Ray Kurzweil 談迫近之奇點大學

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講者：Ray Kurzweil
2009年2月演講，2009年6月在TED上線
MyOOPS開放式課程
翻譯：洪曉慧
編輯：劉契良
簡繁轉換：陳盈
後製：洪曉慧
字幕影片後制：謝旻均
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Ray Kurzweil 談迫近之奇點大學
資訊科技以指數形式增長。它不是線性的，而我們的直覺是線性的。當我們一千多年前穿過草原，我們以線性預測動物的去向。這效果很好，這是深植於我們大腦中的本能。但指數增長確實能描述資訊科技。這不只是計算，線性和指數增長有很大的不同。如果我以線性走30步，一、二、三、四、五，我得到了30。如果我以指數走30步，二、四、八、十六，我則得到了10億。它造成的差異很大，
這正可以描述所謂的資訊科技。
當我還是個MIT的學生時，我們所有人共用一台佔用了整幢大樓的電腦。現今您手機中的電腦已便宜了100萬倍，小了100萬倍，功能更是強了一千倍。這是每美元10億倍能力的增長。這是我從還是一名學生起親身經歷的事。而在未來25年，我們將再次經歷這一切。資訊科技的進步是一系列的S－曲線，每個都是不同的模式。所以人們說，「當摩爾定律到終點時會發生什麼事？」這將發生在2020年左右，然後我們會進入下一個模式。摩爾定律並不是第一個使用指數增長計算的模式。指數增長計算甚至在戈登‧摩爾出生前數十年就存在了。它不僅適用於計算，它是真正的技術，我們可用以測量潛在資訊的性質。
這裡有49台著名的電腦，我把它們放進對數圖中。這個對數表隱藏了增長的刻度，因為這表示自1890年統計開始，幾兆倍的增長。1950年代他們縮小真空管，將它們越做越小，最後他們碰了壁。他們再也無法縮小真空管，並使它保持真空。這就是真空管縮小的告終，但並不是指數增長計算的結束。我們進入了第四種模式，即晶體管，最後是積體電路。當這進行到終點時，我們將進入第六種模式，即三維自組織分子電路。
但真正驚人的，比增長規模更了不起的是，這一切能這麼輕易地被事先預測。我的意思是，這一切，經歷過任何困難，戰爭與和平，經歷過繁榮時期和經濟衰退，大蕭條並沒有對指數增長造成衝擊。在現在所遇到的經濟衰退時期，我們將看到同樣的情形。至少，資訊科技能力的指數增長將有增無減。
我剛剛更新這些圖表。因為我在本人著作《奇點迫近》中，放入了至2002年的圖表資料。因此，我們做了更新，以在此呈現給你們至2007年的資料。有人問我：「你會擔心嗎？也許實際情況並不符合這個指數增長曲線。」我是有點擔心，因為也許這些數據將不是正確的。但我至今已這樣進行了30年，並一直保持這個指數增長。
看看這個圖，在1968年，你可以用一美元買到一個晶體管，在今日你則可以買到 5億個。事實上它們還比較好，因為速度比較快。研究一下這該如何預測。我認為這方面的知識過適於過去的數據。我做這些前瞻性預測大約30年了，晶體管週期的成本，可用以衡量電子產品的價格性能。大約每年都會下降，其平減指數達百分之五十。在其他例子中也是如此，如DNA或大腦數據。但我們不只能夠彌補這一點，事實上，我們上市了超過兩倍的各種資訊科技形式。在過去半世紀期間，在每種資訊科技形式中，有百分之十八穩定市值的增長。儘管你每年可以得到兩倍的增長幅度。
這是一個完全不同的例子。這不是摩爾定律。我們所定序的DNA資料量每年都增加一倍，成本降低了一半，這已得到順利進展，從基因組計劃一開始即是如此。該計畫進行到中途時，懷疑論者說，「這是不可能成功的，基因組計劃進行了一半，而你們只完成百分之一的項目。」但這事實上已如期進行。因為如果你將百分之一平方 7次以上，這正是所發生的結果。你得到了百分之百，而該計畫已如期完成。
通信技術可用50種不同的方法來衡量。位元數不斷改變，網際網路的規模也是。但這是以指數的步伐進展，這是深刻的民主化。超過20年前我在《智能機器時代》一書中所寫，當時蘇聯勢頭強勁，卻因這個潮流所淘汰，就是分散式通訊的成長。
在 21世紀期間，我們將做大量的運算，進行諸如人類大腦區域的模擬。但我們將在何處得到軟體？一些批評者說，「哦，軟體陷入了泥淖。」但我們正學習更多關於人類大腦的事。腦的空間解析度掃描每年增進一倍。我們所獲得關於大腦的資料量每年增加一倍。我們已證明，確實可將資料轉換成大腦區域的運作模型和模擬。
大約有20個大腦區域已經建模，進行模擬和測試。如聽覺皮層，視覺皮層區域；還有小腦，在此處我們從事技能學習；以及大腦皮質層，在那兒我們運作理性思考。所有這一切都不斷得到加碼。生產力增進，且非常平穩和在預料之中。在平均每小時人力勞動價值方面，我們已經從30美元穩定成長到130美元，且是因這個資訊科技而激發。
我們都非常關心能源和環境，這是一個對數圖，顯示出每兩年平穩的倍增，以我們正創造出的太陽能總量計算。特別是我們現在將奈米技術這種資訊科技形式，應用於太陽能電池板上。我們只差8個倍增，就能達到百分之百的能源需求，而我們擁有比需要多一萬倍的陽光。
我們最終將與這項技術融合，它已與我們息息相關。當我還是一名學生時，它佔用整個校園，現在則能適於我們口袋大小。之前佔用整棟建築的東西，現在卻可以裝進我們的口袋。現在適用於我們口袋的東西，25年後將可以適用於血液細胞。我們將開始真正深刻地影響健康和智慧，因為我們越來越接近達成這種技術。
藉此，我們在TED上宣布，以真正的TED傳統，成立奇點大學。這是一所新的大學，由Peter Diamandis所創立，他正在聽眾席中，還有我本人。這是由NASA和Google，以及其他高科技和科學界領袖所支持。我們的目標是匯集這些領導人，包含教師和學生，從事這急劇增長的資訊科技及其應用。不過，Larry Page在我們的組織會議上發表了慷慨激昂的演講，認為我們應致力於這項研究，以真正解決一些人道面臨的重大挑戰。如果我們這樣做，Google將會支持。因此，這就是我們所做的。
在九個星期密集夏季會議的最後第三個星期，將致力於一個團體項目，以解決一些人道的重大挑戰。例如，運用網際網路，現在是普遍存在的，在中國或非洲的農村地區，將健康資訊傳播到世界的開發中區域。這些專案在會議期間將持續進行，使用交互式合作溝通。所有創建及傳授的智慧產權，將會上線共享，並以合作方式做線上開發。
這是我們的成立大會，但在今天宣布，將永久總部設在矽谷的NASA艾密斯研究中心中。有一些不同的課程，為研究生及不同公司管理人員所準備的。首批六項領域為人工智慧、先進的運算技術、生物技術、奈米技術，是不同的資訊科技核心領域。然後，我們將它們應用到其他領域，如能源、生態、政策、法律、道德和創業精神，使人們可將這些新技術貢獻給世界。
因此，我們非常感謝這些支持，來自兩間睿智的高科技巨人公司，尤其是Google 和 NASA。這是一個令人振奮的新企業，我們邀請您共襄盛舉，非常感謝。
（掌聲）
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以下為系統擷取之英文原文
About this talk
Ray Kurzweil's latest graphs show that technology's breakneck advances will only accelerate -- recession or not. He unveils his new project, Singularity University, to study oncoming tech and guide it to benefit humanity.
About Ray Kurzweil
Ray Kurzweil is an engineer who has radically advanced the fields of speech, text, and audio technology. He's also one of our finest thinkers, revered for his dizzying -- yet convincing --… Full bio and more links

Transcript

Information technology grows in an exponential manner. It's not linear. And our intuition is linear. When we walked through the savanna a thousand years ago we made linear predictions where that animal would be. And that worked fine. It's hardwired in our brains. But the pace of exponential growth is really what describes information technologies. And it's not just computation. There is a big difference between linear and exponential growth. If I take 30 steps linearly, one, two, three, four, five, I get to 30. If I take 30 steps exponentially, two, four, eight, 16, I get to a billion. It makes a huge difference. And that really describes information technology.

When I was a student at MIT we all shared one computer that took up a whole building. The computer in your cellphone today is a million times cheaper, a million times smaller, a thousand times more powerful. That's a billion-fold increase in capability per dollar that we've actually experienced since I was a student. And we're going to do it again in the next 25 years. Information technology progresses through a series of S-curves where each one is a different paradigm. So people say, "What's going to happen when Moore's Law comes to an end?" Which will happen around 2020. We'll then go to the next paradigm. And Moore's Law was not the first paradigm to bring exponential growth to computing. The exponential growth of computing started decades before Gordon Moore was even born. And it doesn't just apply to computation. It's really any technology where we can measure the underlying information properties.

Here we have 49 famous computers. I put them in a logarithmic graph. The logarithmic scale hides the scale of the increase. Because this represents trillions-fold increase since the 1890 census. In 1950s they were shrinking vacuum tubes, making them smaller and smaller. They finally hit a wall. They couldn't shrink the vacuum tube any more and keep the vacuum. And that was the end of the shrinking of vacuum tubes. But it was not the end of the exponential growth of computing. We went to the fourth paradigm, transistors. And finally integrated circuits. When that comes to an end we'll go to the sixth paradigm, three-dimensional self-organizing molecular circuits.

But what's even more amazing, really, than this fantastic scale of progress, is that look at how predictable this is. I mean this went through thick and thin, through war and peace, through boom times and recessions. The Great Depression made not a dent in this exponential progression. We'll see the same thing in the economic recession we're having now. At least the exponential growth of information technology capability will continue unabated.

And I just updated these graphs. Because I had them through 2002 in my book, The Singularity is Near. So we updated them so I could present it here, to 2007. And I was asked, "Well aren't you nervous? Maybe it kind of didn't stay on this exponential progression." I was a little nervous. Because maybe the data wouldn't be right. But I've done this now for 30 years. And it has stayed on this exponential progression.

Look at this graph here.You could buy one transistor for a dollar in 1968. You can buy half a billion today. And they are actually better, because they are faster. But look at how predictable this is. And I'd say this knowledge is over-fitting to past data. I've been making these forward-looking predictions for about 30 years. And the cost of a transistor cycle, which a measure of the price performance of electronics, comes down about every year. That's a 50 percent deflation rate. And it's also true of other examples like DNA data or brain data. But we more than make up for that. We actually ship more than twice as much of every form of information technology. We've had 18 percent growth in constant dollars in every form of information technology for the last half century. Despite the fact that you can get twice as much of it each year.

This is a completely different example. This is not Moore's Law. The amount of DNA data we've sequenced has doubled every year. The cost has come down by half every year. And this has been a smooth progression since the beginning of the genome project. And halfway through the project, skeptics said, "This is not working out. You're halfway through the genome project and you've finished one percent of the project." But that was really right on schedule. Because if you double one percent seven more times, which is exactly what happened, you get 100 percent. And the project was finished on time.

Communication technologies: 50 different ways to measure this. The number of bits being moved around, the size of the Internet. But this has progressed at an exponential pace. This is deeply democratizing. I wrote, over 20 years ago in The Age of Intelligent Machines, when the Soviet Union was going strong, that it would be swept away by this growth of decentralized communication.

And we will have plenty of computation as we go through the 21st century to do things like simulate regions of the human brain. But where will we get the software? Some critics say, "Oh, well software is stuck in the mud." But we are learning more and more about the human brain. Spatial resolution of brain scanning is doubling every year. The amount of data we're getting about the brain is doubling every year. And we're showing that we can actually turn this data into working models and simulations of brain regions.

There is about 20 regions of the brain that have been modeled, simulated and tested: the auditory cortex, regions of the visual cortex, cerebellum, where we do our skill formation, slices of the cerebral cortex, where we do our rational thinking. And all of this has fueled and increase, very smooth and predictable, of productivity. We've gone from 30 dollars to 130 dollars in constant dollars in the value of an average hour of human labor, fueled by this information technology.

And we're all concerned about energy and the environment. Well this is a logarithmic graph. This represents a smooth doubling, every two years, of the amount of solar energy we're creating. Particularly as we're now applying nanotechnology, a form of information technology, to solar panels. And we're only eight doublings away from it meeting 100 percent of our energy needs. And there is 10 thousand times more sunlight than we need.

We ultimately will merge with this technology. It's already very close to us. When I was a student it was across campus. Now it fits in our pockets. What used to take up a building now fits in our pockets. What now fits in our pockets would fit in a blood cell in 25 years. And we will begin to actually deeply influence our health and our intelligence, as we get closer and closer to this technology.

Based on that we are announcing, here at TED, in true TED tradition, Singularity University. It's a new university that's founded by Peter Diamandis, who is here in the audience, and myself. It's backed by NASA and Google, and other leaders in the high-tech and science community. And our goal was to assemble the leaders, both teachers and students, in these exponentially growing information technologies, and their application. But Larry Page made an impassioned speech at our organizing meeting, saying we should devote this study to actually addressing some of the major challenges facing humanity. And if we did that, then Google would back this. And so that's what we've done.

The last third of the nine week intensive summer session will be devoted to a group project to address some major challenge of humanity. Like for example, applying the Internet, which is now ubiquitous, in the rural areas of China or in Africa, to bringing health information to developing areas of the world. And these projects will continue past these sessions, using collaborative interactive communication. All the intellectual property that is created and taught will be online and available, and developed online in a collaborative fashion.

Here is our founding meeting. But this is being announced today. It will be permanently headquartered in Silicon Valley, at the NASA Ames research center. There are different programs for graduate students, for executives at different companies. The first six tracks here, artificial intelligence, advanced computing technologies, biotechnology, nanotechnology are the different core areas of information technology. Then we are going to apply them to the other areas, like energy, ecology, policy law and ethics, entrepreneurship, so that people can bring these new technologies to the world.

So we're very appreciative of the support we've gotten from both the intellectual leaders, the high-tech leaders, particularly Google and NASA. This is an exciting new venture. And we invite you to participate. Thank you very much. (Applause)
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