So let me with start with Roy Amara. Roy's argument is that most new technologies tend to be overestimated in their impact to begin with, and then they get underestimated in the long term because we get used to them.
讓我從羅伊·阿馬拉說起。 羅伊的論點是,大多數的新技術 一開始的影響力往往被高估了, 之後,時間久了, 它們的影響力就會被低估, 因為我們已經習以為常。
These really are days of miracle and wonder. You remember that wonderful song by Paul Simon? There were two lines in it. So what was it that was considered miraculous back then? Slowing down things -- slow motion -- and the long-distance call. Because, of course, you used to get interrupted by operators who'd tell you, "Long distance calling. Do you want to hang up?" And now we think nothing of calling all over the world. Well, something similar may be happening with reading and programming life.
「這真是充滿奇蹟和驚奇的日子。」 各位還記得保羅·賽門的 這首好歌嗎? 裡面有兩句歌詞。 所以,在那個年代, 哪些事情會被視為是奇蹟呢? 讓事物慢下來的——慢動作—— 以及長途電話。 沒錯,因為過去的你 經常被接線生打斷, 他會告訴你:「長途電話喔, 您要先掛斷嗎?」 如今,與世界各地通話 我們已經習以為常。 是的,也許類似的事情也正發生在 生命密碼的解讀與編程上。
But before I unpack that, let's just talk about telescopes. Telescopes were overestimated originally in their impact. This is one of Galileo's early models. People thought it was just going to ruin all religion.
但在我解說之前, 我們先來談談望遠鏡。 望遠鏡的影響力一開始被高估了。 這是伽利略早期的款式之一。 大家以為它會毀掉所有宗教。
(Laughter)
(笑聲)
So we're not paying that much attention to telescopes. But, of course, telescopes launched 10 years ago, as you just heard, could take this Volkswagen, fly it to the moon, and you could see the lights on that Volkswagen light up on the moon. And that's the kind of resolution power that allowed you to see little specks of dust floating around distant suns. Imagine for a second that this was a sun a billion light years away, and you had a little speck of dust that came in front of it. That's what detecting an exoplanet is like. And the cool thing is, the telescopes that are now being launched would allow you to see a single candle lit on the moon. And if you separated it by one plate, you could see two candles separately at that distance.
現在我們沒怎麼注意望遠鏡了。 不過,就如各位前幾天聽到的 十年前升空的(克卜勒)太空望遠鏡, 如果我們把這輛福斯汽車送到月球上, 你可透過那望遠鏡 看到福斯汽車車燈亮著。 其解析度能讓你看見 漂浮在遙遠太陽周邊的小黑點。 想像這是十億光年外的一顆恆星, 你可看到它前方的一個小塵埃。 偵測系外行星就是像這樣。 很酷的是,新近升空的望遠鏡 可以讓你看到在月球上 一根點著的蠟燭。 如果你放一個盤子在兩根蠟燭之間, 你可以從這麼遠的距離 分別看到兩根蠟燭。
And that's the kind of resolution that you need to begin to image that little speck of dust as it comes around the sun and see if it has a blue-green signature. And if it does have a blue-green signature, it means that life is common in the universe. The first time you ever see a blue-green signature on a distant planet, it means there's photosynthesis there, there's water there, and the chances that you saw the only other planet with photosynthesis are about zero. And that's a calendar-changing event. There's a before and after we were alone in the universe: forget about the discovery of whatever continent. So as you're thinking about this, we're now beginning to be able to image most of the universe. And that is a time of miracle and wonder. And we kind of take that for granted.
有了這樣的解析度, 你就可以開始成像 圍繞在太陽周邊的小塵埃, 看看是否有藍綠色的顏色。 如果確實有藍綠色的顏色, 就意味著,生命在宇宙中是普遍存在的。 你第一次在遠方的星球上 看到藍綠色的顏色, 就表示那裡有光合作用, 那裡有水, 除了地球外,你能在其它星球上 看到光合作用的可能性 幾乎是零。 那是個劃時代的事件, 區分「宇宙中是否獨存人類」的前後, 別再想發現什麼新大陸了。 當你們還在想這件事時, 我們現在已經可以 把大部分的宇宙成像出來。 這是充滿奇蹟和神奇的時代。 我們也視為理所當然了。
Something similar is happening in life. So we're hearing about life in these little bits and pieces. We hear about CRISPR, and we hear about this technology, and we hear about this technology. But the bottom line on life is that life turns out to be code. And life as code is a really important concept because it means, just in the same way as you can write a sentence in English or in French or Chinese, just in the same way as you can copy a sentence, just in the same way as you can edit a sentence, just in the same way as you can print a sentence, you're beginning to be able to do that with life. It means that we're beginning to learn how to read this language. And this, of course, is the language that is used by this orange.
