Comment by fooker
4 hours ago
Interesting.
By unsolved I guess I meant: this looks like it should be easy and efficient but we don't know how to do it yet.
Usually this means we are missing some important science in the classification/complexity of problems. I don't know what it could be.
Perhaps. It's also possible that the approach simply precludes the use of the best tool for the job. Backprop is quite powerful and it just doesn't work in the face of heavy quantization.
Whereas if you're already using evolution strategies or a genetic algorithm or similar then I don't expect changing the bit width (or pretty much anything else) to make any difference to the overall training efficiency (which is presumably already abysmal outside of a few specific domains such as RL applied to a sufficiently ambiguous continuous control problem).