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Human Go Champion 'Speechless' After 2nd Loss To Machine (phys.org)

Posted by msmash on from the still-struggling-but-won't-give-up dept.

Reader chasm22 points to a Phys.org report about the second straight loss of Lee Sedol to AlphaGo, the program developed by Google's DeepMind unit. The human Go champion, Sedol found himself "speechless" after the showdown on Thursday. The human versus machine face-off lasted more than four hours, which to Sedol's credit is a slight improvement over his previous match, which had ended with him resigning nearly half an hour remaining on the clock. "It was a clear loss on my part," Sedol said at a press conference on Thursday. "From the beginning there was no moment I thought I was leading." Demis Hassabis, who heads Google's DeepMind, said, "Because the number of possible Go board positions exceeds the number of atoms in the universe, top players rely heavily on their intuition." Sedol will battle Google's AlphaGo again on Saturday, Sunday, and Tuesday.

13 of 338 comments (clear)

  1. Milestone by Lisandro · · Score: 5, Insightful

    Having a competitive Go engine capable of beating a 9-dan player is huge. Huge.

    1. Re:Milestone by irrational_design · · Score: 5, Funny

      My brother dan is older than 9, maybe he should have a go.

    2. Re:Milestone by Lisandro · · Score: 5, Informative

      This is nothing like the "regular" AI used on modern chess engines - those are useless for the essentially infinite game tree possibilities like the ones presented in Go. AlpaGo decides moves using a machine learning neural network and then selects the best one using classic heuristics.

    3. Re:Milestone by Lisandro · · Score: 5, Informative

      Search space, basically, and the amount of moves you have to inspect before selecting a best one. Chess has about 10^120 possible moves, but you can reduce this using opening books and heuristics to a sensible number which still lets you pick very strong moves. At that point it is just a matter of throwing CPU power at the problem.

      Go is a completely different beast though. A "small" 13x13 board has 10^170 valid moves, and the count for a 21x21 board is well over 10^210. So for even small, beginner-level sized boards no amount of CPU power, now or in the future, is bound to help you solve the problem. Go is interesting because every engine out there uses some form of adaptative AI - AlphaGo uses a machine learning neural net which had to be trained like a human would, but with over 30 million recorded moves.

    4. Re:Milestone by larryjoe · · Score: 5, Interesting

      I agree that this achievement by AlphaGo is extremely significant. However, I wonder if future experiments can focus more on the human vs. computer move selection algorithm comparison by minimizing tangential aspects. By tangential aspects, I'm referring to the other existing differences that perhaps reflect human failings more than strength of computation. In particular, I would like to see the removal of tournament rules because such rules were formulated to limit humans.

      First, I would like to see time limits for moves eliminated. The computer can be augmented with extra hardware, higher clock frequencies, etc. to render time limits inconsequential for it, but the human cannot. As was seen in the 2nd match, time potentially impacted Mr. Lee by not only limiting his thinking time but more importantly by decreasing his emotional stability.

      Second, I would like to see how the computer fares against a consensus of experts. By consensus, I'm imagining a group of 5-10 top players who discuss the best next move and then select the next move hopefully by consensus or at least by majority vote. Even the top players rarely maintain top play for every single move of a match. My hope is that a consensus of experts minimizes this human failing.

      As a side note, I think that the setup for the human vs. computer experiment is extremely significant. As an example, the Watson triumph in Jeopardy was entirely expected but not very significant in terms of comparing human vs. computer thought. Rather, human buzzer pushing reflexes were compared against computer reflexes, and for that comparison, the computer should never lose. In Jeopardy, the buzzer impact is only minimized when one contestant knows more than the others. If all contestants know most of the answers, then the game devolves to a buzzer contest, which was the situation with Watson, Ken Jennings, and Brad Rutter. What would have been much more interesting would have been to allow Watson and the humans to each respond within a certain time window and to compare the percentage of correct responses without the impact of buzzers. Watson might have still won, but I would be shocked if the disparities were large. I.e., eliminate the tournament rules that are intended to impose artificial limits on humans that were crafted to maximize entertainment value and magnify the differences between actual skill.

    5. Re: Milestone by TuringTest · · Score: 5, Funny

      You, sir, broke my parser.

