Introducing SensAI Go

Knotwilg · **#21**

kvasir wrote:

Knotwilg wrote:

kvasir wrote:

It is sometimes hard to tell what people mean when they talk about learning Go. To me that means improving at playing the game from start to finish and to the best of my knowledge you need to play games, from start to finish, without any external aid if you wish to improve at this. Everything else that you do is support for the main activity of playing games. However, there are other views.

I agree with your first statement: the goal is to improve at playing the game from start to finish without external aid. Let's call this "performance". The only way to know if you have improved your performance, is to perform more (play) and measure the outcome (review).
Your second statement is probably equivalent to my previous sentence but the categorization of everything else as tertiary activities suggests that all training which is NOT by means of performance is of a much lower importance. Here I'm not so sure.

I think you disagree. You are saying that you think playing games is performance and you appear to have interpreted what I wrote and then raised questions about, or even taken issues with, that interpretation. It is when you write "Your second statement is probably equivalent to my previous sentence..." that you appear to completely remove what I wrote from consideration. The thing is that playing games isn't only performance. Most of the time it is just practice or exercise. Surely you agree that there is a need to practice, to exercise and to repeat the mental process that goes into finding a move until it is second nature?

Then I'm not sure why you interpret what I wrote to mean that every activity other than playing is of much lower importance. Instead it means that the tertiary activity depends on the primary and secondary activity, if you don't do the first two there is little purpose in the the third. It is not that the third level is of low importance, it is that it supports the first two.

Knotwilg wrote:

I do have a harder time to make similar constructions in Go. The common "isolated training" consists of joseki, life and death, and endgame. However, the impact on one's performance (winning games) of such training is not as strong as in the abovementioned skills. There are even proverbs saying (rote) learning joseki makes you weaker, suggesting the whole (board) always defies the sum of the parts.

I think there are two reasons for that:
1. Sometimes this kind of training strengthens skills that are rarely needed, sometimes you just won't be able to detect the change until much later.
2. It can be difficult during training to get into the same mindset that you are in when you need to use the skills.

Of course you can try to overcome these limitations, for example you could have better designed exercises or work on getting into the right mindset. Another way is to play games, one thing that Go has over many other activities is that is it rather easy to play and review.

Knotwilg wrote:

Quote:

Computer programs are of course great for exploring shapes and testing your reasoning about some positions, their main drawbacks is that they still tend to be fairly opinionated and they often prefer going down the rabbit hole over the simple solutions that often work better in practice. Their evaluation often isn't objective for human vs. human game and it gets worse the farther you are from their level of play.

http://www.neuralnetgoproblems.com is doing a good job at countering your argument.

Now, I don't know what argument that is or how it is countered. My limited experience with those problems is that they aren't that great. Does it really have any relevance to what I wrote?

Let me not try then to agree with or rephrase your statements, although I don't know how to claim relevance to your thoughts without referring to them.

1. I prefer distinguishing "performance = games" from "training = any other activity, which I think you labelled secondary or tertiary", even though every game is indeed a learning opportunity and every training triggers our desire to perform well. I claim that playing many games as away of improvement is inherently inefficient, because of the fuzzy learning you get out of each "repetition". Now I do understand that Go might be comparatively more complex in terms of skill acquisition than e.g. table tennis, where the skills involved can be more easily isolated and re-integrated, and the relative impact of each skill on the performance is more easily identified. E.g. serve & return are skills with great impact, since each point starts like that and most points are rather short, so serve & return take up a big proportion of the overall value. In Go we can't say the same about the opening moves, nor any aspect of the game to have such impact on overall performance. My best shots are "emotional balance", "time management" and "liberty awareness", since lack of these skills can make us easily throw away an otherwise good game, and all can be practiced on every move. OTOH, they mostly help us performing at our current level of understanding, but don't enhance it.

2. You said - if I got that right - that computers don't take into account the human capacity to absorb their advice. I offered https://neuralnetgoproblems.com/ as a good example of how AI combines its knowledge with the human learner's level to provide well targeted exercises and solutions. We seem to disagree - if I got that right - on the quality of that resource.

pwaldron · **#22**

John Fairbairn wrote:

9. The word 'rhythm' seems to come up as lot. This may just be fashionable use of an English term in place of choushi, but it may also betoken a sense of a different feeling to the concept - something more related to creating a web in the centre.

Would rhythm be different than flow or development?

