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31:00EN
AI Explained· 2026년 10월 12일Why AI Labs Keep Racing Despite Their Own Warnings of a Major BreachSam Altman, John Schulman · OpenAIAI Explained examines weakening safeguards, the incentives behind the frontier race, and why research breakthroughs make the next 18 months difficult to forecast.
1:57:00EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 28일팟캐스트Less Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI First진행자 Nathan LabenzDoom Debates host Liron Shapira presses OpenAI technical staffer roon on extinction odds, alignment-by-default, and a plan that even he admits is balancing on razor wire.
1:54:44ENCognitive Revolution "How AI Changes Everything"· 2024년 11월 30일팟캐스트Preferences Are Data. The Alignment Target Is Norms.진행자 Nathan LabenzMIT PhD student Tan Zhi Xuan tells The Cognitive Revolution why role ethics and contractualism should replace preference maximization — and how grid-world agents infer rules from apples left uneaten.
1:59:47ENCognitive Revolution "How AI Changes Everything"· 2024년 10월 5일팟캐스트BCI Would Take 30 Years. This Studio Pivoted to Alignment Instead진행자 Nathan LabenzJudd Rosenblatt and Mike Vaiana of AE Studio describe two biologically inspired results that do not need interpretability breakthroughs to work.
2:15:39EN
Lex Fridman· 2024년 6월 2일팟캐스트 · 2명Roman Yampolskiy Puts Superintelligent Ruin at 99.99 Percent게스트 Roman Yampolskiy · 진행자 Lex FridmanThe AI safety researcher tells Lex Fridman that controlling AGI is as impossible as a perpetual motion machine, and that tests, open source, and regulation cannot close the gap.
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.
1:23:56EN
Unsupervised Learning: With Jacob Effron팟캐스트A Three-Month Window: The AI 2027 Authors on Superhuman Coders, Faked Alignment and Who Ends Up in Control진행자 Jacob EffronDaniel Kokotajlo and Thomas Larsen walk through their AI 2027 scenario, where they disagree on timelines and alignment, and what they think governments and the public should do.
11:41ENLex Fridman팟캐스트 · 2명Teaching Machines Humility: Stuart Russell on Escaping the King Midas Problem게스트 Stuart Russell · 진행자 Lex FridmanIn a short clip from a 2018 conversation, Berkeley's Stuart Russell explains why fixed objectives make superintelligent AI dangerous and why uncertainty about our goals is the fix.
1:55:04ENLex Fridman팟캐스트 · 2명Mining the Computational Universe: Stephen Wolfram on What AI Can and Can't Be Told to Do게스트 Stephen Wolfram · 진행자 Lex FridmanIn a talk for MIT's AGI course, Stephen Wolfram connects Wolfram Alpha, simple programs, computational irreducibility and the problem of telling machines what humans want.