類似的狀況也正發生在生命領域裡。 我們零零碎碎地聽到 關於生命的資訊。 我們聽說過 CRISPR 技術, 我們聽到這種技術, 我們聽到那種技術。 但生命的本質基本上就是編碼。 用編碼來看生命是個非常 重要的概念,因為它的意義 就像是你能夠寫出一段句子一樣, 不論是用英文、法文或中文, 就如同你可以複製一個句子一樣, 就像你可以編輯一個句子一樣, 就像你可以列印一個句子一樣, 你也開始可以對生命做同樣的事。 那就意味著,我們要開始學習 如何閱讀這種語言。 當然,這也是這顆柳橙的語言。
So how does this orange execute code? It doesn't do it in ones and zeroes like a computer does. It sits on a tree, and one day it does: plop! And that means: execute. AATCAAG: make me a little root. TCGACC: make me a little stem. GAC: make me some leaves. AGC: make me some flowers. And then GCAA: make me some more oranges.
所以,這顆柳橙如何執行程式? 它不能像電腦用 0 和 1 來執行。 它待在樹上,有一天它會 : 撲通掉下來! 那就是:執行。 AATCAAG 生根, TCGACC 開枝, GAC 生葉,AGC 開花, 然後 GCAA 長出更多的柳橙果實。
If I edit a sentence in English on a word processor, then what happens is you can go from this word to that word. If I edit something in this orange and put in GCAAC, using CRISPR or something else that you've heard of, then this orange becomes a lemon, or it becomes a grapefruit, or it becomes a tangerine. And if I edit one in a thousand letters, you become the person sitting next to you today. Be more careful where you sit.
如果我用文字處理軟體 來編輯一段英文句子, 就是從這個字改成那個字。 如果我在這顆柳橙裡動些手腳, 用 CRISPR 或其它 你聽過的工具把 GCAAC 放入, 這個柳橙就會變成檸檬, 或是變成葡萄柚, 或是變成橘子。 如果我編輯一千個字母中的一個, 你就會變成你身旁坐的那個人。 選座位的時候小心點。
(Laughter)
(笑聲)
What's happening on this stuff is it was really expensive to begin with. It was like long-distance calls. But the cost of this is dropping 50 percent faster than Moore's law. The first $200 full genome was announced yesterday by Veritas. And so as you're looking at these systems, it doesn't matter, it doesn't matter, it doesn't matter, and then it does.
事情是這樣的, 通常新的技術在一開始非常昂貴。 就像長途電話。 但它的成本降低的速度 比摩爾定律還要快 50%。 昨天 Veritas 公司首推 200 美元的完整基因組定序服務。 所以,當你在看這些系統, 它無所謂,它無所謂, 它無所謂,接著,它有所謂了。
So let me just give you the map view of this stuff. This is a big discovery. There's 23 chromosomes. Cool. Let's now start using a telescope version, but instead of using a telescope, let's use a microscope to zoom in on the inferior of those chromosomes, which is the Y chromosome. It's a third the size of the X. It's recessive and mutant. But hey, just a male. And as you're looking at this stuff, here's kind of a country view at a 400 base pair resolution level, and then you zoom in to 550, and then you zoom in to 850, and you can begin to identify more and more genes as you zoom in. Then you zoom in to the state level, and you can begin to tell who's got leukemia, how did they get leukemia, what kind of leukemia do they have, what shifted from what place to what place. And then you zoom in to the Google street view level. So this is what happens if you have colorectal cancer for a very specific patient on the letter-by-letter resolution.
