Where's Google going next? | Larry Page

1,096,291 views ・ 2014-03-22

TED


請雙擊下方英文字幕播放視頻。

譯者: Kuan-Yi Li 審譯者: Ana Choi
00:13
Charlie Rose: So Larry sent me an email
0
13381
3626
查理.羅斯:賴瑞發了封信給我,
00:17
and he basically said,
1
17007
1987
基本上他就是說,
00:18
we've got to make sure that we don't seem like we're
2
18994
3729
我們得確保我們看起來不能像
00:22
a couple of middle-aged boring men.
3
22723
4491
兩個乏味的中年人。
00:27
I said, I'm flattered by that --
4
27214
3042
我回他說,你這麼講我深感榮幸──
00:30
(Laughter) —
5
30256
2372
(笑聲)──
00:32
because I'm a bit older,
6
32628
3515
因為我年紀大一點,
00:36
and he has a bit more net worth than I do.
7
36143
4151
而他的淨資產又比我多一點。
00:40
Larry Page: Well, thank you.
8
40294
2599
賴瑞.佩吉:呵,謝謝。
00:42
CR: So we'll have a conversation about
9
42893
2980
查理.羅斯:我們會聊聊網際網路,
00:45
the Internet, and we'll have a conversation Google,
10
45873
2698
還會聊聊 Google,
00:48
and we'll have a conversation about search
11
48571
1434
聊聊搜尋,
00:50
and privacy,
12
50005
1367
和隱私,
00:51
and also about your philosophy
13
51372
1555
還有你的處世哲學,
00:52
and a sense of how you've connected the dots
14
52927
2456
以及你如何把這 一切聯接起來的,
00:55
and how this journey that began
15
55383
2091
以及多年前開始的
00:57
some time ago
16
57474
1284
這個旅程,
00:58
has such interesting prospects.
17
58758
1895
具有怎樣的有趣前景。
01:00
Mainly we want to talk about the future.
18
60653
2596
我們主要來討論一下未來。
01:03
So my first question: Where is Google
19
63249
1589
那我的第一個問題是:Google 身在何處,
01:04
and where is it going?
20
64838
2046
它將前往何方?
01:06
LP: Well, this is something we think about a lot,
21
66884
1459
賴瑞.佩吉: 好的,這個問題我們思考過很多,
01:08
and our mission we defined a long time ago
22
68343
3575
我們很早以前所定下的目標
01:11
is to organize the world's information
23
71918
2263
就是將全世界的資訊組織起來
01:14
and make it universally accessible and useful.
24
74181
3438
讓全世界的人們可以 獲得它並且從中受益。
01:17
And people always say,
25
77619
2042
人們總會問,
01:19
is that really what you guys are still doing?
26
79661
2215
你們還在做這樣的事情嗎?
01:21
And I always kind of think about that myself,
27
81876
2118
我自己也常思考這問題,
01:23
and I'm not quite sure.
28
83994
2196
我還不是很確定。
01:26
But actually, when I think about search,
29
86190
4007
但事實上,說到搜尋,
01:30
it's such a deep thing for all of us,
30
90197
2616
對所有人來說都 是個深奧的問題,
01:32
to really understand what you want,
31
92813
2243
要真正理解你想要的是什麼,
01:35
to understand the world's information,
32
95056
2368
要理解這個世界的資訊,
01:37
and we're still very much in the early stages of that,
33
97424
3532
我們還處於非常早期的階段,
01:40
which is totally crazy.
34
100956
1813
這真的很誇張。
01:42
We've been at it for 15 years already,
35
102769
2518
我們在這個領域裡已有十五年,
01:45
but it's not at all done.
36
105287
3575
卻離實現它還差得很遠。
01:48
CR: When it's done, how will it be?
37
108862
2676
查理.羅斯: 當實現時,它會是什麼樣?
01:51
LP: Well, I guess,
38
111538
2717
賴瑞.佩吉:我猜,
01:54
in thinking about where we're going --
39
114255
2400
想想我們的前進方向──
01:56
you know, why is it not done? --
40
116655
2287
像是,為什麼還沒有完成?──
01:58
a lot of it is just computing's kind of a mess.
41
118942
2436
大部分原因是 數據計算還是一團亂。
02:01
You know, your computer doesn't know where you are,
42
121378
1803
電腦不知道你在哪、
02:03
it doesn't know what you're doing,
43
123181
2035
不知道你在做什麼,
02:05
it doesn't know what you know,
44
125216
1682
也不知道你懂什麼。
02:06
and a lot we've been trying to do recently
45
126898
2576
近年來我們花了很多的精力,
02:09
is just make your devices work,
46
129474
3295
只為了讓你的設備運作起來,
02:12
make them understand your context.
47
132769
2341
讓它理解你的大致意圖。
02:15
Google Now, you know, knows where you are,
48
135110
2003
Google Now 知道你人在哪,
02:17
knows what you may need.
49
137113
2182
知道你可能需要什麼。
02:19
So really having computing work and understand you
50
139295
4108
所以讓電腦真正地 運作起來、理解你
02:23
and understand that information,
51
143403
2056
並且理解這些資訊,
02:25
we really haven't done that yet.
52
145459
2310
我們還沒真的做到那步。
02:27
It's still very, very clunky.
53
147769
1549
它仍非常地不成熟。
02:29
CR: Tell me, when you look at what Google is doing,
54
149318
2366
查理.羅斯: 對於 Google 正在做的事,
02:31
where does Deep Mind fit?
55
151684
2969
DeepMind 扮演什麼角色?
02:34
LP: Yeah, so Deep Mind is a company
56
154653
1584
賴瑞.佩吉:DeepMind 這家公司,
02:36
we just acquired recently.
57
156237
2531
我們最近才併購進來。
02:38
It's in the U.K.
58
158768
3082
它在英國。
02:41
First, let me tell you the way we got there,
59
161850
2654
首先,我講一下我們當時的狀況,
02:44
which was looking at search
60
164504
2228
當時我們焦點放在搜尋,
02:46
and really understanding,
61
166732
1623
並真正地理解,
02:48
trying to understand everything,
62
168355
2233
試圖理解一切,
02:50
and also make the computers not clunky
63
170588
1605
讓電腦不那麼遲鈍,
02:52
and really understand you --
64
172193
2201
並且真正地理解你──
02:54
like, voice was really important.
65
174394
2112
比如,語音非常重要。
02:56
So what's the state of the art on speech recognition?
66
176506
2861
最先進的語音辨識技術是怎樣的?
02:59
It's not very good.
67
179367
1660
它不是很好,
03:01
It doesn't really understand you.
68
181027
2066
它並不能真正地理解你。
03:03
So we started doing machine learning research
69
183093
2003
於是我們研究機器學習,
03:05
to improve that.
70
185096
1537
以改進它,
03:06
That helped a lot.
71
186633
1703
結果成效很大。
03:08
And we started just looking at things like YouTube.
72
188336
2367
然後我們開始轉向 YouTube 之類的東西。
03:10
Can we understand YouTube?
