An RNN conditions the generation of each character on the entire previous history of characters generated. A Markov chain only conditions on a fixed window. Perhaps a particular RNN will learn to truncate its conditioning context and behave as a Markov chain, or perhaps not; but RNNs in general certainly can generate formal languages that Markov chains cannot.<p>For example, consider that the RNN in Karpathy&#x27;s post (the one linked to in this article) was capable of generating well-formed XML, generating matching opening and closing tags with an apparently unbounded amount of material between them. No Markov chain can do this.