He is rather controversial in machine learning circles. I would say he is essentially right about the fact that a lot of ml work is crap. Like most of anything

He is rather controversial in machine learning circles. I would say he is essentially right about the fact that a lot of ml work is crap. Like most of anything is crap, so that is not a groundbreaking insight and it comes off as somewhat grandstanding to keep saying that. He has however really turned this into a personal brand which many suspect he is using to advertise his startups. Many people feel he is sort of disingenuous about the actual progress being made in computer vision and NLP, even if there is many ways to go. To answer your question: You can read a single piece of his and maybe get some value from that, but he keeps rehashing the same points to sh*t over different new work, and there is not much to be learned from that after a while. Disclaimer: I did not read the above article in full, I am just familiar with Gary Marcus + work in ML industry. Edit: Keep expanding this but it got me thinking. Earlier in my career, I was also eager for the 'gotchas', for being able to point out why something is crap, exaggerated, cannot do what it promises, and so forth. As I outgrew this impulse to focus more on what is good about some work, I began spotting it on new students a lot. They would come into seminars and smugly crap all over recent papers. I have since come to the conclusion that it is useful to have realistic internal assessment of progress in your field, but that sharing your harshest criticisms is not necessarily a good way to look smart or make progress. It often turns out that while feeling clever about realizing limitations of some work, the field just moves forward. The people you just criticized leapfrogged while you were busy thinking about how to one-up them.