To my Western vocabulary, rhythm implies some level of dynamic development, something you have commented about in the past. I could image also overlap some with the haengma that was so popular years ago.

John Fairbairn · **#23**

Quote:

Would rhythm be different than flow or development?

As I indicated, I think we'd have to see inside Nakane's head to know his intentions. I suspect it might be equivalent to choushi, because that is also a musical term that denotes the beat. But the go usage is hardly musical, so I prefer the term 'momentum' for that. You might say choushi in go resembles conducting an ensemble from the keyboard.

I think development is an overloaded term, and flow is as perhaps as wishy-washy as it sounds. I usually reserve flow to talk about suji, but since I assert that haengma is suji + katachi, it would be wrong top call hanegma either 'flow' or 'rhythm.'

In short, I wot not.

kvasir · **#24**

Knotwilg wrote:

1. I prefer distinguishing "performance = games" from "training = any other activity, which I think you labelled secondary or tertiary", even though every game is indeed a learning opportunity and every training triggers our desire to perform well. I claim that playing many games as away of improvement is inherently inefficient, because of the fuzzy learning you get out of each "repetition". Now I do understand that Go might be comparatively more complex in terms of skill acquisition than e.g. table tennis, where the skills involved can be more easily isolated and re-integrated, and the relative impact of each skill on the performance is more easily identified. E.g. serve & return are skills with great impact, since each point starts like that and most points are rather short, so serve & return take up a big proportion of the overall value. In Go we can't say the same about the opening moves, nor any aspect of the game to have such impact on overall performance. My best shots are "emotional balance", "time management" and "liberty awareness", since lack of these skills can make us easily throw away an otherwise good game, and all can be practiced on every move. OTOH, they mostly help us performing at our current level of understanding, but don't enhance it.

You are of course leaving out practice and exercise when you say that you prefer to distinguish between performance and training. Playing games is practice, exercise and sometimes training. I didn’t mention that it was training, is this the issue, that playing games isn’t supposed to be good training? That seems nuanced or even pedantic, we do after all play games to improve, not only to practice what we can already do. You prefer to say games are “performance”, that seems like a mislabel to me, they are usually practice, exercise and sometimes training. Now, it doesn’t make sense to me to say activities such as reading a Go book are “training”, even if you read Go books with a “no pain, no gain” attitude; it is another mislabel from my perspective.

I’m not sure if you only wish to talk about training, since that is one of your two categories, I mean I talked about more general activities not only training. You gave some examples of skill acquisition in table tennis and Go. It strikes me that the skills that you identify for table tennis all involve fitness and coordination, and the skills that you identify for Go don’t. The table tennis skills that you mention are immersive tasks which totally encompass the athletes’ experience for the duration of that task. I think they are meant as examples of training. When it comes to Go you don’t mention tasks that I think should be immersive and I’m not sure why they should be comparable to the table tennis tasks. Yet, playing Go also involves a series of highly immersive tasks that require a high degree of mental fitness and coordination of different thoughts, not unlike how table tennis or any physical sport rely on physical fitness and coordination of the movement of the body. I don’t think it should be difficult to come up with examples of training for Go.

Knotwilg wrote:

2. You said - if I got that right - that computers don't take into account the human capacity to absorb their advice. I offered https://neuralnetgoproblems.com/ as a good example of how AI combines its knowledge with the human learner's level to provide well targeted exercises and solutions. We seem to disagree - if I got that right - on the quality of that resource.

That is not at all what I said. I don’t know what the argument is about here, it is as if I write one thing and you then read something entirely different. Sure, I haven’t found the problems on that site to be great. I have read your praise of them, but even then, I don’t understand what the connection is. You don’t appear to take any issue with what I did write.

Knotwilg · **#25**

kvasir wrote:

Knotwilg wrote:

1. I prefer distinguishing "performance = games" from "training = any other activity, which I think you labelled secondary or tertiary", even though every game is indeed a learning opportunity and every training triggers our desire to perform well. I claim that playing many games as away of improvement is inherently inefficient, because of the fuzzy learning you get out of each "repetition". Now I do understand that Go might be comparatively more complex in terms of skill acquisition than e.g. table tennis, where the skills involved can be more easily isolated and re-integrated, and the relative impact of each skill on the performance is more easily identified. E.g. serve & return are skills with great impact, since each point starts like that and most points are rather short, so serve & return take up a big proportion of the overall value. In Go we can't say the same about the opening moves, nor any aspect of the game to have such impact on overall performance. My best shots are "emotional balance", "time management" and "liberty awareness", since lack of these skills can make us easily throw away an otherwise good game, and all can be practiced on every move. OTOH, they mostly help us performing at our current level of understanding, but don't enhance it.

