Finding life we can't imagine | Christoph Adami

44,026 views ・ 2011-10-04

TED


請雙擊下方英文字幕播放視頻。

譯者: Jerry Liu 審譯者: Ana Choi
00:15
So, I have a strange career.
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我的職業很奇怪。
00:17
I know it because people come up to me, like colleagues, and say,
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這麼講是因為常有人這樣告訴我,例如我的同事
00:20
"Chris, you have a strange career."
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都會說:「克里斯,你的職業很奇怪耶。」
00:22
(Laughter)
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(觀眾笑聲)
00:24
And I can see their point,
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其實我理解他們的意思,
00:25
because I started my career as a theoretical nuclear physicist.
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因為我一開始當過
理論核子物理學家。
00:30
And I was thinking about quarks and gluons and heavy ion collisions,
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那時我成天想的都是夸克和膠子,
還有重離子的撞擊,
00:34
and I was only 14 years old --
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那時我才14歲而已。
00:36
No, no, I wasn't 14 years old.
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不,不對,不是14歲那年的事。
00:40
But after that,
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不過在那之後
我有了一間專屬的實驗室,
00:43
I actually had my own lab
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就在計算神經科學系那邊,
00:45
in the Computational Neuroscience department,
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但是我完全都沒有做神經科學的研究。
00:47
and I wasn't doing any neuroscience.
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00:48
Later, I would work on evolutionary genetics,
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後來我開始研究演化基因,
00:51
and I would work on systems biology.
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接著便是系統生物學。
00:53
But I'm going to tell you about something else today.
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不過以上這些跟我今天要講的主題一點關係也沒有。
00:56
I'm going to tell you about how I learned something about life.
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我要講的是
我如何探悉到生命的一些東西。
01:00
And I was actually a rocket scientist.
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我以前當過火箭專家。
01:04
I wasn't really a rocket scientist,
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但嚴格上來說我不算是真正的火箭專家,
01:06
but I was working at the Jet Propulsion Laboratory
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只不過我曾經在
位於陽光普照的加州的太空總署的
噴射推進實驗室工作過;
01:11
in sunny California, where it's warm;
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01:13
whereas now I am in the mid-West, and it's cold.
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而我現在在中西部,
氣候很寒冷。
01:17
But it was an exciting experience.
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不過這是一個很有趣的經驗。
01:20
One day, a NASA manager comes into my office,
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有一天NASA主管走進我的辦公室,
01:23
sits down and says,
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坐下後說:
01:26
"Can you please tell us, how do we look for life outside Earth?"
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「請你告訴我們,
如何能尋找到外太空的生命?」
我當時很驚訝,
01:31
And that came as a surprise to me,
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因為我當初是被請來
01:33
because I was actually hired to work on quantum computation.
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進行量子計算研究的。
然而我回答得很漂亮。
01:37
Yet, I had a very good answer.
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01:38
I said, "I have no idea."
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我答:「我一點也不知道。」
01:40
(Laughter)
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01:41
And he told me, "Biosignatures, we need to look for a biosignature."
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接著他對我說:「生命跡象,
我們必須找出生命跡象。」
我問他:「那是什麼?」
01:47
And I said, "What is that?"
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01:48
And he said, "It's any measurable phenomenon
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他說:「生命跡象就是能讓我們能
辨識出任何可量化
01:51
that allows us to indicate the presence of life."
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生命的存在的現象。」
01:54
And I said, "Really?
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我說:「真的嗎?
01:56
Because isn't that easy?
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真的有這麼簡單嗎?
01:58
I mean, we have life.
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我是說,我們有生命。
02:00
Can't you apply a definition,
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但你能為生命下一個
02:02
for example, a Supreme Court-like definition of life?"
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類似最高法院般的終極定義嗎?」
我再想了想, 然後說,
02:07
And then I thought about it a little bit, and I said,
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「就只有這樣而已嗎?
02:09
"Well, is it really that easy?
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沒錯,如果你看到這個,
02:11
Because, yes, if you see something like this,
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02:13
then all right, fine, I'm going to call it life --
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毫無疑問,我會稱它為生命--
02:15
no doubt about it.
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這是無庸置疑的。
02:17
But here's something."
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但如果換成這個。」
02:19
And he goes, "Right, that's life too. I know that."
