Podcasts about gpu

Gonka AI is a decentralized network that provides efficient AI computing power by leveraging global GPU resources for tasks like model training and inference. It challenges centralized providers like AWS and Google by using a novel "Proof of Work 2.0" mechanism, where nearly all compute goes to productive AI workloads rather than blockchain security. Guest: David Liberman and Daniil Liberman- Co-founders~This episode is sponsored by Gonka~Website: https://gonka.ai/X: https://x.com/gonka_aiDiscord: https://discord.gg/REcpeYc7P7GitHub: https://github.com/gonka-ai/gonka/pulls00:00 Intro01:00 Gonka's mission02:30 How can a platform use Gonka?03:45 Network capacity surge05:45 Scale growth in 18months08:45 Bitcoin of A.I.?11:30 Why decentralization?15:00 Security risks18:30 Value for token holders22:30 AI agents integration25:30 Gonka use cases28:00 Outro#Crypto #AI #cryptocurrency ~Decentralized A.I. At Warp Speed

On this episode of The GAP Luke Lawrie and Joab Gilroy return for another year of talking about video games. The Games they've been playing this week include Dispatch, Death Stranding 2, Hades II, Dying Light: The Beast, Nonolith, Hytale, Cubic Odyssey, The Séance of Blake Manor, Quarantine Zone, Patient Zero: Pandemic Simulator, and Magic: The Gathering – Lorwyn Eclipsed. Over in the news Meta lays off over 1,000 staff and shuts three VR studios, a new expansion is reportedly in development for The Witcher 3, GPU prices may spike due to hardware shortages, and The Division director Julian Gerighty departs Massive for DICE. This episode goes for 2 hours and 25 minutes, it also contains coarse language. Timestamps – 00:00:00 – Start 00:10:09 – Magic: The Gathering – Lorwyn Eclipsed 00:15:29 – Patient Zero: Pandemic Simulator 00:22:20 – Quarantine Zone 00:29:46 – The Séance of Blake Manor 00:36:26 – Cubic Odyssey 00:40:44 – Hytale 00:44:39 – Nonolith 00:46:18 – Dying Light: The Beast 00:58:44 – Hades II 01:11:43 – Death Stranding 2 01:24:35 – Dispatch 01:37:39 – News 01:59:17 – Questions 02:14:39 – Weekly Plugs 02:19:36 – End of Show Subscribe in a reader iTunes / Spotify

Episode 144Happy New Year! This is one of my favorite episodes of the year — for the fourth time, Nathan Benaich and I did our yearly roundup of AI news and advancements, including selections from this year's State of AI Report.If you've stuck around and continue to listen, I'm really thankful you're here. I love hearing from you.You can find Nathan and Air Street Press here on Substack and on Twitter, LinkedIn, and his personal site. Check out his writing at press.airstreet.com.Find me on Twitter (or LinkedIn if you want…) for updates on new episodes, and reach me at editor@thegradient.pub for feedback, ideas, guest suggestions.Outline* (00:00) Intro* (00:44) Air Street Capital and Nathan world* Nathan's path from cancer research and bioinformatics to AI investing* The “evergreen thesis” of AI from niche to ubiquitous* Portfolio highlights: Eleven Labs, Synthesia, Crusoe* (03:44) Geographic flexibility: Europe vs. the US* Why SF isn't always the best place for original decisions* Industry diversity in New York vs. San Francisco* The Munich Security Conference and Europe's defense pivot* Playing macro games from a European vantage point* (07:55) VC investment styles and the “solo GP” approach* Taste as the determinant of investments* SF as a momentum game with small information asymmetry* Portfolio diversity: defense (Delian), embodied AI (Syriact), protein engineering* Finding entrepreneurs who “can't do anything else”* (10:44) State of AI progress in 2025* Momentous progress in writing, research, computer use, image, and video* We're in the “instruction manual” phase* The scale of investment: private markets, public markets, and nation states* (13:21) Range of outcomes and what “going bad” looks like* Today's systems are genuinely useful—worst case is a valuation problem* Financialization of AI buildouts and GPUs* (14:55) DeepSeek and China closing the capability gap* Seven-month lag analysis (Epoch AI)* Benchmark skepticism and consumer preferences (”Coca-Cola vs. Pepsi”)* Hedonic adaptation: humans reset expectations extremely quickly* Bifurcation of model companies toward specific product bets* (18:29) Export controls and the “evolutionary pressure” argument* Selective pressure breeds innovation* Chinese companies rushing to public markets (Minimax, ZAI)* (21:30) Reasoning models and test-time compute* Chain of thought faithfulness questions* Monitorability tax: does observability reduce quality?* User confusion about when models should “think”* AI for science: literature agents, hypothesis generation* (23:53) Chain of thought interpretability and safety* Anthropomorphization concerns* Alignment faking and self-preservation behaviors* Cybersecurity as a bigger risk than existential risk* Models as payloads injected into critical systems* (27:26) Commercial traction and AI adoption data* Ramp data: 44% of US businesses paying for AI (up from 5% in early 2023)* Average contract values up to $530K from $39K* State of AI survey: 92% report productivity gains* The “slow takeoff” consensus and human inertia* Use cases: meeting notes, content generation, brainstorming, coding, financial analysis* (32:53) The industrial era of AI* Stargate and XAI data centers* Energy infrastructure: gas turbines and grid investment* Labs need to own models, data, compute, and power* Poolside's approach to owning infrastructure* (35:40) Venture capital in the age of massive GPU capex* The GP lives in the present, the entrepreneur in the future, the LP in the past* Generality vs. specialism narratives* “Two or 20”: management fees vs. carried interest* Scaling funds to match entrepreneur ambitions* (40:10) NVIDIA challengers and returns analysis* Chinese challengers: 6x return vs. 26x on NVIDIA* US challengers: 2x return vs. 12x on NVIDIA* Grok acquired for $20B; Samba Nova markdown to $1.6B* “The tide is lifting all boats”—demand exceeds supply* (44:06) The hardware lottery and architecture convergence* Transformer dominance and custom ASICs making a comeback* NVIDIA still 90–95% of published AI research* (45:49) AI regulation: Trump agenda and the EU AI Act* Domain-specific regulators vs. blanket AI policy* State-level experimentation creates stochasticity* EU AI Act: “born before GPT-4, takes effect in a world shaped by GPT-7”* Only three EU member states compliant by late 2025* (50:14) Sovereign AI: what it really means* True sovereignty requires energy, compute, data, talent, chip design, and manufacturing* The US is sovereign; the UK by itself is not* Form alliances or become world-class at one level of the stack* ASML and the Netherlands as an example* (52:33) Open weight safety and containment* Three paths: model-based safeguards, scaffolding/ecosystem, procedural/governance* “Pandora's box is open”—containment on distribution, not weights* Leak risk: the most vulnerable link is often human* Developer–policymaker communication and regulator upskilling* (55:43) China's AI safety approach* Matt Sheehan's work on Chinese AI regulation* Safety summits and China's participation* New Chinese policies: minor modes, mental health intervention, data governance* UK's rebrand from “safety” to “security” institutes* (58:34) Prior predictions and patterns* Hits on regulatory/political areas; misses on semiconductor consolidation, AI video games* (59:43) 2026 Predictions* A Chinese lab overtaking US on frontier (likely ZAI or DeepSeek, on scientific reasoning)* Data center NIMBYism influencing midterm politics* (01:01:01) ClosingLinks and ResourcesNathan / Air Street Capital* Air Street Capital* State of AI Report 2025* Air Street Press — essays, analysis, and the Guide to AI newsletter* Nathan on Substack* Nathan on Twitter/X* Nathan on LinkedInFrom Air Street Press (mentioned in episode)* Is the EU AI Act Actually Useful? — by Max Cutler and Nathan Benaich* China Has No Place at the UK AI Safety Summit (2023) — by Alex Chalmers and Nathan BenaichResearch & Analysis* Epoch AI: Chinese AI Models Lag US by 7 Months — the analysis referenced on the US-China capability gap* Sara Hooker: The Hardware Lottery — the essay on how hardware determines which research ideas succeed* Matt Sheehan: China's AI Regulations and How They Get Made — Carnegie EndowmentCompanies Mentioned* Eleven Labs — AI voice synthesis (Air Street portfolio)* Synthesia — AI video generation (Air Street portfolio)* Crusoe — clean compute infrastructure (Air Street portfolio)* Poolside — AI for code (Air Street portfolio)* DeepSeek — Chinese AI lab* Minimax — Chinese AI company* ASML — semiconductor equipmentOther Resources* Search Engine Podcast: Data Centers (Part 1 & 2) — PJ Vogt's two-part series on XAI data centers and the AI financing boom* RAAIS Foundation — Nathan's AI research and education charity Get full access to The Gradient at thegradientpub.substack.com/subscribe

This week, the hosts go deep on out-of-band updates, unwanted "innovations," and the uneasy cost of tech's latest gold rush. Plus, securing a Microsoft account is not as hard as some think, and neither are passkeys once you get past the jargon. And for developers, AI Dev Gallery offers a fascinating glimpse at what you can do for free with AI used against a CPU, GPU, or NPU. Windows 11 Microsoft issues an emergency fix for a borked Windows Update. Right. A fix for a fix. Hell freezes over, if only slightly: Microsoft quietly made some positive changes to forced OneDrive Folder Backup. Donʼt worry, itʼs still forced (and appears to be opt-in, but isnʼt). But you can back out more elegantly. So itʼs opt-out, not opt-in, but a step forward. Plus, a new behavior Windows 11 on Arm PCs can now download games from the Xbox app (previously only through the Insider program) Over 85 percent of Xbox games on PC work in WOA now Prism emulator now supports AVX and AVX2 and Epic Anti-Cheat, and there is a new Windows Performance Fit feature offering guidance on which titles should play well. Beta: New 25H2 build with account dialog modernization, Click to Do and desktop background improvements. Not for Dev, suggesting itʼs about to move to 26H1 Notepad and Paint get more features yet again. Notably, these updates are for Dev and Canary only, suggesting these might be 26Hx features (then again, versions don't matter, right?) AI Just say no: To AI, to Copilot, and to Satya Nadella Our national nightmare is over: You can now (easily) hide Copilot in Microsoft Edge ChatGPT Go is now available worldwide, ads are on the way because of course Wikipedia partners with Amazon, Meta, Microsoft, more on AI Xbox & gaming January Xbox Update brings Game Sync Indicator, more Solid second half of January for Xbox Game Pass Microsoft will likely introduce a free, ad-supported Xbox Cloud Gaming tier because of course Tips & picks Tip of the week: Secure your Microsoft account App pick of the week: AI Dev Gallery RunAs Radio this week: Ideation to Implementation with Amber Vandenburg Liquor pick of the week: Estancia Raicilla Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. 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

This week, the hosts go deep on out-of-band updates, unwanted "innovations," and the uneasy cost of tech's latest gold rush. Plus, securing a Microsoft account is not as hard as some think, and neither are passkeys once you get past the jargon. And for developers, AI Dev Gallery offers a fascinating glimpse at what you can do for free with AI used against a CPU, GPU, or NPU. Windows 11 Microsoft issues an emergency fix for a borked Windows Update. Right. A fix for a fix. Hell freezes over, if only slightly: Microsoft quietly made some positive changes to forced OneDrive Folder Backup. Donʼt worry, itʼs still forced (and appears to be opt-in, but isnʼt). But you can back out more elegantly. So itʼs opt-out, not opt-in, but a step forward. Plus, a new behavior Windows 11 on Arm PCs can now download games from the Xbox app (previously only through the Insider program) Over 85 percent of Xbox games on PC work in WOA now Prism emulator now supports AVX and AVX2 and Epic Anti-Cheat, and there is a new Windows Performance Fit feature offering guidance on which titles should play well. Beta: New 25H2 build with account dialog modernization, Click to Do and desktop background improvements. Not for Dev, suggesting itʼs about to move to 26H1 Notepad and Paint get more features yet again. Notably, these updates are for Dev and Canary only, suggesting these might be 26Hx features (then again, versions don't matter, right?) AI Just say no: To AI, to Copilot, and to Satya Nadella Our national nightmare is over: You can now (easily) hide Copilot in Microsoft Edge ChatGPT Go is now available worldwide, ads are on the way because of course Wikipedia partners with Amazon, Meta, Microsoft, more on AI Xbox & gaming January Xbox Update brings Game Sync Indicator, more Solid second half of January for Xbox Game Pass Microsoft will likely introduce a free, ad-supported Xbox Cloud Gaming tier because of course Tips & picks Tip of the week: Secure your Microsoft account App pick of the week: AI Dev Gallery RunAs Radio this week: Ideation to Implementation with Amber Vandenburg Liquor pick of the week: Estancia Raicilla Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. 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

