TED2012
Peter Diamandis: Abundance is our future
Peter Diamandis: 富足係我哋嘅未來
Filmed:
Readability: 4.7
1,664,920 views
喺 2012 年嘅 TED 演講，Peter Diamandis 提出一個樂觀嘅諗法︰我哋會發明、創新，同諗方法應付各種迎面而來嘅挑戰。佢話：「我哋當然會有問題，唔會話完全無問題，但最後，問題都會被我哋解決。」
Peter Diamandis - Space activist
Peter Diamandis runs the X Prize Foundation, which offers large cash incentive prizes to inventors who can solve grand challenges like space flight, low-cost mobile medical diagnostics and oil spill cleanup. He is the chair of Singularity University, which teaches executives and grad students about exponentially growing technologies. Full bio
Peter Diamandis runs the X Prize Foundation, which offers large cash incentive prizes to inventors who can solve grand challenges like space flight, low-cost mobile medical diagnostics and oil spill cleanup. He is the chair of Singularity University, which teaches executives and grad students about exponentially growing technologies. Full bio
Double-click the English transcript below to play the video.
00:15
(Applause)
0
0
3000
（掌聲）
00:18
(Video) Announcer: Threats, in the wake of Bin Laden's death, have spiked.
1
3000
3000
（賓拉登死後，威脅層出不窮。）
00:21
Announcer Two: Famine in Somalia. Announcer Three: Police pepper spray.
2
6000
2000
（索馬利亞嘅飢荒。）
（警方用嘅胡椒噴霧。）
（警方用嘅胡椒噴霧。）
00:23
Announcer Four: Vicious cartels. Announcer Five: Caustic cruise lines.
3
8000
2000
（企業使用惡意壟斷。）
（遊船上嘅混亂。）
（遊船上嘅混亂。）
00:25
Announcer Six: Societal decay. Announcer Seven: 65 dead.
4
10000
3000
（社會嘅腐敗。）
（六十五人死亡。）
（六十五人死亡。）
00:28
Announcer Eight: Tsunami warning. Announcer Nine: Cyberattacks.
5
13000
2000
（海嘯警報。）
（網路上嘅駭客攻擊。）
（網路上嘅駭客攻擊。）
00:30
Multiple Announcers: Drug war. Mass destruction. Tornado.
6
15000
2000
（毒品罪行。）
（大規模毀滅。龍捲風。）
（大規模毀滅。龍捲風。）
00:32
Recession. Default. Doomsday. Egypt. Syria.
7
17000
2000
（經濟衰退。債務拖欠。
世界末日。埃及。敘利亞。）
世界末日。埃及。敘利亞。）
00:34
Crisis. Death. Disaster.
8
19000
2000
（危機。死亡。災難。）
00:36
Oh, my God.
9
21000
3000
「喔！我嘅天啊！」
00:39
Peter Diamandis: So those are just a few of the clips
10
24000
2000
呢啲新聞頭條只係我喺過去六個月
00:41
I collected over the last six months --
11
26000
2000
收集到嘅一小部分
00:43
could have easily been the last six days
12
28000
2000
同過去六日嘅頭條
00:45
or the last six years.
13
30000
2000
或者過去六年嘅頭條冇咩差別
00:47
The point is that the news media
14
32000
2000
重點係，新聞媒體
00:49
preferentially feeds us negative stories
15
34000
3000
鐘意報導負面新聞
00:52
because that's what our minds pay attention to.
16
37000
3000
因為呢類新聞可以吸引我哋關注
00:55
And there's a very good reason for that.
17
40000
2000
理由係
00:57
Every second of every day,
18
42000
2000
每日
00:59
our senses bring in way too much data
19
44000
2000
我哋接收嘅資訊
01:01
than we can possibly process in our brains.
20
46000
3000
超過我哋大腦負荷
01:04
And because nothing is more important to us
21
49000
2000
對我哋嚟講
01:06
than survival,
22
51000
2000
冇嘢比生存更加重要
01:08
the first stop of all of that data
23
53000
2000
我哋嘅大腦接收信息嘅第一站
01:10
is an ancient sliver of the temporal lobe
24
55000
2000
係一片發現已久嘅
01:12
called the amygdala.
25
57000
2000
叫做「扁桃體」嘅腦葉
01:14
Now the amygdala is our early warning detector,
26
59000
3000
扁桃體係我哋身體最初期嘅
01:17
our danger detector.
27
62000
2000
警告同危險偵測系統
01:19
It sorts and scours through all of the information
28
64000
3000
佢搜尋同整理所有訊息
01:22
looking for anything in the environment that might harm us.
29
67000
3000
揾出喺環境裡邊對我哋有害嘅物質
01:25
So given a dozen news stories,
30
70000
2000
所以喺眾多嘅新聞裡邊
01:27
we will preferentially look
31
72000
2000
我哋會鍾意睇
01:29
at the negative news.
