Podcasts about Mistral

Europe already produces world-class technology companies. The mistake is assuming future winners will look obvious before they become winners.In this episode of This Week in European Tech, Dan Bowyer and Mads Jensen of SuperSeed speak with Joe Schorge, Founder and Managing Partner at Isomer Capital, about why the best investors focus less on predicting outliers and more on building exposure to exceptional founders, technologies and ecosystems.Joe shares why Europe's next trillion-dollar company is probably already operating today, what Amazon and Google teach us about identifying future winners and why diversification remains one of the most powerful tools in venture capital.The conversation also covers AI sovereignty, Anthropic's model shutdown, DeepSeek's $7 billion round, Mistral's latest raise and Europe's position in the global AI race.Key highlights:Why Europe's next trillion-dollar company probably already existsWhy future winners rarely look obvious early onThe LP case for backing ecosystems instead of chasing predictionsLessons from Amazon and GoogleWhy Europe already produces world-class technology companiesWhy tech sovereignty depends on world-class productsDeepSeek, Mistral and the future of AI infrastructureWhether Europe can compete with the US and China in frontier technologyTimestamps(00:00) Introduction(05:00) Why Accenture matters for the future of AI adoption(12:00) Anthropic's model shutdown and AI sovereignty(15:00) Why tech sovereignty is creating opportunities for European startups(20:00) AI alliances, geopolitics and Europe's position(26:00) DeepSeek's $7 billion funding round(31:00) Mistral's next chapter and Europe's AI ambitions(35:00) Can Europe build a trillion-dollar technology company?(38:00) Why future winners rarely look obvious(40:00) Europe's world-class technology companies(41:00) Isar Aerospace and European winners(42:00) European tech deal of the week(43:00) The week ahead in AI and ventureLearn more about the Love Tomorrow Summit and the programmes EUVC is curating, and secure your tickets here.

Guillaume Decugis a mis vingt ans d'entrepreneuriat dans la tech derrière lui avant de passer de l'autre côté de la table. Polytechnicien passé par Stanford, il a fondé MusicWave, plateforme de musique mobile vendue à OpenWave puis à Microsoft, avant de piloter Linkfluence, spécialiste de la veille sociale, jusqu'à son rachat. Depuis deux ans, il est partner chez Serena Ventures, où il cogère Data Ventures, un fonds de 100 millions d'euros entièrement dédié aux couches d'infrastructure et de data à l'ère de l'IA.Sa thèse d'investissement : les Européens excellent dans les technologies conceptuelles (bases de données, outils de développement, middlewares), mais peinent à en faire des standards mondiaux. Il veut combler ce manque en traquant les pépites partout en Europe, en s'aidant d'outils très sophistiqués qui suivent 5 000 profils de fondateurs et scrutent les tendances sur GitHub. Résultat : la découverte et la cession à Mistral d'Emmi AI, jeune pousse autrichienne spécialisée dans les modèles d'IA capables de simuler des phénomènes physiques complexes. Pour lui, la souveraineté technologique européenne doit se construire en faisant émerger des leaders mondiaux, quitte à ce qu'ils s'américanisent en chemin. Le modèle israélien est sa référence. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

The hosts discuss a favorite scene from the 1981 film Caveman before introducing Project Synapse, their weekly show on AI and new technology. They cover a hectic week in AI news, including talk of SpaceX buying Cursor for $60B, Cursor's role as an AI-enabled IDE using multiple models, and concerns over token costs and profitability. They describe Anthropic taking Fable offline after a government order cutting off foreign nationals, raising fears about reliance on U.S.-based AI and digital sovereignty, and note Europe's renewed push toward open-source alternatives. They highlight open-source and lower-cost models such as Mistral, DeepSeek, and GLM 5.2, Google's strategy of free tools and local processing, and a DeepMind paper "From AGI to ASI." The episode ends with Midjourney's announced non-radiation full-body scanner concept and spa rollout plans for 2027. Find the links we talked about on our Discord Server. This is the link to you our Discord server  https://discord.gg/e9476SGMsz 00:00 Caveman Music Discovery 01:57 Show Intro and Hosts 03:03 SpaceX Buys Cursor 07:23 Is Cursor Still Best 09:18 Fable AI Vanishes 11:20 Government Shutdown Fallout 13:57 Digital Sovereignty Wakeup 18:09 Open Source Reality Check 20:23 Economics Detour Debate 22:30 Governments Back Open Source 27:00 Mistral DeepSeek Shift 29:51 Google Gives AI Away 31:35 Avatars Tokens and X 32:54 Local Models Slow Iteration 33:58 Local AI Smart Speakers 34:40 Chrome Model Backlash 35:20 BitTorrent Style Inference 37:43 Distrust And Data Centers 38:19 Small Models And Transformers 39:45 Google AI Tool Rundown 41:17 DeepMind From AGI To ASI 45:40 Beyond Transformers Next Minds 48:19 AI Splintering And Niches 49:20 Diffusion And SubQ Attention 54:39 Forking And Competition 57:26 Monopolies And CEO Culture 01:02:30 Midjourney Medical Scanner 01:08:59 Innovation Hopeful Wrap

What happens when one of the world's largest enterprise software companies declares that it is no longer a software company, but an AI company? At SAP Sapphire, I caught up with James Bates, Head of Customer Advisory at SAP UK & Ireland, to discuss the company's vision for what it calls the Autonomous Enterprise and why this year's event felt different from any SAP conference before it. From standing-room-only AI sessions to bold declarations from SAP leadership, there was a clear sense that the conversation around AI has moved beyond experimentation and into the world of measurable business outcomes. In our conversation, James explained why so many organizations remain stuck in what he described as the experimentation phase of AI, despite years of investment and countless pilot projects. We explored why successful AI initiatives begin with business outcomes rather than technology choices and why data, governance, and process context have become the foundations of enterprise AI success. We also examined some of the standout announcements from Sapphire, including SAP's AI Agent Hub, the growing role of Joule as a new interface for work, and the company's expanding ecosystem of partnerships with organizations including Anthropic, NVIDIA, Microsoft, Google Cloud, Palantir, and Mistral. James shared why SAP believes the future lies in combining large language models with business context, process knowledge, and trusted enterprise data. The discussion also touched on real-world examples that demonstrate how AI agents are beginning to transform customer experiences, automate complex workflows, and support employees across finance, supply chain, and customer-facing operations. Rather than replacing people, James sees AI assistants and agents working alongside employees, removing repetitive tasks and helping teams focus on higher-value activities. We also explored the challenge many business leaders continue to wrestle with: how to balance autonomy with governance. As AI agents become more capable, maintaining visibility, accountability, and control becomes increasingly important. James shared why governance, trusted data, and strong business processes must remain at the center of every AI strategy. If you've been wondering whether enterprise AI is finally moving beyond the hype cycle and into meaningful business transformation, this conversation offers a fascinating perspective from the heart of SAP's AI strategy and its vision for the future of work. What role do you think AI agents will play inside your organization over the next few years? Share your thoughts.

Snap stellt seine AR-Brille vor. SpaceX übernimmt Cursor für $60 Mrd. Welche Firma kauft Elon Musk als nächstes? Im Anthropic-Streit kommen neue Details ans Licht: Wired berichtet, das Weiße Haus wolle "alle Jailbreaks" blockieren, die G7-Sitzordnung verrät die Trump-KI-Präferenzen. Ein neues Buch enthüllt, dass Trump Musk die speichelleckenden Textnachrichten von Zuckerberg und Bezos gezeigt hat. Microsoft testet DeepSeek für Copilot Cowork. DeepSeek schließt eine $7-Mrd.-Funding-Runde mit ungewöhnlicher SPV-Struktur ab. GLM 5.2 wird zum besten Open-Weights-Modell, Midjourney pivotiert in den Medizin-Markt mit einem 3D-Ultraschall-Gerät. Maia Arson Crimew hackt die Dialog-Konferenz von Peter Thiel, die 222 Namen lange Gästeliste taucht auf, Jens Spahn ist dabei. Allbirds rebrandet zu SmartBird. Warum hat Google den Consumer-KI-Markt eigentlich schon längst gewonnen? Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Snap Specs Brille (00:04:15) SpaceX kauft Anysphere/Cursor (00:12:50) Anthropic: Block all Jailbreaks (00:13:49) SK-Telekom & Mythos-Liste (00:19:28) Speichelleck-Texte aus Trump-Buch (00:21:05) Sacks-Backpedaling (00:29:30) Microsoft testet DeepSeek (00:30:38) DeepSeek $7 Mrd. SPV-Runde (00:35:23) Midjourney Medical-AI (00:40:18) Peter-Thiel-Dialog-Leak (00:47:50) xAI-Mississippi-Verfahren (00:49:33) Allbirds → SmartBird (00:50:00) Sono Motors (00:51:50) Mistral (00:54:48) ChatGPT Marktanteil (01:01:36) 1Komma5° plant Börsengang Shownotes Snap Specs: AR-Brillen Launch-Date & Preorder - theverge.com SpaceX wertvoller als Amazon - bbc.com SpaceX kauft Anysphere (Cursor) für $60 Mrd. - reuters.com Wired: White House will alle Anthropic-Jailbreaks blocken - wired.com David-Sacks-Post zum Anthropic-Streit - xcancel.com Fotos G7 - xcancel.com Pip-Post zu Anthropic - xcancel.com Politico: White House Anthropic-Move bringt Kongress in KI-Debatte - politico.com The Information: DeepSeek schließt Rekord-Runde über $7 Mrd. - theinformation.com Microsoft Copilot Cowork & "Token-Maxing" - axios.com DeepSeek zu Investoren: "No Poaching unserer Leute" - cnbc.com Artificial Analysis: GLM 5.2 ist neues führendes Open-Weights-Modell - artificialanalysis.ai Midjourney baut Medical-AI für Ultraschall - theverge.com Wired Dialog Thiel - wired Reddit-Leak: Mitglieder von Peter Thiels Geheimclub - reddit.com NYT: NAACP klagt gegen xAI wegen Grok-Gasturbinen in Mississippi - nytimes.com Allbirds rebrandet zu SmartBird, neuer Ex-AWS-CEO - reuters.com Mistral - ft.com TechCrunch: ChatGPT-Marktanteil fällt erstmals unter 50% - techcrunch.com Sono Motors: Trump-Manager macht aus Solarauto-Firma Bitcoin-Bude - manager-magazin.de Trump Texts - wired 1Komma5° plant Börsengang & Frontalangriff auf Enpal - manager-magazin.de Stern: Jens Spahn in der Kritik nach Peter-Thiel-Treffen - stern.de

Herkese merhaba! Bu hafta yapay zeka dünyası kelimenin tam anlamıyla alev alev... Beyaz Saray'ın nükleer silah alarmına geçer gibi kısıtlamalar getirmesinden girdik , Çin'in Alibaba ve DeepSeek gibi devlerle bu duruma verdiği hızlı cevaplardan çıktık. Claude'un yeni MCP entegrasyonu sayesinde Photoshop ve çeşitli araçlarla bağlantı kurarak grafik tasarımcıları nasıl ihya ettiğini detaylıca anlattık. Bununla da kalmadık; Midjourney'nin sadece görsel üretmekle kalmayıp, ultrasonik ses dalgalarıyla çalışan ve MR çekimini bir "spa" keyfine dönüştüren yepyeni bir tıbbi tarama cihazı projesiyle Tıp dünyasına nasıl bomba gibi düştüğünü inceledik. Elon Musk'ın Grok hamleleri , Avrupa Birliği'nin 2 Ağustos'ta yürürlüğe girecek katı Yapay Zeka Yasası ve Meta'nın içeride yaşadığı büyük motivasyon krizi de masamızdaydı. Ayrıca yerli yapay zeka modelimiz TÜBİTAK Bilge'nin altyapısını ve Türk Telekom'un görme engelliler için geliştirdiği stadyum projesini de değerlendirdik. Peki sizce içeriklerde insan dokunuşu mu olmalı, yoksa yapay zeka da aynı tadı verebilir mi? Gerçekle yapay zeka arası sizin için fark eder mi? Yorumlarda kendi görüşlerinizi paylaşmayı unutmayın! Videoyu beğenmeyi, sevdiklerinizle paylaşmayı ve kanalımıza abone olmayı unutmayın, iyi seyirler! 00:00 - Giriş ve ABD'nin Nükleer Silah Statüsünde Yapay Zeka Kısıtlamaları 00:36 - Çin'in Hızlı Atağı: DeepSeek, Qwen ve Amerika'yı Tokatlamaya Hazır Veri Merkezleri 06:01 - Claude'dan Tasarımcılara Kıyak: MCP ile Photoshop Entegrasyonu 07:33 - Midjourney Tıp Dünyasında: MR Kalitesinde Ultrasonik Tarayıcı Spa Cihazı 12:22 - Grok 1.5 Video Modeli, Elon Musk'ın Destekleri ve Görme İmplantları 14:52 - Microsoft'un AWS'ye Geçişi ve Goldman Sachs'tan 7.6 Trilyon Dolarlık Yatırım Beklentisi 16:30 - Mistral "Le Chat" Yapay Zeka Memleri ve Test Tabloları 17:58 - Avrupa Birliği Yapay Zeka Yasası Geliyor: Şeffaflık Zorunluluğu ve Dev Cezalar 19:48 - Soyma Uygulamalarına ve İstismara Karşı Katı Avrupa Önlemleri 21:46 - Güney Kore'nin Endişeleri ve Yerli Yapay Zeka TÜBİTAK Bilge Tartışmaları 25:27 - Meta'nın Çöküşü: İşten Çıkarmalar ve "Cenaze Evi" Gibi Çalışma Ortamı 26:30 - Türk Telekom'un Görme Engelliler İçin Geliştirdiği Özel Stadyum Projesi 28:50 - Yapay Zekaya Karşı İnsanı Üstün Kılan Şey: Kusurlarımız ve Nüanslar 29:33 - Kapanış ve Yorumlarınızı Bekliyoruz #fable5 #claudemythos #yapayzeka

Aujourd'hui dans "Les voix de l'économie", Stéphane Pedrazzi reçoit Corine de Bilbao, directrice générale de Microsoft France, pour aborder les enjeux de souveraineté numérique qui préoccupent l'Union Européenne. Alors que 80% des produits et services numériques utilisés en Europe proviennent de géants américains, la question de la dépendance technologique est au cœur des débats. L'invitée, à la tête de la filiale française du géant Microsoft, apporte un éclairage nuancé sur cette problématique. Bien que Microsoft soit une entreprise américaine, elle souligne que le groupe s'est profondément enraciné en France depuis plus de 40 ans, faisant travailler un écosystème de 10 500 partenaires et 80 000 personnes. Pour répondre aux préoccupations de souveraineté, Microsoft a notamment mis en place un cloud souverain en partenariat avec Capgemini et Orange.Elle revient également sur la place de la France dans la course à l'intelligence artificielle, un domaine où le pays se distingue avec une adoption massive par les entreprises et les salariés. Elle évoque les atouts de l'écosystème français en IA, avec des acteurs comme Mistral, tout en soulignant que Microsoft entend s'appuyer sur cet écosystème dynamique pour développer ses propres solutions.Au-delà des enjeux de souveraineté, Corine de Bilbao aborde la question de la cybersécurité, un sujet majeur alors que la France est le deuxième pays le plus touché par les fuites de données. Elle insiste sur l'importance pour les entreprises de disposer de plateformes sécurisées, un défi que Microsoft s'efforce de relever.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Van een tuinbouwzoon wiens familiebedrijf failliet ging tot de oprichter van Europa's grootste arbeidsbemiddelaar — met bijna een miljard omzet, 27.000 werknemers en een Falcon 900 privéjet. Sponsors & Kortingen Probeer AG1 via drinkag1.com/doorzetters en ontvang 5 travel packs, Vitamine D3+K2 en de Welcome Kit gratis (t.w.v. €69) bij je eerste bestelling

AGENDA: 00:00 — SpaceX Completes the Largest IPO in History 03:45 — Elon Musk Adds a Warren Buffett Fortune in 24 Hours 20:45 — Anthropic's Claude Fable Launches Monday, Gets Banned by Thursday 25:00 — Washington Declares War on Frontier AI 39:00 — Europe's Sovereign AI Push Accelerates as Mistral Targets $20B 43:30 — Benchmark Admits Its Biggest Miss: Passing on the Model Labs 45:15 — Salesforce Buys Fin for $3.6B and Rewrites the SaaS Survival Playbook 1:02:00 — Adobe Beats, Raises, and Still Crashes as AI Fears Intensify 1:06:30 — Why Every Legacy SaaS Company Is Trapped in an AI Death Spiral 1:10:00 — The AI Acquisition Window Has Officially Closed 1:13:00 — Nvidia at 16x Earnings vs SaaS at 8x Cash Flow: Where Should Investors Be? 1:17:00 — The Great Rotation: Why Wall Street Is Abandoning Software for AI Infrastructure

