Cho Chikun is a legendary player ,and was top of the world in the 70's. From that era, along with Takemiya Masaki, he was one of the only ones that kept playing and kept winning titles even in his old age.

The style of 70's players was artistic and not as sports-like as koreans were when they rose in the 90's. They always showed a higher level of philosophy and art in game, but it was ultimately crushed by the "machine-like" tactical capacity of korean players. Cho chikun has very little chance to beat Lee sedol. But he was confident on beating Zen, and he did something unspeakable in the LeeSedol Matches: he came back from a losing game, from a machine that looked that would never relent its edges.

As a retired semi-professional Go player that learnt by replaying games from Cho Chikun, it is exciting to see the Japenese artistic and humane vision dominate the computer over the Korean Tactical sports-minded way.

Cho Chikun had the large advantage over Lee Sedol that his opponent (Zen) and similar programs (Crazy Stone, Leela) are simply available for him to practice against and probe for weaknesses.

Then of course there's also a significant reduction in the speed of the hardware.

Both of those matter a lot. I won't make a firm statement how relevant the style argument is you mention, but really, don't underestimate those two.

"Machines reaching a level of play that is consistently better than humans" and "the game is solved" are two completely different statements and it isn't particularly useful to conflate them.

We will likely never be able to solve Go in the formal sense.

Very good point

>We will likely never be able to solve Go in the formal sense.

I'm not sure if it would be precise to say chess will be solved either. The number of outcomes in a 50-move chess game approaches Graham's Number--a number larger than the number of atoms in the observable universe.

In a 100-move game, the number would be many orders of magnitude than an already incomprehensibly large number. So chess also will probably in a precise definition of the word, also never be solved.

Edit: It's kind of mind boggling to think about every atom in the universe representing one position in a game of chess and there not being enough atoms in the universe to represent each one.

10^(number of outcomes in a 50-move chess games) also does not come close.

I did find this interesting statement about Graham's number (unsure of the veracity):

> Graham's number is greater than all of the Planck lengths in the universe. There literally isn't room in the universe to write it out in numerical form.

Edit: It looks like we confused Graham's Number for Shannon's number: https://en.wikipedia.org/wiki/Shannon_number

But according to the Wiki on Shannon's number, a the number of possible outcomes in chess does still far exceed the number of atoms in the universe: >Allis also estimated the game-tree complexity to be at least 10123, "based on an average branching factor of 35 and an average game length of 80". As a comparison, the number of atoms in the observable universe, to which it is often compared, is estimated to be between 4×10^79 and 4×10^81.

I don't believe your comparison between fundamentally different games is sufficient to support your conclusion that an extremely large number of calculations does not pose a challenge for computer programs to solve.

Rather, to the best of my knowledge, to support your conclusion what you would need to do is to prove there exists a method or formula for reducing the number of permutations to a manageable number while still coming to an optimal solution. Apparently if Sudoku is easy to solve, that exists in Sudoku, but it certainly does not yet exist in the realm of human knowledge in chess.

The fact is that Sudoku and many card games are easy to solve, while chess is in fact a much, much more challenging problem for a computer program, and there are a lot of very smart people that have worked on that problem.

HOWEVER, arguing that they aren't solvable purely from a point of view of "the number of possible games / states is greater than the number of particles in the universe" type arguments is that there are many problems we routinely solve with massive search spaces.

Well, you could just do a Google search for yourself to see why your reasoning is wrong. The problem with using a computer to play Go is precisely what I described, the extremely high number of permutations involved, and it's the same concept with chess (Go just has even more of them): https://www.wired.com/2016/01/googles-go-victory-is-just-a-g...

I still disagree with your argument. The problem with Go isn't just the high number of permutations involved, there are real-world problems, with just as many permutations, which have been solved.

The extra problem with Go (and chess to a lesser degree) is that's it's incredibly hard to be sure, with any certainty, to be sure that a move is a "good" choice.

Comparing to the sudoku example again, when "playing" sudoku it's usually obvious as soon as you make a bad move, you've put two '1's in the same row/column/box for example. With Go if we want to play well, or perfectly, we really have to explore the entire search space.

Sudoku is a game, and in which to solve it, a computer program has an obvious method to limit possible permutations to compute in finding a solution. In other words, it is not faced with the challenge of a requirement to compute permutations > 10^86 (roughly atoms in the observable universe).

In contrast to sudoku, chess and go are games which have no yet discovered or theoretical method to limit permutations to solve, therefore to solve them you would be required to computer permutations > 10^86.

So the problem is still with the number of permutations.

Like I said in my other post: if you could develop a technique to reduce the number of permutations while still solving the optimal solution then you would be onto something. Right now no one has been able to dream up such a theory and there are a lot of very smart people who have worked on this problem.

Chess players mentions this a lot. And then they consider chess a sport. For a sport, it shure is a mind boggingly low number of game states :)

(ps: I don't mean to start an uninteresting sport-or-not debate. It is what it is.)

