Better Babblers - by Robin Hanson - Overcoming Bias
You can think of knowing how to write as knowing how to correlate words. Given no words, what first word should you write. Then given one word, what second word best correlates with that. Then given two words, what third word best fits with those two. And so on. Thus your knowledge of how to write can be broken into what you know at these different correlation orders: one word, two words, three words, and so on. Each time you pick a new word you can combine knowledge at these different orders, by weighing all their different recommendations for your next word.
This correlation order approach can also be applied at different scales. For example, given some classification of your first sentence, what kind of second sentence should follow? Given a classification of your first chapter, what kind of second chapter should follow? Many other kinds of knowledge can be similarly broken down into correlation orders, at different scales. We can do this for music, paintings, interior decoration, computer programs, math theorems, and so on.
Given a huge database, such as of writings, it is easy to get good at very low orders; you can just use the correlation frequencies found in your dataset. After that, simple statistical models applied to this database can give you good estimates for correlations to use at somewhat higher orders. And if you have enough data (roughly ten million examples per category I’m told) then recently popular machine learning techniques can improve your estimates at a next set of higher orders.