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他說:「沒錯,這個也是生命。我很確定。」
02:22
Except, if you think that life is also defined by things that die,
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可是倘若你認為得生命
是由會死亡的物體來定義,
02:26
you're not in luck with this thing,
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那你就無法解釋這個東西,
02:28
because that's actually a very strange organism.
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因為這是一個相當奇怪的有機體。
02:30
It grows up into the adult stage like that
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當它進入成年期的時候就像這樣,
然後就像班傑明的奇幻旅程一樣
02:33
and then goes through a Benjamin Button phase,
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02:35
and actually goes backwards and backwards until it's like a little embryo again,
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不斷退化,
直到胚胎為止,
接著又長回來,再長大 -- 像溜溜球一樣過程循環 --
02:40
and then actually grows back up, and back down and back up --
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而永生不死。
02:43
sort of yo-yo -- and it never dies.
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02:44
So it's actually life,
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這也算是生命的一種,
只不過它不是
02:47
but it's actually not as we thought life would be.
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我們一般所認知的型態。
02:51
And then you see something like that.
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再來你如果看到這個。
02:53
And he was like, "My God, what kind of a life form is that?"
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他問:「天啊,這到底是什麼樣的生命形態呢?」
有人知道嗎?
02:56
Anyone know?
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其實這不算是生命,這是一種結晶體。
02:58
It's actually not life, it's a crystal.
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所以當你觀察的東西
03:01
So once you start looking and looking at smaller and smaller things --
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越來越小時--
03:04
so this particular person wrote a whole article and said,
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有位老兄
花了整篇文章的篇幅 只為傳達一件事:「嗨, 這是細菌。」
03:08
"Hey, these are bacteria."
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03:09
Except, if you look a little bit closer,
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但如果你靠近一點觀察
03:11
you see, in fact, that this thing is way too small to be anything like that.
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你會發現,事實上這個物體 已經比細菌還要小。
於是他被說服了,
03:15
So he was convinced, but, in fact, most people aren't.
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可是大部分的人還是不相信。
當然,
03:19
And then, of course, NASA also had a big announcement,
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NASA做了一個重大的宣布,
03:22
and President Clinton gave a press conference,
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此外前總統柯林頓也召開記者會,
宣布在火星的隕石裡
03:25
about this amazing discovery of life in a Martian meteorite.
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發現有生命的存在。
但是現今這個說法受到嚴重的質疑。
03:30
Except that nowadays, it's heavily disputed.
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如果你仔細地研究這些照片,
03:34
If you take the lesson of all these pictures,
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03:36
then you realize, well, actually, maybe it's not that easy.
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就會發覺區別生命並沒有那麼簡單。
也許我需要
03:39
Maybe I do need a definition of life
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一個生命的定義
03:42
in order to make that kind of distinction.
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才能夠來做區別。
生命能被定義嗎?
03:45
So can life be defined?
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你會如何著手?
03:47
Well how would you go about it?
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當然
03:49
Well of course, you'd go to Encyclopedia Britannica and open at L.
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你會從大英百科的L開始查起。
不,你當然不會那樣做; 你會用Google搜尋。
03:53
No, of course you don't do that; you put it somewhere in Google.
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然後你或會得到一些資料。
03:56
And then you might get something.
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03:57
(Laughter)
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03:58
And what you might get --
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接著把你搜尋到的 --
04:00
and anything that actually refers to things that we are used to,
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所有我們習以為常的觀念
拋諸腦後。
04:04
you throw away.
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然後你可能會得到這段
04:05
And then you might come up with something like this.
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複雜的解釋,
04:07
And it says something complicated with lots and lots of concepts.
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裡頭包括許許多多的概念。
到底有誰會寫出
04:11
Who on Earth would write something as convoluted and complex and inane?
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這麼人費解,複雜
又空洞的東西?
但是這段定義確實涵蓋了 一堆非常重要的概念。
04:18
Oh, it's actually a really, really, important set of concepts.
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我標出了幾個關鍵字眼,
04:22
So I'm highlighting just a few words
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04:24
and saying definitions like that rely on things
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這類的定義
不是基於
04:28
that are not based on amino acids or leaves or anything that we are used to,
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胺基酸或葉子
或者我們熟悉的東西,
而是只基於過程。
04:34
but in fact on processes only.
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如果你仔細看這段話的出處,
04:36
And if you take a look at that,
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就知道是從我寫的一本 有關人造生命的書而來。
04:38
this was actually in a book that I wrote that deals with artificial life.
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這說明了
04:41
And that explains why that NASA manager was actually in my office to begin with.
