Podcasts about Hardware

Tech giants and chipmakers are facing off as AI-fueled memory shortages trigger sweeping price hikes on everything from Macs to game consoles. Hear why global supply chain standoffs, long-term contracts, and old-school market forces are quietly reshaping your daily technology. • Apple and Microsoft hike prices on devices amid global memory shortages • Surge in AI data centers drives RAM and storage crisis • Intel's comeback: Core Ultra chips compete with AMD in handheld gaming • Microsoft's pivot to ARM, Qualcomm-NVIDIA alliance, and x86 rivalry • AI fear and backlash; organic concern amplified by international actors • White House abruptly pulls Anthropic's Fable model, sparking industry uproar • US government U-turns on AI regulation, restricts top models to select partners • Tension over AI innovation vs. regulatory "rug pull" and global competition • Smart home chaos: Matter 1.6 standard, Samsung and Level Lock shake-up • Debate over local vs. cloud smart home control and API access fees • Ring and Flock cameras ignite privacy and surveillance state concerns • Social media bans for under-16s fail in Australia, UK, and Norway plan similar rules • BBC Radio 4 long wave broadcast ends after a century • Meta gets caught tracking employees for AI; PlayStation deletes owned movies • US regulators propose removing brake pedals from Robotaxis • Ford's automated systems flop, company rehiring engineers • Farewell to tech journalist and GigaOm founder Om Malik Host: Leo Laporte Guests: Jennifer Pattison Tuohy, Dan Patterson, and Daniel Rubino Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: Simply CX box.com/AI meter.com/twit ZipRecruiter.com/twit superhuman.com

Google is about to roll out its external billing changes to the Play Store, and Micron earnings are through the roof as demand for its chips continue to sky rocket.Starring Jason Howell and Huyen Tue Dao Show notes found here. Hosted on Acast. See acast.com/privacy for more information.

Today, the blow-out Micron earnings report is doing all it can to revive the AI hardware momentum trade, and it will be interesting to see how the huge jump in Micron shares ages into the options expiry this Friday. Elsewhere, the US dollar has continued its rally, but will fresh drivers for further strength be hard to come by? A focus on sterling's upside potential on the potential Burnham political revolution unfolding as well. In commodities, we discuss the latest on crude oil and gold and especially silver getting into existential chart territory. Today's pod features Saxo Head of Commodity Strategy Ole Hansen and is hosted by Saxo Global Head of Macro Strategy John J. Hardy. Links John's The FX Trader piece on whether USD can find fresh fuel and special GBP focus. Bloomberg piece on a hedge fund manager looking to short private equity in interesting ways New York times piece on what kind of managers have demanded that their workers stop working from home.  About twice per week (in normal times, hopefully soon to resume), you will find links discussed on the podcast and a chart-of-the-day over at the John J. Hardy substack. Read daily in-depth market updates from the Saxo Market Call and the Saxo Strategy Team here. Please reach out to us at marketcall@saxobank.com for feedback and questions. Click here to open an account with Saxo. Intro music by AShamaluevMusic DISCLAIMER This content is marketing material. Trading financial instruments carries risks. Always ensure that you understand these risks before trading. This material does not contain investment advice or an encouragement to invest in a particular manner. Historic performance is not a guarantee of future results. The instrument(s) referenced in this content may be issued by a partner, from whom Saxo Bank A/S receives promotional fees, payment or retrocessions. While Saxo may receive compensation from these partnerships, all content is created with the aim of providing clients with valuable information and options.

In this episode, Madelyn O'Farrell talks with Oana Jinga, Co-Founder and Chief Commercial Officer of Dexory, about her non-technical path into tech, how her experience at Telefonica and Google shaped her approach to “knowing the user and knowing the magic,” and how Dexory evolved from a home security robot to retail shelf scanning and ultimately to a global warehouse intelligence platform. They discuss why Dexory chose tall, ground-based robots over drones to safely and efficiently digitize warehouses in real time, what it really takes to win and support enterprise customers like Maersk, DHL, and GXO, and how a robotics-as-a-service model lets customers buy data and insights rather than hardware. Oana also dives into the ethics of robotics and unbiased AI, emphasizing transparency with workers, privacy-aware data practices, and building a diverse team, before painting a picture of the future: supply chains transformed into connected, predictive supply networks powered by distributed intelligence and shared best practices across global sites. Highlights from their conversation include: Oana's Nontraditional Path Into Tech and Career at Telefonica and Google (0:43) What Dexory Is and How It Digitizes Warehouses in Real Time (2:44) Evolution From Home Security Robot to Retail Shelf Scanning to Warehouses (3:40) Why Dexory Chose Tall Ground Robots Instead of Drones (5:30) Selling Enterprise Robotics to Maersk, DHL, GXO, and Other Logistics Leaders (8:40) Robotics as a Service and Selling Data Instead of Hardware (11:51) Global Deployments Across the US, Europe, Australia, and Asia (12:30) Ethics of Robotics, Workforce Impact, and Unbiased AI Practices (15:00) Future of Connected, Predictive Supply Networks and Distributed Intelligence (17:44) Final Thoughts and Takeaways (20:17) Dynamo Ventures is a venture firm backing founders upgrading the physical economy. As intelligence moves into critical infrastructure and technology collides with physics, industry is entering a new era of transformation - the industrial renaissance. Born from the dirt and grit of supply chains and shaped by operations, not spreadsheets, Dynamo focuses on the complex realities of building in the real world. We invest in companies transforming infrastructure, manufacturing, logistics, transportation, and the systems that power global commerce. Dynamo works closely with founders who combine ambition with a bias to action, bringing a builder mindset to venture capital through deep operational insight, systematic pressure-testing and hands-on partnership. Our purpose is simple: to back the relentless shaping the industrial renaissance. Learn more at www.dynamo.vc. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

