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スライド 16 枚23:39ZH
跟李沐学AI· 2025年7月23日李沐:给文本大模型加入一千万小时语音,开源 Higgs Audio李沐 · Boson AI李沐介绍团队如何在文本大语言模型的训练里加入大量语音数据,做成能听能说的 AudioLLM,并把 Higgs Audio 开源。他讲了架构取舍、token 压缩、数据从哪来,以及怎么在 3090 上跑起来。音声 AIMultimodal AIモデルと学習+2
18:46EN
Lex FridmanポッドキャストDeep Learning Plus One Idea: Ilya Sutskever on Building AGIホスト Lex FridmanIn a May 2020 conversation, Sutskever discusses self-play, simulation, bodies and consciousness, tests of intelligence, and how an AGI might be governed and aligned.モデルと学習AGI(汎用人工知能)Reinforcement Learning+3
17:40EN
Lex FridmanポッドキャストFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AIホスト Lex FridmanDeepMind's David Silver explains why removing human knowledge made AlphaZero stronger and more general, and how MuZero extended the idea to worlds with unknown rules.モデルと学習Reinforcement LearningAI research+3
16:41EN
Lex FridmanポッドキャストAlphaFold 2 and the Protein-Folding Breakthrough: Why Lex Fridman Calls It a Landmark for AI and Biologyホスト Lex FridmanA quick explainer on DeepMind's CASP14 result, how protein folding works, how AlphaFold 1 and 2 likely differ, and what the advance could unlock.モデルと学習AI for scienceDeep Learning+2
20:36EN
Lex FridmanポッドキャストWhy Simple Theories Win: Marcus Hutter on Occam's Razor, Compression and Kolmogorov Complexityホスト Lex FridmanDeepMind researcher Marcus Hutter explains Solomonoff induction, why compression equals understanding, and how a simple universe can still look rich.モデルと学習機械学習の基礎AI research+3
20:50EN
Lex FridmanポッドキャストGlitches as Features: What John Hopfield Says Artificial Neural Networks Are Missingホスト Lex FridmanIn a short conversation with Lex Fridman, physicist and neural-network pioneer John Hopfield compares evolved brains with today's artificial networks and explains why he expects AI to borrow from biology generation after generation.モデルと学習Neuroscience & AI機械学習の基礎+3