This week, the hosts go deep on out-of-band updates, unwanted "innovations," and the uneasy cost of tech's latest gold rush. Plus, securing a Microsoft account is not as hard as some think, and neither are passkeys once you get past the jargon. And for developers, AI Dev Gallery offers a fascinating glimpse at what you can do for free with AI used against a CPU, GPU, or NPU. Windows 11 Microsoft issues an emergency fix for a borked Windows Update. Right. A fix for a fix. Hell freezes over, if only slightly: Microsoft quietly made some positive changes to forced OneDrive Folder Backup. Donʼt worry, itʼs still forced (and appears to be opt-in, but isnʼt). But you can back out more elegantly. So itʼs opt-out, not opt-in, but a step forward. Plus, a new behavior Windows 11 on Arm PCs can now download games from the Xbox app (previously only through the Insider program) Over 85 percent of Xbox games on PC work in WOA now Prism emulator now supports AVX and AVX2 and Epic Anti-Cheat, and there is a new Windows Performance Fit feature offering guidance on which titles should play well. Beta: New 25H2 build with account dialog modernization, Click to Do and desktop background improvements. Not for Dev, suggesting itʼs about to move to 26H1 Notepad and Paint get more features yet again. Notably, these updates are for Dev and Canary only, suggesting these might be 26Hx features (then again, versions don't matter, right?) AI Just say no: To AI, to Copilot, and to Satya Nadella Our national nightmare is over: You can now (easily) hide Copilot in Microsoft Edge ChatGPT Go is now available worldwide, ads are on the way because of course Wikipedia partners with Amazon, Meta, Microsoft, more on AI Xbox & gaming January Xbox Update brings Game Sync Indicator, more Solid second half of January for Xbox Game Pass Microsoft will likely introduce a free, ad-supported Xbox Cloud Gaming tier because of course Tips & picks Tip of the week: Secure your Microsoft account App pick of the week: AI Dev Gallery RunAs Radio this week: Ideation to Implementation with Amber Vandenburg Liquor pick of the week: Estancia Raicilla Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. 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

This week, the hosts go deep on out-of-band updates, unwanted "innovations," and the uneasy cost of tech's latest gold rush. Plus, securing a Microsoft account is not as hard as some think, and neither are passkeys once you get past the jargon. And for developers, AI Dev Gallery offers a fascinating glimpse at what you can do for free with AI used against a CPU, GPU, or NPU. Windows 11 Microsoft issues an emergency fix for a borked Windows Update. Right. A fix for a fix. Hell freezes over, if only slightly: Microsoft quietly made some positive changes to forced OneDrive Folder Backup. Donʼt worry, itʼs still forced (and appears to be opt-in, but isnʼt). But you can back out more elegantly. So itʼs opt-out, not opt-in, but a step forward. Plus, a new behavior Windows 11 on Arm PCs can now download games from the Xbox app (previously only through the Insider program) Over 85 percent of Xbox games on PC work in WOA now Prism emulator now supports AVX and AVX2 and Epic Anti-Cheat, and there is a new Windows Performance Fit feature offering guidance on which titles should play well. Beta: New 25H2 build with account dialog modernization, Click to Do and desktop background improvements. Not for Dev, suggesting itʼs about to move to 26H1 Notepad and Paint get more features yet again. Notably, these updates are for Dev and Canary only, suggesting these might be 26Hx features (then again, versions don't matter, right?) AI Just say no: To AI, to Copilot, and to Satya Nadella Our national nightmare is over: You can now (easily) hide Copilot in Microsoft Edge ChatGPT Go is now available worldwide, ads are on the way because of course Wikipedia partners with Amazon, Meta, Microsoft, more on AI Xbox & gaming January Xbox Update brings Game Sync Indicator, more Solid second half of January for Xbox Game Pass Microsoft will likely introduce a free, ad-supported Xbox Cloud Gaming tier because of course Tips & picks Tip of the week: Secure your Microsoft account App pick of the week: AI Dev Gallery RunAs Radio this week: Ideation to Implementation with Amber Vandenburg Liquor pick of the week: Estancia Raicilla Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. 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

In this episode of Lead-Lag Live, Melanie Schafer sits down with Michael Mo, CEO of KULR Technology Group (NYSE: KULR), to explore why energy reliability is emerging as the critical constraint behind AI, robotics, drones, telecom infrastructure, and next-generation data centers.Fresh off CES and following KULR's newly announced $30M telecom battery supply agreement, Mo explains how high-power, high-safety battery systems are becoming mission-critical as electrification accelerates. From NASA-proven thermal technologies to lithium-ion replacements for legacy lead-acid systems, KULR is positioning itself at the center of multiple multi-year secular growth trends.The conversation covers AI data center power resilience, UAV and drone electrification, telecom backup systems, and why battery safety, reliability, and domestic supply chains matter more than ever as power demand explodes.In this episode:– Why power—not chips—may be the next AI bottleneck– KULR's NASA-derived battery safety and thermal technologies– The Cooler One platform and growth across drones, robotics, and aviation– Replacing lead-acid batteries in telecom with lithium-based solutions– Energy-as-a-Service and reducing total cost of ownership– AI data center battery buffers and GPU-level power protection– Scaling execution with a debt-free balance sheet and strong cash positionLead-Lag Live brings you inside conversations with the leaders shaping markets at the intersection of technology, energy, and investing. Subscribe for insights that cut through the noise.#AIInfrastructure #EnergyStorage #BatteryTechnology #Drones #Telecom #DataCenters #Electrification #KULR #MarketOutlook #CleanEnergy #InvestingStart your adventure with TableTalk Friday: A D&D Podcast at the link below or wherever you get your podcasts!Youtube: https://youtube.com/playlist?list=PLgB6B-mAeWlPM9KzGJ2O4cU0-m5lO0lkr&si=W_-jLsiREjyAIgEsSpotify: https://open.spotify.com/show/75YJ921WGQqUtwxRT71UQB?si=4R6kaAYOTtO2V Support the show

As constraints on energy, water, and permitting collide with exploding demand for AI and compute, a once-fringe idea is moving rapidly toward the center of the conversation: putting data centers in space. Starcloud believes orbital infrastructure isn't science fiction—it's a necessary extension of the global compute stack if scaling is going to continue at anything close to its current pace.Founded by Philip Johnston, Starcloud is building space-based compute systems designed to compete on cost, performance, and scale with terrestrial data centers. The company has already flown a data center–grade GPU in orbit and is now working toward larger, commercially viable systems that could reshape where and how AI is powered. We discuss:How energy and permitting constraints are reshaping the future of computeWhy space-based data centers may be economically inevitable, not optionalWhat Starcloud proved by running an H100 GPU in orbitHow launch costs, watts-per-kilogram, and chip longevity define the real economicsThe national security implications of who controls future compute capacity • Chapters •00:00 - Intro00:50 - The issue with data centers02:20 - Explosion of the data center debates04:58 - Philip's 5GW data center rendering and early conceptions of data centers in space at YC08:16 - Proving people wrong11:17 - The team at Starcloud today12:29 - Competing against SpaceX's data center14:42 - Sam Altman's beef with Starlink16:52 - Economics of Orbital vs Terrestrial Data Centers by Andrew McCallip21:33 - Where are we putting these things?23:50 - Latency in space25:59 - Political side of building data centers28:36 - Starcloud 130:16 - Space based processors30:51 - Shakespeare in space32:00 - Hardening an Nvidia H100 against radiation and making chips in space economical34:43 - Cooling systems in space36:01 - How Starcloud is thinking about replacing failed GPUs38:46 - The mission for Starcloud 240:05 - Competitors outside of SpaceX40:49 - Getting to economical launch costs44:35 - Will the next great wars be over water and power for data centers?46:25 - What keeps Philip up at night?47:11 - What keeps Mo up at night? • Show notes •Starcloud's website — https://www.starcloud.com/Philip's socials — https://x.com/PhilipJohnstonMo's socials — https://x.com/itsmoislamPayload's socials — https://twitter.com/payloadspace / https://www.linkedin.com/company/payloadspaceIgnition's socials — https://twitter.com/ignitionnuclear /  https://www.linkedin.com/company/ignition-nuclear/Tectonic's socials — https://twitter.com/tectonicdefense / https://www.linkedin.com/company/tectonicdefense/Valley of Depth archive — Listen: https://pod.payloadspace.com/ • About us •Valley of Depth is a podcast about the technologies that matter — and the people building them. Brought to you by Arkaea Media, the team behind Payload (space), Ignition (nuclear energy), and Tectonic (defense tech), this show goes beyond headlines and hype. We talk to founders, investors, government officials, and military leaders shaping the future of national security and deep tech. From breakthrough science to strategic policy, we dive into the high-stakes decisions behind the world's hardest technologies.Payload: www.payloadspace.comTectonic: www.tectonicdefense.comIgnition: www.ignition-news.com

This week, the hosts go deep on out-of-band updates, unwanted "innovations," and the uneasy cost of tech's latest gold rush. Plus, securing a Microsoft account is not as hard as some think, and neither are passkeys once you get past the jargon. And for developers, AI Dev Gallery offers a fascinating glimpse at what you can do for free with AI used against a CPU, GPU, or NPU. Windows 11 Microsoft issues an emergency fix for a borked Windows Update. Right. A fix for a fix. Hell freezes over, if only slightly: Microsoft quietly made some positive changes to forced OneDrive Folder Backup. Donʼt worry, itʼs still forced (and appears to be opt-in, but isnʼt). But you can back out more elegantly. So itʼs opt-out, not opt-in, but a step forward. Plus, a new behavior Windows 11 on Arm PCs can now download games from the Xbox app (previously only through the Insider program) Over 85 percent of Xbox games on PC work in WOA now Prism emulator now supports AVX and AVX2 and Epic Anti-Cheat, and there is a new Windows Performance Fit feature offering guidance on which titles should play well. Beta: New 25H2 build with account dialog modernization, Click to Do and desktop background improvements. Not for Dev, suggesting itʼs about to move to 26H1 Notepad and Paint get more features yet again. Notably, these updates are for Dev and Canary only, suggesting these might be 26Hx features (then again, versions don't matter, right?) AI Just say no: To AI, to Copilot, and to Satya Nadella Our national nightmare is over: You can now (easily) hide Copilot in Microsoft Edge ChatGPT Go is now available worldwide, ads are on the way because of course Wikipedia partners with Amazon, Meta, Microsoft, more on AI Xbox & gaming January Xbox Update brings Game Sync Indicator, more Solid second half of January for Xbox Game Pass Microsoft will likely introduce a free, ad-supported Xbox Cloud Gaming tier because of course Tips & picks Tip of the week: Secure your Microsoft account App pick of the week: AI Dev Gallery RunAs Radio this week: Ideation to Implementation with Amber Vandenburg Liquor pick of the week: Estancia Raicilla Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to Windows Weekly at https://twit.tv/shows/windows-weekly Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. 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

