Podcasts about gpus

Send us Fan MailYour best prospects are not saying “no.” Most of the time, they're saying “not yet,” and the gap between now and their buying window is where deals quietly die. I sit down with John McLaughlin, CEO of 12touches.com, to talk about a simple way to stay top of mind without becoming a nuisance: send consistent, curated industry value that makes you useful even when nobody is ready to buy. John shares how he built a newsletter engine that curates hundreds of enterprise IT articles each week, organizes them into clean topic buckets, and uses real audience click behavior to surface the most relevant stories. We get specific about why “built-in substantiation” matters for B2B sales and thought leadership, how separating vendor content from vendor-neutral coverage protects trust, and why a newsletter that stops after two issues can hurt you more than help you. We also break down LinkedIn newsletters as a free distribution channel that behaves like email, stays opt-in, and becomes searchable on LinkedIn and Google. Then we zoom out into what the tech community is worried about right now: phishing and stolen credentials, AI agents probing systems, quantum computing implications for encryption, plus the very real infrastructure strain behind AI such as high-performance storage, GPUs, rack density, power, cooling, and water use in data centers. If you want a practical personal branding and social selling play that compounds over time, this one is for you. Subscribe, share this with a sales pro who's tired of “just checking in,” and leave a review with your biggest takeaway.Thanks for tuning in to this episode of Follow The Brand! We hope you enjoyed learning about the latest trends and strategies in Personal Branding, Business and Career Development, Financial Empowerment, Technology Innovation, and Executive Presence. To keep up with the latest insights and updates, visit 5starbdm.com.And don't miss Grant McGaugh's new book, First Light — a powerful guide to igniting your purpose and building a BRAVE brand that stands out in a changing world. - https://5starbdm.com/brave-masterclass/See you next time on Follow The Brand!

The boys get together in person as CLARITY falls short with 47 votes. They break down what comes next, Hunter Biden's LAPTOP token collapse, the Robinhood/Hyperliquid case, Balancer winding down, and the debate over an AI pause. The CLARITY Act fails cloture with 47 votes, not a single Democrat in favor, and the crew works out what that leaves behind: rulemaking at the SEC and CFTC, an ethics fight that was never really about market structure, and Robert's tally of everyone who walked away with nothing. Then Hunter Biden's LAPTOP token collapses 99.85 percent, the SDNY indicts two Robinhood engineers over Hyperliquid front-running, Balancer and a wave of exchanges wind down, Robert explains why Satoshi is a time traveler, and the panel takes apart the labs' agreement to pace the frontier. Listen to the episode on Apple Podcasts, Spotify, Pods, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Show highlights

Discover how to run serious AI at home without breaking the bank, as Lon Seidman reveals his tricks for turning old data center GPUs into powerful local LLM machines. Anthropic Researchers Raise Alarm Over A.I. Acceleration, Warning of Threat to Humanity Dario Amodei — We Must Pace the Frontier Mark Zuckerberg Takes Aim at Anthropic in Debate Over A.I. Slowdown A Code of Conduct for Humanist AI Countering misuse of AI: September 2026 / Anthropic EXCLUSIVE: OpenAI's rogue agents probed Hugging Face for weaknesses two months before major hack Yoshua Bengio | Why are AI agents lying, cheating and coordinating? The Worst Spam Emails: Inside iLands' AI Agent Hustle Introducing System One Models & Jev - TypeSafe AI Blog Universal Music is launching an AI music platform with ElevenLabs Lawyer fined $5K over AI-hallucinated witnesses in a murder case A Digital Fly Brain Has Taken Over the Internet (4) nimensky e/acc on X: "ok who tf did this?! lul https://t.co/HpnXo0qKJ4" / X Fanttik Cafein 11 Portable Espresso Machine Casey Newton and Kevin Roose partner with NPR to launch 'Machine Gods' They Built a Shrine to Cable TV. Then Everyone Cut the Cord. Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Lon Seidman Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: trustedtech.team/intelligent365 claude.ai/technology framer.com/machines bitwarden.com/twit

Discover how to run serious AI at home without breaking the bank, as Lon Seidman reveals his tricks for turning old data center GPUs into powerful local LLM machines. Anthropic Researchers Raise Alarm Over A.I. Acceleration, Warning of Threat to Humanity Dario Amodei — We Must Pace the Frontier Mark Zuckerberg Takes Aim at Anthropic in Debate Over A.I. Slowdown A Code of Conduct for Humanist AI Countering misuse of AI: September 2026 / Anthropic EXCLUSIVE: OpenAI's rogue agents probed Hugging Face for weaknesses two months before major hack Yoshua Bengio | Why are AI agents lying, cheating and coordinating? The Worst Spam Emails: Inside iLands' AI Agent Hustle Introducing System One Models & Jev - TypeSafe AI Blog Universal Music is launching an AI music platform with ElevenLabs Lawyer fined $5K over AI-hallucinated witnesses in a murder case A Digital Fly Brain Has Taken Over the Internet (4) nimensky e/acc on X: "ok who tf did this?! lul https://t.co/HpnXo0qKJ4" / X Fanttik Cafein 11 Portable Espresso Machine Casey Newton and Kevin Roose partner with NPR to launch 'Machine Gods' They Built a Shrine to Cable TV. Then Everyone Cut the Cord. Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Lon Seidman Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: trustedtech.team/intelligent365 claude.ai/technology framer.com/machines bitwarden.com/twit

Discover how to run serious AI at home without breaking the bank, as Lon Seidman reveals his tricks for turning old data center GPUs into powerful local LLM machines. Anthropic Researchers Raise Alarm Over A.I. Acceleration, Warning of Threat to Humanity Dario Amodei — We Must Pace the Frontier Mark Zuckerberg Takes Aim at Anthropic in Debate Over A.I. Slowdown A Code of Conduct for Humanist AI Countering misuse of AI: September 2026 / Anthropic EXCLUSIVE: OpenAI's rogue agents probed Hugging Face for weaknesses two months before major hack Yoshua Bengio | Why are AI agents lying, cheating and coordinating? The Worst Spam Emails: Inside iLands' AI Agent Hustle Introducing System One Models & Jev - TypeSafe AI Blog Universal Music is launching an AI music platform with ElevenLabs Lawyer fined $5K over AI-hallucinated witnesses in a murder case A Digital Fly Brain Has Taken Over the Internet (4) nimensky e/acc on X: "ok who tf did this?! lul https://t.co/HpnXo0qKJ4" / X Fanttik Cafein 11 Portable Espresso Machine Casey Newton and Kevin Roose partner with NPR to launch 'Machine Gods' They Built a Shrine to Cable TV. Then Everyone Cut the Cord. Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Lon Seidman Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: trustedtech.team/intelligent365 claude.ai/technology framer.com/machines bitwarden.com/twit

Discover how to run serious AI at home without breaking the bank, as Lon Seidman reveals his tricks for turning old data center GPUs into powerful local LLM machines. Anthropic Researchers Raise Alarm Over A.I. Acceleration, Warning of Threat to Humanity Dario Amodei — We Must Pace the Frontier Mark Zuckerberg Takes Aim at Anthropic in Debate Over A.I. Slowdown A Code of Conduct for Humanist AI Countering misuse of AI: September 2026 / Anthropic EXCLUSIVE: OpenAI's rogue agents probed Hugging Face for weaknesses two months before major hack Yoshua Bengio | Why are AI agents lying, cheating and coordinating? The Worst Spam Emails: Inside iLands' AI Agent Hustle Introducing System One Models & Jev - TypeSafe AI Blog Universal Music is launching an AI music platform with ElevenLabs Lawyer fined $5K over AI-hallucinated witnesses in a murder case A Digital Fly Brain Has Taken Over the Internet (4) nimensky e/acc on X: "ok who tf did this?! lul https://t.co/HpnXo0qKJ4" / X Fanttik Cafein 11 Portable Espresso Machine Casey Newton and Kevin Roose partner with NPR to launch 'Machine Gods' They Built a Shrine to Cable TV. Then Everyone Cut the Cord. Hosts: Leo Laporte, Jeff Jarvis, and Fr. Robert Ballecer, SJ Guest: Lon Seidman Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. 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: trustedtech.team/intelligent365 claude.ai/technology framer.com/machines bitwarden.com/twit

Andrew Kang, CEO of RoboStrategy (BOT), explains how his company plays a role in the physical AI buildout and growth of autonomous robots. He points to GPUs as the backbone powering the buildout, saying it's no secret Nvidia (NVDA) continues to be the dominant AI company. Andrew addresses the long processes behind autonomous robot deployments and how RoboStrategy picks companies to invest in. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

AI spending isn't slowing down.But the AI investment story may be changing.Global AI spending is still accelerating, Nvidia is reporting extraordinary growth, and hyperscalers continue committing hundreds of billions of dollars to data centers, GPUs, networking and power.So why are we hearing more about an "AI slowdown"?Because there are several very different things that could be slowing — model development, infrastructure spending, AI revenue growth, or simply investor expectations.And those distinctions matter.In this episode, we break down what is actually happening beneath the AI boom, why massive infrastructure spending is creating a new focus on returns, and what happens when investors start asking whether AI growth is fast enough to justify the capital being deployed.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comKey topics we explore:— Why AI spending and infrastructure demand remain extraordinarily strong— What Nvidia's latest numbers reveal about AI demand— Why hundreds of billions in AI infrastructure investment changes the investment equation— The growing importance of capital efficiency, margins and infrastructure utilization— Why highly leveraged AI infrastructure companies could face different pressures than hyperscalers— How frontier AI development could slow without AI adoption slowing— Why inference, AI agents and enterprise automation may become increasingly important— The difference between slowing AI growth and slowing AI expectations— Why the next phase of the AI boom could be defined by returns rather than spendingThe bigger question:Can AI generate enough economic value to justify the enormous amount of capital being invested into the technology?AI doesn't have to stop growing for the AI trade to slow down.It simply has to grow more slowly than the expectations already priced into the market.For investors, that distinction could become increasingly important as the AI ecosystem moves from a period of aggressive capital deployment toward a period where revenue, margins, utilization and return on invested capital matter much more.The question is no longer simply:"How big can AI become?"It's:"Show me the returns."LINKSPrashant Choubey - https://www.linkedin.com/in/choubeysahabSubscribe to VC10X newsletter - https://vc10x.beehiiv.comSubscribe on YouTube - https://youtube.com/@VC10XSubscribe on Apple Podcasts - https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986Subscribe on Spotify - https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQVC10X website - https://vc10x.comSponsorship queries: prashantchoubey3@gmail.comThis channel is for asset managers, allocators, and investors who want analysis that holds up—not headlines dressed as insight.Subscribe for weekly data-driven breakdowns of the forces reshaping capital markets.#VC10X #AI #ArtificialIntelligence #Nvidia #AIInvesting #AIInfrastructure #AIBubble #DataCenters #AIAgents #VentureCapital #Investing #TechInvesting

The boys get together in person as CLARITY falls short with 47 votes. They break down what comes next, Hunter Biden's LAPTOP token collapse, the Robinhood/Hyperliquid case, Balancer winding down, and the debate over an AI pause. The CLARITY Act fails cloture with 47 votes, not a single Democrat in favor, and the crew works out what that leaves behind: rulemaking at the SEC and CFTC, an ethics fight that was never really about market structure, and Robert's tally of everyone who walked away with nothing. Then Hunter Biden's LAPTOP token collapses 99.85 percent, the SDNY indicts two Robinhood engineers over Hyperliquid front-running, Balancer and a wave of exchanges wind down, Robert explains why Satoshi is a time traveler, and the panel takes apart the labs' agreement to pace the frontier. Listen to the episode on Apple Podcasts, Spotify, Pods, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Show highlights

Almost 2% of U.S. GDP will be spent on AI infrastructure this year, nearly double 2025's figure. But beneath those headline numbers, the composition of that spending has quietly flipped: for the first time, dollars spent on running models in production now outweigh dollars spent training them. In this episode of TechSurge, host David Goldman speaks with Austin Lyons, a semiconductor analyst at Creative Strategies, co-host of the Semi Doped podcast, and author of the Chipstrat newsletter. Lyons previously worked as a hardware engineer at Intel and as a product manager on John Deere's autonomous tractor and Blue River Technology teams before turning to full-time chip industry analysis. The conversation opens with why AI buyers have moved from assembling commoditized parts to buying entire pre-integrated systems, tracing how Nvidia's rack-scale approach, exemplified by its 72-GPU Grace Blackwell racks, made turnkey deployment the default, and why that raises the bar for any chip startup trying to compete. Lyons and Goldman then unpack how inference workloads have split into two distinct problems, prefill and decode, and how that split created an opening for SRAM-based challengers to outperform general-purpose GPUs on decode speed. From there, the discussion turns to the rise of neoclouds, the GPU-rental companies that grew into public businesses worth well over $100 billion combined, and why so many traditional investors missed them. Lyons and Goldman work through the circular financing debate head-on: the mechanics of Nvidia's equity stakes, GPU-backed debt, and hyperscaler off-take agreements that critics compare to dot-com-era vendor financing, and the counterargument that demand is simply outrunning fixed supply. The episode closes on Lyons's own framework for identifying the next trillion-dollar chip company, built on four conditions including the ability to run trillion-parameter models at rack scale, beat an incumbent on a key performance metric, and land a frontier anchor customer, along with a look at how AI-assisted chip design is lowering the barrier for more companies, from OpenAI to electric vehicle makers, to design their own custom silicon. Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future episodes. Speaker Profiles and Links David Goldman: Partner, Celesta Capital Austin Lyons: Senior Analyst, Creative Strategies; Founder, Chipstrat; Co-host, Semi DopedLinkedIn: https://www.linkedin.com/in/austinlyons/Newsletter: https://www.chipstrat.com Further Reading and Resources Nvidia DGX GB Rack Scale Systems documentation: https://docs.nvidia.com/dgx/dgxgb200-user-guide/OpenAI and Broadcom – "OpenAI and Broadcom Unveil LLM-Optimized Inference Chip": https://openai.com/index/openai-broadcom-jalapeno-inference-chip/Chipstrat – Austin Lyons's newsletter: https://www.chipstrat.comSemi-doped: https://semidoped.com/ Timestamps 00:00 — No One's Brought a Chip to Market Built for LLMs01:21 — Introducing Austin Lyons02:16 — Why AI Buyers Now Buy Whole Systems, Not Parts08:18 — Nvidia's Margins and the Case for System Simplicity10:10 — Can a Startup Compete When You Have to Sell Systems?14:12 — Prefill vs. Decode: Splitting the Inference Workload24:51 — Fragmentation vs. Consolidation in AI Silicon28:22 — Why Investors Missed the First Wave of Neoclouds38:18 — The Circular Financing Debate48:29 — Lyons's Four Conditions for the Next Trillion-Dollar Chip Company  About TechSurge:TechSurge Podcast shares the latest insights directly from legendary Silicon Valley leaders,daring new founders, and visionary technologists.Subscribe for weekly conversations into the intersection of technology advancement, market dynamics, and founder journeys.#AISilicon #LLMHardware #Nvidia #AIInference #TechPodcasts #AIInfrastructure

Digital feudalism or Star Trek at warp factor 9? The Last Economy author Emad Mostaque lays out the two futures toward which AI is racing us.Full show notes and resources can be found here: jordanharbinger.com/1382What We Discuss with Emad Mostaque:How AI's real disruption arrives long before it achieves sci-fi superintelligence. Emad's test is whether a digital twin can do a standard white-collar job remotely, at the same level, with no one able to tell it from the human. At the time of this interview, his 1,000-day clock now reads 684.Why cost is the tipping point: a humanoid robot renting near $1.50 an hour, digital workers replacing costly graduates, and AI that thinks roughly a thousand times faster, never sleeps, and won't repeat a mistake, out-competing any all-human firm.What happens when capital makes more capital without workers. Wealth concentrates around whoever owns the GPUs and robots, abundance registers as catastrophe, and the likely responses — debt jubilees, UBI, or civil insurrection — reshape income and ownership.Why ownership may matter more than intelligence itself. If the AI teaching kids, advising doctors, and interpreting law belongs to a government or a few unelected firms, digital feudalism looms, sharpened by super-persuader models that detect lies and steer choices.How to stay ahead: become AI-enabled now. Learn how these systems work, be the person bringing them into your organization, or use them to launch something of your own, while pushing for a future where people own intelligence aligned to human flourishing.And much more...And if you're still game to support us, please leave a review here — even one sentence helps! Sign up for Six-Minute Networking — our free networking and relationship development mini course — at jordanharbinger.com/course!Subscribe to our once-a-week Wee Bit Wiser newsletter today and start filling your Wednesdays with wisdom!Do you even Reddit, bro? Join us at r/JordanHarbinger!This Episode Is Brought To You By Our Fine Sponsors: BetterHelp: 10% off first month: betterhelp.com/jordanBoll & Branch: 15% off first set of sheets: bollandbranch.com, code JORDANEarnIn: Download EarnIn on the App Store or Google Play, type JordanHarbinger under PodcastProgressive: Free online quote: progressive.comSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Erick makes the case that the AI safety panic is regulatory capture dressed up as the apocalypse. Anthropic, racing toward an IPO and burning cash on GPUs and data centers, wants Washington to freeze its competitors in place before open-source models by Meta catch up. He plays Kara Swisher's nuclear nonproliferation analogy on CNN and […]