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那位NASA主管來辦公室找我的原因。
04:45
Because the idea was that, with concepts like that,
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因為用這樣的想法與概念,
04:48
maybe we can actually manufacture a form of life.
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我們也許能創造
一個生命的形式。
04:52
And so if you go and ask yourself, "What on Earth is artificial life?",
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如果你反問自己
「到底什麼是人工生命?」
04:57
let me give you a whirlwind tour of how all this stuff came about.
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就讓我快速地帶你認識
人工生命的由來。
05:01
And it started out quite a while ago,
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這是好幾年前發生的,
05:04
when someone wrote one of the first successful computer viruses.
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有人寫了早期史上
上最具破壞力的電腦病毒。
對年紀較輕的觀眾來說,
05:09
And for those of you who aren't old enough,
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05:11
you have no idea how this infection was working --
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你們可能不清楚這種病毒是從哪裡散播開來的...
05:14
namely, through these floppy disks.
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就是從這種磁碟片傳染的。
05:16
But the interesting thing about these computer virus infections
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不過這種電腦中毒有趣的地方
可以從電腦的
05:20
was that, if you look at the rate at which the infection worked,
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感染速率來看,
05:23
they show this spiky behavior that you're used to from a flu virus.
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這張圖表反映出的上下波動
跟一般的流感病毒沒有兩樣。
05:27
And it is in fact due to this arms race
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事實上因為駭客
05:30
between hackers and operating system designers
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和作業系統開發人員之間發生的爭奪戰,
05:33
that things go back and forth.
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而使結果反反復複。
05:35
And the result is kind of a tree of life of these viruses,
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這張電腦病毒的關係圖
便成樹狀展開,
05:39
a phylogeny that looks very much like the type of life
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一個看似我們熟悉的生命發展史,
至少從病毒的層面來看是如此。
05:43
that we're used to, at least on the viral level.
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05:45
So is that life?
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病毒能算是生命嗎? 我可不這麼認為。
05:47
Not as far as I'm concerned.
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怎麼說呢? 因為它們無法自行演化。
05:49
Why? Because these things don't evolve by themselves.
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事實上,電腦病毒是駭客寫出來的。
05:52
In fact, they have hackers writing them.
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但是這個想法不久就有了一點進展,
05:54
But the idea was taken very quickly a little bit further,
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05:57
when a scientist working at the Santa Fe Institute decided,
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有一個在新墨西哥州的科學家決定,
06:00
"Why don't we try to package these little viruses
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「我們為何不把這些電腦病毒
06:03
in artificial worlds inside of the computer
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放進電腦的虛擬世界,
讓它們自行演化?」
06:06
and let them evolve?"
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06:07
And this was Steen Rasmussen.
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這位科學家就是斯蒂恩•拉斯穆森。
06:09
And he designed this system, but it really didn't work,
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他設計了這套系統,不過沒效,
06:11
because his viruses were constantly destroying each other.
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因為他的病毒會不斷自相殘殺。
06:14
But there was another scientist who had been watching this, an ecologist.
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但當時還有一位科學家對這件事情很關心,是一名生態學者。
他回了家說:「我知道怎麼解決。」
06:18
And he went home and says, "I know how to fix this."
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06:20
And he wrote the Tierra system,
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他寫出Tierra系統,
06:22
and, in my book,
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根據我書裡寫的,Tierra正是最早出現的
06:23
is in fact one of the first truly artificial living systems --
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人造生命系統之一--
06:27
except for the fact that these programs didn't really grow in complexity.
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只不過這些程式沒有真正複雜性的成長。
06:30
So having seen this work, worked a little bit on this,
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看過這個成果之後,我自己也做了一點研究,
06:33
this is where I came in.
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而我的研究就從此展開。
06:35
And I decided to create a system that has all the properties
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我決定創造一個系統,
該系統必須滿足
06:39
that are necessary to see, in fact, the evolution of complexity,
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複雜演化的所有必要條件,
有越來越多複雜的問題持續在演變。
06:43
more and more complex problems constantly evolving.
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當然,由於我不會編碼,所以我找了槍手。
06:46
And of course, since I really don't know how to write code, I had help in this.
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我請到了兩位
06:50
I had two undergraduate students
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在加州理工學院與我共事的大學生。
06:51
at California Institute of Technology that worked with me.