73
190703
1968
我們可以理解 YouTube 嗎?
03:12
But we actually ran machine learning on YouTube
74
192671
2686
我們實際在 YouTube 上 進行機器學習,
03:15
and it discovered cats, just by itself.
75
195357
4085
它找到了貓,完全靠自己。
03:19
Now, that's an important concept.
76
199442
2091
這是個重要的概念。
03:21
And we realized there's really something here.
77
201533
2991
我們意識到,其中有著深義。
03:24
If we can learn what cats are,
78
204524
2117
如果我們能學習貓是什麼,
03:26
that must be really important.
79
206641
2075
那一定是非常重要的。
03:28
So I think Deep Mind,
80
208716
2629
所以我認為 DeepMind,
03:31
what's really amazing about Deep Mind
81
211345
2364
它的真正神奇之處
03:33
is that it can actually --
82
213709
2004
在於它真的可以
03:35
they're learning things in this unsupervised way.
83
215713
3557
自主學習,無需人的干預。
03:39
They started with video games,
84
219270
2567
他們從遊戲開始,
03:41
and really just, maybe I can show the video,
85
221837
2493
真的只是 ──也許我可以播一下那影片──
03:44
just playing video games,
86
224330
2204
只是玩遊戲,
03:46
and learning how to do that automatically.
87
226534
2015
並且學習怎樣自動地玩。
03:48
CR: Take a look at the video games
88
228549
1852
查理.羅斯:看一下這遊戲,
03:50
and how machines are coming to be able
89
230401
2410
機器是如何開始有能力
03:52
to do some remarkable things.
90
232811
2456
做一些驚人的事情。
03:55
LP: The amazing thing about this
91
235267
1329
賴瑞.佩吉:這驚人之處在於,
03:56
is this is, I mean, obviously,
92
236596
1680
我覺得很明顯,
03:58
these are old games,
93
238276
1474
這些都是老遊戲,
03:59
but the system just sees what you see, the pixels,
94
239750
4798
但是系統和你看到的 完全一樣,就是像素,
04:04
and it has the controls and it has the score,
95
244548
2431
並且它能控制、能得分,
04:06
and it's learned to play all of these games,
96
246979
2211
還有它學會了所有這些遊戲,
04:09
same program.
97
249190
1579
同一個程式。
04:10
It's learned to play all of these games
98
250769
2037
它學會了所有這些遊戲,
04:12
with superhuman performance.
99
252806
1786
而且表現是超人級的。
04:14
We've not been able to do things like this
100
254592
1855
在過去,電腦是做不到這些事的。
04:16
with computers before.
101
256447
1518
04:17
And maybe I'll just narrate this one quickly.
102
257965
2295
我要簡單說明一下,
04:20
This is boxing, and it figures out it can
103
260260
2805
這是拳擊遊戲,系統算出
04:23
sort of pin the opponent down.
104
263065
2634
如何制伏對手。
04:25
The computer's on the left,
105
265699
1739
左邊的是電腦,
04:27
and it's just racking up points.
106
267438
3085
它就是要贏得高分。
04:30
So imagine if this kind
107
270523
2086
所以設想一下,如果這樣的
04:32
of intelligence were thrown at your schedule,
108
272609
2127
人工智慧能用在你的排程、
04:34
or your information needs, or things like that.
109
274736
4637
解決你的訊息需求, 或類似的事情。
04:39
We're really just at the beginning of that,
110
279373
2618
機器學習其實還在起步階段,
04:41
and that's what I'm really excited about.
111
281991
2365
而這讓我感到無比興奮。
04:44
CR: When you look at all that's taken place
112
284356
2470
查理.羅斯: 當你看到 DeepMind 和拳擊遊戲
04:46
with Deep Mind and the boxing,
113
286826
2584
上所發生的這一切,
04:49
also a part of where we're going
114
289410
2340
加上人工智慧
04:51
is artificial intelligence.
115
291750
2889
也是我們前進的方向之一。
04:54
Where are we, when you look at that?
116
294639
2799
從這些來看,我們走到哪步了?
04:57
LP: Well, I think for me,
117
297438
1785
賴瑞.佩吉:我認為對於我來說,
04:59
this is kind of one of the most exciting things
118
299223
1503
這是我看到的 最令人興奮的事情之一,
05:00
I've seen in a long time.
119
300726
1912
在很長時間以來。
05:02
The guy who started this company, Demis,
120
302638
2413
創立這家公司的德米斯
05:05
has a neuroscience and a computer science background.
121
305051
2778
擁有神經學和電腦科學的背景。
05:07
He went back to school
122
307829
1630
他回學校攻讀博士,
05:09
to get his Ph.D. to study the brain.
123
309459
3126
課題是研究大腦。
05:12
And so I think we're seeing a lot of exciting work
124
312585
2620
我們看到許多激勵人心的成果,
05:15
going on that sort of crosses computer science
125
315205
3081
出現在跨神經學與 電腦科學的領域。
05:18
and neuroscience
126
318286
1750
05:20
in terms of really understanding
127
320036
2325
關於如何真正去理解,
05:22
what it takes to make something smart
128
322361
2454
去打造出有智慧的機器,
05:24
and do really interesting things.
129
324815
1715
來做一些有趣的事。
05:26
CR: But where's the level of it now?
130
326530
2138
查理.羅斯: 我們現在處於什麼階段呢?
05:28
And how fast do you think we are moving?
131
328668
2706
你覺得我們的進展速度如何?
05:31
LP: Well, this is the state of the art right now,
132
331374
3269
賴瑞.佩吉: 這是當前達到的最高水準,
05:34
understanding cats on YouTube
133
334643
2131
理解 YouTube 上的貓
05:36
and things like that,
134
336774
1283
還有類似的事情,
05:38
improving voice recognition.
135
338057
2147
加強語音辨識技術。
05:40
We used a lot of machine learning
136
340204
2418
我們使用了許多機器學習
05:42
to improve things incrementally,
137
342622
2479
來逐步改進各種問題,
05:45
but I think for me, this example's really exciting,
138
345101
3394
我個人認為這例子非常令人興奮,
05:48
because it's one program
139
348495
2243
因為它只是一個程式
05:50
that can do a lot of different things.
140
350738
2044
卻可以做許多不同事情。
05:52
CR: I don't know if we can do this,
141
352782
1138
查理.羅斯: 我不知道這樣做合不合適,
05:53
but we've got the image of the cat.
142
353920
1185
我這兒有一張貓的圖片,
05:55
It would be wonderful to see this.
143
355105
1754
這張圖意義非凡。
05:56
This is how machines looked at cats
144
356859
2509
這就是機器看貓,
05:59
and what they came up with.
145
359368
1115
反映出的形象。
06:00
Can we see that image?
146
360483
1055
可以看一下圖片嗎?
06:01
LP: Yeah. CR: There it is. Can you see the cat?
147
361538
2402
賴瑞.佩吉:好的。 查理.羅斯:這就是了。你能看到貓嗎?