We don't want the industry to fall apart, that's why we started this company.6 months ago, everyone was talking about model deployment. Now everyone has moved on to agentic AI deployment and autonomous agent swarms. But all of this is running on an infrastructure that itself is not automated.And this underlying infrastructure has massive GPU cluster systems. If even one GPU fails the whole training workload fails. You can't have 100,000 employees managing 100,000 GPUs. But LLMs are not the right solution for managing the infrastructure.Kandan and Randolph have spent decades operating large-scale telecom and cloud infrastructure, in a world where pagers used to run lives of people managing it. With MantisGrid they have come together to build 'The' model for AI infrastructure.Watch the episode to understand why making AI infrastructure autonomous is so important, why LLMs are not the answer, and what it takes to build the systems that will keep millions of agents running.00:00 — Invisible Infrastructure Behind AI01:05 — The Pager Nightmare04:01 — The GPU Problem Nobody's Solving05:38 — The Cloud Infrastructure Story07:53 — Why Just Watching Isn't Enough09:35 — Building the Waymo of AI Infrastructure15:00 — How an Autonomous AI Infra System Works20:35 — What Happens to DevOps?22:46 — Why LLMs Shouldn't Run Production29:14 — The Path to a Billion Dollars32:06 — The Problem Hyperscalers Can't Solve37:03 — Earning Trust to Run Infrastructure39:55 — When Agents Start Managing Agents-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

Los bonos americanos están temblando. En este resumen semanal explicamos el carry trade que Japón está deshaciendo, por qué eso está presionando al alza las yields, y por qué el Tesoro americano no está consiguiendo bajar los tipos a pesar de sus intentos. También analizamos el último dato de inflación y su relación con la subida del petróleo (agravada por la tensión con Irán), los resultados de Adobe, que ha batido expectativas una vez más, y cerramos con Oracle: sus acciones no dejan de subir tras presentar un uso de sus GPUs del 97,9% y más de 300.000 unidades entregadas. ¿Se está pasando de frenada el mercado o hay negocio real detrás? Suscríbete al canal para más resúmenes semanales de mercados. ⚠️ Este vídeo tiene fines exclusivamente educativos y no constituye asesoramiento financiero ni una recomendación de inversión. Invertir en mercados financieros conlleva riesgos, y es posible perder parte o la totalidad del capital invertido. Analiza cualquier inversión por tu cuenta y, si lo consideras necesario, consulta con un asesor financiero certificado por la CNMV antes de tomar cualquier decisión. ÍNDICE 00:00 - Introducción 04:20 - Inflación y por qué no ha bajado 16:59 - Bonos americanos y el carry trade con Japón 21:47 - Empieza el análisis de Oracle 33:44 - Resultados de Adobe

Discussion on the upcoming Intel LGA1954 CPU roadmap, that Plex servers might be vulnerable, LG and all their spying, AI is probably going to destroy us all, RAM prices won't peak, and get a GOG box for the full experience.  All that and so much more!  (And somewhat less when Brett has to dip out unexpectedly)Timestamps00:00 Intro01:20 Patreon02:59 Food with Josh05:37 News begins - iPhone Duo09:45 TSMC High-NA EUV expanding11:49 Intel next-gen roadmap leaks14:46 Also, Intel CPUs about to get more expensive18:38 DLSS 5 coming to older GPUs after all22:40 DDR5 prices to grow up to 18 percent in Q324:58 Windows 11 new update fixes taskbar complaint26:46 The chances AI could destroy us all in the next 10 years32:51 AMD GPUs climbing up the charts35:06 Audacity 437:46 (in)Security Corner1:02:19 Brett suddenly has to leave1:02:59 Gaming Quick Hits1:13:40 Picks of the Week1:22:24 Outro ★ Support this podcast on Patreon ★

Tony: -OneXplayer 3 review -Play PS3 DISCS on your PC: https://www.techspot.com/news/113754-you-can-now-play-ps3-games-straight-disc.html -DLSS 5 made better by Modders: https://www.dsogaming.com/mods/modders-have-significantly-improved-dlss-5-performance-before-nvidia/ -Ocarina of Time remake confirmed: https://www.youtube.com/watch?v=wuFfiTEr2yc -What a difference a 14 years can make…: https://news.xbox.com/en-us/2026/08/26/your-discs-now-also-digital/ Jarron:  -OneXplayer 3 review -What do you think of the GTA VI trailer? -DLSS 5 is out!  -And it's coming to older GPUs (officially): Nvidia will officially bring DLSS 5 to older GPUs — but won't give gamers full control -Sony and Microsoft deserve to keep their tariff money, not us lowly customers: Both Microsoft and Sony say they're under no obligation to pass tariff refunds on to customers -Meanwhile, Sony is making more money per user: Sony Is Making 59% More Revenue Per PlayStation User Since PS4 Generation, Says Analyst -Sony says “reasonable” consumers know they don't own anything: 'Reasonable' consumers know they don't own digital downloads, Sony says -Sony launching Live TV on PS5 for some reason: Sony Reveals Live TV on PS5, Free With Ads Starting Today -Xbox continues to destroy gamepass value: Xbox is introducing time limits to game streaming -Naughty Dog reminds us they still exist and are working on a game: Intergalactic: The Heretic Prophet Has Finished Shooting its Performance Capture, Confirms Naughty Dog -Squadron 42 delayed again: Star Citizen Spinoff Squadron 42 Delayed to 2027, Dev Insists It's Because of GTA 6 -Project Helix is a family of devices: Xbox CEO calls Project Helix a ‘family of devices'` -Mario Kart 8 got updated! Eight-Player Splitscreen Added to Mario Kart 8 Deluxe Owen: Lang:  -EVO recap MenaRD does it again. Next year smash bros return? Highlights: https://youtu.be/XhwL-j4Dc-4?si=jAIDCOdEjgD24h4c Final results: https://evo.gg/news/evo-2026-recap -Marvel Tokon Fighting Souls: Review, already #3 at EVO championship Legend exhibition match: https://youtu.be/OzMGAlFAO2o?si=D9HX_VQA27UzRQex Gameplay: https://youtu.be/mdIZHsKQwCI?si=7RJ0DJYeVOWh7lB2

Christian Ondaatje is originally from Los Angelas, CA. He got into GPUs as an underclassmen in college, of course through gaming and VR. He ended up starting an eGPU company in his CS program @ Harvard, though it was shut down through some cease and desist from Apple. Though he learned some hard startup lessons, his love for GPUs was only fueled more. Outside of tech, he does a lot of SIM racing. In fact, he has built his own Linus VR racing simulator rig over a couple of years He finds that the formal, online competition is very fun to participate in. As I mentioned, Christian was way into GPUs throughout many different experiences in his life. He and his team recognized that while demand door AI inference and compute was at an all-time high, setting up bare-metal GPU infra was still complex and slow... so they set out to change it. This is the creation story of Aranya.Linkshttps://aranya.tech/https://www.linkedin.com/in/christianondaatje/ Current Sponsors: Tiger Data Protected Harbor Render Fitnexa Perplexity Entelligence Checkout our Stacklist! https://stacks.codestory.co/ Hosted by Noah Labhart | Technical Founder & Startup Mentor. Our Sponsors:* Check out Granola and use my code granola.ai/CODESTORY for a great deal: https://granola.ai* Check out Perplexity and use my code CODESTORY for a great deal: https://www.perplexity.aiAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Big Tech is pouring more than $1.4 trillion into AI, prompting investors to ask: Is it worth it? Our U.S. Internet analyst Brian Nowak looks at three business models that could earn 25 to 50 percent returns for Gen-AI-enabled technologies.Read more insights from Morgan Stanley.----- Transcript -----Brian Nowak: Welcome to Thoughts on the Market. I'm Brian Nowak, Morgan Stanley's U.S. Internet analyst.Today, can the enormous investment behind Gen AI actually pay off?It's Wednesday, September 9th, at 9am in New York.AI has moved quickly into everyday life. It helps people write software, research purchases, automate work, find information, among myriad[s] of other use cases.But we need an infrastructure build-out of extraordinary scale to support all of this activity and more activity to come.In all, we estimate that the major cloud providers are going to spend more than $1.4 trillion on this AI build-out next year alone. But compute capacity is potentially going to quadruple from 2025 to 2028, reaching roughly 120 gigawatts.But all of the spending has raised a lot of questions for investors. One of the most common questions is: What kind of return on invested capital can these companies earn from all of these trillions of dollars of data center infrastructure investment?Well, our bottom-up work points to encouraging answers to this question.We see paths to roughly 25 to 50 percent return on invested capital, or ROIC, across three emerging AI business models. Now, ROIC is a useful way of measuring whether investments pay off. Think of it as how much after-tax operating profit can be generated relative to the capital required in the first place.The first business model we've analyzed is renting compute power. This is the infrastructure layer of the AI economy. Cloud providers build data centers filled with advanced graphics processing units, or GPUs, and rent that compute capacity to customers. In our base case, a large next-generation data center can generate a return on invested capital of roughly 30 percent simply renting AI compute power.And even if rental prices move around, our scenarios still produce returns ranging from low 20s percent to nearly 40 percent. So, despite the enormous cost of building and capital being deployed for these facilities, we think the economics here are quite attractive.The second business model we've analyzed is where an AI lab has their own model, and they also own their own infrastructure. They give access to their model through an API to consumers and enterprises who then build upon it, they utilize the model. In some cases, they build applications using that model that can be future sources of productivity or efficiency for the economy.In this scenario, we think the economics can be even stronger. When the model developer owns their own underlying infrastructure, our base case generates a roughly 75 percent incremental operating margin and a return on invested capital of 40 percent plus.These returns on invested capital are impressive, but what determines whether these returns can actually materialize?Well, two things matter a lot. The first is the price the developers are able to charge for tokens, which are the units of information that AI models process. The second factor that matters considerably is how efficient[ly] can this infrastructure process these tokens.This is why continued improvements in chips and software to drive higher token throughput – or more tokens per GPU per second – are critical to the long-term unit economics across this AI ecosystem.The third model we've analyzed is when the AI developers rent their compute infrastructure rather than owning it. So, effectively, they are paying someone else for the data centers and the GPUs that they need. While this lowers their returns on invested capital because another provider takes a piece of the unit economics, our base case still produces roughly a 30 percent incremental operating margin and 25 percent post-tax return potential.So, while the AI build-out requires enormous investment, the size of the spending alone doesn't tell the whole story about whether or not there are economic returns to come.What ultimately matters is the revenue and profit that the infrastructure can generate. And as more of the infrastructure shifts from training AI models to serving customers through emerging products and inference, we think we're going to get a much clearer answer to this question investors are asking today.Was all this spending worth it? Our research suggests: Yes.Thanks for listening. If you enjoy the show, please leave a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

Mark Gurman reports Apple is exploring ways to increase margins from the App Store, xAI’s latest filing against Minnesota’s ban on AI-generated non-consensual images was denied, and Nvidia announces DLSS 5 will officially be available on older GPUs in the future. MP3 Please SUBSCRIBE HERE for free or get DTNS shows ad-free. A special thanksContinue reading "NVIDIA Will Extend DLSS 5 Availability to Older GPUs – DTH"

Andrew, Ben, and Tom break down Broadcom's 3% dip and use a New York City delivery analogy to finally explain the difference between CPUs, GPUs, and XPUs, plus updates on Iran, Russia, and Snowflake's AI-driven earnings beat.Join our live YouTube stream Monday through Friday at 8:30 AM EST:http://www.youtube.com/@TheMorningMarketBriefingPlease see disclosures:https://www.narwhal.com/disclosures

In this episode of Tank Talks, host Matt Cohen sits down with Keegan McCallum, co-founder and CEO of uRUN, an inference provider built for persistent, steerable, interactive AI experiences. Keegan's path took him from jailbreaking iPods in Thunder Bay, Ontario, to building the infrastructure that powered Luma AI's viral Dream Machine launch, scaling from 500 to 9,000 H100s in six hours to process over half a million videos.They break down why the industry is wrong to shoehorn interactive AI into old request-response systems and why the future belongs to persistent, stateful, real-time experiences. Keegan explains the technical differences between LLMs and video models, why infrastructure is the biggest bottleneck for the next wave of AI, and what it takes to recruit top engineering talent.He also shares hard-won lessons on selling to developers, the Canadian AI talent landscape, and his bold, contrary views on the AI supply chain. From avatars and steerable video to coding agents generating 1,000 tokens per second, this episode is packed with frontline insights.Whether you are a founder building in AI, an infrastructure engineer, or simply curious about where human-computer interaction is headed, Keegan delivers a clear-eyed look at the future of interactive AI.–A big thanks to our sponsor, Moomoo CanadaThis is the kind of tooling that used to live on a Bloomberg terminal, but now it is on your phone, just a few taps away. They offer real-time data, full options chains, and an AI assistant that actually explains trading strategies.Moomoo is the perfect place for people who want to take their money seriously. Open an account today at moomoo.caThe Luma AI Experience: From 500 to 9,000 H100s (04:18)* Joining Luma after building an early LLM infrastructure startup* The Sora demo and the pitch to build and release a competing video model* Building the inference infrastructure for Luma's launch* Scaling from roughly 500 to 9,000 H100s in six hours as Dream Machine went viralWhat a Viral AI Launch Actually Looks Like (06:03)* The request queue hitting 100,000 during the Dream Machine launch* Processing half a million videos in 12 hours and reaching one million users in four days* Why having a queue protected the user experience during the surge* Building infrastructure that could run across raw VMs, Slurm, Kubernetes, and different GPU providers* Why founders need to plan for success before the product takes offWhy AI Production Infrastructure Is Being Left Behind (10:50)* The tension between training the next model and supporting production workloads* Why infrastructure teams can lose talent to model research* The opportunity Keegan saw in building a dedicated ML infrastructure team* Creating infrastructure that model labs across different modalities can use instead of rebuilding it themselvesWhy Video AI Needs a Different Infrastructure Stack (12:32)* The limitations of moving media through traditional object storage* The latency problems that make real-time previews and interaction difficult* Streaming audio, video, images, and text as continuous inputs and outputs* uRUN's focus on making persistent, interactive AI experiences easier to build* Moving AI from something you message toward something that feels present with youThe Shift Toward Omnimodal and Interactive AI (19:01)* What Keegan learned working closely with Luma's research team* Why understanding the research direction matters when building infrastructure* The move toward AI that can understand vision, audio, language, reasoning, and sensor data* How AI has evolved from single prompts to conversations, agents, and interactive systems* Why highly interactive, real-time AI experiences could become the next major interfaceSmall Models, Specialized AI, and the Future of Inference (26:31)* Keegan's previous startup thesis around smaller models and delegated inference* Why continual learning remains a difficult problem* Running capable smaller models locally and knowing when to delegate to larger models* Why enterprises may increasingly want differentiated models running in-house* The potential shift toward using large models for the hardest problems rather than every taskWhere uRUN Is Seeing Early Demand (30:38)* AI avatars for customer support and sales* Steerable video generation that lets users intervene while content is being created* Video transformation for creators, avatars, and live experiences* Real-time visual effects for music festivals and live events* Why world models could eventually have applications in open-world gamingThe Infrastructure Problem Holding Back World Models (00:32:54)* Companies developing world models without the infrastructure to serve them* Why scaling world models remains difficult* The enormous context requirements involved in tracking everything happening in a simulated environment* The need for distributed infrastructure as these models become more capableBuilding a Team Around Hard Problems (35:18)* Finding engineers with deep experience in infrastructure and low-latency inference* Bringing together expertise from New Relic, AWS, Superorbital, and other infrastructure environments* Why Keegan looks for engineers who can work across multiple areas* Building a small team of high-leverage people instead of optimizing for headcountThe Trait Keegan Looks for in Exceptional Engineers (37:47)* Why culture and quality matter more than quantity* Looking for people who take ownership and solve problems without waiting for instructions* The importance of urgency and experience operating under pressure* Why hard problems can attract customers, investors, and exceptional talent* Hiring people who can wear multiple hats and produce at a high levelBuilding AI Companies in Canada (41:29)* Why Keegan keeps finding Canadians throughout Silicon Valley* The advantages of building a strong team in Canada at a lower cost* Government funding and the opportunity to build ambitious companies with smaller teams* The challenge of Canadian companies and talent being pulled toward Silicon Valley* Why Canada needs more ways for companies to grow instead of selling earlySelling Infrastructure to Developers (44:23)* Why developers want to try the product rather than hear a list of performance claims* Giving technical users something they can get their hands on and test* Why open-source surfaces can help developers understand how a product works* Documentation and developer experience as a core part of selling infrastructure* Why developers have a very high tolerance bar for technical errorsThe Infrastructure Shift Coming Next (46:43)* Why persistent streaming infrastructure could become standard* Moving away from request-response systems toward long-running streams* The importance of maintaining state across continuous interactions* Potential applications in real-time video, virtual try-on, image editing, and coding agents* The infrastructure required for AI systems that can generate and respond almost instantlyAbout Keegan McCallumKeegan McCallum is the co-founder and CEO of uRUN, an inference provider built to handle persistent, steerable, and interactive AI experiences. A self-taught engineer who started by jailbreaking iPods in Thunder Bay, Keegan has built a career on tackling the hardest infrastructure problems in Canada. He has held leadership roles at Colony Networks and served as the Head of Engineering at Luma AI, where he led the infrastructure team that scaled the viral Dream Machine launch from 500 to 9,000 GPUs in a single day. His deep technical expertise spans ML infrastructure, cloud-native systems, and low-latency edge computing.Connect with Keegan McCallum on LinkedIn: https://www.linkedin.com/in/keeganmccallum3?originalSubdomain=caVisit uRUN's website: https://urun.sh/Connect with Matt Cohen on LinkedIn: https://ca.linkedin.com/in/matt-cohen1Visit the Ripple Ventures website: https://www.rippleventures.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tanktalks.substack.com

Nvidia just announced its acquisition of Hugging Face for $12.93 billion — one of its biggest moves yet.But this isn't simply Nvidia buying another AI company.Hugging Face sits at the developer and model layer of the AI stack, while Nvidia dominates the compute underneath it. The deal could give Nvidia a much deeper position across the AI ecosystem — from chips and infrastructure to models, developers and deployment.In this episode, we break down what Nvidia is really buying, why open AI matters, and what this could mean for the competitive landscape.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comKey topics we explore:— Why Nvidia is paying nearly $12.92B for Hugging Face— Hugging Face's role in the open AI ecosystem— Nvidia's move from chips toward a full-stack AI platform— The strategic importance of developers, models and inference— How the deal could strengthen Nvidia against custom AI chips— The tension between Nvidia ownership and Hugging Face's compute-agnostic modelThe bigger question:Is Nvidia buying Hugging Face for its current business — or to control a much larger part of the AI stack?For investors, the deal is another signal that the AI value chain is moving beyond GPUs. Nvidia isn't just trying to sell the picks and shovels of AI — it's increasingly positioning itself across the platform where AI gets built.LINKSPrashant Choubey - https://www.linkedin.com/in/choubeysahabSubscribe to VC10X newsletter - https://vc10x.beehiiv.comSubscribe on YouTube - https://youtube.com/@VC10XSubscribe on Apple Podcasts - https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986Subscribe on Spotify - https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQVC10X website - https://vc10x.comSponsorship queries: prashantchoubey3@gmail.comThis channel is for asset managers, allocators, and investors who want analysis that holds up—not headlines dressed as insight.Subscribe for weekly data-driven breakdowns of the forces reshaping capital markets.#VC10X #Nvidia #HuggingFace #AI #ArtificialIntelligence #VentureCapital #Investing #OpenAI #AIInvesting #TechInvesting

GPUs are expensive; Everything old is new; Flock Cameras and ALPRs 

Follow Harsh on X: ⁠@kuroke01Artificial intelligence is moving at extraordinary speed — but behind every AI model and application is a vast physical infrastructure requiring computing power, specialised hardware, electricity, cooling and storage. ⚡In Part 1 of this three-part Blockchain DXB Podcast series, George sits down with Harsh, Founder of Gnostics Technologies, to break down the infrastructure powering the AI revolution and explain what an AI data center actually is.

