I found this to be a great survey post on a question I've been wondering more and more as I hear about all of the machine learning going on. I'm no academic nor

I found this to be a great survey post on a question I've been wondering more and more as I hear about all of the machine learning going on. I'm no academic nor mathematician, and I fear that diving into actual papers would quickly blow out the few remaining neurons I have left, but this article was mostly understandable and brought up a lot of points that have been floating around in my head. Kudos to the author. The one substantive comment I want to make is that I really wonder about the difficult to reproduce findings. What's going on when attempts to reproduce them fail? It's a general question, but I do wonder how much of that is because other effects are swamping the signal, and how much is that the finding only applies to limited situations. (Not that those are entirely different.) If I don't see the double-u curve, is it because my problem space has an atypical shape, or because the researchers' did?