Controversial opinion: We should stop teaching students any ML methods other than neural networks. There is so much inertia against forgetting things that never panned out. It's hard to let go of ideas, especially one's own, but our objective should be to make real progress in AI

Ok, a bit of nuance is in order. There is a wealth of connections between ML and other established mathematical fields and we should emphasize those! We should studying statistics, linear algebra, ODEs, optimal transport etc... The only "pure ML" things we need are NNs.

Also, my opinion is about the ideas needed to make real progress in Artificial Intelligence. The most common response seems to be that other methods are still used in production. I don't know how long that is going to be the case, but it's not what I'm arguing about.