Abundance is our future | Peter Diamandis

491,306 views ・ 2012-03-01

TED


請雙擊下方英文字幕播放視頻。

譯者: Jesse Chen 陳鉦翰 審譯者: Wang-Ju Tsai
00:15
(Applause)
0
15260
3000
(掌聲)
00:18
(Video) Announcer: Threats, in the wake of Bin Laden's death, have spiked.
1
18260
3000
(賓拉登死後 威脅不斷竄出)
00:21
Announcer Two: Famine in Somalia. Announcer Three: Police pepper spray.
2
21260
2000
(索馬利亞的飢荒) (警方的胡椒噴霧)
00:23
Announcer Four: Vicious cartels. Announcer Five: Caustic cruise lines.
3
23260
2000
(企業的惡意壟斷) (嚴峻的航線)
00:25
Announcer Six: Societal decay. Announcer Seven: 65 dead.
4
25260
3000
(社會的腐敗) (六十五人死亡)
00:28
Announcer Eight: Tsunami warning. Announcer Nine: Cyberattacks.
5
28260
2000
(海嘯警報) (網路駭客攻擊)
00:30
Multiple Announcers: Drug war. Mass destruction. Tornado.
6
30260
2000
(毒品戰爭) (大規模毀滅) (龍捲風)
00:32
Recession. Default. Doomsday. Egypt. Syria.
7
32260
2000
(經濟衰退) (國家債務) (世界末日) (埃及) (敘利亞)
00:34
Crisis. Death. Disaster.
8
34260
2000
(危機) (死亡) (災難)
00:36
Oh, my God.
9
36260
3000
(喔!我的天啊)
00:39
Peter Diamandis: So those are just a few of the clips
10
39260
2000
彼得.戴曼迪斯:這些新聞只是我過去
00:41
I collected over the last six months --
11
41260
2000
六個月所蒐集的一小部分
00:43
could have easily been the last six days
12
43260
2000
有六天前的
00:45
or the last six years.
13
45260
2000
也有六年前的新聞
00:47
The point is that the news media
14
47260
2000
重點是新聞媒體
00:49
preferentially feeds us negative stories
15
49260
3000
喜歡報導負面新聞
00:52
because that's what our minds pay attention to.
16
52260
3000
因為這類的新聞能吸引大家注意
00:55
And there's a very good reason for that.
17
55260
2000
這有理由可以解釋
00:57
Every second of every day,
18
57260
2000
每天的每分每秒
00:59
our senses bring in way too much data
19
59260
2000
我們的感官接收了太多資訊
01:01
than we can possibly process in our brains.
20
61260
3000
超過了我們大腦的負荷
01:04
And because nothing is more important to us
21
64260
2000
而且對我們來說沒有任何東西
01:06
than survival,
22
66260
2000
是比活著更重要的
01:08
the first stop of all of that data
23
68260
2000
我們接收訊息的第一站
01:10
is an ancient sliver of the temporal lobe
24
70260
2000
是一個在「顳葉」(腦葉之一)中的古老小裂片
01:12
called the amygdala.
25
72260
2000
稱為「扁桃體」
01:14
Now the amygdala is our early warning detector,
26
74260
3000
扁桃體是我們身體最初期的
01:17
our danger detector.
27
77260
2000
警告和危險偵測系統
01:19
It sorts and scours through all of the information
28
79260
3000
它整理、搜尋所有訊息
01:22
looking for anything in the environment that might harm us.
29
82260
3000
偵測環境中任何對我們有害的物質
01:25
So given a dozen news stories,
30
85260
2000
所以在眾多的新聞中
01:27
we will preferentially look
31
87260
2000
我們會偏好於
01:29
at the negative news.
32
89260
2000
負面的新聞
01:31
And that old newspaper saying,
33
91260
2000
曾有一個新聞業界的格言說
01:33
"If it bleeds it leads,"
34
93260
2000
「有血才會賣」
01:35
is very true.
35
95260
2000
一點也沒錯
01:37
So given all of our digital devices
36
97260
3000
我們從各種數位設備
01:40
that are bringing all the negative news to us
37
100260
2000
接收各種負面的新聞
01:42
seven days a week, 24 hours a day,
38
102260
3000
一個禮拜七天、一天24小時毫無間斷
01:45
it's no wonder that we're pessimistic.
39
105260
2000
這也難怪我們這麼悲觀
01:47
It's no wonder that people think
40
107260
2000
難怪人們想的都是
01:49
that the world is getting worse.
