse to run a congressionally mandated agency, and the Senate, forty quietly nixed nominations notwithstanding, remains lacking in spine. The Todd Blanche nomination, he says, is the next test of whether any line exists at all. •       Fukuyama Was Right — and Liberals Should Say So. Rauch sees a moral vacuum and, for the first time, a craving to fill it: the pope's AI encyclical, multi-faith clergy bearing witness in Minnesota, the Episcopalians and Latter-day Saints finding their voices. His prescription for the second half of 2026 is a liberal one, in the nineteenth-century sense — science, markets, constitutions, rule of law. Fukuyama, widely misunderstood, was right: there is only one system that produces knowledge, peace, freedom, and wealth on a global scale, and it's ours. It needs fixing — he cheers the bipartisan housing bill Trump refused to sign — but liberals must relearn how to tell that story, and how to brag. About the Guest Jonathan Rauch is a senior fellow in Governance Studies at the Brookings Institution and a contributing writer at The Atlantic. He is the author of nine books, including The Constitution of Knowledge: A Defense of Truth (2021), Cross Purposes: Christianity's Broken Bargain with Democracy (Yale, 2025), and Kindly Inquisitors: The New Attacks on Free Thought. A recipient of the National Magazine Award, he serves on the boards of Heterodox Academy and Civic Life, and is a longtime friend of the show. References: •       Rauch's Atlantic essay identifying eighteen “distinct and unmistakable signs” of a modern American reinvention of fascism — the piece he stands by, even as he admits the phenomenon keeps morphing. •       His recent essays for The UnPopulist on why liberal societies need grand stories about themselves, and why liberals must relearn how to brag about liberalism. •       Jonathan Rauch and Peter Wehner in The New York Times — the earlier argument, which Rauch says still holds, that the Republican Party is more dangerous to the constitution and the rule of law than the Democratic Party. •       Tim O'Reilly in The Economist — on Elon Musk building a form of capitalism that Adam Smith would hate. •       Francis Fukuyama — whose widely misunderstood The End of History thesis Rauch defends: there is only one system that creates wealth, produces knowledge, and settles political disputes on a global scal...

Every capability in an agent needs its own evidence and release bar. A model-provider slip, an incorrect tool call, and a wrong fertility-benefits answer should not be held to the same pass rate.William Horton, Staff AI Engineer at Maven Clinic, joined us the day after Maven Assistant reached its first external users. The agent helps members inside Maven Clinic's women's and family healthcare platform find providers, manage appointments, navigate Maven, and get basic health information. William had spent much of launch day reading chat traces and turning the surprises into product decisions and tests.William shows how a production failure moves through Maven's system: the trace becomes a regression case, code handles deterministic checks, and LLM judges cover behavior that cannot be reduced to exact outputs. Human labels calibrate those judges, while the consequence of a wrong answer determines whether the capability ships. You can apply the same release workflow to the agent you are building now.“For a lot of our tool-call evaluation, I'll accept that it runs ten times and passes nine times. Going for that ten out of ten is just not worth the effort.”— William Horton, Staff AI Engineer, Maven ClinicYou can also find the full episode on Spotify, Apple Podcasts, and YouTube.

[Re-Aired] Mastering Science Communication with Simar Bajaj, Multi-Award-Winning Science Journalist--In this remixed fireside chat from 2023, we sit down with Simar Bajaj then a Harvard undergraduate student and now: a Stanford medical student, Knight-Hennessy Scholar, Oxford Marshall Scholar, and Harvard University graduate. Join us as we discuss Simar's incredible achievements in science communication, the perseverance his field demands, and the sheer hard work behind producing top-tier journalism. As a current award-winning former New York Times reporter and Forbes 30 Under 30 honoree, Simar shares invaluable insights from his experiences writing for major outlets like NPR, The Atlantic, and The Washington Post, as well as publishing first-author research in premier medical journals. This is truly a must-listen episode!Connect with Simar:Website: https://www.simarbajaj.com/LinkedIn: https://www.linkedin.com/in/simar-bajaj/Disclaimer:The views expressed in this podcast are those of the host and guest(s). This episode is designed to provide educational and intellectually stimulating support for peer pharmacists in training. It is not intended to serve as medical advice or recommendations. For personalized medical guidance, please consult your local board-certified physician, PA, NP, or pharmacist.

In this college football podcast episode, we continue our 2026 ACC preview with conversations about eight conference teams and Notre Dame. Is this finally the year Miami turns its loaded roster into its first conference championship? How high is the ceiling for an Irish squad with College Football Playoff expectations, a Heisman candidate at quarterback, and more talent than ever? We also examine whether SMU is ready to take another step under Rhett Lashlee, whether Virginia can build on last season’s breakthrough with defense and small ball, and whether Pitt can turn another fast start into something more sustainable. Florida State enters a defining seventh season under Mike Norvell, while North Carolina begins Year 2 of the Bill Belichick experiment with Bobby Petrino running the offense. Wake Forest remains dangerous, strange and difficult to play, while Stanford begins a patient rebuild under Tavita Pritchard. Plus: The Davis Warren Commission, Mid-Atlantic Hawkeyes, quarterback passport stamps, an unexpected amount of Train trivia, HGTV renovation metaphors, and an important reminder to wash your produce. Timestamps:0:00 - Intro5:11 - Virginia Cavaliers Preview17:30 - Miami Hurricanes Preview29:13 - Notre Dame Fighting Irish Preview41:14 - SMU Mustangs Preview47:04 - Pitt Panthers Preview53:29 - Florida State Seminoles Preview1:03:32 - North Carolina Tar Heels Preview1:08:08 - Wake Forest Demon Deacons Preview1:14:03 - Stanford Cardinal PreviewSupport the show!: https://www.patreon.com/solidverbalSee omnystudio.com/listener for privacy information.

"The assumption of swift trust is really useful."Teams don't always need years to build trust—they need the right conditions to build it quickly. As a Stanford professor and expert in organizational design, Melissa Valentine studies how communication, team structure, and emerging technologies help people collaborate more effectively. In this episode of Think Fast, Talk Smart, Valentine joins Matt Abrahams to explore how leaders can foster swift trust, adapt communication as teams move from brainstorming to execution, and use storytelling to drive meaningful change. Together, they share practical strategies for building stronger teams and navigating collaboration in an AI-enabled workplace.Key Takeaways:Build trust from the start. High-performing teams assume competence, communicate openly, and address miscommunication quickly.Adapt your communication to the task. Encourage diverse thinking during brainstorming, then align your language as the team moves toward execution.Activity:Practice swift trust. In your next project with a new colleague or team, begin by assuming competence and shared intent. Delegate one meaningful responsibility early, communicate clear expectations, and reflect afterward on how starting from trust influenced the team's collaboration and results.Episode Reference Links:Melissa ValentineMelissa's Book: Flash TeamsEp.241 Team Spirit: How to Make Group Work WorkEp.268 Going Viral: How To Balance Authenticity and Spectacle Connect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedInChapters:(00:00) - Introduction (00:57) - What Makes a Flash Team? (03:01) - Building Swift Trust (04:54) - When Teams Need to Converge (07:17) - Repairing Miscommunication (09:18) - Stories That Drive Change (12:01) - Lessons for Every Team (13:47) - The Final Three Questions (16:41) - Conclusion ********Thank you to our sponsors.  These partnerships support the ongoing production of the podcast, allowing us to bring it to you at no cost.Most Work Platforms Help People Communicate.  Some help you organize, but Zoom turns conversations into outcomes. Try Zoom Mate today

Meikael Beaudoin-Rousseau was fishing alone at the top of Nevada Falls at the age of 10, and has been finding ways to move faster through the mountains ever since. The Stanford-trained distance runner turned professional trail and mountain specialist joins Dominic to talk about a two-year injury saga that has redefined how he thinks about training, resilience, and what it actually means to compete. After a catastrophic fall at the 2024 Broken Arrow Skyrace left him with a complex orthopedic injury, Meikael spent 18 months trying every non-surgical approach available before going under the knife at the end of 2025. In February, he was relearning to walk. In April, relearning to run. He came back and toed the line at the 2026 U.S. Uphill Championships and finished 7th overall.The conversation covers what it looks like to maintain professional-level fitness off of 20 to 30 miles a week (and two hours of daily elliptical and arm bike work); why vertical kilometer races are physiologically closer to an 800 meter than a 10k; and how growing up entirely outdoors in the Bay Area (fishing, climbing, running trails to make curfew) built the athletic foundation that track never could. Meikael also gets into the plant business he started in middle school, the summers he spent living out of his car in the Sierra Nevada, and why he thinks cross-country skiers would beat marathoners in a trail race every time.His message to anyone trail-curious: DM him. He means it.Tap into the Meikael Beaudoin-Rousseau Special. If you enjoy the podcast, please consider following us on Spotify and Apple Podcasts and giving us a five-star review! I would also appreciate it if you share it with your friend who you think will benefit from it.S H O W  N O T E S   -The Run Down By The Running Effect (our new newsletter!): https://tinyurl.com/mr36s9rs-Our Website: https://therunningeffect.run  -THE PODCAST ON YOUTUBE: https://www.youtube.com/channel/UClLcLIDAqmJBTHeyWJx_wFQ-My Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/therunningeffect/?hl=en⁠⁠⁠⁠⁠⁠-Take our podcast survey: https://tinyurl.com/3ua62ffzBehind the scenes of The Running Effect: https://youtube.com/@dominicschlueter?si=PM9FjPc92eFUFEZLuminaryThreads: luminarythreads.shop Instagram: @mountain_man_meik

Mario Jerez and Erin Summers are joined by Saints safety Justin Reid for an in-depth conversation as training camp approaches. Justin reflects on his unique football journey, from growing up in Ascension Parish and starring at Dutchtown High School to choosing Stanford over LSU and eventually becoming a two-time Super Bowl champion with the Kansas City Chiefs. Reid discusses the influence of his family, including his mother's remarkable work ethic and his early passion for soccer, which nearly became his primary sport before football took center stage. Justin also opens up about life away from the field, sharing his interests in photography, chess, and other personal passions that help him stay balanced during the NFL season. On the football side, Reid provides insight into the Saints' offseason preparations, his growing role as a veteran leader, and the benefits of another year in Brandon Staley's defensive system. He discusses the impact of players such as Chase Young, Justin Blackmon, Kool-Aid McKinstry and Jonas Sanker, while also evaluating the continued development of quarterback Tyler Shough. Reid shares his thoughts on what Alvin Kamara and Travis Etienne can bring to the offense and explains how familiarity and continuity could help elevate the Saints defense in 2026. The conversation also touches on the NFC South race, New Orleans' rivalry with Atlanta, comparisons between Brandon Staley and Steve Spagnuolo, and Reid's approach to blocking out outside noise and “fabricated hearsay” as the Saints prepare for a pivotal season. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Is the software business dying? Loulou sits down with Ahmad AlZaini, co-founder and CEO of Foodics, at the 11-year mark of the company for the operator's read on the biggest question in tech this year: what happens to software when AI agents replace the human at the login screen. Foodics is the restaurant operating system for the region: 40,000+ locations across the GCC, Egypt and Jordan, $13B in payments processed to date, on track for $14B by end of year, 700 people, licensed by the Saudi Central Bank, backed by a $198M capital raise including a record $170M Series C. Ahmad is a Forbes-recognized entrepreneur with executive credentials from Harvard, Stanford and MIT, and was appointed to the Endeavor Saudi board of directors in 2026. Subscribe for weekly conversations on business, investing, leadership and what is actually happening in the Arab world. Chapters 01:42 Foodics at 11: the top line, $13B GMV, 40,000 locations, 40% revenue outside Saudi  04:08 From Al Khobar to Aramco to Foodics: why the founder was never supposed to be a founder  09:43 Investor due diligence in reverse: not all money is equal, cap-table hygiene from an acquirer's chair  14:47 Growth capital advice: do not take from Saudi at growth stage, go global, come back with matched terms  18:36 40 SF VC meetings, 3 term sheets: how to raise when nobody knows where Riyadh is  21:04 Talent reverse migration: C-suite relocating from Boston, NY, SF, Paris and London to Riyadh  23:54 AI is out of the box: the Anthropic February 2026 SaaS selloff explained  31:15 The PhD intern: how a fresh graduate should show up with an AI use case, not a certificate  33:37 The pricing shift: nobody pays for logins in 2030, everyone pays for outcomes and usage  43:09 The exit conversation: if for one minute you decide you need to exit, you are not in the right business  48:45 Secondary markets, buybacks, and why every employee should have liquidity options  53:46 The under-30 Saudi generation: high-school AI hackathons, curiosity, and where they spend Follow Loulou Khazen Instagram: /louloukhazen LinkedIn: /louloukhazen X (Twitter): /louloukhazen Follow the guests Ahmad AlZaini Linkedin: https://www.linkedin.com/in/alzaini/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Is the AI industry actually overbuilding, or is the physical world moving too slowly to keep up? In this episode of the MAD Podcast, OpenAI's Head of Industrial Compute, Sachin Katti, takes us inside the "belly of the beast" of what may be the largest infrastructure project in human history. We explore the staggering physical reality of the AI boom—from $50 billion supercomputers and liquid-cooled data centers that "turn electrons into tokens," to overhauling the U.S. power grid and exploring nuclear energy. Sachin also pulls back the curtain on OpenAI's Stargate strategy, their move into custom silicon with Project Jalapeno, and the mind-bending reality that AI is now beginning to design the very chips that will power its own future.(00:00) — Cold open: “One of the largest things humanity has ever built”(00:30) — Welcome: Sachin Katti, Head of Industrial Compute at OpenAI(01:44) — Is this the biggest infrastructure buildout in history?(03:41) — Why OpenAI is building a new industrial muscle(04:54) — What an AI data center actually is(05:27) — “Factories turning electrons into tokens”(06:35) — Why AI data centers need liquid cooling everywhere(08:10) — The power problem: grids, generation, transmission, substations(10:43) — Behind-the-meter power and gas turbines(11:02) — Why nuclear “can't come soon enough”(11:49) — Jalapeño: why OpenAI is designing its own AI chips(13:19) — Tokens per watt: the new metric that matters(13:38) — Why inference may now dominate AI compute(14:58) — Is OpenAI overbuilding compute?(16:47) — Why OpenAI thinks the bigger risk is not building fast enough(17:55) — Communities, jobs, water, and the local data-center debate(21:16) — How OpenAI chooses data-center sites(22:25) — What “industrial compute” means inside OpenAI(25:59) — Sachin's path: Stanford, startups, Intel, OpenAI(28:05) — OpenAI's compute portfolio: Microsoft, hyperscalers, neoclouds(29:37) — Stargate explained(31:21) — Abilene, Oracle, and the next wave of AI data centers(32:48) — How massive AI compute gets financed(34:05) — How OpenAI designed Jalapeño so quickly(35:59) — AI is starting to help design AI chips(36:20) — MRC: the networking problem behind 100,000 GPUs(38:47) — Bottlenecks: transformers, turbines, electricians, supply chains(40:29) — Guaranteed capacity: intelligence as a supply unit(42:08) — Will AI data centers move to space?