A structural repricing of memory and silicon components is forcing a shift in the economics of hardware resale for managed service providers (MSPs) and IT service providers. This shift is driven by concentrated demand for memory components from AI infrastructure build-outs, as evidenced by data from IDC and remarks from companies including Apple, Micron, SK Hynix, and Samsung. The episode highlights that memory costs have quadrupled in a year, and that both endpoint devices and servers are experiencing durable price inflation due to component scarcity and intensified competition for supply. The most consequential development cited is Apple's acknowledgment—confirmed by Tim Cook to the Wall Street Journal—that device price increases are now “unavoidable” because the cost of memory can no longer be absorbed. Memory manufacturers' share prices rallied on this signal, reinforcing an investor consensus that higher component costs will persist. IDC data showed AI-focused, non-x86 servers using Nvidia's ARM chips generated $58.7 billion—or nearly 48% of all server revenue—up 107% year over year, while x86 server revenue declined due to DRAM and NAND shortages. This dynamic indicates that AI infrastructure is bidding up component costs at the expense of standard business hardware. Secondary developments further reinforce this mechanism. The market's response to U.S. government announcements regarding Intel chip capacity expansion demonstrates that relief from the silicon crunch remains years away, not months. Channel partners—according to industry reporting—were already pivoting from hardware resale to services prior to these price shocks, with thinning hardware margins preceding the current pressure. The combination of fixed-fee hardware contracts and rising component costs now places providers in a position where they are “short silicon,” having unknowingly absorbed inflation risk they cannot pass on under existing contractual terms. For MSPs and IT leaders, the principal operational implications center on contract structure, exposure to component price volatility, and diminished hardware margins. Providers with fixed monthly agreements or hardware-as-a-service contracts based on last year's component costs are at an increasing risk of margin erosion, as their ability to reprice is contractually limited. Practical mitigation steps include auditing all fixed-fee agreements for exposure, amending contracts to include component index or price adjustment clauses, and separating hardware as a transparent, pass-through line item. Failing to adapt contract terms or refresh timing may compound both financial risk and the security profile of client endpoints. 00:00 Not the Tokens  03:31 An Auction for the Parts 05:46 Short Silicon 07:44 Why Do We Care?   Supported by: Pax8 ScalePad    Sign up for the SMB Online Conference: www.smbonlineconference.com

This week on ClassHorrorCast, we sit down with filmmaker, writer, adventurer and one of cinema's true originals - Richard Stanley.We begin with a look back at his cult classic Hardware and discuss why its themes feel more relevant today than ever before, before moving into Dust Devil and how the film has continued to find new audiences year after year.From there, we dive headfirst into one of the most infamous stories in movie history. The Island of Dr. Moreau.Richard tells the full story of being hired to direct the film, being fired, the complete chaos that surrounded the production, and the strange aftermath that followed.We also talk about how he feels about the experience today and whether his original vision for the film could still one day be seen.We also explore Richard's work as a writer on films such as The Abandoned and Imago Mortis, his process for writing, and his years spent away from filmmaking before making a remarkable return in 2019 with Color Out of Space starring Nicolas Cage.Bringing things right up to the present day, Richard tells us the unbelievable story of writing the third installment in the Winnie the Pooh: Blood and Honey franchise and how he ended up playing the role of villain… or hero… Balthazar von Woozle.Outside of film, Richard has spent years pursuing interests that go far beyond cinema.Living in the French Pyrenees, we discuss his fascination with the Holy Grail, Cathar history and the remarkable story behind his 2001 documentary The Secret Glory, which explored the life of Otto Rahn and his strange place in history.We also talk about his recent book Otto Rahn, Grail Hunter.Finally, we touch on projects still waiting to emerge from the shadows and Richard's continued desire to bring his long-held vision of The Dunwich Horror to life.This is a wide-ranging, fascinating and completely unpredictable conversation with one of genre cinema's most unique voices and one you definitely don't want to miss.For more of my content and to grab a copy of my book - CLICK HEREFor more on Richard's work - CLICK HEREBecome a supporter of this podcast: https://www.spreaker.com/podcast/class-horror-cast-horror-movie-podcast--4295531/support.

Valves neue Steam Machine verspricht den perfekten Plug-and-Play-Wohnzimmer-PC im wunderschönen Design, doch der saftige Preis sorgt aktuell für kollektives Kopfschütteln. Rechtfertigen das offene SteamOS und der winzige Formfaktor die enormen Anschaffungskosten, oder liefert die verbaute Hardware einfach zu wenig Leistung für modernes 4K-Gaming? Gemeinsam mit unseren Tech-Experten Jan und Jusuf analysieren wir die ersten Reviews, zeigen euch günstigere Mini-ITX-Alternativen zum Selberbauen. Für wen sich der kleine Edel-Würfel wirklich lohnt und warum du vorerst vielleicht doch lieber bei deiner Konsole bleiben solltest klären wir im Talk! Alle Links zum GameStar Podcast und unseren Werbepartnern: https://linktr.ee/gamestarpodcast

The Reload's Stephen Gutowski joins Cam to discuss the holding pattern five hardware cases are in at the Supreme Court, with justices once again taking no action on two magazine bans and three challenges to "assault weapon" bans.

Bickley and Tim Ring talk Suns, go through Social Studies, and give out Hardware.

Bickley, Tim, Sammy, and Jarertt hand out awards for the best and worst of the weekend.

We're back! Tonight we're doing something special! We finally discuss the results of our challenge from the WHEEL of DOOM! ==== Special Thanks to Our Patrons! ==== https://thelinuxcast.org/patrons/ ===== Follow us

Habt ihr schon mal mit einer KI über intime Angelegenheiten, wie Beziehungsprobleme oder Ähnliches, gesprochen? Wir haben die selbstständige Psychologin Jolina eingeladen, um mit ihr genau darüber zu sprechen, ob das funktionieren kann und wo die Sache hakt. Wie gut taugen Chatbots wie ChatGPT, Gemini und Co. als Ersatz-Therapeuten? Wie entwickelt sich der menschliche Verstand, wenn man permanent bestätigt wird? Diesen Fragen stellen sich Jan und Maxe, zusammen mit Jolina, im neuesten GameStar Tech Talk. Alle Links zum GameStar Podcast und unseren Werbepartnern: https://linktr.ee/gamestarpodcast

In dieser Ausgabe sprechen wir zunächst über Rückmeldungen zur letzten Sendung und über die Frage, wie digitale Souveränität bei Zahlungen, Banken und Finanzbildung praktisch aussehen kann. Außerdem behandeln wir aktuelle technische Themen wie Cursor, alte P2P-Projekte, lokale LLM-Nutzung auf Apple-Hardware sowie Tools zur Analyse großer Codebasen und zum statistischen Testen nicht-deterministischer Systeme. Im weiteren Verlauf geht es um mehrere Sicherheits- und Open-Source-Themen, darunter einen FreeBSD-Exploit, eine Schwachstelle im Arch User Repository, Systemd als CNA für CVE-Nummern und Probleme mit KI-Agenten in Fedora. Wir sprechen außerdem über Public Money, Public Code, den Umstieg auf Linux in Frankreich, Secure Boot und auslaufende Zertifikate sowie über verschiedene Hardware-, Smart-Home- und 3D-Druck-Projekte.

