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This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today, we're joined by Jacob Buckman, co-founder and CEO of Manifest AI to discuss achieving long context in transformers. We discuss the bottlenecks of scaling context length and recent techniques to overcome them, including windowed attention, grouped query attention, and latent space attention. We explore the idea of weight-state balance and the weight-state FLOP ratio as a way of reasoning about the optimality of compute architectures, and we dig into the Power Retention architecture, which blends the parallelization of attention with the linear scaling of recurrence and promises speedups of >10x during training and >100x during inference. We review Manifest AI's recent open source projects as well: Vidrial—a custom CUDA framework for building highly optimized GPU kernels in Python, and PowerCoder—a 3B-parameter coding model fine-tuned from StarCoder to use power retention. Our chat also covers the use of metrics like in-context learning curves and negative log likelihood to measure context utility, the implications of scaling laws, and the future of long context lengths in AI applications. The complete show notes for this episode can be found at https://twimlai.com/go/750.
Join The Full Nerd gang as they talk about the latest PC building news. In this episode the gang is joined by special guest Edward Crisler, NA PR Manger at @SapphireTechnology , to talk about the current state of GPU's, including manufacturing challenges and benchmarking changes. And of course we answer your questions live! Join the PC related discussions and ask us questions on Discord: https://discord.gg/SGPRSy7 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 Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
Andrew Feldman is Co-Founder & CEO of Cerebras, building the world's fastest AI inference and training. Cerebras recently closed a $1.1BN Series G round at an $8.1 billion valuation, backed by top names including Fidelity, Atreides, Tiger Global, Valor Equity and 1789 Capital. Under his leadership, they've leapfrogged GPU limits in inference, operate at trillions of tokens per month, and are filing to go public soon. AGENDA: 02:43 Why We Did Not IPO and Raised $1BN From Fidelity 05:03 Analysis of Chip and Compute Landscape Today 07:14 NVIDIA Showing Signs They Are Running Out of Ideas 13:57 The Real Questions to Ask on Chip Depreciation 24:54 Energy Requirements for AI: Is it Feasible? 29:25 Mag7 Value Concentration: Feature or a Bug 31:57 Talent is the Bottleneck and Trump Makes it Worse 32:55 The War for Talent: Secrets No One Sees 34:22 Evaluating the Data Centre Economy: Many Will Lose Money 38:01 Three Changes the US Could Make to Beat China in AI 42:30 Why 80% of our Revenues are in the UAE 47:26 Quick Fire Questions 58:59 Why Work Life Balance is Total BS
一张来自彭博社的图表揭示了一个颠覆性的转变：美国办公楼建设正在快速萎缩，而数据中心的建设却在飞速增长。这不仅仅是地产行业的变迁，它预示着我们的经济和工作方式正在被彻底重塑。我们正在从一个以人力为核心的时代，迈向一个以算力为核心的新纪元。在这个视频里，我将深入剖析这一转变对你和你的职业生涯意味着什么。我会解释为什么公司现在更看重 GPU 算力而非办公室工位，并为你提供 4 个具体、可行的行动步骤，帮助你在新时代保持领先。你将学到：如何成为“翻译官”： 弥合 AI 算力与现实问题之间的鸿沟。动手拥抱 AI： 学习如何将 ChatGPT 等 AI 工具和自动化流程融入日常工作，提升效率。盘活你的历史资产： 利用 AI 工具，让你的旧作品和过往经验焕发新生。掌握快速实验的艺术： 培养小步快跑的习惯，在实践中找到杠杆点。这不是空洞的理论，而是一份实用的行动指南，教你如何与机器协作，放大你作为人类的独特价值。无论你是设计师、产品经理，还是任何一位科技行业的职场人，这个视频都将为你提供一张清晰的未来职场地图。3. 一句话核心卖点通过一张彭博社的图表，深度解读经济如何从“人资时代”转向“算力时代”，并为你提供一份在 AI 新纪元中保持领先的 4 步行动指南。4. 视频文案（Show Notes）彭博社图表来源： 展示办公楼和数据中心建设对比的原始图表。链接： https://www.bloomberg.com/news/articles/2024-06-07/how-ai-is-changing-the-geography-of-the-us-economy黄仁勋金句： 关于“AI 工厂”的引用。来源： 来源于他的多次演讲和访谈，包括 2024 年 GTC 大会主题演讲。视频中提到的 AI 工具和概念：ChatGPT自动化工具AI 生成内容Support this podcast at — https://redcircle.com/beartalk/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy
Scott Guthrie is the executive vice president of Cloud and AI at Microsoft. Guthrie joins Big Technology Podcast to discuss the tech industry's massive AI infrastructure buildout and whether it is overdoing it with the hundreds of billions of investment. Guthrie discusses the way Microsoft thinks about its OpenAI investment, whether it's worth investing in scaling pre-training, and Silicon Valley's growing debt problem Tune in for the second half where we discuss the longevity of the GPU, custom silicon, and competing with NVIDIA. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Questions? Feedback? Write to: bigtechnologypodcast@gmail.com
Welcome to another episode of Data Driven, where we dive deep into how data and AI are shaping—sometimes shaking—the modern world. In this episode, hosts Frank La Vigne, Andy Leonard, and Carmen Li sit down with Carmen Lee, the trailblazing CEO of Silicon Data and a former Bloomberg data aficionado.Carmen's on a mission to bring clarity to the wild west of GPU compute markets, and she shares with us how she's turning raw compute into a true tradable commodity—think futures markets for GPUs, the “Bloomberg terminal” for AI infrastructure, and perhaps even a Carfax for your next used GPU cluster.Together, they explore everything from why AI startups struggle with fluctuating margins, to the crucial role TSMC plays in the world economy, all the way to the data transparency that might be the missing piece in AI's explosive growth. Whether you're curious about benchmarking GPUs, tokenomics, managing infrastructure costs, or just want a glimpse into the future of data markets, this one's for you.Stay tuned for a fascinating conversation on normalizing chaos, hedging tech costs, geeking out over hardware, and even a few laughs about used GPU “car lots” in Virginia. Let's get data driven!LinksSilicon Data -https://www.silicondata.com/Dancing with Qubits -https://amzn.to/4mIOG8UThe Nvidia Way -https://amzn.to/3VH9aUvTime Stamps00:00 "AI Commodities and GPU Markets"06:56 Ecosystem Transparency Benefits All10:55 AI SaaS Cost Optimization Challenges13:41 Token Economics in Cloud AI15:27 Optimizing GPU and Token Commitment18:41 Token-Based Product Innovation25:00 "Verifying UIDs and Connectivity"28:43 Measuring GPU Performance30:41 Supply Chain Impact on GPU Industry35:43 "TNC's Unchallenged Leadership in Supply Chain"36:31 Silicon Ecosystem Collaboration39:38 Nvidia's Strategic TSMC Capacity Purchase42:51 Bloomberg's Media and Finance Expansion46:53 "Quantum Reading Challenges"50:13 "Data Driven Podcast Wrap-Up"
professorjrod@gmail.comWhat if the real cause of your random reboots isn't the GPU at all—but the power plan behind it? We take you end to end through a stability-first build, starting with the underrated hero of every system: clean, properly sized power. You'll learn how to calculate wattage with 25–30% headroom, navigate 80 Plus efficiency tiers, and safely adopt ATX 3.0 with the 12VHPWR connector—no sharp bends, modular cable sanity, and the UPS/surge stack that prevents nasty surprises when the lights flicker.From there, we shift into storage strategy that balances speed and safety. HDD, SATA SSD, and NVMe each earn their place, and we break down RAID 0/1/5/6/10 in plain language so you can pick the right array for your workload. We underline a hard truth: RAID protects against disk failure, not human error, so versioned offsite backups remain non-negotiable. Real-world stories—including a painful RAID 5 rebuild gone wrong—highlight why RAID 6 and RAID 10 matter for bigger or busier systems.Memory and CPU round out the backbone. We simplify DDR4 vs DDR5, explain how frequency and CAS affect real latency, and show why matched pairs and dual channel deliver the performance you paid for. You'll get quick wins like enabling XMP/EXPO, when ECC is worth it, and how to troubleshoot training hiccups. Then we open the CPU: cores, threads, cache, sockets, chipsets, and why firmware comes before hardware when upgrades fail to post. Cooling decisions—air, AIO, or custom—tie directly to performance ceilings, along with safe overclock/undervolt practices and thermal targets under sustained load.By the end, you'll have a practical checklist to build smarter, troubleshoot faster, and feel ready for the CompTIA A+ exam: power headroom, cable stewardship, airflow planning, RAID with backups, memory matching, BIOS compatibility, and validation testing. If this guide helps you ship a rock-solid PC, share it with a friend, leave a quick review, and hit follow so you never miss the next masterclass.Support the showIf you want to help me with my research please e-mail me.Professorjrod@gmail.comIf you want to join my question/answer zoom class e-mail me at Professorjrod@gmail.comArt By Sarah/DesmondMusic by Joakim KarudLittle chacha ProductionsJuan Rodriguez can be reached atTikTok @ProfessorJrodProfessorJRod@gmail.com@Prof_JRodInstagram ProfessorJRod
Nvidia has created trillions of dollars in value by providing GPU chips to the world for use in the AI industry. This crypto project is doing the same thing but in a decentralized cloud fashion, and is built using the most cutting edge AI technology in crypto, which is Bittensor. Find out why Lium could be the next big thing in GPU cloud computing and should become a leading Bittensor subnet.
Cerebrium is a serverless AI infrastructure platform orchestrating CPU and GPU compute for companies building voice agents, healthcare AI systems, manufacturing defect detection, and LLM hosting. The company operates across global markets handling data residency constraints from GDPR to Saudi Arabia's data sovereignty requirements. In a recent episode of Category Visionaries, I sat down with Michael Louis, Co-Founder & CEO of Cerebrium, to explore how they built a high-performance infrastructure business serving enterprise customers with high five-figure to six-figure ACVs while maintaining 99.9%+ SLA requirements. Topics Discussed: Building AI infrastructure before the GPT moment and strategic patience during the hype cycle Scaling a distributed engineering team between Cape Town and NYC with 95% South African talent Partnership-driven revenue generation producing millions in ARR without traditional sales teams AI-powered market engineering achieving 35% LinkedIn reply rates through competitor analysis Technical differentiation through cold start optimization and network latency improvements Revenue expansion through global deployment and regulatory compliance automation GTM Lessons For B2B Founders: Treat go-to-market as a systems engineering problem: Michael reframed traditional sales challenges through an engineering lens, focusing on constraints, scalability, and data-driven optimization. "I try to reframe my go to market problem as an engineering one and try to pick up, okay, like what are my constraints? Like how can I do this, how can it scale?" This systematic approach led to testing 8-10 different strategies, measuring conversion rates, and building automated pipelines rather than relying on manual processes that don't scale. Structure partnerships for partner success before revenue sharing: Cerebrium generates millions in ARR through partners whose sales teams actively upsell their product. Their approach eliminates typical partnership friction: "We typically approach our partners saying like, look, you keep the money you make, we'll keep the money we make. If it goes well, we can talk about like rev share or some other agreement down the line." This removes commission complexity that kills B2B partnerships and allows partners to focus on customer value rather than internal revenue allocation conflicts. Build AI-powered competitive intelligence for outbound at scale: Cerebrium's 35% LinkedIn reply rate comes from scraping competitor followers and LinkedIn engagement, running prospects through qualification agents that check funding status, ICP fit, and technical roles, then generating personalized outreach referencing specific interactions. "We saw you commented on Michael's post about latency in voice. Like, we think that's interesting. Like, here's a case study we did in the voice space." The system processes thousands of prospects while maintaining personalization depth that manual processes can't match. Position infrastructure as revenue expansion, not cost optimization: While dev tools typically focus on developer productivity gains, Cerebrium frames their value proposition around market expansion and revenue growth. "We allow you to deploy your application in many different markets globally... go to market leaders love us and sales leaders because again we open up more markets for them and more revenue without getting their tech team involved." This messaging resonates with revenue stakeholders and justifies higher spending compared to pure cost-reduction positioning. Weaponize regulatory complexity as competitive differentiation: Cerebrium abstracts data sovereignty requirements across multiple jurisdictions - GDPR in Europe, data residency in Saudi Arabia, and other regional compliance frameworks. "As a company to build the infrastructure to have data sovereignty in all these companies and markets, it's a nightmare." By handling this complexity, they create significant switching costs and enable customers to expand internationally without engineering roadmap dependencies, making them essential to sales teams pursuing global accounts. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM
Welcome back to another episode of Upside at the EUVC Podcast, where Dan Bowyer, Mads Jensen of SuperSeed and Lomax from Outsized Ventures unpack what's happening in European tech and venture capital.This week: The UK lands $150B of US pledges and 120,000 Nvidia GPUs—can London turn its AI hype into substance? NATO on edge after Russian incursions across Poland and Denmark. Are we witnessing an AI bubble, or just the infrastructure wave of the century? Plus: cyber risk after JLR's ransomware hit, Trump's $100K H-1B visa fee, and the week's billion-dollar deals.