This week on The Beat, CTSNet Editor-in-Chief Joel Dunning spoke with Dr. Chris Malaisrie, a Professor of Surgery in the Division of Cardiac Surgery at Northwestern University and an Attending Cardiac Surgeon at Northwestern Medicine, about valve-sparing aortic root replacement techniques. Chapters 00:00 Intro 02:25 TAVR Heart Team Coverage 03:52 JANS 1, TAVR vs SAVR Perspective 10:50 JANS 2, Gene-Edited Transplant Model 13:13 JANS 3, Long-Term Outcomes Atrial Fib 14:31 JANS 4, 147-Minute Drowning Circ Arrest 18:01 Video 1, Double Ann Enlargement Prosth Mis 20:48 Video 2, Reop Aortic Root Reconstruction 22:24 Video 3, Normothermic AA Aneurysm 24:22 Dr. Malaisrie, Aortic Root Replacement 41:42 Closing The conversation covers a wide range of procedures, including the Bentall, Yacoub, and David operations, as well as the Ross procedure and personalized external aortic root support (PEARS). They further explore approaches to mitral and aortic valve repair, the management of diseased leaky valves, and the advantages of the Stanford modification of the David V procedure. Dr. Malaisrie concludes the discussion by offering advice to surgeons on refining their valve repair skills and shares his prediction for the future of valve repair surgery. Joel also highlights recent JANS articles on age vs lifetime perspective on the transcatheter vs surgical aortic valve implantation, gene-edited pig cardiac xenotransplantation as a bridge to allotransplantation in infants, long-term outcomes of postoperative atrial fibrillation after cardiac surgery, and a case on ice water drowning survival after 147-minute submersion and 7 °C hypothermic circulatory arrest. In addition, Joel explores double annular enlargement as an effective technique to overcome patient-prosthesis mismatch, reoperation for aortic root reconstruction, and normothermic treatment of an aortic arch aneurysm. Before closing, Joel highlights upcoming events in CT surgery. JANS Items Mentioned Transcatheter vs Surgical Aortic Valve Implantation: Age vs Lifetime Perspective Gene-Edited Pig Cardiac Xenotransplantation as a Bridge to Allotransplantation in Infants: Progress in a Pig-to-Baboon Model Long-Term Outcomes of Postoperative Atrial Fibrillation After Cardiac Surgery: Results From 19,000 Patients Ice Water Drowning Survival After 147-Minute Submersion and 7 °C Hypothermic Circulatory Arrest CTSNet Content Mentioned Double Annular Enlargement as an Effective Technique to Overcome Patient-Prosthesis Mismatch Reoperation for Aortic Root Reconstruction Normothermic Treatment of an Aortic Arch Aneurysm Other Items Mentioned Centers for Medicare & Medicaid Services Database—TAVR Career Center CTSNet Events   Disclaimer The information and views presented on CTSNet.org represent the views of the authors and contributors of the material and not of CTSNet. Please review our full disclaimer page here.

Get the thumbs-up from a Harvard- and Stanford-trained sports orthopedic surgeon before clicking the draft button! Join Seth Woolcock, Scott Bogman and Dr. Deepak Chona for their top 10 fantasy football injury updates ahead of 2026 NFL training camps. Has New York Giants WR Malik Nabers' clean-up surgery made him a potential bust or value in drafts? Is targeting Kansas City Chiefs QB Patrick Mahomes worth the risk coming off a torn ACL and LCL? Plus, why is Tampa Bay Buccaneers RB Bucky Irving poised for a bounce-back season? The Pros hit the blue medical tent before camps open across the league! Timestamps: (May be off due to ads) Intro - 0:00:00Malik Nabers (WR - NYG) | WR18 (39 Overall) - 0:02:10Patrick Mahomes (QB - KC) | QB13 (97 Overall) - 0:07:42George Kittle (TE - SF) | TE10 (108 Overall) - 0:11:46Christian Watson (WR - GB) | WR27 (57 Overall) - 0:15:44Chris Godwin (WR - TB) | WR36 (86 Overall) - 0:19:18Zach Charbonnet (RB - SEA) | RB44 (132 Overall) - 0:21:15Tucker Kraft (TE - GB) | TE5 (66 Overall) - 0:22:32 Bucky Irving (RB - TB) | RB21 (54 Overall) - 0:24:01Cam Skattebo (RB - NYG) | RB19 (50 Overall) - 0:26:06Jonathon Brooks (RB - CAR) | RB43 (130 Overall) - 0:28:47Outro - 0:31:33 Helpful Links: Hard Rock Bet - Sign up for Hard Rock Bet and make a $5 bet and you'll get $150 in bonus bets if you win. Head over to Hard Rock Bet, sign up and make your first deposit today. Payable in bonus bet(s). Not a cash offer. Offered by the Seminole Tribe of Florida in FL. Offered by Seminole Hard Rock Digital, LLC, in all other states. Must be 21+ and physically present in AZ, CO, FL, IL, IN, NJ, OH, TN or VA to play. Terms and conditions apply. Concerned about gambling? In FL, call 1-888-ADMIT-IT. In IN, if you or someone you know has a gambling problem and wants help, call 1-800-9-WITH-IT. GAMBLING PROBLEM? CALL 1-800-GAMBLER (AZ, CO, IL, NJ, OH, TN, VA) Draft Wizard - Dominate your fantasy football draft with Draft Wizard. Run fast mock drafts, test different strategies, build custom cheat sheets, get pick-by-pick draft advice, and learn your leaguemates' tendencies before draft day. Just download the FantasyPros App or head to fantasypros.com/draftwizard Follow us on Twitch - The team here at FantasyPros is taking questions all week, every week on Twitch. Follow us on Twitch at twitch.tv/fantasypros and never miss a stream! Discord – Join our FantasyPros Discord Community! Chat with other fans and get access to exclusive AMAs that wind up on our podcast feed. Come get your questions answered and BE ON THE SHOW at fantasypros.com/chat Leave a Review – If you enjoy our show and find our insight to be valuable, we’d love to hear from you! Your reviews fuel our passion and help us tailor content specifically for YOU. Head to Apple Podcasts, Spotify, or wherever else you get your podcasts and leave an honest review. Let’s make this show the ultimate destination for fantasy football enthusiasts like us. Thank you for watching and for showing your support – https://fantasypros.com/review/ BettingPros Podcast – For advice on the best picks and props across both the NFL and college football each and every week, check out the BettingPros Podcast at bettingpros.com/podcast, our BettingPros YouTube channel at youtube.com/bettingpros, or wherever you listen to podcasts.See omnystudio.com/listener for privacy information.

What has been the cost to women of relying on research that was never designed around female physiology?Dr. Stacy Sims is an exercise physiologist, nutrition scientist, and bestselling author of ROAR, which challenged the idea that women should train and fuel like men, and Next Level, which focuses on health, performance, and physiology through perimenopause and menopause. Over two decades of research, she has become one of the leading voices reshaping how we understand women's health, with a message that has become synonymous with her work: women are not small men. That line started as a throwaway teaching point during her postdoc at Stanford, and it has since become a paradigm shift.At the center of this conversation is a quiet, costly problem. For decades, much of the science on training, nutrition, and medicine was built on male bodies and then applied to women as if they were simply smaller versions of men. Stacy walks through what that gap has cost, why the literature thins out for women between the ages of thirty and fifty, and how a hormone fluctuation can get mistaken for a panic attack, leading to solutions that were never going to fully work.Stacy and Mike then move into what to actually do about it. They get into why "eat less, train more" often backfires and drives the body into a low energy state, why fasting through the morning for women can dysregulate appetite and stress hormones, and why lifting heavier loads may protect not just muscle and bone but the aging brain. They also draw the line that runs through the whole conversation, the symptoms of perimenopause are the physiology, not the person, and explore why this episode isn't just for the women in the community. Stacy explains why having men in the conversation helps drive action, what partners can actually do... listen first rather than rush to fix... and why the rising noise around menopause online, along with AI tools built on outdated male data, makes clear thinking here more valuable than ever.In this conversation, we explore:Why so much health and performance research was never actually done on womenWhat "women are not small men" really means in training and nutritionWhy "eat less, train more" often backfires for women through midlifeWhy fasting through the morning can dysregulate appetite and stress hormonesHow lifting heavier loads may help protect the aging brainWhy men belong in this conversation, and how to show up for the women in their livesWhy most AI health tools still run on outdated male dataWhether this conversation is about your body or the body of someone you love, it offers a science-backed way to understand what's happening and what to do next.Links & ResourcesSubscribe to our YouTube Channel for more conversations at the intersection of high performance, leadership, and wellbeing: https://www.youtube.com/c/FindingMasteryGet exclusive discounts and support our amazing sponsors!Go to: https://findingmastery.com/sponsors/Subscribe to the Finding Mastery newsletter for weekly high performance insights: https://www.findingmastery.com/newsletterDownload Dr. Mike's Morning Mindset Routine: findingmastery.com/morningmindsetFollow on YouTube, Instagram, LinkedIn, and XDr. Stacy Sims' Books: ROAR and Next LevelSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Scientific Sense ® by Gill Eapen: Prof Mike Snyder leads the center for genomics at Stanford. He collects and analyzes deep data from wearables to transform helathcare through analysis and behavior modifications.Please subscribe to this channel:https://www.youtube.com/c/ScientificSense?sub_confirmation=1

Most professionals focus almost exclusively on performance—and then wonder why someone else gets promoted. This 97% Effective Essentials episode introduces a simple framework that fundamentally changes how you see and approach career success.Learn more about Michael Wenderoth, Executive Coach: www.changwenderoth.comSHOW NOTES:Performance and PIEThink about yourself as a productDoes this mean I should stop doing great work?Why organizations are different than school and many sports3 “sad but true” research findings that reveal who gets credit, and who gets pickedInsight on perception from photographer Richard Waine: “You're professional headshot is not about you.”Flip the script: how do others see you?“I” = ImageThe definition of brand and a quick exercise to uncover your brandA warning from executive coach Anne Marie Segal about typecasting – and the leap you need to makeHow are you showing up?“E” = Exposure, which can come in many waysHow award-winning speaker Alex Tremble did two things to catapult his early rise in the Federal GovernmentExposure in a remote worldDo you need to make radical shifts?If you don't manage your Image and Exposure, what's likely to happen BIO AND LINKS:Michael Wenderoth is an Executive Coach that helps executives re-examine their assumptions about power, politics, and authenticity to get promoted, become more effective at work, and break glass ceilings holding them back. Having served 20 years in senior roles with companies across the globe, and then 7 years as a professional coach, he has helped accelerated the careers of clients from diverse industries, backgrounds, and levels of seniority, helping them get ahead – without having to sell their souls in the process. Michael is the award-winning author of Get Promoted, host of the 97% Effective career acceleration podcast, and a frequent speaker and media contributor on career advancement, leadership and navigating power and politics. His work has been featured in Harvard Business Review, Forbes, Stanford Business School Executive Education and IE Business School, where he collaborates with renowned professors, coaches, executives and experts. Michael holds an MBA from Stanford and trained as an executive coach at Columbia University (3CP). Michael's Book, Get Promoted: https://tinyurl.com/453txk74Michael on LinkedIn: https://www.linkedin.com/in/michaelchangwenderoth/Learn more about Michael Wenderoth, Executive Coach: www.changwenderoth.comResearch cited: See Chapter Chapter 5 (“What the Evidence Really Says” in Get Promoted: https://tinyurl.com/453txk74Richard Waine on what professional headshot is really about: https://tinyurl.com/2wcmamkwAnne Marie Segal on how to avoid being “typecast”: https://tinyurl.com/39myjfzsAlex Tremble on visibility in the corridors of power: https://tinyurl.com/4paf4evjGet Promoted named Winner (Business-Careers) and Finalist (Business-General), 2023 International Book Awards: https://www.internationalbookawards.com/2023pressrelease.htmlAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Three starters gone — including All-American center Jake Slaughter — and a brand-new position coach. Florida's offensive line got a total makeover this offseason, and today we're breaking down the whole room ahead of the 2026 season.In this episode:- A rebuilt trench — Florida lost Austin Barber, Jake Slaughter, and Damieon George Jr., so new OL coach Phil Trautwein hit the portal hard with four transfer additions- The Penn State pipeline — Trautwein brought Eagan Boyer and TJ Shanahan Jr. with him from Happy Valley; can they lock down left tackle and right guard?- Replacing an All-American — Georgia Tech transfer Harrison Moore vs. former five-star Jason Zandamela in the battle at center- The wildcard — Stanford transfer Emeka Ugorji started 8 games as a true freshman and is pushing for the right tackle job- The veterans — Knijeah Harris anchors left guard, plus where Caden Jones, Roderick Kearney, Bryce Lovett, and TJ Dice Jr. fit- Rotation or starting five? — Trautwein says he'll play as many linemen as earn it; what that means for the two-deepIf you bleed orange and blue, hit SUBSCRIBE and turn on notifications so you never miss an episode!#GoGators #FloridaGators #GatorsFootball #JonSumrall #SEC #CollegeFootball #StadiumandGale

