TED2018
Kai-Fu Lee: How AI can save our humanity
李开复: 人工智能如何拯救我们的人性
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人工智能正在大规模地改变我们的世界，但有一件事是它无法做到的：爱。在一次富有远见的演讲中，计算机科学家李开复详细介绍了美国和中国如何推动深度学习革命，并分享了人类如何在人工智能时代利用同情心和创造力茁壮成长的蓝图。 “人工智能的发展是机缘巧合，”李说。 “它的到来将把我们从常规工作中解放出来， 它的到来也提醒我们人因何为人。”
Kai-Fu Lee - Investor, computer scientist
At Sinovation Ventures, Kai-Fu Lee invests in the next generation of Chinese high-tech companies. Full bio
At Sinovation Ventures, Kai-Fu Lee invests in the next generation of Chinese high-tech companies. Full bio
Double-click the English transcript below to play the video.
00:12
I'm going to talk about
how AI and mankind can coexist,
how AI and mankind can coexist,
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我将会谈谈人工智能和人类如何能够共存，
00:17
but first, we have to rethink
about our human values.
about our human values.
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但首先，我们需要重新思考人类价值观。
00:21
So let me first make a confession
about my errors in my values.
about my errors in my values.
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所以首先让我坦白我价值观中曾有的错误。
00:25
It was 11 o'clock, December 16, 1991.
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那是1991年12月16日11点。
我即将首次成为父亲。
00:30
I was about to become a father
for the first time.
for the first time.
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00:33
My wife, Shen-Ling,
lay in the hospital bed
lay in the hospital bed
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我的妻子，先铃，躺在病床上
00:36
going through a very difficult
12-hour labor.
12-hour labor.
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经历着一段艰辛并为时12小时的分娩。
00:40
I sat by her bedside
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我坐在床边
00:42
but looked anxiously at my watch,
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但却焦虑地望着我的手表，
00:45
and I knew something that she didn't.
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而我知道一些她不知道的事。
00:47
I knew that if in one hour,
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我知道如果在一小时内，
00:50
our child didn't come,
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我们的孩子还未出生，
00:52
I was going to leave her there
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我将要将她留在那里
00:54
and go back to work
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赶去上班
00:55
and make a presentation about AI
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并向我的老板，苹果的首席执行官
00:58
to my boss, Apple's CEO.
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做一个有关人工智能的报告。
01:03
Fortunately, my daughter
was born at 11:30 --
was born at 11:30 --
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幸运的是，我的女儿在11:30出生了--
01:07
(Laughter)
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（笑声）
01:09
(Applause)
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（掌声）
01:11
sparing me from doing the unthinkable,
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让我免做荒唐事，
01:15
and to this day, I am so sorry
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而一直到今天，我非常惭愧曾经
01:17
for letting my work ethic
take precedence over love for my family.
take precedence over love for my family.
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把工作摆在家庭前面。
01:22
(Applause)
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（掌声）
01:28
My AI talk, however, went off brilliantly.
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但是，我做的人工智能报告非常成功。
01:30
(Laughter)
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（笑声）
01:33
Apple loved my work
and decided to announce it
and decided to announce it
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苹果喜欢我的工作成果
并决定在TED1992会议上将其宣布，
01:36
at TED1992,
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01:39
26 years ago on this very stage.
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26年前就在这个舞台上。
01:42
I thought I had made one of the biggest,
most important discoveries in AI,
most important discoveries in AI,
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我以为我完成了人工智能领域
一个最重大的发现，
一个最重大的发现，
01:47
and so did the "Wall Street Journal"
on the following day.
on the following day.
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第二天《华尔街日报》也是这么认为。
01:51
But as far as discoveries went,
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但随着越来越多的发现，
结果是，
01:54
it turned out,
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我并没有发现印度或是美洲。
01:55
I didn't discover India, or America.
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或许我发现的是葡萄牙附近的一个小岛。
01:58
Perhaps I discovered
a little island off of Portugal.
a little island off of Portugal.
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02:02
But the AI era of discovery continued,
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但是人工智能的发现时代持续了下去，
02:06
and more scientists
poured their souls into it.
poured their souls into it.
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而越来越多的科学家全心全意投入其中。
02:09
About 10 years ago, the grand AI discovery
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大约10年前，三名北美科学家
02:11
was made by three
North American scientists,
North American scientists,
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做出了重大的人工智能发现，
02:15
and it's known as deep learning.
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那就是深度学习。
02:17
Deep learning is a technology
that can take a huge amount of data
that can take a huge amount of data
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深度学习是一个能利用海量数据
02:21
within one single domain
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在单一领域中
02:22
and learn to predict or decide
at superhuman accuracy.
at superhuman accuracy.
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学会做超高精确度的预测或决策的技术。
02:27
For example, if we show
the deep learning network
the deep learning network
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例如，如果我们向深度学习网络显示
02:30
a massive number of food photos,
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海量的食物照片，
02:33
it can recognize food
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它可以辨认出食物，
02:35
such as hot dog or no hot dog.
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比如热狗或不是热狗。
02:38
(Applause)
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(掌声)
02:41
Or if we show it many pictures
and videos and sensor data
and videos and sensor data
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若如果我们向它显示许多
02:46
from driving on the highway,
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在高速公路上开车的照片、
视频和传感数据，
视频和传感数据，
02:49
it can actually drive a car
as well as a human being
as well as a human being
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它其实可以把车开得像人一样好
02:53
on the highway.
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行驶在高速公路上。
02:55
And what if we showed
this deep learning network
this deep learning network
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若我们向这深度学习网络显示
02:57
all the speeches made by President Trump?
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特朗普总统发表过的所有演讲呢？
03:01
Then this artificially
intelligent President Trump,
intelligent President Trump,
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那么这个人工智能的特朗普总统，
03:05
actually the network --
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其实是该网络 --
03:07
(Laughter)
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（笑声）
03:09
can --
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可以 --
03:10
(Applause)
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（掌声）
03:14
You like double oxymorons, huh?
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你们喜欢一语双关的话，对吧？
03:17
(Laughter)
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（笑声）
03:21
(Applause)
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（掌声）
03:27
So this network, if given the request
to make a speech about AI,
to make a speech about AI,
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所以此网络，若被要求发表一场
关于人工智能的演讲，
关于人工智能的演讲，
03:32
he, or it, might say --
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他，或它，或许会说 --
03:36
(Recording) Donald Trump:
It's a great thing
It's a great thing
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（录音）特朗普：运用人工智能来建造
03:38
to build a better world
with artificial intelligence.
with artificial intelligence.
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一个更完美的世界是件大好事。
03:41
Kai-Fu Lee: And maybe in another language?
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李开复：或许用另一种语言来说？
特朗普（讲中文）：人工智能正在改变世界
03:43
DT: (Speaking Chinese)
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03:45
(Laughter)
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（笑声）
03:46
KFL: You didn't know
he knew Chinese, did you?
he knew Chinese, did you?
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你们不知道他会说中文吧？
03:50
So deep learning has become the core
in the era of AI discovery,
in the era of AI discovery,
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所以深度学习已成为人工智能发现时代的核心，
03:55
and that's led by the US.
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并由美国领导着。
03:57
But we're now in the era
of implementation,
of implementation,
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但我们现在身处实践时代，
04:00
where what really matters is execution,
product quality, speed and data.
product quality, speed and data.
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真正关键的是执行力、产品质量、速度和数据。
04:05
And that's where China comes in.
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这就是中国上场的时候了。
04:07
Chinese entrepreneurs,
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中国企业家，
04:09
who I fund as a venture capitalist,
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我作为风险投资人提供他们资本，
04:11
are incredible workers,
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他们是非凡的实干者，
04:13
amazing work ethic.
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工作拼命。
04:15
My example in the delivery room is nothing
compared to how hard people work in China.
compared to how hard people work in China.
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我在产房的例子与中国人的工作卖力程度
相比根本不算什么。
相比根本不算什么。
04:20
As an example, one startup
tried to claim work-life balance:
tried to claim work-life balance:
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例如，有个创业公司声称能工作生活平衡：
04:24
"Come work for us because we are 996."
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“加入我们吧，因为我们是996。”
04:27
And what does that mean?
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那是什么意思？
04:29
It means the work hours
of 9am to 9pm, six days a week.
of 9am to 9pm, six days a week.
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那是指工作时间从上午9点至晚上9点、
每周六天。
每周六天。
04:34
That's contrasted
with other startups that do 997.
with other startups that do 997.
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这与其他实施997的创业公司形成对比。
04:39
And the Chinese product quality
has consistently gone up
has consistently gone up
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中国产品的质量在
过去十年中持续提升，
04:42
in the past decade,
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04:44
and that's because of
a fiercely competitive environment.
a fiercely competitive environment.
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这归功于极其激烈的竞争环境。
04:48
In Silicon Valley, entrepreneurs
compete in a very gentlemanly fashion,
compete in a very gentlemanly fashion,
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在硅谷，企业家用非常绅士的方式来竞争，
有点像是旧时的战争
04:54
sort of like in old wars
in which each side took turns
in which each side took turns
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双方轮流向对方开火。
04:58
to fire at each other.
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（笑声）
04:59
(Laughter)
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05:00
But in the Chinese environment,
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但在中国的环境里，
05:03
it's truly a gladiatorial
fight to the death.
fight to the death.
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它真的是一场不死不休的角斗士之战。
05:06
In such a brutal environment,
entrepreneurs learn to grow very rapidly,
entrepreneurs learn to grow very rapidly,
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在如此残酷的环境里，
企业家学会如何迅速成长，
企业家学会如何迅速成长，
他们学会如何雷厉风行地改进产品，
05:13
they learn to make their products
better at lightning speed,
better at lightning speed,
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他们学会如何完善其商业模式
05:17
and they learn
to hone their business models
to hone their business models
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直至坚不可摧。
05:19
until they're impregnable.
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05:21
As a result, great Chinese products
like WeChat and Weibo
like WeChat and Weibo
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结果是，优秀的中国产品，如微信和微博
05:25
are arguably better
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可以说比脸书和推特等同类美国产品更好。
05:26
than the equivalent American products
from Facebook and Twitter.
from Facebook and Twitter.
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中国市场欢迎这种变化，
并进一步加速变化和转型。
并进一步加速变化和转型。
05:31
And the Chinese market
embraces this change
embraces this change
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05:35
and accelerated change
and paradigm shifts.
and paradigm shifts.
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比如说，如果你们中任何人去中国，
05:38
As an example, if any of you go to China,
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05:40
you will see it's almost cashless
and credit card-less,
and credit card-less,
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你将会看到它几乎是无现金和无信用卡社会，
05:44
because that thing that we all
talk about, mobile payment,
talk about, mobile payment,
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因为我们都在讨论的那件事，移动支付，
05:47
has become the reality in China.
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在中国已成为现实。
05:49
In the last year,
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在过去一年，
05:50
18.8 trillion US dollars
were transacted on mobile internet,
were transacted on mobile internet,
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18.8万亿美金通过移动网络完成交易，
而这归功于支撑其项背的强劲科技。
05:56
and that's because
of very robust technologies
of very robust technologies
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05:59
built behind it.
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06:00
It's even bigger than the China GDP.
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它甚至大过中国的国内生产总值。
06:04
And this technology, you can say,
how can it be bigger than the GDP?
how can it be bigger than the GDP?
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而此技术，你可以说，
它怎么会大过国内生产总值？
它怎么会大过国内生产总值？
06:07
Because it includes all transactions:
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这是因为它包括了所有交易：
06:09
wholesale, channels,
retail, online, offline,
retail, online, offline,
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批发、渠道、零售、网上、离线，
去大商场或去这样的农贸市场。
06:13
going into a shopping mall
or going into a farmers market like this.
or going into a farmers market like this.
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这项技术被7亿人用来互相支付，
06:18
The technology is used
by 700 million people
by 700 million people
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06:22
to pay each other, not just merchants,
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不仅局限于商家，
06:24
so it's peer to peer,
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所以它是点对点的，
06:25
and it's almost transaction-fee-free.
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而它几乎是无手续费的。
06:29
And it's instantaneous,
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它是即时的，
被到处使用。
06:32
and it's used everywhere.
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06:34
And finally, the China market is enormous.
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最后一点，中国市场十分巨大。
06:37
This market is large,
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市场庞大，
06:39
which helps give entrepreneurs
more users, more revenue,
more users, more revenue,
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帮助了企业家获得更多用户、
更高收入、更多投资，
更高收入、更多投资，
06:44
more investment, but most importantly,
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但最重要的，
06:46
it gives the entrepreneurs a chance
to collect a huge amount of data
to collect a huge amount of data
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它给了企业家一个收集海量数据的机会
这成为了人工智能引擎的燃料。
06:51
which becomes rocket fuel
for the AI engine.
for the AI engine.
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06:54
So as a result, the Chinese AI companies
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结果，中国人工智能公司已往前飞跃，
06:57
have leaped ahead
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06:59
so that today, the most valuable companies
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所以如今，在电脑视觉、语音识别、
07:02
in computer vision, speech recognition,
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语音合成、机器翻译和无人机领域中
07:05
speech synthesis,
machine translation and drones
machine translation and drones
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最具价值的公司都是中国公司。
07:08
are all Chinese companies.
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07:11
So with the US leading
the era of discovery
the era of discovery
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所以，随着美国引领发现时代
和中国引领实践时代，
07:14
and China leading
the era of implementation,
the era of implementation,
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我们正处于一个伟大时代
07:17
we are now in an amazing age
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两个超级大国的双联引擎正合作共进
07:20
where the dual engine
of the two superpowers
of the two superpowers
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07:23
are working together
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07:25
to drive the fastest
revolution in technology
revolution in technology
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驱动我们人类从未见过的
最迅速的科技革命。
07:29
that we have ever seen as humans.
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07:32
And this will bring tremendous wealth,
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这将会带来极大的财富、
07:35
unprecedented wealth:
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前所未有的财富：
07:36
16 trillion dollars, according to PwC,
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据普华永道估计，到2030年，
人工智能将带来16万亿美元的全球GDP增长
07:40
in terms of added GDP
to the worldwide GDP by 2030.
to the worldwide GDP by 2030.
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07:46
It will also bring immense challenges
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它也将带来巨大挑战
07:48
in terms of potential job replacements.
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在可能出现的失业再就业问题上。
07:52
Whereas in the Industrial Age
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在工业革命时代，
07:55
it created more jobs
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它创造了更多工作
因为手工工匠的工作被分解成
生产线上的各种工作，
生产线上的各种工作，
07:57
because craftsman jobs were being
decomposed into jobs in the assembly line,
decomposed into jobs in the assembly line,
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08:03
so more jobs were created.
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所以创造了更多工作。
08:05
But AI completely replaces
the individual jobs
the individual jobs
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但是人工智能让流水线上的个体工作
完全被机器人取代。
08:10
in the assembly line with robots.
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08:12
And it's not just in factories,
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这不仅发生在工厂里，
08:14
but truckers, drivers
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而且货车司机、驾驶员
08:16
and even jobs like telesales,
customer service
customer service
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甚至于像是电话销售、客服、
08:20
and hematologists as well as radiologists
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血液科和放射科医生的工作，
08:23
over the next 15 years
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在未来的15年内
08:25
are going to be gradually replaced
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都将慢慢被人工智能取代。
08:28
by artificial intelligence.
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08:30
And only the creative jobs --
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而只有创造性工作--
08:32
(Laughter)
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（笑声）
08:34
I have to make myself safe, right?
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我必须保护我自己，对吧？
08:38
Really, the creative jobs
are the ones that are protected,
are the ones that are protected,
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真的，创造性工作是有保障的工作，
08:41
because AI can optimize but not create.
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因为人工智能可以优化但不能创造。
08:45
But what's more serious
than the loss of jobs
than the loss of jobs
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但比失去工作更严重的是失去意义，
08:49
is the loss of meaning,
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08:51
because the work ethic
in the Industrial Age
in the Industrial Age
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因为工业革命时代的工作伦理
08:54
has brainwashed us into thinking
that work is the reason we exist,
that work is the reason we exist,
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已让我们洗脑相信工作赋予我们存在的理由，
09:00
that work defined
the meaning of our lives.
the meaning of our lives.
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工作赋予我们生活的意义。
而我就是个典型并自愿接受
那种工作狂思想的受害者。
那种工作狂思想的受害者。
09:03
And I was a prime and willing victim
to that type of workaholic thinking.
to that type of workaholic thinking.
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09:09
I worked incredibly hard.
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我工作异常努力。
09:11
That's why I almost left
my wife in the delivery room,
my wife in the delivery room,
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那就是为什么我几乎将我的妻子独自留在产房内，
09:14
that's why I worked 996
alongside my entrepreneurs.
alongside my entrepreneurs.
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那就是为什么我996地与企业家们工作。
09:18
And that obsession that I had with work
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我对工作的痴迷在几年前戛然而止
09:23
ended abruptly a few years ago
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因为我被确诊患上
09:26
when I was diagnosed
with fourth stage lymphoma.
with fourth stage lymphoma.
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第四期淋巴瘤。
09:31
The PET scan here shows
over 20 malignant tumors
over 20 malignant tumors
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这个PET扫描显示二十多个恶性肿瘤
09:35
jumping out like fireballs,
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如火球般喷涌而出，
09:37
melting away my ambition.
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把我的壮志雄心付之一炬。
09:40
But more importantly,
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但更重要的是，
09:41
it helped me reexamine my life.
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它帮我重新审视我的人生。
09:44
Knowing that I may only have
a few months to live
a few months to live
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知道我可能只剩下几个月的生命
09:47
caused me to see how foolish it was
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令我看清
09:50
for me to base my entire self-worth
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把自我价值完全建立在
09:54
on how hard I worked
and the accomplishments from hard work.
and the accomplishments from hard work.
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工作强度和工作成就上是多么愚蠢。
09:59
My priorities were
completely out of order.
completely out of order.
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我生活中的优先级完全本末倒置。
10:02
I neglected my family.
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我疏于关心家庭。
10:05
My father had passed away,
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我的父亲过世了，
10:06
and I never had a chance
to tell him I loved him.
to tell him I loved him.
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我从没机会告诉他我爱他。
10:10
My mother had dementia
and no longer recognized me,
and no longer recognized me,
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我的母亲失智了，再也认不出我，
我的孩子们都已长大成人。
10:13
and my children had grown up.
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10:16
During my chemotherapy,
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在我化疗期间，
10:18
I read a book by Bronnie Ware
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我读了邦妮·韦尔的一本书
10:20
who talked about dying wishes and regrets
of the people in the deathbed.
of the people in the deathbed.
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写的是人们濒死时的心愿和懊悔。
10:26
She found that facing death,
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她发现面对死亡时，
10:28
nobody regretted that they didn't
work hard enough in this life.
work hard enough in this life.
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没人遗憾自己工作得不够努力。
10:32
They only regretted that they didn't
spend enough time with their loved ones
spend enough time with their loved ones
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他们只后悔自己没花更多时间
与所爱之人相伴相守，
与所爱之人相伴相守，
10:38
and that they didn't spread their love.
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后悔没有传递自己的爱。
10:42
So I am fortunately today in remission.
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值得庆幸的是，我的病情现在有所缓解
10:46
(Applause)
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（掌声）
10:53
So I can be back at TED again
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所以我可以重回TED舞台
10:55
to share with you
that I have changed my ways.
that I have changed my ways.
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和你们分享我的改变。
10:59
I now only work 965 --
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我如今只工作965 --
11:03
occasionally 996, but usually 965.
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偶尔996，但通常965。
11:07
I moved closer to my mother,
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我搬到离母亲更近的住所，
11:09
my wife usually travels with me,
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我妻子通常与我相伴旅行，
11:11
and when my kids have vacation,
if they don't come home, I go to them.
if they don't come home, I go to them.
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当我的孩子们休假时，
若他们不回家，我会去看他们。
若他们不回家，我会去看他们。
11:15
So it's a new form of life
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这种新生活方式帮我认清
11:17
that helped me recognize
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爱对我来说是多么重要，
11:19
how important it is that love is for me,
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11:22
and facing death
helped me change my life,
helped me change my life,
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濒死经历改变了我的生活，
而且让我重新审视
11:26
but it also helped me see a new way
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11:28
of how AI should impact mankind
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人工智能应如何影响人类
11:32
and work and coexist with mankind,
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影响工作，与人共存，
11:36
that really, AI is taking away
a lot of routine jobs,
a lot of routine jobs,
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确实，人工智能正带走很多重复性工作，
但我们并非因为擅长重复性工作而为人。
11:41
but routine jobs are not what we're about.
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11:44
Why we exist is love.
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我们存在的理由是爱。
11:47
When we hold our newborn baby,
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当我们怀抱新生儿，
11:49
love at first sight,
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当我们一见钟情，
11:50
or when we help someone in need,
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当我们助人于难，
11:52
humans are uniquely able
to give and receive love,
to give and receive love,
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唯独人类才能爱与被爱，
11:56
and that's what differentiates us from AI.
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爱使我们有别于人工智能。
12:00
Despite what science fiction may portray,
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无论科幻电影如何描述，
12:03
I can responsibly tell you
that AI has no love.
that AI has no love.
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我可以负责任地告诉你，
人工智能程序没有爱的能力。
人工智能程序没有爱的能力。
12:07
When AlphaGo defeated
the world champion Ke Jie,
the world champion Ke Jie,
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当阿法狗围棋打败世界冠军柯洁时，
12:10
while Ke Jie was crying
and loving the game of go,
and loving the game of go,
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柯洁哭着并爱着围棋，
12:13
AlphaGo felt no happiness from winning
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但阿法狗无法从胜利中感受到喜悦，
12:17
and certainly no desire
to hug a loved one.
to hug a loved one.
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也不会渴望拥抱一个心爱的人。
12:23
So how do we differentiate ourselves
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那我们如何在人工智能时代中
12:26
as humans in the age of AI?
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将自己作为人类区分出来？
12:28
We talked about the axis of creativity,
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我们谈到过创造性维度，
12:31
and certainly that is one possibility,
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那当然是一个可能性，
现在我们要介绍一个新维度，
称之为同情心、爱或同理心。
称之为同情心、爱或同理心。
12:34
and now we introduce a new axis
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12:37
that we can call compassion,
love, or empathy.
love, or empathy.
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12:40
Those are things that AI cannot do.
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那些都是人工智能做不到的事。
12:43
So as AI takes away the routine jobs,
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当人工智能带走重复性工作时，
12:46
I like to think we can, we should
and we must create jobs of compassion.
and we must create jobs of compassion.
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我想我们可以、应该而且必须创造关爱型工作。
12:51
You might ask how many of those there are,
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你或许会问那种工作到底有多少？
12:54
but I would ask you:
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但我想问问你：
12:55
Do you not think that we are going
to need a lot of social workers
to need a lot of social workers
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你不认为我们将需要许多社工
12:59
to help us make this transition?
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来帮助我们平稳过渡吗？
13:01
Do you not think we need
a lot of compassionate caregivers
a lot of compassionate caregivers
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你不认为我们需要许多富有同情心的看护
13:05
to give more medical care to more people?
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来为更多人提供更多医疗护理吗？
13:07
Do you not think we're going to need
10 times more teachers
10 times more teachers
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你不认为我们将需要多10倍的老师
13:11
to help our children find their way
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来帮助孩子们寻找
13:14
to survive and thrive
in this brave new world?
in this brave new world?
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在这个勇敢新世界里的生存和成长之道吗？
有了新获得的财富，
13:17
And with all the newfound wealth,
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13:19
should we not also make
labors of love into careers
labors of love into careers
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我们不应该创造以人性关爱为本的工作
13:24
and let elderly accompaniment
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把老人护工或在家教育变成工作种类吗？
13:27
or homeschooling become careers also?
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13:30
(Applause)
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（掌声）
13:36
This graph is surely not perfect,
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这个图表不甚完美，
13:39
but it points at four ways
that we can work with AI.
that we can work with AI.
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但展示了四种我们与人工智能共事的方式。
13:42
AI will come and take away
the routine jobs
the routine jobs
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人工智能将代替我们承担重复性工作，
到时候我们将甚感欣慰。
13:46
and in due time, we will be thankful.
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13:49
AI will become great tools
for the creatives
for the creatives
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人工智能将成为创造者的好工具
13:52
so that scientists, artists,
musicians and writers
musicians and writers
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所以科学家、艺术家、音乐家和作家
能变得更有创造力。
13:55
can be even more creative.
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13:58
AI will work with humans
as analytical tools
as analytical tools
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人工智能将作为分析工具与人共事，
人类将温暖倾注于高同情性工作。
14:03
that humans can wrap their warmth around
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14:06
for the high-compassion jobs.
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14:08
And we can always differentiate ourselves
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我们可以区分自己
14:10
with the uniquely capable jobs
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通过独特擅长的工作
14:12
that are both compassionate and creative,
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兼具同情心和创造性，
14:16
using and leveraging
our irreplaceable brains and hearts.
our irreplaceable brains and hearts.
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充分利用我们独一无二的头脑和内心。
14:21
So there you have it:
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这就是：
14:22
a blueprint of coexistence
for humans and AI.
for humans and AI.
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人类与人工智能共存的蓝图。
14:27
AI is serendipity.
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人工智能的发展是机缘巧合。
14:29
It is here to liberate us
from routine jobs,
from routine jobs,
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它的到来将把我们从常规工作中解放出来，
14:32
and it is here to remind us
what it is that makes us human.
what it is that makes us human.
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它的到来也提醒我们人因何为人。
14:36
So let us choose to embrace AI
and to love one another.
and to love one another.
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所以让我们选择拥抱人工智能并互相关爱。
14:40
Thank you.
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谢谢。
14:41
(Applause)
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（掌声）
ABOUT THE SPEAKER
Kai-Fu Lee - Investor, computer scientistAt Sinovation Ventures, Kai-Fu Lee invests in the next generation of Chinese high-tech companies.
Why you should listen
Dr. Kai-Fu Lee has a unique perspective on the global technology industry, having worked extensively between the US and China, and has been in artificial intelligence research, development and investment for more than 30 years. He is one of China's top technology investors, undertaking early pioneering work in the field of artificial intelligence and working with multiple US technology giants.
Lee is the Chairman and CEO of Sinovation Ventures, managing a $1.7 billion dual-currency investment fund. Sinovation is a leading technology-savvy investment firm focusing on developing Chinese high-tech companies. Lee also serves as president of the Sinovation Ventures Artificial Intelligence Institute.
Prior to founding Sinovation in 2009, Lee was the President of Google China. Previously, he held executive positions at Microsoft, SGI and Apple. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), and he was Vice Chairman of the Committee of 100 and named one of the 100 most influential people in the world by TIME Magazine. He is the author of seven best-selling books in Chinese, launching his new book AI Superpowers internationally in fall 2018, and has over 50 million followers on social media.
In the field of artificial intelligence, Lee founded Microsoft Research China, which was named as the hottest research lab by MIT Technology Review. Later renamed Microsoft Research Asia, this institute has trained the great majority of AI leaders in China, including CTOs or AI heads at Baidu, Tencent, Alibaba, Lenovo, Huawei and Haier. While with Apple, Lee led AI projects in speech and natural language, which appeared on Good Morning America on ABC Television and the front page of The Wall Street Journal. He has authored 10 US patents, and more than 100 journal and conference papers.
Kai-Fu Lee | Speaker | TED.com