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1:03EN → 简体中文
MBMatthew Berman· 2026年5月9日为什么《EVE Online》适合用于 AI 研究Matthew Berman · Forward FutureMatthew Berman 解释游戏中持续运转的经济和玩家联盟为何可能为长期规划能力提供高难度测试。智能体Reinforcement LearningMulti-agent systems+1
14:55EN
Lex Fridman· 2019年10月29日播客 · 2 人对谈Kasparov on Deep Blue, AlphaZero, and Why Machines Win Closed Systems but Humans Still Choose the Questions嘉宾 Garry Kasparov · 主持 Lex FridmanGarry Kasparov revisits the 1997 loss to Deep Blue, explains why machines beat humans in closed systems, and argues that the human role is to pick the right questions and not interfere with superior machine knowledge.AI HistoryPhilosophyHuman-AI Collaboration+3
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
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