AI making us lazy?

Talk about improving your game, resources you like, games you played, etc.
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Re: AI making us lazy?

Post by kvasir »

I am not sure AI makes us lazy. On the other hand it surely does let us indulge in overanalyzes.

When we review games it is often that we go through the game move-by-move questioning everything or we stop at a few places and spend an hour trying to come to some conclusions. It is especially common when a group of players sits down after their match in tournaments, but it is clear that many people do this on their own (I have found myself doing this). I never found it useful to ponder over a game and I have started calling it to overanalyze.

The best review is always a quick review that gives you some idea why the game was won/lost, if you are making the same mistakes as usual and if your important decisions were good (and what you could have done if they were not). Many times the only thing to learn from a game is "never make that mistake again".

First when I started reviewing my games using AI it was just this kind of overanalyzes. I hooked up a server with multiple brand new GPUs (only to learn that I could only use one at a time but it was fast enough anyways) then I downloaded the best leela weights and would just step through the game having the AI ponder on every move. Fairly useless, the top weights easily find fault in normal play and more playouts usually means their logic is irrefutable (except that they can't always find a logical resolution in very complicated local situations). Once you see their moves you just can't un-see them and your chances of learning anything are diminished.

This seems to be similar to how many players use the computer. Just have it do the work for you and then try to understand its reasoning. Be very confused and not try to discern something that you could actually improve.

Later I discovered that if I used weaker weights that they would actual agree with most of my moves and if they were not good they would usually not refute them with too crazy lines. So I started using Katrain on my laptop (that has bad GPU that is fast enough per-se but overheats and slows down after awhile). Now I find it very useful to run analysis to 250 playouts for every move and looking for obvious errors, something around -1.5 points seems to be a big mistake at my Pandanet level most of the time, if I have time (and the ambient temperature where I am is not too high for the laptop to cool off) I'll do a second run to 2500 playouts for every move to make sure the mistakes are actually mistakes (they are not always). If there is something interesting, then I will try to playout some variations (as opposite to thinking about them) to see if I can find a reasonable way to play that I might not easily think of or be unsure what to think of.

Sometimes I just throw the game into Katrain and start another game. Even though that often means that reviewing it will not have very high priority later. That seems to be a good thing because playing more is better than reviewing more.

Someone might say I am obviously lazy now that I have figured out my AI analyzes :D It is just that I really think that you are better off finding just a single mistake in every single game than you are finding improvements for all your normal moves.
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Re: AI making us lazy?

Post by Knotwilg »

kvasir wrote:I am not sure AI makes us lazy. On the other hand it surely does let us indulge in overanalyzing.
I do review every game nowadays but thanks to KataGo's sizing of the gap, I tend to focus more on the big swings in the estimated score, whereas in the past I may have dwelled on choices that didn't really matter. I find my game reviews have become much more productive.
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Re: AI making us lazy?

Post by dust »

kvasir wrote:...if I have time (and the ambient temperature ...)
Good to see the correct use of 'temperature' for once in relation to a Go game.
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Re: AI making us lazy?

Post by dust »

John Fairbairn wrote:
I
For me the benchmark is the well known case of T Mark Hall. He said (and I know it's true) that transcribing the games of Go Seigen (at that time I think it was about 750 games) got him from 2-dan to 4-dan (and British Champion). I can't remember how long it took him in the course of real life, but he could do about 3 games an hour. (Turns to calculator...) That's 250 hours. How much demonstrably stronger has AI made any dan player here in such a short space of time?

(Note that transcribing from one or two diagrams is very different from playing over a game in Go World. When transcribing, if you want to achieve any decent speed you have to learn to "guess" where the next move will be. Mark excelled at that. And conversely, when he transcribed amateur games he had to spend sometimes more than twice as long because he had no idea where the next crap move would be.)
I don't doubt this example at all, but I wonder if something is awry with the description of timing. T Mark was a fairly longstanding 3 dan (looking back at the online British Go Journal this seems to be since at least the early 80s, if not before). His promotion to 4 dan was in the early 90s I think (1994?).
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Re: AI making us lazy?

Post by John Fairbairn »

I don't doubt this example at all, but I wonder if something is awry with the description of timing. T Mark was a fairly longstanding 3 dan (looking back at the online British Go Journal this seems to be since at least the early 80s, if not before). His promotion to 4 dan was in the early 90s I think (1994?).
You may be right and, if so, you can safely assume it's because it involves numbers - they scramble my brain. One difference between Mark and me that we often commented on was that, although not a mathematician, he was a numbers guy. We both travelled a lot as part of our work - somewhere between 60 and 90 countries. He could tell me the exact dates he went to each place. I can't even remember if I've even been to certain places. For example, Houston and Atlanta (which I pick just because of the current World Series). I'm certain I've been to one but not sure if I've been to both. Mark would have been able to give me not just places and dates but his hotel room numbers. He kept all his boarding passes and hotel stationery samples.

