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13:34ENSam Altman’s “Intelligence Age”: Superintelligence, Scaling and WorkMatthew Berman · Forward FutureMatthew Berman reads Altman’s 2024 essay and discusses its predictions for AI assistants, education, infrastructure and jobs.
14:55ENKasparov on Deep Blue, AlphaZero, and Why Machines Win Closed Systems but Humans Still Choose the QuestionsInvitado: Garry Kasparov · Presenta: Lex FridmanGarry Kasparov revisits the 1997 loss to Deep Blue, explains why machines beat humans in closed systems, and argues that the human role is to pick the right questions and not interfere with superior machine knowledge.
11:11ENYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not GeneralInvitado: Yann Lecun · Presenta: Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.
11:41ENTeaching Machines Humility: Stuart Russell on Escaping the King Midas ProblemInvitado: Stuart Russell · Presenta: 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.
10:17ENNeither Saints Nor Sinners: Ben Goertzel on the Selfish and Altruistic Human MixPresenta: Lex FridmanAI researcher Ben Goertzel explains why humans are a blend of selfishness and altruism, and how much culture can shift that balance.
11:23ENScience Is a Self-Improving System That Isn't Exploding: Chollet on the Limits of an Intelligence ExplosionInvitado: François Chollet · Presenta: Lex FridmanFrançois Chollet uses the history of science to argue that recursive self-improvement meets exponential friction and yields linear, not explosive, progress.








