[mlurp]

Is this true? From what I've read about Alpha Zero/etc, in both Go and chess, it's going interesting move sequences that people hadn't considered viable before. That certainly seems like an interesting thing to learn.

Also, sure, you can dismiss it all as statistics. But how sure are you that what's happening with humans isn't in some form? I'd also say that MCTS is something people kind of do too in games: look a few moves deep and try to judge the value of that position, which is definitely more interesting than simple RL/bookkeeping/stats.

[dfan]

No, it isn't. The top humans are much better at Go than they were four years ago, largely due to learning from the new engines. If it were all just about sampling the phase space zillions of times, this would not be the case.

[breatheoften]

This is interesting to me ... how exactly is this assessed ...?

Do people keep around versions of “alpha go year 2017” and play against it in order to measure human improvement over time?

If the basis for observing improvement has become “I can beat old versions of the ai more reliably than I used to be able to” or if I have learned to beat players who have not studied alpha zero I suppose that’s a form of usefully learning “about go” by analyzing the games played by alpha zero ...

I wonder if we might ever arrive at a point where human vs fixed-year x ai performance at go pretty much stops increasing over time ...?

[Madmallard]

The sequences are viable because alpha go assessed state much deeper than humans do. Doesn't mean humans will be able to utilize them correctly.

[tfha]

Nah at least in chess all the grandmasters lean heavily on the chess engines, including studying top games between the best AI