Deep Learning for AI
Todays presentation is a lecture by Turing award winner Yoshua Bengio presented at the Heielberg Laureate Forum in 2019. It provides a higher level overview of the current state of the art and future directions than the kind of info you get in something like yesterdays nuts and bolts full stack lecture.This lecture will look back at some of the principles behind the recent successes of deep learning as well as acknowledge current limitations, and finally propose research directions to build on top of this progress and towards human-level AI.
1: The whole discussion on misconceptions associated with local minima in deep learning systems is an interesting one.
It provides some intuition for the very non-intuitive strategy seen in some architectures to actually increase the dimensionality of the system to improve the ability to get to a solution.