It's also makes for a lot of terrible talks. In my field (bioinformatics) it's frustratingly common for a PI to give a keynote which boils down to "some grads s

It's also makes for a lot of terrible talks. In my field (bioinformatics) it's frustratingly common for a PI to give a keynote which boils down to "some grads students made DeepX and got an AUC of 0.85 on this problem and some others made ML-Y and got an AUC of 0.78 on this other problem and a postdoc did this other ML thing." There's no details or insight, basically just a sales pitch for their software package. Nothing in the talk can be transferred to other topics. The only time the talk is useful is if you happen to need to solve problem X and they've got a tool to solve it for you. You couldn't give a talk about a statistics model without explaining the model, but it seems to be totally OK to give talks about ML projects without saying anything more than that it's a deep net or random forest.