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1:57:00ENLess Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI FirstModeration: 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.
1:54:44ENPreferences Are Data. The Alignment Target Is Norms.Moderation: 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.
1:59:47ENBCI Would Take 30 Years. This Studio Pivoted to Alignment InsteadModeration: Nathan LabenzJudd Rosenblatt and Mike Vaiana of AE Studio describe two biologically inspired results that do not need interpretability breakthroughs to work.
2:15:39ENRoman Yampolskiy Puts Superintelligent Ruin at 99.99 PercentGast: Roman Yampolskiy · Moderation: 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.
3:17:51ENWhoops is the sound of getting less wrong: Yudkowsky, two weeks after GPT-4Gast: Eliezer Yudkowsky · Moderation: 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.
1:23:56ENA Three-Month Window: The AI 2027 Authors on Superhuman Coders, Faked Alignment and Who Ends Up in ControlModeration: 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.
1:55:04ENMining the Computational Universe: Stephen Wolfram on What AI Can and Can't Be Told to DoGast: Stephen Wolfram · Moderation: 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.