So the fact that Cho Chikun won against a less powerful machine is not necessarily an indication that the entire system is weaker than DeepMind's one. To know that you'd have to run Zen against AlphaGo.

______________

[1] A big hint of why it didn't is that, at the time, IBM was still selling more hardware than software.

That's an argument against Go having been solved by AlphaGo, not for. If Lee Sedol could beat AlphaGo given the opportunity to practice against it, then nothing is solved.

Also, for a system to dominate against humans in a game it must be able to beat any opponent every time. AlphaGo hasn't demonstrated this yet, so while in the popular opinion AlphaGo "dominates", in the technical sense it does not, and Go won't be "solved" conclusively until it has.

This is false. Ke Jie is far far below Lee Sedol.

Lee Sedol has no equal. Well, AlphaGo beat him but we are talking about player ranks.

With much tighter time constraints, I don't believe machines would do as well because they are using full-breadth search (to my knowledge) -- searching every possibliity. Whereas humans use visual pattern recognition, and we can run this programs quite fast.

Zen is commercial software sold to people with a normal PC, so obviously reaching AlphaGo performance on AlphaGo hardware does their customers no good either.

It's for sure stronger than Darkforest. Some free PC programs like Leela have reached Darkforest levels on normal PC hardware (Darkforest used 44 NVIDIA Tesla cards, Leela uses a single normal "gaming" GPU), and Zen is several stones stronger than Leela.

Note, it looks like only version 6 is out:

https://book.mynavi.jp/ec/products/detail/id=62646

It appears that DeepZen would be a new version that is not quite yet released to the public.

Still, major props to Hideki Kato, who's developing cutting edge AI at the age of 62. I wish to have his drive at that age!

Your certainty is based on what data?

You can see the graph of its playstrength; its quite impressive to see the gains Zen got from implementing ValueNet (and previously with PolicyNet) really.

https://www.gokgs.com/graphPage.jsp?user=Zen19K2

Hardware for ZenK2 was given on computer-go mailinglist:

Zen19K2's information is

------------------------------------- Computer program Zen running on KURISU server provided by DWANGO.

CPU: Xeon E5-2623 v3 x2 GPU: GeForce GTX TITAN X x4

http://computer-go.org/pipermail/computer-go/2016-October/00...

author of Zen gave the hardware behind this match, in a post to the same mailinglist as:

http://computer-go.org/pipermail/computer-go/2016-November/0...

CPU: 2 x Intel Xeon E5-2699v4 (44 cores/2.2 GHz) GPU: 4 x nVidia Titan X (Pascal ) RAM: 128GB

So rather similar.

~10d is way way lower than what AlphaGo had to be to play on par with one of the top players of Go. Pro ranks start around or just above the KGS 9d (which is around what a 7d rank would be for regular amateurs in most world amateur organisations). A rough approximation is that you can take 3-4 pro ranks for each dan rank/stone of handicap (well, to the extent one can even approximate strength by the rank, as a rank once won is kept for life, so as you age and young pro players pass you by, your rating is getting inflated). So apriori you could expect Zen to play around middling pro ranks, and maybe around the strength of the v13 of AlphaGo, the one that beat Fan Hui, and described in the Nature paper. And that's about what his play with Chikun indicates as well.

Cho Chikun's rating is 3239, while Lee Sedol's is 3508. so around 300 elo difference, which seems a conservative estimate of the difference scale (and the results of the two matches do indicate, if weakly, that the actual difference is even larger). A 230 point gap corresponds to a 79% probability of winning.

For comparison, distributed AlphaGo v13, the one that played vs Fan Hui is 250 elo points stronger than a single machine version of the same version of AlphaGo.

Also if that would carry any weight with you, you could just take it on the say-so of Myungwan Kim 9p, who was doing commentary on both DeepZen and AlphaGo matches. Really the difference in strength seems rather obvious to such a strong go player, as you can see in the way he criticized some DeepZen's moves, and how impressed he was with so many of AlphaGo's.

So many of my coworkers seem to have lost intellectual curiosity as they have gotten older.

I'm fairly close to retirement, and have friends who are getting there (or retired already). I really enjoy programming, and intend to continue indefinitely; most of my friends tolerate it as a job, and look forward to not doing it when they retire.

So it's the old "follow your passion" thing, again, I guess... I have that curiosity about such things, they don't.

my backwater go community doesnt really care about computers because we're too focussed on trying not to be so lousy, and on the conversation. the light chase.

i'm super curious...when you see alpha against sedol, or whatever this is against chikun. do you read something there? is there a character?

Looking at alpha, something similar but at higher level happens: it looks so profoundly tactical that its hard to catch character from it. I can tell how Lee felt however: like i felt playing people close to his level, like you play a wall that you cant read.

