Have we learnt anything technically about AlphaGo Zero implementation ?
(new version of AlphaGo, not using human data sets, overbeating previous version, while reinventing Go…)
Lots of press but mainly copies of official communication.
It utilizes a form of reinforcement learning which is no covered in these courses.
Yes, thanks, that’s why I am asking, as applied (and very efficient) techniques are apparently quite new and state of art
I am starting fast.ai courses soon, but I wanted to have this in mind too ^^
But maybe it has to be firstly trivialized/worked/conceptualized before being accessible to mere mortals o_o
The techniques you will learn in this course are equally on the cutting edge, it is just they are from different domain
Sort of like you would be comparing being a world class piano player vs being a world class chess player. Both equally good but different domains
If you want to built more of a conceptual understanding on what the difference is you might want to google supervised learning (what we do in this course - image recognition, sentiment analysis of text) vs reinforcement learning (computer learning to play atari games).
Well, either way - enjoy the course, I think you will have a blast! Doing the course myself at the moment and having a great time
Here is a very nice single image overview of the architecture of AlphaGo Zero