06:03
Designed by machines, seen by machines.
148
363940
2027
機器自己設計、看到了它。
06:05
LP: That's right.
149
365967
1110
賴瑞.佩吉:是的。
06:07
So this is learned from just watching YouTube.
150
367077
2607
這是僅僅透過觀看 YouTube 學到的。
06:09
And there's no training,
151
369684
1867
沒有事先訓練過,
06:11
no notion of a cat,
152
371551
1384
沒有貓的概念,
06:12
but this concept of a cat
153
372935
2561
但這個貓的概念挺重要的,
06:15
is something important that you would understand,
154
375496
2808
我們都知道什麼是貓,
06:18
and now that the machines can kind of understand.
155
378304
2523
而現在機器也有了一定理解。
06:20
Maybe just finishing
156
380827
1172
也許它已經完成了搜尋這部分,
06:21
also on the search part,
157
381999
2222
06:24
it started with search, really understanding
158
384221
2786
它從搜尋開始,去理解人的意圖
06:27
people's context and their information.
159
387007
2564
和他們的資訊。
06:29
I did have a video
160
389571
1860
我有一個影片,
06:31
I wanted to show quickly on that
161
391431
2010
我想快速展示一下
06:33
that we actually found.
162
393441
1647
我發現了什麼。
06:35
(Video) ["Soy, Kenya"]
163
395088
5112
(影片) 「肯亞,索伊」
06:40
Zack Matere: Not long ago,
164
400580
1872
查克.馬泰爾:不久之前,
06:42
I planted a crop of potatoes.
165
402452
2586
我種了一片馬鈴薯,
06:45
Then suddenly they started dying one after the other.
166
405038
3400
然後突然地, 不斷有馬鈴薯死掉。
06:48
I checked out the books and they didn't tell me much.
167
408438
2750
我查了書,但沒發現多少資訊,
06:51
So, I went and I did a search.
168
411188
1946
所以我去搜尋了一下。
06:53
["Zack Matere, Farmer"]
169
413134
3119
「查克.馬泰爾,農民」
06:57
Potato diseases.
170
417609
3147
馬鈴薯、疾病。
07:00
One of the websites told me
171
420756
1728
有一個網站告訴我
07:02
that ants could be the problem.
172
422484
1902
問題可能是螞蟻。
07:04
It said, sprinkle wood ash over the plants.
173
424386
2271
它說,在作物上撒一些木灰。
07:06
Then after a few days the ants disappeared.
174
426657
2284
幾天之後螞蟻消失了。
07:08
I got excited about the Internet.
175
428941
2594
網路讓我非常興奮。
07:11
I have this friend
176
431535
1665
我有個朋友,
07:13
who really would like to expand his business.
177
433200
3618
他很想擴展生意,
07:16
So I went with him to the cyber cafe
178
436818
3195
於是我和他一起去了網咖,
07:20
and we checked out several sites.
179
440013
2541
我們查了一些網站。
07:22
When I met him next, he was going to put a windmill
180
442554
2541
再次見到他時,
他準備在當地學校建一座風車。
07:25
at the local school.
181
445095
2694
07:27
I felt proud because
182
447789
1604
我感到很驕傲,
07:29
something that wasn't there before
183
449393
2028
因為一個以前沒有的東西,
07:31
was suddenly there.
184
451421
1887
就這樣突然出現了。
07:33
I realized that not everybody
185
453308
2690
我意識到,
並不是所有人都能夠用
07:35
can be able to access
186
455998
1534
07:37
what I was able to access.
187
457532
1486
我能用的東西。
07:39
I thought that I need to have an Internet
188
459018
1838
我想我需要有種網路,
07:40
that my grandmother can use.
189
460856
1801
讓我奶奶也會用它。
07:42
So I thought about a notice board.
190
462657
2457
所以我想到了一個公告欄,
07:45
A simple wooden notice board.
191
465114
1916
一個簡單的木製公告欄。
07:47
When I get information on my phone,
192
467030
2315
我從手機上得到資訊的時候,
07:49
I'm able to post the information
193
469345
2237
我就可以把它
07:51
on the notice board.
194
471582
1722
公布在公告欄上。
07:53
So it's basically like a computer.
195
473304
2858
所以,它有點像部電腦,
07:56
I use the Internet to help people.
196
476162
3889
我用網際網路來幫助別人。
08:00
I think I am searching for
197
480051
3410
我認為我是在尋找
08:03
a better life
198
483461
1541
一個更好的生活,
08:05
for me and my neighbors.
199
485002
4114
為我,也為我的鄰居們。
08:09
So many people have access to information,
200
489116
3984
這樣許多人都可以得到資訊,
08:13
but there's no follow-up to that.
201
493100
2581
但是在這之後就沒有後續了。
08:15
I think the follow-up to that is our knowledge.
202
495681
2508
我認為「後續」就是我們的知識。
08:18
When people have the knowledge,
203
498189
1606
人們有了知識,
08:19
they can find solutions
204
499795
1630
他們就能找到方法,
08:21
without having to helped out.
205
501425
1984
而不需要找人幫忙。
08:23
Information is powerful,
206
503440
2121
資訊的力量很強大,
08:25
but it is how we use it that will define us.
207
505561
4602
但是如何使用資訊 才決定我們的未來。
08:30
(Applause)
208
510163
4381
(掌聲)
08:34
LP: Now, the amazing thing about that video,
209
514544
2546
賴瑞.佩吉: 這段影片的精彩之處在於,
08:37
actually, was we just read about it in the news,
210
517090
1466
我們是先從新聞看到,
08:38
and we found this gentlemen,
211
518556
2505
我們才找這位先生,
08:41
and made that little clip.
212
521061
2315
錄了這段影片。
08:43
CR: When I talk to people about you,
213
523376
1391
查理.羅斯:當我和別人說起你,
08:44
they say to me, people who know you well, say,
214
524767
2605
這些很了解你的人,他們對我說,
08:47
Larry wants to change the world,
215
527372
1891
賴瑞想要改變世界,
08:49
and he believes technology can show the way.
216
529263
4112
他相信科技可以指引方向,
08:53
And that means access to the Internet.
217
533375
1858
而這需要有網路。
08:55
It has to do with languages.
218
535233
1731
這也和語言有關。
08:56
It also means how people can get access
219
536964
2829
這也意味著, 人們要如何存取網路
08:59
and do things that will affect their community,
220
539793
2706
來做一些事情, 會影響到他所在的群體。
09:02
and this is an example.
221
542499
2493
這就是一個例子。
09:04
LP: Yeah, that's right, and I think for me,
222
544992
3576
賴瑞.佩吉:是的,對我來說,
09:08
I have been focusing on access more,
223
548568
2382
我致力於更易用的網路,
09:10
if we're talking about the future.
224
550950
2198
如果我們說的是未來的話。
09:13
We recently released this Loon Project
225
553148
2674
我們最近推出了 Loon 專案,
09:15
which is using balloons to do it.
226
555822
2300
用熱氣球來存取網路,
09:18
It sounds totally crazy.