AI data centers are no longer just buildings full of racks. They are tightly coupled systems where power, cooling, IT, and operations all depend on each other, and where bad assumptions get expensive fast. On the latest episode of The Data Center Frontier Show, Editor-in-Chief Matt Vincent talks with Sherman Ikemoto of Cadence about what it now takes to design an “AI factory” that actually works. Ikemoto explains that data center design has always been fragmented. Servers, cooling, and power are designed by different suppliers, and only at the end does the operator try to integrate everything into one system. That final integration phase has long relied on basic tools and rules of thumb, which is risky in today's GPU-dense world. Cadence is addressing this with what it calls “DC elements”:  digitally validated building blocks that represent real systems, such as NVIDIA's DGX SuperPOD with GB200 GPUs. These are not just drawings; they model how systems really behave in terms of power, heat, airflow, and liquid cooling. Operators can assemble these elements in a digital twin and see how an AI factory will actually perform before it is built. A key shift is designing directly to service-level agreements. Traditional uncertainty forced engineers to add large safety margins, driving up cost and wasting power. With more accurate simulation, designers can shrink those margins while still hitting uptime and performance targets, critical as rack densities move from 10–20 kW to 50–100 kW and beyond. Cadence validates its digital elements using a star system. The highest level, five stars, requires deep validation and supplier sign-off. The GB200 DGX SuperPOD model reached that level through close collaboration with NVIDIA. Ikemoto says the biggest bottleneck in AI data center buildouts is not just utilities or equipment; it is knowledge. The industry is moving too fast for old design habits. Physical prototyping is slow and expensive, so virtual prototyping through simulation is becoming essential, much like in aerospace and automotive design. Cadence's Reality Digital Twin platform uses a custom CFD engine built specifically for data centers, capable of modeling both air and liquid cooling and how they interact. It supports “extreme co-design,” where power, cooling, IT layout, and operations are designed together rather than in silos. Integration with NVIDIA Omniverse is aimed at letting multiple design tools share data and catch conflicts early. Digital twins also extend beyond commissioning. Many operators now use them in live operations, connected to monitoring systems. They test upgrades, maintenance, and layout changes in the twin before touching the real facility. Over time, the digital twin becomes the operating platform for the data center. Running real AI and machine-learning workloads through these models reveals surprises. Some applications create short, sharp power spikes in specific areas. To be safe, facilities often over-provision power by 20–30%, leaving valuable capacity unused most of the time. By linking application behavior to hardware and facility power systems, simulation can reduce that waste, crucial in an era where power is the main bottleneck. The episode also looks at Cadence's new billion-cycle power analysis tools, which allow massive chip designs to be profiled with near-real accuracy, feeding better system- and facility-level models. Cadence and NVIDIA have worked together for decades at the chip level. Now that collaboration has expanded to servers, racks, and entire AI factories. As Ikemoto puts it, the data center is the ultimate system—where everything finally comes together—and it now needs to be designed with the same rigor as the silicon inside it.

Wilder Lopes is the CEO and Founder of Ogre.run, working on AI-driven dependency resolution and reproducible code execution across environments.How Universal Resource Management Transforms AI Infrastructure Economics // MLOps Podcast #357 with Wilder Lopes, CEO / Founder of Ogre.runJoin the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractEnterprise organizations face a critical paradox in AI deployment: while 52% struggle to access needed GPU resources with 6-12 month waitlists, 83% of existing CPU capacity sits idle. This talk introduces an approach to AI infrastructure optimization through universal resource management that reshapes applications to run efficiently on any available hardware—CPUs, GPUs, or accelerators.We explore how code reshaping technology can unlock the untapped potential of enterprise computing infrastructure, enabling organizations to serve 2-3x more workloads while dramatically reducing dependency on scarce GPU resources. The presentation demonstrates why CPUs often outperform GPUs for memory-intensive AI workloads, offering superior cost-effectiveness and immediate availability without architectural complexity.// BioWilder Lopes is a second-time founder, developer, and research engineer focused on building practical infrastructure for developers. He is currently building Ogre.run, an AI agent designed to solve code reproducibility.Ogre enables developers to package source code into fully reproducible environments in seconds. Unlike traditional tools that require extensive manual setup, Ogre uses AI to analyze codebases and automatically generate the artifacts needed to make code run reliably on any machine. The result is faster development workflows and applications that work out of the box, anywhere.// Related LinksWebsite: https://ogre.runhttps://lopes.aihttps://substack.com/@wilderlopes https://youtu.be/YCWkUub5x8c?si=7RPKqRhu0Uf9LTql~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Wilder on LinkedIn: /wilderlopes/Timestamps:[00:00] Secondhand Data Centers Challenges[00:27] AI Hardware Optimization Debate[03:40] LLMs on Older Hardware[07:15] CXL Tradeoffs[12:04] LLM on CPU Constraints[17:07] Leveraging Existing Hardware[22:31] Inference Chips Overview[27:57] Fundamental Innovation in AI[30:22] GPU CPU Combinations[40:19] AI Hardware Challenges[43:21] AI Perception Divide[47:25] Wrap up

It is only mid-January 2026, and the world has already reached peak "end-times" energy. In this episode of the LTS podcast, Marcos, Mr. G, and Josue attempt to find the humor in our collective digital collapse as they navigate the total wreckage of the GPU market and the AI-driven "hardware apocalypse." Between dodging cosmic glitches and whatever military-grade "extraterrestrials" are currently haunting the skies, the trio dives into the soul-deep debate of anime subbing versus dubbing—passionately arguing that Japanese voice acting in Demon Slayer is the only thing still providing pure emotional stability in this cursed timeline. If the first two weeks of the year are already this unhinged, at least we'll have high-quality animation to watch while the RAM prices send us into early retirement.#AnimeRecommendations #Gaming #TechIndustryMr. G Social Mediahttps://www.instagram.com/ameliorationautos?igsh=eTIwOGhxazA4ZGJs-------------------------------------------------- IG: ⁠⁠https://bit.ly/IG-LTS -------------------------------------------------- ⁠⁠LTS on X: ⁠⁠https://bit.ly/LTSTweets -------------------------------------------------- ⁠⁠Buy Me Coffee: ⁠⁠https://www.buymeacoffee.com/LTS2020

In this episode of The Circuit, Ben Bajarin and Jay Goldberg discuss the launch of Ben's new publication, "The Diligent Stack." The duo then performs a deep dive into TSMC's recent earnings, analyzing the risks of semiconductor cyclicality, the massive CapEx requirements for the future, and the specific bottlenecks in advanced packaging (CoWoS). Later, they shift focus to OpenAI's partnership with Cerebras and the introduction of ads to fund massive compute needs. Finally, they break down the latest data on GPU pricing, highlighting the significant premiums hyperscalers charge compared to NeoClouds and the difficulty of tracking pricing for Nvidia's new Grace Blackwell chips.

What happens when the AI race stops being about size and starts being about sense? In this episode of Tech Talks Daily, I sit down with Wade Myers from MythWorx, a company operating quietly while questioning some of the loudest assumptions in artificial intelligence right now. We recorded this conversation during the noise of CES week, when headlines were full of bigger models, more parameters, and ever-growing GPU demand. But instead of chasing scale, this discussion goes in the opposite direction and asks whether brute force intelligence is already running out of road. Wade brings a perspective shaped by years as both a founder and investor, and he explains why today's large language models are starting to collide with real-world limits around power, cost, latency, and sustainability. We talk openly about the hidden tax of GPUs, how adding more compute often feels like piling complexity onto already fragile systems, and why that approach looks increasingly shaky for enterprises dealing with technical debt, energy constraints, and long deployment cycles. What makes this conversation especially interesting is MythWorx's belief that the next phase of AI will look less like prediction engines and more like reasoning systems. Wade walks through how their architecture is modeled closer to human learning, where intelligence is learned once and applied many times, rather than dragging around the full weight of the internet to answer every question. We explore why deterministic answers, audit trails, and explainability matter far more in areas like finance, law, medicine, and defense than clever-sounding responses. There is also a grounded enterprise angle here. We talk about why so many organizations feel uneasy about sending proprietary data into public AI clouds, how private AI deployments are becoming a board-level concern, and why most companies cannot justify building GPU-heavy data centers just to experiment. Wade draws parallels to the early internet and smartphone app eras, reminding us that the playful phase often comes before the practical one, and that disappointment is often a signal of maturation, not failure. We finish by looking ahead. Edge AI, small-footprint models, and architectures that reward efficiency over excess are all on the horizon, and Wade shares what MythWorx is building next, from faster model training to offline AI that can run on devices without constant connectivity. It is a conversation about restraint, reasoning, and realism at a time when hype often crowds out reflection. So if bigger models are no longer the finish line, what should business and technology leaders actually be paying attention to next, and are we ready to rethink what intelligence really means? Useful Links Connect with Wade Myers Learn More About MythWorx Thanks to our sponsors, Alcor, for supporting the show.

We're just out of the recent earnings season and we've seen a wild range of results and some interesting implications. Melissa Otto CFA, head of S&P Global's Visible Alpha research team, returns to discuss what that markets have been saying and what she makes of the data with host Eric Hanselman. Macroeconomic effects are having some impact, as consumer sentiment diverges across the top and the bottom of the economy. In technology, there are mixed feelings about AI as the hunt continues for use cases with decisive revenue returns. The hyperscalers are continuing to invest capital at staggering rates and, so far, the markets have mostly approved. AI supply chain companies, like NVIDIA, are generally moving forward with solid results. The larger question is where is the AI boom headed. There are constraints not only in supply chains for data centers, but also in energy supply. Agentic AI has a lot of promise, but needs to prove out its value and earn trust, as providers look to improve efficiency with more targeted silicon, like ASICs, to stand up alongside the forests of GPU's being deployed. As investors hunt for improved returns, they may be rotating to international opportunities and small cap companies that might be able to see faster returns from AI deployments. More S&P Global Content: Next in Tech podcast: Agentic Customer Experience Nvidia GTC in DC Blackwell expectations increase Otto: Markets are grappling with how to price AI-related stocks   Next in Tech podcast, Episode 239: AI Infrastructure For S&P Global Subscribers: A view of peaks and plateaus AI to lead tech spending in 2026, but orgs losing track of energy efficiency – Highlights from Macroeconomic Outlook, SME Tech Trends Hyperscaler earnings quarterly: Alphabet, Amazon and Microsoft charge ahead on AI capacity buildouts Agents are already driving workplace impact and agentic AI adoption – Highlights from VotE: AI & Machine Learning Big Picture 2026 AI Outlook: Unleashing agentic potential Credits: Host/Author: Eric Hanselman Guest: Melissa Otto, CFA Producer/Editor: Feranmi Adeoshun Published With Assistance From: Sophie Carr, Kyra Smith

Discover how Cerebras is challenging NVIDIA with a fundamentally different approach to AI hardware and large-scale inference.In this episode of Startup Project, Nataraj sits down with Andrew Feldman, co-founder and CEO of Cerebras Systems, to discuss how the company built a wafer-scale AI chip from first principles. Andrew shares the origin story of Cerebras, why they chose to rethink chip architecture entirely, and how system-level design decisions unlock new performance for modern AI workloads.The conversation explores:Why inference is becoming the dominant cost and performance bottleneck in AIHow Cerebras' wafer-scale architecture overcomes GPU memory and communication limitsWhat it takes to compete with incumbents like NVIDIA and AMD as a new chip companyThe tradeoffs between training and inference at scaleCerebras' product strategy across systems, cloud offerings, and enterprise deploymentsThis episode is a deep dive into AI infrastructure, semiconductor architecture, and system-level design, and is especially relevant for builders, engineers, and leaders thinking about the future of AI compute.

