TED2009
Ray Kurzweil: A university for the coming singularity
雷·库兹韦尔：奇点大学
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雷·库兹韦尔的最新图表展示了科技发展只会向前进，完全与经济的衰退或繁荣无关。他同时揭开了“奇点大学”的神秘面纱。“奇点大学”是为研究接踵而来的科技和使之造福人类而建的。
Ray Kurzweil - Inventor, futurist
Ray Kurzweil is an engineer who has radically advanced the fields of speech, text and audio technology. He's revered for his dizzying -- yet convincing -- writing on the advance of technology, the limits of biology and the future of the human species. Full bio
Ray Kurzweil is an engineer who has radically advanced the fields of speech, text and audio technology. He's revered for his dizzying -- yet convincing -- writing on the advance of technology, the limits of biology and the future of the human species. Full bio
Double-click the English transcript below to play the video.
00:13
Information technology grows in an exponential manner.
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信息技术正以指数幅度发展。
00:16
It's not linear. And our intuition is linear.
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它并不是线性的。而对我们来说，直觉却是线性的。
00:20
When we walked through the savanna a thousand years ago
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千年前，当我们的祖先经过热带草原时，
00:22
we made linear predictions where that animal would be,
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他们常常会线性预测(根据直觉找寻)野兽的踪迹。
00:24
and that worked fine. It's hardwired in our brains.
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这的确行得通。因为这些是我们与生俱来的本能。
00:27
But the pace of exponential growth
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然而信息技术当下的发展速度
00:30
is really what describes information technologies.
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只能用指数发展来形容。
00:33
And it's not just computation.
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这两者的差异不仅仅局限于数值。
00:36
There is a big difference between linear and exponential growth.
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它们是天差地别的。
00:38
If I take 30 steps linearly -- one, two, three, four, five --
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假如我直走30步，一、二、三、四、五，
00:42
I get to 30.
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我会一直走到30。
00:44
If I take 30 steps exponentially -- two, four, eight, 16 --
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可是假如我以指数方式走三十步，二、四、八、16，
00:47
I get to a billion.
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我会到达十亿多。
00:49
It makes a huge difference.
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这之间差了十万八千里啊。
00:51
And that really describes information technology.
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偏偏指数增长正确描述了当今的信息技术发展。
00:53
When I was a student at MIT,
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当我尚是一位麻省理工的学生时，
00:55
we all shared one computer that took up a whole building.
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我们班共用一台占据了整栋房子的电脑。
00:57
The computer in your cellphone today is a million times cheaper,
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不过现在的手机芯片比那台电脑便宜一百万倍
01:00
a million times smaller,
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体型也小了一百万倍，
01:02
a thousand times more powerful.
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但功能却强大了千倍。
01:04
That's a billion-fold increase in capability per dollar
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这就相当于一美元有亿倍的增长能力
01:07
that we've actually experienced since I was a student.
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从我尚是一名学生到现在，这就是我所经历的。
01:09
And we're going to do it again in the next 25 years.
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这样的快速发展还会保持25年。
01:12
Information technology progresses
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信息技术通过一系列
01:14
through a series of S-curves
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S-曲线的考验后
01:16
where each one is a different paradigm.
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将可以到达不同的模式。
01:18
So people say, "What's going to happen when Moore's Law comes to an end?"
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因此有人问：”当摩尔定律效尽时，这世界将会如何？“
01:21
Which will happen around 2020.
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我相信这大概会在2020年发生。
01:23
We'll then go to the next paradigm.
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我们将会进入一新纪元。
01:25
And Moore's Law was not the first paradigm
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摩尔定律并不是第一个
01:27
to bring exponential growth to computing.
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导致信息技术进行指数增长的范式。
01:29
The exponential growth of computing started
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信息技术的指数增长发生于
01:31
decades before Gordon Moore was even born.
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戈登·摩尔出生的十几年前。
01:33
And it doesn't just apply to computation.
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它不仅仅局限于信息技术。
01:37
It's really any technology where we can measure
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而且包含了我们
01:39
the underlying information properties.
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所知的所有科技中。
01:42
Here we have 49 famous computers. I put them in a logarithmic graph.
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我将49台不同年代的电脑整理进一幅对数图。
01:46
The logarithmic scale hides the scale of the increase,
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对数的大小遮掩住真正增长的比率。
01:50
because this represents trillions-fold increase
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因为这些代表着自1890年以来，
01:52
since the 1890 census.
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科技的万亿倍增长。
01:55
In 1950s they were shrinking vacuum tubes,
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在50年代，工程师们都为尽可能地
01:57
making them smaller and smaller. They finally hit a wall;
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缩小真空管而努力。但最终碰了壁。
02:00
they couldn't shrink the vacuum tube any more and keep the vacuum.
