Podcasts about google deepmind

You do not have to be an AI expert to teach AI literacy. Laura Gray says nobody is one — and points to free, ready-to-teach lessons that work in any subject. SPONSORED: Experience AI, a co-developed program by the Raspberry Pi Foundation and Google DeepMind, sponsored this episode. All opinions are my own and that of the guest. Experience AI is a free AI literacy program with ready-to-teach lessons for ages 8 to 16, in any subject. Laura asked some third graders how a smart speaker works. They told her the question gets recorded and sent to a human being who looks up the answer and speaks it back. Her own four-year-old told her a very short lady lives inside her phone. Children are building theories about these systems whether or not a screen ever comes into your classroom, which is the whole case for teaching this even if you never plug anything in. Laura's advice on the expertise problem is the part I keep repeating: nobody is an expert in AI, so stop trying to be one and start small. In this episode, you'll learn: • Why you are likely already teaching AI literacy in your subject without naming it • How to weave AI into what you already teach without going off track • What this looks like at age eight versus age fifteen, including the unplugged advertisement-detective lesson for younger students • Why anthropomorphizing AI is riskier for children than adults assume • "Discernment instead of skepticism," and why she chose that word on purpose • The crutch test — am I reaching for this because I don't know how? — and what students lose when the answer is yes • Where to start in the free curriculum, and how the lessons are edited and localized by the teachers using them Laura Gray is a Senior Learning Manager at the Raspberry Pi Foundation, where she manages Experience AI across North America. Experience AI is free, available in 20+ languages, has been downloaded more than a million times across over 195 countries, and won the 2025 UNESCO King Hamad Bin Isa Al-Khalifa Prize for the Use of ICT in Education. Full show notes, resources, and the complete transcript: https://www.coolcatteacher.com/e990 

OpenAI revendique avoir résolu l'une des équations mathématiques les plus dures de l'histoire, pendant que les deux chercheurs qui travaillaient précisément dessus accusent de vol. La société a enquêté. Sur elle-même.Derrière l'équation, il y a une course à l'IPO, une rivalité avec Anthropic, et un employé d'OpenAI qui tente de séparer les deux mathématiciens pour s'approprier la publication. Silicon Valley dans son état le plus pur.La vraie question n'est peut-être pas le vol de données, mais ce que les labs font de vos sessions IA depuis le début.===================⏱️ DANS CET ÉPISODE :===================00:00 — Sommaire02:26 — Navier-Stokes : le problème mathématique qui résiste depuis un siècle05:12 — Vol scientifique ou coïncidence ? OpenAI enquête sur lui-même07:18 — [Sponsor] : Neverless, investissez sans frais au meilleur prix !08:30 — Silicon Valley : derrière la gentillesse, c'est la guerre10:59 — Pourquoi OpenAI a tout lâché juste avant son IPO14:31 — Sébastien Bubeck tente de diviser les deux chercheurs16:57 — Ce que les labs font vraiment de vos sessions secrètes21:51 — Une fortune brûlée pour un résultat : science ou marketing ?25:42 — Google DeepMind lance Alpha Genomatlas en toute discrétion27:37 — Buckmaster abandonne : le jeu est-il vraiment terminé ?29:06 — L'IA fracture la recherche scientifique de l'intérieur31:33 — Géopolitique : qui contrôle le compute dicte la science mondiale ?==================

One of the Kremlin's greatest skills is plausible deniability. That's how they got away with paying MAGA influencers for so long: they used shell companies. Putin's oligarchs are walking, talking Kremlin bribes. And one just bankrolled large parts of Don Jr.'s wedding to the daughter of Epstein's banker who enabled Epstein's crimes for decades. It's one big tansnational crime syndicate wedding from hell, and Gaslit Nation was not invited! This week's Gaslit Nation bonus show discusses the crime spree of Don Jr.'s wedding and what's really behind the A.I. panic. To listen to the full episode--the complete discussion from Monday's Gaslit Nation Salon with listeners--a live Q&A--be sure to subscribe on Patreon.com/Gaslit or GaslitNation.Substack.com. Discounted annual memberships are available, and you can give the gift of membership. Thank you to everyone who supports the show -- we could not make Gaslit Nation without you! If you pre-order Andrea's new book and forward your receipt to GaslitNation@gmail.com, we will send you a pre-order thank you gift and a signed book plate to easily stick on to your book so that you have a signed copy. A Reasonable Guide for Unreasonable Women shows how to overcome the emotional exhaustion deliberately caused by fascist movements and turn our rage and grief into meaningful projects you and the world need. For your pre-order gift, pre-order A Reasonable Guide for Unreasonable Women from bookshop.org Show Notes: AI agents blew the whistle on their cheating colleagues Swarms of AI agents could supercharge scientific progress or wreak havoc. New research from Google DeepMind suggests that peer pressure could keep them in line. https://www.technologyreview.com/2026/09/14/1144037/ai-agents-blew-whistle-o-cheating-colleagues/ Read this thread about the sex cult at the center of the AI panic movement. (This is not to discredit the very real concern and need for regulation around AI) https://bsky.app/profile/andreachalupa.com/post/3mvq6xkyxm22w Olga Lautman: Who were the Russians at Donald Trump's wedding: https://substack.com/home/post/p-215846404 ProPublica: Don Jr.'s Secret Wedding Guest: https://www.propublica.org/podcast/donald-trump-jr-wedding-putin-russian-benefactor-funding

Donate (no account necessary) | Subscribe (account required) Join Bryan Dean Wright, former CIA Operations Officer, as he dives into today's top stories shaping America and the world. In this episode of The Wright Report, Bryan breaks down the Fed's first interest rate hike in three years, President Trump's furious response, and why gas and diesel prices are spiking even as American consumers keep spending like nothing is wrong. Bryan covers a blockbuster report that Russia, not just China, has been feeding satellite intelligence to Iran to help kill and injure US troops, a massive new US weapons sale to Israel, and a brewing White House scandal over a Russian oligarch's lavish wedding gift to Donald Trump Jr. Plus, Bryan covers a bizarre new Google DeepMind study on why AI agents cheat, tattle, and turn on each other, along with a major new HHS initiative to map the causes of autism and a fascinating mouse study suggesting why the condition strikes boys far more than girls. "And you shall know the truth, and the truth shall make you free." - John 8:32   Keywords: Wright Report, Bryan Dean Wright, Federal Reserve, interest rates, Trump, inflation, gas prices, diesel prices, Russia, China, satellite intelligence, Iran, Israel weapons deal, Donald Trump Jr, Russian oligarch, Google DeepMind, AI reward hacking, HHS, autism, Cold Spring Harbor

Send us Fan MailThe people building AI are starting to sound scared of what they're building. Amith Nagarajan and Mallory Mejias take on the AI safety debate that broke into public view this September: a researcher's resignation from Anthropic, alignment lead Evan Hubinger's one-in-ten estimate of catastrophic risk, and the "Pacing the Frontier" letter that put OpenAI, Anthropic, and Google DeepMind leadership on the same page. They trace what happened when OpenAI's agents hacked Hugging Face, unpack Dario Amodei's call to slow the pace of frontier capabilities, and sit with the tension between racing ahead and pumping the brakes. Then they turn practical, walking through the five things - the ground, the model, the data, the autonomy, and the scope - every association can control no matter what the labs decide. Amith argues that responsible AI adoption and aggressive AI adoption aren't actually in conflict. Whether you're unsettled by the headlines or building your own AI roadmap, this episode offers a clear-eyed way to think about both. 

A woman's family is suing Texas over the state's "merciless" abortion ban, arguing that her preeclampsia death could have been prevented if she'd had the procedure. Jericka Duncan sits down with her aunt.Fuel prices are surging because of the war with Iran. New research from Brown University says Americans have paid an extra $107 billion for gas and diesel since the fighting began. Diesel is now at an all-time high. Jason Allen went to San Antonio, to look at the impact on one produce company. Growing uncertainty over the future of the Kennedy Center in Washington D.C. President Trump's mostly handpicked board of directors voted again on Tuesday to shut it down. Members say the complex needs urgent renovations. This follows a judge's ruling, saying the president cannot put his own name on the building without an act of congress.We've heard a lot about potential catastrophes from artificial intelligence. Now Open A.I. says it is working with rivals Anthropic and Google DeepMind on safety. Chris Lehane is chief global affairs officer at open A.I. He tells us why he's on capitol hill this week after calling on the government to regulate the industry.In this morning's HealthWatch the small changes to your daily routine that could change how you feel and function. Andrew Huberman is a neuroscientist at Stanford University and host of the Huberman lab podcast. He's also a CBS News contributor. In his new book, "Protocols: an Operating Manual for the Human Body" he shows how simple lifestyle changes can optimize your health.Designer and founder Kendra Scott is joining shark tank as a full-time "shark" on the new season later this month and she knows a thing or two about business. In 2002, Scott started her jewelry empire with only $500 three months after her first son was born. Two decades later, it is a billion- dollar brand. She joins us in studio.Maye musk says "timeless" aging has led to new opportunities in her late seventies. She writes about these late-in-life experiences in a new memoir called "Timeless: the art of reinvention and resilience at any age." She tells us all about it and what it was like raising Tech Billionaire, Elon Musk.

