I'm also quite dismissive of AI overuse. My preferred substitution is s/Machine Learning/Machine Guessing. However, these are 3 people who overcame a lot of na

I'm also quite dismissive of AI overuse. My preferred substitution is s/Machine Learning/Machine Guessing. However, these are 3 people who overcame a lot of nay-sayers to prove some something could actually work. I remember back in university the lecturer said that neural networks couldn't scale because of the vanishing gradient problem. It was actually very easy to be critical, you want fit a massive number of parameters which are not-very-orthoganal to an under constrained problem? Sounds pretty dumb to me! I think these 3 deserve recognition for their tenacity and the new world of "under defined gradient decent", sometimes called DL, which they opened up.