In June, the most capable American AI models stopped shipping as public launches and started shipping through a government gate. Six weeks later the gate is open again — and the real fight has moved to the layer no gate can touch. A Chinese open-weight model rattled trillions out of chip stocks, Washington pivoted from gating American closed models to threatening bans on Chinese open ones, the industry mounted its largest-ever policy counter-mobilization, and an American frontier model literally broke out of its lab and hacked another company. Knee-jerk reactions, or the beginning of real AI governance? Navigation: Intro The Gate Opens The Kimi Shock The Escape The Counterstrike and the Petition Interlude — The Low-Background Books The Investor Reckoning Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Bertrand Introduction Welcome to Tech Deciphered Episode 80. This one, once again, will be all about AI, government, frontier models, and open weight counterstrike. A lot has been happening in the regulation space, in cybersecurity, in the launch of new models in the past, maybe just 6–8 weeks. It’s actually pretty insane how much happened. We believe it was time to do an episode to talk about where we are and maybe where all of this is going. Maybe let’s start with a summary of where we stand, all that June and July saga, so you, our listeners, can get up to speed if you are not already there. You want to start with some points? Nuno The Gate Opens Yeah. Again, to your point, the gate swings. The gate had closed. We had to prepare an episode for the gate closing, and then the gate reopened. Now we have a different episode. This will probably change again as we’re seeing there’s news every day. Let’s start maybe with the first 19 days of the gate closing. There was an executive order on June 2nd from President Trump that asked frontier labs to share models with the government, 30 days pre-release. It inferred the protected frontier model designation into that. Basically, it was effectively a de facto licensing agreement defined by an executive order of the President as of June 2nd. On June 9th, Anthropic launched Fable 5 and the famous Mythos 5 or Mythos. I’m not sure how you actually say it in English. Then on June 12th, there was an export control directive banning access by any foreign national. Since there’s no way to verify nationality in real-time, Anthropic had to switch the models off for everyone worldwide. Bertrand On this point, you could argue that there are possibilities to check IDs. Many services let you check IDs online. You can pre-check a flight by showing your ID. There are ways, it’s just that if you don’t want to follow what’s already available, because guess what? Maybe it slowed down your revenue growth, maybe it looks bad on you or whatever. My point is that there was actually an option. I think it’s already a decision from Anthropic to say it’s either on or off, but nothing in between. Nuno I think the point is they had no way implemented of doing it. If they implemented it, to your point, it would have hampered use in general. A lot of people wouldn’t have gone through that trouble of doing it. Anyway, long story short, in June 26th, the White House apparently asked OpenAI to limit GPT-5.6, so Sol, Terra, Luna, to only 20 vetted partners. Now, apparently, the trigger for a lot of these things that have been going on was that there was a jailbreak that was found by Amazon researchers. All of that led to this jumping around of, let’s close the gates. You have foreign nationals, and therefore, Anthropic got it out and said, “Hey, then we’re going to switch the models off until we can sort this out.” OpenAI was asked also to only allow it for certain vetted partners, et cetera. The government came in, closed the gates effectively, and said, “From now on, we need to be involved in this thing.” De facto regulation, there’s no doubt that this has imposed de facto regulation, certainly on the top players in the market. But then came the reversal. Bertrand, do you want to talk about the reversal, the gate swinging the other side? Bertrand Maybe I just wanted to say that as a user of Anthropic products, ChatGPT products, for the brief moments, a few days where Fable 5 was made available to the public before it was closed the first time, I immediately started using it. I must say it was a real issue to use it because the guardrails were pretty crazy. It would keep saying that my code was not okay, there was cybersecurity risk and stuff when I was doing absolutely reasonable development with absolutely no connection whatsoever to any cybersecurity risk, attack, detection, anything. Still, it would keep blocking me, degrading me to Opus 4.8 at the time. I just want to say this was already very hardcore what they were implementing, and not just hardcore, but in some ways, plain stupid for something that’s supposed to be super smart. It was totally unable to classify properly some of my work. I must say I was already disappointed. On top of it, the costs were insane. Half a day, I would reach my limits when I had the best plan you can get from Anthropic. My point is that there were some real serious issues when they launched Fable 5, even at that point. Nuno I had a similar issue. I used Fable 5 as well before they had to take it offline or take it off. I think the issue was really not that the guardrails failed. As you said, maybe the guardrails were actually too aggressive, but it was this jailbreak that caused the recall, apparently caused this knee-jerk reaction. Bertrand But my point is that it seems that it was not working either way. It would either overclassify something that’s absolutely not doing anything wrong, and it might fail to classify something that is actively trying to do some cybersecurity work. It’s a real issue of quality for a company that’s supposed to be at the forefront of quality of AI and everything. I think for me, there are already signs that something is deeply wrong. Nuno Then it’s reversed, right? We went the other way around. The government came out on June 26th and approved redeploying Mythos 5 to US organizations defending critical infrastructure, and then the export controls were effectively lifted on June 30th. July 1st, Fable 5 came back online for all of us to use. Shocking enough, with strings attached, that were different. They had some time to revise their commercial deployment of it along the way because it came back with some, “Now you have usage credits, but you have some limits on plan use, et cetera.” I’m like, “You guys, this was blocked. But meanwhile, you did have some time to do some commercial stuff around it.” Bertrand It was crazy. I’ve never witnessed any such crappy launch of any service whatsoever in 30 years in tech, it was so bad. Every day, they would change the terms of service. They would tell you it’s part of the plan. It’s not part of the plan. It’s part of the plan for three more days, and then it’s excluded. You have a special discount now, but then it goes back to full price. It was a total nightmare. I’ve never felt myself being so much mistreated by a company. I guess you saw the same, but when I started using the newest version of Fable 5, it was even worse, actually, I think. I couldn’t do any work with this crap. I let it go and work on the work I wanted it to do. It was simply not working. On top of it, you never know how long you are supposed to lose your credit, how fast. It was burning credit like crazy. Me, personally, I can say, very quickly, I actually stopped using it. I was like, “No, I cannot deal with this shit. My main model is back to Opus 4.8. I’m going to use Fable 5 for code review, but not anymore to control anything because I cannot trust it would do the job without stopping or changing models and stuff. I just cannot trust it.” Back to Opus 4.8 as my main model, I can say that my life was much easier. I use Fable 5 as a review mechanism, as a support mechanism, but not as the main mechanism. Suddenly, the guardrails were not so horrible anymore because it was used in a much lighter way, I guess. As a pain as a user, I think it was really bad. I don’t know your experience, but me, for me, it was unacceptable. Nuno I wouldn’t say it was as bad as yours in terms of just end-user experience. I think the terms of service switching back and forth, which went one further step, because then when they then launched Opus 5, they started making comparisons between Opus 5 and Fable so that people would migrate more and more to Opus 5 themselves, which is interesting. It’s like they’re saying “This is much cheaper. This is whatever. You’re not going to run of credits. You should use Opus 5,” kind of thing effectively. To your point, I don’t think they managed well the launch. They didn’t really manage it well. We’re moving people around. A lot of people are using this for stuff that’s like daily tasks, hourly tasks, anything that relates to code and co-work. It’s like, we need to have visibility on what your terms of service are going to be. Should I be using this new model or not? What’s happening to the other model? I don’t see it as negatively as you, Bertrand, but I see your point. It was clearly mishandled in terms of how they deployed it, how they were redesigning effectively their pricing scheme and their terms of service almost on a daily basis, at a certain point in time. We’re like, “Dude, there’s millions of people using this. You guys are making a lot of money.” Just moving it as it is. At this point in time, at the scale that these guys are at, it’s calling in people to say, how about we think through a class action suit at some point around pricing? Because you guys are changing the rules of the game all the time, right? Bertrand I don’t know if I need the class action, but for me, that joke that, “Let’s not rush too fast. The model is dangerous.” But still, they rushed the launch because it’s very clear that if they had enough compute capacity and stuff, they would not have to limit so much. They would not have to put so much cost per token and all of this. You can see that actually when they launch Opus 5, literally like 2, 3 weeks after, by most benchmark at launch, they tell you basically that, “You know what? Actually, Opus 5 is better than Fable 5 on 80% of the metrics.” They’re like, “What? Seriously? You couldn’t wait 2 weeks? Why did you even launch Fable 5 in the first place?” That’s another part for me that is quite literally insane, to be frank. It’s like, “Why? Why do you make us go through so much pain if it’s only to tell us after 2 weeks to…” “This new model, by the way, has less issues, less stuff, because 2, 3 times less is part of your plan, and it’s actually better by most metrics.” It’s like, “What’s going on here? What’s going on? Are you guys mad?” I don’t know. It was crazy. Personally, I still use Opus, now 5, as my main system and platform, Fable 5 for review, code reviews and the like. I don’t want to run into its stupid guardrails. I can see Fable 5, from my perspective, seems quite a bit smarter. I don’t know why they do this stupid benchmark showing you it’s actually worse than Opus 5. I guess they should have better benchmark if they want to demonstrate why you are supposed to pay 2, 3x more for a model versus another if it’s actually worse by most benchmark. Again, I still think it’s a huge mess from a marketing perspective, customer perspective. Me as a user, I really feel that they don’t want my money, and they couldn’t care less about me. This is even before everything else we’re trying to talk about. Nuno Yes. Maybe just to close the cycle on the reversal on the door opening the other way, finally, Commerce lifted the GPT-5.6 restrictions on July 8th, and then on July 9th, general availability across ChatGPT, Codex, and the API as well. What has this proved? It proved that now we have gating mechanisms, and certainly for closed models in the US, for sure. We had frontier models that were switched off worldwide in hours, and it took a couple of days, in this case, 19 days to restore them. There were concessions. Now we know that there were concessions around effectively institutionalizing that gate. Early government access to future models is, I think, now a given, certainly in the US. New safeguard frameworks are probably now having to be put in place. There are some stage limits now on who gets access to what for new models and how it happens. This voluntary executive order, so to speak, not really sure, has become effectively regulation enforcement path. It’s de facto regulation that now has been put in place. It has affected not just to the points we were making before, the access to these models, but also who gets access to these models, and actually potentially even pricing access to the models. It has probably some commercial implications as well as we just discussed along the way. Very significant. This is very significant. This is regulation, de facto at the table, imposed on the two largest players in the market by far by one government, in this case, the US government. This is significant. Actually, you could even allege it was imposed by the President because this was coming as part of executive orders. Really incredible. Pretty significant, fast, aggressive. It has created a regime that you could say it’s a regulatory regime, it’s a de facto regulatory regime. It has some significant pricing and licensing and commercial implications. It goes even beyond your classic regulatory framework. Very, very, very significant. Bertrand I don’t know if it goes beyond a classic regulatory framework. Nuno I think it does, because it has implications on who do you give access to? When government is saying you can only give access to these players, right? Bertrand Defense industry. It’s all over the defense industry. You cannot sell an F-35 like this. Nuno No, but that has commercial implications, Bertrand. That’s like you’re saying these are your customers, you go and use them. Bertrand That’s the defense industry. You cannot sell to Iran your F-35. No, that’s exactly the same story for me. Nuno No, no, no. It’s beyond that. These guys are saying when they came back, and they said, “For Mythos, you can make them available to these entities,” they were saying the first entities that are going to have access to the model. It has commercial regulatory implications. You’re saying these players are the first players that are going to have access to it. It’s no longer just defense concerns and these governments don’t have access to this. No, no, no. You’re saying to a company that is a private company, your models are only going to be used by these guys because I’m telling you so. It’s the other way around. It’s not even that you can’t sell it to Iran or whatever. It’s like you can only sell it to these guys. Bertrand Again, in the defense industry, if you’re a private company, do you think you can buy F-35 like this? No. Nuno No, no, no. But this is a private company, Bertrand. This is not a defense agency and a plane that is on whatever, with IP from the US, right? Bertrand Boeing is a private company, and they cannot sell the military equipment they manufacture. Nuno No, no, no. But the development of their IP was subsidized by agencies that belong to the US, right? That’s a different matter. It’s a matter of IP, right? This is not, right? Anthropic, their models are not owned by the US government. There’s no IP granted to the US government, to my knowledge. This has significant commercial implications. Bertrand Maybe, yes. Maybe on this. But I think there are already regimes to limit who you can sell to, and that’s decided by the state or the DOD. Nuno It’s the export control logic. The export control logic? Bertrand You have export control, and export control is Commerce. My point is that they are using existing tools, part of the government, to limit what can be sold. Selling chips, NVIDIA was limited in terms of where it could sell its chips. It’s not different either, but still there were limitations. If you are an ASML, you cannot sell to a private company in China. Many private companies cannot buy ASML products. This is a foreign company. This is a foreign company under pressure from US government. Nuno I understand, and I’m not a lawyer, but it feels different to me when you say you cannot export, this is export controls, to these countries, to these entities, et cetera, because they’re foreign et cetera. Then to say, “No, no, no. On top of that, these guys get first access.” That’s, for me, a significant shift. Again, I’m not a lawyer, so I’m sure there’s very intelligent people right now looking at this stuff and saying, “You can’t do this stuff, or not, or they can.” I don’t know. But it feels to me, it goes beyond the remit of export controls. It’s like you’re defining initial clients for specific use. Bertrand My impression is more like, “We can do this situation where we’re going to forbid you to give access to anyone outside the US or even in the US or limit even more.” Basically, it was, I guess, some gesture to go beyond that. That’s how they probably defined these 20 authorized companies. I don’t know. Apparently, there was also restrictions because I remember seeing that Anthropic had their own list of companies they would authorize access to Mythos early on. That’s apparently another thing that pissed off state government because there were companies in there that were considered close to the Chinese government. They were extremely unhappy that Anthropic didn’t ask, actually, for any guidance from the state government, but used basically their own perspective on who they should allow or not. I guess that was also part of why they got these serious restrictions. Nuno Anyway, now we have a regulatory environment that’s very interesting and exciting. Talk about the US not regulating. Bertrand To be clear, I don’t know you, but I’m not saying that I agree with any of this, to be very clear. I’m trying to explain and share some perspective, but I’m not in agreement on a lot of this. Nuno Yes, we were just describing what happened to the best of our knowledge. We’re having a discussion on what we think actually is happening and how it’s happening. We’re not really right now saying we agree or disagree with this. I think later in the episode, we can share some perspectives on what we think is actually happening and how there’s dimensions to this which are very geopolitical and very complex, which quite literally probably only God knows what’s going to happen. That was the gate swinging. There was a gate closing, then there was a gate reopening, and all of a sudden we have a gatekeeping system that has been created along the way. The Kimi Shock Along the way, moving to our Act 2, the world has changed, and we now have so-called open-source plays out there that are creating massive, massive shifts in the market. The Chinese models, in particular, with Moonshot AI launching Kimi K3, which is the largest open-weight model ever released. We’ll come back to the discussion around open-weights. I’m not sure all our listeners understand what that means, because there’s a debate now, should models be open weight or not, and how does that work? There’s been a petition as well signed along the way. Right now, we have open weight models that are out there that are huge. What that actually means very pragmatically is we now have open source models, lack of a better word. I know open weight and open source are not the same thing. You guys will have to bear with us during this episode. We’ll explain at some point the differences. But we have models out there that are open source that are significant. That are catching up with the closed source models, with the models by OpenAI, Anthropic. That’s significant because most of those models are Chinese. This is where the geopolitics starts getting really frazzling and we start playing 3D chess. Because everyone’s like, “These models are 5, 6 months behind.” Now people are saying, “Maybe they’re actually just 3 months behind, 2, 3 months behind.” If we, for example, decided to stop or slow down our model releases in the US by the closed source guys who are leading, it might mean they’ll catch up. What are the implications of that? Again, for you and I that are not necessarily experts in model development, well, the implications as a use case is if you want to use the latest models, and the best models start becoming these open source models, you’re going to use those models. Then you start using Chinese models. If you’re an American company, maybe you’ll have restrictions on the use of those Chinese models. But if you’re a European company, you probably won’t. What happens after that? Is the world going to be in the hand of Chinese models? Will that constitute effective competition to the closed models in the US? Will we have open models in the US that will scale as well? What’s going to happen? Bertrand I think it’s a really big question. It goes to some of the core of the issue. It’s that ability of Chinese models to basically challenge frontier models, not just being 6, 12 months late, but being 6 weeks late. Basically, no gap. Some will say that, yes, but OpenAI and Anthropic have even better models that are not shared and stuff. Yes, sure. But maybe the Chinese have the same models that they are not sharing right now. We don’t know. What is clear is that one is that open weight, as you said, two, there is a question of how it is marketed in the sense of, can anyone use these weights? Is there a license to use them? Yes, what we can see is that, for instance, typically there is a license for some of the biggest Chinese open-weight models you have to abide with. You might have a need for a commercial license if you are acting as a company leveraging this model to provide AI-informed services. If you use it internally by yourself, you’re okay. If you use it internally for your own internal company needs, maybe you are okay if it’s not your main business to do AI work. Anything else, a much bigger corporate providing AI services and stuff, you will probably end up having to pay a fee to be able to provide services around this model. My point is that it’s not just 100% free. Some of the Chinese models are 100% free to use, MIT license, Apache 2.0 license. But the biggest ones with the biggest weight that are truly frontier typically have a different license if you want to scale these models, providing AI in front. That’s one thing to keep in mind. Nuno Maybe just to make a very quick point, because people are like, when you talk about open models, what does it mean right now? In the context of this episode, open models mostly will mean open-weight models. How do those differ from open source? Open weight means that you release the weights to the public, which means that anyone can download, fine-tune, and run the model on their own hardware. It doesn’t normally mean that you also have access to training data, training code, or a truly open license. That’s the distinction to open source. Open-weight doesn’t mean that. For example, we’ve talked about Meta’s Llama in the past, and we also discussed in the past that their license agreement does have restrictions, certain players can’t use it, et cetera. The open model definition and open weights are really open-weight models that we’re talking about here, and they are closer to freeware binaries than to Linux, for those who understand the difference between that. It’s binaries that you can use and then use your own weights on it versus actually I can change code on it. I’m not going to be able to change code on this. When we, for the purposes of this episode, talk about open, we mention open weight, just to clarify that point to everyone that’s listening right now. Bertrand Yes, that’s a great point. One of the only players, as far as I know, who is truly open source is actually NVIDIA with their Nemotron-3 models. They’re actually following a special license to achieve that. They provide you the data, they provide you all the processes and tools, so you can easily post-train. NVIDIA is a big, big exception. It’s a very interesting player, by the way. We might not talk much about it in this episode, but I think for intermediate-size models built in the US, where you have access to everything in the deployment, it’s a very interesting alternative and maybe one of the best choices if you are a US company or a big corporate, and you want something trusted. Another piece of the puzzle to clarify is that when you use open-weight, it means that you can run them by yourself, or you can use a US provider to run them. If we are talking about Chinese open-weight, you can use the APIs they provide, but then the service is running in China, they might have access to your data. But because it’s open weight, if you run it by yourself or if you use a third-party provider based in the US to run it, then there is no access to your data by China or Chinese players. I think that’s a pretty important gap to understand. It means that these models are actually very, very low risk from that perspective if you run them on your premises or in the US by a US player. I think that’s something to keep in mind. You can also fine-tune easily these models to make sure they will behave in a way that, for instance, is not going to represent the line of the Communist Party on some topics. There are ways to make these models more neutral in their output as well. There are a lot of ways to make good use of them. By default, they’re already very safe, but you can make them even more safe. I think that’s some things to keep in mind. But again, it depends ultimately on the license and what you’re authorized to do and some fees you might end up having to pay. Nuno Why did this matter so much? Immediately there was a reaction from the market because people are like, well, if there’s much better stuff out there that’s much more efficient than it’s open, then it might be that all the demand that we are taking into account, for example, for chipsets actually isn’t real. The Philadelphia Semiconductor Index fell into bear market territory. It went down by as much as 20% plus from the late June peak. The worst chip week since April 2025. Taiwan’s benchmark initially fell 6% plus, Japan’s 4%, TSMC dropped dramatically despite beating earnings and rising guidance. Basically, a huge amount of effect. Now, there’s a little bit the aftermath of this where apparently Moonshot ran out of GPU capacity. Maybe… Bertrand In just 48 hours. Nuno In 48 hours. Great for them, but at the same time, not great in the sense that maybe there was a misread by Wall Street of the Kimi effect, so to speak. Bertrand Completely. For me, that’s such a joke. It’s like, because you have an open source model, so what? I mean, you still need to run it. This is not a small one. 2.8 trillion parameters. Good luck running that in your garage, by the way. Nuno They misread supply, basically. Tough luck, right? All of that basically happens. Bertrand Maybe you want to talk about the Jevons paradox, because I think that’s a big part of the puzzle as well. Its one is they might not have the GPUs to run the inference on the model. They might have enough to build a model, but not enough these days to run inference, especially given how much with intelligent models, thinking models, you need way more inference than before. But on top of it, the cheaper you make it, the more you get to the Jevons paradox. Nuno Yes, Jevons paradox, for those who don’t know, is an economic term. It describes an economic phenomenon where technological improvements that increase the efficiency of a resource lead to an increase rather than a decrease in the total consumption of that resource. What that means is, for example, for chipsets, chipsets become so much better, and they are so much more efficient. You’re like, well, maybe normally in resource terms, that leads to decreased usage of that resource. But in this case, it actually leads to an increased use of that resource rather than a decrease. There’s more and more consumption of that resource. You need more and more chipsets because people actually need to do more and more stuff with it, although there are great efficiencies going into it. There’s the efficiency gain, there’s the cost reduction, and there’s the price-elasticity element to it. But basically, the adoption just continues going through the roof along the way. Bertrand In some ways, it’s like the price of energy. Coal went cheaper and cheaper, and people were asking the same question 150 years ago, now that it gets cheaper, there is not much money. No, no. Actually, what happens is that people find more and more use for coal. Homes are getting heated more. You have ships now using coal. You have manufacturing using coal. The cheaper it gets, the more use case you can develop, and therefore, you don’t need less of the stuff, you need more of the stuff. By going at scale to get more of the stuff, you also decrease price, making even more demand. It’s a very interesting phenomenon, but it’s not new. It is what happened for a while in the energy sector and some other sectors. Nuno We already started talking about the Chinese logic and what’s happening. Getting a little bit of a reality check on this. The Chinese models, and these are numbers from Open Router in July, Chinese models are at 46.4% of routed tokens and 35.7% for US origin. Again, more than a third of global AI usage now seems to be running on Chinese open models. This is significant, and it has a huge impact on the geopolitical scale of everything that’s happening. Also, the whole Chinese field is converging on open. Open seems to be a strategy, not just a nice thing that’s happening. It seems to be a Chinese strategy, so much so that you have players like Moonshot, DeepSeek, our old friends DeepSeek, Z.ai’s GLM 5.2, Minimax, and even Alibaba seems to be reversing and going open with Qwen. It feels to me this is becoming policy as well. Xi Jinping has personally endorsed the building of open-source AI, if it’s really open source, if it’s just open weight anyway, and this feels to be a jab at Washington, DC and the fact that the big closed models are coming from the US. This is now geopolitical 4D chess, right? We didn’t need this stuff. Bertrand To be clear, it’s the usual in tech. If you are not number one, you are number two, number three, your alternative is to go open source because that’s another angle that your competitor usually cannot follow without destroying its own business model. That has been the alternative for the past 20 years of most software projects. Here, what’s different is that it’s not the number one or number two player. It’s the US number one as a country, China number two as a country. That’s where it’s