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左邊的是查爾斯•奧佛瑞亞,右邊這位是提多•布朗。
06:54
That's Charles Ofria on the left, Titus Brown on the right.
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他們如今都是在密西根州立大學
06:57
They are now, actually, respectable professors
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06:59
at Michigan State University,
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備受尊崇的教授了,
07:01
but I can assure you, back in the day, we were not a respectable team.
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但我可以向你保證, 在當時
我們並不是可受尊敬的團隊。
我很慶幸我們三人形影不離的合照,
07:06
And I'm really happy that no photo survives
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一張都沒有留下。
07:08
of the three of us anywhere close together.
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這個系統是什麼樣子?
07:11
But what is this system like?
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我不方便探討細節,
07:13
Well I can't really go into the details,
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07:15
but what you see here is some of the entrails.
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不過我可以給你們看一點內部的構造。
我著重的是
07:18
But what I wanted to focus on is this type of population structure.
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這種族群結構圖。
這裡大約有一萬個程式。
07:22
There's about 10,000 programs sitting here.
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07:24
And all different strains are colored in different colors.
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每個種類都用不同顏色來分類。
07:27
And as you see here, there are groups that are growing on top of each other,
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你會發現族群間會相互掩蓋,
因為它們散播開來了。
07:31
because they are spreading.
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07:32
Any time there is a program that's better at surviving in this world,
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不論何時都有一個程式
較能夠在虛擬世界中存活下來,
07:36
due to whatever mutation it has acquired,
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因為經過突變的過程,
07:38
it is going to spread over the others and drive the others to extinction.
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這個程式將會蓋過其它群體甚至把它們趕盡殺絕。
在我接下來要放的影片裡你們可以觀察到這樣的變化。
07:42
So I'm going to show you a movie
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07:43
where you're going to see that kind of dynamic.
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這個實驗是從我們
07:46
And these kinds of experiments are started with programs that we wrote ourselves.
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自行開發的程式進行的。
我們寫了程式, 然後進行複製,
07:50
We write our own stuff, replicate it, and are very proud of ourselves.
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我們對此感到非常驕傲。
07:53
And we put them in, and what you see immediately
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我們把程式放到系統裡,
07:56
is that there are waves and waves of innovation.
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就成了你現在看到不斷變動的波形。
07:59
By the way, this is highly accelerated,
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順便提一下,這段影片是加快播放,
08:01
so it's like a 1000 generations a second.
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所以變化的速度大約是一秒衍生一千次。
08:03
But immediately, the system goes like, "What kind of dumb piece of code was this?
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很快系統就有了改變,
「這究竟是什麼蠢代碼呢?
08:07
This can be improved upon in so many ways, so quickly."
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這可以藉由很多種方法
快速獲得改善。」
08:11
So you see waves of new types taking over the other types.
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你可以看到新種類
取代其它種類的過程。
08:15
And this type of activity goes on for quite a while,
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這樣子的過程會持續一段時間,
08:17
until the main easy things have been acquired by these programs.
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直到這些程式把大多數單純的結構納入為止。
08:22
And then, you see sort of like a stasis coming on
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接下來系統會面臨停滯期,
08:26
where the system essentially waits
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系統在等待一個
08:28
for a new type of innovation, like this one,
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全新的轉變,就像這樣。
08:31
which is going to spread over all the other innovations that were before
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它將會覆蓋
先前所有的變化
08:35
and is erasing the genes that it had before,
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並且消滅之前所有的基因,
08:38
until a new type of higher level of complexity has been achieved.
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直到系統演化到更具複雜性的層面。
08:42
And this process goes on and on and on.
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這個過程會不斷重複上演。
08:45
So what we see here
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所以我們在這看到的
08:47
is a system that lives in very much the way we're used to how life goes.
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就是一個與我們熟悉的
生命形式雷同的系統。
08:51
But what the NASA people had asked me really was,
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但NASA官員問我的是
「這些玩意兒
08:56
"Do these guys have a biosignature?
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有生命跡象嗎?」
08:59
Can we measure this type of life?
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我們可不可以衡量這樣的生命形式?
09:01
Because if we can,
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因為如果我們可以,
09:02
maybe we have a chance of actually discovering life somewhere else
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也許我們就能以客觀角度
09:06
without being biased by things like amino acids."
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證實其它星球有生命存在,
而不需靠胺基酸來判別。」
09:10
So I said, "Well, perhaps we should construct a biosignature
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我說:「我們必須建立一個
生命跡象,
09:15
based on life as a universal process.
