Podcasts about Pollution

durée : 00:01:47 - Le Vrai ou Faux passe à l'heure d'été pendant la première semaine d'août. Chaque jour, on passe en revue des idées reçues sur des sujets estivaux. Ce lundi 3 août : la crème solaire. - équipe : Armêl Balogog, La cellule Vrai ou faux Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

San Diego lost a legend this week.Billy Ray Smith passed away at 64 after a long journey with dementia. His family said it was caused by Chronic Traumatic Encephalopathy (CTE).On KPBS Roundtable, we remember the iconic San Diego Chargers linebacker and sportscaster with his long-time radio co-host, Scott Kaplan.Then, we unpack why voters rallied against a union-backed initiative to overhaul local government in Chula Vista.Plus, how pollution from the Salton Sea is impacting a nearby Little League in Calipatria. And, what high rates of childhood asthma in the region reveal about the problem.Guests:Scott Kaplan, sportscaster and former co-host of "Scott and B.R." on The Mighty 1990Jim Hinch, South county reporter, Voice of San DiegoZoe Meyers, freelance photo and video journalistRebecca Plevin, freelance journalistKeep reading:Former Chargers linebacker Billy Ray Smith Jr. dies at 64Scott Kaplan Remembers Billy Ray SmithHow a Union-Backed Bid to Overhaul Chula Vista's Government Unraveled Near the Salton Sea, Little League Players Struggle to BreatheCalifornia's Lithium Valley Dreams Meet Reality at the Only Restaurant in Town

How did the river that literally put Kuala Lumpur on the map end up sidelined by concrete walls, urban neglect, and endless pollution? As flash floods become an all-too-familiar headline, sticking band-aids on policy failures isn't cutting it anymore.In this episode of RealiTEA Podcast, hosts Amir, Izzati, Hannah, and Aqilah sit down with Encik Syaiful Azmen Nordin, Managing Director of Landasan Lumayan Sdn Bhd (LLSB), to discuss what it actually takes to clean up and reactivate the Klang River. We dive into the deep end of urban planning, tackle the systemic causes of river degradation, and explore how moving from passive neglect to strategic "river activation" can transform a forgotten drain into a thriving community asset.It's time to move past quick fixes and rethink our urban future. Hit play to get the real tea on sustainable policy, river rehabilitation, and how we can reclaim our main waterway before it's too late.We're on socials!Twitter: @realiteapodcas1TikTok: @realiteaktok#RealiTEAPodcast #RiverActivation #LandasanLumayan #KlangRiver #UrbanPlanningMY #EcoRealTalk #SustainabilityMY #ReclaimOurRiversExecutive Producer: Dr. A. Hamid SaifuddinSupervising Producer: Sir Mohd Nur Najmi Nuji

John Maytham speaks to Hellen Kahaso Dena, Pan-African Plastic Project Lead at Greenpeace Africa, who is calling for South Africa to move beyond levies and introduce a total legislative ban on single-use plastic carrier bags. She argues that responsibility should shift from consumers to producers and retailers, while investment in refill and reuse systems offers a more sustainable long-term solution. Presenter John Maytham is an actor and author-turned-talk radio veteran and seasoned journalist. His show serves a round-up of local and international news coupled with the latest in business, sport, traffic and weather. The host’s eclectic interests mean the program often surprises the audience with intriguing book reviews and inspiring interviews profiling artists. A daily highlight is Rapid Fire, just after 5:30pm. CapeTalk fans call in, to stump the presenter with their general knowledge questions. Another firm favourite is the humorous Thursday crossing with award-winning journalist Rebecca Davis, called “Plan B”. Thank you for listening to a podcast from Afternoon Drive with John Maytham Listen live on Primedia+ weekdays from 15:00 and 18:00 (SA Time) to Afternoon Drive with John Maytham broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show go to https://buff.ly/BSFy4Cn or find all the catch-up podcasts here https://buff.ly/n8nWt4x Subscribe to the CapeTalk Daily and Weekly Newsletters https://buff.ly/sbvVZD5 Follow us on social media: CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

*Tim Kaine embraces Democratic Socialists? *Fauci was indeed a mega-monster *Never forget Covid and the attack on freedom *Remember what Kaine said during Covid? *Spanberger ushers in a sanctuary state. Homeland Security begs her for help *Talarico says prisons are violence? and Pollution? *Musk no longer a trillionaire? *Social media exposes the worst of people *Richmond wants 1% tax for schools *Fredericksburg gun buy back program And more!

durée : 00:10:50 - Le 6/9 de l'été - par : Alexis Morel - Stéphanie Rist, ministre de la Santé, des Familles, de l'Autonomie et des Personnes handicapées, affirme que l'État a envoyé 2,5 millions de masques FFP2 dans le sud-ouest de la France pour faire face aux fumées des incendies. Elle rappelle les règles de sécurité. - invités : Stéphanie Rist Femme politique française Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

durée : 00:10:50 - Les interviews d'Inter - par : Alexis Morel - Stéphanie Rist, ministre de la Santé, des Familles, de l'Autonomie et des Personnes handicapées, affirme que l'État a envoyé 2,5 millions de masques FFP2 dans le sud-ouest de la France pour faire face aux fumées des incendies. Elle rappelle les règles de sécurité. - invités : Stéphanie Rist Femme politique française Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

2013, en Indonésie. Une vidéo devenue virale cache une réalité bien plus sombre. 50 ans d'exploitation dans la forêt de Bornéo. Les humains et l'environnement ne sont pas épargnés... Les conséquences sont désastreuses. Mais comment combattre une catastrophe aussi lucrative ? ⭐️ Abonnez-vous à MINUIT+ pour écouter nos épisodes en avance et sans publicité → https://m.audiomeans.fr/s/S-pSlDfzMxCatastrophes • Histoires Vraies est un podcast produit par MINUIT. Narration : Florent OulliéScript : Yann Kral Hébergé par Audion. Visitez https://www.audion.fm/fr/privacy-policy pour plus d'informations.