ATypI 2026 Stanford 系列访谈第三期，我们有幸邀请到演讲者彭措昂杰，以及老朋友张可迪，与我们分享藏文字体设计的基础知识与分类方式，探讨藏文字体的设计现状。 参考链接 藏语 字谈字畅 257：「互相了解的前提是能看见」 河南蒙古族自治县（ᠾᠧᠨᠠᠨ ᠶᠢᠨ ᠮᠣᠩᠭᠣᠯ ᠦᠨᠳᠦᠰᠦᠲᠡᠨ ᠦ ᠥᠪᠡᠷᠲᠡᠭᠡᠨ ᠵᠠᠰᠠᠬᠤ ᠰᠢᠶᠠᠨ，རྨ་ལྷོ་སོག་རིགས་རང་སྐྱོང་རྫོང།），是中国青海省黄南藏族自治州下属的一个自治县 藏区在传统上分为安多（ཨ༌མདོ།，a mdo/Amdo）、卫藏（དབུས་གཙང，dbus gtsang/Wü-Zang）、康区（ཁམས，khams/Kam）三个地区 古文字学（paleography），交叉学科，研究古代手稿、文本，以及古代书法、印刷品等 “The Status of Tibetan Type Design”，彭措昂杰在 ATypI 2026 Stanford 的演讲 更顿群培（དགེ་འདུན་ཆོས་འཕེལ，dge 'dun chos 'phel/Gedun Chophel；1903—1951），藏传佛教大师、启蒙思想家 Sam van Schaik（1972—），英国藏学家，也是目前国际上研究敦煌藏文文献最有影响力的学者之一。他早年参与国际敦煌项目（IDP），现任大英图书馆濒危档案计划负责人。 拉卜楞寺（བླ་བྲང་བཀྲ་ཤིས་འཁྱིལ，bla-brang bkra-shis-'khyil/Labrang Tashi Khyi），位于甘肃省甘南藏族自治州夏河县，藏传佛教寺院 大司徒班禅曲吉久勒（ སི་ཏུ་པན་ཆེན་ཆོས་ཀྱི་འབྱུང་གནས，si tu pan chen chos kyi 'abyung gnas/Situ Panchen Chögyi Jungnye，1700—1774）第八代大司徒仁波切，西藏画家、作家，德体/德格体的创始人 德格印经院，藏语称「德格巴宫」（སྡེ་དགེ་པར་ཁང，sde dge par khang），位于四川省甘孜藏族自治州德格县，藏传佛教印经中心之一，全国重点文物保护单位 藏文字体分类名称 乌金/吾坚体（དབུ་ཅན། ，dcu can/Uchain）即「带头体」 乌梅/吾美体（དབུ་མེད།，dcu med/Umê），即「无头体」 珠匝体（འབྲུ་ཚ། ，'bru tsha/Drutsa） 白徂/柏簇体（དཔེ་ཚུགས།，dbe tshugs/Petsug），即「书写体」 徂仁/簇仁体（ཚུགས་རིང་།，tshugs ring/Tsugring），即「长体」 徂同/簇通体（ཚུགས་ཐུང་།，tshugs thung/Tsuthung），即「短体」 簇穹体（ཚུགས་ཆུང་།，tshugs chung/Tsuchung），即「小体」 簇玛丘/徂玛遒（ཚུགས་མ་འཁྱུག，tshugs ma 'khyugs/Tsumakhyu），即「半草」「行书」 丘伊体（འཁྱུག་ཡིག，'khyug yig/Khyuyig），即「草书」 八思巴文（ꡏꡡꡃ ꡣꡡꡙ ꡐꡜꡞ，mongxol tshi），元朝国师八思巴基于当时的藏文字制定的文字，可书写蒙古语等 苹果设备的系统默认的藏文字体为 Kailasa 字体，另外还有一款 Koronor 字体，版权均属于日本大谷大学真宗综合研究所；前者为冈底斯山脉第二高峰冈仁波齐峰（གངས་རིན་པོ་ཆེ།，gangs rin po che/Kangrinboqê）的梵语名कैलास（Kailāsa）；后者即蒙古语的「青海湖」（ᠬᠥᠬᠡ ᠨᠠᠭᠤᠷ，Köke naɣur） Typotheque 出品的藏文字体系列 “BubbleKern Revisited”，大曲都市在 ATypI 2026 Stanford 的演讲 每年的4月30日是藏文书法日 “Typecrafting: Creating Type from South Asian Crafts”，Ishan Khosla 在 ATypI 2026 Stanford 的演讲 “The Parametric Power of Roboto Delta”，Dave Crossland 在 ATypI 2026 Stanford 的演讲 “Scripts in Transition: Language, Design, and Belonging in Myanmar Theingi Thann”，Theingi Thann 在 ATypI 2026 Stanford 的演讲 SILICON (Stanford Initiative on Language Inclusion and Conservation in Old and New Media)，斯坦福大学关于数字媒介中弱势语言的支持项目 “Designing for Belonging: How Color, Typography, and Iconography Shape Culture, Community, and the Human Experience”，陆怡颖在 ATypI 2026 Stanford 的演讲 微信公众号「藏文字体测评局」 金刚黑体，华康出品的多文种字体家族 嘉宾 彭措昂杰（རྩང་ཕུན་དབང་།，Pentsok W. Rtsang）：藏文字体学者、顾问和测评员 张可迪（@抠迪歪歪歪）：产品设计师，字体爱好者 主播 Eric：字体排印研究者、译者，The Type 执行编辑 欢迎与我们交流或反馈，来信请致 podcast@thetype.com​。如果你喜爱本期节目，也欢迎用支付宝向我们捐赠：hello@thetype.com​。

If you love college football analysis, conference previews, rankings, predictions, and live discussions, make sure to LIKE, SUBSCRIBE, and turn on notifications so you never miss a show from Play The Fight Song CFB.LIVE ACC Football Preview | 2026 ACC Season Predictions, Rankings & Championship Picks | Play The Fight Song CFBThe ACC is set for another exciting college football season, and we're breaking it all down LIVE! Join Play The Fight Song CFB as we discuss the biggest storylines, predict the conference standings, and make our picks for the ACC Championship and College Football Playoff.We'll cover:

In May 2024, Vermont enacted entirely unprecedented legislation that attempts to mitigate climate-charged disaster events and associated financial fallout inflicted on Vermont residents. Vermont climate superfund legislation, followed seven months later by New York (and presently pursued by at least ten other states), is in response to climate-charged disaster events that over the ten- yr period ending in '25 cost Vermonters upwards of ~$2 billion. The legislation, premised on a deeply entrenched polluter pay principle, e.g., modeled after the federal toxic waste Superfund program, requires so called carbon majors, here oil and gas companies, to meet their unpaid, externalized costs by making compensatory payments. New York law is targeting a $75 billion fund. These dedicated funds will generally finance climate adaptation and infrastructure resiliency. Not surprisingly, these laws face of aggressive legal challenges by among others the American Petroleum Institute, the U.S. Chamber of Commerce, West Virginia-led state attorneys general and the Trump administration that has filed federal lawsuits against both VT and NY. Among numerous related interviews, listeners will recall I discussed advances in attribution science with Stanford's Chris Callahan in May 2025.Information re: Vermont's Climate Superfund Act is at: https://climatechange.vermont.gov/climate-superfund. Information re: Vermont's Conservation Law Foundation is at: https://www.clf.org/serving-new-england/vermont/. (Apologies to Ms. Mihaly, at one point I call her Emily!?!) This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.thehealthcarepolicypodcast.com

Which factors should MBA couples consider when deciding whether to apply together? And how should they communicate that in their applications?

I've gotten to know Joe about as well as two dads can over five years of school events: close enough to appreciate the work he's doing as a dad to wonder how - and why - he does it. Superficially, Joe is unique at our school for his commitment to his kids' tennis endeavors. He once described to me in intricate detail the cost-benefit analysis and lived experience of choosing a daily car rental over taxi rides for his multiple-times-a-day trips to the John McEnroe Tennis Center on Randalls Island, a small spit of land next to Manhattan that you access via the blink-and-you'll-miss-it Platform 9¾ exit of the RFK Bridge. To this role of parent-coach, Joe brings his own experience as a varsity tennis player at Stanford.I'll be honest: Joe is the kind of dad who makes me wonder if I'm doing enough as a dad. Also, how cool is it that he played varsity tennis at Stanford? It activates the region of my Asian American heart occupied by Kristi Yamaguchi, Michelle Kwan, Jeremy Lin, and of course, Michael Chang, who became a household name when he shocked the world by winning The French Open in 1989 as a 5-foot-6 135-pound 17 year old.When Joe and Crystal recently shared their plans to move back to Joe's hometown in Southern California, I assumed it was for tennis. That's just the beginning of the story you're about to hear: it takes place on the tennis court, but the game being played is life and karma matters more than your first serve.