      --
      Singularity: a belief in the "God" idea with the "demiurge" relation inverted.
    6. Re:Milestone by Bender0x7D1 · · Score: 5, Funny

      Second, I would like to see how the computer fares against a consensus of experts. By consensus, I'm imagining a group of 5-10 top players who discuss the best next move and then select the next move hopefully by consensus or at least by majority vote.

      So you want a RAGE against the machine? (Redundant Array of Go Experts)

      --
      Reading code is like reading the dictionary - you have to read half of it before you can go back and understand it.
    7. Re:Milestone by ljw1004 · · Score: 5, Informative

      Li will eventually learn to manipulate the machine; it's *very* intelligent, but not creative or insightful.

      Not creative? That's your opinion. Here are what other people (including serious Go professionals) think...

      "AlphaGo met Lee’s solid, prudent play with a creativity and flexibility that surprised professional commentators" - https://gogameguru.com/alphago...

      An Youngil (8d) wrote of AlphaGo playing Black: "Black 13 was creative ... Black 37 was a rare and intriguing shoulder hit ... Black 151, 157 and 159 were brilliant moves, and the game was practically decided by 165 ... AlphaGo’s style of play in the opening seems creative! Black 13, 15, 29 and 37 were very unusual moves." -- https://gogameguru.com/alphago...

      Redmond (9d) wrote "I was impressed with AlphaGo’s play. There was a great beauty to the opening ... It was a beautiful, innovative game. ... AlphaGo started with some very unusual looking moves ... It played this shoulder-hit here which was a very innovative move ... I really liked the way it played in the opening, because I wasn't so impressed about the orthodox October games, but now it's playing a much more interesting exciting game." -- http://googleasiapacific.blogs...

      Anders Kierulf (3d, creator of SmartGo) wrote: "The peep at move 15: This is usually played much later in the game, and never without first extending on the bottom. AlphaGo don’t care. It adds 29 later, and makes the whole thing work with the creative shoulder hit of 37 ... AlphaGo don’t care, it just builds up its framework, and then shows a lot of flexibility in where it ends up with territory." -- http://www.smartgo.com/blog/al...

      Maybe you start with a philosophical axiom that "a computer can by definition never be considered creative". That's fair enough, but it's not the way that the Go playing community use the word "creative".

    8. Re: Milestone by Your.Master · · Score: 5, Interesting

      It's a trained neural network and other machine learning techniques, not just a bespoke algorithm. It operates specifically by combining old knowledge to create novel knowledge. That's the fundamental of the algorithm.

      It's not obvious why this "creativity" in the context of Go is fundamentally less effective than human "creativity" in the context of Go.

  2. Re:What about Magic the Gathering? by Anonymous Coward · · Score: 5, Funny

    They tried to program a computer to play Magic The Gathering, but the computer immediately received a wedgie, and was stuffed into a locker.

  3. Re:What about Magic the Gathering? by PvtVoid · · Score: 5, Funny

    AI's will also never best you at sitting on the couch in your parents' basement eating cheetos and watching anime. Your skillz are safe.

  4. Date clarification by Anonymous Coward · · Score: 5, Informative

    Sedol will battle Google's AlphaGo again on Saturday, Sunday, and Tuesday.

    Note that for many people in the western hemisphere, the days are actually Friday, Saturday, and Monday.

    Live streams are here.

  5. Re:the problem by LateArthurDent · · Score: 5, Interesting

    he's playing against it like it's a human opponent, he's playing against it like he's a go champion, he needs to play against it like he's a programmer. I would be curious as to how it deals with mirror play, or wildly suboptimal plays. I would wonder if it's overfit to go played well.

    Ever tried that with a chess program? Doesn't go over well. A wildly suboptimal play just makes the tree search look really good for the computer. It doesn't get emotionally distraught because it thinks you've seen something it didn't. It just sees better valued moves.

    This Go algorithm is even more complex. It's a neural-network algorithm combined with tree-search (I don't play Go, but as I understand it, the number of permutations are so high, tree-search alone isn't feasible). This neural network was trained using input from previous tournaments, using games against expert players, and using games against itself. I don't think you can throw anything at it that will break it. Computers have officially become better than humans at Go. In a decade or so, when the really good Go programs can run in your phone, you'll be seeing the same type of cheating attempts going on that currently plague chess competitions.