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1:29:02EN
Cognitive Revolution "How AI Changes Everything"· 1 juil. 2026PodcastFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can ExploreAnime : Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.Entreprise et stratégieFine-tuningAgent orchestration+3
44:52EN
Sequoia Capital· 24 juin 2026PodcastAn 80GB Wikipedia Cache Versus a 100GB Model That Holds the InternetEngram’s founders argue that stuffing a company into the context window is the expensive kind of memory—and that baking it into the weights can cut token use by two orders of magnitude.RAG et connaissancesContinual learningFine-tuning+3
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 1 mai 2026PodcastThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.Anime : Nathan LabenzCoreWeave's Kyle Corbitt walks Nathan Labenz through GRPO, rubrics, RL environments, and why most reward hacks are easy to catch once you know to look.Modèles et entraînementReinforcement LearningPost-training+3
2:25:10EN
Cognitive Revolution "How AI Changes Everything"· 22 janv. 2026PodcastFine-Tuning Isn't Dead — But It Turned a Helpful Model EvilAnime : Nathan LabenzNathan Labenz on why prompting replaced fine-tuning for most work, what emergent misalignment actually showed, and how he is thinking about jobs, UBI, and AGI.Modèles et entraînementFine-tuningSécurité et gouvernance+3
1:32:38EN
Cognitive Revolution "How AI Changes Everything"· 6 déc. 2025PodcastPolish Is 1% of Frontier Training Data, So Poland Built Its Own ModelAnime : Nathan LabenzMarek Kozlowski of Poland's National Information Processing Institute explains how PLLuM uses language adaptation, organic instructions, and on-prem small models to keep a mid-size country in control of its AI.Entreprise et stratégieOpen-weight modelsData quality & curation+3
1:55:12EN
Cognitive Revolution "How AI Changes Everything"· 8 nov. 2025Podcast28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AIAnime : Nathan LabenzLongbeard CEO Matthew Harvey Sanders tells The Cognitive Revolution how a mission-driven team is aligning models to the Catholic magisterium — and why fine-tuning was not enough.Modèles et entraînementGénération augmentée par récupérationFine-tuning+3
50:00EN
Sequoia Capital· 2 sept. 2025PodcastCrosby Bills by the Document, Not the Hour, and Turns Contracts Around in Under an HourThe founders of an AI-native law firm explain why they became lawyers with engineers at the next desk instead of shipping legal software, and how deal velocity became the product.Entreprise et stratégieFine-tuningIngénierie du contexte+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 16 juil. 2025PodcastPlus Five for Format, Plus Ten if It CompilesAnime : 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.Modèles et entraînementFine-tuningPost-training+3
1:28:48EN
Cognitive Revolution "How AI Changes Everything"· 10 juil. 2025PodcastDoctors code at 45%. The model beat them by 12 points — then 4,000 physicians had to try it once.Anime : Nathan LabenzAmbience Healthcare and Cleveland Clinic walk through the AI scribe that cut pajama time, climbed ICD-10 with reinforcement fine-tuning, and won 75% voluntary use.Entreprise et stratégieAI in healthcareFine-tuning+3
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Sequoia Capital· 8 juil. 2025PodcastGoodfire’s Eric Ho thinks we will decode neural nets by 2028On Sequoia’s Training Data, the interpretability founder argues that sparse autoencoders, model editing, and a third-party lab are how AI stops being grown from data and starts being designed.Évaluations et observabilitéModel InterpretabilitySécurité et gouvernance+3
1:42:06EN
Cognitive Revolution "How AI Changes Everything"· 8 juil. 2025PodcastEvery Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It GoesAnime : Nathan LabenzLabelbox CEO Manu Sharma on the $15 billion Scale deal, RL “gyms,” $250,000 trainers, and why post-training now eats the budget that used to belong to pre-training.Modèles et entraînementPost-trainingData quality & curation+3
47:00EN
Unsupervised Learning: With Jacob Effron· 8 mai 2025PodcastAn Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a DecadeAnime : Jacob EffronOpenAI’s GPT-4.1 post-training lead Michelle Pokrass tells Unsupervised Learning how the team spent three months on evals before training, why agents fail on wiring more than intelligence, and when to reach for RFT.Modèles et entraînementÉvaluationsPost-training+3
