[vkazanov]

Yes, I was a bit vague. If we are to be serious then we would have to come with definitions of grammar-based approaches vs stohastic approaches.

All I am saying is that grammars (as per Chomsky) or even high-school rule-based stuff are imperfect and narrow models of human languages. They might work locally, for a given sentence, but fall apart when applied to the problem at scale. They also (by definition) fail to capture both more subtle and more general complexities of languages.

And the universal grammar hypothesis is just that - a hypothesis. It might be convenient at times to think about languages in this way in certain contexts but that's about it.

Also, remember, this is Hacker News, and I am just a programmer who loves his programming/natural languages so I look at everything from a computational point of view.

[foobarqux]

All this comes down to is that language is not a solved problem. By the same logic why not just stop doing any research in physics and just put everything through a neural net which is going to give better predictions than the current best theories?

The fact that a deep-neural-net can predict the weather better than a physics-based model does not mean that the weather is not physics-based. Furthermore deep-neural-nets predict but don't explain while a physics-based model tries to explain (and consequently predict).