讓我用地圖的方式呈現給各位看。 這是一項大發現。 這裡有 23 對染色體。 很酷。 我們現在開始從望遠鏡的視角, 但不是使用望遠鏡, 而是用顯微鏡來放大 那些染色體中比較小的, 也就是 Y 染色體。 它的尺寸只有 X 的三分之一, 它是隱性的、突變的。 但,嘿, 只是個男性罷了。 看這個, 這像是在看整個國家, 以 400 個鹼基對的解析度來看, 然後你放大到 550 個解析度, 然後你放大到 850 個解析度, 在你放大時,你就可以 開始識別越來越多的基因。 然後你放大到州的大小, 你可以開始識別出誰有白血病, 他們是怎麼得到白血病, 那是什麼樣的白血病, 從什麼地方轉移到什麼地方。 然後你放大到像是 Google 街景的大小。 這就是你從某個患有 結直腸癌病人身上, 以字母解析度級別所看到的狀況。
So what we're doing in this stuff is we're gathering information and just generating enormous amounts of information. This is one of the largest databases on the planet and it's growing faster than we can build computers to store it. You can create some incredible maps with this stuff. You want to understand the plague and why one plague is bubonic and the other one is a different kind of plague and the other one is a different kind of plague? Well, here's a map of the plague. Some are absolutely deadly to humans, some are not. And note, by the way, as you go to the bottom of this, how does it compare to tuberculosis? So this is the difference between tuberculosis and various kinds of plagues, and you can play detective with this stuff, because you can take a very specific kind of cholera that affected Haiti, and you can look at which country it came from, which region it came from, and probably which soldier took that from that African country to Haiti.
我們在這個方面做的是在收集訊息, 以及生成非常大量的訊息。 這是世界上最大的數據庫之一, 而且它增長的速度比 我們建造電腦來存儲它還更快。 你可以用這些資料 創造出不可思議的地圖。 你想了解瘟疫,想了解為什麼 這個瘟疫是腺鼠疫, 另一個是不同的瘟疫, 另一個又是不同的瘟疫? 這就是瘟疫的地圖。 有些對人類絕對致命,有些則否。 順便說一下, 當你追根究底要知道 它與結核病相比會如何呢? 所以這就是結核病 和各種瘟疫之間的區別。 你可以像個偵探去探究, 因為你可以拿一種特定的霍亂, 例如影響了海地的那種, 你可以看它來自哪個國家, 來自哪個地區, 以及可能是哪個士兵把那個霍亂 從那個非洲國家帶到海地。
Zoom out. It's not just zooming in. This is one of the coolest maps ever done by human beings. What they've done is taken all the genetic information they have about all the species, and they've put a tree of life on a single page that you can zoom in and out of. So this is what came first, how did it diversify, how did it branch, how large is that genome, on a single page. It's kind of the universe of life on Earth, and it's being constantly updated and completed.
現在遠看, 它不只能近看。 這是人類製作過的最酷的地圖之一。 他們把所有物種的全部遺傳信息 做成一株生命樹放在一頁上, 你可以放大和縮小。 看得到先是什麼,如何分化、分支, 該基因組有多大, 全部以一頁呈現。 像是地球上生命的宇宙, 一直不斷被更新和匯齊。
And so as you're looking at this stuff, the really important change is the old biology used to be reactive. You used to have a lot of biologists that had microscopes, and they had magnifying glasses and they were out observing animals. The new biology is proactive. You don't just observe stuff, you make stuff. And that's a really big change because it allows us to do things like this. And I know you're really excited by this picture.
所以當你看著這個, 真正重要的變化是 以前是被動的舊的生物學。 過去很多生物學家有顯微鏡, 他們也有放大鏡,會去觀察動物。 新的生物學要你主動出擊。 你不只觀察東西,還可以創造東西。 那是一個非常大的變化, 因為它使我們能夠做像這樣的事情。 而且我知道你真的 對這張照片感到很興奮。
(Laughter)
(笑聲)
It only took us four years and 40 million dollars to be able to take this picture.
我們花了四年時間和四千萬美元 才拍到這張照片。
(Laughter)
(笑聲)
And what we did is we took the full gene code out of a cell -- not a gene, not two genes, the full gene code out of a cell -- built a completely new gene code, inserted it into the cell, figured out a way to have the cell execute that code and built a completely new species. So this is the world's first synthetic life form.
我們做的是 把一個細胞的基因代碼抽取出來—— 不是一個基因,兩個基因,而是 一個細胞中的完整基因代碼 -- 建立了一個全新的基因代碼。 再將它植入細胞中, 找出一個可以讓細胞 執行該代碼的方法, 然後就創造了一個全新的物種。 所以這是世界上第一個 合成的生命形式。
And so what do you do with this stuff? Well, this stuff is going to change the world. Let me give you three short-term trends in terms of how it's going to change the world.
