[intuitionist]

> Deep learning and machine learning don’t work. Quantitative math will always prevail, as it always has.

What do you think machine learning is, if not “quantitative math”? Deep learning is just linear algebra and calculus, and things like random forests are even simpler mathematically.

[acdc4life]

Machine learning is glorified curve fitting. DL isn't even mathematically sound, back propagation has no proof of convergence. Quantitative math is about extracting natural laws, and mapping them to mathematical structures. You could use DL to predict planetary motion, and get pretty good at it. But this isn't a quantitative understanding of the world. You didn't learn anything. Physics in contrast has the laws of motion and gravitation. You can directly model arbitrary planets. Moreover, you can model arbitrary rigid bodies, from cars to space shuttles. Your ML, DL random forrest etc. all use math, sure. But so did the Keplarian models of motion. You aren't qualitatively deducing math that governs the world, but forcing an arbitrarily chosen mathematical structure to your data.

[intuitionist]

If we’re throwing out anything that doesn’t have a proof of convergence as “not mathematically sound,” you can kiss fluid mechanics goodbye, as well as lots of other subfields of physics that rely on partial differential equations.