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In this episode, we declare the end of the experimental NISQ era and the arrival of "Utility Scale" quantum computing, where 100+ qubit processors are finally delivering tangible value. We dive deep into the necessity of "hardware-aware" programming using frameworks like Cirq, explaining why developers can no longer treat the chip as a black box but must instead manage gate timing, "moments," and error mitigation strategies like Zero Noise Extrapolation. We also explore the critical role of GPU-accelerated simulations in bridging the gap to fault tolerance and discuss the acute talent shortage in the market, making the case that mastering these noisy, intermediate tools today is the only way to be ready for the logical qubit revolution of 2026.
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.
Dale Smothers believes the markets are correcting to the upside after "overreactions" against the A.I. CapEx story and FOMC uncertainties. That said, he believes markets won't see as stellar of gains in 2026 compared to 2025. However, Dale pounds the table on the A.I. trade as long as use cases develop. He sees Amazon (AMZN) and Apple (AAPL) rallying strong in the coming year after serving as Mag 7 laggards in 2025. He adds that Nvidia (NVDA) will continue to dominate due to its GPU business. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about
As the data center industry enters the AI era in earnest, incremental upgrades are no longer enough. That was the central message of the Data Center Frontier Trends Summit 2025 session “AI Is the New Normal: Building the AI Factory for Power, Profit, and Scale,” where operators and infrastructure leaders made the case that AI is no longer a specialty workload; it is redefining the data center itself. Panelists described the AI factory as a new infrastructure archetype: purpose-built, power-intensive, liquid-cooled, and designed for constant change. Rack densities that once hovered in the low teens have now surged past 50 kilowatts and, in some cases, toward megawatt-scale configurations. Facilities designed for yesterday's assumptions simply cannot keep up. Ken Patchett of Lambda framed AI factories as inherently multi-density environments, capable of supporting everything from traditional enterprise racks to extreme GPU deployments within the same campus. These facilities are not replacements for conventional data centers, he noted, but essential additions; and they must be designed for rapid iteration as chip architectures evolve every few months. Wes Cummins of Applied Digital extended the conversation to campus scale and geography. AI demand is pushing developers toward tertiary markets where power is abundant but historically underutilized. Training and inference workloads now require hundreds of megawatts at single sites, delivered in timelines that have shrunk from years to little more than a year. Cost efficiency, ultra-low PUE, and flexible shells are becoming decisive competitive advantages. Liquid cooling emerged as a foundational requirement rather than an optimization. Patrick Pedroso of Equus Compute Solutions compared the shift to the automotive industry's move away from air-cooled engines. From rear-door heat exchangers to direct-to-chip and immersion systems, cooling strategies must now accommodate fluctuating AI workloads while enabling energy recovery—even at the edge. For Kenneth Moreano of Scott Data Center, the AI factory is as much a service model as a physical asset. By abstracting infrastructure complexity and controlling the full stack in-house, his company enables enterprise customers to move from AI experimentation to production at scale, without managing the underlying technical detail. Across the discussion, panelists agreed that the industry's traditional design and financing playbook is obsolete. AI infrastructure cannot be treated as a 25-year depreciable asset when hardware cycles move in months. Instead, data centers must be built as adaptable, elemental systems: capable of evolving as power, cooling, and compute requirements continue to shift. The session concluded with one obvious takeaway: AI is not a future state to prepare for. It is already shaping how data centers are built, where they are located, and how they generate value. The AI factory is no longer theoretical—and the industry is racing to build it fast enough.
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
as with all demo-heavy and especially vision AI podcasts, we encourage watching along on our YouTube (and tossing us an upvote/subscribe if you like!) From SAM 1's 11-million-image data engine to SAM 2's memory-based video tracking, MSL's Segment Anything project has redefined what's possible in computer vision. Now SAM 3 takes the next leap: concept segmentation—prompting with natural language like "yellow school bus" or "tablecloth" to detect, segment, and track every instance across images and video, in real time, with human-level exhaustivity. And with the latest SAM Audio (https://x.com/aiatmeta/status/2000980784425931067?s=46), SAM can now even segment audio output! We sat down with Nikhila Ravi (SAM lead at Meta) and Pengchuan Zhang (SAM 3 researcher) alongside Joseph Nelson (CEO, Roboflow) to unpack how SAM 3 unifies interactive segmentation, open-vocabulary detection, video tracking, and more into a single model that runs in 30ms on images and scales to real-time video on multi-GPU setups. We dig into the data engine that automated exhaustive annotation from two minutes per image down to 25 seconds using AI verifiers fine-tuned on Llama, the new SACO (Segment Anything with Concepts) benchmark with 200,000+ unique concepts vs. the previous 1.2k, how SAM 3 separates recognition from localization with a presence token, why decoupling the detector and tracker was critical to preserve object identity in video, how SAM 3 Agents unlock complex visual reasoning by pairing SAM 3 with multimodal LLMs like Gemini, and the real-world impact: 106 million smart polygons created on Roboflow saving humanity an estimated 130+ years of labeling time across fields from cancer research to underwater trash cleanup to autonomous vehicle perception. We discuss: What SAM 3 is: a unified model for concept-prompted segmentation, detection, and tracking in images and video using atomic visual concepts like "purple umbrella" or "watering can" How concept prompts work: short text phrases that find all instances of a category without manual clicks, plus visual exemplars (boxes, clicks) to refine and adapt on the fly Real-time performance: 30ms per image (100 detected objects on H200), 10 objects on 2×H200 video, 28 on 4×, 64 on 8×, with parallel inference and "fast mode" tracking The SACO benchmark: 200,000+ unique concepts vs. 1.2k in prior benchmarks, designed to capture the diversity of natural language and reach human-level exhaustivity The data engine: from 2 minutes per image (all-human) to 45 seconds (model-in-loop proposals) to 25 seconds (AI verifiers for mask quality and exhaustivity checks), fine-tuned on Llama 3.2 Why exhaustivity is central: every instance must be found, verified by AI annotators, and manually corrected only when the model misses—automating the hardest part of segmentation at scale Architecture innovations: presence token to separate recognition ("is it in the image?") from localization ("where is it?"), decoupled detector and tracker to preserve identity-agnostic detection vs. identity-preserving tracking Building on Meta's ecosystem: Perception Encoder, DINO v2 detector, Llama for data annotation, and SAM 2's memory-based tracking backbone SAM 3 Agents: using SAM 3 as a visual tool for multimodal LLMs (Gemini, Llama) to solve complex visual reasoning tasks like "find the bigger character" or "what distinguishes male from female in this image" Fine-tuning with as few as 10 examples: domain adaptation for specialized use cases (Waymo vehicles, medical imaging, OCR-heavy scenes) and the outsized impact of negative examples Real-world impact at Roboflow: 106M smart polygons created, saving 130+ years of labeling time across cancer research, underwater trash cleanup, autonomous drones, industrial automation, and more — MSL FAIR team Nikhila: https://www.linkedin.com/in/nikhilaravi/ Pengchuan: https://pzzhang.github.io/pzzhang/ Joseph Nelson X: https://x.com/josephofiowa LinkedIn: https://www.linkedin.com/in/josephofiowa/ [FLIGHTCAST_CHATPERS]
Welcome to Active Reload! This week, James and Grant open the show giving their good, bad, and ugly of all the Game Awards reveal trailers!Next, Marathon got a re-reveal from Bungie with a 23-minute inside look into the development of the upcoming extraction shooter. The guys discuss if the new look, price point, and release date is enough to attract players.Finally, Nvidia is reportedly planning to cut production by 30-40% of their RTX 50 series GPU's in the first half of 2026. What should we expect from console and PC prices with the possible increase in prices. Never a better time for pre-builts?Remember to rate, follow, like, and subscribe!
