TEDxBeaconStreet
Alex Wissner-Gross: A new equation for intelligence
阿历克斯•维斯纳-格罗斯: 有关智能的新公式
Filmed:
Readability: 5.9
2,098,891 views
是否存在一个关于智能的公式？是的， F = T ∇ Sτ 。在这个既长见识又饶有趣味的讲话中，物理学家兼电脑科学家阿历克斯•维斯纳-格罗斯解释了智能的意义。
Alex Wissner-Gross - Scientist, entrepreneur, inventor
Alex Wissner-Gross applies science and engineering principles to big (and diverse) questions, like: "What is the equation for intelligence?" and "What's the best way to raise awareness about climate change?" Full bio
Alex Wissner-Gross applies science and engineering principles to big (and diverse) questions, like: "What is the equation for intelligence?" and "What's the best way to raise awareness about climate change?" Full bio
Double-click the English transcript below to play the video.
智能--它是什么？
00:12
Intelligence -- what is it?
0
899
3667
00:16
If we take a look back at the history
1
4566
2291
当我们回顾在历史上
00:18
of how intelligence has been viewed,
2
6857
2624
智能是如何被看待的，
00:21
one seminal example has been
3
9481
3618
一个开创性的例子是
00:25
Edsger Dijkstra's famous quote that
4
13099
3477
艾兹格•迪杰斯特拉的著名引述，
00:28
"the question of whether a machine can think
5
16576
3111
"关于一台机器能否思考的问题
00:31
is about as interesting
6
19687
1310
与关于
00:32
as the question of whether a submarine
7
20997
2971
一艘潜艇是否会游泳的问题
00:35
can swim."
8
23968
1790
几乎同样有趣"。
00:37
Now, Edsger Dijkstra, when he wrote this,
9
25758
3844
当艾兹格•迪杰斯特拉
写下这句话的时候，
写下这句话的时候，
00:41
intended it as a criticism
10
29602
2054
他的用意是去批判那些
00:43
of the early pioneers of computer science,
11
31656
3000
早年间开辟了计算机科学的先锋，
00:46
like Alan Turing.
12
34656
1747
比如阿兰 · 图灵。
00:48
However, if you take a look back
13
36403
2499
然而，如果你回顾过去
00:50
and think about what have been
14
38902
1965
并予以思考，有哪些
00:52
the most empowering innovations
15
40867
1996
最有利于发展的创新，
00:54
that enabled us to build
16
42863
1879
让我们有机会能够制造出
00:56
artificial machines that swim
17
44742
2234
会游泳的机器
00:58
and artificial machines that [fly],
18
46976
2573
和会[飞]的机器，
01:01
you find that it was only through understanding
19
49549
3547
你会发现，只有通过了解
01:05
the underlying physical mechanisms
20
53096
2608
游泳和飞行
01:07
of swimming and flight
21
55704
2779
背后的物理机制，
01:10
that we were able to build these machines.
22
58483
3172
我们才有能力去制造这些机器。
01:13
And so, several years ago,
23
61655
2256
所以说，在几年前，
01:15
I undertook a program to try to understand
24
63911
3249
我着手了一个项目，
试图去了解
试图去了解
01:19
the fundamental physical mechanisms
25
67160
2634
智能背后的
01:21
underlying intelligence.
26
69794
2768
基础物理机制。
01:24
Let's take a step back.
27
72562
1860
我们先退一步说。
01:26
Let's first begin with a thought experiment.
28
74422
3149
首先，让我们从一个思维实验开始。
01:29
Pretend that you're an alien race
29
77571
2854
假装你是一个外星人，
01:32
that doesn't know anything about Earth biology
30
80425
3041
你对地球上的生物学、
01:35
or Earth neuroscience or Earth intelligence,
31
83466
3116
神经科学和智能一无所知，
01:38
but you have amazing telescopes
32
86582
2192
但你有绝佳的望远镜，
01:40
and you're able to watch the Earth,
33
88774
2362
因此你能观望地球，
01:43
and you have amazingly long lives,
34
91136
2332
你的寿命也惊人地长，
01:45
so you're able to watch the Earth
35
93468
1499
所以你可以观察地球
01:46
over millions, even billions of years.
