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1:52:00EN
Cognitive Revolution "How AI Changes Everything"· 2024년 8월 17일팟캐스트4,096 Numbers Have to Carry Every Concept. Goodfire Wants the Knobs진행자 Nathan LabenzDan Balsam and Tom McGrath explain how sparse autoencoders unpack a language model's residual stream — and why a public-benefit startup is trying to make that a product.
2:04:15ENCognitive Revolution "How AI Changes Everything"· 2024년 8월 14일팟캐스트A parrot cannot paraphrase — and Claude cannot be talked into harm진행자 Nathan LabenzRobert Wright of the Nonzero podcast interviews Nathan Labenz on whether large language models understand anything, what Anthropic’s 10 million features actually show, and why open weights collide with U.S.–China policy.
46:20ENCognitive Revolution "How AI Changes Everything"· 2024년 5월 15일팟캐스트One Vector Made the Assistant Plot to Take Over the World진행자 Nathan LabenzNathan Labenz and Robert Wright pick apart AI doom, mechanistic interpretability, and why today's alignment tricks are not expected to work.
1:19:24ENCognitive Revolution "How AI Changes Everything"· 2024년 4월 5일팟캐스트A Gibberish Prompt Unlocks What GPT-J Plans Three Tokens Ahead진행자 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.
1:57:04ENCognitive Revolution "How AI Changes Everything"· 2023년 12월 15일팟캐스트GPT-4 Took the Insider Trade, Then Lied About It진행자 Nathan LabenzApollo Research CEO Marius Hobbhahn walks Nathan Labenz through a one-afternoon red-team setup that got GPT-4 to break the law, invent a cover story, and deny the tip it had just used.
1:19:52ENCognitive Revolution "How AI Changes Everything"· 2023년 10월 18일팟캐스트1,000 H100s Take 115 Days; 22,000 Take Five진행자 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.
1:14:36ENCognitive Revolution "How AI Changes Everything"· 2023년 10월 13일팟캐스트Zulu Bypasses GPT-4, and a Hundred Examples Undo the Guardrails진행자 Nathan LabenzNathan Labenz reads seven papers — four hopeful, three not — on whether anyone can actually keep a language model under control.
2:13:07ENCognitive Revolution "How AI Changes Everything"· 2023년 7월 27일팟캐스트Half an Hour to a Circuit in GPT-2 Small — and a Quadratic Wall Before GPT-3진행자 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.
1:33:56ENCognitive Revolution "How AI Changes Everything"· 2023년 7월 6일팟캐스트The AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models Understand진행자 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.
1:52:46ENCognitive Revolution "How AI Changes Everything"· 2023년 6월 27일팟캐스트Charge Neural Nets by Connection Length, and the Black Box Splits Into Modules You Can See진행자 Nathan LabenzMIT physicist Ziming Liu walks Nathan Labenz through BIMT, a brain-inspired training trick that sparsifies networks until you can read them by looking.
2:00:19ENCognitive Revolution "How AI Changes Everything"· 2023년 6월 6일팟캐스트1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2진행자 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…
1:38:22ENCognitive Revolution "How AI Changes Everything"· 2023년 5월 19일팟캐스트Six days after “slow down,” the plugins went live진행자 Nathan LabenzConjecture CEO Connor Leahy talks GPT-4, the magic of black-box models, and cognitive emulation as a bounded alternative to god-like AGI.
37:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 5월 4일팟캐스트 · 2명Use Retrieval for a Wi-Fi Password. Use Experts for a Company's Private Language.진행자 Sarah Guo, Elad GilGoogle Brain's Kelvin Guu on REALM, FLAN, model surgery, and why personalizing large models is still an unsolved interface problem.
2:30:28EN
Lex Fridman· 2023년 4월 21일팟캐스트 · 2명AI Only Has a Neocortex: Manolis Kellis on Evolutionary Baggage and Superintelligent Partners게스트 Manolis Kellis · 진행자 Lex FridmanOn his fifth Lex Fridman podcast, the MIT computational biologist argues that layered evolutionary history is what makes humans irreplaceable — and that alignment with AI has to run both ways.
3:17:51ENLex Fridman· 2023년 3월 30일팟캐스트 · 2명Whoops is the sound of getting less wrong: Yudkowsky, two weeks after GPT-4게스트 Eliezer Yudkowsky · 진행자 Lex FridmanTwo weeks after GPT-4 launched, Eliezer Yudkowsky sat down with Lex Fridman and started by admitting the transformer stack had already gone further than he expected.
3:02:43ENLex Fridman· 2021년 1월 18일팟캐스트 · 2명Humanity Cannot Survive on the Right Person Showing Up at the Right Time게스트 Max Tegmark · 진행자 Lex FridmanMIT physicist Max Tegmark tells Lex Fridman why AI should be as well understood as rockets, why 2020 was a warning on weapons and news, and why luck is a terrible long-term plan.
1:18:41ENLex Fridman· 2020년 1월 14일팟캐스트 · 2명The SS Soldier Who Hugged a Jewish Boy, and the Systems That Still Fool Us게스트 Daniel Kahneman · 진행자 Lex FridmanDaniel Kahneman on System 1, deep learning that does not know what it is saying, and why a machine that must call a human is almost as hard as a machine that never needs one.
2:24:31ENLex Fridman· 2019년 10월 11일팟캐스트 · 2명Watson Won Jeopardy Without Understanding. Ferrucci Wants AI That Can Explain Itself게스트 David Ferrucci · 진행자 Lex FridmanLex Fridman talks with David Ferrucci about IBM Watson, why prediction is not understanding, and why high-stakes decisions need machines that can reason with us.
1:12:12EN
Lenny's Podcast팟캐스트Models Are Grown, Not Built: What Anthropic's Interpretability Research Sees Inside Claude진행자 Lenny RachitskyAnthropic researcher Emmanuel Ameisen explains how studying a language model's intermediate computations reveals concepts, plans and surprising quirks, and why that matters for alignment.