41
109260
4000
世界越來越沒希望
01:53
But perhaps that's not the case.
42
113260
3000
但這也許不是事實
01:56
Perhaps instead,
43
116260
2000
這或許是
01:58
it's the distortions brought to us
44
118260
2000
媒體帶給我們
02:00
of what's really going on.
45
120260
3000
對現今新聞的偏見
02:03
Perhaps the tremendous progress we've made
46
123260
2000
也許我們在上個世紀
02:05
over the last century
47
125260
2000
藉由一連串的努力
02:07
by a series of forces
48
127260
2000
創造的大幅進步
02:09
are, in fact, accelerating to a point
49
129260
3000
事實上已帶給我們現在的優勢
02:12
that we have the potential in the next three decades
50
132260
3000
在未來三十年是有潛力
02:15
to create a world of abundance.
51
135260
3000
去創造一個富足的世界
02:18
Now I'm not saying
52
138260
2000
我不是說
02:20
we don't have our set of problems --
53
140260
2000
我們沒有以下一連串的問題:
02:22
climate crisis, species extinction,
54
142260
2000
『氣候危機、物種滅絕、
02:24
water and energy shortage -- we surely do.
55
144260
3000
水源和能源匱乏』這些問題是存在的
02:27
And as humans, we are far better
56
147260
2000
身為人類,我們好多了
02:29
at seeing the problems way in advance,
57
149260
3000
我們早就看到這些問題的產生
02:32
but ultimately we knock them down.
58
152260
4000
但最後我們仍解決了這些問題
02:36
So let's look
59
156260
2000
我們來看看
02:38
at what this last century has been
60
158260
2000
上個世紀到底發生了什麼事
02:40
to see where we're going.
61
160260
2000
而接下來會把我們帶到哪去
02:42
Over the last hundred years,
62
162260
2000
過去一百多年以來
02:44
the average human lifespan has more than doubled,
63
164260
3000
人類的平均壽命成長了兩倍以上
02:47
average per capita income adjusted for inflation
64
167260
3000
經過調整通膨的各國平均國民所得
02:50
around the world has tripled.
65
170260
2000
也成長了三倍以上
02:52
Childhood mortality
66
172260
2000
兒童死亡率
02:54
has come down a factor of 10.
67
174260
2000
也下降到為原來的十分之一
02:56
Add to that the cost of food, electricity,
68
176260
2000
再加上糧食、電能、
02:58
transportation, communication
69
178260
2000
交通、通訊的花費
03:00
have dropped 10 to 1,000-fold.
70
180260
4000
也變成以前的十分之一到千分之一
03:04
Steve Pinker has showed us
71
184260
2000
史迪芬.平克(實驗心理學家)告訴我們
03:06
that, in fact, we're living during the most peaceful time ever
72
186260
3000
我們現在生活的世代
03:09
in human history.
73
189260
2000
是人類史上最和平的一段時間
03:11
And Charles Kenny
74
191260
2000
而查爾斯.肯尼(作家)說
03:13
that global literacy has gone from 25 percent to over 80 percent
75
193260
3000
過去130年,我們的全球識字率
03:16
in the last 130 years.
76
196260
3000
也從25%上升到80%
03:19
We truly are living in an extraordinary time.
77
199260
4000
我們真的生活在一個黃金時期
03:23
And many people forget this.
78
203260
2000
但很多人都忘了這個
03:25
And we keep setting our expectations higher and higher.
79
205260
3000
我們不斷把期望設的越來越高
03:28
In fact, we redefine what poverty means.
80
208260
3000
事實上我們重寫了貧窮的定義
03:31
Think of this, in America today,
81
211260
2000
想想看現今的美國
03:33
the majority of people under the poverty line
82
213260
3000
在貧窮線以下的大多數人
03:36
still have electricity, water, toilets, refrigerators,
83
216260
3000
卻還擁有水、電、馬桶、冰箱、
03:39
television, mobile phones,
84
219260
2000
電視、手機、
03:41
air conditioning and cars.
85
221260
3000
甚至是冷氣和車子
03:44
The wealthiest robber barons of the last century, the emperors on this planet,
86
224260
3000
上個世紀最富有的強盜貴族、各國的帝王
03:47
could have never dreamed of such luxuries.
87
227260
3000
根本想不到會有這種奢侈品
03:53
Underpinning much of this
88
233260
3000
鞏固這種現象的
03:56
is technology,
89
236260
2000
是科技
03:58
and of late,
90
238260
2000
是最近以來
04:00
exponentially growing technologies.