GPUs dominate today's AI landscape, but Google argues they are not necessary for every workload. As AI adoption has grown, customers have increasingly demanded compute options that deliver high performance with lower cost and power consumption. Drawing on its long history of custom silicon, Google introduced Axion CPUs in 2024 to meet needs for massive scale, flexibility, and general-purpose computing alongside AI workloads. The Axion-based C4A instance is generally available, while the newer N4A virtual machines promise up to 2x price performance.In this episode, Andrei Gueletii, a technical solutions consultant for Google Cloud joined Gari Singh, a product manager for Google Kubernetes Engine (GKE), and Pranay Bakre, a principal solutions engineer at Arm for this episode, recorded at KubeCon + CloudNativeCon North America, in Atlanta. Built on Arm Neoverse V2 cores, Axion processors emphasize energy efficiency and customization, including flexible machine shapes that let users tailor memory and CPU resources. These features are particularly valuable for platform engineering teams, which must optimize centralized infrastructure for cost, FinOps goals, and price performance as they scale.Importantly, many AI tasks—such as inference for smaller models or batch-oriented jobs—do not require GPUs. CPUs can be more efficient when GPU memory is underutilized or latency demands are low. By decoupling workloads and choosing the right compute for each task, organizations can significantly reduce AI compute costs.Learn more from The New Stack about the Axion-based C4A: Beyond Speed: Why Your Next App Must Be Multi-ArchitectureArm: See a Demo About Migrating a x86-Based App to ARM64Join our community of newsletter subscribers to stay on top of the news and at the top of your game. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. Why is AI so powerful in the cloud but still so limited inside everyday devices, and what would it take to run intelligent systems locally without draining battery or sacrificing privacy? In this episode of Eye on AI, host Craig Smith speaks with Steve Brightfield, Chief Marketing Officer at BrainChip, about neuromorphic computing and why brain inspired architectures may be the key to the future of edge AI. We explore how neuromorphic systems differ from traditional GPU based AI, why event driven and spiking neural networks are dramatically more power efficient, and how on device inference enables faster response times, lower costs, and stronger data privacy. Steve explains why brute force computation works in data centers but breaks down at the edge, and how edge AI is reshaping wearables, sensors, robotics, hearing aids, and autonomous systems. You will also hear real world examples of neuromorphic AI in action, from smart glasses and medical monitoring to radar, defense, and space applications. The conversation covers how developers can transition from conventional models to neuromorphic architectures, what role heterogeneous computing plays alongside CPUs and GPUs, and why the next wave of AI adoption will happen quietly inside the devices we use every day. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI
In this episode of the Data Center Frontier Show, DCF Editor in Chief Matt Vincent speaks with Uptime Institute research analyst Max Smolaks about the infrastructure forces reshaping AI data centers from power and racks to cooling, economics, and the question of whether the boom is sustainable. Smolaks unpacks a surprising on-ramp to today's AI buildout: former cryptocurrency mining operators that “discovered” underutilized pockets of power in nontraditional locations—and are now pivoting into AI campuses as GPU demand strains conventional markets. The conversation then turns to what OCP 2025 revealed about rack-scale AI: heavier, taller, more specialized racks; disaggregated “compute/power/network” rack groupings; and a white space that increasingly looks purpose-built for extreme density. From there, Vincent and Smolaks explore why liquid cooling is both inevitable and still resisted by many operators—along with the software, digital twins, CFD modeling, and new commissioning approaches emerging to manage the added complexity. On the power side, they discuss the industry's growing alignment around 800V DC distribution and what it signals about Nvidia's outsized influence on next-gen data center design. Finally, the conversation widens into load volatility and the economics of AI infrastructure: why “spiky” AI power profiles are driving changes in UPS systems and rack-level smoothing, and why long-term growth may hinge less on demand (which remains strong) than on whether AI profits broaden beyond a few major buyers—especially as GPU hardware depreciates far faster than the long-lived fiber built during past tech booms. A sharp, grounded look at the AI factory era—and the engineering and business realities behind the headlines.
Des géants de la tech envisagent d'installer des data centers dans l'espace pour répondre aux besoins explosifs de l'IA, en misant sur l'énergie solaire et des infrastructures orbitales inédites mondiales.Interview : Julien Villeret, directeur de l'innovation d'EDFEn partenariat avec EDFPourquoi l'idée d'installer des data centers dans l'espace séduit-elle les géants de la tech ?Un data center, ce n'est pas seulement de l'informatique et des serveurs : c'est avant tout une question d'énergie, et de beaucoup d'énergie. Même si les puces et les modèles d'IA deviennent plus sobres, les usages explosent, notamment avec l'IA générative et l'inférence. Résultat : les besoins en calcul augmentent de façon exponentielle, et donc la consommation électrique aussi. La vraie question, aujourd'hui, c'est comment fournir une énergie massive, fiable et au coût le plus bas possible à ces infrastructures. C'est là que l'espace commence à faire rêver les grands acteurs du numérique comme Google, Amazon ou Tesla.En quoi l'espace apporterait-il un avantage décisif par rapport à la Terre ?Sur Terre, raccorder un data center au réseau électrique prend des années. Il faut des autorisations, creuser des tranchées, poser des câbles à très haute tension : c'est lourd, long et peu compatible avec le rythme du numérique. Dans l'espace, l'idée est de se rapprocher du Soleil. L'énergie solaire y est quasi permanente et beaucoup plus intense qu'au sol : en orbite géostationnaire, on capte jusqu'à 20 à 50 fois plus d'énergie. Il n'y a quasiment pas de cycle jour-nuit, ce qui permet une production continue. Sur le papier, c'est une source d'énergie abondante, puissante et presque illimitée.Comment communiquer avec des data centers situés en orbite ?Les technologies existent déjà. On fait exactement comme avec des constellations de satellites type Starlink : des communications à très haut débit entre l'espace et la Terre. Certes, la latence est un peu plus élevée qu'avec des infrastructures terrestres, mais pour des services d'IA, quelques dizaines de millisecondes ne posent aucun problème. Ce n'est pas idéal pour le gaming ultra-réactif, mais pour le traitement de données ou l'IA, c'est tout à fait acceptable et déjà opérationnel.Est-ce réellement faisable aujourd'hui, ou est-ce encore de la science-fiction ?Techniquement, c'est crédible. Économiquement, c'est encore un énorme pari. Des acteurs comme la startup StarCloud, soutenue par NVIDIA, ont déjà lancé un premier satellite avec des GPU embarqués, mis en orbite par SpaceX, capable d'exécuter des modèles d'IA comme Gemma de Google. C'est encore très symbolique, mais ça fonctionne réellement.Les défis restent immenses : rayonnements cosmiques, températures extrêmes, usure accélérée des composants et surtout le refroidissement, très complexe dans le vide spatial. Sans parler du coût des lancements, encore élevé malgré les progrès. Si les promesses de lanceurs comme Starship ou New Glenn se concrétisent, avec des coûts divisés par dix, l'équation pourrait changer. Pour l'instant, on est clairement sur un moonshot, comme le projet Suncatcher développé par Google au sein de sa division X, ambitieux et audacieux… mais encore loin d'un déploiement massif.-----------♥️ Soutien : https://mondenumerique.info/don
On this episode of the Engineering Influence Podcast, host Diana O'Lare sits down with Peter Nabhan to explore how artificial intelligence—particularly GPU-driven workloads—is reshaping the future of data center development. As AI adoption accelerates, demand for power is surging, fueling the rise of massive, campus-scale data center projects across the U.S. The conversation dives into the evolving strategies of hyperscalers and co-location providers, the growing strain on the electric grid, and the increasing role of on-site power generation. Diana and Peter also unpack the critical engineering challenges around cooling, water usage, and sustainability, while spotlighting the top U.S. markets seeing the most rapid growth. Finally, they tackle the big question facing the industry: Are we heading toward an oversupply of data centers—or is this simply the next major technology cycle transforming the built environment? Read the Market Intelligence Data Brief: https://www.acec.org/resource/special-edition-data-centers-market-intelligence-brief-fall-2025/
Linux released the 6.19-rc1 kernel early from Japan, introducing major driver updates for GPU, networking, media, and sound subsystems, expanding automatic compiler cleanup infrastructure in the Virtual File System layer, advancing Rust integration with new drivers and subsystems, and preparing for AMD Zen 6 and Intel Nova Lake and Diamond Rapids platforms. The update also includes expanded file-system capabilities, tooling and documentation updates, and improvements to memory management and scheduling.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.
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
Episode 92: Edward Crisler from Radeon-exclusive AIB Sapphire joins the podcast to chat about the current GPU market. How will rising DRAM prices affect gaming GPUs? Can the GPU makers and AIBs absorb some of the increased cost? Also we talk about RDNA 4 and how successful it's been compared to previous generations, AMD's true market share, and of course, the Sapphire Puke box artCHAPTERS00:00 - Intro01:03 - RDNA 4 Launch at Sapphire05:11 - RDNA 4 vs Older Generations Success11:32 - The DRAM Crisis20:25 - AIBs Want More Control24:48 - Thoughts on 12VHPWR26:32 - How Are SKU Decisions Made?32:35 - Sapphire Puke35:27 - DRAM Pricing: What Can AMD and AIBs Do?44:50 - AI-Focused GPU Makers Owe Everything to Gamers50:56 - AMD's True Market Share59:05 - The Key to RDNA 4's Success1:03:13 - Outro with Ed's Favorite Sapphire GenerationSUBSCRIBE 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.
Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Intro to Bayes Course (first 2 lessons free)Advanced Regression Course (first 2 lessons free)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:DADVI is a new approach to variational inference that aims to improve speed and accuracy.DADVI allows for faster Bayesian inference without sacrificing model flexibility.Linear response can help recover covariance estimates from mean estimates.DADVI performs well in mixed models and hierarchical structures.Normalizing flows present an interesting avenue for enhancing variational inference.DADVI can handle large datasets effectively, improving predictive performance.Future enhancements for DADVI may include GPU support and linear response integration.Chapters:13:17 Understanding DADVI: A New Approach21:54 Mean Field Variational Inference Explained26:38 Linear Response and Covariance Estimation31:21 Deterministic vs Stochastic Optimization in DADVI35:00 Understanding DADVI and Its Optimization Landscape37:59 Theoretical Insights and Practical Applications of DADVI42:12 Comparative Performance of DADVI in Real Applications45:03 Challenges and Effectiveness of DADVI in Various Models48:51 Exploring Future Directions for Variational Inference53:04 Final Thoughts and Advice for PractitionersThank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Giuliano Cruz, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Aubrey Clayton, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Andreas Kröpelin, Raphaël...
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
AI demand for GPUs is exploding – and most of that capacity is locked inside underused data centers.In this episode, I talk with Mark from Aethir, a decentralized GPU cloud that aggregates idle, enterprise-grade GPUs into a global network. We discuss how Aethir feels like AWS on the front end but works like “Airbnb for data centers” behind the scenes, why compute demand outpaces supply, and how they keep latency low across 90+ countries.Mark also explains Aethir's token and revenue model, their work with EigenLayer, and why he believes solo founders now have superpowers in an AI-native world.Nothing in this episode is financial or investment advice.Key timestamps[00:00:00] Intro: Sam introduces Mark and Aethir's decentralized GPU cloud.[00:01:00] Mark's journey: From oil and gas infra and biotech to building GPU infrastructure for AI.[00:04:00] What Aethir is: AWS-style GPU cloud on the front end, “Airbnb for data centers” on the back end.[00:06:00] Enterprise-only GPUs: Why they only use data-center-grade hardware and no consumer devices.[00:07:00] Exploding demand: GPU demand 6–8x supply, with inference-heavy apps driving the next wave.[00:14:00] Global coverage: 90+ countries and routing users to nearby nodes for low latency.[00:31:00] Business model: 20% protocol fee, 80% to GPU hosts, plus token rewards and staking for large clusters.[00:39:00] Solo founder era: Why one-person AI-native companies will be extremely powerful.[00:41:00] Mark's message: Focus on projects with strong fundamentals and keep building through cycles.Connecthttp://aethir.com/https://www.linkedin.com/company/aethir-limited/https://x.com/AethirCloudhttps://www.linkedin.com/in/markrydon/https://x.com/MRRydonDisclaimerNothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Get featuredBe a guest on the podcast or contact us – https://www.web3pod.xyz/
NEW THEME SONG VERSION - Thanks ClaytonThis episode has some of the best information I've put out there and how I compare stocks - but I used several AI agents to figure out strategies too! $TSLA vs. $RIVN and what do you think of $BAC? THESE SALES END SOON: TRENDSPIDER HOLIDAY SALE - Get 52 trainings for the next year at 68% off. Become a Trendspider master! SEEKING ALPHA BUNDLE - ALPHA PICKS AND PREMIUM Save over $200Seeking Alpha Premium - FREE 7 day trial Alpha Picks - Save $100 Seeking Alpha Pro - for the Pros EPISODE SUMMARY
Satish Bhambri is a Sr Data Scientist at Walmart Labs, working on large-scale recommendation systems and conversational AI, including RAG-powered GroceryBot agents, vector-search personalization, and transformer-based ad relevance models.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractThe MLOps Community Podcast features Satish Bhambri, Senior Data Scientist with the Personalization and Ranking team at Walmart Labs and one of the emerging leaders in applied AI, in its newest episode. Satish has quietly built one of the most diverse and impactful AI portfolios in his field, spanning quantum computing, deep learning, astrophysics, computer vision, NLP, fraud detection, and enterprise-scale recommendation systems. Bhambri's nearly a decade of research across deep learning, astrophysics, quantum computing, NLP, and computer vision culminated in over 10 peer-reviewed publications released in 2025 through IEEE and Springer, and his early papers are indexed by NASA ADS and Harvard SAO, marking the start of his long-term research arc. He also holds a patent for an AI-powered smart grid optimization framework that integrates deep learning, real-time IoT sensing, and adaptive control algorithms to improve grid stability and efficiency, a demonstration of his original, high-impact contributions to intelligent infrastructure. Bhambri leads personalization and ranking initiatives at Walmart Labs, where his AI systems serve more than (5% of the world's population) 531 million users every month, roughly based on traffic data. His work with Transformers, Vision-Language Models, RAG and agentic-RAG systems, and GPU-accelerated pipelines has driven significant improvements in scale and performance, including increases in ad engagement, faster compute by and improved recommendation diversity.Satish is a Distinguished Fellow & Assessor at the Soft Computing Research Society (SCRS), a reviewer for IEEE and Springer, and has served as a judge and program evaluator for several elite platforms. He was invited to the NeurIPS Program Judge Committee, the most prestigious AI conference in the world, and to evaluate innovations for DeepInvent AI, where he reviews high-impact research and commercialization efforts. He has also judged Y Combinator Startup Hackathons, evaluating pitches for an accelerator that produced companies like Airbnb, Stripe, Coinbase, Instacart, and Reddit.Before Walmart, Satish built supply-chain intelligence systems at BlueYonder that reduced ETA errors and saved retailers millions while also bringing containers to the production pipeline. Earlier, at ASU's School of Earth & Space Exploration, he collaborated with astrophysicists on galaxy emission simulations, radio burst detection, and dark matter modeling, including work alongside Dr. Lawrence Krauss, Dr. Karen Olsen, and Dr. Adam Beardsley.On the podcast, Bhambri discusses the evolution of deep learning architectures from RNNs and CNNs to transformers and agentic RAG systems, the design of production-grade AI architectures with examples, and his long-term vision for intelligent systems that bridge research and real-world impact. and the engineering principles behind building production-grade AI at a global scale.// Related LinksPapers: https://scholar.google.com/citations?user=2cpV5GUAAAAJ&hl=enPatent: https://search.ipindia.gov.in/DesignApplicationStatus ~~~~~~~~ ✌️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: /dpbrinkm
By David Stephen There is a new [December 2, 2025] paper in Nature, Artificial intelligence for quantum computing, stating that, "Quantum computing (QC) has the potential to impact every domain of science and industry, but it has become increasingly clear that delivering on this promise rests on tightly integrating fault-tolerant quantum hardware with accelerated supercomputers to build accelerated quantum supercomputers." Will Conceptual Brain Science Advance Quantum Computing? "However, transitioning hardware from noisy intermediate-scale quantum (NISQ) devices to fault-tolerant quantum computing (FTQC) faces a number of challenges. Though recent quantum error correction (QEC) demonstrations have been performed, all popular qubit modalities suffer from hardware noise, preventing the below-threshold operation needed to perform fault-tolerant computations." "Though high-performance computing (HPC), and in particular, accelerated GPU computing, already drives QC research through circuit and hardware simulations, the rise of generative artificial intelligence (AI) paradigms has only just begun." "Despite the considerable promise of AI, it is critical to recognize its limitations when applied to QC. AI, as a fundamentally classical paradigm, cannot efficiently simulate quantum systems in the general case due to exponential scaling constraints imposed by the laws of quantum mechanics. Classical simulation of quantum circuits suffers from exponential growth in computational cost and memory consumption." "In the broadest of strokes, we can categorize deep neural network (DNN) applications as discriminative and generative. The former seeks to learn the conditional probability distribution P(y?x) of value vector y given feature vector x, whereas the latter seeks the joint probability distribution P(x, y)." "Critical for training all of these deep learning methods is high-quality data. In the case of QC, this data must often be obtained via simulation with supercomputers due to noise and scale limitations of quantum computers, as well as the cost (time and economic) of obtaining quantum data." "AI for quantum computer development and design. Device design. Learning models of quantum systems. AI for preprocessing. Quantum circuit compilation. Unitary synthesis. AI for circuit optimization. AI models to generate compact circuits. AI for device control and optimization. Designing optimal dynamics. Remove unwanted dynamics. AI for quantum error correction. AI for post-processing. Efficient observable estimation and tomography. Error mitigation techniques. Accelerated quantum supercomputing systems. Simulating high quality data sets." "Most importantly, each aspect of QC needs to scale, and AI might be the only tool with the ability to both solve these problems effectively and do so efficiently at scale. AI has only begun to benefit QC, and it is likely that AI will play an increasingly critical role into the realization of useful QC applications and FTQC." AI A simple way to describe AI is a technology that copied what works: the brain. Or, simply, AI is a technology that looked at the best case of intelligence in nature, the human brain, and imitated it, in the ways that is mathematically possible. Also, large language models [LLMs] copied a major basis of intelligence, language. While it is possible to operate intelligence in other ways, language is central - to human intelligence - for thinking, listening, writing, reading, singing, signing, speaking and so on. So, AI is as good as it is, following the lead of the brain, directly. Now, if this made AI relevant more than any technology that has ever existed, what should any other aspirational technology do? Copy the imitation, AI, or copy the source, the human brain? Quantum Computing There are several engineering gaps in quantum computing where fundamental answers should be sought in the brain. While AI can be currently useful for several improvement cases, the brain should be aggres...
