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Lex Fridman PodcastDmitry Korkin: Evolution of Proteins, Viruses, Life, and AI | Lex Fridman Podcast #153
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Episode Details
EPISODE INFO
- Released
- January 11, 2021
- Duration
- 2h 12m
- Channel
- Lex Fridman Podcast
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
Dmitry Korkin is a professor of bioinformatics and computational biology at WPI. Please support this podcast by checking out our sponsors:
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EPISODE LINKS: Dmitry's Website: http://korkinlab.org/ Dmitry's Twitter: https://twitter.com/dmkorkin 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/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 OUTLINE: 0:00 - Introduction 1:57 - Proteins and the building blocks of life 9:00 - Spike protein 15:48 - Coronavirus biological structure explained 20:45 - Virus mutations 27:16 - Evolution of proteins 37:02 - Self-replicating computer programs 44:38 - Origin of life 52:11 - Extraterrestrial life in our solar system 54:08 - Joshua Lederberg 1:00:07 - Dendral 1:03:01 - Why did expert systems fail? 1:05:12 - AlphaFold 2 1:26:50 - Will AI revolutionize art and music? 1:33:49 - Multi-protein folding 1:38:16 - Will AlphaFold 2 result in a Nobel Prize? 1:40:47 - Will AI be used to engineer deadly viruses? 1:55:54 - Book recommendations 2:05:37 - Family 2:08:15 - A poem in Russian CONNECT:
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SPEAKERS
Lex Fridman
hostDmitry Korkin
guestNarrator
other
EPISODE SUMMARY
In this episode of Lex Fridman Podcast, featuring Lex Fridman and Dmitry Korkin, Dmitry Korkin: Evolution of Proteins, Viruses, Life, and AI | Lex Fridman Podcast #153 explores Decoding Proteins, Viruses, and AI: From Spike to AlphaFold Lex Fridman and bioinformatician Dmitry Korkin explore the modular nature and evolution of proteins, emphasizing domains, linkers, and alternative splicing as key building blocks of biological complexity.
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