Ep 268Apple nešto smatrao, izgleda još misle da ih plebs većinski blagonaklono gleda. Nope.EU Has 'No Intention' to Repeal DMA Following Apple ChallengeCraig Hockenberry:Here's my guess what happened in the lead up to WWDC25:Apple realized it was deep in the weeds with Apple Intelligence (and associated PR) and needed a tentpole feature that wasn't AI.Liquid Glass was in development for some upcoming edgeless hardware. It needed another year of work, but management/marketing was fucked.A thing that wasn't ready got moved up. Bug fixing took a back seat. Everyone grabbed paint brushes, not screwdrivers.The next year is going to be rough for EVERYONE.Apple pobrojao novostu u iOS 26, iPadOS 26 i macOS 26.Christopher Lawley: iPadOS 26 Walkthrough: THIS Reboots the iPadThe Tech Chap: iPhone Air FULL REVIEW - Not What I Expected...Steve Troughton-Smith:The A19 Pro in the iPhone Air is 50% faster than the M1 in my primary Mac mini in singlecore, 10% faster in multicore, and 13% faster in GPU compute. That's a lot of chip in a tiny slab of glassIt works sideways!Ozbiljno dobar zoom na 17 ProMiki pomenuo PowerPrint.iPhone Satellite Features Remain Free for Another Year - TidBITSApple Drops iCloud Support for iOS 10 and macOS SierraSupport for FireWire Removed from macOS 26 Tahoe - TidBITSRogue Amoeba: Our product lineup is ready for Tahoe, but Tahoe may not be ready for you.Steve Troughton-Smith:You know who wasn't ready on launch day with iOS/macOS 26 versions of all their apps on the App Store?Miguel Arroz: macOS Tahoe UI has a HUGE new feature for folks like me who have 24/7 Mac Minis running and access them remotely: you can now type the boot password remotely via SSH!macOS 26 Tahoe Pushes FileVault Use - TidBITSSteve Troughton-Smith:I'm having a ton of trouble updating apps using the Mac App Store (on Tahoe) if there was a TestFlight version installed.CodeSource: The Untold Story of Databases60 years after Gemini, newly processed images reveal incredible detailsZahvalniceSnimano 16.9.2025.Uvodna muzika by Vladimir Tošić, stari sajt je ovde.Logotip by Aleksandra Ilić.Artwork epizode by Saša Montiljo, njegov kutak na Devianartu
“It's happening. The question is whether it's a dream or a nightmare. This week, OpenAI introduced Pulse, an AI assistant that knows what we want to do and think before we do. That Was The Week publisher Keith Teare welcomes Pulse as a “habit” that will “shape your day.” Unlike the techno-teleological Keith, however, I'm less enamored by Pulse. Do we really want a proactive AI assistant that not only controls what Keith calls the “front door” but every other door (and window) in our lives? Keith describes this as the “consumer install moment” - Sam Altman's $10 trillion bet on ‘Abundant Intelligence.' But what, exactly, is so abundant about this personalized machine intelligence that installs itself into our lives? Having a smart assistant determine our daily calendar might actually make us dumber. Such an “agentic” future is certainly no friend of human agency. Yeah, it's happening. The end of the beginning or the beginning of the end?* The “Front Door” Battle is On: OpenAI's Pulse represents a strategic shift from reactive search to proactive assistance, with tech giants racing to control the primary interface through which we interact with information and make decisions.* Privacy Becomes an Afterthought: While OpenAI claims privacy protections, most users don't understand what data these AI assistants access. The $200/month price point currently limits exposure, but mass adoption will create unprecedented privacy challenges.* The Infrastructure Gold Rush: Sam Altman's 10-gigawatt power deals and NVIDIA's GPU dominance reveal the massive energy and capital investment required to scale AI - with an $800 billion gap between current investment and projected revenue.* “Consumer Pull” is Driving the Boom: Unlike previous tech bubbles, AI demand from actual users (not just hype) is outstripping supply, forcing companies to race to build data centers and power infrastructure to meet real usage.* The “Idiocracy Trap” Question: As AI assistants take over more cognitive tasks - from scheduling to decision-making - we face a fundamental question about whether this technology will enhance human intelligence or create dependency that makes us collectively dumber.Keen On America is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit keenon.substack.com/subscribe
Cipher Mining landed its first AI tenant, with $1.3 billion in the deal backstopped by Google, and MicroBT has opened a U.S. distribution hub with 10,000 ASIC miners per month in volume. Click Here To Join the BitAxe Giveaway! Welcome back to The Mining Pod! On today's round up, we dive deep into Cipher Mining's $3 billion AI hosting deal with Fluid Stack, backed by Google's $1.4 billion guarantee. And as hashrate surges to 1,100 EH/s, miners are struggling with sub-$50 hash prices. Plus MicroBT has opened a U.S. distribution hub, and IREN's aggressive GPU expansion. **Notes:** • Cipher signed $3B AI deal with Fluid Stack • Google backstopping $1.4B of obligations • Hash price under $50/PH/day (6mo low) • Network hash rate at 1,100 EH/s • IREN doubled GPU fleet to 23K units, raises Q1-2026 ARR to $500M • MicroBT opens 10K unit/month US shop Timestamps: 00:00 Start 03:03 Difficulty Report by Luxor 07:08 Cipher and Fluidstack deal! 13:15 MicroBT opens up shop in US 17:34 Cleanspark Ad 18:03 IREN doubles GPU fleet (again)
Episode 83: Intel and Nvidia have formed a partnership, but because APUs are not that relevant to desktop PC gamers, we discuss whether this deal will actually impact gaming significantly. Also, we put Intel's Arc GPUs into our GPU rankings, and chat about some newsCHAPTERS00:00 - Intro00:33 - Intel and Nvidia APU team up, but gamers don't use APUs37:00 - We add Intel Arc GPUs to the rankings45:38 - Ryzen 7 9800X3D drops in price49:52 - RX 9070 BIOS mod52:01 - 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.
No Morins this week—just Jess and Sam, trading Gossip Girl “dear listener” asides for a tour of tech's new power map. From Meta's in-store glasses push to Apple's “Find My” doubling as Gen Z's stealth social network, the real story is how distribution and lock-in shape the future. Sam frames “mercantilism 2.0,” where global trade routes of capital now run through Silicon Valley, Tel Aviv, and Riyadh, with figures like Elon Musk and Sam Altman acting as brokers of $10B+ flows.In true Sam fashion, the conversation highlights why LLMs aren't true moats, pointing instead to the infrastructure layer (chips, power, data centers) and the UX layer (distribution, product polish). Nvidia's securitized GPU deals illustrate how structured finance and alliances are reshaping competition.The takeaway: early-stage VC may finally be moving past hype, becoming sober—and therefore interesting—again.Chapters:02:02 – Meta Ray-Bans: friction as onboarding strategy05:31 – Mercantilism 2.0: Tech's new trade routes07:56 – Elon's real genius: moving $10B+ into frontier tech09:27 – Sam Altman as mega-capital trade-route broker12:40 – Starlink V3 and the network-layer power shift16:08 – Could Elon own planetary communications?18:35 – Find My = stealth social network21:04 – Strategy assets over DCF: power, data centers, chips23:41 – LLMs aren't the moat; moats shift lower/higher27:44 – AI's expense revives structured finance30:56 – Nvidia as the East India Company of compute33:50 – Will a handful of players control all the assets?39:57 – Early-stage VC is sober (and exciting) again43:05 – TikTok's heat moved to AI: the attention shiftWe're also on ↓X: https://twitter.com/moreorlesspodInstagram: https://instagram.com/moreorlessSpotify: https://podcasters.spotify.com/pod/show/moreorlesspodConnect with us here:1) Sam Lessin: https://x.com/lessin2) Dave Morin: https://x.com/davemorin3) Jessica Lessin: https://x.com/Jessicalessin4) Brit Morin: https://x.com/brit
Click Here To Join the BitAxe Giveaway! Welcome back to The Mining Pod! On today's round up, we dive deep into Cipher Mining's $3 billion AI hosting deal with Fluid Stack, backed by Google's $1.4 billion guarantee. And as hashrate surges to 1,100 EH/s, miners are struggling with sub-$50 hash prices. Plus MicroBT has opened a U.S. distribution hub, and IREN's aggressive GPU expansion. **Notes:** • Cipher signed $3B AI deal with Fluid Stack • Google backstopping $1.4B of obligations • Hash price under $50/PH/day (6mo low) • Network hash rate at 1,100 EH/s • IREN doubled GPU fleet to 23K units, raises Q1-2026 ARR to $500M • MicroBT opens 10K unit/month US shop Timestamps: 00:00 Start 03:03 Difficulty Report by Luxor 07:08 Cipher and Fluidstack deal! 13:15 MicroBT opens up shop in US 17:34 Cleanspark Ad 18:03 IREN doubles GPU fleet (again)
En este episodio se sienta con nosotros Horacio Martos (cofundador de Social Point y hoy fundador de Labhouse) para una conversación abierta con todo el equipo sobre cómo pasar del gaming a construir productos B2B rentables sin depender de rondas. Hablamos de visión, ejecución y esa mezcla poco glamourosa pero esencial de producto y marketing: cuándo iterar, cuándo escalar y cómo mantener la disciplina de métricas en cada decisión.La tertulia recorre el camino de cero a tracción: validación rápida, pricing y empaquetado, retención como norte, y los canales que están funcionando ahora mismo (ASA, Meta, Google) con tácticas concretas para no quemar presupuesto. Debatimos el papel real de la IA de la generación de assets al soporte en desarrollo y dónde aporta ventaja competitiva frente a ser “commodity”. También entramos en cultura operativa: equipos pequeños, foco extremo, cadencia de releases y “lo suficiente” de proceso para sostener velocidad sin romper calidad.Sigue a los "tertulianos" en Twitter:• Bernat Farrero: @bernatfarrero• Jordi Romero: @jordiromero• César Migueláñez: @heycesrSOBRE ITNIG
In this episode, ARK's Brett Winton, Charles Roberts and Frank Downing sit down with Stephen Balaban, CEO and co-founder of Lambda Labs — a company building AI-specific cloud infrastructure. The conversation explores Lambda's role in the AI value chain, the evolving economics of data centers, and why traditional hyperscalers might be too slow to meet the moment.Stephen explains why he believes we're transitioning from deterministic, rule-based software to what he calls “neural software” — stochastic, neural network-driven systems that will eventually replace nearly all traditional software. He shares Lambda's mission to enable this transformation by rapidly deploying GPU infrastructure and supporting the AI research and application build-out happening today.The discussion spans infrastructure strategy, regulatory bottlenecks, AI safety, energy constraints, and long-term visions of neural operating systems. Stephen offers a bold perspective on the hardware demands and philosophical shifts required to usher in a world where software is generated, not written.Key Points From This Episode:00:01:21 How Lambda positions itself as a “neo-cloud” provider competing with AWS, Azure, and GCP for AI workloads.00:02:46 Why ARK estimates $1.5 trillion in annual AI-related data center investment by 2030 and what it could mean for Lambda.00:05:26 Why hyperscalers may be too slow to meet the unique demands of AI training compared to specialized players.00:06:29 How AI infrastructure requires new rack designs, higher power density, and different utilization patterns.00:09:20 Why AI may disrupt the entire computing stack—from Nvidia overtaking Intel to reshaping platform and cloud services.00:14:50 Stephen explains Lambda's “secret mission” to replace all traditional software with neural networks.00:16:36 Why companies trust Lambda to deploy GPU infrastructure faster and more reliably than incumbents.00:20:27 How the concept of a “neural operating system” reframes software as stochastic rather than deterministic.00:23:04 How hallucinations in neural systems could be managed with checks and balances similar to financial approvals.00:25:04 Why Stephen sees AI safety and alignment as the cybersecurity of the future.00:39:00 How real-time AI tasks may run locally at the edge, while deeper reasoning gets pushed to the cloud.00:44:11 Why running modern large language models still resembles the supercomputer era rather than the PC era.00:46:06 How Stephen views the long-term convergence of AI with quantum computing and brain–computer interfaces.00:50:20 Why scaling AI requires the “heroic effort” of Nvidia, TSMC, OpenAI, energy providers, and Lambda together.00:53:43 Back-of-the-envelope math on CapEx per megawatt—from power plants and data centers to GPUs.00:57:11 Why power infrastructure and deregulation could become the biggest stumbling blocks for AI growth.01:02:02 How software creation is shifting from a labor-driven process to a capital-intensive one.01:06:06 Why Stephen and Brett describe data centers as “AI factories” producing custom neural software.
這集節目是9/19胡說科技Youtube直播內容，想看影像版歡迎點擊連結：https://lihi.cc/4gsEH 黃仁勳的挑戰者終於出現了！不是AMD蘇姿丰，更不用提中國寒武紀了。 真正能稱得上「輝達剋星」的，是剛公布財報的博通（Broadcom）。阿榕伯稱執行長陳福陽是最被低估的CEO。博通最新財報出爐，AI成長預期喊出60%，比輝達更快。因為ASIC指標性勝利出現了！ 為什麼ASIC成長的速度比GPU更快？輝達的市佔會被吃掉嗎？盤點ASIC三傑！台灣的機會在哪裡？這場直播，阿榕伯為你解答。 主持人：天下雜誌總主筆 陳良榕 ＊Podcast限定優惠方案！訂閱一年《胡說科技》還附天下新書《造光者》：https://bit.ly/4n8h6tW ＊意見信箱：bill@cw.com.tw -- Hosting provided by SoundOn
In this DCF Trends-Nomads at the Summit Podcast episode, Chris James, CEO of NoesisAI, delivers a sweeping, insight-rich overview of how different classes of AI models—from LLMs and RAG to vision AI and scientific workloads—are driving a new wave of infrastructure decisions across the data center landscape. With a sharp focus on the diverging needs of training vs. inference, James breaks down what it takes to support today's AI—from GPU-intensive clusters with high-speed interconnects and liquid cooling to inference-optimized, edge-deployed accelerators. He also explores the rapidly shifting hardware ecosystem, including the rise of custom silicon, heterogeneous computing, and where the battle between NVIDIA, AMD, Intel, and hyperscaler-designed chips is headed. Whether you're designing for scalability, sustainability, or the bleeding edge, this conversation offers a field guide to the infrastructure behind intelligent computing.
When time-to-action requires very low latency, the immediacy of data visualization makes all the difference. Being able to analyze vast amounts of multi-dimensional data in real-time requires massive throughput, and an in-memory architecture designed to deliver instant insights at scale. Check out this episode of DM Radio to hear how advanced optimization techniques leveraging multi-core CPU, GPU, contiguous memory, and advanced compression are re-inventing what is possible. Marc Stevens and Mikhail Pikalov of Row64 will demonstrate several use cases where traditional approaches would falter. Attendees will learn: * How the real-time visualization of data changes decision-making dynamics when seconds matter; * How hardware-accelerated computing stacks can deliver speed and scale to visualization layers; * Practical use cases, from cyber security to city intelligence, where ultra-low-latency visualization drives faster, better decisions; * Key architectural principles for building environments that deliver immediacy, scalability, and reliability.