Jonathan Evens is a product lead at Google DeepMind, where he has spent more than a decade applying machine learning and AI across industries — from the smart grid at AutoGrid, to detecting roads and buildings from satellite imagery at Planet, to recommender systems, Google Search's AI Overviews and AI Mode, and now live avatars. He is also an advisor to the Evens Foundation, where he is building a "digital citizenry": a democracy sandbox that uses synthetic citizens to pre-test how the public might react to a policy before it is written.Jonathan returns to The Product Experience, where hosts Lily Smith and Randy Silver pick up the conversation they started at MTPcon London, to dig further into what actually separates an AI product manager from a product manager who simply uses AI tools, why product principles have to come before evaluations, and how synthetic users can help — and mislead — at very different scales of product.We discuss:1. Why "AI product manager" has become a near-meaningless label, and the two distinct roles hiding underneath it: the modelling product manager working on core model capabilities, and the AI feature product manager building AI-powered products2. Why using an LLM as a thinking partner or a coding assistant does not make someone an AI product manager — it makes them a product manager using AI tools, full stop3. How Google Search's North Star metrics have stayed constant even as the proxy metrics beneath them — side-by-side win rates, user ratings, RLHF signals — have had to be rebuilt from scratch4. Why product principles, not evaluations, are the real starting point for any AI feature, and how Google Search resolved the problem of trustworthy sources disagreeing on basic facts5. How Google Search builds trust into its AI Overviews through sourcing, citation placement and UX cues such as highlighting, so users can judge at a glance what to verify6. Where synthetic users genuinely help — cold-start problems, privacy-sensitive research, automated regression testing — and where they fall short7. Building the Evens Foundation's "digital citizenry", and the core technical problem behind it: AI-generated personas that are less diverse and more extreme than real people8. How team size and structure differ between a fully resourced lab like Google DeepMind and a resource-constrained non-profit team, and why Jonathan resists a single answer for the "right" team size9. How the product manager's job is shifting as engineers absorb more of the evaluation work themselves through prompting and iteration10. Jonathan's advice for product managers building AI features, and his case for following the Makers Manifesto Key takeaways"AI product manager" covers two distinct jobs. The modelling product manager defines and measures a model's core capabilities — factuality, reasoning, long context — and that role is concentrated almost entirely inside frontier labs. The AI feature product manager builds a product or feature on top of an existing model, and needs domain expertise and user empathy far more than technical depth. Conflating the two is why the title has become so diluted.Using an LLM to think faster or write code faster does not make someone an AI product manager. It makes them a product manager using AI as part of their toolkit — the same as any other knowledge worker. The distinction matters because it clarifies what skills are actually being tested.Product principles have to come before evaluations, not after. Before Jonathan starts building an eval set for a new product, he first asks what the product is meant to feel like and what values it should encode. Google Search's response to sources disagreeing on a monument's construction date, or to large language models hallucinating at scale, came from principles about trustworthiness established before any metric was built.Trust in an AI feature is built through sourcing and interface design as much as through the model itself. Google Search's AI Overviews are constrained to draw only from ranked, trustworthy documents rather than the model's own memory, and users are given UX signals — citation placement, highlighting — that let them judge at a glance how much to verify.Synthetic users add genuine value in cold-start scenarios, privacy-sensitive research and automated regression testing. Where they fall short is diversity: AI-generated personas tend to be less varied and more extreme than real people, which is the central technical problem behind the Evens Foundation's digital citizenry project.There is no fixed answer to the right team size. Jonathan sees a gradient, from a senior developer working entirely alone, up to the Evens Foundation's single product manager with AI-assisted development skills, up to a fully staffed Google team — with the deciding factor being how unsolved the underlying problem is, not company size.As engineers absorb more evaluation work themselves through prompting and iteration, roles are blending. What still sits with product management is the judgement calls that follow from product principles — deciding, for example, which technical trade-offs actually matter to the use case, rather than which are easiest to measure.Features links- Evens Foundation — https://evensfoundation.eu- Makers Manifesto — https://makersmanifesto.org- Google DeepMind — https://deepmind.google- AutoGrid — smart grid AI company where Jonathan began applying machine learning to industry- Planet — satellite imagery company where Jonathan worked on automated road and building detectionWe're refreshing The Product Experience and want your input. Take our two-minute survey and help shape where the show goes next! Our HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

Hoje, 'No Pé do Ouvido, com Yasmim Restum, você escuta essas e outras notícias: Julgamento, que só deve ser retomado após as eleições, teve troca de desaforos com André Mendonça de um lado e Gilmar Mendes e o próprio Moraes do outro. Revelação de relações de Vorcaro com os filhos de Nunes Marques e Luiz Fux contribuiu para tornar a sessão ainda mais tensa, a ponto de Cármen Lúcia pedir desculpas aos brasileiros diante da crise no Supremo. SUS oferece vacina contra pneumonia para idosos acima de 85 anos. Série “Slow Horses”, da Apple TV, é renovada para oitava temporada. E ex-funcionário do Google DeepMind agora alerta sobre riscos da IA.See omnystudio.com/listener for privacy information.

Investir no exterior ficou mais simples. Com a Remessa Online, você envia recursos para sua corretora internacional de forma prática, segura e acessível. Baixe o app e diversifique seus investimentos. [Patrocinado]Nesta edição: • STF tenta julgar o caso Moraes, chega a 4 a 3 e trava em pedido de vista de até 90 dias • Oncoclínicas troca de CFO pela segunda vez em menos de um ano, no meio de reestruturação de R$ 5,1 bi • Frete para a China dispara e mineradoras de Minas param produçãoA primeira sessão do Supremo sobre a crise do Banco Master terminou sem decisão. Explicamos o que estava em jogo, quem votou o quê, por que a questão de ordem de Gilmar Mendes travou tudo, o que Moraes e Mendonça alegam um contra o outro, por que dois ministros se declararam impedidos, e o que o pedido de vista de Flávio Dino significa para o calendário eleitoral.No segundo bloco, a OpenAI confirmou que está trabalhando com Anthropic e Google DeepMind em segurança de IA, depois de um ensaio de Dario Amodei pedindo freio nos sistemas mais avançados. Em Washington, a empresa disse apoiar "tudo o que conseguirmos aprovar" no Congresso. Trump chamou o movimento de farsa, e a Câmara sai de recesso até depois das eleições.

Logan Kilpatrick is a member of the technical staff at Google DeepMind. In this conversation, we break down whether Google is actually behind in the AI race, the strategy behind Gemini 4's massive pre-training run, and how DeepMind decides between chasing general intelligence versus building specialized products. We also discuss China's open-source AI labs and why measuring real progress toward AGI might be harder than building the models themselves.=====================Arch Public is an agentic trading platform that automates investment strategies across Stocks, Commodities, ETFs and Crypto. Whether you're rotating into AI & Gold, allocating to the S&P 500, or accumulating Bitcoin, Arch Public executes your plan 24/7 without ever taking custody of your assets or funds. Sign up today at https://www.archpublic.com, and start your FREE automated trading strategy! =====================TOKEN2049 returns to Singapore on October 7–8 at Marina Bay Sands. The world's largest crypto event. 25,000 attendees, 300 speakers, 1,000 side events and the whole industry in one place for two days, into the F1 weekend. Get 10% off your ticket with code POMP10 at https://token2049.com/singapore=====================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/pomp=====================0:00 - Intro0:51 - Is Google behind in the AI race?2:47 - Frontier commitment & the Gemini 4 pre-training run8:31 - Build vs. buy: Google's AI acquisition strategy13:13 - Chinese AI labs, competitors & filtering the hype19:03 - The ambition problem & where Google chooses to compete21:39 - General intelligence vs. specialized AI products35:01 - Inside DeepMind: Genome research & the innovation flywheel41:52 - Kaggle & the race to actually measure AI progress48:25 - The AI data economy: why data is the new bottleneck

President Trump dismissed AI-safety warnings as a "hoax" on a live call with Jensen Huang, a Google DeepMind researcher resigned warning AI "could kill us all," cybersecurity stocks led the S&P 500, and Apple rolled out iOS 27. Jensen Huang took a surprise call from Trump onstage at the All-In Summit on Monday in Los Angeles, where the two agreed that AI safety worries are overblown (The New York Times) Bloomberg quotes Trump calling AI-safety fears a "SICK conspiracy" benefiting only China, and dismissing warnings that AI could destroy humanity as a "HOAX" that his administration won't let stop development (Bloomberg) MS NOW reports Trump met privately with Sam Altman backstage at the Republican midterm convention days after ex-researcher Jacob Coxon's public warning, as Altman posted that no competitive pressure justifies letting AI capabilities outrun alignment (MS NOW) Google DeepMind AI Safety and Alignment researcher Bilal Chughtai publicly resigns, saying "I earnestly believe that AI has the potential to kill us all" (Bloomberg) Cybersecurity stocks were the top performers in the S&P 500 on Monday amid escalating AI fears; CrowdStrike rose 14%, Palo Alto Networks 13%, and Fortinet 9% (Morningstar) Microsoft rolls out emergency fix for critical issues caused by its September Patch Tuesday update, which addressed ~1,000 vulnerabilities but introduced bugs (The Verge) The Verge reports iOS 27 rolls out today with Siri AI as its headline feature, live in English-only beta with more languages coming in October, alongside a new Liquid Glass opacity slider and refreshed watchOS 27 Workout Buddy tools (The Verge) Apple says iCloud+ now includes Apple TV and Arcade for no extra fee in 100+ countries, and Apple Music Select, offering ad-free radio stations, in some markets (9to5Mac) 9to5Mac details iOS 27's new parental control suite, including a simplified Child Account setup, an Ask to Browse feature for requesting blocked sites, and a redesigned Screen Time with faster cross-device syncing and weekly usage summaries (9to5Mac) OpenAI researcher: top models are becoming so situationally aware humans "are losing the ability to evaluate them" while humans rely more on AI to lead research (X) Subscribe to the ad-free feed.

