Skylar Tibbits: Can we make things that make themselves?

75,656 views ・ 2011-09-01

TED


請雙擊下方英文字幕播放視頻。

譯者: Ana Choi 審譯者: Ann Lee
00:15
Today I'd like to show you
0
15260
2000
今天,我想向你們展示
00:17
the future of the way we make things.
1
17260
2000
我們未來製造東西的方式。
00:19
I believe that soon our buildings and machines
2
19260
2000
我相信,我們的建築物和機器
00:21
will be self-assembling,
3
21260
2000
將很快便能自組,
00:23
replicating and repairing themselves.
4
23260
2000
複製和修復自己。
00:25
So I'm going to show you
5
25260
2000
所以,我要告訴你,
00:27
what I believe is the current state of manufacturing,
6
27260
2000
我相信是當前的製造業狀態,
00:29
and then compare that to some natural systems.
7
29260
3000
然後比較一些自然生態系統。
00:32
So in the current state of manufacturing, we have skyscrapers --
8
32260
3000
在當前的製造業狀態,我們有摩天大樓 --
00:35
two and a half years [of assembly time],
9
35260
2000
兩年半的時間,
00:37
500,000 to a million parts,
10
37260
2000
50萬至一百萬個部分組成,
00:39
fairly complex,
11
39260
2000
相當複雜,
00:41
new, exciting technologies in steel, concrete, glass.
12
41260
3000
有令人振奮的新技術, 鋼鐵,水泥,玻璃。
00:44
We have exciting machines
13
44260
2000
我們亦有令人振奮的機器,
00:46
that can take us into space --
14
46260
2000
我們可以帶到太空 --
00:48
five years [of assembly time], 2.5 million parts.
15
48260
3000
250萬個部分。
00:51
But on the other side, if you look at the natural systems,
16
51260
3000
但在另一方面,如果你看一下在自然生態系統,
00:54
we have proteins
17
54260
2000
我們有
00:56
that have two million types,
18
56260
2000
兩百萬類型的蛋白質,
00:58
can fold in 10,000 nanoseconds,
19
58260
2000
可以在一萬納秒折叠,
01:00
or DNA with three billion base pairs
20
60260
2000
或DNA有30億個鹼基對,
01:02
we can replicate in roughly an hour.
21
62260
3000
我們可以在大約一個小時複製。
01:05
So there's all of this complexity
22
65260
2000
因此,雖然在我們這
01:07
in our natural systems,
23
67260
2000
自然生態系統的複雜性,
01:09
but they're extremely efficient,
24
69260
2000
但它們效率非常高,
01:11
far more efficient than anything we can build,
25
71260
2000
遠遠超過任何我們可以建立的東西,
01:13
far more complex than anything we can build.
26
73260
2000
遠遠超過任何我們可以建立複雜的高效。
01:15
They're far more efficient in terms of energy.
27
75260
2000
它們在能源方面更為有效。
01:17
They hardly ever make mistakes.
28
77260
3000
它們幾乎沒有犯錯誤。
01:20
And they can repair themselves for longevity.
29
80260
2000
而且它們可以修復自己健康長壽。
01:22
So there's something super interesting about natural systems.
30
82260
3000
因此,有一些自然生態系統是超級有趣。
01:25
And if we can translate that
31
85260
2000
如果我們能夠將它轉化
01:27
into our built environment,
32
87260
2000
為我們的建築環境,
01:29
then there's some exciting potential for the way that we build things.
33
89260
2000
那麼便會有一些令人興奮的潛力方式幫助我們建設東西。
01:31
And I think the key to that is self-assembly.
34
91260
3000
我認為關鍵是自我組裝。
01:34
So if we want to utilize self-assembly in our physical environment,
35
94260
3000
因此,如果我們要利用我們的物理環境中的自組裝,
01:37
I think there's four key factors.
36
97260
2000
我認為有四個關鍵因素。
01:39
The first is that we need to decode
37
99260
2000
首先,我們需要我們所要
01:41
all of the complexity of what we want to build --
38
101260
2000
建設的複雜性解碼--
01:43
so our buildings and machines.
39
103260
2000
便是我們的建築物和機器。
01:45
And we need to decode that into simple sequences --
40
105260
2000
我們需要解碼成簡單的序列 --
01:47
basically the DNA of how our buildings work.
41
107260
2000
基本上是我們的建築物如何運作的DNA。
01:49
Then we need programmable parts
42
109260
2000
然後,我們需要可編程的部分,
01:51
that can take that sequence
43
111260
2000
可以利用該序列
01:53
and use that to fold up, or reconfigure.
44
113260
3000
便使用來折疊起來,或重新配置。
01:56
We need some energy that's going to allow that to activate,
45
116260
3000
我們需要一些能源將允許激活,
01:59
allow our parts to be able to fold up from the program.
46
119260
3000
讓我們的部分可以折疊程序。
02:02
And we need some type of error correction redundancy
47
122260
2000
我們需要某種類型的糾錯冗餘,
02:04
to guarantee that we have successfully built what we want.