91
240260
2000
快速發展的科技做出的貢獻
04:02
My good friend Ray Kurzweil
92
242260
2000
我的好朋友 雷.庫茨魏爾(科學家)說
04:04
showed that any tool that becomes an information technology
93
244260
3000
任何變成資訊科技的工具
04:07
jumps on this curve, on Moore's Law,
94
247260
3000
都躍上了這個摩爾定律曲線
04:10
and experiences price performance doubling
95
250260
2000
感受科技行情在每一年
04:12
every 12 to 24 months.
96
252260
3000
或每兩年的雙倍成長
04:15
That's why the cellphone in your pocket
97
255260
2000
這就是為什麼你們口袋裡的手機
04:17
is literally a million times cheaper and a thousand times faster
98
257260
2000
比起70年代的超級電腦
04:19
than a supercomputer of the '70s.
99
259260
2000
還要更便宜、更快速了幾百萬倍
04:21
Now look at this curve.
100
261260
2000
請看這個曲線
04:23
This is Moore's Law over the last hundred years.
101
263260
2000
這是一百多年前的摩爾定律
04:25
I want you to notice two things from this curve.
102
265260
2000
我要你注意這曲線上的兩個東西
04:27
Number one, how smooth it is --
103
267260
4000
第一,它是十分平穩的曲綫
04:31
through good time and bad time, war time and peace time,
104
271260
3000
曲線穿越過好時期和壞時期、戰爭時期和和平時期、
04:34
recession, depression and boom time.
105
274260
3000
經濟衰退期、低迷和繁榮時期
04:37
This is the result of faster computers
106
277260
2000
這是速度快的電腦
04:39
being used to build faster computers.
107
279260
3000
被用來創造更快速的電腦的結果
04:42
It doesn't slow for any of our grand challenges.
108
282260
4000
它不因爲我們面對艱鉅的挑戰而慢下來
04:46
And also, even though it's plotted
109
286260
2000
雖然它描繪成
04:48
on a log curve on the left,
110
288260
2000
左邊向上發展
04:50
it's curving upwards.
111
290260
2000
的對數曲線
04:52
The rate at which the technology is getting faster
112
292260
2000
這個是科技進步的比率
04:54
is itself getting faster.
113
294260
3000
科技本身越來越先進
04:57
And on this curve, riding on Moore's Law,
114
297260
3000
在這條摩爾定律曲線上
05:00
are a set of extraordinarily powerful technologies
115
300260
3000
是一連串我們可利用的
05:03
available to all of us.
116
303260
2000
強大而先進的科技
05:05
Cloud computing,
117
305260
2000
「雲端運算」
05:07
what my friends at Autodesk call infinite computing;
118
307260
2000
我在"歐特克公司(Autodesk)"的朋友都稱它為「無限運算」
05:09
sensors and networks; robotics;
119
309260
3000
感應器、網路、自動化設備、3D印刷
05:12
3D printing, which is the ability to democratize and distribute
120
312260
3000
都是在全球能被大眾化跟
05:15
personalized production around the planet;
121
315260
2000
廣為運用的人性化產品
05:17
synthetic biology;
122
317260
2000
人造生物學、
05:19
fuels, vaccines and foods;
123
319260
3000
燃料、疫苗和食物、
05:22
digital medicine; nanomaterials; and A.I.
124
322260
3000
數位醫學、奈米材料和人工智慧
05:25
I mean, how many of you saw the winning of Jeopardy
125
325260
3000
你們有多少人看過IBM沃森
05:28
by IBM's Watson?
126
328260
2000
贏了《危險邊緣》(美國智力競賽節目)?
05:30
I mean, that was epic.
127
330260
3000
那次很經典
05:33
In fact, I scoured the headlines
128
333260
2000
為了找一個最好的頭條標題
05:35
looking for the best headline in a newspaper I could.
129
335260
2000
事實上我搜尋了很多報紙
05:37
And I love this: "Watson Vanquishes Human Opponents."
130
337260
4000
而我喜歡這個:《沃森擊敗了"人類"對手》
05:42
Jeopardy's not an easy game.
131
342260
2000
《危險邊緣》不是個容易的比賽
05:44
It's about the nuance of human language.
132
344260
3000
它關係著人類語言的細微差別
05:47
And imagine if you would
133
347260
2000
想像一下
05:49
A.I.'s like this on the cloud
134
349260
2000
人工智慧就跟這個一樣
05:51
available to every person with a cellphone.
