Chomsky argued that it was literally impossible for a statistical model to learn language, so to the extent it's possible, it refutes Chomsky's argument.
We won't know how humans learn language until we understand how humans learn language, but the fact that a crude general-purpose model like ANN works as well as it does is certainly evidence that humans can learn language statistically. We don't know for sure, but we rarely do.
> but the fact that a crude general-purpose model like ANN works as well as it does is certainly evidence that humans can learn language statistically
Humans learn language intuitively (subconsciously), as well as formally (through academic training). Humans understand language (to a greater or lesser extent in any particular case).
Statistical NLP is not, in any human-translatable way, understanding. It is approximation and prediction, in a purely mathematical sense.
Perhaps one of us misunderstands, or is imprecisely using, the phrase "learning language statistically", but I am unaware of any evidence that humans do so.
Chomsky's linguistic theories are not about understanding. Hence his famous example of "colorless green ideas sleep furiously", which is a meaningless sentence that we recognize as grammatical.
Actually understanding language the way humans do would require AGI, I suspect.
Chomsky argued that it was literally impossible for a statistical model to learn language, so to the extent it's possible, it refutes Chomsky's argument.
That's a different claim to the one I countered.
I agree with your last point with the caution that there is no reason yet to think the hyped current AI tools have great relation to the way the human mind works, solely on the basis of the lack of progress towards AGI.
We won't know how humans learn language until we understand how humans learn language, but the fact that a crude general-purpose model like ANN works as well as it does is certainly evidence that humans can learn language statistically. We don't know for sure, but we rarely do.