I also spent a full ten minutes yesterday looking for my house key seconds after opening the door with it. It was in my pocket. I actually think I have a very good memory. I just choose to use it on things that matter to me.

And using that memory, I was able to dredge up a description that Mark wrote about himself. It may be of interest to younger people here who have heard only the name:
T Mark Hall’s first posting as a diplomat was to Tokyo. He returned from there bearing the unique gift of a diploma signed by Iwamoto Kaoru, Rin Kaiho and Shimamura Toshihiro. In the course of transcribing pro games for the database (with no other go study) he improved two grades and became 4-dan. He tied for a place in the 2009 British Championship match, and also won the 2000 British Open in Norwich, subsequently winning the 2003, 2004 and 2008 events (and also the 2008 Lightning Championship). He represented Britain in amateur events in Japan, China and Korea. He was Treasurer and Council Member of the British Go Association for more than two decades. His bequests included significant funds to help promote British go, and young British players in particular, and his antique board was accepted as a donation by the British Museum.
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Re: AI making us lazy?

Post by Javaness2 »

TMark's promotion record is reasonably simple to find, especially if you know where to look for it

Code: Select all

 title="4 dan 1994-01-03 
3 dan 1979-01-05 
2 dan 1975-05-14 
1 dan 1974-01-09" Mark Hall
I'm not sure why AI would make us any more lazy than a joseki dictionary would do. It's simply another source of knowledge you can refer to.
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Re: AI making us lazy?

Post by Knotwilg »

John Fairbairn wrote:One difference between Mark and me that we often commented on was that, although not a mathematician, he was a numbers guy. We both travelled a lot as part of our work - somewhere between 60 and 90 countries. He could tell me the exact dates he went to each place. I can't even remember if I've even been to certain places.
Off to a tangent of tangents here: I'm probably a numbers guy but while I'm borderline savant on (birth) years, I'm disastrous at (birth) days and months. The only explanation I found for that is that years are linear, while day+month is circular. I tend to assign a kind of (synesthetic) identity to a number. That works for a year but it doesn't for a date of any year. I guess ...

I can also relate to frantically searching for X while X is in my pocket/hand/... I have changed my idea about this trait from being absent minded to being caught in a preconception. The idea that I lost my wallet overrules the sense of holding it in my pocket.
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Re: AI making us lazy?

Post by Farodin »

A lot of interesting comments!

Now that the curious case of T Mark Hall has been mentioned again, I wanted to bring up something that I've recently been wondering about the advice of "replay pro games to get stronger", especially if the claim is that doing so is actually the fastest way to improve.

Before I go on, I want to say that would love for this to be true. Studying pro's games (Go Seigen in particular) is one of my favourite ways to spend time in front of the Go board, and I have in fact replayed about 200 of Go Seigen's games so far in the same way that T Mark Hall did, which is by replaying them from a single diagram that contains all the moves of the game.

The main thing I noticed was that my intuition became a lot better, but this lasts about as long as the opponent plays somewhat "proper" moves. Take the following example:
Click Here To Show Diagram Code
[go]A common shape
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ . . . . . B . B . . .
$$ . . . . . . a . . . .
$$ . . O . . O . B . . .
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ -------------------------
$$[/go]
This marked shape comes up very often in one's games, and so naturally also occurs often in Go Seigen's games. However, play this shape in a DDK (or even SDK) game, and it's quite likely that your opponent will play at 'a'. How do you handle it? This might be a bit of an easier example, but my point is that (I believe) simply playing through Go Seigen's games will not really teach you how to handle the move at 'a', because the black player (either Go or his opponent) will not play this shape to begin with if the move at 'a' is a good move for the opponent. So when you're training your neural network by playing over 1000 pro games, you will not really encounter the types of suboptimal moves that your opponent plays against you. This could foster the type of player who manages to win against a 2 dan but then loses to a 5kyu, but I think most people here would agree that this type of player doesn't truly "understand" the moves he's playing then. That brings me to the point of overplays and punishing mistakes, and that's where AI comes in again. Even if we simply compare the two methods of "studying pro games" and "reviewing with AI", and abstract all the rest away, I think AI is capable of giving more practical advice on your own game, because it can and will show you how to mercilessly punish the opponent when he oversteps his limits.