36
94967
3442
超过数百万年，甚至几十亿年。
01:50
And you observe a really strange effect.
37
98409
3015
然后你观察到一个很奇怪的现象。
01:53
You observe that, over the course of the millennia,
38
101424
4312
你观察到，几千年来，
01:57
Earth is continually bombarded with asteroids
39
105736
4285
地球不断地与小行星发生碰撞
02:02
up until a point,
40
110021
2087
直到某一刻，
02:04
and that at some point,
41
112108
1531
而在那一刻，
02:05
corresponding roughly to our year, 2000 AD,
42
113639
4192
大约对应的是公元2000年，
02:09
asteroids that are on
43
117831
1716
那些在地球撞击轨道
02:11
a collision course with the Earth
44
119547
1931
上的小行星，
02:13
that otherwise would have collided
45
121478
1975
本该相撞
02:15
mysteriously get deflected
46
123453
2415
但却被神秘地弹开了
02:17
or they detonate before they can hit the Earth.
47
125868
3072
或者在碰到地球之前就引爆了。
02:20
Now of course, as earthlings,
48
128940
2083
当然，作为地球人，
02:23
we know the reason would be
49
131023
1544
我们知道其中的原因是
02:24
that we're trying to save ourselves.
50
132567
1756
我们正试图自我拯救。
02:26
We're trying to prevent an impact.
51
134323
3080
我们要防止撞击发生。
02:29
But if you're an alien race
52
137403
1711
但如果你是一个外星人，
02:31
who doesn't know any of this,
53
139114
1146
对这些一无所知，
02:32
doesn't have any concept of Earth intelligence,
54
140260
2514
对地球上的智能也没有任何概念，
02:34
you'd be forced to put together
55
142774
1728
这就迫使你去总结
02:36
a physical theory that explains how,
56
144502
2918
一种物理理论，
去解释其原因，
去解释其原因，
02:39
up until a certain point in time,
57
147420
2538
直到在某一刻，
02:41
asteroids that would demolish the surface of a planet
58
149958
4449
本应摧毁一个星球表面的小行星，
02:46
mysteriously stop doing that.
59
154407
3231
神秘地停止了这种行为。
02:49
And so I claim that this is the same question
60
157638
4204
因此我声称这个问题
02:53
as understanding the physical nature of intelligence.
61
161842
3998
与理解智能的物理本质的问题
是相同的。
是相同的。
02:57
So in this program that I
undertook several years ago,
undertook several years ago,
62
165840
3882
因此，在我几年前着手的
这个项目中，
这个项目中，
03:01
I looked at a variety of different threads
63
169722
2765
我研究了许多不同的线程，
03:04
across science, across a variety of disciplines,
64
172487
3162
跨越科学界，跨越多个学科，
03:07
that were pointing, I think,
65
175649
1892
在我看来，他们都指向
03:09
towards a single, underlying mechanism
66
177541
2548
一个统一的、潜在的
03:12
for intelligence.
67
180089
1581
智能机制。
03:13
In cosmology, for example,
68
181670
2546
例如在宇宙学中，
03:16
there have been a variety of
different threads of evidence
different threads of evidence
69
184216
2747
就存在着各种各样的线索，
03:18
that our universe appears to be finely tuned
70
186963
3407
它们显示我们的宇宙就
为了智能的开发，
为了智能的开发，
03:22
for the development of intelligence,
71
190370
2153
而被精准地调试过，
03:24
and, in particular, for the development
72
192523
2389
和特别是的对于发展
03:26
of universal states
73
194912
1886
世界各国
03:28
that maximize the diversity of possible futures.