227
558122
1660
聽起來很瘋狂。
09:19
We can show the video here.
228
559782
2539
我們可以在這裡播一下影片。
09:22
Actually, two out of three people in the world
229
562321
1480
世界上三分之二的人
09:23
don't have good Internet access now.
230
563801
2386
沒好的網路可用。
09:26
We actually think this can really help people
231
566187
2906
我們認為這個專案可以幫助人們,
09:29
sort of cost-efficiently.
232
569093
2057
並且費用低廉。
09:31
CR: It's a balloon. LP: Yeah, get access to the Internet.
233
571150
3371
查理.羅斯:這是一個氣球。 賴瑞.佩吉:是的,可以連網。
09:34
CR: And why does this balloon give you access
234
574521
2143
查理.羅斯:為什麼可以透過這氣球連網?
09:36
to the Internet?
235
576664
1213
09:37
Because there was some interesting things
236
577877
1215
因為你得想出一些有趣的辦法,
09:39
you had to do to figure out how
237
579092
1834
09:40
to make balloons possible,
238
580926
2131
來讓氣球連網成為可能,
09:43
they didn't have to be tethered.
239
583057
1749
還不用給氣球插上線。
09:44
LP: Yeah, and this is a good example of innovation.
240
584806
2081
賴瑞.佩吉: 是的,這是個關於創新的好例子。
09:46
Like, we've been thinking about this idea
241
586887
2544
在我們在著手之前
09:49
for five years or more
242
589431
1772
就已經在思考這想法了,
09:51
before we started working on it,
243
591203
1601
有五年甚至更久,
09:52
but it was just really,
244
592804
1319
但問題在於,
09:54
how do we get access points up high, cheaply?
245
594123
3520
如何才能便宜地 在天上設一個存取點?
09:57
You normally have to use satellites
246
597643
1792
傳統得用人造衛星,
09:59
and it takes a long time to launch them.
247
599435
2939
但發射需要很長時間。
10:02
But you saw there how easy it is to launch a balloon
248
602374
2494
然後我們就想到,放個氣球到天上,
10:04
and get it up,
249
604868
1519
是多麼簡單的事,
10:06
and actually again, it's the power of the Internet,
250
606387
2001
這再次說明網路的力量。
10:08
I did a search on it,
251
608388
1780
我確實搜尋過這件事,
10:10
and I found, 30, 40 years ago,
252
610168
2304
我發現三四十年前
10:12
someone had put up a balloon
253
612472
1889
就有人放出過一個氣球,
10:14
and it had gone around the Earth multiple times.
254
614361
2805
而這個氣球繞著地球轉了不少圈。
10:17
And I thought, why can't we do that today?
255
617166
2835
然後我想,我們如今 為何不這麼做呢?
10:20
And that's how this project got going.
256
620001
2367
這個專案就這樣開始了。
10:22
CR: But are you at the mercy of the wind?
257
622368
2330
查理.羅斯: 但是你受風的影響大嗎?
10:24
LP: Yeah, but it turns out,
258
624698
2122
賴瑞.佩吉:是的,但實際上,
10:26
we did some weather simulations
259
626820
1493
我們做了些氣象模擬,
10:28
which probably hadn't really been done before,
260
628313
2547
很可能以前從來沒人做過,
10:30
and if you control the altitude of the balloons,
261
630860
2110
如果控制氣球的高度,
10:32
which you can do by pumping air into them
262
632970
2281
可以通過充氣或別的方法實現,
10:35
and other ways,
263
635251
1822
10:37
you can actually control roughly where they go,
264
637073
2929
就可以大致控制氣球的動向,
10:40
and so I think we can build a worldwide mesh
265
640002
2205
因此,我想我們可以 建造一個世界性網路,
10:42
of these balloons that can cover the whole planet.
266
642207
3339
用這些氣球來覆蓋全球。
10:45
CR: Before I talk about the future and transportation,
267
645546
2242
查理.羅斯: 在我們聊未來和運輸之前
10:47
where you've been a nerd for a while,
268
647788
1895
──這兩樣你已浸淫了一段時間。
10:49
and this fascination you have with transportation
269
649683
2424
你對運輸、自動駕駛汽車和 自行車研究很深──
10:52
and automated cars and bicycles,
270
652107
2063
10:54
let me talk a bit about what's been the subject here
271
654170
1737
我先提一下有關 愛德華.史諾登的話題,
10:55
earlier with Edward Snowden.
272
655907
2443
稍早前也是 TED 主題,
10:58
It is security and privacy.
273
658350
3106
事關安全與隱私。
11:01
You have to have been thinking about that.
274
661456
2340
你一定一直有在思考這問題。
11:03
LP: Yeah, absolutely.
275
663796
1354
賴瑞.佩吉:是的,毫無疑問。
11:05
I saw the picture of Sergey with Edward Snowden yesterday.
276
665150
2843
昨天我看到了謝爾蓋和 愛德華.史諾登的照片。
11:07
Some of you may have seen it.
277
667993
2870
在座的有些人應該也看到了。
11:10
But I think, for me, I guess,
278
670863
3171
但我個人覺得,
11:14
privacy and security are a really important thing.
279
674034
3662
隱私和安全是非常重要的事情。
11:17
We think about it in terms of both things,
280
677696
2245
我們在這兩方面都有所思考,
11:19
and I think you can't have privacy without security,
281
679941
2903
我認為沒有安全就不存在隱私,
11:22
so let me just talk about security first,
282
682844
2371
所以我先談談安全,
11:25
because you asked about Snowden and all of that,
283
685215
2596
因為你問到了有關史諾登的事情,
11:27
and then I'll say a little bit about privacy.
284
687811
2441
然後我會再講一點隱私。
11:30
I think for me, it's tremendously disappointing
285
690252
3800
我個人感到極度失望,
11:34
that the government
286
694052
1439
政府偷偷做了這些事 沒有告訴我們。
11:35
secretly did all this stuff and didn't tell us.
287
695491
2330
11:37
I don't think we can have a democracy
288
697821
3303
我將不再擁有民主,
11:41
if we're having to protect you and our users
289
701124
3430
如果我們被迫由政府手中,
11:44
from the government
290
704554
1696
保護大家
11:46
for stuff that we've never had a conversation about.
291
706250
2803
不受未討論的事情侵害的話。
11:49
And I don't mean we have to know
292
709053
1896
我倒不是說我們必須知道
11:50
what the particular terrorist attack is they're worried
293
710949
1695
政府所擔心的具體 恐怖襲擊是什麼,
11:52
about protecting us from,
294
712644
1762
11:54
but we do need to know
295
714406
1798
而是我們需要知道
11:56
what the parameters of it is,
296
716204
2410
在什麼樣的情況下,
11:58
what kind of surveillance the government's
297
718614
2044
政府要進行何種監控,
12:00
going to do and how and why,
298
720658
2168
打算怎麼做,為什麼這樣做,
12:02
and I think we haven't had that conversation.