135
351260
3000
有手機的人都能擁有
05:54
Four years ago here at TED,
136
354260
2000
四年前
05:56
Ray Kurzweil and I started a new university
137
356260
2000
雷.庫茨魏爾和我進了一所
05:58
called Singularity University.
138
358260
2000
叫「奇點大學」(Singularity University)的新學校教書
06:00
And we teach our students all of these technologies,
139
360260
3000
我們教導學生這些所有科技
06:03
and particularly how they can be used
140
363260
2000
尤其是教他們如何運用
06:05
to solve humanity's grand challenges.
141
365260
3000
這些科技解決人類的巨大挑戰
06:08
And every year we ask them
142
368260
2000
我們每年都要求他們
06:10
to start a company or a product or a service
143
370260
3000
去開新公司、生產產品或是提供服務
06:13
that can affect positively the lives of a billion people
144
373260
3000
希望在十年內帶給
06:16
within a decade.
145
376260
2000
幾百萬人正面的影響
06:18
Think about that, the fact that, literally, a group of students
146
378260
3000
想想看,一群學生說真的
06:21
can touch the lives of a billion people today.
147
381260
3000
可以影響百萬人的生活
06:24
30 years ago that would have sounded ludicrous.
148
384260
2000
這在30年前聽起來是很荒唐的
06:26
Today we can point at dozens of companies
149
386260
3000
現在我們可以說出幾百家的公司
06:29
that have done just that.
150
389260
2000
都在做這種事
06:31
When I think about creating abundance,
151
391260
6000
當我說要創造富足的社會
06:37
it's not about creating a life of luxury for everybody on this planet;
152
397260
3000
不是說要讓世界上每個人都享受奢華生活
06:40
it's about creating a life of possibility.
153
400260
3000
而是要創造出生命的可能性
06:43
It is about taking that which was scarce
154
403260
3000
是要豐富我們
06:46
and making it abundant.
155
406260
2000
所缺乏的東西
06:48
You see, scarcity is contextual,
156
408260
3000
缺乏是因人而異
06:51
and technology is a resource-liberating force.
157
411260
5000
而科技是一個資源解放的力量
06:56
Let me give you an example.
158
416260
3000
我舉個例
06:59
So this is a story of Napoleon III
159
419260
2000
這是在十八世紀中關於
07:01
in the mid-1800s.
160
421260
2000
拿破崙三世的故事
07:03
He's the dude on the left.
161
423260
3000
左邊那個是他
07:06
He invited over to dinner
162
426260
2000
他邀請暹羅國王
07:08
the king of Siam.
163
428260
2000
來共進晚餐
07:10
All of Napoleon's troops
164
430260
2000
拿破崙的軍隊
07:12
were fed with silver utensils,
165
432260
3000
用的是銀製餐具
07:15
Napoleon himself with gold utensils.
166
435260
2000
拿破崙則是用金製餐具
07:17
But the King of Siam,
167
437260
2000
但暹羅國王
07:19
he was fed with aluminum utensils.
168
439260
2000
用的卻是鋁製餐具
07:21
You see, aluminum
169
441260
2000
07:23
was the most valuable metal on the planet,
170
443260
3000
曾是世上最高貴的金屬
07:26
worth more than gold and platinum.
171
446260
3000
甚至比黃金和白金更有價值
07:29
It's the reason that the tip of the Washington Monument
172
449260
3000
這就是為什麼華盛頓紀念碑的頂端
07:32
is made of aluminum.
173
452260
2000
是由鋁所製成
07:34
You see, even though aluminum
174
454260
2000
雖然鋁礦有大批的藏量
07:36
is 8.3 percent of the Earth by mass,
175
456260
3000
佔地球質量的8.3%
07:39
it doesn't come as a pure metal.
176
459260
2000
但鋁不是純金屬的方式存在
07:41
It's all bound by oxygen and silicates.
177
461260
3000
而是由以「氧」和「矽酸鹽」化合物的方式存在
07:44
But then the technology of electrolysis came along
178
464260
3000
隨著電解科技的到來
07:47
and literally made aluminum so cheap
179
467260
3000
使得鋁越來越廉價
07:50
that we use it with throw-away mentality.
180
470260
3000
我們也就把鋁視為平凡的金屬
07:53
So let's project this analogy going forward.
181
473260
4000
我們可以依此類推
07:57
We think about energy scarcity.
