Yes, I stopped reading when it mentioned the last good paper was from 2017. This is simply not true. I don't have time to go through all of their papers right now, but as someone else mentioned the protein folding one was a real breakthrough. They also have lots of great stuff in the NLP space (something similar to gpt-3 like 2 years earlier). Also tons of stuff on the actual training architecture/methods.

Edit: I want to add that saying the title has nothing to do with the article is not helping the case. I finished reading the article in case I was being unfair, but I still stand with my original comment.

To be fair, you wouldn't know that from the article's subtitle:

> What does Timnit Gebru’s firing and the recent papers coming out of Google tell us about the state of research at the world’s biggest AI research department.

I read the article and I don't get what's the focus of it. It seems a disconnected rambling about vague deep learning issues with Gebru's name interspersed several time in the text as to suggest her relevance.