AB sits down with Zeus Kerravala, founder of ZK Research and a leading technology industry analyst, for a great conversation on the role analysts play in the world of tech, trends and innovations related to AI infrastructure, why the network is critical to AI workloads , and more.
Nvidia Distinguished Engineer Kevin Klues noted that low-level systems work is invisible when done well and highly visible when it fails — a dynamic that frames current Kubernetes innovations for AI. At KubeCon + CloudNativeCon North America 2025, Klues and AWS product manager Jesse Butler discussed two emerging capabilities: dynamic resource allocation (DRA) and a new workload abstraction designed for sophisticated AI scheduling.DRA, now generally available in Kubernetes 1.34, fixes long-standing limitations in GPU requests. Instead of simply asking for a number of GPUs, users can specify types and configurations. Modeled after persistent volumes, DRA allows any specialized hardware to be exposed through standardized interfaces, enabling vendors to deliver custom device drivers cleanly. Butler called it one of the most elegant designs in Kubernetes.Yet complex AI workloads require more coordination. A forthcoming workload abstraction, debuting in Kubernetes 1.35, will let users define pod groups with strict scheduling and topology rules — ensuring multi-node jobs start fully or not at all. Klues emphasized that this abstraction will shape Kubernetes' AI trajectory for the next decade and encouraged community involvement.Learn more from The New Stack about dynamic resource allocation: Kubernetes Primer: Dynamic Resource Allocation (DRA) for GPU WorkloadsKubernetes v1.34 Introduces Benefits but Also New Blind SpotsJoin our community of newsletter subscribers to stay on top of the news and at the top of your game. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Damien Lucas explore les enjeux de souveraineté, de puissance de calcul et d'indépendance technologique à l'heure où l'IA redéfinit le marché du cloud pour les entreprises.Interview : Damien Lucas, CEO de ScalewayEn quoi l'adoption massive de l'IA change-t-elle les besoins des entreprises dans le cloud ?L'IA transforme avant tout la manière dont nos clients utilisent leurs données. Pour entraîner ou exploiter des modèles, il faut rapprocher l'IA de la data. Comme le rappelle souvent l'industrie, envoyer toutes ses données chez des acteurs extérieurs comme OpenAI n'est pas viable à long terme : cette data est stratégique. Notre rôle, chez Scaleway, est donc de fournir un cloud souverain, immunisé aux lois extraterritoriales et indépendant des technologies américaines, afin que les entreprises développent leurs infrastructures IA sans compromis.Comment Scaleway renforce-t-il sa capacité technologique face à la demande croissante en puissance de calcul ?Nous investissons massivement dans les GPU, désormais indispensables aux grands modèles de langage et à des usages émergents comme l'agentique ou la robotique. Nous avons été les premiers en Europe à proposer les nouveaux GPU NVIDIA Blackwell B300. En parallèle, nous soutenons l'écosystème européen : les modèles d'agentique développés par la startup française H sont par exemple disponibles dans notre cloud. Notre réseau de data centers — de Paris à Stockholm, en passant bientôt par Berlin — garantit une haute disponibilité tout en maintenant une souveraineté forte.Quelles sont les raisons concrètes qui poussent une entreprise à choisir Scaleway plutôt qu'un hyperscaler américain ?Trois raisons principales reviennent. D'abord, la souveraineté : nos clients veulent éviter la dépendance aux technologies américaines comme AWS ou Google Cloud, et protéger leurs données des lois extra-européennes. Ensuite, le prix : nous sommes significativement moins chers, notamment parce que nous ne facturons pas les egress fees, ces frais de sortie que les hyperscalers imposent systématiquement. Enfin, nous couvrons 90 % des besoins cloud du marché grâce à une offre d'environ 200 produits, bien plus simple à maîtriser que les 600 services proposés par AWS.La migration depuis AWS ou Google Cloud est-elle réellement accessible pour une startup ou une grande organisation ?Oui, très clairement. Si l'entreprise a adopté des standards modernes comme Kubernetes, Terraform ou une architecture microservices, la migration est fluide : on traduit l'infrastructure existante et on la redéploie chez Scaleway. Le frein principal est financier : comme lors d'un déménagement physique, le double loyer pèse lourd. C'est pourquoi nous proposons une “franchise de loyer”, avec plusieurs mois gratuits pour absorber la période de transition et éviter les coûts doublés.L'Europe a-t-elle encore une chance de devenir un acteur majeur du cloud ?Absolument. La transformation induite par l'IA représente une rupture technologique qui pousse toutes les entreprises à reconsidérer leur fournisseur cloud pour les années à venir. Les acteurs européens existent, la technologie est là, et les signaux politiques — comme ceux du sommet franco-allemand sur la souveraineté numérique — montrent une prise de conscience forte. Avec trois ou quatre champions solides, l'Europe peut tout à fait rivaliser avec les États-Unis. Il ne manque plus que la commande publique et privée pour accélérer cette dynamique.-----------♥️ Soutien : https://mondenumerique.info/don
Ho ho holy chaos… the Nonsense crew is BACK with a Christmas episode stuffed fuller than Santa's DUI report!We kick things off with a Kelly Fact straight out of Norwegian folklore: apparently the witches and evil creatures come out on Christmas Eve looking for brooms to joyride through the sky. Henvincible immediately pictures a squad of hammered witches weaving around Santa's airspace like GTA NPCs, while FNBob tries to figure out whether they have to file a flight plan with air traffic control.Then the Wheel of Nonsense returns, and it is UNHINGED this week. FNBob and Henvincible hit everything from crime sprees to Marvel Rivals to P. Diddy vs. 50 Cent, all the way to Kevin Durant taking shots at Michael Jordan (AGAIN).It's messy, it's festive, it's petty — it's Nonsense at its holiday finest.
fal is building the infrastructure layer for the generative media boom. In this episode, founders Gorkem Yurtseven, Burkay Gur, and Head of Engineering Batuhan Taskaya explain why video models present a completely different optimization problem than LLMs, one that is compute-bound, architecturally volatile, and changing every 30 days. They discuss how fal's tracing compiler, custom kernels, and globally distributed GPU fleet enable them to run more than 600 image and video models simultaneously, often faster than the labs that trained them. The team also shares what they're seeing from the demand side: AI-native studios, personalized education, programmatic advertising, and early engagement from Hollywood. They argue that generative video is following a trajectory similar to early CGI—initial skepticism giving way to a new medium with its own workflows, aesthetics, and economic models.Hosted by Sonya Huang, Sequoia Capital
LE sujet TECH 2025 qui m'a le plus surpris en 2025 ?Mat : Toutes les actualités sur l'iA particulièrement : NotebookLM et cette semaine NanoBanana proBaptiste: Claude Code tu as essayé Antigravity ? https://antigravity.google/ https://www.claude.com/product/claude-code Guillaume: Les Meta Rayban connectées ne sont pas un bide commercialSyde Malgré les Trump tariffs - the AI bubble continue : 30% of the S&P 500 in Mag 5": Apple, Microsoft, Amazon, Alphabet, Nvidia / $500B+ AI spend; $12B consumer revenue / stock increase +18% DAX YTD - FTSE +15% /S&P 15% / NASDAQ +20% / FR +11% / Ben: China Just Powered Up the World's First Thorium Reactor — and Reloaded It Mid-Run (La Chine a réussi à recharger un réacteur au thorium sans arrêter la production, utilisant une technologie à sels fondus qui élimine le risque de fusion du cœur et est très bonne pour les petits réacteurs). Aussi les nouvelles façon de faire de la géothermiePRÉDICTION TECH pour 2026 ?Ben: L'année des architectures de calcul "post-GPU": Exemple mais il y a en a d'autres: le "Sensory Edge" Neuromorphique : Innatera (mais aussi thermodynamique: Extropic)Mat : Le post-GPU qui sera après la bulle !Guillaume: PAF! C'est le bruit d'une bulle qui éclateSyde: AI disenchantment - hype cycle model of technology adoption - le descente from the PEAK https://www.slideteam.net/gartner-hype-cycle-model-of-technology-adoption-in-product-lifecycle.html Baptiste: Revert des politiques contre l'IA, par exemple contre les voitures autonomes ou les data centers. InspirationFilms: Mat : Running Man l'ancien comme le nouveau) on réalise la présence des régimes autoritaires et le pouvoir des médiasRunning Man (1985) https://www.imdb.com/title/tt0093894/ Running Man (2025) https://www.imdb.com/title/tt14107334/ Documentaires:BEN: Demis Hassabis et Deepmind:The Thinking Game | Full documentary | Tribeca Film Festival official selection https://www.youtube.com/watch?v=d95J8yzvjbQ&t=2s Guillaume: interview de François Jarrige sur le progrèsLa TECHNOLOGIE: PROGRÈS ou DÉSASTRE écologique? l François Jarrige https://www.youtube.com/watch?v=O0DGYoTq4r4&t=4661s Baptiste: How to Change Your Mind https://www.netflix.com/ch-en/title/80229847 Livres: SYDE :: Breath: The New Science of a Lost Art by James Nestor https://www.amazon.com/Breath-New-Science-Lost-Art/dp/0735213615 Respirer https://amzn.eu/d/gha9HEG MyoTape: Mouth Tapes https://myotape.com/ Podcasts: Mat : Moteur de recherche Moteur de recherche | Balado https://www.youtube.com/playlist?list=PLJ7ZzojPlv5D8gcq90A16Eqp0ICipabg5 Quote: “Tends la main et ouvre ton cœur, car, bien avant les médicaments et les docteurs, l'humain reste le meilleur remède pour son prochain.” du livre Déconnecter de Boucar Diouf Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.