182
477260
2000
想想看能源缺乏
07:59
Ladies and gentlemen,
183
479260
2000
各位
08:01
we are on a planet
184
481260
2000
我們生活在一個星球
08:03
that is bathed with 5,000 times more energy
185
483260
3000
一個擁有高出我們一年
08:06
than we use in a year.
186
486260
3000
所使用能源5000倍的星球
08:09
16 terawatts of energy hits the Earth's surface
187
489260
2000
每88分鐘就有16兆瓦的能源
08:11
every 88 minutes.
188
491260
4000
降落在地球表面
08:15
It's not about being scarce,
189
495260
2000
所以問題並不在於缺乏能源
08:17
it's about accessibility.
190
497260
2000
而在於能源的可利用性
08:19
And there's good news here.
191
499260
2000
有個好消息
08:21
For the first time, this year
192
501260
2000
今年是有史以來第一次
08:23
the cost of solar-generated electricity
193
503260
3000
印度的太陽能發電的花費
08:26
is 50 percent that of diesel-generated electricity in India --
194
506260
4000
是柴油發電的一半
08:30
8.8 rupees versus 17 rupees.
195
510260
3000
8.8盧比對17盧比的差別
08:33
The cost of solar dropped 50 percent last year.
196
513260
2000
去年太陽能發電花費就降了一半
08:35
Last month, MIT put out a study
197
515260
2000
上個月麻省理工學院發表了一項研究
08:37
showing that by the end of this decade,
198
517260
2000
他們表示約在十年後
08:39
in the sunny parts of the United States,
199
519260
2000
美國陽光普照的地區
08:41
solar electricity will be six cents a kilowatt hour
200
521260
2000
太陽能電價格跟現在平均一度要價15分美元相比
08:43
compared to 15 cents
201
523260
2000
每一度電
08:45
as a national average.
202
525260
2000
只要價六分美元
08:47
And if we have abundant energy,
203
527260
3000
我們有了充足的能源
08:50
we also have abundant water.
204
530260
3000
我們就會有充足的水源
08:53
Now we talk about water wars.
205
533260
5000
再來談水資源的戰爭
08:58
Do you remember
206
538260
2000
你是否記得
09:00
when Carl Sagan turned the Voyager spacecraft
207
540260
2000
當卡爾.薩根(天文學家)在1990年
09:02
back towards the Earth,
208
542260
2000
把剛通過土星的航海家1號
09:04
in 1990 after it just passed Saturn?
209
544260
2000
送回地球的時候?
09:06
He took a famous photo. What was it called?
210
546260
3000
他拍了一張很出名的相片,那叫什麼?
09:09
"A Pale Blue Dot."
211
549260
2000
《蒼藍小點》
09:11
Because we live on a water planet.
212
551260
3000
我們住在一個水星球
09:14
We live on a planet 70 percent covered by water.
213
554260
3000
一個表面被70%的水覆蓋的星球
09:17
Yes, 97.5 percent is saltwater,
214
557260
2000
其中97.5%是鹹水
09:19
two percent is ice,
215
559260
2000
2%是冰
09:21
and we fight over a half a percent of the water on this planet,
216
561260
3000
我們為了地球上一半的水在爭吵
09:24
but here too there is hope.
217
564260
2000
天無絕人之路
09:26
And there is technology coming online,
218
566260
3000
一個新科技出現了
09:29
not 10, 20 years from now,
219
569260
2000
不是在十幾二十年後
09:31
right now.
220
571260
2000
是現在
09:33
There's nanotechnology coming on, nanomaterials.
221
573260
3000
奈米科技製造的奈米材料誕生了
09:36
And the conversation I had with Dean Kamen this morning,
222
576260
3000
我今天早上和狄恩.卡門聊天
09:39
one of the great DIY innovators,
223
579260
2000
他是一個偉大的DIY發明家
09:41
I'd like to share with you -- he gave me permission to do so --
224
581260
3000
他允許我可以跟你們分享這段對話
09:44
his technology called Slingshot
225
584260
2000
他的發明-"Slingshot"
09:46
that many of you may have heard of,
226
586260
2000
你們應該都聽過
09:48
it is the size of a small dorm room refrigerator.
227
588260
2000
那是一個約一個小宿舍房間大的冰箱
09:50
It's able to generate
228
590260
2000
它可以發電
09:52
a thousand liters of clean drinking water a day
229
592260
2000
可以每天淨化一千加侖的飲用水
09:54
out of any source -- saltwater, polluted water, latrine --
230
594260
3000
鹹水、汙染水、廁所汙水它都能淨化
09:57
at less than two cents a liter.