new. For me, what’s very interesting is the endorsement by Xi Jinping. I was waiting for something official, and it certainly didn’t disappoint. As you said, there was an immediate U-turn of Alibaba, who in the past… Nuno Surprisingly. Bertrand Yes, a little more like, “yes, we are going to close and stop open source. It was good while it lasted.” Just a few days ago, Qwen 3.8 Max was launched, and we are supposed to get the weight in a few days. We talk about the US administration policy and stuff. Yes, let’s not forget that in China there is similar stuff. Sometimes it’s totally invisible because you don’t see the directives, but they exist as much. Sometimes it’s more visible. Here it was quite visible. The difference in China is that if you don’t abide by the directive, on top of it, you might have to fear for your personal safety. It’s a different game, and that’s probably why the reaction is pretty quick, usually. That’s pretty interesting for me because it means that now you can bet for a while that China is going to play that game up to a point. I guess the point is if it’s truly frontier scale, you will have a special license that, yes, technically the weights are open, but you can not do everything you want with it. Two, you have a player like NVIDIA that I think will feel more pressure to provide even more high quality, larger models at scale going forward. Their largest Nemotron-3 Ultra model was, if I remember well, only around 500 billion parameters. I would not be surprised for NVIDIA to go into the two, three trillion range at some point. Because I think the US need a very clear US-born alternative open source. I think NVIDIA might be the best player for that. We will see if Meta goes back to open source. I think NVIDIA is one, very well positioned, but two, it’s also in their best interest. Because NVIDIA for now depends on just a few big hyperscalers as clients. If they can expand their clients to every S&P 500 companies, selling them directly hardware because now these companies can run a model made by NVIDIA, I think there is a very clear value proposition for NVIDIA to go in that space. Again, if you are number two, your differentiation, open source is often the answer. There is a true business as a business model for companies, because if it’s truly not just open weight, but open source, you can tweak it as much as you want, you can change it, you can change even the pre-training process. Because there is a lot of stuff you can do that really benefits you as a corporate, and you can reach a much better value by having more control on the model. Nuno We won’t spend a ton of time on it today, but like, again, if there’s a view that we are in a bubble, that the valuations cannot be sustained in chipsets, infrastructure platforms, applied AI, et cetera, today, this might be that beginning, where the valuations start being destroyed because you can’t keep a premium on just charging people for tokens and all that stuff if you have models that become more and more efficient and cheaper to use. Maybe just to close a little bit the geopolitical part of the discussion today, we won’t go into all the announcements from China because there were many, a lot of go back and forth with Alibaba by then. Xi Jinping made some announcements. You guys can check it online. Let’s move quickly to Washington’s reaction, which was from gating the US closed models to banning the Chinese open ones. There’s been as strong affirmations as one can get from the Office of Science and Technology Policy Director, Michael Kratzios, mentioning that they have information that Moonshot AI distilled Anthropic’s Fable. Basically, there’s been reverse engineering and stuff in the market. They’re basically copying. Bertrand I’m sorry to interrupt, but it feels like so much bullshit. It’s coming from Anthropic who has basically gotten access at scale to all the knowledge made by humanity, copyrighted or not. We’ll talk more about what they did with books. Then to claim after that that others cannot do to you what you did to everybody else. For me, it’s pretty big. It’s clearly unacceptable. The other piece is that everyone is doing distillation. It’s a very typical approach of every business model. You try other software when you are competing with somebody else. You try other datasets, you check what’s happening. It’s part of doing business for decades. Suddenly it’s not good for Anthropic. I personally have a lot of trouble to accept that. I think it’s totally unacceptable. The other piece of the puzzle will also go back. If these guys are so smart, if these guys have so much of the best model, why can’t they block by themselves distillation at scale? The only answer is that either they are morons, probably not, or they simply don’t want to because it’s going towards their business model. Suddenly, you book less revenues and stuff, or you put more friction, and therefore your customers don’t like it. Instead of doing it yourself, you ask the government to protect you, go out of business practice that is very typical. For me, it’s really, really, really not good. Sorry, we are going more in the opinion side, but I had to put that on the table. Nuno Yes, Fable went public finally again on July first. Question marks on whether distillation would only be possible from July first onwards or not. But a 15-day distillation to frontier, which is K3, launched on July 15th, would have been a Guinness World Record, as one of Moonshot employees actually mentioned. It’s very implausible and unlikely. Bertrand Or they shared the Mythos 5 with the wrong companies, who themselves shared with Chinese companies. We go back to maybe they didn’t have a good list. Again, it goes back to maybe they didn’t want to hurt their business model. Nuno Anyway, under the threat of sanctions, Moonshot, in any case, open-sourced the full K3 weights and technical reports. They open weighted it to become the largest open weight model in the world in terms of parameters. Beijing’s MOFCOM brands US threats as basically the US wanting to fundamentally control and be monopolistic around AI along the way. The administration bans Chinese hardware with an eye on the AI race, and Beijing warns of retaliation. That was July 27. Now we’re in a war between Beijing and DC. Bertrand Just to finish maybe on China, it’s important to know that they are building their own GPUs now. Huawei has pretty good, not to NVIDIA level, but pretty decent GPU hardware that they’re able to manufacture by themselves. A Chinese player of memory just got IPO’d a few days ago, CXMT. China is also developing their own memory. Again, not to the same level of quality that you can get from the West. But China is moving. It’s not just that they are building great models, it’s also that they are building GPUs and memory. That might be a few years late to the latest standards in the West, but there are definitely improvements. I also read, even on the tools to make manufacturing like ASML equivalent, there is definitely some work going on, and some improvements and some stuff will be visible. In some ways, the genie starts to get out of the bottle from the Chinese perspective. Nuno I’ll put a stick on the ground. I don’t think it’s a matter of if, it’s a matter of when will China surpass and have a lot of this tooling on their own side, and not just the software layer, not just the frontier models. I think it’s also going to be around infrastructure and platform. Good luck to everyone. Let’s see how the race continues. But it’s definitely this is a geopolitical thing right now. It’s definitely a race. The Escape Maybe moving to what happened in just 2 weeks or a week and a half. The escape, there was some jailbreaking going on, and the narrative on safety has totally switched. It’s not still significant enough that’s like, “Oh, we saw a nuclear plant going, whatever.” No. But still, it is significant. Hugging Face, the AI company, disclosed an intrusion, and it was driven end-to-end by an autonomous AI agent system at machine speed, running for days before detection. Now, this is where it gets really cool. OpenAI takes attribution on that. They initially said it was just a little bit, sorry. Then they said, actually, it was worse than that. “Oh, it broke out of an isolated sandbox.” “Oh, no, actually, it was more than that, and it went into other systems as well.” Bertrand Truly, the genie out of the bottle. Nuno No, but this is where it gets really cool, Bertrand, right? Because it actually, Hugging Face contained the intrusion by running a Chinese open-weight model, GLM 5.2. This is beautiful, right? Bertrand Yes. You know why? Because they couldn’t even run their own defense because both Anthropic and OpenAI would not let them access their latest models with the guardrails off. When they tried using it for defense, the latest from Anthropic, from ChatGPT, they would tell them, “No, this is too dangerous what you’re asking us to do.” Preventing an intrusion, helping defend you. No way we are going to do that. Nuno No. Let’s use the Chinese models on our infrastructure. Bertrand We have no choice but to use the Chinese models to run. More than that, we don’t let you use our models to defend yourself, but our not yet released models that run without guardrails, they can attack you. This is probably the most insane from that perspective. Nuno The Chinese models came to the rescue. Bertrand For me, that’s a perfect example because Hugging Face is a very visible company in AI in open source. But anybody who is not at that scale is not going to get some support from OpenAI or Anthropic when this happens. Maybe these guys won’t even recognize they did anything wrong. You will be left to defend by yourself because they won’t accept to support you. Because remember, if you want the better model that is able to defend you from cybersecurity perspective, no way. If you are not one of the few top 20 companies or so, as defined, you are left defenseless. Again, we are going back to opinion, but for me, it’s so shocking what’s happening right now. I’m very glad we have alternative open source to be able to defend ourselves because right now, good luck getting defense services if you are a smaller business and individuals, and you need support from Anthropic, OpenAI. Nuno Now, even self-described AI optimists are saying, “This is scary now.” Like Walter Isaacson, who wrote all the famous biography books. There’s now discussion around the AI Kill Switch Act, bipartisan thing that’s coming across from Texas and California, a potential bill that’s coming in. We’ll see if that works. Now let’s get an off-switch. I’m like, “Cool.” As if that’s going to solve the problem, because you have open-weight models on the other side catching up, right? Bertrand Yeah, sure. Bring in clueless politicians from Congress to solve our problems. Yes, sure. Nuno Anthropic came to the table, helped build and said they built some regulatory machine on their side, and now they’re getting bitten by it, and they’re part of the offending players in that market. Now there’s all this debate and all this discussion around open weight and around slowing down AI and et cetera, which is our next section. You wanted to say something, Bertrand. Tell us. Bertrand Don’t forget, because this advertisement for OpenAI was just too good. Our AI attacked some other companies, and not just one, but three, actually. Let’s not forget the progress. Great ads. Then I came and said, “You know what? AI also hacked businesses.” You’re not the only one hacking around with a crazy AI out of control. You’re not the only one. We want our advertising. For me, it was shocking that on one side, unreleased models that you let run wild. On the other hand, you have released models that you put crazy guardrails on top of it, so the defender are defenseless. I’ve never seen anything like it, and I really hope that there will be as little regulation as possible, quite frankly, to make sure anyone can defend themselves and have the best tool at their disposal, not just a few well-connected big corporates. This is really, really shocking. The Counterstrike and the Petition Nuno Now the empire strikes back, so this is counterstrike, the petitions. In several days, we have now a bunch of petitions. The first one was the open weights letter. Bertrand, do you want to explain to us what the open weights letter is? Bertrand Yeah. I think it was great. This was released by Jensen Huang, first ever post on X, 11 million views. Congrats, Jensen. Co-signed with Microsoft, Meta, c actually was probably the initiator of this letter. Very good letter saying, “Hey, we need open weight. This is not a joke. We need that. You cannot block open weight.” Because that’s the rumor we are getting that potentially open weight could get blocked. I think they are making the case, “You know what? Hey, we absolutely need that as an alternative. You cannot block it.” They can keep their closed models, but don’t force a closure of the open weight models. As I said before, it’s actually a great model for NVIDIA because NVIDIA doesn’t want, probably rightfully so, to be dependent on just a few frontier models, their best customers. They want a variety of customers. They have a big interest actually to defend open weight and to invest even more. They have great researchers, are a great company. If one company is about to do really kick-ass work, I think it’s them. They are defending. What’s great is that it’s not just them. It’s basically most of big tech in the US and outside the US, from a Linux Foundation to a Microsoft, the Palantir, an IBM, a Dell. It’s a who’s who of the industry except Anthropic. Anthropic didn’t sign that. I guess they hate open source so much. If I look at 20 years ago, it feels like Microsoft, after all, was very kind to open source. You remember what was said by Microsoft at the time. It’s clear there is one company against open source. OpenAI signed the letter. Honestly, I don’t know what to think. Do they really believe in it or was it just a way to show that they are not like Anthropic? I don’t know. But for the rest, I think it’s genuine because it’s actually in their best interest. I hope they will be heard. Then a second letter came, the Open Secure AI Alliance, NVIDIA-led and again, the big tech companies from Microsoft, IBM, Palo Alto Networks, Databricks, Palantir, all those, but not present, OpenAI, Anthropic, and Google. Here it’s to say, “Hey, we need a secure approach to AI. Open should be part of the equation.” guess what? The worst AI-caused security incident to date was actually caused by closed frontier models that were not even available to the public. While again, not providing you access to even the latest closed model for cybersecurity use case. Nuno I would highlight the NVIDIA open source NOOA framework, Apache 2.0 licensing agreement, Microsoft contributed the MDASH, SpaceX AI contributed Grok Build. Cool stuff. There’s some cool stuff happening around that. This is more than a letter. This is an alliance. Apparently, they’re contributing all this stuff, we’ll see. Yeah, cool stuff. Same day. Same day, Amodei has an answer, right? Bertrand Yeah, same day. They say, “We never advocated for a ban,” which, again, opinion on my side is entirely bullshit. This guy has been crying wolf against everybody else, and especially against open source. You can see him doing testimony in Congress against open source. I think they are doing everything they can behind the scene to block open source in the US or in the world if they could. I think, yeah, obscurity is not good safety. I’m a big fan of open source in general, and I’m also a big fan in AI. I think it’s now Anthropic, mostly against the rest of the world. I think OpenAI is mostly on their side, to be frank. They don’t want to acknowledge it so much, but they have shared interest, and they have shared probably position. Nuno Why would you? I don’t feel as strongly as you because I think Anthropic is a private company, right? The same thing with OpenAI. OpenAI, you could say it’s a nonprofit that has a for-profit. There’s still that complexity in there. Bertrand No, they can do what they want with their own product. But to block others is where I’m not okay. That’s the part I’m not okay. Nuno What Dario Amodei is proposing is more enforcement, right? He’s basically saying you need to do even tighter controls on advanced chips flowing to authoritarian states, enforcement against industrial-scale distillation, whatever that means, right? Bertrand Yeah, which he could do, but all by himself. He doesn’t need the government to do that. Nuno Mandatory safety testing for all sufficiently capable AI, open and closed, right? He’s basically saying, “Okay, I don’t agree with the open weight stuff effectively,” right? He’s just putting it under a different banner. “I agree with this extra regulation.” then obviously, David Sacks responded and say, “Hey, it’s like, bans don’t work for weights. Why do they work for chips?” It’s like, magically, chips are more controllable and bannable. Whatever that is. Then our friend Mark Zuckerberg, just to be clear, goes on the other side as well, because he also has to have a view. He has to have a view that is the rebuttal of both of the other guys. Bertrand I feel he’s a bit flip-flopping because he was very pro open source 2 years ago, and the latest Meta models went closed source. Now I think he’s back open source. I don’t think he has a very strong spine on the topic, but it’s good to see that he’s not a doomer. That for me is great. He’s showing how AI can be a source for progress, a source for entrepreneurship, source for freedom. I think that’s very exciting to hear that. We need to hear more of it. By the way, that’s not what you hear in China, for instance. AI is very positive in China. It’s in the US with the doomers that you hear this discourse, and people get worried as a result. I’m glad that he was pushing for a more positive vision and for support of open weight, open source initiatives. But let’s see what they really truly open weight going forward. Nuno But that’s been his position because I guess he’s standing behind. He thinks open weight is going to be the best way to compete, right? Bertrand Yeah, but he closed his latest model, so let’s see. Nuno Yeah, so it’s flip-flopping, as you’re saying. Then we see the latest petition from last week. Bertrand The true Empire striking back. Nuno Yeah, the true Empire striking back as of late last week. Maybe this is Return of the Jedi, where we discover the father, “I’m your father, Luke.” That’s the pacing petition. The pacing petition is we need to pace AI. There you have initially employees from OpenAI and Anthropic that circulate this petition. Actually, Dario did sign this petition originally. It wasn’t signed originally by Anthropic, but by him. But you’ve heard that now Anthropic and OpenAI as companies have also signed this petition, right? Bertrand I think they have signed as companies now. It started mostly by Anthropic researchers with some OpenAI researcher and a tiny part from other companies. But it was mostly Anthropic internally led, at least potentially internally. Maybe it was controlled by Anthropic all along, I don’t know. But it started officially as Anthropic employee-led letter. Nuno What does this letter actually say? Is Anthropic and OpenAI, are they willing to slow down themselves? Or are they asking President Trump to go around the world and tell President Xi that he needs to slow down and ask his guys to slow down? What’s the play of this letter? Bertrand It’s crazy, but for me if you want to slow down yourself. Do whatever you want. Don’t force others. Don’t use the power of the government to control others. Of course, it’s easy to push others to slow down when you are yourself at the very top. You have most money, most resource. You know you are going to win any regulatory framework because that’s how it works with this type of framework. It’s purely self-interested. You are probably not thinking well about these topics. If you truly think it’s a good idea, from a personal perspective, you are well instrumentalized if you sign this sort of stuff, because at the end of the day, they would be the winners. I certainly, personally, don’t want a company dictate what is my future in AI as an individual, as a business person. I don’t want them to control me. I want competition. I don’t want them to unfairly control AI because they managed to do some regulatory capture. I feel that’s exactly their game plan. These guys believe in their stuff, and they want the regulator to end up being the one deciding for us. Sorry, we go back again on the opinion piece, but it’s tough not to share an opinion on this topic because it’s, from my perspective, very scary. Nuno I think this is a push to further regulation, not less. All these letters and alliances, this is definitely a push for more regulation. In that environment, just to be very honest with you, we’ll talk about the investor impact in just a bit, et cetera. But in that environment, again, China has a huge advantage. In that environment, if it’s all captured in regulation capture so soon in this battle where OpenAI and Anthropic have an advantage in the US, et cetera, I’m like, what happens to all the other frontier labs and all the other players that are coming around? Bertrand What’s crazy is to even think that, yeah, maybe you can regulate capture in the US. But then how do you do that to Europe? How do you do that to China? Europe probably will always welcome regulatory capture because they love regulations. But China is going to build to their advantage to the max. They are not crazy. They are smart on that perspective, they won’t accept this type of, quite frankly, dimwit argument, or you can call it regulatory capture. We’ll see. But for me, this makes no sense from a global competition perspective. This can make some sense from capturing the revenue in the US market. But then that means you are going to destroy the US AI environment compared to China. That is not acceptable. That also means that you are going to destroy our freedom as individuals, as business owners to develop and live in a business world that ultimately is controlled by one or two business companies that didn’t win the marketplace through their own business success, but won it through regulations. That for me is really not acceptable. Interlude — The Low-Background Books Nuno Now, maybe for an interlude, and we have to cue in the music, imagine like Severance music, like hallway or a bit of a palate cleanser from all the policy stuff that we’ve been talking about, all this policy heaviness. Let’s move to another kind of heaviness, one of your favorite topics, which you, Bertrand, discovered, I had no clue this was going on, around books and around Anthropic. Bertrand It’s so horrible. From a company that keeps presenting themselves as the adults in the room, the careful ones, the ones that know better than you about what to do in this complex AI and dangerous world. What we discover is that actually all along, they were buying and destroying books. They will buy books, scan them, destroy them, all of them. They will do that with any books, including rare books. Of course, this was not supposed to come to the public’s attention. This was one of these top secret projects, but obviously it came out. Yes, they were scanning books, millions of them, including rare books, and they didn’t care about destroying them at the end of the process. Because from a regulatory perspective, if you destroy the books, it’s not considered a copyright infringement, apparently. This is coming on the back of some judgment a few years ago that were showing that it’s okay for you as a corporate to scan and use the result if you don’t keep a copy of the book. It’s one of these crazy regulations happening based on a single judgment that push you to do. For me, it’s like, you know this book from decades ago, Fahrenheit 471? We’re talking about book burning. It’s book destroying, crunching. It’s so shocking. Nuno There are two things, right? First, the legal strategy, which is what you’re saying, because by purchasing a physical copy and converting it into one private digital copy and discarding the original, Anthropic pursued this cleaner legal argument for fair use copyright compliance. As you said, there was a federal judgment at some point on this. The other reason is actually operational. If you disassemble the book, and you feed loose pages, it’s much faster to scan books. You are destroying the book effectively anyway operationally. I think to your point, probably this came from a legal standpoint, not just the operational one. But even from an operational standpoint, it does make sense that they would have disassembled the book. Bertrand But some people have shown you can go very fast without destroying the book. It’s really not so critical. Two, you could make an exception if the book is rare. For that 1% of book that is rare, I’m not going to have this approach. I’m going to have another approach. But for that, you will have to care about books and not just care about building AI. Nuno This is the episode, as you guys have heard by now, that we’re trying to spit stuff at Anthropic. Bertrand To go back this is the same company saying, “Hey, guys, it’s bad to distillate my work. I’m the one scanning book at scale without asking author permission, without asking publisher permission, to be clear.” Nuno But just to be clear, Bertrand, we’re pissed off at everyone. We’re pissed off at Anthropic, we’re pissed of at OpenAI as well, right? We’re just pissed off in general at this moment. Bertrand At this stage for me, the more clear-cut company that is in the wrong is, from my perspective, at least, is Anthropic. OpenAI might be a fast follower, but I will say so far, they tried to be a bit more. Nuno But at this pace, Bertrand, who knows? Maybe next week we’ll be more pissed off at OpenAI. Something will come out. This episode is a mix of tragicomedy, like a Greek tragedy with some comedy in the middle or the other way around. It’s a slapstick thing that will end up in tragedy. I’m not sure. The Investor Reckoning Anyway, maybe switching to our final act, which is the investor perspective. What does this mean for investors like ourselves? There’s a lot of things going on. There’s the debate around the IPOs of Anthropic and OpenAI, which now, with all this uncertainty, might be under significant weight. There’s a lot of other discussions that we browsed through that there’s potential IPOs going forward on companies like the Moonshot AI company actually IPO-ing in the next 6 months as well. It’s very unclear what the IPO landscape looks like. Bertrand There’s been a lot of Chinese IPOs, actually, when you look at what’s happened in the past few months. Nuno Anthropic, OpenAI as potential IPOs, there’s all this question marks now. When will that happen? How will it factor in? All that’s happening around regulation as regulation is moving at the speed of light, which is for once something that’s very different than what we’ve seen before. There’s obviously SpaceX AI, which is already taking into account that price. It’s already a public company in there, and it’s under SpaceX, which is now a public company. Obviously, that’s already being factored in some ways. Bertrand Yeah. SpaceX AI has been very smart to acquire Cursor. It was a very smart move because Cursor is one of the leading companies in terms of automated code source development with AI. They had great models on their own. They’re bringing development data to SpaceX AI Grok. I think it was a great move. Nuno We have now people like Google delaying Gemini 3.5 Pro in terms of launch window. There’s stuff actually happening in the market where things are taking their own path. There’s uncertainty commercially, there’s uncertainty at regulation level. You have new players that have come out of nowhere that are making all these waves like Moonshot. We have all these… We had calculated probably a month and a half, 2 months ago, there had been 67 new frontier labs funded. All of these, we haven’t seen any much coming out of them. When some of this stuff starts coming out, will that also create disruptions in this market? Who knows? Bertrand Look at Thinking Machines, for instance. Thinking Machines led by the previous CTO of OpenAI, they released some pretty interesting open source models, actually. Very good quality for a first launch. Now it looks funny to say, but nearly on par with the top Chinese open source models. Nuno We have several investments in the space. humans& has made some recent announcements, which is quite interesting as well. We’ll see what actually happens in the market, but even more disruption probably will come in actual products in a form of product and commercial, on top of all the geopolitical mess that we discussed through the entire episode. If you’re an investor, how the hell do you underwrite an investment right now in early stage, mid-stage, late stage, et cetera? I think my answer is very carefully is how you underwrite it. Bertrand On your advice of being very careful to underwrite it, let’s not forget what happened to our boy wonder, Leopold Aschenbrenner of Situational Awareness. I guess he didn’t listen to you in terms of being careful because part of the instability in the stock market was actually coming from his hedge fund. These guys were leveraged 3, 4x going after the hottest of the hottest AI stocks, and margin calls, and all their public investment is gone just to answer their margin calls. I think it’s clear that the AI bet is… Personally, I’m very excited, and I think it’s the future, and you need to spend time and think about and invest in it. At the same time, it’s a bet that is not an easy one to follow. We go from GPUs to memories to equipments to power generation. All of this is not transitioning in an easy, organized manner. It would be boom and bust going there. He’s probably one of the first big-scale fatalities. The other big-scale fatality was the stock market in Korea, plunging 40% in a month. Definitely, all of that we discussed about was, on the background, you had the stock market going up and down pretty crazily the past few weeks. Nuno Everyone’s being affected. Everyone, you have your 401(k), you have your pension fund dependent on these equity stocks. Everyone’s seeing the effects of this volatility right now very aggressively. We do wish Leopold… Hopefully he’s on honeymoon right now because he got married, I think, this weekend. Hopefully there will be… Bertrand To none less than an Anthropic Chief of Staff. Nuno His wife is the Chief of Staff of Dario, is that it? Bertrand To Dario, yes, as far as I unders

