Comment by somenameforme
3 hours ago
As another question, does it not operate similarly to the top chess engines? The way the neural network systems work is by using the probabilistic matching paired with a Monte Carlo simulation. So you can get to extreme depth very rapidly. Obviously the breadth is going to be limited, but if the neural network side is well tuned (so high probability hits are indeed generally the most challenging moves), then that's not such a problem.
And you can run a huuuuuuuge number of sims in 16 seconds.
I believe the basic idea is similar, but there's an enormous difference in the space of possible moves between chess and Go. Go has a larger board and moves are less restricted. There was a major breakthrough in Go playing programs a decade or two ago when good Monte Carlo methods were developed for it. But still I think the ability to simulate many moves is less powerful in Go.