Philip Johnston is co-founder and CEO of Starcloud, a company building data centers in space to solve AI's power crisis. Starcloud has already launched the first NVIDIA H100 GPU into orbit and is partnering with cloud providers like Crusoe to scale orbital computing infrastructure.As AI demand accelerates, data centers are running into a new bottleneck: access to reliable, affordable power. Grid congestion, interconnection delays, and cooling requirements are slowing the deployment of new AI data centers, even as compute demand continues to surge. Traditional data centers face 5-10 year lead times for new power projects due to permitting, interconnection queues, and grid capacity constraints.In this episode, Philip explains why Starcloud is building data centers in orbit, where continuous solar power is available and heat can be rejected directly into the vacuum of space. He walks through Starcloud's first on-orbit GPU deployment, the realities of cooling and radiation in space, and how orbital data centers could relieve pressure on terrestrial power systems as AI infrastructure scales.Episode recorded on Dec 11, 2025 (Published on Jan 13, 2026)In this episode, we cover: [04:59] What Starcloud's orbital data centers look like (and how they differ from terrestrial facilities)[06:37] How SpaceX Starship's reusable launch vehicles change space economics[10:45] The $500/kg breakeven point for space-based solar vs. Earth [14:15] Why space solar panels produce 8x more energy than ground-based arrays [21:19] Thermal management: Cooling NVIDIA GPUs in a vacuum using radiators [25:57] Edge computing in orbit: Real-time inference on satellite imagery [29:22] The Crusoe partnership: Selling power-as-a-service in space [31:21] Starcloud's business model: Power, cooling, and connectivity [34:18] Addressing critics: What could prevent orbital data centers from workingKey Takeaways:Starcloud launched the first NVIDIA H100 GPU into orbit in November 2024 Space solar produces 8x more energy per square meter than terrestrial solar Breakeven launch cost for orbital data centers: $500/kg Current customers: DOD and commercial Earth observation satellites needing real-time inference Target: 10 gigawatts of orbital computing capacity by early 2030s Enjoyed this episode? Please leave us a review! Share feedback or suggest future topics and guests at info@mcj.vc.Connect with MCJ:Cody Simms on LinkedInVisit mcj.vcSubscribe to the MCJ Newsletter*Editing and post-production work for this episode was provided by The Podcast Consultant

An airhacks.fm conversation with Thomas Wuerthinger (@thomaswue) about: clarification of GraalVM release cadence changes and decoupling from openJDK releases, GraalVM focusing on LTS Java releases only (skipping non-LTS like Java 26), GraalVM as a multi-vendor polyglot project with community edition and third-party vendors like Red Hat BellSoft and microdoc, increased focus on python support due to AI popularity, GraalVM team alignment with Oracle Database organization, Oracle Multilingual Engine (MLE) for running JavaScript and Python in Oracle Database, MySQL MLE integration, native image support for stored procedures in Oracle Database, shipping lambda functions from client applications to database for temporary execution, treating Oracle Database as an operating system for running business logic, serverless workloads directly in Oracle Database, application snapshotting similar to CRaC but running in user space without kernel privileges, efficient scale-to-zero capabilities with native images, Oracle REST Data Services service generalization for serverless execution platform, database triggers for workflow systems and application wake-up, durable functions with transactional state storage in Oracle Database, comparison to AS400 architecture with transaction manager database and operating system in same memory, memory price increases making GraalVM native image more attractive, lower memory consumption benefits of native image beyond just startup time, CPU-based inference support with SIMD and Vector API, TornadoVM for GPU-based inference built on Graal compiler, WebAssembly compilation target for native images, edge function deployment with WebAssembly, Intel memory protection keys for sandboxed native image execution, native image layers for shared base libraries similar to docker layers, profile-guided optimizations for size reduction, upx binary compression for 3x size reduction, memory savings from eliminated class metadata and profiling data not garbage collector differences, 32-bit object headers in serial GC smaller than HotSpot, polyglot integration allowing Python and JavaScript embedding in Java applications, Micronaut framework compile-time annotation processing, quarkus framework best alignment with native image for smallest binaries, GraalVM roadmap focused on database synergies and serverless innovation Thomas Wuerthinger on twitter: @thomaswue

In this episode of the Crazy Wisdom podcast, host Stewart Alsop sits down with Peter Schmidt Nielsen, who is building FPGA-accelerated servers at Saturn Data. The conversation explores why servers need FPGAs, how these field-programmable gate arrays work as "IO expanders" for massive memory bandwidth, and why they're particularly well-suited for vector database and search applications. Peter breaks down the technical realities of FPGAs - including why they "really suck" in many ways compared to GPUs and CPUs - while explaining how his company is leveraging them to provide terabyte-per-second bandwidth to 1.3 petabytes of flash storage. The discussion ranges from distributed systems challenges and the CAP theorem to the hardware-software relationship in modern computing, offering insights into both the philosophical aspects of search technology and the nuts-and-bolts engineering of memory controllers and routing fabrics.For more information about Peter's work, you can reach him on Twitter at @PTRSCHMDTNLSN or find his website at saturndata.com.Timestamps00:00 Introduction to FPGAs and Their Role in Servers02:47 Understanding FPGA Limitations and Use Cases05:55 Exploring Different Types of Servers08:47 The Importance of Memory and Bandwidth11:52 Philosophical Insights on Search and Access Patterns14:50 The Relationship Between Hardware and Search Queries17:45 Challenges of Distributed Systems20:47 The CAP Theorem and Its Implications23:52 The Evolution of Technology and Knowledge Management26:59 FPGAs as IO Expanders29:35 The Trade-offs of FPGAs vs. ASICs and GPUs32:55 The Future of AI Applications with FPGAs35:51 Exciting Developments in Hardware and BusinessKey Insights1. FPGAs are fundamentally "crappy ASICs" with serious limitations - Despite being programmable hardware, FPGAs perform far worse than general-purpose alternatives in most cases. A $100,000 high-end FPGA might only match the memory bandwidth of a $600 gaming GPU. They're only valuable for specific niches like ultra-low latency applications or scenarios requiring massive parallel I/O operations, making them unsuitable for most computational workloads where CPUs and GPUs excel.2. The real value of FPGAs lies in I/O expansion, not computation - Rather than using FPGAs for their processing power, Saturn Data leverages them primarily as cost-effective ways to access massive amounts of DRAM controllers and NVMe interfaces. Their server design puts 200 FPGAs in a 2U enclosure with 1.3 petabytes of flash storage and terabyte-per-second read bandwidth, essentially using FPGAs as sophisticated I/O expanders.3. Access patterns determine hardware performance more than raw specs - The way applications access data fundamentally determines whether specialized hardware will provide benefits. Applications that do sparse reads across massive datasets (like vector databases) benefit from Saturn Data's architecture, while those requiring dense computation or frequent inter-node communication are better served by traditional hardware. Understanding these patterns is crucial for matching workloads to appropriate hardware.4. Distributed systems complexity stems from failure tolerance requirements - The difficulty of distributed systems isn't inherent but depends on what failures you need to tolerate. Simple approaches that restart on any failure are easy but unreliable, while Byzantine fault tolerance (like Bitcoin) is extremely complex. Most practical systems, including banks, find middle ground by accepting occasional unavailability rather than trying to achieve perfect consistency, availability, and partition tolerance simultaneously.5. Hardware specialization follows predictable cycles of generalization and re-specialization - Computing hardware consistently follows "Makimoto's Wave" - specialized hardware becomes more general over time, then gets leapfrogged by new specialized solutions. CPUs became general-purpose, GPUs evolved from fixed graphics pipelines to programmable compute, and now companies like Etched are creating transformer-specific ASICs. This cycle repeats as each generation adds programmability until someone strips it away for performance gains.6. Memory bottlenecks are reshaping the hardware landscape - The AI boom has created severe memory shortages, doubling costs for DRAM components overnight. This affects not just GPU availability but creates opportunities for alternative architectures. When everyone faces higher memory costs, the relative premium for specialized solutions like FPGA-based systems becomes more attractive, potentially shifting the competitive landscape for memory-intensive applications.7. Search applications represent ideal FPGA use cases due to their sparse access patterns - Vector databases and search workloads are particularly well-suited to FPGA acceleration because they involve searching through massive datasets with sparse access patterns rather than dense computation. These applications can effectively utilize the high bandwidth to flash storage and parallel I/O capabilities that FPGAs provide, making them natural early adopters for this type of specialized hardware architecture.

Moiz Kohari, VP of Enterprise AI and Data Intelligence at DDN, breaks down what it actually takes to get AI into production and keep it there. If your org is stuck in pilot mode, this conversation will help you spot the real blockers, from trust and hallucinations to data architecture and GPU bottlenecks.Key takeaways• GenAI success in the enterprise is less about the demo and more about trust, accuracy, and knowing when the system should say “I don't know.”• “Operationalizing” usually fails at the handoff, when humans stay permanently in the loop and the business never captures the full benefit.• Data architecture is the multiplier. If your data is siloed, slow, or hard to access safely, your AI roadmap stalls, no matter how good your models are.• GPU spend is only worth it if your pipelines can feed the GPUs fast enough. A lot of teams are IO bound, so utilization stays low and budgets get burned.• The real win is better decisions, faster. Moving from end of day batch thinking to intraday intelligence can change risk, margin, and response time in major ways.Timestamped highlights00:35 What DDN does, and why data velocity matters when GPUs are the pricey line item02:12 AI vs GenAI in the enterprise, and why “taking the human out” is where value shows up08:43 Hallucinations, trust, and why “always answering” creates real production risk12:00 What teams do with the speed gains, and why faster delivery shifts you toward harder problems12:58 From hours to minutes, how GPU acceleration changes intraday risk and decision making in finance20:16 Data architecture choices, POSIX vs object storage, and why your IO layer can make or break AI readinessA line worth stealing“Speed is great, but trust is the frontier. If your system can't admit what it doesn't know, production is where the project stops.”Pro tips you can apply this week• Pick one workflow where the output can be checked quickly, then design the path from pilot to production up front, including who approves what and how exceptions get handled.• Audit your bottleneck before you buy more compute. If your GPUs are waiting on data, fix storage, networking, and pipeline throughput first.• Build “confidence behavior” into the system. Decide when it should answer, when it should cite, and when it should escalate to a human.Call to actionIf you got value from this one, follow the show and turn on notifications so you do not miss the next episode.

What if we told you that CES did not feature any new GPUs?  But it did feature more frames!  MSI with LIGHTNING and GPU safeguard, Phison's new controller, and that wily AMD with new Ryzen 7 9850X3D (and confirmed Ryzen 9 9950X3D2) - whee!  Remember the Reboot computer generated cartoon?  Remember D-Link Routers and Zero Days?  Remember Intel?  It's all here! That and everything old is new again with Old GPUs and CPUs coming back .. because RAM.Thanks again to our sponsor with CopilotMoney!  Get on your single pane of financial glass and bring order to your money and spending - it's even actually fun to save again.  Get the web version and use our code for 26% off at http://try.copilot.money/pcperTimestamps:0:00 Intro00:56 Patreon01:37 Food with Josh04:10 AMD announces Ryzen 7 9850X3D05:41 AMD sort of confirmed the 9950X3D207:00 NVIDIA DLSS 4.509:34 Intel was at CES12:50 MSI LIGHTNING returns14:54 MSI also launching GPU Safeguard Plus PSUs19:44 WD_Black is now Sandisk Optimus GX Pro21:54 Phison has the most efficient SSD controller26:11 ASUS ROG RGB Stripe OLED28:44 First computer-animated TV show restored33:29 Podcast sponsor - Copilot Money34:57 (In)Security Corner44:32 Gaming Quick Hits1:06:31 Picks of the Week1:24:08 Outro ★ Support this podcast on Patreon ★

BS Section and House Keeping Discord Server geekoholics.com/discord/ Whatcha Been Playing?  Ready Or Not   Demeo X D&D DorfRomantik Stick it to the Stick man Arc Raiders Marvel's Cosmic Invasion Dispatch (completed) Donkey Kong Bananaza (Completed)  Lost Soul Aside News:  Cross Platform / PC / Misc. Vince Zampella, co-creator of Call of Duty and Respawn Entertainment, has died 'It's going into very good hands': CD Projekt is selling GOG Marathon art lead departs Bungie of his own volition, ahead of game's new release date AMD and Nvidia will reportedly raise GPU prices "significantly" in 2026 Yes, aggression-matchmaking is now a thing in Arc Raiders From the Air Force to arcades to home consoles: Sega co-founder David Rosen dies aged 95 Fortnite's latest collab with an adult animated series that's somehow still going is none other than South Park | Rock Paper Shotgun Ubisoft close the studio behind Assassin's Creed Rebellion days after the developers vote to unionise | Rock Paper Shotgun Top Five Most-Played Games on PlayStation and Xbox in 2025 in the US Were the Same as in 2024 - IGN 007 First Light has been Delayed Top Selling Steam games of the year Nintendo   Nintendo will offer an alternative to Switch 2's controversial Game Key Cards, dev claims PlayStation Sony announces the Hyperpop collection PSA's: Epic Games Store Freebies: Bloons TD6 Monthly PS games are out Free 4 All SpongeBob movie Messing around with my Spectrum Steam sale shame Steelseries Nova 7 Wireless V2 Rewatching Reacher Reading Reacher (The book that matches season 3)  Finished Gen V