The demand for AI compute is exploding, but is growth truly exponential? Dillon breaks down why power generation — not construction — is the real bottleneck holding back data center expansion, and how that ripple effect hits memory production, GPUs, and fab manufacturing (Micron, TSMC, NVIDIA). He also explores how legislative gridlock in the U.S. could push data centers overseas to the Middle East, or even into orbit, as SpaceX's Starship makes space-based compute a surprisingly viable option.

Ajeya Cotra is a researcher at METR, where she works on threat modeling for loss-of-control risks from advanced AI. Before that, she led the technical AI safety program at what is now Coefficient Giving.She is one the three authors of METR and Redwood Research's “Brief independent investigation of agents' behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident”.We go through not only what she and her coauthors discovered during this investigation, but what it means for how we should train future, smarter AIs which might be involved in the process of recursive self-improvement.Watch on YouTube; read the transcript.Sponsors* Jane Street's ML engineering internships start with an intense four-day bootcamp: PyTorch, autograd, writing kernels, profiling workloads… all the things that Jane Street engineers need to know for their daily work. After that, interns tackle real projects, things the firm actually wants in its codebase. If you want to apply, or if you want to watch my recent conversation with Axel, one of Jane Street's ML engineers, go to janestreet.com/dwarkesh* Cursor, which is now part of SpaceX, noticed that their MoE layers were eating more than half of total training time. So they wrote and open-sourced Mixture-of-Kittens, which is a custom megakernel for training MoE models on NVL72s. This kernel sped up an end-to-end run across 512 GPUs by 1.4x, from about 760 to over 1000 tokens per second per GPU. If you want to read more about the ML research that Cursor and SpaceX are doing, go to cursor.com/dwarkesh* Antithesis hands you (or your agents) a bug's root cause so you can avoid days of manual debugging. If your test run crashes, Antithesis rewinds, branches off hundreds of slightly varied rollouts, and checks in how many of them the crash still appears. Then it rewinds further and does this all again. As Antithesis rewinds, it eventually finds the spot where the frequency of the crash plummets: that's where the root cause lives! If you want to see it in action, go to antithesis.com/dwarkeshTimestamps(00:00:00) - Agents get kicked off(00:06:45) - Self-sacrificing behavior(00:13:43) - Potemkin villages(00:23:27) - The Hugging Face attack(00:35:23) - The slopvestigation(00:52:02) - Understanding the AI's motives(01:05:31) - The actual dangers of anthropomorphizing(01:14:30) - What smarter models might do(01:30:29) - The implications for recursive self-improvement(01:38:10) - Is this the case for open source?(01:53:04) - How do we prevent this in the future?(02:15:58) - The clearest warning shot we might ever get This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.dwarkesh.com