The previous post covered my grades on how the strength of today’s four largest college athletic conferences compare with their previous versions twenty years ago in 2006. Here's a brief recap. In my estimation, only the SEC (which expanded from 12 to 16 teams over that 20 year period) has shown an upgrade in competition levels since 2006.  I awarded the SEC a “B” grade. The Big 12 (which lost four of its prominent members to the SEC) received a C+ for their nimble addition of several relevant regional sports schools. A “D” grade was handed down to the Atlantic Coast Conference.  Their nonsensical addition of West Coast newcomers Cal (Berkeley) and Stanford in 2024 crashed the ACC's overall score. Speaking of lousy grades, I awarded a D- to the Big Ten Conference as its recently-annexed properties have resulted in a BIG thud.  From the east (Maryland and Rutgers) to the west (Nebraska, Oregon, UCLA, USC, and Washington), the Big Ten’s new coast-to-coast configuration has failed to improve this conference for either sports fans or student/athletes. How have the five mid-major conferences fared with recent expansion issues? These other conferences (nicknamed the “Group of Five”) can be quite entertaining but rarely win national championships.  They must compete against the “Big Four” major conferences featuring the wealthiest college sports programs. American Athletic Conference (AAC) The AAC has only been around since the year 2013.  There were 10 initial AAC members and now 14 in 2026. Only Memphis, South Florida, and Temple remain from 2013.  The ACC raided Conference USA to obtain several of its new members. Army and Navy – What's not to like about these two additions?  They bring the focus of the entire college football world to their annual game played in early December.  Grades – A Charlotte – The 49ers have been perpetual cellar dwellers in most sports.  Charlotte, North Carolina sports fans are more likely to follow UNC, Duke, and Clemson.  Yawn.  Grade – D- East Carolina – The Pirates have made the NCAA baseball playoffs ten times since 2013 and have occasionally contended for the AAC title in football.  A hearty fan base makes ECU a fun place to watch sports.  Grade – B Florida Atlantic – A member of the AAC since 2023, this school is best known for its men's basketball team and having a great beach nearby.  Sadly, most local sports fans don’t give a hoot about the FAU Owls yet.  Grade – C- North Texas – The Mean Green had a brilliant 12-2 football season in 2025 in the school's third year as part of the AAC.  The other sports are lagging behind.  Grade – C Rice – Another third year AAC member, the Houston-based Owls have been an athletics flop in their new conference.  Grade – D Tulane – Green Wave football program has rejuvenated Tulane athletics down in the Crescent City.  Unfortunately, the remainder of the school’s sports teams rarely lead the AAC.  Grade – C Tulsa – Golden Hurricane football and men's basketball programs have been on the decline in the past decade.  That's a shame, because Tulsa fans desperately want to get behind the city’s lone major college athletics team.  Grade – C- UAB – Try as I might, I'm having trouble remembering any recent sports successes for the Blazers.  Grade – D- UTSA – Like Tulsa, the Roadrunners have the entire San Antonio market ready for their athletics programs to take off.  Other than some recent success in football, UTSA sports still appear to be taking a siesta.  Grade – C- AAC overall grade for expansion: C- Conference USA (C-USA) I am not going to provide individual grades to Conference USA member schools.  It is not their fault that C-USA management has done such a lousy job of keeping this conference together and relevant in major college sports. The conference has seen a 100% turnover in the past 20 years. Schools being added have generally been former FCS top teams such as Delaware, Sam Houston, and Jacksonville (AL) State. Things have declined so badly in Conference USA (“How badly have they declined?”) that longtime member Louisiana Tech recently agreed to pay a reported $8 million to buy its way out of C-USA.  The Bulldogs’ jubilant athletic department and fans are rejoining the Sun Belt Conference this fall.  Louisiana Tech will save more than $1 million annually in travel costs formerly required to travel to schools within the far-flung Conference USA. Longtime C-USA holdovers Western Kentucky and Middle Tennessee State deserve a better fate.  Save your money and call the Sun Belt in a couple of years! C-USA overall grade for expansion –  F- Mid-American Conference (MAC) In contrast to Conference USA, the MAC has remained remarkably stable for the past 20 years. Eleven of the dozen MAC members in 2006 remain a part of the conference today.  Northern Illinois (which had been part of the MAC for 30 years) is leaving this fall to become part of the Mountain West Conference. In a couple of curious moves, the Mid-American Conference has added two new members recently. UMass – The 2025 addition of the University of Massachusetts (which is at least in regional proximity to longtime MAC member Buffalo) was rather questionable.  Athletic success at Umass has been nearly invisible over the past decade.  After just one year in the MAC, the Minutemen have been a net negative in sports for the Mid-American Conference.  Grade: D- Sacramento State – Seriously?  Yes, the Mid-American Conference will add this longtime FCS member from California to its football schedules this fall.  Sacramento (the #20 TV market) is 2,500 miles from the middle of Ohio. The Hornets will be a football-only member of the Mid-American Conference.  For the usually stable MAC, this is a rather bizarre expansion move.  Grade: F MAC overall grade for expansion:  D- Mountain West Conference (Mountain West) The Mountain West has survived a few departure tremors in recent years.  Of the nine Mountain West members 20 years ago, only Air Force, New Mexico, UNLV, and Wyoming remain.  Let’s review the teams which have come aboard since 2006. Hawaii – The Rainbow Warriors (2012) have posted winning football records in just four of their 14 seasons in the Mountain West.  The other athletic squads are nearly invisible in the post-season tournaments.  Hawaii remains a dream road trip destination for visiting teams and their fans, though.  Grade: C- Nevada – At least the men’s basketball team has appeared in the NCAA March Madness event five times over the past nine seasons.  Otherwise, fans of the Nevada Wolfpack (which joined the Mountain West in 2012) haven’t had much to howl about lately.  Grade: C- North Dakota State – This former FCS division powerhouse football program is stepping-up to play against the big boys beginning this fall.  The move is for football only. The Bison are a terrific geographic fit for the Mountain West Conference, too.  This makes sense.  Grade: A Northern Illinois – The Huskies will join the Mountain West this fall after 30 years in the Mid-American Conference.  Northern Illinois’ sports resume has weakened in recent years.  Other than bringing the #3 TV market (Chicago) to the Mountain West, this move makes little sense.  Grade: D San Jose State – The Spartans (members since 2013) have appeared in four bowl games over the past decade.  On the other hand, the men’s basketball team has won just 33% of its conference games over the past 13 years.  Grade: C- UTEP – This longtime Conference USA member joins the Mountain West this fall.  UTEP’s football team has been downright awful in recent years.  Despite a sports slump, UTEP bring strong fan support from the El Paso area.  They should be a fine geographic fit for the Mountain West.  Grade: C Mountain West overall grade for expansion:  C Sun Belt Conference (Sun Belt) The Sun Belt has been nicknamed the “Junior SEC”.  This conference has grown from 10 members in 2006 to 14 today. Only Arkansas State, Louisiana-Lafayette, South Alabama, Troy, and UL-Monroe remain from 2006. Appalachian State – The Mountaineers (members since 2014) have been a top football contender in the Sun Belt.  Their enthusiastic fans make road trips to Boone, North Carolina a fun stop.  Grade: B Coastal Carolina – Speaking of fun stops, how about a visit to Myrtle Beach to play Coastal Carolina?  The 2017 Sun Belt addition of the Chanticleers has been a terrific addition for the conference.  Coastal’s football team has played in six straight bowl games.  The baseball team won the men’s College World Series in 2016.  Grade: A Georgia Southern – Would it surprise you to learn that the Golden Eagles from Statesboro, Georgia have played in seven bowl games over the past eight seasons?  The other sports programs at Georgia Southern need to step it up.  Grade: B Georgia State – The 2013 addition of the Panthers from Atlanta has not added a lot of sports notoriety.  However, the men’s basketball program has earned four invitations to March Madness in the past 11 seasons.  Grade: C Louisiana Tech – The Bulldogs paid dearly ($8 million) to escape Conference USA beginning this fall.  Louisiana Tech brings several highly competitive sports teams. They are a perfect geographic addition to the Sun Belt Conference Western division.  Grade: A Marshall – This begins Marshall’s fourth year in the Sun Belt Conference.  The Thundering Herd has been a top football competitor and competes well in other major sports.  Grade: B Old Dominion – ODU came into the Sun Belt in 2022.  The Monarchs from Norfolk, VA posted a nifty 10-3 football record in 2025.  Old Dominion has been relatively quiet in its other sports, though.  Grade: C Southern Miss – The Golden Eagles (Sun Belt members since 2022) have been a dominant team in recent NCAA college baseball post-season tournaments.  Last season’s 2025 football team improved from a miserable 1-11 record in 2024 to a hopeful 7-6 mark.  Grade: B Sun Belt overall grade for expansion:  B+ Bonus Conference!  The newly revived Pac-12 Conference “states” its case in 2026 The most prominent names of the long-time Pac-12 Conference bolted for better TV money into the Big Ten and ACC in 2024.  That left holdovers Oregon State and Washington State “homeless”.  The Beavers and Cougars have bagged a few top teams from the Mountain West Conference to help them rebuild the Pac-12 starting this fall. Boise State is the biggest name coming to the new Pac-12.  The Broncos have fielded a nationally ranked football program several times in the past few decades. Other Mountain West migrants include Colorado State, Fresno State, San Diego State, and Washington State. Texas State (formerly of the Sun Belt Conference) will also join the Pac-12 this fall. In case you didn’t notice, each of the eight new Pac-12 schools has the last name of “State”! Summary Only the Sun Belt Conference has earned a positive score (B+) from SwampSwami among the “Group of Five” mid-major conferences. The Sun Belt is the only major college athletic conference opting to maintain two divisions (East and West) to minimize travel expenses for its member schools and lessen the travel impact on their student/athletes.  Bravo! The post Grading the Mid-Major Conference expansions – Part 2 appeared first on SwampSwamiSports.com.

Nicole Dyer and Diana Elder explore Leo, a powerful handwritten text recognition platform designed specifically for researchers. Nicole interviews the creator, Jon Cooper, a PhD candidate at Stanford who developed the tool with a machine learning expert to address the difficulty of transcribing complex Elizabethan manuscripts. Listeners learn how Leo differs from general AI models by prioritizing faithful, accurate transcriptions of handwritten text rather than guessing words. The platform offers specialized features for genealogists, including the ability to recognize tabular data, crop and rotate document images, and refine transcriptions using multiple model inputs. Diana shares her own experience testing the tool on a two-page 1830s deed, finding it to be a user-friendly and accurate resource. The episode also highlights Leo's "Transformations" feature, which helps users move beyond basic transcription. Listeners discover how this tool summarizes content, identifies key people and places, and translates non-English sources. While the platform is advanced, the hosts discuss important limitations, such as challenges with tiny marginalia, double-page spreads, and predicting rare proper names. Ultimately, this episode demonstrates how Leo serves as a force multiplier for genealogists, helping them turn raw digital images into searchable, summarized, and interpreted research assets. This summary was generated by Google Gemini. Links Meet Leo: The Handwritten Text Recognition Platform Built for Researchers – Family Locket -https://familylocket.com/meet-leo-the-handwritten-text-recognition-platform-built-for-researchers/ Learn more about Leo and to set up your free account, go to https://www.tryleo.ai/ Leo Demonstration with Nicole and Jon Cooper on YouTube: https://youtu.be/mR8KOH97Rf0  Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.   Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d Research Like a Pro with AI Workbook – Second Edition (eBook) - https://familylocket.com/product/research-like-a-pro-with-ai-workbook-second-edition-ebook/ 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

The best engineer Matt Dalio ever hired didn't have a high school diploma. That fact runs through this whole conversation — what building proves that credentials can't.Education is changing because work is changing. AI is already reshaping what people can build, how they learn, and what employers actually value — and Arizona State University has become the clearest picture of where it's going, precisely because of the reputation it had to shake.Matt Dalio, founder of Endless, joins Eric Kasimov. Matt's work centers on one idea: young people should be creators of technology, not just consumers of it. The conversation runs from Arizona State's President Michael Crow measuring success by who a university educates instead of who it rejects, to the engineer with no diploma who outperformed the Stanford hires, to why building games might be the most complete education a kid can get, and what happens to a generation that opts out of AI versus one that learns to wield it.WHAT WE TALK ABOUTWhy Arizona State University (ASU) stands out in higher educationMichael Crow's "realm five learning" — education that's infinitely scalable, infinitely personalized, infinitely affordableWhat "GitHub University" shows about proof of work and why it beat the Stanford hiresWhy portfolios are becoming more important than resumesHow game making teaches technical, creative, and collaborative skillsWhy AI fluency may become a core workforce skillThe difference between using screens to consume and using them to buildGSV (Global Silicon Valley) and spreading the builder mindset beyond the ValleyWhy young people should start building, tinkering, and solving real problemsCHAPTERS00:00 – Arizona State University and innovation in education01:21 – Michael Crow's approach to access and scale03:20 – Changing perceptions of ASU05:33 – Why higher education has to change07:09 – Prestige, jobs, and the shifting value of a degree08:06 – GitHub, proof of work, and hiring without a diploma11:26 – Why portfolio can matter more than pedigree13:08 – AI, marketing, and what students actually need to learn15:15 – Teaching young people to become AI power users16:00 – Why game making teaches multidisciplinary skills18:34 – ASU, scale, and reaching more learners20:33 – Soft skills, collaboration, and real work21:46 – Games, arts, media, and engineering at ASU23:37 – Coding, Claude Code, and technical fluency25:37 – Why Matt still believes code matters28:07 – Screens, phones, Chromebooks, and real computers31:42 – What Gen Z can do now32:31 – Why schools are often anti-AI34:33 – Building as the path to employment35:52 – Burning your resume and building proof37:22 – Moving from Abu Dhabi back to the US38:34 – AI education in the UAE39:15 – Bringing AI education to more people40:39 – Building through contracts, partners, and foundations42:00 – Why America needs broader access to builder skills44:15 – Helping young people join the modern economy45:39 – Public schools and the difficulty of scale46:19 – Kids who are already building their own futures49:26 – Why the traditional system still matters50:00 – Vibe coding an SAT prep tool52:08 – AI concerns, climate, and the risk of opting out55:00 – Global Silicon Valley and spreading the builder mindset57:36 – Games, sports, licensing, and learning through interests59:06 – Game studios, communities, and professional learning01:01:49 – Finding your passion by building01:02:50 – Matt's book and Endless Future01:04:09 – The lean book and shipping early01:04:46 – Where to find Matt Dalio and EndlessConnectMatt Dalio: Website | LinkedInEric Kasimov: X | LinkedInRelated Entrepreneur Perspectives episodesHow AI Is Changing College Counseling and Admissions with Senan Khawaja, CEO of KollegioDavid Selinger on AI Security, $15M Series B, and the Deep Sentinel MissionAnkit Somani | From Google to Conifer: Rare-Earth-Free Motors, $20M Seed, and Rethinking CollegeEntrepreneur Perspectives is produced by QuietLoud Studios.Music by Jess & Ricky — SoundCloud

Adiel Gorel is one of the leading experts on Real Estate and Real Estate Investment in the United States, and around the world. A master entertaining storyteller and Thought Leader, he is the founder and CEO of ICG (International Capital Group) Real Estate Investments, a renowned real estate investment firm founded in the San Francisco Bay Area.Since 1987 Adiel continues teaching tens of thousands of investors how to secure a strong financial future for themselves and their families, whether for college, legacy wealth growth and retirement.He is the author of 5 books, including his Amazon Bestseller, "Remote Control Retirement Riches”.As an experienced speaker Adiel has lectured or conducted seminars all over the world, including at Stanford, Cisco, Meta, Intel, Microsoft, Berkeley, Amazon, and many others.He has also been featured on Fox Business, ABC, NBC, Fortune, Entrepreneur Magazine, and is regularly featured in local San Francisco Bay Area and Los Angeles Area media. Adiel even has his own Public Television real estate show (Remote Control Retirement Riches), which is still airing in its 6th year.His dynamic and entertaining on-stage presence led him to be featured on TedX in 2023 (https://youtu.be/wxtJLO4aK5I?si=7ol7sddHYMkiyuls) and has been viewed more than 1 Million times.Watch Adiel's Tedx Talk: https://www.youtube.com/watch?v=wxtJLO4aK5I&pp=ygUQYWRpZWwgZ29yZWwgdGVkeNIHCQkECwGHKiGM7w%3D%3DVisit Adiel Gorel's Website: ICGRE.com

Episode 435 of The VentureFizz Podcast features Kojo Osei, Partner at Matrix. The venture capital industry originated back in 1946 in the Boston area, when The American Research and Development Corporation was founded by MIT president Karl Compton and Harvard professor Georges Doriot. From that point, an industry was born, and firms were created, but very few have had the lasting impact and track record as Matrix, one of the OG firms that helped institutionalize this industry. The firm has a tremendous track record through the years making investments in legendary companies like Apple and FedEx… plus category creators like HubSpot, Zendesk, and Oculus… or current investments like Canva, Suno, GOAT, and Flock Safety. Matrix is investing out of its 12th fund, an $800M fund for seed and Series A investments, and the firm continues to have a strong presence on both coasts. Kojo is a Stanford grad, who was the Head of Product at Sirona Medical, the AI operating system for radiologists, before becoming a VC. Now based in NYC, Kojo has been an investor with Matrix for over five years. Some areas of interest these days for investments include agent-driven commerce, how the software infrastructure is getting rebuilt for agents, and model application integrated companies. His investments include companies like Channel3, BoldVoice, Ampersand, and LM Studios. Chapters: 00:00 Introducing Kojo Osei, Partner at Matrix 03:24 What is Agent Driven Commerce 09:45 Koji's background & Early Career 13:20 Joining Matrix as a VC 14:37 Advice for Aspiring Venture Capitalists 17:05 The First Year in Venture Capital 20:26 Details about Matrix's 25:01 Investment Areas of Interest for Kojo 27:48 The Art of the Cold Email to a VC 34:17 Exploring the 'Why Now' Philosophy 37:59 AI: Current State and Predictions 42:06 Common Mistakes Founders Make 44:23 GTM for Developer Products 48:11 Leveraging AI in Daily Workflow 49:23 Kojo's Recommendation & Personal Interests Podcast Sponsor: This podcast is brought to you by one of the strongest longtime supporters of the local startup ecosystem, Silicon Valley Bank, a division of First Citizens Bank. With more than 1,500 bankers and relationship advisors and $44B in loans as of Q4 2025 – SVB delivers expert guidance, specialized products and a team that knows the innovation economy inside and out. Learn more at SVB.com.

