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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.
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.
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 1. Mai 2026PodcastThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.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.
3:36:29ENCognitive Revolution "How AI Changes Everything"· 23. Apr. 2026PodcastClaude Rated Its Own Welfare 4.49 — the First Time Any Version Crossed NeutralModeration: Nathan LabenzCameron Berg returns to The Cognitive Revolution to survey six months of introspection, functional-emotion, and model-welfare research, plus a still-unpublished case that learning and feeling may be the same phenomenon.
2:31:27ENCognitive Revolution "How AI Changes Everything"· 15. Apr. 2026PodcastAn AI store manager, a 2.6-star rating, and a constitution nobody has to keepModeration: Nathan LabenzA live Cognitive Revolution episode puts PCB layout, AI constitutions, and San Francisco’s first AI-run grocery on the same morning clock.
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.
54:26ENCognitive Revolution "How AI Changes Everything"· 22. Feb. 2026PodcastTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-ReadyModeration: Nathan LabenzMiniMax researcher Olive Song explains how M2 was trained with expert developers as reward models, interleaved thinking, and a perturbation pipeline that treats every scaffold change as the real generalization test.
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.
1:01:49ENCognitive Revolution "How AI Changes Everything"· 2. Okt. 2025PodcastChatGPT's Co-Creator Left to Put Nature in the Reward LoopModeration: Nathan LabenzLiam Fedus and Ekin Dogus Cubuk on why language models still fail at physics, why literature data is too noisy to train on, and why Periodic Labs is aiming at a 200K superconductor.
1:02:05ENUnsupervised Learning: With Jacob Effron· 24. Sept. 2025Podcast$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the MathModeration: Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.
3:14:49ENCognitive Revolution "How AI Changes Everything"· 6. Sept. 2025PodcastNothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI TimelinesModeration: Nathan LabenzOn his tenth visit to The Cognitive Revolution, Zvi Mowshowitz argues that GPT-5 and IMO gold stayed on trend, while chip policy, energy, and reinforcement learning nudged his p(doom) slightly up.
38:10ENCognitive 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.
57:31ENUnsupervised Learning: With Jacob Effron· 22. Mai 2025PodcastThe New Ruler for Models Is How Long They Can WorkModeration: Jacob EffronOn Claude 4's launch day, Anthropic researcher Sholto Douglas argued that the next phase of AI is less about harder puzzles and more about hours of unsupervised work.
1:14:11ENCognitive Revolution "How AI Changes Everything"· 5. Apr. 2025PodcastThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIModeration: Nathan LabenzDeepMind's thinking-and-inference lead explains why RL-for-reasoning felt sudden, why Gemini shows raw chain of thought, and why a million-token window still is not memory.
1:56:38ENCognitive Revolution "How AI Changes Everything"· 8. März 2025Podcasto3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligenceModeration: Nathan LabenzOn Consistently Candid, the Cognitive Revolution host argues that math and coding will be superhuman by 2026, and that a reasoning core plus specialist “intuitive physics” may already be enough.
44:34ENUnsupervised Learning: With Jacob Effron· 19. Feb. 2025PodcastThe Cheaper Intelligence Gets, the More of It We'll BuyModeration: Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.
2:16:17ENCognitive Revolution "How AI Changes Everything"· 5. Feb. 2025PodcastA 10B Model Trained Across Three Continents — and an H200 for $1.49 an HourModeration: Nathan LabenzPrime Intellect's founders lay out a four-step plan to turn spare global GPUs into collectively owned intelligence, and argue that reinforcement learning just made their job easier.
1:48:20ENCognitive Revolution "How AI Changes Everything"· 25. Jan. 2025PodcastFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the TableModeration: Nathan LabenzOn Inauguration Day 2025, DeepSeek and Moonshot dropped reasoning-model results that Nathan Labenz reads as proof the reinforcement-learning recipe is simple, public, and still climbing.
30:29ENHow Researchers Think o1-Style Reasoning Models WorkMatthew Berman · Forward FutureMatthew Berman explains a research survey of policy initialization, rewards, search and reinforcement learning, and the open questions behind reasoning models.
1:27:33ENCognitive Revolution "How AI Changes Everything"· 3. Dez. 2024PodcastA 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a DayModeration: Nathan LabenzMultiOn CEO Div Garg returns to The Cognitive Revolution to recap 18 months of agent hype, the AgentQ stack, and why 2025 might still be the year of vertical agents.
52:45ENCognitive Revolution "How AI Changes Everything"· 13. Juni 2024PodcastA $150 million model, $5 million six months later: Benchmark’s AI investment mathModeration: Nathan LabenzEric Vishria and Quilter’s Sergiy Nesterenko explain why PCB layout is not a Copilot problem, why human board data would be the wrong training set, and which AI companies look like sugar highs.
56:56ENCognitive Revolution "How AI Changes Everything"· 25. Apr. 2024PodcastA Week of PCB Layout in an Hour: Quilter Trains Agents, Not ImitatorsModeration: Nathan LabenzSpaceX alum Sergiy Nesterenko tells Will Summerlin how Quilter uses reinforcement learning to compile schematics into manufacturable boards, and why cloning human layouts would cap the system at human skill.
1:58:43ENCognitive Revolution "How AI Changes Everything"· 7. Feb. 2024PodcastA Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.Moderation: Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.
1:07:29EN
Lex FridmanPodcastDeep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZeroModeration: Lex FridmanLex Fridman's MIT 6.S091 opening lecture walks from the basic RL framework through DQN, actor-critic methods and AlphaZero to the unsolved problem of moving from simulation to the real world.Mehr laden24 von 34 angezeigt