(00:00:00) 226: Itchy & Bitchy ClinicCrawl: Plastic in Your Penis and Herpes Contagion (00:00:11) Welcome to Itchy and BITCHI (00:00:42) Doc Itchy Medical Pets Supplements (00:01:02) Microplastics in the Human Body (00:04:38) Shingles and Canine Quarantine (00:08:00) Closing Remarks and Contact Information (00:08:23) Follow and Contact Information Scientists have confirmed microplastics are now showing up in human penile tissue, with four out of five samples from men with erectile dysfunction containing seven different types of microplastics. Microplastics have also been detected in human brain, placenta, and testes .... because apparently your body is now a landfill.Meanwhile, everyone's favorite lurking virus is back for revenge: shingles itself isn't contagious, but the varicella-zoster virus absolutely can spread to ONLY people who NEVER had chickenpox or the Vaccine. Visit itchyandbitchy.comFrom gut health and hormone health to autoimmune disease and chronic pain, we investigate what science actually says. We examine functional medicine, holistic health, and alternative medicine with the same skeptical If it's pseudoscience, we'll call it. If it's medical gaslighting, patient advocacy failure, or misdiagnosis we'll call that too. For chronic illness warriors, self-advocacy seekers, and wellness skeptics WE OFFER  No filters. No BS. Just the truth your doctor didn't have time to tell you. Become a supporter of this podcast: https://www.spreaker.com/podcast/itchy-bitchy-podcast--4303608/support.Itchy & Bitchy: Have you felt dismissed, misdiagnosed, or gaslit by a broken medical system.  From gut health, hormones, autoimmune disease, chronic pain, holistic health, and alternative medicine ... medical gaslighting, patient advocacy , or misdiagnosis we'll call that too.  For chronic illness warriors, self-advocacy seekers: WE OFFER  No BS 

Even “healthy” fish carries health and environmental risks. Learn why the panel prefers plant sources over seafood. #FishToxins #SustainableEating #BrainHealth

Xavier Raufer est criminologue, essayiste et spécialiste des phénomènes criminels, du terrorisme et des nouvelles formes de criminalité.⁠Site Internet⁠⁠Chaîne Youtube⁠ Livres:⁠Jeffrey Epstein - L'âme damnée de la IIIe culture⁠ ⁠A qui profite le Djihad ?⁠⁠Le Crime mondialisé - Etat des lieux en 99 vérités⁠ CHAPITRES :0:00 Introduction5:38 L'ère de l'hyperinformation8:37 Trois grandes criminalités13:12 Pollution et trafics toxiques17:29 Mafias et terrorisme20:07 Le rôle du souverain23:56 Le crime, phénomène normal27:48 Crise de confiance politique35:39 Menace de guerre en Europe42:47 Guerre civile en France47:04 Drogue et justice débordée54:54 Rue contre cols blancs1:00:43 Soigner les causes profondes1:04:08 Le terrorisme aujourd'hui1:11:17 Drogue et profits mafieux1:17:40 Blanchiment et argent sale1:34:35 Cybercriminalité et numérique1:39:11 Intelligence artificielle1:44:49 Retard de l'État1:50:46 Racine du mal1:54:49 Zones hors contrôle1:59:43 Corruption des cols blancs2:07:00 Fliquage ou sécurité2:07:57 Homogénéité sociale et crimeBIOMÉCANIQUE :​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Discord⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠​⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠La Lettre Biomécanique⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠™ Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

La catastrophe de Seveso est une catastrophe industrielle aux conséquences écologiques et sanitaires majeures, qui s'est produite le 10 juillet 1976, à Seveso, en Lombardie dans le nord de l'Italie. Un nuage d'herbicide contenant des produits toxiques s'échappe de l'usine Icmesa et contamine les alentours, provoquant à la fois des hospitalisations pour les enfants des communes voisines et la mort de plusieurs dizaines de milliers d'animaux d'élevage.⭐️ Abonnez-vous à MINUIT+ pour écouter nos épisodes en avance et sans publicité → https://m.audiomeans.fr/s/S-pSlDfzMxCatastrophes • Histoires Vraies est un podcast produit par MINUIT. Narration : Florent OulliéScript : Baptiste Foriel Hébergé par Audion. Visitez https://www.audion.fm/fr/privacy-policy pour plus d'informations.

July is on course to be the driest in Wales for almost 190 years. It means that North Wales and the Upper Severn catchment are the first areas in the UK to be declared officially in drought, this year. So far this month they've seen less than two per cent of the usual rainfall. Natural Resources Wales says river levels are approaching all time lows after a series of back-to-back heatwaves, with impacts on wildlife and soil. In South East England, Sussex, Hampshire and the Isle of Wight have been moved into 'prolonged dry weather' status which is one step away from drought. That won't be news to farmers and growers in the area where some veg businesses are already investing to adapt to the 'new normal'. Barfoots grow broccoli and sweetcorn, amongst a long list of crops, for the supermarkets. The company's spent a million pounds on a new reservoir, at its farm near Chichester, which holds 28 million gallons of rain water supplemented by recycled treated water from their factory. Barfoots Commercial Director tells us the company is looking at building more reservoirs to store winter rainfall, to use in increasingly hot and dry summers.Farmers have a crucial role in cleaning up one of the UK's most polluted river systems and could save themselves money in the process, according to a new study. The eastern and western Cleddau rivers in Pembrokeshire flow through farmland which produces as much as 25% of Wales' milk. Researchers from Lancaster University found the area's farms were buying in more fertiliser and processed animal feed than needed, causing a build-up of phosphorus in the soil and polluting waterways. Now dairy farmers are working out their "nutrient footprint" to help tackle the problem.Presenter: Charlotte Smith Producer: Sarah Swadling

Il y a quelque chose d'invisible dans chaque geste du quotidien. Un smartphone qui s'allume, une voiture électrique qui démarre en silence, un panneau solaire qui capte la lumière… Derrière ces progrès technologiques, il y a une réalité que nous préférons ne pas regarder. Cette réalité, c'est l'exploitation des minerais du continent africain. Aujourd'hui, nous vous emmenons dans la Copperbelt. La ceinture de cuivre. Un arc de terre rouge qui s'étend entre la Zambie et la République démocratique du Congo, et qui contient une part vertigineuse de ce dont le monde a besoin pour sa transition énergétique. Cuivre, cobalt, et bien d'autres métaux qu'on appelle, pudiquement, « critiques ». Critiques pour nos batteries et nos éoliennes mais critiques aussi pour les populations locales ! À l'approche de l'élection présidentielle zambienne, le 13 août prochain, Igor Strauss et Yang Mei sont allés voir pour RFI les conséquences de la ruée vers ces minerais sur les habitants de la ville de Chingola, où de nombreuses multinationales sont présentes pour extraire du cuivre. Cette situation n'est malheureusement pas spécifique à la Zambie… L'exploitation des terres et des sous-sols du continent africain devrait être une opportunité économique formidable, mais aujourd'hui dans de nombreuses régions c'est une malédiction pour les populations. Avec Symphorien Ongolo, politiste chargé de recherche à l'Institut de recherche pour le développement (IRD – France). Musiques diffusées dans l'émission Paul Ngozi - Having No Future  The Four Pals - Maselino Yayayuyayu Paul Ngozi - The Ghetto.

