There somehow seems to be an unwritten law of the Python generation like "Thou shalt not criticise Machine Learning". Or is there a better explanation for the emotions that flare up every time someone dampens the exaggerated expectations and reminds us of earlier research in the field of linguistics or AI?
Let's not make this a generational divide thing, shall we? There's people of all ages who seem to think AI research is like a silly ball game, where one cheers their home team's plays and boos their er, whatsitcalled, the other team's plays, no matter the plays.
And who can blame them? AI (read: machine learning) (read: deep learning) research has turned into a huge feeding frenzy. People see all the billions thrown about by Google, Facebook et al. and they go crazy. Maybe they think that if they cheer hard enough and boo hard enough they'll look knowledgeable and "passionate about machine learning" and maybe someone will hire them. Maybe they just want to be on the right side of history, with the winners, not the losers. And when there's so much money to win, there sure are plenty of losers!
A while ago someone posted here an article that advised that to become expert in machine learning one should (among other things) "flashcard X papers in major sub-fields" or something along those lines. Pretty revealing of what people are thinking of: Google is hiring machine learning specialists. Shut up Garry Marcus, you'll scare the fish off.
There's plenty of good criticism of given products, papers, and approaches. There's also bad criticism though and it's important to distinguish the two.
>appears less biased than others who benefit from the current high level of investment in DNN.
Yes, instead he blatantly tries to benefit from the counter-investment in AI skepticism.