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Something that has really interested me recently are Markov Chains. They are often used to generate realistic looking outputs for this style of thing. They take inputs as lists of states; so a sentence would have several states - each state being a word. When given a large input, they build probability trees for each state following another. This has led to the hilarious /r/subredditsimulator on reddit and some really interesting other stuff besides. This reasonably simple technique can build surprisingly varied and realistic outputs - so long as there is a large enough amount of input data. I probably made a bad job of that explanation because I barely understand myself but here is a good explanation on /r/Python