絞り込み結果
9 件並び順
13:30EN
3Blue1Brown· 2025年8月17日How AlphaGeometry Combines Logical Proof with Creative ConstructionAleph0Aleph0 explains how a symbolic geometry solver gets surprisingly far without AI, and how a language model supplies the auxiliary constructions that take it to Olympiad level.
9:59EN
Lex FridmanポッドキャストIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learningホスト Lex FridmanIn a short clip from his 2020 conversation with Lex Fridman, Ilya Sutskever explains why vision, language and reinforcement learning share the same few principles, and why asking which problem is harder is the wrong question.
11:11ENLex Fridmanポッドキャスト · 2 人Yann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not Generalゲスト Yann Lecun · ホスト Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.
10:16ENLex Fridmanポッドキャスト · 2 人Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Thinkゲスト Yann Lecun · ホスト Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
13:58ENLex FridmanポッドキャストDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoホスト Lex FridmanDavid Silver of DeepMind walks through what reinforcement learning is, how its building blocks fit together, and why deep neural networks keep surprising even the experts.
10:34ENLex Fridmanポッドキャスト · 2 人Why Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AIゲスト François Chollet · ホスト 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.
10:39ENLex FridmanポッドキャストStatistics as Decision-Making: Michael I. Jordan on Bayesians, Frequentists and the Ideas Between Themホスト Lex FridmanBerkeley's Michael I. Jordan explains where statistics came from, why it is really about decisions, and how empirical Bayes and false discovery rate bridge two rival philosophies.
11:29ENLex FridmanポッドキャストWhy Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has Seenホスト Lex FridmanLex Fridman walks through the neural network, data annotation, Dojo and Tesla Bot announcements and what they say about solving real-world robotics.
11:23ENLex Fridmanポッドキャスト · 2 人Science Is a Self-Improving System That Isn't Exploding: Chollet on the Limits of an Intelligence Explosionゲスト François Chollet · ホスト Lex FridmanFrançois Chollet uses the history of science to argue that recursive self-improvement meets exponential friction and yields linear, not explosive, progress.