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並假設所有生命都會經歷一個共通的過程。
09:18
In fact, it should perhaps make use of the concepts that I developed
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實際上,這必須應用我
開發的概念來達成,
得以了解
09:23
just in order to sort of capture what a simple living system might be."
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一個簡單的生命體系如何運作。」
為了解釋我想到的方法--
09:27
And the thing I came up with --
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09:28
I have to first give you an introduction about the idea,
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首先我得介紹一個概念,
09:32
and maybe that would be a meaning detector,
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或許這概念是個存在探測器,
而不是生命探測器。
09:36
rather than a life detector.
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09:38
And the way we would do that --
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我們的做法就是--
09:40
I would like to find out how I can distinguish text
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先辨認出一段文字,
09:42
that was written by a million monkeys, as opposed to text that is in our books.
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是由一百萬隻猴子聯合寫出來的,
還是從我們平常看的書籍中節錄出來的。
09:47
And I would like to do it in such a way
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我會這樣處理,
09:49
that I don't actually have to be able to read the language,
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我不需要看懂這段文字的語言,
因為我知道我根本辦不到。
09:52
because I'm sure I won't be able to.
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但只要我可以認出其中有的是字母。
09:54
As long as I know that there's some sort of alphabet.
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這是一張次數分配圖,
09:57
So here would be a frequency plot
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告訴你在這段
09:59
of how often you find each of the 26 letters of the alphabet
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由猴群隨機寫出來的文字裡
10:02
in a text written by random monkeys.
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其中26個字母出現的次數。
10:05
And obviously, each of these letters comes off about roughly equally frequent.
202
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顯然這些字母
出現的頻率大約相等。
但是如果你看到的是一段英文段落的字母次數分配,
10:10
But if you now look at the same distribution in English texts,
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10:13
it looks like that.
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就會長成這樣。
10:15
And I'm telling you, this is very robust across English texts.
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而且這種現象在英文裡非常明顯。
如果是法語就會不太一樣,
10:19
And if I look at French texts, it looks a little bit different,
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甚至是義大利文或德文。
10:22
or Italian or German.
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各種語言都有獨特的次數分配模式,
10:23
They all have their own type of frequency distribution,
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但是結果都很一致。
10:26
but it's robust.
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不管內容是有關政治或科學。
10:28
It doesn't matter whether it writes about politics or about science.
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3207
還是一首詩,
10:31
It doesn't matter whether it's a poem or whether it's a mathematical text.
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甚至是一段數學式子。
都有一個明顯的特徵,
10:37
It's a robust signature,
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而且非常穩定。
10:39
and it's very stable.
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1820
10:40
As long as our books are written in English --
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2157
只要我們的書籍是用英文寫的--
因為人們會不斷重寫並抄寫書籍--
10:43
because people are rewriting them and recopying them --
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10:45
it's going to be there.
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就會產生這個特徵。
10:47
So that inspired me to think about, well, what if I try to use this idea
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這讓我想到
如果我用這個概念,
不是為了要從有意義的文章中
10:53
in order, not to detect random texts from texts with meaning,
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挑出雜亂無章的文字,
10:56
but rather detect the fact that there is meaning
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而是探測
11:00
in the biomolecules that make up life.
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形成生命體的生物分子特徵。
但首先我有個問題:
11:03
But first I have to ask:
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11:04
what are these building blocks,
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這些組成的基本單位是什麼? 就像我剛給你們看的字母。
11:05
like the alphabet, elements that I showed you?
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事實證明,我們有很多種選擇
11:08
Well it turns out, we have many different alternatives
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可用來做為構成的基礎。
11:11
for such a set of building blocks.
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2314
我們能利用胺基酸,
11:13
We could use amino acids,
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1248
11:14
we could use nucleic acids, carboxylic acids, fatty acids.
227
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3202
核酸、羧酸或不飽和脂肪酸。
11:17
In fact, chemistry's extremely rich, and our body uses a lot of them.
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3438
事實上化學物質存在相當廣泛,我們人體就充滿許多化學物質。
所以,為了試驗這個想法,
11:21
So that we actually, to test this idea,
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11:23
first took a look at amino acids and some other carboxylic acids.
230
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3547
我們研究了胺基酸和其他的羧酸。
這就是結果。
11:27
And here's the result.