You are of course leaving out practice and exercise when you say that you prefer to distinguish between performance and training. Playing games is practice, exercise and sometimes training. I didn’t mention that it was training, is this the issue, that playing games isn’t supposed to be good training? That seems nuanced or even pedantic, we do after all play games to improve, not only to practice what we can already do. You prefer to say games are “performance”, that seems like a mislabel to me, they are usually practice, exercise and sometimes training. Now, it doesn’t make sense to me to say activities such as reading a Go book are “training”, even if you read Go books with a “no pain, no gain” attitude; it is another mislabel from my perspective.

I’m not sure if you only wish to talk about training, since that is one of your two categories, I mean I talked about more general activities not only training. You gave some examples of skill acquisition in table tennis and Go. It strikes me that the skills that you identify for table tennis all involve fitness and coordination, and the skills that you identify for Go don’t. The table tennis skills that you mention are immersive tasks which totally encompass the athletes’ experience for the duration of that task. I think they are meant as examples of training. When it comes to Go you don’t mention tasks that I think should be immersive and I’m not sure why they should be comparable to the table tennis tasks. Yet, playing Go also involves a series of highly immersive tasks that require a high degree of mental fitness and coordination of different thoughts, not unlike how table tennis or any physical sport rely on physical fitness and coordination of the movement of the body. I don’t think it should be difficult to come up with examples of training for Go.

Knotwilg wrote:

2. You said - if I got that right - that computers don't take into account the human capacity to absorb their advice. I offered https://neuralnetgoproblems.com/ as a good example of how AI combines its knowledge with the human learner's level to provide well targeted exercises and solutions. We seem to disagree - if I got that right - on the quality of that resource.

That is not at all what I said. I don’t know what the argument is about here, it is as if I write one thing and you then read something entirely different. Sure, I haven’t found the problems on that site to be great. I have read your praise of them, but even then, I don’t understand what the connection is. You don’t appear to take any issue with what I did write.

OK, let's put it to rest then. I'm rather tired of misreading and misquoting you. I'm not doing it on purpose but neither do I question my ability to read English.

Javaness2 · **#26**

It's an interesting idea, but I'm not sure that's the best medium with which to deliver feedback during the same.
I think if I was playing I would just find the additional noise offputting. Did you try the same idea but with a purely visual feedback for the key ideas, urgency & state.

When I review a games I probably focus on a few things
- If there was a fight I totally misread, I revisit that.
- If I wanted to play something but didn't out of fear, I revisit that.
- Look for places that I felt I went wrong

If I have an AI handy I would additionally (after doing the above)
- Look to see where I totally messed up, according to the AI
- Look at any move the AI might suggest which is just unexpected for me
- Where I had no idea what to do, check the AI's suggestion

John Fairbairn · **#27**

One thing I've noticed over the years in many fields is that mathematicians, programmers, scientists and the like cleave religiously to the scientific method, logic, repeated testing and the like, and the aim is always to end up understanding rigorously how things work, or what is going on, and how to avoid mistakes. In their own fields, I think that is a wonderful thing. I'd certainly prefer to be treated by a doctor who knows what he is doing and why, for example.

But there is a risk among such people of déformation professionelle -- looking at fields in which they are not experts through the prism of their own major work. Like applying logic to go, for example.

There are problems even within scientific fields. All the fancy maths, logic, scientific theories and philosophising that went into "experts" telling us that the world began with a Big Bang has been shot down in an instant (if - big if - I can believe Youtube) by the Webb telescope. That telescope is itself a masterpiece of human ingenuity based on maths, logic and scientific method, of course. But looking at the rather wider problem of the universe, their methods have failed.

Indeed, these methods have failed on the slightly smaller universe of the go board. AlphaGo and its spawn produced bots that beat the best humans, yes. But have they explained how go works, why some moves are better than others, etc etc? No.

Yet in this thread and others on L19 we are repeatedly seeing mathematicians, programmers, scientists and the like trying to apply their professional procedures to go - and getting nowhere.

But along comes a little girl with no special interest in maths, science or programming - and certainly no expertise, and no time to acquire it yet - and she reaches a level (1-dan pro) at age 11 that far exceeds any of the mathematicians, programmers, scientists and the like. And she's not that unusual. Lots of young kids in the main go-playing countries are playing at pro level.