74
196798
4098
去实现有最大多样化可能性的未来。
03:32
In game play, for example, in Go --
75
200896
2344
在棋牌界，举个例子，围棋--
03:35
everyone remembers in 1997
76
203240
3025
大家都记得在1997年的时候
03:38
when IBM's Deep Blue beat
Garry Kasparov at chess --
Garry Kasparov at chess --
77
206265
3951
IBM制作的机器人“深蓝“打败了
世界象棋冠军加里·卡斯帕罗夫--
世界象棋冠军加里·卡斯帕罗夫--
03:42
fewer people are aware
78
210216
1523
很少有人意识到
03:43
that in the past 10 years or so,
79
211739
2018
在过去10年左右的时间里，
03:45
the game of Go,
80
213757
1198
围棋，
03:46
arguably a much more challenging game
81
214955
1956
可以说是一个更具挑战性的游戏，
03:48
because it has a much higher branching factor,
82
216911
2425
因为它具有更高的分支系数，
03:51
has also started to succumb
83
219336
1702
也已开始屈服于
03:53
to computer game players
84
221038
1865
电脑这个游戏对手，
03:54
for the same reason:
85
222903
1573
出于同样的原因：
03:56
the best techniques right now
for computers playing Go
for computers playing Go
86
224476
2800
现在，电脑下围棋的
最佳技术方法
最佳技术方法
03:59
are techniques that try to maximize future options
87
227276
3696
是在下棋的过程中，
试图最大化
试图最大化
04:02
during game play.
88
230972
2014
未来的各种可能性。
04:04
Finally, in robotic motion planning,
89
232986
3581
最后，在机器人的运动规划中，
04:08
there have been a variety of recent techniques
90
236567
2182
有各种各样的新颖技术，
04:10
that have tried to take advantage
91
238749
1902
它们有试图利用
04:12
of abilities of robots to maximize
92
240651
3146
机器人的能力去将
04:15
future freedom of action
93
243797
1506
未来的行动自由最大化，
04:17
in order to accomplish complex tasks.
94
245303
3097
从而完成复杂的任务。
04:20
And so, taking all of these different threads
95
248400
2355
因此，考虑所有这些不同的线程
04:22
and putting them together,
96
250755
1622
并把它们放在一起，
04:24
I asked, starting several years ago,
97
252377
2640
从几年前开始我就在问，
04:27
is there an underlying mechanism for intelligence
98
255017
2850
有没有一种潜在的智能机制
04:29
that we can factor out
99
257867
1673
可以让我们分解出
04:31
of all of these different threads?
100
259540
1774
所有这些不同的线程？
04:33
Is there a single equation for intelligence?
101
261314
4593
是否存在一个
关于智能的公式？
关于智能的公式？
04:37
And the answer, I believe, is yes.
["F = T ∇ Sτ"]
["F = T ∇ Sτ"]
102
265907
3371
而我相信答案是有。
["F = T ∇ SΤ"]
["F = T ∇ SΤ"]
04:41
What you're seeing is probably
103
269278
1913
你看到的可能是
04:43
the closest equivalent to an E = mc²
104
271191
3294
我所见过最接近于 E = mc²
04:46
for intelligence that I've seen.
105
274485
2830
的智慧。
04:49
So what you're seeing here
106
277315
1702
所以你在这里看到的
04:51
is a statement of correspondence
107
279017
2669
是一张对应表，
04:53
that intelligence is a force, F,
108
281686
4435
其中智能是一种力量，F，
04:58
that acts so as to maximize future freedom of action.
109
286121
4650
它的作用是为了便于将未来的
行动自由最大化。
行动自由最大化。
05:02
It acts to maximize future freedom of action,
110
290771
2375
它的作用是将未来的
行动自由最大化，
行动自由最大化，
05:05
or keep options open,
111
293146
1628
或是保留灵活的选择权，
05:06
with some strength T,
112
294774
2225
与一种力量 T，
05:08
with the diversity of possible accessible futures, S,
113
296999
4777
和有多种可能性的、
可实现的未来，S，
可实现的未来，S，
05:13
up to some future time horizon, tau.
114
301776
2550
一直到某个未来的开始，
tau（希腊字母）。
tau（希腊字母）。
05:16
In short, intelligence doesn't like to get trapped.
