It's _mostly_ hardware and data. There are some smarter steps in training etc., but most of the ideas have been around for decades; it's the scale that made the difference.

> I'm not sure why conceptually that wouldn't be enough.

This one is harder to refute. I guess it's because statistics doesn't involve understanding. Try considering something like LDA for topic discovery: there's no understanding of the semantics of the model, it just identifies them statistically. There's a huge difference.