François CholletVerified account

You can handle arbitrarily complex tasks with large parametric models trained with SGD. The problem is that doing it well requires a *dense sampling* of the input/output space you're learning, because the generalization power of these models is extremely weak. That's expensive. https://t.co/Lsc7zlQBFE 

Deep learning is immensely useful, but it does not bring meaningfully closer to understanding intelligence (as for "AGI", that's a sci-fi talking point, as even human intelligence is specialized). Intelligence is 100% about efficient generalization. DL is orthogonal to that.

Schematically, intelligence is skill divided by experience (I = S/E). Deep learning enables arbitrarily high skill levels, but requires insanely high amounts of "experience" (data) to achieve these levels, resulting in an extremely low intelligence factor.