He's not exactly retired, you know: https://www.goratings.org/players/98.html

i.e. "Lee Sedol used about 20 Watts of power to operate. By contrast, AlphaGo runs on a whopping 1920 CPUs and another 280 GPUs for an estimated power consumption of approximately 1 MW (200 W per CPU and 200 W per GPU). That’s 50,000 times as much power as the amount of power that Lee Sedol’s brain uses and the two are not quite evenly matched but it is close enough to use for comparison."[0]

I mean, sure, it's apples to oranges, but it feels like a pyrrhic victory to have to use 1MW of computing power to beat a 20w brain.

I want there to be a series of AI vs. AI games where everyone has an equal power budget for their AI. Everyone has to bring their own equipment and they receive exactly X kwh from a calibrated power supply to train their model. Training data could possibly also be standardized.

Each team would received a standardized power supply for the actual competition (e.g 20w). There could be bonuses for using less energy for training or during gameplay, or for faster response times between moves.

I believe this would drive innovation in building special purpose hardware, more efficient training models, and so on.

[0] http://jacquesmattheij.com/another-way-of-looking-at-lee-sed...

Simply making a statement like this doesn't really say much. You really need to back it up with evidence, justification and/or reasoning, or at least elaborate on it a little.

What's the advantage of this over simply providing every team with identical hardware and equal computing time? It seems like providing a fixed power supply would favor whoever can afford to buy more efficient computing equipment.

Also, there's no reason why you couldn't have different competition categories where you're limited to using X dollars worth of time on a specific cloud provider, for example.

I mean, it's mildly interesting that DeepZen uses fewer resources (just ~40 CPUs and 4 GPU, compared to AlphaGo's ~2k CPU and ~200 GPUs, IIRC). But that's relevant only to hardcore Go enthusiasts who would want to run such AIs on their own hardware.

In contrast, the next interesting milestones in Go AI are:

* AI beating a team of cooperating top pros, say top-10 humans vs AI (easy)

* solving Go (hard)

* finding ways to translate insights gained from observing strong Go AI into real-life situations relevant outside of Go (my personal favourite; Go has that fascinating simple-meets-complex abstracting property [1])

[1] https://rare-technologies.com/go_games_life/

It is not clear at all that the cooperating team is more difficult to beatä

> * solving Go (hard) Not only hard, but 'solving Go' it is beyond AI, and probably cannot be done.

* finding ways to translate insights gained from observing strong Go AI into real-life situations relevant outside of Go (my personal favourite; Go has that fascinating simple-meets-complex abstracting property [1])

Here I fully agree, as conan noted in another thread, stylistic factors are quite important, and the art-like approach is a thing in Go, so I would love to know "what the AI thinks about it" :)

1. Perfect play from any game position.

2. Proof of perfect play.

#1 may be achievable with a sufficiently clever algorithm. (We may suspect it is perfect and may only later prove it.) #2 may be much much harder. Neither are suitable for brute force approaches to play or proof as some problem spaces are.

But so far commentators such as Ke Jie (higher rating than Lee Sedol), said that Deep Zen Go's yose (end-game) is very weak compared to Alpha Go.

Another factor is that Cho Chikun had the advantage of studying more MCTS/DL bot games. Today you can find MCTS/DL bots in servers such as KGS that you can play against.

Cho Chikun had more clear expectations of the bot playing level. e.g: Lee Sedol greatly underestimated Alpha Go initially, then he was in shock and did not know what to expect. Your playing strategy can vary depending of strengths and weaknesses of your opponent.

[0] https://en.wikipedia.org/wiki/Solving_chess

The best computer algos beat humans at chess by a huge margin, to the point a regular PC beats Carlsen (and I heard even the best smartphone apps beat him).

Carlsen's ELO rating = 2853

Top chess program ELO rating = 3381

The number of DIFFERENT programs stronger than Carlsen = 59

http://www.computerchess.org.uk/ccrl/4040/

https://ratings.fide.com/top.phtml?list=men

I don't think it has. Much like horseback riding has not made olympic races obsolete, human competition remained fascinating. I for one very much followed the rise of Magnus Carlsen.

Personally, the fact that computers are better at chess than humans makes me less interested in the game so I'm a bit biased.

I do think that technological advances in general affect the appeal of certain games and sports by rendering them less mysterious or by bringing them further from a real world activity/situation.

Of course, I'm talking about relative, not absolute, popularity. Chess and horseback riding will remain popular for a long, long time.

It hasn't, in the slightest. The fact that computers playing at full strength can beat top humans makes no difference in the enjoyability of the game for people.

not sure if suggests any comparison between AlphaGo and Zen. I'd like to see Cho play against AlphaGo.

How many matches with other computers did Deep Blue play after its victory over Kasparov? (zero)

How many world championships did Deep Blue win? (zero, it played one in 1995 and lost to Fritz)

How many people tought Deep Blue was the strongest computer in the world in 1996? (All of them, because IBM said so and conveniently forgot about the lost world championship)

Google has already said AlphaGo is much stronger than other programs. There's no point in playing a match then, is there?