I'm about to get on a plane and will be gone for a couple weeks, but didn't want to leave you Breaking Changeless so I did the thing where I stand up in front of a microphone and talked at you. Again. Like I do. Fun fact: this is the first and only time I've taken a phone call live, on-air! I was just too lazy to edit that out gracefully. Whenever I go to Japan solo, I experience moments of loneliness, so I'd really appreciate it if you sent me some praise or complaints or ideas to podcast@searls.co and I'll feel comforted by the knowledge that you exist. Your engagement sustains me. Lotta weird and dumb links this go-round: Eric Doggett is a great friend/artist Fortune Feimster isn't spelled how I would've guessed Ray-Ban Meta Wayfarer (Gen 2) is the best gift anyone's given me in a while POSSE Party's tutorial videos are just enough to convince you to either bother or not bother Reddit's r/selfhosted is at least a little self-aware I'm giving myself some grace when it comes to the newsletter EDID Emulators are a hardware product that exist only because Windows is bad Looking forward to trying Happy for remote Claude Code / Codex CLI work Aaron's puns, ranked Pebble Index 01 Google's / XReal Putting It All on Glasses Next Year XReal is partnering with Asus ROG, too Google and Apple partner on better Android-iPhone switching NYT profiles John Ternus AirPods Pro with IR cameras (instead of stem clicks?!) JPMorgan Chase Reaches a Deal to Take Over the Apple Credit Card (News+) The Clicks Power Keyboard looks rad Expedition 33's Game Awards sweep has me asking, who will be the first to VEGOT? Valve still sending this guy chocolates every Christmas The post-GeForce era: What if Nvidia abandons PC gaming? The 5090 could cost $5090 by the end of 2026 Nvidia plans heavy cuts to GPU supply in early 2026 Racks of AI chips are too damn heavy (News+) Vera Rubin is probably even heavier GPT Image 1.5 is better but not good enough PSA: make ChatGPT less warm, enthusiastic, and emoji-tastic (News+) You can (supposedly) buy your Instacart groceries without leaving ChatGPT The massive year-end Ed Zitron newsletter. Podcasts are AI now (News+) Copywriters reveal how AI has decimated their industry A Stanford degree wont save you (News+) 'Godfather of SaaS' Says He Replaced Most of His Sales Team With AI Agents NYC phone ban reveals some students can't read clocks Swearing Actually Seems to Make Humans Physically Stronger Corporation for Public Broadcasting to Shut Down After 58 Years Due to Trump Eliminating Funding Grok Is Generating Sexual Content Far More Graphic Than What's on X (News+) Outer Worlds 2 Ball X Pit Stranger Things Season 5 Reddit's terrific r/RealOrAI sub The RayNeo Air 3s are the display glasses I'd recommend if you can find them for $199 Murderbot UDCast universal subtitling (and the movie I wanted to watch) Beckygram.com

The AI boom is hitting real limits. In this episode, the Newcomer team breaks down why data centers are running out of power, what is really happening inside OpenAI after its latest shakeup, and why neocloud players like CoreWeave may be heading toward a financial crunch.Eric Newcomer, Tom Dotan, and Maline Renberg explain the investor panic behind the scenes, the brutal GPU economics, and what these cracks mean for the future of AI infrastructure.

A new week means new questions! Hope you have fun with these!The Oscars are presented by which professional honorary organization Headquartered in Beverly Hills, California?The French company Van Cleef & Arpels is a business mainly specializing in what?A quay is a structure primarily built on or along what kind of geographical feature?The first successful tornado warning in history occurred in 1948 at Tinker Air Field Air Force Base near what city?Till We Have Faces, The Great Divorce, and The Screwtape Letters are lesser-known novels by which author?In video and tabletop games, what does "NPC" stand for?Biellmann Spin, Lutz, and Crossover are all terms used in which sport?In a computer or video gaming system, what does the acronym GPU stand for?H2O2 is the chemical structure for what common product?In Greek myth, which monster was beheaded by the hero Perseus?Before decimalisation in the UK, how many pence made a shilling?The German state that existed from 1701 to 1918 was known as the Kingdom of what?Chad Kroeger and his Canadian chums enjoy this slightly sweet dark rye bread from Germany.In military tech, falconets, culverins, and carronades were all types of what?On The Office, what are the awards called that Michael hands out to his employees?MusicHot Swing, Fast Talkin, Bass Walker, Dances and Dames, Ambush by Kevin MacLeod (incompetech.com)Licensed under Creative Commons: By Attribution 3.0 http://creativecommons.org/licenses/by/3.0/Don't forget to follow us on social media:Patreon – patreon.com/quizbang – Please consider supporting us on Patreon. Check out our fun extras for patrons and help us keep this podcast going. We appreciate any level of support!Website – quizbangpod.com Check out our website, it will have all the links for social media that you need and while you're there, why not go to the contact us page and submit a question!Facebook – @quizbangpodcast – we post episode links and silly lego pictures to go with our trivia questions. Enjoy the silly picture and give your best guess, we will respond to your answer the next day to give everyone a chance to guess.Instagram – Quiz Quiz Bang Bang (quizquizbangbang), we post silly lego pictures to go with our trivia questions. Enjoy the silly picture and give your best guess, we will respond to your answer the next day to give everyone a chance to guess.Twitter – @quizbangpod We want to start a fun community for our fellow trivia lovers. If you hear/think of a fun or challenging trivia question, post it to our twitter feed and we will repost it so everyone can take a stab it. Come for the trivia – stay for the trivia.Ko-Fi – ko-fi.com/quizbangpod – Keep that sweet caffeine running through our body with a Ko-Fi, power us through a late night of fact checking and editing!

a16z co-founder and General Partner Marc Andreessen joins an AMA-style conversation to explain why AI is the largest technology shift he has experienced, how the cost of intelligence is collapsing, and why the market still feels early despite rapid adoption. The discussion covers how falling model costs and fast capability gains are reshaping pricing, distribution, and competition across the AI stack, why usage-based and value-based pricing are becoming standard, and how startups and incumbents are navigating big versus small models and open versus closed systems. Marc also addresses China's progress, regulatory fragmentation, lessons from Europe, and why venture portfolios are designed to back multiple, conflicting outcomes at once. Resources:Follow Marc Andreessen on X: https://twitter.com/pmarcaFollow Jen Kha on X: https://twitter.com/jkhamehl Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X :https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://twitter.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.    Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This is a recap of the top 10 posts on Hacker News on January 06, 2026. This podcast was generated by wondercraft.ai (00:30): Vietnam bans unskippable adsOriginal post: https://news.ycombinator.com/item?id=46514677&utm_source=wondercraft_ai(01:52): enclose.horseOriginal post: https://news.ycombinator.com/item?id=46509211&utm_source=wondercraft_ai(03:14): AWS raises GPU prices 15% on a Saturday, hopes you weren't paying attentionOriginal post: https://news.ycombinator.com/item?id=46511153&utm_source=wondercraft_ai(04:36): The Post-American InternetOriginal post: https://news.ycombinator.com/item?id=46509019&utm_source=wondercraft_ai(05:59): 65% of Hacker News posts have negative sentiment, and they outperformOriginal post: https://news.ycombinator.com/item?id=46512881&utm_source=wondercraft_ai(07:21): Opus 4.5 is not the normal AI agent experience that I have had thus farOriginal post: https://news.ycombinator.com/item?id=46515696&utm_source=wondercraft_ai(08:43): C Is Best (2025)Original post: https://news.ycombinator.com/item?id=46511470&utm_source=wondercraft_ai(10:05): Why is the Gmail app 700 MB?Original post: https://news.ycombinator.com/item?id=46514692&utm_source=wondercraft_ai(11:28): Stop Doom Scrolling, Start Doom Coding: Build via the terminal from your phoneOriginal post: https://news.ycombinator.com/item?id=46517458&utm_source=wondercraft_ai(12:50): Show HN: Prism.Tools – Free and privacy-focused developer utilitiesOriginal post: https://news.ycombinator.com/item?id=46511469&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

The future of AI training is shaped by one constraint: keeping GPUs fed.In this episode, Lukas Biewald talks with CoreWeave SVP Corey Sanders about why general-purpose clouds start to break down under large-scale AI workloads.According to Corey, the industry is shifting toward a "Neo Cloud" model to handle the unique demands of modern models.They dive into the hardware and software stack required to maximize GPU utilization and achieve high goodput.Corey's conclusion is clear: AI demands specialization.Connect with us here:Corey Sanders: https://www.linkedin.com/in/corey-sanders-842b72/ CoreWeave: https://www.linkedin.com/company/coreweave/ Lukas Biewald: https://www.linkedin.com/in/lbiewald/ Weights & Biases: https://www.linkedin.com/company/wandb/(00:00) Trailer(00:57) Introduction(02:51) The Evolution of AI Workloads(06:22) Core Weave's Technological Innovations(13:58) Customer Engagement and Future Prospects(28:49) Comparing Cloud Approaches(33:50) Balancing Executive Roles and Hands-On Projects(46:44) Product Development and Customer Feedback

It's been a travel-heavy hiatus—Mark's been living in Spain and Shashank's been bouncing across Asia (including a month in China)—but they're back to unpack a packed week of AI news. They start with the headline hardware story: the Groq (GROQ) deal/partnership dynamics and why ultra-fast inference is becoming the next battleground, plus how this could reshape access to cutting-edge serving across the ecosystem. From there, they pivot to NVIDIA's CES announcements and what “Vera Rubin” implies for data center upgrades, cost-per-token curves, and the messy real-world math of rolling hardware generations. Shashank then brings the future to life with on-the-ground stories from China: a Huawei “everything store” that feels like an Apple Store meets a luxury dealership, folding devices that look straight out of sci-fi, and a parade of robots—from coffee bots to delivery robots that can ride elevators and deliver to your hotel room. They also touch on companion-style consumer robots and why “cute” might be a serious product strategy. Finally, Mark announces the launch of Novacut, a long-form AI video editor built to turn hours of travel footage into a coherent vlog draft—plus export workflows for Premiere, DaVinci Resolve, and Final Cut. They close by talking about the 2026 shift from single model calls to “agentic” systems, including a fun (and slightly alarming) lesson from LLM outcome bias using poker hand reviews. Topics include: Groq inference, NVIDIA + CES, Vera Rubin GPUs, GPU depreciation math, China robotics, Huawei ecosystem, hotel delivery bots, companion robots, Novacut launch, Cursor vs agent workflows, and why agents still struggle with sparse feedback loops. Link mentioned: Novacut — https://novacut.ai

NVIDIA is rumored to be bringing back the GeForce RTX 3060 again due to skyrocketing RAM and GPU prices, with AI being blamed. Man, you really don't want to build a gaming PC in 2026...Watch this podcast episode on YouTube and all major podcast hosts including Spotify.CLOWNFISH TV is an independent, opinionated news and commentary podcast that covers Entertainment and Tech from a consumer's point of view. We talk about Gaming, Comics, Anime, TV, Movies, Animation and more. Hosted by Kneon and Geeky Sparkles.D/REZZED News covers Pixels, Pop Culture, and the Paranormal! We're an independent, opinionated entertainment news blog covering Video Games, Tech, Comics, Movies, Anime, High Strangeness, and more. As part of Clownfish TV, we strive to be balanced, based, and apolitical. Get more news, views and reviews on Clownfish TV News - https://more.clownfishtv.com/On YouTube - https://www.youtube.com/c/ClownfishTVOn Spotify - https://open.spotify.com/show/4Tu83D1NcCmh7K1zHIedvgOn Apple Podcasts - https://podcasts.apple.com/us/podcast/clownfish-tv-audio-edition/id1726838629