48
124260
3000
以保證我們已經成功地構建我們所希望的西東。
02:07
So I'm going to show you a number of projects
49
127260
2000
所以我要告訴你一些項目,
02:09
that my colleagues and I at MIT are working on
50
129260
2000
是我在麻省理工學院的同事和正在
02:11
to achieve this self-assembling future.
51
131260
2000
實現這種未來的自我組裝。
02:13
The first two are the MacroBot and DeciBot.
52
133260
3000
第一兩個是MacroBot和DeciBot。
02:16
So these projects are large-scale reconfigurable robots --
53
136260
4000
因此,這些項目都是大型的可重構機器人 --
02:20
8 ft., 12 ft. long proteins.
54
140260
3000
8英尺,12英尺長的蛋白質。
02:23
They're embedded with mechanical electrical devices, sensors.
55
143260
3000
它們與機電設備,傳感器嵌入。
02:26
You decode what you want to fold up into,
56
146260
2000
你想要解碼什麼便折疊成什麼,
02:28
into a sequence of angles --
57
148260
2000
成序列的角度 --
02:30
so negative 120, negative 120, 0, 0,
58
150260
2000
負120,負120,0,0,
02:32
120, negative 120 -- something like that;
59
152260
3000
120,負120 -- 類似的東西,
02:35
so a sequence of angles, or turns,
60
155260
2000
這樣的角度,或輪流順序,
02:37
and you send that sequence through the string.
61
157260
3000
你便發送通過字符串序列。
02:40
Each unit takes its message -- so negative 120 --
62
160260
3000
每個單位都需要它的消息 -- 負120。
02:43
it rotates to that, checks if it got there
63
163260
2000
它是旋轉​​的,檢查它是否到了那裡,
02:45
and then passes it to its neighbor.
64
165260
3000
然後把它傳遞給它的鄰居。
02:48
So these are the brilliant scientists,
65
168260
2000
這些傑出的科學家,
02:50
engineers, designers that worked on this project.
66
170260
2000
工程師,設計師,在這個項目上工作。
02:52
And I think it really brings to light:
67
172260
2000
我認為它真正在揭示:
02:54
Is this really scalable?
68
174260
2000
這是否真正的可擴展呢?
02:56
I mean, thousands of dollars, lots of man hours
69
176260
2000
我的意思是,數千美元,大量的工時,
02:58
made to make this eight-foot robot.
70
178260
3000
製造這8英尺的機器人。
03:01
Can we really scale this up? Can we really embed robotics into every part?
71
181260
3000
我們能否真正大規模跟進呢?我們能不能真正嵌入機器到每一個部分?
03:04
The next one questions that
72
184260
2000
下一個問題,
03:06
and looks at passive nature,
73
186260
2000
以及著眼於被動性,
03:08
or passively trying to have reconfiguration programmability.
74
188260
3000
或被動地試圖重新配置可編程。
03:11
But it goes a step further,
75
191260
2000
但它更進一步,
03:13
and it tries to have actual computation.
76
193260
2000
嘗試以實際式計算。
03:15
It basically embeds the most fundamental building block of computing,
77
195260
2000
它基本上是最根本的計算,
03:17
the digital logic gate,
78
197260
2000
數字邏輯,
03:19
directly into your parts.
79
199260
2000
直接嵌入到你的零件。
03:21
So this is a NAND gate.
80
201260
2000
這是一個與非門。
03:23
You have one tetrahedron which is the gate
81
203260
2000
你有一個正四面體, 它是門,
03:25
that's going to do your computing,
82
205260
2000
會做你的計算,
03:27
and you have two input tetrahedrons.
83
207260
2000
和你有兩個可以輸入的正四面體。
03:29
One of them is the input from the user, as you're building your bricks.
84
209260
3000
其中之一是來自用戶的輸入,像為你構建你的磚。
03:32
The other one is from the previous brick that was placed.
85
212260
3000
另一種是從以前被放置的磚。
03:35
And then it gives you an output in 3D space.
86
215260
3000
然後它可以讓你在三維空間中的輸出。
03:38
So what this means
87
218260
2000
因此,這意味著
03:40
is that the user can start plugging in what they want the bricks to do.
88
220260
3000
用戶可以啟動他們想要做的磚堵。
03:43
It computes on what it was doing before
89
223260
2000
它計算它是之前做什麼,
03:45
and what you said you wanted it to do.
90
225260
2000
你說什麼,你想要它做的事情。
03:47
And now it starts moving in three-dimensional space --
91
227260
2000
現在它已經開始在三維空間中移動 --
03:49
so up or down.
92
229260
2000
向上或向下。
03:51
So on the left-hand side, [1,1] input equals 0 output, which goes down.
93
231260
3000
因此,在左側,[1,1]輸入等於輸出0,它便向下。
03:54
On the right-hand side,
94
234260
2000
在右側,
03:56
[0,0] input is a 1 output, which goes up.
95
236260
3000
[0,0]輸入1輸出,它便上升。
03:59
And so what that really means
96
239260
2000
這真正的意思是什麼,
04:01
is that our structures now contain the blueprints
97
241260
2000
這是我們的結構現在正包含着
04:03
of what we want to build.