Send us Fan MailPaul Vizzio is a seasoned hardware engineering leader with deep expertise in building complex electromechanical systems and scaling them from early prototypes to full production. Currently serving as Director of Hardware Engineering at Proteus Motion, Paul led the end-to-end development of a patented 3D resistance training system that has been deployed in more than 400 locations across the U.S. and Canada. His leadership spanned the full product lifecycle—from system architecture and CAD design to manufacturing, supply chain development, and field deployment—culminating in a dramatic cost reduction to approximately 20% of the original prototype while improving assembly efficiency and scalability.  Paul's career reflects a strong ability to operate at both the startup and production scale levels. He has built and led cross-functional teams, driven design-for-manufacturing initiatives, and delivered production-ready systems on aggressive timelines, including bringing initial production units to market in under a year. His work consistently focuses on simplifying complexity—whether through system architecture decisions, supplier strategy, or thoughtful engineering tradeoffs. In addition to his work at Proteus, Paul is the founder of RemieDog, a direct-to-consumer hardware brand, and Vizeng, a consultancy that helps startups accelerate product development from concept to production. Through these ventures, he has worked hands-on across prototyping, injection molding, supplier sourcing, and go-to-market strategy—giving him a well-rounded perspective on both engineering and business execution. Paul is also deeply committed to the broader engineering community. He co-organizes a New York–based hardware meetup with over 14,000 members, serves as a visiting lecturer at Cornell Tech, and has been recognized as one of ASME's Top 25 Early Career Engineers. Across all his work, Paul brings a practical, execution-focused mindset to hardware development—bridging the gap between ambitious ideas and real-world, manufacturable products. LINKS: Paul Vizzio LinkedIn: https://www.linkedin.com/in/paul-vizzio/ RemieDog website: https://remiedog.com/ Aaron Moncur, host Subscribe to the show to get notified so you don't miss new episodes every Friday.The Being An Engineer podcast is brought to you by Pipeline Design & Engineering. Pipeline partners with medical & other device engineering teams who need turnkey equipment like cycle test machines, custom test fixtures, automation equipment, assembly jigs, inspection stations and more. You can find us at www.teampipeline.usWatch the show on YouTube: www.youtube.com/@TeamPipelineus 

In this episode, we discuss Midjourney's surprising pivot to hardware with their full-body ultrasound scanner, a game-changer in preventative healthcare. Additionally, we explore Anthropic's federal ban turning into a marketing narrative, the drama surrounding Amazon's film 'Artificial', and the competitive landscape of AI chips involving AWS, NVIDIA, and Intel.Chapters00:00 Introduction00:00 Midjourney's Ultrasound Pivot00:25 Anthropic's Federal Ban00:44 Amazon's Film 'Artificial'00:49 AWS and Tranium Chips11:32 Intel's Stock Surge Show LinksGet the top 80+ AI Models for $8.99 with the AI Box MCP: ⁠⁠https://aibox.ai/mcpHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

Explore how the latest advancements in AI are shifting from traditional training to inference-focused efficiencies, and how companies like Adaptation Labs are pioneering adaptive, full-stack AI solutions that democratize control across industries.Key topics:The evolution from compute-heavy training models to efficient inference layersHow inference costs are changing despite increasing AI demandThe role of adaptive, gradient-free learning in democratizing AI customizationChallenges with the last 5% reliability gap and continuous learningThe importance of full-stack optimization—from data to interfaces in AI systemsFuture trends: decentralized AI, edge computing, and ongoing innovationTimestamps:00:00 - Introduction to AI trends: scaling vs inference efficiencies01:01 - Sudip's background: Google Brain, DeepMind, and inference infrastructure01:34 - The rapid growth of foundation and large language models02:36 - Comparing traditional ML project timelines to large foundation models04:20 - The transformative potential of foundation models in enterprise and underserved communities05:33 - The shift from task-specific models to general-purpose foundation models07:07 - How inference costs have evolved: the rising demand vs falling per-token costs08:37 - The challenge of inference in trillion-parameter models and the move towards smaller, verticalized models10:14 - Factors driving high inference costs: model size, reasoning, agentic workloads12:13 - The probabilistic nature of inference and API pricing complexities13:07 - Variability in inference costs and demand in real-world scenarios14:14 - The autoregressive, sequential nature of LLM inference and system challenges16:45 - Cost implications of autoregressive inference and the move to more efficient, localized models18:18 - The motivation behind Adaptation Labs: democratizing AI control and customization19:47 - Adaptive, gradient-free continual learning and environment interaction21:26 - Co-optimizing full-stack AI: systems, interfaces, and models22:34 - How interface design impacts AI adoption and continuous learning23:55 - The evolution of techniques: from foundational training to open-source innovations26:18 - Handling the ‘last 5%' reliability challenge in enterprise AI deployments28:02 - The importance of system feedback and adaptive learning in coding and decision-making31:12 - Adaptive Data and AutoScientist: seamless data transformation and model co-optimization32:55 - Use cases: finance, low-resource languages, long context data34:13 - The role of inference techniques and creating high-quality data for customization36:10 - Future of adaptive, task-specific interfaces and continuous, real-time learning38:49 - Full-stack AI: data, models, interfaces, and their iterative feedback loops41:18 - The competition between fine-tuning and adaptive inference techniques43:29 - The origin of new inference techniques: industry labs, open source, and innovation hubs45:27 - The “last 5%” reliability gap: why it's critical and how dynamic learning can help48:27 - Hardware vs software optimization in AI systems and the future of systemic efficiency51:25 - Growing AI demand, hardware constraints, and the opportunity for systemic innovation52:48 - The shift from training to inference and decentralized AI models at the edge54:12 - Final thoughts: the evolving landscape and long-term AI innovationConnect with Sudip:LinkedInConnect with Nataraj:⁠LinkedIn⁠

En weer moet ASML dealen met de Amerikaanse regering. Dit keer is het handelsminister Howard Lutnick die de directie op het matje roept. Volgens hem zouden de nieuwste machines van ASML naar China gaan, ondanks het exportverbod. Persbureau Bloomberg sprak met mensen uit de Amerikaanse regering. Die zeggen bewijs te hebben, zonder bewijs te overleggen. ASML ontkent en zegt dat ze helemaal geen nieuwste machines leveren. Hoe dan ook: het is wéér gedoe dat ASML op zijn bordje krijgt. Hoe moet het bedrijf hier nu weer mee omgaan? We kijken er deze aflevering na. Ook wat dit met je ASML-aandeel doet. Hebben we het ook over het nieuws Prosus. Dat krijgt steeds meer vorm, blijkt uit de nieuwe trading update. Maar wanneer kennen beleggers ook die hogere beurswaarde toe aan het bedrijf? Verder gaat het over SpaceX. Dat ging als een raket op de beurs, maar de motor begon te haperen. De koers van het aandeel ging naar beneden. Ondertussen probeert het bedrijf nog even 20 miljard op te halen bij investeerders, nadat het afgelopen week al ruim 80(!) miljard ophaalde. Gaat het ze lukken? Ook kijken we naar de falende robotaxi's van Aplhabet, mogelijke claims tegen Meta en we bespreken de deal tussen Iran en de VS. Is die deal nu alweer mislukt? Te gast: Errol Keyner van de Vereniging van Effectenbezitters 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. Je hoort hem ook in de BNR-podcast Moerdijk: dorp van de rekening. 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.