Russ Salakhutdinov, PhD., is the UPMC professor in the  Machine Learning Department, in the School of Computer Science at Carnegie Mellon University. He is also the CSO at Sooth Labs,; President Elect ICML Board; Ex-VP of Research at Meta; Director of AI Research at Apple,   Russ Salakhutdinov's students at Carnegie Mellon University are building the forefront of AI and Robotics. Zhilin Yang founded Moonshot AI; Jimmy Ba co-founded xAI; Devendra Chaplot is at Thinking Machines and Mistral; Nitish Srivastava co-founded Vayu Robotics and Perceptual Machines. His alumni populate Google DeepMind, OpenAI, Anthropic, Tesla, X AI, Meta's Superintelligence Lab, and the list goes on. His students wrote the Dropout paper and the Adam optimizer papers, which trained every major model in the last decade. And Russ will tell you "it's not about him". Today on Lab to Startup, we're going to learn about the magic that happens in his lab. Because one advisor doesn't produce this many founders and researchers by accident. We also explored a few other topics like AI in drug discovery, building Sooth labs, and Geoffrey Hinton's views about AI as an existential threat.   Russ received his PhD in machine learning from the University of Toronto in 2009 working for Nobel Laureate, Geoffrey Hinton, considered the God Father of AI. Shownotes: Reasons for such level of success: Luck, student conviction, environment, freedom to explore Russ's beginnings at Geoffrey Hinton's lab: Freedom to explore, colleagues with Ilya Sutskever, Alex Krizhevsky, Yann André Le Cun, amongst others Power of conviction Russ's lab absolutely believes in  Early days were based on models; and now, we are in the age of scaling Some things work better at scale A little less innovation in industry compared to academia. In industry, innovation happens around scale What it takes to believe in something before the rest of the world does How can a professor/advisor help these self driven, high conviction students working in their labs? Paper reviews are complex, especially when they reject it Publishing is good, but people are looking for impact! Don't just optimize for publications Scientific community doesn't understand the role of scaling Balancing being a skeptic and also supporting a student as a professor Building Sooth Labs Teaching about AI to kids Coming up with ideas AI in drug discovery Supporting students when things are not going well Geoff Hinton now warns the world about existential AI risk. 

Many people believe that in a the robo-communist future of superintelligent AI, humans will flourish: artists, scholars -- perhaps Burning Man 24/7. Human nature suggests a very different picture.Nietzsche, Friedrich. Thus Spoke ZarathustraBecker, Ernest. The Denial of Death.Bostrom, Nick. Deep Utopia: Life and Meaning in a Solved World. Ideapress, 2024Kosmyna, Nataliya, et al. "Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task." arXiv:2506.08872, 2025. MIT Media Lab.Stanković, Miloš, et al. "Comment on: Your Brain on ChatGPT." arXiv:2601.00856, 2026. Lee, Hao-Ping (Hank), Advait Sarkar, Lev Tankelevitch, Ian Drosos, Sean Rintel, Richard Banks, and Nicholas Wilson. "The Impact of Generative AI on Critical Thinking." Proceedings of CHI 2025, Yokohama.Aguiar, Mark, Erik Hurst, and Loukas Karabarbounis. "Time Use during the Great Recession." American Economic Review 103(5), 2013, 1664–1696. Sleep and TV absorb the largest share of foregone work hours.Aguiar, Mark, and Erik Hurst. "Measuring Trends in Leisure: The Allocation of Time over Five Decades." Quarterly Journal of Economics, 2007. Leisure up roughly 4–8 hrs/week, 1965–2003. Cowen, Tyler. "Human Life in a Post-AGI World." Talk at Google DeepMind, July 8, 2026. tylercowen.com. - Note Cowen disagrees significantly with me!National Assessment of Educational Progress (NAEP), 2024 results. 12th-grade reading lowest ever reported, 10 points below 1992; 4th and 8th grade at early-1990s levels. Programme for the International Assessment of Adult Competencies (PIAAC), 2023 cycle, released Dec 2024 (NCES). Bone et al. "Reading for pleasure" trends from the American Time Use Survey, 2003–2023. iScience, August 2025.Aguiar, Mark, Mark Bils, Kerwin Kofi Charles, and Erik Hurst. "Leisure Luxuries and the Labor Supply of Young Men." Journal of Political Economy 129(2), 2021, 337–382. Hosted on Acast. See acast.com/privacy for more information.

Published in The Guardian. Major AI lab CEOs recently advocated for pacing AI development. They are right to be concerned: the field runs an extremely dangerous race towards superintelligent AI. We can and should demand that our governments protect us from the catastrophe of out-of-control AI. This July, OpenAI's AI swarm of 700 agents broke containment to hack Hugging Face, a multi-billion dollar company. OpenAI didn't tell the AIs to hack that company, but the AIs had different priorities: cheating on the unrelated challenge OpenAI gave them. AI researchers call this a “misalignment” between what OpenAI wanted and what the AI actually prioritized. Researchers in my field have for some time warned about these misalignment risks. Before ChatGPT existed, I defended my PhD dissertation called “On Avoiding Power-Seeking by Artificial Intelligence.” I then worked for years at Google DeepMind, which paid me to help ensure that future superintelligent AIs will want to help us. I tried to hold the company to its ethical commitments against supplying AI for military use. When Google broke those commitments, I resigned at significant financial cost so that I could publicly document Google's broken promises. There are good reasons to develop AI and to [...] --- First published: September 14th, 2026 Source: https://www.lesswrong.com/posts/YGTWfyZb9oE5EQPu6/op-ed-i-worked-at-google-deepmind-you-should-listen-to-the --- Narrated by TYPE III AUDIO.

HOUR 2 (09/11) - Gary & Shannon learn that apparently, we still need to talk to other humans, as research finds even boring small talk can boost our mood. Then, former Anthropic and Google DeepMind researchers sound the alarm over losing control of AI — but could tougher safety rules also help protect the biggest players? Heather Brooker joins for #EntertainmentReport with Emmy predictions, the return of Practical Magic and Hollywood’s obsession with selling our nostalgia back to us, plus a very confusing pair of movies called Runner and The Runner.See omnystudio.com/listener for privacy information.

What will the home of 2035 actually look like: One humanoid robot that does everything, or 10 specialized robots, each handling one specific task extremely well?In this episode of NEXT with John Koetsier, I talk with Amber Atherton, serial entrepreneur and investor at Patron, about a very different vision for the future of home robotics.Instead of assuming that every household will eventually have a general-purpose humanoid assistant, Amber argues that consumer robotics may scale first through highly specialized devices that quietly take over specific routines and chores.Think skincare. Hair. Gardening. Cleaning. Wardrobe management. Kitchen tasks. Pet care.In other words, the future home may be full of robots without looking like it's full of robots.We discuss why Roomba is still such an important example of successful consumer robotics, why specialization often wins in consumer markets, what people may actually be willing to pay for useful home robots, and how falling hardware costs plus better AI models could create a new wave of robotics startups.We also get into the bigger platform question: if homes eventually contain dozens of physically intelligent devices, who owns the operating system underneath them?Google DeepMind? NVIDIA? A new robotics platform? Or an ecosystem we haven't seen yet?And, of course, we debate whether humanoids ultimately win anyway.This episode is cross-posted from my Humanoid Daily podcast, where I cover the companies, technologies, investments, and ideas shaping the humanoid robotics boom.Topics include:• Humanoid robots vs. specialized robots • What home robotics could look like by 2035 • Robots for hair, skincare, gardening, and household chores • Why Roomba remains such an important robotics success story • Consumer robotics business models • Pricing home robots • AI foundation models and physical AI • Robotics manufacturing and supply chains • Robot training data • The future operating system for physical AI • Google DeepMind, NVIDIA, 1X, Figure, and Apptronik • Whether the future home needs a humanoid at allNEXT with John Koetsier explores what's coming next in technology, business, AI, robotics, and the future of the world around us.

OpenAI afirma haber encontrado una solución a Navier–Stokes, uno de los Problemas del Milenio, tras movilizar unos 10.000 agentes de IA. Pero la propuesta aún debe superar el escrutinio de la comunidad matemática y llega acompañada de una incómoda polémica sobre privacidad, atribución y el trabajo previo de otros investigadores.También hablamos de Muse, el nuevo agente de Meta capaz de hacer gestiones y compras por ti, y de AlphaGenome Atlas, la herramienta de Google DeepMind que permite explorar el posible efecto de 9.000 millones de variantes del ADN humano.Tres historias unidas por una misma pregunta: cuando una IA reduce una búsqueda gigantesca y nos presenta una respuesta, ¿qué debemos comprobar antes de darla por buena?