Last 4 days before regular tickets sell out at AI Engineer World's Fair - this is the single biggest gathering of AI Engineers, Founders, Leaders, and Researchers in the world. Attendees get >$5000 worth of sponsor credits and talk tracks are looking FANTASTIC. Join us!The AI scaling debate always focuses on the question of “how do we get more GPUs?” but the better question may be: how do we make the most of ones we already have.The fact that a frontier lab like xAI could be running at sub-10% MFU (Model FLOPs Utilization) is just a hint at what the real problem may be.For context, older frontier-scale training runs were already much higher than 10%. GPT-3 was around 21% MFU. Gopher was around 32%. Megatron-Turing NLG was around 30%. PaLM reached around 46%. And our guest Anjney says best-in-class MFU today is closer to 60–70%.It's not necessarily that xAI is uniquely incompetent (it's clear they have talented folks) but rather the priorities may be flipped in the GPU arms race.While GPU access is a bottleneck, simply increasing CapEx won't automatically translate to better models as frontier AI is increasingly a systems problem: scheduling, utilization, networking, kernels, frameworks, data pipelines, parallelism, cluster reliability, and the thousand small decisions that determine whether your theoretical FLOPs become real training progress.From building Discord's developer platform and backing frontier AI companies like Anthropic, Mistral, Black Forest Labs, and Periodic Labs to now building AMP's independent compute grid, Anjney Midha has spent years close to the real bottlenecks of AI scaling. In this episode, Anjney joins swyx at Periodic Labs to unpack why the AI race is not just about buying more GPUs, why 95% utilization would have been considered an outage at Google, and why the next era of AI infrastructure has to be more aligned, more efficient, and more responsible.We go deep on AMP's vision for a compute grid that makes FLOPs flow like megawatts, the difference between full-stack AI labs and horizontal pooling, why AI data centers need community buy-in, and how compute markets could evolve into something closer to an independent system operator. Anjney also explains why DeepMind's unpublished research points to a market failure, why end-of-life prediction remains one of the most important AI applications he has thought about for fourteen years, and why “output maxing” may become a new discipline for frontier systems.We also discuss Anthropic's culture, why “luck favors the prepared mind” in coding models, how Claude cracked coding, why too much capital too early can make AI labs fragile, what Periodic Labs is trying to do with science and superconductors, why great researchers can become great CEOs, and why Silicon Valley is both deeply missionary and deeply mercenary.We discuss:* Why 95% utilization was considered an outage at Google* Why AI infrastructure waste compounds at frontier-lab scale* Why “move fast and break things” does not work for AI data centers* How data center backlash, power grids, and community incentives shape AI scaling* AMP's vision for making FLOPs flow like megawatts* Why compute needs an independent system operator* How interruptible demand and dynamic prioritization worked inside Google* Why DeepMind research hoarding creates negative externalities* AMP's 1.2GW base-load ambition and the need for 6GW of spike capacity* Why end-of-life prediction could become one of AI's most important healthcare applications* Frontier Systems, output maxing, and full-stack alignment* Why APIs and abstraction layers become lossy as organizations scale* Superconductors, standards, and the dream of lossless systems* SF Compute, open protocols, and the future of compute marketplaces* Why non-NVIDIA chips can still benefit from NVIDIA's reference architecture* Trust boundaries and why chip startups need visibility into future model architectures* Why VCs often underestimate researchers as CEOs* Scientists as star athletes of the mind* Why great CEOs need to be confrontational up and down the stack* Why leading the frontier matters more than “winning”* How Anthropic cracked coding* Why culture is fragile, not a permanent moat* Why hardship was a feature, not a bug, for Anthropic* Why Anthropic's P0 was coding from day one* Periodic Labs, physics as the constraint, and technical reality* Silicon Valley mercenaries, missionary teams, and what happens after a breakthroughAnjney Midha* LinkedIn: https://www.linkedin.com/in/anjney* X: https://x.com/AnjneyMidhaAMP PBC* Website: https://amppublic.com/* X: https://x.com/amppublicTimestamps00:00:00 Introduction00:00:09 Why AI Compute Is Being Wasted00:03:17 Responsible Infrastructure and Data Center Backlash00:06:07 AMP Grid: Making FLOPs Flow Like Megawatts00:12:41 Foundry, Frontier Labs, and Research Hoarding00:14:42 Gigawatt-Scale Compute and End-of-Life Prediction00:24:08 Frontier Systems, Output Maxing, and Alignment00:27:38 Compute Markets, SF Compute, and Non-NVIDIA Chips00:32:57 Trust Boundaries, Co-Design, and Researcher CEOs00:38:17 AI Coachella and First-Principles Thinking00:42:43 Leading vs Winning in Frontier AI00:45:54 How Anthropic Cracked Coding00:48:25 Culture, Hardship, and Anthropic's P000:54:03 Periodic Labs, Physics, and Silicon Valley Mercenaries00:56:26 Rishi Valley, Singapore, and Money as a Measure00:58:47 Closing ThoughtsTranscriptIntroduction: Anjney Midha, AMP, and Compute WasteSwyx [00:00:00]: We're in Periodic Labs with Anjney Midha, CEO, founder of AMP. Welcome.Compute Utilization: Node Allocation, MFU, and AlignmentAnjney [00:00:09]: Thanks for having me. At Google, there are two types of utilization usually, right? That you're measuring in these clusters. One is node allocation, and then the other's MFU. Node utilization is usually like what percentage of cards in the data center are just, used, and that, if it's not at, 95%-Swyx [00:00:29]: There is no excuseAnjney [00:00:29]: There's no excuse, right? I think 95% at Google, which is where my co-founder, Seb, came from, he built the Borg, PBorg/GQM scheduler at Google, and there I think 95% was considered an outage, so 96% node utilization is, should be standard. And most single-tenant clusters are not running at that. So that's one. And then MFU should be, I would say the best in class today is somewhere between 60 and 70%. I think this is a leadership question, right? Fundamentally it's an alignment question, which is are the people who are funding the cluster and then deploying the cluster actually aligned? And sometimes theoretically they are, but in practice the number of people in the chain, the supply chain between, the capital and all the way to whoever's managing the cluster and then whoever's measuring what the output is, are just so many, degrees of separation away that, the, The Have you ever heard the radian metaphor, which is at the beginning of an arc, if you have two arcs that are two lines that are just off by a few degrees, that-Swyx [00:01:33]: It spreads outAnjney [00:01:34]: It spreads out, right? Or at scale. And I think what's happening is a lot of cluster implementations and infrastructure, a lot of frontier labs and other teams, that's what's happening, is they're, they initialize the plan, which is kind of like North Star with a team that wants to do good, but then they're, required to scale so fast instead of iteratively that the wastage just compounds really fast at scale. And so I think we know the answer, which is just do iterative bring ups. If you spend time with people who've been in the semiconductor industry or the DSN industry for a long time, this is not new, and I don't think AI should be an excuse. Sure. Something What is new? Okay. We have a lot of new capabilities, but that doesn't mean just abandon common sense. Common sense should always be in fashion. ? AI scaling doesn't change the in fact, if anything, AI scaling should be putting a premium on the value of common sense and infrastructure because the margin of error now is so much lower and the costs of wastage are so much higher. And the cost of wastage, by the way, is not just economic. I'm, obviously I'm, I'm an investor, or I'm an investor by background. Over the last few years now we're running an AI infrastructure business called, AMP. And I think that it's okay to say this time is different on the capabilities front. We are genuinely getting capabilities at, of the, of a kind we haven't had before. That doesn't give you an excuse to say this time is different for everything, especially infrastructure. So look, I love the hacker mindset and the hustler mindset. Now, that's great for the startup mindset, but you remember this moment where Zuck went from saying, “Move fast, break things” to, move-Responsible Infrastructure and Data Center BacklashSwyx [00:03:10]: Fast and stable infrastructureAnjney [00:03:11]: Move fast with stable infrastructure. I think now we need to move fast with, responsible infrastructure. People are going to ask where the impact is. There was a really In our class yesterday, Scott Nolan, who's the founder of General Matter, came by at Stanford to speak about energy bottlenecks. And he had a phenomenal idea. He said, “if you look at the marginal unit economics of compute per hour,” he goes, “let's call it, $4 an hour. If you're having to bring up a new data center in a new community, why not just say we're going to charge 4.50 an hour, and that marginal impact or that marginal increase, we just literally take that and give it to the local community as cash?” I can tell you as a customer of that compute, I would love that. I'd be happy to pay an additional 50 cents per hour at scale.Swyx [00:03:57]: Wow. Yeah.Anjney [00:03:58]: Because if that means the public benefit is so clear to the communities that the data centers are coming up in, I'm going to feel like that compute is much more reliable. Up to 20% of all data centers this year in the US, my understanding is are at risk.Swyx [00:04:13]: Of community backlash?Anjney [00:04:14]: Correct. Of not getting the community support they need to get brought up.Swyx [00:04:19]: Wow. That's a huge number.Anjney [00:04:20]: Yeah. Now, we, I think we should dig into what that number is. I think it's a little bit of overstated. These things can get over-reported, but it-Swyx [00:04:27]: They don't just care about jobs. They care about all the other stuff around it, right? They care about power grid, they care about environments-Anjney [00:04:33]: Power grid, permitting, and so on. And imagine I think if you said there's a new AI deal. If we're bringing up a data center in your community, we're actually going to reduce the cost of your electricity bill. Okay, now we're talking. Right? The community's going, “Okay. Now this is a deal. I feel like a partner in this.” Right now that's not happening. There will be audits, there will be investigations, and when the, when the regulators come, I don't know when it's going to be, the folks who are moving fast and breaking things in the name of AI progress better be prepared. That's certainly not how we're procuring compute. Or we're, we're trying as much as we can to work with partners who have long-term track records. Many of whom, by the way, are not, AI providers. I think this whole idea of neoclouds being somehow this new category is a lot of marketing speak. There are really good, reliable, trusted data center providers in America who've been around 20 plus years. I love those folks. They know how to Sure. Are they sponsoring happy hours at NeurIPS? No. Are they legibly listed in Build? No. Are they hanging out in my, in, situational awareness parties? No. But they're adults. I trust them.Swyx [00:05:44]: They can run LAN. They can run power.Anjney [00:05:45]: They can run LAN, power, and shell. They have credit histories. We sit down, we have a conversations. Many of them live in Silicon Valley. They've, they've had to deal with the boom and bust cycles of the internet, and I love those folks. They are stable infrastructure partners and thinkers. And I think there's a lot of short-term thinking going on in the compute layer, and it's going to catch up to us. It's not going to be good.AMP Grid: Making FLOPs Flow Like MegawattsSwyx [00:06:07]: You talk about aligning incentives, and, I would think that aligning incentives means you have the full stack in one company, which is xAI and OpenAI, right? So you as a standalone infrastructure layer, why are you somehow more aligned to your portfolio companies than people who just own the whole thing?Anjney [00:06:28]: In systems design, right, there's, there's two regimes of, architecture, right? You have integration, and then you have pooling and utilization, right? So the Or rather, the way to increase utilization often is you can do systems integration where you collapse a lot of process into one node, or you can pull out a process from a node and share that amongst various That resource amongst several different nodes. And so we see the AMP grid, which is, the, what, the system we're building here, which is basically a compute grid. We're trying to do for compute what the electric grid-Swyx [00:07:02]: PowerAnjney [00:07:02]: Yeah, what the power grid did for electricity. It-- this is a pooling and utilization layer across clouds, And so we're actually the opposite of a full stack integration like approach.Swyx [00:07:12]: Super horizontal.Anjney [00:07:13]: Where it's much more horizontal and it's, it's multi-cloud, it's multi-silicon. The goal is to try to make FLOPs flow like megawatts, and that is very hard to do today for many reasons. There's stranded pools of compute all over the place and there's no fungibility. And so right now we do it at the level of scheduling, and we often do it at the economic layer. But as we start to announce what we're working on, it's extraordinary like how many folks are coming out of the woodworks and saying, “Hey, I'm actually working on a way to make compute fungible at this part of the stack and that part of the stack.” And as a grid, we'd like all of these folks to participate on the grid. There's, people often ask me, “Andra, are you a new cloud?” And I go, “No, actually neoclouds are suppliers.” sometimes they'll ask, “Are you a venture capital firm?” I go, “No, actually they are, they are demand like sort of off-takers of the grid.” We see ourselves as what's called an independent system operator. So if you study the history of the electric grid, once it became legible to a lot of factories and industrial sort of participants that, hey, actually it turns out pooling is a good idea. We should pool our generators instead of all having a generator running at half capacity in our backyard. There was a need for an independent entity who could coordinate all these parties. Transmission line, power generation, facilities, transmission lines, factories, and that neutral coordination mechanism is very critical. In order-- If you study like the history of grids, the most enduring ones were those that never owned their own assets. They were ones that had, or often started with long-term anchors who are uncorrelated sources of demand, a steel factory, a shoe mill or whatever in a particular town who weren't competitive, where the steel factory want to spike up at night, the shoe mill wanted to spike up during the day. So then you pool and you share, right? So each of you is guaranteed some base load, but then you kind of schedule your spikes to drive a peak utilization across the town. The gold standard, so to speak, historically, has been these utility companies like PJM Interconnect in the northeast of America, where they, over many years became this what's called an ISO, an independent system operator of the grid. So that's how we see ourselves. Economically, that's what we are. From a technical perspective, we started at the scheduling layer because Seb and Mihai, who, run engineering here, built that at-Swyx [00:09:28]: Did your schedulingAnjney [00:09:28]: They did that at Google. And, -Swyx [00:09:32]: And you have infra shops from Discord as well.Anjney [00:09:35]: I have some.Swyx [00:09:35]: I don't know, I don't know if Discord is like the primary identity, but what-whatever, I'm just kind of-Anjney [00:09:39]: No, D-Discord was-Swyx [00:09:40]: Choosing a well-known name.Anjney [00:09:42]: Well, I So I was running the developer platform there. The internal infrastructure I was not responsible for. That was actually a guy by the name of Mark Smith, who was extraordinary. And yes, Discord did pool So Discord is actually a counter example. I had the chance to learn a lot about fully, full stack infra there because-Swyx [00:09:56]: It's the same thing, yeahAnjney [00:09:57]: It's the, it's the other architecture which is, Discord built its own WebRTC vo-voice and video infra. So like Discord did not use-Swyx [00:10:08]: For the calls, yeah.Anjney [00:10:09]: Yeah, did not For communication, Discord did not use third party infra. It was all built in-house. And then the way you maximize utilization was you pool demand from the world's 200 million plus monthly active gamers, right? And so that's, that's how those stacks were constructed. Again, in systems design, the two concepts that keep coming up over and over again are abstraction and composition, right? And-Swyx [00:10:31]: Bundling and unbundlingAnjney [00:10:33]: Bundling and unbundling, abstraction, composition, like verticalization and-Swyx [00:10:36]: HorizontalAnjney [00:10:36]: Horizontalization. So in that sense, AMP is an independent system operator of the grid. We pool demand, we pool supply from a number of partners we trust At about 1.3 gigawatt scale over four years. And then we pool demand from some of the world's best, research labs and so on. We're sitting at one, periodic labs who need extraordinary long-term demand. And the idea is that, each of them is guaranteed base load on the grid, but they can spike up and down flexibly on, for compute, with much shorter timelines as needed. That was roughly the design of the program I came up with at a16z called Oxygen. The same-- That was the same design of the GQM, BorgX, Borg GQM implementation at Google that Mihai and Seb had built. Which was that how do you allow, teams inside of Google, on the internal infrastructure to be guaranteed capacity, for their base workloads? But when they need to spike up on research, how could they ensure that was sufficiently there? And of course, the big innovation that was not discovered, but kind of implemented in the space, this infra space maybe three, four years ago at Google was the idea of interruptible demand, right? Where you just queue up a bunch of jobs and through this like sort of credit system, there can be a bidding mechanism.Swyx [00:11:53]: Like priorities.Anjney [00:11:54]: It's a dynamic prioritization Basically. And jobs can get interrupted based on somebody else who's saying, “what? I have 10 tokens, 10 credits I want to spend on this job.” Another like team lead, research lead is “Genie 3 or whatever is only worth five, credits, and NanoBanana2 is worth 10 credits,” and so the NanoBanana job gets priority. That's a, that's a made up example.Swyx [00:12:15]: It's very real. Brain Marketplace was real. And, we've, we've covered this on the pod with David Luan, who was-Anjney [00:12:20]: Oh, great. OkaySwyx [00:12:20]: Was there. And the criticism is that, well, actually sometimes you need central command to go all in on a thing. And actually sometimes capitalism via credits doesn't work. Not, this is not a criticism of AMP. I'm just saying, this is a thing that has been tried, internally within Google, and it led to Google missing GPT.Foundry, Frontier Labs, and Research HoardingAnjney [00:12:41]: Like, we structured ourself essentially very similarly to Google. We are structured as a holdings company. So, Alphabet holdings is Alphabet holdings, and then they've got these subsidiaries called Google and-Swyx [00:12:51]: Other betsAnjney [00:12:52]: Other bets and so on. We've got, AMP holdings, and we've got our infrastructure business, and then we've got a capital business called Foundry that incubates new frontier AI labs or invests in them as venture capital, like Periodic. We put a few hundred million dollars into Anthropic from our fund earlier this year. So wherever we feel like teams are making progress, especially researchers and so on who've pushed the frontier inside of existing labs like DeepMind, I find, there comes a point where they feel misaligned with the dictatorship of Alphabet holdings. And at that point, sometimes the dictatorship doesn't want them anymore. And they're “Thank you. You've done your job here. You've kind of helped us through the zero to one phase, and for whatever reason, we're going to deprioritize your amazing, omni model or whatever it is, and instead we're going to prioritize coding.” And, I think that's a tragedy, but I get it. They're Sergey and team are running their own business there. But that doesn't mean we the rest of us should sit around waiting for that progress to get unlocked for the rest of the world and humanity. If you think about how much extraordinary research has happened inside of DeepMind over the last 10 years, I, Demis and Sergey and those guys did such a great job. But at the end of the day, so much of that has never seen the light of day?Swyx [00:14:00]: Or they're like papers only, but they never actually shipped it to production or-Anjney [00:14:03]: What's worse is the paper is actually not even being published anymore ‘cause there's a six-month embargo inside of DeepMind, right? We've heard about this where a paper comes out, and then I think there's a six-month embargo window where if anybody on the business team says, “This could be interesting” It's embargoed for life.Swyx [00:14:18]: Exactly. So the stuff that gets published is the stuff that's not good enough.Anjney [00:14:21]: There's an adverse selection problem, basically. Yeah. At this point-Swyx [00:14:25]: It's, it's a common complaint at NeurIPS, by the way, that's “Well, why would I look at the papers that are the trash of GDM?”Anjney [00:14:31]: Again, I think it's a tragedy. I get it. They're running their business, but the rest of the I think there's negative externalities of research being hoarded, and so that'there's a market failure. And somebody needs to unlock that research, and we can't do it on our own. We only have 1.2 gigawatts of compute. That's nothing. That's about $40 billion of cloud spend. We're going to need a lot-Gigawatt-Scale Compute and End-of-Life PredictionSwyx [00:14:51]: By the way, is that's a new number. I haven't, haven't come across that gigawatt number. That's huge.Anjney [00:14:56]: Yeah. And to be clear, we haven't secured all of it. That's how much demand we have started to secure. I think publicly we haven't actually confirmed how much we have for this year. In order-Swyx [00:15:04]: Where do you want to get to?Anjney [00:15:06]: I think the steady state would be that we have a base load pool Of 1.2 gigawatts at all times Of base load capacity. For spike capacity, right now my estimate is we need roughly six gigawatts over the next four years for all our teams to feel like they were able to keep moving the frontier, whatever they're working on, whether it's, like superconductor discovery over here. There's a new investment we're working on right now, which is in the end of life prediction space in healthcare. It's extraordinary how much you can, you can give this was actually my graduate school work. I went to grad school for bioinformatics at Stanford Med. And I know we-Swyx [00:15:40]: Econ, MCS, bio.Anjney [00:15:41]: So my-- I was this really weird cat where, I was never satisfied with my major options. So at one point I was an econ major, then I was a CS major, then I was a MCS major called mathematical computational science, and they decided they were going to end that major. So I took all that coursework, and I applied it to grad school, my graduate degree in bioinformatics, which was the master's program, and then I thought I was going to do a PhD. I never ended up doing it. I dropped out and went to work at Kleiner. But I was lucky enough to apprentice with this professor at, Stanford Med. His name is Nigam Shah, and he was working on end of life prediction. Stanford is one of the only research facilities in America that has a longitudinal patient data set that's larger at scale. I think it's at least 12 million patient lives. The only larger data set is at the VA, the Veterans Affairs, of America. And to do research, like do any deep learning and so on that data set, it was called the STRIDE data set at that time, you had to be a Stanford Med School affiliate, which is why I went and enrolled in the bioinformatics department. End of deep learning was early. Nigam Shah had the visibility-- the vision to see that, you could do end of life prediction to help palliative care. In America, the, over 30% of all Medicare, Medicaid spend, at least at that time, was spent on end of life care. And what's we grew up in Asia, so we all-- Yeah, at least I won't speak for you, but I have A very different relationship with death than I find folks who grew up in America do. In America, spiritually and culturally, especially in Western societies where Christianity, the Christian tradition sort of frames death as this terminal point, there's often a judgment day and so on. The way we view death is with a finality. In Indian culture, in Hindu culture, death is one-Swyx [00:17:35]: Also, he's Buddhist as well.Anjney [00:17:36]: You're Buddhist, yeah. So it's one, it's one step in a journey of many lives, right? And so, I grew up in this city called Chennai in the south of India, and when people die, you dance on the street. There's like a procession where your body is carried to be cremated and your family, like celebrates and there's drums and so on. It's this huge thing. And, It's because the idea is that you're going to be reincarnated. You've been liberated from the responsibilities of this life, and now you're onto your next. It's a new It's like going off to a new college or whatever, right? And so it was so alien to me when I got here as an undergrad- That the medical system works backwards from that assumption that we have to view death as this terminal thing and delay it, postpone it's a bad thing. And so at the time, clinical decision support in the United States was this very primitive field. Even to this day, physicians in the United States often will tell you when you have a terminal disease, this is your, we've diagnosed you, which is great. Our ability to diagnose you is extraordinary. You have somewhere between six months to six years to live. What do you do with that information? The error bars are so high that then you In times of uncertainty, we default to culture, and when the culture is let's-- this is a bad thing, I've got to prolong my life, then you start doing things like And just to, just sort of from a systems perspective, what's going on there is Physicians often feel like they need to provide such high error bars because there's always some uncertainty in end of life diagnosis, and if you provide the wrong Diagnosis or recommendation to your patient, you can be sued for medical malpractice. And then your license can be taken away. It can be catastrophic for your career. In contrast, if in countries where that's not the case, what you often observe is that patients, physicians are quite prescriptive with their recommendation. They say, “Hey, this is your condition. The literature says that you probably have this much time on Earth left. My expert opinion is that you are an outlier or whatever.” And they try to be more prescriptive, and that empowers a patient, right? ‘Cause then a patient can say, “I trust my doctor. They said on average, I have six months to live, but if I do these things, I may have a shot because of my particular predispositions or my genetic history or whatever.” And that empowers you to go about your life in a actually more scientific way than leaning on religion, culture, spirituality, and so on. In contrast, here, because of that medical malpractice sort of thing looming over your head, a physician never gives you a clear recommendation. So instead you say, “Okay, Doc, well, let's try it all.” And then you start a whole regime of drugs and therapies, and then you often spend weeks and weeks in the hospital, and that deteriorates your quality of life. And when that deteriorates your quality of life, you instead of spending your last few days doing the things you love with your family, you're spending it on a hospital bed. And that ends up being thirty percent of Medicare and Medicaid. So it's worse for the patients. The doctors feel terrible. The American taxpayer is paying a huge amount of money. And so this is why Nigam Shah, who was this professor at Stanford, said, “Anjney, if there's “ I kind of sat down with him. I was this young, I'd, I was twenty-one, and I was “I want to work on a big problem.” He's “The big problem is end of life care.” And so we tried to do deep learning to say, to-- So we started trying to run deep learning on these tried patient data sets to say, “Could you have an AI system make a recommendation that is orders of magnitude more precise about how much time you have left once you've been diagnosed with a terminal condition than a human?” And then if we can get that precision to be high enough, then you can empower the patient. And it turns out the tech works. Like it's-- Once you get the data set, like RL works. Honestly, even regression models work. You don't need to get that fancy. At the time, we were just trying, doing like very simple neural nets.Swyx [00:21:54]: Simple solutions, yeah.Anjney [00:21:54]: Today, what we can do with RL is extraordinary. The problem remains then and now is regulatory, because you actually can't shift the burden of the wrong clinical diagnoses from the physician to the AI system. And so at that time, I got quite disillusioned ten years ago for, twelve years ago where, ‘cause I felt I just didn't have the resources to influence regulation. Today, I'm very lucky. I'm in a different place. I've, I'm a lot older, and so I've been spending a lot of time on my next incubation, which is how can we unlock the, patient empowerment by training AI models to do end of life prediction much, with much more precision and ac-Swyx [00:22:37]: Oh, wow. You're still focused on this the whole time.Anjney [00:22:40]: The-- I haven't been able to get, this out of my mind a single day for the last fourteen years. This is the hill I want, I would like to die on. There's two, I would say. What? I actually, I'd prefer not to die.Swyx [00:22:51]: Yeah, exactly.Anjney [00:22:52]: But I think two bipartisan issues, I think two issues that should be bipartisan in America are how do we empower patients to make the right clinical decisions at the end of their life, such that we're reducing the taxpayer burden with science? It's just good old science, and AI can help here. And the second is, net positive data centers, ‘cause I think that's the biggest critical bottleneck on training and good enough AI models to help people at the end of their life. So there's sort of two sides of the, of the same scaling bottleneck curve, but those two, we formed AMP as a public benefit corporation. My wife and I, who you've met, you've met Viv. Her passion is education. Her family is a long line of educators and so on, and, of physicists. And so this class is my attempt to stop being the black sheep of the family and be a, an educator. But if I'm not educating, the thing I would be doing is working, on these two problems, whether on the political spectrum or as a researcher back at, in some lab. And my hope is if anyone's listening to this podcast, if they're passionate about either of those two topics, I'd love to hear from them. We'll, we'll we can share the contact in the show notes, but, we're looking for people to join both of those missions on the, on the political side as well as on the medical side, on the research side.Frontier Systems, Output Maxing, and AlignmentSwyx [00:24:08]: You said, this is a discipline that you want to form. You call it's called variously called Frontier System. It's variously called One Person Frontier Lab. What is the