In this episode, we discuss Midjourney's surprising pivot to hardware with their full-body ultrasound scanner, a game-changer in preventative healthcare. Additionally, we explore Anthropic's federal ban turning into a marketing narrative, the drama surrounding Amazon's film 'Artificial', and the competitive landscape of AI chips involving AWS, NVIDIA, and Intel.Chapters00:00 Introduction00:00 Midjourney's Ultrasound Pivot00:25 Anthropic's Federal Ban00:44 Amazon's Film 'Artificial'00:49 AWS and Tranium Chips11:32 Intel's Stock Surge Show LinksGet the top 80+ AI Models for $8.99 with the AI Box MCP: ⁠⁠https://aibox.ai/mcpHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

In this episode, we discuss Midjourney's surprising pivot to hardware with their full-body ultrasound scanner, a game-changer in preventative healthcare. Additionally, we explore Anthropic's federal ban turning into a marketing narrative, the drama surrounding Amazon's film 'Artificial', and the competitive landscape of AI chips involving AWS, NVIDIA, and Intel.Chapters00:00 Introduction00:00 Midjourney's Ultrasound Pivot00:25 Anthropic's Federal Ban00:44 Amazon's Film 'Artificial'00:49 AWS and Tranium Chips11:32 Intel's Stock Surge Show LinksGet the top 80+ AI Models for $8.99 with the AI Box MCP: ⁠⁠https://aibox.ai/mcpHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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

We hebben het over Kevin Warsh, kersverse baas van de Fed. Op zijn eerste persconferentie maakte hij duidelijk dat het anders moet. De afgelopen vijf jaar heeft de Amerikaanse centrale bank de doelstelling niet gehaald en dat gaat hij nu anders doen. De Fed gaat op de schop. Er komen vijf werkgroepen die onderzoek wat er moet veranderen. Eén ding is al gelijk aangepast: de schriftelijk verklaring. Die is drastisch ingekort. Alleen doet hij niet wat hij (van president Trump) moet doen en dat is de rente verlagen. Sterker nog, die gaat dit jaar zo goed als zeker omhoog. Deze aflevering kijken we wat dit alles betekent voor jou en of hij jou óók teleurstelt. Tim Cook komt ook voorbij. De vertrekkend ceo van Apple kwam met slecht nieuws voor klanten. De prijzen moeten omhoog, want de inkoop van chips is veel te duur geworden. Opvallend, want Apple was een van de laatste technologiebedrijven die het tekort aan geheugenchips juist de baas bleef. We hebben het ook over de beleggersdag van Besi. Daar is voor ons Jordy Beuving van De Aandeelhouder. Hij vertelt waarom Besi zijn omzet- en winstdoel flink verhoogt en vertelt meer over de orders voor hun paradepaardje. Verder ook aandacht voor Box 3, de Iran-deal en Maserati. Te gast: Hans Oudshoorn van Saxo (die ook meer vertelt over investeren in netcongestie) 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. Je hoort hem ook in de BNR-podcast Moerdijk: dorp van de rekening. 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.

BRADY KANNON (Golf.com, SportsGrid, CBS Sports) The US Open tees off at Shinnecock Hills tomorrow and the conditions could make an already difficult course set-up almost unplayable, so which golfers could benefit from the weather and playing conditions? No surprise, Scottie Scheffler is the favorite, but are the odds not actually in his favor? Who else does Brady like for golf's third major? :30- Get out the bacon; it's time for the Baseball Brunch! Today's brunch is starring Cal Raleigh and Logan Gilbert, the two best friends that anybody could have! :45- It's time to hand out some hardware! See omnystudio.com/listener for privacy information.

Na vele dagen aan bombardementen en escalatie zijn de VS en Iran het eens over een voorlopig vredesakkoord. Een plan dat bestaat uit veertien punten, waarvan de opening van de Straat van Hormuz de belangrijkste is. Een ander punt valt ook op: een fonds van 300 miljard dollar voor de wederopbouw van Iran. Deze aflevering kijken we wat deze deal nu precies voor jou als belegger betekent. Hebben we het ook over het nieuwe dreigement van president Trump. De deal moet nog ondertekend worden, maar hij waarschuwt de Iraniërs nu al. 'Als ik het er toch niet mee eens ben, of als ze zich niet gedragen, gaan we weer op ze schieten en bommen op hun hoofd gooien.' Of die oorlog in Iran nu eindigt of niet, één sector is al slachtoffer. De autosector. De koersen van autobouwers tuimelen omlaag. Allemaal na een winstwaarschuwing van BMW. De Duitse bouwer verwacht een lagere operationele winstmarge dit jaar. Tussen de 1 en 3 procent. Terwijl die verwachting eerder nog op 6 procent lag. Dat moet beter, zegt Noud Broekhof van de Nationale Autoshow. Je hoort hem deze aflevering. Verder staan we stil bij SpaceX (de koers daalt) en het feit dat 'Mr Big Short' niet short wil gaan op het nieuwe beursbedrijf. Ook in de aflevering: De Snap Specs. Het 'levenswerk' van Evan Spiegel Het aandeel Ahold Delhaize. Waarom daalt dat al sinds het bekendmaken van de kwartaalcijfers? Intel moet bewijzen dat het de extreme koersstijging waard is Te gast: Niels Koerts van Stockwatch.nl 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. Je hoort hem ook in de BNR-podcast Moerdijk: dorp van de rekening. 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.

Are your fleets investing in the wrong AI dashcam technology? Nuclear verdicts and climbing insurance costs mean you can't afford to treat dashcams like commodity hardware. Dr. Stefan Heck, CEO of Nauto, explains the critical difference between reactive and predictive AI, highlighting how advanced systems can prevent collisions and save lives. Learn why accuracy, speed of detection, and real-time driver coaching are crucial for true safety. Follow the FreightWaves Today Podcast Other FreightWaves Shows Learn more about your ad choices. Visit megaphone.fm/adchoices

What if the biggest bottleneck in hardware design isn't your engineer's skill — it's the sheer volume of manual work standing between a great idea and a working schematic? And once you decide to embrace AI-assisted design, how do you make sure the output is actually trustworthy enough to build from? What you'll learn… (00:12) Why fragmented workflows hit SMB hardware teams hardest (02:39) The real cost of going from requirements to prototype without specialist support (07:33) How functional block-level design changes early decisions — including when a SOM beats building from scratch (12:04) Why system-level abstraction catches wrong-path decisions before they reach the schematic (14:39) The "rubber duck debugging" effect: how AI clarifies requirements before they become costly mistakes (17:54) The biggest AI misconception in hardware design — and why the engineer must own every decision (20:30) How CELUS's NXP collaboration delivers manufacturer-validated, human-in-the-loop solutions (25:05) Why abstraction-first tools help SMBs take on projects that would otherwise be out of reach (28:19) The CELUS Success Program: high-touch onboarding for SMBs on the Siemens instance More about the episode… In this episode of the Printed Circuit Podcast, host Steph Chavez welcomes back Antonio Becerra Esteban, VP of Customer Success at CELUS — a physicist-turned-engineer with experience at Infineon and Altium who now leads the team ensuring customers extract real value from the platform. The conversation tackles the fragmented, manual journey from requirements to schematic that burdens small hardware teams. Antonio explains how CELUS's functional block-level design approach lets engineers define system architectures, navigate component trade-offs with an AI assistant, and output fully-interconnected schematics — illustrating the point with a Linux-based HMI example where the right abstraction layer turns a complex MPU build into a simple SOM selection. On the trust question, Antonio is direct: the engineer must own every decision. CELUS backs this up with manufacturer-validated design blocks, transparent sourcing, and a human-in-the-loop process — putting engineers in the driving seat rather than asking them to ship whatever the model produces. SMBs can join CELUS' Success Program by sending an email to cs@celus.io. Connect with Steph Chavez: LinkedIn Website Connect with Antonio Becerra Esteban: LinkedIn CELUS Website