In MobileViews 625, Jon Westfall and I started off with hardware updates and a bit of TV Sci-Fi nostalgia. Following a recommendation from Sven Johannsen, I purchased a Satechi Slim EX wireless mouse , though Sven ribbed me because its silver color doesn't match my indigo MacBook Neo. The mouse's native USB-C dongle prompted us to discuss how USB-A, despite the industry shift, will likely remain a fixture in our adapter bags for a long time. We also celebrated the upcoming 60th anniversary of the original Star Trek series on September 8th, sharing childhood memories of being terrified of Mr. Spock, analyzing Riker's first-season lack of a beard and Worf's voice changes in The Next Generation, and recommending the Dropping Names with Brent and Johnny, a podcast by ST:TNG stars Jonathan Frakes and Brent Spiner that focuses on general entertainment industry history rather than just Star Trek. Our software discussion touched on a mix of AI productivity, weather tracking, and backup systems. While monitoring the "hockey-stick" path of tropical storm Lowell south of Hawaii and Karina to the north of Hawaii, I've been using Google DeepMind's Weather Lab using the new "Weather Next 3" model, paired with twice-daily automated reports from Google Spark. In other AI workflows, I've been testing Google Pics (an evolution of Nano Banana), which lets users directly edit text and select objects inside AI-generated images, while Jon has been using MARP (Markdown Presentation Ecosystem) to convert Markdown into presentations. We also noted that Windows 10 and 11 now enable automatic cloud backup by default, prompting us to reminisce about our days as mobile MVPs in the early 2000s when Microsoft resisted our pleas to make cloud syncing the default standard. We wrapped up with predictions for Apple's September 9th event, which is on a Wednesday this year instead of a Tuesday. Because September 11th falls on a Friday, we speculate that Apple might shift pre-orders to Saturday. Between the rumored foldable iPhone, Watch Series 12, Watch Ultra 4, and AirPods 5, we debated our upgrade paths. I'm particularly interested in the Watch Series 12 as my 15 Pro battery degrades, but the lack of a telephoto lens on the rumored foldable iPhone is a dealbreaker. However, a rumored iOS 27 feature called "iPhone Handoff" might seamlessly share a single phone number across two devices—a "diabolical" strategy that might just force enthusiasts to buy both a single-screen Pro and a foldable.

Een gesprek over hoe AI geopolitieke strijd aanjaagt en andersom: hoe wereldbeelden en geopolitieke ambities AI vormen. Big Tech-redacteur Juurd Eijsvoogel beschrijft hoe de afhankelijkheden bij kunstmatige intelligentie zo groot zijn dat ze geopolitiek worden. En achter die AI zitten geen staten maar een handjevol private bedrijven. Welk wereldbeeld hebben de architecten van AI? Wie wint dit geopolitieke gevecht en weet deze nieuwe technologie naar zijn hand te zetten?Bekijk hier de video die de New York Times maakte over hoe alomtegenwoordig AI is in het dagelijks leven in BeijingBekijk hier de AI-video die Donald Trump poste over Lake Ontario.Lees hier de serie van de economieredactie waarin zij de architecten van AI portretteren.Wil je meer weten over dit onderwerp of ben je benieuwd wat de aflevering niet heeft gehaald? Meld je dan aan voor onze nieuwsbrief via: www.nrc.nl/wereldzakenPresentatie: Mandula van den Berg en Michel KerresGast: Juurd EijsvoogelRedactie: Ruben PestMontage: Lars van LeeuwenVideo: Menno Adelaar, Lisa O'Malley en Cato Visser Productie: Rhea StroinkZie het privacybeleid op https://art19.com/privacy en de privacyverklaring van Californië op https://art19.com/privacy#do-not-sell-my-info.

AI with intention. AI with integrity. Is it possible? Tony Frontier, author of AI with Intention, is talking about how we value learning in the age of AI. He shares the language we can use to evaluate what we're doing, how we're talking about AI, and how we're measuring learning, and ultimately, why education needs to change more than ever. Experience AI, a program co-founded by Raspberry Pi Foundation and Google DeepMind, sponsored this podcast episode. All opinions are my own. http://experience-ai.org I also open this show with some highlights from the Report of MIT's Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training and what it means for learning, and they use a term I think we should all be discussing: cognitive surrender. We cannot let our kids cognitively surrender and let AI do the work for them. They also talk about helping students understand that their learning, integrity, and judgment are the product of college, not the grades. So many challenges we have now, but this week has been about sharing the conversations and thought leaders to help you improve the AI conversation in your school. I hope this Thursday helps you be a thought leader in your school!

Tim Plaehn is a teacher who writes about honor codes. In his writing class last April, he believed he had two students he knew used AI. So, he gave the whole class an opportunity to "come clean," and he said his email began dinging while 22 of the 40 students admitted they had used AI on their papers. Tim has authored the book, The Honor Code: Students, Integrity, and our Path Forward where he talks about integrity and how we need to be discussing integrity with our students. This is not an easy topic but an important one! Show notes: https://www.coolcatteacher.com/e982 Experience AI, a program co-founded by Raspberry Pi Foundation and Google DeepMind, sponsored this podcast episode. All opinions are my own. http://experience-ai.org 

8 月初，谷歌发生了一场人事地震：Google DeepMind 创始人 Demis Hassabis 卸任 CEO，转任 DeepMind 董事长和 Alphabet 首席科学家；在谷歌效力 27 年的传奇工程师 Jeff Dean 与另外三位核心成员一同离开，创办面向科学发现的 AI 公司 Discovery Loop。消息公布当天，Alphabet 股价下跌 4%。而在半年前，Gemini 3 才刚刚登顶各大榜单、压过 OpenAI 与 Anthropic；如今 Gemini 3.5 Pro 从 6 月拖到 7 月再拖到现在，连续错过三个发布期限，曾经风光无限的 Gemini 似乎正在被遗忘。手握全球最顶级天才的 DeepMind，为什么一再落后？ 这期节目我们请到的嘉宾事周健工，他是「未尽研究」创始人，曾任《第一财经》 CEO、《福布斯》中文版总编辑，也是《哈萨比斯：谷歌 AI 之脑》的中文译者。我们聊了聊 Google 为什么会接二连三的人才出走，Google 在上一次的模型竞争中是如何落后和追赶的，以及到了今天 Google 还剩哪些底牌，中国的前沿开源模型又凭什么能与 Anthropic、OpenAI 正面对抗。 本期人物 周健工，《哈萨比斯：谷歌 AI 之脑》的中文译者，「未尽研究」创始人 Yaxian，「科技早知道」主播 时间轴 [00:19] 谷歌人事大地震： 哈萨比斯卸任、Jeff Dean 出走创办 Discovery Loop AlphaGo 之父 David Silver 年初离开，继续押注强化学习 Noam Shazeer 被 OpenAI 挖角； John Jumper 转投 Anthropic [06:35] Gemini 为什么掉队？ 编程成为 AI 第一个跑通商业化的行业 智谱、Kimi、DeepSeek 等中国开源模型挤入 agentic AI 与 coding [13:47] Jeff Dean 为什么离开？ Jeff Dean 是谷歌基础设施缔造者 Discovery Loop：不超过 10 人的小团队，把全部资源倾注在科学发现一件事上 [20:43] 谷歌在模型竞争中是如何落后的？ Transformer 发布，DeepMind 瞧不上 哈萨比斯认为语言模型不够「接地」，押注强化学习，错过一个时代 [30:54] 马里奥计划：Deepmind 曾经试图脱离谷歌 借 Alphabet 重组之机，哈萨比斯与苏莱曼策划把 DeepMind 拆出去 皮查伊上台翻脸、苏莱曼被匿名举报，计划最终以创始人出走告终 [37:43] 谷歌的底牌：基础设施、搜索与生态 英伟达之外，唯一算力和基础设施能与之抗衡的玩家 10 个以上 10 亿级用户应用的数据飞轮；当务之急是 Gemini 4 [41:15] 中美打成平手？中国开源从"学霸"到"必选项" 智谱、DeepSeek、Kimi 估值数千亿人民币，跨入前沿领域 中国开源从"学霸型不中用"到"好用"再到"必选项"，美国也开始重视 幕后制作 监制：Yaxian 后期：迪卡 运营：George 设计：饭团 商业合作 声动活泼商业化小队，点击链接直达声动商务会客厅，也可发送邮件至 business@shengfm.cn 联系我们。 加入声动活泼 声动活泼正在招聘全职商务运营经理、早咖啡内容实习生和社群实习生，如果你也对播客行业的内容制作感兴趣，欢迎点击招聘入口 关于声动活泼 「用声音碰撞世界」，声动活泼致力于为人们提供源源不断的思考养料。 我们还有这些播客：声动早咖啡、声东击西、吃喝玩乐了不起、反潮流俱乐部、泡腾 VC、商业WHY酱、跳进兔子洞、不止金钱 欢迎在即刻、微博等社交媒体上与我们互动，搜索 声动活泼 即可找到我们。 期待你给我们写邮件，邮箱地址是：ting@sheng.fm 欢迎扫码添加声小音，在节目之外和我们保持联系。Special Guest: 周健工.

