I spent about ten years working on Markov based chat programs. I gave up on themwhen I realized that no matter how sophisticated your statistical model it will never be more than a statistical analysis of text, unless it includes some rich rule based model of mental processes and mental objects. It may be that such a model of mental processes must itself be fuzzy and probabilistic, but it must exist. Therefore I come…
This is the same argument that was used against artificial neural networks. Neural network of type A can't do X, therefore neural networks will never do Y.
Language is immensely complex, and real human language involves things which are not encoded in text (and i'd remind you that you were trying to infer meaning from text specifically, not the full multi-channel robustness of humans communicating), we don't even have a full handle on what all of the cognitive processes and factors are that go into the production and understanding of language (although we've developed a lot of interesting work to those ends).
So hearing folks give up claim that Chomsky is correct because our current tools aren't up to the job is a bit puzzling, because we don't even have a complete understanding of what sort of thing language is or what sorts of things we are as systems which can use language.
Chomsky has opinions (and some facts) about what language is, and we are, but he does not have solid proof to confirm his specific conjectures. Is human language context free? context sensitive? Something else? (Chomsky's minimalist program uses movement along a tree to preserve referentiality and a bunch of junk, alternative syntactic frameworks such as HPSG uses directed graphs as the basis of their language modeling. Still others do weirder things like higher order combinatoric logics. And unfortunately none of the theoretical frameworks appear to be without their drawbacks)