In this panel session from the 2025 Data Center Frontier Trends Summit (Aug. 26-28) in Reston, Va., JLL's Sean Farney moderates a high-energy panel on how the industry is fast-tracking AI capacity in a world of power constraints, grid delays, and record-low vacancy. Under the banner “Scaling AI: The Role of Adaptive Reuse and Power-Rich Sites in GPU Deployment,” the discussion dives into why U.S. colocation vacancy is hovering near 2%, how power has become the ultimate limiter on AI revenue, and what it really takes to stand up GPU-heavy infrastructure at speed. Schneider Electric's Lovisa Tedestedt, Aligned Data Centers' Phill Lawson-Shanks, and Sapphire Gas Solutions' Scott Johns unpack the real-world strategies they're deploying today—from adaptive reuse of industrial sites and factory-built modular systems, to behind-the-fence natural gas, microgrids, and emerging hydrogen and RNG pathways. Along the way, they explore the coming “AI inference edge,” the rebirth of the enterprise data center, and how AI is already being used to optimize data center design and operations. During this talk, you'll learn: * Why record-low vacancy and long interconnection queues are reshaping AI deployment strategy. * How adaptive reuse of legacy industrial and commercial real estate can unlock gigawatt-scale capacity and community benefits. * The growing role of liquid cooling, modular skids, and grid-to-chip efficiency in getting more power to GPUs. * How behind-the-meter gas, virtual pipelines, and microgrids are bridging multi-year grid delays. * Why many experts expect a renaissance of enterprise data centers for AI inference at the edge. Moderator: Sean Farney, VP, Data Centers, Jones Lang LaSalle (JLL) Panelists: Tony Grayson, General Manager, Northstar Lovisa Tedestedt, Strategic Account Executive – Cloud & Service Providers, Schneider Electric Phill Lawson-Shanks, Chief Innovation Officer, Aligned Data Centers Scott Johns, Chief Commercial Officer, Sapphire Gas Solutions
Jonathan Bryce, the new CNCF executive director, argues that inference—not model training—will define the next decade of computing. Speaking at KubeCon North America 2025, he emphasized that while the industry obsesses over massive LLM training runs, the real opportunity lies in efficiently serving these models at scale. Cloud-native infrastructure, he says, is uniquely suited to this shift because inference requires real-time deployment, security, scaling, and observability—strengths of the CNCF ecosystem. Bryce believes Kubernetes is already central to modern inference stacks, with projects like Ray, KServe, and emerging GPU-oriented tooling enabling teams to deploy and operationalize models. To bring consistency to this fast-moving space, the CNCF launched a Kubernetes AI Conformance Program, ensuring environments support GPU workloads and Dynamic Resource Allocation. With AI agents poised to multiply inference demand by executing parallel, multi-step tasks, efficiency becomes essential. Bryce predicts that smaller, task-specific models and cloud-native routing optimizations will drive major performance gains. Ultimately, he sees CNCF technologies forming the foundation for what he calls “the biggest workload mankind will ever have.” Learn more from The New Stack about inference: Confronting AI's Next Big Challenge: Inference Compute Deep Infra Is Building an AI Inference Cloud for Developers Join our community of newsletter subscribers to stay on top of the news and at the top of your game. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
We start with jokes about accents and Apple's floating fireworks, then head straight into the AI spiral: soaring RAM and GPU costs, bot-driven guest pitches, and whether today's generative models can sustain their own weight. From there we tackle meaning at work, the Emperor's New Clothes of corporate incentives, and how to find purpose by getting closer to customers.• AI guest spam and inbox fatigue• Memory crunch across RAM, GDDR, and SSD• GPU price inflation from crypto to AI demand• Sustainability and profit realities of generative AI• Internal, domain-specific AI vs public mega-models• Corporate meaning, incentives, and the Emperor's New Clothes• Gaming's shift to microtransactions and compulsion• Healthcare incentives, Ozempic, and quick-fix economics• A three-legged stool: employees, customers, fair return• Regaining purpose by moving closer to the customer• Community support, therapy, and practical resetsShare this pod with one person you know. Join the Discord via the Linktree. Buy us a coffee to keep the pod online. “Maybe share this episode as a holiday solid.”Click/Tap HERE for everything Corporate StrategyElevator Music by Julian Avila Promoted by MrSnoozeDon't forget ⭐⭐⭐⭐⭐ it helps!
【Insider】投资热点盘点是我们从2024年开始做的一期年度特别节目，意在和大家一起盘点回顾过去一年投资行业的热点。去年我们聊了商业航天、AI和具身智能、低空经济，而今年最明显的趋势是热点“除了AI还是AI”，从年初的具身智能，到海外链和国产链同步催化的AI Infra，再到全行业万众期待的AI应用落地，今年的AI投资热闹非凡，也成为了很多投资机构的关注重点。本期节目邀请到多年关注硅谷科技行业的投资人王子和科技行业记者伊凡，和我们聊一聊今年投资行业又有哪些值得关注的点。无时差研究所限定热红酒返场，单瓶仅需69元，额外赠送无时差研究所购物袋+贴纸，购买链接 https://xhslink.com/m/9cGs4MOm3QB本期节目我们主要聊了以下几点，⭕️ 交成绩单，大家今年都投了些啥？⭕️ 今年有哪些投资热点？年初Deepseek横空出世，杭州六小龙引爆AI国资allin热潮，延续具身投资热潮●杭州六小龙，谁才是唯一真龙？●具身今年的投资思路是什么？（更多投创业公司）●本体和大脑今年有什么新的进展吗？●明年的具身会像今年的大语言模型一样归于沉寂吗？国产GPU上市轮的交易型机会，最后豪赌●市场分成了投到沐曦、摩尔的公司和没投到的公司●超节点时代的到来●寻找新的算力方向，边缘侧和存算一体AI进入应用落地阶段，但新应用乏善可陈●AI眼镜迎来大厂下场●寻找其他硬件载体，哪些爆款硬件们走了出来？哪些是是昙花一现？○plaud.ai是目前最成功的AI硬件吗？它做对了哪些？○AIGC给3D打印带来了什么新的发展？○陪伴玩具有哪些？爆款应该具备什么样的特质？○我们还看到了啥？轮椅、外骨骼、智能戒指、智能相机...（可以简单盘点一下）●垂类的AI软件应用○新概念AI Agent今年爆火，究竟什么是AI Agent？○年末Gemini3出现，是否意味着toC AI应用已死？○在中国saas被证伪的今天，toB AI应用还有哪些机会？○中国能够出现自己的applovin和plantir呢？⭕️ 复盘去年的预测，我们猜对了哪些？商业航天今年波折颇多● 蓝箭朱雀2e发射失败● 星河动力发射失败● 蓝箭朱雀3可回收入轨成功但是一级火箭回收任务未能成功● 长十二12月12号待发⭕️ 展望下一年，哪些值得我们关注？“每一次准备播客的过程，都带我们走到了某一个小小议题的门口，而每个嘉宾都是一把钥匙，ta 领着我们看到了全新的、更大的世界，ta 让我对世界多了一些了解，即便每次都有一点点，它都成为了我们生命里的一个小小刻度，也希望它也能帮助到你~”如果你喜欢我们，欢迎关注无时差研究所同名公众号给我们送来你的心意哦！同时欢迎在全平台搜索并订阅无时差研究所。
2025 was hella weird. The AI revolution is here whether we asked for it or not. This week, George K and George A reflect on the year and what it means for 2026.At AWS re:Invent, George A watched a machine create a custom fragrance and marketing campaign in real-time from a voice prompt. What does that portend for product prototyping, and scaled manufacturing?Could voice and natural language finally replacing typing as the primary interface? We're watching the biggest shift in human-computer interaction since the mouse.Worldwide AI adoption isn't hype anymore—it's happening and doing so unevenly. Some enterprises are getting serious and some are still noodling. The tools are maturing. The question shifted from "if" to "how do we do this responsibly."There are serious questions to answer. GPU lifecycles. The Magnificent Seven's circular financing models. The human cost of moving this fast. But that's the work—building technology that serves us instead of the other way around.The revolution came. Now comes the interesting part: what we actually build with it.2026 is going to be wild. We remain up to the challenge.Mentioned: Brookings Institution, “New data show no AI jobs apocalypse—for now” Discussed in further detail with Ethan Mollick on Your Undivided Attention Reid Hoffman's interview with Wispr Flow founder/CEO Tanay Kothari More on Coreweave's financing model at The Verge