Preston and Seb launch their tech book review series with a deep dive into The Thinking Machine, a book about NVIDIA and its CEO Jensen Huang. They explore NVIDIA's transformation from a gaming hardware company to a key player in AI, discussing CUDA, leadership strategy, robotics, and the speed of innovation. The episode ends with a preview of their next review, Empire of AI. IN THIS EPISODE YOU'LL LEARN: 00:00 - Intro 05:29 – How NVIDIA transitioned from gaming GPUs to leading AI infrastructure 09:26 – Why CUDA was a turning point in GPU development for AI research 15:37 – The role of NVIDIA in enabling modern AI models, including transformers 19:55 – Jensen Huang's leadership style and strategic market thinking 20:14 – The significance of creating new markets versus competing in existing ones 24:44 – How NVIDIA trains robots in hyper-realistic digital environments 27:47 – The impact of LiDAR and simulation on robotics advancement 38:53 – Whether Jensen's success is due to luck, skill, or strategic foresight 50:30 – The meaning behind Jensen's "speed of light" principle 01:01:00 – What's coming next in the book review series, starting with Empire of AI BOOKS AND RESOURCES Related Book: The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip. Seb's Website and book: The Hidden Cost of Money. Related books mentioned in the podcast. Ad-free episodes on our Premium Feed. NEW TO THE SHOW? Join the exclusive TIP Mastermind Community to engage in meaningful stock investing discussions with Stig, Clay, Kyle, and the other community members. Follow our official social media accounts: X (Twitter) | LinkedIn | | Instagram | Facebook | TikTok. Check out our Bitcoin Fundamentals Starter Packs. Browse through all our episodes (complete with transcripts) here. Try our tool for picking stock winners and managing our portfolios: TIP Finance Tool. Enjoy exclusive perks from our favorite Apps and Services. Get smarter about valuing businesses in just a few minutes each week through our newsletter, The Intrinsic Value Newsletter. Learn how to better start, manage, and grow your business with the best business podcasts. SPONSORS Support our free podcast by supporting our sponsors: Simple Mining HardBlock AnchorWatch Human Rights Foundation Linkedin Talent Solutions Vanta Unchained Onramp Netsuite Shopify Abundant Mines Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm
輝達展現新氣魄，將砸下3兆投資OpenAI、部署500萬顆GPU。輝達從賣硬體變身AI建設霸主，黃仁勳這一招，背後盤算比你想得深。 文：張詠晴 製作團隊：莊志偉、張雅媛、鄭子鴻 ＊閱讀零時差，點這看全文
NVIDIA is doubling down on AI dominance with massive investments across cloud, chips, and infrastructure. It struck a $6.3B deal with CoreWeave to secure long-term GPU demand, is investing $5B in Intel to co-develop custom CPUs and PC chips that pair Intel processors with NVIDIA GPUs, and is committing up to $100B with OpenAI to build data centers requiring 10 gigawatts of power. These moves lock in demand, expand NVIDIA's role across computing ecosystems, and cement its leadership in the race to scale global AI infrastructure. This and more on the Tech Field Day News Rundown with Alastair Cooke and guest host Scott Robohn. Time Stamps: 0:00 - Cold Open 0:36 - Welcome to the Tech Field Day News Rundown1:22 - Hugging Face Brings Open-Source Models to GitHub Copilot Chat3:52 - Pulumi Introduces AI Agents to Automate Infrastructure Management6:51 - Cisco DevNet is now Cisco Automation 9:12 - North Dakota to Test Portable Micro Data Centers for AI in Oil Fields12:14 - Sumo Logic Launches AI Agents to Streamline Cybersecurity Operations14:46 - Justice Department Moves to Break Up Google's Ad Business17:43 - NVIDIA's Multi-Billion-Dollar Moves Expand AI and Computing Leadership21:35 - The Weeks Ahead22:58 - Thanks for Watching the Tech Field Day News RundownGuest Host: Scott Robohn, CEO of SolutionalFollow our hosts Tom Hollingsworth, Alastair Cooke, and Stephen Foskett. Follow Tech Field Day on LinkedIn, on X/Twitter, on Bluesky, and on Mastodon.
Elon Musk's xAI has raised $10 billion at a $200 billion valuation, doubling its worth in just four months. The round includes familiar backers like Andreessen Horowitz, Sequoia, and Fidelity, and gives xAI the second-highest valuation in private AI. This episode breaks down what investors are really buying into: Grok's integration with X, the push toward open-source models, plans for a massive GPU cluster, and the growing fusion of social media and AI under Musk's control. We also look at what xAI still lacks compared to OpenAI and Anthropichttps://wilwaldon.com
Trumps FCC Chairman is looking for other shows to punish. Nokia hopes an Intel executive can turn their fortunes around. NVIDIA invests in Intel, and Intel looks to be cancelling an upcoming GPU. Microsoft raises prices on XBOX again. Samsung will put ads on your really expensive fridge. Vivo shares some fun slow motion footage from the X300. TSMC chip prices are even higher than last year. And we have to chat about MediaTek's new premium SOC, the Dimensity 9500! Let's get our tech week started right! -- Show Notes and Links https://somegadgetguy.com/b/4Qh Video Replay https://youtube.com/live/VYprI5x7Cw8 Support Talking Tech with SomeGadgetGuy by contributing to their tip jar: https://tips.pinecast.com/jar/talking-tech-with-somegadgetgu Find out more at https://talking-tech-with-somegadgetgu.pinecast.co This podcast is powered by Pinecast. Try Pinecast for free, forever, no credit card required. If you decide to upgrade, use coupon code r-c117ce for 40% off for 4 months, and support Talking Tech with SomeGadgetGuy.
Big thanks to Proton VPN for sponsoring this video. To get 64% discount to your Proton VPN Plus subscription, please use the following link: https://protonvpn.com/davidbombal Want a “hacker” laptop without wasting cash? In this candid breakdown with OTW, we cut through the hype and show you what actually matters for learning pentesting in 2025: prioritising RAM over flashy GPUs, picking VMware (free for personal use) for reliable labs, using refurbs/minis/Raspberry Pi, and planning for where wireless hacking is going (Bluetooth/BLE/Zigbee) — not just Wi-Fi. We also cover AMD vs Intel vs Apple M-chips/ARM for Linux VMs, when cloud cracking makes sense, and why daily practice beats buying gadgets. Highlights: • Best beginner specs (RAM first, SSD nice, storage ≠ speed) • VMware vs VirtualBox for home labs • AMD/Intel vs Apple M-chips/ARM for Kali/Parrot VMs • Alpha adapters & aircrack-ng compatibility; Nordic nRF52 for BLE • Budget path: used/refurb, mini-PCs, Pi, phone/cloud labs (HTB/THM) • The 80/20 rule of hacking: skills are greater than gear If you're delaying until you can afford a $2 – 3k laptop, don't. Start now, learn daily, and upgrade later. // Occupy The Web SOCIAL // X: / three_cube Website: https://hackers-arise.net/ // Occupy The Web Books // Linux Basics for Hackers 2nd Ed US: https://amzn.to/3TscpxY UK: https://amzn.to/45XaF7j Linux Basics for Hackers: US: https://amzn.to/3wqukgC UK: https://amzn.to/43PHFev Getting Started Becoming a Master Hacker US: https://amzn.to/4bmGqX2 UK: https://amzn.to/43JG2iA Network Basics for hackers: US: https://amzn.to/3yeYVyb UK: https://amzn.to/4aInbGK // OTW Discount // Use the code BOMBAL to get a 20% discount off anything from OTW's website: https://hackers-arise.net/ // Playlists REFERENCE // Linux Basics for Hackers: • Linux for Hackers Tutorial (And Free Courses) Mr Robot: • Hack like Mr Robot // WiFi, Bluetooth and ... Hackers Arise / Occupy the Web Hacks: • Hacking Tools (with demos) that you need t... // David's SOCIAL // Discord: discord.com/invite/usKSyzb Twitter: www.twitter.com/davidbombal Instagram: www.instagram.com/davidbombal LinkedIn: www.linkedin.com/in/davidbombal Facebook: www.facebook.com/davidbombal.co TikTok: tiktok.com/@davidbombal YouTube: / @davidbombal Spotify: open.spotify.com/show/3f6k6gE... SoundCloud: / davidbombal Apple Podcast: podcasts.apple.com/us/podcast... // MY STUFF // https://www.amazon.com/shop/davidbombal // SPONSORS // Interested in sponsoring my videos? Reach out to my team here: sponsors@davidbombal.com // MENU // 0:00 - Coming up 01:21 - Proton VPN sponsored segment 03:16 - Get started and start learning 08:39 - Computer specs: CPU, GPU, RAM & Hard drives 16:46 - Time vs Money 17:58 - Virtual machines 19:15 - Computer specs overview 22:17 - Wi-Fi adaptors for Wi-Fi hacking 24:17 - Bluetooth dongles for Bluetooth hacking 26:57 - "80% Person & 20% Machine" 29:17 - Do you need hacking gadgets? 31:57 - Apple vs Intel vs AMD 35:53 - Learn hacking with a smartphone 37:01 - Learn hacking with a Raspberry Pi 39:32 - Kali Linux vs ParrotOS (Which OS to use?) 40:58 - The problem with Chromebooks 42:02 - Using Hack The Box/TryHackMe // Conclusion Please note that links listed may be affiliate links and provide me with a small percentage/kickback should you use them to purchase any of the items listed or recommended. Thank you for supporting me and this channel! Disclaimer: This video is for educational purposes only. #hacking #laptop #vm
欢迎收听雪球出品的财经有深度，雪球，国内领先的集投资交流交易一体的综合财富管理平台，聪明的投资者都在这里。今天分享的内容叫关于英伟达入股英特尔的几点看法。来自雨枫。2025年9月18日，全球GPU巨头英伟达宣布，将以50亿美元的巨额投资入股其传统竞争对手英特尔，同时双方将在人工智能基础设施和个人计算机产品领域展开深度合作。我就此发表我的几点看法。第一，单纯就是跟英伟达结成深度的战略合作关系，即使先不考虑那50亿美元，对于这两年深陷泥潭的英特尔以数据为中心的人工智能来说，也是一剂强心针。毕竟各条业务线当中，受到压力最大、丢失份额最多的就是这块了。反而对面向消费级的全球化智库来说，继续用自己的核显还是集成英伟达的显卡，销量上的区别其实并不会有那么大。第二，对于英特尔来说，如今所面临的问题，短期来看是制程研发、是服务器CPU份额流失、是要不要转型无晶圆厂模式公司。但长期来看，一切苦难的根源，还是因为x86市场本身在不断萎缩，日渐衰弱的主营业务收入，覆盖不了下一代制程研发和生产所需的巨额资本开销，这才是今天所有问题的根源。第三，长期来看，美国政府会想尽一切办法让本土的无晶圆厂转移一部分订单给英特尔，包括但不限于关税层面和更强硬的司法层面。所以现在没有公布制程方面的代工合作，不代表后面不可以有。不过另一方面，这也说明18A这代制程，眼下确实还打动不了英伟达；第四，陈立武既然上台伊始没有选择分拆IFS公司，还拿了特朗普政府的钱，那起码在短时间内，就更不可能选择分拆了。所以换个角度来说，要想让英特尔彻底活过来，最重要的三件事：订单、订单、还是订单。其他都不是问题的关键。这个原则，也适用于和英伟达的合作。第五，9月18日晚有一个很大的疑问是英特尔自研的显卡业务线还要不要继续保留，还是说以后彻底就放弃了这方面的所有念想？如果是后者的话，那这50亿美元对英特尔来说还是挺昂贵的。第六，黄仁勋这个操作，在一定程度上也是对AMD的一种反制，毕竟AMD这两年能活得这么滋润，甚至还有余力去挑战老黄在AI市场上的江湖地位，说到底还是因为在x86服务器业务上赚到了真金白银。如果老黄能通过与英特尔的合作，在服务器芯片市场上给AMD施加更大的压力，那其实也是一种变相的围魏救赵之举。退一万步说，如果是单纯为了高速显卡互连技术和GPU方面的合作，英伟达其实犯不上非要花钱入股。毕竟以英伟达目前的市场地位，老黄只要招招手，陈立武就得跑过去候着。选择入股，本身就说明了一些事情。第七，对于英伟达来说，丧失增长性的x86市场肯定不是它所感兴趣的蛋糕，但却是它无论如何也绕不开的一道墙。想用ARM彻底取代x86，听起来确实是很美好的，但具体实施的过程却存在着无数的障碍，何况如今的ARM并不掌握在英伟达手里。在这种情况下，拥抱而不是排斥x86，对老黄来说是最理性的选择，而在x86生态里，目前性价比最高的选项就是与英特尔合作了。
Build and run everything from simple web apps to AI supercomputing by matching each workload to the right Azure VM in minutes. Find and know exactly what you're provisioning by understanding the naming format to see CPU type, memory, storage, and features before deployment to match what your app or workload needs. Use free tools like Azure Migrate to right-size and plan. Matt McSpirit, Microsoft Azure expert, shows how to choose, size, and deploy workloads such as burstable web apps, massive in-memory databases, GPU-driven AI training, and high-performance scientific modeling, all with automatic scaling and confidential computing when needed. ► QUICK LINKS: 00:00 - Azure Virtual Machines 01:12 - Decode Azure VM Names 01:28 - Right-Size with Azure Migrate 02:15 - B series 02:45 - D series 03:23 - E series 04:14 - F series 04:29 - L series 05:01 - M series 05:23 - Constrained vCPU VMs 05:49 - H series 06:20 - N series 06:55 - Azure Boost 07:24 - Confidential VMs & Deploying your VMs 08:28 - Wrap up ► Link References Get started at https://aka.ms/VMAzure Azure VM naming conventions at https://aka.ms/VMnames ► Unfamiliar with Microsoft Mechanics? As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics
AI Chat: ChatGPT & AI News, Artificial Intelligence, OpenAI, Machine Learning
In this episode, Jayden interviews Carmen Li, founder and CEO of Silicon Data, a company focused on bringing transparency to the GPU market. They discuss the importance of a real-time pricing index for GPUs, the need for better risk management tools in the AI industry, and how financial services can benefit from improved data transparency. Carmen shares insights on the dynamics of GPU pricing, the impact of regional differences, and the future of AI technology. The conversation highlights common misconceptions in the industry and the potential for significant advancements in the coming years.Try AI Box: https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleVisit Silicon Data: https://www.silicondata.com/Find Carmen: https://www.linkedin.com/in/carmenrliChapters00:00 Introduction to Silicon Data and AI Infrastructure02:36 The Importance of Transparency in GPU Markets05:26 Bridging the Gap Between Finance and AI08:18 Challenges in Data Accuracy and Pricing10:45 Regional Pricing Discrepancies in GPU Rentals13:30 Dynamic Pricing Models for AI Tokens15:55 The Role of Data in Risk Management18:43 Understanding the Secondary GPU Market21:28 Common Misconceptions in the GPU Industry24:08 Future Trends in AI and GPU Technology
Join this episode of DM Radio, as host Eric Kavanagh dives into the emerging concept of “AI factories” with special guests Mark Madsen of Third Nature and Denise Muyco of Ravel. Together, they explore how modern data centers are being transformed to handle the massive compute demands of AI-balancing workloads, optimizing power usage, and rethinking infrastructure for the GPU era. From high-performance computing roots to today's generative AI breakthroughs, this discussion unpacks the challenges and opportunities of scaling intelligence at industrial levels.