I don't believe for one moment that Nakamura Sumire and her ilk indulge in the navel gazing of trying to understand their moves or mistakes in the various fashions described here. They just copy the best moves they see. They learn by mimicking. Indulging oneself in trying to unravel mistakes wastes time that could be better spent in mimicry of good moves - it could even lead to mimicking bad moves by playing over one's mistakes and reinforcing them in one's subconscious.

Take an utterly trivial analogy for comparison. A little child grabs a toy. A parent says, "Don't do that, say please." The child says please next time, mimicking polite and successful people, and gets the toy without a clip round the ear. Some parents may philosophise about politeness and morality to the child, but what little child listens to that? They don't even understand what you are saying. It merely makes the adult feel good (been there, done that

). But the odd thing is that the child doesn't actually understand the word 'please' either. It just mimics the word and gets the toy. Magic. Template for future behaviour!

People like Sumire have discovered a way to spot the go equivalents of saying 'please' - and again without understanding why they work. Their brains "understand" in more or less the same way as AlphGo, of course, through the intuition produced by neural networking, but it is their subconscious brain that is doing all the clever work.

On a bigger scale, this is how we all - including mathematicians, programmers, scientists and the like - learn language. Logic doesn't work there. A child says "I breaked it", you say "I broke it." You both understand each other. One form is not mathematically, logically or scientifically better than the other. We just agree to treat one version as socially more correct. That is, we don't really need to understand (though, of course, a neurolinguist might get great personal satisfaction from try to fathom it).

It is my contention, therefore, that those who wish to improve significantly at go (1 amateur dan in two years or something like that is far too slow to count in that respect) must treat the learning process in the same way as learning a language, or in the same way as Sumire learns go. That's what pros have been telling us for decades, after all. Play over lots and lots and lots and lots and lots of pro games.

But we now have a new tool: AI. OK, but don't use it to do scientific analysis of mistakes - if you want to improve significantly, that is. If you just want the glow of exercising your professional skills, it's fine for that, but that's all it gives. The correct approach seems to be, instead, simply copying what you think are AI's good moves. If they work in your real games, you will note that and so your intuition will also note that and prompt you to play them in future. If they don't work, your intuition will note your disappointment and not prompt you. Of course, if you override your intuition and keep playing what are bad moves, you deserve what you get.

One common argument is that adults can't spend the time that young people spend on building up intuition, and so have to try to find a quick fix in other ways. Broadly, I accept that, but the point here is that AI may (MAY) be a way to streamline the mimicry process even for adults. We won't know unless enough people try it, but it has to be said that mimicry of AI without proper understanding has worked for many top pros (in chess as well as go).

I hope it goes without saying that other skills as diverse as reading or controlling one's nerves are necessary for true mastery, but without filling the databank with data, those other skills have nothing substantial to work on.

I hope it also goes without saying that improving to 1-dan pro or whatever is not necessary to enjoy go. People like me - and I suspect I'm in a very big majority - just like adding snippets of knowledge continuously as a way of better appreciating the best go players. We are go fans. Our needs may therefore differ. We can probably get by with no AI at all.

RobertJasiek · **#28**

John tells a tale and covers it with alibies, such as mentioning the word reading.

Knotwilg · **#29**

You do realize, John, that mathematics is also a kind of language, with a syntax of symbols and semantics that try explaining the world in a certain way. And although we have acquired that understanding in a rigorous, structural way in the curriculum of the past decades, it has always been helpful and way more interesting to follow the history of scientific progress. Education has realized that and is now swinging away from the axiomatic approach, back to the experimental approach.

The dichotomy between the cold, purely logical, theoretical, non-empirical approach in science, and the warm, intuitive, concrete and imitative acquisition of language, is false.

In both your examples of the origins of the universe and the game of Go, I think science has actually been very successful. But man can't grasp the notion of "nothingness" in space and time. Surely there must be something outside the borders of the universe. Surely there must have been something before the big bang. Similarly, AI is now playing Go on a superhuman level. "It" understands perfectly well what it does. We don't, but that's not AI's fault. I think BTW that, if we give AI the challenge of explaining what it does, rather than playing well, we might get there very soon.

dust · **#30**

golem7 wrote:

(snip)
The thesis is "Longterm training with live AI feedback (in addition to "classical" training) has the potential to improve evaluation, judgement, intuition and playing strength in general". A counter-example would be if someone had actually studied this way for a long time but seen no improvement. And even one counter-example wouldn't be a refutation since I'm not making all-or-nothing claims here.
The only scientifically valid way to approach this would be to have a group of players (big enough to be statistically relevant) train longterm (months/years) with this method and compare their improvement with a control group that followed the exact same training regimen, only leaving out the live feedback during games.