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1471
11:28
Here is, in fact, what you get
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事實上,
11:31
if you, for example, look at the distribution of amino acids
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譬如, 如果你觀察一個彗星或星際空間,
11:34
on a comet or in interstellar space or, in fact, in a laboratory,
234
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4735
或者一個實驗室裡
所充斥的胺基酸,
11:39
where you made very sure that in your primordial soup,
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2659
但必須保證在原生湯裡
沒有任何生命存在。
11:42
there is no living stuff in there.
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1918
你能找到的大部分是甘氨酸和丙氨酸,
11:44
What you find is mostly glycine and then alanine
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還有一些其它的元素。
11:47
and there's some trace elements of the other ones.
238
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2359
11:49
That is also very robust --
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這個結果也相當明顯--
11:52
what you find in systems like Earth
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你可以在地球的生態系統裡
11:55
where there are amino acids, but there is no life.
241
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找到胺基酸
但是沒有生命。
11:59
But suppose you take some dirt and dig through it
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但假設你採集一些土壤
在裡面找尋一番
12:03
and then put it into these spectrometers,
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放到光譜儀下,
12:06
because there's bacteria all over the place;
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因為土壤佈滿了細菌;
12:08
or you take water anywhere on Earth,
245
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或者是你取地球上任何一處的水,
因為水裡富含生命,
12:11
because it's teaming with life,
246
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1517
12:12
and you make the same analysis;
247
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然後你做一樣的分析;
12:14
the spectrum looks completely different.
248
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光譜結果會截然不同。
當然結果仍然含有甘氨酸和丙氨酸,
12:17
Of course, there is still glycine and alanine,
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12:20
but in fact, there are these heavy elements, these heavy amino acids,
250
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但是更重要的因素是大量的胺基酸,
12:23
that are being produced because they are valuable to the organism.
251
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3395
因而大量產生,
因為胺基酸對有機體而言非常重要。
而那些二十個以外
12:28
And some other ones that are not used in the set of 20,
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的沒被用的,
在任何情況下,
12:32
they will not appear at all in any type of concentration.
253
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則毫無出現的可能。
12:35
So this also turns out to be extremely robust.
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這個結果極為顯著。
12:37
It doesn't matter what kind of sediment you're using to grind up,
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不管你是要研磨哪種沙土,
不管是細菌或是動植物。
12:41
whether it's bacteria or any other plants or animals.
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到處都有生命存在,
12:44
Anywhere there's life,
257
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12:45
you're going to have this distribution,
258
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1951
你會得到這個分配圖,
12:47
as opposed to that distribution.
259
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而不是無生物的分配圖。
12:49
And it is detectable not just in amino acids.
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不光是胺基酸可被探测。
12:52
Now you could ask:
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這時你可能會問:
12:54
Well, what about these Avidians?
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那Avidians呢?
Avidians是存在電腦世界裡的產物,
12:57
The Avidians being the denizens of this computer world
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13:00
where they are perfectly happy replicating and growing in complexity.
264
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它們在那快樂地繁殖成長。
13:03
So this is the distribution that you get if, in fact, there is no life.
265
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這就是Avida的分配圖,
假設Avida裡沒有生命存在。
13:08
They have about 28 of these instructions.
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圖裡有28種指令。
13:11
And if you have a system where they're being replaced one by the other,
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而且你如果可以創造一個供這些指令相互取代的系統,
彷彿是猴群在打字機上亂打字。
13:15
it's like the monkeys writing on a typewriter.
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則每一種指令
13:17
Each of these instructions appears with roughly the equal frequency.
269
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所出現的頻率會大約相等。
13:22
But if you now take a set of replicating guys
270
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但是如果是剛在影片裡出現的
會複製的玩意兒,
13:27
like in the video that you saw,
271
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看起來會像這樣。
13:29
it looks like this.
272
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有部分的指令
13:31
So there are some instructions
273
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1473
13:32
that are extremely valuable to these organisms,
274
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對於有機體相當重要,
所以這些指令的出現頻率相對會很高。
13:35
and their frequency is going to be high.
275
815413
1970
13:37
And there's actually some instructions that you only use once, if ever.
276
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不過也有一些指令
只出現過一次。
13:41
So they are either poisonous
277
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它們不是有毒
13:43
or really should be used at less of a level than random.
278
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4505
不然就是使用上必須低於隨機的水平。
13:47
In this case, the frequency is lower.
279
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這種情況下出現頻率會比較低。
那麼我們現在所看到的算是一個明顯的指標嗎?