32
74000
2000
負面嘅新聞
01:31
And that old newspaper saying,
33
76000
2000
有一份舊報紙寫話：
01:33
"If it bleeds it leads,"
34
78000
2000
「有血嘅嘢最好賣。」
01:35
is very true.
35
80000
2000
呢句嘢好啱
01:37
So given all of our digital devices
36
82000
3000
宜家各種數碼設備
01:40
that are bringing all the negative news to us
37
85000
2000
一個禮拜七日、一日 24 小時
01:42
seven days a week, 24 hours a day,
38
87000
3000
猛咁對我哋輸啲負面新聞
01:45
it's no wonder that we're pessimistic.
39
90000
2000
唔怪得我哋咁悲觀
01:47
It's no wonder that people think
40
92000
2000
難怪啲人諗
01:49
that the world is getting worse.
41
94000
4000
世界越來越冇希望
01:53
But perhaps that's not the case.
42
98000
3000
事實上可能唔係噉
01:56
Perhaps instead,
43
101000
2000
其實，有可能係
01:58
it's the distortions brought to us
44
103000
2000
媒體帶畀我哋嘅消息
02:00
of what's really going on.
45
105000
3000
係扭曲咗嘅
02:03
Perhaps the tremendous progress we've made
46
108000
2000
可能我哋喺上個世紀
02:05
over the last century
47
110000
2000
藉一連串努力
02:07
by a series of forces
48
112000
2000
而創造嘅進步
02:09
are, in fact, accelerating to a point
49
114000
3000
加速到一個位
02:12
that we have the potential in the next three decades
50
117000
3000
使我哋喺未來三十年有潛力
02:15
to create a world of abundance.
51
120000
3000
去創造一個富足嘅世界
02:18
Now I'm not saying
52
123000
2000
我唔係話
02:20
we don't have our set of problems --
53
125000
2000
我哋冇問題
02:22
climate crisis, species extinction,
54
127000
2000
氣候危機、物種滅絕、水源同能源匱乏
02:24
water and energy shortage -- we surely do.
55
129000
3000
呢哋問題都一直存在
02:27
And as humans, we are far better
56
132000
2000
身為人類，我哋比其他動物
02:29
at seeing the problems way in advance,
57
134000
3000
早睇到問題好多
02:32
but ultimately we knock them down.
58
137000
4000
然後我哋解決呢哋問題
02:36
So let's look
59
141000
2000
我哋睇下
02:38
at what this last century has been
60
143000
2000
上個世紀到底發生咗咩事
02:40
to see where we're going.
61
145000
2000
同我哋下一步會去邊到
02:42
Over the last hundred years,
62
147000
2000
過去百幾年嚟
02:44
the average human lifespan has more than doubled,
63
149000
3000
人類嘅平均壽命係以前嘅兩倍
02:47
average per capita income adjusted for inflation
64
152000
3000
通貨膨脹調整之後
嘅各國平均國民所得
嘅各國平均國民所得
02:50
around the world has tripled.
65
155000
2000
係以前嘅三倍
02:52
Childhood mortality
66
157000
2000
童年嘅死亡率
02:54
has come down a factor of 10.
67
159000
2000
都下降到原來嘅十分之一
02:56
Add to that the cost of food, electricity,
68
161000
2000
仲有，糧食、電能、
02:58
transportation, communication
69
163000
2000
交通、通訊嘅花費
03:00
have dropped 10 to 1,000-fold.
70
165000
4000
變成以前嘅十分之一到千分之一
03:04
Steve Pinker has showed us
71
169000
2000
史迪芬．平克話俾我哋聽
03:06
that, in fact, we're living during the most peaceful time ever
72
171000
3000
宜家係
03:09
in human history.
73
174000
2000
人類史上最和平嘅時代
03:11
And Charles Kenny
74
176000
2000
Charles Kenny 話
03:13
that global literacy has gone from 25 percent to over 80 percent
75
178000
3000
過去 130 年，全球識字率
03:16
in the last 130 years.
76
181000
3000
從 25% 升到 80%
03:19
We truly are living in an extraordinary time.
77
184000
4000
我哋宜家生活喺一個黃金時期
03:23
And many people forget this.
78
188000
2000
但係好多人都唔記得呢樣嘢
03:25
And we keep setting our expectations higher and higher.
79
190000
3000
我哋不斷噉將期望設得越來越高
03:28
In fact, we redefine what poverty means.
80
193000
3000
事實上，我哋重寫咗貧窮嘅定義
03:31
Think of this, in America today,
81
196000
2000
諗下宜家嘅美國
03:33
the majority of people under the poverty line
82
198000
3000
喺貧窮線以下嘅大多數人
03:36
still have electricity, water, toilets, refrigerators,
83
201000
3000
都仲擁有水、電、馬桶、冰箱
03:39
television, mobile phones,
84
204000
2000
電視、手機
03:41
air conditioning and cars.