ideal name or shape of this? Like the, what is the mission?Anjney [00:24:24]: Of the class?Swyx [00:24:26]: Of the discipline that you're, exploring, right? I The class is called Frontier Systems. But like for me, maybe one phrase is you're, you're just anti-waste, right? Which is wasting GPUs, wasting in human and Medicare. But is there, is there a broader theme that I'm, that maybe you can encapsulate more succinctly?Anjney [00:24:45]: Yeah. The, from an engineering perspective, it's very simple. It's output maxing. It's the, it's the department of output maxing.Swyx [00:24:51]: Making the most of what we have.Anjney [00:24:52]: Exactly. I'm a huge believer in optimal outcomes. I think both in America and other countries, we are losing our appreciation for nuance, and this is the thing of And AI is the same case, right? Oh, the bitter lesson holds. Okay, fine. But that doesn't mean you just like throw 500 GB300, 500,000 GB300s at your suboptimal model scaling and you waste a bunch of compute. It also doesn't mean that, the most optimal is to have like 50 different architectures where there isn't enough standardization. One of the reasons Anthropic has had extraordinary sort of velocity is ‘cause they picked the transform architecture and said, “This is simple. Let's double down on it,” right? And now luckily there's enough investment going to the space that we can afford other architectures, but at the time, investment was just too fragmented into other architectures, so that arguably unlocked scaling. So I think there's a philosophy. I think we all owe it to ourselves to do output maxing with a new capability called AI on a global level. I think if I was starting a new department at Stanford, depending on how fuzzy or technical I wanted to be, I'd probably call it the Department of Alignment. Like-Swyx [00:25:59]: It's an overloaded termAnjney [00:26:01]: But it is, But alignment really Is a hard problem. And I think when you unlock it, full stack alignment is super hard in any organization and in any system. Like in a, in a venture capital firm, if you can have full stack alignment between your limited partners and your, the founders who are creating the value and ultimately the public that owns the IPO stock, that is a gift that keeps giving. And when you study the history of these systems, when they start off, they usually start out small scale where the feedback loop is actually so tight that there's alignment. And then the more you try to scale, the more division of labor happens, the more specialization happens, and at each step you add abstractions. And wherever there's an API interface, there's like loss. There's communication loss. And so I think a really cool thing would be for us to figure out is there a way for us to have our cake and eat it too as an engineering discipline? Is there a way to actually scale up and scale out Without losing any alignment, without lossy transmission?Swyx [00:27:01]: You mean standards?Anjney [00:27:02]: So standards is one way. The other way is you just have net new capabilities. So like what we're trying to do here is discover new superconductors. A room temperature superconductor would be a lossless transmission mechanism for energy. We would have flying cars. We are right within a few years of having a new room temperature superconductor. So I think those are the two. You either have to standardize On protocols or API specs that allow lossless communication, or you can come up with a whole new capability that unlocks so much abundance, the standardization doesn't matter ‘cause you just unlock net new capacity. This, the, so this is what I spend my days thinking about these days.Compute Markets, SF Compute, and Non-NVIDIA ChipsSwyx [00:27:38]: No, I think every infra person at, who wants scale and wants to output max does eventually end up thinking about this. We don't have time to go into it, but we have done an episode with SF Compute-Anjney [00:27:50]: Oh, coolSwyx [00:27:50]: That is trying to standardize The futures contract for compute. I don't, I don't know how that's going by the way, but like at some point this will be public.Anjney [00:27:57]: Oh, I think Evan is awesome and SF Compute is the kind of effort that I hope we can accelerate because what often happens is these exchanges are very hard to get, they, it's hard to bootstrap them, right? Because they often require-- There's many inefficiencies between parties. There's trust boundary inefficiencies in infrastructure because you don't trust, one part of the stack doesn't trust another part of the stack to give them visibility. There's capital markets inefficiencies, there's operational efficiencies. So if you can inject like a single shock to the system of a ton of compute demand or supply, then you can accelerate, these new flywheels. And so my hope is one day, or soon, if SF Compute needs extra like has excess capacity, they just hook it up to the grid and they get flooded with demand from us. And on the other side, if they have a ton of demand but they don't have supply, they just again hook up to the grid and it's a two-way protocol where they can just hook up to our capacity. And I don't think we're too far from that. Today our working implementation of it is mostly through a group of labs, universities, and a few sort of trusted parties who are, who all feel like they're in alignment to borrow an over sort of used word. But our hope is to just have it be an open protocol that anyone can hook up to on-Swyx [00:29:20]: Hook up for demand or hook up for supply? In primarily demand, it sounds like. Like you-Anjney [00:29:25]: No, bothSwyx [00:29:26]: You would want to offer demand.Anjney [00:29:27]: Both. Yeah. Unfortunately, what's happened in the last six weeks is, we thought we'd have a bunch of excess capacity by the end of this year. It's all gone.Swyx [00:29:37]: It's exploding.Anjney [00:29:38]: It, yeah. It's all gone. And so I have, my text messages are full of friends, we know many of these people, these are founders who've raised billions of dollars in San Francisco going, “Oh, any chance you have like 50 nodes in the next few weeks?”Swyx [00:29:51]: What is the scope for, non-Nvidia, right? You have Lisa Su coming and, Rainer Pope as well. And so There is a lot of demand for, more performance Alternative architectures and all that. At the same time, this hurts your standardization.Anjney [00:30:11]: I don't think so. So actually Rainer's a great example, right? Rainer is a CEO and founder of, MatX. I actually had him by for office hours in the class earlier today, and there was an insight he brought up that I hadn't considered before, which is when they decided to pick the standard For their data center, they picked the NVIDIA reference architecture. So the MatX chips Just plug in to any site that has an NVIDIA bring up planned. And, the-Swyx [00:30:42]: It's just software then. It's, it's not the-Anjney [00:30:44]: A-Swyx [00:30:44]: Hardware.Anjney [00:30:46]: Well, from an input and IO perspective It's the same footprint as an NVIDIA rack.Swyx [00:30:52]: That makes sense.Anjney [00:30:53]: Where they have done, innovated a bunch from what I can tell is on systems co-design. Which is where a lot of the gains are to be had. And so he picked He was “Anjney, we, there's just so much work to do when you're building a new chip company.”Swyx [00:31:08]: Can't fight every front.Anjney [00:31:08]: You just can't fight on every front. So my question to him was, “Well, you're working on this new chip. Their tape-out is next year. What, who are you going to partner with to host the chips?” And he said, “Whoever will host them. That's just not, that's not my focus.” And I said, “But how did you “ you decided back to our earlier systems design question, he decided that, he didn't want to be a full, fully integrated chip provider. The bottleneck they're focused on is the logic die, and they, he feels they can crank out a ton of performance gains through co-design there. But then that means you delegate, to our question earlier, it, you he's the data center provider is a different part of the stack, and so then he's dependent on that part of the ecosystem to host his chips to get the performance gains to the customer. So now you have another abstraction, and you might have loss. So I asked him, “How do you prevent loss?” And back to your point, he said, “I just picked the NVIDIA standard ‘cause I didn't want to Like I wanted to piggyback off of an existing protocol.” And that, what's great about NVIDIA is that reference architecture is known.Swyx [00:32:15]: Open.Anjney [00:32:15]: It's open. They've published it. So Jensen's actually enabled someone like Rainer to build a chip company like MatX, and I don't see them as competitive. The compute demand is so high. Like, I don't I think NVIDIA's not able to meet the demands of production, so we just need more chips. And I think it's very smart what MatX has done, which is say, “We're just going to we're not going to innovate on the data center design ‘cause actually, thank you, Jensen, you've done all the hard work. Where we can innovate is somewhere else.” And I think that's, that's very healthy. I think that's how we unblock new bottlenecks. And my view is these, the, chip teams like MatX, who have arrived at the insight that co-design is the way, The primary bottleneck for them is trust boundary. To do co-design well, you need visibility into the next model generation as soon as possible ‘cause it takes two years to tape out. So if by the time I bring my chip to market, your model architecture's changed, I'm host. Now, when he was inside Google, he was sitting next to the Gemini team. He was on Palm or whatever.Trust Boundaries, Co-Design, and Researcher CEOsSwyx [00:33:19]: His co-founder was the, was one, was one of the Palm guys, I think.Anjney [00:33:23]: Yes. Yes, exactly. So when you're inside the trust boundary of Google, then your systems co-design loop is super tight. When you leave as a founder, one of the biggest risks you take is now you're outside the trust boundary. And so what I love doing is helping chip teams who can help us unlock more capacity for the independent ecosystem access to trust. Because when I If I've been, involved with a lab from day one, and I was lucky enough to work with Anthropic, and then I'm on the board of Mistral and helped Black Forest Labs get started. I think at this point I'm on six or seven different teams.Swyx [00:33:57]: Only six? I feel like my mental number was going to be 13, but yeah, it's-Anjney [00:34:02]: No, I go deep with one at a time.Swyx [00:34:04]: You're founding CEO of Arena.Anjney [00:34:07]: Nah, that was an, that was an-Swyx [00:34:08]: Administrative CEOAnjney [00:34:09]: It was an administrative five-month gig where Whalen and Anastasios were graduating from their PhDs, and they didn't need a product team. So I helped recruit the head of engineering product and design. But Anastasios has always been the CEO of that company. I played a pinch-hitting I'm an intern. I was CEO intern For five months. -Swyx [00:34:33]: I interviewed him, and he's he's very well-spoken. I think he's a debate, former debate, champion. But also very quantitative and mathematical, which is-Anjney [00:34:41]: He-Swyx [00:34:41]: Such a unicorn.Anjney [00:34:43]: See, what's amazing about him? If you look at his output, he's an output maxer. By the time he was graduating from his PhD, which he only graduated last year, he had published more work with a citation count than, people twice his age. But at the same time, he'd already started a project called LLM Arena that was being used by millions of people As a side project. And time and time again, what I've realized is venture capitalists suck at seeing human beings as, dynamic agents where-Swyx [00:35:14]: They want to put you in a boxAnjney [00:35:15]: They want to put you in a box.Swyx [00:35:15]: This is your thing.Anjney [00:35:16]: So the first time I got introduced to Anastasios, somebody had told me “Oh, he's amazing, but he's a researcher.” I was “what? What do you mean he's a researcher?” That's what-Swyx [00:35:28]: Like he's not a CEO, not a founder.Anjney [00:35:29]: Not a CEO, exactly. I was “Are you crazy? Do you Have you met Dario?” Dario's a scientist. He's gone from zero to, what will soon be a trillion-dollar company in four years. Being a CEO, nominally speaking, is not that hard. Being a good CEO is hard. Being a great CEO actually requires a level of performance that scientists who have already published at the top of their field have accomplished. It is super hard to be a competitive scientist. To publish in academia over the last 20, 30 years, to make it to the top of your discipline at a place like Berkeley, you are a star athlete. Like, you are an athlete of the mind, and you perform at the highest levels. And to get there, whether you're, Anastasios or Whalen at Berkeley, or you are Robin, who-Swyx [00:36:23]: BFL, yeahAnjney [00:36:24]: With Black Forest, who created Stable Diffusion, or if you're, like Guillaume at Meta, who created Llama before he started Mistral. The amount of human leadership you have to demonstrate to get the resources, like get the trust of the organization, publish it, put it up. I would just fund researchers all day Right? If who have contributed already to the field. If they've, if they've put SOTA out there, they're, they're star athletes already. If they haven't done SOTA Look, they can still be good CEOs, but then I find the failure mode is that they just don't want to be CEOs, they primarily want to publish, and that's okay, too. One of the things we do with the AMP Grid is we donate excess compute. We have two nonprofits, like university labs. We carved out like a couple thousand H100s. But I do think there's extraordinary research being done on university campuses. My father-in-law's a physicist. He's a professor. Extraordinary work in physics, and we need that. But if you want to be a CEO, what you need to be willing To do is be super confrontational, outside of science. Like within the scientific community, some of the best researchers are very confrontational about their convictions, right? This architecture is right. To be a great CEO, you basically have to be willing to be confrontational up and down the stack.Swyx [00:37:41]: To your own team.Anjney [00:37:42]: To your own team-Swyx [00:37:43]: To customersAnjney [00:37:43]: Hiring, recruiting customers. Well, I would say, Yeah, pretty much to everyone Everybody. Of course-Swyx [00:37:50]: I see, I feel a little bit of that in my own work, but yeah, I can't imagine the stakes that Dario has had to go through. It's, it's pretty insane.Anjney [00:37:56]: No, I don't think the stakes are that different From how you're feeling it, right? Stakes are personal scaling vectors, right? The stakes that seem so low to you, like having this podcast where you can talk to somebody and just have a you're an extraordinary communicator, right? Like already in this conversation, you've pulled more out of me than most people, and I've been on 12 podcasts in the last two weeks.AI Coachella and First-Principles ThinkingSwyx [00:38:17]: I think I, we've just seen each other enough that there's some base trust.Anjney [00:38:20]: There's base trust.Swyx [00:38:20]: And I think, and I know that you, that I've done my homework and like I know that trust is a big deal for you, so.Anjney [00:38:27]: I think trust is about consistency, and you and I have seen each other In the community for years, right? Like, I remember the first time we met was at NeurIPS in New Orleans. I don't know if you remember that, luncheon.Swyx [00:38:38]: Oh my God.Anjney [00:38:39]: Reiko had set up this Reiko's amazing, and he set up this luncheon and-Swyx [00:38:43]: Yeah, I was “Who's this Discord guy?” I'm “Okay.” But-Anjney [00:38:45]: No, you weren't-Swyx [00:38:46]: You were just “You made some investments.”Anjney [00:38:47]: You were much less polite. You were “Who's this VC?” You're like-Swyx [00:38:51]: No, I Was I? Oh my God.Anjney [00:38:53]: It was-Swyx [00:38:53]: I'm so sorryAnjney [00:38:53]: It was visible on your face.Swyx [00:38:54]: I'm so sorry. But you weren't, you weren't The introduction was bad. I was I didn't know who you were.Anjney [00:39:00]: The, see, this is the thing about context, right? Like, but then I think I heard your accent. And I was “Are you-”Swyx [00:39:06]: Singapore, yeahAnjney [00:39:06]: “Are you Singaporean?” And you're “Yeah.” And I said, “I went to high school, JC, in Singapore.” And then the ice broke. But This is the there are in the scientific community, sometimes the stakes are very high for people who haven't had the emotional, what is called EQ Coaching and mentorship, right? Which is like to have scientific impact, you often need to be a extraordinary emotional, like emotionally in tune person with the folks you're trying to influence. And so what comes so naturally to you is actually a super high stakes thing to other people. And so I wouldn't assume that Dario's more stressed out than you. These things are you'd be surprised how similar and small sometimes the problems are to you That some of the world's biggest, leaders are facing. And that's what I've learned from this class. The guest speakers are Sam, Satya, Jensen.Swyx [00:40:01]: AI Coachella.Anjney [00:40:02]: Yeah. It's AI Coachella, right? So we got to get all the headliners, and they're I'm very lucky that some of these people have either mentored me over the years or I've done business with them. And when you, take the performative stuff out and any assumptions you may have about these people that you read in the press or on Twitter, We're all just humans. We're all trying to get along. And what's so special about this moment is AI is forcing, like scaling, the bitter lesson is forcing a lot of people to revise their assumptions for how the world works and go back to first principles or go and educate themselves. So the kind of people I was, I won't name who this person is, but I was at an event last week in Texas and, ran to somebody who said, “Anjney, I came across the class. What do you think about real time action prediction models?” And I was, don't know how happy it made me feel when they asked me that question. I know they've done the work. They've challenged themselves. I'm, they didn't ask me, “What do you think of world models?” They said, “What do you think of n-”Swyx [00:41:04]: Real time action predictionAnjney [00:41:05]: “action, real time action prediction models?” World models, don't get me wrong, are cool and everything, but you and I both know that is a layer of abstraction that is sometimes not usefully precise enough. Right? Ours-Swyx [00:41:16]: There's like four different kinds of world models.Anjney [00:41:17]: Yes, exactly.Swyx [00:41:18]: We've done the part with general intuition, by the way, which is very focused on, -Anjney [00:41:22]: Oh, cool. Yes. I love Pim. Pim is great. And this is what I love about people who've done that level of work. They realize they're not in competition with people who the rest of the world thinks they're in competition with.Swyx [00:41:34]: Because they're not in the category, they're in the specific thing they're trying to do.Anjney [00:41:37]: They're focused on their mission, and they have a systems understanding of the bottleneck they're trying to solve. And when somebody else says, “I'm working on real time, action prediction models too,” Pim goes, “Oh, I love that person. I want, I can learn from them.” But the minute they're “Oh, that person's a world model person,” it's “like which type of world model person?” But mostly they're just trying to figure out if it's a waste of their time, because we don't have enough time. So, Pim, for example, is super, loves this other company I work with we've talked about called Black Forest Labs. And he's mentioned to me multiple times that he's so, He thinks what Flux is doing is really cool. Andy Blattman came by and spoke in the class. And what I find over and over again is for people who do the work, who can be usefully precise enough about like what is actually going on in the world of frontier research, The sense of camaraderie is still well and alive, but it gets lost sometimes when you have to like abstract The technical complexities in, business terms And then the VCs are “How are you different from that world model?” I'm going to say Where do I even start to explain this stuff? And then the misalignment creeps in.Leading vs. Winning in Frontier AISwyx [00:42:43]: This is good. Yeah, I think, people listening get a sense of, what it is like to operate at a real level, like yourself, rather than at, the journalist level, where you have to sort of put everyone in, a rough category and create a narrative of competition, and who's winning today, who's behind.Anjney [00:42:58]: It-- this idea of winning is so Weird to me.Swyx [00:43:03]: You do want to win. You want you want competitiveness.Anjney [00:43:06]: No, I think you want to lead.Swyx [00:43:07]: You want SOTA.Anjney [00:43:07]: No, I think you want to lead. Yes, so you want to push the frontier. You want to push the SOTA. You want to do something that hasn't been done before. You want to capture value, but you don't want to capture so much value that, people think you're unaligned with your mission or trying to do what's best for the world. You want to capture enough value that you can keep innovating, right? And I think that people want to lead, they don't really This idea of winning and losing, again, I love Jensen. He's a, he's a leader. The mindset that he talked about on Dwarkesh's podcast, right? He's “I didn't wake up with a loser mindset.” I think that was awesome, right? Because he's, he's an engineer. Dwarkesh has done the work. So there's at least-- even though the, to me, it was very obvious they're talking about the same thing, they just passed each other. They just had to basically, Jensen has this, five-layer cake abstraction of how the industry works. And Dwarkesh had, I think from that podcast, had more of, a pre-training, mid-training, post-training systems loop concept.Swyx [00:44:04]: It's just a factor of who he talks to, right? Again, it's very clear.Anjney [00:44:06]: It's the systems It's the abstraction, the mental models, the It's the whole-- Dude, so much of the problem in the world is reasoning by analogy. And then the assumptions that are held invisibly.Swyx [00:44:19]: Yeah, I've, I've said, this is actually the best time in human history for first principles thinkers. Because everything you think will happen is actually now coming true.Anjney [00:44:28]: Correct. And the venture capital community is, notorious for this, where people look-- In times of uncertainty, they, cling to axioms that ended up being true from the previous era, and they kind of like proclaim them with confidence as if they're truths, but they're not. And it's very important to see the distinction between a heuristic and an axiom. An axiom can be proven-Swyx [00:44:55]: Like from internal consistency point of viewAnjney [00:44:56]: With internal consistency. A heuristic is a way you kind of a shortcut. And my God, the number of people I have had to put up with over the last few years who proclaim-- use heuristics As axioms to judge people, to judge which companies are going to succeed or the number of people who are “Oh, yeah, Anthropic, they're just training models right now,” but this one continue.Swyx [00:45:22]: Because that's a B2B SaaS?Anjney [00:45:23]: Yeah, the, like Which over the fullness of time, if you squint at it, maybe. But the way you arrive there is so important that you can-- you just, you can dismiss people. Here's what happened, right? What happened is Anthropic basically achieved takeoff in October of last year. That training run-Swyx [00:45:41]: Whatever, three seven?Anjney [00:45:42]: I forget the numbers now, but whatever that checkpoint was-Swyx [00:45:45]: We saw the cognition.Anjney [00:45:46]: Yeah. Right? You probably-- The, to those of us in the community, especially once post-training was done and it was released in December-Swyx [00:45:52]: Yeah. Can I sneak a sneaky question in there? I don't know if you have a perspective, maybe you don't, I just The number one question is how did Anthropic crack coding, right? Because Claude One, Claude Two, okay, like it was part of it, but it wasn't a big deal. And the leading hypothesis, it's a lucky dice roll that was then compounded, right? Like it was like Mildly better, but then they saw it and they were “Okay, let's really invest.”How Anthropic Cracked CodingAnjney [00:46:17]: I had this very annoying teacher. I went to this boarding school called Rishi Valley in India, which is like this, bird preserve. It's like three hundred and fifty acres of bird preserve in rural India, and there was no technology for seven years. There was this teacher, I won't name them, but they would have this-- I hated it every time he said this to me. He was “Luck fa-favors the prepared mind,” which is like a common saying, but the way he delivered it, always grated me, ‘cause he was always I was always one of those kids who got, a good grade without trying very hard. ‘Cause like high middle school is not that hard if you, if you're generally, paying attention and so on. And there was this one time where I-- But then I would get an eighty percent grade, and he would keep pushing me to say “The reason you didn't get the ninety-five plus percent is because you're not that lucky.” And I would say, “What do you mean?” ‘Cause I would think that I deserved that grade, and I would sometimes argue with him. And he'd say, “You didn't have a prepared mind. If you want to get lucky again “ There was basically one time where I got like ninety-five or ninety-six on this, on this subject, and I, now that I felt entitled. I was “Okay, I'm going to keep doing this,” and I didn't. And then he was “Luck favors a prepared mind. You got lucky last time, but you got to stay prepared.” And I didn't understand what he meant. Now, as I'm older, I'm okay, these adults actually knew a thing or two. Anthropic has been the most prepared company for four years. And so then when the right, context data comes in, the right developers start sending in, the right context diffs, Sure, you could say you got lucky, but if you ask me, they're pr-pretty damn prepared with paranoia for like four years. And you have to remember, it was so hard for them to get going early on that they had to do so much more with so much less that you just have to be prepared to be so efficient.Swyx [00:48:06]: Yes. There's numbers on their burn compared to OpenAI. I've, I've written about it, but they are so much more efficient in their, in their tech stack.Anjney [00:48:14]: It's not even It's not funny.Swyx [00:48:14]: Not even close.Anjney [00:48:15]: Yeah. But it's so clear, right? Like how to output max for the world. They have been prepared, and you could call that luck, but Luck favors the prepared mind.Culture, Hardship, and Anthropic's P0Swyx [00:48:25]: This is one of those things that I was going over some of your old lectures and, you were data, people think it's a moat and actually it's culture and actually it's team Actually. And I, it's-- there's different levels of moats, and this is the ultimate one that determines everything else. Which you can then compoundAnjney [00:48:43]: You're saying culture is the ultimate moat? Yeah. But the thing about culture is it's very fragile. So moats, I don't think they're-- there's very few moats I found that are actually moats. They're-- It's, it's a nice concept, but in reality, you have to replenish your culture. Ben Horowitz was, the speaker in CS153 on Tuesday, and I asked him this question about the culture bottleneck in teams because, there are several AI teams-Swyx [00:49:09]: His book, Hard Things About Hard ThingsAnjney [00:49:11]: Hard Thing About Hard Things. But more concretely, there are so many AI labs today that have all the cash they need, they have all the compute they need, and they're still not able to ship anything SOTA. And then you start seeing people leave and so on, and my diagnosis, it's, is it's the culture. And so I asked him, Ben, they're-- He's been one of the most aggressive investors in AI labs. He goes back to this thing which resonates in my mind a lot. It-- When I used to work at a16z, I would, book a conference room, and right outside the conference room, which is closest to the toilet ‘cause it was the fastest way for me to go use the bathroom between Zoom meetings-Swyx [00:49:45]: Oh my God, I'll put maxing my toilet optimization. Okay, never mind.Anjney [00:49:48]: It was not healthy in hindsight, but maybe this is TMI. But anyway, outside that conference on the wall was this quote that was printed that said, “Culture is not a set of beliefs, it's a set of actions.” And it's by Bushido, is this, Japanese philosopher. And if you stop taking the actions that demonstrate the mission alignment to what you've said to your team and to your-- the world matters to you, then your culture starts to fray. So it's not actually a moat, I would say. It's a very brittle, fragile thing that requires daily tending to like a garden. But if you figure out the system to keep that garden tended, which I think ultimately comes down to knowing yourself ‘cause you most naturally, if you're authentic and so on, you'll naturally make trade-offs that seem effortless to you, but that reinforce your culture. And then That becomes this very hard thing for other people to catch up to. And at Anthropic, from day one, there was this mission like-- missionary like zeal and belief that, hey, these capabilities will scale. These systems are stochastic, not deterministic. There will be error bars, and until we crack interpretability, there's risk. And at some point, people will go-- stop using Claude just for coding. They'll use it in some mission-critical context where there's-- it'll throw off a bug, and then people are going to come blame them, and they want to be on the right side of history where they said, “Yes, this is a powerful technology. We think it's going to change the world, And we want to be very measured and scientific about the fact that, ‘Hey, guys, these are stats models, statistical models.' That's how statistics works.” ultimately, when you're training neural nets, it is just a statistical system. And I think that Belief that safety is important and that it might seem toy-like in the early days, and sometimes, you could say, “Anjney, they totally over-exaggerated the risk,” like two years ago when they said, “Let's not launch Claude One,” or whatever. Well, okay, maybe in hindsight, but hindsight is twenty/twenty. And at the time, they didn't know how that model would be used, and to them it felt existential if somebody came and said, “You weren't responsible. It-- This wrote a bug.” The liability associated with that is massive. So how do you prevent against that? Well, day in, day out, you say safety. And when you start deviating from that, you have the team hold you accountable, you have the world hold you accountable, and I think that becomes a moat over time. At some point, that moat will get challenged and so on, and then it become fragile. I hope it endures because that's the beauty of having founders run the show, ‘cause they can make really hard trade-offs to do mission alignment. The hardest part is in the earliest days when you don't have a group of people who are going through difficulty, stress, crisis together, then your culture doesn't get defined sharply enough, and that's what I'm worried about right now, is there's so much money going to these labs. There's no hardship. There's no-Swyx [00:52:50]: To anyone who knowsAnjney [00:52:51]: There's no to anyone who knows. And that, in hindsight, was a feature, not a bug for Anthropic. The number of people who said no, the number of people who said, “Sorry, we're all doing investors in OpenAI,” that is competitive difference. It forces you to really understand, what is the hill you want to die on at the expense of everything else. What's the P zero? And there, P zero from day one was coding. The reason, the mechanism system there was if we crack coding, Then we will crack AGI. Our mission is AGI. We want to get there safely. If we focus on codin