CoreWeave, a cloud provider backed by NVIDIA, secured a $6.3 billion order for AI computing capacity, with NVIDIA agreeing to buy any unused supply through 2032. The deal highlights CoreWeave's reliance on NVIDIA, its sole GPU supplier and investor, while boosting its role in powering AI workloads. Despite strong growth—$1.21 billion in Q2 revenue, up 207% year-over-year—the company remains unprofitable, losing $290.5 million. Major contracts, including an $11.9 billion deal with OpenAI, have fueled demand and pushed CoreWeave's market value above $58 billion.Time Stamps: 0:00 - Cold Open0:25 - Welcome to the Tech Field Day News Rundown1:20 - Tarboro Data Center Rebuff Tests North Carolina's Development Future5:17 - Broadcom and OpenAI Team Up for AI Chips8:53 - OpenAI and Microsoft Restructure Deal12:20 - Scattered Lapsus$ Hunters is shutting down14:59 - Google Sued by Rolling Stone Owner for AI Summaries18:26 - Anthropic Report Reveals Misuse of Claude in Cyberattacks21:31 - CoreWeave and NVIDIA Strike $6.3 Billion Cloud Deal24:44 - Microsoft Partners with Nebius in AI Cloud Deal29:16 - The Weeks Ahead31:16 - Thanks for Watching the Tech Field Day News RundownFollow our hosts Tom Hollingsworth, Alastair Cooke, and Stephen Foskett. Follow Tech Field Day on LinkedIn, on X/Twitter, on Bluesky, and on Mastodon.
Improve your sleep today! Head to https://evening.ver.so/toe to get 15% off your first order of Verso's Nightcap Elixir. As a listener of TOE you can get a special 20% off discount to The Economist and all it has to offer! Visit https://www.economist.com/toe Live from MIT Media Lab's Augmentation Lab Summit, I speak with Andres Gomez-Emilsson of the Qualia Research Institute about modeling consciousness and rendering it. You haven't seen psychedelic visuals /experiences explained like this before. We separate qualia from sensory input and map the “geometry” of experience through color—synesthesia, pure hues, after-images, and “is your blue my blue?” Andres demos QRI's GPU tool, a Photoshop for psychedelia built on coupled oscillators and feedback. It recreates LSD/psilocybin's fractal tapestries, DMT's entity-like mirror tunnels, global synchrony, and “white-out.” We cover “psychedelic thermodynamics,” neural annealing and valence flips, and pseudo-time—loops and timeless stretches. The episode makes a case for real-time, in-state phenomenology over questionnaires. This was specifically structured to be informative to both those who have never experienced psychedelics and those who are, let's say, well acquainted. Thank you to Dunya Baradari, Addy Cha, and Andres, of course. Join My New Substack (Personal Writings): https://curtjaimungal.substack.com Listen on Spotify: https://open.spotify.com/show/4gL14b9... SUPPORT: Become a YouTube Member (Early Access Videos): / @theoriesofeverything Support me on Patreon: / curtjaimungal Support me on Crypto: https://commerce.coinbase.com/checkou... Support me on PayPal: https://www.paypal.com/donate?hosted_... Twitter: / toewithcurt Discord Invite: / discord SOCIALS: Guests do not pay to appear. Theories of Everything receives revenue solely from viewer donations, platform ads, and clearly labelled sponsors; no guest or associated entity has ever given compensation, directly or through intermediaries. Learn more about your ad choices. Visit megaphone.fm/adchoices
To get to the benefits that AI offers, organizations have to address their technology infrastructure in ways that are much broader than historical approaches. Senior analyst Greg Macatee joins host Eric Hanselman to delve into what's required and what enterprises are identifying in the recent Voice of the Enterprise AI and Machine Learning study. Enterprises are struggling with raising the success levels of AI projects. Over 60% report moderate to severe challenges in achieving AI success. Bringing together the computational power and the right quality data in the right locations can be complicated in the hybrid environments that more are operating. It's not just a matter of being more selective with use cases, AI requires a set of organizational skills that have to be honed. Starting small and iterating can reduce risk while building competency. Infrastructure has to shift in new ways, as well. Data management processes that can build the necessary data pipelines to feed AI applications bring together a broader set of tech disciplines. There are new wrinkles in AI infrastructure ecosystems, with new providers looking to address supply chain constraints, like the Neocloud or GPU as a Service (GPUaaS) providers. Even hyperscalers are looking to them to meet surging demand in a tight market. Those new options offer new choices, but enterprises need to match them with their AI goals. More S&P Global Content: Navigating the AI infrastructure landscape The path from LLMs to agentic AI Next in Tech | Ep. 225: Security for MCP For S&P Global Subscribers: AI infrastructure strategies evolve amid widespread data challenges – Highlights from VotE: AI & Machine Learning Generative AI Market Monitor & Forecast AI infrastructure: Trends, thoughts and a 2025 research agenda Credits: Host/Author: Eric Hanselman Guest: Greg Macatee Producer/Editor: Adam Kovalsky Published With Assistance From: Sophie Carr, Feranmi Adeoshun, Kyra Smith
CoreWeave (CRWV) got an upgrade from JMP Securities as it sees its GPU-as-a-service business as a benefit in an evolving A.I. trade. Marley Kayden adds that its recent $6.3 billion contract with Nvidia (NVDA) offers another line of defense for the stock. Tim Biggam offers an example options trade for the company.======== 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
Francois Daost is a W3C staff member and co-chair of the Web Developer Experience Community Group. We discuss the W3C's role and what it's like to go through the browser standardization process. Related links W3C TC39 Internet Engineering Task Force Web Hypertext Application Technology Working Group (WHATWG) Horizontal Groups Alliance for Open Media What is MPEG-DASH? | HLS vs. DASH Information about W3C and Encrypted Media Extensions (EME) Widevine PlayReady Media Source API Encrypted Media Extensions API requestVideoFrameCallback() Business Benefits of the W3C Patent Policy web.dev Baseline Portable Network Graphics Specification Internet Explorer 6 CSS Vendor Prefix WebRTC Transcript You can help correct transcripts on GitHub. Intro [00:00:00] Jeremy: today I'm talking to Francois Daoust. He's a staff member at the W3C. And we're gonna talk about the W3C and the recommendation process and discuss, Francois's experience with, with how these features end up in our browsers. [00:00:16] Jeremy: So, Francois, welcome [00:00:18] Francois: Thank you Jeremy and uh, many thanks for the invitation. I'm really thrilled to be part of this podcast. What's the W3C? [00:00:26] Jeremy: I think many of our listeners will have heard about the W3C, but they may not actually know what it is. So could you start by explaining what it is? [00:00:37] Francois: Sure. So W3C stands for the Worldwide Web Consortium. It's a standardization organization. I guess that's how people should think about W3C. it was created in 1994. I, by, uh, Tim Berners Lee, who was the inventor of the web. Tim Berners Lee was the, director of W3C for a long, long time. [00:01:00] Francois: He retired not long ago, a few years back. and W3C is, has, uh, a number of, uh. Properties, let's say first the goal is to produce royalty free standards, and that's very important. Uh, we want to make sure that, uh, the standard that get produced can be used and implemented without having to pay, fees to anyone. [00:01:23] Francois: We do web standards. I didn't mention it, but it's from the name. Standards that you find in your web browsers. But not only that, there are a number of other, uh, standards that got developed at W3C including, for example, XML. Data related standards. W3C as an organization is a consortium. [00:01:43] Francois: The, the C stands for consortium. Legally speaking, it's a, it's a 501c3 meaning in, so it's a US based, uh, legal entity not for profit. And the, the little three is important because it means it's public interest. That means we are a consortium, that means we have members, but at the same time, the goal, the mission is to the public. [00:02:05] Francois: So we're not only just, you know, doing what our members want. We are also making sure that what our members want is aligned with what end users in the end, need. and the W3C has a small team. And so I'm part of this, uh, of this team worldwide. Uh, 45 to 55 people, depending on how you count, mostly technical people and some, uh, admin, uh, as well, overseeing the, uh, the work, that we do, uh, at the W3C. Funding through membership fees [00:02:39] Jeremy: So you mentioned there's 45 to 55 people. How is this funded? Is this from governments or commercial companies? [00:02:47] Francois: The main source comes from membership fees. So the W3C has a, so members, uh, roughly 350 members, uh, at the W3C. And, in order to become a member, an organization needs to pay, uh, an annual membership fee. That's pretty common among, uh, standardization, uh, organizations. [00:03:07] Francois: And, we only have, uh, I guess three levels of membership, fees. Uh, well, you may find, uh, additional small levels, but three main ones. the goal is to make sure that, A big player will, not a big player or large company, will not have more rights than, uh, anything, anyone else. So we try to make sure that a member has the, you know, all members have equal, right? [00:03:30] Francois: if it's not perfect, but, uh, uh, that's how things are, are are set. So that's the main source of income for the W3C. And then we try to diversify just a little bit to get, uh, for example, we go to governments. We may go to governments in the u EU. We may, uh, take some, uh, grant for EU research projects that allow us, you know, to, study, explore topics. [00:03:54] Francois: Uh, in the US there, there used to be some, uh, some funding from coming from the government as well. So that, that's, uh, also, uh, a source. But the main one is, uh, membership fees. Relations to TC39, IETF, and WHATWG [00:04:04] Jeremy: And you mentioned that a lot of the W3C'S work is related to web standards. There's other groups like TC 39, which works on the JavaScript spec and the IETF, which I believe worked, with your group on WebRTC, I wonder if you could explain W3C'S connection to other groups like that. [00:04:28] Francois: sure. we try to collaborate with a, a number of, uh, standard other standardization organizations. So in general, everything goes well because you, you have, a clear separation of concerns. So you mentioned TC 39. Indeed. they are the ones who standardize, JavaScript. Proper name of JavaScript is the EcmaScript. [00:04:47] Francois: So that's tc. TC 39 is the technical committee at ecma. and so we have indeed interactions with them because their work directly impact the JavaScript that you're going to find in your, uh, run in your, in your web browser. And we develop a number of JavaScript APIs, uh, actually in W3C. [00:05:05] Francois: So we need to make sure that, the way we develop, uh, you know, these APIs align with the, the language itself. with IETF, the, the, the boundary is, uh, uh, is clear as well. It's a protocol and protocol for our network protocols for our, the IETF and application level. For W3C, that's usually how the distinction is made. [00:05:28] Francois: The boundaries are always a bit fuzzy, but that's how things work. And usually, uh, things work pretty well. Uh, there's also the WHATWG, uh, and the WHATWG is more the, the, the history was more complicated because, uh, t of a fork of the, uh, HTML specification, uh, at the time when it was developed by W3C, a long time ago. [00:05:49] Francois: And there was been some, uh, Well disagreement on the way things should have been done, and the WHATWG took over got created, took, took this the HTML spec and did it a different way. Went in another, another direction, and that other, other direction actually ended up being the direction. [00:06:06] Francois: So, that's a success, uh, from there. And so, W3C no longer works, no longer owns the, uh, HTML spec and the WHATWG has, uh, taken, uh, taken up a number of, uh, of different, core specifications for the web. Uh, doing a lot of work on the, uh, on interopoerability and making sure that, uh, the algorithm specified by the spec, were correct, which, which was something that historically we haven't been very good at at W3C. [00:06:35] Francois: And the way they've been working as a, has a lot of influence on the way we develop now, uh, the APIs, uh, from a W3C perspective. [00:06:44] Jeremy: So, just to make sure I understand correctly, you have TC 39, which is focused on the JavaScript or ECMAScript language itself, and you have APIs that are going to use JavaScript and interact with JavaScript. So you need to coordinate there. The, the have the specification for HTML. then the IATF, they are, I'm not sure if the right term would be, they, they would be one level lower perhaps, than the W3C. [00:07:17] Francois: That's how you, you can formulate it. Yes. The, the one layer, one layer layer in the ISO network in the ISO stack at the network level. How WebRTC spans the IETF and W3C [00:07:30] Jeremy: And so in that case, one place I've heard it mentioned is that webRTC, to, to use it, there is an IETF specification, and then perhaps there's a W3C recommendation and [00:07:43] Francois: Yes. so when we created the webRTC working group, that was in 2011, I think, it was created with a dual head. There was one RTC web, group that got created at IETF and a webRTC group that got created at W3C. And that was done on purpose. Of course, the goal was not to compete on the, on the solution, but actually to, have the two sides of the, uh, solution, be developed in parallel, the API, uh, the application front and the network front. [00:08:15] Francois: And there was a, and there's still a lot of overlap in, uh, participation between both groups, and that's what keep things successful. In the end. It's not, uh, you know, process or organization to organization, uh, relationships, coordination at the organization level. It's really the fact that you have participants that are essentially the same, on both sides of the equation. [00:08:36] Francois: That helps, uh, move things forward. Now, webRTC is, uh, is more complex than just one group at IETF. I mean, web, webRTC is a very complex set of, uh, of technologies, stack of technologies. So when you, when you. Pull a little, uh, protocol from IETFs. Suddenly you have the whole IETF that comes with you with it. [00:08:56] Francois: So you, it's the, you have the feeling that webRTC needs all of the, uh, internet protocols that got, uh, created to work Recommendations [00:09:04] Jeremy: And I think probably a lot of web developers, they may hear words like specification or standard, but I believe the, the official term, at least at the W3C, is this recommendation. And so I wonder if you can explain what that means. [00:09:24] Francois: Well. It means it means standard in the end. and that came from industry. That comes from a time where. As many standardization organizations. W3C was created not to be a standardization organization. It was felt that standard was not the right term because we were not a standardization organization. [00:09:45] Francois: So recommend IETF has the same thing. They call it RFC, request for comment, which, you know, stands for nothing in, and yet it's a standard. So W3C was created with the same kind of, uh thing. We needed some other terminology and we call that recommendation. But in the end, that's standard. It's really, uh, how you should see it. [00:10:08] Francois: And one thing I didn't mention when I, uh, introduced the W3C is there are two types of standards in the end, two main categories. There are, the de jure standards and defacto standards, two families. The de jure standards are the ones that are imposed by some kind of regulation. so it's really usually a standard you see imposed by governments, for example. [00:10:29] Francois: So when you look at your electric plug at home, there's some regulation there that says, this plug needs to have these properties. And that's a standard that gets imposed. It's a de jure standard. and then there are defacto standards which are really, uh, specifications that are out there and people agree to use it to implement it. [00:10:49] Francois: And by virtue of being used and implemented and used by everyone, they become standards. the, W3C really is in the, uh, second part. It's a defacto standard. IETF is the same thing. some of our standards are used in, uh, are referenced in regulations now, but, just a, a minority of them, most of them are defacto standards. [00:11:10] Francois: and that's important because that's in the end, it doesn't matter what the specific specification says, even though it's a bit confusing. What matters is that the, what the specifications says matches what implementations actually implement, and that these implementations are used, and are used interoperably across, you know, across browsers, for example, or across, uh, implementations, across users, across usages. [00:11:36] Francois: So, uh, standardization is a, is a lengthy process. The recommendation is the final stage in that, lengthy process. More and more we don't really reach recommendation anymore. If you look at, uh, at groups, uh, because we have another path, let's say we kind of, uh, we can stop at candidate recommendation, which is in theoretically a step before that. [00:12:02] Francois: But then you, you can stay there and, uh, stay there forever and publish new candidate recommendations. Um, uh, later on. What matters again is that, you know, you