231
597260
3000
且一加侖成本少於2分美元
10:02
The chairman of Coca-Cola has just agreed
232
602260
2000
可口可樂的董事長也同意
10:04
to do a major test
233
604260
2000
做一個大規模測試
10:06
of hundreds of units of this in the developing world.
234
606260
3000
在開發中國家置入幾百套這種設備
10:09
And if that pans out,
235
609260
2000
如果成功了
10:11
which I have every confidence it will,
236
611260
2000
當然我有信心它會成功
10:13
Coca-Cola will deploy this globally
237
613260
2000
可口可樂公司就會
10:15
to 206 countries
238
615260
2000
將此計畫推展至
10:17
around the planet.
239
617260
2000
全球206個國家
10:19
This is the kind of innovation, empowered by this technology,
240
619260
3000
這就是現代科技
10:22
that exists today.
241
622260
4000
所帶來的革新
10:26
And we've seen this in cellphones.
242
626260
2000
手機就是一個代表
10:28
My goodness, we're going to hit 70 percent penetration
243
628260
2000
天啊,我們要在2013之前
10:30
of cellphones in the developing world
244
630260
2000
讓手機在開發中國家
10:32
by the end of 2013.
245
632260
2000
達到70%的使用率
10:34
Think about it,
246
634260
2000
想想看
10:36
that a Masai warrior on a cellphone in the middle of Kenya
247
636260
3000
一個肯亞馬賽族戰士用的手機
10:39
has better mobile comm
248
639260
2000
比25年前雷根總統在位時的
10:41
than President Reagan did 25 years ago.
249
641260
3000
通訊品質還要更好
10:44
And if they're on a smartphone on Google,
250
644260
2000
如果他們用谷歌(Google)的智慧型手機
10:46
they've got access to more knowledge and information
251
646260
2000
就能比15年前柯林頓總統在位時
10:48
than President Clinton did 15 years ago.
252
648260
2000
接收更多的知識和資訊
10:50
They're living in a world of information and communication abundance
253
650260
3000
他們就此生活在一個有富足資訊和通訊的世界
10:53
that no one could have ever predicted.
254
653260
3000
這原本是沒人能預料到的
10:57
Better than that,
255
657260
2000
更好的是
10:59
the things that you and I
256
659260
2000
我們花了
11:01
spent tens and hundreds of thousands of dollars for --
257
661260
2000
好幾十萬在這些東西上:
11:03
GPS, HD video and still images,
258
663260
3000
GPS、高畫質影片和靜止圖像
11:06
libraries of books and music,
259
666260
3000
書本和音樂庫、
11:09
medical diagnostic technology --
260
669260
2000
醫療診斷科技...
11:11
are now literally dematerializing and demonetizing
261
671260
3000
而現在這些東西都漸漸的被融入
11:14
into your cellphone.
262
674260
3000
在你們的手機上
11:19
Probably the best part of it
263
679260
2000
而維護人民健康的收費的下降
11:21
is what's coming down the pike in health.
264
681260
3000
大概是其中最好的部分吧
11:24
Last month, I had the pleasure of announcing with Qualcomm Foundation
265
684260
4000
上個月我很榮幸跟「高通基金會」(Qualcomm Foundation)一起宣布
11:28
something called the $10 million Qualcomm Tricorder X Prize.
266
688260
4000
高通"Tricorder"的「X大獎」千萬得主
11:32
We're challenging teams around the world
267
692260
2000
我們向全球參賽者們提出挑戰
11:34
to basically combine these technologies
268
694260
2000
把這些全部功能
11:36
into a mobile device
269
696260
2000
融合在一個移動式的設備裡
11:38
that you can speak to, because it's got A.I.,
270
698260
2000
因為有人工智慧,所以你能對著它講話
11:40
you can cough on it, you can do a finger blood prick.
271
700260
3000
可以對它咳嗽或是做手指血液採樣
11:43
And to win, it needs to be able to diagnose you better
272
703260
2000
要贏得此獎,該儀器的診斷技術
11:45
than a team of board-certified doctors.
273
705260
4000
必須比公會認證的醫師團隊還要精確
11:49
So literally, imagine this device
274
709260
3000
想像一下這個儀器
11:52
in the middle of the developing world where there are no doctors,
275
712260
3000
能被用在沒有醫生的開發中國家
11:55
25 percent of the disease burden
276
715260
2000
在那裏有25%的地區在疾病肆虐的壓力下
11:57
and 1.3 percent of the health care workers.