Is the VR industry going through a "Great Reset"? In this episode of the Gamertag & Bradley Podcast, we break down the reality of mainstream VR adoption, Valve's imminent Steam Frame and Steam Machine launch preparations, and Apple's massive Vision OS developer updates. We also dive into how AI hardware demand is creating component shortages that could drastically impact next-gen headset pricing!Main topics:

Are your fleets investing in the wrong AI dashcam technology? Nuclear verdicts and climbing insurance costs mean you can't afford to treat dashcams like commodity hardware. Dr. Stefan Heck, CEO of Nauto, explains the critical difference between reactive and predictive AI, highlighting how advanced systems can prevent collisions and save lives. Learn why accuracy, speed of detection, and real-time driver coaching are crucial for true safety. ⁠Follow the FreightWaves Today Podcast⁠ ⁠Other FreightWaves Shows⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

Bickley and Marotta talk Diamondbacks, go through Social Studies, and hand out Hardware.

Dan, Vince, Sammy, and Jarrett hand out awards for the best and worst of the weekend.

(0:00) Intro *Reference to the Boardroom Governance Summit at Limerick Lane Cellars, Healdsburg, California (Aug 26-27, 2026)  (2:12) About the podcast sponsor: The American College of Governance Counsel. (2:59) Start of interview.  (4:00) Origin Story of Emily, and Stewardship  (6:15) From Engineer to CEO  (7:14) Companies that she led: Elo Touch Systems (97-00), Capstone Turbine (02-03), Apexon (04-07) and NovaTorque (09-17). (9:50) Changing geopolitics of manufacturing (10:49) First Boards and Public Company Lessons (first board experience in Japan) "The soft skills are the hard part to do." (15:48) On serving in private VC-backed boards. "If you know one board, you know one board. I mean, they are all so different." (22:43) On serving in non-profit boards. "It's one of the best possible ways to get governance experience." (26:20) CEO Mistakes (32:03) Board Succession for leadership and skills. (35:33) Board Evaluations Done Right  (37:41) What Makes Great Directors. *reference to Leading Edge Stewardship, by Linda Riefler and Mayree Clark (Stanford Women on Boards). "Asking the right question, at the right time, in the right way." (39:57) AI and the Boardroom. (46:16) Innovation Versus Oversight. "The goal is informed oversight without operational interference" (49:34) Teaching Governance to Stanford Students  (52:17) Boards need to have a long-term orientation in this short-term world. (52:34) Books that have greatly influenced her life: The Bible Why Nations Fail: The Origins of Power, Prosperity, and Poverty, by Daron Acemoglu and James A. Robinson (2012) The Count of Monte Cristo by Alexandre Dumas (1846) (54:12) Her mentors. "[T]hey told me things I needed to hear in a way that I could hear them because it's easy to get defensive." (55:38) Quotes that she thinks of often or lives her life by. "Never doubt that a small group of thoughtful, committed, citizens can change the world. Indeed, it is the only thing that ever has.' by Margaret Mead. (56:43) An unusual habit or an absurd thing that she loves.  (57:30) The living person she most admires in governance: Bob Joss. Emily Liggett serves on the boards of Ultra Clean Technology and Materion Corporation. She also serves as Lecturer at Stanford GSB, where she teaches corporate governance and board leadership. You can follow Evan on social media at:X: @evanepsteinLinkedIn: https://www.linkedin.com/in/epsteinevan/ Substack: https://evanepstein.substack.com/__To support this podcast you can join as a subscriber of the Boardroom Governance Newsletter at https://evanepstein.substack.com/__Music/Soundtrack (found via Free Music Archive): Seeing The Future by Dexter Britain is licensed under a Attribution-Noncommercial-Share Alike 3.0 United States License