get this, virtuous feedback loop, uh, with implementers, and usage. [00:12:18] Jeremy: So if the candidate recommendation ends up being implemented by all the browsers, what's ends up being the distinction between a candidate and one that's a normal recommendation. [00:12:31] Francois: So, today it's mostly a process thing. Some groups actually decide to go to rec Some groups decide to stay at candidate rec and there's no formal difference between the, the two. we've made sure we've adopted, adjusted the process so that the important bits that, applied at the recommendation level now apply at the candidate rec level. Royalty free patent access [00:13:00] Francois: And by important things, I mean the patent commitments typically, uh, the patent policy fully applies at the candidate recommendation level so that you get your, protection, the royalty free patent protection that we, we were aiming at. [00:13:14] Francois: Some people do not care, you know, but most of the world still works with, uh, with patents, uh, for good, uh, or bad reasons. But, uh, uh, that's how things work. So we need to make, we're trying to make sure that we, we secure the right set of, um, of patent commitments from the right set of stakeholders. [00:13:35] Jeremy: Oh, so when someone implements a W3C recommendation or a candidate recommendation, the patent holders related to that recommendation, they basically agree to allow royalty-free use of that patent. [00:13:54] Francois: They do the one that were involved in the working group, of course, I mean, we can't say anything about the companies out there that may have patents and uh, are not part of this standardization process. So there's always, It's a remaining risk. but part of the goal when we create a working group is to make sure that, people understand the scope. [00:14:17] Francois: Lawyers look into it, and the, the legal teams that exist at the all the large companies, basically gave a green light saying, yeah, we, we we're pretty confident that we, we know where the patterns are on this particular, this particular area. And we are fine also, uh, letting go of the, the patterns we own ourselves. Implementations are built in parallel with standardization [00:14:39] Jeremy: And I think you had mentioned. What ends up being the most important is that the browser creators implement these recommendations. So it sounds like maybe the distinction between candidate recommendation and recommendation almost doesn't matter as long as you get the end result you want. [00:15:03] Francois: So, I mean, people will have different opinions, uh, in the, in standardization circles. And I mentioned also W3C is working on other kind of, uh, standards. So, uh, in some other areas, the nuance may be more important when we, but when, when you look at specification, that's target, web browsers. we've switched from a model where, specs were developed first and then implemented to a model where specs and implementing implementations are being, worked in parallel. [00:15:35] Francois: This actually relates to the evolution I was mentioning with the WHATWG taking over the HTML and, uh, focusing on the interoperability issues because the starting point was, yeah, we have an HTML 4.01 spec, uh, but it's not interoperable because it, it's not specified, are number of areas that are gray areas, you can implement them differently. [00:15:59] Francois: And so there are interoperable issues. Back to candidate rec actually, the, the, the, the stage was created, if I remember correctly. uh, if I'm, if I'm not wrong, the stage was created following the, uh, IE problem. In the CSS working group, IE6, uh, shipped with some, version of a CSS that was in the, as specified, you know, the spec was saying, you know, do that for the CSS box model. [00:16:27] Francois: And the IE6 was following that. And then the group decided to change, the box model and suddenly IE6 was no longer compliant. And that created a, a huge mess on the, in the history of, uh, of the web in a way. And so the, we, the, the, the, the candidate recommendation sta uh, stage was introduced following that to try to catch this kind of problems. [00:16:52] Francois: But nowadays, again, we, we switch to another model where it's more live. and so we, you, you'll find a number of specs that are not even at candidate rec level. They are at the, what we call a working draft, and they, they are being implemented, and if all goes well, the standardization process follows the implementation, and then you end up in a situation where you have your candidate rec when the, uh, spec ships. [00:17:18] Francois: a recent example would be a web GPU, for example. It, uh, it has shipped in, uh, in, in Chrome shortly before it transition to a candidate rec. But the, the, the spec was already stable. and now it's shipping uh, in, uh, in different browsers, uh, uh, safari, uh, and uh, and uh, and uh, Firefox. And so that's, uh, and that's a good example of something that follows, uh, things, uh, along pretty well. But then you have other specs such as, uh, in the media space, uh, request video frame back, uh, frame, call back, uh, requestVideoFrameCallback() is a short API that allows you to get, you know, a call back whenever the, the browser renders a video frame, essentially. [00:18:01] Francois: And that spec is implemented across browsers. But from a W3C specific, perspective, it does not even exist. It's not on the standardization track. It's still being incubated in what we call a community group, which is, you know, some something that, uh, usually exists before. we move to the, the standardization process. [00:18:21] Francois: So there, there are examples of things where some things fell through the cracks. All the standardization process, uh, is either too early or too late and things that are in spec are not exactly what what got implemented or implementations are too early in the process. We we're doing a better job, at, Not falling into a trap where someone ships, uh, you know, an implementation and then suddenly everything is frozen. You can no longer, change it because it's too late, it shipped. we've tried, different, path there. Um, mentioned CSS, the, there was this kind of vendor prefixed, uh, properties that used to be, uh, the way, uh, browsers were deploying new features without, you know, taking the final name. [00:19:06] Francois: We are trying also to move away from it because same thing. Then in the end, you end up with, uh, applications that have, uh, to duplicate all the properties, the CSS properties in the style sheets with, uh, the vendor prefixes and nuances in the, in what it does in, in the end. [00:19:23] Jeremy: Yeah, I, I think, is that in CSS where you'll see --mozilla or things like that? Why requestVideoFrameCallback doesn't have a formal specification [00:19:30] Jeremy: The example of the request video frame callback. I, I wonder if you have an opinion or, or, or know why that ended up the way it did, where the browsers all implemented it, even though it was still in the incubation stage. [00:19:49] Francois: On this one, I don't have a particular, uh, insights on whether there was a, you know, a strong reason to implement it,without doing the standardization work. [00:19:58] Francois: I mean, there are, it's not, uh, an IPR (Intellectual Property Rights) issue. It's not, uh, something that, uh, I don't think the, the, the spec triggers, uh, you know, problems that, uh, would be controversial or whatever. [00:20:10] Francois: Uh, so it's just a matter of, uh, there was no one's priority, and in the end, you end up with a, everyone's happy. it's, it has shipped. And so now doing the spec work is a bit,why spend time on something that's already shipped and so on, but the, it may still come back at some point with try to, you know, improve the situation. [00:20:26] Jeremy: Yeah, that's, that's interesting. It's a little counterintuitive because it sounds like you have the, the working group and it, it sounds like perhaps the companies or organizations involved, they maybe agreed on how it should work, and maybe that agreement almost made it so that they felt like they didn't need to move forward with the specification because they came to consensus even before going through that. [00:20:53] Francois: In this particular case, it's probably because it's really, again, it's a small, spec. It's just one function call, you know? I mean, they will definitely want a working group, uh, for larger specifications. by the way, actually now I know re request video frame call back. It's because the, the, the final goal now that it's, uh, shipped, is to merge it into, uh, HTML, uh, the HTML spec. [00:21:17] Francois: So there's a, there's an ongoing issue on the, the WHATWG side to integrate request video frame callback. And it's taking some time but see, it's, it's being, it, it caught up and, uh, someone is doing the, the work to, to do it. I had forgotten about this one. Um, [00:21:33] Jeremy: Tension from specification review (horizontal review) [00:21:33] Francois: so with larger specifications, organizations will want this kind of IPR regime they will want commit commitments from, uh, others, on the scope, on the process, on everything. So they will want, uh, a larger, a, a more formal setting, because that's part of how you ensure that things, uh, will get done properly. [00:21:53] Francois: I didn't mention it, but, uh, something we're really, uh, Pushy on, uh, W3C I mentioned we have principles, we have priorities, and we have, uh, specific several, uh, properties at W3C. And one of them is that we we're very strong on horizontal reviews of our specs. We really want them to be reviewed from an accessibility perspective, from an internationalization perspective, from a privacy and security, uh, perspective, and, and, and a technical architecture perspective as well. [00:22:23] Francois: And that's, these reviews are part of the formal process. So you, all specs need to undergo these reviews. And from time to time, that creates tension. Uh, from time to time. It just works, you know. Goes without problem. a recurring issue is that, privacy and security are hard. I mean, it's not an easy problem, something that can be, uh, solved, uh, easily. [00:22:48] Francois: Uh, so there's a, an ongoing tension and no easy way to resolve it, but there's an ongoing tension between, specifying powerful APIs and preserving privacy without meaning, not exposing too much information to applications in the media space. You can think of the media capabilities, API. So the media space is a complicated space. [00:23:13] Francois: Space because of codecs. codecs are typically not relative free. and so browsers decide which codecs they're going to support, which audio and video codecs they, they're going to support and doing that, that creates additional fragmentation, not in the sense that they're not interoperable, but in the sense that applications need to choose which connect they're going to ship to stream to the end user. [00:23:39] Francois: And, uh, it's all the more complicated that some codecs are going to be hardware supported. So you will have a hardware decoder in your, in your, in your laptop or smartphone. And so that's going to be efficient to decode some, uh, some stream, whereas some code are not, are going to be software, based, supported. [00:23:56] Francois: Uh, and that may consume a lot of CPU and a lot of power and a lot of energy in the end. So you, you want to avoid that if you can, uh, select another thing. Even more complex than, codecs have different profiles, uh, lower end profiles higher end profiles with different capabilities, different features, uh, depending on whether you're going to use this or that color space, for example, this or that resolution, whatever. [00:24:22] Francois: And so you want to surface that to web applications because otherwise, they can't. Select, they can't choose, the right codec and the right, stream that they're going to send to the, uh, client devices. And so they're not going to provide an efficient user experience first, and even a sustainable one in terms of energy because they, they're going to waste energy if they don't send the right stream. [00:24:45] Francois: So you want to surface that to application. That's what the media, media capabilities, APIs, provides. Privacy concerns [00:24:51] Francois: Uh, but at the same time, if you expose that information, you end up with ways to fingerprint the end user's device. And that in turn is often used to track users across, across sites, which is exactly what we don't want to have, uh, for privacy reasons, for obvious privacy reasons. [00:25:09] Francois: So you have to balance that and find ways to, uh, you know, to expose. Capabilities without, without necessarily exposing them too much. Uh, [00:25:21] Jeremy: Can you give an example of how some of those discussions went? Like within the working group? Who are the companies or who are the organizations that are arguing for We shouldn't have this capability because of the privacy concerns, or [00:25:40] Francois: In a way all of the companies, have a vision of, uh, of privacy. I mean, the, you will have a hard time finding, you know, members saying, I don't care about privacy. I just want the feature. Uh, they all have privacy in mind, but they may have a different approach to privacy. [00:25:57] Francois: so if you take, uh, let's say, uh, apple and Google would be the, the, I guess the perfect examples in that, uh, in that space, uh, Google will have a, an approach that is more open-ended thing. The, the user agents has this, uh, should check what the, the, uh, given site is doing. And then if it goes beyond, you know, some kind of threshold, they're going to say, well, okay, well, we'll stop exposing data to that, to that, uh, to that site. [00:26:25] Francois: So that application. So monitor and react in a way. apple has a more, uh, you know, has a stricter view on, uh, on privacy, let's say. And they will say, no, we, the, the, the feature must not exist in the first place. Or, but that's, I mean, I guess, um, it's not always that extreme. And, uh, from time to time it's the opposite. [00:26:45] Francois: You will have, uh, you know, apple arguing in one way, uh, which is more open-ended than the, uh, than, uh, than Google, for example. And they are not the only ones. So in working groups, uh, you will find the, usually the implementers. Uh, so when we talk about APIs that get implemented in browsers, you want the core browsers to be involved. [00:27:04] Francois: Uh, otherwise it's usually not a good sign for, uh, the success of the, uh, of the technology. So in practice, that means Apple, uh, Microsoft, Mozilla which one did I forget? [00:27:15] Jeremy: Google. [00:27:16] Francois: I forgot Google. Of course. Thank you. that's, uh, that the, the core, uh, list of participants you want to have in any, uh, group that develops web standards targeted at web browsers. Who participates in working groups and how much power do they have? [00:27:28] Francois: And then on top of that, you want, organizations and people who are directly going to use it, either because they, well the content providers. So in media, for example, if you look at the media working group, you'll see, uh, so browser vendors, the ones I mentioned, uh, content providers such as the BBC or Netflix. [00:27:46] Francois: Chip set vendors would, uh, would be there as well. Intel, uh, Nvidia again, because you know, there's a hardware decoding in there and encoding. So media is, touches on, on, uh, on hardware, uh, device manufacturer in general. You may, uh, I think, uh, I think Sony is involved in the, in the media working group, for example. [00:28:04] Francois: and these companies are usually less active in the spec development. It depends on the groups, but they're usually less active because the ones developing the specs are usually the browser again, because as I mentioned, we develop the specs in parallel to browsers implementing it. So they have the. [00:28:21] Francois: The feedback on how to formulate the, the algorithms. and so that's this collection of people who are going to discuss first within themselves. W3C pushes for consensual dis decisions. So we hardly take any votes in the working groups, but from time to time, that's not enough. [00:28:41] Francois: And there may be disagreements, but let's say there's agreement in the group, uh, when the spec matches. horizontal review groups will look at the specs. So these are groups I mentioned, accessibility one, uh, privacy, internationalization. And these groups, usually the participants are, it depends. [00:29:00] Francois: It can be anything. It can be, uh, the same companies. It can be, but usually different people from the same companies. But it the, maybe organizations with a that come from very, a very different angle. And that's a good thing because that means the, you know, you enlarge the, the perspectives on your, uh, on the, on the technology. [00:29:19] Francois: and you, that's when you have a discussion between groups, that takes place. And from time to time it goes well from time to time. Again, it can trigger issues that are hard to solve. and the W3C has a, an escalation process in case, uh, you know, in case things degenerate. Uh, starting with, uh, the notion of formal objection. [00:29:42] Jeremy: It makes sense that you would have the, the browser. Vendors and you have all the different companies that would use that browser. All the different horizontal groups like you mentioned, the internationalization, accessibility. I would imagine that you were talking about consensus and there are certain groups or certain companies that maybe have more say or more sway. [00:30:09] Jeremy: For example, if you're a browser, manufacturer, your Google. I'm kind of curious how that works out within the working