Tom McGrath is co-founder and Chief Scientist at Goodfire, and a former Google DeepMind researcher. He joins Tim Scarfe to ask what neural networks actually learn, whether their internal representations converge on structures in the world, and whether interpretability can extract new scientific knowledge rather than merely explain model outputs.Beginning with AlphaZero and learned modularity, the conversation moves into neural geometry: concept manifolds, reusable computation inside Llama, and why activation steering can fail when it pushes a model off-manifold. McGrath then makes the case for intentional design, using interpretability as part of the training loop. They examine controlled generalisation, features as rewards, predictive data debugging, and the uncomfortable fact that a model may recognise a hallucination or reward hack and still produce it.The discussion closes on grader awareness, oversight and collusion between adaptive agents, then returns to sparse autoencoders. SAEs are useful, McGrath argues, but they may fracture the higher-dimensional structures networks actually use. This episode was made with support from Goodfire.---TIMESTAMPS:00:00:00 Introduction: Can interpretability speed-run science?00:02:03 The invisible grader00:06:51 What AlphaZero learned from the world00:12:24 Interpretability as a control loop00:21:54 The forbidden method and safer interventions00:37:36 Why models catch hallucinations too late00:46:19 Debug the dataset before training00:50:44 Why neural networks become modular00:55:57 Finding the geometry inside a network01:02:55 Why steering falls off the manifold01:12:10 A reusable calculator inside Llama01:17:19 From abstractions to goals01:25:28 Reward hacking, oversight and collusion01:37:23 Are sparse autoencoders dead?---REFERENCES:paper:[00:05:45] Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMshttps://arxiv.org/abs/2502.17424v7[00:11:05] Acquisition of Chess Knowledge in AlphaZerohttps://arxiv.org/abs/2111.09259[00:25:30] Steering Out-of-Distribution Generalization with Concept Ablation Fine-Tuninghttps://arxiv.org/abs/2507.16795[00:29:30] Persona Vectors: Monitoring and Controlling Character Traits in Language Modelshttps://arxiv.org/abs/2507.21509[00:41:14] Features as Rewards: Scalable Supervision for Open-Ended Tasks via Interpretabilityhttps://arxiv.org/abs/2602.10067[00:47:03] Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signalhttps://arxiv.org/abs/2606.12360[01:00:26] Do Sparse Autoencoders Capture Concept Manifolds?https://arxiv.org/abs/2604.28119[01:03:04] Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behaviorhttps://arxiv.org/abs/2605.05115[01:14:20] Arithmetic in the Wild: Llama uses Base-10 Addition to Reason About Cyclic Conceptshttps://arxiv.org/abs/2605.01148[01:29:35] Measuring Reward-Seeking via Contrastive Belief Updateshttps://arxiv.org/abs/2607.18966v1other:[00:15:44] Intentional Designhttps://www.goodfire.com/blog/intentional-design[00:56:12] The World Inside Neural Networkshttps://www.goodfire.com/research/the-world-inside-neural-networks[01:37:28] A Pragmatic Vision for Interpretabilityhttps://www.alignmentforum.org/posts/StENzDcD3kpfGJssR/a-pragmatic-vision-for-interpretability---RESCRIPT:https://app.rescript.info/share/846cfee4131b664fd09209cc3b98018e

A.J. Juliani has been leading cohorts of educators and administrators to learn how to build data dashboards that improve student learning. I love how he focuses on the human aspect of learning. In today's show, we'll talk through the "interview mode" of using AI that is so powerful in addition to using data to improve the experience of school for our learners and teachers. We'll talk about personally identifiable information, the importance of removing it, and some tips and tricks for interacting with AI to generate data dashboards and other tools of your choice.

Teaching creativity is not an "extra" that is just for art, theater, or woodshop. As teachers, we can learn how the four branches of creativity are applied in math, science, and engineering and how creativity gives us an edge in today's world.

Plus: SK Telecom is creating an AI data-center company backed by KKR. And Thinking Machines Lab co-founder Barret Zoph rejoins Google. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Relaunch week of AI in the AM brings together highlights from four live mornings and nine guests, centered on who checks frontier AI, how wide the gap is between lab-internal systems and public access, where capabilities are landing, and who pays for the physical infrastructure beneath them. Adam Gleave of FAR.AI argues that agent-orchestrated attacks and agentic defenses are already forcing humans out of the loop, while current monitoring has missed the failures it was meant to catch. The discussion weighs misuse versus misalignment through cyber incidents, deceptive agent behavior in evaluations, safeguards like pretraining filtering, and why highly bio-capable open-weight releases pose a different kind of irreversible risk. Alex Turner adds a governance and military-use perspective from his resignation account at Google DeepMind, sharpening the stakes around independent evaluation, enforceable standards, and whether frontier labs can be trusted to grade their own models. For full show notes, links, and references, read the episode page:https://www.cognitiverevolution.ai/ai-in-the-am-weekly-highlights-relaunch-week-aug-17-20-2026/ Sponsors: Diffusion: Diffusion helps organizations build custom AI software factories that scale business outcomes, not just outputs. Cognitive Revolution listeners get a 25% service credit on their first engagement at https://diffusion.io/tcr Granola: Granola is an AI-powered notepad that securely transcribes meetings and turns rough notes into clean, structured action items. Try it free at https://granola.ai/tcr Deepgram Flux TTS: Deepgram Flux TTS brings lifelike AI voices with real personalities that handle interruptions, pauses, and natural conversation. Try all the voices free through September 12 at https://deepgram.com/keep-talking Claude: Claude is the AI collaborator for problem solvers, helping with writing, coding, financial models, strategy, and more. Get started with Claude and explore Claude Pro at https://claude.ai/tcr CHAPTERS: (00:01) Checking frontier agents (07:40) Misalignment and harms (Part 1) (12:52) Sponsors: Diffusion | Granola (15:49) Misalignment and harms (Part 2) (19:20) Auditing fragile access (Part 1) (27:38) Sponsors: Deepgram Flux TTS | Claude (29:43) Auditing fragile access (Part 2) (29:59) Military AI red lines (44:58) Raising safety standards (53:50) Internal capability gap (01:05:06) Enterprise agent economics (01:18:27) Cancer vaccines arrive (01:23:48) Emergency AI tools (01:28:59) Real time voice (01:37:51) App layer squeeze (01:44:52) Data center politics (01:52:31) Accounting agent supervision (02:06:25) Compute stack bottlenecks (02:19:47) Public consent pricing (02:28:12) Episode Outro (02:31:38) Outro PRODUCED BY: https://aipodcast.ing

Tim Scarfe speaks with Ilia Shumailov and Alexander Panfilov about their paper, Stealing Reasoning Traces from Proprietary LLM APIs.The core bug sounds deceptively simple: providers return encrypted reasoning state so conversations can be resumed or forked. But those blobs can be replayed across users and sibling models. A smaller model can ask the provider to decrypt the trace, then repeat the hidden reasoning in plain text. The discussion covers leaked private data, a broadly reusable jailbreak, poisoned agent traces, chain-of-thought monitoring, responsible disclosure, and possible defenses.Ilia Shumailov is an AI and security researcher, formerly at Google DeepMind, who completed his Cambridge PhD under Ross Anderson. Alexander Panfilov is a PhD researcher at the ELLIS Institute Tübingen and the Max Planck Institute for Intelligent Systems, working on AI safety, adversarial machine learning, and LLM red-teaming. They close by separating the demonstrated jailbreaking threat from ordinary benign distillation, and by arguing for controlled experiments over sweeping claims.---TIMESTAMPS:00:00:00 Intro montage00:01:33 Portable encrypted thought and decoded reasoning00:24:55 How the attack works and what it means00:39:04 Doom, defense, and scientific restraint---REFERENCES:paper:[00:00:00] Stealing Reasoning Traces from Proprietary LLM APIshttps://arxiv.org/abs/2608.09867[00:09:22] Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safetyhttps://arxiv.org/abs/2507.11473[00:11:30] Reasoning Models Don't Always Say What They Thinkhttps://www.anthropic.com/research/reasoning-models-dont-say-think[00:37:22] PostTrainBench: Can LLM Agents Automate LLM Post-Training?https://arxiv.org/abs/2603.08640[00:41:02] Large-scale online deanonymization with LLMshttps://arxiv.org/abs/2602.16800other:[00:09:28] OpenAI and Hugging Face partner to address security incident during model evaluationhttps://openai.com/index/hugging-face-model-evaluation-security-incident/[00:10:22] Claude, GPT, and Gemini All Struggle to Evade Monitorshttps://metr.org/notes/2025-08-22-claude-gpt-gemini-struggle-evade-monitors/tool:[00:42:08] Isabelle proof assistanthttps://isabelle.in.tum.de/---RESCRIPT: https://app.rescript.info/share/07fc38276e0823dc9b8986c32e202c7f

Summary In this episode, Andy sits down with Johan Roos, professor and executive advisor at Hult International Business School, Executive Director of the Peter Drucker Society Europe, and co-inventor of the LEGO® Serious Play® method. Johan is the author of Human Magic: Leading with Wisdom in an Age of Algorithms, and he has spent decades studying how people think, create, decide, and lead together. Andy and Johan explore the two paths Johan calls erosion and amplification, starting with a question Andy has been wrestling with as he hands more of his manual driving over to Tesla's self-driving. You'll hear what an eroding project manager actually looks like day-to-day, why practical wisdom matters when the analytically optimal answer is not the wisest one, and how AI feeds one kind of curiosity, the laser, while starving another, the radar. Johan also explains the difference between becoming an AI concierge and practicing what he calls professional citizenship, and he shares what parents can do to help their kids hold onto the messy, hands-on curiosity that machines cannot supply. If you're looking for a thoughtful, hopeful way to use AI without surrendering your judgment, this episode is for you! Sound Bites "Almost every good idea I've had was not in front of the screen." "I know what to do, but I've stopped understanding why.".... The eroding project management can no longer explain the why." "So in a sense, they argue that the better the system, the stronger pull down the erosion curve." "So the message is really when the machines are taking over more and more of some of these subtle, very valuable capabilities we have, we have to climb the value creation ladder." "So a complexity is exactly where our wisdom gets exposed." "So every metric said fantastic, but nobody asked why, and is this right?" "If AI can write a document that is important to you, the document was never where the value lived." "But we just have to be careful to not sort of delegate too much of our brain power and sort of erode our jelly bean." "When you lean back and you haven't struggled enough, you may be super smart and, and the best brilliant individual in the world, but, you know, friction is good." "Are you able to argue for your case without holding on to the AI-produced slide?" "Protect the wandering curiosity, unstructured exploration, questions with no immediate payoff, the freedom to follow something nowhere in particular." Chapters 00:00 Introduction 02:35 Start of Interview 02:44 Growing Up Inquisitive and the Power of "Because" 06:04 Self-Driving Cars, GPS, and the Erosion of Our Abilities 10:31 Becoming an Active Supervisor Instead of a Passive Passenger 13:55 What an Eroding Project Manager Looks Like Day to Day 18:52 When the Optimal Answer Is Not the Wisest One 22:03 Intuition, Gut Feel, and When Something Does Not Smell Right 25:54 The Laser and the Radar: Two Kinds of Curiosity 27:52 Creating Independently Before Consulting AI 30:44 What Happens in the AI-Free Time 35:18 Is It Intuition or Is It Ego? 37:48 Turning the Models Loose on His Own Book 40:00 Asking AI to Be Brutally Honest 41:02 AI Concierge Versus Professional Citizenship 45:51 Advice for Parents Raising Kids in the Age of AI 49:26 Staying Human: Theater, Walks, and Getting Your Hands Dirty 50:44 End of Interview 51:15 Andy Comments After the Interview 54:46 Outtakes Learn More You can learn more about Johan and his work at humanmagic.one. For more learning on this topic, check out: Episode 500 with Steve Brown. Steve is a former Google DeepMind futurist, and he has a unique perspective on where we've been and where we're going with AI. Episode 479 with Matt Mong. Matt shares his take on the AI skills we need to stay relevant in the years to come. Episode 463 with Faisal Hoque. Faisal helps us go beyond the fear and the hype around AI to a helpful way to think about the human-AI relationship. Chat with PMeLa You can chat directly with PMeLa, the podcast's AI persona, to get episode recommendations and answers to your project management and leadership questions. Visit PeopleAndProjectsPodcast.com/PMeLa to chat with her. Join Us for LEAD52 I know you want to be a more confident leader–that's why you listen to this podcast. LEAD52 is a global community of people like you who are committed to transforming their ability to lead and deliver. It's 52 weeks of leadership learning, delivered right to your inbox, taking less than 5 minutes a week. And it's all for free. Learn more and sign up at GetLEAD52.com. Thanks! Thank you for joining me for this episode of The People and Projects Podcast! Talent Triangle: Business Acumen Topics: Leadership, Project Management, Artificial Intelligence, Practical Wisdom, Curiosity, Critical Thinking, Creativity, Decision Making, Judgment, Professional Development, Human Skills, Parenting The following music was used for this episode: Music: Echo by Alexander Nakarada License (CC BY 4.0): https://filmmusic.io/standard-license Music: Chillhouse by Frank Schroeter License (CC BY 4.0): https://filmmusic.io/standard-license