Then there are even skills that neither AI nor pro games can really teach you. One of them would be "visualisation" (as an aspect of "reading"). In-Seong sometimes tells us students to "train our go eye" by trying to read out the solution to a tsumego again after having solved it together. It's there that I noticed the astounding but obvious gap in "visualisation" capabilities between me and In-Seong. Sure, replaying pro games would help a lot with shape recognition and pruning away branches, but without the ability to hold a 30-move variation in your mind and evaluate the result, the shape knowledge will end up coming short.

Anyway, I'm deviating from the topic at hand, so I'll better stop rambling before I deviate even further.
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Re: AI making us lazy?

Post by John Fairbairn »

Anyway, I'm deviating from the topic at hand, so I'll better stop rambling before I deviate even further.
No, no, no, no! You are neither rambling nor deviating. Some topic headings are very specific, and so it's not always polite to derail them, but others are just starting points for a good old natter. As here. After all, if we start a conversation in the pub with "Chilly today, isn't it?" we wouldn't expect to talk about the weather all evening.

I found what you said interesting but I do disagree with some of it. For example, in the magari pattern you showed, you may never see a pro play at A and so get flummoxed when your amateur opponent plays it. But your brain still learns something from the fact you never see it, and so it will tend not throw it up as a candidate move (which may be a good thing).

I would suggest that what is supposed to be happening when you are playing over pro games is that you are learning suji. How to make your stones flow, how to get the right (long-term) shapes, and how to pick out the best candidate moves. What you are referring to in amateur games is something quite different: reading (yomi). You don't learn reading by playing over pro games. For that you do tsumego, tesuji problems or visualisation reps.

You need both suji and yomi, but suji is often the best one to start with because its knack of throwing up good candidate plays enables you to prune the dense trees that pure reading generates.

The drawback with suji is that you can become very LAZY (see how easy it is to get back on topic!). We amateurs are too apt to play by shape alone and not read out the consequences.

A problem with using AI in this sort of situation is that you get a "you can have any colour you like so long as it's blue" response, and also a response that is very game-specific. I'd suggest using suji and kombilo instead. Put in a shape as above and you'll get the full range of moves ever played, and in order of frequency, along with the pro games that show you various contexts and also the follow-ups to the very end of the game. I just put in the pattern you showed into kombilo and got 63 pro-game hits for the kosumi (so it does occur after all - never say never!). In reply, the two possible connections are the main moves and are split about 50-50 relative to each other, but there are other possible replies, some very surprising. These too are precisely the types of move that can improve your suji no end by showing you new stuff you can experiment with.
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Re: AI making us lazy?

Post by gowan »

Some comments on the topic of using AI for studying and laziness. I understand how Mark Hall could improve his playing strength through transcribing pro games. Pros also recommend laying out the moves of a game as a method of studying. Yoda Norimoto pro 9-dan wrote a book titled Yoda Ryuu--naraberu dake de tsuyoku naru--Kogo Meikyoku Shuu (Yoda-style--Become stronger just by laying out the moves--A Collection of Old Go Master Games). It is common knowledge that there is a correlation between playing strength and speed of finding moves in game records.
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Re: AI making us lazy?

Post by Kirby »

Click Here To Show Diagram Code
[go]A common shape
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ . . . . . B . B . . .
$$ . . . . . . a . . . .
$$ . . O . . O . B . . .
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ -------------------------
$$[/go]
Analogies rarely fit perfectly, but this example brings to mind shooting free throws in basketball. If you're not a basketball player, you can look up the "proper form" to shoot a free throw on the internet: position your body, bend your knees, shift your weight, line up your shooting arm, yada yada yada.

Practice all of the textbook stuff, and you can have the proper form to shoot a basketball.

But it's not the same as learning how to... properly shoot a basketball. For that, you need to practice and gain experience. Play some real games. Get used to shooting when there's pressure. The list goes on. But the proper form will help you in the end. Combine proper form and experience, and you should see a good result. Why? Because "proper form" has been developed by players over the years, and with enough practice, we know that people can apply it to make it work.

Back to AI. Reviewing a game with AI can give you ideas on the "proper form" to play in a given position. Same thing with joseki and/or learning from pros. But it's necessary to combine that knowledge with experience.

Someone with bad form in both basketball and in go may be able to win games by sheer experience and strength. But if you're going to be practicing anyway, why not practice with good form?
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Re: AI making us lazy?

Post by gowan »

As for laziness, what about playing through game records by using a computer app rather than reading a game record and putting stones on a board? Using a computer app tends to encourage just clicking through, the moves hardly registering. Playing through in person with a board and stones offers us more opportunity to experience the moves. First you have to find the move in the diagram, second you have to pick up a stone and put it in the proper place on the board. Both of these activities allow us to "see" the move and its relationship to the whole board position. Teachers know that students who take handwritten notes in class tend to learn more that just listening to the lecture and even reviewing the lecture if it was recorded.
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Re: AI making us lazy?