Il y a quelque chose d'invisible dans chaque geste du quotidien. Un smartphone qui s'allume, une voiture électrique qui démarre en silence, un panneau solaire qui capte la lumière… Derrière ces progrès technologiques, il y a une réalité que nous préférons ne pas regarder. Cette réalité, c'est l'exploitation des minerais du continent africain. Aujourd'hui, nous vous emmenons dans la Copperbelt. La ceinture de cuivre. Un arc de terre rouge qui s'étend entre la Zambie et la République démocratique du Congo, et qui contient une part vertigineuse de ce dont le monde a besoin pour sa transition énergétique. Cuivre, cobalt, et bien d'autres métaux qu'on appelle, pudiquement, « critiques ». Critiques pour nos batteries et nos éoliennes mais critiques aussi pour les populations locales ! À l'approche de l'élection présidentielle zambienne, le 13 août prochain, Igor Strauss et Yang Mei sont allés voir pour RFI les conséquences de la ruée vers ces minerais sur les habitants de la ville de Chingola, où de nombreuses multinationales sont présentes pour extraire du cuivre. Cette situation n'est malheureusement pas spécifique à la Zambie… L'exploitation des terres et des sous-sols du continent africain devrait être une opportunité économique formidable, mais aujourd'hui dans de nombreuses régions c'est une malédiction pour les populations. Avec Symphorien Ongolo, politiste chargé de recherche à l'Institut de recherche pour le développement (IRD – France). Musiques diffusées dans l'émission Paul Ngozi - Having No Future  The Four Pals - Maselino Yayayuyayu Paul Ngozi - The Ghetto.

It's Thursday and that means it's time to catch up on the week in politics with Stephanie Grace, editorial director and columnist for the Times-Picayune/The Advocate. Today, we discuss major changes coming to FEMA and preview the upcoming congressional races.A new investigation examines how Louisiana's public air monitoring network often fails to measure pollution where it's needed most. Not only are air monitors often located miles from the sources of  pollution, but they don't measure all of the elements seeping into the air. This leaves many communities in the dark about the safety of the air they breathe.Ames Alexander reported on this for Floodlight and the Guardian. He joins us with the findings.Charity Hospital provided accessible medical care for the New Orleans community for more than 200 years. Its latest building opened in 1939 but has been closed since Hurricane Katrina. Despite being in good enough condition to reopen shortly after the storm, state officials decided to board up the hospital while plans for what is now the Tulane Avenue hospital corridor came to fruition. Now, more than twenty years later, Tulane University is repurposing the hospital as an education and medical research hub. President of Tulane University Michael Fitts tells us more about this investment.—Today's episode of Louisiana Considered was hosted by Bob Pavlovich. Our managing producer is Alana Schreiber. We get production and technical support from Garrett Pittman, Adam Vos and our assistant producer, Aubry Procell. You can listen to Louisiana Considered Monday through Friday at noon and 7 p.m. It's available on Spotify, Google Play and wherever you get your podcasts. Louisiana Considered wants to hear from you! Please fill out our pitch line to let us know what kinds of story ideas you have for our show. And while you're at it, fill out our listener survey! We want to keep bringing you the kinds of conversations you'd like to listen to.Louisiana Considered is made possible with support from our listeners. Thank you!

Scientists have confirmed there's frozen water on Mars. But there is a challenge. Martian water is full of toxic chemicals.

Our air was getting cleaner. Now, wildfire smoke has reversed that progress. On this episode, a new University of Iowa study finds wildfires have undone years of gains against ground-level ozone pollution, and the effects are reaching deep into the Midwest. First, we hear from former Iowa residents Jerry and Sue Prothero, who watched ash fall like snow in northern Minnesota. Then, we talk with Jun Wang, the study's lead author, about why ozone pollution is worsening and what it means for Iowans. We also talk with Peter Thorne of the University of Iowa College of Public Health about the health impacts of wildfire smoke and ozone pollution. And we address the health and air quality impacts of a proposed gas plant in Linn County with Abe Kellison of Save Morgan Valley. Save Morgan Valley is a community organization opposing Alliant Energy's proposed 720-megawatt natural gas power plant in unincorporated western Linn County.

with Brad Friedman & Desi Doyen

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

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

It's Indicators of the Week (now on YouTube!). On today's episode: What happened to Trump's proposed Strait of Hormuz fee?; China's pollution takes a dip … and maybe solves a mystery?; IMAX is expensive. But BIG. (For our eyes and theater owners.) Fact checking by Julia Ritchey and Cooper Katz McKim. Your Next Listen —The curious rise of novelty popcorn bucketsConnect with The Indicator — Sign up for The Indicator's brand new newsletter — Find our socials, YouTube and more! — For sponsor-free episodes, subscribe to NPR+ See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

