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3 diapositivas13:34EN
MBMatthew Berman· 23 sept 2024Sam 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.AGIScaling LawsAgentes+1
14:55EN
Lex Fridman· 29 oct 2019Pódcast · 2 vocesKasparov 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.AI HistoryPhilosophyHuman-AI Collaboration+3
11:11EN
Lex FridmanPódcast · 2 vocesYann 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.Modelos y entrenamientoBenchmarksAGI+3
11:41EN
Lex FridmanPódcast · 2 vocesTeaching 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.SeguridadSeguridad y gobernanzaExistential Risk+3
10:17EN
Lex FridmanPódcastNeither 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.PhilosophyEvolutionAGI
11:23EN
Lex FridmanPódcast · 2 vocesScience 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.Modelos y entrenamientoAGIAI research+3