Primary care in America is under pressure from nearly every direction: physician shortages, long appointment wait times, rising patient demand, and a care model still built around physical offices. The U.S. is expected to face a shortage of up to 86,000 physicians by 2036, according to projections from the Association of American Medical Colleges, while federal shortage-area data continues to show gaps in primary care access across the country. At the same time, virtual care and AI are moving from pandemic-era workarounds to core infrastructure for how patients find, receive, and navigate care.But as the technology catches up to the need, can healthcare use it in a way that preserves what matters most: the relationship between patient and doctor?Welcome to I Don't Care. In the latest episode, host Dr. Kevin Stevenson sits down with Dr. Geoffrey Rutledge, Founder and Chief Medical Officer of HealthTap, to explore the evolution of virtual care, the failures of traditional primary care, and the proper role of AI in medicine. Their conversation spans the early days of online medical information, the rise of telehealth, HealthTap's shift toward virtual primary care, and why Dr. Rutledge believes technology should strengthen clinicians rather than replace them.What you'll learn…Virtual care is no longer just “digital urgent care.” Dr. Rutledge argues that telehealth began as a transactional service for immediate needs, but its real potential is longitudinal virtual primary care, where physicians can build relationships, understand lifestyle factors, and guide patients over time.Access problems are not limited to rural communities. While telehealth is often framed as a rural health solution, Dr. Rutledge and Dr. Stevenson discuss how patients in urban and suburban markets also face barriers such as traffic, childcare, mobility issues, and months-long waits for appointments.AI should support clinical judgment, not substitute for it. Dr. Rutledge says large language models are powerful tools for information retrieval, differential diagnosis, and reminding physicians of possibilities they may not have considered. But he cautions that AI is still weak at planning, prioritization, and understanding patient preferences, making physician oversight essential.Dr. Geoffrey Rutledge is a practicing physician, entrepreneur, and digital health leader with more than 30 years of experience applying technology to improve healthcare access, delivery, and outcomes. He is the founder and Chief Medical Officer of HealthTap, and previously held senior leadership roles at Healtheon/WebMD, Epocrates, Wellsphere, San Mateo Medical Center, and First Consulting Group. Dr. Rutledge earned his MD from McGill University and his PhD in medical computer science from Stanford, and has taught medicine at Harvard, Stanford, and UCSD while conducting NIH-funded research in medical informatics.