In the latest episode of The Line Podcast, recorded on July 17th, 2026, Matt Gurney and Jen Gerson keep things refreshingly brief as both are juggling family matters. They begin with Jen's unsuccessful attempt to achieve cottage zen, as she unloads on the latest complaints from American politicians about wildfire smoke drifting south from Canada. Both hosts independently arrive at the same tongue-in-cheek solution: if the Americans don't stop griping, Canada should simply schedule its forest fires for days when the wind is blowing south. (They're kidding. Mostly.) They also discuss Donald Trump's latest bizarre speech and the increasingly revealing comments from senior U.S. officials, who seem unable to hide just how much Prime Minister Mark Carney has gotten under their skin.This episode is brought to you by Fractional Execs Canada. Need help with a serious business problem? As Canadian businesses grow they often require expert help to solve key business challenges. Fractional Execs Canada have assembled a team of experienced strategists, implementors, sales and marketing operators that can help transform your business into a growth engine. They match you with the right person, or team to move your business forward at a pace your business can manage. Talk to Fractional Execs Canada and discover a better, more collaborative way to take your business and your ‘busyness' in a better direction. Canadian expertise to support the growth of Canadian businesses. Build your business with those that know how. Find them Fractional-Execs.ca.Your hosts then turn to the slow-burning civil war within Canadian conservatism. Jen, still falling well short of cottage zen, has a few things to say. Matt observes that while Carney may be a practicing Catholic, he also seems to have accumulated an extraordinary amount of good karma in previous lives — politically speaking, he's facing remarkably little effective opposition from either the left or the right. Matt also warns the Conservatives that, whether they realize it or not, they're in danger of getting "Jagmeet Singhed." And it's not subtle.This episode is also brought to you by BioCanRx, a federally-funded Canadian not-for-profit research network focused on cutting-edge cancer immunotherapy research that they're helping Canadian researchers bring from labs to patients in clinical trials –– all in Canada.A new treatment for your cancer has been approved. Can you get it? Maybe, maybe not. Canada isn't just one health jurisdiction. At the federal level, Health Canada assesses the safety and efficacy of all drugs and therapies in the country, and in a year — sometimes less — they can approve one for sale in Canada. Once approved, — or sometimes while the assessment is happening— the drug's cost effectiveness is evaluated by Canada's Drug Agency.Then the ball goes to the provinces. They work together to negotiate prices with the drug maker, to confirm that it doesn't duplicate something they're already stocking, and that its potential value justifies its cost. Only after that can it be provided by each province's ministry of health. This process can take years. It's one reason that Canadian innovations leave the country to be developed elsewhere, and why drug companies don't always choose Canada to initially to launch their products. In the U.S., they get FDA approval, set a price, and wait for the market to decide if the price is right. In Canada, Heath Canada approves and lengthy negotiations start, with no revenue or guarantee of future approval.Organizations like BioCanRx are willing to wait out the dry years because they're not-for-profit, but companies with shareholders might skip the Canadian market until they're making big money elsewhere. This means Canadians have to wait on the system for drugs that could save them, and are saving people in other countries. We'll talk more about these problems in the weeks to come. Stay tuned for more.The hosts wrap up by discussing Naheed Nenshi's apology for speaking with an Israeli, which Matt suggests has elevated the Alberta NDP leader to full windbag status. Matt reminds Jen that he used to complain Nenshi needed to get himself into the public eye more often. After this week, he'd like to politely withdraw that recommendation. Jen wonders if maybe this is why he's been invisible — he might just actually be awful at this. Anyway, congrats to Danielle Smith. At this rate, she'll be premier for life.All that and more in the latest episode of The Line Podcast. Check out our main page at ReadTheLine.ca, and keep your kindling and torches ready. Wait for the code word.#TheLinePodcast#MarkCarney#CanadianPolitics#DonaldTrump#CanadaUSRelations#ConservativeParty#NaheedNenshi#AlbertaPolitics#PoliticalAnalysis#CurrentAffairs

with Brad Friedman & Desi Doyen

This Week in Oklahoma Politics, KOSU's Michael Cross talks with Civic Leader Andy Moore and former state Representative Chairman Mark McBride about supporters of a ballot initiative to open primaries arguing their case before the state supreme court, Attorney General Gentner Drummond announcing a settlement in the 21-year-old lawsuit over chicken waste in the Illinois River and Oklahoma schools scrambling to add extra time to their schedules after a new law doubled recess time for elementary students.The trio also discusses scathing audits of Epic Charter School showing financial mismanagement and students struggling academically and Oklahoma taxpayers spending $145,000 for a booth at President Trump's Great American State Fair.

Chief and Lou start off the show with the air pollution from wild fires and then in the testosterone testing in the military. Then discuss the congress act to stay with daylight all the time. Andrew and Wayne came on and continue about the air pollution from Canadian wild fires.

7.14.2026 #RolandMartinUnfiltered: Black Teen's Violent Arrest Goes Viral. Judge Restores Black Farmer Grants. xAI Pollution_ For free and unbiased Medicare help, dial (724) 264-8281 to speak with my trusted partner, Chapter, or go to https://askchapter.org/roland *Paid Partnership*_ A video of a Black teenager in Wisconsin being violently arrested has gone viral on Instagram but has been largely overlooked by mainstream media. We'll show it to you and delve into the details of the case. White Michigan progressive congressional candidate William Lawrence is facing backlash for comments he made about Black elected officials. A federal judge has reversed Trump's cancellation of $127 million in grants for Black farmers. We'll talk with one of the plaintiffs in the case and the lawyer who fought the administration in court. A new investigation reveals that Elon Musk's xAI data centers are releasing significant amounts of pollution into Black communities across the country. In today's Shop Black-Star-Network marketplace, we'll feature a conversation with the husband-and-wife duo who founded Tribe and Oak, a company that produces clean wax candles. And I'll share my sit-down interview with Lamont Bagby, the chairman of the Democratic Party of Virginia. Download the Kalshi app and use code Soccer10 to get $10 when you trade $10. You can also sign up at kalshi.com/r/soccer10, which auto-applies the code at checkout. Kalshi. Trade What's Next_ Black Star Network Partner: ChapterChapter and its affiliates are not connected with or endorsed by any government entity or the federal Medicare program. Chapter Advisory, LLC represents Medicare Advantage HMO, PPO, and PFFS organizations and stand alone prescription drug plans that have a Medicare contract. Enrollment depends on the plan’s contract renewal. While we have a database of every Medicare plan nationwide and can help you to search among all plans, we have contracts with many but not all plans. As a result, we do not offer every plan available in your area. Currently we represent 50 organizations which offer 18,160 products nationwide. We search and recommend all plans, even those we don’t directly offer. You can contact a licensed Chapter agent to find out the number of products available in your specific area. Please contact Medicare.gov, 1-800-Medicare, or your local State Health Insurance Program (SHIP) to get information on all of your options.____Download the Black Star Network app at http://www.blackstarnetwork.com! We're on iOS, AppleTV, Android, AndroidTV, Roku, FireTV, XBox and SamsungTV. The #BlackStarNetwork is a news reporting platform covered under Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research.See omnystudio.com/listener for privacy information.

