Is deep learning a Markov chain in disguise?

Andrej Karpathy’s post “The Unreasonable Effectiveness of Recurrent Neural Networks” made splashes last year. The basic premise is that you can create a recurrent neural network to learn language features character-by-character. But is the resultant model any different from a Markov chain built for the same purpose? I implemented a character-by-character Markov chain in R to find out. First, let’s play a variation of the Imitation Game with generated text from Karpathy’s tinyshakespeare dataset. Which snippets are from the RNN and which are from the Markov chain? Note that Karpathy’s examples are from the complete works, whereas my Markov chain is from tinyshakespeare (about 1/4 the size) because I’m lazy. DUKE VINCENTIO: Well, your wit is in the care of side and that. FRIAR LAURENCE: Or walk liest; And the…

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