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4 件
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4:25:13EN
Lex Fridman· 2026年1月31日ポッドキャストThe Architecture Barely Changed. Data, Cost, and Open Weights Did.ホスト Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.モデルと学習Scaling LawsOpen-weight models+3
2:29:04EN
Lex Fridman· 2024年10月6日ポッドキャスト · 2 人Keep the Programmer in the Driver's Seat: Cursor's Founders on Tab, Agents, and Zero-Entropy Editingゲスト Cursor Team · ホスト Lex FridmanMichael Truell, Aman Sanger, Sualeh Asif, and Arvid Lunnemark tell Lex Fridman why they forked VS Code, how Tab and Apply actually work, and why most programming still needs a human iterating in real time.コーディングエージェント開発ワークフローとテストAI interface design+3
26:02EN
Lex Fridman· 2020年2月9日ポッドキャストMoore’s Law Is Not Dead—It Is a Cascade of S-Curvesホスト Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.インフラとデプロイSemiconductorsScaling Laws+3
1:18:48EN
Lex FridmanポッドキャストData Movement, Not Math: How to Make Deep Learning Fit on Robots and Phonesホスト Lex FridmanMIT professor Vivienne Sze explains why moving data dominates the energy cost of neural networks and how co-designing hardware and algorithms can cut it by orders of magnitude.インフラとデプロイInferenceAI cost & performance+3