Are the AlphaGo games similar?
The AI popularized a move that has been known since ages, but wasn't used by strong humans much because it was considered a mistake (the early 33 invasion).
The thing with this move is: It gives you a small advantage very early in the game, but gives your opponent a superior fighting position in exchange. This fighting position was considered better. Not early on, but in later stages of the game it oughtweights the small advantage taken early.
Then came AI and it found out, given enough fighting power, it can mostly cancel that later game advantage.
So the new move is actually a good one, but only if you have very strong fighting skills. AI has this, some very strong players as well.
But for the rest of us, the pre AI strategy is often better because we can't handle the complexity.
It is common to see casual players copying the AI style and digging their own grave while doing so.
If human players do the new AI move, an attack to cancel out the better fighting position is unavoidable. We've learned from AI how to attack and defend in this situation, so even human players are prepared and know what to do. So it is fair game for the two human brains again.
The player who gets out of this fight with the worse position is on a rather high disadvantage for the rest of the game.
So you can think of this new strategy as doubling the stake of the game very early on. For players who are really good at fighting and handle the complexity that will arise from this fight this strategy is a good choice.
> It is common to see casual players copying the AI style and digging their own grave while doing so.
I think this point is greatly overstated. Amateur go style has always been modelled on professional play even though amateurs have no idea of the subtleties of it, and this was rarely bemoaned much in the past. It's easy to find examples of amateur players getting it wrong and turning a slightly-good position into a bad one, but this is true of just about anything and I think there's a lot of confirmation bias in associating it with AI moves in particular - it doesn't in itself mean they've disadvantaged themselves by trying.
It also greatly overstates how bad it is to play the 3-3 early and not fight aggressively. Even if you don't worry about the fighting variations we're talking about a small number of points, much less than amateur games tend to swing via mistakes every few moves. This is also true about those professional-like lines that have always been mimicked but played imperfectly, and is probably a big reason the lack of amateur understanding of them never mattered too much. Plus let's not forget that both amateur players in the game are relatively bad at fighting, it's just about as hard for the defensive player to really get it right as for the offensive player to utilise their theoretical advantage.
Overall I think the modern focus on AI-like play is much more of a fashion in line with other general shifts following what's professionally popular than a mistake. Players do pay attention to how well they do and associate it with specific moves and lines they recognise they don't understand well, but AI-inspired lines don't seem to have attracted any widespread cautiousness.
> Then came AI and it found out, given enough fighting power, it can mostly cancel that later game advantage.
Also worth noting that the AIs play the 3-3 invasion in a specific different way to what was the accepted human pattern, and this alone does make a big but understandable difference to how the shape commonly continues. It isn't that they only turned around the evaluation of the standard position through superhuman reading, they revealed a line that humans had undervalued but could then learn from.
As we know, Lee Sedol managed to win game 4 by a lucky break, but lost the rest, so the GM's comments were incredibly perceptive. I took a few notes while watching so I may be able to dig them up and check the details, but the surprising play became quite well-known and involved something called a "dog's head" formation, which might be enough for Go aficionados to identify it.
Move 78 was not a lucky break. At least in my mind.
There are not many movies I cried to, in this movie I cried twice, once when Lee Sedol was apologizing for the loss, and once when he made move 78 and Alpha Go's probability to win dropped with 10%.
Now for me move-78 means hope.
Unless humanity moves to a point where the average skill is that of Lee, and the average intelligence is akin to JvN's I don't see hope for humanity.
Although I always wonder if give that the software was designed in a way to allow the computer to make mistakes and take risks to a reasonable amount, like humans do, would they still be crappy drivers?
The move in question should be move 102, which is an invasion that human would not try.
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.
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.