Happy New Year! NVIDIA just spent $20 billion to hollow out an AI company for its brains, while Meta and Google scramble to scoop up fresh talent before AI gets "too weird to manage." Who's winning, who's left behind, and what do these backroom deals mean for the future of artificial intelligence? Andrej Karpathy admits programmers cannot keep pace with AI advances Economic uncertainty in AI despite massive stock market influence Google, Anthropic, and Microsoft drive AI productization for business and consumers OpenAI, Claude, and Gemini battle for consumer AI dominance Journalism struggles to keep up with AI realities and misinformation tools Concerns mount over AI energy, water, and environmental impact narratives Meta buys Manus, expands AI agent ambitions with Llama model OpenAI posts high-stress "Head of Preparedness" job worth $555K+ Training breakthroughs: DeepSeek's mHC and comparisons to Action Park U.S. lawmakers push broad, controversial internet censorship bills Age verification and bans spark state laws, VPN workaround explosion U.S. drone ban labeled protectionist as industry faces tech shortages FCC security initiatives falter; Cyber Trust Mark program scrapped Waymo robotaxis stall in blackouts, raising AV urban planning issues School cellphone bans expose kids' struggle with analog clocks MetroCard era ends in NYC as tap-to-pay takes over subway access RAM, VRAM, and GPU prices soar as AI and gaming squeeze supply CES preview: Samsung QD-OLED TV, Sony AFEELA car, gadget show hype Remembering Stewart Cheifet and Computer Chronicles' legacy Host: Leo Laporte Guests: Dan Patterson and Joey de Villa Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zscaler.com/security canary.tools/twit - use code: TWIT monarch.com with code TWIT Melissa.com/twit redis.io

Happy New Year! NVIDIA just spent $20 billion to hollow out an AI company for its brains, while Meta and Google scramble to scoop up fresh talent before AI gets "too weird to manage." Who's winning, who's left behind, and what do these backroom deals mean for the future of artificial intelligence? Andrej Karpathy admits programmers cannot keep pace with AI advances Economic uncertainty in AI despite massive stock market influence Google, Anthropic, and Microsoft drive AI productization for business and consumers OpenAI, Claude, and Gemini battle for consumer AI dominance Journalism struggles to keep up with AI realities and misinformation tools Concerns mount over AI energy, water, and environmental impact narratives Meta buys Manus, expands AI agent ambitions with Llama model OpenAI posts high-stress "Head of Preparedness" job worth $555K+ Training breakthroughs: DeepSeek's mHC and comparisons to Action Park U.S. lawmakers push broad, controversial internet censorship bills Age verification and bans spark state laws, VPN workaround explosion U.S. drone ban labeled protectionist as industry faces tech shortages FCC security initiatives falter; Cyber Trust Mark program scrapped Waymo robotaxis stall in blackouts, raising AV urban planning issues School cellphone bans expose kids' struggle with analog clocks MetroCard era ends in NYC as tap-to-pay takes over subway access RAM, VRAM, and GPU prices soar as AI and gaming squeeze supply CES preview: Samsung QD-OLED TV, Sony AFEELA car, gadget show hype Remembering Stewart Cheifet and Computer Chronicles' legacy Host: Leo Laporte Guests: Dan Patterson and Joey de Villa Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zscaler.com/security canary.tools/twit - use code: TWIT monarch.com with code TWIT Melissa.com/twit redis.io

Happy New Year! NVIDIA just spent $20 billion to hollow out an AI company for its brains, while Meta and Google scramble to scoop up fresh talent before AI gets "too weird to manage." Who's winning, who's left behind, and what do these backroom deals mean for the future of artificial intelligence? Andrej Karpathy admits programmers cannot keep pace with AI advances Economic uncertainty in AI despite massive stock market influence Google, Anthropic, and Microsoft drive AI productization for business and consumers OpenAI, Claude, and Gemini battle for consumer AI dominance Journalism struggles to keep up with AI realities and misinformation tools Concerns mount over AI energy, water, and environmental impact narratives Meta buys Manus, expands AI agent ambitions with Llama model OpenAI posts high-stress "Head of Preparedness" job worth $555K+ Training breakthroughs: DeepSeek's mHC and comparisons to Action Park U.S. lawmakers push broad, controversial internet censorship bills Age verification and bans spark state laws, VPN workaround explosion U.S. drone ban labeled protectionist as industry faces tech shortages FCC security initiatives falter; Cyber Trust Mark program scrapped Waymo robotaxis stall in blackouts, raising AV urban planning issues School cellphone bans expose kids' struggle with analog clocks MetroCard era ends in NYC as tap-to-pay takes over subway access RAM, VRAM, and GPU prices soar as AI and gaming squeeze supply CES preview: Samsung QD-OLED TV, Sony AFEELA car, gadget show hype Remembering Stewart Cheifet and Computer Chronicles' legacy Host: Leo Laporte Guests: Dan Patterson and Joey de Villa Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zscaler.com/security canary.tools/twit - use code: TWIT monarch.com with code TWIT Melissa.com/twit redis.io

Happy New Year! NVIDIA just spent $20 billion to hollow out an AI company for its brains, while Meta and Google scramble to scoop up fresh talent before AI gets "too weird to manage." Who's winning, who's left behind, and what do these backroom deals mean for the future of artificial intelligence? Andrej Karpathy admits programmers cannot keep pace with AI advances Economic uncertainty in AI despite massive stock market influence Google, Anthropic, and Microsoft drive AI productization for business and consumers OpenAI, Claude, and Gemini battle for consumer AI dominance Journalism struggles to keep up with AI realities and misinformation tools Concerns mount over AI energy, water, and environmental impact narratives Meta buys Manus, expands AI agent ambitions with Llama model OpenAI posts high-stress "Head of Preparedness" job worth $555K+ Training breakthroughs: DeepSeek's mHC and comparisons to Action Park U.S. lawmakers push broad, controversial internet censorship bills Age verification and bans spark state laws, VPN workaround explosion U.S. drone ban labeled protectionist as industry faces tech shortages FCC security initiatives falter; Cyber Trust Mark program scrapped Waymo robotaxis stall in blackouts, raising AV urban planning issues School cellphone bans expose kids' struggle with analog clocks MetroCard era ends in NYC as tap-to-pay takes over subway access RAM, VRAM, and GPU prices soar as AI and gaming squeeze supply CES preview: Samsung QD-OLED TV, Sony AFEELA car, gadget show hype Remembering Stewart Cheifet and Computer Chronicles' legacy Host: Leo Laporte Guests: Dan Patterson and Joey de Villa Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zscaler.com/security canary.tools/twit - use code: TWIT monarch.com with code TWIT Melissa.com/twit redis.io

Happy New Year! NVIDIA just spent $20 billion to hollow out an AI company for its brains, while Meta and Google scramble to scoop up fresh talent before AI gets "too weird to manage." Who's winning, who's left behind, and what do these backroom deals mean for the future of artificial intelligence? Andrej Karpathy admits programmers cannot keep pace with AI advances Economic uncertainty in AI despite massive stock market influence Google, Anthropic, and Microsoft drive AI productization for business and consumers OpenAI, Claude, and Gemini battle for consumer AI dominance Journalism struggles to keep up with AI realities and misinformation tools Concerns mount over AI energy, water, and environmental impact narratives Meta buys Manus, expands AI agent ambitions with Llama model OpenAI posts high-stress "Head of Preparedness" job worth $555K+ Training breakthroughs: DeepSeek's mHC and comparisons to Action Park U.S. lawmakers push broad, controversial internet censorship bills Age verification and bans spark state laws, VPN workaround explosion U.S. drone ban labeled protectionist as industry faces tech shortages FCC security initiatives falter; Cyber Trust Mark program scrapped Waymo robotaxis stall in blackouts, raising AV urban planning issues School cellphone bans expose kids' struggle with analog clocks MetroCard era ends in NYC as tap-to-pay takes over subway access RAM, VRAM, and GPU prices soar as AI and gaming squeeze supply CES preview: Samsung QD-OLED TV, Sony AFEELA car, gadget show hype Remembering Stewart Cheifet and Computer Chronicles' legacy Host: Leo Laporte Guests: Dan Patterson and Joey de Villa Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: zscaler.com/security canary.tools/twit - use code: TWIT monarch.com with code TWIT Melissa.com/twit redis.io

How can AI weather models improve the accuracy and scale of catastrophe modelling? Matthew Grant is joined by David Wood, Managing Director at JBA Risk Management, and Jochen Papenbrock, Head of Financial Technology (EMEA) at NVIDIA, to explore how accelerated computing is unlocking new ways to simulate and manage flood risk. JBA has long been a pioneer in flood modelling, while NVIDIA's GPU technology has helped drive the recent breakthroughs in AI and generative modelling. Together, they discuss how high-resolution simulations, new ensemble methods and open-source tools are pushing the limits of what's possible in climate and catastrophe analytics. Key Talking Points: The early bet – how JBA's adoption of GPU computing over a decade ago made national-scale flood mapping possible From gaming to GenAI – how NVIDIA's evolution from graphics to AI led to the development of physics-informed weather models Ensemble power – why running 1,000+ simulations helps capture more extremes than the historic record ever could Event sets reimagined – how AI models are enabling richer, more diverse flood scenarios for Europe and beyond Real-time relevance – the potential to use AI models to simulate how a flood might unfold, as it's happening Making AI usable – how Earth-2 Studio and open-source frameworks are opening up generative models to catastrophe modellers Proving value – how NVIDIA and JBA worked together to quantify the benefits of faster, more flexible modelling approaches Looking ahead – why cross-sector collaboration will be essential to turn acceleration into real-world impact If you like what you're hearing, please leave us a review on whichever platform you use or contact Matthew Grant on LinkedIn.  Sign up to the InsTech newsletter for a fresh view on the world every Wednesday morning.

Gary Shapiro has spent decades at the center of the global consumer technology industry, leading the Consumer Technology Association (CTA) and building CES into one of the most important stages for innovation, policy, and deal-making on the planet. In this first episode of 2026, Gary joins Charlie, Rony, and Ted to preview CES, unpack the explosion of AI across every category, and deliver unusually blunt takes on tariffs, China, manufacturing, and U.S. innovation policy. He explains how CES has evolved from a TV-and-gadgets show into a global platform where boards meet, standards are set, and policymakers, chip designers, robotics firms, and health-tech startups all collide.In the News: Before Gary joins, the hosts break down Nvidia's $20 billion “not-a-deal” with Singapore's Groq, the stake in Intel, and what that combo might signal about the edge of the GPU bubble and the shift toward inference compute, x86, and U.S. industrial policy. They also dig into Netflix's acquisition of Ready Player Me and what it suggests about a Netflix metaverse and location-based entertainment strategy, plus Starlink's rapid growth and an onslaught of “AI everything” products ahead of CES.Gary walks through new features at this year's show: CES Foundry at the Fontainebleau for AI and quantum, expanded tracks on manufacturing, wearables, women's health, and accessibility, plus an AI-powered show app already fielding thousands of questions (top query: where to pick up badges). He also talks candidly about his biggest concern—that fragmented state-level AI regulation (1,200+ state bills in 2025) will crush startups while big players shrug—and why he believes federal standards via NIST are the only realistic path. The discussion ranges from AI-driven healthcare and precision agriculture to robotics, demographics, labor culture, global supply chains, and what CES might look like in 2056.5 Key Takeaways from Gary:AI is now the spine of CES. CES 2026 centers on AI as infrastructure: CES Foundry at the Fontainebleau for AI + quantum, AI training tracks for strategy, implementation, agentic AI, and AI-driven marketing, and an AI-powered app helping attendees navigate the show.Fragmented state AI laws are an existential risk for startups. Over 1,200 state AI bills in 2025—including proposals to criminalize agentic AI counseling—could create a compliance maze only large incumbents can survive, which is why Gary argues for federal standards via NIST.Wearables are becoming systems, not gadgets. Oura rings, wrist devices, body sensors, and subdermal glucose monitors are starting to be designed as interoperable families of devices, with partnerships emerging to combine data into unified health services.Robotics is breaking out of the industrial niche. CES will showcase the largest robotics presence yet, moving beyond factory arms and drones to humanoids, logistics, social companions, and applied AI systems across sectors.Tariffs, alliances, and AI will reshape manufacturing. Gary is skeptical of “Fortress USA” strategies that try to onshore everything, pointing instead to allied reshoring (Latin America, Europe, Japan, South Korea) and the long-term role of AI-powered robotics in changing labor economics and global supply chains.This episode is brought to you by Zappar, creators of Mattercraft—the leading visual development environment for building immersive 3D web experiences for mobile headsets and desktop. Mattercraft combines the power of a game engine with the flexibility of the web, and now features an AI assistant that helps you design, code, and debug in real time, right in your browser. Whether you're a developer, designer, or just getting started, start building smarter at mattercraft.io.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

