machine intelligence

Today we explore the age-old question of whether machines can think. Looking at definitions of "thinking", philosophical perspectives, and Alan Turing's famous test, we found machines can now excel at many narrow tasks but general human-level cognition remains elusive. Current AI excels at optimization, pattern recognition, and quantitative performance but still lacks abilities like creativity, reasoning, and consciousness that are hallmarks of human thought. Exciting innovations are emerging in natural language processing and neural networks that may continue to blur the lines between artificial and biological intelligence.

But for now, while machines have come a long way, the essence of human thinking remains difficult to replicate artificially. How we ethically combine the complementary strengths of humans and AI promises to be an increasingly important conversation as technology progresses.

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This podcast was generated with the help of artificial intelligence. We do fact check with human eyes, but there might still be hallucinations in the output. Music credit: "Modern Situations by Unicorn Heads"

Yann LeCun is the Chief AI Scientist at Meta, professor at NYU, Turing Award winner, and one of the seminal researchers in the history of machine learning. Please support this podcast by checking out our sponsors: - Public Goods: https://publicgoods.com/lex and use code LEX to get $15 off - Indeed: https://indeed.com/lex to get $75 credit - ROKA: https://roka.com/ and use code LEX to get 20% off your first order - NetSuite: http://netsuite.com/lex to get free product tour - Magic Spoon: https://magicspoon.com/lex and use code LEX to get $5 off EPISODE LINKS: Yann's Twitter: https://twitter.com/ylecun Yann's Facebook: https://www.facebook.com/yann.lecun Yann's Website: http://yann.lecun.com/ Books and resources mentioned: Self-supervised learning (article): https://bit.ly/3Aau1DQ PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: - Check out the sponsors above, it's the best way to support this podcast - Support on Patreon: https://www.patreon.com/lexfridman - Twitter: https://twitter.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Medium: https://medium.com/@lexfridman OUTLINE: Here's the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) - Introduction (06:58) - Self-supervised learning (17:17) - Vision vs language (23:08) - Statistics (28:55) - Three challenges of machine learning (34:45) - Chess (42:47) - Animals and intelligence (52:31) - Data augmentation (1:13:51) - Multimodal learning (1:25:40) - Consciousness (1:30:25) - Intrinsic vs learned ideas (1:34:37) - Fear of death (1:42:29) - Artificial Intelligence (1:56:18) - Facebook AI Research (2:12:56) - NeurIPS (2:29:08) - Complexity (2:37:33) - Music (2:42:28) - Advice for young people

If a machine told you it was conscious, how could you tell if it was lying? Indeed, how can you tell that any random human in your life is lying when they speak of their own consciousness. Join Robert Lamb and Joe McCormick for a stirring discussion on AI consciousness, philosophical zombies and the coming techno-cognitive dilemma. 

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