Joe Illidge Breaks Down Dakota's Legacy and the Future of Milestone in DC's New History of the DC Universe Comic book history is full of legendary moments, but few were as revolutionary as the arrival of Milestone Media in the 1990s. Created by industry visionaries including Dwayne McDuffie, Denys Cowan, Michael Davis, and Derek Dingle, Milestone introduced a wave of heroes that reflected communities and perspectives rarely seen in mainstream comics. Now, that legacy continues with New History of the DC Universe: The Dakota Incident #1, a powerful new anthology exploring Dakota City's place within the larger DC mythology. At the center of this project is Joe Illidge, a respected creative voice in the comics industry who has worked across editorial, writing, and cultural advocacy roles throughout his career. Illidge has long been connected to the spirit of Milestone storytelling — stories that combine superhero action with real-world themes about identity, community, and social change. In The Dakota Incident, the narrative digs deeper into the events surrounding Dakota City and the heroes who protect it, exploring how these characters intersect with the broader history of the DC Universe. For longtime fans, the story represents a powerful return to one of comics' most important cultural milestones. For new readers, it offers an opportunity to discover why characters like Static, Icon, Rocket, and Hardware remain so influential today. As Illidge and the creative team expand the mythology of Dakota, they also reaffirm something fans have always known: Milestone isn't just a comic imprint. It's a movement. YT: https://www.youtube.com/watch?v=C4vlc6tw7tw If you love comic book history, storytelling, and behind-the-scenes industry insights, this episode is for you. Subscribe for more creator interviews and comic book news! Follow Joe on Social Media at @illmasterone Get your copy of THE DAKOTA INCIDENT is #1 On Sale Now! Also check out ILLUMINOUS at https://www.illuminousideas.com. The Milestone Revolution: A Visual Timeline of Dakota City 1993 — Milestone Media Is Born In 1993, four visionary creators Dwayne McDuffie, Denys Cowan, Michael Davis, and Derek T. Dingle launched Milestone Media, a publishing initiative designed to bring new voices, authentic communities, and diverse perspectives into superhero comics. Partnering with DC Comics for distribution, Milestone quickly became one of the most culturally important imprints in comics history. Their mission was simple but revolutionary: Create Superheroes that reflected the REAL World! 1994 — Dakota City Debuts The world is introduced to Dakota City, a fictional urban setting inspired by real American cities. Four major series launch almost simultaneously: • Static – teenage hero Virgil Hawkins becomes the electrifying voice of a new generation • Icon – an alien with the perspective of a Black conservative intellectual • Hardware – a corporate genius turned armored vigilante • Blood Syndicate – a street-level gang of superpowered antiheroes These comics brought social commentary, urban realism, and cultural authenticity rarely seen in superhero books at the time. 2000 — Static Shock Hits Television The character Static explodes into mainstream pop culture with the animated series Static Shock. The show runs for four seasons and introduces Dakota City and its heroes to an entirely new generation of fans. For many viewers, Static Shock becomes their first Black teenage superhero role model on television. 2020 — Milestone Returns After years of absence, Milestone Media returns with a major revival initiative. New series reintroduce Dakota City for modern readers: • Static Season One • Icon and Rocket Season One • Hardware Season One The revival reconnects the characters to the modern DC Universe while maintaining the cultural themes that made Milestone iconic. 2026 — The Dakota Incident Expands the DC Universe   With New History of the DC Universe: The Dakota Incident #1, Dakota City's heroes are woven deeper into the mythology of the DC Universe. This anthology explores how Dakota's heroes and history intersect with the larger DC timeline expanding the legacy of Milestone while opening new doors for future storytelling. For longtime fans, it's a celebration of a revolutionary imprint. For new readers, it's a reminder that Dakota City remains one of the most important settings in comic book history. Thank you for Watching / Listening! We appreciate your support! Host Al Mega Follow on Twitter | Instagram | Facebook: @TheRealAlMega / @ComicCrusaders Make sure to Like/Share/Subscribe if you haven't yet Rumble/Twitch: ComicCrusaders YouTube: / comiccrusadersworld Visit the official Comic Crusaders Comic Book Shop: comiccrusaders.shop Visit the OFFICIAL Comic Crusaders Swag Shop at: comiccrusaders.us Main Site: https://www.comiccrusaders.com/​​​​ Edited/Produced/Directed by Al Mega Want to create amazing live streams like ours? Then look no further than StreamYard! The BEST and EASIEST to use Streaming Solution on Earth! Check it out at: : https://streamyard.com/pal/d/6492786798886912

Nach den umstrittenen Experimenten der Vorgänger kehrt die legendäre Shooter-Reihe mit Gears of War: E-Day endlich zu ihren Wurzeln zurück. Das Prequel schickt uns 14 Jahre vor den allerersten Teil und lässt uns die dreitägige Tragödie des Emergence Days hautnah miterleben. Felix diskutiert mit Tobi und Dimmy, warum die Rückkehr der Fan-Lieblinge Marcus und Dom sowie die strikte Absage an leere Open-World-Areale genau die richtige Entscheidung von Microsoft ist. Wir analysieren alle frischen Infos direkt von den Entwicklern zu den neuen Movement-Details, der von Grund auf neu gebauten Grafik-Pracht und dem gewohnt starken Koop-Modus. Alle Links zum GameStar Podcast und unseren Werbepartnern: https://linktr.ee/gamestarpodcast

Het is gelukt: er ligt een deal tussen Iran en de VS. Komende vrijdag wordt 'ie ondertekend in Zwitserland. Dan krijgen we ook de details. Voor nu is er nog een hoop onduidelijk, bovendien moet een deel ook nog ná het tekenen worden uitonderhandeld. Toch stelt het beleggers, zeker in de VS, vast gerust. Amerikaanse beurzen staan fors hoger. Is dat terecht of voorbarig? We zoeken het voor je uit. Gaan we je ook vertellen over de nieuwste tegenslag van Anthropic. De twee paradepaardjes van het bedrijf, AI-modellen Fable en Mythos, mogen de VS niet meer uit door een ingreep van de Amerikaanse overheid. Het zoveelste voorbeeld van de bekoelde relatie tussen die twee en bovendien een pijnlijke tegenvaller zo vlak voor de aanstaande beursgang. In hoeverre die daarmee ook in gevaar komt, gaan we ook bespreken. Hoor je ook nog over: Wéér een social media verbod en in hoeverre dat een gevaar is voor social media bedrijven Een kans in defensie voor een Frans autobedrijf RvC's die aandeelhouders passeren in hun bonusbeleid Nieuwe importheffingen van Donald Trump Te gast: Jean-Paul van Oudheusden van eToro en Markets Are Everywhere 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. Je hoort hem ook in de BNR-podcast Moerdijk: dorp van de rekening. 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.

Josh Swihart is the founder of ZODL: the Zcash Open Development Lab. Basically a for profit reincarnation of the old Electric Coin Company, which inherited the dev teams and projects. During his previous Bitcoin Takeover podcast appearance in November 2024 (S15 E62), Zcash was a struggling privacy project with very little support and a rather disappointing price action. In June 2026, Zcash is the rising star of the cryptocurrency market, with plans to scale to billions of users and ever-improving shielding technology. In this episode, we talk about the good, the bad, and the controversial moments in the recent history of Zcash... and why Bitcoin didn't activate Zerocash yet. Time stamps: 00:01:14 Intro: Josh Swihart returns after 20 months 00:02:07 Why Zcash is "in a class of its own" (and self-defeating) 00:03:28 Shielded note Q: the run on the Orchard pool before Iron Wood 00:05:22 What are shielded pools? Sprout, Sapling, Orchard explained 00:06:26 The Orchard vulnerability found by Taylor Hornby 00:06:48 Why Zcash matters to Bitcoin: Zerocoin, Zerocash, Halo 2 00:09:06 The secret: from near-delisting at $30 to near top 10 00:11:03 Governance battles, killing the dev fund, refocusing ECC 00:13:03 Peacemonger research and focusing on the first 100 users 00:14:09 Keystone, NEAR intents swaps, and shielded pool growth 00:15:23 Reflexivity and the macro case (Canadian truckers, seizures) 00:16:32 Cake Wallet, Vic Sharma, and the ZEC integration recognition problem 00:17:57 The Monero rivalry and the privacy renaissance 00:19:35 "Cypherpunk does not mean criminal": Samourai vs Wasabi 00:23:04 Railgun comparison and why fungibility matters 00:25:02 Zmap, Flexa, and spending shielded ZEC in stores 00:26:21 Buying lunch at Chipotle and a Ford F150 truck with Zcash 00:27:33 Giveaway setup + sponsors 00:30:32 Why is Zcash "lied about a ton"? 00:34:03 Debunking the low anonymity-set myth and DeFi integrations 00:35:48 "Main character syndrome," paid FUD, and the influencer claim 00:38:50 Uncorrelated price + maximalist FUD around the Orchard bug 00:40:40 The ethics of disclosure and Taylor Hornby's character 00:45:03 The security budget problem and Network Sustainability Module 00:46:56 Scaling Zcash: Tachyon, recursion, and off-chain services 00:49:35 Do shielded memos bloat the chain? 00:51:32 The shielded stablecoins / shielded assets debate 00:58:31 Last giveaway call + ZODL phone overheating 00:59:12 New user Q: where's the privacy when you spend? 01:01:02 Shielded vs transparent transactions explained 01:03:22 Number reveal and winners 01:06:39 Crypto Visa/Mastercard debit cards: winning or losing? 01:09:56 Has Bitcoin been co-opted? Adam Back and incentives 01:15:20 What stops Zcash from being co-opted like Bitcoin? 01:19:52 Decentralization and killing the trademark agreement 01:21:31 Many orgs now: Foundation, Shielded Labs, Tachyon, Valor 01:23:21 No funding from exchanges or mining pools 01:26:04 ZODL origin: Balaji, fundraising, and the ECC split 01:29:17 ZODL's business model: 50 bps on swaps 01:30:01 Hardware wallets: Keystone, Passport, Trezor Safe 7 01:34:07 How Slush discovered Bitcoin through Zooko 01:35:37 Zcash ASIC demand and decentralizing mining 01:38:51 ECC wind-down, the Bootstrap settlement, and dev funds 01:42:38 Thoughts on ZNS (Zcash Naming Service) 01:44:47 Living with the FUD and "Zionist coin" conspiracies 01:46:31 Why disclose the bug publicly? Transparency vs trust 01:48:18 Inside the emergency coordination with pools and exchanges 01:49:52 Echoes of Bitcoin's 2013 hard fork 01:51:49 Iron Wood and Tachyon upgrade timelines 01:53:31 Closing: the Zcash dance and where to follow Josh