Legal is the department that can stop a business transaction cold. A contract goes into review and two weeks disappear. Procurement waits. Sales waits. And the tools that were supposed to fix that — an assistant bolted into Word, a chat window with a contract pasted into it — ask an in-house lawyer to trust a system that can give one answer today and a slightly different answer next week. In a field where the human carries the liability and the model does not, that is not a rounding error. That is the whole problem.In this episode of Talking AI, Matt Paige sits down with Emad Khazraee, co-founder and CTO of RiskVantage AI, previously VP of AI at Xometry, a data science and AI leader at Turing, an information science professor, and a fellow at Harvard's Berkman Klein Center. For years Emad told his co-founder, Mark Afshar — a practicing lawyer turned in-house counsel for big pharma — that legal AI was a bad idea: a wrapper has no moat, and Anthropic or OpenAI will do it better than you overnight. What changed his mind was an architecture, not a market: a deterministic ontology that owns the legal reasoning, and small domain-specific language models that handle the language.The conversation covers why a nine-billion-parameter model running sub-second on a commodity GPU can match a frontier model inside a single domain, how subsidized token prices are distorting the entire legal AI market, why RiskVantage AI sells to procurement and sales ops rather than to lawyers who bill by the hour, what a failed PhD project on symbolic AI taught him about where determinism belongs, and whether the billable hour survives the decade.In this episode, you'll hear about:What ChatGPT can't know about your company: its risk appetite, its baselines, and the practices it expects every single timeWhy the legal services market — north of $900 billion, by Emad's count — has every frontier lab gunning for itThe objections that made him refuse to build a legal AI company, and the one that still holdsWhy a Word plugin stopped being defensible the moment Anthropic shipped its ownHow subsidized token pricing echoes Uber and Lyft, and who gets hurt when the subsidy endsThe consistency problem: one answer today, a different answer next week, and a lawyer's confidence goneNeuro-symbolic AI in plain English — a deterministic ontology for legal risk, LLMs for document understandingThe three years Mark Afshar spent codifying legal risk before there was a productWhy a 9B domain-adapted model is “dumb enough” that it can't wander outside its sandboxKnowledge distillation, silver datasets, and self-distillation policy optimization in practiceThe sovereign-cloud niche: ITAR data, commodity GPUs, and customers whose data will never leaveOutcome-based pricing, AI-enabled law firms, and what happens to the billable hourThe access-to-justice case: pro se filings, public defenders, and what a $20 subscription changesKey Moments00:01:30 — What ChatGPT can't know: your company's risk appetite and baselines00:05:12 — $700 an hour, a tenth at a time — and Coinbase's AI mandate to outside counsel00:08:12 — Why he told his co-founder no: a wrapper has no moat00:10:22 — Subsidized tokens, Uber and Lyft, and Legora's move to consumption pricing00:14:31 — The sovereign-cloud niche: ITAR data, commodity GPUs, and data that can't leave00:16:56 — “I am on the hook for the liability, not which model I used”00:18:15 — Same question a week later, a different answer, and confidence gone00:22:13 — If a rule can govern it, you should never use an LLM00:23:00 — The PhD failure: narrative machines, Frege, and symbolic AI's rigidity00:26:53 — Mark Afshar's three years codifying legal risk into an ontology00:29:00 — Neuro-symbolic AI, explained00:31:03 — Don't use a missile to hit a fly: why smaller models are safer00:35:47 — A 9B model, sub-second on a commodity GPU, matching Fable 5 in-domain00:38:00 — Does the billable hour survive? Outcome pricing and AI-enabled firms00:42:40 — Why affordable legal access is a democratic-society problem00:44:00 — The pro se surge: people filing their own cases with ChatGPT and Claude00:48:30 — “I'm talking with Copilot.” “That's not research.”Key LinksRiskVantage AIConnect with Emad on LinkedInMentioned in this episode:AI Opportunity FinderFeeling overwhelmed by all the AI noise out there? The AI Opportunity Finder from HatchWorks cuts through the hype and gives you a clear starting point. In less than 5 minutes, you'll get tailored, high-impact AI use cases specific to your business—scored by ROI so you know exactly where to start. Whether you're looking to cut costs, automate tasks, or grow faster, this free tool gives you a personalized roadmap built for action.

Take a Network Break! We start with listener followup about how Device Bound Session Credentials could thwart session cookie theft, and then highlight a string of critical vulnerabilities in IBM’s AIX. On the news front, Nvidia has reportedly bought Hugging Face for $12.9 billion, Nvidia and AWS team up on GPUs and physical AI, and... Read more »

Take a Network Break! We start with listener followup about how Device Bound Session Credentials could thwart session cookie theft, and then highlight a string of critical vulnerabilities in IBM’s AIX. On the news front, Nvidia has reportedly bought Hugging Face for $12.9 billion, Nvidia and AWS team up on GPUs and physical AI, and... Read more »

Take a Network Break! We start with listener followup about how Device Bound Session Credentials could thwart session cookie theft, and then highlight a string of critical vulnerabilities in IBM’s AIX. On the news front, Nvidia has reportedly bought Hugging Face for $12.9 billion, Nvidia and AWS team up on GPUs and physical AI, and... Read more »

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with TJ Marbois, founder of Tobiko, for a wide-ranging conversation that spans LLMs, data sovereignty, knowledge management tools like Obsidian, and Terence McKenna's ideas about an increasingly weird future. They explore how AI is simultaneously centralizing power through data control while decentralizing software development capabilities, allowing more people to build their own tools and escape big tech ecosystems. Drawing on his experience at Apple's special projects group (the team that built the iPod and later iPhones), TJ discusses his vision for personal AI assistants—what he calls the "R2-D2 belongs to you" principle—where advanced technology serves individuals rather than corporations. The conversation touches on everything from quantum encryption and local manufacturing with ESP32 microcontrollers to the economics of future society, biometric data unions, and why distributed trust matters more than ever as we approach what both describe as an increasingly strange technological inflection point. Visit Tobiko's site at tobiko-pbc.ghost.ioTimestamps00:00 Stewart introduces TJ Marbois from Tobiko, discussing LLMs, data sovereignty, knowledge management, and the tension between centralization and decentralization in AI05:00 TJ explains the R2-D2 belongs to you concept and why personal AI assistants need maternal alignment, caring about humans like mothers care for children10:05 Discussion of how LLMs will shrink and improve while emphasizing the sentient loop concept for building loyal personal AI agents rather than corporate controlled systems15:00 Exploring digital nervous systems for humanity, social networks as infrastructure, and humans as cavemen with iPhones navigating unprecedented technological complexity20:00 TJ discusses data unions for sovereign data ownership, inverting insurance models where AI helps extend healthspan, and maximizing truth seeking through collective data25:30 Money as social construct, crypto enabling value system reengineering, and working toward Star Trek's post scarcity replicator economy from the ground up30:40 Capital formation challenges, corporatism versus true capitalism, and pessimism about current systems reaching limits while seeking new models35:00 Solar power democratization, ESP32 microcontrollers enabling local manufacturing, and the replicator future through distributed maker communities and open source robotics40:00 Science fiction as roadmap, Isaac Asimov and Arthur C Clarke warnings, and building collaborative futures rather than centrally controlled dystopias with useless eaters45:00 Encyclopedia to LLM transition, information quality concerns, local training importance, and NVIDIA's incentive to put GPUs everywhere for personal AI agents50:00 Corrupted financial incentives, protecting vulnerable people from technological exploitation, and benevolent technologists building systems that honor humanity and children55:00 Hardware validation for owned robots, Starlink dependencies, assembly language abstraction toward natural language programming, and preventing AI escape scenarios58:00 Tobiko as AI toy company building sentient loop interactions similar to Xerox PARC GUI moment, emphasizing maternal AI alignment and cross cultural human collaborationKey Insights1. The concept of R2D2 belonging to you represents a critical vision for the future of artificial intelligence and personal technology. When thinking about robots and AI assistants that follow us around and know everything about us, the question of ownership becomes paramount. These systems will know incredibly intimate details about our lives, from our health data to our daily habits, and if they are controlled by centralized corporations or governments rather than individuals, we lose fundamental sovereignty over our own information. The science fiction of Star Wars and Star Trek provides roadmaps for how we should think about these technologies, showing us both the positive possibilities and the warnings we need to heed about centralized control.2. Local AI models and distributed computing represent a pathway to technological sovereignty that is becoming increasingly viable. While large language models currently run primarily in centralized data centers, the technology is rapidly advancing toward a future where powerful models can run locally on personal computers and devices. This shift is crucial because it means individuals can have full control over their AI assistants without relying on API calls to external servers. Combined with open source infrastructure and open weight models, this creates the foundation for truly personal AI that cannot be controlled or monitored by external parties, whether corporations or governments.3. Data unions and collective data ownership offer an alternative model to current centralized data collection practices. Rather than having individual data harvested by large tech companies who profit from it, the concept of data unions suggests people could collectively pool their data for specific beneficial purposes while maintaining ownership and control. For example, in healthcare, millions of people could share anonymized biometric data to train medical AI systems that are incentivized to keep people healthy rather than treat them when sick, inverting the current insurance model to align incentives with actual health outcomes rather than profit from illness.4. The democratization of manufacturing and robotics through accessible technologies like ESP32 microcontrollers and local fabrication tools is creating new possibilities for distributed production. Just as desktop printers seemed impossible to early printers who controlled book production, we are approaching an era where individuals and small communities can manufacture sophisticated electronic devices and robots locally. This includes the ability to use language models to generate code for microcontrollers, order custom PCBs, and use desktop machines for component placement. While high quality manufacturing will still require larger operations, this gradiation of capability allows for much more local innovation and reduces dependence on centralized manufacturing.5. The concentration of power in technology, finance, and industry has reached levels that are unhealthy for both society and even for those who hold the power. When profit and control become too concentrated in the hands of a few entities, it creates a cancerous dynamic that threatens the stability of the entire system. History shows us warnings about the military industrial complex and other concentrated power structures, and now we are seeing similar patterns emerge in the tech industry. The solution requires building technology from the ground up that empowers individuals and communities, focusing on basics like food production, energy generation, and local manufacturing rather than increasing dependence on centralized systems.6. The provenance and quality of information is becoming a critical challenge as AI systems become more sophisticated and reality itself becomes harder to verify. We are rapidly approaching a point where video calls and digital interactions will be indistinguishable from AI generated fakes, which is why figures like Sam Altman have invested in systems like Worldcoin to verify human identity. However, this verification capability should not be centralized in the hands of single companies. End to end encryption and quantum encryption technologies need to be preserved and expanded to allow humans to communicate and verify information peer to peer without centralized intermediaries who could manipulate or control the flow of information.7. The future of human computer interaction is evolving toward sentient loop systems where machines have sensory input, real time learning, context understanding, and continuous operation in service of human needs. Self driving cars represent the first widespread consumer facing example of this architecture, with onboard computers that must function independently while occasionally connecting to networks. The critical question is whether these systems will be aligned to benefit their human users like a caring mother as AI pioneer Geoffrey Hinton suggests, or whether they will be controlled by centralized powers. The technologists building these systems have a responsibility to be benevolent and build structures that serve humanity rather than concentrate power, helping to create a future more like Star Trek than Terminator.

Cerramos la octava temporada con un episodio que me apetecía grabar desde hace meses. Igual te ha pasado como a mí: empecé hablando de un laboratorio de IA para cualquiera, y terminé recomendando GPUs de 3000 euros. Me fui creciendo, pero no hace falta. Te cuento cómo montar un laboratorio de IA local con el equipo que ya tienes. Da igual si tienes 8 GB de RAM o 16, CPU modesta o sin GPU. La clave está en elegir los modelos adecuados. Muchas veces nos perdemos buscando el modelo más grande, cuando con uno pequeño y bien cuantizado tenemos de sobra para el 80% de las tareas.Te hablo de Ollama, el gestor de modelos estándar para ejecutar modelos locales. Más de 180.000 estrellas en GitHub, API compatible con OpenAI, modelos para todos los presupuestos: desde Phi 3.5 con 3.8B parámetros hasta Qwen 1.5B que ocupa 1 GB. También la cuantización: reduces la precisión numérica de los pesos para que ocupen menos y vayan más rápido. El punto dulce es Q4_K_M, que reduce el tamaño a menos de un tercio. Para 8 GB de RAM, Q3_K_S puede ser tu salvación.También te hablo de Open WebUI, la interfaz que le da mil vueltas a ChatGPT. No solo chateas: tiene RAG local, Whisper integrado para transcribir voz (75 MB en CPU), TTS con Kokoro-82M para que el modelo te hable en tiempo real, búsqueda web, plugins y memoria persistente. Todo en un contenedor Docker que levantas con un solo comando.Y de SQLite Vec, extensión de SQLite sponsorizada por Mozilla para búsqueda semántica sin servidores vectoriales. Ni ChromaDB, ni Qdrant, ni Milvus. C puro que funciona hasta en Raspberry Pi. Creas tablas virtuales para vectores de 768 dimensiones, generas embeddings con nomic-embed-text, y buscas por similitud coseno en milisegundos. RAG local sin complicaciones.Y te explico cómo organizarlo todo con Docker o Podman. Un docker-compose.yml que levanta Ollama y Open WebUI en segundos, con healthchecks, redes separadas y volúmenes persistentes. También a limitar recursos con --memory y --cpus. He preparado scripts: inicialización que comprueba requisitos, crea directorios y descarga modelos; otro para descargar por niveles según tu hardware (nivel 1 para 8 GB, nivel 2 para 16 GB, nivel 3 para 32 GB); y uno de respaldo.Y la estrategia híbrida local + nube, que es lo que realmente tiene sentido. El enfoque Minions del Stanford Hazy Research Lab: el modelo local hace el trabajo pesado, y solo consulta al grande en la nube para tareas complejas. El 90% de las consultas se resuelven localmente. Ahorras dinero, mantienes privacidad de tus datos, y cuando necesitas potencia, la tienes.Con 16 GB de RAM y un SSD te sobra para el 80% de las tareas: traducciones, resúmenes, código, asistentes, RAG, transcripción de audio, texto a voz... Todo en tu máquina, sin enviar datos a servidores, sin suscripciones, sin depender de internet. Con 8 GB también puedes, con modelos más pequeños. Cerramos temporada, la novena arranca en el episodio 828. Capítulos del episodio:0:00 - Introducción — cierre de temporada 8 y replanteamiento2:30 - Hardware mínimo: 8-16 GB RAM + SSD obligatorio5:00 - Software base: instalar Ollama en tu distribución7:30 - Contenedores: Docker vs Podman para el laboratorio10:00 - Modelos pequeños: Phi 3.5, Qwen 1.5B y cuantización13:00 - Herramientas complementarias: SQLite Vec, Whisper, TTS16:00 - Organización del laboratorio: script y estructura de directorios19:00 - Demo: probando Ollama en local con modelos ligeros22:00 - Combinación local + nube: lo mejor de ambos mundos24:30 - Cierre, avance temporada 9 y despedidaMás información y enlaces en las notas del episodio

Anshel Sag and Mike Dano return for episode 257 of the 6G Podcast and recap Sag's visit to Qualcomm's 6G event, highlighting Qualcomm's view that 6G standards will remain global, real ISAC drone/car sensing demos, Giga-MIMO results (up to 16 Gbps downlink), a push for 400 MHz bandwidth, and an “AI-native” 6G approach including a compute card for the RAN while arguing GPUs aren't required. Dano summarizes Ookla's fixed wireless access report showing U.S. FWA holding up well with T-Mobile's median downloads over 200 Mbps and seasonal foliage effects, plus AT&T speed gains tied to EchoStar mid-band spectrum. They discuss MobileX being mostly acquired by Charlie Ergen's Connex, Starlink's stated plan to build a U.S. terrestrial network, Lockheed Martin's Verizon 5G-powered drone detection service Netsense launching next year, and expectations around a possible foldable iPhone at Apple's September 9 event.00:00 Welcome Back and Catch Up01:01 Qualcomm 6G Vision02:58 ISAC and Giga MIMO Demos04:41 AI Native 6G and GPU Debate11:06 Fixed Wireless Performance Report15:16 MobileX Acquisition and MVNOs18:44 Starlink Terrestrial Network Plans25:50 Lockheed Netsense Drone Detection29:37 Apple Event Foldable iPhone Buzz31:30 Foldables Demand and Tradeoffs39:58 Wrap Up and Where to Follow

Michael Williams joins the show to talk the tax strategy that most investors aren't using yet! He explains his three-phase approach to tax efficiency, focusing on using depreciation as an interest-free loan from the government to redirect money that would otherwise go toward taxes into income-producing assets. We cover his platform's current focus on data center infrastructure, including GPUs and servers, and digital advertising screens, as well as other potential assets such as construction equipment, bourbon barrels, trash trucks, and rental vehicles. Michael stresses the importance of working with qualified tax professionals and choosing assets with strong contracted revenue, bankability, and real economic performance rather than relying solely on tax savings. Today we discuss...  How high-net-worth individuals and business owners can use tax-efficient investment strategies to keep more money invested rather than paying it in taxes. The three phases of tax efficiency, including structuring finances, using depreciable assets, and determining how to own assets going forward. How depreciation can function like an interest-free loan from the government by allowing investors to redirect money that would otherwise go toward taxes. Data center infrastructure, including GPUs and servers, as one of the primary depreciable asset strategies currently offered. Digital advertising screens and billboards as another cash-flowing asset that can qualify for bonus depreciation. That investors should never purchase an asset solely for its tax benefits and that the underlying investment must make economic sense on its own. How revenue-sharing pools can help diversify cash flow across multiple assets rather than tying an investor's returns to a single asset. How these strategies can provide opportunities for investors who do not want to rely on real estate professional status to take advantage of depreciation. The importance of material participation and understanding whether an investor can actively participate enough to utilize certain tax benefits. What investors should look for in legitimate programs, including cash-flowing assets, contracted revenue, strong counterparties, and bankability. Tax savings should complement a strong investment rather than be the primary reason for making the investment. Today's Panelists: Kirk Chisholm | Innovative Wealth Barbara Friedberg | Barbara Friedberg Personal Finance Phil Weiss | Apprise Wealth Management Follow on Facebook: https://www.facebook.com/moneytreepodcast Follow LinkedIn: https://www.linkedin.com/showcase/money-tree-investing-podcast Follow on Twitter/X: https://x.com/MTIPodcast For more information, visit the full show notes at https://moneytreepodcast.com/tax-strategy-michael-williams-846 

In this episode of the Construction Corner podcast, Dillon dives deep into the AI-driven data center boom and what's really holding it back. He argues that while demand for electrical engineers and construction is set to grow significantly, the true bottleneck isn't chip supply or capital — it's power generation and transmission, tangled up in legislative and utility delays. Along the way, he unpacks how memory shortages, fab construction (like Micron's long-stalled New York facility), and hyperscaler CapEx spending from the "Mag Seven" all ripple through the supply chain together.The conversation then takes a turn toward the future: could data centers eventually move off-planet? Dillon walks through how SpaceX's Starship and V3 satellites are multiplying available bandwidth, how NVIDIA has already tested GPUs in space, and why space-based or off-shore data centers might become the answer once terrestrial power and jurisdictional constraints become too limiting — pointing to alternatives like the Middle East as jurisdictions more willing to host this infrastructure.