277
717260
3000
且只有1.3%的人是醫療保健工作者
12:00
When this device sequences an RNA or DNA virus
278
720260
2000
而當這個儀器無法辨識出
12:02
that it doesn't recognize,
279
722260
2000
所排列的RNA或DNA病毒時
12:04
it calls the CDC
280
724260
2000
它就會通報「疾病防治中心」(CDC)
12:06
and prevents the pandemic from happening in the first place.
281
726260
3000
進而防止疾病從該地區散播出去
12:11
But here, here is the biggest force
282
731260
3000
這有一個最強大的力量
12:14
for bringing about a world of abundance.
283
734260
2000
能帶來一個富足的世界
12:16
I call it the rising billion.
284
736260
3000
我稱它為「上升十億」
12:19
So the white lines here are population.
285
739260
3000
白色那條代表人口
12:22
We just passed the seven billion mark on Earth.
286
742260
3000
我們剛通過了七十億大關
12:25
And by the way,
287
745260
2000
順道一提
12:27
the biggest protection against a population explosion
288
747260
2000
防止人口爆炸的最大力量
12:29
is making the world educated
289
749260
2000
就是教育
12:31
and healthy.
290
751260
3000
和健康
12:34
In 2010,
291
754260
2000
在2010年
12:36
we had just short of two billion people
292
756260
2000
全球還不到20億人口
12:38
online, connected.
293
758260
2000
有網際網路的連線
12:40
By 2020,
294
760260
2000
到2020年
12:42
that's going from two billion to five billion
295
762260
2000
網路使用者會從20億
12:44
Internet users.
296
764260
2000
躍進到50億
12:46
Three billion new minds
297
766260
2000
新加入的30億人口
12:48
who have never been heard from before
298
768260
2000
之前從沒聽過網路這種東西
12:50
are connecting to the global conversation.
299
770260
4000
他們終於能跟世界對話
12:54
What will these people want?
300
774260
2000
這些人想要什麼?
12:56
What will they consume? What will they desire?
301
776260
2000
他們會接收到什麼?他們渴望什麼?
12:58
And rather than having economic shutdown,
302
778260
2000
當然不是經濟的蕭條
13:00
we're about to have the biggest economic injection ever.
303
780260
3000
而是要感受有史以來最繁榮的經濟
13:03
These people represent
304
783260
2000
這些人意味著
13:05
tens of trillions of dollars
305
785260
2000
有幾十兆美元
13:07
injected into the global economy.
306
787260
3000
投入了全球經濟市場
13:10
And they will get healthier
307
790260
2000
他們就會藉由
13:12
by using the Tricorder,
308
792260
2000
"Tricorder"(剛提過的診斷儀器)變健康
13:14
and they'll become better educated by using the Khan Academy,
309
794260
2000
和藉由「可漢學院」(非營利教育組織)得到較好的教育
13:16
and by literally being able to use
310
796260
3000
漸漸地能使用
13:19
3D printing and infinite computing
311
799260
3000
3D列印技術和無限運算功能
13:22
[become] more productive than ever before.
312
802260
3000
變得更有生產力
13:25
So what could three billion rising,
313
805260
3000
所以這30億
13:28
healthy, educated, productive members of humanity
314
808260
3000
健康、教育良好和高生産力的人口
13:31
bring to us?
315
811260
2000
能帶給我們什麽?
13:33
How about a set of voices that have never been heard from before.
316
813260
3000
說到之前一堆被忽視的聲音
13:36
What about giving the oppressed,
317
816260
2000
他們無論到哪裡
13:38
wherever they might be,
318
818260
2000
都被壓迫著
13:40
the voice to be heard and the voice to act
319
820260
2000
他們的聲音要到哪時候才能
13:42
for the first time ever?
320
822260
3000
被重視而不被忽略?
13:45
What will these three billion people bring?
321
825260
3000
這30億人能帶來什麼?
13:48
What about contributions we can't even predict?
322
828260
3000
有可能是誰也無法預料到的貢獻?
13:51
The one thing I've learned at the X Prize
323
831260
2000
我在「X大獎」學到的一件事
13:53
is that small teams
324
833260
2000
就是即使一個小團隊
13:55
driven by their passion with a clear focus
325
835260
3000
當目標明確又被熱情所驅動下
13:58
can do extraordinary things,
326
838260
2000
也能完成一番不平凡的大事業
14:00
things that large corporations and governments
327
840260
2000
能完成在以前
14:02
could only do in the past.
