Stats are somewhat like doing spam with Bayes, Fisher/Robinson etc. For certain tasks they can make useful 'educated' guesses but they are still 'dumb' algorithms. If you look at how a child learns language they do seem to use a suck it and see approach. They then get feedback on if that was a 'winner' or not. As approaches to AI go I think both knowledge and stats based are 'wrong'. While there is no doubt that both can yield useful results they appear to my mind to have finite limits. I favour a fuzzy logic nodal learning framework ie try to build a machine that can learn without trying to tell it exactly how to learn that. The main issue with this is processor speed (or rather the lack of it) combined with the training time. Language processing is actually a good task for this as you have what is effectively a character based input and output stream making the interface simple.
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