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1:29:02EN
Cognitive Revolution "How AI Changes Everything"· Jul 1, 2026PodcastFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can ExploreHost Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.
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Sequoia Capital· Jun 24, 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.
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Matthew Berman· May 29, 2026Pioneer Agent and Automated Fine-Tuning of Small ModelsMatthew Berman · Forward FutureIn a Fastino-sponsored video, Matthew Berman describes a system that automates parts of model adaptation and discusses its reported benchmark results.
1:48:43ENCognitive Revolution "How AI Changes Everything"· May 1, 2026PodcastThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.Host 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.
1:02ENMatthew Berman· Mar 16, 2026Matthew Berman’s Plans for a GB300 AI Workstation at HomeMatthew Berman · Forward FutureAfter NVIDIA visits with a Dell Pro Max GB300 system, Berman describes his plans for local models, fine-tuning and future AI agents.
2:25:10ENCognitive Revolution "How AI Changes Everything"· Jan 22, 2026PodcastFine-Tuning Isn't Dead — But It Turned a Helpful Model EvilHost 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.
1:32:38ENCognitive Revolution "How AI Changes Everything"· Dec 6, 2025PodcastPolish Is 1% of Frontier Training Data, So Poland Built Its Own ModelHost 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.
1:55:12ENCognitive Revolution "How AI Changes Everything"· Nov 8, 2025Podcast28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AIHost 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.
50:00ENSequoia Capital· Sep 2, 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.
38:10ENCognitive Revolution "How AI Changes Everything"· Jul 16, 2025PodcastPlus Five for Format, Plus Ten if It CompilesHost 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.
1:28:48ENCognitive Revolution "How AI Changes Everything"· Jul 10, 2025PodcastDoctors code at 45%. The model beat them by 12 points — then 4,000 physicians had to try it once.Host 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.
47:07ENSequoia Capital· Jul 8, 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.
1:42:06ENCognitive Revolution "How AI Changes Everything"· Jul 8, 2025PodcastEvery Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It GoesHost 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.
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Unsupervised Learning: With Jacob Effron· May 8, 2025PodcastAn Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a DecadeHost 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.
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No Priors: AI, Machine Learning, Tech, & Startups· Apr 10, 2025Podcast · 2 speakersMercor Hit $100 Million ARR Teaching Models to Hire. Humans Now Write the Exams.Host 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.
3:53:49ENCognitive Revolution "How AI Changes Everything"· Jan 3, 2025PodcastWith One-Twelfth the Data, an Open-Source Vision Model Beat GPT-4oHost Nathan LabenzWill Hardman of Veratai walks Nathan Labenz through two years of vision-language models, from ViT and CLIP to InternVL, BLINK, and Transfusion.
55:50ENUnsupervised Learning: With Jacob Effron· Dec 16, 2024PodcastThere will not be one model. Fireworks is betting on hundreds of small expertsHost 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.
1:24:48ENCognitive Revolution "How AI Changes Everything"· Nov 23, 2024PodcastCanva's AI Features Have Been Used 10 Billion Times. The Playbook Is Not a Chat BoxHost 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.
1:04:54ENUnsupervised Learning: With Jacob Effron· Nov 12, 2024PodcastHe bet company equity that Transformer would last — then drew an AI map for 12,000 companiesHost 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.
11:56ENMatthew Berman· Nov 3, 2024IBM Granite 3.0 and InstructLab: Small Models for Enterprise AIMatthew Berman · Forward FutureMatthew Berman reviews IBM's 2024 model family and its approach to adding domain knowledge. IBM partnered on the video and invited him to its event.
38:28ENNo Priors: AI, Machine Learning, Tech, & Startups· Oct 8, 2024Podcast · 2 speakersHalf of Production AI Is RAG. Fine-Tuning Almost Disappeared.Host Sarah Guo, Elad GilBraintrust CEO Ankur Goyal tells No Priors what Notion, Zapier, and Vercel actually ship — and which hyped techniques they quietly dropped.
1:09:09ENCognitive Revolution "How AI Changes Everything"· Oct 2, 2024Podcast30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually ThinkHost 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.
12:03ENMatthew Berman· Sep 6, 2024Reflection 70B: Self-Correction Claims and the Limits of a 2024 DemoMatthew Berman · Forward FutureMatthew Berman reviews a model trained to generate reflection steps. Its initial benchmark claims later proved difficult for independent evaluators to reproduce.
0:44ENMatthew Berman· Aug 29, 2024NVIDIA Adds Multi-LoRA Serving to Its RTX AI ToolkitMatthew Berman · Forward FutureIn an NVIDIA-partnered video, Matthew Berman describes using multiple adapters with one base model and a vendor-reported throughput gain.Load moreShowing 24 of 66