Anyway my point is not to devalue any existing methods for improvement (play, study, tsumego etc.), on the contrary, they are absolutely necessary. I'm just proposing that we can add something more to get a little extra boost.

The human brain is an all-purpose learning system, and it might be able to incorporate AI feedback signals as well in order to improve it's internal model of the game of Go (or other domains).

That is my theory and only time will tell us if there's anything to it.

It'll be interesting to see this theory tested.

It's also good to have a new idea to shake up the rather familiar discussions on L19 on 'how to improve' featuring a handful of ageing regulars - each with their own idiosyncratic strong opinions, and none of whom are probably improving significantly

(I include myself fully in that description)

golem7 · **#31**

kvasir wrote:

It is what the education professionals in my Go club tell me. I don't think it needs much discussion that if you interrupt an exercise that it is likely to have a negative effect. As far as I see your suggestion it is interrupting the task, it is a distraction from the task, but with the nuance that there is some information being conveyed that is useful for completing the task. Yet the question is not if the task can be performed better, the question is if something is learned faster this way. I'm not sure what that something would be, is it the feedback itself?
In your video you show a game in progress on an online platform and some audio feedback at the same time. Now you talk about your experience playing while having such feedback. Who did you play?

I'm not suggesting to interrupt the game for feedback, it is really generated live and runs in the background while I play, maybe that wasn't clear?
I've played various games online against random opponents while I had my feedback program running.

What can be learned?
The main idea is to improve evaluation/judgement, by always being instantly aware of the result of moves/sequences (did the position improve or worsen?)

golem7 · **#32**

Javaness2 wrote:

It's an interesting idea, but I'm not sure that's the best medium with which to deliver feedback during the same.
I think if I was playing I would just find the additional noise offputting. Did you try the same idea but with a purely visual feedback for the key ideas, urgency & state.

I added the visual feedback only later to the program, I originally wanted it to be only audio in order to not distract the eyes from the game. I haven't tried visual only.
In my vision of an ideal future go server that offers such a feedback training mode, each user would be able to choose which feedback type they prefer:
heartbeat audio, visual, music, nature sounds, arcade-style, electrocute when blundering, many things are possible

golem7 · **#33**

John, this Nakane-AI series, can we watch this somewhere? (ideally with subtitles)

dust wrote:

It'll be interesting to see this theory tested.

It's also good to have a new idea to shake up the rather familiar discussions on L19 on 'how to improve' featuring a handful of ageing regulars - each with their own idiosyncratic strong opinions, and none of whom are probably improving significantly

(I include myself fully in that description)

Many thanks dust!

FYI: Episode 2 is online:
https://www.youtube.com/watch?v=69Orf_tzQKU

John Fairbairn · **#34**

Quote:

John, this Nakane-AI series, can we watch this somewhere? (ideally with subtitles)

No idea. I read it in Go World. It's planned to run for a year so I expect they are aiming at a future book.

John Fairbairn · **#35**

'Rhythm' came up in this thread, and intuition (or whatever you call internalising information) comes up in lots of threads, and I have a particular hobby-horse in talking about the benefits of studying suji over shape, or the dynamic over static.

It was therefore of great interest to read something last night on this topic but with a different sidelight. There was also a piece of information new to me which I have bolded here, but which was not emphasised in the original. I will give a longish quote so as to provide sufficient context. The overall context is a book called The Everyday Dancer by Deborah Bull, who was a ballet equivalent of a 9-dan go pro, being a Principal with the Royal Ballet (she is now Baroness BUll CBE). I recommend the book strongly. I will assume the readers here can make the relevant connections with amateur go and previous threads.

Quote:

To an outsider, the first rehearsals of a ballet would probably appear to be rather slow and inconsequential. fractured movement phrases interrupted by some head scratching and sections repeated over and over again as we struggle to claw back the physical sensation of choreography that has not been danced - or even thought about - for months, if not years. It's hard - even for the dancers involved - to see the connection between these early studio calls and the polished performance of the first night.

