TED2011
Skylar Tibbits: Can we make things that make themselves?
Skylar Tibbits: 我們能不能製造一些可以製造自己的東西呢?
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麻省理工學院的研究員 Skylar Tibbits在建立自組裝工程 -- 想法是: 不是建設東西（一把椅子，或一個摩天大樓），我們可以創造自己製造的材料，很像DNA本身拉鍊的方式。這是一個在早期階段的大概念; Tibbits向我們顯示了三個在實驗室的項目, 隱射着在一個自我組裝的未來會可能是什麼樣子。
Skylar Tibbits - Inventor
Skylar Tibbits, a TED Fellow, is an artist and computational architect working on "smart" components that can assemble themselves. Full bio
Skylar Tibbits, a TED Fellow, is an artist and computational architect working on "smart" components that can assemble themselves. Full bio
Double-click the English transcript below to play the video.
00:15
Today I'd like to show you
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今天，我想向你們展示
00:17
the future of the way we make things.
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我們未來製造東西的方式。
00:19
I believe that soon our buildings and machines
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我相信，我們的建築物和機器
00:21
will be self-assembling,
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將很快便能自組，
00:23
replicating and repairing themselves.
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複製和修復自己。
00:25
So I'm going to show you
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所以，我要告訴你，
00:27
what I believe is the current state of manufacturing,
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我相信是當前的製造業狀態，
00:29
and then compare that to some natural systems.
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然後比較一些自然生態系統。
00:32
So in the current state of manufacturing, we have skyscrapers --
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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],
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兩年半的時間,
00:37
500,000 to a million parts,
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50萬至一百萬個部分組成，
00:39
fairly complex,
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相當複雜，
00:41
new, exciting technologies in steel, concrete, glass.
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有令人振奮的新技術, 鋼鐵，水泥，玻璃。
00:44
We have exciting machines
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我們亦有令人振奮的機器，
00:46
that can take us into space --
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我們可以帶到太空 --
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five years [of assembly time], 2.5 million parts.
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250萬個部分。
00:51
But on the other side, if you look at the natural systems,
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但在另一方面，如果你看一下在自然生態系統，
00:54
we have proteins
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我們有
00:56
that have two million types,
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兩百萬類型的蛋白質，
00:58
can fold in 10,000 nanoseconds,
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可以在一萬納秒折叠，
01:00
or DNA with three billion base pairs
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或DNA有30億個鹼基對，
01:02
we can replicate in roughly an hour.
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我們可以在大約一個小時複製。
01:05
So there's all of this complexity
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因此，雖然在我們這
01:07
in our natural systems,
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自然生態系統的複雜性，
01:09
but they're extremely efficient,
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但它們效率非常高，
01:11
far more efficient than anything we can build,
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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.
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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.
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它們在能源方面更為有效。
01:17
They hardly ever make mistakes.
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它們幾乎沒有犯錯誤。
01:20
And they can repair themselves for longevity.
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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.
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因此，有一些自然生態系統是超級有趣。
01:25
And if we can translate that
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如果我們能夠將它轉化
01:27
into our built environment,
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為我們的建築環境，
01:29
then there's some exciting potential for the way that we build things.
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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.
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我認為關鍵是自我組裝。
01:34
So if we want to utilize self-assembly in our physical environment,
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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.
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我認為有四個關鍵因素。
01:39
The first is that we need to decode
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首先，我們需要我們所要
01:41
all of the complexity of what we want to build --
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建設的複雜性解碼--
01:43
so our buildings and machines.
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便是我們的建築物和機器。
01:45
And we need to decode that into simple sequences --
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我們需要解碼成簡單的序列 --
01:47
basically the DNA of how our buildings work.
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基本上是我們的建築物如何運作的DNA。
01:49
Then we need programmable parts
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然後，我們需要可編程的部分，
01:51
that can take that sequence
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可以利用該序列
01:53
and use that to fold up, or reconfigure.
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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,
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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.
