筛选结果
24 篇排序
50:57EN
Unsupervised Learning: With Jacob Effron· 2026年7月9日播客A Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuber主持 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日播客Two Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.主持 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日播客A Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still Miss主持 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日播客Gradient Descent at Test Time: Titans Pushes LLM Context to 10 Million Tokens主持 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日播客He bet company equity that Transformer would last — then drew an AI map for 12,000 companies主持 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日播客A DNA Model That Can Tell Which Genes You Cannot Touch主持 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日播客 · 2 人对谈A perfect demo is ten years from a product you can pay for主持 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日播客267 Papers in Seven Months: Albert Gu Explains the State Space Model Revolution主持 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日播客 · 2 人对谈Five Independent Teams Found the Same 10-to-1 Mix That Beats Transformers主持 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日播客A Gibberish Prompt Unlocks What GPT-J Plans Three Tokens Ahead主持 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日播客Seeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 Days主持 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日播客Trained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home Turf主持 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日播客 · 2 人对谈Reliability is the bottleneck. Autonomy is what would make AI feel alive.主持 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日播客 · 2 人对谈The Author of Attention Is All You Need Now Compiles mRNA Like Bytecode主持 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日播客AI’s product advantage is consistency. Its real weakness is getting conned.主持 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日播客Half an Hour to a Circuit in GPT-2 Small — and a Quadratic Wall Before GPT-3主持 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日播客A Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer Away主持 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日播客1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2主持 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日播客 · 2 人对谈AGI as a side effect: Noam Shazeer on Transformers, Character.AI, and two-hour chats主持 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日播客 · 2 人对谈The Night AlphaStar Beat TLO, the Team Went to a Bar嘉宾 Oriol Vinyals · 主持 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日播客Deep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke Through主持 Lex FridmanA tour of the architectural, applied, and automation breakthroughs that defined deep learning in 2018 and set up 2019.
9:59ENLex 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.
1:16:52ENCognitive Revolution "How AI Changes Everything"播客Mamba After 90 Days: What 30 Papers Reveal About State Space Models, Hybrids, and Mixture of Experts主持 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"播客Pause Tokens, Analogical Prompts and Ring Attention: A Tour of the Transformer's Next Upgrades主持 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.