85
206000
3000
甚至冷氣同車
03:44
The wealthiest robber barons of the last century, the emperors on this planet,
86
209000
3000
上個世紀最富有嘅強盜、貴族、國王
03:47
could have never dreamed of such luxuries.
87
212000
3000
都冇呢啲奢侈品
03:53
Underpinning much of this
88
218000
3000
令呢種現象出現
03:56
is technology,
89
221000
2000
全靠以前嘅科技
03:58
and of late,
90
223000
2000
以至最近嘅
04:00
exponentially growing technologies.
91
225000
2000
幾何級數發展嘅科技
04:02
My good friend Ray Kurzweil
92
227000
2000
我嘅好朋友 Ray Kurzweil 畫咗一幅圖
04:04
showed that any tool that becomes an information technology
93
229000
3000
說明只要物件變成資訊科技工具
04:07
jumps on this curve, on Moore's Law,
94
232000
3000
就會按著摩爾定律嘅曲線
每一至兩年
04:10
and experiences price performance doubling
95
235000
2000
04:12
every 12 to 24 months.
96
237000
3000
性能就會翻倍
04:15
That's why the cellphone in your pocket
97
240000
2000
咁就係點解你哋衫袋裡邊嘅手機
04:17
is literally a million times cheaper and a thousand times faster
98
242000
2000
比起 70 年代嘅超級電腦
04:19
than a supercomputer of the '70s.
99
244000
2000
仲要平咗一百萬倍
同快咗一千倍
同快咗一千倍
04:21
Now look at this curve.
100
246000
2000
睇下呢個曲線
04:23
This is Moore's Law over the last hundred years.
101
248000
2000
呢個係一百幾年前嘅摩爾定律
04:25
I want you to notice two things from this curve.
102
250000
2000
留意下呢條曲線上嘅兩樣嘢
04:27
Number one, how smooth it is --
103
252000
4000
第一，條曲綫好平穩
04:31
through good time and bad time, war time and peace time,
104
256000
3000
唔受時期嘅好壞，或者戰爭同和平
04:34
recession, depression and boom time.
105
259000
3000
經濟衰退、低迷或者繁榮嘅影響
04:37
This is the result of faster computers
106
262000
2000
個結果就係速度快嘅電腦
04:39
being used to build faster computers.
107
264000
3000
用來造更快嘅電腦
04:42
It doesn't slow for any of our grand challenges.
108
267000
4000
電腦冇因爲任何我哋面對嘅問題而慢咗
04:46
And also, even though it's plotted
109
271000
2000
雖然曲線圖採用咗
04:48
on a log curve on the left,
110
273000
2000
對數曲線
04:50
it's curving upwards.
111
275000
2000
佢嘅方向係向上嘅
04:52
The rate at which the technology is getting faster
112
277000
2000
即係，科技進步嘅比率
04:54
is itself getting faster.
113
279000
3000
越來越快
04:57
And on this curve, riding on Moore's Law,
114
282000
3000
喺呢條摩爾定律曲線上邊
05:00
are a set of extraordinarily powerful technologies
115
285000
3000
係一連串可供我哋利用嘅
05:03
available to all of us.
116
288000
2000
強大而先進嘅科技
05:05
Cloud computing,
117
290000
2000
我喺 Autodesk 嘅朋友
05:07
what my friends at Autodesk call infinite computing;
118
292000
2000
叫雲端運算做無限運算
05:09
sensors and networks; robotics;
119
294000
3000
感應器。網路。自動化設備
05:12
3D printing, which is the ability to democratize and distribute
120
297000
3000
3D 印刷有可能喺全球將產品
05:15
personalized production around the planet;
121
300000
2000
大眾化同人性化
05:17
synthetic biology;
122
302000
2000
人造生物學
05:19
fuels, vaccines and foods;
123
304000
3000
燃料、疫苗同食物
05:22
digital medicine; nanomaterials; and A.I.
124
307000
3000
數位醫學。納米材料。人工智慧
05:25
I mean, how many of you saw the winning of Jeopardy
125
310000
3000
在座有幾多人睇到 IBM 沃森
05:28
by IBM's Watson?
126
313000
2000
喺《危險邊緣》贏通街？
05:30
I mean, that was epic.
127
315000
3000
嗰次個節目真係好經典
05:33
In fact, I scoured the headlines
128
318000
2000
我摷勻好多報紙
05:35
looking for the best headline in a newspaper I could.
129
320000
2000
想揾個最好嘅頭條
05:37
And I love this: "Watson Vanquishes Human Opponents."
130
322000
4000
我好鐘意呢個：《沃森擊敗人類對手》
05:42
Jeopardy's not an easy game.
131
327000
2000
《危險邊緣》呢個比賽好難
05:44
It's about the nuance of human language.
