[acdc4life]

> evolution selected for a language skill

Yes it did, and we do know a lot about general principles behind, from different disciplines. This is still an early science. NLP research still hasn’t considered many important aspects of language learning that we have discovered in such a short period of time.

> starting with an empirical result

What makes you think these benchmarks are empirical? They were hand constructed to fit some objective, assuming that being good at the said objective is required for NLP tasks. Where’s the empirical experiments to validate the notion that said objectives lead to language? Science hasn’t worked this way, datasets aren’t constructed, you do an experiment and MEASURE it. Then you make models, try to explain the phenomenon, and test new ideas and validate your models. Can your model extrapolate new information and suggest new experiments to validate? I used the word extrapolate over predict intentionally.

[bumby]

It’s a little hard for me to follow your last paragraph but it sounds like you are confusing AI and AGI. I don’t think anybody using BERT is claiming the latter.

I assume the empirical results are the validation sets run. I.e., the tests that show it provides better results than the base rate. Again, it’s important not to conflate verifiable results with understanding the underpinnings of why it works. If you’re walking and I race you with my car over and over again, I can conclude my car is a faster mode off transportation without understanding anything other than “push right peddle to go faster”. My ignorance doesn’t invalidate the results