From undergraduate research seminars at Princeton to winning Best Paper award at NeurIPS 2025, Kevin Wang, Ishaan Javali, Michał Bortkiewicz, Tomasz Trzcinski, Benjamin Eysenbach defied conventional wisdom by scaling reinforcement learning networks to 1,000 layers deep—unlocking performance gains that the RL community thought impossible. We caught up with the team live at NeurIPS to dig into the story behind RL1000: why deep networks have worked in language and vision but failed in RL for over a decade (spoiler: it's not just about depth, it's about the objective), how they discovered that self-supervised RL (learning representations of states, actions, and future states via contrastive learning) scales where value-based methods collapse, the critical architectural tricks that made it work (residual connections, layer normalization, and a shift from regression to classification), why scaling depth is more parameter-efficient than scaling width (linear vs. quadratic growth), how Jax and GPU-accelerated environments let them collect hundreds of millions of transitions in hours (the data abundance that unlocked scaling in the first place), the "critical depth" phenomenon where performance doesn't just improve—it multiplies once you cross 15M+ transitions and add the right architectural components, why this isn't just "make networks bigger" but a fundamental shift in RL objectives (their code doesn't have a line saying "maximize rewards"—it's pure self-supervised representation learning), how deep teacher, shallow student distillation could unlock deployment at scale (train frontier capabilities with 1000 layers, distill down to efficient inference models), the robotics implications (goal-conditioned RL without human supervision or demonstrations, scaling architecture instead of scaling manual data collection), and their thesis that RL is finally ready to scale like language and vision—not by throwing compute at value functions, but by borrowing the self-supervised, representation-learning paradigms that made the rest of deep learning work. We discuss: The self-supervised RL objective: instead of learning value functions (noisy, biased, spurious), they learn representations where states along the same trajectory are pushed together, states along different trajectories are pushed apart—turning RL into a classification problem Why naive scaling failed: doubling depth degraded performance, doubling again with residual connections and layer norm suddenly skyrocketed performance in one environment—unlocking the "critical depth" phenomenon Scaling depth vs. width: depth grows parameters linearly, width grows quadratically—depth is more parameter-efficient and sample-efficient for the same performance The Jax + GPU-accelerated environments unlock: collecting thousands of trajectories in parallel meant data wasn't the bottleneck, and crossing 15M+ transitions was when deep networks really paid off The blurring of RL and self-supervised learning: their code doesn't maximize rewards directly, it's an actor-critic goal-conditioned RL algorithm, but the learning burden shifts to classification (cross-entropy loss, representation learning) instead of TD error regression Why scaling batch size unlocks at depth: traditional RL doesn't benefit from larger batches because networks are too small to exploit the signal, but once you scale depth, batch size becomes another effective scaling dimension — RL1000 Team (Princeton) 1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities: https://openreview.net/forum?id=s0JVsx3bx1 Chapters 00:00:00 Introduction: Best Paper Award and NeurIPS Poster Experience 00:01:11 Team Introductions and Princeton Research Origins 00:03:35 The Deep Learning Anomaly: Why RL Stayed Shallow 00:04:35 Self-Supervised RL: A Different Approach to Scaling 00:05:13 The Breakthrough Moment: Residual Connections and Critical Depth 00:07:15 Architectural Choices: Borrowing from ResNets and Avoiding Vanishing Gradients 00:07:50 Clarifying the Paper: Not Just Big Networks, But Different Objectives 00:08:46 Blurring the Lines: RL Meets Self-Supervised Learning 00:09:44 From TD Errors to Classification: Why This Objective Scales 00:11:06 Architecture Details: Building on Braw and SymbaFowl 00:12:05 Robotics Applications: Goal-Conditioned RL Without Human Supervision 00:13:15 Efficiency Trade-offs: Depth vs Width and Parameter Scaling 00:15:48 JAX and GPU-Accelerated Environments: The Data Infrastructure 00:18:05 World Models and Next State Classification 00:22:37 Unlocking Batch Size Scaling Through Network Capacity 00:24:10 Compute Requirements: State-of-the-Art on a Single GPU 00:21:02 Future Directions: Distillation, VLMs, and Hierarchical Planning 00:27:15 Closing Thoughts: Challenging Conventional Wisdom in RL Scaling

Kyle Okamoto is the Chief Technology Officer at Aethir: the leading decentralized enterprise-grade cloud computing network. With over 20 years of experience in cloud and edge computing, digital media, IoT and AI, Kyle's leadership has been pivotal in scaling growth businesses and driving technological innovation at Aethir.Before joining Aethir, Kyle served as the General Manager of Aeris Communications and Ericsson's enterprise businesses, overseeing Internet of Things, Security, and Connected Vehicle portfolio companies. He was also the Chief Executive Officer of Edge Gravity, a global edge cloud platform facilitating cloud gaming, AI, and media and entertainment applications. Kyle's extensive experience also includes his tenure as Chief Network Officer of Verizon Media and his role as a founding member of Verizon Digital Media Services, which grew to a multi-billion dollar business before its acquisition by Private Equity.In addition to his work with Aethir, Kyle is an early investor and advisor to Theta Labs, holds board positions in various technology companies and non-profit organizations, and is an active angel investor and advisor in the venture capital and private equity spaces. Kyle holds a Master of Business Administration from New York University and a Bachelor of Engineering degree from Stevens Institute of Technology.In this conversation, we discuss:- AI's growth is now gated by access to compute rather than model quality - Compute is becoming a financial asset class - AI demand continues to outpace supply - GPUs - Investors are starting to treat compute like infrastructure, not software - Financial structures are becoming essential to scaling AI infrastructure - Decentralized compute offers an alternative path during the global GPU shortage- Enterprises are moving toward multi-source compute strategies - Financing compute - The financing of compute is as important as the tech side AethirX: @AethirCloudWebsite: www.aethir.comLinkedIn: AethirKyle OkamotoLinkedIn: Kyle Okamoto---------------------------------------------------------------------------------This episode is brought to you by PrimeXBT.PrimeXBT offers a robust trading system for both beginners and professional traders that demand highly reliable market data and performance. Traders of all experience levels can easily design and customize layouts and widgets to best fit their trading style. PrimeXBT is always offering innovative products and professional trading conditions to all customers.  PrimeXBT is running an exclusive promotion for listeners of the podcast. After making your first deposit, 50% of that first deposit will be credited to your account as a bonus that can be used as additional collateral to open positions. Code: CRYPTONEWS50 This promotion is available for a month after activation. Click the link below: PrimeXBT x CRYPTONEWS50FollowApple PodcastsSpotifyAmazon MusicRSS FeedSee All

Tesla's Optimus robot faced a setback when a video of it falling went viral, impacting Tesla stock. The conversation also covered Apple's use of AI in health data analysis, leadership changes, and advancements in GPU chips. Additionally, the hosts discussed Apple and Google's warnings about a hacking scheme and speculated about Tim Cook's potential successor.Conversations on technology and tech adjacent subjects since July of 2020, with two and sometime three generations of tech nerds. New shows on (mostly) TUESDAYS!

From investing through the modern data stack era (DBT, Fivetran, and the analytics explosion) to now investing at the frontier of AI infrastructure and applications at Amplify Partners, Sarah Catanzaro has spent years at the intersection of data, compute, and intelligence—watching categories emerge, merge, and occasionally disappoint. We caught up with Sarah live at NeurIPS 2025 to dig into the state of AI startups heading into 2026: why $100M+ seed rounds with no near-term roadmap are now the norm (and why that terrifies her), what the DBT-Fivetran merger really signals about the modern data stack (spoiler: it's not dead, just ready for IPO), how frontier labs are using DBT and Fivetran to manage training data and agent analytics at scale, why data catalogs failed as standalone products but might succeed as metadata services for agents, the consumerization of AI and why personalization (memory, continual learning, K-factor) is the 2026 unlock for retention and growth, why she thinks RL environments are a fad and real-world logs beat synthetic clones every time, and her thesis for the most exciting AI startups: companies that marry hard research problems (RAG, rule-following, continual learning) with killer applications that were simply impossible before. We discuss: The DBT-Fivetran merger: not the death of the modern data stack, but a path to IPO scale (targeting $600M+ combined revenue) and a signal that both companies were already winning their categories How frontier labs use data infrastructure: DBT and Fivetran for training data curation, agent analytics, and managing increasingly complex interactions—plus the rise of transactional databases (RocksDB) and efficient data loading (Vortex) for GPU-bound workloads Why data catalogs failed: built for humans when they should have been built for machines, focused on discoverability when the real opportunity was governance, and ultimately subsumed as features inside Snowflake, DBT, and Fivetran The $100M+ seed phenomenon: raising massive rounds at billion-dollar valuations with no 6-month roadmap, seven-day decision windows, and founders optimizing for signal ("we're a unicorn") over partnership or dilution discipline Why world models are overhyped but underspecified: three competing definitions, unclear generalization across use cases (video games ≠ robotics ≠ autonomous driving), and a research problem masquerading as a product category The 2026 theme: consumerization of AI via personalization—memory management, continual learning, and solving retention/churn by making products learn skills, preferences, and adapt as the world changes (not just storing facts in cursor rules) Why RL environments are a fad: labs are paying 7–8 figures for synthetic clones when real-world logs, traces, and user activity (à la Cursor) are richer, cheaper, and more generalizable Sarah's investment thesis: research-driven applications that solve hard technical problems (RAG for Harvey, rule-following for Sierra, continual learning for the next killer app) and unlock experiences that were impossible before Infrastructure bets: memory, continual learning, stateful inference, and the systems challenges of loading/unloading personalized weights at scale Why K-factor and growth fundamentals matter again: AI felt magical in 2023–2024, but as the magic fades, retention and virality are back—and most AI founders have never heard of K-factor — Sarah Catanzaro X: https://x.com/sarahcat21 Amplify Partners: https://amplifypartners.com/ Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction: Sarah Catanzaro's Journey from Data to AI 00:01:02 The DBT-Fivetran Merger: Not the End of the Modern Data Stack 00:05:26 Data Catalogs and What Went Wrong 00:08:16 Data Infrastructure at AI Labs: Surprising Insights 00:10:13 The Crazy Funding Environment of 2024-2025 00:17:18 World Models: Hype, Confusion, and Market Potential 00:18:59 Memory Management and Continual Learning: The Next Frontier 00:23:27 Agent Environments: Just a Fad? 00:25:48 The Perfect AI Startup: Research Meets Application 00:28:02 Closing Thoughts and Where to Find Sarah