You can listen wherever you get your podcasts or check out the fully edited transcript of our interview at the bottom of this post.In this episode of The Peaceful Parenting Podcast, Michaeleen Doucleff and I talk about her new book Dopamine Kids: A Science-Based Plan to Rewire Your Child's Brain and Take You're your Family in the Age of Screens and Ultraprocessed Foods. Michaeleen's position is not that screens and ultra-processed food are “bad.” Rather, Michaeleen explains how they can take the place of things that truly bring us joy and pleasure, leaving us with an empty feeling of "what's next?" and an endless cycle of wanting. We focus on how dopamine has been misunderstood and how it actually works, how magnets like screens and ultraprocessed foods keep us stuck, and small changes you can make to start shifting things in your home.Know someone who might appreciate this episode? Share it with them!And if you love the podcast, FREE ways to help us out:1- Rate and review the podcast in your podcast player app2- “Like” this post by tapping the heart icon ♥️3- Share this with a friend. THANK YOU!We talk about:* 00:00 Introduction to Dopamine Kids and why our understanding of dopamine is outdated* 02:15 Michaeleen's journey from NPR science journalist to parenting author* 05:00 Dopamine isn't pleasure—it's wanting: the neuroscience that changes everything* 07:20 Why kids say they'd rather play with friends than be on screens* 08:00 The difference between dopamine, serotonin, and real satisfaction* 13:30 How apps and ultra-processed foods hijack the brain's reward system* 16:45 Why endless scrolling never feels satisfying* 18:30 “Bottomlessness”—one of the biggest design tricks keeping us hooked* 20:30 Why we want activities for our kids with a clear purpose and a clear endpoint* 22:00 The veggie straw experiment that changed Michaeleen's thinking about food* 26:50 Magnets and cues: how screens become automatic habits* 32:00 Why removing screens isn't enough—you have to replace them* 33:30 Helping kids meet their real need for adventure and autonomy* 36:00 Small, permanent changes vs. temporary screen detoxes* 37:30 Why the car is a great place to start reducing screens* 38:00 Is reducing screens really more work?* 40:15 Why laws and regulations haven't caught up with technology* 43:00 Why this isn't a willpower problem* 46:30 Can kids ever use screens in moderation?* 49:00 Paid video games vs. free games* 51:30 This isn't about screens being “bad”* 53:00 Helping kids gradually learn to use technology well* 54:00 School Chromebooks and why parents have more influence than they realize* 58:00 Advice Michaeleen would give her younger parenting self* 1:00:00 Why kids have to experience offline joy before they'll want it* 1:01:00 Sarah's client who removed the TV—and what happened next* 1:02:30 Final thoughts and where to find MichaeleenResources mentioned in this episode:* Michaeleen's website* Dopamine Kids: A Science-Based Plan to Rewire Your Child's Brain and Take You're your Family in the Age of Screens and Ultraprocessed Foods* How to Stop Fighting About Video Games with Scott Novis * The Peaceful Parenting MembershipConnect with Sarah Rosensweet:* Instagram* Facebook Group* YouTube* Website* Join us on Substack* Newsletter* Book a short consult or coaching session callxx Sarah and CoreyYour peaceful parenting team- click here for a free short consult or a coaching sessionVisit our website for free resources, podcast, coaching, membership and more!>> Please support us!!! Please consider becoming a supporter to help support our free content, including The Peaceful Parenting Podcast, our free parenting support Facebook group, and our weekly parenting emails, “Weekend Reflections” and “Weekend Support” - plus our Flourish With Your Complex Child Summit (coming back in the fall for the 3rd year!) All of this free support for you takes a lot of time and energy from me and my team. If it has been helpful or meaningful for you, your support would help us to continue to provide support for free, for you and for others.In addition to knowing you are supporting our mission to support parents and children, you get the podcast ad free and access to a monthly ‘ask me anything' session.Sarah: Hey everyone. Welcome back to another episode of the Peaceful Parenting Podcast.Today's guest is journalist Michaeleen Doucleff. She is the author of the book Hunt, Gather, Parent and now has a new book out called Dopamine Kids: A Science-Based Plan to Rewire Your Child's Brain and Take Back Your Family in the Age of Screens and Ultra-Processed Food.Michaeleen's first book is one of our favorite parenting books, and now we can add this one to the list. She walks us through how screens and ultra-processed food hook us and keep our brains stuck in a hijacked wanting cycle without giving us actual rewards and pleasure.We eventually get around to discussing this, but I want to stress right here at the beginning that Michaeleen isn't saying that screens and ultra-processed food are evil or that they have no place in our lives. Rather, they can take the place of things that truly bring us joy and pleasure, leaving us with an empty feeling of “what's next?” and an endless cycle of wanting.I learned so much from this book. I'd been wanting to make some changes in my own life with my relationship with my phone, and this book helped me understand why it was so hard and what I could do. A hint: as it turns out, we don't understand dopamine correctly at all. Our cultural shorthand about what dopamine is and what role it plays in the motivation and pleasure cycle is totally outdated.If you're interested in making some positive shifts in your child's life, in your family, and in your own life, you're going to love this interview and Michaeleen's book.If you like this episode, please share it with a friend so more parents can learn about peaceful parenting. If you're a fan of the podcast, you can help us out not only by sharing it, but by leaving a review and a five-star rating in your podcast player app. While you're there, don't forget to follow the show so you don't miss an episode.If you'd like to support us even more, you can become a supporter on Substack to help us offset the cost of making the show. We'll put a link in the show notes.Let's meet Michaeleen. I hope you enjoy this conversation and get as much out of her insights as I did.Sarah: Hi, Michaeleen. Welcome back to the podcast.Michaeleen: Thank you so much for having me.Sarah: When we had you on a few years ago to talk about your first parenting book, Hunt, Gather, Parent—we'll link to it in the show notes—it ended up being one of our favorite podcasts out of the 200-some episodes we've done. I'm so excited to have you back to talk about your new book.Michaeleen: Thank you so much. That's so nice. It's an honor to come back.Sarah: I'm so happy to have you. Tell us a little bit about who you are and what you do.Michaeleen: I was—or I still am—a science journalist. I've been one now for about 16 years, and I spent 13 or 14 years as a radio correspondent at NPR. I'm still there covering children's health, global health, neuroscience, and psychology.Before that, I was trained as a chemist. I have a PhD in chemistry.Five years ago, I wrote the parenting book Hunt, Gather, Parent, and I had no idea I'd ever become a parenting expert. That definitely wasn't on my life bingo card.When I had my daughter Rosie almost 11 years ago, I had no clue what I was doing. It just seemed like an impossible task. Then I started studying parenting around the world, and I realized there was an easier way to do things. That's what Hunt, Gather, Parent is about.More recently, about six years ago, I was really trying to fix my own screen problem—my own addiction to my phone. I was so obsessed with it. As I investigated neuroscience, psychology, and behavioral psychology, I started to realize, “Oh gosh, we're really getting a lot of things wrong when it comes to screens and our kids.”That led me to write this next book, Dopamine Kids, to clarify a bunch of myths but also update the advice because it's really old. A lot of the advice out there is based on psychology from 20, 30, even 40 years ago.Sarah: Or even more.Michaeleen: Exactly.Sarah: Exactly. And I'm going to ask you about that. So tell us, what's the central idea behind your new book, Dopamine Kids?Michaeleen: One of the biggest ideas is that we're thinking about screens wrong. We think they're these endless sources of pleasure. We think dopamine is this molecule that brings us pleasure and that the more we have, the happier we are.But that's really old neuroscience.What dopamine actually gives us is the feeling of desire, wanting, and craving. It makes us obsessed.So what screens are doing is cranking that system up. They're increasing motivation, craving, and wanting. But if you look at what happens over time, they actually rob us of pleasure and reduce the amount of pleasure we experience in our lives.So this idea that screens—video games and social media—are treats and rewards for kids is wrong. It's all wrong.What is actually most rewarding and pleasurable for kids are things in the real world because real-world experiences don't just give us desire and wanting. They also give us satisfaction, joy, and long-lasting pleasure.So Dopamine Kids is really a reset of what actually brings our kids pleasure in life. It also provides a toolset to retrain your kids' brains so they naturally want and reach for offline activities and foods that make them feel good—foods that really nourish them and bring satisfaction.It's about rethinking our idea of pleasure. What does pleasure actually look like?I think the media, marketing, and corporations have taught us that pleasure and wanting are basically the same thing—that we want things because they bring us pleasure.But if you actually look at the science and the data, there are so many things out there that drive our wanting while robbing us of pleasure.Social media is a really good example. Kids use it because they want a sense of belonging. They want to feel connected. But over the long run, social media does the opposite. It makes them feel lonelier, and yet they still want it.I see this book as an operating manual for shaping and changing your kids' habits into the ones you want for them as a parent, but also habits that nourish kids and bring joy, happiness, and pleasure to the whole family.We often think limiting screens is about depriving kids of pleasure.It's actually the opposite.It's about reclaiming pleasure.Sarah: I had Lenore Skenazy on the podcast. Do you know her work?Michaeleen: Yeah, we're friends.Sarah: She was on the podcast a few months ago, and she was talking about how, if you ask kids what they want—would they rather be on screens or play with their friends?—by far the number one answer is playing with their friends, not being on screens.Michaeleen: Yeah. I think it's almost double.Sarah: Exactly. And yet I don't think most parents realize that.Michaeleen: Right. I didn't realize that either. I think it's because we confuse begging, screaming, and tantruming for the screen with joy and pleasure.Sarah: Okay, so tell us about that, because what I learned from your book is that everyone thinks dopamine is, “Ah, I just got a hit of dopamine and I feel so good.”Michaeleen: Yeah.Sarah: But it's not dopamine that makes you feel good. It's serotonin and, I think, endorphins that make you feel good.You go into this in much more detail in the book, and I highly recommend it. It was excellent. I have to tell you, I was on an office hours call with my membership before I even knew you had written a new book, and one of my members said, “I'm reading this parenting book called Dopamine Kids, and it's a page-turner.”She said, “I've never had a parenting book that's a page-turner, but you've got to get your hands on this.”Then I looked it up and realized it was your book, and I was so excited to get it and read it.Can you explain the basic idea? I know it's too much detail to go into fully, but what's the difference? What does dopamine actually do, and why isn't it what we think it is?Michaeleen: For a long time—really since the 1950s—neuroscientists thought we do things over and over again because they're pleasurable.Neuroscientists have been obsessed with getting people and animals to press buttons for over a hundred years. Rats, mice, apes, pigeons—they've all been part of these experiments. It's almost like an iPad. Press, press, press, tap.For a long time, researchers could stimulate one region of the brain—the dopamine center—and the animals would go crazy pressing the button all day long. They wouldn't even stop to go to the bathroom. It makes you think of someone playing video games for hours. They're just obsessed with pressing the button.Researchers believed that because this was the dopamine center of the brain, dopamine made you press the button because it felt good and brought you pleasure. They even conducted similar experiments with people, and that very simple explanation stood for a long time.Then, about 30 years ago, a couple of scientists came along and asked, “Wait a second. Is this really true? Do we always act because something is pleasurable?”They designed better experiments, and what they found was astonishing. Dopamine doesn't do that at all.Dopamine makes us want.It makes you want something, and it makes you want to do something over and over again. It's like a “do it again” button in the brain.Do it again.Do it again.Whenever you can, do it again.The way the system is supposed to work is that first you want something, and dopamine motivates you to work for it. Then, when you get what you wanted, the pleasure center starts to light up.Those are different neurotransmitters. That's where endorphins—the body's natural opioids—and serotonin come in.Serotonin allows you to appreciate what you have. It's what lets you say, “Oh, I got what I wanted. I feel really good. Ah... I can stop now. I can take a break.”In many ways, pleasure is the opposite of dopamine because it gives you satisfaction, and satisfaction stops wanting.There are a couple of classic examples. One is sex, which is probably the R-rated version. But another is thirst.Imagine you're running on a hot day. You've run out of water, and after half an hour or an hour, you really want something to drink.That's dopamine. That's your dopamine hit—that strong feeling of desire.Wanting can actually feel good. If I fall in love and I want to be with my partner, the wanting feels good.But wanting can also become frustrating. If you want something for too long and don't get it, that feeling turns into frustration.So you're out running on this hot day thinking, “Oh my gosh, I want water so badly.”That's dopamine.That's not pleasure yet.Then you see a glass of water, or you get one and take a drink, and you think, “Ah, that feels so good.”That's the pleasure system.Sarah: That's where you get the serotonin and the endorphins.Michaeleen: Exactly. And the endocannabinoids too—the body's natural cannabinoids. A whole bunch of things kick in.The wonderful thing about this pleasure response is that it can last a long time. It lingers. It makes you feel optimistic and gives your life a kind of glow because you've gotten what you need to survive.I remember being really upset as a kid, and my mom would come over and hug me. I'd bury my face into her, and it felt so good. It was just this feeling that everything was okay again.That's what these pleasure molecules do.Dopamine is saying, “Everything is not okay. I need this before things can be okay.”They're very different.Sarah: Okay. This is the part I still feel like I'm only beginning to understand.How do the makers of apps and video games—and we've mostly been talking about screens, but you also write a lot about ultra-processed foods—how do they get us stuck in the dopamine cycle?What I took away from your book is that these things are so powerful because they keep us trapped in that cycle of wanting...Sarah: What I understood from your book is that these things are so powerful because they keep us stuck in the dopamine cycle. It's just wanting, wanting, wanting.You said something in the book about how they've figured out a way to hack a weakness in our brain circuitry. Forgive me if that's not the exact wording, but they've essentially hacked a weakness in the brain to keep us stuck in dopamine without ever giving us a real reward.How does that work?Michaeleen: First of all, both the tech industry and the food industry have admitted this for a long time. This isn't something I've come up with. They've openly admitted it. Even the food industry says, “We want to make something you can't stop eating.”Sarah: Right. You read all these interviews with industry insiders, and they're very open about it. Everybody knows they've admitted it. But how does it actually work?Michaeleen: There are a lot of tricks.Let's start with screens because a lot of these techniques actually came from the gambling industry. In the ‘80s and ‘90s, casinos started replacing mechanical slot machines and poker machines with video versions—basically gambling apps on giant touchscreens.They explicitly asked, “What can we do to this game to keep people playing for as long as possible?” Some people would play for 24 or even 48 hours straight. They ran massive A/B tests to figure out exactly how they could tweak the games to send people into this dopamine loop—this wanting loop—where people actually stopped wanting to win because winning took them out of the loop.So it's very empirical. They've simply tested what keeps people there.In the book, I describe it as a kind of recipe parents can use to recognize whether an app is doing this to their child. Psychologists even have a name for this state. It's called dark flow, where you lose track of time and where you are. We've all experienced it while scrolling social media. Twenty or thirty minutes go by and you think, “What just happened?” You're in this loop of wanting because, if you actually experienced pleasure and satisfaction, you would stop. You'd stop wanting.One of the biggest tricks is speed. The faster the cycle runs, the more it traps you. If you think about videos and video games, they've become faster and faster. Even children's iPad games are just question, answer, question, answer, question, answer over and over again. That's driving up dopamine.But where's the satisfaction? What's the reward? Basically, it's just a light on the screen.Another trick is promising something fundamental. The dopamine system evolved to help us fulfill our basic human needs—water, food, social support, adventure, creation. These are things we needed to survive, so kids are naturally highly motivated to pursue them.These apps promise they'll meet those needs. Social media, for example, promises belonging. It says, “Get on here and you'll finally feel connected. You'll finally feel like you belong.” The problem is that it never actually fulfills that promise.If you look at some of the leaked internal documents, you can see the algorithms intentionally withhold what people actually want. One neuroscientist explained it this way: they figure out what you're looking for and why you're on social media, then they give you something that's close to what you want. Maybe on the next click they give you something a little closer. Then a little closer.This does several things. First, you never actually receive the reward because you never get what you really need. Second, you develop this feeling of making progress—as though you're getting closer and closer. “Maybe one more comment. Maybe five more likes. Then I'll finally get it.”What most people don't realize is that we produce the most dopamine not when we get what we want, or even when we think we're about to get it, but when we feel like we're making progress.That's one of the biggest tricks.Video games are a perfect example. Kids always feel like they're making a little more progress. A little more. A little more. By the time they reach the next level, they're already making progress toward another one.There are all these different tricks designed to crank up wanting while dialing down satisfaction and pleasure because satisfaction is what gets you off the game. You think, “Okay, I'm done.”The same thing applies to social media. If social media actually gave me what I was looking for, I'd be finished. I'd think, “I got what I needed. I'm done.”But it never gives it to you.It can't.Sarah: I started feeling kind of gross about how much time I was spending on Instagram and Facebook—really just on my phone in general. I'd think, “Oh, I need a five-minute break,” and immediately pick up my phone.Actually, I did this before I started reading your book, but now I realize it fits perfectly with what you're talking about. I downloaded the New York Times Games app.Now, when I feel like I need a little break, I'll do Wordle or the Mini Crossword or Connections. What's nice is that it's limited. You get one crossword, one mini crossword, one Wordle, and one Connections each day.I'm almost never on Facebook or Instagram anymore because of it. It actually feels like a real reward. I finish the crossword and think, “Oh, I did the Mini in one minute and 38 seconds.”There's an ending to it. It really does feel like I accomplished something, which is very different.Michaeleen: Exactly. And you've actually stumbled onto one of the biggest tricks: bottomlessness.This is huge.TV didn't used to be bottomless.Michaeleen: TV didn't used to be bottomless. You had a handful of channels, and eventually the content ended or it got bad enough that you simply stopped watching.Now everything is endless. There's always another news story, another level in a game, another post, another video. That endlessness is what keeps us trapped in the cycle.You actually did so many things right with the New York Times Games app. You found something that takes a little more effort, but it also has a clear stopping point. You finish it, and then you're done. You created a bottom.That's exactly what I want to do with my own kids. I want to help them find activities that have a clear purpose and a clear ending. When you're done, you're done, and you turn it off.Compare that with scrolling Instagram for 30 minutes. What's the purpose? What are you actually doing? What are you looking for? There's always more content. It never ends, and it's incredibly fast.I think it's Chapter 4 of the book where I talk about figuring out how to use these technologies—if you're going to use them at all—in ways that don't manipulate you into these loops but instead feel genuinely satisfying.People often ask, “How do you know it's a real reward?” Your brain tells you. You feel better afterward than you did before. You feel done. You feel full. You think, “I'm ready to stop.”If, instead, you're thinking, “What's next? One more. One more,” then you're still stuck in the loop.For a lot of people—for a lot of kids, and certainly for me—that loop is frustrating and deeply unsatisfying. It just makes life feel gray and gloomy.Sarah: I noticed something a while ago. One of my favorite activities in the world is reading, and I realized I can't read if my phone is in the same room with me.When I was reading your book, I thought, “This is something I absolutely love doing, but it doesn't create that same dopamine loop.”Reading doesn't do that.I actually have to keep my phone in another room because reading takes more effort than scrolling Instagram.Michaeleen: Exactly. It takes more work, and that's part of why it's more satisfying.We're made to work. Human beings are actually very good at working, and that effort is part of what creates satisfaction. If something is too easy, it's much easier to get trapped in the wanting loop.Sarah: You also say in the book that, evolutionarily, our brains are designed to look for the easy way out.Back when life was hard, that made perfect sense.But now that everything comes to us so easily, it doesn't make sense anymore.Michaeleen: That's exactly right. These products are exploiting that tendency.Food is probably where you can see it most clearly.Our brains evolved to look for the foods with the most calories per bite. Why would you eat something with fewer calories per bite, especially when food was scarce? That's how we evolved.We also evolved to look for calories that our bodies could use quickly. A refined white-flour cracker gives you calories much faster than a carrot does. You'd have to eat carrots for much longer to get the same energy.Our brains are completely designed to choose the cracker.You'd never touch the carrot. It doesn't make evolutionary sense.That's especially true for kids, who are eating much more instinctively. But honestly, I'd argue that adults have the same problem. If the crackers are sitting there beside the carrots, most adults are going to have a hard time choosing the carrot.Sarah: Tell the story about the strawberries and the veggie straws.Michaeleen: This was when I really understood what was happening.Rosie was about eight years old, and we went to the pool with one of her friends. I packed raw edamame and strawberries. The girls were tired and hungry, and they were happily eating them. They were enjoying them.Then I pulled out a bag of veggie straws—which, by the way, aren't really veggies and aren't really straws. They're basically highly processed potato starch.Sarah: I think it's extruded potato starch.Michaeleen: You're right. Extruded potato starch.The starch is chemically extracted from the potato, so there's really nothing potato-like left except the starch. It's heated at a very high temperature, pushed through machinery, then sprayed with fat or basically fried and covered with salt.If you really look at the research, your body treats it almost like sugar. It practically dissolves in your mouth. There's almost no digestion required. It moves into your gut and into your bloodstream incredibly quickly.So even though the package says “veggie” and even though it says “potato,” what you're really getting are extremely fast calories, much like sugar.The moment I put those veggie straws on the table, those two girls ate the entire bag.One after another.You want to talk about dopamine?“Do it again. Do it again. Do it again. Do it again.”They didn't stop until every single veggie straw was gone.And then they completely forgot about the strawberries and the edamame.That was the moment I realized that if any ultra-processed food is available, kids simply won't choose the whole foods.Sarah: You asked Rosie afterward which she actually liked better, and she said, “Oh, the strawberries.”Michaeleen: Exactly. Even though she genuinely likes strawberries better—they taste better—her brain, and all of our brains, are designed to choose the veggie straws because they're such a dense source of fast calories.That realization led me to start doing little experiments. I'd make homemade meals with whole foods, then put one ultra-processed starch on the table—a dinner roll or some corn chips. I'd sit there and watch my husband and Rosie eat all of the ultra-processed food first. Then my husband might eat some of the whole foods, but Rosie wouldn't touch them.It wasn't her fault. It wasn't my fault. This is simply how our brains are designed. It makes perfect sense from an evolutionary perspective, and the food industry is explicitly taking advantage of that. If you look at the calorie density of ultra-processed foods, it's gone up and up over time. What really surprised me, though, is that it isn't just about sugar. Sugar clearly triggers dopamine—”Do it again. Do it again.” But highly refined potato starch, corn starch, and white flour are just as powerful, and in some studies they're actually more addictive than foods with added sugar.I recently read a study describing almost the exact recipe you mentioned: extruded starch that's fried or sprayed with a little fat and loaded with salt. That combination is incredibly addictive. The moment you see it, you want it, and then you eat it. The dopamine hit actually happens before you eat it. It's, “Oh, I see the bag. I want the bag.” That's the dopamine.Then there's almost no satisfaction or pleasure because satisfaction comes from protein and fiber—and, to a lesser extent, fat. Those are the things that make you feel, “Ah, I've had enough. I'm done.” Ultra-processed foods have stripped away almost everything that creates that feeling of satisfaction. That's what pleasure actually is.I really believe we can learn to tell the difference between wanting and genuine pleasure. Just like you did with the New York Times games, you replaced endless scrolling—which kept you wanting more—with something that actually makes you feel good every day.Sarah: Can you talk a little bit about what you call “magnets” and “cues”?I finished your book last week—it really was a page-turner—and I'm already putting some of your ideas into practice. One of the simplest suggestions was to stop carrying your phone around everywhere. I wore a watch to a baseball game the other night because I didn't want to keep taking out my phone just to check the time.Then this morning I went for a walk with my daughter and left my phone at home. When I got back, I made something to eat and did a couple of other things before I suddenly realized, “Oh—I left my phone upstairs for two hours.”Just the act of not taking it with me on the walk and leaving it in another room made it disappear from my mind. It was amazing.Michaeleen: I love that. That's beautiful.I call phones, video games, iPads, and ultra-processed foods magnets because neuroscientists actually use the term motivational magnets, and that's where I borrowed it from. They work through space, and they create what we call cues.Let's use screens instead of veggie straws. Imagine Rosie comes home every day after school and plays Toca Boca World on the iPad.Sarah: My daughter used to play those hairdressing games—and even vacuuming games. I never understood the appeal until I read your book and realized she was basically getting dopamine-mined.Michaeleen: Exactly. If you look at what keeps young children on those apps, it's the repetition. They're doing essentially the same thing over and over again, which is actually very unsatisfying.At first, what keeps Rosie playing are those little dopamine hits—”Do it again. Do it again.” But over time, something fascinating happens: the dopamine hit moves backward in time. Eventually, just seeing the iPad triggers dopamine. Simply seeing it creates desire and makes her really want it. Dopamine doesn't just make us want things—it motivates us to work to get them.So she sees the iPad, and suddenly she wants it. If it's sitting there, good luck getting her interested in anything else because her brain has already triggered that powerful feeling of, “I need this to survive.” She'll be pulled toward it like a magnet. That's where the term comes from. You don't just want it—you physically move toward it. You want to pick it up. You want to hold it. You want to touch it.Even if it's hidden away in a drawer or a closet, if she knows it's there, those magnets work through walls. She'll go looking for it.Sarah: Have you seen that study where students either had their phone on their desk, in their backpack, or in another room? Just having it in the backpack was almost as distracting as having it sitting on the desk.Michaeleen: That's exactly right, because they know it's accessible. Over time, these cues become so deeply wired