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  • Dear Fellow Scholars, this is Two Minute Papers withroly Zsolnai-Fehér.

    親愛的學者夥伴們,這裡是 Károly Zsolnai-Fehér 的二分鐘報導

  • In 1997, the news took the world by storm - Garry Kasparov, world champion and grandmaster chess player

    在 1997 年,這個新聞席捲了全世界 - 世界西洋棋冠軍同時也是棋聖的 Garry Kasparov

  • was defeated by an artificial intelligence program by the name Deep Blue.

    被一個名叫 Deep Blue 的人工智慧程式擊敗

  • In 2011, IBM Watson won first place in the famous American Quiz Show, Jeopardy.

    在 2011 年,IBM Watson 贏得美國有名的智力測驗電視節目《危險邊緣》的第一名

  • In 2014, Google DeepMind created an algorithm that that mastered a number of Atari games by working on raw pixel input.

    在 2014 年,Google DeepMind 建立一套演算法藉由一列一列分析影像像素來學習許多 Atari 遊戲

  • This algorithm learned in a similar way as a human would.


  • This time around, Google DeepMind embarked on a journey to write an algorithm that plays Go.

    此時此刻,Google DeepMind 己經踏上寫出一個圍棋演算法的旅程

  • Go is an ancient chinese board game where the opposing players try to capture each other's stones on the board.


  • Behind the veil of this deceptively simple ruleset, lies an enormous layer of depth and complexity.


  • As scientists like to say, the search space of this problem is significantly larger than that of chess.


  • So large, that one often has to rely on human intuition to find a suitable next move,


  • therefore it is not surprising that playing Go on a high level is, or maybe was widely believed to be intractable for machines.


  • This chart shows the skill level of previous artificial intelligence programs.


  • The green bar is shows the skill level of a professional player used as a reference.


  • The red bars mean that these older techniques required a significant starting advantage to be able to contend with human opponents.


  • As you can see, DeepMind's new program's skill level is well beyond most professional players.

    如你所見,DeepMind 推出的新程式技術水平高過大部分的專業玩家。

  • An elite pro player and European champion Fan Hui was challenged to play AlphaGo, Google DeepMind's newest invention

    樊麾,一位曾獲歐洲冠軍的菁英職業棋士被 Google DeepMind 最新的發明 AlphaGo 挑戰

  • and got defeated in all five matches they played together.


  • During these games, each turn it took approximately 2 seconds for the algorithm to come up with the next move.

    在這幾盤棋中,演算法每次會花大約 2 秒鐘計算出下一步

  • An interesting detail is that these strange black bars show confidence intervals,


  • which means that the smaller they are, the more confident one can be in the validity of the measurements.


  • As one can see, these confidence intervals are much shorter for the artificial intelligence programs than the human player,


  • likely because one can fire up a machine and let it play a million games,


  • and get a great estimation of its skill level, while the human player can only play a very limited number of matches.


  • There is still a lot left to be excited for, in March, the algorithm will play a world champion.


  • The rate of improvement in artificial intelligence research is accelerating at a staggering pace.


  • The only question that remains is not if something is possible, but when it will become possible.


  • I wake up every day excited to read the newest breakthroughs in the field, and of course,


  • trying to add some leaves to the tree of knowledge with my own projects.


  • I feel privileged to be alive in such an amazing time.


  • As always, there's lots of references in the description box, make sure to check them out.


  • Thanks for watching and for your generous support, and I'll see you next time!


Dear Fellow Scholars, this is Two Minute Papers withroly Zsolnai-Fehér.

親愛的學者夥伴們,這裡是 Károly Zsolnai-Fehér 的二分鐘報導


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B1 中級 中文 美國腔 演算法 圍棋 技術 人工 水平 冠軍

兩分鐘論文--DeepMind如何用深度學習(AlphaGo)征服圍棋? (Two Minute Papers - How DeepMind Conquered Go With Deep Learning (AlphaGo))

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    Vincent Liu 發佈於 2021 年 01 月 14 日