My point is a bit different though. It's not about culture wars or being anti or pro AI. It's about how silly it is to call one optimization function AI and a

My point is a bit different though. It's not about culture wars or being anti or pro AI. It's about how silly it is to call one optimization function AI and another "not AI" and then make a whole curfuffel about bucking trends, when what you've done is actually something very similar. (Maybe very interesting in its own right and a good solution though, with its own desirable properties.. again, I'm not commenting on the paper itself, just this one off-hand comment in the blog.) In my view calling a solution "neural" and "AI" because you are optimizing a stack of relus, and then turning around and solving the same (or almost the same) problem by optimizing a bunch of Gaussian model parameters on the same data, and then saying that is "not AI" and "at least it's not neural!" is just a very specious and unnecessary way to delineate things imho. They're just two solutions to the same problem, both data driven, both generating "models".. they have differences, just not differences that I think warranted such a comment in the blog, and moreover I thought it weird to attribute some kind of normative evaluation based on how you categorize the solution.