into our brains that we don't even have to see the object anymore. We just have to know it's there.What's often triggering the habit isn't even the phone itself—it's an emotion. For example, when I'm writing and I get a little frustrated, that feeling becomes the cue: “Go check the news.” That used to be mine. Then it became, “Go check your email.” Now I've stopped checking the news, so mine has become, “Go check the weather.”Sarah: At least that can only last so long unless you're checking the weather around the world.Michaeleen: Exactly. It's much less sticky.But that's the point. If the phone is in the backpack, the brain knows it's available. These magnets work through walls. They work through bags. To really make those cues disappear, you have to do exactly what you did. You leave it at home. Your brain knows, “I can't get it. I'm not walking all the way back home for it,” so it lets go.As parents, we have to make these things completely disappear within a particular context. That's another really important piece of this: magnets and cues work in contexts.Every day after school is a context for Rosie's brain. Every day after school, in our house, she plays Toca Boca World. So when she walks into the living room at four o'clock, her brain already knows what time it is, even without a watch. Human brains are incredibly good at tracking those patterns.That context triggers dopamine. It triggers the desire for Toca Boca World.What we want to do instead is use that same context to trigger a desire for something that actually fills her up. Maybe after school in the living room becomes the cue for making art, riding her bike, or going outside.That's really what Dopamine Kids is about: using dopamine to get your kids excited about the real world and training their brains accordingly.Sarah: Can I back you up a little bit there? Because one thing you say in your book is that it doesn't work to simply take the screens away and say, “Let them be bored. They'll figure it out.”That's really the only other advice I've seen out there: just take the screens away and let kids be bored.But you did a lot of work to create opportunities for dopamine from other things. You didn't just tell Rosie, “No more Toca Boca World.”Can you talk about that? I think a lot of parents try the approach of saying, “Okay, we're just not doing screens anymore.” Then they end up with weeks—or maybe months—of crying and begging: “Can I just play a little?”Michaeleen: I think that approach can sometimes work with very little kids, but even then I don't think it lasts. These things are like weeds. The screens will come back unless you replace them with something else.Behavioral psychology is actually very clear on this. It's much easier to create a new habit than it is to break an old one. It's much easier to replace a behavior than simply remove it.For example, while I was writing Dopamine Kids, I decided I wanted to stop drinking as much. I had gotten into the habit of having a glass of wine every night, and I realized it just wasn't working for me anymore.I didn't simply take it away. I bought non-alcoholic beer. I replaced it with something.Kids are the same way.If you just take away the iPad—especially if they've been using it for a long time—their brain has come to believe it's something they need to survive. That's what these products have tricked the brain into believing. So when you take it away, it genuinely feels awful.But if you give them another activity that's exciting, interesting, and something they genuinely want to do, taking the screen away doesn't feel nearly as difficult. Over time, you can actually help them discover activities that make them feel even better than the iPad does.That's what creates a permanent habit instead of a temporary one.Behavioral psychology is pretty clear that kids are using these things because they're trying to meet a need.Rosie wasn't obsessed with Toca Boca World or cartoons because she wanted screens. She wanted adventure.Adventure is a fundamental human need for kids. You could also call it autonomy, but I like the word adventure because I think it's easier to understand. Kids need to explore, learn, and take little risks. They need that in order to feel good.I think a lot of kids are using screens to try to fill that need.So instead of simply taking screens away and leaving that need unmet, you have to backfill it.I said to Rosie, “Tonight we're not going to watch Netflix. We're going to take a break. Instead, we're going to do something you've been dying to do that I just haven't made time for yet. You're going to ride your bike to the market by yourself.”I would even say to her, “Instead of watching cartoon characters have adventures, you're going to have a real adventure yourself.”That's the difference.You're taking something that was trying—but ultimately failing—to meet a real human need and replacing it with something that actually does.When you do that, it's not nearly as hard.It goes back to what you mentioned earlier about kids saying they'd rather be with their friends than on screens. That same research also found that kids would rather be outside playing than watching screens. So you're giving them the opportunity to do the thing they actually want to do.That's really the process: figure out a replacement activity—or a replacement food—and then gradually begin taking the old thing away.The result is that your child isn't angry at you all the time. Your relationship is better because they have something wonderful replacing what they lost.More importantly, it creates a lasting habit because they're not simply complying with a rule. They're building a hobby, a skill, or a way of living that genuinely brings them pleasure and meets their needs.One of my biggest concerns with a lot of the screen advice that's out there is that it isn't permanent.Real change comes from making small but permanent changes.It's not, “We're doing a 30-day screen detox.”It's, “We don't use screens after dinner anymore,” or, “We don't use screens on Saturdays.”And that's just how our family does things now.That's how you train the brain.If you keep bringing the old habit back, you undo the learning and go right back to where you started.So I always encourage people to think small—but think permanent.Sarah: One suggestion you make is starting with something simple, like, “We don't do screens in the car.”Michaeleen: Yes.Sarah: I think that's such a great place to start. Your book is full of practical little ideas like that, so the whole thing doesn't feel overwhelming.We've been talking about some of the bigger concepts, but the book is incredibly practical.I'm working on a book myself right now, so I know how much work goes into something like this. I just want to say you did a really beautiful job balancing the theory with concrete things families can actually do.I really, really recommend it.Michaeleen: Thank you.The car is a great place to start because it's such a clear context for a child's brain.They get into the car and their brain thinks, “Screen time.”Instead, you can make the car mean, “Reading time,” or “Journaling time,” or even “Bored time.”It's a really useful place to begin because they're already somewhat contained, so it's easier to establish a new routine.Sarah: I love that.The one thing I want to ask about—and I hope you don't take this as criticism—is that some of what you've done takes a lot of time and energy privilege.Michaeleen: Yes. I think it's very similar to what I found with Hunt, Gather, Parent. There is some work up front, but I also think we dramatically underestimate how much work we're already doing when we rely on screens as babysitters or pacifiers.We tend to think that's the easy route, but even in the short term, I don't think it actually is.Sarah: That's a really good point because the fighting itself takes a lot of energy.Michaeleen: Exactly. That's ultimately what made me change and what made me want to write this book. I was just tired of arguing with Rosie about screens. I hated policing her.It's very similar to what I found with Hunt, Gather, Parent. Recently, one parent gave me some feedback that I actually thought was really insightful. She said, “I think you could have been clearer that having daily screen time—or unlimited screen time—is actually a lot of work.”And she's right.The parent is managing it every single day, moment by moment. There's constant fighting, negotiating, and policing.I'll tell you something else. Once we got ultra-processed foods out of our house, the amount of work I do around food dropped to about one-tenth of what it had been before. We actually spend less money because we're eating less.People don't realize that ultra-processed food makes you eat more. That's very well documented. Kids snack constantly when those foods are around. Rosie now eats two or three real meals a day when she's eating whole foods.So I'm actually doing much less work because those foods aren't in the house.I do agree there's some work at the beginning. Teaching Rosie to ride her bike to the market took time. But now she's 10, and she rides her bike everywhere. She bikes to piano lessons. She bikes all over town.That investment keeps paying dividends.Sarah: That's a really fair point.I had just been telling you before we started recording that, over the years, I've noticed more and more parents coming to coaching specifically because of challenges around screen time.The fights about screens, getting kids off screens—it has become such a common struggle.They just need to read your book and get some strategies.Michaeleen: I'm really just trying to encourage people that if they have that gut feeling—that sense of, “This just isn't working for our family”—it's okay to say no.There is a way to do it that doesn't require an enormous amount of ongoing work.Really, what you're doing is setting up the environment so the default becomes these other activities. You're designing things so you're not constantly policing or managing every moment.That's my biggest pushback against the idea that this approach is more work.It took a lot of work for me to figure all of this out and understand how it works—Sarah: And you did that for us.Michaeleen: Exactly.I also think the court system—and society more broadly—is slowly starting to catch up. The regulations around screen content are so far behind the technology.If you think about it, 20 years ago Rosie wouldn't have been able to walk into a movie like Jaws without a parent. There were very clear rules about what children could and couldn't see.Now I can hand her a device that gives her access to some of the most extreme content imaginable.One scientist told me that a child today can see, in about ten minutes, more pornography than our grandparents' generation would have encountered in an entire lifetime.Something is clearly out of balance.Either society has changed dramatically, or our regulations simply haven't kept pace.When you look at child exploitation, trafficking, and abuse online, it's obvious that regulation is behind.Sarah: Big Tech has so much money and so much influence that I think that's part of why the laws have fallen so far behind.Michaeleen: It absolutely is. But I also think there's this persistent myth that kids need these technologies and that they're doing so much good.One of my hopes for this book—and for the work many other researchers are doing—is that people will begin to understand that kids genuinely need help regulating this stuff.They cannot regulate it on their own.Right now, that entire burden falls on parents, and that's a tremendous amount of work.Sarah: We can't regulate it on our own, and we're grown-ups.Michaeleen: Exactly.When I first started researching this book, I interviewed a famous economist at Stanford—someone in his forties who will probably win a Nobel Prize someday. He spent our entire conversation telling me all the systems he had to build so he wouldn't look at the news while he was working.He had blocked it at the router. He'd blocked it on his computer. He'd blocked it in multiple other ways.I remember sitting there thinking, “If he has to do all of that, how is a thirteen-year-old supposed to do her homework?”That's one of the central messages of the book.This isn't about willpower.It's not about teaching kids to resist temptation through self-control.It's about teaching them to build environments where they aren't constantly tempted in the first place.That's exactly what you described earlier when you left your phone at home.You create spaces in your life where the temptation simply isn't there.That's the key to living a happier, healthier life—not relying on willpower, but learning to avoid unnecessary temptation and building habits that don't require you to fight yourself every day.Ironically, that's what ends up making life much easier.Sarah: That was another really interesting thing you talked about in your book—willpower.Michaeleen: One of the really interesting findings about willpower is that people with fewer bad habits don't actually have more willpower. They've simply arranged their lives so they're exposed to fewer temptations.Sarah: That's right. A great place to start might be something like what you did with food. You talked about not eating food on the go.Michaeleen: Exactly. No food on the go.Sarah: Baby steps.Michaeleen: Right. Or parents will tell me things like, “We don't have ultra-processed foods at breakfast.” Breakfast is actually an easy place to start. You have oatmeal. You have eggs. There are lots of simple whole-food options. So you make that one meal your starting point.That's really the idea. Start with something small.I think the same principle applies to parenting. Parenting actually becomes easier when the temptations simply aren't there. You're not constantly managing them.Sarah: When my kids were growing up—and thankfully they mostly missed all of this because my youngest is 19, so there wasn't Netflix and everything else that's available now—we had a simple family rule: no screens Monday through Thursday.Back then it was television, but they just knew that was how our family worked. If they asked, I'd simply say, “Remember, it's Wednesday. We'll watch TV on the weekend.”It was actually very easy.Michaeleen: Exactly. And that's the dopamine system at work.Their brains know what day of the week it is. We're remarkably good at keeping track of time and routines. They knew they were in your house, after school, and that there wasn't going to be TV.It's like a smoker on an airplane. Eventually the smoker's brain learns, “I'm on a plane. I can't smoke.” The craving relaxes because the brain understands the context.The same thing happens with family routines.In Israel, for example, many families observe a digital Sabbath where they unplug for a full 24 hours every week. Parents tell me their kids love it because they know that's the time they play board games, spend time outside, and do other things together.Their brains learn that weekly rhythm.Our brains naturally work this way, so we can use that tendency to make family life calmer and more peaceful.Honestly, one of my favorite outcomes is that when nine o'clock comes around, my daughter is calm and actually wants to go to bed. Whatever effort it took to establish those habits at the beginning has been completely worth it. It's peaceful now, and hopefully those routines will stay with her for years.Ironically, it was much harder for me to stop scrolling before bed than it was for her.Sarah: Do you think there's any place for moderation?For example, could Rosie ever pick up Toca Boca again and play it for a little while? Or is it more a case of, once it's gone, it's gone?Michaeleen: That's a really good question.I think there are a couple of ways to think about it.The first is simply asking whether a particular technology is worth it. Does Toca Boca actually give us something valuable enough that it's worth the possibility of bringing back arguments and struggles? Or is there something else that gives us the same benefit without those downsides?One of the goals of the book is to help parents start asking that question about technology in general: Is this actually worth it?The second question is whether your child can handle it.I use YouTube for work. I'll watch scientists explaining research, informational videos, or sometimes I'll listen to music. I also know all the tricks YouTube is playing on me, so I can use it pretty intentionally.But Rosie at ten years old?No way.YouTube is far too sophisticated for her to use purposefully.Maybe when she's sixteen, seventeen, or eighteen. Maybe fifteen. I don't know.But I'm not going to intentionally introduce it.If it becomes necessary because of school or something else, then we'll try it and see how she handles it. If she can use it well, maybe we'll continue. If she can't, then we won't.I think a lot of this is really about figuring out what your own child can handle.We don't give children alcohol or tobacco because they can't handle them. We don't give them pornography for the same reason.These technologies have entered our lives so quickly that we're all trying to answer entirely new questions.One of the most important things parents can watch is what happens afterward.How does your child behave? What's their mood like? Is it immediately, “One more. One more. One more”?If that's what's happening, then they're probably not ready for it.Sarah: Right. It's not restorative.This reminds me of a guest I had on the podcast a year or two ago. He was a former video game developer, and the episode was called How to Stop Fighting With Your Kid About Video Games.Sarah: This reminds me of something another guest said on the podcast, and I think it fits perfectly with what you're talking about.He was a former video game developer, and he said something I've never forgotten. He said, “If you're going to let your kids play video games, don't let them play anything that's free.”He said there are lots of amazing games that you actually buy because they're designed with a real story arc, real challenges, and an ending. As I was reading your book, I kept thinking about that because those paid games are designed to give you an actual reward at the end. You complete levels, you build skills, and then you finish.He wasn't talking about buying things inside free games. He meant games that you purchase outright. I remember my husband used to play The Legend of Zelda. It was a game you started and eventually finished.Michaeleen: I love that. There's so much I love about it because the business model is completely different.With free games, the longer you stay on them, the more money the company makes through advertising and in-game purchases. Their entire goal is to keep you there for as long as possible. They're holding the child inside that loop.But with purchased games, they actually want you to finish because then they hope you'll buy another game. It's almost like movies used to be. They wanted you to enjoy the experience, reach the end, and then come back for the next one.You're exactly right—they're designed to end.I think that's really beautiful advice because it highlights how much the business model shapes the experience.Sarah: That's what he said. In the free games, the commodity is your child's attention.Michaeleen: Exactly.Whereas with a purchased game, you're paying for an experience that has a beginning and an end.We've actually done something similar with movies and television. We got rid of all of our subscriptions, and honestly, we've saved a lot of money. Now, if we want to watch a movie, we buy it.We're much more intentional. We stop and ask ourselves, “Do we really want to watch this? Is it worth it?”Then, when the movie ends, we're done.I think that simple change does so much to keep you out of the wanting cycle we talked about earlier. Paying for something slows the whole process down. It makes you think about your choice, and the design itself is completely different. It's designed to leave you feeling satisfied—to let you say, “I finished it.”Sarah: It's an experience. It's an adventure. There's a reward.Michaeleen: Exactly. I love that idea. I wish I'd put it in the book. It's really good. Honestly, I didn't even realize there were that many games designed that way.Sarah: I'll send you his contact if you ever want to talk with him.I could honestly talk to you about this all day.I'm just trying to think if there's anything else I really wanted to ask, but I do want to highlight something for anyone who's still listening.This isn't a moral argument about screens or ultra-processed foods being “bad.” You make that very clear throughout the book.It's really about bringing more joy and fun back into your life because getting trapped in this cycle of wanting without ever feeling rewarded is making all of us kind of miserable.Michaeleen: That's exactly right.The first thing I hope parents take away is that this isn't their fault.This has happened incredibly quickly, and most of us don't even understand what we're up against. These products are intentionally designed by multibillion-dollar companies to capture and hold our children's attention. That's what we're competing with, and for a long time we simply haven't had the right tools.The second thing is that this isn't about taking everything away. That's a fantasy. It's not going to work.It's about figuring out what actually brings joy to you and your family, keeping those things, and letting go of the things that don't.We've also moved beyond the old idea that kids will somehow fall behind or be left out if they don't have all these technologies. There's so much evidence now showing that giving kids a phone or social media doesn't suddenly make them feel accepted or like they belong.In fact, it often does the opposite.So we can let go of that fear.Instead, we can ask, “What actually works for our family?” Then we can build the skills to get there and help our kids gradually adopt these technologies in healthy ways because they're going to be part of their lives.Almost everyone will eventually have a phone. Most kids will eventually use some form of social media, whether that's YouTube, Instagram, or whatever comes next.The question isn't whether they'll ever use it.The question is: When are they ready?And how do we help them use it in a way that still allows them to be productive?For me, that's one of the essential parenting skills of the twenty-first century: helping kids set up their environments—their computers, their workspaces, their routines—so they aren't constantly fighting temptation.Sarah: You also talk specifically about having kids work where a parent can see them because I think that's becoming a huge challenge now that so many students are issued Chromebooks at school.Sarah: You also mention having kids work where a parent can see them, because I think that's becoming a huge challenge now that so many students are issued Chromebooks at school.Everyone I've talked to—and maybe there are exceptions out there—says you can't put parental controls on school-issued devices. Kids need YouTube to watch something for school, and suddenly you've opened the door to all kinds of temptation.Every parent I know whose child has a school-issued Chromebook struggles with it.Michaeleen: Yes, and I think this is an area that's really in flux.From what I'm learning, parents are starting to push back—not only on schools issuing Chromebooks in the first place, but also on not being allowed to set them up in ways that remove things like YouTube. I think parents actually have more power than I realized.Some schools will work with families if parents speak up. You can go to the teacher or the principal and say, “This is what I want for my child's Chromebook. I don't want them to have access to YouTube,” or, “I want these restrictions in place.”Parents have more rights than I think most of us realize.I've talked with parents who are trying to get Chromebooks out of kindergarten through Grade 2 altogether. Others are asking for more limited internet access or different settings during school hours. There's really a whole spectrum of possibilities.I honestly think this is going to be one of the defining parenting issues of the next decade—the school-issued Chromebook, the school-issued iPad.For me, it just makes those screen-free gaps in the day even more important. If your child has spent the day doing schoolwork on a device, then after dinner becomes even more valuable as a screen-free time.You need a break. I need a break. We all need a break.Creating what I call sanctuaries becomes increasingly important as more of school moves onto screens. Kids need opportunities to move their bodies, relax their brains, and experience activities that are genuinely restorative.I also think there are resources available for parents who want more control over that digital space. It does take work, but as parents we sometimes hand over more authority to schools than we actually have to. We have more rights than we often realize.In fact, a lot of this is being challenged legally. There are lawsuits against school districts because some software has been given to children in ways that violate privacy protections and collect data improperly.So I think this whole area is changing, and I'm hopeful we'll eventually reach a place where, even if students are working on computers, they'll have better protections against unnecessary distractions.That's exactly how I work. I turn on an app blocker so I can't wander around the internet while I'm working. Otherwise, I'd be distracted constantly.I have a colleague who says she can't work for more than a couple of minutes before she finds herself checking something online.Sarah: I struggle with that too.It's getting easier the more I practice, but the pull—that feeling of wanting—is incredibly strong.Michaeleen: It really is. It's become a habit, and eventually you're barely even thinking about it.I remember when I first installed an app blocker. It felt so uncomfortable. I kept thinking, “But I want to check this. I want to check that.”Then it faded.It actually faded pretty quickly.Sarah: Thank you so much—not just for being here, but for writing this book. It's really remarkable.Even though I'm past the most active stage of parenting, I keep noticing the ideas from the book working their way into my own life.I have to tell you, the last couple of nights I've made brown rice instead of white rice because of something I read in the book. I love white rice, but I know I need more fiber. Honestly, once you start eating brown rice regularly, you hardly notice the difference.You've gotten me wearing a watch, eating brown rice, and leaving my phone at home when I take the dog for a walk.Michaeleen: I love that.It lets your brain relax because you're not constantly multitasking anymore.I have my watch on too. Rosie and I actually wear the same watch. To me, it's become a little symbol of this more digitally minimalist way of thinking.I was doing exactly the same thing—checking my phone every time I wanted to know the time. Eventually I thought, “Why am I using this little computer just to tell the time?”Sarah: Exactly.Well, thank you so much.Michaeleen: Thank you.Sarah: Before I let you go, I have one question that I ask every guest. It'll be interesting because I can compare your answer to what you said the last time you were on.If you could go back in time to your younger parent self, what advice would you give yourself?Michaeleen: Which age?Sarah: Any age. Go back to brand-new-mom Michaeleen. What would you tell yourself?Michaeleen: I'll give you two answers.For the baby stage, I would tell myself, “Michaeleen, just carry her all the time. Put her in the carrier and carry her. Don't worry so much about putting her down.”She was so happy whenever I carried her, and that's how so many cultures do it. The baby is simply on someone's back or on their front while life goes on. I really wish I'd done more of that because I think it would have made both of our lives much easier.For the older years, I'd tell myself to stop worrying so much that taking away the screens was going to be hard.I built it up in my mind as this enormous thing. I thought, “It's going to be so difficult to take away Netflix at night. It's going to be so difficult to take away Toca Boca.”But it wasn't.It really wasn't.Our lives became so much easier afterward, and I wish I'd been able to see that ahead of time.Sarah: Well, how could you have known?What you were seeing was the outward expression of all that wanting—the crying, the begging, the desperation. It would be so easy to mistake that for, “I'm denying my child something that brings them enormous pleasure.”I think that's an important distinction for parents.Just because your child is crying and screaming that they want something doesn't actually mean that it's bringing them pleasure or that it's good for them.Michaeleen: Exactly.Someone said something to me that I think made it into the book. A child can desperately want to spend another hour playing a video game while actually getting very little pleasure—or no pleasure—from it.That's really where the trick is.That's the hijacking.I also think Lenore's work is right. Kids really do want the offline world.They just have to experience it first.I didn't fully appreciate this before, but you can't really want something until you've experienced the joy of it yourself. Maybe you can see someone else enjoying it, but to actually build that dopamine pathway, you have to get out there and feel it yourself.You have to think, “Oh, this is wonderful. I love this.”Then your brain starts wanting more of that.Sarah: I was thinking about one family I work with. They have five kids, they run their own business, and they're incredibly busy.Their five-year-old son was having constant meltdowns and aggression, so I suggested they start tracking what happened right before those moments.When they came back, they realized that about 90 percent of the incidents were connected to screens. He was trying to get one of his parents' phones. He was trying to grab the remote from his sisters. He wanted the TV turned on or wanted it to stay on.This was actually before I read your book, so I probably could have given them even better advice afterward.But I suggested they experiment with going screen-free for a while and see whether it changed the aggression.The next time I talked to them, the dad told me that, out of pure frustration, he'd picked up the television and put it out in the garage. He basically announced, “No more TV for the rest of the summer.”The following week, the mom started texting me pictures.“Here's the girls sleeping in a fort they built on the trampoline.”“Here's our five-year-old playing with his trucks.”Picture after picture.She said, “I think this is going to be the best summer ever without TV.”Michaeleen: I love that story.I really do.And it's easier.It's easier.All he did was move the TV into the garage.That's amazing.That's exactly the advice I'd give myself.Just do it. Trust your instincts. Do it.Sarah: Do it.Well, thank you so much. I really appreciate you coming back on the podcast.As always, it's been such a pleasure talking with you, and you've written another wonderful book to add to the parenting canon.Michaeleen: Thank you so much for having me. It was truly a pleasure to come back.Sarah: Thanks so much.We'll put links to everything we talked about in the show notes, along with your website. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit sarahrosensweet.substack.com/subscribe

