Stonefight at the Goke Corral
Will there be any man left standing?
|Sensei’s Library player bio source|
Lee Sedol of South Korea, who is currently ranked #4 on the unofficial GoRatings list, may be on his way to being #5. AlphaGo, a computer project sponsored by Google DeepMind, is ahead 2-0 in their five-game match.
Today I take stock, explain some of what has happened, and briefly discuss the prospects for AI and human ingenuity.
Go is our most ancient and deepest of games. Whereas the Western rules of chess weren’t settled until the Renaissance, Go has been substantially the same for over 2,500 years. The largest change was about 1,500 years ago to move from a 17×17 to a 19×19 board. This is over five times the size of a chess board, creates a high bandwidth of reasonable moves at each turn, and leads to games up to and over 100 moves for each player compared to an average near 40 at chess. Most Go moves have consequences far beyond the horizon of most chess “combinations,” yet human players have a reliable “feel” for strong play without express calculation.
I discussed aspects of depth and computer advances a year-plus ago. Despite my hedge there against expecting the long timeframe obtained by extrapolating my “Moore’s Law of Games,” I must say I expected Go to last at least to 2030. The “nonlinear jump” has apparently come from actuating the human approach through multiple layers of convolutional neural networks. This has produced many human-savvy moves, but also some “inhuman” stunners have come from AlphaGo’s go-ke (the Japanese term for the jar of stones) with devastating effect.
Not Just the Ear Was Red
As with the “Immortal,” “Evergreen,” and “Shower of Gold” games at chess, Go has its own lore of historical games with evocative names: “Blood on the Board,” “Reddened Ear,” “Atomic Bomb” (which was continued after the Hiroshima blast damaged the venue and injured spectators), and Lee Sedol’s own “Broken Ladder” victory. The “Reddened Ear” came in 1846 when a champion realized after his opponent’s surprising center move that he was in danger on two fronts.
I was watching the second game when AlphaGo with the black stones played a move that the master commentator, Mike Redmond, thought was a mis-transmission—see his reaction 30 seconds from the video point here:
|Modified from game replay source
Sedol had just played his white stone to Q11 to stake out territory in the east. Redmond opined that a “more normal” reply would have been P7—to support the posse of black stones at lower right and contemplate disputing the land claim by riding out to R8. But AlphaGo played at P10. Perhaps all of Sedol turned red as he left his chair despite his own clock running down, and he did not reply until over 15 of his remaining 95 minutes had elapsed.
My own first impression of P10 was a beginner move allowing White to firm up the whole right side by Q10. In Go it is considered most valuable to own the corners and the edges—indeed well over half the points are within 3 of the edge. However, this move also had influence to the center and north. Sedol didn’t play Q10 after all—he felt he had to defend the north by P11 instead, and in the closing phase he was forced back two whole rows to cells S10 through S7 from what he could have had by walling from Q10 to Q7 if left undisturbed.
In analytical terms, P10 did not win the game—this expert commentary page says that Sedol was ahead for several stretches afterward. But in human terms it was a blow, much as my own work indicates that Garry Kasparov played 200 rating points below his usual form against Deep Blue. In the game’s last quarter, Sedol had to play on one-minute grace periods called “byo-yomi” and seemed to stumble for lack of time to his defeat on move 211. On the other hand, AlphaGo’s own evaluation was said to be a steady advantage over that phase, and whom could we ask to verify the human-commentator opinions now besides AlphaGo? Chess programs have found many errors in classic game commentaries.
All this leads us to ask, what’s in store humanly when the duel resumes at 11pm ET tonight?
Slim Chance or Fat Chance?
“Slim” is a common Old West cowboy name, and was chosen by the actor Slim Pickens. However, a gunslinger avatar of AlphaGo would have to be the opposite: phagó is Greek for “`eating” so AlphaGo might translate to “Fat Al.” As in fatal—for any human opponent. Does Lee Sedol stand a chance in any of the remaining games?
We will find out overnight Saturday, Sunday, and Tuesday US time, which is afternoon time in Seoul where the matches are being played. The YouTube links and times for live video commentary have already been fixed on the Google DeepMind channel; here they are individually:
- Game 3, video start 10:30pm EST Friday;
- Game 4, video start 10:30pm EST Saturday;
- Game 5, video start 11:30pm EDT Monday.
The games start a half-hour in. The page also has the saved feeds and shorter 15-minute summaries of the first two games. A second place for live commentary in English is the American Go Association’s YouTube channel.
Unless Sedol can find a silver bullet it may be the Tombstone for human supremacy at strategy games. But it already comes with a silver lining: Go programs that relied primarily on exact calculations had stayed far below professional human players even after Monte Carlo self-play was introduced ten years ago. AlphaGo uses both—indeed the paper shows six interlinked components—but the main fillip comes from imitating the learning process of the human mind. This shows concretely that our brains embody computing efficacy that is not simply replaced by calculation in overt numeric and symbolic terms, per argument here. This also underscores what a tremendous achievement this is already for the Google DeepMind team.
To date there has not seemed to be any reason in Go to hold top-level freestyle tournaments in which multiple human and computer players consult as a team. Will there be now, and will the combination prevail over computers playing alone as it did for chess, at least for awhile?
Update (10:50pm 3/11): The Game 3 AlphaGo broadcast has begun with a lengthy discussion/interview about the P10 move in which an AlphaGo team member explained how it came about. (3/12): AlphaGo won game 3 most convincingly per the GoGameGuru commentary page. Great article by Albert Silver covering the games and comparing chess and Go programs.
[some minor word changes, fixed Friday time, added AGA channel, linked previous post re “silver lining” argument at end]