>First off right now there seems to be a drive to explain many phenomena in ML in particular why neural networks are good at what they do. A large body of them

>First off right now there seems to be a drive to explain many phenomena in ML in particular why neural networks are good at what they do. A large body of them reaches a point of basically "they are good at modeling functions that they are good at modeling". Since this is closely related to my current research, yes, ML research is kind of crappy at this right now, and can scarcely even be considered to be trying to actually explain why certain methods work. Every ML paper or thesis I read nowadays just seems to discard any notion of doing good theory in favor of beefing up their empirical evaluation section and throwing deep convnets at everything. I'd drone on more, but that would be telling you what's in my research, and it's not done yet!