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1:08:02EN
Sequoia Capital· Oct 13, 2026PodcastAlphaGo Took Two Years. AlphaZero Took Hours. Silver Is Making the Same Bet on SuperintelligenceDavid Silver and Lasse Espeholt left DeepMind to build Ineffable Intelligence, a twenty-person lab that wants a superlearner to discover science, math, and language from experience rather than from a pre-training run.
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Unsupervised Learning: With Jacob Effron· Oct 6, 2026PodcastPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabHost 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.
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No Priors: AI, Machine Learning, Tech, & Startups· Sep 18, 2026Podcast · 2 speakersDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom SiliconHost 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.
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Cognitive Revolution "How AI Changes Everything"· Aug 8, 2026PodcastThe Periodic Table Was Already in the WeightsHost Nathan LabenzGoodfire CTO Dan Balsam tells Nathan Labenz how concept manifolds, predictive data debugging, and a $1,000-a-month research agent are turning interpretability into a product.
47:22ENSequoia Capital· Aug 4, 2026PodcastFrom One in a Thousand to 15 Percent: Chai Discovery Treats Drug Design as a Scaling ProblemJoshua Meier and Matthew McPartlon tell Sequoia’s Training Data why antibody design is an engineering problem, not a bespoke science, and why they sell a molecular CAD suite instead of their own drugs.
49:12ENSequoia Capital· Jul 29, 2026PodcastThe People Writing the Transformer’s Eulogy Want a Lab That Can Take Vacation Without Themo1’s reasoning lead and a Gemini pre-training lead argue the architecture, not more scale, is now the bottleneck — and that replacing it starts with automating kernel generation.
2:06:41ENCognitive Revolution "How AI Changes Everything"· Jul 9, 2026PodcastZero the J-Space and a Model's Hidden Goal Lights Up on Token OneHost 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.
50:57ENUnsupervised Learning: With Jacob Effron· Jul 9, 2026PodcastA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen SchmidhuberHost 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.
1:47:38ENCognitive Revolution "How AI Changes Everything"· Jul 4, 2026Podcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipHost 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.
2:59:44ENCognitive Revolution "How AI Changes Everything"· Jun 3, 2026PodcastTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Host Nathan LabenzGoogle researcher Ali Behrouz tells Nathan Labenz how stacking update frequencies — not just layers — and an offline sleep phase could give language models genuine continual learning.
1:13:33ENUnsupervised Learning: With Jacob Effron· Jun 3, 2026PodcastA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still MissHost Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.
59:41ENUnsupervised Learning: With Jacob Effron· May 22, 2026PodcastThe GPT moment for video hasn’t arrived, but AGI may already be hereHost Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.
1:21:56ENUnsupervised Learning: With Jacob Effron· May 15, 2026PodcastYann LeCun Left Meta Because LLMs Will Not Get You to IntelligenceHost Jacob EffronThe Turing Award winner tells Jacob Effron why he spun AMI Labs out of Meta, why JEPA-style world models beat pixel generators, and why he thinks Hinton changed his mind in 2023.
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.
58:46ENUnsupervised Learning: With Jacob Effron· Apr 9, 2026PodcastTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028Host Jacob EffronJakub Pachocki tells Jacob Effron why those timelines still hold, why continual learning is not a detour, and why showing chain of thought in the product would train the monitor away.
1:49:53ENCognitive Revolution "How AI Changes Everything"· Mar 5, 2026PodcastDon't Fight Backprop: Goodfire's Bet on Designing What Models LearnHost Nathan LabenzDan Balsam and Tom McGrath return to The Cognitive Revolution with a $150 million Series B, a new research pillar called intentional design, and a rule for anyone who wants to steer training: stop trying to out-muscle gradient descent.
1:34:29ENCognitive Revolution "How AI Changes Everything"· Feb 18, 2026PodcastThree IMO Golds Missed the Same Problem. Harmonic Wants Math to CompileHost Nathan LabenzVlad Tenev and Tudor Achim built Aristotle to emit Lean proofs a kernel can check—and they argue that is how mathematical superintelligence stays trustworthy.
1:04:51ENCognitive Revolution "How AI Changes Everything"· Feb 1, 2026Podcast125 million cells took a decade. The next billion takes monthsHost Nathan LabenzMark Zuckerberg and Priscilla Chan on pairing a frontier biology lab with a frontier AI lab so models train on data that was designed for them.
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Lex Fridman· Jan 31, 2026PodcastThe Architecture Barely Changed. Data, Cost, and Open Weights Did.Host 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.
1:03:00ENUnsupervised Learning: With Jacob Effron· Jan 29, 2026PodcastA Model That Solves New Math Problems Every Week Still Isn't AGIHost Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.
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.
1:01:38ENSequoia Capital· Jan 6, 2026Podcast13-Hour Coffee and 2x Throughput: Physical Intelligence Crosses the Deployment LineKarol Hausman and Tobi Springenberg tell Sequoia’s Training Data how a general robot brain, plus real-world RL, turned coffee, laundry, and chocolate boxes into jobs that actually run.
41:36ENSequoia Capital· Nov 18, 2025PodcastFour Months to Drive Tokyo: How Wayve Bet the Company on One End-to-End NetworkWayve CEO Alex Kendall tells Sequoia’s Training Data why AV 2.0 ditches HD maps and hand-written stacks for a foundation model that can adapt to a new car and a new country in weeks.
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.Load moreShowing 24 of 196