The Wall Street Journal reported that a $13 billion AI startup is betting on cheaper alternatives to OpenAI and Anthropic. Enterprises are shifting from pilots to production and seeking to control inference costs across support, copilots, and content workflows. Open source options such as Meta's Llama and models from Mistral enable targeted deployments with retrieval and fine-tuning to improve cost predictability. Procurement teams weigh SLAs, latency, security certifications, data retention, indemnity, and regional hosting against premium providers. Vendors distribute through AWS, Microsoft Azure, and Google Cloud marketplaces, while access to Nvidia accelerators influences performance and cost. Pricing includes per token and per seat plans, with some platforms routing simple tasks to lower cost models and reserving premium models for complex work. Founders are advised to build evaluation harnesses, track cost per outcome, and negotiate for predictable terms.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

Qué pasa, hacedor/a.Cada final de temporada de Haciendo Cosas tiene algo de ritual. Hacemos recuento, nos miramos los datos aunque duelan un poco, y contamos lo que ha pasado sin filtros.Este año, sin embargo, el cierre se siente distinto.No porque hayamos hecho más episodios, sino porque hemos hecho menos y nos hemos sentido mejor haciéndolos. Paradojas del hacedor.La quinta temporada en números15 episodios en total. La temporada con menos capítulos de la historia de Haciendo Cosas. También la que nos ha dejado menos agotados al llegar a junio. Y, para qué ocultarlo, la más rentable de todas.Sí, a veces publicar menos y apostar a algo concreto funciona mejor que el hamster wheel de “un episodio por semana pase lo que pase”.La gran jugada de esta temporadaPausar HC+ fue una decisión que daba un poco de vértigo. Teníamos 60 personas dentro, tres años de audios privados acumulados, talleres, comunidad en Telegram. No es fácil decir “paramos aquí”.Pero concentrar el esfuerzo en Más Listo que la IA, el programa sobre inteligencia artificial con el enfoque que nosotros le damos, ha resultado ser la mejor decisión que tomamos en mucho tiempo.Más de 100 personas ya han pasado por el programa. Para un proyecto que arrancó a finales de diciembre del año pasado, eso no está nada mal.Si tienes curiosidad, tienes toda la info en maslistoquelaia.com.El estado del podcast (con datos un poco tristes, aviso)Limpiamos la lista de Substack y pasamos de 3.600 suscriptores a 2.400. Eran lectores zombie, así que sin dramas, pero visualmente la gráfica pega un susto.Las descargas de audio llevan tiempo en decadencia. Y no es solo cosa nuestra: el formato podcast puro, sin vídeo y sin la maquinaria detrás, lo tiene muy crudo para crecer hoy. El propio Guillermo dice que cada vez escucha menos podcasts, y probablemente no sea el único.La buena noticia es que los episodios más relacionados con IA tienen picos buenos. Hay algo ahí pero no viene de las plataformas de podcasting.Y ya que estamos, hablemos de IAEn el episodio hacemos también un repaso rápido de cómo ha estado el sector estos últimos meses porque, oye, ha dado para mucho.También hablamos de los agentes (que han llegado fuerte en 2026), los modelos chinos open source compitiendo ya de tú a tú con los privados a una fracción del coste de API, y el meme del “Chatón Fat” de Mistral, que es básicamente Twitter convenciéndose a sí mismo de que existe un modelo francés todopoderoso que no existe.Escucha el episodio completo en tu app de podcasts favorita o en haciendocosas.online.Un abrazo grande y buen verano :)Guillermo, Víctor y el

Hey yall, Alex here, let me catch you up! I came back from vacation expecting to cover Fable 5 after a week of using it. The first two days after we all first got access to a Mythos level model were super exciting! But then the news hit, US Government issued an order banning Anthropic from giving access to Fable 5 and Mythos 5 to any foreign national, causing Anthropic to pull the models completely (even internally to their employees!). So, this wasn't the show I planned, but it turned into a great show about Open Source, as two models hit the top rankings and are both MIT licence, filling a Fable shaped hole in our hearts!GLM released 5.2 with folks really excited about it web building capabilities, and Kimi 2.7 Code released (and is available on CW Inference with crazy speeds!). We also saw the SpaceX IPO and Cursor $60B acquisition, Noam Shazeer joining Open and Midjourney, the image company, launching a new Ultrasound full body scanner to kill MRIs! Great show today with Dexter Horthy from HumanLayer, Chris Van Pelt and Adrian Swanberg from W&B announcing our new product HiveMind and Tanishq Abraham came back to help cover Midjourney's new Ultrasound scanner! Let's dive in!ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.The US Government bans Fable 5! (X, Anthropic statement)Here's a story in 3 parts: * Anthropic announces Mythos 5 preview - saying that this model is to dangerous to release, and only gives corporations access to it via project GlassWing. * Anthropic works hard on limitations and safery and releases Fable 5 (same weights as Mythos 5) built with guardrails so strong it refuses to do any cybersecurity tasks and switches back to Opus frequently* US Government receives a tip (reportedly from Amazon) that Fable 5 can be jailbroken to do cybersecurity tasks, and issues an order to Anthropic, citing national security concerns, banning them from giving access to Fable 5 and Mythos 5 to any foreign national, causing Anthropic to pull the models completely (even internally to their employees!)This is the first time that we see the US Government directly intervene in the AI space and restrict access to frontier models. The most updated reporting on this I could find is that Anthropic and US Government officials are in the process of negotiating a safe release framework. Given that preventing all jailbreaks is impossible, I hope they will land on a solution that gives me Fable 5 back!This hit especially hard because last week we were all high on Fable. Not in the usual AI Twitter benchmark sense, in the actual “oh, this is a different level” sense. Me and my wife Fable maxxed throughout our flight to Vacation. Peter had saved outputs he kept going back to because other models suddenly felt like a step down. Dexter later said it was the closest he had felt in a while to the old “I need to keep prompting this thing overnight” feeling.Peter Gostev made a point that stuck with me. It's easy for us in the bubble to call this ridiculous, and on the technical merits it kind of is. But if you've spent weeks telling normal people “this thing is like a nuclear weapon, it'll take everyone's jobs,” and then someone asks “okay, can you make it safe?” and the answer is “no, I can't,” then you can see how an outsider lands on “well, maybe you shouldn't have it.” His takeaway, and I agree: we need to be way more careful with the imagery we use, because the nuclear-weapon framing came home to roost.The bigger questions are the scary ones. Wolfram framed it as a sovereign AI wake-up call, and he's right. For the first time we're seeing a real gap in intelligence available to people based on their nationality. Imagine building a company on a model that an outside government can switch off with one letter. Peter pointed out it's commercially bad for the US but completely disastrous for Europe, which has basically one frontier lab and a pile of startups that suddenly look very exposed. And there's the obvious irony Nisten enjoyed a little too much: the Europeans who spent years lecturing everyone about AI restrictions just got restrictions imposed on them.If anyone in the government is listening: we want Fable back, please.SpaceX IPOs and acquires Cursor for $60B (X)SpaceX went and did the largest IPO in the history of the world, around seventy-five billion dollars, which on a roughly two-trillion-dollar valuation made Elon the first trillionaire. (Did anything materially change for him? No. He can still fly his private plane. There's nothing left to buy.) Three days later, SpaceX exercised its option and bought Cursor (Anysphere) for sixty billion dollars in an all-stock deal, paid in shares minted at the IPO and now trading around $211. The four Cursor co-founders are all billionaires now. Largest software acquisition ever, and for SpaceX it's barely a blip on the radar.Why are we covering a stock-market story? Because it's not really a coding-tools story, it's an AI story. Cursor gave away its IDE to a lot of people while collecting their data, then quietly became a training company with Composer. SpaceX/xAI was always strong on compute and weak on code, and the missing ingredient was exactly that kind of data. Now Composer 2.5 is already showing up rebranded inside the xAI stack, and if you pay for X Premium you can use it. Composer 3, trained on the Memphis supercluster, is reportedly coming very soon and is going to hit hard.Nisten's take was the spicy one. For the data alone it's worth it, because xAI now has insight into how essentially every enterprise that touched Cursor operates. And he had zero sympathy for the companies that assumed “no data retention for training” meant the data was actually gone. We see in legal cases all the time that deleted data is still there. His view: it should have gone open source.Cursor has over a million paying customers, $2.6 billion in revenue, projected to hit $6 to $10 billion by end of 2026. But here's the thing that matters for us, the AI coding angle. Cursor was one of Anthropic's biggest revenue pipelines because Composer runs on Claude under the hood. That pipeline is now owned by xAI. They're already jointly training Grok 4.3, a 1.5 trillion parameter model, with Cursor's proprietary coding data injected directly into pre-training, not fine-tuning. Pre-training. That's a fundamentally different thing. Composer 2.5 was already Pareto dominant on coding benchmarks before the deal closed. Now pair that with Colossus, the biggest GPU cluster in the world.Will this be enough to put XAI (now SpaceXAI) at the frontline of the AI race? Will Grok 5 be Fable level code? We'll find out. Either way, this is the most consequential AI acquisition we've seen. Period.Open Source AI GLM-5.2 takes the open source crown (X, Blog, HF, Docs)Z.ai dropped GLM-5.2 and it's now the strongest open source model for coding and long-horizon work. The headline number: 74.4% on FrontierSWE, which measures whether an agent can finish full engineering projects over hours. That trails Opus 4.8 by about one point and beats GPT-5.5. On Terminal-Bench 2.1 it jumps to 81% from GLM-5.1's 63.5%, which is a big leap. It's a 753B parameter MoE, MIT licensed, no regional restrictions, weights on HuggingFace. The 1M context window is real and usable, backed by a clever IndexShare technique that cuts per-token FLOPs by about 2.9x at full context. People are reporting roughly 8x cost savings versus Opus 4.8 for comparable quality on real coding tasks.The most interesting thing on the show was that this was a confusing release, in a good way. Peter put it well: normally a catching-up lab ships cherry-picked benchmarks and then independent testing deflates them. Here it's the opposite, almost every benchmark holds up, even crossing above Fable at certain points, and yet when he actually used it over a couple of days he wasn't blown away. His verdict, and I think it's the calibration we needed: this is clearly an amazing model, and the fact that it's open and you can run it is incredible, but it is nowhere near Fable, and it would frankly be implausible if a 700-odd-billion-parameter model matched a model that's rumored to be in the trillions. Though, I think the comparison to Fable is really really unfair, and the comments online seem to suggest that 5.2 from GLM is a banger model. Just looking at this Harvey benchmark on legal tasks from Vals, a benchmark that there's 0 chance Z.ai folks have seen! GLM 5.2 scores #3 on this benchmark! Just after Fable and Opus, and per TeorTaxes on X, previous GLM 5.1 scored an absolute 0% on this one! Where it genuinely shines is design. On Design Arena, which is a head-to-head ELO vote, people have been picking GLM-5.2's website designs over Fable's by a real margin (around 1360 to 1350). LDJ's framing is the one I buy: specialization is becoming valuable again, and GLM is clearly leaning into front-end design and taste. Wolfram added the necessary asterisk, every benchmark only tells you the model did well on that specific test, so “as good as Fable” should always carry the “on this benchmark, with these tasks” disclaimer. Fair. I'd just say this: I don't want to compare everything to Fable, because we can't even use Fable anymore. Compared to the models we can actually touch, GLM-5.2 is a fantastic deal.Kimi K2.7 Code from Moonshot (X, HF, Announcement)The other big drop. Kimi is the darling of open source while we wait on DeepSeek, and Moonshot shipped K2.7 Code, a 1 trillion parameter MoE built specifically for coding, available through Kimi Code and the API, with a modified MIT license. The standout for me isn't a single benchmark, it's efficiency: roughly 30% fewer reasoning tokens than K2.6, which matters enormously when you're running long agentic loops that burn tokens like crazy. Benchmark jumps over K2.6 are real (+21.8% on their Code Bench v2, +11% on Program Bench), though Peter and Wolfram both noticed something odd, on a few benchmarks including their Agentic Arena, the older K2.6 actually edged out K2.7. The likely explanation is that K2.7 is narrowly trained for code with reduced reasoning, so it may trade away some general capability. Moonshot themselves recommend K2.6 for general non-coding tasks. Also worth knowing: it's not multimodal, no vision, which is a real gap for coding these days. And thinking-off isn't supported, it's reasoning-on by default.The model is available on our CW Inference, with the fastest token streaming in the industry, over 280 tok/s (Announcement, try it), with very decent pricing $0.94 - $0.19 - $4.00 (input - cached - output) per million tokens. This Week's Buzz: W&B launched HiveMind

