Uh, guys with the big bucks: AL/ML are at most a tiny fraction of the material, tools, power, and value of the pure/applied math on the shelves of the research libraries.<p>If you have a problem you want solved with AI/ML, 99 44/100% of the time you are better off going for what's on the shelves of the libraries, as taught in various high end grad schools, than with anything currently specifically AL/ML.<p>So, broadly, go for work in statistics, optimization, stochastic processes, and optimal control. For a specific application, may want some work that stands on that existing material and is also at least somewhat original.<p>E.g., the crucial technical core of my startup is some original applied math I derived based on pure/applied math that's long been on the shelves of the research libraries. For the valuable work of my startup, what's in AI/ML now is in comparison at best weak, nearly silly early grade school baby talk.<p>Really, guys, 99 44/100% of the good stuff is still where it's long been -- on the shelves of the best research libraries. And for the education for that work, it's definitely NOT in departments of computer science. Instead look at selected programs in pure/applied math in some of the best research universities.