group. [00:30:15] Francois: Yes, it's, I guess I would be lying if I were saying that, uh, you know, all companies are strictly equal in a, in a, in a group. they are from a process perspective, I mentioned, you know, different membership fees with were design, special specific ethos so that no one could say, I'm, I'm putting in a lot of money, so you, you need to re you need to respect me, uh, and you need to follow what I, what I want to, what I want to do. [00:30:41] Francois: at the same time, if you take a company like, uh, like Google for example, they send, hundreds of engineers to do standardization work. That's absolutely fantastic because that means work progresses and it's, uh, extremely smart people. So that's, uh, that's really a pleasure to work with, uh, with these, uh, people. [00:30:58] Francois: But you need to take a step back and say, well, the problem is. Defacto that gives them more power just by virtue of, uh, injecting more resources into it. So having always someone who can respond to an issue, having always someone, uh, editing a spec defacto that give them more, uh, um, more say on the, on the directions that, get forward. [00:31:22] Francois: And on top of that, of course, they have the, uh, I guess not surprisingly, the, the browser that is, uh, used the most, currently, on the market so there's a little bit of a, the, the, we, we, we, we try very hard to make sure that, uh, things are balanced. it's not a perfect world. [00:31:38] Francois: the the role of the team. I mean, I didn't talk about the role of the team, but part of it is to make sure that. Again, all perspectives are represented and that there's not, such a, such big imbalance that, uh, that something is wrong and that we really need to look into it. so making sure that anyone, if they have something to say, make making sure that they are heard by the rest of the group and not dismissed. [00:32:05] Francois: That usually goes well. There's no problem with that. And again, the escalation process I mentioned here doesn't make any, uh, it doesn't make any difference between, uh, a small player, a large player, a big player, and we have small companies raising formal objections against some of our aspects that happens, uh, all large ones. [00:32:24] Francois: But, uh, that happens too. There's no magical solution, I guess you can tell it by the way. I, uh, I don't know how to formulate the, the process more. It's a human process, and that's very important that it remains a human process as well. [00:32:41] Jeremy: I suppose the role of, of staff and someone in your position, for example, is to try and ensure that these different groups are, are heard and it isn't just one group taking control of it. [00:32:55] Francois: That's part of the role, again, is to make sure that, uh, the, the process is followed. So the, I, I mean, I don't want to give the impression that the process controls everything in the groups. I mean, the, the, the groups are bound by the process, but the process is there to catch problems when they arise. [00:33:14] Francois: most of the time there are no problems. It's just, you know, again, participants talking to each other, talking with the rest of the community. Most of the work happens in public nowadays, in any case. So the groups work in public essentially through asynchronous, uh, discussions on GitHub repositories. [00:33:32] Francois: There are contributions from, you know, non group participants and everything goes well. And so the process doesn't kick in. You just never say, eh, no, you didn't respect the process there. You, you closed the issue. You shouldn't have a, it's pretty rare that you have to do that. Uh, things just proceed naturally because they all, everyone understands where they are, why, what they're doing, and why they're doing it. [00:33:55] Francois: we still have a role, I guess in the, in the sense that from time to time that doesn't work and you have to intervene and you have to make sure that,the, uh, exception is caught and, uh, and processed, uh, in the right way. Discussions are public on github [00:34:10] Jeremy: And you said this process is asynchronous in public, so it sounds like someone, I, I mean, is this in GitHub issues or how, how would somebody go and, and see what the results of [00:34:22] Francois: Yes, there, there are basically a gazillion of, uh, GitHub repositories under the, uh, W3C, uh, organization on GitHub. Most groups are using GitHub. I mean, there's no, it's not mandatory. We don't manage any, uh, any tooling. But the factors that most, we, we've been transitioning to GitHub, uh, for a number of years already. [00:34:45] Francois: Uh, so that's where the work most of the work happens, through issues, through pool requests. Uh, that's where. people can go and raise issues against specifications. Uh, we usually, uh, also some from time to time get feedback from developers and countering, uh, a bug in a particular implementations, which we try to gently redirect to, uh, the actual bug trackers because we're not responsible for the respons implementations of the specs unless the spec is not clear. [00:35:14] Francois: We are responsible for the spec itself, making sure that the spec is clear and that implementers well, understand how they should implement something. Why the W3C doesn't specify a video or audio codec [00:35:25] Jeremy: I can see how people would make that mistake because they, they see it's the feature, but that's not the responsibility of the, the W3C to implement any of the specifications. Something you had mentioned there's the issue of intellectual property rights and how when you have a recommendation, you require the different organizations involved to make their patents available to use freely. [00:35:54] Jeremy: I wonder why there was never any kind of, recommendation for audio or video codecs in browsers since you have certain ones that are considered royalty free. But, I believe that's never been specified. [00:36:11] Francois: At W3C you mean? Yes. we, we've tried, I mean, it's not for lack of trying. Um, uh, we've had a number of discussions with, uh, various stakeholders saying, Hey, we, we really need, an audio or video code for our, for the web. the, uh, png PNG is an example of a, um, an image format which got standardized at W3C and it got standardized at W3C similar reasons. There had to be a royalty free image format for the web, and there was none at the time. of course, nowadays, uh, jpeg, uh, and gif or gif, whatever you call it, are well, you know, no problem with them. But, uh, um, that at the time P PNG was really, uh, meant to address this issue and it worked for PNG for audio and video. [00:37:01] Francois: We haven't managed to secure, commitments by stakeholders. So willingness to do it, so it's not, it's not lack of willingness. We would've loved to, uh, get, uh, a royalty free, uh, audio codec, a royalty free video codec again, audio and video code are extremely complicated because of this. [00:37:20] Francois: not only because of patterns, but also because of the entire business ecosystem that exists around them for good reasons. You, in order for a, a codec to be supported, deployed, effective, it really needs, uh, it needs to mature a lot. It needs to, be, uh, added to at a hardware level, to a number of devices, capturing devices, but also, um, uh, uh, of course players. [00:37:46] Francois: And that takes a hell of a lot of time and that's why you also enter a number of business considerations with business contracts between entities. so I'm personally, on a personal level, I'm, I'm pleased to see, for example, the Alliance for Open Media working on, uh, uh, AV1, uh, which is. At least they, uh, they wanted to be royalty free and they've been adopting actually the W3C patent policy to do this work. [00:38:11] Francois: So, uh, we're pleased to see that, you know, they've been adopting the same process and same thing. AV1 is not yet at the same, support stage, as other, codecs, in the world Yeah, I mean in devices. There's an open question as what, what are we going to do, uh, in the future uh, with that, it's, it's, it's doubtful that, uh, the W3C will be able to work on a, on a royalty free audio, codec or royalty free video codec itself because, uh, probably it's too late now in any case. [00:38:43] Francois: but It's one of these angles in the, in the web platform where we wish we had the, uh, the technology available for, for free. And, uh, it's not exactly, uh, how things work in practice.I mean, the way codecs are developed remains really patent oriented. [00:38:57] Francois: and you will find more codecs being developed. and that's where geopolitics can even enter the, the, uh, the play. Because, uh, if you go to China, you will find new codecs emerging, uh, that get developed within China also, because, the other codecs come mostly from the US so it's a bit of a problem and so on. [00:39:17] Francois: I'm not going to enter details and uh, I would probably say stupid things in any case. Uh, but that, uh, so we continue to see, uh, emerging codecs that are not royalty free, and it's probably going to remain the case for a number of years. unfortunately, unfortunately, from a W3C perspective and my perspective of course. [00:39:38] Jeremy: There's always these new, formats coming out and the, rate at which they get supported in the browser, even on a per browser basis is, is very, there can be a long time between, for example, WebP being released and a browser supporting it. So, seems like maybe we're gonna be in that situation for a while where the codecs will come out and maybe the browsers will support them. Maybe they won't, but the, the timeline is very uncertain. Digital Rights Management (DRM) and Media Source Extensions [00:40:08] Jeremy: Something you had, mentioned, maybe this was in your, email to me earlier, but you had mentioned that some of these specifications, there's, there's business considerations like with, digital rights management and, media source extensions. I wonder if you could talk a little bit about maybe what media source extensions is and encrypted media extensions and, and what the, the considerations or challenges are there. [00:40:33] Francois: I'm going to go very, very quickly over the history of a, video and audio support on the web. Initially it was supported through plugins. you are maybe too young to, remember that. But, uh, we had extensions, added to, uh, a realplayer. [00:40:46] Francois: This kind of things flash as well, uh, supporting, uh, uh, videos, in web pages, but it was not provided by the web browsers themselves. Uh, then HTML5 changed the, the situation. Adding these new tags, audio and video, but that these tags on this, by default, support, uh, you give them a resources, a resource, like an image as it's an audio or a video file. [00:41:10] Francois: They're going to download this, uh, uh, video file or audio file, and they're going to play it. That works well. But as soon as you want to do any kind of real streaming, files are too large and to stream, to, to get, you know, to get just a single fetch on, uh, on them. So you really want to stream them chunk by chunk, and you want to adapt the resolution at which you send the stream based on real time conditions of the user's network. [00:41:37] Francois: If there's plenty of bandwidth you want to send the user, the highest possible resolution. If there's a, some kind of hiccup temporary in the, in the network, you really want to lower the resolution, and that's called adaptive streaming. And to get adaptive streaming on the web, well, there are a number of protocols that exist. [00:41:54] Francois: Same thing. Some many of them are proprietary and actually they remain proprietary, uh, to some extent. and, uh, some of them are over http and they are the ones that are primarily used in, uh, in web contexts. So DASH comes to mind, DASH for Dynamic Adaptive streaming over http. HLS is another one. Uh, initially developed by Apple, I believe, and it's, uh, HTTP live streaming probably. Exactly. And, so there are different protocols that you can, uh, you can use. Uh, so the goal was not to standardize these protocols because again, there were some proprietary aspects to them. And, uh, same thing as with codecs. [00:42:32] Francois: There was no, well, at least people wanted to have the, uh, flexibility to tweak parameters, adaptive streaming parameters the way they wanted for different scenarios. You may want to tweak the parameters differently. So they, they needed to be more flexibility on top of protocols not being truly available for use directly and for implementation directly in browsers. [00:42:53] Francois: It was also about providing applications with, uh, the flexibility they would need to tweak parameters. So media source extensions comes into play for exactly that. Media source extensions is really about you. The application fetches chunks of its audio and video stream the way it wants, and with the parameters it wants, and it adjusts whatever it wants. [00:43:15] Francois: And then it feeds that into the, uh, video or audio tag. and the browser takes care of the rest. So it's really about, doing, you know, the adaptive streaming. let applications do it, and then, uh, let the user agent, uh, the browser takes, take care of the rendering itself. That's media source extensions. [00:43:32] Francois: Initially it was pushed by, uh, Netflix. They were not the only ones of course, but there, there was a, a ma, a major, uh, proponent of this, uh, technical solution, because they wanted, uh, they, uh, they were, expanding all over the world, uh, with, uh, plenty of native, applications on all sorts of, uh, of, uh, devices. [00:43:52] Francois: And they wanted to have a way to stream content on the web as well. both for both, I guess, to expand to, um, a new, um, ecosystem, the web, uh, providing new opportunities, let's say. But at the same time also to have a fallback, in case they, because for native support on different platforms, they sometimes had to enter business agreements with, uh, you know, the hardware manufacturers, the whatever, the, uh, service provider or whatever. [00:44:19] Francois: and so that was a way to have a full back. That kind of work is more open, in case, uh, things take some time and so on. So, and they probably had other reasons. I mean, I'm not, I can't speak on behalf of Netflix, uh, on others, but they were not the only ones of course, uh, supporting this, uh, me, uh, media source extension, uh, uh, specification. [00:44:42] Francois: and that went kind of, well, I think it was creating 2011. I mean, the, the work started in 2011 and the recommendation was published in 2016, which is not too bad from a standardization perspective. It means only five years, you know, it's a very short amount of time. Encrypted Media Extensions [00:44:59] Francois: At the same time, and in parallel and complement to the media source extension specifications, uh, there was work on the encrypted media extensions, and here it was pushed by the same proponent in a way because they wanted to get premium content on the web. [00:45:14] Francois: And by premium content, you think of movies and, uh. These kind of beasts. And the problem with the, I guess the basic issue with, uh, digital asset such as movies, is that they cost hundreds of millions to produce. I mean, some cost less of course. And yet it's super easy to copy them if you have a access to the digital, uh, file. [00:45:35] Francois: You just copy and, uh, and that's it. Piracy uh, is super easy, uh, to achieve. It's illegal of course, but it's super easy to do. And so that's where the different legislations come into play with digital right management. Then the fact is most countries allow system that, can encrypt content and, uh, through what we call DRM systems. [00:45:59] Francois: so content providers, uh, the, the ones that have movies, so the studios here more, more and more, and Netflix is one, uh, one of the studios nowadays. Um, but not only, not only them all major studios will, uh, would, uh, push for, wanted to have something that would allow them to stream encrypted content, encrypted audio and video, uh, mostly video, to, uh, to web applications so that, uh, you. [00:46:25] Francois: Provide the movies, otherwise, they, they are just basically saying, and sorry, but, uh, this premium content will never make it to the web because there's no way we're gonna, uh, send it in clear, to, uh, to the end user. So Encrypting media extensions is, uh, is an API that allows to interface with, uh, what's called the content decryption module, CDM, uh, which itself interacts with, uh, the DR DRM systems that, uh, the browser may, may or may not support. [00:46:52] Francois: And so it provides a way for an application to receive encrypted content, pass it over get the, the, the right keys, the right license keys from a whatever system actually. Pass that logic over to the, and to the user agent, which passes, passes it over to, uh, the CDM system, which is kind of black box in, uh, that does its magic to get the right, uh, decryption key and then the, and to decrypt the content that can be rendered. [00:47:21] Francois: The encrypted media extensions triggered a, a hell of a lot of, uh, controversy. because it's DRM and DRM systems, uh, many people, uh, uh, things should be banned, uh, especially on the web because the, the premise of the web is that the, the user has trusts, a user agent. The, the web browser is called the user agent in all our, all our specifications. [00:47:44] Francois: And that's, uh, that's the trust relationship. And then they interact with a, a content provider. And so whatever they do with the content is their, I guess, actually their problem. And DRM introduces a third party, which is, uh, there's, uh, the, the end user no longer has the