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他们无法继续缩小真空管并同时保持着真空的状态。
02:02
And that was the end of the shrinking of vacuum tubes,
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这就是真空管缩小事件的结果。
02:05
but it was not the end of the exponential growth of computing.
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却不是信息技术的指数增长的停滞。
02:08
We went to the fourth paradigm, transistors,
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于是我们进入到第四种模式，晶体管，
02:10
and finally integrated circuits.
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然后来到集成电路。
02:12
When that comes to an end we'll go to the sixth paradigm;
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当上述过程结束后，我们将会迈进第六种模式，
02:14
three-dimensional self-organizing molecular circuits.
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三维自组分子电路。
02:18
But what's even more amazing, really, than this
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但更惊人的是，
02:21
fantastic scale of progress,
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比这神奇的过程更惊人的是，
02:23
is that -- look at how predictable this is.
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预测科技发展的简单性。
02:25
I mean this went through thick and thin,
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科技发展是经历了所有时期，
02:27
through war and peace, through boom times and recessions.
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如战争期与和平期、繁荣期与衰退期。
02:30
The Great Depression made not a dent in this exponential progression.
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大萧条根本没有影响科技发展的指数增长。
02:34
We'll see the same thing in the economic recession we're having now.
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我相信我们会在这次金融危机中见到同样的东西。
02:38
At least the exponential growth of information technology capability
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至少信息技术的指数增长能力
02:41
will continue unabated.
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将不会减弱。
02:44
And I just updated these graphs.
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这些图是我刚刚更新过的。
02:46
Because I had them through 2002 in my book, "The Singularity is Near."
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于我所著的书《奇点将至》中，这些数据只更新到2002年。
02:49
So we updated them,
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所以我将它们
02:51
so I could present it here, to 2007.
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更新至2007年。
02:54
And I was asked, "Well aren't you nervous?
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很多问我：”你不紧张么？
02:56
Maybe it kind of didn't stay on this exponential progression."
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或许它们并不能证明指数增长的说法。”
03:00
I was a little nervous
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我的确有点紧张，
03:02
because maybe the data wouldn't be right,
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因为这些数据有可能是错误的，
03:04
but I've done this now for 30 years,
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但我在这行里干了30多年，
03:06
and it has stayed on this exponential progression.
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而且这行的发展趋势的确遵照指数增长的规律。
03:09
Look at this graph here.You could buy one transistor for a dollar in 1968.
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看，在1968年，一件晶体管需要一美元。
03:12
You can buy half a billion today,
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现在，你则可以买五亿件。
03:14
and they are actually better, because they are faster.
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实际上，现在的晶体管质量更好。
03:16
But look at how predictable this is.
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看看科技发展是多么好预测的。
03:18
And I'd say this knowledge is over-fitting to past data.
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只是我会说这些资讯是过去式的了。
03:21
I've been making these forward-looking predictions for about 30 years.
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我已经做过30年的前瞻性预测了。
03:25
And the cost of a transistor cycle,
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晶体管的费用
03:27
which is a measure of the price performance of electronics,
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相应地呈现了电子市场的价格水准，
03:29
comes down about every year.
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这每年都在下降。
03:31
That's a 50 percent deflation rate.
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那说明了百分之50的下降率。
03:33
And it's also true of other examples,
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这也适用于其他例子
03:35
like DNA data or brain data.
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如DNA数据或大脑数据。
03:37
But we more than make up for that.
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不过社会发展的更快。
03:39
We actually ship more than twice as much
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事实上，我们的生产力比
03:41
of every form of information technology.
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同等的科技要高两倍。
03:43
We've had 18 percent growth in constant dollars
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这半个世纪里，每样科技的价值
03:46
in every form of information technology for the last half-century,
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都增长了百分之18。
03:49
despite the fact that you can get twice as much of it each year.
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尽管你每年可以收获两次回报，
03:53
This is a completely different example.
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这是一全新的例子。
03:55
This is not Moore's Law.
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这并不是摩尔定律。
03:57
The amount of DNA data
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我们每年都可以获得
03:59
we've sequenced has doubled every year.
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增加了一倍以上的DNA数据。
04:01
The cost has come down by half every year.
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费用却每年减少一半。
04:04
And this has been a smooth progression
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自从人类基因定序计划以来，
04:06
since the beginning of the genome project.
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这已成为一持续的发展定律。
04:08
And halfway through the project, skeptics said,
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当计划进行至一半时，
04:10
"Well, this is not working out. You're halfway through the genome project
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怀疑者们说：“这不会成功的。计划时间已过了一半，
04:13
and you've finished one percent of the project."
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而你们只完成了百分之一的工作。”
04:15
But that was really right on schedule.
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但按照时间表来说，这是可行的。
04:17
Because if you double one percent seven more times,
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假如你将百分之一用而乘七次，
04:19
which is exactly what happened,
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这就是实际上会发生的，
04:21
you get 100 percent. And the project was finished on time.
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那就是百分之百。计划也按时完成了。
04:24
Communication technologies:
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通信技术有
04:26
50 different ways to measure this,
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50种不同的方式来评量。
04:28
the number of bits being moved around, the size of the Internet.
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如移动的位元数目和网络的大小。
04:31
But this has progressed at an exponential pace.
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但科技正以指数步伐前进。
04:33
This is deeply democratizing.
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这是强烈地民主化。
04:35
I wrote, over 20 years ago in "The Age of Intelligent Machines,"
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20年前，我在《智能简史》中写到，
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when the Soviet Union was going strong, that it would be swept away
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随着苏联的扩张，它将会被增长的
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by this growth of decentralized communication.
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通信势力所瓦解。
04:45
And we will have plenty of computation as we go through the 21st century
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当我们走过21世纪时，我们将会拥有新技术
04:48
to do things like simulate regions of the human brain.
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来协助我们进行模拟大脑区域等实验。
04:52
But where will we get the software?
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但我们从哪里得到这些技术？
04:54
Some critics say, "Oh, well software is stuck in the mud."
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一些评论家说：“哦，科技还没到那种地步呢。”
04:57
But we are learning more and more about the human brain.
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岂知我们正逐步了解大脑。
04:59
Spatial resolution of brain scanning is doubling every year.
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大脑扫描的空间分辨率，每年都有一倍地提高。
05:02
The amount of data we're getting about the brain is doubling every year.
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相关的数据，也随之一倍增长。
05:05
And we're showing that we can actually turn this data
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我们正在证明我们可以转化这些数据
05:08
into working models and simulations of brain regions.
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为大脑区域的模型和模拟实验。
05:11
There is about 20 regions of the brain that have been modeled,
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我们目前已模拟和测试了
05:13
simulated and tested:
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20个大脑区域：
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the auditory cortex, regions of the visual cortex;
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听觉和视觉皮层，
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cerebellum, where we do our skill formation;
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小脑，我们身体的协调器，
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slices of the cerebral cortex, where we do our rational thinking.
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部分大脑皮层，我们进行理性思考的部分。
05:24
And all of this has fueled
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这些发现都非常平稳
05:26
an increase, very smooth and predictable, of productivity.
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和在预料之中帮助和增长了生产力。
05:29
We've gone from 30 dollars to 130 dollars
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我们的小时工资已从
05:31
in constant dollars in the value of an average hour of human labor,
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30美元增长至130美元了，
05:35
fueled by this information technology.
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这就是因信息技术的进步。
05:38
And we're all concerned about energy and the environment.
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这还只是对能源和环境的影响。
05:41
Well this is a logarithmic graph.
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这里又是一幅对数图。
05:43
This represents a smooth doubling,
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我们所利用的太阳能
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every two years, of the amount of solar energy we're creating,
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每两年都增长一倍。
05:49
particularly as we're now applying nanotechnology,
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正是由于现时的纳米技术，
05:51
a form of information technology, to solar panels.
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这是一种信息技术。
05:54
And we're only eight doublings away
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我们只要再经历八次双倍增长，
05:56
from it meeting 100 percent of our energy needs.
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我们就可以百分之百地利用太阳能。
05:58
And there is 10 thousand times more sunlight than we need.
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而这些能力将会是万倍多于我们所需的。
06:02
We ultimately will merge with this technology. It's already very close to us.
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我们会最终接受这项技术。它的脚步已近了。
06:07
When I was a student it was across campus, now it's in our pockets.
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当我尚是一名学生时，电脑有整个校园那么大，而现在却可以装进口袋里。
06:10
What used to take up a building now fits in our pockets.
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以前需求整栋大楼的资源却被现时的口袋替代了。
06:13
What now fits in our pockets would fit in a blood cell in 25 years.
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哪知25年后，这些将可以装进我们的红血球里。
06:16
And we will begin to actually deeply influence
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当我们迈向这项技术时，
06:20
our health and our intelligence,
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它将会真正左右
06:22
as we get closer and closer to this technology.
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我们的健康和智慧。
06:26
Based on that we are announcing, here at TED,
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根据TED的传统，
06:29
in true TED tradition, Singularity University.
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我将在此公布，奇点大学。
06:32
It's a new university
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这是一所全新的大学，
06:34
that's founded by Peter Diamandis, who is here in the audience,
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由我和台下的彼得·迪曼蒂斯先生
06:36
and myself.
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共同创立。
06:38
It's backed by NASA and Google,
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它还获得美国太空总署和谷歌的赞助，
06:40
and other leaders in the high-tech and science community.
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以及其他高科领域的领袖们的支持。
06:44
And our goal was to assemble the leaders,
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我们的目标是召集领袖们，
06:47
both teachers and students,
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不管是学生还是老师，
06:49
in these exponentially growing information technologies,
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来共同研究正在指数增长的信息技术和
06:51
and their application.
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它的应用。
06:53
But Larry Page made an impassioned speech
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拉里·佩奇先生在我们的内部会议上
06:55
at our organizing meeting,
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发表了以慷慨激昂的演讲，
06:57
saying we should devote this study
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他说我们应致力研究
07:02
to actually addressing some of the major challenges facing humanity.
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如何真正解决人类面临的一些重大挑战。
07:06
And if we did that, then Google would back this.
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假使我们这样做，谷歌定会资助我们。
07:08
And so that's what we've done.
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这就是我们所做的改变。
07:10
The last third of the nine-week intensive summer session
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在紧张的九周暑假学营的最后三周里，
07:14
will be devoted to a group project to address
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我们将会投身于研究
07:16
some major challenge of humanity.
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一些现实社会里的重大问题。
07:18
Like for example, applying the Internet,
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如将网络普及至
07:20
which is now ubiquitous, in the rural areas of China or in Africa,
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中国和非洲的乡村地区，
07:25
to bringing health information
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从而将健康资讯
07:27
to developing areas of the world.
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传播至世界的每个角落。
07:30
And these projects will continue past these sessions,
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这项计划将会延伸至学营外，
07:33
using collaborative interactive communication.
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通过协作来讨论。
07:36
All the intellectual property that is created and taught
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而这些讨论所催生的智慧财产
07:40
will be online and available,
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将会在网络上公开
07:42
and developed online in a collaborative fashion.
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并在网络上进一步深入。
07:45
Here is our founding meeting.
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这是创校会议的照片。
07:47
But this is being announced today.
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我今天将在这宣布。
07:49
It will be permanently headquartered in Silicon Valley,
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奇点大学会永久设置于硅谷里的
07:52
at the NASA Ames research center.
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美国太空总署的埃米斯研究所。
07:54
There are different programs for graduate students,
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研究生和公司的主管们将会
07:56
for executives at different companies.
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被提供不同的课程。
07:59
The first six tracks here -- artificial intelligence,
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主要的方面将会是，人工智能，
08:01
advanced computing technologies, biotechnology, nanotechnology --
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先进的电脑技术，生物技术，纳米技术，
08:04
are the different core areas of information technology.
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这些都是信息技术里不同的核心领域。
08:08
Then we are going to apply them to the other areas,
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然后我们将会将他们应用至其它领域，
08:10
like energy, ecology,
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如能源，生态环境，
08:13
policy law and ethics, entrepreneurship,
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政策法律，道德和企业等，
08:15
so that people can bring these new technologies to the world.
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因此学员们可以将这些新技术带给全世界。
08:19
So we're very appreciative of the support we've gotten
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我们非常感谢那些帮过我们的人，
08:24
from both the intellectual leaders, the high-tech leaders,
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不管是学者领袖，还是高科领域的领袖，
08:26
particularly Google and NASA.
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特别感谢谷歌和美国太空总署。
08:28
This is an exciting new venture.
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这是一次崭新的刺激冒险。
08:30
And we invite you to participate. Thank you very much.
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我们邀请你们来参加。非常感谢。
08:33
(Applause)
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(鼓掌)
ABOUT THE SPEAKER
Ray Kurzweil - Inventor, futuristRay Kurzweil is an engineer who has radically advanced the fields of speech, text and audio technology. He's revered for his dizzying -- yet convincing -- writing on the advance of technology, the limits of biology and the future of the human species.
Why you should listen
Inventor, entrepreneur, visionary, Ray Kurzweil's accomplishments read as a startling series of firsts -- a litany of technological breakthroughs we've come to take for granted. Kurzweil invented the first optical character recognition (OCR) software for transforming the written word into data, the first print-to-speech software for the blind, the first text-to-speech synthesizer, and the first music synthesizer capable of recreating the grand piano and other orchestral instruments, and the first commercially marketed large-vocabulary speech recognition.
Yet his impact as a futurist and philosopher is no less significant. In his best-selling books, which include How to Create a Mind, The Age of Spiritual Machines, The Singularity Is Near: When Humans Transcend Biology, Kurzweil depicts in detail a portrait of the human condition over the next few decades, as accelerating technologies forever blur the line between human and machine.
In 2009, he unveiled Singularity University, an institution that aims to "assemble, educate and inspire leaders who strive to understand and facilitate the development of exponentially advancing technologies." He is a Director of Engineering at Google, where he heads up a team developing machine intelligence and natural language comprehension.
Ray Kurzweil | Speaker | TED.com