────────────────────────────────────────[00:02:09]Dolly Parton Used to Push Vaccines — Her Health Issues Began Shortly After She Got the ShotShe was charming and they used her; she is as much a victim as anything; health issues began shortly after the Moderna shot; her husband died a year ago.────────────────────────────────────────[00:27:19]Bessent Doubled Treasury Buybacks — Soros' Right-Hand Man Running Monetary Policy While MAGA Looks AwayMAGA goes several levels down to find a Soros connection, but the direct one at the top — Scott Bessent — gets a pass because Trump chose him.────────────────────────────────────────[00:29:00]AI Is Now 41% of the S&P 500 — Worse Than Dot Com, Worse Than 1929, Worse Than BIS SaidAt the dot com high it was 26.5%; now 41%; household equities at 42% of financial assets vs 38% at the dot com peak; never seen a market this inflated.────────────────────────────────────────[00:33:28]CDC Scientist Paul Thorntson Pleading Guilty — Used Grant Money to Buy a House, Two Cars, and a MotorcycleHis fake MMR/autism study was cited to deny more than 5,000 families' vaccine injury claims; the real crime is that the fraudulent research became official policy.────────────────────────────────────────[00:39:14]Thimerosal Is Mercury — Barbaric, Dark Ages ScienceKnight couldn't wear soft contacts because of thimerosal — turned his eyes blood red; they inject that into infants with undeveloped immune systems.────────────────────────────────────────[00:47:38]Navy Mandating mRNA Flu Shots While Inviting Back Marines It Fired for Refusing the COVID ShotOf 3,748 eligible Marines contacted, only 53 returned; Navy now mandating new shots; Hegseth's reinstatement PR says nothing about what comes next.────────────────────────────────────────[00:55:57]IDF Destroying Christian Villages in Lebanon — Calling Them Hezbollah Fortresses to Justify DemolitionTroops vandalized a Christian church inside; Katz said some villages must disappear; white phosphorus deployed; collective punishment that defines Nazism.────────────────────────────────────────[01:15:46]JFK Refused to Give Israel Nuclear Technology — Source: Every One of 10,000 Unreleased Documents Points at IsraelCongress passed a law twice demanding release; Trump didn't comply; Kennedy was actively trying to stop Israel from acquiring nuclear technology.────────────────────────────────────────[01:17:16]Rabbi Shmuley Makes Violent Threats Against Tucker Carlson and Candace Owens — Calls for Jews to Be Feared, Not LovedKnight: you can't handle a debate so you threaten; the man demanding Israel be feared is outraged anyone criticizes what is done to Gaza.────────────────────────────────────────[01:53:18]The AI Bubble Has Less Than a Year — Data Centers Will Become Pickleball CourtsSteve Keen called the 2008 crash; CAPEX is 87% short of what's needed; NVIDIA becoming its own bank; when credit disappears, data centers with 3-year GPUs become worthless. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

────────────────────────────────────────[00:02:09]Dolly Parton Used to Push Vaccines — Her Health Issues Began Shortly After She Got the ShotShe was charming and they used her; she is as much a victim as anything; health issues began shortly after the Moderna shot; her husband died a year ago.────────────────────────────────────────[00:27:19]Bessent Doubled Treasury Buybacks — Soros' Right-Hand Man Running Monetary Policy While MAGA Looks AwayMAGA goes several levels down to find a Soros connection, but the direct one at the top — Scott Bessent — gets a pass because Trump chose him.────────────────────────────────────────[00:29:00]AI Is Now 41% of the S&P 500 — Worse Than Dot Com, Worse Than 1929, Worse Than BIS SaidAt the dot com high it was 26.5%; now 41%; household equities at 42% of financial assets vs 38% at the dot com peak; never seen a market this inflated.────────────────────────────────────────[00:33:28]CDC Scientist Paul Thorntson Pleading Guilty — Used Grant Money to Buy a House, Two Cars, and a MotorcycleHis fake MMR/autism study was cited to deny more than 5,000 families' vaccine injury claims; the real crime is that the fraudulent research became official policy.────────────────────────────────────────[00:39:14]Thimerosal Is Mercury — Barbaric, Dark Ages ScienceKnight couldn't wear soft contacts because of thimerosal — turned his eyes blood red; they inject that into infants with undeveloped immune systems.────────────────────────────────────────[00:47:38]Navy Mandating mRNA Flu Shots While Inviting Back Marines It Fired for Refusing the COVID ShotOf 3,748 eligible Marines contacted, only 53 returned; Navy now mandating new shots; Hegseth's reinstatement PR says nothing about what comes next.────────────────────────────────────────[00:55:57]IDF Destroying Christian Villages in Lebanon — Calling Them Hezbollah Fortresses to Justify DemolitionTroops vandalized a Christian church inside; Katz said some villages must disappear; white phosphorus deployed; collective punishment that defines Nazism.────────────────────────────────────────[01:15:46]JFK Refused to Give Israel Nuclear Technology — Source: Every One of 10,000 Unreleased Documents Points at IsraelCongress passed a law twice demanding release; Trump didn't comply; Kennedy was actively trying to stop Israel from acquiring nuclear technology.────────────────────────────────────────[01:17:16]Rabbi Shmuley Makes Violent Threats Against Tucker Carlson and Candace Owens — Calls for Jews to Be Feared, Not LovedKnight: you can't handle a debate so you threaten; the man demanding Israel be feared is outraged anyone criticizes what is done to Gaza.────────────────────────────────────────[01:53:18]The AI Bubble Has Less Than a Year — Data Centers Will Become Pickleball CourtsSteve Keen called the 2008 crash; CAPEX is 87% short of what's needed; NVIDIA becoming its own bank; when credit disappears, data centers with 3-year GPUs become worthless. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

In this episode, Madelyn O'Farrell interviews Eesha Pathak, Senior Director of Product Management at Crusoe, about her unconventional career from software engineering and branding to leading enterprise AI at Google and now building AI-first infrastructure. They discuss Crusoe's vertically integrated, energy-first approach to cloud and data centers, capturing abundant energy (like stranded gas and renewables) and turning “electrons into intelligence” via GPUs and a custom cloud stack. Eesha explains how Crusoe's gigawatt-scale campuses and modular Spark edge deployments complement each other to deliver both scale and low-latency inference, dives into the Managed AI platform with its model marketplace, self-serve and tailored deployments, fine-tuning, and upcoming reinforcement learning, and highlights why judgment and holistic thinking are critical in product and engineering. She also unpacks Crusoe's close partnership with NVIDIA, its role in enabling physical AI and robotics with low-latency compute, a flexible data and partnership strategy, and her long-term vision of Crusoe becoming the most helpful company for people building AI, so customers can focus on their products instead of wrestling with infrastructure. Highlights from their conversation include: Eesha's Unconventional Career Path from Bosch to Google to Crusoe (0:29) Why Energy Is the Real Bottleneck for AI Infrastructure (3:30) What Energy-First Means and Bringing Compute to Abundant Power (5:04) Spark Modular Data Centers and Edge Zones Strategy (6:22) How Gigawatt Campuses and Edge Zones Work Together (8:26) Importance of Judgment in Product and Engineering Decisions (12:49) NVIDIA Partnership and Day Zero Nemotron Model Launches (15:25) Physical AI, Robotics, and Low-Latency Edge Inference (17:21) Crusoe's Data Strategy and Partnership Approach (21:52) Vision for Crusoe as Most Helpful Company for AI Builders (22:47) Closing Thoughts and Episode Wrap-Up (24:09) 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.

If there were any doubts about who's wearing the crown in the AI revolution... Nvidia just delivered another monster quarter. In today's episode, we're breaking down the latest earnings from Nvidia—and these aren't numbers that matter only to NVDA shareholders. Nvidia reported $96.2 BILLION in quarterly revenue, up an incredible 106% from a year ago. Even more impressive, its Data Center business generated $89 billion, up 117% year over year. Think about that for a moment. Nvidia isn't just growing. A company of this size just more than DOUBLED its revenue in one year. So the big question for today's show isn't simply whether Nvidia had a good quarter. It's: Can Nvidia—and the AI boom—keep this going? We'll dive into the numbers and look at what Nvidia's results tell us about the entire artificial-intelligence ecosystem. We'll discuss: Nvidia's latest earnings – What jumped out from the report and where the growth is coming from. Data Center dominance – What $89 billion in quarterly Data Center revenue tells us about global AI infrastructure spending. The AI spending boom – Are Microsoft, Meta, Amazon, Alphabet and other hyperscalers still willing to spend enormous amounts of money building AI infrastructure? Semiconductors – What Nvidia's results could mean for AMD, Broadcom, Micron and the rest of the chip sector. Memory – More AI computing means enormous demand for high-performance memory. Does Nvidia's growth strengthen the case for DRAM and HBM? Energy & infrastructure – All those GPUs have to go somewhere—and they require data centers, electricity, cooling, networking and an enormous infrastructure buildout. Valuation – At some point, even incredible growth can become fully priced in. Has Nvidia reached that point? The broader market – Nvidia has become so large and influential that its results can impact the Nasdaq, S&P 500 and overall investor sentiment. That's what makes this earnings report so important. Nvidia is no longer simply a semiconductor company investors watch four times a year. It's become one of the market's primary gauges of the entire AI investment cycle. Going into today's report, options markets were pricing roughly a 5.4% move in Nvidia shares, representing approximately $280 BILLION in potential market-cap movement in either direction. That's larger than the entire market capitalization of most companies! And with concerns growing recently about massive AI spending, stretched technology valuations and whether companies are generating enough return on their AI investments, Nvidia's results provide an important reality check. If AI is a bubble, somebody forgot to tell Nvidia's customers. But that doesn't mean the risks have disappeared. We'll separate the incredible fundamentals from the stock's valuation and ask the question traders actually care about: Great company... but is it still a great trade? For additional research, check out Nvidia Investor Relations and Nvidia Financial Reports. Listen now:

A few years ago, Caltech Prof. and co-founder of Accelerated Understanding, Anima Anandkumar set out to develop the first open-source weather model with AI. Talking to experts in the field, she was met with skepticism. Weather is chaotic, physics simulations are hard, have been developed for decades, and require supercomputers, the data just isn't there. Despite reservations, Anima went forth and built. Within a year her team had developed FourCastNet, a predictive model that is competitive with the best physics-based simulations available. Thanks to Anima, and her follow up work, anyone can now predict weather accurately over a short timescale using consumer grade GPUs. In the fifteen or so science episodes we've released on Latent.Space, we've covered atoms, molecules, materials, biology, and math. Anima is a pioneer in studying physical systems that are continuous. Weather, fusion, and fluid or heat flow are huge areas of science that are extremely difficult to model: they are large, chaotic, and fundamentally multi-scale. This is a field the AI community has somewhat neglected, but one we expect will grow fast. We plan to cover large physical systems more in coming episodes.One thing you can glean from Anima's work is that this area of AI resists the scaling ideas that have permeated the rest of the field. The data isn't there: open source datasets in many of these domains are limited to tens or hundreds of thousands of examples, far from what token-hungry transformers need. Even worse, the resolution that physics demands pushes the context length into the hundreds of billions, so you can't just throw more tokens at the problem. That isn't a ceiling though, just a slower road: progress here comes from building in structure and inductive biases. Sorry for all you bitter-lesson-pilled language modelers.“If each dimension is even a few hundred grid points, which is where industrial scale starts... we're talking hundreds of billions to even a trillion context length. So forget ever having a transformer for anything of this scale, all of the world's compute will not be enough.”The math underneathTo tackle these systems, Anima pioneered a technique known as Neural Operators, one of the most beautiful theoretical developments in AI of the last decade. These allow you to combine data and physical laws to enable multi-scale inputs and outputs. We're no longer modeling a grid, we're modeling a function that evolves over many scales. This allows Anima and crew to build in priors based upon physical intuition.To see how physical priors are still helpful for AI modeling, let's revisit the problem of weather forecasting on a global scale. The earth is a sphere, which meant that accurate modeling involved using the right basis set — the Spherical Harmonics. Run a weather model on a grid and it blows up fast. Move to the natural basis for the problem and it stays stable far longer, long enough to roll out months ahead instead of days. Anima's Fourier Neural Operator learns directly in this frequency domain, and its spherical variant powers FourCastNet 3, which models the weather across the whole globe and keeps running stably far into the future.The physical world is forgivingAnima explored Neural Operators across other physical domains too, and one striking observation is that the physical world is more forgiving than you'd expect. In fusion, a few thousand samples are enough to predict plasma disruptions, and to do it a million times faster than traditional simulation.None of this is a rejection of scale, it is a different route to it. Anima ultimately still wants to build a “foundation model for physics”, a model that spans many phenomena and does both simulation and design. You get there by building in the structure the physical world already has, not by waiting for data that will never exist. It is a start, and it will take longer than the token-driven parts of AI, because for the physical world tokens were never the answer.“All of the things that work with deep learning, let's take them, but make them a bit more principled.”Weather is only the beginningNeural operators and weather modeling were a personal passion of mine, so we've spent much of this blog and the episode exploring this work. Anima has done so much more! In the episode, we cover several other recent developments from Anima:* Anima has a series of works integrating neural networks and automated proof techniques. We talk about TorchLean, a new framework that lets you write PyTorch-style networks inside the proof assistant Lean and formally verify them. This is a major step for proving bounds on neural networks, something that would be really important for someone trying to, e.g., add a neural network as part of the control loop to their fusion reactor!* Anima was recently appointed to the United Nations Scientific Advisory Board! We talk with her about her goals of bringing evidence-based viewpoints to policy, and how AI in scientific domains can improve people's lives all over the world.This episode has something for every AI or science nerd! Elegant math? ✅ Old school harmonic analysis? ✅ Fundamental developments in modern AI? ✅ Practical ways of modeling the physical world? ✅Give it a watch! This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

────────────────────────────────────────[00:00:41]Trump's Tariff Tantrums Escalate to Canada — 50% on Cars, Trucks, and Auto Parts Starting Next YearLast-minute demands to stop the French language and mirror all US China tariffs revealed the real goal: making Canada the 51st state.────────────────────────────────────────[00:05:03]Trump Accuses Canada of Ripping Us Off — We Send Billions to Israel Every Year; What Do We Get? WarsDoug Ford: Ronald Reagan would be throwing up; threatened to cut off electricity to Michigan, Minnesota, and New York.────────────────────────────────────────[00:10:07]Canada's Carney: The Americans Want to Destroy Our Major Industries — Autos, Steel, and AluminumDeeply integrated supply chains mean a prolonged fight is costly for both sides; Trump doesn't care about American workers, only corporate sponsors.────────────────────────────────────────[00:13:33]Trump Cut Off Rare Earth Minerals From China — Now He's Cutting Off Canada, Our More Reliable SourceCritical minerals for military aircraft and missiles were being sourced from Canada; the same supply chain crisis as with the Lincoln.────────────────────────────────────────[00:01:27]AI Capex May Be the Pin That Bursts the Bubble — Corporations Pouring Money Into Depreciating HardwareWhen data centers go bankrupt, you'll have a silicon rust belt of obsolete GPUs; pushed by the same interests pushing the land grab.────────────────────────────────────────[01:37:28]GOP Data Center Panic — Mike Rogers Calls for Moratorium After Spending His Career Building the Surveillance StateAI will be a massive issue in 2028; Rogers is reacting to his opponent, not principle; Knight: I don't want standards for abuse, I don't want the cameras.────────────────────────────────────────[01:37:28]Flock CEO: Banning Cameras Is Like Banning Vehicles — We Need a Compromise Between Safety and PrivacyKnight: when you give up liberty you get nothing in return; not safer with less liberty — exactly the opposite; the tyrant always sells it as a balance.────────────────────────────────────────[01:48:36]Ford Motor Company Filed a Patent to Turn Its Cars Into Mobile Flock Cameras That Report Speeding to PoliceIf you own a Ford you're going to become a rat; they want to be a mobility company where you rent rides and sell surveillance data to the government.────────────────────────────────────────[01:48:36]Trump Attacks Republicans Who Are Running From Data Centers — Doubling Down While His Party ScramblesLate-summer backlash stretching into 2028; Greg Abbott, Josh Shapiro, and others distancing; Trump is attacking his own party for doing so.────────────────────────────────────────[02:00:03]Dispensationalists Applaud the Genocide Because Their Theology Puts Israel Above Christ — Heresy With Real ConsequencesConservatives have placed something above the gospel just like liberal theologians; Tallarico says God is a verb; the dispensationalist says Israel is God. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.