299
722826
2277
我認為我們並沒有 討論過這些問題。
12:05
So I think the government's actually done
300
725103
2567
我認為政府偷做這些事情,
12:07
itself a tremendous disservice
301
727670
2168
這種失職造成了嚴重的傷害。
12:09
by doing all that in secret.
302
729838
2161
12:11
CR: Never coming to Google
303
731999
1615
查理.羅斯: 絕不要找 Google 要任何東西?
12:13
to ask for anything.
304
733614
1525
12:15
LP: Not Google, but the public.
305
735139
2030
賴瑞.佩吉:不是 Google,而是大眾。
12:17
I think we need to have a debate about that,
306
737169
3773
我認為我們需要討論一下這個問題,
12:20
or we can't have a functioning democracy.
307
740942
2499
否則我們的民主就名不符實。
12:23
It's just not possible.
308
743441
1406
這不可能稱為民主。
12:24
So I'm sad that Google's
309
744847
2244
對於 Google 處在一個,
12:27
in the position of protecting you and our users
310
747091
2616
要防範政府偷雞摸狗的位置,
12:29
from the government
311
749707
1534
12:31
doing secret thing that nobody knows about.
312
751241
2244
我覺得很可悲。
12:33
It doesn't make any sense.
313
753485
1747
這毫無道理。
12:35
CR: Yeah. And then there's a privacy side of it.
314
755232
2990
查理.羅斯:沒錯,然後還有隱私方面的問題。
12:38
LP: Yes. The privacy side,
315
758222
2427
賴瑞.佩吉:是的,還有隱私面,
12:40
I think it's -- the world is changing.
316
760649
1969
我認為,世界在變。
12:42
You carry a phone. It knows where you are.
317
762618
3905
你帶著手機,它知道你在哪裡。
12:46
There's so much more information about you,
318
766523
3085
還有許多你的個人資訊,
12:49
and that's an important thing,
319
769608
2846
這是件非常重要的事情,
12:52
and it makes sense why people are asking
320
772454
2272
人們也合理地提出一些,
12:54
difficult questions.
321
774726
2036
難以回答的問題。
12:56
We spend a lot of time thinking about this
322
776762
3367
我們花了很多時間去思考這一點,
13:00
and what the issues are.
323
780129
2711
以及問題所在。
13:02
I'm a little bit --
324
782840
1729
我有一點……
13:04
I think the main thing that we need to do
325
784569
1260
我認為我們需要做的事情裡最主要的一點,
13:05
is just provide people choice,
326
785829
2362
就是讓人們可以選擇,
13:08
show them what data's being collected --
327
788191
2512
告訴他們什麼數據會被收集──
13:10
search history, location data.
328
790703
4751
搜尋記錄、位置資訊。
13:15
We're excited about incognito mode in Chrome,
329
795454
2772
我們對於 Chrome 瀏覽器的 無痕模式感到很興奮,
13:18
and doing that in more ways,
330
798226
2249
將它應用到更多的方面,
13:20
just giving people more choice
331
800475
1396
也就是給予人們更多選擇,
13:21
and more awareness of what's going on.
332
801871
3293
讓他們更完整地 認識到發生了什麼事。
13:25
I also think it's very easy.
333
805164
2393
我也認為這非常簡單。
13:27
What I'm worried is that we throw out
334
807557
1277
我所擔心的是,
13:28
the baby with the bathwater.
335
808834
2090
我們會因噎廢食。
13:30
And I look at, on your show, actually,
336
810924
2914
我看到,在你的節目上,
13:33
I kind of lost my voice,
337
813838
1719
我嗓子有點啞了,
13:35
and I haven't gotten it back.
338
815557
1331
我還沒有恢復。
13:36
I'm hoping that by talking to you
339
816888
1644
我希望和你聊聊
13:38
I'm going to get it back.
340
818532
1653
能恢復得快一點。
13:40
CR: If I could do anything, I would do that.
341
820185
1732
查理.羅斯: 如果我能幫上什麼忙,我一定會幫。
13:41
LP: All right. So get out your voodoo doll
342
821917
2180
賴瑞.佩吉:那好,拿出你的巫毒娃娃,
13:44
and whatever you need to do.
343
824097
2419
該做什麼儘管做。
13:46
But I think, you know what, I look at that,
344
826516
2328
但是我認為,我看著這件事,
13:48
I made that public,
345
828844
1830
我把它公開化了,
13:50
and I got all this information.
346
830674
1217
我得到很多資訊。
13:51
We got a survey done on medical conditions
347
831891
2729
我做了個關於身體狀況的調查,
13:54
with people who have similar issues,
348
834620
3371
調查對象都有些類似的問題。
13:57
and I look at medical records, and I say,
349
837991
4741
我一邊看著醫療記錄,一邊說,
14:02
wouldn't it be amazing
350
842732
1405
如果每個人的醫療記錄
14:04
if everyone's medical records were available
351
844137
2050
都可以匿名地提供給
14:06
anonymously
352
846187
1683
14:07
to research doctors?
353
847870
2636
做研究的醫生,
豈不是很好?
14:10
And when someone accesses your medical record,
354
850506
3041
當有人查看你的醫療記錄時,
14:13
a research doctor,
355
853547
1609
一個做研究的醫生,
14:15
they could see, you could see which doctor
356
855156
2634
他們可以看到,你也可以看到
14:17
accessed it and why,
357
857790
1860
是哪位醫生看了,為什麼,
14:19
and you could maybe learn about
358
859650
1580
然後你也許可以了解到
14:21
what conditions you have.
359
861230
1630
你的狀況如何。
14:22
I think if we just did that,
360
862860
1502
我想我們若做到這點,
14:24
we'd save 100,000 lives this year.
361
864362
2165
一年就可以多救十萬人。
14:26
CR: Absolutely. Let me go — (Applause)
362
866527
2948
查理.羅斯:毫無疑問。讓我…… (掌聲)
14:29
LP: So I guess I'm just very worried that
363
869475
2762
賴瑞.佩吉:我想我就是非常擔心
14:32
with Internet privacy,
364
872237
1806
網路隱私的問題。
14:34
we're doing the same thing we're doing with medical records,
365
874043
2300
我們的問題和醫療記錄一樣,
14:36
is we're throwing out the baby with the bathwater,
366
876347
2529
就是我們因噎廢食了,
14:38
and we're not really thinking
367
878876
1828
我們沒有真正地思考過
14:40
about the tremendous good that can come
368
880704
2210
資訊共享帶來的巨大益處,
14:42
from people sharing information
369
882914
2191
人們分享資訊,
14:45
with the right people in the right ways.
370
885105
2577
與正確的人分享,用正確的方式。
14:47
CR: And the necessary condition
371
887682
2237
查理.羅斯:還有一個必要條件,
14:49
that people have to have confidence
372
889919
1702
就是人們得有信心,
14:51
that their information will not be abused.
373
891621
2455
相信他們的資訊不會被濫用。
14:54
LP: Yeah, and I had this problem with my voice stuff.
