Grandiose claims, barely-readable and buzzword-saturated language, really weird experiment setup, lack of critical self-examination. These common features of recent AI research papers begin to annoy me. Especially when it's seen in corporate research, where (supposedly) results should be more important than a kind of lingual tribalism seen in academia. Is it really that hard to produce a human-readable description of the architecture and put it in a particular place of the paper instead of spreading them all over? Also, it took me quite a while to understand what the heck they were measuring (and how) in the first place.