This is a special episode, highlighting a session from ELC Annual 2025! OpenAI evolved from a pure research lab into the fastest-growing product in history, scaling from 100 million to 700 million weekly users in record time. In this episode, we deconstruct the organizational design choices and cultural bets that enabled this unprecedented velocity. We explore what it means to hire "extreme generalists," how AI-native interns are redefining productivity, and the real-time trade-offs made during the world's largest product launches. Featuring Sulman Choudhry (Head of ChatGPT Engineering) and Samir Ahmed (Technical Lead), moderated by Lawrence Bruhmeller (Eng Management @ Sigma). ABOUT SULMAN CHOUDHRYSulman leads ChatGPT Engineering at OpenAI, driving the development and scaling of one of the world's most impactful AI products. He pushes the boundaries of innovation by turning cutting‑edge research into practical, accessible tools that transform how people interact with technology. Previously at Meta, Sulman founded and scaled Instagram Reels, IGTV, and Instagram Labs, and helped lead the early development of Instagram Stories.He also brought MetaAI to Instagram and Messenger, integrating generative AI into experiences used by billions. Earlier in his career, Sulman was on the founding team that built and launched UberEATS from the ground up, helping turn it into a global food delivery platform. With a track record of marrying technical vision, product strategy, and large‑scale execution, Sulman focuses on building products that meaningfully change how people live, work, and connect.ABOUT SAMIR AHMEDSamir is the Technical Lead for ChatGPT at OpenAI, where he currently leads the Personalization and Memory efforts to scale adaptive, useful, and human-centered product experiences to over 700 million users. He works broadly across the OpenAI stack—including mobile, web, services, systems, inference, and product research infrastructure.Previously, Samir spent nine years at Snap, working across Ads, AR, Content, and Growth. He led some of the company's most critical technical initiatives, including founding and scaling the machine learning platform that powered nearly all Ads, Content, and AR workloads, handling tens of billions of requests and trillions of inferences daily.ABOUT LAWRENCE BRUHMELLERLawrence Bruhmuller has over 20 years of experience in engineering management, much of it as an overall head of engineering. Previous roles include CTO/VPE roles at Great Expectations, Pave, Optimizely, and WeWork. He is currently leading the core query compiler and serving teams at Sigma Computing, the industry leading business analytics company.Lawrence is passionate about the intersection of engineering management and the growth stage of startups. He has written extensively on engineering leadership (https://lbruhmuller.medium.com/), including how to best evolve and mature engineering organizations before, during and after these growth phases. He enjoys advising and mentoring other engineering leaders in his spare time.Lawrence holds a Bachelors and Masters in Mathematics and Engineering from Harvey Mudd College. He lives in Oakland, California, with his wife and their three daughters. This episode is brought to you by Span!Span is the AI-native developer intelligence platform bringing clarity to engineering organizations with a holistic, human-centered approach to developer productivity.If you want a complete picture of your engineering impact and health, drive high performance, and make smarter business decisions…Go to Span.app to learn more! SHOW NOTES:From research lab to record-breaking product: Navigating the fastest growth in history (4:03)Unpredictable scaling: Handling growth spurts of one million users every hour (5:20)Cross-stack collaboration: How Android, systems, and GPU engineers solve crises together (7:06)The magic of trade-offs: Aligning the team on outcomes like service uptime vs. broad availability (7:57)Why throwing models "over the wall" failed and how OpenAI structures virtual teams (11:17)Lessons from OpenAI's first intern class: Why AI-native new grads are crushing expectations (13:41)Non-hierarchical culture: Using the "Member of Technical Staff" title to blur the lines of expertise (15:37)AI-native engineering: When massive code generation starts breaking traditional CI/CD systems (16:21)Asynchronous workflows: Using coding agents to reduce two-hour investigations to 15 minutes (17:35)The mindset shift: How rapid model improvements changed how leaders audit and trust code (19:00)Predicting success: "Vibes-based" decision making and iterative low-key research previews (20:43)Hiring for high variance: Why unconventional backgrounds lead to high-potential engineering hires (22:09) LINKS AND RESOURCESLink to the video for this sessionLink to all ELC Annual 2025 sessions This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Catching yourself rereading last year's VC emails while you're back in Silicon Valley is a pretty good way to realize how wild the last 12 months have been. Colin, Chuck, Canisius, and Todd break down how Collide AI is turning fast POCs into real production workflows, why change management is the actual moat, and how a stacked forward deployed team plus community driven distribution is setting up 2026 to be the year everything scales.Click here to watch a video of this episode.Join the conversation shaping the future of energy.Collide is the community where oil & gas professionals connect, share insights, and solve real-world problems together. No noise. No fluff. Just the discussions that move our industry forward.Apply today at collide.ioClick here to view the episode transcript. 00:00 Product market fit jokes and kickoff00:28 VC email flashback and velocity01:29 Forward deployed model and AI first mindset02:18 Sam Texas and AI coding shift04:04 What AI first actually means06:18 Not just podcast bros anymore07:00 AI breaks silos across the business08:21 Doglegs example and incentives09:57 Change management is the advantage10:18 Client story and regulatory filings win12:42 Selling outcomes not hype13:36 Building the FTE team and faster delivery16:24 AI strategy as workflow ROI first18:26 Grok as a thought partner and GPU cluster20:15 Shale revolution mindset parallel22:29 Recruiting, software DNA, and stacked team26:16 Content and community as a recruiting engine29:11 Distribution flywheel in the real world30:22 Team distribution vs product debate32:32 2026 is the scaling year34:02 Community platform finally clicking36:09 Building the community platform the hard way39:20 Scaling clients, POCs, and production41:09 Why mom and pops matter41:55 Energy demand tailwinds and macro impact44:44 One word answer for next year: scale45:20 POC to production cycle time focus47:12 Scaling tech, sales, and financing49:45 Moving at AI speed story50:14 Raising capital and building serious software52:56 Collide as the operator layer vision54:02 Gratitude and community over everythinghttps://twitter.com/collide_iohttps://www.tiktok.com/@collide.iohttps://www.facebook.com/collide.iohttps://www.instagram.com/collide.iohttps://www.youtube.com/@collide_iohttps://bsky.app/profile/digitalwildcatters.bsky.socialhttps://www.linkedin.com/company/collide-digital-wildcatters

In this episode, Ben Bajarin, Jay Goldberg, and Austin Lyons delve into the evolving landscape of networking, particularly in the context of AI and GPU technologies. They discuss the transition from traditional networking methods to more complex AI-driven networking, the significance of scaling strategies, and the critical role of SerDes in modern data centers. The conversation also touches on the ongoing debate between copper and optical networking solutions, highlighting the challenges and innovations in the field.

Links James on LinkedIn (https://www.linkedin.com/in/jahuang/) Mike on LinkedIn (https://www.linkedin.com/in/dominucco/) Mike's Blog (https://dominickm.com) Show on Discord (https://discord.com/invite/k8e7gKUpEp) Alice Promo (https://go.alice.dev/data-migration-offer-hands-on) AI on Red Hat Enterprise Linux (RHEL) Trust and Stability: RHEL provides the mission-critical foundation needed for workloads where security and reliability cannot be compromised. Predictive vs. Generative: Acknowledging the hype of GenAI while maintaining support for traditional machine learning algorithms. Determinism: The challenge of bringing consistency and security to emerging AI technologies in production environments. Rama-Llama & Containerization Developer Simplicity: Rama-Llama helps developers run local LLMs easily without being "locked in" to specific engines; it supports Podman, Docker, and various inference engines like Llama.cpp and Whisper.cpp. Production Path: The tool is designed to "fade away" after helping package the model and stack into a container that can be deployed directly to Kubernetes. Behind the Firewall: Addressing the needs of industries (like aircraft maintenance) that require AI to stay strictly on-premises. Enterprise AI Infrastructure Red Hat AI: A commercial product offering tools for model customization, including pre-training, fine-tuning, and RAG (Retrieval-Augmented Generation). Inference Engines: James highlights the difference between Llama.cpp (for smaller/edge hardware) and vLLM, which has become the enterprise standard for multi-GPU data center inferencing.

Episode 93: A rumor and news episode to round out 2025. We chat a bit more about 9850X3D expectations, the current and future state of Intel CPUs following some 225F testing, Nvidia cutting GPU supply, potential new GPUs and Steve kills some hardware.CHAPTERS00:00 - Intro02:33 - More Thoughts on the 9850X3D06:13 - Where is Intel at With Their CPUs?24:42 - Nvidia Cutting GPU Supply?37:38 - AMD Launches Radeon RX 9060 XT LP43:22 - More Intel Arc B770 Rumors49:12 - Updates From Our Boring LivesSUBSCRIBE TO THE PODCASTAudio: https://shows.acast.com/the-hardware-unboxed-podcastVideo: https://www.youtube.com/channel/UCqT8Vb3jweH6_tj2SarErfwSUPPORT US DIRECTLYPatreon: https://www.patreon.com/hardwareunboxedLINKSYouTube: https://www.youtube.com/@Hardwareunboxed/Twitter: https://twitter.com/HardwareUnboxedBluesky: https://bsky.app/profile/hardwareunboxed.bsky.social Hosted on Acast. See acast.com/privacy for more information.

Timestamps: 0:00 thank you for coming to this meeting 0:13 Firefox, AI, Larian, and impulsive backlash 3:22 Nvidia's rumored GPU production cuts 4:28 War Thunder! 5:11 QUICK BITS INTRO 5:20 Ford batteries for data centers 6:05 700Credit data breach 6:43 AppX high CPU usage on W11 7:29 Apple helping businesses with manufacturing 8:16 Twitter (X) sues Operation Bluebird 8:55 YouTube Playables AI games, Google '6 7' meme NEWS SOURCES: https://lmg.gg/s83nI Learn more about your ad choices. Visit megaphone.fm/adchoices

This week in bitcoin mining news, ERCOT sees a 266 GW of interconnection requests in 2026, IREN closed a $2.3 billion convertible note offering, and GPUs are leaving ASICs in the dust. Subscribe to the Blockspace newsletter for market-making news as it hits the wire! Welcome back to The Mining Pod! Today, Ethan Vera, COO of Luxor, joins us as we dive into MicroBT's Whatsminer M70 launching into a challenging ASIC market, IREN's $2.3 billion convertible note offering, the precarious state of hashprice, Luxor's new GPU hardware sales business, the staggering 270% leap in ERCOT interconnection requests, and the controversial Cat bitcoin fork proposal aimed at filtering ordinals / inscriptions. Subscribe to the newsletter! https://newsletter.blockspacemedia.com **Notes:** - Hash price is below $40 per second - Three negative difficulty adjustments - Ercot requests leaped 270% in 2025 - 73% of requests from data centers - IREN raised $2.3B in convertible notes - M70 efficiency: 12.5 J/TH 00:00 Start 02:35 Difficulty Report by Luxor 07:26 IREN note 10:44 M70 launch 20:02 Luxor launches GPU trading 27:12 ERCOT LL requests up 270% in 2025 34:10 Cry Corner: another filter fork proposal

Jensen Huang is the founder, president, and CEO of NVIDIA, the company whose 1999 invention of the GPU helped transform gaming, computer graphics, and accelerated computing. Under his leadership, NVIDIA has grown into a full-stack computing infrastructure company reshaping AI and data-center technology across industries.www.nvidia.com www.youtube.com/nvidia Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Visible. Live in the know. Join today at https://www.visible.com/rogan Don't miss out on all the action - Download the DraftKings app today! Sign-up at https://dkng.co/rogan or with my promo code ROGAN GAMBLING PROBLEM? CALL 1-800-GAMBLER, (800) 327-5050 or visit gamblinghelplinema.org (MA). Call 877-8-HOPENY/text HOPENY (467369) (NY). Please Gamble Responsibly. 888-789-7777/visit ccpg.org (CT), or visit www.mdgamblinghelp.org (MD). 21+ and present in most states. (18+ DC/KY/NH/WY). Void in ONT/OR/NH. Eligibility restrictions apply. On behalf of Boot Hill Casino & Resort (KS). Pass-thru of per wager tax may apply in IL. 1 per new customer. Must register new account to receive reward Token. Must select Token BEFORE placing min. $5 bet to receive $200 in Bonus Bets if your bet wins. Min. -500 odds req. Token and Bonus Bets are single-use and non-withdrawable. Token expires 1/11/26. Bonus Bets expire in 7 days (168 hours). Stake removed from payout. Terms: sportsbook.draftkings.com/promos. Ends 1/4/26 at 11:59 PM ET. Sponsored by DK. Learn more about your ad choices. Visit podcastchoices.com/adchoices