那你能用這個技術做什麼呢? 好吧,這個技術將會改變世界。 讓我告訴你們三個短期趨勢, 理解它將如何改變世界。
The first is we're going to see a new industrial revolution. And I actually mean that literally. So in the same way as Switzerland and Germany and Britain changed the world with machines like the one you see in this lobby, created power -- in the same way CERN is changing the world, using new instruments and our concept of the universe -- programmable life forms are also going to change the world because once you can program cells in the same way as you program your computer chip, then you can make almost anything.
首先,我們將看到 一場新的工業革命。 我說的是真的,不誇張。 所以就像瑞士、德國和英國 用你在大廳看到的機器 改變了世界一樣, 創造能量。 與歐洲核子研究中心 一樣的方式正在改變世界, 使用新儀器和我們對宇宙的概念。 可編程的生命形式也將改變世界, 因為一旦你可以編程細胞 和你編程電腦晶片一樣, 你幾乎可以做出任何東西。
So your computer chip can produce photographs, can produce music, can produce film, can produce love letters, can produce spreadsheets. It's just ones and zeroes flying through there. If you can flow ATCGs through cells, then this software makes its own hardware, which means it scales very quickly. No matter what happens, if you leave your cell phone by your bedside, you will not have a billion cell phones in the morning. But if you do that with living organisms, you can make this stuff at a very large scale. One of the things you can do is you can start producing close to carbon-neutral fuels on a commercial scale by 2025, which we're doing with Exxon. But you can also substitute for agricultural lands. Instead of having 100 hectares to make oils or to make proteins, you can make it in these vats at 10 or 100 times the productivity per hectare. Or you can store information, or you can make all the world's vaccines in those three vats. Or you can store most of the information that's held at CERN in those three vats. DNA is a really powerful information storage device.
你的電腦晶片可以製作照片、 製作音樂、製作電影、 製作情書以及製作電子表格。 其運作原理就是一些 1 和 0 在晶片裡飛來飛去 。 如果你可以讓 ATCG 在細胞中流通, 這個軟件就可以製作自己的硬體, 這意味著它擴展的速度非常快。 無論發生了什麼, 如果你將手機放在你的床邊, 你在早上不會有十億支手機。 但如果你用活的生物體, 你可以大量製造。 一件你可以在 2025 年以前做的事 就是以商業規模生產 接近碳中性的燃料。 那是我們和埃克森美孚石油公司 正在合作進行的。 你也可以用它來取代農田。 不是用 100 公頃的土地 來製油或蛋白質, 你可以在這些大桶裡做, 以每公頃 10 到 100 倍的產量來生產。 你可以存儲資訊 或製作世界上所有的疫苗, 就在那三個大桶裡。 或者在那三個大桶裡存儲 歐洲核子研究中心的大部分資料。 DNA 真的是很強大訊息存儲設備。
Second turn: you're beginning to see the rise of theoretical biology. So, medical school departments are one of the most conservative places on earth. The way they teach anatomy is similar to the way they taught anatomy 100 years ago. "Welcome, student. Here's your cadaver." One of the things medical schools are not good at is creating new departments, which is why this is so unusual. Isaac Kohane has now created a department based on informatics, data, knowledge at Harvard Medical School. And in a sense, what's beginning to happen is biology is beginning to get enough data that it can begin to follow the steps of physics, which used to be observational physics and experimental physicists, and then started creating theoretical biology. Well, that's what you're beginning to see because you have so many medical records, because you have so much data about people: you've got their genomes, you've got their viromes, you've got their microbiomes. And as this information stacks, you can begin to make predictions.
第二個趨勢是: 你會開始看到理論生物學的崛起。 所以,醫學院系是 地球上最保守的地方之一。 他們教解剖學的方式 和 100 年前他們 教解剖學的方式相似。 「歡迎,同學,這是你的屍體。」 醫學院不擅長創建新部門, 這是為什麼它很少見的原因。 艾薩克·寇韓現在已經在哈佛醫學院 創建了一個基於訊息學、 數據和知識的部門。 從某種意義上,開始要發生的是 生物學開始會獲得足夠的數據 可以開始追隨物理學發展的步伐, 物理學曾經是「觀測」物理 和「實驗」物理, 然後開始創建理論生物學。 這就是你即將會看到的, 因為你有這麼多的病歷紀錄, 因為你所擁有的 有關人的數據如此之多: 有他們的基因組,有他們的病毒, 有他們的微生物群。 而從這個訊息庫, 你就可以開始做預測。
The third thing that's happening is this is coming to the consumer. So you, too, can get your genes sequenced. And this is beginning to create companies like 23andMe, and companies like 23andMe are going to be giving you more and more and more data, not just about your relatives, but about you and your body, and it's going to compare stuff, and it's going to compare stuff across time, and these are going to become very large databases.