374
894076
1777
賴瑞.佩吉:是的, 我在嗓音上有同樣的問題,
14:55
I was scared to share it.
375
895853
1508
我害怕分享出來。
14:57
Sergey encouraged me to do that,
376
897361
1890
謝爾蓋鼓勵我這麼做,
14:59
and it was a great thing to do.
377
899251
1827
這件事非常值得做。
15:01
CR: And the response has been overwhelming.
378
901078
1734
查理.羅斯: 而且大家的反應出奇地好。
15:02
LP: Yeah, and people are super positive.
379
902812
1660
賴瑞.佩吉: 是的,而且人們的反應極為正面。
15:04
We got thousands and thousands of people
380
904472
2833
我們調查了成千上萬的人,
15:07
with similar conditions,
381
907305
1288
都有類似狀況,
15:08
which there's no data on today.
382
908593
3028
而這些數據至今都是沒有的。
15:11
So it was a really good thing.
383
911621
1356
所以這是件非常好的事情。
15:12
CR: So talking about the future, what is it about you
384
912977
3019
查理.羅斯: 說到未來,你是怎麼
15:15
and transportation systems?
385
915996
3758
注意到運輸系統的?
15:19
LP: Yeah. I guess I was just frustrated
386
919754
2177
賴瑞.佩吉: 我在密西根州讀大學的時候,
15:21
with this when I was at college in Michigan.
387
921931
2539
我是感到非常沮喪的。
15:24
I had to get on the bus and take it
388
924470
1450
我必須坐公共汽車,
15:25
and wait for it.
389
925920
1642
還要等它。
15:27
And it was cold and snowing.
390
927562
2179
當時很冷,又在下雪。
15:29
I did some research on how much it cost,
391
929741
2655
我做了點成本研究,
15:32
and I just became a bit obsessed with transportation systems.
392
932396
6425
然後我就有點迷上了運輸系統。
15:38
CR: And that began the idea of an automated car.
393
938821
2370
查理.羅斯: 於是就有了自動駕駛汽車的想法。
15:41
LP: Yeah, about 18 years ago I learned about
394
941191
1694
賴瑞.佩吉: 是的,大約 18 年前我發現
15:42
people working on automated cars,
395
942885
3182
有人在研究自動駕駛,
15:46
and I became fascinated by that,
396
946067
1623
我被深深吸引,
15:47
and it takes a while to get these projects going,
397
947690
2777
讓這些專案有所進展得花點時間,
15:50
but I'm super excited about the possibilities of that
398
950467
5097
但是想到有可能讓世界變得更好,
我感到無比興奮。
15:55
improving the world.
399
955564
1668
15:57
There's 20 million people or more injured per year.
400
957232
4526
每年有超過兩千萬人受傷。
16:01
It's the leading cause of death
401
961758
1986
這是美國 34 歲以下群體
16:03
for people under 34 in the U.S.
402
963744
2130
的主要死因。
16:05
CR: So you're talking about saving lives.
403
965874
1551
查理.羅斯:這就是拯救生命了。
16:07
LP: Yeah, and also saving space
404
967425
2355
賴瑞.佩吉:是的,也是節省空間
16:09
and making life better.
405
969780
3915
和讓生活更美好。
16:13
Los Angeles is half parking lots and roads,
406
973695
4245
在洛杉磯一半的土地 都是停車場和道路,
16:17
half of the area,
407
977940
1733
一半的土地,
16:19
and most cities are not far behind, actually.
408
979673
2827
而且大部分城市其實也差不多了。
16:22
It's just crazy
409
982500
1564
這實在是太瘋狂了,
16:24
that that's what we use our space for.
410
984064
1593
我們居然這樣利用空間。
16:25
CR: And how soon will we be there?
411
985657
2343
查理.羅斯:我們什麼時候可以實現?
16:28
LP: I think we can be there very, very soon.
412
988000
1926
賴瑞.佩吉: 我想非常、非常快就可以實現了。
16:29
We've driven well over 100,000 miles
413
989926
3501
我們已正常行駛超過十萬英里,
16:33
now totally automated.
414
993427
4093
現在完全是自動行駛。
16:37
I'm super excited about getting that out quickly.
415
997520
3652
能夠這麼快地實現它,讓我無比興奮。
16:41
CR: But it's not only you're talking about automated cars.
416
1001172
2405
查理.羅斯:但你考慮的 不只是自動駕駛汽車,
16:43
You also have this idea for bicycles.
417
1003577
2386
你對自行車也有這樣的想法。
16:45
LP: Well at Google, we got this idea
418
1005963
2246
賴瑞.佩吉: 在 Google,我們有個想法,
16:48
that we should just provide free bikes to everyone,
419
1008209
3451
我們應該向每一個人 提供免費自行車,
16:51
and that's been amazing, most of the trips.
420
1011660
2768
這非常棒,對大多數旅行都是。
16:54
You see bikes going everywhere,
421
1014428
1586
自行車哪都能去,
16:56
and the bikes wear out.
422
1016014
1566
而自行車會磨損,
16:57
They're getting used 24 hours a day.
423
1017580
1454
一天 24 小時都在用。
16:59
CR: But you want to put them above the street, too.
424
1019034
2160
查理.羅斯:但你也想把自行車放到街道上。
17:01
LP: Well I said, how do we get people
425
1021194
1575
賴瑞.佩吉:我就說,怎樣才能
17:02
using bikes more?
426
1022769
1527
讓人們多騎自行車呢?
17:04
CR: We may have a video here.
427
1024296
1625
查理.羅斯:我們這有一段影片。
17:05
LP: Yeah, let's show the video.
428
1025921
1278
賴瑞.佩吉: 好,我們來播一下影片,
17:07
I just got excited about this.
429
1027199
3092
這個讓我非常興奮。
17:10
(Music)
430
1030291
4042
(音樂)
17:16
So this is actually how you might separate
431
1036213
2425
其實這就是把自行車與 汽車分離的最經濟方法,
17:18
bikes from cars with minimal cost.
432
1038638
3629
17:26
Anyway, it looks totally crazy,
433
1046711
1755
這看起來很瘋狂,
17:28
but I was actually thinking about our campus,
434
1048466
2327
但實際上我考慮的是我們的校園,
17:30
working with the Zippies and stuff,
435
1050793
2060
和許多城市等等一起合作,
17:32
and just trying to get a lot more bike usage,
436
1052853
2298
就是想大大提高自行車使用率,
17:35
and I was thinking about,
437
1055151
1548
我還在想,
17:36
how do you cost-effectively separate
438
1056699
2831
我們怎樣才能有效並且廉價地
17:39
the bikes from traffic?
439
1059530
1414
把自行車從車流中分離?
17:40
And I went and searched,
440
1060944
1150
我做了研究,
17:42
and this is what I found.
441
1062094
1371
這就是我所得到的。
17:43
And we're not actually working on this,
442
1063465
1845
我們其實沒有研究這個,
17:45
that particular thing,
443
1065310
1292
我是說這個具體方案,
17:46
but it gets your imagination going.