Post by gennan »

For those who are not familiar with the implications of that black shape, I'd like to share some shape knowledge about it (as we are allowed and even encouraged to wander somewhat off-topic here).

The stability of that black shape relies on this tesuji.
Click Here To Show Diagram Code
[go]$$W Refuting the double peep ("Elephant's eye") and cut
$$ . . . . . . . . . . .
$$ . . . . . . 4 5 . . .
$$ . . . . . B 3 B . O .
$$ . . . . . . 1 2 . . .
$$ . . . . 6 O . B . O .
$$ . . . . 7 8 . . . . .
$$ . . . . . . . . . . .
$$ -------------------------
$$[/go]
So white's cut is not working well. White needs an extra stone at any of the marked spots to invalidate black's tesuji.
Click Here To Show Diagram Code
[go]$$W White's threats
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ . . . . . B . B . O .
$$ . . . . M M a . . . .
$$ . . . M M O M B . O .
$$ . . . . M M M . . . .
$$ . . . . . M . . . . .
$$ -------------------------
$$[/go]
Note that this does not include a white 2-space extension or knight move to the left, so those moves would not really prompt black to defend against a.

So a common way for white to activate the a cut, is a one space jump to the left (a double purpose move, defending and attacking).
Click Here To Show Diagram Code
[go]$$W Black needs to defend
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ . . . . . B . B . O .
$$ . . . . . . a . . . .
$$ . . . 1 . O . B . O .
$$ . . . . b . . . . . .
$$ . . . . . . . . . . .
$$ -------------------------
$$[/go]
A clever black defence is the probe at b, making miai of A...
Click Here To Show Diagram Code
[go]$$W Sabaki for black
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ . . . . . B . B . O .
$$ . . . . . 4 . . . . .
$$ . . . 1 5 O . B . O .
$$ . . . . 2 3 . . . . .
$$ . . . . . . . . . . .
$$ -------------------------
$$[/go]
and B...
Click Here To Show Diagram Code
[go]$$W Sabaki for black
$$ . . . . . . . . . . .
$$ . . . . . . . . . . .
$$ . . . . . B . B . O .
$$ . . . . . . . . . . .
$$ . . . 1 3 O 4 B . O .
$$ . . . . 2 5 . . . . .
$$ . . . . . . . . . . .
$$ -------------------------
$$[/go]
I probably aqcuired this knowledge from books and lessons I got from stronger players. I suspect it would have been difficult to discover this kind of shape knowledge totally by myself, even with the help of AI.
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Re: AI making us lazy?

Post by CDavis7M »

gennan wrote:For those who are not familiar with the implications of that black shape, I'd like to share some shape knowledge about it (as we are allowed and even encouraged to wander somewhat off-topic here)...The stability of that black shape relies on this tesuji...I probably aqcuired this knowledge from books and lessons I got from stronger players. I suspect it would have been difficult to discover this kind of shape knowledge totally by myself, even with the help of AI.
Thanks for sharing. I have often seen the shape but I don't know if I ever recognized the tesuji, instead just focusing on the cuts.

Without AI or study, my understanding of this shape comes from the following position in a professional game, supposedly great for White. White has the 2-stone wall 2 spaces away and bumped against the cap before playing the peep.
Click Here To Show Diagram Code
[go]$$W
$$ | . . . , . . . . . , . . . . . , . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . X . . . . . . . . . . . . . O . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . 5 . . . . . |
$$ | . . . O . . . 8 6 . 2 . . . . . X . . |
$$ | . . O , . O . . 7 9 . . . . . 4 . . . |
$$ | . . . . X O . . O . X . 1 . 3 X . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ -------------------------
$$[/go]
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Re: AI making us lazy?

Post by gennan »

Surrounding positions matter. With the support of the nearby 2 stone wall, a one space jump would be very inefficient shape, so naturally, white didn't play there.
But still the elephant's eye is not working because of black's refuting crosscut tesuji, so white bumped to urge black to defend. But black didn't want to follow white's orders, so he resisted, allowing white to play the elephant's eye that is now working (move 80 of Akaboshi vs Jowa, "The blood vomiting game").

That white bump up (uppercut?) seems to be quite rare in pro games though. So I'd say that it looks like a very circumstantial move, not like the "book" move against this black shape.

So if you only play the uppercut against black's shape (because of that game), then maybe you also want to check out some of the many pro games where white plays the much more standard one space jump.
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