Aujourd'hui dans "Les voix de l'économie", Stéphane Pedrazzi reçoit Olivier Nollent, PDG de SAP France. Ce dernier nous plonge au cœur des enjeux stratégiques de l'intelligence artificielle et de la souveraineté technologique européenne.Présent au salon VivaTech, l'invité partage son analyse avisée sur les deux thématiques phares de l'événement : l'essor de l'IA à grande échelle dans les entreprises et la nécessité pour l'Europe de développer sa propre souveraineté dans ce domaine. En tant que représentant d'un fleuron européen des logiciels de gestion, il nous éclaire sur la transformation profonde que connaît son secteur face à l'arrivée de l'IA.Loin de voir cette révolution technologique comme une menace, il y voit au contraire une opportunité pour SAP de renforcer son expertise et sa valeur ajoutée auprès de ses clients. Grâce à sa connaissance approfondie des processus métiers, le groupe est en mesure de développer des agents IA spécialisés et adaptés aux besoins spécifiques de chaque entreprise, offrant ainsi une alternative aux modèles de langage généralistes et coûteux.L'actualité brûlante de la suspension par Anthropique de l'accès à ses derniers modèles d'IA à la demande des États-Unis illustre de manière saisissante les enjeux de souveraineté qui se jouent autour de cette technologie. Olivier Nollent souligne avec force la nécessité pour l'Europe de se doter de ses propres champions dans ce domaine, à l'image des efforts menés par SAP en collaboration avec Mistral en France.Au-delà des investissements dans les infrastructures de calcul, le dirigeant insiste sur l'importance cruciale de développer des logiciels et des modèles d'IA souverains, seuls garants d'une véritable indépendance technologique. Dans cette optique, il appelle à une mobilisation accrue de la France et de l'Allemagne, deux piliers de la souveraineté européenne.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Claude's Fable 5 just got yanked, and the story why keeps shifting by the hour. A contested jailbreak, an export-control, crackdown, and a lot of fingers pointing. This week on AI For Humans, Anthropic's Claude Fable 5 is still unavailable and the explanations keep changing. We dig into the contested jailbreak report, the export-control directive that pulled it, and the reporting that Amazon raised concerns before the crackdown. Then we get into why this matters far beyond one model: what happens when the government steps into the AI world, why Fable 5 was such a leap, and what it signals for whatever comes next. Plus, Epic's game designers are using AI tools alongside artists and the internet is furious, Disney Imagineering is testing Adobe Firefly in the parks, ChatGPT's market share slips under 50 percent for the first time, a fake Mistral model called Le Chaton Fat takes over the internet, and PJ Accetturo breaks down exactly how he made his viral AI short film with prompts. THE BEST AI WE EVER USED IS BEHIND BARS. AND NOW WE WAIT. SHOW LINKS Original Anthropic statement on Fable and Mythos access https://www.anthropic.com/news/fable-mythos-access Full timeline of the Anthropic, Amazon, and White House story https://www.axios.com/2026/06/13/anthropic-amazon-white-house Amazon CEO reportedly raised Anthropic model concerns before the government crackdown https://techcrunch.com/2026/06/13/amazon-ceo-reportedly-raised-anthropic-model-concerns-before-government-crackdown/ Simon Willison on the contested Fable jailbreak report https://x.com/simonw/status/2066722034491789720 ChatGPT market share slips below 50 percent for the first time https://techcrunch.com/2026/06/16/chatgpts-market-share-slips-below-50-for-first-time/ GPT-5.6 next week? Polymarket odds https://x.com/Polymarket/status/2066644087340495081 Possible new ChatGPT voice mode leak https://x.com/testingcatalog/status/2066919098236146167 Space X Buys Cursor https://www.cnbc.com/2026/06/16/spacex-spcx-cursor-acquisition-ipo.html Epic explores using NanoBanana and GPT-Image-2 in workflows with humans https://x.com/UnrealEngine/status/2066686216779509850 SEGA's Crazy Taxi AI statement https://x.com/SEGAInforment/status/2063990392085766622 PJ Accetturo breaks down how he made his three minute short film with prompts https://x.com/PJaccetturo/status/2066582776934289438 Le Chaton Fat, the fake Mistral model that took over the internet https://x.com/AlexanderKnigge/status/2066267845546442762  

La periodista de Onda Cero se ha detenido en el encuentro que mantendrán los líderes de las principales potencias del mundo con los CEO de Anthropic, OpenAI, DeepMind y Mistral, en el que determinarán el destino del mundo.

Today, we are learning from Mila Aliana. Mila works in the messy, uncharted spaces where complexity lives, across industries, sectors, coalitions, and multi-stakeholder systems, where things are no longer working and no one quite knows how to navigate what's next. Mila tends to work at the level of patterns and relationships, helping people see what's really shaping behaviour beneath the surface, not just what's visible. Her practice has been shaped by working across very different contexts, from government and global consortiums to sitting with indigenous elders, and Mila brings that into how she holds spaces for people to sense, relate, and move differently together. At the moment, she is closely involved in stewarding the transition of the Inner Development Goals ecosystem, staying with the tension between structure, culture, and what it actually takes to shift how we lead and work. Let's get started... In this conversation with Mila Aliana, I learned: 00:00 Intro - how we met and why I invited Mila Aliana 04:00 How do you become a weaver? 07:00 When we say system, it is relationships that weave together. 08:55 Time is my kin (family) 10:10 Wayfinding is the orientation. 17:25 Control is a coping strategy when we face uncertainty. 19:30 Wayfinding and weaving in the no-map territory. 21:35 Learning from sensing and knowing, and how can it be supported by science? 22:30 We are all participants in life, not answers. We are all relational. 25:20 The land is not a resource; it is our relative. Time is our kin. 25:40 I am part of the relay team that passes down to the next generation. 29:35 The fundamental question: Does it actually matter? 30:10 How do you make it possible for others to become the best version of themselves? (this part is important to me) 32:50 Does it matter to you that you know what the impact is? Why does it matter to you? 35:10 How do we make a living from this work? (important section) 36:10 If I create value, money will follow. 37:55 Translate what you work into something that people can pay for in their language. 40:10 Go where you are invited. 42:40 Separate survival from your purpose. 43:05 Design for mutual reciprocity and not transactional relationships. 45:45 Four criteria for mutual reciprocity in living systems. Does it give mutual benefit to each other? Is it complementary? Are you adaptive to change? Is it readily available? 53:30 Using the spiritual level in the decision-making. 56:55 The trust cultivated about boundaries. 58:05 The misunderstanding of purpose in your work. 1:06:40 Mila asks Erno what he will use tomorrow based on what he has learned in this conversation. 1:09:10 A before and after embodied experience in a workshop or meeting. 1:12:55 Experimentation and adaptive action. 1:15:30 Working in collaboration in a participatory process. More about Mila Aliana: https://www.linkedin.com/in/milaaliana/ Resources we mention: Arnold Mindell, a quantum flirt The Transition working group - for the transition of the IDG organisation. Barry's Economics - YouTube channel by Barry Ferns Diary Of A CEO Is Making You Less Successful - Barry's Economics Vibe by Mistral (formerly Le Chat) De Trias Economica - book by Babette Porcelijn Zo krijgen we een economie zonder verborgen impact – Babette Porcelijn Chantal Walg IDG Guide IDG skill finder Video of the conversation with Mila Aliana https://youtu.be/QwbVoipQQ9Q Watch the conversation here https://youtu.be/QwbVoipQQ9Q Summary (created with AI) In episode 492 of the Decide for Impact podcast, host Erno Hannink interviews Mila Aliana about working in complex, uncharted multi-stakeholder systems and her role as a “chief weaver.” Mila explains weaving as making visible the relational dynamics, patterns, narratives, and intergenerational tensions that shape behavior in living systems, and wayfinding as sensing an inner compass to move without a clear map by listening to emergence rather than controlling outcomes. They discuss how silence and culture co-create toxicity (including reflections on rising fascism), how humans are participants in interdependent systems rather than in control, and how impact matters through relationships and ripple effects without needing recognition. Mila shares practical guidance on earning a living through boundaries, creating value, translating work into clients' language, building trust-based mutual reciprocity instead of transactional funnels, and choosing projects via deep knowing; they end with applying “before/after” experiences to introduce IDG work and experimenting through collaborative events and questions. Transcript [00:00:00] Erno Hannink: Hello, and welcome to episode 492 of the Decide for Impact podcast. Today, you're listening to the conversation with Mila Aliana. Mila works in the messy, uncharted spaces where complexity lives across industries, sectors, coalitions, and multi-stakeholder systems, where things are no longer working and no one quite knows how to navigate what's next. [00:00:29] Erno Hannink: Mila tends to work at the level of patterns and relationships, helping people see what's really shaping behavior beneath the surface, not just what's visible. Her practice has been shaped by working across very different contexts, from governments and global consortiums to sitting with indigenous elders, and Mila brings that into how she holds spaces for people to sense, relate, and move differently together. [00:01:00] Erno Hannink: At the moment, she is closely involved with stewarding the transition of the Inner Development Goals ecosystem, staying with the tension between structure, culture, and what it actually takes to shift how we lead and work. My name is Erno Hannink, and I share my knowledge, experience, and expertise with you. [00:01:21] Erno Hannink: I coach entrepreneurs so they make decisions that will help them to grow their impact. In this conversation with Mila, I learned so much about working differently based on relationships and how to make impact and how it does maybe impact my personal ego. Let's get started. Welcome in this new podcast episode. [00:01:47] Erno Hannink: Today, I'm talking to Mila Aliana [00:01:52] Mila Aliana: Yes. And- Thank you, Miguel. Very honored ... [00:01:56] Erno Hannink: yes, I am very honored that you're here, so thank you for being here. I got to know you... I've heard your name on several occasions when I w- in the, in the development goals environment. I was very active o- on the Global Practitioners Network. [00:02:09] Mila Aliana: Yes. [00:02:10] Erno Hannink: Uh, very active in my own community here that, that we organize meetings every month for, and, uh, then I finally met you in call last year- [00:02:19] Mila Aliana: Yes, that's right ... [00:02:20] Erno Hannink: when we had the conversations about the ambassadors, and I found that you were like a breath of fresh air and calmness in all these heated debates that were happening around ambassadors we need, and we need, we need this, and we need this, and- [00:02:34] Mila Aliana: Yeah [00:02:34] Erno Hannink: I was going like, "What? What are you, what are you doing?" I didn't understand what these people were just so mad about. [00:02:39] Mila Aliana: Yes. A- [00:02:40] Erno Hannink: and you were just very calm, asking questions, listening, bringing calm to the meeting, and I, I was very impressed with how you did then. I'm very happy that you were there, and even though you were just there a, a day and a half, you just, just very short, ha, like a breath of, a breath of fresh air. [00:03:00] Erno Hannink: So then I decide... I'm gonna just intro this, right? Yeah, sure. So then I decided to, 'cause I have this great project, also a large project that I'm working on right now. I'm building my new house with my wife, and so I'm doing all the installation work myself. I wanna be as much as I can with the build, with the builder. [00:03:19] Erno Hannink: It's bio-based. It's, it's w- wood. It's everything as, as good as I can afford. So I decided to l- dec- last December to say I'm gonna stop, uh, the Global Practitioners Network. I, I- Yeah ... have no space for the monthly meetings to- Yeah ... organize everything. [00:03:34] Mila Aliana: Yeah. [00:03:34] Erno Hannink: And then the request came along. We have this transition going on. [00:03:39] Erno Hannink: We need volunteers who w- is willing to help you. [00:03:42] Mila Aliana: Yeah. [00:03:42] Erno Hannink: And I felt the calling. I felt like I, I have to do this. I have to be part of this. Yes. I don't know how to find time, but I have to be part of this. Yes. So that's how we met again, because you were running this. But that's just an intro, a long one. [00:03:55] Mila Aliana: Yes. [00:03:56] Erno Hannink: But it's okay. It's an intro of how I got to know you and h- why I wanna have a conversation with you. My first real question for you is, and you call yourself a, a chief weaver. Well, somebody who's weaving. [00:04:09] Mila Aliana: Mm-hmm. [00:04:09] Erno Hannink: What does a weaver do, and h- how do you become a weaver? [00:04:14] Mila Aliana: So I think I'll start with how do you become a weaver? [00:04:20] Mila Aliana: It's really organically born because we are all weavers, uh, funnily enough. And it was just a conversation with, um, with one of my clients, and he says, "What do you actually do?" And I, I shared... 'cause normally when I have clients, they are-- it's very challenging for them to give me a label. I'm not a strategic advisor only. [00:04:45] Mila Aliana: I'm not a consultant only. I can also coach when I need to. But mainly big, huge collaborations, consortiums into really messy,...

La periodista de Onda Cero se ha detenido en el encuentro que mantendrán los líderes de las principales potencias del mundo con los CEO de Anthropic, OpenAI, DeepMind y Mistral, en el que determinarán el destino del mundo.Conviértete en un supporter de este podcast: https://www.spreaker.com/podcast/mas-noticias--4412383/support.ESCUCHAR RADIO 

In dieser Folge sprechen Rüdiger Trost und Tobias Schrödel über die spannendsten Entwicklungen der Woche aus IT-Sicherheit, KI und Digitaltechnik: Kommt endlich das Touch-MacBook? Die beiden diskutieren neue Hinweise aus macOS und warum Tobi schon seit Jahren darauf wartet. Ärger mit defekten USB-C-Ports und Apples Reparaturpolitik. Spam-Anrufe bekämpfen: Ein Hörer-Tipp zu PhoneBlock für FritzBox und Smartphone. Apple kündigt Verbesserungen für Siri, Mail-Suche und einen automatischen Passwort-Agenten an. Praktische Hilfe oder Kontrollverlust? Erfolg gegen Cyberkriminalität: Der Krypto-Mixer „Audi A6“ wurde stillgelegt. KI als Cyberwaffe? Die Diskussion um angebliche Exportbeschränkungen für leistungsfähige KI-Modelle und Europas digitale Abhängigkeit. Tool-Tipp: Lucid Notes als Teleprompter für Videokonferenzen und Aufzeichnungen. Neue Betrugsmasche an Parkautomaten: Statt QR-Codes werden gleich ganze Kartenterminals überklebt. Warum echte Domains von Sparkassen und Bahn oft wie Phishing aussehen. Zum Abschluss: Eine geblitzte Rollator-Fahrerin sorgt für Schmunzeln. -- Links zur Folge immer auf https://podcast.ichglaubeeshackt.de/ Wenn Euch unser Podcast gefallen hat, freuen wir uns über eine Bewertung! Feedback wie z.B. Themenwünsche könnt Ihr uns über sämtliche Kanäle zukommen lassen: Email: podcast@ichglaubeeshackt.de Web: podcast.ichglaubeeshackt.de Instagram: http://instagram.com/igehpodcast

Als Anthropic das leistungsstärkste KI-Modell Fable 5 auf Anweisung der Trump-Regierung innerhalb von Stunden abschaltet, wird etwas überdeutlich: Europa hängt am Tropf amerikanischer und chinesischer Technologiekonzerne, ohne Fallback und ohne eigene Infrastruktur. Don Dahlmann und Sascha Pallenberg analysieren, was die Abschaltung von Fable 5 politisch bedeutet, wie ein drohender KI-Handelskrieg zwischen USA und China Europa in die Zange nehmen könnte und warum die Abhängigkeit von US-Cloudinfrastruktur kein Trump-Problem ist, sondern ein Strukturproblem. Dazu: Eurooffice als erster Schritt, Mistral als Alternative, Linux als Blaupause, und die entscheidende Frage, ob Europa den Open-Source-Weg einschlägt, bevor die Tür zugeht. Ein Pflichttermin für alle, die verstehen wollen, warum KI nicht nur eine Technologiefrage ist, sondern eine geopolitische. 