444
1066602
2054
但它擴展了想像力。
17:48
CR: Let me close with this.
445
1068656
1764
查理.羅斯: 我們把這個話題先告一段落,
17:50
Give me a sense of the philosophy of your own mind.
446
1070420
2345
說一下你內心的哲學。
17:52
You have this idea of [Google X].
447
1072765
2488
你有了 Google X 這個想法,
17:55
You don't simply want
448
1075253
2996
你想要的不只是一些
17:58
to go in some small, measurable arena of progress.
449
1078249
5596
小的,規模有限的舞臺。
18:03
LP: Yeah, I think
450
1083845
1713
賴瑞.佩吉:是的,我認為
18:05
many of the things we just talked about are like that,
451
1085558
2131
我們剛討論過的許多事情就是這樣,
18:07
where they're really --
452
1087689
2952
它們真是……
18:10
I almost use the economic concept of additionality,
453
1090641
3630
我差點要用經濟學 概念上的額外性了,
18:14
which means that you're doing something
454
1094271
2190
就是說,你要做的事情 本來並不會發生,
18:16
that wouldn't happen unless you were actually doing it.
455
1096461
2948
除非你真的動手做。
18:19
And I think the more you can do things like that,
456
1099409
3140
我認為這樣的事情你做得越多,
18:22
the bigger impact you have,
457
1102549
2071
你的影響力就越大,
18:24
and that's about doing things
458
1104620
2990
重點在於
18:27
that people might not think are possible.
459
1107610
3607
去做人們認為不可能的事。
18:31
And I've been amazed,
460
1111217
1829
我驚訝地發現,
18:33
the more I learn about technology,
461
1113046
2229
我懂的技術越多,
18:35
the more I realize I don't know,
462
1115275
2196
就越意識到自己的不足。
18:37
and that's because this technological horizon,
463
1117471
3337
這是因為技術的眼界提高了,
18:40
the thing that you can see to do next,
464
1120808
2897
也就是預見下一步 該怎麼做的能力。
18:43
the more you learn about technology,
465
1123705
1840
你懂的技術越多,
18:45
the more you learn what's possible.
466
1125545
2602
你就越知道什麼是可能的。
18:48
You learn that the balloons are possible
467
1128147
2246
你知道氣球專案是可能的,
18:50
because there's some material that will work for them.
468
1130393
2337
因為有合適的材料可用。
18:52
CR: What's interesting about you too, though, for me,
469
1132730
2379
查理.羅斯:不過在我看來, 你的有趣之處在於,
18:55
is that, we have lots of people
470
1135109
1711
有很多的人在思考未來,
18:56
who are thinking about the future,
471
1136820
2142
有很多的人在思考未來,
18:58
and they are going and looking and they're coming back,
472
1138962
3268
他們去看了看,又回來了,
19:02
but we never see the implementation.
473
1142230
2127
而我們卻沒有看到最終實現。
19:04
I think of somebody you knew
474
1144357
1605
我想到了一個人,你一定知道,
19:05
and read about, Tesla.
475
1145962
2907
特斯拉。
19:08
The principle of that for you is what?
476
1148869
3804
你在這方面的原則是怎樣的?
19:12
LP: Well, I think invention is not enough.
477
1152673
1785
賴瑞.佩吉: 我認為僅僅有發明是不夠的。
19:14
If you invent something,
478
1154458
1221
如果你發明一樣東西,
19:15
Tesla invented electric power that we use,
479
1155679
3195
特斯拉發明了 我們用的電力系統,
19:18
but he struggled to get it out to people.
480
1158874
2661
但是他推廣起來就非常困難,
19:21
That had to be done by other people.
481
1161535
1684
普及是由別人實現的,
19:23
It took a long time.
482
1163219
1626
花費了很長時間。
19:24
And I think if we can actually combine both things,
483
1164845
3867
我認為,如果我們能將 二者真正結合起來,
19:28
where we have an innovation and invention focus,
484
1168712
3531
同時著眼於創新與發明,
19:32
plus the ability to really -- a company
485
1172243
2972
再加上一家公司,
19:35
that can really commercialize things
486
1175215
1998
可以使成果真正商業化,
19:37
and get them to people
487
1177213
1630
讓人們接觸到它,
19:38
in a way that's positive for the world
488
1178843
2075
讓它對世界有積極的影響,
19:40
and to give people hope.
489
1180918
2056
並給人們帶來希望。
19:42
You know, I'm amazed with the Loon Project
490
1182974
2774
你知道,大家對氣球專案的關注程度
19:45
just how excited people were about that,
491
1185748
2786
讓我很是吃驚,
19:48
because it gave them hope
492
1188534
1814
因為它帶來了希望,
19:50
for the two thirds of the world
493
1190348
1621
尤其是對世界上無法 上網的三分之二來說,
19:51
that doesn't have Internet right now that's any good.
494
1191969
2726
19:54
CR: Which is a second thing about corporations.
495
1194695
2122
查理.羅斯: 這就是關於公司的第二件事。
19:56
You are one of those people who believe
496
1196817
2476
有些人,包括你,認為,
19:59
that corporations are an agent of change
497
1199293
2317
公司可以成為帶來改變的媒介,
20:01
if they are run well.
498
1201610
1471
如果好好經營的話。
20:03
LP: Yeah. I'm really dismayed
499
1203081
1821
賴瑞.佩吉:是的, 多數人認為企業是邪惡的,
20:04
most people think companies are basically evil.
500
1204902
3294
這讓我很是沮喪,
20:08
They get a bad rap.
501
1208196
1766
這麼說並不公正,
20:09
And I think that's somewhat correct.
502
1209962
2241
但我認為在某程度上又是正確的。
20:12
Companies are doing the same incremental thing
503
1212203
2870
公司做的事情就是漸進發展,
20:15
that they did 50 years ago
504
1215073
1763
五十年前的公司就這樣做,
20:16
or 20 years ago.
505
1216836
1631
或者說二十年前,
20:18
That's not really what we need.
506
1218467
1370
這也並非是我們真正需要的。
20:19
We need, especially in technology,
507
1219837
2218
我們需要的是,特別是在科技上,
20:22
we need revolutionary change,
508
1222055
2117
是革命性改變,
20:24
not incremental change.
509
1224172
1413
而不是漸進式改變。
20:25
CR: You once said, actually,
510
1225585
1169
查理.羅斯:你曾說過,
20:26
as I think I've got this about right,
511
1226754
1818
我希望我的理解是對的,
20:28
that you might consider,
512
1228572
1645
就是,你可能考慮,
20:30
rather than giving your money,
513
1230217
1753
相較於直接捐出你的錢,
20:31
if you were leaving it to some cause,
514
1231970
3320
你更願意用於某些事業,
20:35
just simply giving it to Elon Musk,
515
1235290
2006
給伊隆.馬斯克就好了,
20:37
because you had confidence
516
1237296
1163
因為你相信
20:38
that he would change the future,
517
1238459
1842
他會改變未來,
20:40
and that you would therefore —
518
1240301
1777
因此你就會……
20:42
LP: Yeah, if you want to go Mars,
519
1242078
1584
賴瑞.佩吉:是的,如果你想去火星,
20:43
he wants to go to Mars,
520
1243662
1721
他想去火星,
20:45
to back up humanity,
521
1245383
1971
來為人類尋找後備方案,
20:47
that's a worthy goal, but it's a company,
522
1247354
1672
這目標很有價值, 但對公司來說是慈善事業。
20:49
and it's philanthropical.
