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Lex Fridman PodcastDonald Knuth: Programming, Algorithms, Hard Problems & the Game of Life | Lex Fridman Podcast #219
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Episode Details
EPISODE INFO
- Released
- September 9, 2021
- Duration
- 2h 21m
- Channel
- Lex Fridman Podcast
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
Donald Knuth is a computer scientist, Turing Award winner, father of algorithm analysis, author of The Art of Computer Programming, and creator of TeX. Please support this podcast by checking out our sponsors:
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EPISODE LINKS: Donald's Stanford Page: https://profiles.stanford.edu/donald-knuth Donald's Books: https://amzn.to/3heyBsC 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 0:48 - First programs 24:11 - Literate programming 27:20 - Beauty in programming 33:15 - OpenAI 42:26 - Optimization 48:31 - Consciousness 57:14 - Conway's game of life 1:10:01 - Stable marriage 1:13:21 - Richard Feynman 1:24:15 - Knuth-Morris-Pratt Algorithm 1:33:47 - Hardest problem 1:51:26 - Open source 1:56:39 - Favorite symbols 2:06:12 - Productivity 2:13:53 - Meaning of life SOCIAL:
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- Support on Patreon: https://www.patreon.com/lexfridman
SPEAKERS
Lex Fridman
hostDonald Knuth
guestNarrator
otherNarrator
otherNarrator
otherNarrator
other
EPISODE SUMMARY
In this episode of Lex Fridman Podcast, featuring Lex Fridman and Donald Knuth, Donald Knuth: Programming, Algorithms, Hard Problems & the Game of Life | Lex Fridman Podcast #219 explores Donald Knuth on Programming Craft, Beauty, Faith, and Future Machines Donald Knuth reflects on his early days programming the IBM 650 in raw decimal machine code, using stories about factoring numbers and a learning tic-tac-toe program to illustrate how he discovered debugging, algorithms, and even primitive machine learning.
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