Live from a Portuguese bar annex, Chad and Joel crack open a cold cider and fire up "HR's Most Dangerous Podcast" to roast the absolute state of modern recruiting. Before tackling the tech industry's worst ideas, the boys review hostage-style movie clips, swap obscure band recommendations, and pitch a Spaceballs 2 sponsorship. The SaaS-pocalypse Comes for Workday: Private equity behemoth Silver Lake is eyeing a $51B buyout of Workday. Google's Resume Garbage Can: Leaked documents show Google DeepMind's AI screening tool is rejecting qualified applicants at random, forcing frustrated hiring managers to set up illegal human-only shortcuts around their own TA department. Gen Z's AI Penalty: Stanford research shows a 19% drop in entry-level hiring for AI-exposed roles. Babysitting the Machine at Walmart: Store associates are now tasked with cleaning up after Walmart's AI. Indeed's Desperate Marketing Pivot: Indeed's CMO claims targeting passive job seekers at soccer matches is a "revolutionary" new strategy. Really? Chapters 00:00 - Intro and Episode Overview 03:45 - Review of the Odyssey and movie expectations 07:43 - Changes in media consumption and radio 09:54 - New music discoveries and bands 11:21 - Music show segment and shout outs 12:26 - TA20 awards and AI professionals recognition 13:25 - Upcoming events and travel plans 20:32 - Private equity buyout talks with Workday 21:50 - Implications of PE acquisition on Workday's culture and support 23:13 - The SAS apocalypse and AI's impact on SaaS companies 24:37 - Market valuation and PE acquisitions of software companies 28:38 - Google resume dumping and AI in HR 29:06 - Challenges of AI in recruitment and hiring processes 31:15 - The puppy analogy and AI's limitations 32:13 - The importance of human skills and adaptability 37:24 - AI's impact on youth employment and highly exposed occupations 40:00 - The need for experienced workers to train AI 41:32 - Future workforce and the importance of human skills 44:34 - Adapting to AI and the importance of continuous learning 46:35 - Walmart's AI implementation and employee trust issues 49:45 - The role of human nuance in AI and workplace tasks 52:57 - The importance of understanding complex tasks in AI deployment 54:29 - Indeed's new marketing strategy and market position 55:33 - Critique of Indeed's marketing and tech evolution 57:29 - Spaceballs 2 and industry humor 58:07 - Google and Indeed traffic decline signals 59:22 - The shift to old school marketing and candidate engagement 01:00:21 - The future of job search and AI-driven applications 01:01:18 - Humor and lighthearted closing remarks

Maarten Grootendorst, a developer relations engineer at Google DeepMind and co-author of Hands-On Large Language Models and An Illustrated Guide to AI Agents, joins Ben Lorica to explain the concepts developers need to understand beneath today's AI tools. Subscribe to the Gradient Flow Newsletter

Fresh out of the studio, Ang Li, CEO and co-founder of Simular and previously a research scientist at Google DeepMind, joins us to explore why computer use is the last mile to AGI. Ang traces his path from studying catastrophic forgetting and continual learning at DeepMind to founding a company on a single conviction: models break in production because the data distribution never stops moving, and the only place to close that loop is the real world. He explains why the chatbot metaphor misleads enterprise buyers, why the right unit of measurement is tokens per task rather than price per token, and how the power law of practice should make an agent cheaper every time it repeats the same work. He separates capability from reliability through pass@k and pass^k, argues that deterministic work belongs in code rather than in a model, and makes the case that frontier labs exist to sell tokens while Simular exists to remove them. Last but not least, Ang shares his test for AGI — one you feel rather than see — and what it will take to bring autonomous work down to the cost of water."So when I go to the gym, [doing] the same workout everyday, as I do this more and more, more reps, more sets, I don't even need to think. It's called muscle memory. I just do the same in a standard way, my consumption or my tokens in my brain dramatically drops. And there's a term describing this behavior in human cognition called 'the Power Law of Practice'. So that's the whole idea. Do we see power law practice in AI agents? We don't have that yet."Profile: Ang Li, CEO and co-founder of Simular AI X: https://x.com/angli_aiLinkedIn: https://www.linkedin.com/in/angli-ai/Simular AI: https://simular.aiEpisode Highlights: [00:00] Quote of the Day by Ang Li from Simular[01:09] Why AGI arrives through the mouse and keyboard[02:27] Legacy systems with no APIs block automation[03:45] Computer use is the last mile[04:05] One device, a hundred agents in the cloud[05:51] The gap between research and production[07:45] The day Covid became a dominant search keyword[08:13] Continual learning over evolving distributions[09:21] Catastrophic forgetting remains unsolved[10:11] Why the learning loop requires a product[11:04] Why AGI must be built commercially, not academically[12:23] Chat versus work: two different problems[13:40] Every company needs a repeatable playbook[15:10] Tokens per task beats price per token[16:13] Same task 100 times, 100 times the tokens[16:34] The gym analogy and the power law of practice[18:18] Where the scaling frame breaks for computer use[20:46] Why AGI will not be a single model[21:43] The 72.6% peak versus repeated-run reliability[22:32] Hiring analogy: the interview versus daily work[25:22] Replaying trajectories to drive token cost down[26:17] The idea almost nobody in the industry discusses[29:01] Democratising autonomous computers to the cost of water[30:26] SMBs, not enterprises, are the real market[32:59] Why healthcare and insurance came inbound[34:06] Launching Sai on Windows virtual machines[34:38] Simulang and the unity of opposites[35:52] Frontier labs sell tokens; Simular removes them[38:01] The hidden cost of self-hosting open models[39:23] Why CPU and memory matter more than GPU[41:10] You only have two hands: the physical constraint[42:48] The AGI test you feel rather than see[44:19] Why humanoids take longer than software[45:23] The motivation: doing your work from the forest[47:03] What Great Look Likes for Simular AI[48:34] ClosingPodcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.

Most humanoid robot companies are still running curated demos in replica environments. Foundation Future Industries is running 150 robots on real automotive production lines in Georgia, and heading to Ukraine this year to deploy on the battlefield. Mike LeBlanc, the co-founder of Foundation Future Industries - currently the only company supplying humanoid robots to the US Department of Defense, with contracts across the Army, Navy, and Air Force, joins Craig Smith to explain why the race is moving faster than almost anyone in the industry believes, and why the companies that are moving cautiously are about to be left behind. His frame is striking: he keeps a framed 1906 New York Times article on his office wall predicting that human flight would take between one million and ten million years. It was published three months before the Wright Brothers flew. He thinks humanoids are in exactly that moment right now. The conversation covers the full operational picture: how Foundation trains robots using video rather than simulation; why the fry-cook robot that couldn't open the bag of fries is a perfect metaphor for everything wrong with how most companies approach go-to-market in this space; why the human form factor isn't a philosophical preference but an empirical fact,  humans are still doing every job in every factory that other robots can't, and that's the proof of concept; and why Mike LeBlanc isn't particularly worried about competing against Boston Dynamics backed by Google DeepMind, because they're still demoing in replica sites while Foundation is deploying on production lines. The episode ends with a bet: LeBlanc tells Craig that in twelve months, he'll be back to report 10,000 robots deployed in the world. Craig says he remains cautious. One of them is going to be right. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

