絞り込み結果
23 件並び順
50:57EN
Unsupervised Learning: With Jacob Effron· 2026年7月9日ポッドキャストA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuberホスト Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.
2:59:44EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月3日ポッドキャストTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.ホスト Nathan LabenzGoogle researcher Ali Behrouz tells Nathan Labenz how stacking update frequencies — not just layers — and an offline sleep phase could give language models genuine continual learning.
1:13:33ENUnsupervised Learning: With Jacob Effron· 2026年6月3日ポッドキャストA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still Missホスト Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.
2:12:00ENCognitive Revolution "How AI Changes Everything"· 2025年5月15日ポッドキャストGradient Descent at Test Time: Titans Pushes LLM Context to 10 Million Tokensホスト Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.
1:04:54ENUnsupervised Learning: With Jacob Effron· 2024年11月12日ポッドキャストHe bet company equity that Transformer would last — then drew an AI map for 12,000 companiesホスト Jacob EffronDatabricks chief AI scientist Jonathan Frankle tells enterprises when to prompt, fine-tune, or pre-train, and why he still refuses to forecast the next architecture.
1:18:32ENCognitive Revolution "How AI Changes Everything"· 2024年9月20日ポッドキャストA DNA Model That Can Tell Which Genes You Cannot Touchホスト Nathan LabenzStanford's Brian Hie walks through hybrid architectures, a genome-scale language model trained only on DNA, and an antibody that binds 25 times tighter than nature.
44:16EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年9月5日ポッドキャスト · 2 人A perfect demo is ten years from a product you can pay forホスト Sarah Guo, Elad GilAndrej Karpathy uses Waymo's decade-long gap, Tesla's software bet, and a new AI course to argue that autonomous intelligence will stall at product and globalization, not at the first impressive clip.
1:42:16ENCognitive Revolution "How AI Changes Everything"· 2024年7月4日ポッドキャスト267 Papers in Seven Months: Albert Gu Explains the State Space Model Revolutionホスト Nathan LabenzThe Mamba co-author walks through five years of recurrent-model work, why selective compression beats a growing KV cache, and what Mamba 2 trades away to train faster.
34:09ENNo Priors: AI, Machine Learning, Tech, & Startups· 2024年6月27日ポッドキャスト · 2 人Five Independent Teams Found the Same 10-to-1 Mix That Beats Transformersホスト Sarah Guo, Elad GilThe authors of S4 and Mamba argue that mostly state-space layers plus a dash of attention is the architecture that actually works—and they are shipping it first as real-time speech.
1:19:24ENCognitive Revolution "How AI Changes Everything"· 2024年4月5日ポッドキャストA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens Aheadホスト Nathan LabenzNortheastern’s Bau Lab shows that a 40,000-parameter soft prompt can read a model’s future words, and that about ten attention heads carry the task itself.
1:20:44ENCognitive Revolution "How AI Changes Everything"· 2024年3月30日ポッドキャストSeeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 Daysホスト Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.
2:30:06ENCognitive Revolution "How AI Changes Everything"· 2023年12月22日ポッドキャストTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home Turfホスト Nathan LabenzIn a solo emergency episode, Nathan Labenz argues that Albert Gu and Tri Dao's selective state space model is the first architecture since 2017 that deserves to share the Transformer’s throne.
41:58ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023年11月2日ポッドキャスト · 2 人Reliability is the bottleneck. Autonomy is what would make AI feel alive.ホスト Sarah Guo, Elad GilIlya Sutskever talks with Sarah Guo and Elad Gil about AlexNet, OpenAI’s capped-profit bet, why smaller models mainly lose reliability, and the line he draws for digital life.
35:24ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023年8月24日ポッドキャスト · 2 人The Author of Attention Is All You Need Now Compiles mRNA Like Bytecodeホスト Sarah Guo, Elad GilJakob Uszkoreit on why Transformers won, why models spend compute on the wrong things, and why drug discovery has to become generation rather than screening.
39:02ENCognitive Revolution "How AI Changes Everything"· 2023年8月10日ポッドキャストAI’s product advantage is consistency. Its real weakness is getting conned.ホスト Nathan LabenzNathan Labenz updates the Cognitive Revolution scouting report: jailbreaks, resume automation, Med-PaLM’s 40% radiology win, and what might follow Transformers.
2:13:07ENCognitive Revolution "How AI Changes Everything"· 2023年7月27日ポッドキャストHalf an Hour to a Circuit in GPT-2 Small — and a Quadratic Wall Before GPT-3ホスト Nathan LabenzArthur Conmy walks Nathan Labenz through ACDC, the algorithm that automates the most tedious step of mechanistic interpretability: finding which transformer components actually do a task.
1:32:22ENCognitive Revolution "How AI Changes Everything"· 2023年6月29日ポッドキャストA Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer Awayホスト Nathan LabenzLili Yu of Meta AI explains a multiscale transformer that predicts million-byte sequences, skips tokenization, and aims to model any file as raw bytes.
2:00:19ENCognitive Revolution "How AI Changes Everything"· 2023年6月6日ポッドキャスト1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2ホスト Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…
35:36ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023年4月13日ポッドキャスト · 2 人AGI as a side effect: Noam Shazeer on Transformers, Character.AI, and two-hour chatsホスト Sarah Guo, Elad GilIn April 2023, the Transformer co-author told No Priors how a 22-person startup turned open-ended chat into a consumer product — and treated AGI as a byproduct of making the model smarter.
1:46:01EN
Lex Fridman· 2019年4月29日ポッドキャスト · 2 人The Night AlphaStar Beat TLO, the Team Went to a Barゲスト Oriol Vinyals · ホスト Lex FridmanOriol Vinyals on how DeepMind turned StarCraft II into a sequence problem, built a league of agents, and still refuses to call the game solved.
46:25ENLex Fridman· 2019年1月17日ポッドキャストDeep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke Throughホスト Lex FridmanA tour of the architectural, applied, and automation breakthroughs that defined deep learning in 2018 and set up 2019.
1:16:52ENCognitive Revolution "How AI Changes Everything"ポッドキャストMamba After 90 Days: What 30 Papers Reveal About State Space Models, Hybrids, and Mixture of Expertsホスト Nathan LabenzNathan Labenz and AI scout Jason Meaux survey the first wave of Mamba-inspired research, from mechanistic studies and synthetic-task tradeoffs to hybrid architectures and MoE variants.
1:03:10ENCognitive Revolution "How AI Changes Everything"ポッドキャストPause Tokens, Analogical Prompts and Ring Attention: A Tour of the Transformer's Next Upgradesホスト Nathan LabenzNathan Labenz and Trey Kollmer walk through five recent papers on pausing, backspacing, prompting, streaming and long-context training, and sketch how they might combine into a more capable model.