523
1249026
2555
20:51
So I think we aim to do kind of similar things.
524
1251581
2952
所以我覺得我們的目標 是做些類似的事情。
20:54
And I think, you ask, we have a lot of employees
525
1254533
2987
你問過,我們在 Google 有許多員工,
20:57
at Google who have become pretty wealthy.
526
1257520
3315
他們非常富有,
21:00
People make a lot of money in technology.
527
1260835
2520
通過技術賺了很多錢,
21:03
A lot of people in the room are pretty wealthy.
528
1263355
2156
很多人都非常富有。
21:05
You're working because you want to change the world.
529
1265511
2314
你工作的目的是改變世界,
21:07
You want to make it better.
530
1267825
1762
你想讓世界變得更好。
21:09
Why isn't the company that you work for
531
1269587
3445
為什麼你工作的這家公司,
21:13
worthy not just of your time
532
1273032
1943
值得你投入時間,
21:14
but your money as well?
533
1274975
2151
卻不值得你投入金錢呢?
21:17
I mean, but we don't have a concept of that.
534
1277126
1722
我的意思是,我們並不這樣認為,
21:18
That's not how we think about companies,
535
1278848
2304
我們也不是這樣看待公司的。
21:21
and I think it's sad,
536
1281152
1467
我也覺得很傷感,
21:22
because companies are most of our effort.
537
1282619
3767
因為我們所付出的努力 絕大部分都花在了公司上。
21:26
They're where most of people's time is,
538
1286386
2515
人們在這裡付出了最多的時間,
21:28
where a lot of the money is,
539
1288901
1854
也花費了許多金錢,
21:30
and so I think I'd like for us to help out
540
1290755
2352
所以我想我要幫助大家,
21:33
more than we are.
541
1293107
1126
而非只顧自己。
21:34
CR: When I close conversations with lots of people,
542
1294233
1721
查理.羅斯: 我跟許多人的談話結束時,
21:35
I always ask this question:
543
1295954
1779
我總是問這樣的一個問題:
21:37
What state of mind,
544
1297733
1515
怎樣的心態,
21:39
what quality of mind is it
545
1299248
1809
怎樣的心靈特質,
21:41
that has served you best?
546
1301057
1767
讓你最有收穫?
21:42
People like Rupert Murdoch have said curiosity,
547
1302824
2521
像魯柏.梅鐸這樣的人 說是好奇心,
21:45
and other people in the media have said that.
548
1305345
2628
別的媒體人士也這樣說。
21:47
Bill Gates and Warren Buffett have said focus.
549
1307973
3024
比爾.蓋茲和華倫.巴菲特 說是專注,
21:50
What quality of mind,
550
1310997
1427
什麼樣的心靈特質
21:52
as I leave this audience,
551
1312424
1374
──在與觀眾說再見前──
21:53
has enabled you to think about the future
552
1313798
3530
使得你能夠思考未來,
21:57
and at the same time
553
1317328
1647
而且與此同時,
21:58
change the present?
554
1318975
2205
改變現在?
22:01
LP: You know, I think the most important thing --
555
1321180
1670
賴瑞.佩吉: 我認為最重要的事情,
22:02
I looked at lots of companies
556
1322850
1612
我見過很多公司,
22:04
and why I thought they don't succeed over time.
557
1324462
3303
為什麼我認為它們 沒能經受時間的考驗。
22:07
We've had a more rapid turnover of companies.
558
1327765
2833
如今公司的人員流動更快,
22:10
And I said, what did they fundamentally do wrong?
559
1330598
2769
我問,他們出錯的根源是什麼?
22:13
What did those companies all do wrong?
560
1333367
2167
這些公司都錯在了哪裡?
22:15
And usually it's just that they missed the future.
561
1335534
3272
通常就是因為他們錯失了未來。
22:18
And so I think, for me,
562
1338806
2444
所以在我看來,
22:21
I just try to focus on that and say,
563
1341250
2424
我就是專注於這一點,並且在想,
22:23
what is that future really going to be
564
1343674
2184
未來將真正走向何方,
22:25
and how do we create it,
565
1345858
1787
我們要如何創造未來,
22:27
and how do we cause our organization,
566
1347645
4667
我們怎樣才能讓我們的組織
22:32
to really focus on that
567
1352312
2440
真正專注於它,
22:34
and drive that at a really high rate?
568
1354752
3325
並且帶領組織快速行動呢?
22:38
And so that's been curiosity,
569
1358077
1360
所以那就是好奇心,
22:39
it's been looking at things
570
1359437
1733
去尋找人們
22:41
people might not think about,
571
1361170
1718
可能沒有想過的東西,
22:42
working on things that no one else is working on,
572
1362888
3105
研究別人所沒有研究過的東西,
22:45
because that's where the additionality really is,
573
1365993
3306
因為那才是真正的額外性,
22:49
and be willing to do that,
574
1369299
1551
同時樂於去做,
22:50
to take that risk.
575
1370850
1382
樂於承擔風險。
22:52
Look at Android.
576
1372232
1065
看看 Android,
22:53
I felt guilty about working on Android
577
1373297
2785
為 Android 花心力曾讓我感到內疚,
22:56
when it was starting.
578
1376082
1316
在它剛起步時,
22:57
It was a little startup we bought.
579
1377398
1958
我們併購它時, 它只是個小公司。
22:59
It wasn't really what we were really working on.
580
1379356
2670
它當時也不是我們 真正努力的方向。
23:02
And I felt guilty about spending time on that.
581
1382026
2495
為它花時間讓我感到內疚,
23:04
That was stupid.
582
1384521
1454
那真是非常傻。
23:05
That was the future, right?
583
1385975
1051
但那就是未來,對吧?
23:07
That was a good thing to be working on.
584
1387026
2285
那是個很棒的東西, 值得為之努力。
23:09
CR: It is great to see you here.
585
1389311
1417
查理.羅斯: 很高興在這裡見到你,
23:10
It's great to hear from you,
586
1390728
1460
很高興聽到你的講述,
23:12
and a pleasure to sit at this table with you.
587
1392188
2297
和你一起坐在這也是我的榮幸。
23:14
Thanks, Larry.
588
1394485
928
謝謝賴瑞。
23:15
LP: Thank you.
589
1395413
2103
賴瑞.佩吉:謝謝你。
23:17
(Applause)
590
1397516
3932
(掌聲)
23:21
CR: Larry Page.
591
1401448
3311
查理.羅斯:賴瑞.佩吉。
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