115
304326
3209
简而言之，智能不喜欢被困住。
05:19
Intelligence tries to maximize
future freedom of action
future freedom of action
116
307535
3055
智能试图将未来的行动自由最大化，
05:22
and keep options open.
117
310590
2673
并保留选择权。
05:25
And so, given this one equation,
118
313263
2433
所以，鉴于这一公式，
05:27
it's natural to ask, so what can you do with this?
119
315696
2532
你自然会问，
那么这些可以让你做什么？
那么这些可以让你做什么？
05:30
How predictive is it?
120
318228
1351
它是预测性有多高？
05:31
Does it predict human-level intelligence?
121
319579
2135
它能否预测人类的智能水平？
05:33
Does it predict artificial intelligence?
122
321714
2818
它能够预测人工智能吗？
05:36
So I'm going to show you now a video
123
324532
2042
因此，我将要展示给你们一段视频，
05:38
that will, I think, demonstrate
124
326574
3420
我认为，它会展示出
05:41
some of the amazing applications
125
329994
2288
单是这一个公式的
05:44
of just this single equation.
126
332282
2319
一些惊人的应用。
05:46
(Video) Narrator: Recent research in cosmology
127
334601
1979
（视频）讲述人：
宇宙学的最近研究
宇宙学的最近研究
05:48
has suggested that universes that produce
128
336580
2047
反应了那些产生更多混乱、
05:50
more disorder, or "entropy," over their lifetimes
129
338627
3481
或者"熵"的宇宙，
在他们的生命中
在他们的生命中
05:54
should tend to have more favorable conditions
130
342108
2478
应该倾向于产生更多
有利的情况，
有利的情况，
05:56
for the existence of intelligent
beings such as ourselves.
beings such as ourselves.
131
344586
3016
让像我们这样的智慧生物
得以存在。
得以存在。
05:59
But what if that tentative cosmological connection
132
347602
2574
但假如那个在熵与智能之间
06:02
between entropy and intelligence
133
350176
1843
暂定的宇宙链接
06:04
hints at a deeper relationship?
134
352019
1771
暗示着更深层的关系呢？
06:05
What if intelligent behavior doesn't just correlate
135
353790
2564
如果智能的行为不仅只与
06:08
with the production of long-term entropy,
136
356354
1844
长期熵的生产相关，
06:10
but actually emerges directly from it?
137
358198
2318
而是直接由其产生的呢？
06:12
To find out, we developed a software engine
138
360516
2406
为了找到答案，
我们开发了一个软件引擎
我们开发了一个软件引擎
06:14
called Entropica, designed to maximize
139
362922
2503
称为 Entropica，
设计的意图是将
设计的意图是将
06:17
the production of long-term entropy
140
365425
1768
长期熵的生产最大化，
06:19
of any system that it finds itself in.
141
367193
2576
无论它身在任何系统内。
06:21
Amazingly, Entropica was able to pass
142
369769
2155
惊人的是，Entropica 通过了
06:23
multiple animal intelligence
tests, play human games,
tests, play human games,
143
371924
3456
多个动物的智能测验、
玩人类的游戏、
玩人类的游戏、
06:27
and even earn money trading stocks,
144
375380
2146
甚至在股票交易中赚钱，
06:29
all without being instructed to do so.
145
377526
2111
而且完全没有被给出那些指示。
06:31
Here are some examples of Entropica in action.
146
379637
2518
下面是一些 Entropica 的行动实例。
06:34
Just like a human standing
upright without falling over,
upright without falling over,
147
382155
3205
就像人类站立不会跌到，
06:37
here we see Entropica
148
385360
1230
这里我们可以看到 Entropica
06:38
automatically balancing a pole using a cart.
149
386590
2885
自动地使用购物车去平衡棍子。
06:41
This behavior is remarkable in part
150
389475
2012
这种行为可以说是非常卓越的
06:43
because we never gave Entropica a goal.
151
391487
2331
因为我们从未给 Entropica
设定一个目标。
设定一个目标。
06:45
It simply decided on its own to balance the pole.