328
842260
3000
只有大企業和政府才能作到的事
14:05
Let me share and close with a story
329
845260
2000
我分享一個故事作結尾
14:07
that really got me excited.
330
847260
3000
這真的很激勵我
14:10
There is a program that some of you might have heard of.
331
850260
2000
應該有人聽過這個程式
14:12
It's a game called Foldit.
332
852260
2000
一個叫《Foldit》的遊戲程式
14:14
It came out of the University of Washington in Seattle.
333
854260
4000
它是由西雅圖華盛頓大學開發的
14:18
And this is a game
334
858260
2000
它是一個遊戲
14:20
where individuals can actually take a sequence of amino acids
335
860260
4000
玩家能決定胺基酸的排列
14:24
and figure out how the protein is going to fold.
336
864260
4000
進而算出蛋白質接下來如何折疊
14:28
And how it folds dictates its structure and its functionality.
337
868260
2000
蛋白質的折疊方式決定了它的結構和功能
14:30
And it's very important for research in medicine.
338
870260
3000
這對藥物的研究很重要
14:33
And up until now, it's been a supercomputer problem.
339
873260
3000
但現在,這是超級電腦要做的事
14:36
And this game has been played
340
876260
2000
這個遊戲
14:38
by university professors and so forth.
341
878260
2000
已被大學教授之類的人玩過
14:40
And it's literally, hundreds of thousands of people
342
880260
3000
現在漸漸的有幾十萬人
14:43
came online and started playing it.
343
883260
2000
也開始在玩
14:45
And it showed that, in fact, today,
344
885260
2000
這顯示出事實上現在
14:47
the human pattern recognition machinery
345
887260
2000
人類的模式識別機器
14:49
is better at folding proteins than the best computers.
346
889260
3000
比現在最好的電腦更能折疊蛋白質
14:52
And when these individuals went and looked
347
892260
2000
這些玩家都想知道
14:54
at who was the best protein folder in the world,
348
894260
3000
誰是世界上最會折疊蛋白質的人
14:57
it wasn't an MIT professor,
349
897260
2000
不是麻省理工學院的教授
14:59
it wasn't a CalTech student,
350
899260
2000
也不是加州理工學院的學生
15:01
it was a person from England, from Manchester,
351
901260
3000
是一個住在英國曼徹斯特的女人
15:04
a woman who, during the day,
352
904260
4000
在白天
15:08
was an executive assistant at a rehab clinic
353
908260
3000
她是一個復健診所的行政助理
15:11
and, at night, was the world's best protein folder.
354
911260
4000
到了晚上她就是世界上最會折疊蛋白質的人
15:16
Ladies and gentlemen,
355
916260
2000
各位
15:18
what gives me tremendous confidence
356
918260
2000
是什麼東西讓我
15:20
in the future
357
920260
4000
對未非常有信心?
15:24
is the fact that we are now more empowered as individuals
358
924260
4000
我們現在能活得更自主更完整
15:28
to take on the grand challenges of this planet.
359
928260
3000
能接受各種襲來的巨大挑戰
15:31
We have the tools with this exponential technology.
360
931260
3000
我們有讓科技快速成長的工具
15:34
We have the passion of the DIY innovator.
361
934260
3000
有DIY發明家的熱情
15:37
We have the capital of the techno-philanthropist.
362
937260
3000
也有科技慈善家(高通基金會)當作資本
15:40
And we have three billion new minds
363
940260
2000
還有30億的新人
15:42
coming online to work with us
364
942260
2000
來幫助我們
15:44
to solve the grand challenges,
365
944260
2000
解決艱鉅的挑戰
15:46
to do that which we must do.
366
946260
4000
做我們該做的事
15:50
We are living into extraordinary decades ahead.
367
950260
2000
未來的黃金年代正等著我們!
15:52
Thank you.
368
952260
2000
謝謝
15:54
(Applause)
369
954260
14000
(掌聲)
關於本網站

本網站將向您介紹對學習英語有用的 YouTube 視頻。 您將看到來自世界各地的一流教師教授的英語課程。 雙擊每個視頻頁面上顯示的英文字幕,從那裡播放視頻。 字幕與視頻播放同步滾動。 如果您有任何意見或要求,請使用此聯繫表與我們聯繫。

https://forms.gle/WvT1wiN1qDtmnspy7