Apple Intelligence au rabais en Europe : pourquoi ? • Web Summit Rio : gros plan sur la tech brésilienne • Anthropic bride ses modèles les plus sensibles • En France, Mistral AI contre les ayants droit • Le Canada veut limiter les réseaux sociaux aux moins de 16 ans • L'IA bouscule le droit, les médias et l'éducation • VivaTech se prépare à Paris.Avec Bruno Guglielminetti (Mon Carnet)Apple Intelligence : qui prive l'Europe du nouveau Siri ?Nous revenons sur la keynote Apple, marquée par l'arrivée annoncée d'iOS 27 et de nouvelles fonctions d'Apple Intelligence. Mais le vrai sujet, c'est l'absence de Siri AI en Europe : Apple accuse le Digital Markets Act, tandis que Bruxelles renvoie la balle à l'entreprise américaine. Derrière ce bras de fer, une réalité : des centaines de millions d'utilisateurs européens pris en otage. Zoom sur la tech brésilienne à l'occasion du Web Summit RioDepuis Copacabana, nous partons à la découverte du Web Summit Rio et d'un écosystème brésilien encore trop peu observé depuis l'Europe. Le Brésil apparaît comme un terrain passionnant pour parler souveraineté numérique, innovation locale et rapprochements possibles avec le Sud global. L'objectif : sortir du face-à-face habituel entre États-Unis, Europe et Asie.Anthropic : l'IA puissante, mais sous surveillanceNous revenons sur le sujet Claude Fable 5, présenté comme une version plus encadrée de Mythos 5, notamment sur les usages sensibles comme la cybersécurité ou la biologie. Les modèles d'IA les plus avancés ne sont plus seulement des produits technologiques : ils deviennent aussi des enjeux stratégiques, politiques et sécuritaires (EPISODE ENREGISTRÉ AVANT LE BLOCAGE DE FABLE POUR POUR LES NON AMERICAINS). Mistral AI face au droit d'auteurMistral AI dans la tourmente avec la loi sur le droit d'auteur de l'IA. Les médias et ayants droit dénoncent un pillage massif, tandis que Mistral craint d'être freiné face aux géants américains. Le débat oppose protection de la création et ambition de bâtir un champion européen de l'IA.Réseaux sociaux : le Canada veut protéger les jeunesLe Canada envisage d'interdire ou de limiter l'accès aux réseaux sociaux pour les moins de 16 ans. Bruno souligne les limites d'une telle mesure, déjà visibles dans d'autres pays : contournements, faux comptes et migration vers d'autres plateformes. Pour nous, la loi ne suffira pas sans un vrai travail d'éducation numérique.IA et justice : quand les hallucinations coûtent cherNous évoquons l'affaire d'avocats sanctionnés aux États-Unis après avoir déposé des documents contenant de fausses références juridiques générées par IA. L'épisode rappelle que ces outils peuvent aider les professionnels, mais qu'ils ne remplacent ni la vérification, ni la responsabilité humaine. Dans le droit, l'IA doit rester un assistant, pas une source aveuglément copiée.Médias et école : le faux débat du “sans IA”Nous discutons de la tentation de revendiquer des contenus “100 % humains”. Cette promesse nous semble trop simpliste, car l'IA peut aussi servir à corriger, traduire, comparer, entraîner ou donner du feedback sans remplacer l'humain. Le vrai sujet n'est pas d'interdire l'outil, mais de savoir comment on l'utilise.VivaTech à Paris : qui est l'invité vedette ? VivaTech 2026 aura lieu la semaine prochaine. Cette édition marque le 10ème anniversaire du salon parisien. L'événement s'annonce comme un moment fort pour la French Tech, avec de grands invités attendus et un contexte très marqué par l'IA. La semaine prochaine, le Debrief Transat se fera depuis Paris, en direct de l'écosystème tech français.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Apple réserve son nouveau Siri IA aux États-Unis et relance le débat sur la souveraineté numérique européenne • Mistral se met à dos les éditeurs de presse • VivaTech : 10 ans déjà ! • Reportage exclu au Web Summit Rio pour découvrir la tech brésilienne, ses fintechs, son IA et ses ambitions de souveraineté numérique⭐️ Découvrez Frogans à Vivatech 2026

Le piège des tokens Par Régis BAUDOUIN « Les premiers verres étaient gratuits, l’addition s’annonce salée. » En ce début juin 2026, le modèle économique de l'Intelligence Artificielle générative vit son premier grand retour de bâton. Après deux ans d’une guerre des prix féroce et largement subventionnée par le capital-risque pour capter le marché, les éditeurs de grands modèles de langage (LLM) opèrent un virage stratégique majeur. Face à des impératifs de rentabilité, OpenAI, Anthropic et Google ajustent leurs grilles tarifaires à la hausse sur leurs token et API premium. Pour les entreprises qui ont intégré ces outils au cœur de leurs applications de production, c’est l’alerte rouge : la dépendance aux tokens devient un gouffre financier. XY Magazine analyse les coulisses de cette inflation numérique et dévoile les stratégies pour reprendre le contrôle. L’inflation du token en 2026 Pendant de longs mois, les directions techniques ont été bercées par l’illusion d’une IA toujours plus puissante et toujours moins chère. Cette époque est révolue. L’entraînement et le fonctionnement des architectures de frontières (comme les générations GPT-5 ou Claude 4) se heurtent à un mur de coûts réels : la pénurie et le prix des puces Nvidia, ainsi que l’explosion des factures énergétiques et hydriques des data centers, un sujet que nous évoquions dans notre précédente édition sur la crise de l’eau. Sans évoquer les couts des composants comme la mémoire ou le stockage qui ont connu des hausse de 400% Les investisseurs exigent désormais des marges positives. L’inflation se répercute directement sur le coût des “tokens” — ces fragments de mots qui servent d’unité de mesure à la facturation des API. On ne peut pas soutenir des investissements de plusieurs milliard sans à un moment que les financiers demandent un retour sur investissement. Les fournisseurs de token agissent comme des dealers. Les premières doses sont gratuites pour vous accoutumer, ensuite il faut passer à la caisse. L’effet d’échelle : Pour une entreprise, le piège réside dans le volume. Si une startup dépense initialement quelques centaines d’euros par mois pour des tests de validation, le passage à l’échelle (analyse de milliers de contrats, agents autonomes de service client tournant 24h/24) démultiplie la consommation. À volume égal, certaines entreprises voient la facture de leurs appels d’API multipliée par trois en ce printemps 2026, menaçant directement la viabilité économique de leurs produits connectés. Dans l’actualité les exemple se multiplient d’entreprises qui ont consommé tout leur budget token en cours d’année. Comme Microsoft qui a annoncé arreter avec Claude code. Également, Chez Uber, le CTO Praveen Neppalli Naga a reconnu qu'en quatre mois, l'entreprise a consommé l'intégralité du budget 2026 dédié aux outils d'IA pour développeurs. La direction avait auparavant incité à « sur-utiliser » l'IA, avec des tableaux de bord internes récompensant les équipes les plus gourmandes. (source) Fournisseur / APIType de ModèleTendance Tarifaire (Mi-2026)Impact Stratégique pour l’EntrepriseOpenAI(Série GPT-Premium / o-series)Frontière / Raisonnement avancéEn hausse(Facturation au temps de calcul/Tokens de réflexion)Augmente considérablement le coût des tâches de logique pure et d’audit de code complexe.Anthropic(Série Claude Opus / Pro)Analyse de contexte massif / RAGStable à la hausse(Surtaxe sur les contextes longs répétés)Pénalise les applications qui injectent des catalogues entiers ou des liasses juridiques à chaque requête.Google Cloud(Gemini Ultra / Pro)Multimodalité native (Vidéo/Audio)Stable(Introduction de quotas stricts hors abonnement)Le coût d’analyse des flux vidéo ou audio en temps réel reste prohibitif pour un déploiement de masse.Écosystème Open Source(Mistral AI / Llama 3 / Phi-3)Modèles locaux / SLMCoût marginal proche de 0(Hors coût d’hébergement brut)Devient l’alternative mathématique et financière incontournable pour toutes les tâches standardisées. Le syndrome du Vendor Lock-in algorithmique Cette crise tarifaire met en lumière une vulnérabilité stratégique majeure : le verrouillage technologique (vendor lock-in). En se précipitant pour intégrer l’IA, de nombreuses entreprises ont construit l’intégralité de leur code, de leurs bases de données vectorielles et de leurs structures de requêtes (prompts) autour d’une seule et unique API propriétaire. Sans évoquer, en plus, le lieu de stockage des données et du code dépendant d’un hyperscaler qui peut aussi être un GAFAM. Rompre cette dépendance à la hâte s’avère techniquement complexe. Chaque modèle possède sa propre sensibilité aux consignes, sa propre gestion des contextes et ses propres biais de sortie. Migrer d’un modèle fermé américain à un autre ne résout pas le problème : cela ne fait que déplacer la dépendance. De plus, pour les entreprises européennes, confier leur intelligence métier à des serveurs tiers basés outre-Atlantique induit un risque de conformité juridique persistant face au Règlement européen sur l’IA (AI Act), tout en subissant de plein fouet les fluctuations du cours du dollar et du token. Dans cette tendance à la hausse des prix, il y a en même temps encore des offres bas cout. Les stratégies de riposte Pour ne pas subir cette inflation, les directeurs techniques (CTO) doivent abandonner le réflexe du “tout-API” et adopter des stratégies de contournement hybrides. [ Requête Utilisateur ] │ ▼ [ Routeur d'IA Intelligent ] │ ┌────────────────┴────────────────┐ ▼ ▼ [ Tâche Simple / Standard ] [ Tâche Haute Complexité ] - Classification, Résumé - - Raisonnement Avancé - │ │ ▼ ▼ [ SLM local / Open Source ] [ API LLM Premium Payante ] (Coût marginal = Zéro) (Usage minimal & ciblé) Le passage aux modèles légers locaux (SLM) La grande tendance de 2026 est à la spécialisation. Utiliser un modèle géant à mille milliards de paramètres pour classer des emails ou résumer des fiches produits équivaut à utiliser un semi-remorque pour livrer une lettre. Les entreprises se tournent massivement vers les Small Language Models (SLM) open source (comme les séries Llama de Meta ou Mistral de la pépite française Mistral AI). Déployés localement sur des serveurs privés ou chez des hébergeurs cloud souverains, ces modèles réduisent le coût du token à zéro : l’entreprise ne paie que l’infrastructure physique, qu’elle maîtrise de bout en bout. L’architecture “Multi-LLM” et les routeurs intelligents Plutôt que de choisir un camp, les architectures modernes intègrent un “routeur d’IA”. Ce composant logiciel analyse la complexité de la demande de l’utilisateur. Si la tâche est simple, elle est aiguillée vers un modèle open-source interne ultra-économique. Si la tâche exige un raisonnement logique de très haut niveau, elle est transférée vers l’API premium payante. Ce filtrage permet de réduire jusqu’à 70% le volume de tokens envoyés vers les infrastructures payantes. Le prompt engineering d’optimisation La sobriété numérique s’invite dans le code. Les développeurs apprennent à “dégraisser” les requêtes. Réduire la taille des instructions système, optimiser les exemples fournis au modèle (few-shot prompting) et nettoyer les historiques de conversation inutiles permet d’économiser de précieux tokens à chaque appel. En finance et en logistique, l’optimisation des prompts est devenue un levier d’optimisation financière à part entière. Une crise de maturité salutaire La hausse des prix des tokens marque la fin de l’adolescence de l’IA générative. Cette transition, bien que douloureuse pour les budgets IT, est une excellente nouvelle pour l’écosystème numérique. Elle force le marché à sortir de la paresse technique qui consistait à tout déléguer à des serveurs tiers. En 2026, la maturité technologique d’une entreprise ne se mesure plus au nombre d’API qu’elle connecte, mais à sa capacité à orchestrer sa propre intelligence, de manière locale, sobre et souveraine.The post La hausse des prix des tokens va forcer les entreprises à la sobriété first appeared on XY Magazine.

SpaceX priced the biggest IPO ever at $135/share, raising $75B and debuting at $1.77T. ShinyHunters exploited an unpatched Oracle PeopleSoft flaw hitting 100+ organizations, Mistral seeks €3B at €20B, MrBeast hit 500M subscribers, and SBF lost his appeal. SpaceX raises $75B in the biggest-ever IPO, pricing 555.6M shares at $135 each, giving it a market value of $1.77T (Bloomberg) Founders Fund's ~3% SpaceX stake is worth $50B+, Sequoia's ~1.5% is worth $20B+, and a16z will see its biggest return ever at $10B+ (Bloomberg) Some investors question SpaceX's valuation, citing its $4.3B loss on $4.7B in revenue in Q1, as well as concerns over space data centers (NYT) Oracle warns customers of a critical PeopleSoft flaw after ShinyHunters claimed breaches of 100+ organizations using PeopleSoft; Oracle has not issued a patch (TechCrunch) Sources: French startup Mistral AI is in talks to raise ~€3B at a ~€20B valuation; it was last valued at €11.7B during a funding round in September 2025 (Bloomberg) MrBeast hits 500M subscribers on YouTube, a record for the platform (The Wrap) Sam Bankman-Fried loses his bid to overturn his fraud conviction and 25-year prison sentence over the collapse of FTX (Reuters) Longreads As companies are hit by rising AI costs, they are increasingly using tools that tap cheaper models, including some from China, putting price pressure on OpenAI and Anthropic (WSJ) Sixteen economists weigh in on what AI will mean for the US economy, workers, and workplaces; only two expect AI to actually create more jobs (WSJ) Learn more about your ad choices. Visit megaphone.fm/adchoices

SpaceX startet mit einem ordentlichen Pop in den Handel. Tausende Mitarbeiter werden zu Millionären, Founders Fund und Andreessen Horowitz vermelden Rekord-Returns. Anthropic launcht Fable 5 und das Mythos-Modell für Testpartner. OpenAI plant laut Wall Street Journal drastische Preissenkungen für den User-Krieg mit Anthropic. China plant $300 Mrd. für nationalen KI-Ausbau über fünf Jahre. Xiaomi MiMo Code schlägt Claude Code in den gängigen Benchmarks. OpenAI übernimmt das Kieler Startup ONA, Mistral kauft das Linzer Emmi AI für eine Industrie-KI-Plattform und verhandelt selbst eine $20-Mrd.-Bewertung. Dario Amodei mit neuem Essay zur AI-Exponential-Politik. Oracle Earnings, Prometheus von Jeff Bezos bei $41 Mrd. Die Trump-Familie hat $2,3 Mrd. mit Krypto eingestrichen. Palantir verliert vor dem Zürcher Handelsgericht gegen die Zeitschrift Republik. Neura Robotics raised $1,4 Mrd. mit Tether als Lead. Landgericht München: Google haftet für seine AI-Overviews.  Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) SpaceX-IPO (00:08:04) Mitarbeiter-Millionäre (00:11:51) OpenAI/Anthropic-IPO-Outlook (00:15:31) Elon-Puppe vor der Nasdaq (00:16:13) Anthropic Fable 5 & Mythos 5 (00:19:54) OpenAI Preiskrieg (00:27:27) Token-Wert pro Abo (00:30:30) Messi für ChatGPT (00:34:48) China $300 Mrd. KI-Plan (00:37:31) Xiaomi MiMo Code (00:39:46) OpenAI kauft ONA (00:42:54) Anthropic: AI Exponential Policy (00:46:53) Oracle Earnings (00:48:07) Mistral kauft Emmi AI (00:49:08) Prometheus von Bezos (00:50:48) Trump Phone (00:51:22) Waymo Premier (00:55:40) Google Trade-Worker (00:57:08) Anthropic Claude Corps (00:58:37) Trump-Krypto-Scam (00:59:35) The Platform Group (01:03:48) Palantir vs. Republik (01:05:48) Mistral $20 Mrd. Runde (01:07:07) Neura Robotics Series C (01:10:47) NYT: China und Robotik (01:13:19) Google haftet für AI-Overviews Shownotes SpaceX-IPO zieht $70 Mrd. an Retail-Orders - bloomberg.com Founders Fund + Andreessen: Rekord-Returns aus SpaceX-IPO - bloomberg.com SpaceX Proteste - xcancel.com Anthropic launcht Claude Fable 5 & Mythos 5 - wired.com OpenAI plant drastische Preissenkungen für User-Krieg mit Anthropic - wsj.com Bitte manuell prüfen (petergostev-Post) - xcancel.com SemiAnalysis - xcancel.com China plant $295 Mrd. für nationalen KI-Ausbau - bloomberg.com ONA: Kieler KI-Startup raised - linkedin.com Anthropic: Policy on the AI Exponential - anthropic.com Oracle Q4 Earnings - cnbc.com Mistral übernimmt Emmi AI für Industrie-KI-Plattform - handelsblatt.com Prometheus: Bezos' Industrial-AI-Startup - axios.com Teardown: Trump Phone ist HTC U24 Pro in Gold - de.ifixit.com Waymo launcht Loyalty-Programm mit 10% Cashback - techcrunch.com Google launcht Trade-Worker-Initiative für KI - axios.com Daniela Amodei startet Anthropics Claude Corps - apnews.com Xiaomi MiMo Code schlägt Claude Code bei 200-Step-Tasks - venturebeat.com Trump-Crypto-Playbook: Family wins, Investors don't - reuters.com The Platform Group - manager-magazin.de Einstweilige Verfügung: The Platform Group vs. Manager Magazin - lhr-law.de Palantir - ft.com Mistral verhandelt $20 Mrd. Bewertung - bloomberg.com Bitte manuell prüfen (dreger-Post) - linkedin.com Neura Robotics schließt Rekord-Series-C - neura-robotics.com Chinas Humanoid-Robot-Schub - nytimes.com Deutsches Gericht: Google haftbar für AI-Overviews - thenextweb.com

Philippe Mizrahi is the CEO and Co-Founder of Linkup, a Paris-based startup building the web search layer for the AI era. Previously a Group Product Manager at Lyft, Mizrahi co-founded Linkup in 2024 alongside Denis Charrier, whose prior company Niland — one of Europe's first vector search engines — was acquired by Spotify, and Boris Toledano (ex-McKinsey). The company has raised over $10M in funding, including a seed round led by Gradient, and is backed by Seedcamp, Motier Ventures, and angel investors including founders from Mistral, Datadog, and Deel. Linkup's API powers AI agents at enterprise clients including KPMG, and holds state-of-the-art results on OpenAI's SimpleQA benchmark.AGENDA:• 00:00:55 - Phil Mizrahi and the bet that became Linkup• 00:04:07 - Why Linkup's original vision was wrong• 00:07:00 - The MVP mistake most founders never catch• 00:10:05 - Fundraise or bootstrap: what Linkup chose and why• 00:13:08 - What Phil looks for in a founding team• 00:15:50 - Why Linkup wins in a crowded AI market• 00:19:07 - How Linkup got its first customers• 00:21:55 - The market bet Linkup is building toward• 00:36:22 - The pricing psychology behind Linkup's strategy• 00:39:05 - Why most startups target the wrong customer• 00:42:07 - The growth loop that scaled Linkup• 00:44:40 - Running a global team before you're ready• 00:46:45 - What separates founders who execute from those who don't• 00:50:09 - What most founders still get wrong about AI• 00:53:25 - How AI rewrites the zero-to-one playbook• 00:56:36 - What Phil tells every early-stage founder

Le Canada veut passer de la recherche IA à l'industrie • L'Europe tente de réduire sa dépendance numérique • Qwant devient un symbole de souveraineté • Mistral se heurte au droit d'auteur • Microsoft pousse l'IA agentique partout • Alexa+ trop lent • Mon Carnet explore les batteries lourdes • Monde Numérique reçoit Qwant et enquête sur la cybersécurité et l'hôpitalAvec Bruno Guglielminetti (Mon Carnet)Le Canada veut industrialiser son IAAu Canada, le gouvernement de Mark Carney présente sa stratégie « AI for All », avec l'objectif de faire passer l'adoption de l'IA par les entreprises d'un peu plus de 12 % à 60 % d'ici 2034 et de créer 250 000 emplois liés à l'IA sur cinq ans. On retient surtout le changement de cap : le pays veut rester fort en recherche, mais pousser davantage la commercialisation, les infrastructures souveraines, la littératie numérique et la cybersécurité.Souveraineté numérique : même combat des deux côtés de l'AtlantiqueEn Europe, la Commission européenne lance un paquet de mesures pour renforcer la souveraineté technologique dans les semi-conducteurs, l'IA, le cloud et les infrastructures numériques. On souligne que l'objectif n'est pas l'autarcie totale, mais une réduction des dépendances critiques vis-à-vis des fournisseurs américains et asiatiques, avec une préférence européenne qui pourrait bouleverser les habitudes d'achat public.Qwant, symbole européen au ParlementLe Parlement européen remplace Google par Qwant comme moteur de recherche par défaut sur Edge et Firefox à partir du 4 juin 2026, tout en laissant les utilisateurs choisir une alternative. On y voit un geste fort, peut-être symbolique, mais révélateur d'un mouvement plus large : faire exister des outils européens face aux géants américains. Dans Monde Numérique, Jérôme annonce une interview du directeur général de Synfonium, la société qui possède Qwant.Mistral face au casse-tête du droit d'auteurMistral AI se retrouve au cœur d'un dilemme européen : protéger les ayants droit ou ne pas fragiliser l'une des rares pépites européennes de l'IA. Nous revenons sur cette tension entre innovation, souveraineté et rémunération des contenus, avec un risque clair : imposer aux acteurs européens des contraintes que les géants américains ont déjà largement contournées.Microsoft veut rendre l'IA incontournableÀ l'occasion de Microsoft Build 2026, Microsoft pousse une vision très agentique de l'informatique, où l'IA devient l'interface principale entre l'utilisateur, ses données et ses appareils. On évoque notamment les nouvelles briques autour de Copilot, les agents, les modèles embarqués et les machines capables de faire tourner localement des modèles puissants, dont une dev box fondée sur la technologie NVIDIA RTX Spark.L'ordinateur sans applications se rapprocheBruno relève une idée forte : demain, l'appareil pourrait ne plus être organisé autour d'applications, mais autour d'un assistant capable de tout orchestrer à la demande. On met cette évolution en perspective avec les annonces de Microsoft, les travaux d'OpenAI sur de nouveaux appareils, et les ambitions de Qualcomm, Intel ou MediaTek dans l'IA locale.Alexa+ : plus intelligent, mais trop lentJérôme partage son retour d'expérience avec Alexa+, désormais testé à la maison en France. L'assistant paraît plus courtois, plus conversationnel et compatible avec de nombreux appareils existants, mais la latence devient gênante, surtout pour les gestes simples de domotique comme allumer les lumières ou baisser les volets. Il note aussi la disparition de plusieurs « skills », toujours visibles dans l'application mobile mais inutilisables sur certains appareils Echo récents.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

AI vam neće uzeti posao... osim ako niste osrednji u onome što radite. Evo šta se zapravo dešava u industriji.

