I feel like the emphasis of your comment misses how the game has changed for humans since AlphaGo.
That is the crux of it though; we're seeing the same effect as every time a new strong player arises. That doesn't scream "wow, this is like when chess engines discovered impossible new lines!".
It was probably a matter of time until some human pro started winning with the 3-3 invasion for example. It isn't like 3-3 invasions are a radical new thing, professional play just underweighted them. I've played amateurs who loved 3-3 invasions.
There is no question that the neural nets are substantially stronger than humans and that they're causing a monumental rethink of all aspects of the game. They're a big deal. But the difference is that they are bringing a very large number of innovations all at once, combined with far more accurate reading, rather than that any individual innovation is special.
It is really difficult for one sequence in Go to be special, because it is so common for a special sequence to happen.
AIs have changed all the details about what is considered an acceptable result in the corners.
Although AI do brutally outplay humans in the centre when the game gets there, no question. Normally after outplaying them everywhere else first.
Ok, I agree with you there. It's like AlphaGo is the next in the line of Dosaku -> Shusaku -> Go Seigen. These types of players that have revolutionized the game have been very rare, and I see AlphaGo as fitting into that mold.
> That doesn't scream "wow, this is like when chess engines discovered impossible new lines!".
I admittedly don't know enough about chess to understand this aspect of the discussion.
Computer Go is obviously making calculations that a human couldn't, but as an observer it just looks like not making any mistakes. There is the occasional spectacular attack or defence, but humans do that too from time to time - human players often see or try moves that others wouldn't. In complicated situations computers will do a better job at assessing what the impacts are.
In Go, to win a player needs to consistently make moves that are on average 0.0025 points better than their opponent for 300 moves. It is hard to detect the genius if a neural net decides it is going to win the game that way.
The games are interesting to study, they are all masterworks. But the strength of a Go player is in the consistency rather than individual flashes of insight.