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A single page in a standard-format hardcover book contains approximately 1,500 characters. There are 26 letters in the English alphabet, plus 14 standard punctuation marks. Therefore, the state space of a single page is 40**1500, or about 12 followed by 2402 zeros.
Now imagine having a generative model that allows you to sample from the space of *intelligible* pages...
Let's do it!
(sweeps everything from my desktop. opens a new @TensorFlow project...)
But how many n-gram(3) based symbols is that, about 75 per page? With variable length bit codes in order of frequency of use based on a huge corpus. That gets rid of a lot of redundancy yes?
Monkeys typing…?
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