Yes, he's famous for that, but that didn't earn him his PhD nor would it have gotten him tenure. As he remarks about his teaching of his course, him doing a good job actively worked against him because... it's not writing a sexy new paper or networking.
> He also recommend you to release code in this article, so I'm not really sure what you are getting at.
Releasing code isn't the same thing as creating polished end-user applicable stuff on the level of char-rnn. In ML, you're increasingly expected to at least chuck over the wall a barebones implementation to demonstrate it works at all, but there is no expectation that it will be generalized, well-written, or polished, or maintained, and typically they are not. (Most ML releases I've looked at are kind of horrifying from a software engineering perspective. Just thinking about improved-gan makes me shudder.)