第三件正在發生的是有關消費者的。 現在你也可以對自己的基因做定序了。 這類的服務會造就出 像 23andMe 這類的公司, 而像 23andMe 這類的公司 會給你越來越多的數據, 不只是有關你的親戚的訊息, 而且還有關於你和你的身體, 它會做比較, 而且它會與不同時間的資料做比較, 而這些將成為非常大的數據庫。
But it's also beginning to affect a series of other businesses in unexpected ways. Normally, when you advertise something, you really don't want the consumer to take your advertisement into the bathroom to pee on. Unless, of course, if you're IKEA. Because when you rip this out of a magazine and you pee on it, it'll turn blue if you're pregnant.
但它也會開始以意想不到的方式 影響到許多其他的行業。 通常,當你做廣告時, 你真的不希望消費者 拿你的廣告到浴室,在上面小便。 當然,除非你是宜家。 因為當你從一本雜誌上 撕下這個,然後你撒尿在上面, 如果你懷孕了,它會變成藍色。
(Laughter)
(笑聲)
And they'll give you a discount on your crib.
他們會給你嬰兒床的折扣。
(Laughter)
(笑聲)
Right? So when I say consumer empowerment, and this is spreading beyond biotech, I actually really mean that.
對嗎? 所以當我還在說消費者賦權時, 商人早已超越了生物技術, 我真心認為如此。
We're now beginning to produce, at Synthetic Genomics, desktop printers that allow you to design a cell, print a cell, execute the program on the cell. We can now print vaccines real time as an airplane takes off before it lands. We're shipping 78 of these machines this year. This is not theoretical biology. This is printing biology.
我們現在開始在 Synthetic Genomics 公司生產 桌上型打印機, 它可以讓你設計細胞、 列印細胞、 在細胞上執行程序。 我們現在可以即時, 在飛機起飛和降落其間, 完成疫苗的打印。 今年我們將生產 78 台這種機器。 這不是理論生物學。 這是印刷生物學。
Let me talk about two long-term trends that are coming at you over a longer time period. The first one is, we're starting to redesign species. And you've heard about that, right? We're redesigning trees. We're redesigning flowers. We're redesigning yogurt, cheese, whatever else you want. And that, of course, brings up the interesting question: How and when should we redesign humans? And a lot of us think, "Oh no, we never want to redesign humans." Unless, of course, if your child has a Huntington's gene and is condemned to death. Or, unless if you're passing on a cystic fibrosis gene, in which case, you don't just want to redesign yourself, you want to redesign your children and their children. And these are complicated debates and they're going to happen in real time.
我來談談兩個長期趨勢, 未來會慢慢地在你面前發生。 第一個是,我們開始重新設計物種。 你已經聽說過,對嗎? 我們正在重新設計樹木。 我們正在重新設計鮮花。 我們正在重新設計優格、 奶酪,無論你想要什麼。 那當然帶出了一個有趣的問題: 我們應該如何以及何時 重新設計人類呢? 我們很多人在想,「不! 我們永遠不要重新設計人類。」 當然,除非你的孩子 有亨丁頓舞蹈症的基因, 那等於被判死刑。 或者,你有囊性纖維化基因 可能會傳給下一代, 這時,你不只是想要重新設計自己, 你也會想重新設計你的孩子 和他們的孩子。 這些複雜的辯論未來都會發生。
I'll give you one current example. One of the debates going on at the National Academies today is you have the power to put a gene drive into mosquitoes so that you will kill all the malaria-carrying mosquitoes. Now, some people say, "That's going to affect the environment in an extreme way, don't do it." Other people say, "This is one of the things that's killing millions of people yearly. Who are you to tell me that I can't save the kids in my country?" And why is this debate so complicated? Because as soon as you let this loose in Brazil or in Southern Florida -- mosquitoes don't respect walls. You're making a decision for the world when you put a gene drive into the air.
