Reinventing Entropy | Compression & Intelligence Part 1

What is the fundamental compressibility of language?
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Animation credit:
Manim scenes by Aaron Gostein and Grant Sanderson
Shannon’s story, as well as those for various pi creatures, by Mitchell Zemil.
Lunar robot and prediction/compression coin by Paul Dancstep
NanoGPT animations by Clayton Rabideau

Shannon’s “A Mathematical Theory of Communication”
https://people.math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf

Shannon’s “Prediction and Entropy of Printed English”
https://www.princeton.edu/~wbialek/rome/refs/shannon_51.pdf

Scientific American article that mentions the story with Von Neumann suggesting the name Entropy:
https://www.esalq.usp.br/lepse/imgs/conteudo_thumb/Energy-and-Information.pdf

Timestamps:

0:00 - On “Compression is intelligence.”
3:28 - The warmup example
10:46 - What perfect compression looks like
14:47 - Defining information
17:40 - Information of language
24:29 - Defining Entropy
31:14 - 3b1b Talent

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These animations are largely made using a custom Python library, manim. See the FAQ comments here:
https://3b1b.co/faq#manim

Music by Vincent Rubinetti.
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u

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