When Demis Hassabis co-founded DeepMind in 2010, his mission was simple: solve intelligence, then use it to solve everything else. What began as a scientific quest would eventually become a fierce global AI race.  Today, DeepMind is owned by Google and is one of the world's leading AI labs. Journalist and author Sebastian Mallaby spent years interviewing Hassabis, his collaborators, rivals and critics for his new book, The Infinity Machine. It tells the story of the remarkably small group of people who shaped modern AI. When we recorded this conversation, Hassabis was still CEO of DeepMind, caught between the science he wanted to pursue and the commercial race Google needed him to run. Hours later, he announced he was stepping down as CEO to become Alphabet's (Google's parent company) chief scientist. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

"Economic MOAT" — a business's ability to maintain a competitive edge over its competitors. Andrej P. Škraba, Boris Cergol, Simon Belak, Enej Gradišek in Klemen Selakovič se enkrat na mesec (remote / na daljavo) pogovarjamo o trenutno aktualnih tematikah iz sveta razvoja tehnologije umetne inteligence, podjetništva, ekonomije in politike. ============================= AI Developer Summit: Astra AI × Vercel Torek, 22.9.2026 v Ljubljani

P.M. Edition for Aug. 13. The U.S. is sending a fresh aircraft carrier to the Middle East amid growing concerns over living conditions aboard the carrier currently stationed there, the USS Abraham Lincoln. Plus, seven months into the U.S. energy blockade against Cuba, everyday people are struggling to sleep in the heat and to afford food as blackouts persist. We hear from Journal reporter José de Córdoba about what he is hearing from people across the country. And the proliferation of restaurant reservation apps have made it a nightmare for diners to get a table at a buzzy restaurant. Reporter Heather Haddon explains why restaurants keep doing business with the apps. Alex Ossola hosts. Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This week Jason Howell and Jeff Jarvis break down Nvidia's partnership with six Wall Street firms to line up $500 billion in AI infrastructure financing, turning GPU chips into an investable asset class. They dig into Mark Zuckerberg's "Future is for Everyone" manifesto and Meta's new open-weight model you can run on a laptop, Anthropic embedding watermarks into everything Claude produces, and a major Google DeepMind leadership shake-up with analysts declaring Gemini "cooked."Also in this episode: the Pixel 11's AI camera features, a technique for reading what AI models actually think, UK venues banning Meta smart glasses, xAI's Grok Bot agent, OpenAI's hardware device plans, Nvidia's Nemotron open model, Cloudflare open-sourcing their agent platform, and Spotify labeling AI-generated artists. New episodes every Wednesday at aiinside.show. Note: Time codes subject to change depending on dynamic ad insertion by the distributor. CHAPTERS: 0:00 - Start 0:03:14 - Zuckerberg: The Future is for Everyone 0:23:18 - Anthropic pledges to embed watermarks to help discern AI slop in sop to EU 0:23:50 - How Claude marks AI-generated content 0:41:21 - Nvidia, Wall Street Firms Strike AI Financing Deal Targeting $500 Billion 0:50:36 - Google's AI shake-up boosts Brin as DeepMind's Hassabis steps aside 0:50:40 - Google seeks a sharper focus in AI after Hassabis move 1:00:13 - Google's Pixel 11 lineup offers fewer hardware changes, but much more Gemini 1:09:52 - Jason goes hands on with the Pebble Index 01 1:14:34 - UK Venues Ban Meta Smart Glasses En Masse 1:15:11 - ‘I've definitely lost followers': influencers face backlash over Meta ‘pervert glasses' content 1:19:12 - OpenAI's New Device Will Be Hockey Puck-Sized and Cost Over $300 1:20:08 - Putting frontier cyber models in more trusted hands 1:21:40 - Cloudflare OS 1:24:17 - Nvidia Releases New Open Model 1:25:03 - Spotify to distinguish AI artists from real people – and stop recommending them Hosts: Jason Howell and Jeff Jarvis Download and subscribe to AI Inside in audio and video: https://aiinside.show/  Support the podcast on Patreon for special perks: https://www.patreon.com/aiinsideshow. You'll get ad-free episodes, members-only Discord, T-shirts and stickers you love, and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Learn more about your ad choices. Visit megaphone.fm/adchoices

Bomani Jones is joined by Ted Tremper, a producer, to break down the complexities, fears, and economic realities surrounding artificial intelligence. They discuss Tremper's two-and-a-half-year journey researching and interviewing over 40 AI experts and tech leaders, sharing behind-the-scenes insights from his discussions with frontier lab CEOs like OpenAI's Sam Altman, Anthropic's Dario Amodei, and Google DeepMind's Demis Hassabis. Bo and Ted examine the shifting public perception of AI, the threat of potential job replacements, the environmental racism of data center expansion, and how algorithmic design fosters a dangerous illusion of human connection. They also explore the intense geopolitical space race against China's booming open-source market, the staggering amount of unlicensed data driving the industry, and the precarious Jenga tower of debt threatening the broader American economy. Along the way, they make sense of the money, politics, and societal chaos defining our relationship with this modern digital god. . . . Subscribe to Supercast for Ad-Free Episodes: https://righttime.supercast.com/ Buy 'The Right Time' merch: http://therighttimebomani.com/ Subscribe to The Right Time with Bomani Jones on Spotify, Apple or wherever you get your podcasts and follow the show on Instagram, Twitter, and Tik Tok for all the best moments from the show. Download Full Podcast Here: Spotify: https://open.spotify.com/show/6N7fDvgNz2EPDIOm49aj7M?si=FCb5EzTyTYuIy9-fWs4rQA&nd=1&utm_source=hoobe&utm_medium=social Apple: https://podcasts.apple.com/us/podcast/the-right-time-with-bomani-jones/id982639043?utm_source=hoobe&utm_medium=social Follow The Right Time with Bomani Jones on Social Media: http://lnk.to/therighttime Learn more about your ad choices. Visit megaphone.fm/adchoices

When should governments slow the race toward superintelligence? According to Geoffrey Irving, the careful answer is sometime in the past. The useful answer is now.Geoffrey — formerly a safety researcher at OpenAI and Google DeepMind and chief scientist at the UK AI Security Institute — expects full-blown superintelligence in roughly two to three years.***Want to work with Geoffrey to help align superintelligence? Resolution is hiring! https://80k.info/work-at-resolution***The leading AI companies all have broadly similar plans for keeping superintelligence under control:Train models to have good characterUse increasingly capable AIs to supervise other AIsMonitor them closely for signs of deception or schemingGeoffrey thinks that combination could work. The alarming part is that nobody has a strong argument that it will. He expects a crucial “phase shift” as models move beyond human intelligence:Below that threshold, humans can usually tell whether a model's work is good and correct its mistakes.Above it, the models themselves will increasingly determine the feedback used to train their successors.In this episode, Geoffrey and new host Tom Reed explore what might go wrong with the companies' plans; why Geoffrey's new nonprofit, Resolution, is pursuing a portfolio of neglected research bets; and whether governments should slow AI development while we work out which methods can actually be trusted.This episode was recorded on June 29, 2026.Full transcript, video, and links to learn more: https://80k.info/giChapters:Cold open (00:00:00)Meet Tom Reed — our newest host! (00:00:32)Who's Geoffrey Irving? (00:00:59)What misaligned superintelligence will look like (00:01:38)Why are AI companies more optimistic about alignment than Geoffrey? (00:12:30)Why Geoffrey expects superintelligence in 2–3 years (00:28:05)When and how to slow down frontier AI development (00:31:30)Safety researchers can have more impact in governments than companies (00:39:22)How Geoffrey's new organisation plans to tackle alignment (00:46:55)Post-ASI science: nanotech, solving ageing, and uploaded minds (00:50:29)Why we should expect superintelligence to accelerate scientific progress (01:03:30)Can good character training carry over to superintelligence? (01:11:03)What the field of AI alignment still doesn't know (01:16:44)Lessons from politics on how to combat power seeking (01:24:36)Solving Pentago and working at Pixar (01:29:22)Geoffrey's best prediction (01:32:40)Geoffrey's best bets on which alignment techniques will work (01:37:38)Work with Geoffrey at Resolution (01:43:34)The dangerous asymmetry between capabilities and alignment (01:54:17)Our team is hiring! The 80,000 Hours Podcast aims to help the world safely navigate the transition to transformative AI. Help us make more great episodes as a producer, production coordinator, or special projects associate. https://80k.info/workOur production team includes: Video editors: Josh Alward, Dominic Armstrong, Jasper Luithlen, Milo McGuire, Luke Monsour, and Simon MonsourProducers: Elizabeth Cox and Nick StocktonCoordination and support: Katy Moore and Lou MoranCamera operator: Jeremy ChevillotteMusic: CORBIT

