筛选结果
23 篇排序
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月4日播客19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chip主持 Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.
1:13:33EN
Unsupervised 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.
4:25:13EN → 简体中文
Lex Fridman· 2026年1月31日播客架构几乎没变，变的是数据、成本和开放权重主持 Lex FridmanNathan Lambert 和 Sebastian Raschka 带 Lex Fridman 回顾了这一年：训练方法和数据集的变化，远大于模型设计的变化。展望 2026 年，争论的焦点似乎是推理成本、智能体，以及真正开放的模型该归谁。
1:03:00ENUnsupervised Learning: With Jacob Effron· 2026年1月29日播客A Model That Solves New Math Problems Every Week Still Isn't AGI主持 Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.
1:18:05ENUnsupervised Learning: With Jacob Effron· 2025年12月18日播客The Real Bottleneck in AI Research Is Compute, Not Ideas主持 Jacob EffronAfter NeurIPS, Ari Morcos and Rob Toews sit down with Jacob Effron to argue about plateauing models, SSI’s secrecy, OpenAI’s cash burn, and a set of spicy 2026 bets.
1:39:05ENCognitive Revolution "How AI Changes Everything"· 2025年10月29日播客The Summer GPT-5 Disappointed Does Not Mean AI Progress Has Stalled主持 Nathan LabenzNathan Labenz tells Erik Torenberg why the GPT-5 backlash mixed up product mishaps, naming chaos, and a real jump in capabilities.
1:02:05ENUnsupervised Learning: With Jacob Effron· 2025年9月24日播客$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Math主持 Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.
51:08ENUnsupervised Learning: With Jacob Effron· 2025年4月15日播客The Transformer Co-Author Who Says Scaling Hit a Wall主持 Jacob EffronCohere CEO Aidan Gomez tells Redpoint that a $100 million model is still an amnesiac genius, and that enterprise AI money is concentrating in support, research, and the back office.
1:10:23ENUnsupervised Learning: With Jacob Effron· 2025年3月17日播客A Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still Untapped主持 Jacob EffronThe Transformer co-inventor and Gemini researcher Jack Rae walk through test-time compute, Ilya Sutskever's AGI critique, and a four-year-old who now lectures his teacher about lizards.
48:18ENUnsupervised Learning: With Jacob Effron· 2024年12月6日播客Noam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of Headroom主持 Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.
2:40:58ENCognitive Revolution "How AI Changes Everything"· 2024年11月16日播客Zvi Mowshowitz Still Puts P(doom) at 60%—and Says Not Updating Is Self-Deception主持 Nathan LabenzA six-month recap with the Don't Worry About the Vase author covering Ilya’s SSI, OpenAI’s o1, Claude’s computer use, the SB 1047 veto, and Trump’s return.
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.
1:23:57ENCognitive Revolution "How AI Changes Everything"· 2024年9月4日播客A Training Run Is a Particle Collider—and the China Contest Is a Fifty-Year Race主持 Nathan LabenzSamo Burja tells Nathan Labenz why ChatGPT's virality may have slowed AI science, and why Washington should treat Beijing as an economic rival rather than a military one.
1:01:55ENCognitive Revolution "How AI Changes Everything"· 2024年6月1日播客A $9 AI nurse, an 86 on the medical boards, and a 10% extinction line主持 Nathan LabenzNathan Labenz’s solo scouting report walks from medical state of the art through how models actually learn, then to live players, scaling trends, and a control plan that still does not exist.
1:01:39ENCognitive Revolution "How AI Changes Everything"· 2024年4月13日播客GPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?主持 Nathan LabenzTraining GPT-3 took about a trillion tokens; GPT-4 took about ten trillion. The next jump is a data question as much as a compute one.
1:19:52ENCognitive Revolution "How AI Changes Everything"· 2023年10月18日播客1,000 H100s Take 115 Days; 22,000 Take Five主持 Nathan LabenzNathan Labenz and Trey Kollmer walk through cluster math that turns GPT-4-scale training into a weekly experiment, then four papers on search-augmented models, recursive code improvers, spatial maps inside Llama 2, and what networks do when they have no idea.
1:33:56ENCognitive Revolution "How AI Changes Everything"· 2023年7月6日播客The AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models Understand主持 Nathan LabenzNathan Labenz spends a solo episode walking through what general-purpose models can do, how they are trained, how capabilities unlock, and whether they understand anything at all.
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.
26:02ENLex Fridman· 2020年2月9日播客Moore’s Law Is Not Dead—It Is a Cascade of S-Curves主持 Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.
1:10:19ENUnsupervised Learning: With Jacob Effron播客The Robot That Folded the Laundry: Physical Intelligence’s Three Frontiers主持 Jacob EffronKarol Hausman and Danny Driess explain how robot foundation models moved from coded primitives to web-scale pretraining, and why performance is now the hard gate.
1:14:59EN → 简体中文
Lenny's Podcast播客Ben Mann：AI 还在加速，对齐却不能等到超级智能到来再做主持 Lenny RachitskyAnthropic 联合创始人谈人才争夺、缩放定律、经济图灵测试、就业冲击、离开 OpenAI、宪法式 AI，以及他对超级智能风险的预测。
1:19:48ENLex Fridman播客Bigger Models, Cleaner Splits and Human Baselines: Andrew Ng's Practical Recipe for Applied Deep Learning主持 Lex FridmanIn a 2016 Deep Learning School talk, Andrew Ng distills lessons from leading Baidu's AI team into a workflow for diagnosing models, handling data and building a career.
1:13:40ENUnsupervised Learning: With Jacob Effron播客The Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing Moment主持 Jacob EffronVincent, a distinguished engineer at Waymo, explains how foundation models became teachers for self-driving, why the long tail and causality are the real frontier, and where robotics still lacks its generalist proof point.