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讓我們的部分可以折疊程序。
02:02
And we need some type of error correction redundancy
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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.
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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
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所以我要告訴你一些項目，
02:09
that my colleagues and I at MIT are working on
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是我在麻省理工學院的同事和正在
02:11
to achieve this self-assembling future.
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實現這種未來的自我組裝。
02:13
The first two are the MacroBot and DeciBot.
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第一兩個是MacroBot和DeciBot。
02:16
So these projects are large-scale reconfigurable robots --
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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.
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8英尺，12英尺長的蛋白質。
02:23
They're embedded with mechanical electrical devices, sensors.
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它們與機電設備，傳感器嵌入。
02:26
You decode what you want to fold up into,
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你想要解碼什麼便折疊成什麼，
02:28
into a sequence of angles --
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成序列的角度 --
02:30
so negative 120, negative 120, 0, 0,
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負120，負120，0，0，
02:32
120, negative 120 -- something like that;
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120，負120 -- 類似的東西，
02:35
so a sequence of angles, or turns,
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這樣的角度，或輪流順序，
02:37
and you send that sequence through the string.
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你便發送通過字符串序列。
02:40
Each unit takes its message -- so negative 120 --
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每個單位都需要它的消息 -- 負120。
02:43
it rotates to that, checks if it got there
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它是旋轉的，檢查它是否到了那裡，
02:45
and then passes it to its neighbor.
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然後把它傳遞給它的鄰居。
02:48
So these are the brilliant scientists,
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這些傑出的科學家，
02:50
engineers, designers that worked on this project.
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工程師，設計師，在這個項目上工作。
02:52
And I think it really brings to light:
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我認為它真正在揭示：
02:54
Is this really scalable?
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這是否真正的可擴展呢？
02:56
I mean, thousands of dollars, lots of man hours
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我的意思是，數千美元，大量的工時，
02:58
made to make this eight-foot robot.
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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?
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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
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下一個問題，
03:06
and looks at passive nature,
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以及著眼於被動性，
03:08
or passively trying to have reconfiguration programmability.
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或被動地試圖重新配置可編程。
03:11
But it goes a step further,
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但它更進一步，
03:13
and it tries to have actual computation.
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嘗試以實際式計算。
03:15
It basically embeds the most fundamental building block of computing,
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它基本上是最根本的計算，
03:17
the digital logic gate,
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數字邏輯，
03:19
directly into your parts.
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直接嵌入到你的零件。
03:21
So this is a NAND gate.
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這是一個與非門。
03:23
You have one tetrahedron which is the gate
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你有一個正四面體, 它是門，
03:25
that's going to do your computing,
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會做你的計算，
03:27
and you have two input tetrahedrons.
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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.
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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.
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另一種是從以前被放置的磚。
03:35
And then it gives you an output in 3D space.
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然後它可以讓你在三維空間中的輸出。
03:38
So what this means
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因此，這意味著
03:40
is that the user can start plugging in what they want the bricks to do.
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用戶可以啟動他們想要做的磚堵。
03:43
It computes on what it was doing before
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它計算它是之前做什麼，
03:45
and what you said you wanted it to do.
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你說什麼，你想要它做的事情。
03:47
And now it starts moving in three-dimensional space --
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現在它已經開始在三維空間中移動 --
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so up or down.
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向上或向下。
03:51
So on the left-hand side, [1,1] input equals 0 output, which goes down.
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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,
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在右側，
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[0,0] input is a 1 output, which goes up.
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[0,0]輸入1輸出，它便上升。
03:59
And so what that really means
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這真正的意思是什麼，
04:01
is that our structures now contain the blueprints
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這是我們的結構現在正包含着
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of what we want to build.
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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.
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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.
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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,
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在這種情況下，我把它稱為自導複製，
04:14
because your structure contains the exact blueprints.
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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.
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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.
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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
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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.
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並且可以在一對一輸出。
04:25
It's directly embedded; there's no external instructions.