AWS's silicon line is helping customers reduce GPU dependency. The business now brings in billions annually. We discuss the cost and efficiency advantages.Get the top 40+ AI Models for $20 at AI Box: https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Derniers modèles d’intelligence artificielle et outils comme Captain Safari et Anytalker qui transforment la production de contenu vidéo. Nous discutons également de l’état des travaux de George R. R. Martin sur « A Song of Ice and Fire » et des implications de l’IA dans la créativité littéraire. Défis liés à la fabrication de matériel informatique, notamment l’impact environnemental croissant des data centers. Patreon YouTube Discord Modèles et idioties de la semaine Captain Safari, Any talker, VR Bench et Gen VIRE. L'IA se normalisera… doucement. Et en attendant, attention… Une moitié des nouveaux textes ne sont pas synthétiques. Est-ce encore trop ? C'est officiel, le DOGE a été une calamité et Elon en est toujours une. Georges RR Martin ne veut pas utiliser l'IA, donc c'est foutu. Explosion des datacenters : au moins les saumons seront contents. C'est Métal Dell sauvé par l'IA, pas par Windows 11. Partage de “talents” entre Intel et TSMC, Rapidus accélère. Partage de GPU avec la Chine. Et les TPU ? La DDR7 arrive ! Ça tombe bien, toutes les autres sont parties. Black Sky vous a à l'oeil et les magnétomètres quantiques. Bientôt un téléphone qui voit comme un dinosaure. C'est nickel : Google passe du Chrome à l'Aluminium. Y'a qu'une télé, c’est Telehack… Bonus : les beaux arts ASCII. Participants Une émission préparée par Guillaume Poggiaspalla Présenté par Guillaume Vendé
Cette semaine : The Finals S9, Marvel Cosmic Invasion, LOL : Twilight's End | 2025 Season 3 Cinematic, Bubble Bobble: Sugar Dungeons, Elite Dangerous: Caspian Explorer, Metroid Prime 4: Beyond, SoundSource 6 (Rogue Amoeba), RekaB - Never Ending Void, Micron (Crucial) prend sa retraite, les augmentations touchent aussi les GPU, et Nvidia rétablit le support de PhysX pour certains jeux. Lisez plutôt Torréfaction #354 : The Finals S9, Marvel Cosmic Invasion, Elite Dangerous: Caspian Explorer, Micron tue Crucial et AMD augmente ses prix avec sa vraie mise en page sur Geekzone. Pensez à vos rétines.
Amazon Web Services (AWS) has made significant advancements in artificial intelligence (AI) at its reInvent event, introducing a new AI training chip, Trainium 3, which reportedly enhances performance for AI training and inference by up to four times while reducing energy consumption by 40%. Additionally, AWS launched new features in its Agent Core platform, allowing developers to set boundaries for AI agents and log user interactions. The introduction of customizable AI models through the new service, NovaForge, aims to make AI model development more accessible for businesses, addressing the high costs associated with creating models from scratch.Microsoft is facing challenges in selling its AI tools, with reports indicating a slowdown in customer adoption. Despite Microsoft's assertion that it has not lowered sales quotas for AI products, the situation highlights a broader issue: customers are struggling to see the value in AI investments due to messy data, inconsistent processes, and unclear governance. This resistance suggests that while demand for AI exists, readiness among customers remains low, presenting an opportunity for IT service providers to facilitate the transition by offering readiness assessments and governance frameworks.Managed Service Providers (MSPs) are increasingly utilizing AI, with a survey indicating that 80% have adopted AI-powered chatbots, which have improved customer support. However, one-third of MSPs report challenges in implementing AI, including high costs and a lack of internal expertise. As client expectations regarding data security rise, MSPs are deploying AI-driven threat detection solutions. The survey results indicate a commitment to leveraging AI for business transformation, but the complexity of integrating AI into existing workflows remains a significant hurdle.The surge in demand for RAM, driven by the AI industry, has led to a 500% increase in memory prices, creating a shortage of consumer-grade memory. This situation mirrors previous GPU shortages and indicates that high-performance computing components are now subject to the purchasing power of major AI companies. MSPs must prepare for ongoing volatility in hardware costs and communicate these changes to clients, adjusting budgets and refresh cycles accordingly. The evolving landscape emphasizes the need for MSPs to adopt a structured approach to AI, ensuring they are not merely adding tools but effectively transforming their service offerings. Four things to know today00:00 AWS Expands Full-Stack AI Strategy From Chips to Private Regions, Raising Governance and Lock-In Stakes for MSPs07:38 Reports of AI Sales Friction at Microsoft Highlight Market Hesitation and Open the Door for MSP Readiness Services09:28 Survey Shows AI Adoption Surging Among MSPs, Yet Cost, Expertise, and Security Pressures Undercut True Transformation11:51 AI-Driven RAM Shortage Forces MSPs to Reforecast Budgets as Prices Spike 500%This is the Business of Tech. Supported by: https://mailprotector.com/mspradio/
AI agents can already write code, build websites, and manage workflows ... but they still can't pay for anything on their own. That bottleneck is about to disappear.In this episode of TechFirst with John Koetsier, we sit down with Jim Nguyen, former PayPal exec and cofounder/CEO of InFlow, a new AI-native payments platform launching from stealth. InFlow wants to give AI agents the ability to onboard, pay, and get paid inside the flow of work, without redirects, forms, or a human typing in credit card numbers.We talk about: • Why payments — not intelligence — are the missing link for AI agents • How agents become a new kind of customer • What guardrails and policies keep agents from spending all your money • Why enterprises will need HR for agents, budgets for agents, and compliance systems for agents • The future of agent marketplaces, headless ecommerce, and machine-speed commerce • How InFlow plans to become the PayPal of agentic systemsIf AI agents eventually hire, fire, transact, and manage entire workflows, someone has to give them wallets. This episode explores who does it, how it works, and what it means for the economy.
