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