Afaik this was stated in my Intro to ML course. A kernel machine can do anything when the similarity function has infinite dimensions. Similarly, I think they mentioned an infinitely wide MLP is also all you need.
Also, this all breaks down when you introduce reinforcement learning methods.
There's no longer a concept of training examples to be close to, since it's just going along the gradient of high reward actions in the RL environment and going away from those with low reward.
Also, this all breaks down when you introduce reinforcement learning methods.