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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,
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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
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它可能是我們現在被動自組裝系統
04:33
of passive self-assembly systems.
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最令人興奮的例子。
04:35
So it takes the reconfigurability
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它採取需要的可重構性
04:37
and programmability
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和可編程性，
04:39
and makes it a completely passive system.
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並使它製造完全處於被動的系統。
04:43
So basically you have a chain of elements.
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所以基本上你是有一個元素鏈。
04:45
Each element is completely identical,
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每個元素是完全相同的，
04:47
and they're biased.
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而且它們偏倚。
04:49
So each chain, or each element, wants to turn right or left.
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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.
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所以當你組裝鏈，你基本上是在編程。
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You're telling each unit if it should turn right or left.
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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,
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所以，當你搖晃鏈，
05:01
it then folds up
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它便從然折疊成
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into any configuration that you've programmed in --
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任何你編程的配置--
05:06
so in this case, a spiral,
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在這種情況下，一個螺旋，
05:08
or in this case,
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或在這種情況下，
05:11
two cubes next to each other.
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兩個彼此相鄰的立方體。
05:14
So you can basically program
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因此你基本上可以序程
05:16
any three-dimensional shape --
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任何立體形狀 --
05:18
or one-dimensional, two-dimensional -- up into this chain completely passively.
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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?
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這是告訴我們的未來是什麼呢？
05:23
I think that it's telling us
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我認為，它告訴我們，
05:25
that there's new possibilities for self-assembly, replication, repair
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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.
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複製，機器維修的可能性。
05:31
There's new programmability in these parts.
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在這些地區有新的可編程。
05:33
And from that you have new possibilities for computing.
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並從這些你會有新的計算可能性。
05:35
We'll have spatial computing.
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我們將會有空間的計算。
05:37
Imagine if our buildings, our bridges, machines,
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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.
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我們所有的磚其實可以計算。
05:41
That's amazing parallel and distributed computing power,
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這是驚人的並行和分佈式的計算能力，
05:43
new design possibilities.
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新的設計可能性。
05:45
So it's exciting potential for this.
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因此，這是一個令人興奮的潛力。
05:47
So I think these projects I've showed here
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所以，我覺得我已給你表明的，
05:49
are just a tiny step towards this future,
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僅僅是對這個未來的一小步，
05:51
if we implement these new technologies
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如果我們能實施這些新技術
05:53
for a new self-assembling world.
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創造一個新的自組裝世界。
05:55
Thank you.
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謝謝。
05:57
(Applause)
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(掌聲)
ABOUT THE SPEAKER
Skylar Tibbits - InventorSkylar Tibbits, a TED Fellow, is an artist and computational architect working on "smart" components that can assemble themselves.
Why you should listen
Can we create objects that assemble themselves -- that zip together like a strand of DNA or that have the ability for transformation embedded into them? These are the questions that Skylar Tibbits investigates in his Self-Assembly Lab at MIT, a cross-disciplinary research space where designers, scientists and engineers come together to find ways for disordered parts to become ordered structures.
A trained architect, designer and computer scientist, Tibbits teaches design studios at MIT’s Department of Architecture and co-teaches the seminar “How to Make (Almost) Anything” at MIT’s Media Lab. Before that, he worked at a number of design offices including Zaha Hadid Architects, Asymptote Architecture, SKIII Space Variations and Point b Design. His work has been shown at the Guggenheim Museum and the Beijing Biennale.
Tibbits has collaborated with a number of influential people over the years, including Neil Gershenfeld and The Center for Bits and Atoms, Erik and Marty Demaine at MIT, Adam Bly at SEED Media Group and Marc Fornes of THEVERYMANY. In 2007, he and Marc Fornes co-curated Scriptedbypurpose, the first exhibition focused exclusively on scripted processes within design. Also in 2007, he founded SJET, a multifaceted practice and research platform for experimental computation and design. SJET crosses disciplines from architecture and design, fabrication, computer science and robotics.
Skylar Tibbits | Speaker | TED.com