13:51
And so now we can see, is that really a robust signature?
280
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2671
13:53
I can tell you indeed it is,
281
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我可以告訴你的確是,
13:55
because this type of spectrum, just like what you've seen in books,
282
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3248
因為這種分配型態,如同你剛看到的書,
13:58
and just like what you've seen in amino acids,
283
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2153
還有胺基酸的例子,
14:00
it doesn't really matter how you change the environment,
284
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不管你怎麼改變環境,特徵就是這麼明顯;
14:03
it's very robust, it's going to reflect the environment.
285
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2624
並且會反映出環境的特色。
我現在要給你們看一個我們做的實驗。
14:06
So I'm going to show you now a little experiment that we did.
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我得解釋一下,
14:09
And I have to explain to you,
287
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這張圖表的上方
14:10
the top of this graph
288
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1182
14:11
shows you that frequency distribution that I talked about.
289
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2744
指的是我剛講到的頻率分配。
14:14
Here, that's the lifeless environment
290
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3807
事實上,這是個無生命的環境,
每種指令出現的頻率
14:18
where each instruction occurs at an equal frequency.
291
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3412
都相等。
下面的圖表
14:22
And below there, I show, in fact, the mutation rate in the environment.
292
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4993
代表環境的突變率。
14:27
And I'm starting this at a mutation rate that is so high
293
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3303
我把一開始的突變率調得很高,
14:30
that even if you would drop a replicating program
294
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高到就算你
放入一個會
14:34
that would otherwise happily grow up to fill the entire world,
295
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4125
快速成長的複製程式,
然後佈滿整個空間,
當你把程式放進去時,它會立刻突變至死。
14:39
if you drop it in, it gets mutated to death immediately.
296
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3010
14:42
So there is no life possible at that type of mutation rate.
297
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5346
在這種突變率之下
沒有任何生命能夠存活。
14:47
But then I'm going to slowly turn down the heat, so to speak,
298
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4036
但是接下來我要把突變率降低,
14:51
and then there's this viability threshold
299
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2185
到一個適當的程度,
14:53
where now it would be possible for a replicator to actually live.
300
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3892
如此一來就有一個複製體
能夠存活。
14:57
And indeed, we're going to be dropping these guys into that soup all the time.
301
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5345
然後我們要把這些玩意兒
放到原生湯裡。
看看會發生什麼事。
15:03
So let's see what that looks like.
302
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一開始沒有事情發生。一點都沒有。
15:05
So first, nothing, nothing, nothing.
303
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然後發生劇烈的變化。
15:08
Too hot, too hot.
304
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1815
15:09
Now the viability threshold is reached,
305
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2296
現在已經達到可行數值
15:12
and the frequency distribution has dramatically changed
306
912260
4492
以及頻率分配。
一開始發生劇烈變化, 然後, 事實上, 緩和下來。
15:16
and, in fact, stabilizes.
307
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1476
接著我就很邪惡的
15:18
And now what I did there
308
918276
1510
15:19
is, I was being nasty, I just turned up the heat again and again.
309
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3598
把溫度一再再調高。
當然它就能達到可行數值。
15:23
And of course, it reaches the viability threshold.
310
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2346
15:25
And I'm just showing this to you again because it's so nice.
311
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這實在是太讚了,所以我要再放一次給你們看。
15:28
You hit the viability threshold.
312
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1542
一旦降到可行數值
15:30
The distribution changes to "alive!"
313
930260
1976
分配就變成「有生命的, 萬歲!」。
15:32
And then, once you hit the threshold
314
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3217
當點突變率
15:35
where the mutation rate is so high that you cannot self-reproduce,
315
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4049
回升到可行數值
就不能自我複製,
也不能將信息
15:40
you cannot copy the information forward to your offspring
316
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4921
毫無錯誤地
15:44
without making so many mistakes that your ability to replicate vanishes.
317
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4730
傳給後代,
因此複製能力就消失了。
15:49
And then, that signature is lost.
318
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代表生命指標也消失了。
我們從中學到了什麼?
15:53
What do we learn from that?
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15:54
Well, I think we learn a number of things from that.