152
393818
3157
它自己就决定去平衡那根棍子。
06:48
This balancing ability will have appliactions
153
396975
2132
这种平衡能力将能应用于
06:51
for humanoid robotics
154
399107
1397
人形机器人
06:52
and human assistive technologies.
155
400504
2515
和人类的辅助科技。
06:55
Just as some animals can use objects
156
403019
2001
正如一些动物可以使用
06:57
in their environments as tools
157
405020
1442
环境中的物体作为工具
06:58
to reach into narrow spaces,
158
406462
1987
去伸入狭窄的空间，
07:00
here we see that Entropica,
159
408449
1882
这里我们可以看到 Entropica，
07:02
again on its own initiative,
160
410331
1838
同样是自主的，
07:04
was able to move a large
disk representing an animal
disk representing an animal
161
412169
2910
能够移动一个表示动物的大圆盘
07:07
around so as to cause a small disk,
162
415079
2345
去把一个表示工具的小圆盘，
07:09
representing a tool, to reach into a confined space
163
417424
2771
去深入一个狭窄的空间，
07:12
holding a third disk
164
420195
1537
那里有第三个圆盘，
07:13
and release the third disk
from its initially fixed position.
from its initially fixed position.
165
421732
2972
并把第三个圆盘从它初始
的静态解放出来.
的静态解放出来.
07:16
This tool use ability will have applications
166
424704
2189
这种工具的使用能力将能运用于
07:18
for smart manufacturing and agriculture.
167
426893
2359
智能制造业和农业。
07:21
In addition, just as some other animals
168
429252
1944
此外，正如其他一些动物
07:23
are able to cooperate by pulling
opposite ends of a rope
opposite ends of a rope
169
431196
2696
能够合作起来同时去拉
一根绳子的两端
一根绳子的两端
07:25
at the same time to release food,
170
433892
2053
从而释放食物，
07:27
here we see that Entropica is able to accomplish
171
435945
2295
这里我们可以看到 Entropica 有能力完成
07:30
a model version of that task.
172
438240
1988
这项任务的模型版本。
07:32
This cooperative ability has interesting implications
173
440228
2522
这种合作能力能够带来有趣的影响，
07:34
for economic planning and a variety of other fields.
174
442750
3435
在经济规划和各种其他领域中。
07:38
Entropica is broadly applicable
175
446185
2071
Entropica 可以广泛适用于
07:40
to a variety of domains.
176
448256
1943
各种各样的领域。
07:42
For example, here we see it successfully
177
450199
2442
例如，在这里我们看到它成功的
07:44
playing a game of pong against itself,
178
452641
2559
与自己玩乒乓球游戏，
07:47
illustrating its potential for gaming.
179
455200
2343
说明其在游戏界的潜力。
07:49
Here we see Entropica orchestrating
180
457543
1919
在这里我们看到 Entropica 指挥着
07:51
new connections on a social network
181
459462
1839
社交网络上新的关系，
07:53
where friends are constantly falling out of touch
182
461301
2760
在这朋友们不断的失去联系
07:56
and successfully keeping
the network well connected.
the network well connected.
183
464061
2856
并成功地保持有效的网络连接。
07:58
This same network orchestration ability
184
466917
2298
这种相同的网络指挥能力
08:01
also has applications in health care,
185
469215
2328
在医疗保健、能源、和智能方面
08:03
energy, and intelligence.
186
471543
3232
都有相关的应用。
08:06
Here we see Entropica directing the paths
187
474775
2085
这里我们可以看到 Entropica
08:08
of a fleet of ships,
188
476860
1486
指挥一支舰队的路径，
08:10
successfully discovering and
utilizing the Panama Canal
utilizing the Panama Canal
189
478346
3175
成功地发现并利用巴拿马运河，
08:13
to globally extend its reach from the Atlantic
190
481521
2458
然后将其范围从大西洋到太平洋
08:15
to the Pacific.
191
483979
1529
全球性地扩大。
08:17
By the same token, Entropica
192
485508
1727
同样的，Entropica
08:19
is broadly applicable to problems
193
487235
1620
可以广泛地适用于
08:20
in autonomous defense, logistics and transportation.