(00:00) Co tam u nas słychać?(02:16) Metroid, Disco Samurai i Project Thea(04:38) Luther, Ona jedzie z przodu, Zaginiony autokar(11:10) Koniec aplikacji messenger na desktopy(16:20) Stranded: Alien Dawn(18:32) Tematy z zeszłego odcinka (21:56) Spotify Wrapped i co się liczy na YT(28:50) Problemy z RAMem(30:35) Powody wzrostu cen pamięci RAM(34:15) Skala inwestycji w infrastrukturę AI(36:15) Do kiedy potrwa kryzys(44:16) Jakie produkty podrożeją?(53:00) Chmura i GTA 6 Project Thea Release Trailerhttps://youtu.be/SxJFj9rGvSU?si=3hZuo7wATgq6OTMSDisco Samurai - Release Date Trailerhttps://youtu.be/sf35SK0V1qk?si=ceBCNXINNBm6GgM5Kryzys pamięci RAM może potrwać nawet do 2028 roku; Samsung i SK Hynix zabrali głos w sprawiehttps://www.gry-online.pl/newsroom/kryzys-pamieci-ram-moze-potrwac-nawet-do-2028-roku-samsung-i-sk-h/z02fa6aNvidia reportedly no longer supplying VRAM to its GPU board partners in response to memory crunch — rumor claims vendors will only get the die, forced to source memory on their ownhttps://www.tomshardware.com/pc-components/gpus/nvidia-reportedly-no-longer-supplying-vram-to-its-gpu-board-partners-in-response-to-memory-crunch-rumor-claims-vendors-will-only-get-the-die-forced-to-source-memory-on-their-ownPamięć DRAM drożeje szybciej niż złoto. Twój komputer będzie kosztował fortunęhttps://ithardware.pl/aktualnosci/pamiec_dram_drozeje_zloto-46384.htmlGrupa Rock i Borys na FB - https://www.facebook.com/groups/805231679816756/Podcast Remigiusz "Pojęcia Nie Mam" Maciaszekhttps://tinyurl.com/yfx4s5zzShorty Rock i Boryshttps://www.facebook.com/rockiboryshttps://www.tiktok.com/@borysniespielakSerwer Discord podcastu Rock i Borys!https://discord.com/invite/AMUHt4JEvdSłuchaj nas na Lectonie: https://lectonapp.com/p/rckbrsSłuchaj nas na Spotify: https://spoti.fi/2WxzUqjSłuchaj nas na iTunes: https://apple.co/2Jz7MPSProgram LIVE w niedzielę od osiemnastej - https://jarock.pl/live/rockRock i Borys to program o grach, technologii i życiu
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
Send us a textWe break down Cloudflare's outage, why a small config change caused big waves, and what better guardrails could look like. We then unpack AWS and Google's cross‑cloud link, Megaport's move into bare metal and GPUs, Webex adding deepfake defenses, and a new startup aiming to tune AI networks at microsecond speed.• Cloudflare outage root cause and fallout• Automation guardrails, validation and rollbacks• AWS–Google cross‑cloud connectivity preview• Pricing, routing and policy gaps to watch• Megaport acquires Latitude SH for compute• Bare metal and GPU as a service near clouds• Webex integrates deepfake and fraud detection• Accuracy risks, UX and escalation paths• Apstra founders launch Aria for AI networks• Microburst telemetry, closed‑loop control and SLAsIf you enjoyed this please give us some feedback or share this with a friend we would love to hear from you as well and we will see you in two weeks with another episodePurchase Chris and Tim's book on AWS Cloud Networking: https://www.amazon.com/Certified-Advanced-Networking-Certification-certification/dp/1835080839/ Check out the Monthly Cloud Networking Newshttps://docs.google.com/document/d/1fkBWCGwXDUX9OfZ9_MvSVup8tJJzJeqrauaE6VPT2b0/Visit our website and subscribe: https://www.cables2clouds.com/Follow us on BlueSky: https://bsky.app/profile/cables2clouds.comFollow us on YouTube: https://www.youtube.com/@cables2clouds/Follow us on TikTok: https://www.tiktok.com/@cables2cloudsMerch Store: https://store.cables2clouds.com/Join the Discord Study group: https://artofneteng.com/iaatj
Join The Full Nerd gang as they talk about the latest PC building news. In this episode the gang talks about Adam's recent trip to Intel's performance testing lab, Black Friday deals for PC parts, how generative AI is hitting game developers and much more. And of course we answer your questions live! Links: - Cheap Black Friday build: https://www.pcworld.com/article/2992089/i-crafted-the-cheapest-black-friday-gaming-pc-build-again-its-brutal-this-year.html - CES 2026 expectations: https://videocardz.com/newz/what-to-expect-from-amd-nvidia-and-intel-at-ces-2026 - 9850X3D leaks: https://www.pcgamer.com/hardware/processors/amd-has-just-launched-the-ryzen-7-9850x3d-with-zero-fanfare-and-i-think-i-understand-why/ - Intel 1% GPU marketshare: https://www.pcworld.com/article/2996364/intel-storms-back-to-power-1-percent-of-pc-graphics-cards.html Join the PC related discussions and ask us questions on Discord: https://discord.gg/WWnEzTDhw Follow the crew on X and Bluesky: @AdamPMurray @BradChacos @MorphingBall @WillSmith ============= Read PCWorld! Website: http://www.pcworld.com Newsletter: http://www.pcworld.com/newsletters/signup =============
The Giving TreeMichael and Susan Dell to donate $6.25 billion to fund 'Trump accounts' for 25 million U.S. kidsLyft CEO: This Giving Tuesday, I'm matching every rider's donationDavid Risher: $78M in 2023Jeff Bezos and Lauren Sánchez Bezos commit $102.5 million to organizations combatting homelessness across the U.S.: ‘This is just the beginning'The wedding of Jeff Bezos and Lauren Sánchez in Venice is estimated to have cost between $46.5 million and $55.6 millionMacKenzie Scott's $19 billion donations have turned philanthropy on its head—why her style of giving actually worksFighting back! (Stakeholders Rule!)New York City Council passes landmark AI oversight packageThe New York City Council unanimously passed a collection of bills that are designed to provide a heightened level of oversight for the city's use of artificial intelligence tools.Bernie Sanders and Mamdani joined the Starbucks picket line in Brooklyn More than 1,000 Amazon employees sign open letter warning the company's AI ‘will do staggering damage to democracy, our jobs, and the earth'Costco sues Trump administration over tariffs, seeks full refundCostco filed a lawsuit at the U.S. Court of International Trade on Friday, saying the administration's tariffs imposed under the International Emergency Economic Powers Act (IEEPA) are unlawful.The 1977 law has historically been used to impose sanctions against other nations.Exxon bid to dismiss Connecticut climate lawsuit failsA judge moved the case closer to trial after rejecting the company's request to toss it out.OpenAI Completed Its Conversion. A New Ballot Initiative Seeks to Reverse ItA coalition that tried and failed to block OpenAI's conversion earlier this year is back with a new tactic: a California ballot initiative aimed at reining in the startup's power.The planned initiative, dubbed the California Charitable Assets Protection Act, was filed Monday with California's attorney general. It doesn't mention OpenAI by name, but calls for the creation of an oversight board empowered to review and potentially reverse conversions to nonprofit organizations engaged in scientific and technological research that have happened in the state since January of 2024.Starbucks to settle with over 15,000 New York City workers for roughly $35 millionStarbucks will pay about $35 million to more than 15,000 New York City workers to settle claims it denied them stable schedules and arbitrarily cut their hours.The company will also pay $3.4 million in civil penalties under the agreement with the city's Department of Consumer and Worker Protection.It also agrees to comply with the city's Fair Workweek law going forward.Fighting back! (Shareholders Rule!)Michael Burry calls Tesla ‘ridiculously overvalued' and knocks tech industry for a widely used practiceThe post is critical of Tesla and the technology industry as a whole for its use of stock-based compensation and then ignoring it as a legitimate expense.Burry said Tesla share dilution should continue following shareholder approval of CEO Elon Musk's historic pay package.Second proxy adviser calls for vote against Westpac director over ASX stintA second influential proxy adviser has recommended institutional investors vote against re-electing Westpac non-executive director Peter Nash, citing his six-year stint on the board of the troubled Australian Securities Exchange (ASX).CGI Glass Lewis said in a new report on Tuesday that investors should vote against Nash who joined the Westpac board in March 2018 and chairs the board's audit committee.Norway wealth fund to back call for Microsoft human rights report at AGMMicrosoft AGM takes place on December 5Norway wealth fund is Microsoft's eighth-largest shareholderThe fund also said it would vote against the re-appointment of CEO Satya Nadella as chair of the board, as well as against his pay package.PotpourriOpenAI declares ‘code red' as Google catches up in AI raceIn the memo, reported by the Wall Street Journal and The Information, Altman said the company will be delaying initiatives like ads, shopping and health agents, and a personal assistant, Pulse, to focus on improving ChatGPT.This includes core features like greater speed and reliability, better personalization, and the ability to answer more questions, he said.Corporations say they prioritize people. So why do so few chief people officers become CEOs?Only 16 of the CEOs at the 1,000 biggest companies have HR experience.Stephanie Mehta is CEO and chief content officer of Mansueto Ventures, publisher of Inc. and Fast CompanyMATTUplifting stories:Costco sues Trump admin seeking tariff refunds before Supreme Court rules if they're illegalWhy it's uplifting:Costco is the retail bulwark against stupidity - and they're getting paid for it with persistent quarterly growthCostco board member defends DEI practices, rebukes companies scrapping policiesCostco Under Fire in 19 States for Taking Stand Against TrumpSecond proxy adviser calls for vote against Westpac director over ASX stintWhy it's uplifting:This IS NOT AN ACTIVIST DRIVEN VOTE, and it isn't about attendance! This is purely driven by conflict of interest - an ASX listed company using an ASX board member, a board member who up until 6 years ago lead KPMG in Australia - and KPMG is now Westpac's auditorThe move is underway - ISS/GL were never going to vote against directors in the US first, but Australia is much easier to targetGoogle's data centers could actually be going to the moonWhy it's uplifting:While we couldn't solve the climate crisis for the sake of HUMANITY, we WILL solve it for the sake of AI:one hundred trillion times more energy than we produce in all of Earth todayThe space pitch arrives when Earth is starting to look like a bad long-term landlord for the AI build-out. A 2024 Lawrence Berkeley National Laboratory report found that U.S. data centers already chew through about 4.4% of the country's electricity, and that share could climb to as much as 12% by 2028 as GPU farms multiply. McKinsey puts a price tag on the race to scale data centers: roughly $6.7 trillion in global data center capex by 2030, about $5 trillion of that aimed at AI-ready infrastructureextraterrestrial data centers could cut emissions by a factor of 10 compared with their earthbound cousinsAlso, GTFO!