control on the content. [00:48:03] Francois: It has to rely on something else that, Restricts what it can achieve with the content. So it's, uh, it's not only a trust relationship with its, uh, user agents, it's also with, uh, with something else, which is the content provider, uh, in the end, the one that has the, uh, the license where provides the license. [00:48:22] Francois: And so that's, that triggers, uh, a hell of a lot of, uh, of discussions in the W3C degenerated, uh, uh, into, uh, formal objections being raised against the specification. and that escalated to, to the, I mean, at all leverage it. It's, it's the, the story in, uh, W3C that, um, really, uh, divided the membership into, opposed camps in a way, if you, that's was not only year, it was not really 50 50 in the sense that not just a huge fights, but the, that's, that triggered a hell of a lot of discussions and a lot of, a lot of, uh, of formal objections at the time. [00:49:00] Francois: Uh, we were still, From a governance perspective, interestingly, um, the W3C used to be a dictatorship. It's not how you should formulate it, of course, and I hope it's not going to be public, this podcast. Uh, but the, uh, it was a benevolent dictatorship. You could see it this way in the sense that, uh, the whole process escalated to one single person was, Tim Burners Lee, who had the final say, on when, when none of the other layers, had managed to catch and to resolve, a conflict. [00:49:32] Francois: Uh, that has hardly ever happened in, uh, the history of the W3C, but that happened to the two for EME, for encrypted media extensions. It had to go to the, uh, director level who, uh, after due consideration, uh, decided to, allow the EME to proceed. and that's why we have a, an EME, uh, uh, standard right now, but still re it remains something on the side. [00:49:56] Francois: EME we're still, uh, it's still in the scope of the media working group, for example. but the scope, if you look at the charter of the working group, we try to scope the, the, the, the, the updates we can make to the specification, uh, to make sure that we don't reopen, reopen, uh, a can of worms, because, well, it's really a, a topic that triggers friction for good and bad reasons again. [00:50:20] Jeremy: And when you talk about the media source extensions, that is the ability to write custom code to stream video in whatever way you want. You mentioned, the MPEG-DASH and http live streaming. So in that case, would that be the developer gets to write that code in JavaScript that's executed by the browser? [00:50:43] Francois: Yep, that's, uh, that would be it. and then typically, I guess the approach nowadays is more and more to develop low level APIs into W3C or web in, in general, I guess. And to let, uh. Libraries emerge that are going to make lives of a, a developer, uh, easier. So for MPEG DASH, we have the DASH.js, which does a fantastic job at, uh, at implementing the complexity of, uh, of adaptive streaming. [00:51:13] Francois: And you just, you just hook it into your, your workflow. And that's, uh, and that's it. Encrypted Media Extensions are closed source [00:51:20] Jeremy: And with the encrypted media extensions I'm trying to picture how those work and how they work differently. [00:51:28] Francois: Well, it's because the, the, the, the key architecture is that the, the stream that you, the stream that you may assemble with a media source extensions, for example. 'cause typically they, they're used in collaboration. When you hook the, hook it into the video tag, you also. Call EME and actually the stream goes to EME. [00:51:49] Francois: And when it goes to EME, actually the user agent hands the encrypted stream. You're still encrypted at this time. Uh, encrypted, uh, stream goes to the CDM content decryption module, and that's a black box well, it has some black, black, uh, black box logic. So it's not, uh, even if you look at the chromium source code, for example, you won't see the implementation of the CDM because it's a, it's a black box, so it's not part of the browser se it's a sand, it's sandboxed, it's execution sandbox. [00:52:17] Francois: That's, uh, the, the EME is kind of unique in, in this way where the, the CDM is not allowed to make network requests, for example, again, for privacy reasons. so anyway, the, the CDM box has the logic to decrypt the content and it hands it over, and then it depends, it depends on the level of protection you. [00:52:37] Francois: You need or that the system supports. It can be against software based protection, in which case actually, a highly motivated, uh, uh, uh, attacker could, uh, actually get access to the decoded stream, or it can be more hardware protected, in which case actually the, it goes to the, uh, to your final screen. [00:52:58] Francois: But it goes, it, it goes through the hardware in a, in a mode that the US supports in a mode that even the user agent doesn't have access to it. So it doesn't, it can't even see the pixels that, uh, gets rendered on the screen. There are, uh, several other, uh, APIs that you could use, for example, to take a screenshot of your, of your application and so on. [00:53:16] Francois: And you cannot apply them to, uh, such content because they're just gonna return a black box. again, because the user agent itself does not see the, uh, the pixels, which is exactly what you want with encrypted content. [00:53:29] Jeremy: And the, the content decryption module, it's, if I understand correctly, it's something that's shipped with the browsers, but you were saying is if you were to look at the public source code of Chromium or of Firefox, you would not see that implementation. Content Decryption Module (Widevine, PlayReady) [00:53:47] Francois: True. I mean, the, the, um, the typical examples are, uh, uh, widevine, so wide Vine. So interestingly, uh, speaking in theory, these, uh, systems could have been provided by anyone in practice. They've been provided by the browser vendors themselves. So Google has Wide Vine. Uh, Microsoft has something called PlayReady. Apple uh, the name, uh, escapes my, uh, sorry. They don't have it on top of my mind. So they, that's basically what they support. So they, they also own that code, but in a way they don't have to. And Firefox actually, uh, they, uh, don't, don't remember which one, they support among these three. but, uh, they, they don't own that code typically. [00:54:29] Francois: They provide a wrapper around, around it. Yeah, that's, that's exactly the, the crux of the, uh, issue that, people have with, uh, with DRMs, right? It's, uh, the fact that, uh, suddenly you have a bit of code running there that is, uh, that, okay, you can send box, but, uh, you cannot inspect and you don't have, uh, access to its, uh, source code. [00:54:52] Jeremy: That's interesting. So the, almost the entire browser is open source, but if you wanna watch a Netflix movie for example, then you, you need to, run this, this CDM, in addition to just the browser code. I, I think, you know, we've kind of covered a lot. Documenting what's available in browsers for developers [00:55:13] Jeremy: I wonder if there's any other examples or anything else you thought would be important to mention in, in the context of the W3C. [00:55:23] Francois: There, there's one thing which, uh, relates to, uh, activities I'm doing also at W3C. Um. Here, we've been talking a lot about, uh, standards and, implementations in browsers, but there's also, uh, adoption of these browser, of these technology standards by developers in general and making sure that developers are aware of what exists, making sure that they understand what exists and one of the, key pain points that people, uh. [00:55:54] Francois: Uh, keep raising on, uh, the web platform is first. Well, the, the, the web platform is unique in the sense that there are different implementations. I mean, if you, [00:56:03] Francois: Uh, anyway, there are different, uh, context, different run times where there, there's just one provided by the company that owns the, uh, the, the, the system. The web platform is implemented by different, uh, organizations. and so you end up the system where no one, there's what's in the specs is not necessarily supported. [00:56:22] Francois: And of course, MDN tries, uh, to document what's what's supported, uh, thoroughly. But for MDN to work, there's a hell of a lot of needs for data that, tracks browser support. And this, uh, this data is typically in a project called the Browser Compat Data, BCD owned by, uh, MDN as well. But, the Open Web Docs collective is a, uh, is, uh, the one, maintaining that, uh, that data under the hoods. [00:56:50] Francois: anyway, all of that to say that, uh, to make sure that, we track things beyond work on technical specifications, because if you look at it from W3C perspective, life ends when the spec reaches standards, uh, you know, candidate rec or rec, you could just say, oh, done with my work. but that's not how things work. [00:57:10] Francois: There's always, you need the feedback loop and, in order to make sure that developers get the information and can provide the, the feedback that standardization can benefit from and browser vendors can benefit from. We've been working on a project called web Features with browser vendors mainly, and, uh, a few of the folks and MDN and can I use and different, uh, different people, to catalog, the web in terms of features that speak to developers and from that catalog. [00:57:40] Francois: So it's a set of, uh, it's a set of, uh, feature IDs with a feature name and feature description that say, you know, this is how developers would, uh, understand, uh, instead of going too fine grained in terms of, uh, there's this one function call that does this because that's where you, the, the kind of support data you may get from browser data and MDN initially, and having some kind of a coarser grained, uh, structure that says these are the, features that make sense. [00:58:09] Francois: They talk to developers. That's what developers talk about, and that's the info. So the, we need to have data on these particular features because that's how developers are going approach the specs. Uh. and from that we've derived the notion of baseline badges that you have, uh, are now, uh, shown on MDN on can I use and integrated in, uh, IDE tool, IDE Tools such as visual, visual studio, and, uh, uh, libraries, uh, linked, some linters have started to, um, to integrate that data. [00:58:41] Francois: Uh, so, the way it works is, uh, we've been mapping these coarser grained features to BCDs finer grained support data, and from there we've been deriving a kind of a, a batch that says, yeah, this, this feature is implemented well, has limited availability because it's only implemented in one or two browsers, for example. [00:59:07] Francois: It's, newly available because. It was implemented. It's been, it's implemented across the main browser vendor, um, across the main browsers that people use. But it's recent, and widely available, which we try to, uh, well, there's been lots of discussion in the, in the group to, uh, come up with a definition which essentially ends up being 30 months after, a feature become, became newly available. [00:59:34] Francois: And that's when, that's the time it takes for the, for the versions of the, the different versions of the browser to propagate. Uh, because you, it's not because there's a new version of a, of a browser that, uh, people just, Ima immediately, uh, get it. So it takes a while, to propagate, uh, across the, uh, the, the user, uh, user base. [00:59:56] Francois: And so the, the goal is to have a, a, a signal that. Developers can rely on saying, okay, well it's widely available so I can really use that feature. And of course, if that doesn't work, then we need to know about it. And so we are also working with, uh, people doing so developer surveys such as state of, uh, CSS, state of HTML, state of JavaScript. [01:00:15] Francois: That's I guess, the main ones. But also we are also running, uh, MDN short surveys with the MDN people to gather feedback on. On the, on these same features, and to feed the loop and to, uh, to complete the loop. and these data is also used by, internally, by browser vendors to inform, prioritization process, their prioritization process, and typically as part of the interop project that they're also running, uh, on the site [01:00:43] Francois: So a, a number of different, I've mentioned, uh, I guess a number of different projects, uh, coming along together. But that's the goal is to create links, across all of these, um, uh, ongoing projects with a view to integrating developers, more, and gathering feedback as early as possible and inform decision. [01:01:04] Francois: We take at the standardization level that can affect the, the lives of the developers and making sure that it's, uh, it affects them in a, in a positive way. [01:01:14] Jeremy: just trying to understand, 'cause you had mentioned that there's the web features and the baseline, and I was, I was trying to picture where developers would actually, um, see these things. And it sounds like from what you're saying is W3C comes up with what stage some of these features are at, and then developers would end up seeing it on MDN or, or some other site. [01:01:37] Francois: So, uh, I'm working on it, but that doesn't mean it's a W3C thing. It's a, it's a, again, it's a, we have different types of group. It's a community group, so it's the Web DX Community group at W3C, which means it's a community owned thing. so that's why I'm mentioning a working with a representative from, and people from MDN people, from open Web docs. [01:02:05] Francois: so that's the first point. The second point is, so it's, indeed this data is now being integrated. If you, and you look, uh, you'll, you'll see it in on top of the MDN pages on most of them. If you look at, uh, any kind of feature, you'll see a, a few logos, uh, a baseline banner. and then can I use, it's the same thing. [01:02:24] Francois: You're going to get a baseline, banner. It's more on, can I use, and it's meant to capture the fact that the feature is widely available or if you may need to pay attention to it. Of course, it's a simplification, and the goal is not to the way it's, the way the messaging is done to developers is meant to capture the fact that, they may want to look, uh, into more than just this, baseline status, because. [01:02:54] Francois: If you take a look at web platform tests, for example, and if you were to base your assessment of whether a feature is supported based on test results, you'll end up saying the web platform has no supported technology because there are absolutely no API that, uh, where browsers pass 100% of the, of the, of the test suite. [01:03:18] Francois: There may be a few of them, I don't know. But, there's a simplification in the, in the process when a feature is, uh, set to be baseline, there may be more things to look at nevertheless, but it's meant to provide a signal that, uh, still developers can rely on their day-to-day, uh, lives. [01:03:36] Francois: if they use the, the feature, let's say, as a reasonably intended and not, uh, using to advance the logic. [01:03:48] Jeremy: I see. Yeah. I'm looking at one of the pages on MDN right now, and I can see at the top there's the, the baseline and it, it mentions that this feature works across many browsers and devices, and then they say how long it's been available. And so that's a way that people at a glance can, can tell, which APIs they can use. [01:04:08] Francois: it also started, uh, out of a desire to summarize this, uh, browser compatibility table that you see at the end of the page of the, the bottom of the page in on MDN. but there are where developers were saying, well, it's, it's fine, but it's, it goes too much into detail. So we don't know in the end, can we, can we use that feature or can we, can we not use that feature? [01:04:28] Francois: So it's meant as a informed summary of, uh, of, of that it relies on the same data again. and more importantly, we're beyond MDN, we're working with tools providers to integrate that as well. So I mentioned the, uh, visual Studio is one of them. So recently they shipped a new version where when you use a feature, you can, you can have some contextual, uh. [01:04:53] Francois: A menu that tells you, yeah, uh, that's fine. You, this CSS property, you can, you can use it, it's widely available or be aware this one is limited Availability only, availability only available in Firefox or, or Chrome or Safari work kit, whatever. [01:05:08] Jeremy: I think that's a good place to wrap it up, if people want to learn more about the work you're doing or learn more about sort of this whole recommendations process, where, where should they head? [01:05:23] Francois: Generally speaking, we're extremely open to, uh, people contributing to the W3C. and where should they go if they, it depends on what they want. So I guess the, the in usually where, how things start for someone getting involved in the W3C is that they have some
Polletno poročilo o smernicah zlonamerne programske opreme in ranljivostih kaže na jasno prevlado državnih akterjev, ki kibernetske napade uporabljajo za strateške in geopolitične cilje. Klasične kriminalne združbe pa izkoriščajo različne ranljivosti predvsem za izsiljevalske napade, krajo podatkov in goljufije. Njihove metode so manj prefinjene od kibernetskih operacij, v ozadju katerih so države, so pa bolj množične. Kako odkrivati te napade, jih preiskovati in se zavarovati pred njimi, v tokratnem Studiu ob 17ih. Gostje: Tanja Piškur, Zveza potrošnikov Slovenije; Uroš Svete, direktor vladnega urada za informacijsko varnost; Gorazd Božič, direktor SI-CERTA; David Gracer, kriminalistični inšpektor v Upravi kriminalistične policije na GPU. Avtor oddaje Robert Škrjanc.