194
488855
5302
自主防御、 物流和运输地应用。
08:26
Finally, here we see Entropica
195
494173
2030
最后，在这里我们看到 Entropica
08:28
spontaneously discovering and executing
196
496203
2723
自主地发现和执行
08:30
a buy-low, sell-high strategy
197
498926
2067
一个低买高卖的策略，
08:32
on a simulated range traded stock,
198
500993
2178
这是在模拟的范围交易股票上，
08:35
successfully growing assets under management
199
503171
2331
它成功地将其管理的资产
08:37
exponentially.
200
505502
1424
成指数升涨。
08:38
This risk management ability
201
506926
1308
这种风险管理的能力
08:40
will have broad applications in finance
202
508234
2487
将在金融和保险领域
08:42
and insurance.
203
510721
3328
有广泛的应用。
08:46
Alex Wissner-Gross: So what you've just seen
204
514049
2091
阿历克斯•维斯纳-格罗斯：
你刚看到的
你刚看到的
08:48
is that a variety of signature human intelligent
205
516140
4392
是各种具有代表性的人类智能
08:52
cognitive behaviors
206
520532
1757
的认知行为，
08:54
such as tool use and walking upright
207
522289
2831
例如工具的使用、直立行走
08:57
and social cooperation
208
525120
2029
和社会合作，
08:59
all follow from a single equation,
209
527149
2972
它们都遵循一个公式，
09:02
which drives a system
210
530121
1932
该公式所驱动的系统
09:04
to maximize its future freedom of action.
211
532053
3911
是要将其未来的行动自由最大化。
09:07
Now, there's a profound irony here.
212
535964
3007
现在，这里存在一个深刻的讽刺。
09:10
Going back to the beginning
213
538971
2024
回到最初，
09:12
of the usage of the term robot,
214
540995
3273
机器人这个术语的用法，
09:16
the play "RUR,"
215
544268
2903
"RUR，"这出戏，
09:19
there was always a concept
216
547171
2235
总存在一种概念就是
09:21
that if we developed machine intelligence,
217
549406
3226
如果我们开发了机器智能
09:24
there would be a cybernetic revolt.
218
552632
3027
就会产生一个人工智能的叛变。
09:27
The machines would rise up against us.
219
555659
3551
机器会奋起反抗我们。
09:31
One major consequence of this work
220
559210
2319
这项工作的主要成果之一
09:33
is that maybe all of these decades,
221
561529
2769
就是也许这几十年间，
09:36
we've had the whole concept of cybernetic revolt
222
564298
2976
我们对于人工智能的叛变
的整个概念
的整个概念
09:39
in reverse.
223
567274
2011
是颠倒的。
09:41
It's not that machines first become intelligent
224
569285
3279
机器不是先有了智慧
09:44
and then megalomaniacal
225
572564
2015
然后才变得狂妄
09:46
and try to take over the world.
226
574579
2224
并试图接管世界的。
09:48
It's quite the opposite,
227
576803
1434
其实几乎是相反的，
09:50
that the urge to take control
228
578237
2906
那种迫切的欲望，
09:53
of all possible futures
229
581143
2261
想要控制所有未来的所有可能
09:55
is a more fundamental principle
230
583404
2118
是比智能更基本的
09:57
than that of intelligence,
231
585522
1363
一个原则，
09:58
that general intelligence may in fact emerge
232
586885
3700
综合智能事实上可能是从
10:02
directly from this sort of control-grabbing,
233
590585
3559
这种控制欲中直接产生的，
10:06
rather than vice versa.
234
594144
4185
而不是反之。
10:10
Another important consequence is goal seeking.
235
598329
3769
另一个重要的成果是寻找目标。
10:14
I'm often asked, how does the ability to seek goals
236
602098
4360
我经常被问道，
寻找目标的能力
寻找目标的能力
10:18
follow from this sort of framework?