We chose to spend our 101st episode celebrating and platforming Sage Hardware! It's not often we get to chat with people who blend diverse genres like metalcore, cybergrind, and vaporwave; and Shortstuf888 pulled someone that made perfect sense to fill the role. We started a few minutes late due to some technical difficulties, but we made sure to make time to cover a series of interesting and important topics, like breakcore, digital hardcore, and what it was like touring with a post-rock-influenced screamo band. Alex regaled us with the story behind BasshouseHTML's mantra "steal from big business", he got to share a geekout moment with Shiro about Justin Pearson's many projects, and Sage also mentioned a pivotal moment getting into producing electronic music thanks to his love of Lil Ugly Mane. During several moments, the trio expressed their love of Angel Marcloid's various projects. Alex mentioned that his father plays bassoon in a quartet that covers video game music; and the squad talked about what he learned about Japanese culture while touring in Japan. We had a lot of fun during our 101st episode, so tap in if you want to hear the skinny on Venetian masks, Maryland, West Virginia, and the subjectivity of art and music! You heard it on "Hot Takes"!   "Hot Takes" is a safe space for all opinions! Join the conversation at https://linktr.ee/hottakesvapor

On this episode of For Mac Eyes Only: Join Mike and Darren as they provide a rundown of Apple's sharing technologies and the confusion surrounding them. What are AirPlay, AirDrop, Universal Control, and Continuity? What do they do, how can they help us, and how to make sure they're on if you'd like to take advantage of them. Mike shares a FMEO Quick Tip for removing sensitive data from your photos. The episode wraps with Mike's Essential App pick: Cats Lock!

Artificial intelligence is moving faster than ever, but as AI models continue to grow in size and complexity, the challenges surrounding inference performance are becoming impossible to ignore. In this week's podcast, ElastixAI CEO Dr. Mohammad Rastegari and I chat about how we can overcome those challenges and why a different approach to AI infrastructure is necessary for the next generation of AI innovation. We also explore the key bottlenecks limiting inference performance, how ElastixAI is tackling these issues, and why FPGAs are emerging as a compelling platform for accelerating large language model inference.

Daniel is joined by Dr. Andreas Kuehlmann, General Manager of Security Solutions at Arteris. He has over 35 years of experience in semiconductor design, software, and cybersecurity, including roles at IBM Research, UC Berkeley, Cadence, and Synopsys. Previously, he was CEO of Cycuity, which was acquired by Arteris. Dan explores… Read More

Düstere Story-Ansätze wie in The Witcher, folgenschwere Konsequenzen wie in Baldur's Gate und ein simuliertes Handwerksleben wie in Kingdom Come? Das neue Fable will verdammt viel auf einmal sein, doch hinterlässt das erste Gameplay nach dem großen Reveal viele Fragezeichen. In diesem Talk analysieren Lea, Dimi und Micha, ob der gewagte Spagat zwischen epischer RPG-Tiefe und alberner Sandbox-Lebenssimulation wirklich gelingen kann – oder ob sich das Reboot am Ende völlig zwischen den Stühlen verrennt. Alle Links zum GameStar Podcast und unseren Werbepartnern: https://linktr.ee/gamestarpodcast

Are we prepared for the deployment of a functional quantum computer? This week, Technology Now is returning to the topic of post quantum cryptography. We ask why the deadline for migrating to PQC enabled systems has been moved up, we discover what a quantum computer actually needs to be cryptographically relevant, and we pose the question: when it comes to migrating your systems to quantum resistant forms of encryption, could it already be too late for some people to start?This is Technology Now, a weekly show from Hewlett Packard Enterprise. Every week, hosts Michael Bird and Sam Jarrell look at a story that's been making headlines, take a look at the technology behind it, and explain why it matters to organizations.

Welcome back to the Menlo Midweek Podcast! We are in Week 3 of our series, "GLITCH: Being Human in a Machine World." This week, host Matt Summers and Phil EuBank are joined by a special guest: Paul, co-founder of Faith Work and Tech. In an episode titled "Hardware Crash," the three of them dive into the very real, physical nature of burnout. Living and working in the Bay Area, it's incredibly easy to operate as if we are just a "brain in a jar," ignoring our hardware (our physical bodies) to constantly serve our software (our productivity, careers, and output). But as we see in the story of the prophet Elijah in 1 Kings 19, when you crash hard, God doesn't send a software update or a productivity hack. Sometimes, the most spiritual thing you can do is take a nap and eat a snack.