Tonight's questions: - Did Gears of War: Reloaded flop on PS5? - When will Valve release a Steam Deck 2? - Will Ghost of Yotei sell well? - Why is Borderlands 4 poorly optimized on PC? - What do you look for in a GPU? - Does Nvidia have a monopoly on GPUs? Thanks as always to Shawn Daley for our intro and outro music. Follow him on Soundcloud: https://soundcloud.com/shawndaley Where to find Throwdown Show: Website: https://audioboom.com/channels/5030659 Twitch: https://www.twitch.tv/throwdownshow Twitter: https://twitter.com/ThrowdownShow YouTube: https://www.youtube.com/throwdownshow Discord: https://discord.gg/fdBXWHT Twitter list: https://twitter.com/i/lists/1027719155800317953
Jacob Ward of The Rip Current podcast and newsletter joins Mikah Sargent this week! The impact that generative AI is having on energy and our climate. The privacy and social issues around AI wearables. And everything that was announced at Apple's 'Awe Dropping' event. Jacob shares a paper published recently that covered generative AI and how the massive use of GPU energy is causing concerns about its impact on the climate. Mikah talks about a new wearable AI companion device called Friend and how these always-listening devices present privacy challenges for not just others around the user but also for the company itself. And Zac Hall of 9to5Mac was at Apple's 'Awe Dropping' event this past Tuesday and was fortunate to get his hands on the new hardware the company announced. He shares his initial thoughts on the new AirPods Pro 3 and iPhone Air! Hosts: Mikah Sargent and Jacob Ward Guest: Zac Hall Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: threatlocker.com for Tech News Weekly pantheon.io uscloud.com cachefly.com/twit
Jacob Ward of The Rip Current podcast and newsletter joins Mikah Sargent this week! The impact that generative AI is having on energy and our climate. The privacy and social issues around AI wearables. And everything that was announced at Apple's 'Awe Dropping' event. Jacob shares a paper published recently that covered generative AI and how the massive use of GPU energy is causing concerns about its impact on the climate. Mikah talks about a new wearable AI companion device called Friend and how these always-listening devices present privacy challenges for not just others around the user but also for the company itself. And Zac Hall of 9to5Mac was at Apple's 'Awe Dropping' event this past Tuesday and was fortunate to get his hands on the new hardware the company announced. He shares his initial thoughts on the new AirPods Pro 3 and iPhone Air! Hosts: Mikah Sargent and Jacob Ward Guest: Zac Hall Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: threatlocker.com for Tech News Weekly pantheon.io uscloud.com cachefly.com/twit
Jacob Ward of The Rip Current podcast and newsletter joins Mikah Sargent this week! The impact that generative AI is having on energy and our climate. The privacy and social issues around AI wearables. And everything that was announced at Apple's 'Awe Dropping' event. Jacob shares a paper published recently that covered generative AI and how the massive use of GPU energy is causing concerns about its impact on the climate. Mikah talks about a new wearable AI companion device called Friend and how these always-listening devices present privacy challenges for not just others around the user but also for the company itself. And Zac Hall of 9to5Mac was at Apple's 'Awe Dropping' event this past Tuesday and was fortunate to get his hands on the new hardware the company announced. He shares his initial thoughts on the new AirPods Pro 3 and iPhone Air! Hosts: Mikah Sargent and Jacob Ward Guest: Zac Hall Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: threatlocker.com for Tech News Weekly pantheon.io uscloud.com cachefly.com/twit
Episode 81: We're back! Lots to discuss in this video, including YouTube weirdness, the future of AMD and Intel's CPU platforms, the good old CPU core debate, upcoming GPU rumors and more.CHAPTERS00:00 - Intro03:13 - Our YouTube views are down, this is what the stats say31:14 - Zen 7 on AM5 and Intel's competing platform54:13 - How important is platform longevity?1:07:58 - Six core CPUs are still powerful for gaming1:17:27 - Will Intel make an Arc B770?1:26:22 - No RTX Super any time soon1:29:14 - 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.
Jacob Ward of The Rip Current podcast and newsletter joins Mikah Sargent this week! The impact that generative AI is having on energy and our climate. The privacy and social issues around AI wearables. And everything that was announced at Apple's 'Awe Dropping' event. Jacob shares a paper published recently that covered generative AI and how the massive use of GPU energy is causing concerns about its impact on the climate. Mikah talks about a new wearable AI companion device called Friend and how these always-listening devices present privacy challenges for not just others around the user but also for the company itself. And Zac Hall of 9to5Mac was at Apple's 'Awe Dropping' event this past Tuesday and was fortunate to get his hands on the new hardware the company announced. He shares his initial thoughts on the new AirPods Pro 3 and iPhone Air! Hosts: Mikah Sargent and Jacob Ward Guest: Zac Hall Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: threatlocker.com for Tech News Weekly pantheon.io uscloud.com cachefly.com/twit
This week on The Nerd Chat:- Battlefield 6 begins testing a battle royale mode- The best selling PlayStation games from 1995 to 2025- Xbox Cloud Gaming is getting a major upgrade- GPU prices continue to fall, with several models now selling below MSRPPlus: what we've been playing and the best food we had this week.0:00 Hello and welcome to the show3:30 Permabanned / GGs14:05 Battle Royale coming to BF623:50 PlayStation's best selling games over 30 years37:45 Xbox Cloud Gaming improvements44:50 GPU prices drop to MSRP or below51:00 Shoutouts54:25 What have we been playing or watching?1:07:25 The best food we had this week1:13:05 Closing and end of showGaming. Food. The Good Old Days.Streaming Thursday nights. New episodes posted Fridays.#SeeYouOnlineFollow us everywhere: @TheNerdChatAll links: https://linktr.ee/thenerdchat#BF6 #PlayStation #xCloud #GPUs #GamingPodcast #SeeYouOnline
Jacob Ward of The Rip Current podcast and newsletter joins Mikah Sargent this week! The impact that generative AI is having on energy and our climate. The privacy and social issues around AI wearables. And everything that was announced at Apple's 'Awe Dropping' event. Jacob shares a paper published recently that covered generative AI and how the massive use of GPU energy is causing concerns about its impact on the climate. Mikah talks about a new wearable AI companion device called Friend and how these always-listening devices present privacy challenges for not just others around the user but also for the company itself. And Zac Hall of 9to5Mac was at Apple's 'Awe Dropping' event this past Tuesday and was fortunate to get his hands on the new hardware the company announced. He shares his initial thoughts on the new AirPods Pro 3 and iPhone Air! Hosts: Mikah Sargent and Jacob Ward Guest: Zac Hall Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. 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: threatlocker.com for Tech News Weekly pantheon.io uscloud.com cachefly.com/twit
154 - AI usage dropping?The AI Hype Bubble is Popping? New data from the US Census Bureau shows a significant and surprising drop-off in corporate AI adoption, the largest since the survey began.Unprofitable AI: Despite billions in investment, 95% of companies report their AI software has failed to generate new revenue, raising questions about the return on investment.The Dystopian Jobs Platform: We dissect the controversy surrounding OpenAI's new jobs platform and the accusation that the company that displaced workers is now profiting from "helping" them.Follow the Money: We examine the absurdity of a multi-billion dollar GPU data center deal between OpenAI and Oracle, while the underlying AI applications struggle to prove their value.Media and Gaming Go All-In: A look at where AI is actually finding a profitable footing, from the AI-touched Wizard of Oz at the Las Vegas Sphere to its widespread use among video game developers.The Vibe Check is Not Good: From the disappointing tech news to the unsettling ethical questions, we discuss why this week feels like we're "living in a simulation."
Fill out this short listener survey to help us improve the show: https://forms.gle/bbcRiPTRwKoG2tJx8 Tri Dao, Chief Scientist at Together AI and Princeton professor who created Flash Attention and Mamba, discusses how inference optimization has driven costs down 100x since ChatGPT's launch through memory optimization, sparsity advances, and hardware-software co-design. He predicts the AI hardware landscape will shift from Nvidia's current 90% dominance to a more diversified ecosystem within 2-3 years, as specialized chips emerge for distinct workload categories: low-latency agentic systems, high-throughput batch processing, and interactive chatbots. Dao shares his surprise at AI models becoming genuinely useful for expert-level work, making him 1.5x more productive at GPU kernel optimization through tools like Claude Code and O1. The conversation explores whether current transformer architectures can reach expert-level AI performance or if approaches like mixture of experts and state space models are necessary to achieve AGI at reasonable costs. Looking ahead, Dao sees another 10x cost reduction coming from continued hardware specialization, improved kernels, and architectural advances like ultra-sparse models, while emphasizing that the biggest challenge remains generating expert-level training data for domains lacking extensive internet coverage. (0:00) Intro(1:58) Nvidia's Dominance and Competitors(4:01) Challenges in Chip Design(6:26) Innovations in AI Hardware(9:21) The Role of AI in Chip Optimization(11:38) Future of AI and Hardware Abstractions(16:46) Inference Optimization Techniques(33:10) Specialization in AI Inference(35:18) Deep Work Preferences and Low Latency Workloads(38:19) Fleet Level Optimization and Batch Inference(39:34) Evolving AI Workloads and Open Source Tooling(41:15) Future of AI: Agentic Workloads and Real-Time Video Generation(44:35) Architectural Innovations and AI Expert Level(50:10) Robotics and Multi-Resolution Processing(52:26) Balancing Academia and Industry in AI Research(57:37) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq'd by VMWare) @jordan_segall - Partner at Redpoint
Apple acaba de presentar su nueva generación de dispositivos, pero hay secretos técnicos que no te contaron en el evento. En este episodio de Apple Coding Daily realizamos el análisis más profundo de los iPhone 17, iPhone Air, iPhone 17 Pro, Apple Watch Series 11, Ultra 3, SE 3 y AirPods Pro 3. ¿Sabías que hay un iPhone que es técnicamente superior pero que nadie va a comprar? Descubrimos cuál es la mejor compra calidad-precio que Apple lanzó este año y por qué el modelo más vendido será paradójicamente el peor de todos. Analizamos los secretos del nuevo proceso de fabricación N3P, los revolucionarios Neural Accelerators integrados en la GPU y por qué el cambio del titanio al aluminio en los Pro es una decisión científica brillante que cambia todo el juego térmico. El sistema de refrigeración por Vapor Chamber, por qué la cámara frontal cuadrada es más revolucionaria de lo que parece, las capacidades cinematográficas reales vs marketing, análisis técnico del Ceramic Shield 2 y su resistencia comparable al cuarzo, la detección de hipertesión por IA: cómo funciona realmente y una comparativa técnica entre todos los modelos. Te damos la respuesta definitiva sobre si debes actualizar y a qué modelo exactamente según tu perfil de uso. Un análisis sin filtros donde la técnica prevalece sobre el marketing. Nativamente accesible, la única forma de incluir a todos los colectivos con algún tipo de discapacidad en tu app. Aprende todo lo necesario con el Swift Accessibility Program 2025. Encuentra toda la información pulsando aquí. Suscríbete a nuestro canal de Youtube: Apple Coding en YouTube Descubre nuestro canal de Twitch: Apple Coding en Twitch. Descubre nuestras ofertas para oyentes: - Cursos en Udemy (con código de oferta) - Apple Coding Academy - Suscríbete a Apple Coding en nuestro Patreon. - Canal de Telegram de Swift. Acceso al canal. --------------- Consigue las camisetas oficiales de Apple Coding con los logos de Swift y Apple Coding así como todo tipo de merchadising como tazas o fundas. - Tienda de merchandising de Apple Coding.
Daniel Mahncke and Shawn O'Malley dive into Dell Technologies, the legacy PC giant that's quietly become one of the largest suppliers of AI infrastructure in the world. Once seen as a low-growth hardware player, Dell now sits at the heart of the data center buildout — shipping billions of dollars worth of GPU-powered servers to customers like xAI, Meta, and Microsoft. With a growing AI backlog, enterprise trust, and deep global reach, Dell might be one of the most overlooked players in today's AI cycle. IN THIS EPISODE, YOU'LL LEARN 00:00 – Intro 01:09 - How Dell became a global PC behemoth. 5:27 - Why Dell managed to outcompete IBM. 10:56 - How Dell's business is structured. 14:30 - Why the PC Market is struggling to grow. 20:36 - What role AI Servers play in Dell's future. 47:23 - Whether Dell has a moat. 54:09 - How profitable Dell is and how it allocates capital. 01:11:15 - Why hardware is such a tough business. 01:14:11 - Whether Dell is attractively valued at its current levels. 01:14:11 - Whether Shawn & Daniel add DELL to The Intrinsic Value Portfolio. *Disclaimer: Slight timestamp discrepancies may occur due to podcast platform differences. BOOKS AND RESOURCES Get smarter about valuing businesses in just a few minutes each week through our newsletter, The Intrinsic Value Newsletter. Sign Up for The Intrinsic Value Community. Norges Bank Interviews with Michael Dell. Dell Presentation on the AI PC Revolution. Jensen Huang, Michael Dell Interview on Nvidia and Dell Partnership 3rd Party Report on Dell's Moat. Explore our previous Intrinsic Value breakdowns: Uber, Nike, Reddit, Nintendo, Airbnb, AutoZone, Alphabet, Ulta, John Deere, and Madison Square Garden Sports. Check out the books mentioned in the podcast here. Enjoy ad-free episodes when you subscribe to our Premium Feed. NEW TO THE SHOW? Follow our official social media accounts: X (Twitter) | LinkedIn | Instagram | Facebook | TikTok. Browse through all our episodes (complete with transcripts) here. Try Shawn's favorite tool for picking stock winners and managing our portfolios: TIP Finance. Enjoy exclusive perks from our favorite Apps and Services. Learn how to better start, manage, and grow your business with the best business podcasts. SPONSORS Support our free podcast by supporting our sponsors: Harvest Right Connect with Shawn: Twitter | LinkedIn | Email Connect with Daniel: Twitter | LinkedIn | Email Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm
The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch
Agenda: 04:00 – Anthropic Raises $13BN: The Analysis? 19:00 – Is Zuck's $14BN Scale bet the biggest blunder in AI? 27:00 – Lovable Raising at $4BN and Vercel at $9BN: Justified or Madness? 36:00 – Quarterly Results for Snowflake, Mongo, Okta, Zoom Skyrocket: Is B2B SaaS back from the dead? 48:00 – Is Jensen Huang right there will be $4TRN in AI gains? 57:00 – Will AI wipe out SaaS margins with 10% GPU taxes? Or is Notion the exception? Items Mentioned in Today's Episode: Try NEXOS.AI for yourself with a 14-day free trial: https://nexos.ai/20vc
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