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1:08:02EN
Sequoia Capital· 13. Okt. 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· 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.
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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.
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Cognitive Revolution "How AI Changes Everything"· 8. Aug. 2026PodcastThe Periodic Table Was Already in the WeightsModeration: 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· 4. Aug. 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· 29. Juli 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"· 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.
50:57ENUnsupervised Learning: With Jacob Effron· 9. Juli 2026PodcastA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen SchmidhuberModeration: 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"· 4. Juli 2026Podcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipModeration: 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"· 3. Juni 2026PodcastTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Moderation: 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· 3. Juni 2026PodcastA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still MissModeration: 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· 22. Mai 2026PodcastThe GPT moment for video hasn’t arrived, but AGI may already be hereModeration: 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· 15. Mai 2026PodcastYann LeCun Left Meta Because LLMs Will Not Get You to IntelligenceModeration: 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"· 1. Mai 2026PodcastThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.Moderation: 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· 9. Apr. 2026PodcastTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028Moderation: 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"· 5. März 2026PodcastDon't Fight Backprop: Goodfire's Bet on Designing What Models LearnModeration: 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"· 18. Feb. 2026PodcastThree IMO Golds Missed the Same Problem. Harmonic Wants Math to CompileModeration: 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"· 1. Feb. 2026Podcast125 million cells took a decade. The next billion takes monthsModeration: 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· 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.
1:03:00ENUnsupervised Learning: With Jacob Effron· 29. Jan. 2026PodcastA Model That Solves New Math Problems Every Week Still Isn't AGIModeration: 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"· 22. Jan. 2026PodcastFine-Tuning Isn't Dead — But It Turned a Helpful Model EvilModeration: 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· 6. Jan. 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· 18. Nov. 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"· 8. Nov. 2025Podcast28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AIModeration: 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.Mehr laden24 von 200 angezeigt