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我認為我們學到了幾個重點。
15:58
One of them is,
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第一,
16:00
if we are able to think about life in abstract terms --
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如果我們能夠
以抽象的定義來思考生命--
16:05
and we're not talking about things like plants,
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我們不提植物,
不提胺基酸,
16:08
and we're not talking about amino acids,
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也不提細菌,
16:10
and we're not talking about bacteria,
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16:11
but we think in terms of processes --
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而我們思考的是過程--
如此一來就能探討生命
16:14
then we could start to think about life
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16:16
not as something that is so special to Earth,
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不限於地球特有的生命,
16:18
but that, in fact, could exist anywhere.
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而是, 任何地方都可能有生物的存在。
16:21
Because it really only has to do with these concepts of information,
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因為它只跟這些
儲存訊息的
16:25
of storing information within physical substrates --
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概念有關,
在物質基底之內--
16:29
anything: bits, nucleic acids, anything that's an alphabet --
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可以是任何東西: 位元組、核酸,
任何可當成跟字母一樣的單位--
16:33
and make sure that there's some process
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並且確保能有一個
16:35
so that this information can be stored for much longer than you would expect --
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遠比你預期的時間還要長,
不被時間比例影響信息衰退,
可讓信息儲存起來的程序。
16:40
the time scales for the deterioration of information.
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如果條件都滿足,
16:44
And if you can do that, then you have life.
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就算是生命。
16:47
So the first thing that we learn
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所以我們學到的第一件事就是
16:49
is that it is possible to define life in terms of processes alone,
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生命可以單獨
依照程序來定義,
16:55
without referring at all to the type of things that we hold dear,
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無須借助
其它我們重視的東西,
例如地球的生命型式。
17:00
as far as the type of life on Earth is.
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17:02
And that, in a sense, removes us again,
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這個結論又一次
17:05
like all of our scientific discoveries, or many of them --
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就像所有的科學發現一樣--
17:08
it's this continuous dethroning of man --
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再度證明了
我們的存在並沒有那麼獨特。
17:11
of how we think we're special because we're alive.
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17:13
Well, we can make life; we can make life in the computer.
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我們能夠製造生命,在電腦裡頭製造生命。
17:16
Granted, it's limited,
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當然, 這的確是有限的,
17:18
but we have learned what it takes in order to actually construct it.
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不過我們藉此了解到
架構生命的要素。
17:23
And once we have that,
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一旦我們有了這些要素,
17:26
then it is not such a difficult task anymore
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創造生命便不再是難事,
17:29
to say, if we understand the fundamental processes
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如果我們能掌握基本的過程
17:33
that do not refer to any particular substrate,
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而不透過任何特殊基底,
17:36
then we can go out and try other worlds,
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我們就能走出現有的框架
探索地球以外的世界,
17:40
figure out what kind of chemical alphabets might there be,
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了解那裏會有什麼樣的化學元素符號,
認識普遍的化學物質,
17:45
figure enough about the normal chemistry, the geochemistry of the planet,
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還有該星球的地球科學,
如此一來我們便能了解
17:50
so that we know what this distribution would look like in the absence of life,
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沒有生命存在的分配型態會如何呈現,
17:53
and then look for large deviations from this --
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然後利用分配型態找到一些特例--
17:56
this thing sticking out, which says, "This chemical really shouldn't be there."
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因為偏離值能凸顯出:
「這個化學物質不應該在那裏出現」。
18:01
Now we don't know that there's life then,
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我們現在不確定那裏是否有生命存在,
18:03
but we could say,
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但至少,
18:05
"Well at least I'm going to have to take a look very precisely at this chemical
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「我會仔細研究這個化學物質
18:08
and see where it comes from."
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辨識出它是從哪而來」。
這也許會成為
18:11
And that might be our chance of actually discovering life
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我們發現新生命的機會,
18:14
when we cannot visibly see it.
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即使我們不能看見生命的形體。
18:16
And so that's really the only take-home message that I have for you.
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這便是我要給你們唯一的
重要結論。
18:21
Life can be less mysterious than we make it out to be
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當我們知道其他星球也存在生命,
生命就沒有
18:25
when we try to think about how it would be on other planets.
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我們想像中的那般神祕了。
18:29
And if we remove the mystery of life,
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如果我們能夠揭開生命神祕的面紗,
18:32
then I think it is a little bit easier for us to think about how we live,
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那對我來說,
要思考我們如何生存,
18:37
and how perhaps we're not as special as we always think we are.
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以及我們不是那麼獨特這類的議題,就不再是難事。
18:40
And I'm going to leave you with that.
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我要把這部分留給你們去想。
謝謝大家。
18:43
And thank you very much.
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18:44
(Applause)
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(鼓掌聲)
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