L'Europe relance la bataille pour sa souveraineté numérique face aux GAFAM • Le Parlement européen adopte Qwant comme moteur par défaut • L'IA affronte le droit d'auteur et Mistral monte au créneau • Anthropic relance le débat sur une pause mondiale de l'IA • SoftBank investit 75 milliards d'euros dans des data centers en France • Microsoft dévoile ses nouveaux modèles et ses agents autonomes ⭐️ Découvrez Frogans à Vivatech 2026

As the EU publishes its digital sovereignty plans, we've come up with a little techno-utopian package of our own. Our guest throughout is tech and solar-punk author Cory Doctorow: join us as we explore queer social media take-backs, French AIs, Finish super-computers, Croatian Wikipedia and all the reasons why this might just be the moment in which things start to change for the better.

Taskmaster Technieuws De Apple Car is er en hij heet Ferrari Luce | Elektrische Ferrari Luce onthuld: 530 km en 1.050 pk | Het internet vindt de e-Ferrari van Jony Ive maar niks Mistral doopt Le Chat om tot Vibe | Officiële aankondiging | En ook: Proton Lumo

Mistral CEO Arthur Mensch joins CNBC's Arjun Kharpal to discuss AI infrastructure, the race for computing power, and why access to AI “tokens” is becoming a strategic priority. He also shares his views on AI sovereignty, enterprise adoption, custom chips and the future of AGI.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with returning guest Ekue Kpodar for their third conversation together, covering a wide range of topics at the intersection of technology, geopolitics, and the evolving information age. They dig into Ekue's unconventional setup of running local AI models across roughly 15 computers, the growing case for open source models over closed ones from companies like OpenAI and Anthropic, and how Chinese open source models may be positioned to outcompete Western alternatives on a global scale. The conversation also touches on vibe coding and the democratization of software development, the strategic use of small models for IoT and enterprise applications, the role of Israel and China as dominant players in the information age, and how smaller nations and even individuals may wield outsized power as AI continues to collapse the cost of knowledge work. You can find Ekue Kpodar on X @ekpodar and LinkedIn.Timestamps00:00 Stewart welcomes Ekue for their third episode, diving into vibe coding and AI-driven development changes.05:00 Ekue explains using Claude on Chrome to auto-reply on Skool, burning tokens through screenshots, and Playwright as a more efficient alternative.10:00 Stewart describes his Claude-dependent planning and coding agent system breaking after a model update, prompting him to build his own chatbot.15:00 Small models discussed as critical for IoT, defense, and privacy-focused enterprises building internal APIs instead of routing traffic to OpenAI.20:00 Open source versus closed source debated, with Chinese models gaining global traction while US foundational labs remain expensive and restrictive.25:00 SaaS apocalypse explored as AI commoditizes knowledge work, with Linux and Terraform cited as proof open source still generates wealth.30:00 OpenAI's sci-fi terminator fears explained as the reason they stayed closed source, ultimately handing China a strategic open source advantage.35:00 China's economic dumping strategy applied to AI, potentially displacing US model dominance globally the same way manufacturing was disrupted.40:00 Israel's signals intelligence dominance discussed alongside asymmetric warfare, drones defeating tanks, and information control replacing military muscle.45:00 Global information age rankings debated, Israel leading, US and China tied, France and Poland emerging as sovereign tech players.50:00 Qatar, NVIDIA, and Iran cited as proof that rare resources and technology matter more than population size in the 21st century power landscape.Key Insights1. Running local AI models on a network of affordable computers can be more cost-effective than relying entirely on third-party APIs. By using compressed or smaller open source models locally, developers can handle repetitive or lower-stakes tasks without burning through expensive tokens from providers like Anthropic or OpenAI.2. Small AI models are becoming increasingly important for IoT, defense applications, and companies that do not want to send sensitive data to external providers. Organizations can download open source models, run them on internal servers, and build proprietary APIs around them, creating something like an intranet of specialized small models.3. The value created by AI tools is being redistributed away from traditional SaaS companies toward foundational model providers and individual builders. People are canceling subscriptions to software they once paid hundreds per month for, because AI now allows a single person to build comparable tools themselves.4. Open source technology does not eliminate the ability to profit. Linux and Terraform are both open source yet made their creators wealthy. People will still pay for installation, setup, troubleshooting, and customization even when the underlying software is free.5. China is applying its longstanding manufacturing dumping strategy to artificial intelligence by releasing cheap open source models globally, which threatens to erode US dominance in AI the same way Chinese manufacturing undercut other countries for decades.6. In the information age, the size of a country or institution matters far less than its access to rare resources or advanced technology. Qatar, Israel, and NVIDIA each demonstrate that small populations or headcounts can wield enormous global negotiating power through concentrated technological or resource advantages.7. Asymmetric warfare is redefining military power, with inexpensive drones defeating tanks that cost millions to build. This shifts the advantage toward nations that excel at signals intelligence and information management rather than those with the largest conventional military forces.

What does it take to walk away from a West End career, start over as a novelist and then have every major publisher turn you down before landing a three-book deal?In this episode of The Conversation, Nadine Matheson sits down with Felix Mosse, former West End actor (Les Misérables, The Book of Mormon), TV and film script editor, and now debut author of the epic fantasy The Mistral.Felix is refreshingly candid about the whole journey, the moment COVID forced him to rethink acting, what it actually feels like to sit on submission for the better part of a year, and how a decade spent shaping other people's scripts made him a sharper and more resilient writer. He and Nadine also dig into the world of The Mistral itself: a dying divine wind, a deliberately diverse cast, and the choice to leave most of his characters' appearances open to the reader's imagination. It's a warm, honest conversation about reinvention, persistence, and making peace with your inner nerd.Follow Felix MosseBuy The Mistral Listen To: Nerd Culture: Lore & Craft PodcastPre- Order 'The Shadow Carver' PbBuy me a cup of coffee ☕️ | Buy books by my guestsFollow Me Bluesky | Substack | Instagram | Facebook | Threads Hosted on Acast. See acast.com/privacy for more information.

Mistral dévoile ses ambitions : faut-il y croire ? • Google pousse les agents IA dans tous ses services • Alexa+ transforme l'assistant vocal en compagnon domestique • La contestation anti-IA monte autour des emplois, de l'énergie et des data centers.Avec Free Pro, le meilleur de Free pour les entreprisesAvec François Sorel (BFM Business) et Bruno Guglielminetti (Mon Carnet)Mistral, l'espoir français de l'IA souveraineNous ouvrons ce Grand Débrief avec Mistral AI, qui a organisé son AI Now Summit au Grand Palais, à Paris, avec une ambition claire : ne pas seulement produire des modèles, mais maîtriser toute la chaîne de valeur de l'intelligence artificielle. La stratégie B2B de Mistral, fondée sur l'intégration sur mesure de l'IA dans les grandes entreprises comme BMW, EDF ou CMA CGM, sera-t-elle payante ? Surtout : permettra-t-elle à la la France et à l'Europe de prendre une vraie place face aux géants américains et chinois ? Google I/O : les agents IA entrent dans le quotidienLa conférence Google I/O marque l'autre grand moment du mois, avec une avalanche d'annonces autour de Gemini, de la recherche augmentée, des lunettes connectées et des agents autonomes. Nous nous demandons si Google est en train de reprendre l'avantage dans la bataille de l'IA, notamment en intégrant ses outils au cœur de l'expérience utilisateur. Monde Numérique a consacré plusieurs contenus au sujet, dont un Zoom Tech sur Google I/O 2026 et un épisode sur l'IA agentique qui bouscule le Web.Alexa+ : l'IA générative démocratisée Nous parlons ensuite d'Amazon et d'Alexa+, qui promet un assistant vocal beaucoup plus intelligent, capable de réserver une table, piloter la maison connectée ou dialoguer de manière plus naturelle. François Sorel insiste sur l'avantage des acteurs qui disposent déjà d'enceintes et d'un écosystème matériel installé dans les foyers. Monde Numérique a publié un Zoom Tech consacré au lancement d'Alexa+ en France et à son passage à l'IA générative.La vague anti-IA qui monteDernier grand sujet : la contestation contre l'intelligence artificielle, visible dans les manifestations contre les data centers, les craintes pour l'emploi et les réactions d'hostilité dans certaines universités. Nous distinguons plusieurs ressorts : la peur classique des nouvelles technologies, la crainte plus légitime d'un bouleversement du travail, et le refus local d'accueillir des infrastructures très consommatrices d'énergie ou d'eau. Monde Numérique a également traité cette montée de la fronde anti-IA dans son Hebdo du 30 mai. La Silicon Valley est-elle responsable de ce climat de peur ?Bonus On a bien galéré pour enregistrer cet épisode ! Rendez-vous à la fin pour un aperçu des coulisses

L'intelligenza artificiale entra nell'era della maturità industriale. In questa 12° puntata di Intelligenze Emergenti, analizziamo una settimana che segna un punto di svolta per l'intero settore AI. I riflettori sono puntati sui finanziamenti record di Anthropic, sulle nuove strategie di Microsoft e Mistral AI, sulla crescente pressione per dimostrare un ritorno economico concreto degli investimenti e sulla corsa globale alle infrastrutture hardware necessarie per sostenere la rivoluzione dell'intelligenza artificiale. Scopriremo come i grandi gruppi tecnologici stiano ridefinendo modelli di business, organici aziendali e strategie di cybersecurity, mentre governi, imprese e mercati finanziari si confrontano con sfide senza precedenti legate a energia, chip, data center e sicurezza informatica.Parleremo inoltre di bias algoritmici, proprietà intellettuale, nuove competenze professionali richieste dal mercato e delle battaglie legali che stanno già plasmando il futuro dell'ecosistema AI.Una puntata ad alta densità strategica per imprenditori, manager, innovatori e professionisti che vogliono capire cosa sta realmente accadendo dietro il rumore mediatico. In collaborazione con Claudio Ricci, Amministratore unico di Recomb, una realtà specializzata nel fornire aggiornamenti personalizzati alle organizzazioni orientate all'innovazione sugli sviluppi dell'intelligenza artificiale, oltre a offrire corsi di aggiornamento professionale Per maggiori informazioni: info@recomb.aiFonti principali:https://www.nytimes.com/2026/05/28/technology/anthropic-tops-openai-valuation.htmlThe New York Times – Analisi del finanziamento record di Anthropic e della sua valutazione di mercato. https://uk.finance.yahoo.com/news/apollo-shops-36-billion-debt-210011269.htmlBloomberg – Approfondimento sulle nuove strutture finanziarie per l'acquisto e il leasing di chip AI. https://www.theinformation.com/newsletters/ai-agenda/microsoft-release-new-codingmodel-next-week-comeback-attemptThe Information – Strategia Microsoft per sviluppare modelli proprietari e ridurre la dipendenza da OpenAI. https://www.cnbc.com/2026/05/28/mistral-arthur-mensch-design-chips-ai-data-centers.htmlCNBC – Espansione di Mistral AI tra chip proprietari e data center europei. https://www.wsj.com/tech/ai/mistral-chases-ai-superintelligence-to-counter-u-s-dominance-b2a44fa1The Wall Street Journal – Partnership industriali di Mistral nei settori aerospazio e difesa. https://archive.is/wwgeJAxios – Analisi dei costi reali dell'adozione dell'AI nelle grandi aziende. https://www.theinformation.com/articles/openais-next-ad-move-going-small-scale-bigThe Information – Evoluzione del modello pubblicitario di OpenAI e ChatGPT. https://www.foxbusiness.com/technology/meta-lays-off-nearly-1400-washington-employees-latest-tech-workforce-cutFox Business – Nuovi licenziamenti di Meta e riallocazione delle risorse verso l'AI. https://www.calcalistech.com/ctechnews/article/b1oebi11xgeCTech – Impatto dell'automazione sulla forza lavoro di Wix. https://m.economictimes.com/tech/artificial-intelligence/python-in-the-grass-it-freshers-must-speak-ai-to-stay-on-par/articleshow/131314611.cmsThe Economic Times – Cambiamento delle assunzioni nel settore tecnologico indiano. https://www.cnbc.com/2026/05/27/these-5-ai-proof-skills-are-likely-to-increase-in-value-over-next-5-years-career-expert.htmlCNBC Make It – Le competenze umane che manterranno valore nell'era dell'AI. https://archive.is/eO2szNikkei Asia – Carenza globale di fibre ottiche e componenti per data center. https://www.theinformation.com/newsletters/the-electric/ai-data-center-boom-ignites-tear-lithium-sharesThe Information – Crescente domanda di litio per le infrastrutture computazionali. https://newsroom.ibm.com/2026-05-28-ibm-and-red-hat-commit-5-billion-to-redefine-the-future-of-open-source-in-the-ai-eraIBM Newsroom – Lancio di Project Lightwell per la sicurezza dell'open source. https://futurumgroup.com/insights/can-googles-ai-threat-defense-set-the-pace-for-enterprise-cyber-defense/Futurum Group – Analisi della piattaforma Google Cloud AI Threat Defense. https://archive.is/IZ06KFinancial Times – Studio sui bias algoritmici nei processi di selezione del personale. https://archive.is/FgpSSFinancial Times – Approfondimenti sulle implicazioni normative e di governance dell'AI. https://www.brief.news/us-news/2026/05/28/cnn-sues-ai-startupBrief – La causa legale della CNN contro Perplexity per presunta violazione del copyright.

Ce vendredi 29 mai, le séminaire organisé à Bruxelles pour réfléchir aux outils de défense commerciale face à la menace chinoise, ainsi que la nécessité d'imposer Mistral aux Européens, ont été abordés par Patrick Artus, économiste et conseiller économique de la société de gestion Ossiam, Antonin Bergeaud, Prix du meilleur jeune économiste 2025 et professeur associé à HEC, et Olivier Garnier, expert associé à l'Institut Montaigne, dans l'émission Les Experts, présentée par Raphaël Legendre sur BFM Business. Retrouvez l'émission du lundi au vendredi et réécoutez la en podcast.

Tata Consultancy Services (TCS), a global leader in IT services, consulting and business solutions, who operate a Global Delivery Centre in Letterkenny, Co. Donegal, today announced a landmark strategic partnership with Mistral, one of world's leading AI companies. As part of this collaboration, TCS has become the first global systems integrator partner for Mistral Forge, Mistral's advanced system for enterprises to build frontier-grade AI models grounded in their proprietary enterprise knowledge and domain-specific data. The partnership combines Mistral's frontier AI capabilities with TCS' deep context of enterprise customers, domain knowledge and engineering excellence, to help organisations scale enterprise AI responsibly with greater speed. As part of this strategic collaboration, TCS will leverage Mistral Forge to build custom AI models for enterprises. It will help customers deploy their data and enterprise context to improve decision outcomes. This collaboration draws on TCS' strong global presence across North America, the United Kingdom, Europe, and Asia-Pacific to deliver AI solutions tailored to industry needs, operations and regulatory requirements. The partnership will initially focus on sectors like banking, financial services and insurance (BFSI), manufacturing, healthcare, and the public sector, where trusted AI adoption is becoming increasingly critical. TCS will also establish a dedicated Centre of Excellence for Mistral to drive joint innovation, build industry-specific solutions, support project delivery, and accelerate client value through early access to Mistral's beta models. The Centre of Excellence will serve as a strategic hub for advanced talent, focused training, and the capabilities needed to design, deploy, and govern AI solutions. Arthur Mensch, Chief Executive Officer and Co-Founder at Mistral, said, "TCS' global scale and contextual industry knowledge make them an ideal partner for Mistral. Together, we are enabling enterprises worldwide to move from experimentation to AI deployment with systems that are open, production-ready and aligned with their strategic and operational requirements." K Krithivasan, Chief Executive Officer & Managing Director at TCS said, "The partnership with Mistral reinforces TCS' commitment to scaling enterprise AI with trust, control, and measurable business outcomes at the core. This partnership expands TCS' AI ecosystem, uniquely positioning TCS to create a differentiated solution proposition for our clients. Together with Mistral, we will solve for specific industry challenges, regulatory requirements, and sovereign needs for our enterprise customers." As part of its broader Infrastructure to Intelligence AI strategy, TCS continues to invest across infrastructure, models, data, application, platforms and physical and digital intelligence. This aligns with TCS' ambition to become the world's largest AI-led technology services company, underpinned by a five-pillar strategy focused on embedding AI across the enterprise, scaling AI-led delivery capabilities, and driving measurable business outcomes for clients.

Ce jeudi 28 mai, François Sorel a reçu Frédéric Simottel, journaliste BFM Business, Yves Maitre, operating partner chez Jolt capital, et Didier Sanz, journaliste Tech. Ils se sont penchés sur le domaine de l'intelligence artificielle avec Mistral et l'impact de l'IA sur l'emploi dans l'émission Tech & Co, la quotidienne, sur BFM Business. Retrouvez l'émission du lundi au jeudi et réécoutez-la en podcast.

