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55:13EN
Sequoia Capital· 2024年7月2日播客The Best AI Scores 39% on This Test. Zapier’s Co-Founder Put $1 Million on Beating ItFrançois Chollet designed ARC to measure skill-acquisition efficiency; five years later humans still crush it and frontier models do not.评估与可观测性BenchmarksAGI Timelines+3
1:22:59EN
Cognitive Revolution "How AI Changes Everything"· 2023年12月2日播客If Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%主持 Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.智能体智能体工程Reasoning & test-time compute+3
2:00:19EN
Cognitive Revolution "How AI Changes Everything"· 2023年6月6日播客1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2主持 Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…模型与训练Synthetic dataData quality & curation+3
1:00:36EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年2月2日播客 · 2 人对谈Forty games of Diplomacy, and nobody spotted the bot: Noam Brown’s 100,000x lesson主持 Sarah Guo, Elad GilMeta’s Noam Brown tells Sarah Guo and Elad Gil how Cicero negotiated in English for 40 games on a tiny web community — and why thinking at decision time beat three years of scaling.智能体AI researchReasoning & test-time compute+3
1:26:21EN → 简体中文
Lex Fridman· 2018年12月9日播客 · 2 人对谈机器绝不该把自己的目标奉为圭臬嘉宾 Stuart Russell · 主持 Lex FridmanStuart Russell 与 Lex Fridman 谈元推理(metareasoning)、自动驾驶的可靠性,以及为什么对人类目标的不确定性是控制问题(control problem)的核心。安全安全与治理Autonomous Driving+3
1:45:49EN
Cognitive Revolution "How AI Changes Everything"播客Trust at Scale: Elicit's Founders on Reasoning Languages, World Models and Automating the Company主持 Nathan LabenzAndreas Stuhlmüller and Jungwon Byun explain how Elicit keeps frontier models checkable for high-stakes science, and where they think AI reasoning is heading.智能体World modelsReasoning & test-time compute+3
15:01EN
Lex Fridman播客 · 2 人对谈Deep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still Lacks嘉宾 Daniel Kahneman · 主持 Lex FridmanThe Nobel-winning psychologist tells Lex Fridman how his fast-and-slow thinking framework maps onto deep learning, and why driving among pedestrians may require understanding people.模型与训练Deep LearningAI research+3
10:16EN
Lex Fridman播客 · 2 人对谈Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Think嘉宾 Yann Lecun · 主持 Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.模型与训练机器学习基础Deep Learning+3
58:57EN
Cognitive Revolution "How AI Changes Everything"播客When the Model Learns to Look Around: Apollo Research on Testing o1 for Scheming主持 Nathan LabenzApollo Research founder Marius Hobbhahn explains how his team probed OpenAI's o1 for deception, what it found, and why the trajectory worries him more than the model itself.安全AI security安全与治理+3
57:25EN
Unsupervised Learning: With Jacob Effron播客From RAG to Reasoning: Why the Future of AI Is a System, Not a Model主持 Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.模型与训练Reasoning & test-time computePost-training+3
10:34EN
Lex Fridman播客 · 2 人对谈Why Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AI嘉宾 François Chollet · 主持 Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.模型与训练机器学习基础Deep Learning+2
1:03:10EN
Cognitive Revolution "How AI Changes Everything"播客Pause Tokens, Analogical Prompts and Ring Attention: A Tour of the Transformer's Next Upgrades主持 Nathan LabenzNathan Labenz and Trey Kollmer walk through five recent papers on pausing, backspacing, prompting, streaming and long-context training, and sketch how they might combine into a more capable model.模型与训练Transformers & attention机器学习基础+3