In so-called “red states” and “blue states” around the US, from rural areas to urban centers, the explosion of new data center projects is impacting residents in poor, working-class, and middle-class communities alike. In this episode of Working People, we speak with a diverse panel of residents fighting new and proposed data center projects in Texas and Maryland about what it means for you and your community when one of these loud, polluting, energy- and water-guzzling behemoths comes to your town—and how to fight back.Panelists include: Cheryl Shadden, a registered nurse anesthetist who lives right next to the site of a Marathon bitcoin mine in Granbury, Texas; Karen Pearson, a licensed professional counselor and a resident of Granbury who also lives right next to the Marathon bitcoin mine; Dr. Shannon Wolf, Precinct Chair in Hood County, who lives three miles from the Marathon bitcoin mine; Craig Jackson, a resident of Granbury who lives 300 feet from the site of a new proposed data center, and who is also a plaintiff in a current lawsuit residents have filed against the city of Granbury; Micaiah Lloyd, a grassroots organizer and resident of Charles County, Maryland, who lives near the site of a proposed data center; Hillary Gonzalez, an eco-poet, author, founder of Sacred Parks & Waterways, and a resident of Baltimore, Maryland, who lives right next to the site of Johns Hopkins University's future Data Science and Artificial Intelligence complex.Additional links/info: Protect Hood County website and Facebook pageSacred Parks & Waterways website and InstagramViral MS Now clip featuring Cheryl Shadden of Granbury, TexasMaximillian Alvarez, Working People / TRNN, “A bitcoin mine in Texas is ‘killing us slowly,' local residents say”Maximillian Alvarez, Working People / TRNN, “‘Like being tortured': Texas residents living next to bitcoin mine are getting sick and being ignored”Maximillian Alvarez, Working People / TRNN, “Toxic Avengers: America's poisoned and abandoned communities must stand together or die”Christine Condon, Maryland Matters, “Data center frustrations cause upheaval in county primary elections”Emmanuel Rivas Valenzuela, KERA News, “Granbury residents sue city over data center plan, allege Texas Open Meetings Act violations”Featured Music: Jules Taylor, Working People Theme SongCredits: Audio Post-Production: Jules TaylorBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-real-news-podcast--2952221/support.Help us continue producing radically independent news and in-depth analysis by following us and becoming a monthly sustainer.Follow us on:Bluesky: @therealnews.comFacebook: The Real News NetworkTwitter: @TheRealNewsYouTube: @therealnewsInstagram: @therealnewsnetworkBecome a member and join the Supporters Club for The Real News Podcast today!

On Wednesday's show: We discuss the latest developments in politics in our weekly roundup.Also this hour: We continue our weeklong series examining the state of several areas of life in Greater Houston by discussing the state of the environment.And more and more people these days own dogs who serve as service animals or emotional support animals. But where can they venture in Houston and where can't they? And are there limits some area businesses can set?Watch

En Zambie, dans la province de la Copperbelt, se trouvent d'immenses réserves de cuivre et d'autres minerais de la transition, essentiels pour la fabrication des batteries électriques. Une région stratégique pour toutes les grandes puissances mondiales qui souhaitent s'accaparer ces minerais et pour la Zambie qui espère tirer profit de ces ressources pour sortir de son endettement évalué à environ 30 milliards de dollars en 2024. Le président sortant, Hakainde Hichilema, candidat à sa propre succession, a ainsi fait une promesse de campagne : tripler la production de cuivre pour renflouer les caisses d'un État déclaré en faillite en 2021. Mais sur place, le constat est amer. De notre envoyé spécial à Chingola, Pour répondre à la question que vous rapportent les mines de cuivre ? Eugene Mulanga de la fondation Caritas nous emmène au bord de la rivière Kafue : « C'est ici à Chingola que la pollution des mines est la plus importante, dénonce-t-il. Pollution de la rivière et de ses rives mais également pollution du sol. C'est pour ça que la plupart des agriculteurs sont affectés, ainsi que la faune et la vie aquatique. Je crois que c'est le pire endroit de Zambie tant la pollution est répandue. » Depuis des années, des entreprises minières rejettent illégalement leurs résidus dans la rivière. Et le bilan est désastreux. Tout est contaminé aux métaux lourds. La rivière et les poissons bien sûr, mais également les sols, l'air et même l'eau du robinet. Une catastrophe écologique, sanitaire et économique qui fait enrager Felix Chipoya, directeur de l'Alliance territoriale, une ONG locale. « Quand les sols sont contaminés, cela signifie que les agriculteurs doivent utiliser davantage d'engrais. Or ces engrais sont de plus en plus chers et les petits producteurs ne peuvent pas les acheter. Tout ça pourquoi ? Parce que les sols sont pollués. Donc, les agriculteurs s'enfoncent dans la pauvreté. Ce n'est pas ça le développement », s'irrite-t-il.  À lire aussiEn Afrique, la course aux minerais stratégiques bat son plein sur la «ceinture de cuivre» Pour une « situation gagnant-gagnant » C'est tout le paradoxe de la Copperbelt. Une région extrêmement riche dont la population reste très pauvre. Car ces immenses réserves de cuivre, exploitées par des multinationales étrangères, n'ont pas permis son développement. « Le premier objectif des investisseurs, c'est de faire des profits. Mais, de la même façon qu'ils font des profits, nous aussi, les Zambiens, nous devons en tirer des bénéfices », insiste Felix Chipoya.   En 2022, près de 65 % de la population zambienne vivait avec moins de 2 dollars par jour. Pour redresser la situation, l'actuel président Hakainde Hichilema, candidat à sa propre succession lors de la prochaine élection présidentielle d'août 2026, souhaite tripler la production de cuivre du pays. Encore faut-il que cette future manne financière profite réellement au pays. « Nous pensons qu'il est tout à fait possible d'arriver à une situation gagnant-gagnant, plaide Eugene Mulanga. D'autant plus que le cuivre, le cobalt et tous ces minerais sont très recherchés dans le monde. Nous aimerions que le gouvernement adopte une autre approche, en taxant davantage l'industrie minière ». Pour les habitants de la Copperbelt, il est temps que les mines de cuivre leur apportent autre chose que la pollution.  À écouter dans Grand reportageZambie : dans la Copperbelt, des minerais et des larmes

with Brad Friedman & Desi Doyen

A decades-long lawsuit over chicken pollution in the Illinois River moves closer to ending.Democrats are raising concerns about next month's ballot measure on Voter ID.Indigenous elders in Oklahoma got a chance to compete and learn.You can find the KOSU Daily wherever you get your podcasts, you can also subscribe, rate us and leave a comment.You can keep up to date on all the latest news throughout the day at KOSU.org and make sure to follow us on Facebook, TikTok and Instagram at KOSU Radio.This is The KOSU Daily, Oklahoma news, every weekday.

