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32 Folien1:50:48EN
Y Combinator· 24. Okt. 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.InferenceGPU programming & kernelsKV caching & prefix reuse+2
1:25:33EN
Latent Space· 22. Okt. 2026Podcast · 2 StimmenWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, ModalGast: Erik Bernhardsson · Moderation: 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.Infrastruktur & DeploymentSandboxes & isolationAI cost & performance+2
2 Folien17:42EN
AI Engineer· 21. Okt. 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?AI cost & performanceInferenceQuantization+2
1:26:46EN
Cognitive Revolution "How AI Changes Everything"· 8. Okt. 2026PodcastThere Likely Is a Level of Intelligence We Shouldn't Go PastModeration: 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.Unternehmen & StrategieSicherheit & GovernanceAGI Timelines+3
1:04:26EN
Sequoia Capital· 6. Okt. 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.Infrastruktur & DeploymentAI cost & performanceInference+3
56:31EN
Unsupervised Learning: With Jacob Effron· 6. Okt. 2026PodcastPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabModeration: 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.Modelle & TrainingPost-trainingReinforcement Learning+3
35:39EN
No Priors: AI, Machine Learning, Tech, & Startups· 2. Okt. 2026Podcast · 2 StimmenCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioModeration: 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.Infrastruktur & DeploymentInferenceAI cost & performance+3
38:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 18. Sept. 2026Podcast · 2 StimmenDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom SiliconModeration: 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.Modelle & TrainingInferenceAI cost & performance+3
2:19:30EN
Cognitive Revolution "How AI Changes Everything"· 5. Sept. 2026PodcastThe investigators were allowed six days. The word protein appeared once.Moderation: 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.SicherheitSicherheit & GovernanceAgent red teaming+3
2:06:41EN
Cognitive Revolution "How AI Changes Everything"· 9. Juli 2026PodcastZero the J-Space and a Model's Hidden Goal Lights Up on Token OneModeration: 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.Modelle & TrainingModel InterpretabilitySicherheit & Governance+3
1:10:15EN
Sequoia Capital· 30. Juni 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.Infrastruktur & DeploymentInferenceBenchmarks+3
30:34EN
No Priors: AI, Machine Learning, Tech, & Startups· 21. Mai 2026Podcast · 2 StimmenCerebras Waited Ten Years for a Market That Finally Needed SpeedModeration: 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.Infrastruktur & DeploymentCompany BuildingLeadership+3
1:26:16EN
Cognitive Revolution "How AI Changes Everything"· 9. Mai 2026PodcastMilliseconds to Match: How Criteo Bids on a Billion Anonymous ProfilesModeration: 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.Unternehmen & StrategieRecommendation systemsEmbeddings+3
42:57EN
No Priors: AI, Machine Learning, Tech, & Startups· 1. Mai 2026Podcast · 2 StimmenInference Is the Last Market: Baseten’s 30x YearModeration: 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.Infrastruktur & DeploymentInferencePost-training+3
1:57:29EN
Cognitive Revolution "How AI Changes Everything"· 4. Apr. 2026PodcastFrontier vision models score 12.5%: Joseph Nelson on the real waterline of computer visionModeration: 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.Multimodal & MedienMultimodal AIVision & Video+3
44:19EN
Sequoia Capital· 17. März 2026PodcastThe $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.Infrastruktur & DeploymentInferenceAI cost & performance+2
4:25:13EN
Lex Fridman· 31. Jan. 2026PodcastThe Architecture Barely Changed. Data, Cost, and Open Weights Did.Moderation: 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.Modelle & TrainingScaling LawsOpen-weight models+3
1:02:19EN
Sequoia Capital· 10. Dez. 2025PodcastA 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.Infrastruktur & DeploymentGenerative mediaVision & Video+3
41:32EN
Sequoia Capital· 28. Okt. 2025PodcastMoore'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.Infrastruktur & DeploymentDistributed training & inferenceInference+2
1:22:07EN
Cognitive Revolution "How AI Changes Everything"· 25. Sept. 2025PodcastEvery payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%Moderation: 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.Modelle & TrainingKI im FinanzwesenEmbeddings+3
1:32:47EN
Cognitive Revolution "How AI Changes Everything"· 13. Sept. 2025PodcastA transformer co-author wants a $160 million model no company ownsModeration: 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.Infrastruktur & DeploymentInferenceAI security+3
59:06EN
Unsupervised Learning: With Jacob Effron· 10. Sept. 2025PodcastInference Costs Fell 100x. Tri Dao Says There's Another 10x — and NVIDIA's 90% Won't HoldModeration: 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.Infrastruktur & DeploymentInferenceAI cost & performance+3
47:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 14. Aug. 2025Podcast · 2 StimmenThe Analyst Tracking 200 GPU Clouds Breaks Nvidia Into a Three-Headed DragonModeration: 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.Infrastruktur & DeploymentInferenceAI cost & performance+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 16. Juli 2025PodcastPlus Five for Format, Plus Ten if It CompilesModeration: 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.Modelle & TrainingFine-TuningPost-training+3
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