Een pijnlijke ruzie tussen China en de EU. Eentje die kan uitmonden in een handelsoorlog. Het begon allemaal met een plan van Brussel. De Europese Commissie vindt dat de handel met China niet eerlijk verloopt en wil de tarieven op Chinese spullen gaan verhogen. Tot woede van de Chinezen. China waarschuwt dat het tegenmaatregelen neemt als Europa doorzet. En over die escalatie hebben we het deze aflevering. Wat gebeurt er als China terugslaat? Welke aandelen hebben er dan last van? En is Trump de lachende derde? Over Trump gesproken: hij viel opnieuw Iran aan. Net nu het leek dat er een akkoord lag tussen het Iraanse regime en de Trump-regering. We kijken wat die aanval betekent voor de olieprijs en voor de beurzen wereldwijd. Ook hoor je over het opvallende vertrek van de CFO van Adyen. Hij was tien jaar lang belangrijk voor het bedrijf, maar gaat weg. De financiele man gaat zelfs helemaal de fintechwereld uit. Verder vertellen we je alles over de bijzondere stap van KPN. Dat slaat de handen ineen met de eigenaar van Lidl. Samen willen ze een vuist bieden tegen de cloud-macht van de Amerikanen. Te gast: debutant Thomas Pellegrom van ABN Amro MeesPierson BNR Beurs is een journalistiek onafhankelijke productie, mede mogelijk gemaakt door Saxo. Over de makers: Jelle Maasbach is presentator van BNR Beurs en freelance financieel journalist. Zijn favoriete aandeel om over te praten is Disney, maar daar lijkt hij de enige in te zijn. Sinds de eerste uitzending van BNR Beurs is 'ie er bij. Maxim van Mil is presentator van BNR Beurs en journalist bij BNR, waar hij zich focust op de financiële markten en ontwikkelingen in de tech-wereld. Je krijgt hem het meest enthousiast als hij kan praten over ASML, of oer-Hollandse bedrijven zoals Ahold of ABN Amro. Jorik Simonides is presentator van BNR Beurs, economieredacteur en verslaggever bij BNR. Hij wordt er vooral blij van als het een keer níet over AI gaat. Milou Brand is presentator van BNR Beurs, freelance podcastmaker en columnist bij het Financieele Dagblad. Jochem Visser is presentator van BNR Beurs, maakt Beursnerd XL en is redacteur bij de podcast Onder Curatoren. Vraag hem naar obscure zaken op financiële markten en hij vertelt je waarom het eigenlijk nóg leuker is dan je al dacht. Over de podcast: Met BNR Beurs ga je altijd voorbereid de nieuwe beursdag in. We praten je in een kleine 25 minuten bij over alle laatste ontwikkelingen op de handelsvloer. We blijven niet alleen bij de AEX of Wall Street, maar vertellen je ook waar nog meer kansen liggen. En we houden het niet bij de cijfers, maar zoeken ook iedere dag voor je naar duiding van scherpe gasten en experts. Of je nu een ervaren belegger bent of net begint met je eerste stappen op de beurs, de podcast biedt waardevolle inzichten voor je beleggingsstrategie. Door de focus op zowel de korte termijn als de lange termijn, helpt BNR Beurs luisteraars om de ruis van de markt te scheiden van de essentie. Van Musk tot Microsoft en van Ahold tot ASML. Wij vertellen je wat beleggers bezighoudt, wie de markten in beweging zet en wat dat betekent voor jouw beleggingsportefeuille. See omnystudio.com/listener for privacy information.

//The Wire//2300Z May 27, 2026// //ROUTINE// //BLUF: GANG WAR CONTINUES IN GRENOBLE. WAR IN LEBANON EXPANDS AS DRONE ATTACKS INTENSIFY. CONFLICT MOUNTS IN CONGO AS EBOLA CRISIS WORSENS. PROBABLE CHINESE AGENTS DETAINED WHILE ATTEMPTING TO INFILTRATE SOUTHERN US BORDER.// -----BEGIN TEARLINE------International Events-Middle East: Israeli attacks in Lebanon have increased over the past few days, with more significant bombings taking place in Beirut. FPV drone attacks by Hezbollah have continued to devastate Israeli forces, as most of the IDF is not equipped or prepared to handle the threats that drones bring to modern warfare. As a result, the fighting has become much more intense, which in turn has increased the efforts to expand the Israeli bombing campaign.France: Last night a small arms attack was reported in Grenoble, as a war between rival gangs of migrants has broken out. One engagement was reported in the Mistral neighborhood overnight, with several people being gunned down on the street. One person was killed, and three others wounded during this attack, which locals sources claim was a targeted assassination. Three days ago, another assassination was reported, with a Cartel-style video being posted online before a body was found in a vehicle in the Échirolles community.-HomeFront-New Jersey: Protests at the Delaney Hall Detention Facility have continued, which have mostly transitioned into more of a long-term protest site once again. A few local politicians have made appearances over the past few days, but apart from occasional flare-ups and riots, the weekday attendance at this facility has remained fairly regular.Texas: Overnight a group of Chinese nationals were arrested after attempting to illegally cross the southern US border in the vicinity of Eagle Pass. US Border Patrol trackers located the group of individuals who had crossed the border illegally and were concealing themselves on a private ranch. Among this group were a total of 6x Chinese citizens, who federal authorities have classified as Special Interest Aliens (SIAs) for reasons that have not been disclosed. In the photos of the group provided by Customs and Border Patrol, one of the Chinese individuals has a military-style haircut, and another individual is wearing military-style combat boots. All are wearing civilian-style camouflage jackets and pants, all of the same type and construction.Analyst Comment: Most coyotes illegally smuggling people over the border have either required or furnished themselves camouflage "uniforms" for the illegals to don, in order to cross the border as covertly as possible. As a result, these individuals being detained while wearing camouflage is very normal these days. Illegal border crossings still take place along the vast wilderness areas which comprise most of the border, but it's become a lot harder to make the crossing and also much more expensive to do so. For Chinese immigrants, it's never been easier to get legal paperwork and enter the US at an official port of entry, so the fact that these individuals made the crossing illegally indicates that they were up to no good.-----END TEARLINE-----Analyst Comments: In the Congo, the situation regarding the current Ebola outbreak has become increasingly more serious over the past few days, as the current civil war is impacting efforts to control the disease. Separately, social tensions flared up overnight, after a domestic situation spiraled out of control at a treatment center. Last night, police fired warning shots at the perimeter of Rwampara Hospital, as a crowd of people attempted to breach the facility to recover the bodies of relatives who had died from Ebola. Upon being told that they can't have the remains of their family members due to fears of the disease spreading, the crowd promptly set a tent on fire at the compound and a state of pandemonium erupted. During the fray, a handful of Ebola-positive patients fled from the facility and are currently unaccounted for.Around the continent, nations bordering the Congo have begun to close the border checkpoints to those fleeing both the simmering civil war, and also the spread of Ebola. Uganda closed their borders this morning, and several other nations have implemented travel controls to restrict travel out of the hardest-hit areas.Analyst: S2A1 Research: https://publish.obsidian.md/s2underground Disclaimer: No LLMs were used in the writing of this report. //END REPORT//

Oil prices whipsaw with Brent up almost 3 per cent following an Iranian missile and drone attack on a U.S. air base in Kuwait. The strikes were followed by the U.S. targeting of a ground control station in Bandar-e-Abbas just hours after optimistic peace talks comments from U.S. Secretary of State Marco Rubio had pushed crude lower. Federal Reserve governors Neel Kashkari and Austan Goolsbee warn CNBC rising inflation and price pressures are not easing. Global equity markets fall into the red again following yesterday's record session on Wall Street. The EU is reportedly looking to decrease its dependency on American technology and champion European companies. Mistral AI CEO Arthur Mensch tells CNBC he welcomes the bloc's direction.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In diesem Deep Dive spricht Markus mit Dennis Just, CEO von Emmi AI, über seinen ungewöhnlichen Weg vom professionellen E-Sports-Spieler über mehrere Startup-Exits bis hin zur KI für Industrieunternehmen. Dennis erzählt, wie Emmi AI Physik-Simulationen mit KI ersetzt, warum Siemens Energy ihr erster großer Kunde wurde und wie der Exit zu Mistral zustande kam. Außerdem: Was Mistral von Aleph Alpha unterscheidet, warum Top-Down-Sales der entscheidende Hebel war und was Dennis über AI, Energieverbrauch und die Gesellschaft denkt.Production: Hanna MoserMusik (Intro/Outro): www.sebastianegger.com

AI is no longer just a technology story. It is reshaping capital markets, infrastructure and industrial policy.In the latest episode of This Week in European Tech, Mads Jensen and Dan Bowyer of SuperSeed break down NVIDIA's dominance of the AI economy, the return of the IPO market through OpenAI, Anthropic and SpaceX, and Europe's push to build sovereign technology capabilities.HighlightsNVIDIA and the economics of AI infrastructureOpenAI, Anthropic and the IPO market reopeningEurope's sovereign AI pushAI backlash and political risk in the USUnitree and the rise of humanoid roboticsIsomorphic Labs and AI-driven drug discoveryTimestamps(03:00) NVIDIA is swallowing the AI economy(06:20) The IPO market is reopening through OpenAI, Anthropic and SpaceX(08:40) Why SpaceX is really an AI infrastructure story(11:40) OpenAI's IPO could expose the real economics of AI(13:40) Why Unitree and humanoid robotics matter for Europe(20:10) Europe's sovereign AI push through Mistral, EQT and Quantexa(27:40) Americans are turning against AI(36:10) Isomorphic Labs and Europe's biggest AI biotech opportunitySubscribe to EUVC, the home of European tech, for more insights.

Natürlich geht es heute um die SpaceX-S1-IPO-Filings, aber vorher sprechen wir über die Google I/O (Universal Cart, Gemini Spark, Gemini 3.5 Flash und viele mehr). Wir vergleichen Umsatz und Verlust (Gewinn) von OpenAI und Anthropic. Andrej Karpathy wechselt zu Anthropic, Cursor erreicht $3 Mrd. Annual Sales Rate. Starlink ist die SpaceXs Cashcow ($11 Mrd. Umsatz, $4,4 Mrd. Profit) und subventioniert die mit 12,5% wachsende KI-Sparte. OpenAI kündigt am Tag des S1-Filings überraschend frühen IPO an. Binance launcht SpaceX Pre-IPO Perpetuals. Bezos hat sich diese Woche auch zu Wort gemeldet. Zudem sprechen wir über Forum-AI-Studie: Falsche News-Antworten von KI, Google holt Contextual-AI-Team für $100 Mio, Airbnb erweitert auf Hotels und Mietwagen. Earnings von Nvidia und Workday. SAP, Mistral und unser Digitalminister Wildberger lässt offenbar Texte/Reden von schreiben. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:04:00) Google I/O Recap (00:25:44) OpenAI Q1 Earnings: $5,7 Mrd. (00:34:33) Anthropic Q1 & profitable im Juni (00:41:21) Karpathy zu Anthropic (00:42:40) Cursor bei $3 Mrd. Runrate (00:44:39) SpaceX S1 Filing Deep Dive (01:19:30) SpaceX kauft Cybertrucks für $140 Mio. (01:24:30) OpenAI IPO-Filing kommt früher (01:28:29) SpaceX Pre-IPO Perpetuals (01:32:37) Arbeiter stirbt in Starbase (01:33:28) Bezos: Space-Datacenter & Steuer-Debatte (01:38:34) Forum AI: GROK unzuverlässig bei News (01:41:19) Google holt Contextual-AI-Team für $100 Mio. (01:41:51) Airbnb: Hotels, Mietwagen, Everything-Travel (01:43:39) Nvidia Earnings +85% (01:46:51) Workday Earnings +14% (01:47:22) Zuckerberg-Audio: Mitarbeiter-Spionage (01:47:44) Enhanced Games (Steroid-Olympics) (01:52:21) Reuters: GROK 3 von 400 US-Behörden-Fällen (01:53:12) WaPo: DOGE-Datenzugriffe geheim (01:54:04) Trump schützt sich vor IRS (01:54:46) Cohere übernimmt Reliant AI Shownotes Google I/O 2026: Größte AI-Ankündigungen - theverge.com OpenAI behält $1 Mrd. Umsatz-Vorsprung vor Anthropic in Q1 - theinformation.com OpenAI Action-Figur-Werbung auf Instagram - instagram.com Anthropic wird erstmals profitabel - wsj.com Andrej Karpathy wechselt zu Anthropic - bloomberg.com Cursor erreicht $3 Mrd. Annual Sales Rate - bloomberg.com SpaceX-IPO: Founders Fund vor $60 Mrd. Return - theinformation.com OpenAI IPO-Filing kommt früh - wsj.com OpenAI klaut SpaceX die Show mit IPO-Ankündigung - marketwatch.com Binance launcht Pre-IPO Perpetuals für SpaceX - prnewswire.com SpaceX: Arbeiter stirbt in Starbase - futurism.com Bezos / Blue Origin: Data Center im All - cnbc.com WOLF Financial Tweet (bitte manuell prüfen) - xcancel.com Studie: ChatGPT, Claude, Gemini, Grok bei News unzuverlässig - bloomberg.com Google: $100 Mio. Acqui-License von Bezos' Contextual AI - bloomberg.com Airbnb fügt Hotels und Mietwagen hinzu - cnbc.com Nvidia-Earnings: +85% durch AI Boom - theguardian.com Workday Q1 Earnings: Aktie +14% - cnbc.com LayoffAI Tweet - xcancel.com Steroid Olympics - ft.com Christian Angermayer und die Enhanced Games - theguardian.com Grok fällt in Washington durch: Nur 3 von 400 Behörden-Fällen - reuters.com Behörden verweigern Auskunft über DOGE-Datenzugriffe - washingtonpost.com Trump schützt eigene Steuererklärungen vor IRS-Prüfung - spiegel.de Cohere übernimmt deutsches KI-Startup Reliant AI - manager-magazin.de Reliant-AI-Gründer Karl-Moritz Hermann verkündet Cohere-Deal - linkedin.com Schreibt ChatGPT die Reden des Digitalministers? - de.linkedin.com

 Netflix qui teste une recherche vocale alimentée par IA, capable d'interpréter des requêtes vagues pour recommander films et séries selon l'ambiance ou l'usage recherché. Les IA de la semaine (notamment pour les robots) et une nouvelle peluche robot inutile.  Me soutenir sur Patreon Me retrouver sur YouTube On discute ensemble sur Discord Modèles de la semaine RLWRLD, GENE, SVGS, et la recherche intelligente de Netflix. Mistral souffle plus fort, assez pour compenser le vent d'est ? Gemma4 accélère ! Et s'incruste dans Chrome… depuis deux ans. EVE lève toi : Deepmind se lance dans la guerre spatiale. C'est rassurant. L'IA déjà en orbite mais sans datacenter. Souriez, vous serez filmés. Tout le temps, partout. L'IA va créer des emplois ! Oui. Ouiiiii, bien sûr. Appareillage Robotique sous tous les Angle : après le trilobite, la peluche. Les boules ! Encore des datacenters à la dérive. Cerebras de plus en plus de pognon. La RAMpocalypse touche les archivistes… Et pas seulement, mais AMD à d'autres cordes à son arc. Un petit tour au Fouqet's : on est serein chez ASML. La prochaine génération d'hélicoptère martien. Participants Une émission préparée par Guillaume Poggiaspalla Présenté par Guillaume Vendé

Our 244th episode with a summary and discussion of last week's big AI news!Recorded on 05/08/2026Hosted 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:OpenAI released GPT-5.5 Instant as ChatGPT's new default model, showing large benchmark gains and crossing a “high” cyber-risk threshold under its preparedness framework, while bio-safety results were mixed.OpenAI investigated and patched ChatGPT's “goblin” obsession, attributing it to reinforcement-learning rewards that over-amplified playful creature metaphors in a nerdy persona that later bled across versions.Major industry moves included xAI's Grok 4.3 price cuts and voice tools, Mistral's unified Medium 3.5 model and Work mode, and Anthropic's managed-agent upgrades alongside a surprise SpaceX compute deal and reports of a much higher Anthropic valuation.Key policy and security developments covered the Musk–OpenAI trial details, Pentagon AI deployments on classified networks, expanded U.S. government pre-release model reviews, and reports of NSA testing Anthropic's Mythos on Microsoft software.Timestamps:(00:00:10) Intro / Banter(00:01:14) News Preview(00:04:39) Response to listener commentsTools & Apps(00:13:40) OpenAI releases GPT-5.5 Instant, a new default model for ChatGPT | TechCrunch(00:18:23) ChatGPT Became So Obsessed With Goblins That OpenAI Had to Intervene(00:27:14) xAI launches Grok 4.3 at an aggressively low price and a new, fast, powerful voice cloning suite | VentureBeat(00:33:49) Mistral's new flagship Medium 3.5 folds chat, reasoning, and code into one model(00:39:28) Anthropic updates Claude Managed Agents with three new features - 9to5Mac(00:43:42) ElevenLabs Revamps AI Music Platform as Fan-Focused ServiceApplications & Business(00:44:57) A diary, a threat, and a $30 billion stake: What the Musk vs OpenAI trial has actually shown in its first week - The Times of India(00:55:28) Anthropic, SpaceX Sign Deal to Boost AI Computing Power for Claude Software - Bloomberg(01:01:48) Anthropic in talks with investors to raise funds at $900 billion valuation, higher than OpenAI(01:02:37) Anthropic and OpenAI are both launching joint ventures for enterprise AI services | TechCrunch(01:06:15) Anthropic and FIS Are Building an AI Agent to Help Banks Police Financial Crimes(01:07:02) AMD's revenue jumps 38 percent from last year as Q1 data center sales hit $5.8 billion. | The Verge(01:08:51) Banks seek to offload risk to avoid ‘choking' on data centre debt(01:14:08) DeepSeek could be valued at up to $50 billion in first fundraising, sources say | ReutersProjects & Open Source(01:16:14) Natural Language Autoencoders Produce Unsupervised Explanations of LLM Activations(01:22:23) OpenAI just open-sourced its data center networking technologyPolicy & Safety(01:25:02) Pentagon inks deals with Nvidia, Microsoft, and AWS to deploy AI on classified networks | TechCrunch(01:27:27) Google, Microsoft, and xAI will allow the US government to review their new AI models | The Verge(01:32:11) NSA Testing Anthropic's Mythos to Find Flaws in Microsoft Tech(01:35:42) Introspection Adapters: Training LLMs to Report Their Learned BehaviorsResearch & Advancements(01:41:18) Recursive Multi-Agent Systems(01:51:47) Frontier Coding Agents Can Now Implement an AlphaZero Self-Play Machine Learning Pipeline For Connect Four That Performs Comparably to an External SolverSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week, Salesforce, OpenAI, Microsoft, and Google all made major moves toward "headless" software — platforms designed for agents rather than human users. The episode explores what this shift means for business models, the future of SaaS pricing, and who captures the value when agents become the primary consumers of enterprise tools. In the headlines: OpenAI triples its compute targets to 30 gigawatts, Google unveils separate TPU chips for training and inference, and Mistral may be joining forces with xAI.AI Practitioner's Credential Survey - ⁠⁠⁠https://tally.so/r/vGOLr4⁠⁠⁠Brought to you by:KPMG – Agentic AI is powering a potential $3 trillion productivity shift, and KPMG's new paper, Agentic AI Untangled, gives leaders a clear framework to decide whether to build, buy, or borrow—download it at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.kpmg.us/Navigate⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Granola - The AI notepad for people in back-to-back meetings. 100% off your first 3 months with code AIDAILY at ⁠⁠⁠⁠⁠⁠⁠http://granola.ai/aidaily⁠⁠⁠⁠⁠⁠⁠Mercury - Modern banking for business and now personal accounts. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://mercury.com/personal-banking⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Zenflow Work - Agents for knowledge work - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://zenflow.free/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Drata - The agentic trust management platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://drata.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai