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譯者: Lilian Chiu
審譯者: 易帆 余
00:12
Today I'm here, actually,
to pose you a question.
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今天我來這裡其實
是要問各位一個問題。
00:15
What is life?
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生命是什麼?
00:17
It has been really puzzling me
for more than 25 years,
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這個問題困惑了我 25 年,
00:21
and will probably continue doing so
for the next 25 years.
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可能在接下來的 25 年
繼續困惑著我。
00:25
This is the thesis I did
when I was still in undergraduate school.
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這是我在大學時做的論文。
00:31
While my colleagues still treated
computers as big calculators,
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當我的同學仍然把電腦
視為是大型計算機時,
00:38
I started to teach computers to learn.
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我就開始教電腦學習了。
00:41
I built digital lady beetles
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我打造了數位瓢蟲,
00:44
and tried to learn from real lady beetles,
just to do one thing:
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試圖向真實的瓢蟲學習,
讓它們只做一件事:
00:49
search for food.
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尋找食物。
00:51
And after very simple neural network --
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經過了非常簡單的神經網路──
00:53
genetic algorithms and so on --
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基因演算法等等──
00:56
look at the pattern.
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看這個模型,
00:57
They're almost identical to real life.
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它們幾乎和真實的生命一模一樣。
01:01
A very striking learning experience
for a twenty-year-old.
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對一個 20 歲的小伙子來說
這是很驚人的學習經驗。
01:07
Life is a learning program.
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生命本身就是一個學習程式。
01:12
When you look
at all of this wonderful world,
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這個大千世界,
01:15
every species has
its own learning program.
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每個物種都有自己的學習程式。
01:19
The learning program is genome,
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這學習程式就是基因組,
01:22
and the code of that program is DNA.
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程式碼就是 DNA。
01:26
The different genomes of each species
represent different survival strategies.
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每個物種的不同基因組
代表著不同的生存策略。
01:33
They represent hundreds of millions
of years of evolution.
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代表著數億年的進化演變,
01:38
The interaction between
every species' ancestor
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記錄了每個物種的祖先
01:42
and the environment.
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與環境之間的互動。
01:45
I was really fascinated about the world,
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我完全迷上了這個世界,
01:48
about the DNA,
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迷上了 DNA,
01:49
about, you know, the language of life,
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迷上了,你知道的,生命的語言,
01:52
the program of learning.
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學習的程式。
01:54
So I decided to co-found
the institute to read them.
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所以我決定找人共同創辦一個
讀取基因組的機構。
01:59
I read many of them.
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我讀了很多基因組。
02:01
We probably read more than half
of the prior animal genomes in the world.
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我們可能解讀了
世界上超過一半的動物基因組。
02:06
I mean, up to date.
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我是指,與時俱進。
02:09
We did learn a lot.
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我們學到了很多。
02:11
We did sequence, also,
one species many, many times ...
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我們對一個物種進行了
多次基因定序,做了許多次……
02:15
human genome.
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即人類基因組。
02:16
We sequenced the first Asian.
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我們完成了第一個
亞洲人基因組的定序。
02:17
I sequenced it myself many, many times,
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剛好利用平台的優勢,
02:20
just to take advantage of that platform.
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我對自己的基因也進行了多次定序。
02:24
Look at all those repeating base pairs:
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看著所有那些重覆的鹼基對:
02:27
ATCG.
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ATCG。
(註:四種 DNA 鹼基)
02:29
You don't understand anything there.
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你幾乎無法從中讀懂任何含義。
02:31
But look at that one base pair.
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但看看這一組鹼基對。
02:32
Those five letters, the AGGAA.
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AGGAA,這五個字母。
02:35
These five SNPs represent
a very specific haplotype
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這五個 SNP(單核苷酸多態性)
代表了一種非常特別的單倍型,
02:39
in the Tibetan population
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它們是藏族人的身體中
02:41
around the gene called EPAS1.
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一種叫做 EPAS1 的基因。
02:43
That gene has been proved --
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這個基因已被證明是──
02:44
it's highly selective --
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高度選擇性的結果──
02:46
it's the most significant signature
of positive selection of Tibetans
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這是藏族人對高海拔適應性
進行正向選擇的重要指標。
02:50
for the higher altitude adaptation.
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02:52
You know what?
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你知道嗎?
02:54
These five SNPs were the result
of integration of Denisovans,
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這五個 SNP 是來自
滅絕的丹尼索瓦人,
02:59
or Denisovan-like individuals into humans.
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或與丹尼索瓦人有親緣關係的
個體 DNA 與人類雜交的結果。
03:04
This is the reason
why we need to read those genomes.
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這就是為什麽我們需要
讀這些基因組的原因。
03:06
To understand history,
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它可以讓你了解歷史,
03:08
to understand what kind
of learning process
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了解基因組這套學習程序
03:12
the genome has been through
for the millions of years.
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在數百萬年中經歷了什麽樣的演變。
03:17
By reading a genome,
it can give you a lot of information --
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透過閱讀基因組,
你能得到許多資訊──
03:20
tells you the bugs in the genome --
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它能告訴你基因組中的一些錯誤──
03:21
I mean, birth defects,
monogenetic disorders.
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我指的是像天生缺陷、
單基因遺傳病。
03:25
Reading a drop of blood
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而僅僅需要一滴血的判讀,
03:26
could tell you why you got a fever,
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就能告訴你為什麼會發燒,
03:28
or it tells you which medicine
and dosage needs to be used
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或告訴你在你生病,
03:31
when you're sick, especially for cancer.
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特別是得了癌症時,
需要服用什麼藥、多少劑量。
03:35
A lot of things could be studied,
but look at that:
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可以研究的東西很多,但看看這個:
03:38
30 years ago, we were still poor in China.
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三十年前,我們中國還很窮。
03:42
Only .67 percent of the Chinese
adult population had diabetes.
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只有 0.67% 的
中國成年人有糖尿病。
03:47
Look at now: 11 percent.
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看看現在:11%。
03:49
Genetics cannot change over 30 years --
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遺傳學不會在三十年間改變──
03:52
only one generation.
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才一個世代而已。
03:54
It must be something different.
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一定有什麼其他原因。
03:56
Diet?
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飲食嗎?
03:57
The environment?
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環境嗎?
03:59
Lifestyle?
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生活方式嗎?
04:01
Even identical twins
could develop totally differently.
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即使是同卵雙生的雙胞胎
也可能有完全不同的發展。
04:06
It could be one becomes
very obese, the other is not.
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可能其中一個極肥胖,
另一個不會。
04:10
One develops a cancer
and the other does not.
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其中一個得了癌症,另一個沒有。
04:13
Not mentioning living
in a very stressed environment.
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更不用提處在壓力很大的環境中了。
04:19
I moved to Shenzhen 10 years ago ...
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我十年前搬到深圳…...
04:22
for some reason, people may know.
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有些人可能知道理由。
04:25
If the gene's under stress,
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如果基因在壓力下,
04:27
it behaves totally differently.
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它的行為會全然不同。
04:30
Life is a journey.
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人生是一趟旅程。
04:32
A gene is just a starting point,
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基因只是個起始點,
04:35
not the end.
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不是終點。
04:37
You have this statistical risk
of certain diseases when you are born.
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在你出生時,就註定會有
某些疾病的風險。
04:42
But every day you make different choices,
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但,你每天做出不同的選擇,
04:45
and those choices will increase
or decrease the risk of certain diseases.
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那些選擇會增加或滅少
某些疾病的風險。
04:51
But do you know
where you are on the curve?
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但你知道你在曲線上的哪個點嗎?
04:54
What's the past curve look like?
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過去的曲線是什麼樣子的?
04:56
What kind of decisions
are you facing every day?
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你每天在面對的是什麼樣的決策?
04:59
And what kind of decision is the right one
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什麼樣的決策才是對的,
05:02
to make your own right curve
over your life journey?
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才能為你人生旅程產生出對的曲線?
05:07
What's that?
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那是什麼?
05:09
The only thing you cannot change,
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你唯一無法改變的,
05:11
you cannot reverse back,
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你無法逆轉的,
05:13
is time.
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就是時間。
05:14
Probably not yet; maybe in the future.
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目前還不能,但將來不一定。
05:16
(Laughter)
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(笑聲)
05:17
Well, you cannot change
the decision you've made,
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你無法改變你已做的決定,
05:20
but can we do something there?
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但我們能不能做點什麼?
05:22
Can we actually try to run
multiple options on me,
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我們能否對自己測試多個選項,
05:27
and try to predict right
on the consequence,
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試著預測正確的結果,
05:31
and be able to make the right choice?
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以做出正確的選擇?
05:33
After all,
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畢竟,
05:35
we are our choices.
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我們就是我們的選擇所決定的。
05:38
These lady beetles came to me afterwards.
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這些瓢蟲後來啟發了我。
05:41
25 years ago, I made
the digital lady beetles
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25 年前,我做了數位瓢蟲,
05:44
to try to simulate real lady beetles.
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試圖模擬自然界的真實瓢蟲。
05:47
Can I make a digital me ...
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我是否可以同樣做出數位化的我……
05:49
to simulate me?
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來模擬真實的我?
05:51
I understand the neural
network could become
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我當然明白其中的神經網絡可能會
05:54
much more sophisticated
and complicated there.
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更精密且複雜許多。
05:57
Can I make that one,
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但我能否做到,
05:59
and try to run multiple options
on that digital me --
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然後試著用那個數位化的我
來測試多重選項……
06:02
to compute that?
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來計算出不同的選擇結果?
06:04
Then I could live in different universes,
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那樣一來,我就可以
06:07
in parallel, at the same time.
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同時活在不同的平行宇宙中。
06:10
Then I would choose
whatever is good for me.
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我就可以選擇對我最好的選項。
06:14
I probably have the most comprehensive
digital me on the planet.
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我的生命數據可能是
這個星球最全面的,
06:17
I've spent a lot of dollars
on me, on myself.
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我花了很多錢在我自己身上。
06:21
And the digital me told me
I have a genetic risk of gout
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這個數位化的我,
透過這些東西告訴我,
06:27
by all of those things there.
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我有痛風的基因風險。
06:29
You need different technology to do that.
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你需要不同的技術才能做到那樣。
06:31
You need the proteins, genes,
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你需要蛋白質、基因,
06:32
you need metabolized antibodies,
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你需要心陳代謝抗體,
06:35
you need to screen all your body
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你需要掃瞄你的整個身體,
06:37
about the bacterias and viruses
covering you, or in you.
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來找出你身上或體內的細菌及病毒。
06:41
You need to have
all the smart devices there --
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你需要各種智慧的儀器──
06:44
smart cars, smart house, smart tables,
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智慧車、智慧房屋、智慧桌子、
06:47
smart watch, smart phone
to track all of your activities there.
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智慧手表、智慧手機,
才能追縱你所有的活動。
06:51
The environment is important --
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環境很重要──
06:52
everything's important --
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一切都很重要──
06:53
and don't forget the smart toilet.
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別忘了智慧馬桶。
06:55
(Laughter)
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(笑聲)
06:56
It's such a waste, right?
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這真的很浪費,對吧?
06:58
Every day, so much invaluable information
just has been flushed into the water.
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每天有那麼多個人資訊
就這樣被水沖掉了。
07:04
And you need them.
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你需要這些資訊。
07:05
You need to measure all of them.
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你需要測量這些資訊。
07:07
You need to be able to measure
everything around you
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你需要能夠測量你周遭的一切,
07:10
and compute them.
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並計算它們。
07:11
And the digital me told me
I have a genetic defect.
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數位化的我告訴我,我有基因缺陷。
07:16
I have a very high risk of gout.
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我的痛風風險很高。
07:19
I don't feel anything now,
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我現在感覺不出來,
07:21
I'm still healthy.
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我仍然很健康。
07:22
But look at my uric acid level.
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但看看我的尿酸濃度。
07:24
It's double the normal range.
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是正常範圍的兩倍。
07:26
And the digital me searched
all the medicine books,
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數位的我搜尋了所有的醫學書籍,
07:29
and it tells me, "OK, you could
drink burdock tea" --
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它告訴我:「好,
你可以喝牛蒡茶」──
07:33
I cannot even pronounce it right --
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我甚至不會唸這個字──
07:35
(Laughter)
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(笑聲)
07:36
That is from old Chinese wisdom.
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那是來自中國的古老智慧。
07:38
And I drank that tea for three months.
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我喝了那種茶三個月。
07:41
My uric acid has now gone back to normal.
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我的尿酸現在回到正常了。
07:44
I mean, it worked for me.
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我是說,它對我有效耶。
07:46
All those thousands of years
of wisdom worked for me.
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數千年的智慧對我有用。
07:49
I was lucky.
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我很幸運。
07:50
But I'm probably not lucky for you.
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但可能對於你們來說就不一定了。
07:55
All of this existing
knowledge in the world
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所有世界上既有的知識
07:57
cannot possibly be efficient enough
or personalized enough for yourself.
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對你自己而言都不夠有效或個人化。
08:03
The only way to make
that digital me work ...
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要讓這個數位化的我
有效的唯一方法,
08:07
is to learn from yourself.
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就是要向你自己學習。
08:10
You have to ask a lot
of questions about yourself:
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你得要問很多關於你自己的問題:
08:13
"What if?" --
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「假如……?」
08:15
I'm being jet-lagged now here.
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我現在在這裡有時差。
08:16
You don't probably see it, but I do.
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你們可能看不出來,但確實有。
08:19
What if I eat less?
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如果我吃少一點呢?
08:21
When I took metformin,
supposedly to live longer?
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如果我吃抗糖尿病藥,
會不會比較長壽?
08:25
What if I climb Mt. Everest?
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如果我去爬聖母峰呢?
08:26
It's not that easy.
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那並不容易。
08:28
Or run a marathon?
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或跑馬拉松呢?
08:29
What if I drink a bottle of mao-tai,
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如果我喝一瓶茅臺酒呢?
08:32
which is a Chinese liquor,
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那是種中國酒,
08:33
and I get really drunk?
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且喝得非常醉呢?
08:34
I was doing a video rehearsal last time
with the folks here,
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上次我和這裡的人在做視訊排演,
08:39
when I was drunk,
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當時我醉了,
08:40
and I totally delivered
a different speech.
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我的演說完全不一樣。
08:42
(Laughter)
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(笑聲)
08:45
What if I work less, right?
178
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2301
如果我工作少一點呢?
08:47
I have been less stressed, right?
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我就會少點壓力,對吧?
08:49
So that probably never happened to me,
180
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1810
那可能永遠不會發生在我身上,
08:51
I was really stressed every day,
181
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2098
我每天都非常有壓力,
08:53
but I hope I could be less stressed.
182
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1966
但我希望我能少點壓力。
08:56
These early studies told us,
183
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早先的研究告訴我們,
08:58
even with the same banana,
184
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1983
即使是吃同樣的香蕉,
09:00
we have totally different
glucose-level reactions
185
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不同的個體也會有全然不同的
09:03
over different individuals.
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葡萄糖濃度反應。
09:04
How about me?
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那我呢?
09:06
What is the right breakfast for me?
188
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一頓正確的早餐應該吃什麽?
09:08
I need to do two weeks
of controlled experiments,
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2918
我需要做兩週的對照實驗,
09:11
of testing all kinds of different
food ingredients on me,
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3745
測試各種不同食材的反應,
09:14
and check my body's reaction.
191
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2288
並檢查我的身體反應。
09:17
And I don't know
the precise nutrition for me,
192
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3117
我不知道對我來說,精確的營養
09:20
for myself.
193
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到底應該包含什麽。
09:23
Then I wanted to search
all the Chinese old wisdom
194
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接著我想要搜尋所有的中國古智慧,
09:27
about how I can live longer,
and healthier.
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2992
了解我要如何活得更久、更健康。
09:30
I did it.
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我去做了。
09:31
Some of them are really unachievable.
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2251
有些真的無法達成。
09:34
I did this once last October,
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2865
我是在去年十月做的,
09:37
by not eating for seven days.
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1718
七天沒有吃東西。
09:39
I did a fast for seven days
with six partners of mine.
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4124
我和我的六個伙伴一同禁食七天。
09:44
Look at those people.
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看看那些人。
09:45
One smile.
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1151
有一個人在笑。
09:47
You know why he smiled?
203
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猜猜為何他會笑?
09:48
He cheated.
204
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1167
他作弊。
09:49
(Laughter)
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1000
(笑聲)
09:50
He drank one cup of coffee at night,
206
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3136
晚上他喝了一杯咖啡,
09:53
and we caught it from the data.
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1485
我們從資料中抓到的。
09:55
(Laughter)
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1045
(笑聲)
09:56
We measured everything from the data.
209
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2460
我們從資料中測量一切。
09:58
We were able to track them,
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2214
我們能夠追縱它們,
10:00
and we could really see --
211
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1558
我們真的能看到──
10:02
for example, my immune system,
212
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2001
比如,我的免疫系統,
10:04
just to give you a little hint there.
213
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1762
給各位一點小暗示。
10:06
My immune system changed
dramatically over 24 hours there.
214
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4304
我的免疫系統在 24 小時
發生了巨大改變。
10:11
And my antibody regulates my proteins
215
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3133
而我的抗體為了適應這樣的變化,
10:14
for that dramatic change.
216
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1536
開始對我體內的蛋白質進行調節,
10:16
And everybody was doing that.
217
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1381
所有參與體驗的人都是如此,
10:17
Even if we're essentially
totally different at the very beginning.
218
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3332
儘管每個人的免疫系統各不相同。
10:21
And that probably will be
an interesting treatment in the future
219
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3045
這很可能是將來治療癌症
10:24
for cancer and things like that.
220
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1643
或類似疾病的一個有趣方法。
10:25
It becomes very, very interesting.
221
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1630
這件事變得越來越有趣。
10:28
But something you probably
don't want to try,
222
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2701
但有些方法你可能未必想嘗試,
10:30
like drinking fecal water
from a healthier individual,
223
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3676
比如去喝健康人的尿
10:34
which will make you feel healthier.
224
634531
1667
會讓你更健康。
10:36
This is from old Chinese wisdom.
225
636222
1715
這是來自古老中國的智慧。
10:37
Look at that, right?
226
637961
1436
你看,是吧?
10:39
Like 1,700 years ago,
227
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2166
大約 1700 年前,
10:41
it's already there, in the book.
228
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2280
書籍上就有這樣的記載了。
10:44
But I still hate the smell.
229
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1327
但我仍然很討厭那味道。
10:46
(Laughter)
230
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1150
(笑聲)
10:47
I want to find out the true way to do it,
231
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2406
我想要找一種真正的方式來做它,
10:49
maybe find a combination of cocktails
of bacterias and drink it,
232
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4354
也許用雞尾酒和細菌
來合成,再喝下去,
10:54
it probably will make me better.
233
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1524
也許會讓我感覺好些。
10:55
So I'm trying to do that.
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1191
我在試著這麼做。
10:56
Even though I'm trying this hard,
235
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3002
雖然我非常努力在試,
10:59
it's so difficult to test out
all possible conditions.
236
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5026
但是要測試出所有可能的方法
是非常困難的,
11:04
It's not possible to do
all kinds of experiments at all ...
237
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5237
完全不可能去做所有各種實驗……
11:11
but we do have seven billion
learning programs on this planet.
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3813
但在地球上我們仍然有
七十億個學習程式。
11:14
Seven billion.
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1266
七十億。
11:16
And every program
is running in different conditions
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3651
每個程式都以不同的條件在執行,
11:19
and doing different experiments.
241
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1781
做著不同的實驗。
11:21
Can we all measure them?
242
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1851
我們能不能把它們全部都量測出來?
11:24
Seven years ago,
I wrote an essay in "Science"
243
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3215
七年前我在《科學》期刊中
寫了一篇短文,
11:28
to celebrate the human genome's
10-year anniversary.
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3292
來讚頌人類基因組的十週年紀念。
11:31
I said, "Sequence yourself,
245
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1654
我說:「定序你自己,
11:33
for one and for all."
246
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1623
為自己,也為所有人。」
11:35
But now I'm going to say,
247
695618
1868
但現在我只打算說:
11:37
"Digitalize yourself for one and for all."
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3746
「把你自己數位化,
為自己,也為所有人。」
11:42
When we make this digital me
into a digital we,
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5600
當我們把「數位化的我」
變成「數位化的我們」,
11:47
when we try to form an internet of life,
250
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3752
當我們嘗試建構數位化生命網路、
11:51
when people can learn from each other,
251
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2861
當人們可以從中彼此學習、
11:54
when people can learn
from their experience,
252
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2707
當人們可以從他們的經驗、
11:57
their data,
253
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1731
他們的資料來學習,
11:58
when people can really form
a digital me by themselves
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3601
當人們能真正做出
「數位化的自己」,
12:02
and we learn from it,
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1611
我們可以從中進行學習,
12:05
the digital we will be
totally different with a digital me.
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5732
那麼「數位化的我們」就會和
「數位化的我」截然不同了。
12:10
But it can only come from the digital me.
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3420
但它必須要由
「數位化的我」開始建立起。
12:15
And this is what I try to propose here.
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2979
這是我在這裡想要提議的事。
12:19
Join me --
259
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1150
加入我──
12:21
become we,
260
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1150
變成「我們」,
12:23
and everybody should build up
their own digital me,
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4938
每個人都應該要建立
自己的「數位化的我」,
12:28
because only by that
will you learn more about you,
262
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4519
因為只有這樣做,
你才能學到更多關於你自己、
12:33
about me,
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1424
關於我、
12:34
about us ...
264
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1165
關於我們…...
12:36
about the question I just posed
at the very beginning:
265
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3680
關於我在一開頭提出的問題:
12:40
"What is life?"
266
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1150
「生命是什麼?」
12:41
Thank you.
267
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1169
謝謝。
12:43
(Applause)
268
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5950
(掌聲)
12:49
Chris Anderson:
One quick question for you.
269
769053
2761
克里斯安德森:很快請教一個問題。
12:52
I mean, the work is amazing.
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1974
這項研究很令人驚奇。
12:54
I suspect one question people have is,
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3198
我想人們可能會有一個疑問,
12:57
as we look forward to these amazing
technical possibilities
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3281
當我們在期待著這些
個人化醫學的
13:01
of personalized medicine,
273
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1361
非凡技術可能性時,
13:02
in the near-term it feels like
they're only going to be affordable
274
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3303
在短期來看,
似乎只有少數的人能負擔,
13:05
for a few people, right?
275
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1276
對吧?
13:07
It costs many dollars to do
all the sequencing and so forth.
276
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2991
需要很多錢才能做這些定序等等。
13:10
Is this going to lead to a kind of,
277
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2912
這是否會導致某種……
13:13
you know, increasing inequality?
278
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2317
不平等的增加?
13:15
Or do you have this vision
that the knowledge that you get
279
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3911
或者您是否有這樣的願景:
從這些早期的志願者
身上獲取的知識,
13:19
from the pioneers
280
799921
1352
13:21
can actually be
pretty quickly disseminated
281
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2096
快速地複製推廣,
13:23
to help a broader set of recipients?
282
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4124
從而幫助更廣泛的群體?
13:27
Jun Wang: Well, good question.
283
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1534
王俊:嗯,好問題。
13:29
I'll tell you that seven years ago,
when I co-founded BGI,
284
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3551
我可以告訴你,
當我七年前共同創立了華大基因,
13:32
and served as the CEO
of the company there,
285
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3405
並擔任公司執行長時,
13:36
the only goal there for me to do
286
816127
2381
我唯一想做到的目標
13:38
was to drive the sequencing cost down.
287
818532
1983
是要把做定序的成本降低。
13:40
It started from 100 million dollars
per human genome.
288
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2775
早先的人類基因組定序要一億元。
13:43
Now, it's a couple hundred dollars
for a human genome.
289
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2591
現在每個人類基因組只要幾百塊錢。
13:46
The only reason to do it
is to get more people to benefit from it.
290
826278
3614
這麼做的唯一理由,
就是想讓更多人從中受益。
13:50
So for the digital me,
it's the same thing.
291
830198
2157
所以,對「數位化的我」也一樣。
13:52
Now, you probably need,
292
832379
1489
現在,你可能會需要…...
13:53
you know, one million dollars
to digitize a person.
293
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3229
一百萬元才能把一個人數位化。
13:57
I think it has to be 100 dollars.
294
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1675
我想價格得要降到一百元。
13:59
It has to be free for many of those people
that urgently need that.
295
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4049
有緊急需求的人要是可以免費的。
14:04
So this is our goal.
296
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1267
這是我們的目標。
14:05
And it seems that with all
this merging of the technology,
297
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3423
似乎,把所有這些科技結合,
14:09
I'm thinking that in the very near future,
298
849260
2592
我想,在不遠的將來,
14:11
let's say three to five years,
299
851876
2365
也許三到五年,
14:14
it will come to reality.
300
854265
1482
它就會實現。
14:15
And this is the whole idea
of why I founded iCarbonX,
301
855771
3979
這就是為什麼
我會成立第二間公司 :
14:19
my second company.
302
859774
1219
iCarbonX(碳雲智能)。
14:21
It's really trying to get the cost down
303
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2868
我們是真的想把成本下降,
14:23
to a level where every individual
could have the benefit.
304
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3420
下降到人人都可受惠的程度。
14:27
CA: All right, so the dream is not
elite health services for few,
305
867353
3048
克里斯:好,所以這個夢想
並不是給少數人的菁英健康服務,
14:30
it's to really try
306
870425
1234
是真的要試著去
14:31
and actually make overall health care
much more cost effective --
307
871683
3111
且實際上去讓整體的
健康照護更有成本效益──
14:34
JW: But we started
from some early adopters,
308
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2430
王俊:我們需要從一些
早期的先行者開始,
14:37
people believing ideas and so on,
309
877272
2506
從更加相信這個想法的一些人開始,
14:39
but eventually, it will become
everybody's benefit.
310
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3642
但最終它將能夠讓每個人都受益。
14:44
CA: Well, Jun, I think
it's got to be true to say
311
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2333
克里斯:王俊,我想這麼說不為過,
14:46
you're one of the most amazing
scientific minds on the planet,
312
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2958
你是地球上很有
慈善心腸的科學家之一,
14:49
and it's an honor to have you.
313
889462
1429
非常榮幸能邀請到你。
14:50
JW: Thank you.
314
890915
1158
王俊:謝謝。
14:52
(Applause)
315
892097
1150
(掌聲)
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