Throughout the 2026 World Cup, state and local organizations have used NASA air quality data to provide a clear picture of the air that players and fans are breathing.

Chris Jones and Krissy Kasserman expose Iowa's factory farm crisis, linking manure, nitrates, cancer concerns, clean water, family farms, and electoral accountability.Subscribe to our Newsletter:https://politicsdoneright.com/newsletterPurchase our Books: As I See It: https://amzn.to/3XpvW5o How To Make AmericaUtopia: https://amzn.to/3VKVFnG It's Worth It: https://amzn.to/3VFByXP Lose Weight And BeFit Now: https://amzn.to/3xiQK3K Tribulations of anAfro-Latino Caribbean man: https://amzn.to/4c09rbE

durée : 00:07:07 - Les Matins de France Culture - 24 départements en vigilance rouge canicule. La France suffoque et est en outre confrontée à une importante pollution à l'ozone. - équipe : La Rédaction de France Culture, Alison Vicrobeck Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

durée : 00:07:07 - Journal de 8 h - 24 départements en vigilance rouge canicule. La France suffoque et est en outre confrontée à une importante pollution à l'ozone. - équipe : La Rédaction de France Culture, Alison Vicrobeck Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

durée : 00:07:07 - Les journaux de France Culture - 24 départements en vigilance rouge canicule. La France suffoque et est en outre confrontée à une importante pollution à l'ozone. - équipe : La Rédaction de France Culture, Alison Vicrobeck Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

Stay informed on current events, visit www.NaturalNews.com  - China's Gold Market and U.S. Treasury Speculation (0:11) - Impact of China's Gold Market Regulations (4:14) - Expansion of Gold Storage in Hong Kong (7:24) - China's Gold Accumulation and Future Plans (16:19) - Potential Impact on Global Gold Markets (20:30) - China's Financial Strategy and Geopolitical Implications (23:20) - Mike Adams' Financial Advice and Investment Strategies (23:36) - Concerns About AI and Tech Stock Bubbles (32:55) - Historical Context of Weather Warfare (44:51) - Challenges in Proving Weather Warfare (58:57) - U.S. Military and Carbon Black Dust (1:12:30) - Florida Legislation and Weather Modification (1:23:26) - Historical Context of Cloud Seeding (1:27:46) - Chemtrails and Jet Fuel Emissions (1:30:22) - Stratospheric Aerosol Injection and Geoengineering (1:38:38) - Jet Fuel Sulfur Content and Environmental Impact (1:42:18) - Technocratic Control and Weather Modification (1:51:32) - Personal Experiences and Observations (1:54:22) - After-Party Discussion and Further Insights (1:54:36) - Promotion of Products and Services (2:10:52) Watch more independent videos at http://www.brighteon.com/channel/hrreport  ▶️ Support our mission by shopping at the Health Ranger Store - https://www.healthrangerstore.com ▶️ Check out exclusive deals and special offers at https://rangerdeals.com ▶️ Sign up for our newsletter to stay informed: https://www.naturalnews.com/Readerregistration.html Watch more exclusive videos here:

Episode Highlights With MichaelWhy he thinks synthetic fragrance is the new secondhand smoke and how he can back this up with dataSecondhand smoke was such a brilliant marketing push and why fragrance needs this nowThe worst offenders and what to look forWhat “fragrance” actually is when you see it on a packageSafe swaps that actually workHaving safe and beneficial indoor air quality The air freshener industry is a 7 billion dollar industry. The air filtration industry is less than half of thatPeople are spending double the money to pollute their air than to clean itFragrance = chemicalsThey work by hijacking your ability to smellWhat to know about candles and which to avoid- some can be great!Turning your home into a sanctuary The 80/20 of health: sleep sanctuary, scrub sleeping air, filter water.Resources MentionedJaspr air scrubber - use the link for a discountOrganic beddingHealthy mattress I loveWater filtersHealthy lightingNon-toxic dishwasher and laundry detergentBranch Basics non-toxic cleanerJust Thrive:Just Thrive Health has been one of my longtime favorite brands for gut health and they have an amazing Daily Gut Detox. Your immune system, gut barrier, and digestion get the support they need to stay strong and healthy. You can find this and their probiotics at justthrivehealth.com/wellnessmama or use code wellnessmama for 20% off your order. BioptimizersI love and use so many products from them, but I especially love the magnesium (Magnesium Breakthrough) and digestive enzymes (Masszymes). Visit bioptimizers.com/wellnessmama to get the best deal!

10 years before the catastrophic train derailment and chemical disaster in East Palestine, Ohio, one of the deadliest rail disasters in North American history took place in the Canadian town of Lac-Mégantic, Quebec.On July 6, 2013, an unattended freight train that had been parked on the tracks overnight began to roll downhill and gather alarming speed as it careened towards the city center of Lac-Mégantic. The train, which was operated by Montreal, Maine, and Atlantic Railway and carrying over 2 million gallons of crude oil, derailed around 1:15 AM. The resulting explosions and fire killed 47 people and destroyed over 40 buildings, obliterating a large portion of the downtown area and prompting mass evacuations.In this special episode of Working People, we speak with a panel of survivors of the Lac-Mégantic rail disaster in Canada and the East Palestine rail disaster in the USA.Panelists include: Robert Bellefleur, a resident of Lac-Mégantic and spokesperson for the Lac-Mégantic Citizens' Coalition for Railroad Safety; Gilbert Carette, a resident of Lac-Mégantic and a member of the Lac-Mégantic Citizens' Coalition for Railroad Safety; Gilles Fluet, a resident of Lac-Mégantic who narrowly escaped the 2013 train crash and witnessed the derailment firsthand; Anne-Marie Saint-Cerny, award-winning writer, videographer, social and environmental justice activist, and author of Mégantic: A Deadly Mix of Oil, Rail, and Avarice; Jami Wallace, a displaced resident of East Palestine, Ohio, and founder of the Chemically Impacted Communities Coalition; Christina Siceloff, a Creek Ranger and resident of Beaver County, Pennsylvania, affected by the 2023 Norfolk Southern train derailment and chemical disaster.If you or members of your community are interested in attending or participating in TRNN's 2026 No More Sacrifice Zones conference, please contact us by emailing contact[at]therealnews[dot]com. Additional links/info: Lac-Mégantic Citizens' Coalition for Railroad Safety website and Facebook pageChemically Impacted Communities Coalition (CICC) Facebook pageRailroad Workers United website, Facebook page, and X pageAnne-Marie Saint-Cerny, Talonbooks, Mégantic: A Deadly Mix of Oil, Rail, and AvariceDimitri Lascaris, TRNN, “‘Bomb Train': Oil Execs Try to Blame Workers for Tragic Accident”Maximillian Alvarez, TRNN, “America's toxic future looks like East Palestine, Ohio, today”Maximillian Alvarez, Working People / TRNN, “Toxic Avengers: America's poisoned and abandoned communities must stand together or die”Credits: Pre-Production: Maximillian Alvarez, Dr. Nicole Fabricant, Fritz EdlerStudio Production: Maximillian AlvarezFrench-English Interpretation: Anne Lagacé DowsonVoice Acting: Ethan Cox, Daniel LemieuxAudio Post-Production: Jules Taylor, Alina NehlichMusic: Jules Taylor Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-news-podcast--2952221/support.Help us continue producing radically independent news and in-depth analysis by following us and becoming a monthly sustainer.Follow us on:Bluesky: @therealnews.comFacebook: The Real News NetworkTwitter: @TheRealNewsYouTube: @therealnewsInstagram: @therealnewsnetworkBecome a member and join the Supporters Club for The Real News Podcast today!