Streaming games on Twitch has become really simple with the variety of tools available, capture cards and streaming software. In this episode the duo talk about the involved process of streaming retro games using period correct retro hardware

Das AES+ bring gegen Ende des Jahres einen der größten Arcade-Klassiker zurück auf den Markt: das Neo Geo! Die Hardware von SNK, die gleichzeitig Konsole und Spielhallen-Automat war, blickt bis dahin auf über 35 Jahre Geschichte inklusive Kult-Games und -Serien wie FATAL FURY, KING OF FIGHTERS, LAST RESORT, BIG TOURNAMENT GOLF, BLUE'S JOURNEY, WINDJAMMERS, SUPER SIDEKICKS, GAROU MARK OF THE WOLVES uvm.! Gregor bespricht mit Sia das umfangreiche Lineup und die verschiedene Hardware, die es gegeben hat. Werbung: https://linktr.ee/Podcastsrbtv Learn more about your ad choices. Visit megaphone.fm/adchoices

Get in Touch! Send us a message.The meeting went great. New construction, open concept, mixed materials. Navy island, warm wood tones, and very specific hardware: long, linear, brushed nickel pulls. Not round. They mentioned the round knobs three separate times in a way that made it clear they had feelings about it.You walked them out feeling genuinely good about this one. Then you went to the back office to hand it off.Twenty minutes. You covered the layout, the finishes, the lead times. Hardware: "Brushed nickel pulls. Long, linear. Specific aesthetic." And you moved on.Three weeks later the order comes through for review.Amerock round knobs. Oil-rubbed bronze.Nobody made this mistake on purpose. But every time information passes from one person to another, it degrades. You knew exactly what the clients meant. By the time you summarized it, some of the texture was gone. By the time your PM ordered from your summary, more was gone. By the time it reached the supplier — bronze and round.The issue isn't that your process is broken. It's that you became the filter. And when you're the filter, you're also the bottleneck, the single point of failure, and the person stuck in every handoff to keep information intact.In this episode, we talk about raw data transfer — and what changes when your team hears the client's actual words instead of your summary of them.What you'll hear:Why the telephone game costs you reorders, restock fees, and client trustHow sharing the transcript instead of the summary removes you as the single point of failureWhat happens to your team over time when they access the source directlyGet the AI Note-taking Guide → cabinetnotes.com

Episode 302: This week's episode AI is moving beyond answering questions — it's beginning to rewrite the systems beneath itself, raising a critical question: who builds the brake pedal when autonomous agents start making decisions at scale? We pair that warning with tech that inspires and unsettles, from NASA's Nancy Grace Roman Telescope launching early to Microsoft testing office‑focused AI hardware that sparks immediate privacy concerns. Gwen Way also spotlights the Roro Lee Pocket AI and the real implications of recording‑consent laws and cloud‑stored data.We round things out with the cultural side of automation: Hinge's AI conversation starters, Instagram's AI support bot missteps, and Hasbro testing AI personalities for classic characters. A full hour of tech news with real‑world takeaways, not hype this is the episode you don't skip all coming up on TechTime Radio, with a little whiskey on the side.-- Full Episode Details:AI isn't just answering questions anymore, it's starting to write the system underneath itself, and that should make every tech user pause. We kick things off with a stark warning from inside the AI world: if the industry only has a gas pedal, what does a “brake pedal” look like, and who gets to press it when autonomous AI agents start making decisions at scale?From there, we keep it moving with tech that feels hopeful and tech that feels invasive. We talk NASA's Nancy Grace Roman Space Telescope launching ahead of schedule and why its massive field of view could reshape what we know about dark energy and galaxy formation. Then we come back down to Earth with Microsoft testing AI hardware for office workers, including a wearable badge concept that raises immediate privacy questions. Gwen Way joins us for Gadgets and Gear with the Roro Lee Pocket AI agent, a Kickstarter device designed to capture meeting notes and turn them into action plans, plus a straight talk moment about recording consent laws and where your data really goes when “the cloud” is involved.We also hit the cultural side of automation: Hinge rolling out AI to help people start dating conversations, Instagram's AI support bot creating a security mess, and Hasbro experimenting with AI chatbots for icons like Optimus Prime and Mr. Potato Head. Add a whiskey tasting of Arbeiki 1794 Highland Rye Single Grain Scotch and you've got a full hour of tech news for everyday people with real takeaways. If you like the show, subscribe, share it with a friend, and leave a review so more listeners can find us.Send us Fan MailSupport the show

Tony Fadell created the iPod, co-created the iPhone, and founded Nest (which he sold to Google for $3.2 billion). He's co-authored over 300 patents, was part of the legendary team at General Magic, and wrote one of the most important and inspiring books for builders, called Build.In our in-depth conversation, we discuss:1. The heated internal debates about whether the iPhone should have a physical keyboard2. Why opinion-based decisions are essential for v1 products3. Why marketing matters as much as the product itself, and how the iPod almost failed4. Why voice will eventually become the primary interface with AI5. Why cognitive surrender to AI is the biggest risk facing product builders today—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more: https://workos.com/lennyVanta—Automate compliance, manage risk, and accelerate trust with AI: https://vanta.com/lenny—Episode transcript: https://www.lennysnewsletter.com/p/father-of-the-ipod-and-iphone-on—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Tony Fadell:• X: https://x.com/tfadell• LinkedIn: https://www.linkedin.com/in/tonyfadell• Website: https://www.buildc.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Tony Fadell(02:23) The Blackberry vs. iPhone keyboard debate(07:50) Micromanaging vs. kind lies: what great products actually need(15:57) The Nest thermostat and smoke alarm story(21:22) How to decide what's worth building: pain plus new technology(27:36) The three-generation rule: why nothing works the first time(34:20) The full customer journey: why marketing defines your product(40:53) The power of storytelling and the press-release-first approach(48:37) The evolution of product management and the builder role(50:27) Why AI-generated code creates brittle, unmaintainable products(58:00) Storytelling techniques(1:05:45) The next iPhone(1:13:15) Hardware is back(1:17:01) What Tony is most excited about(1:21:38) Working with Tony(1:25:36) Ethics, morals, and the responsibility of product builders(1:32:40) How to connect with Tony and Build Collective—References: https://www.lennysnewsletter.com/p/father-of-the-ipod-and-iphone-on—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Burnout is what happens when biology rebels against technology. We ignore our hardware (bodies) to serve the software (productivity). We revisit Elijah under the broom tree, a prophet who crashed hard. God didn't send a software update; He sent a nap and a snack. We will address trauma, the body keeping the score, and the "High Tech / Deep Touch" reality that we need physical restoration, not just spiritual ideas. Text Our Team (650) 600-0402 | Connect With Us

- Counterpoint: LATAM Smartphone Shipments Up 2% in Q1FY26 - Counterpoint Sees Smartphone Shipments Dropping 14% YoY - Omdia and AppleInsider at Odds Over OLED MBP Launch Window - Ming-Chi Kuo Says Ternus Killed Apple Headset Development - Interest Drops on Apple Card Savings Account - New Neighbors for "Your Friends & Neighbors" Season-Three - Apple TV Drops a Trailer for "Lucky" - Sponsored by NordLayer: Get an exclusive offer - up to 22% off NordLayer yearly plans plus 10% on top with coupon code: macosken-10-NORDLAYER at nordlayer.com/macosken - Sponsored by Notion: Learn more about Notion's Developer Platform today at notion.com/macosken - Catch Ken on Mastodon - @macosken@mastodon.social - Send Ken an email: info@macosken.com - Chat with us on Patreon for as little as $1 a month. Support the show at Patreon.com/macosken

Pre-show: