筛选结果
165 篇排序
20:34ENTeaching Machines the Frameworks Humans Take for Granted嘉宾 David Ferrucci · 主持 Lex FridmanDavid Ferrucci explains why AI needs shared interpretive frameworks, not just data and pattern matching, to reason and communicate like humans.
1:25:01EN → 简体中文Gary Marcus:深度学习模仿智能,却并不理解嘉宾 Gary Marcus · 主持 Lex Fridman在 Lex Fridman 的播客上,这位纽约大学荣休教授、《重启 AI》(Rebooting AI)的合著者认为,感知与推理需要不同的工具;在机器能够表示伤害、瓶子和意图之前,可信的 AI 不可能实现。
1:59:49EN → 简体中文智能不是楼的高度:François Chollet 谈 Keras、深度学习,以及为什么通用人工智能(AGI)不会爆发式崛起嘉宾 François Chollet · 主持 Lex FridmanKeras 作者在 Lex Fridman 的节目里说,智能是大脑、身体与问题相互作用的产物;科学早已是一个会递归自我改进的超人系统,产出却只呈线性增长;而近期真正的危险是信息流。
2:09:42EN → 简体中文大脑在地图上导航,不靠给图像分类嘉宾 Jeff Hawkins · 主持 Lex FridmanJeff Hawkins 在与 Lex Fridman 的对谈中解释,新皮层(neocortex)为何把世界存成成千上万个会投票的参考框架(reference frame),以及为什么把今天的网络继续做大,无法抵达那里。
1:19:59EN → 简体中文Schmidhuber 的赌注:真正的元学习改写的是学习者本身,而不只是最后一层嘉宾 Juergen Schmidhuber · 主持 Lex FridmanJürgen Schmidhuber 向 Lex Fridman 讲述,哥德尔机、把压缩当作科学、Power Play、LSTM 和世界模型,如何都源于一个少年时的计划:把一个人的好奇心放大,造出一个比他本人强得多的物理学家。
37:53EN → 简体中文Steven Pinker:智能并不等于权力意志嘉宾 Steven Pinker · 主持 Lex Fridman这位哈佛心理学家在和 Lex Fridman 的对谈中说,把 AI 与核武器相类比、回形针的故事,以及对 AI 接管人类的恐惧,为什么都把解决问题和支配混为一谈。
57:54EN → 简体中文通过每一项图灵测试的 2040 年 Siri,仍然不会有意识嘉宾 Christof Koch · 主持 Lex Fridman神经科学家 Christof Koch 在与 Lex Fridman 的对话中说明:智能是一种功能,意识是一种存在;一个完美的大脑模拟,并不比模拟黑洞的笔记本电脑更有内在的体验。
1:38:23EN → 简体中文Yudkowsky 与 Hanson 辩论:智能爆炸会集中于一处吗?Eliezer Yudkowsky, Robin Hanson一场关于自我改进的 AI、知识积累、创新,以及先行者能否取得决定性领先的历史辩论。
15:01ENDeep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still Lacks嘉宾 Daniel Kahneman · 主持 Lex FridmanThe Nobel-winning psychologist tells Lex Fridman how his fast-and-slow thinking framework maps onto deep learning, and why driving among pedestrians may require understanding people.
11:11ENYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not General嘉宾 Yann Lecun · 主持 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.
1:17:38ENBrains Are Body Regulators: Lisa Feldman Barrett on Why Emotions Are Constructed, Not Detected嘉宾 Lisa Feldman Barrett · 主持 Lex FridmanIn a guest talk for MIT's AGI course, neuroscientist Lisa Feldman Barrett explains why faces don't display emotions, why brains exist to run bodies, and what that means for building human-like AI.
1:19:13ENAlien Intelligence, Radical Upside: Nathan Labenz on Why AI Is the Next Industrial Revolution主持 Nathan LabenzIn the second episode of The Cognitive Revolution, Nathan Labenz tells Erik Torenberg how he went from asteroid-watching AI skeptic to full-time AI scout, and lays out the upside and downside cases.
18:46ENDeep Learning Plus One Idea: Ilya Sutskever on Building AGI主持 Lex FridmanIn a May 2020 conversation, Sutskever discusses self-play, simulation, bodies and consciousness, tests of intelligence, and how an AGI might be governed and aligned.
15:41ENAbolishing Involuntary Death: Ben Goertzel on Immortality, Pain and the Meaning of Life主持 Lex FridmanIn a clip from Lex Fridman's podcast, AI researcher Ben Goertzel argues that death and pain should be optional, and sketches what it would take to fund a serious attack on aging.
2:53:45ENJoscha Bach on Seven Stages of Lucidity, Brutalist LLMs, and Why Life on Earth Isn't Only About Humans嘉宾 Joscha Bach · 主持 Lex FridmanA wide-ranging conversation on how minds are built, what language models are missing, and how an AI-saturated world might change consciousness, identity and risk.
17:40ENFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AI主持 Lex FridmanDeepMind's David Silver explains why removing human knowledge made AlphaZero stronger and more general, and how MuZero extended the idea to worlds with unknown rules.
53:39ENA Libertarian's Case for Regulating AI: Kill Switches, Chip Choke Points and a New Form of Life主持 Nathan LabenzLindy founder Flo Crivello explains why a self-described accelerationist makes an exception for superintelligence, and what he thinks of Biden's executive order.
1:30:52ENBuilding Minds from Unified Theories: Nate Derbinsky on Cognitive Architectures, Soar, and the Case for Forgetting嘉宾 MIT AGI · 主持 Lex FridmanA guest lecture in MIT's AGI course on how cognitive architectures try to assemble human-level intelligence, and how studying human memory made the Soar architecture faster and better.
11:41ENTeaching Machines Humility: Stuart Russell on Escaping the King Midas Problem嘉宾 Stuart Russell · 主持 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.
1:55:04ENMining the Computational Universe: Stephen Wolfram on What AI Can and Can't Be Told to Do嘉宾 Stephen Wolfram · 主持 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.
1:00:25ENCan Machines Think? A Guided Tour of Turing's Test, Its Critics and Its Successors嘉宾 Turing Test · 主持 Lex FridmanLex Fridman walks through Alan Turing's 1950 paper, the objections to it, and the benchmarks that have tried to replace or extend the imitation game.
24:08ENIntelligence Is Not Just Prediction: David Ferrucci on Explanation, Persuasion and Shared Meaning嘉宾 David Ferrucci · 主持 Lex FridmanThe lead of IBM's Watson team argues that predicting well is only half of intelligence, and that being understood by others is the other half.
23:11ENNick Bostrom on Superintelligence: Why the Upside Deserves as Much Attention as the Risk嘉宾 Nick Bostrom · 主持 Lex FridmanIn a clip from the Lex Fridman Podcast, Oxford philosopher Nick Bostrom defines superintelligence, discusses intelligence explosions, and sketches what a good AGI future might look like.
20:36ENWhy Simple Theories Win: Marcus Hutter on Occam's Razor, Compression and Kolmogorov Complexity主持 Lex FridmanDeepMind researcher Marcus Hutter explains Solomonoff induction, why compression equals understanding, and how a simple universe can still look rich.
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