The Strange Math That Predicts (Almost) Anything
How a feud in Russia led to modern prediction algorithms.
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A huge thank you to Brian Hayes, David Aldous, Geoff Engelstein, Jeffrey Rosenthal, Jimmy He, Mark Priestley, Michael Choi, Peter Norvig, Sam Power, and Thomas Haigh for their invaluable expertise and contributions to this video.
And a special thank you to Madeline Johnson for her excellent fact-checking.
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0:00 The Law of Large Numbers
4:37 What is a Markov Chain?
9:43 Ulam and Solitaire
12:21 Nuclear Fission
15:46 The Monte Carlo Method
16:32 The first search engines
19:07 Google is born
25:16 How does predictive text work?
27:10 Are Markov chains memoryless?
29:41 How to perfectly shuffle a deck of cards
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References:
https://ve42.co/RefsMarkov
Images & Video:
https://ve42.co/7Z
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Writers: Kaela Albert, Casper Mebius & Derek Muller
Producer & Director: Kaela Albert
Editors: Peter Nelson & Jack Saxon
Camera Operators: Gabe Strong, Gregor Cavlovic & Derek Muller
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Chapters (10)
The Law of Large Numbers
4:37
What is a Markov Chain?
9:43
Ulam and Solitaire
12:21
Nuclear Fission
15:46
The Monte Carlo Method
16:32
The first search engines
19:07
Google is born
25:16
How does predictive text work?
27:10
Are Markov chains memoryless?
29:41
How to perfectly shuffle a deck of cards
๐
Tutor Explanation
DeepCamp AI