Les industriels vont devoir payer une redevance pour l'émission de PFAS dès le 1er septembre. Dans « La Story », le podcast d'actualité des « Echos », Pierrick Fay et Marie Bellan font le point sur ce sujet.« La Story » est un podcast des « Echos » présenté par Pierrick Fay. Cet épisode a été enregistré en juin 2026. Rédaction en chef : Clémence Lemaistre. Invitée : Marie Bellan (journaliste spécialiste des sujets environnement aux « Echos »). Réalisation : Willy Ganne. Chargée de production et d'édition : Clara Grouzis. Musique : Théo Boulenger. Identité graphique : Upian. Photo : Stéphane Audras/REA. Sons : TF1, France Info, Service Public de l'Eau.Retrouvez l'essentiel de l'actualité économique grâce à notre offre d'abonnement Access : abonnement.lesechos.fr Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

TODAY ON THE ROBERT SCOTT BELL SHOW: Jonathan Emord, US Empire at 250, COVID EUA Ends, Trans Ruling, Exit UN, PFAS Delays, Psychiatric Drugs for Children, Dr. Rob Brown, Electro-pollution, Radiation Protection, Helianthus Annuus and MORE! https://robertscottbell.com/jonathan-emord-us-empire-at-250-covid-eua-ends-trans-ruling-exit-un-pfas-delays-dr-rob-brown-helianthus-annuus/ Purpose and Character The use of copyrighted material on the website is for non-commercial, educational purposes, and is intended to provide benefit to the public through information, critique, teaching, scholarship, or research. Nature of Copyrighted Material Weensure that the copyrighted material used is for supplementary and illustrative purposes and that it contributes significantly to the user's understanding of the content in a non-detrimental way to the commercial value of the original content. Amount and Substantiality Our website uses only the necessary amount of copyrighted material to achieve the intended purpose and does not substitute for the original market of the copyrighted works. Effect on Market Value The use of copyrighted material on our website does not in any way diminish or affect the market value of the original work. We believe that our use constitutes a 'fair use' of any such copyrighted material as provided for in section 107 of the U.S. Copyright Law. If you believe that any content on the website violates your copyright, please contact us providing the necessary information, and we will take appropriate action to address your concern.

In this episode, Izzy asks the question everyone's been ignoring: Do reusable water bottles actually prevent pollution? She discusses the history of reusable water bottles, compares the amount of pollution both bottles cause, and what humanity can do about the mass overconsumption happening. How have water bottles and how we view them changed throughout time? How much pollution do water bottles create? How can we change people's perspectives on reusable water bottles? Listen in on her episode and find facts that will make you hesitate the next time you reach for the newest Owala.

A new report examines how America's longstanding racial divides amplify the impacts of climate change.

From the explosion of AI data centers to the increasing number of toxic spills, explosions, and industrial disasters happening across the country, corporations and the government are turning the USA into one giant “sacrifice zone.” In “red” states and “blue” states, in rural areas and urban areas, poor and working people are suffering the toxic effects of a crisis that has resulted from decades of deregulation, corporate-capture of government, and the protection of private profits over the lives and health of the public.No one is coming to save us, and nothing is going to change unless residents of different sacrifice zones and poisoned communities, workers and unions on the frontlines of the industries poisoning us, environmental justice groups, community and faith organizations, scientists, journalists, and all others who have a stake in this fight start coming together, working together, and fighting back together. In this special panel discussion, recorded at the 2026 Railroad Workers United convention in Chicago, Illinois, we speak with a panel of guests who are part of a new coalition that is doing just that.Panelists include: Jeff Kurtz, a retired locomotive engineer, union officer, and Railroad Workers United member who also served as a state representative in the Iowa House of Representatives; Jami Wallace, a displaced resident of East Palestine, Ohio, and founder of the Chemically Impacted Communities Coalition (CICC); Dr. Nicole Fabricant, a professor of anthropology at Towson University and scholar-activist who has been working with chemically impacted communities in South Baltimore, Maryland, for 15 years; Scott Smith, independent testing expert and founder of the Blue Shirt Justice League; and Lesley Pacey, Senior Environmental Officer at the Government Accountability Project.Additional links/info: Railroad Workers United website, Facebook page, and X pageChemically Impacted Communities Coalition (CICC) Facebook pageBlue Shirt Justice League website and Facebook pageGovernment Accountability Project website, Facebook page, X page, Bluesky page, and InstagramCoal-Free Curtis Bay Facebook page and InstagramSouth Baltimore Community Land Trust website, X page, Facebook page, and InstagramNicole Fabricant, University of California Press, Fighting to Breathe: Race, Toxicity, and the Rise of Youth Activism in BaltimoreMaximillian Alvarez, TRNN, “America's toxic future looks like East Palestine, Ohio, today”Maximillian Alvarez, Working People / TRNN, “‘Let's unite!': Poisoned residents of America's sacrifice zones are banding together”Maximilian Alvarez, Working People / TRNN, “Corporations and the government are turning the USA into one giant ‘sacrifice zone'”Featured Music: Jules Taylor, Working People Theme SongCredits: Audio Post-Production: Jules TaylorBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-real-news-podcast--2952221/support.Help us continue producing radically independent news and in-depth analysis by following us and becoming a monthly sustainer.Follow us on:Bluesky: @therealnews.comFacebook: The Real News NetworkTwitter: @TheRealNewsYouTube: @therealnewsInstagram: @therealnewsnetworkBecome a member and join the Supporters Club for The Real News Podcast today!