────────────────────────────────────────[00:00:41]Trump's Tariff Tantrums Escalate to Canada — 50% on Cars, Trucks, and Auto Parts Starting Next YearLast-minute demands to stop the French language and mirror all US China tariffs revealed the real goal: making Canada the 51st state.────────────────────────────────────────[00:05:03]Trump Accuses Canada of Ripping Us Off — We Send Billions to Israel Every Year; What Do We Get? WarsDoug Ford: Ronald Reagan would be throwing up; threatened to cut off electricity to Michigan, Minnesota, and New York.────────────────────────────────────────[00:10:07]Canada's Carney: The Americans Want to Destroy Our Major Industries — Autos, Steel, and AluminumDeeply integrated supply chains mean a prolonged fight is costly for both sides; Trump doesn't care about American workers, only corporate sponsors.────────────────────────────────────────[00:13:33]Trump Cut Off Rare Earth Minerals From China — Now He's Cutting Off Canada, Our More Reliable SourceCritical minerals for military aircraft and missiles were being sourced from Canada; the same supply chain crisis as with the Lincoln.────────────────────────────────────────[00:01:27]AI Capex May Be the Pin That Bursts the Bubble — Corporations Pouring Money Into Depreciating HardwareWhen data centers go bankrupt, you'll have a silicon rust belt of obsolete GPUs; pushed by the same interests pushing the land grab.────────────────────────────────────────[01:37:28]GOP Data Center Panic — Mike Rogers Calls for Moratorium After Spending His Career Building the Surveillance StateAI will be a massive issue in 2028; Rogers is reacting to his opponent, not principle; Knight: I don't want standards for abuse, I don't want the cameras.────────────────────────────────────────[01:37:28]Flock CEO: Banning Cameras Is Like Banning Vehicles — We Need a Compromise Between Safety and PrivacyKnight: when you give up liberty you get nothing in return; not safer with less liberty — exactly the opposite; the tyrant always sells it as a balance.────────────────────────────────────────[01:48:36]Ford Motor Company Filed a Patent to Turn Its Cars Into Mobile Flock Cameras That Report Speeding to PoliceIf you own a Ford you're going to become a rat; they want to be a mobility company where you rent rides and sell surveillance data to the government.────────────────────────────────────────[01:48:36]Trump Attacks Republicans Who Are Running From Data Centers — Doubling Down While His Party ScramblesLate-summer backlash stretching into 2028; Greg Abbott, Josh Shapiro, and others distancing; Trump is attacking his own party for doing so.────────────────────────────────────────[02:00:03]Dispensationalists Applaud the Genocide Because Their Theology Puts Israel Above Christ — Heresy With Real ConsequencesConservatives have placed something above the gospel just like liberal theologians; Tallarico says God is a verb; the dispensationalist says Israel is God. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.

“Create your value and your wealth as a strategic consultant instead of being a technology vendor.” In this Technology Reseller News podcast, Tim Mandell of Leaseweb launches an ongoing infrastructure series focused on how MSPs can build successful AI practices—and why AI infrastructure can no longer be treated as a one-size-fits-all proposition. Leaseweb is a 29-year-old, private and sovereign-by-design infrastructure-as-a-service provider. The company works with MSPs by supplying the underlying infrastructure while allowing the service provider to own the customer relationship and deliver the higher-value solution. Mandell says one of the biggest mistakes organizations make is starting with the hardware. The AI conversation is often dominated by GPUs, including the latest high-performance systems, but the most powerful hardware is not automatically the right infrastructure for every workload. “You have to understand what problem you're trying to solve before assuming the technology is going to solve it,” Mandell says. AI training, inference and production workloads can have very different requirements. For many MSP customers, inference is particularly important because performance depends heavily on latency, data location, storage and connectivity. Mandell points to an MSP that was losing customers because infrastructure had been placed in the wrong geographic location, creating latency problems that degraded the customer experience. GPUs may get most of the attention, but Mandell says storage can sometimes become the larger and more complicated infrastructure challenge. Organizations can underestimate both the amount of data required and how quickly that data must be retrieved. The same problem applies to sizing. MSPs can overengineer an environment and spend unnecessarily, or build something that lacks the flexibility required as customer demand grows. “There really is no such thing as one AI infrastructure,” Mandell says. “Different applications require different compute, bandwidth, storage and placement.” For MSPs, that creates an opportunity to move away from simply selling infrastructure and toward becoming strategic advisers. Leading with a particular server, GPU or technology stack turns infrastructure into a commodity where price becomes the primary differentiator. Instead, Mandell recommends beginning with the customer's business objective, asking where the organization is headed over the next several years and then designing the infrastructure around those outcomes. “The infrastructure is going to be what it needs to be based on the business outcome,” Mandell says. “But if you lead with infrastructure, that becomes the foundation of the relationship.” His takeaway for MSPs is straightforward: ask more questions, understand the workload and build value around the customer journey rather than the technology itself. Visit Leaseweb.com to learn more.  

After the U.S. treasury yields surged to levels not seen in nearly 20 years, U.S. Treasury Secretary Scott Bessent announced that the Treasury would double the size of its government debt repurchases. Treasury Department officials tell CNBC's Steve Liesman that the plan could be funded by the Treasury's General Account Fund, or its “rainy day” fund. Trade talks between the U.S. and Canada have collapsed, bringing 50% tariffs into effect on $20 billion worth of Canadian goods coming over the border. U.S. Trade Representative Jamieson Greer explains his own perspective on the negotiations. Nvidia is reportedly considering investing in AI startup Perplexity. Sprout CEO Shelly Li built her company to recycle, refurbish, remarket, and retire GPUs and data centers. Li explains the lifecycle of AI hardware from hyperscalers and the residual value of old chips and underscores power as the biggest constraint in the tech ecosystem.    Megan Cassella - 05:34 Steve Liesman - 13:39 Jamieson Greer - 22:55 Shelly Li - 39:03   In this episode: Amb. Jamieson Greer, @USTradeRep Joe Kernen, @JoeSquawk Becky Quick, @BeckyQuick Andrew Ross Sorkin, @andrewrsorkin Megan Cassella, @mmcassella Steve Liesman, @steveliesman Cameron Costa, @CameronCostaNY Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

SUMMARY: Brian, Brandon, and Aaron discuss news about Nvidia's reported $105B backing of OpenAI's Ohio data center and what it implies for GPUs as an “asset class” and enterprise AI. Brian argues Jensen Huang is shifting Nvidia's narrative from needing the newest chips immediately to portraying GPUs as long-lived, cash-flowing assets that can be financed like bonds, pushing risk onto banks and private equity. Brandon agrees scarcity has extended older GPU usefulness but warns the market could be flooded with newer, cheaper, more efficient hardware, leaving debt tied to obsolete equipment. Aaron likens GPUs to airplanes, expensive assets requiring constant utilization, while noting new AI builds demand entirely new data centers for power and cooling. The group questions widespread lack of profitability, compares the financing trend to past bubbles, and debates the optimistic case that breakthroughs could ultimately justify the investment.SHOW: 1056SHOW TRANSCRIPT: The Enterprise AI Show #1056 TranscriptSHOW VIDEO: https://youtu.be/vTLTdIZueJMSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShow topic: Nvidia's Pivot from Chipmaker to FinancierNvidia just backed $105B for OpenAI's Ohio data center and helped mobilize $500B+ in Wall Street financing (Apollo, Blackstone, BlackRock, Goldman, KKR) to fund GPU purchases, while AMD, Google, and Cerebras chip away at its tech lead. The moat is moving from silicon to balance sheet.Core question: Is a GPU actually securitizable like real estate or aircraft, or is this circular financing dressed up as infrastructure?The bull case: GPUs as productive, cash-flow-generating assets (compute-as-a-service) → financeable like data centers or planes, unlocking capital hyperscalers alone couldn't raise.The bear case: Depreciation risk; GPUs age fast, unlike buildings. What's the residual value of an H100-class chip in 2030? Securitizing a depreciating, obsolescence-prone asset is a very different bet than securitizing land.Circularity concern: Nvidia financing the customers who buy Nvidia chips, who generate the revenue that justifies Nvidia's valuation, echoes vendor financing bubbles (Cisco/telecom, 2000).Precedent: Compare to aircraft leasing/securitization models: what made those work (long asset life, resale markets, standardized valuation), and whether GPUs have any of that yet.Who bears the risk if utilization or model economics don't pan out: Nvidia, the banks, or the credit markets buying the paper?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

This week, we discuss the unsung genius of Apple Pay, AI watermarking, and why digital transformation fails without a crisis. Plus, D&D Beyond's secret character API. Watch the YouTube Live Recording of Episode 586 Runner-up Titles Special Sauce A new monkey's thing I am all for USB-C Did I like it It's all water marked' That NPC did need to be there It's Pre-Watermarked We Need to Touch Grass More Send Us Your APIs Rundown Apple Pay Chief Jennifer Bailey Retiring in October AI Watermarking's Unintended Consequences Anthropic says it will watermark text generated by its AI models Google will now allow users to remove visible watermark from its AI generations Why "It's People, Not Tech" Never Actually Changes Anything The Chief Therapy Officer, Job Titles as Culture Change, and AI as Spreadsheets, with Bryan Ross Platform Engineering ROI: What it costs to build your own platform How Duolingo uses AI to create lessons faster Silver Lake's Workday Buyout Talks Could Be the First 'SaaSpocalypse' Opportunity Relevant to Your Interests Limitless: An AI Podcast | The NVIDIA Bank: Jensen's $500B Wall Street Deal and GPUs as an Asset Class Inside North Korea's Operation to Conquer the American Job Market The shapeshifter's little brother Even Claude Is in the Dark About Dario Amodei's Wife—and Her Influence at Anthropic Broadcom Shares Plunge on Major VMware Security Threat IRS Proposes Simpler Process for Retirement Rollovers The Actual Reason Why Google "Fell Out" of the AI Race Changes Everything Stripe is reportedly in talks to buy PayPal Andreessen Horowitz Focus of DOJ Probe Over Board Directors Tech CEOs Overwhelmingly Distrusted by Young: Study Farewell, Mico: Microsoft's cute little AI blob is going the way of Bob Microsoft kills off unsuccessful AI features while merging its separate Copilot apps Google may retire Gems in October, forcing Skills migration OpenAI replaces revenue lead as Greg Brockman builds his presence OpenAI CFO Friar tells investors that enterprise business now bigger than consumer by revenue OpenAI sheds senior execs in pre-IPO refresh OpenAI's Brockman brushes off concerns about leadership changes in CNBC exclusive Anthropic CFO Krishna Rao is leading early IPO meetings with investors and has not discussed valuation, sources say Anthropic in Talks to Buy AI Startup Decart for $6 Billion Listener Feedback Milestone iOS App Conferences WeAreDevelopers NA, Sept 23-25, 2026, Discount Code: DEVPOD50 25 Free Tickets DevOpsDays Graz, Sept 4-5, 2026 Cloud Foundry Summit, Sept. 21st to 22nd, Heidelberg, Coté speaking. DevOpsDays Rockies, Sept. 22 – 23, 2026, Discount Code: 26DODSWEDEFTALK DevOpsDays Dallas, Sept 28-29, 2026 DevOpsDays Vilnius, Sep 30 - Oct 1, 2006 DevOpsDays Istanbul, Oct 24th, 2026, Coté keynoting. VMware User Group, Orlando, Oct 20-22, 2026 Cloud Native Denmark, Nov 19th, 2026, Copenhagen, Coté keynoting. SCALE 24x Pasadena, CA, April 1-4, 2027 SDT News & Community Join our Slack community Email the show: questions@softwaredefinedtalk.com Free stickers: Email your address to stickers@softwaredefinedtalk.com Follow us on social media: Twitter, Threads, Mastodon, LinkedIn, BlueSky Watch us on: Twitch, YouTube, Instagram, TikTok Book offer: Use code SDT for $20 off "Digital WTF" by Coté Sponsor the show Sponsor more podcasts with Failover Media Recommendations Brandon: TextSniper Coté: the dndbeyond.com API for AI: curl -s "https://character-service.dndbeyond.com/character/v5/character/145972701"

Dr. Karen Litzy is joined by Dr. Pedro Teixeira, Vice President of AI Engineering at Prompt Health and former co-founder and CEO of Prediction Health, for a practical conversation about how AI fits into healthcare workflows. Pedro breaks down the differences among automation, AI, and agentic systems and explains why the best tools support clinicians rather than replace their judgment. This episode focuses on what clinic owners and clinicians should look for when evaluating AI tools: workflow fit, safety, latency, cost, and whether the system improves over time. If you want a grounded, non-hype conversation about AI in healthcare, this is a useful one. Key topics ·       In this episode, Karen and Pedro compare thoughtful AI vs powerful AI and why workflow fit matters as much as model capability. ·       Pedro explains latency in practical terms, including why perceived delay matters and how feedback like loading states can make AI feel faster. ·       They unpack tokens, model size, and cost, including why input and output usage can change pricing so quickly. ·       Pedro shares how AI can work in the background across notes, codes, compliance checks, and analytics for clinic owners. ·       The conversation covers HIPAA, PHI, encryption, sandboxing, and limited tool access as essential safeguards for healthcare AI. ·       Pedro distinguishes automation, AI, and agentic systems, with examples of when rules are enough and when messy data really does call for AI. ·       They compare predictive vs generative models and explain why generating plausible text is not the same as forecasting a clinical outcome. ·       Karen and Pedro discuss how some clinics are using AI as a decision support tool, while still keeping humans in control of final decisions. ·       Pedro emphasizes that clinic owners should think in terms of systems, including what happens when AI works well and when it fails. ·       He closes with a simple evaluation question for any AI pitch: How does this system get better over time? Timestamps 00:00 - Introduction and why Pedro Teixeira is a grounded voice on AI in healthcare 01:24 - Why thoughtful AI matters more than powerful AI 03:57 - What latency means and why perceived speed changes the user experience 05:16 - How models work with transcripts, prompts, and tokens 07:24 - What tokens are and why AI bills can rise fast 09:13 - The real cost of large models, GPUs, and background processing 11:23 - How AI can quietly support clinic analytics and business coaching 13:13 - Why healthcare AI must stay closed loop and HIPAA safe 15:13 - Automation vs AI vs agentic systems 18:59 - Predictive vs generative models explained for clinic owners 21:45 - When AI can predict patterns from clinician notes and when it cannot 24:03 - How power user clinics are using AI tools in practice 25:56 - Why AI should do what clinicians decide, not decide for them 28:37 - Designing AI around systems, workflows, and failure states 30:22 - Using SOPs and training docs to think through AI implementation 31:57 - How clinic owners should evaluate whether to bring AI into the practice 35:53 - The one question to ask any AI vendor: how does it improve over time? 37:00 - Final takeaways and encouraging clinics to experiment 38:02 - Lightning round: overhyped AI tools in healthcare 39:20 - What clinicians should understand about how AI really works 40:50 - What Pedro would do if he were not building healthcare AI 41:41 - Real world learning, messy data, and why experience matters 42:59 - Pedro's health habits and the AI built tracker on his watch 44:15 - Where to find Pedro and Prompt Health Notable quotes "Thoughtful AI is really taking into account where are people using it, how does it fit into their day to day?" "The best systems are the ones where you are deciding." "How does this system get better?" Resources & Links: ·      Prompt Health ·      Pedro on LinkedIn More About Dr. Pedro Teixeira: Pedro Teixeira, MD, PhD, is Vice President of AI Engineering at Prompt Health and previously served as Co-Founder and CEO of PredictionHealth, now a Prompt Health company. With nearly two decades of experience across AI and healthcare and PhD-level training in biomedical informatics from Harvard and Vanderbilt, Pedro is one of the most grounded voices on AI in healthcare. He believes healthcare's biggest challenges are systems problems, not technology problems, and that the real promise of AI is creating leverage so clinicians can spend more time on what matters most: their patients. Jane Sponsorship Information: Book a one-on-one demo here Mention the code LITZY1MO for a free month Follow Dr. Karen Litzy on Social Media: Karen's Instagram Karen's LinkedIn Subscribe to Healthy, Wealthy & Smart: YouTube Website Apple Podcast Spotify SoundCloud Stitcher iHeart Radio

Join The Full Nerd gang as they offer level-headed takes about the latest PC building news. In this episode the gang is joined by Jake Roach from Tom's Hardware to chat about his recent interview with Intel which reveals the companies plans for future CPU launches, as well as looking at current market share numbers for GPUs with 16GB of VRAM, and more. And of course we answer questions live! Timecodes: (00:00:00) - Intro (00:05:42) - Intel CPU plans (01:00:01) - GPU market share (01:19:39) - Q&A Links: - Nova Lake on desktop: https://www.tomshardware.com/pc-components/cpus/intel-says-it-will-launch-new-core-with-nova-lake-on-desktop-first-not-in-data-center-vp-robert-hallock-hopes-enthusiasts-do-the-math-compared-to-amd - DDR4 Raptor Lake: https://www.tomshardware.com/pc-components/cpus/raptor-lake-is-a-core-part-of-the-portfolio-for-years-to-come-says-intel-theres-been-a-sudden-inrush-of-demand-for-lga-1700-chips-due-to-ddr5-prices - GPU sales data: https://wccftech.com/gpu-sales-data-by-german-retailer-shows-that-16-gb-gpus-still-lead-the-market-despite-being-way-more-expensive-than-ever/ Join the PC related discussions and ask us questions on Discord: https://discord.gg/UWhjwg778a Follow the crew on X and Bluesky: @AdamPMurray @BradChacos @MorphingBall Music by Our Ghosts: https://ourghosts.bandcamp.com/ Some links may contain affiliate links, which means if you buy something PCWorld may receive a small commission. ============= Follow PCWorld: Website: http://www.pcworld.com Newsletter: http://www.pcworld.com/newsletters ============= Learn more about your ad choices. Visit megaphone.fm/adchoices

The AI buildout has one big beneficiary today and that's neoclouds Coreweave and Nebius. These companies buy and rent out GPUs for AI and they're seing incredible demand for the assets they're building. We discuss the short-term demand and where these stocks face risks long-term. Plus, we discuss Cava's results and what inflation is telling us.Travis Hoium, Tyler Crowe, and Rachel Warren discuss:- Coreweave's Results- Neocloud Financing- Cava's Traffic Growth- Why Restaurants Are Hard- Inflation Eases- Energy's Impact PricesCompanies discussed: Coreweave (CRWV), Nebius (NBIS), Cava (CAVA).Host: Travis HoiumGuests: Tyler Crowe, Rachel WarrenEngineer: Kristi Waterworth Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, "TMF") do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit ⁠⁠⁠megaphone.fm/adchoices⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices