This story begins in 1985, when at age 22, I became the World Chess Champion after beating Anatoly Karpov. Earlier that year, I played what is called simultaneous exhibition against 32 of the world's best chess-playing machines in Hamburg, Germany. I won all the games, and then it was not considered much of a surprise that I could beat 32 computers at the same time. To me, that was the golden age.
這個故事開始於 1985 年, 我在 22 歲時, 打敗了卡爾波夫, 成為世界棋王。 那年年初, 我參加了所謂的「車輪戰」, 對抗 32 個世界最強博弈機器, 地點在德國漢堡。 我大獲全勝。 在那時,我能同時戰勝 32 台電腦 並不讓人意外。 對我而言,那是我的黃金年代。
(Laughter)
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Machines were weak, and my hair was strong.
在那時,機器特別弱小, 與此相反,我的頭髮十分強韌。
(Laughter)
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Just 12 years later, I was fighting for my life against just one computer in a match called by the cover of "Newsweek" "The Brain's Last Stand." No pressure.
只不過經過了 12 年, 我卻得用盡吃奶的力氣 與單單一台電腦相博弈, 《新聞週刊》的封面將這場比賽稱為 「人腦的最後一搏」。 不要有壓力。
(Laughter)
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From mythology to science fiction, human versus machine has been often portrayed as a matter of life and death. John Henry, called the steel-driving man in the 19th century African American folk legend, was pitted in a race against a steam-powered hammer bashing a tunnel through mountain rock. John Henry's legend is a part of a long historical narrative pitting humanity versus technology. And this competitive rhetoric is standard now. We are in a race against the machines, in a fight or even in a war. Jobs are being killed off. People are being replaced as if they had vanished from the Earth. It's enough to think that the movies like "The Terminator" or "The Matrix" are nonfiction.
從神話到科幻小說, 人類對抗機器 總是被描述成殊死搏鬥。 約翰亨利, 被稱為「鋼鑽人」, 是十九世紀非裔美國人的民間傳奇。 在一場比賽中,他與氣鑽機競爭, 鑽破山石,鑿出隧道。 約翰亨利的傳奇 是歷史長流中的一部份, 代表著人性與技術的拼鬥。 而在今日,「人與機器之爭」 這種輪調已成常態。 我們正與機器展開角逐, 這是一場鬥爭,甚至一場戰爭。 工作正在不斷減少。 人們被機器取代,彷彿已淪為配角。 所有的一切足以讓人相信: 《魔鬼終結者》或《駭客任務》 並不是杞人憂天。
There are very few instances of an arena where the human body and mind can compete on equal terms with a computer or a robot. Actually, I wish there were a few more. Instead, it was my blessing and my curse to literally become the proverbial man in the man versus machine competition that everybody is still talking about. In the most famous human-machine competition since John Henry, I played two matches against the IBM supercomputer, Deep Blue. Nobody remembers that I won the first match --
極罕見到在一場比賽中 人類的血肉之軀和智慧 能夠與電腦或機器人平等競爭。 事實上我期待能有更多這樣的情況。 但是, 這是我的福氣也是詛咒, 我成為眾所周知的名人,沒誇大, 人們至今仍然會談論 這場人對抗機器的比賽。 在這場自約翰亨利以來 最出名的人類機器競賽中, 我參與了兩場比賽, 對抗 IBM 的超級電腦「深藍」。 沒有人記得我贏了第一場比賽。
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(Applause)
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In Philadelphia, before losing the rematch the following year in New York. But I guess that's fair. There is no day in history, special calendar entry for all the people who failed to climb Mt. Everest before Sir Edmund Hillary and Tenzing Norgay made it to the top. And in 1997, I was still the world champion when chess computers finally came of age. I was Mt. Everest, and Deep Blue reached the summit. I should say of course, not that Deep Blue did it, but its human creators -- Anantharaman, Campbell, Hoane, Hsu. Hats off to them. As always, machine's triumph was a human triumph, something we tend to forget when humans are surpassed by our own creations.
在費城贏得了首場比賽。 而隔年在紐約第二次比賽,我輸了。 但我想那是公平的。 史上未曾有一天記錄著 那些沒能成功登頂聖母峰的人們, 直到艾德蒙希拉蕊爵士和丹增諾蓋 攻頂成功青史留名。 進到 1997 年我仍是世界冠軍, 那時我的機器對手終於成熟了。 我是聖母峰, 而深藍攀上了山巔。 我應該說,當然,這不是深藍辦到的, 是它的人類創造者辦到的: 阿南蕯拉曼、坎柏、洪恩、許峰雄。 在此向他們致敬。 一如既往, 機器的勝利其實是人類的勝利, 當我們人類被自身的創造物所超越時 我們常常會忘了這一點。
Deep Blue was victorious, but was it intelligent? No, no it wasn't, at least not in the way Alan Turing and other founders of computer science had hoped. It turned out that chess could be crunched by brute force, once hardware got fast enough and algorithms got smart enough. Although by the definition of the output, grandmaster-level chess, Deep Blue was intelligent. But even at the incredible speed, 200 million positions per second, Deep Blue's method provided little of the dreamed-of insight into the mysteries of human intelligence.
深藍的確獲勝了, 但它是智慧的嗎? 不,它不是, 至少不是艾倫圖靈及 其他計算機科學之父 所希望的那樣。 結果是,西洋棋臣服於蠻力之下, 只要硬體性能夠強勁, 且演算法夠精妙,就可以做到。 不過從博弈中的表現來定義, 西洋棋特級大師等級, 深藍的確是智慧的。 但即使性能如此之強, 每秒計算兩億步棋, 深藍的方法 無法提供我們期待的洞見 來讓我們深索人類智能之謎。
Soon, machines will be taxi drivers and doctors and professors, but will they be "intelligent?" I would rather leave these definitions to the philosophers and to the dictionary. What really matters is how we humans feel about living and working with these machines.
不用多久, 機器將會擔任計程車駕駛、 醫生、教授, 但它們會有「智慧」嗎? 我更想把這些定義留給 哲學家和字典。 重要的是,我們人類對於 跟這些機器一同居住、 工作有什麼感受。
When I first met Deep Blue in 1996 in February, I had been the world champion for more than 10 years, and I had played 182 world championship games and hundreds of games against other top players in other competitions. I knew what to expect from my opponents and what to expect from myself. I was used to measure their moves and to gauge their emotional state by watching their body language and looking into their eyes.
當我在 1996 年 2 月 初次遇見深藍時, 我保有世界冠軍的頭銜已超過十年, 曾參與過 182 場世界冠軍賽, 以及數以百計 和其他頂尖玩家交手的賽事。 我可以預期我的對手, 我也可以預期我自己。 我習慣于酌量他們的每步棋, 判斷他們的情緒狀態, 方法是觀察他們的肢體語言 以及注視著他們的眼睛。
And then I sat across the chessboard from Deep Blue. I immediately sensed something new, something unsettling. You might experience a similar feeling the first time you ride in a driverless car or the first time your new computer manager issues an order at work. But when I sat at that first game, I couldn't be sure what is this thing capable of. Technology can advance in leaps, and IBM had invested heavily. I lost that game. And I couldn't help wondering, might it be invincible? Was my beloved game of chess over? These were human doubts, human fears, and the only thing I knew for sure was that my opponent Deep Blue had no such worries at all.
接著,我隔著棋盤, 與深藍相對而坐。 我立即有了新的感受, 使人不安的感受。 你可能也有過類似的感受, 比如當你初次坐上 無人駕駛車輛時的感受, 或是聽到你的新任電腦經理 初次下達工作指令時的感受。 但當我比賽第一局時 我無法確定 這東西有什麼能耐。 技術的進步有時會突飛猛進, 且 IBM 投資相當大。 我輸了那一局。 我忍不住會想, 它有可能是無敵的嗎? 我摯愛的西洋棋賽結束了嗎? 這些是人類的懷疑、人類的恐懼, 我只能確定一件事: 我的對手深藍完全沒有這些擔憂。
(Laughter)
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I fought back after this devastating blow to win the first match, but the writing was on the wall. I eventually lost to the machine but I didn't suffer the fate of John Henry who won but died with his hammer in his hand. [John Henry Died with a Hammer in His Hand Palmer C. Hayden] [The Museum of African American Art, Los Angeles] It turned out that the world of chess still wanted to have a human chess champion. And even today, when a free chess app on the latest mobile phone is stronger than Deep Blue, people are still playing chess, even more than ever before. Doomsayers predicted that nobody would touch the game that could be conquered by the machine, and they were wrong, proven wrong, but doomsaying has always been a popular pastime when it comes to technology.
在受到這令我身心交瘁的 一擊後,我還擊回去, 贏得了第一場比賽, 但凶兆已然顯現。 我最終敗給了機器, 但我沒有步上約翰亨利的後塵。 他在勝利中與世長辭, 手中還拿著錘子。 (繪畫《約翰亨利握着錘子離世》, Palmer C. Hayden) (洛杉磯,非裔美國人藝術博物館) 結果,西洋棋的世界 仍然想要有個人類棋王。 即使現今, 當免費的手機西洋棋 app , 比深藍還強, 人們仍然在下西洋棋, 甚至比以前更愛下棋。 災難預言者預測沒人會再碰西洋棋, 因為西洋棋已被機器給征服, 但證據證明他們錯了, 但災難預言一直是種熱門消遣, 特別是在與科技有關時。
What I learned from my own experience is that we must face our fears if we want to get the most out of our technology, and we must conquer those fears if we want to get the best out of our humanity. While licking my wounds, I got a lot of inspiration from my battles against Deep Blue. As the old Russian saying goes, if you can't beat them, join them. Then I thought, what if I could play with a computer -- together with a computer at my side, combining our strengths, human intuition plus machine's calculation, human strategy, machine tactics, human experience, machine's memory. Could it be the perfect game ever played?
我從我自己的經驗學到的是 我們必須要面對恐懼 以讓科技發揮得淋漓盡致; 我們必須要克服恐懼, 以讓人性充分發揮。 當我在舔傷口時, 我得到很多靈感, 來自我和深藍的對戰。 有句很老的俄國諺語, 如果你不能打敗他們,就加入他們。 接著,我想, 如果我能和一台電腦一起 …… 有一台電腦作為盟友, 將我們倆的強項結合, 人類直覺加上機器計算能力, 人類策略,機器戰術, 人類經驗,機器記憶。 那是否會是史上最完美的比賽?
My idea came to life in 1998 under the name of Advanced Chess when I played this human-plus-machine competition against another elite player. But in this first experiment, we both failed to combine human and machine skills effectively. Advanced Chess found its home on the internet, and in 2005, a so-called freestyle chess tournament produced a revelation. A team of grandmasters and top machines participated, but the winners were not grandmasters, not a supercomputer. The winners were a pair of amateur American chess players operating three ordinary PCs at the same time. Their skill of coaching their machines effectively counteracted the superior chess knowledge of their grandmaster opponents and much greater computational power of others. And I reached this formulation. A weak human player plus a machine plus a better process is superior to a very powerful machine alone, but more remarkably, is superior to a strong human player plus machine and an inferior process. This convinced me that we would need better interfaces to help us coach our machines towards more useful intelligence.
我的想法實現了。 在 1998 年 以「進階西洋棋」之名, 我參與了人類搭配機器的比賽 對抗另一位精英玩家。 但在這第一次實驗中, 我們都失敗了,沒能有效 結合人類與機器的技巧。 「進階西洋棋」在網路上找到它的家, 2005 年,所謂的 「自由式西洋棋巡迴賽」 帶來了一個啟示。 參與者包括大師級玩家以及頂尖機器, 但贏家不是大師, 也不是超級電腦。 贏家是一對業餘的美國西洋棋玩家, 他們同時操作三台普通個人電腦。 他們訓練機器所使用的技巧 有效地戰勝了大師級對手的 優秀西洋棋經驗 以及其他人更強大的計算能力。 我得到了這個組合公式: 一個能力不強的人類玩家加一台機器 再加上一個較優的操作流程, 勝過單單一台非常強大的機器, 更棒的是還勝過 一個厲害的人類玩家加上機器, 以及一個次等的操作流程。 這讓我意識到,我們需要 更好的界面來協助我們訓練機器, 導出更有用的智慧。
Human plus machine isn't the future, it's the present. Everybody that's used online translation to get the gist of a news article from a foreign newspaper, knowing its far from perfect. Then we use our human experience to make sense out of that, and then the machine learns from our corrections. This model is spreading and investing in medical diagnosis, security analysis. The machine crunches data, calculates probabilities, gets 80 percent of the way, 90 percent, making it easier for analysis and decision-making of the human party. But you are not going to send your kids to school in a self-driving car with 90 percent accuracy, even with 99 percent. So we need a leap forward to add a few more crucial decimal places.
人類加上機器不在未來 而是現在。 大家都用線上翻譯, 來了解外國報紙文章的要點, 即使知道這翻譯遠非完美。 接著,我們用我們的人類經驗 從翻譯中理出意義來, 接著機器從我們的修正中深入學習。 這個模型被廣泛應用在 醫療診斷和安全性分析方面。 機器計算大量的數據, 計算可能性, 完成了 80%、90% 的工作, 讓人類這一方更容易進行分析和決策。 但你送孩子上學時 不會使用只 90% 精確的自駕車, 甚至 99% 也不行。 所以我們需要更進一步, 再加上幾位重要的小數。
Twenty years after my match with Deep Blue, second match, this sensational "The Brain's Last Stand" headline has become commonplace as intelligent machines move in every sector, seemingly every day. But unlike in the past, when machines replaced farm animals, manual labor, now they are coming after people with college degrees and political influence. And as someone who fought machines and lost, I am here to tell you this is excellent, excellent news. Eventually, every profession will have to feel these pressures or else it will mean humanity has ceased to make progress. We don't get to choose when and where technological progress stops. We cannot slow down. In fact, we have to speed up. Our technology excels at removing difficulties and uncertainties from our lives, and so we must seek out ever more difficult, ever more uncertain challenges. Machines have calculations. We have understanding. Machines have instructions. We have purpose. Machines have objectivity. We have passion. We should not worry about what our machines can do today. Instead, we should worry about what they still cannot do today, because we will need the help of the new, intelligent machines to turn our grandest dreams into reality. And if we fail, if we fail, it's not because our machines are too intelligent, or not intelligent enough. If we fail, it's because we grew complacent and limited our ambitions. Our humanity is not defined by any skill, like swinging a hammer or even playing chess.
在我與深藍的第二場比賽 20 年之後, 這個聳動的「人腦的最後一搏」標題 變得很常見, 因為智慧機器 滲入了每個領域, 且幾乎每天都是如此。 但不像過去, 過去機器是取代 農場動物、手工勞力, 現在它們要與擁有大學文憑 和政治影響力的人們競爭。 身為一個曾和機器對戰 並敗下陣來的人, 我在此告訴大家,這是大好消息。 最終,每個行業 都會感受到這些壓力, 不然就意味著人性已經停止進步了。 我們沒得選 科技進展何時何地會停止。 我們不能放慢腳步。 事實上, 我們要加快腳步。 我們的科技擅長 排除人生中的困難和不確定性, 所以我們必須要找到 更困難、 更不確定的挑戰。 機器擅長計算。 我們強在思維。 機器有指令, 我們有目的。 機器有客觀性, 我們有熱情。 我們不用擔心 現今的機器能做到什麼, 而應該要擔心 現今它們仍做不到什麼。 因為我們將需要新的智慧機器 來協助我們實現偉大的夢想。 如果我們失敗, 如果我們失敗,那不會是 因為我們的機器太聰明, 或不夠聰明。 如果我們失敗, 那是因為我們變得自滿, 限制了我們的野心。 我們的人性並不是 由任何技能來定義的, 比如揮舞錘子或甚至下西洋棋。
There's one thing only a human can do. That's dream. So let us dream big.
有一件事,只有人類才能做到, 就是夢想。 所以,讓我們立下宏願。
Thank you.
謝謝大家。
(Applause)
(鼓掌)