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No Priors: AI, Machine Learning, Tech, & Startups· 10 avr. 2025Podcast · 2 voixMercor Hit $100 Million ARR Teaching Models to Hire. Humans Now Write the Exams.Anime : Sarah Guo, Elad GilBrendan Foody tells Sarah Guo and Elad Gil how Mercor automated recruiting for frontier labs — and why building evals may become the world's most common knowledge job.Entreprise et stratégieÉvaluationsIngénierie d’agents+3
3:53:49EN
Cognitive Revolution "How AI Changes Everything"· 3 janv. 2025PodcastWith One-Twelfth the Data, an Open-Source Vision Model Beat GPT-4oAnime : Nathan LabenzWill Hardman of Veratai walks Nathan Labenz through two years of vision-language models, from ViT and CLIP to InternVL, BLINK, and Transfusion.Multimodal et médiasMultimodal AIVision et vidéo+3
55:50EN
Unsupervised Learning: With Jacob Effron· 16 déc. 2024PodcastThere will not be one model. Fireworks is betting on hundreds of small expertsAnime : Jacob EffronPyTorch veteran Lin Qiao argues that inference is a compound system hyperscalers cannot buy their way through, and that the products with real traction still keep a human in the loop.Infrastructure et déploiementInferenceModel routing & gateways+3
1:24:48EN
Cognitive Revolution "How AI Changes Everything"· 23 nov. 2024PodcastCanva's AI Features Have Been Used 10 Billion Times. The Playbook Is Not a Chat BoxAnime : Nathan LabenzJohn Milinovich, Canva's generative-AI product lead, walks Nathan Labenz through automation versus augmentation, concept-level interfaces, evals without a design arena, and why application-layer companies still have a decade of room.Produit et UXProduct StrategyAI Product Management+3
1:04:54EN
Unsupervised Learning: With Jacob Effron· 12 nov. 2024PodcastHe bet company equity that Transformer would last — then drew an AI map for 12,000 companiesAnime : Jacob EffronDatabricks chief AI scientist Jonathan Frankle tells enterprises when to prompt, fine-tune, or pre-train, and why he still refuses to forecast the next architecture.Entreprise et stratégieTransformers & attentionPretraining & midtraining+3
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No Priors: AI, Machine Learning, Tech, & Startups· 8 oct. 2024Podcast · 2 voixHalf of Production AI Is RAG. Fine-Tuning Almost Disappeared.Anime : Sarah Guo, Elad GilBraintrust CEO Ankur Goyal tells No Priors what Notion, Zapier, and Vercel actually ship — and which hyped techniques they quietly dropped.Évaluations et observabilitéÉvaluationsGénération augmentée par récupération+3
1:09:09EN
Cognitive Revolution "How AI Changes Everything"· 2 oct. 2024Podcast30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually ThinkAnime : Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.Agents de codeIngénierie d’agentsFine-tuning+3
1:51:00EN
Cognitive Revolution "How AI Changes Everything"· 21 août 2024PodcastStart With Ten Gold Examples: A Three-Step Playbook for AI AutomationAnime : Nathan LabenzThe day after OpenAI opened GPT-4o fine-tuning, Nathan Labenz unpacks a three-year method for choosing work, extracting tacit judgment, and raising model performance.Entreprise et stratégieWorkflow automationPrompting & in-context learning+3
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Sequoia Capital· 13 août 2024PodcastOpen and Closed Will Tie at the Same Size: PyTorch's Former Lead on Fast InferenceA six-month library swap at Meta became a five-year rebuild. Lin Qiao wants the rest of the industry to get that stack in five weeks.Infrastructure et déploiementInferenceFine-tuning+3
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No Priors: AI, Machine Learning, Tech, & Startups· 6 juin 2024Podcast · 2 voixA Hundred Million Tokens in Context Would Cost $10 Million. Tengyu Ma Runs the RAG MathAnime : Sarah Guo, Elad GilThe Stanford professor and Voyage AI founder argues that retrieval, not a giant context window, is how enterprises should manage private knowledge.RAG et connaissancesGénération augmentée par récupérationEmbeddings+3
1:10:07EN
Cognitive Revolution "How AI Changes Everything"· 6 juin 2024PodcastSame Intelligence, 1% of the Price: Logan Kilpatrick on Gemini FlashAnime : Nathan LabenzA former OpenAI developer-relations lead, now the product manager for Google AI Studio, walks through what Gemini 1.5 Flash actually changes for builders.Produit et UXAI cost & performanceMultimodal AI+3
1:42:17EN
Cognitive Revolution "How AI Changes Everything"· 20 avr. 2024PodcastThe Cheapest Inference Provider Is the Most DangerousAnime : Nathan LabenzFireworks AI cofounders Lin Qiao and Dmytro Ivchenko explain why subsidized GPU bills vanish, how LoRA serving can cut cost a hundredfold, and why OpenAI is the rival that actually matters.Infrastructure et déploiementInferenceAI cost & performance+3
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