我給你一個當前的例子。 當今國家科學院正辯論的議題之一是 能把一基因塞到蚊子身體裡 來消滅所有攜帶瘧疾的蚊子。 但是有些人說, 「這將會嚴重地影響環境, 不要這樣做。」 其他人說, 這是每年造成數百萬人 死亡的原因之一。 你憑什麼說 我不能拯救我國的小孩。」 為什麼這場辯論如此複雜呢? 因為只要在巴西釋出這種蚊子, 或釋在佛羅里達州南部, 蚊子可不管什麼牆。 釋出一個基因的決定 會影響整個世界。
This wonderful man won a Nobel Prize, and after winning the Nobel Prize he's been worrying about how did life get started on this planet and how likely is it that it's in other places? So what he's been doing is going around to this graduate students and saying to his graduate students, "Build me life but don't use any modern chemicals or instruments. Build me stuff that was here three billion years ago. You can't use lasers. You can't use this. You can't use that." He gave me a vial of what he's built about three weeks ago. What has he built? He's built basically what looked like soap bubbles that are made out of lipids. He's built a precursor of RNA. He's had the precursor of the RNA be absorbed by the cell and then he's had the cells divide. We may not be that far -- call it a decade, maybe two decades -- from generating life from scratch out of proto-communities.
這位出色的男子獲得諾貝爾獎。 在獲得諾貝爾獎後, 他一直在擔心 生命如何在這個星球上開始, 它在其它地方開始的 可能性有多大呢? 所以他一直對他的研究生說, 「幫我創造一些生命,但不要使用 任何現代化學品或儀器。 創造那些三十億年就存在的生命。 不能使用激光, 不能用這個,不能用那個。」 大約三個星期前, 他給了我一瓶他創造的東西。 他創造了什麼? 他的創造基本上看起來像 由脂質製成的肥皂泡。 他創造了前信使 RNA 。 讓前信使 RNA 被細胞吸收 然後讓細胞分裂。 我們可能在不久的將來, 或許十年,或許二十年, 自原始共同體中 從無到有製出生命來。
Second long-term trend: we've been living and are living through the digital age -- we're starting to live through the age of the genome and biology and CRISPR and synthetic biology -- and all of that is going to merge into the age of the brain. So we're getting to the point where we can rebuild most of our body parts, in the same way as if you break a bone or burn your skin, it regrows. We're beginning to learn how to regrow our tracheas or how to regrow our bladders. Both of those have been implanted in humans. Tony Atala is working on 32 different organs. But the core is going to be this, because this is you and the rest is just packaging. Nobody's going to live beyond 120, 130, 140 years unless if we fix this. And that's the most interesting challenge. That's the next frontier, along with: "How common is life in the universe?" "Where did we come from?" and questions like that.
第二個長期趨勢是: 我們已經和正在經歷數位時代, 開始經歷基因時代、 生物學、 CRISPR, 和合成生物學的年代, 所有這些都將融入大腦的年代。 我們即將進入可以重建 大部分身體部位的時期。 就像你斷了的骨頭 或燒傷的皮膚會再生, 我們開始學習 如何重新生出我們的氣管, 或如何重新生出我們的膀胱。 這兩個都已經被移植到人體。 托尼·阿塔拉正努力造出 32 種不同的器官。 但這才是核心, 因為核心是你,其餘的都只是包裝。 沒有人會活過120 歲、 130 歲或 140 年歲, 除非我們解決這個問題。 這是最有趣的挑戰。 這開疆拓土伴隨著: 「宇宙中的生命有多普遍呢?」 「我們從哪裡來?」 和像那樣的問題。
Let me end this with an apocryphal quote from Einstein.
讓我引述杜撰的 愛因斯坦話語來總結:
[You can live as if everything is a miracle, or you can live as if nothing is a miracle.]
【你可以把一切當奇蹟來活, 也可以無視任何奇蹟。】
It's your choice. You can focus on the bad, you can focus on the scary, and certainly there's a lot of scary out there. But use 10 percent of your brain to focus on that, or maybe 20 percent, or maybe 30 percent. But just remember, we really are living in an age of miracle and wonder. We're lucky to be alive today. We're lucky to see this stuff. We're lucky to be able to interact with folks like the folks who are building all the stuff in this room.
這是你的選擇。 你可以專注於壞事,可怕之事, 可怕之事的確存在。 但用你大腦的 10%、20% 或者 30% 來專注這個問題。 但請記住, 我們確實生活在 一個充滿奇蹟和神奇的時代。 我們有幸今天還能活著, 看到這些東西。 我們很幸運能夠 與這個房間裡那些正在建設 所有東西的人互動。
So thank you to all of you, for all you do.
謝謝你們所有人,和所做的一切。
(Applause)
(掌聲)