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1:50:48EN
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.
1:25:33EN
Latent Space· 22 oct 2026Pódcast · 2 vocesWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, ModalInvitado: Erik Bernhardsson · Presenta: 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.
17:42EN
AI 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?
1:26:46EN
Cognitive Revolution "How AI Changes Everything"· 8 oct 2026PódcastThere Likely Is a Level of Intelligence We Shouldn't Go PastPresenta: 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.
1:04:26EN
Sequoia Capital· 6 oct 2026PódcastAt 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.
56:31EN
Unsupervised Learning: With Jacob Effron· 6 oct 2026PódcastPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabPresenta: Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
35:39EN
No Priors: AI, Machine Learning, Tech, & Startups· 2 oct 2026Pódcast · 2 vocesCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioPresenta: 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.
38:14ENNo Priors: AI, Machine Learning, Tech, & Startups· 18 sept 2026Pódcast · 2 vocesDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom SiliconPresenta: 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.
2:19:30ENCognitive Revolution "How AI Changes Everything"· 5 sept 2026PódcastThe investigators were allowed six days. The word protein appeared once.Presenta: Nathan LabenzA week of Cognitive Revolution morning shows on OpenAI’s agent-swarm incident, GPT-6 Astra’s loop transformer, and whether the pause debate is already over.
2:06:41ENCognitive Revolution "How AI Changes Everything"· 9 jul 2026PódcastZero the J-Space and a Model's Hidden Goal Lights Up on Token OnePresenta: Nathan LabenzA weekly Cognitive Revolution cut of Anthropic's global-workspace paper, AI superforecasters, open video world models, and a chip that treats inference as data movement.
1:10:15ENSequoia Capital· 30 jun 2026PódcastThe 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.
30:34ENNo Priors: AI, Machine Learning, Tech, & Startups· 21 may 2026Pódcast · 2 vocesCerebras Waited Ten Years for a Market That Finally Needed SpeedPresenta: Sarah Guo, Elad GilFounder and CEO Andrew Feldman walks No Priors through wafer-scale chips, a $20 billion OpenAI deal, and why a dinner-plate processor only mattered once AI became an everyday tool.
1:26:16ENCognitive Revolution "How AI Changes Everything"· 9 may 2026PódcastMilliseconds to Match: How Criteo Bids on a Billion Anonymous ProfilesPresenta: Nathan LabenzCriteo’s CTO and AI lab head walk through the millisecond auction, the DeepKNN-to-foundation-model stack, and why a live product catalog still beats a frozen LLM.
42:57ENNo Priors: AI, Machine Learning, Tech, & Startups· 1 may 2026Pódcast · 2 vocesInference Is the Last Market: Baseten’s 30x YearPresenta: Sarah Guo, Elad GilCEO Tuhin Srivastava on a billion-dollar inference cloud, why the app layer survives, and a GPU crunch worse than the narrative.
1:57:29ENCognitive Revolution "How AI Changes Everything"· 4 abr 2026PódcastFrontier vision models score 12.5%: Joseph Nelson on the real waterline of computer visionPresenta: Nathan LabenzThe Roboflow CEO tells Nathan Labenz why vision still lags language, how to distill SAM 3 into an edge model for Wimbledon, and why the United States has almost never led open-source vision.
44:19ENSequoia Capital· 17 mar 2026PódcastThe $500-per-Kilogram Line: Why Starcloud Thinks Data Centers Belong in SpaceStarcloud founder Philip Johnston walks through the physics, launch economics, and business model of putting AI compute in orbit.
4:25:13EN
Lex Fridman· 31 ene 2026PódcastThe Architecture Barely Changed. Data, Cost, and Open Weights Did.Presenta: Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.
1:02:19ENSequoia Capital· 10 dic 2025PódcastA Top Video Model's Half-Life Is 30 Days. fal Runs 600 AnywayThe fal founders tell Sequoia why generative video is a compute-bound problem that language-model shops keep underestimating, and why they will not let any customer marry a single model.
41:32ENSequoia Capital· 28 oct 2025PódcastMoore's Law Is Slowing. Nvidia's CTO Still Wants 10× a YearMichael Kagan on why Nvidia's $7 billion Mellanox deal, not just more transistors, is how you turn a data center into one computer.
1:22:07ENCognitive Revolution "How AI Changes Everything"· 25 sept 2025PódcastEvery payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%Presenta: Nathan LabenzEmily Sands, Stripe’s head of data and AI, explains how a domain-specific payments model, shared embeddings, and mixed rules turn a $1.4 trillion network into compounding advantage.
1:32:47ENCognitive Revolution "How AI Changes Everything"· 13 sept 2025PódcastA transformer co-author wants a $160 million model no company ownsPresenta: Nathan LabenzIllia Polosukhin tells Nathan Labenz how NEAR turned a payments headache into a stack for private inference, shared-revenue training, and AI agents that still answer to a court.
59:06ENUnsupervised Learning: With Jacob Effron· 10 sept 2025PódcastInference Costs Fell 100x. Tri Dao Says There's Another 10x — and NVIDIA's 90% Won't HoldPresenta: Jacob EffronThe FlashAttention author and Together AI chief scientist on why hardware portability is a myth, how Claude Code made him 1.5x faster, and why workloads will split the chip market.
47:18ENNo Priors: AI, Machine Learning, Tech, & Startups· 14 ago 2025Pódcast · 2 vocesThe Analyst Tracking 200 GPU Clouds Breaks Nvidia Into a Three-Headed DragonPresenta: Sarah Guo, Elad GilSemiAnalysis founder Dylan Patel on OpenAI’s open-weight model, a coming neocloud wipeout, and why a chip startup has to beat Nvidia on hardware, networking, and software at once.
38:10ENCognitive Revolution "How AI Changes Everything"· 16 jul 2025PódcastPlus Five for Format, Plus Ten if It CompilesPresenta: Nathan LabenzPredibase CEO Dev Rishi explains how reinforcement fine-tuning, production feedback, and narrow specialist models turn one-off training into systems that keep learning.Cargar másMostrando 24 de 55