132
329000
3000
字眼上差小小，答案就唔一樣
05:47
And imagine if you would
133
332000
2000
想像一下
05:49
A.I.'s like this on the cloud
134
334000
2000
呢種雲端嘅人工智慧
05:51
available to every person with a cellphone.
135
336000
3000
喺人人嘅手機度都有
05:54
Four years ago here at TED,
136
339000
2000
四年前喺 TED
05:56
Ray Kurzweil and I started a new university
137
341000
2000
Ray Kurzweil 同我創辦咗
05:58
called Singularity University.
138
343000
2000
一間叫「奇點大學」嘅新大學
06:00
And we teach our students all of these technologies,
139
345000
3000
我哋向學生傳授呢啲全部嘅科技
尤其係點樣用嚟
06:03
and particularly how they can be used
140
348000
2000
解決人類面對嘅巨大挑戰
06:05
to solve humanity's grand challenges.
141
350000
3000
每一年， 我哋要求佢哋
06:08
And every year we ask them
142
353000
2000
06:10
to start a company or a product or a service
143
355000
3000
開新公司、開發新產品或者新服務
希望喺十年內
06:13
that can affect positively the lives of a billion people
144
358000
3000
幫助到十億人
06:16
within a decade.
145
361000
2000
06:18
Think about that, the fact that, literally, a group of students
146
363000
3000
試諗下，呢班學生真係
可以幫到十億人
06:21
can touch the lives of a billion people today.
147
366000
3000
呢種諗法喺 30 年前係幾荒唐
06:24
30 years ago that would have sounded ludicrous.
148
369000
2000
06:26
Today we can point at dozens of companies
149
371000
3000
宜家我哋可以講出邊間公司
喺度做緊呢件事
06:29
that have done just that.
150
374000
2000
06:31
When I think about creating abundance,
151
376000
6000
對我來講，創造富足嘅社會
06:37
it's not about creating a life of luxury for everybody on this planet;
152
382000
3000
唔係話要世界上
每個人都享受奢華生活
每個人都享受奢華生活
而係要創造出生活嘅可能性
06:40
it's about creating a life of possibility.
153
385000
3000
係要使我哋缺乏嘅嘢
06:43
It is about taking that which was scarce
154
388000
3000
06:46
and making it abundant.
155
391000
2000
變得豐富
每個人缺乏嘅嘢唔同
06:48
You see, scarcity is contextual,
156
393000
3000
06:51
and technology is a resource-liberating force.
157
396000
5000
而科技係一個解放資源嘅力量
06:56
Let me give you an example.
158
401000
3000
我舉個例
06:59
So this is a story of Napoleon III
159
404000
2000
呢個係十八世紀中葉
07:01
in the mid-1800s.
160
406000
2000
關於拿破崙三世嘅故事
07:03
He's the dude on the left.
161
408000
3000
佢就係左邊嗰個人
07:06
He invited over to dinner
162
411000
2000
佢邀請暹羅國王
07:08
the king of Siam.
163
413000
2000
共進晚餐
07:10
All of Napoleon's troops
164
415000
2000
拿破崙嘅成個軍隊
07:12
were fed with silver utensils,
165
417000
3000
用銀製餐具
07:15
Napoleon himself with gold utensils.
166
420000
2000
拿破崙自己就用金製餐具
07:17
But the King of Siam,
167
422000
2000
但係暹羅國王
07:19
he was fed with aluminum utensils.
168
424000
2000
用嘅竟然係鋁製餐具
07:21
You see, aluminum
169
426000
2000
原來
07:23
was the most valuable metal on the planet,
170
428000
3000
鋁曾經係世上最貴嘅金屬
07:26
worth more than gold and platinum.
171
431000
3000
甚至貴過黃金同埋白金
07:29
It's the reason that the tip of the Washington Monument
172
434000
3000
咁就係點解華盛頓紀念碑嘅頂端
係由鋁所製成
07:32
is made of aluminum.
173
437000
2000
07:34
You see, even though aluminum
174
439000
2000
雖然鋁嘅礦量
07:36
is 8.3 percent of the Earth by mass,
175
441000
3000
佔地球質量嘅 8.3%
07:39
it doesn't come as a pure metal.
176
444000
2000
但係金屬鋁好罕見
鋁多數喺礦物裡邊
鋁多數喺礦物裡邊
07:41
It's all bound by oxygen and silicates.
177
446000
3000
佢多數同氧或者矽酸鹽
反應生成化合物
反應生成化合物
07:44
But then the technology of electrolysis came along
178
449000
3000
有咗電解科技之後
07:47
and literally made aluminum so cheap
179
452000
3000
提煉鋁就變得好平
07:50
that we use it with throw-away mentality.
180
455000
3000
平到用完就掟
07:53
So let's project this analogy going forward.
181
458000
4000
如此類推
07:57
We think about energy scarcity.