237
606458
1620
怎么会遵循这种框架结构呢？
10:20
And the answer is, the ability to seek goals
238
608078
3028
答案是，寻找目标的能力
10:23
will follow directly from this
239
611106
1882
将直接遵循它，
10:24
in the following sense:
240
612988
1834
道理是这样的：
10:26
just like you would travel through a tunnel,
241
614822
2865
就像你要穿过一条隧道，
10:29
a bottleneck in your future path space,
242
617687
2505
你未来道路空间中的一个瓶颈，
10:32
in order to achieve many other
243
620192
1871
为了在以后实现许多
10:34
diverse objectives later on,
244
622063
2021
其他的各种目标，
10:36
or just like you would invest
245
624084
2372
或者就像你会投资
10:38
in a financial security,
246
626456
1787
于金融证券，
10:40
reducing your short-term liquidity
247
628243
2237
减少你的短期流动性
10:42
in order to increase your wealth over the long term,
248
630480
2400
从而长远的增加你的财富，
10:44
goal seeking emerges directly
249
632880
2337
目标的寻求直接涌现于
10:47
from a long-term drive
250
635217
1729
长期的驱动，
10:48
to increase future freedom of action.
251
636946
4037
为了增加未来的行动自由。
10:52
Finally, Richard Feynman, famous physicist,
252
640983
3528
最后，理查德 · 费曼，
这位著名的物理学家，
这位著名的物理学家，
10:56
once wrote that if human civilization were destroyed
253
644511
3672
曾经写道，
如果人类文明被摧毁
如果人类文明被摧毁
11:00
and you could pass only a single concept
254
648183
1893
并且你只能将一个概念
11:02
on to our descendants
255
650076
1371
传承给我们的后代，
11:03
to help them rebuild civilization,
256
651447
2307
来帮助他们重建文明，
11:05
that concept should be
257
653754
1686
这个概念应该是
11:07
that all matter around us
258
655440
1852
我们身边的一切物质
11:09
is made out of tiny elements
259
657292
2323
都是由微小的元素组成的，
11:11
that attract each other when they're far apart
260
659615
2508
它们之间距离远的时候
会相互吸引，
会相互吸引，
11:14
but repel each other when they're close together.
261
662123
3330
但在靠的很近时
它们会互相排斥。
它们会互相排斥。
11:17
My equivalent of that statement
262
665453
1781
我与这句话等同的声明，
11:19
to pass on to descendants
263
667234
1268
来传递给后代，
11:20
to help them build artificial intelligences
264
668502
2712
帮助他们建立人工智能
11:23
or to help them understand human intelligence,
265
671214
2949
或是帮助他们理解
人类的智慧，
人类的智慧，
11:26
is the following:
266
674163
1267
是如下的话：
11:27
Intelligence should be viewed
267
675430
2053
智能应该被看作是
11:29
as a physical process
268
677483
1413
一个物理过程，
11:30
that tries to maximize future freedom of action
269
678896
2965
它试图将未来的行动自由最大化
11:33
and avoid constraints in its own future.
270
681861
3616
并且避免在自己的未来中的约束。
11:37
Thank you very much.
271
685477
1358
非常感谢。
11:38
(Applause)
272
686835
4000
（掌声）
ABOUT THE SPEAKER
Alex Wissner-Gross - Scientist, entrepreneur, inventorAlex Wissner-Gross applies science and engineering principles to big (and diverse) questions, like: "What is the equation for intelligence?" and "What's the best way to raise awareness about climate change?"
Why you should listen
Alex Wissner-Gross is a serial big-picture thinker. He applies physics and computer science principles to a wide variety of topics, like human intelligence, climate change and financial trading.
Lately Wissner-Gross started wondering: Why have we searched for so long to understand intelligence? Can it really be this elusive? His latest work posits that intelligence can indeed be defined physically, as a dynamic force, rather than a static property. He explains intelligence in terms of causal entropic forces, ultimately defining it as "a force to maximize future freedom of action."
Wissner-Gross is a fellow at the Harvard Institute for Applied Computational Science and a research affiliate at the MIT Media Lab. He has a Ph.D. in physics from Harvard and bachelor's degrees in physics, electrical science and engineering, and mathematics from MIT.
Alex Wissner-Gross | Speaker | TED.com