(Group Learning Program) - Chapter 21 - Do No Harm: What is The Future of The Planet?Currently, it is well known that the planet has experienced massive destruction from the human population and our daily decisions. The human population of the planet has drastically impacted the planet's natural habitat. Pollution, waste, lack of food, water, and other resources plagues our ability to live in a healthy environment where all beings can thrive.The destruction of the planet is a direct result of the destruction of the mind of all of humanity. The pollution of the mind of all of humanity can be seen in the pollution of the planet.In this Podcast, David will explain how learning and practicing The Teachings of Gotama Buddha will lead to improved health for the planet.——-Daily Wisdom - Walking The Path with The BuddhaDedicated to the education of Gotama Buddha's Teachings to attain Enlightenment.https://www.BuddhaDailyWisdom.com(See our website for online learning, courses, and retreats.)Group Learning Program - LIVE Interactive Online Classes, Book, Audiobook, Videos, Podcast and Personal Guidancehttps://mailchi.mp/f958c59262eb/buddhadailywisdomThe Words of The Buddha - Pali Canon in English Study Grouphttps://mailchi.mp/6bb4fdf2b6e0/palicanonstudyprogramFREE Book - Developing a Life Practice: The Path That Leads to Enlightenmenthttps://www.buddhadailywisdom.com/freebuddhabooksFacebook: https://www.facebook.com/groups/DailyWisdom999YouTube: https://www.youtube.com/@DailyWisdom999Podcast: https://creators.spotify.com/pod/profile/buddhadailywisdom/Support our efforts to share The Teachings of Gotama Buddha with you and worldwide for all people using this link.https://www.buddhadailywisdom.com/supportbuddha#buddhism #learnbuddhism #enlightenment #dhamma #dharma #buddha #meditation #meditationretreat #meditationcourse

Every day, we throw things away, only to be forgotten forever. But society didn't always work in the same way. In this episode, we speak with University of Chicago scholar and anthropologist Sarah Newman to discuss her book, Unmaking Waste: New Histories of Old Things. An archaeologist by training, Newman discusses the history of trash across time—from the ancient Mayan civilization through today's disposable culture. She argues that other societies valued objects much more deeply, reusing and recycling items in innovative ways. But will we ever return to this kind of zero-waste mentality? Newman argues that true sustainability requires a radical, systemic overhaul of how products are designed, valued and dismantled. She challenges us to look beyond the recycling bin and imagine a world where waste isn't just managed, but systematically unmade if we are to genuinely rethink our relationship with garbage and reshape our future. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Russian disinformation no longer feels like a foreign problem you read about in long articles. It shapes what you see when you open your phone, what your relatives believe about a war they have never visited, and what large language models tell you when you ask a sincere question about world events. My guest this week on Cults, Culture & Coercion, Chris Sampson, journalist, terrorism analyst, and extremism researcher, publisher of The Wiretap, has spent more than four years reporting from Ukraine. He wakes up to drones and missiles, then opens his laptop to read online claims about the country he lives in describing a place he does not recognize. Few people are positioned to explain this gap with the precision he brings. He sorts Russian information into three streams: state propaganda, general pro-Kremlin bloggers, and military-security bloggers. The third stream sometimes fractures, and analysts who watch carefully see fissures open. Living in Ukraine has given Chris a daily lesson in cognitive dissonance, the discomfort a person feels when they hold two contradictory beliefs and resolve it by changing one of them. He walks through a Ukrainian city the morning after Russian drones strike it, then opens a feed full of Russian disinformation claiming the strikes never happened or accusing Ukrainians of staging them. The flood of falsehoods is the point. Putin and the KGB long ago refined what researchers call the firehose of falsehood, in which an overwhelming volume of contradictory claims exhausts your ability to sort signal from noise. He warned me about a newer escalation. Russia has been seeding pseudo-academic papers and propaganda articles into the training data of large language models. Ask one of the major AI tools a sincere question about the war or about the kidnapped Ukrainian children, and the model has been trained on material with Russian framing baked in. Chris named Kateryna Rashevska, a leading Ukrainian expert on the abducted children, as one of those raising the alarm about academic-looking papers planted to muddy the legal and historical record. This is active measures, the Russian intelligence tradition of psychological and information warfare, applied to a new generation of tools. The mechanism is brainwashing, the systematic use of deception, repetition, and emotional manipulation to shape what a person believes. The kidnapped children case is one of the most painful expressions of this doctrine.  Learn more about your ad choices. Visit megaphone.fm/adchoices

As the Trump administration rolls back environmental regulations, we revisit a 2022 episode that explored the hidden cost of an invisible threat: air pollution.   SOURCES: Angela Duckworth, psychologist at the University of Pennsylvania. Michael Greenstone, economist at the University of Chicago, director of the Energy Policy Institute, co-director of the Climate Impact Lab. Stephan Heblich, economist at the University of Toronto. Andrea La Nauze, economist at Deakin University. Steve Levitt, professor emeritus of economics at the University of Chicago. Edson Severnini, economist at Boston College.   RESOURCES: "Most Polluted Cities," (American Lung Association, 2026). "Air Pollution and Adult Cognition: Evidence from Brain Training," by Andrea La Nauze and Edson Severnini (Journal of the Association of Environmental and Resource Economists, 2025). "Air Pollution and Student Performance in the U.S.," by Michael Gilraine and Angela Zheng (NBER Working Papers, 2022). "Billions of people still breathe unhealthy air: new WHO data," (World Health Organization, 2022). "Evolution of the Clean Air Act," by the United States Environmental Protection Agency (2020). "The Death of U.K. Coal in Five Charts," by Hannah Ritchie (Our World in Data, 2019). "The Colour of Pollution," (The Economist, 2014). Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.