182
462000
2000
我哋試諗下能源缺乏
07:59
Ladies and gentlemen,
183
464000
2000
各位
08:01
we are on a planet
184
466000
2000
我哋生活緊嘅地球，係一個
08:03
that is bathed with 5,000 times more energy
185
468000
3000
擁有我哋一年用嘅能源
08:06
than we use in a year.
186
471000
3000
5,000 倍嘅星球
08:09
16 terawatts of energy hits the Earth's surface
187
474000
2000
每 88 分鐘就有 16 兆瓦嘅能源
08:11
every 88 minutes.
188
476000
4000
來到地球嘅表面
08:15
It's not about being scarce,
189
480000
2000
所以問題唔係缺乏
08:17
it's about accessibility.
190
482000
2000
而係獲取能源嘅途徑
08:19
And there's good news here.
191
484000
2000
有個好消息
08:21
For the first time, this year
192
486000
2000
今年係印度有史以來第一次
08:23
the cost of solar-generated electricity
193
488000
3000
太陽能發電嘅花費
08:26
is 50 percent that of diesel-generated electricity in India --
194
491000
4000
係柴油發電嘅一半
08:30
8.8 rupees versus 17 rupees.
195
495000
3000
8.8 盧比對 17 盧比
08:33
The cost of solar dropped 50 percent last year.
196
498000
2000
舊年太陽能發電花費就降咗一半
08:35
Last month, MIT put out a study
197
500000
2000
上個月麻省理工學院發表咗一項研究
08:37
showing that by the end of this decade,
198
502000
2000
話喺 2020 年之前
08:39
in the sunny parts of the United States,
199
504000
2000
美國陽光充足嘅地區
08:41
solar electricity will be six cents a kilowatt hour
200
506000
2000
太陽能電嘅平均價格
08:43
compared to 15 cents
201
508000
2000
會降到 6 仙美金一度
宜家平均一度要 1 毫 5 仙美元
08:45
as a national average.
202
510000
2000
08:47
And if we have abundant energy,
203
512000
3000
我哋有咗充足嘅能源
08:50
we also have abundant water.
204
515000
3000
我哋就會有充足嘅水源
08:53
Now we talk about water wars.
205
518000
5000
我哋來講下水源嘅戰爭
08:58
Do you remember
206
523000
2000
你記唔記得
09:00
when Carl Sagan turned the Voyager spacecraft
207
525000
2000
1990 年
無人探測船航海家 1 號
無人探測船航海家 1 號
09:02
back towards the Earth,
208
527000
2000
飛過土星之後
卡爾．薩根叫探測船擰轉身
同太陽系影張全家福
同太陽系影張全家福
09:04
in 1990 after it just passed Saturn?
209
529000
2000
09:06
He took a famous photo. What was it called?
210
531000
3000
嗰張相好出名，叫咩？
09:09
"A Pale Blue Dot."
211
534000
2000
《蒼藍小點》
09:11
Because we live on a water planet.
212
536000
3000
我哋住喺一個水星球
09:14
We live on a planet 70 percent covered by water.
213
539000
3000
一個 70% 嘅表面俾水覆蓋嘅星球
09:17
Yes, 97.5 percent is saltwater,
214
542000
2000
其中 97.5% 係鹹水
09:19
two percent is ice,
215
544000
2000
2% 係冰
09:21
and we fight over a half a percent of the water on this planet,
216
546000
3000
我哋喺度爭地球上 0.5% 嘅水
09:24
but here too there is hope.
217
549000
2000
天無絕人之路
09:26
And there is technology coming online,
218
551000
3000
有一個新科技出現咗
09:29
not 10, 20 years from now,
219
554000
2000
唔係喺十、二十年後
09:31
right now.
220
556000
2000
係宜家
09:33
There's nanotechnology coming on, nanomaterials.
221
558000
3000
納米科技同納米材料誕生咗
09:36
And the conversation I had with Dean Kamen this morning,
222
561000
3000
我今朝同 Dean Kamen 傾偈
09:39
one of the great DIY innovators,
223
564000
2000
佢係一個偉大嘅 DIY 發明家
09:41
I'd like to share with you -- he gave me permission to do so --
224
566000
3000
佢畀我同你哋分享
09:44
his technology called Slingshot
225
569000
2000
佢嘅發明︰「Slingshot」
09:46
that many of you may have heard of,
226
571000
2000
可能好多人都聽過
09:48
it is the size of a small dorm room refrigerator.
227
573000
2000
佢係一個宿舍用嘅冰箱噉大
09:50
It's able to generate
228
575000
2000
佢可以
09:52
a thousand liters of clean drinking water a day
229
577000
2000
每日淨化一千升嘅水
09:54
out of any source -- saltwater, polluted water, latrine --
230
579000
3000
咩水都可以淨化
鹹水、污染水、廁所污水
鹹水、污染水、廁所污水
09:57
at less than two cents a liter.