98
243260
2000
我們所要建設的藍圖。
04:05
So they have all of the information embedded in them of what was constructed.
99
245260
3000
它們有所有的構建信息嵌入其中。
04:08
So that means that we can have some form of self-replication.
100
248260
3000
因此,這意味著我們可以有某種形式的自我複製。
04:11
In this case I call it self-guided replication,
101
251260
3000
在這種情況下,我把它稱為自導複製,
04:14
because your structure contains the exact blueprints.
102
254260
2000
因為你的結構包含着確切的藍圖。
04:16
If you have errors, you can replace a part.
103
256260
2000
如果有錯誤,可以更換部件。
04:18
All the local information is embedded to tell you how to fix it.
104
258260
3000
所有局部嵌入的信息會告訴你如何解決它。
04:21
So you could have something that climbs along and reads it
105
261260
2000
所以,你可以擁有攀登的東西將它讀取,
04:23
and can output at one to one.
106
263260
2000
並且可以在一對一輸出。
04:25
It's directly embedded; there's no external instructions.
107
265260
2000
它直接嵌入; 沒有任何外部的指令。
04:27
So the last project I'll show is called Biased Chains,
108
267260
3000
我將展示的最後一個項目被稱為偏置鏈,
04:30
and it's probably the most exciting example that we have right now
109
270260
3000
它可能是我們現在被動自組裝系統
04:33
of passive self-assembly systems.
110
273260
2000
最令人興奮的例子。
04:35
So it takes the reconfigurability
111
275260
2000
它採取需要的可重構性
04:37
and programmability
112
277260
2000
和可編程性,
04:39
and makes it a completely passive system.
113
279260
3000
並使它製造完全處於被動的系統。
04:43
So basically you have a chain of elements.
114
283260
2000
所以基本上你是有一個元素鏈。
04:45
Each element is completely identical,
115
285260
2000
每個元素是完全相同的,
04:47
and they're biased.
116
287260
2000
而且它們偏倚。
04:49
So each chain, or each element, wants to turn right or left.
117
289260
3000
因此,每一條鏈,每個元素,可以拐左邊或右邊。
04:52
So as you assemble the chain, you're basically programming it.
118
292260
3000
所以當你組裝鏈,你基本上是在編程。
04:55
You're telling each unit if it should turn right or left.
119
295260
3000
你是在告訴每個單位是否應該向左或向右轉。
04:58
So when you shake the chain,
120
298260
3000
所以,當你搖晃鏈,
05:01
it then folds up
121
301260
2000
它便從然折疊成
05:03
into any configuration that you've programmed in --
122
303260
3000
任何你編程的配置--
05:06
so in this case, a spiral,
123
306260
2000
在這種情況下,一個螺旋,
05:08
or in this case,
124
308260
3000
或在這種情況下,
05:11
two cubes next to each other.
125
311260
3000
兩個彼此相鄰的立方體。
05:14
So you can basically program
126
314260
2000
因此你基本上可以序程
05:16
any three-dimensional shape --
127
316260
2000
任何立體形狀 --
05:18
or one-dimensional, two-dimensional -- up into this chain completely passively.
128
318260
3000
一維,二維 -- 完全被動地進入這條產業鏈。
05:21
So what does this tell us about the future?
129
321260
2000
這是告訴我們的未來是什麼呢?
05:23
I think that it's telling us
130
323260
2000
我認為,它告訴我們,
05:25
that there's new possibilities for self-assembly, replication, repair
131
325260
3000
在我們的物理結構,建築物有新的自組裝,
05:28
in our physical structures, our buildings, machines.
132
328260
3000
複製,機器維修的可能性。
05:31
There's new programmability in these parts.
133
331260
2000
在這些地區有新的可編程。
05:33
And from that you have new possibilities for computing.
134
333260
2000
並從這些你會有新的計算可能性。
05:35
We'll have spatial computing.
135
335260
2000
我們將會有空間的計算。
05:37
Imagine if our buildings, our bridges, machines,
136
337260
2000
試想一下,如果我們的建築物,橋樑,機器,
05:39
all of our bricks could actually compute.
137
339260
2000
我們所有的磚其實可以計算。
05:41
That's amazing parallel and distributed computing power,
138
341260
2000
這是驚人的並行和分佈式的計算能力,
05:43
new design possibilities.
139
343260
2000
新的設計可能性。
05:45
So it's exciting potential for this.
140
345260
2000
因此,這是一個令人興奮的潛力。
05:47
So I think these projects I've showed here
141
347260
2000
所以,我覺得我已給你表明的,
05:49
are just a tiny step towards this future,
142
349260
2000
僅僅是對這個未來的一小步,
05:51
if we implement these new technologies
143
351260
2000
如果我們能實施這些新技術
05:53
for a new self-assembling world.
144
353260
2000
創造一個新的自組裝世界。
05:55
Thank you.
145
355260
2000
謝謝。
05:57
(Applause)
146
357260
2000
(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