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AlphaGo success

  1. Jan 28, 2016 #1
  2. jcsd
  3. Jan 28, 2016 #2
    Well there you have it, The Terminator is not far off.
     
  4. Jan 31, 2016 #3

    fluidistic

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    Direct link to the paper: https://storage.googleapis.com/deepmind-data/assets/papers/deepmind-mastering-go.pdf [Broken].
    What google did is a huge achievement, a leap of more than at least 10 years in go programming, leaving facebook's team and everyone else (see http://arxiv.org/abs/1511.06410) extremely far lagging behind.
    Very original ideas that were never tried before, in alphago.
    Granted Google bought some extremely talented programmers and also go players (e.g. Aja Huang). Marvelous work. An enormous step for humanity has been achieved.
     
    Last edited by a moderator: May 7, 2017
  5. Feb 1, 2016 #4

    berkeman

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    Can someone comment on why the game of Go is exponentially more complex than chess?

    Sorry, I admit to not having read the full article. Thanks. :smile:
     
  6. Feb 1, 2016 #5
    I believe one of the main reasons had to do with the number of possible moves in each game. Chess has on average about 20 moves per player where as Go has over 200. We can see how this gets exponentially more complex for a computer trying to determine the best move based on possible future moves. 20 options this turn, next turn, next turn 20^n for n moves. 200^n for n moves of Go.
     
  7. Feb 2, 2016 #6

    D H

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    Fixed that for you!


    "There are more configurations of the board than there are atoms in the universe."
     
  8. Feb 2, 2016 #7
    Hi berkeman:

    In addition to the factor of tree search multiplicity discussed in the posts by jtdonoval and D H, there is also the factor of pattern multiplicity. Using very rough and informal number estimates, a world class chess player may recognize perhaps 10,000 patterns which suggest plausible moves, while a world class go player may recognize 100,000.

    Regards,
    Buzz
     
  9. Feb 2, 2016 #8

    D H

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    I played regularly in college, and then years later, in the mid 1980s. My boss at the time was 3 or 4 dan (amateur); we played almost every day after work. I worked my way up through the ranks to perhaps 2 dan (amateur). There were no nearby players when jobs made us part ways, so I bought one of the first computer go games available for sale to the public. This was Bruce Wilcox's Nemesis Go Master. I had to give it a nine stone handicap and then make three or four extremely dumb moves (i.e., right on the corners of the board) just to make it mildly interesting.That's akin to giving away your queen, both of your rooks, and then some in chess. My skills have since degraded due to lack of play and lack of a young mind; I'd be lucky to be 12 kyu now. Computer go on the other hand has improved vastly since then, but this latest development is a huge, huge leap.
     
  10. Feb 2, 2016 #9
    If you think we've mastered artificial intelligence...



    Better call Sol...
     
    Last edited: Feb 2, 2016
  11. Feb 2, 2016 #10
    Wow! I literally told my friend yesterday that no one has managed to make a Go bot that can beat a skilled human, even 20 years after Deep Blue beat world Chess champion Garry Kasparov, and then I randomly see this on the headlines here at PF :O

    Elon Musk's warnings are starting to sound very real.
     
  12. Feb 2, 2016 #11
    In addition to the shear number of moves, there are many more strategic considerations in go than in chess.

    Chess can be thought of in terms of territory covered, mobility of pieces, and tempo. (I'm sure there are more, but those are the big three.)

    In go, there are considerations that don't even have English words. Sente is sort of like initiative, but also includes ideas of tempo and question asking. Other ideas include thickness, heaviness (not related to thickness; thick = good, heavy = bad), shape (how well your stones (pieces) work together), influence, territory, and elegance ("it just looks right"), tesuji (standard "trick" patterns), reading, life and death, and others. These all need to be weighed against each other each move (At least for humans, my understanding is skynet -- sorry -- AlphaGo uses a stochastic process where it fills the board with random moves, and keeps the ones that win -- as a part of its code anyway.)

    All hail President Executron! :bow:
     
  13. Feb 2, 2016 #12
    Hi Nantes:

    Since you did not show any emoticon, I am curious about your actual feelings regarding Musk's warnings. Do you find them to be actually scary, or were you being humorous, like Greg in post #2?