Nathan Sobo has spent nearly two decades pursuing one goal: building an IDE that combines the power of full-featured tools like JetBrains with the responsiveness of lightweight editors like Vim. After hitting the performance ceiling with web-based Atom, he founded Zed and rebuilt from scratch in Rust with GPU-accelerated rendering. Now with 170,000 active developers, Zed is positioned at the intersection of human and AI collaboration. Nathan discusses the Agent Client Protocol that makes Zed "Switzerland" for different AI coding agents, and his vision for fine-grained edit tracking that enables permanent, contextual conversations anchored directly to code—a collaborative layer that asynchronous git-based workflows can't provide. Nathan argues that despite terminal-based AI coding tools visual interfaces for code aren't going anywhere, and that source code is a language designed for humans to read, not just machines to execute. Hosted by Sonya Huang and Pat Grady, Sequoia Capital
Is Black Friday really booming, or are inflated prices and AI shopping assistants just muddying the waters? This episode rips into the data, exposes retailer tactics, and debates if smarter tech is actually making us better shoppers. Black Friday data shows online sales strong, store results mixed Silicon Valley's man in the White House is benefiting himself and his friends View: Trump's AI agenda sails toward an iceberg of bipartisan populist fury 'We do fail ... a lot': Defense startup Anduril hits setbacks with weapons tech Solar's growth in US almost enough to offset rising energy use Datacenters in space are a terrible, horrible, no good idea China leapfrogs US in global market for 'open' AI models Danish authorities in rush to close security loophole in Chinese electric buses The Ford F-150 Lightning was supposed to transform the industry. Now, Ford may pull the plug Roblox is a problem — but it's a symptom of something worse Warner Music and Suno strike deal for AI music, giving artists control over their likeness Leak confirms OpenAI is preparing ads on ChatGPT for public roll out Jony Ive, Sam Altman: OpenAI plans elegantly simple device One tech tip: Modern cars are spying on you. Here's what you can do about it How a GM EV1 was sold for the first time GPU prices are coming to earth just as RAM costs shoot into the stratosphere Host: Leo Laporte Guests: Daniel Rubino, Sam Abuelsamid, and Mike Elgan 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 shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ventionteams.com/twit deel.com/twit zapier.com/twit Melissa.com/twit zscaler.com/security
Scott and CJ sit down live at JSNation NYC with Iwo Plaza, creator of TypeGPU, to dig into how WebGPU is unlocking a new wave of graphics and compute power on the web. They chat about shader authoring in TypeScript, the future of GPU-powered AI in the browser, and what it takes to build a killer developer-friendly graphics library. Show Notes 00:00 Welcome to Syntax! 00:32 What is TypeGPU? High-level overview and why it exists 01:20 WebGPU vs WebGL – the new era of GPU access on the web 01:47 Why shader languages are hard + making them accessible 02:24 Iwo's background in C++, OpenGL, and discovering JS 03:06 Sharing graphics work on the web vs native platforms 03:29 WebGPU frustrations that inspired TypeGPU 04:17 Making GPU–CPU data exchange easier with Zod-like schemas 05:01 Writing shaders in JavaScript + the unified type system 05:38 How the “use_gpu” directive works under the hood 06:05 Building a compiler that turns TypeScript into shader code 07:00 Type inference, primitives, structs, and TypeScript magic 08:21 Leveraging existing tooling via Unplugin + bundler integration 09:15 How TypeGPU extracts ASTs and generates TinyEST metadata 10:10 Runtime shader generation vs build-time macros 11:07 How the AST is traversed + maintaining transparency in output 11:43 Example projects like Jelly Shader and community reception 12:05 Brought to you by Sentry.io 12:30 Does TypeGPU replace 3JS? How it fits the existing ecosystem 13:20 Low-level control vs high-level abstractions 14:04 Upcoming Three.js integration – plugging TypeGPU into materials compute shaders 15:34 Making GPU development more approachable 16:26 Docs, examples, and the philosophy behind TypeGPU documentation 17:03 Building features by building examples first 18:13 Using examples as a test suite + how docs shape API design 19:00 Docs as a forcing function for intuitive APIs 20:21 GPU for AI – browser inference and future abstractions 21:11 How AI examples inform new libraries (noise, inference, etc.) 21:57 Keeping the core package small and flexible 22:44 Building “TypeGPU AI”-style extensions without bloating the core 23:07 The cost of AI examples and building everything from scratch 23:41 Standard library design and future of the ecosystem 24:04 Closing thoughts from Iwo – OSS, GPU renaissance, and encouragement 24:34 Sick Picks & Shameless Plugs Sick Picks Iwo: Perogies Shameless Plugs Iwo: Syntax Podcast Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads
Is Black Friday really booming, or are inflated prices and AI shopping assistants just muddying the waters? This episode rips into the data, exposes retailer tactics, and debates if smarter tech is actually making us better shoppers. Black Friday data shows online sales strong, store results mixed Silicon Valley's man in the White House is benefiting himself and his friends View: Trump's AI agenda sails toward an iceberg of bipartisan populist fury 'We do fail ... a lot': Defense startup Anduril hits setbacks with weapons tech Solar's growth in US almost enough to offset rising energy use Datacenters in space are a terrible, horrible, no good idea China leapfrogs US in global market for 'open' AI models Danish authorities in rush to close security loophole in Chinese electric buses The Ford F-150 Lightning was supposed to transform the industry. Now, Ford may pull the plug Roblox is a problem — but it's a symptom of something worse Warner Music and Suno strike deal for AI music, giving artists control over their likeness Leak confirms OpenAI is preparing ads on ChatGPT for public roll out Jony Ive, Sam Altman: OpenAI plans elegantly simple device One tech tip: Modern cars are spying on you. Here's what you can do about it How a GM EV1 was sold for the first time GPU prices are coming to earth just as RAM costs shoot into the stratosphere Host: Leo Laporte Guests: Daniel Rubino, Sam Abuelsamid, and Mike Elgan 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 shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ventionteams.com/twit deel.com/twit zapier.com/twit Melissa.com/twit zscaler.com/security
Is Black Friday really booming, or are inflated prices and AI shopping assistants just muddying the waters? This episode rips into the data, exposes retailer tactics, and debates if smarter tech is actually making us better shoppers. Black Friday data shows online sales strong, store results mixed Silicon Valley's man in the White House is benefiting himself and his friends View: Trump's AI agenda sails toward an iceberg of bipartisan populist fury 'We do fail ... a lot': Defense startup Anduril hits setbacks with weapons tech Solar's growth in US almost enough to offset rising energy use Datacenters in space are a terrible, horrible, no good idea China leapfrogs US in global market for 'open' AI models Danish authorities in rush to close security loophole in Chinese electric buses The Ford F-150 Lightning was supposed to transform the industry. Now, Ford may pull the plug Roblox is a problem — but it's a symptom of something worse Warner Music and Suno strike deal for AI music, giving artists control over their likeness Leak confirms OpenAI is preparing ads on ChatGPT for public roll out Jony Ive, Sam Altman: OpenAI plans elegantly simple device One tech tip: Modern cars are spying on you. Here's what you can do about it How a GM EV1 was sold for the first time GPU prices are coming to earth just as RAM costs shoot into the stratosphere Host: Leo Laporte Guests: Daniel Rubino, Sam Abuelsamid, and Mike Elgan 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 shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ventionteams.com/twit deel.com/twit zapier.com/twit Melissa.com/twit zscaler.com/security
Is Black Friday really booming, or are inflated prices and AI shopping assistants just muddying the waters? This episode rips into the data, exposes retailer tactics, and debates if smarter tech is actually making us better shoppers. Black Friday data shows online sales strong, store results mixed Silicon Valley's man in the White House is benefiting himself and his friends View: Trump's AI agenda sails toward an iceberg of bipartisan populist fury 'We do fail ... a lot': Defense startup Anduril hits setbacks with weapons tech Solar's growth in US almost enough to offset rising energy use Datacenters in space are a terrible, horrible, no good idea China leapfrogs US in global market for 'open' AI models Danish authorities in rush to close security loophole in Chinese electric buses The Ford F-150 Lightning was supposed to transform the industry. Now, Ford may pull the plug Roblox is a problem — but it's a symptom of something worse Warner Music and Suno strike deal for AI music, giving artists control over their likeness Leak confirms OpenAI is preparing ads on ChatGPT for public roll out Jony Ive, Sam Altman: OpenAI plans elegantly simple device One tech tip: Modern cars are spying on you. Here's what you can do about it How a GM EV1 was sold for the first time GPU prices are coming to earth just as RAM costs shoot into the stratosphere Host: Leo Laporte Guests: Daniel Rubino, Sam Abuelsamid, and Mike Elgan 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 shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: ventionteams.com/twit deel.com/twit zapier.com/twit Melissa.com/twit zscaler.com/security
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