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4 张幻灯片13:30EN → 简体中文
3Blue1Brown· 2025年8月17日AlphaGeometry 如何结合逻辑证明与创造性作图Aleph0Aleph0 讲解了符号几何求解器如何在不使用 AI 的情况下解决大量难题,以及语言模型如何提供辅助作图,让系统达到奥数竞赛水平。MathematicsReasoning & test-time computeAI research+2
9:59EN
Lex Fridman播客Is Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learning主持 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.模型与训练机器学习基础Deep Learning+3
11:11EN
Lex Fridman播客 · 2 人对谈Yann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not General嘉宾 Yann Lecun · 主持 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.模型与训练Benchmarks通用人工智能+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
13:58EN
Lex Fridman播客Deep Reinforcement Learning, Explained by the Researcher Behind AlphaGo主持 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.模型与训练Reinforcement Learning机器学习基础+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
10:39EN
Lex Fridman播客Statistics as Decision-Making: Michael I. Jordan on Bayesians, Frequentists and the Ideas Between Them主持 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.模型与训练机器学习基础Decision Making+2
11:29EN
Lex Fridman播客Why Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has Seen主持 Lex FridmanLex Fridman walks through the neural network, data annotation, Dojo and Tesla Bot announcements and what they say about solving real-world robotics.模型与训练Autonomous DrivingRobotics+3
11:23EN
Lex Fridman播客 · 2 人对谈Science Is a Self-Improving System That Isn't Exploding: Chollet on the Limits of an Intelligence Explosion嘉宾 François Chollet · 主持 Lex FridmanFrançois Chollet uses the history of science to argue that recursive self-improvement meets exponential friction and yields linear, not explosive, progress.模型与训练通用人工智能AI research+3