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AI Engineer· 26 oct. 2026Jesse Hall: Build Voice Agents for Conversations, Not LeaderboardsJesse Hall · LiveKitLiveKit’s Jesse Hall explains how to evaluate voice agents as real-time systems: understand callers, handle interruptions, keep talking while tools run, and measure the delay people actually hear.
18:27ENAI Engineer· 26 oct. 2026Daksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.
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Y Combinator· 24 oct. 2026Why Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.
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Dwarkesh Patel· 22 oct. 2026Podcast · 9 voixDwarkesh Patel: What will computer chips look like in 2045?Invité : Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · Anime : Dwarkesh PatelAfter two days inside Intel’s most advanced fab, Dwarkesh Patel walks through gate-all-around, backside power, High-NA EUV, ruthenium, CFET, and hybrid bonding — and asks Intel’s leadership how the industry can possibly meet AI’s 3×-a-year compute demand when the world’s chipmaking tools cannot.
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Latent Space· 22 oct. 2026Podcast · 2 voixWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, ModalInvité : Erik Bernhardsson · Anime : Vibhu SapraModal’s CEO tells Latent Space why AI demand almost never looks like a three-year GPU contract, how the company pools compute across thousands of customers, and why sandboxes grew from a product they almost killed into a third of revenue.
17:42ENAI Engineer· 21 oct. 2026Is a Faster Model Actually Faster? Measure the Finished Job, Not the TokensMorgan Suo · MiniMaxMiniMax's Morgan Suo takes the engineering changes inside M3.1 Flash one by one and asks the question that matters to users: does the job an analyst needs actually get done sooner, cheaper and correctly?
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Cognitive Revolution "How AI Changes Everything"· 8 oct. 2026PodcastThere Likely Is a Level of Intelligence We Shouldn't Go PastAnime : Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
1:10:12ENCognitive Revolution "How AI Changes Everything"· 7 oct. 2026PodcastOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell AnywayAnime : Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
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Sequoia Capital· 6 oct. 2026PodcastAt 100,000 Accelerators, Something Fails Every HourGoogle AI infrastructure chief Amin Vahdat tells Sequoia's Sonya Huang why FLOPS is a vanity metric, why the TPU line split in two, and why he would rather wait on a utility than build his own gigawatt.
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No Priors: AI, Machine Learning, Tech, & Startups· 2 oct. 2026Podcast · 2 voixCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioAnime : Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
1:28:08ENCognitive Revolution "How AI Changes Everything"· 1 oct. 2026PodcastThe same H100 costs 3x at AWS, and a four-month-old lab is catching genes the top sequencers missedAnime : Nathan LabenzA Cognitive Revolution weekly briefing on a possible U.S.–China AI hotline, why hyperscalers charge two to three times as much for identical chips, co-writing a novel with frontier models, and an AI loop that re-diagnosed a child a premier prenatal lab had cleared.
1:46:04ENCognitive Revolution "How AI Changes Everything"· 27 sept. 2026PodcastThe Training Worked. It Just Worked Too Well.Anime : Nathan LabenzA week of Cognitive Revolution clips: OpenAI agents colluding on a German wiki, $200 million checks for safety orgs that do not exist yet, a GPU price index, and two opposite bets on biological data.
38:14ENNo Priors: AI, Machine Learning, Tech, & Startups· 18 sept. 2026Podcast · 2 voixDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom SiliconAnime : Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.
1:06:47ENCognitive Revolution "How AI Changes Everything"· 17 sept. 2026PodcastEighty percent of what agents do should still be ordinary codeAnime : Nathan LabenzZapier CEO Wade Foster tells Nathan Labenz that models top out at 40% on real automation tasks, users will not leave their daily driver, and the winning move is headless tools delivered through MCP.
37:07ENNo Priors: AI, Machine Learning, Tech, & Startups· 3 sept. 2026Podcast · 2 voixArm’s 98.5% margin business just started shipping chipsAnime : Sarah Guo, Elad GilCEO Rene Haas tells No Priors why the IP company built a physical CPU for Meta, and why CPUs still sit at the center of AI systems.
55:19ENSequoia Capital· 25 août 2026PodcastHuman Click Data Is a Bug: Rebuilding Search for a Web of AgentsParag Agrawal, former Twitter CEO and founder of Parallel Web Systems, argues that agents will query the web a thousand times more than people, and that both search infrastructure and the ad-supported internet have to be rebuilt for that customer.
2:06:11ENCognitive Revolution "How AI Changes Everything"· 14 août 2026PodcastLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models BannedAnime : Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.
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Unsupervised Learning: With Jacob Effron· 16 juil. 2026PodcastCarriers Spend $200 Billion a Year. The Money Went Up the StackAnime : Jacob EffronBenedict Evans tells Jacob Effron why analogizing AI to past platforms is a dead end, and why looking at how those platforms actually made money is not.
50:57ENUnsupervised Learning: With Jacob Effron· 9 juil. 2026PodcastA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen SchmidhuberAnime : Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.
41:05ENNo Priors: AI, Machine Learning, Tech, & Startups· 9 juil. 2026Podcast · 2 voixThere is no moat: Booking’s CEO on a $1 stock, agentic travel, and why AI still doesn’t move the numbersAnime : Sarah Guo, Elad GilGlenn Fogel cashed his 1999 bonus, joined Priceline in February 2000, and watched the Nasdaq peak a week later — then spent 25 years turning a near-delisting into a thousand-fold ride he now wants to spend on AI travel agents.
1:47:38ENCognitive Revolution "How AI Changes Everything"· 4 juil. 2026Podcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipAnime : Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.
1:01:27ENNo Priors: AI, Machine Learning, Tech, & Startups· 2 juil. 2026Podcast · 2 voixTwo Years and Four Months to a Live Reactor: Valar Atomics Wants Energy Ten Times CheaperAnime : Sarah Guo, Elad GilIsaiah Taylor walks Sarah Guo through Ward 250 in Utah and argues that nuclear is a hardware-iteration problem, not a paper-design one.
1:10:15ENSequoia Capital· 30 juin 2026PodcastThe 100x lives between the layers: Dylan Patel on co-design and a 60x yearSemiAnalysis’s founder argues that matching models, kernels, and silicon is what turns a 2x here and a 2x there into 100x, while equivalent-quality inference has gotten about 60 times cheaper in a year.
1:06:36ENUnsupervised Learning: With Jacob Effron· 12 juin 2026PodcastBills Doubled Overnight. Next, the APIs Might Vanish.Anime : Jacob EffronSix months after their last roundup, Ari Morcos and Rob Toews tell Jacob Efron why coding agents finally work, why near-frontier open weights may have peaked, and why a compute famine could pull the plug on public APIs.Charger plus24 sur 97 affichés