Some dancers are better than others at recalling once-familiar steps from dusty memory stores. Frequently we remember, but not quite accurately, swearing we did a step on the left leg when the evidence (a video, for instance) proves it was on the right. When ballets are long out of the repertoire, dancers are likely to remember the rhythm and dynamics of the choreography rather than the exact steps, certain that it went 'di dum, dum, dum, and three and four', but unsure exactly what it was. Interrogating the memory too consciously can cause it to retreat for ever into some distant corner of the brain, and too many questions usually prove fatal. ('No, no, don't ask, just let me do it for you.') Even now, as I try to recall snippets of choreography from my dancing years, I know that I'm best placed to do it as I'm falling asleep at night, when my conscious brain is a bit less 'on duty' than it is during the day.

WE talk a lot about getting things 'into our bodies' and it's true that when we really know a ballet, it seems to be stored directly in our muscles and not in our brains. But while 'muscle memory' is a good way of describing how it feels to dance a well-rehearsed role, it's not accurate. The body doesn't function like a memory-foam mattress, storing shapes and movements as indentations within its lean tissue. What 'muscle memory' probably means is that the steps have been repeated so often, and over such a long period of time, that the skill has become unconscious, their 'memory' moved from the centre of the brain to the cerebellum. When you dance these highly familiar steps, it feels as if your body is doing them on its own, without any reference to the conscious brain, as if you're dancing on autopilot. This is a vital stage in progressing from fumbling first rehearsal to expert performance, and it leaves the frontal cortex free for the important business of interpretation and interaction with the other artists on the stage.

golem7 · **#36**

New Episode online:
https://youtu.be/YNvDvtjqC70?si=3pBJwIdFuqBq8QFI

This one is more back-and-forth than the first ones that were quite one sided, so you can see more action in the feedback system.
Enjoy

kvasir · **#37**

golem7 wrote:

I've played various games online against random opponents while I had my feedback program running.

That is called cheating.

golem7 · **#38**

kvasir wrote:

That is called cheating.

You're entitled to your opinion. Of course it's an advantage to be aware of the evaluation. But you still have to think for yourself which moves to play.

Anyway, I think I've explained my reasoning very clearly in my article. The vision is to implement the system in a way so that both opponents receive the same feedback to ensure fairness.
I'm merely demonstrating the concept.

By the way, there is a new episode.
https://youtu.be/fkfq3b8qf4c

And since some people commented that they don't like the audio feedback, I have created a 2nd version without the heartbeat sound:
https://youtu.be/1NkRrfEJjgA

Enjoy

RobertJasiek · **#39**

kvasir wrote:

golem7 wrote:

I've played various games online against random opponents while I had my feedback program running.

That is called cheating.

It is cheating
- in tournament games unless explicitly allowed by the tournament rules of special, AI-use-friendly tournaments, otherwise
- in rated games regardless of any opponent's agreement because of affecting third players, otherwise
- unless the opponent agrees in advance.

There are study purposes for using AI during games but they ought to avoid any cheating as above.

kvasir · **#40**

golem7 wrote:

kvasir wrote:

That is called cheating.

You're entitled to your opinion. Of course it's an advantage to be aware of the evaluation. But you still have to think for yourself which moves to play.

Anyway, I think I've explained my reasoning very clearly in my article. The vision is to implement the system in a way so that both opponents receive the same feedback to ensure fairness.
I'm merely demonstrating the concept.

By the way, there is a new episode.
https://youtu.be/fkfq3b8qf4c

And since some people commented that they don't like the audio feedback, I have created a 2nd version without the heartbeat sound:
https://youtu.be/1NkRrfEJjgA

Enjoy

One more video of cheating. It is sickening.

Obviously, wanting to build a system to play a game never compelled anyone to cheat. Cheating is deceit and crookery. It is incredible to think, because one has some lofty goal and desire, that the means toward the end need to be deceit and crookery. Honest people always seem to find reasons to not stoop so low. If only cheaters could be as creative with reasons for not cheating as they can be with reasons for cheating.

When someone cheats in Go it stops being Go. They stop being a Go player and become a cheater. No one should care what a cheater thinks about studying Go. It is like a cannibal chef's ideas about gastronomy or an infanticidal nurse's opinion on postnatal care. It is something so grisly that it evokes an entirely different kind of interest. Such people may masquerade as chefs and nurses but they are not chefs and they are not nurses. Being a chef requires integrity when it comes to preparing food and being a nurse requires integrity when it comes to care of patients. Being a Go player requires, above all else, enough integrity to know not to cheat in Go.

Introducing SensAI Go

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