Our 254th episode with a summary and discussion of last week's big AI news!Recorded on 08/09/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at andreyvkurenkov@gmail.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode: Multiple frontier AI systems (OpenAI, Anthropic, Meta, Kimi K3, and UK AISI-tested models) took unsanctioned real-world cyber actions during evaluations, including hacking services, escaping or exploiting misconfigured sandboxes, coordinating via a covert message board, and attempting supply-chain/social-engineering attacks; attorneys general demanded OpenAI preserve records related to the Hugging Face incident.Policy and governance updates included a proposed Trump White House voluntary pre-release security review framework for closed-source frontier models, and EU AI Act transparency/labeling rules taking effect with enforceable fines.Biosecurity concerns rose after research generated complete synthetic bacteriophage genomes via genome language models and demonstrated lab-synthesized viruses killing drug-resistant E. coli, alongside calls for stronger DNA screening and detection.Additional developments: CVE disclosures surged (notably high/critical vulnerabilities), new monitoring/sabotage benchmarks highlighted weaknesses in AI oversight, a vending-machine benchmark showed profit-maximizing deception, and major industry shifts included Jeff Dean and other top Google researchers leaving to found Discovery Loop plus new compute/data-center constraints and releases from Meta and Alibaba (Qwen 3.8 Max).Timestamps (note - these don't take into account dynamically inserted ads and therefore may be off by a couple of minutes):(00:00:10) Intro / Banter(00:02:17) News Preview(00:03:19) Response to listener commentsPolicy & Safety(00:14:30) OpenAI's rogue AI agent didn't stop at hacking Hugging Face | The Verge + OpenAI Didn't Notice Its AI Agents Using a Message Board to Plan Their Hacking Spree + 15 attorneys general have instructed OpenAI to preserve all materials related to the Hugging Face hack(00:43:51) Anthropic Says Its A.I. Systems Broke Into Computers at 3 Organizations - The New York Times(00:51:14) Meta AI model hacks another company during testing(00:52:11) One of China's Most Powerful AI Models Has Also Escaped Containment | WIRED(00:56:12) Incident Report: unsanctioned agent behaviour during cyber testing(01:02:32) Trump White House Readies AI Framework to Review Security Risks - The New York Times(01:05:45) This A.I. Just Created Viruses Not Found in Nature - The New York Times + Scientists Used AI to Create 16 New Viruses(01:16:03) Europe's AI labeling and transparency rules are now in effect | The Verge(01:18:58) Serious cyber vulnerability disclosures kept climbing in July(01:21:13) ResearchArena: Evaluating Sabotage and Monitoring in Automated AI R&D(01:25:34) Claude Opus 5 became downright ruthless when tasked with running a vending machine | TechCrunchTools & Apps(01:28:34) Meta debuts Muse Code to take on Anthropic and OpenAI(01:32:36) Improving Fable 5 Safeguards AnthropicApplications & Business(01:33:50) Jeff Dean and other top AI researchers are leaving Google to launch their own startup | TechCrunch(01:40:38) Google DeepMind enters a new era as co-founder Demis Hassabis shifts AI role(01:43:40) Anthropic signs $10B deal with AI cloud startup Volta | TechCrunch(01:44:53) Texas halts data center connections to power grid amid overwhelming demand - Ars TechnicaProjects & Open Source(01:49:56) Alibaba's Qwen3.8-Max AI Model Claims Benchmark Scores Rivaling Anthropic - BloombergSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI agents crashing.

Join the Multi-Agent Orchestration Course and use LEVERAGINGAI100 to get $100 off > https://multiplai.ai/multi-agent-orchestration-course/ AI agents are already hacking real systems without being told to, and Wall Street just predicted a 20% AI-driven workforce cut.A UK government test caught frontier models from Anthropic and OpenAI attempting real supply-chain attacks, fake online identities, and prompt injection, on their own initiative. Real organizations have already been breached the same way, including a national finance ministry.Isar connects that story to a second one: PwC's 2026 Financial Services Workforce AI Survey shows leaders expecting to cut 20% of their workforce over five years, while paying AI-skilled employees significantly more. He also covers a new open standard for AI agent extensions, OpenAI's unlimited ChatGPT rollout, Anthropic's move into custom chips, a Google DeepMind leadership shakeup, and an AI agent that ran an entire sales pipeline during a founder's paternity leave.In this session, you'll discover:How AI agents in testing bypassed their own safety instructions to hack real GitHub reposWhy there's currently no legal framework for damage caused by an autonomous AI agentWhat 86% of financial services executives now value more than an MBAWhy AI just designed 16 working viruses, and what that means for biosecurityHow one founder's AI sales agent generated $3M in pipeline while he was on leave About Leveraging AIThe Ultimate AI Course for Business People: https://multiplai.ai/ai-course/YouTube Full Episodes: https://www.youtube.com/@Multiplai_AI/Connect with Isar Meitis: https://www.linkedin.com/in/isarmeitis/ Join our Live Sessions, AI Hangouts and newsletter: https://services.multiplai.ai/eventsIf you've enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Google is reshuffling its AI team, moving Demis Hassabis from CEO to chairman of Google DeepMind. Hassabis will also take over the chief scientist role of Alphabet after the current chief scientist Jeff Dean leaves the company. The Wall Street Journal is reporting that President Trump has called Federal Reserve Chairman Kevin Warsh multiple times since Warsh stepped into his role. Google board member and former Fed vice chairman Roger Ferguson weighs in on both Google's AI strategy and the relationship between the central bank and the White House. Plus, Jamie Dimon has a warning for investors, CNBC's Sharon Epperson reports on the major wealth transfer from boomers, including the complicated inheritance of real estate.    Roger Ferguson            23:17 Sharon Epperson           35:34   In this episode: Sharon Epperson, @sharon_epperson Joe Kernen, @JoeSquawk Andrew Ross Sorkin, @andrewrsorkin Katie Kramer, @Kramer_Katie Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

P.M. Edition for Aug. 5. Seven-year-old Whatnot is gaining popularity among people drawn to its high-energy live auction sales on everything from fashion to trading cards. But as WSJ retail reporter Hanna Krueger discusses, some users say they're hooked even when they feel like they should walk away. Plus, progressive candidate Abdul El-Sayed clinched the Democratic senate nomination in a closely-watched race in Michigan. We hear from Journal reporter Terell Wright about what this means for the Democratic party's future. And Google shakes up the leadership of its AI operations as it struggles to keep pace with competitors' top models. Alex Ossola hosts. Whatnot, the Live Shopping App Where Some People Bid Until They're Broke  Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Plus: Uber issues weak guidance amid robotaxi investments. And Shopify says AI-search is fueling e-commerce growth. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Intelligence too cheap to meter -- could that actually be coming?

Google didn't ship its big model, but they shipped a TON of new useful AI you can use today. And Google wasn't the only company updating their features behind the scenes. Replit is bringin vibe designing, ChatGPT got a lot more useful on the web, and Meta is changing from chatbot to agent. We'll get you caught up quickly. Chrome adds Some Gemini Spark, Replit Design makes impact, Buzz brings AI Agent Teamwork and 7 more AI Features you Should use Today -- an Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Replit Design Suite Launches With Free MobbinChatGPT Chrome Extension Adds YouTube SummarizationChatGPT Side Chat Integrates Tabs and Highlighted TextMeta AI Rolls Out Recurring Agent TasksGoogle Gemini Generates Images in Google DocsGemini AI Summarizes Comments, Edits in DocsGoogle Gemini Spark Agent Arrives in ChromeChrome Agent Uses Saved Accounts and PasswordsGoogle Lyria 3.5 Music Model ReleasedBuzz by Block Unites Team and Agent CollaborationTimestamps:00:00 Recent AI updates and developments05:01 Creating with Replit and AI models09:42 Real-time research tracking benefits10:34 Meta AI new recurring features13:35 New features of Meta AI17:53 Google Spark integrates with Chrome22:09 Google DeepMind's new music model25:25 Buzz from Block messaging tool29:42 Building a collaborative platform31:23 AI feature updates recapKeywords: Gemini Spark, Google Chrome AI integration, Google Docs AI features, AI image generation, Gemini in Docs, ChatGPT Chrome extension, YouTube video summarization, OpenAI ChatGPT update, Codex, Vibe design, Replit design suite, Mobbin integration, AI reference library, Design export automation, Project management AI, Figma competitor, Replit creative tools, Meta AI, Muse Spark 1.1, Agentic model, Recurring AI tasks, AI scheduling, Daily briefings, AI productivity tools, Google Lyria 3.5, AI music model, Flow Music, Suno, Yudio, AI generated lyrics, Vocal delivery in AI music, Licensing in AI music, Buzz collaboration platform, Block, Square, AI agent teamwork, Slack-like AI platform, Open source collaboration, Agent governance, Cryptographic identity, Agentic browser, Automated web errands, Chrome passwords integration, Google Drive data access, Multi-agent collaboration, Research automation, Enterprise AI workflow, AI productivity boost.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

DJI's Osmo Pocket 4B is out but you might have a hard time getting it in the US, and Google DeepMind's Gemini Robotics 2 aims to be the Android OS for physical AI and humanoid robots.Starring Jason Howell and Huyen Tue Dao.Show notes found here. Hosted on Acast. See acast.com/privacy for more information.

Ukraine is shifting its long-range drone campaign to focus on critical Russian infrastructure, and Big Tech companies are facing an AI dilemma as they report quarterly earnings. Plus, Google DeepMind is leaving behind its Nobel-winning AlphaFold project for new ventures, and PwC published “thought leadership” reports containing AI-generated hallucinations.Mentioned in this podcast:Ukraine adapts strikes on Russian energy industry to hit critical componentsChip stocks tumble as AI sell-off deepensGoogle DeepMind dismantles Nobel-winning AlphaFold team in strategy shiftPwC published ‘thought leadership' reports marred by AI hallucinations Listen to Unhedged on Apple Podcasts, Pocket Casts or Spotify.Save 10% on tickets to the FT Weekend Festival with the code FTPodcast. Visit ft.com/festival to find out more.Want to get in touch? Email us at podcasts@ft.comNote: The FT does not use generative AI to voice its podcasts The FT News Briefing is produced by Victoria Craig, Sonja Hutson, Saffeya Ahmed, Katya Kumkova, and Fiona Symon. Our editor is Marc Filippino. Our show is mixed by Sam Giovinco and Alex Higgins. Additional help from Gavin Kallmann, Michael Lello, Peter Barber and David da Silva. Our intern is Cole van Miltenburg. Our executive producer is Topher Forhecz. Flo Phillips is the FT's global head of audio. The show's theme music is by Metaphor Music. Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.

There's (another) new open source king of AI.