Having super strong go-engines has definitely changed how the game is played at top level. But how?
I watched a youtube video on subject and from there I got understanding that some basic josekins like san-san invasion are perhaps not the best options. Keeping sente is more valuable than previously taught. Are the other finding and do they have any impact on lower echelons of go players?

Hwang In-seong 8 dan's 2022 Congress lecture series vol.1 [Four Trendy Ideas]
https://www.youtube.com/watch?v=QgUnD434NH4&t=855s

I have not studied the impact on top players but have experienced a wall of those 5d+ opponents with AI study I could not beat before my AI study started. AI study has kept me busy for 9 months now and I notice an impact on my level.

In the 90s, studying the opening from books and pro games was one factor for the 3k to 3d part of my fast improvement. However, later as a 5d I realised that I did not really understand the opening as taught by old books and pros. The more traditional opening theory I learned the more I saw nothing but contradictions. Eventually, I felt that I had no useful opening knowledge at all. I saw stronger players playing stronger opening but did not really understand how to play alike. With no traditional source that could improve my opening, I was stuck.

Therefore, my AI study has been mostly the early stage of the game. What I hoped to learn from AI I can. AI confirms my prior impression that all (ok, maybe 99%) traditional opening theory is useless. In stark contrast, AI opening makes sense and is consistent. It is not always easy though because the exact position can matter, deep tactical reading can be necessary, fights can be correct or very long term developments can be correct.

I presume some top players would also do similar AI study and it is an easy guess that they might draw similar conclusions. Such as: it is insufficient to play just efficiently - it is mandatory to play the most efficiently!

Many observations about AI Go are only in the eye of the beholder. The computer, unlike humans, will do the same thing on every move. If it protects a cutting point that is not because it thinks the alternative is too much, it is something it basically does after considering the alternatives seriously. It is the same with sente and gote, just as the compute will play marvelous sente sequences it also plays astonishing gote moves. A human player can't always do the same thing, they will make choices based on what is good enough and if they can better spend their energy on some other decision.

I think lot of people should pay more attention when it plays simply. If it simply connects, simply lives, simply defends and simply ends in gote, then that is something everyone could have done

One thing I have noticed is that if you look at human games from the past that the computer often thinks there is something fishy. There are weaknesses that it finds and wants to exploit. Sometimes the players of the game have the same idea but don't jump on it as quickly and often the defense is successful. Were as if you study the game with the computer it is clear that the attacker could have succeeded; the computer most of the time is silent about moves that don't work. However, if you look at computer vs. computer games there can be a ton of simple moves and both sides seem to have been ready for everything. The simplest explanation is probably just that the computer is much better at many aspects of the game than top pros were and if a much stronger program came along it would give old computer-computer games a similar treatment

I recon than that the top players have learned a lot from studying with computers but exactly what might be something they have to tell themselves

His section about tenuki is wrong. He says that tenuki is always an option and the whole section conveys this idea but it is wrong. He should have said that AI tenukis more often than previously was common.

For many moves, AI has a clear choice on which is the only correct move, and it is not always tenuki.

Like Takemiya, he fell into the teacher's trap of telling the pupils that they can do what they want. Instead, he should tell what is correct: when to tenuki and when not to tenuki. Of course, this is difficult for everybody including the teacher.

I wonder if what they have learned might be mostly improved assessment and understanding of certain specific positions rather than new concepts and theories. In which case, the SL page on 'Missing Concepts' is sadly still going to remain fairly empty.

Probably many small things and that is just my observation. Possibly they have learned so many things about shape that quantity led to a change in quality. Even that could be something that started before AI, but top pros do appear to play more solid shapes then they did couple of decades ago. That is solid as in it is harder to get a defensive move from the shape. They also appear to have learned many things about soba go

It's things that you'd never have thought top pros could learn anything new about.

Or it could be the other way around. Maybe they did learn how to evaluate some positions better and this led to a change in how they play other aspects of the game. On the other hand, it could be the seed that fell on a good soil, those that found it remarkable how AI evaluates some positions then learned something entirely different. Which is how it plays up to those positions.