231
582000
3000
而且成本低於一升 2 仙美元
10:02
The chairman of Coca-Cola has just agreed
232
587000
2000
可口可樂董事長啱啱批准咗
10:04
to do a major test
233
589000
2000
一個大規模嘅實驗
10:06
of hundreds of units of this in the developing world.
234
591000
3000
喺發展中國家試用幾百套呢種設備
10:09
And if that pans out,
235
594000
2000
如果成功——
10:11
which I have every confidence it will,
236
596000
2000
當然我有信心佢會成功
10:13
Coca-Cola will deploy this globally
237
598000
2000
可口可樂公司就會
將呢個計畫推廣至
10:15
to 206 countries
238
600000
2000
全球 206 個國家
10:17
around the planet.
239
602000
2000
10:19
This is the kind of innovation, empowered by this technology,
240
604000
3000
呢種創新就係
現代科技帶來嘅
10:22
that exists today.
241
607000
4000
10:26
And we've seen this in cellphones.
242
611000
2000
手機就係表表者
10:28
My goodness, we're going to hit 70 percent penetration
243
613000
2000
天啊，喺 2013 之前
10:30
of cellphones in the developing world
244
615000
2000
手機喺開發中國家嘅使用率
10:32
by the end of 2013.
245
617000
2000
就嚟達到 70%
10:34
Think about it,
246
619000
2000
試諗下
10:36
that a Masai warrior on a cellphone in the middle of Kenya
247
621000
3000
一個肯尼亞馬賽族戰士用嘅手機
10:39
has better mobile comm
248
624000
2000
比 25 年前雷根總統在位時
10:41
than President Reagan did 25 years ago.
249
626000
3000
用嘅通訊產品仲要好
10:44
And if they're on a smartphone on Google,
250
629000
2000
如果佢哋用谷歌嘅智能手機
10:46
they've got access to more knowledge and information
251
631000
2000
佢哋就比 15 年前克林頓總統在位時
10:48
than President Clinton did 15 years ago.
252
633000
2000
接收到更多嘅知識同資訊
10:50
They're living in a world of information and communication abundance
253
635000
3000
佢哋生活喺一個
資訊同通訊都充足嘅世界
資訊同通訊都充足嘅世界
10:53
that no one could have ever predicted.
254
638000
3000
冇人原本預料到嘅
10:57
Better than that,
255
642000
2000
更好嘅係
10:59
the things that you and I
256
644000
2000
以前花費
好幾十萬美金嘅嘢：
11:01
spent tens and hundreds of thousands of dollars for --
257
646000
2000
11:03
GPS, HD video and still images,
258
648000
3000
GPS、高畫質影片、靜止圖像
11:06
libraries of books and music,
259
651000
3000
書庫、音樂庫
11:09
medical diagnostic technology --
260
654000
2000
醫療診斷科技
11:11
are now literally dematerializing and demonetizing
261
656000
3000
宜家都漸漸融入
11:14
into your cellphone.
262
659000
3000
你哋嘅手機度
而最好嘅係
11:19
Probably the best part of it
263
664000
2000
醫療成本會下降
11:21
is what's coming down the pike in health.
264
666000
3000
11:24
Last month, I had the pleasure of announcing with Qualcomm Foundation
265
669000
4000
上個月我好榮幸同高通基金會一齊宣布
11:28
something called the $10 million Qualcomm Tricorder X Prize.
266
673000
4000
高通 Tricorder X 大獎
11:32
We're challenging teams around the world
267
677000
2000
我哋向全球嘅參賽者提出挑戰
11:34
to basically combine these technologies
268
679000
2000
11:36
into a mobile device
269
681000
2000
要求將呢啲全部功能
融合入一個移動設備度
11:38
that you can speak to, because it's got A.I.,
270
683000
2000
佢要有人工智慧，令你可以同佢講嘢
11:40
you can cough on it, you can do a finger blood prick.
271
685000
3000
你可以對佢咳或者做手指血液採樣
11:43
And to win, it needs to be able to diagnose you better
272
688000
2000
要贏得呢個獎，個儀器嘅診斷技術
11:45
than a team of board-certified doctors.
273
690000
4000
要好過一隊摞牌營業嘅醫師
11:49
So literally, imagine this device
274
694000
3000
想像一下呢個儀器
11:52
in the middle of the developing world where there are no doctors,
275
697000
3000
可以被用喺缺乏醫生嘅發展中國家
11:55
25 percent of the disease burden
276
700000
2000
發展中國家有全世界 25% 嘅病症
11:57
and 1.3 percent of the health care workers.
