Non-parametric statistics blurs the lines a bit, prequential statistics (ala Dawid) blurs the lines even more, but he is not wrong. A traditional statistician w

Non-parametric statistics blurs the lines a bit, prequential statistics (ala Dawid) blurs the lines even more, but he is not wrong. A traditional statistician will be excited about a method because it can recover the parameter (be it finite dimensional, or infinite dimensional). On the other hand an ML person will be excited about a method because, even if the method sucks at recovering the parameters, it does well on the prediction task (if it can be shown that it approaches the theoretical limit of the best that one can do, no matter what the distribution of the dats, and it can do so with efficient use of compute power, ... that would be the holy grail).