Something that is usually overlooked could be more important. It is that when you play something novel and it doesn't work out your opponent and your so called friends (because we don't have anything better) will never let it go and trash you and your move for years to come. And if it works out it is all the same

I don't remember his name but there was a pro that always played a normal approach move to Kobayashi fuseki. He didn't see what it was he was supposed to be avoiding. Which makes sense when you can find games were Lee Changho(?) only managed to punishing it because he is Lee Changho. Nowadays, he could just have showed them! That is showed them how AI evaluates the move

Remember we've been through all this before with Shin Fuseki. We are still unsure what pros learned from that. We can be sure amateurs learned nothing from it despite books selling over 100,000 copies. But those who did learn a lot from it were the publishers, sponsors, media folk and the like. Bling, bling, kerching, kerching.

As Robert says, openings are the obvious change: new variations for the 3-3 invasion, re-evaluation of "old" joseki, rehabilitation of shapes we were taught are bad, reduced popularity of high concept openings, ... What can we say about the middlegame? I think there has been a real influence there too, but it's harder to describe in a few words.

To my mind, a big factor is that the new AIs are very good at responding to an attack. By this, I don't mean "defending". For an amateur like me, if my stones are threatened with attack, my first instinct is to try and keep them alive. But there's a lot of other options. Sacrifice and build influence. Make a light shape and allow the possibility that part of the "group" is cut off. Tenuki and do something more important elsewhere. Of course we already know this. Most of us learn "light and heavy" some time in the single-digit kyu ranks. But knowing the concept and finding the moves to put it into practice are two different things. And I think AI is taking it to the next level. This is why moyo strategies are becoming less popular, and it's so much more common for games to break out into early and chaotic fighting rather than building a framework first.

One factor is that the AI sees the board anew on each move. It doesn't have an emotional attachment to previously played stones. So it stands to reason that it should be more prepared to make trades in a way that feels risky to humans. (Why shouldn't I take risks in a close position? If it's risky for me, then it's equally risky for the other person. But somehow it seems to go against instincts.)

To some extent this is an acceleration of trends that were already happening in the 1990s. So it's hard to pick out how much AI has given things a push and how much it would be happening anyway.

There's two other things I'm noticing when I review games with KataGo. It seems to play forcing moves earlier than was recommended a few years ago. I've always been taught to avoid pushing the opponent around unless I can see a clear benefit. Leave things open, because you don't know what options you might need later. But it's a fine line between leaving it open versus waiting too late and losing the chance entirely. Except that KataGo seems to be suggesting it's not such a fine line: just do it as soon as the chance comes up (usually, not always).

And I think the definition of "probe" has become a lot broader. I see KataGo saying "Why don't you just drop a stone into that area that looks like your opponent's settled territory? It costs nothing (they have to reply), and might provide some useful aji in the endgame." Again not a new idea, but happening earlier in the game and more often than I'm used to.

Sorry I'm too lazy to pull out specific examples from pro games today. I might come back here next time I notice something. Meanwhile, people can tell me where my opinions are wrong, and we'll have another interesting conversation :-)

I'll also go out on a limb and say that AI has not changed the late endgame (the part where you're down to 6-point moves or smaller). Humans already have a good conceptual framework for that part of the game, and in slow time controls I think the top players have been able to get pretty close to perfect endgame play for some decades. Computers might be stronger in terms of being more consistent, less likely to make mistakes under pressure, but I don't think they've introduced any new concepts for this part of the game.

Actually, no. There's enough randomness in the algorithms (partly from a random number seed, partly from races between multiple threads), and enough positions with two or more moves that have similar evaluations, so that monte carlo based algorithms will not actually do the same thing every time. That's one of the reasons why we don't need opening books for go playing engines (in contrast to computer chess).

You make some good observations but I disagree about the following:



I have also paid close attention to the timing of forcing moves: it differs greatly. In some environments, forcing occurs early. In other environments, it occurs late. In yet other environments, there is a long period during which it can occur, but there are exceptional moments when temporarily something elsewhere is more urgent (such as preventing a big cut in a joseki) when the forcing option is interrupted.



While this is so to some extent, closer study of AI evaluations has often revealed that standard developments emerge from initial randomness after sufficiently many playouts. Therefore, there can be AI style opening books if the author relies on enough playouts and study of positional variation.