277
702000
3000
但係只有全世界 1.3% 嘅醫務人員
12:00
When this device sequences an RNA or DNA virus
278
705000
2000
當呢個儀器遇到一個 RNA 或者 DNA 排列
12:02
that it doesn't recognize,
279
707000
2000
係佢未見過嘅
12:04
it calls the CDC
280
709000
2000
佢就會通報美國疾病防治中心
12:06
and prevents the pandemic from happening in the first place.
281
711000
3000
進而防止疾病從一個地區蔓延開去
12:11
But here, here is the biggest force
282
716000
3000
至於為世界帶來富足嘅
12:14
for bringing about a world of abundance.
283
719000
2000
最強大力量
12:16
I call it the rising billion.
284
721000
3000
我叫佢做「上升十億」
12:19
So the white lines here are population.
285
724000
3000
白線代表人口
12:22
We just passed the seven billion mark on Earth.
286
727000
3000
我哋啱啱超過咗七十億大關
12:25
And by the way,
287
730000
2000
順便提一下
12:27
the biggest protection against a population explosion
288
732000
2000
防止人口爆炸嘅最大力量
12:29
is making the world educated
289
734000
2000
就是教育
12:31
and healthy.
290
736000
3000
同埋醫療
12:34
In 2010,
291
739000
2000
喺 2010 年
12:36
we had just short of two billion people
292
741000
2000
全球有唔到 20 億人口
12:38
online, connected.
293
743000
2000
上網
12:40
By 2020,
294
745000
2000
到 2020 年
12:42
that's going from two billion to five billion
295
747000
2000
網民從 20 億
12:44
Internet users.
296
749000
2000
躍進到 50 億
12:46
Three billion new minds
297
751000
2000
新加入嘅 30 億人口
12:48
who have never been heard from before
298
753000
2000
之前從來冇上過網
12:50
are connecting to the global conversation.
299
755000
4000
但佢哋終於能夠同個世界對話
12:54
What will these people want?
300
759000
2000
呢啲人想要咩？
12:56
What will they consume? What will they desire?
301
761000
2000
佢哋會消費咩？佢哋渴望咩？
12:58
And rather than having economic shutdown,
302
763000
2000
經濟唔會再蕭條
13:00
we're about to have the biggest economic injection ever.
303
765000
3000
而係要迎接有史以來最繁榮嘅經濟
13:03
These people represent
304
768000
2000
呢啲人意味著
13:05
tens of trillions of dollars
305
770000
2000
有幾十兆美元
13:07
injected into the global economy.
306
772000
3000
投入全球嘅經濟市場
13:10
And they will get healthier
307
775000
2000
佢哋就會藉由
13:12
by using the Tricorder,
308
777000
2000
Tricorder 診斷儀器變得更健康
13:14
and they'll become better educated by using the Khan Academy,
309
779000
2000
同藉由可漢學院接受好嘅教育
13:16
and by literally being able to use
310
781000
3000
佢哋可以藉使用
13:19
3D printing and infinite computing
311
784000
3000
3D 打印技術同無限運算功能
13:22
[become] more productive than ever before.
312
787000
3000
變得更有生產力
13:25
So what could three billion rising,
313
790000
3000
所以呢 30 億
13:28
healthy, educated, productive members of humanity
314
793000
3000
健康、教育良好同高生産力嘅人口
13:31
bring to us?
315
796000
2000
能帶畀我哋咩？
13:33
How about a set of voices that have never been heard from before.
316
798000
3000
之前講到被忽視嘅聲音
13:36
What about giving the oppressed,
317
801000
2000
世界各地
13:38
wherever they might be,
318
803000
2000
被壓迫嘅聲音
13:40
the voice to be heard and the voice to act
319
805000
2000
宜家終於會被聽到
13:42
for the first time ever?
320
807000
3000
同受重視
13:45
What will these three billion people bring?
321
810000
3000
呢 30 億人能帶來咩？
13:48
What about contributions we can't even predict?
322
813000
3000
佢哋帶來嘅貢獻可能冇人可以估算
13:51
The one thing I've learned at the X Prize
323
816000
2000
我喺 X 大獎學到嘅一件事
13:53
is that small teams
324
818000
2000
就係即使係一個細團隊
13:55
driven by their passion with a clear focus
325
820000
3000
當佢嘅目標明確同俾熱情所驅動
13:58
can do extraordinary things,
326
823000
2000
都可以做一番大事業
14:00
things that large corporations and governments
327
825000
2000
完成喺以前
14:02
could only do in the past.
328
827000
3000
只有大企業同政府先至作到嘅事
14:05
Let me share and close with a story
329
830000
2000
最尾，我想分享一個故事
14:07
that really got me excited.
330
832000
3000
佢真係好激勵我
14:10
There is a program that some of you might have heard of.
331
835000
2000
應該有人聽過呢個項目
14:12
It's a game called Foldit.
332
837000
2000
有個遊戲叫 Foldit
14:14
It came out of the University of Washington in Seattle.