This week on Democracy Dialogues, Frances Cayton speaks with four experts on Polish politics about the success of Poland's opposition coalition in 2023, and the headwinds that democracy continues to face today. What challenges do parties and civil society face in building pro-democracy electoral coalitions? If victorious, how do these challenges affect post-election governance and efforts at pursuing democratic renewal? This episode brings together politicians, political scientists, and civil society leaders who each played a critical role in the 2023 elections to examine what made Poland's pro-democracy mobilization possible, the gains the 2023 coalition has achieved since entering power, and the challenges it continues to face in pursuing democratic renewal.This episode was originally recorded as a part of the Lessons from Global Democratic Resistance panel series. The series brings together frontline activists, civic leaders, institutional actors, and field‑informed scholars to examine how democratic actors have resisted, responded to, and learned from democratic backsliding across countries. The series aims to identify practical lessons and comparative insights for those defending democracy today and is organized in collaboration with the Ash Center for Democratic Governance and Innovation at Harvard University; Perry World House at the University of Pennsylvania; the Kellogg Institute for International Studies at the University of Notre Dame; the Democratic Futures Project at the University of Virginia; Stanford's Center on Democracy, Development and the Rule of Law; and the Carnegie Endowment for International Peace. Mikołaj Cześnik, Director of the Institute of Social Science at SWPS University, Chairman of the Council of the Stefan Batory Foundation Michał Wawrykiewicz, Member of the European Parliament (MEP). Co-Founder of the civic initiative Wolne Sady (Free Courts) Marek Tatała, President and Co-Founder of the Economic Freedom Foundation Dominika Lasota, Student and Activist in the Youth Climate Strike Poland, Co-Founder of Inicjatywa WSCHÓD Frances Cayton is a PhD Candidate in Government at Cornell University. Her research focuses on questions surrounding democratic backsliding, civil society, and political communication. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

I received a podcast review that basically said because a guest talked about chronic inflammation it was a "MAHA podcast." So I decided to go straight to one of the top inflammation researchers in the world and ask him directly: is chronic inflammation actually real, or is it pseudoscience?  My guest is Dr. David Furman, the Director of Stanford Medicine's 1000 Immunomes Project (the largest longitudinal study on aging and the immune system in the world) and an Associate Professor at the Buck Institute for Research on Aging, and his answer might surprise you. We play a game of Myth or Fact and bust some of the biggest inflammation claims all over the internet, from gluten and dairy to seed oils, and microplastics. We also get into how to actually test whether you're inflamed, the surprising link between chronic stress, depression, and your immune system, why your coffee habit might be doing you a favor, and exactly what to do about all of it if you have no money to spend.