    Regards,
    Buzz
     
  14. Feb 2, 2016 #13
    Way to AlphaGo! I have a new game to learn I see... amazing I've never seen it, or noticed it if I did. Perhaps this can be a precursor to an AI rating system, Go level: alpha. The rest fall in the curve...
    Come on already! I've only been dreaming about it forever... wish I was there.
     
  15. Feb 3, 2016 #14

    D H

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    There's only one site if you live outside of Asia and if you wish to learn the game. That site is Sensei's library, http://senseis.xmp.net . It is 100% free. There's only one option if you live outside of Asia and you wish to play the game, and that's to install an IGS client on your computer and then play against Asians at odd hours of the day (odd hours to you, that is). You can find plenty of IGS clients. Sensei's Library has a large catalog.

    I'm over 60; I can't play at IGS anymore. Go is a game for those with extremely agile, extremely intuitive, and extremely imaginative minds. In this regard, go is a bit like chess. Go is a game best suited for younger adults. The world champion against whom AlphaGo will play next is 33. That's a bit old for a world champion.

    Be very, very careful of what you wish for. You might well get what you wish for.

    DeepMind, the Google subsidiary that created AlphaGo, has created an AI ethics board. What this means, who knows? Playing go at anything beyond the potzer stage requires imagination. (Full disclosure: I gave up chess for go 40+ years ago. Playing chess is mechanical. Playing go is anything but.)

    An algorithmic model of "imagination" is exactly what DeepMind claims to have accomplished. This leaves me split in two. One part of me says "This is so cool!". Another part says SKYNET! (Oh noes!)
     
  16. Feb 3, 2016 #15
    I'm 44 but I've never "stretched" those mental muscles yet, and imagination is by far my best quality. And while I'm learning the game I'll be thinking about how to "spot" patterns to exploit which could take mastery then perhaps I can join the fun and create my version of a quantum supercomputer brain in my garage.
     
  17. Feb 3, 2016 #16

    D H

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    More full disclosure: I took on a new job 35+ years ago. My previous job made me feel a need to cleanse me soul. (Anything more than that, deponent saith not.) My new job sent me all over the world to help develop and install meteorological ground stations, and that included Communist China. This was well before Tiananmen Square. We were assigned "watchers" by the Chinese government, and we knew full well who they were. When my watcher asked me what I most wanted to buy before I went home, I responded that what I wanted most was a pair of sets of jade go pieces and go board to go along with it. We went to a low-scale shopping center, and there it was.

    I still have that set. The stones make the most wondrous sound when one intentionally places one of them on a point.
     
  18. Feb 3, 2016 #17

    jedishrfu

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    The iOS universe has the the SmartGo Kifu app that is pretty decent. It has features to teach the game as well as playing it. It's a bit pricey as compared to other iOS apps at around $20 but it has a cheaper cousin SmartGo Player at $3 with more limited features.

    https://www.smartgo.com/kifu.html

    It also has Windows and MacOS versions as well but no Android version that I can see.

    The cheaper cosin SmartGo Player features vs SmartGo Kifu:

    https://www.smartgo.com/player.html#compare
     
  19. Feb 3, 2016 #18

    atyy

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    The news reports about AlphaGo quote Ilya Sutskever of OpenAI.

    https://openai.com/blog/introducing-openai/

    Aren't Asimov's 3 laws enough?
     
  20. Feb 3, 2016 #19
    I hope no one minds if I make a prediction regarding the near future of go AIs performance vs. human opponents. My prediction is based on my recollections of the history of chess AIs when they first became strong enough to being to win against strong (as I recall master level) human opponents. After less than a year, the chess AIs good performances began to decline significantly. I recall that the reason for the early success and later decline is that the inherent stylistic weakness of those AIs were not at first recognized, but after a while human opponents figured it out. The weakness was that the AIs were excellent at tactics, but had no programmed concepts related to playing positional chess. Later AI generations improved by a combination of deeper analysis and including some aspects of positional play in the position evaluation algorithms.

    I predict that the go AIs, like AlphaGo, will go through a similar performance experience over the next year or so. And when that happens, the developers will then find a way to make another major advance.

    BTW, I also believe that chess AIs, as good as they have become, have the possibility of further major improvement that would make them virtually unbeatable by humans. The improvement will involve adding the ability to set deep traps. If there is interest, I will explain this idea in more detail in a separate thread.
     
  21. Feb 3, 2016 #20
    I thought chess AIs are already unbeatable by humans. You mean MORE unbeatable?
     
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