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56:31EN
Unsupervised Learning: With Jacob Effron· 2026년 10월 6일팟캐스트Post-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab진행자 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.모델과 학습Post-trainingReinforcement Learning+3
59:41EN
Unsupervised Learning: With Jacob Effron· 2026년 5월 22일팟캐스트The GPT moment for video hasn’t arrived, but AGI may already be here진행자 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.모델과 학습World modelsReinforcement Learning+3
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 2026년 5월 1일팟캐스트The reward jumped from 3 to 180. Every Hacker News title was a Google layoff.진행자 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.모델과 학습Reinforcement LearningPost-training+3
3:36:29EN
Cognitive Revolution "How AI Changes Everything"· 2026년 4월 23일팟캐스트Claude Rated Its Own Welfare 4.49 — the First Time Any Version Crossed Neutral진행자 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Revolution to survey six months of introspection, functional-emotion, and model-welfare research, plus a still-unpublished case that learning and feeling may be the same phenomenon.안전과 거버넌스Model InterpretabilityAI research+3
2:31:27EN
Cognitive Revolution "How AI Changes Everything"· 2026년 4월 15일팟캐스트An AI store manager, a 2.6-star rating, and a constitution nobody has to keep진행자 Nathan LabenzA live Cognitive Revolution episode puts PCB layout, AI constitutions, and San Francisco’s first AI-run grocery on the same morning clock.에이전트안전과 거버넌스Reinforcement Learning+3
58:46EN
Unsupervised Learning: With Jacob Effron· 2026년 4월 9일팟캐스트Two Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028진행자 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.모델과 학습Continual learningReinforcement Learning+3
54:26EN
Cognitive Revolution "How AI Changes Everything"· 2026년 2월 22일팟캐스트Ten Billion Active Parameters, and the Unsexy Work of Making Them Agent-Ready진행자 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.코딩 에이전트Reinforcement Learning에이전트 엔지니어링+3
1:03:00EN
Unsupervised Learning: With Jacob Effron· 2026년 1월 29일팟캐스트A Model That Solves New Math Problems Every Week Still Isn't AGI진행자 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.모델과 학습Reinforcement LearningAGI Timelines+3
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2025년 10월 2일팟캐스트ChatGPT's Co-Creator Left to Put Nature in the Reward Loop진행자 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.모델과 학습AI for scienceReinforcement Learning+3
1:02:05EN
Unsupervised Learning: With Jacob Effron· 2025년 9월 24일팟캐스트$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Math진행자 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.기업과 전략AI StrategyAI startups & small teams+3
3:14:49EN
Cognitive Revolution "How AI Changes Everything"· 2025년 9월 6일팟캐스트Nothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI Timelines진행자 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.보안과 안전AGI Timelines안전과 거버넌스+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 2025년 7월 16일팟캐스트Plus Five for Format, Plus Ten if It Compiles진행자 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.모델과 학습파인튜닝Post-training+3
57:31EN
Unsupervised Learning: With Jacob Effron· 2025년 5월 22일팟캐스트The New Ruler for Models Is How Long They Can Work진행자 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.코딩 에이전트에이전트 엔지니어링평가(Evals)+3
1:14:11EN
Cognitive Revolution "How AI Changes Everything"· 2025년 4월 5일팟캐스트The Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGI진행자 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.모델과 학습Reasoning & test-time computeReinforcement Learning+3
1:56:38EN
Cognitive Revolution "How AI Changes Everything"· 2025년 3월 8일팟캐스트o3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligence진행자 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.모델과 학습Reinforcement LearningDistributed training & inference+3
44:34EN
Unsupervised Learning: With Jacob Effron· 2025년 2월 19일팟캐스트The Cheaper Intelligence Gets, the More of It We'll Buy진행자 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.에이전트에이전트 엔지니어링Reinforcement Learning+3
2:16:17EN
Cognitive Revolution "How AI Changes Everything"· 2025년 2월 5일팟캐스트A 10B Model Trained Across Three Continents — and an H200 for $1.49 an Hour진행자 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.인프라와 배포Distributed training & inferenceAI cost & performance+3
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 2025년 1월 25일팟캐스트From 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Table진행자 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.모델과 학습Reinforcement LearningReasoning & test-time compute+3
1:27:33EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 3일팟캐스트A 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a Day진행자 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.에이전트에이전트 엔지니어링Computer use+3
52:45EN
Cognitive Revolution "How AI Changes Everything"· 2024년 6월 13일팟캐스트A $150 million model, $5 million six months later: Benchmark’s AI investment math진행자 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.기업과 전략AI StrategyAI startups & small teams+3
56:56EN
Cognitive Revolution "How AI Changes Everything"· 2024년 4월 25일팟캐스트A Week of PCB Layout in an Hour: Quilter Trains Agents, Not Imitators진행자 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.기업과 전략Reinforcement LearningRL environments & simulators+3
1:58:43EN
Cognitive Revolution "How AI Changes Everything"· 2024년 2월 7일팟캐스트A Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.진행자 Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.모델과 학습AI HistoryNeuroscience & AI+3
1:07:29EN
Lex Fridman팟캐스트Deep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZero진행자 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.모델과 학습Reinforcement LearningDeep Learning+3
1:27:30EN
Lex Fridman팟캐스트From NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lecture진행자 Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.모델과 학습Reinforcement LearningDeep Learning+2
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