333
839000
4000
佢係由西雅圖華盛頓大學開發嘅
14:18
And this is a game
334
843000
2000
佢係一個遊戲
玩家可以決定胺基酸嘅排列順序
14:20
where individuals can actually take a sequence of amino acids
335
845000
4000
14:24
and figure out how the protein is going to fold.
336
849000
4000
進而計算出蛋白質跟住會點折疊
14:28
And how it folds dictates its structure and its functionality.
337
853000
2000
蛋白質嘅折疊決定咗佢嘅結構同埋功能
14:30
And it's very important for research in medicine.
338
855000
3000
呢樣對藥物嘅研究好重要
14:33
And up until now, it's been a supercomputer problem.
339
858000
3000
目前為止，呢個問題得超級電腦先做到
14:36
And this game has been played
340
861000
2000
呢個遊戲
14:38
by university professors and so forth.
341
863000
2000
最初俾大學教授之類嘅人玩
14:40
And it's literally, hundreds of thousands of people
342
865000
3000
宜家有幾十萬人
14:43
came online and started playing it.
343
868000
2000
上網玩緊
14:45
And it showed that, in fact, today,
344
870000
2000
事實顯示
14:47
the human pattern recognition machinery
345
872000
2000
人類對模式嘅識別
14:49
is better at folding proteins than the best computers.
346
874000
3000
好過宜家最好嘅電腦
14:52
And when these individuals went and looked
347
877000
2000
呢啲玩家都想知道
14:54
at who was the best protein folder in the world,
348
879000
3000
世界上最識折疊蛋白質嘅人係邊個
14:57
it wasn't an MIT professor,
349
882000
2000
佢唔係麻省理工學院嘅一個教授
14:59
it wasn't a CalTech student,
350
884000
2000
唔係加州理工學院嘅一個學生
15:01
it was a person from England, from Manchester,
351
886000
3000
佢係一個住喺英國曼徹斯特嘅女人
15:04
a woman who, during the day,
352
889000
4000
喺日頭
15:08
was an executive assistant at a rehab clinic
353
893000
3000
佢係一個復健診所嘅行政助理
15:11
and, at night, was the world's best protein folder.
354
896000
4000
到咗晚黑，她就係
世界上最會折疊蛋白質嘅人
世界上最會折疊蛋白質嘅人
15:16
Ladies and gentlemen,
355
901000
2000
各位
15:18
what gives me tremendous confidence
356
903000
2000
係咩嘢令我
對未來非常有信心?
15:20
in the future
357
905000
4000
15:24
is the fact that we are now more empowered as individuals
358
909000
4000
係因為我哋宜家活得更自主更有能力
15:28
to take on the grand challenges of this planet.
359
913000
3000
可以應對各種巨大嘅挑戰
15:31
We have the tools with this exponential technology.
360
916000
3000
我哋嘅科技幾何級數發展
15:34
We have the passion of the DIY innovator.
361
919000
3000
我哋有 DIY 發明家嘅熱情
15:37
We have the capital of the techno-philanthropist.
362
922000
3000
我哋亦都有科技慈善家嘅資本
15:40
And we have three billion new minds
363
925000
2000
仲有 30 億第一次接觸互聯網嘅人
15:42
coming online to work with us
364
927000
2000
嚟幫我哋解決艱鉅嘅難題
15:44
to solve the grand challenges,
365
929000
2000
15:46
to do that which we must do.
366
931000
4000
做我哋應該做嘅嘢
15:50
We are living into extraordinary decades ahead.
367
935000
2000
未來嘅黃金年代等緊我哋
15:52
Thank you.
368
937000
2000
多謝
15:54
(Applause)
369
939000
14000
（掌聲）
ABOUT THE SPEAKER
Peter Diamandis - Space activistPeter Diamandis runs the X Prize Foundation, which offers large cash incentive prizes to inventors who can solve grand challenges like space flight, low-cost mobile medical diagnostics and oil spill cleanup. He is the chair of Singularity University, which teaches executives and grad students about exponentially growing technologies.
Why you should listen
Watch the live onstage debate with Paul Gilding that followed Peter Diamandis' 2012 TEDTalk >>
Peter Diamandis is the founder and chair of the X Prize Foundation, a nonprofit whose mission is simply "to bring about radical breakthroughs for the benefit of humanity." By offering a big cash prize for a specific accomplishment, the X Prize stimulates competition and excitement around some of the planet's most important goals. Diamandis is also co-founder and chairman of Singularity University which runs Exponential Technologies Executive and Graduate Student Programs.
Diamandis' background is in space exploration -- before the X Prize, he ran a company that studied low-cost launching technologies and Zero-G which offers the public the chance to train like an astronaut and experience weightlessness. But though the X Prize's first $10 million went to a space-themed challenge, Diamandis' goal now is to extend the prize into health care, social policy, education and many other fields that could use a dose of competitive innovation.
Peter Diamandis | Speaker | TED.com