I see people looking at off-the-shelf ML solutions as a panacea for their problems - without understanding the application domain, nor considering simpler solutions, nor thinking about the SE-perspective of AI-powered *software* systems and the challenge that comes with it.
I'd guess I'd summarize it as, being a "deep learning expert" in 2021 is like being a "medicine expert" in 1800. You know a lot less than you think, and most of what you think you know is wrong. Just keep learning and experimenting, and don't play stupid status games.
1/ I was asked how to successfully finish a #phd. To be honest, I owe this merit mostly to my brilliant supervisor @maalejw. Yet, here's my personal advice (w/o order):
- Continuity is key!
5/ Do NOT say yes to everything or you will never find your OWN path.
- Try something NEW! It will never be so easy again in your life to jump into the cold water. Escape the established patterns and impress people with a different point of view or yet unexplored problems!