TED2011
Skylar Tibbits: Can we make things that make themselves?
Skajlar Tibits: Možemo li da stvorimo predmete koji će sami stvarati?
Filmed:
Readability: 4.4
1,072,366 views
Istraživač Instituta za tehnologiju Masačusets, Skajlar Tibits, radi na samokonstrukciji -- ideji da, umesto da stvorimo nešto (stolicu, neboder), možemo stvoriti materijale koji sami sebe konstruišu, nalik na lance DNK koji se sami kombinuju. Reč je o velikom konceptu koji je još uvek u ranoj fazi; Tibits nam pokazuje tri laboratorijska projekta koja daju uvid u to kako bi samokonstruktivna budućnost mogla da izgleda.
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
0
0
2000
Danas bih hteo da vam pokažem
00:17
the future of the way we make things.
1
2000
2000
budućnost našeg stvaranja predmeta.
00:19
I believe that soon our buildings and machines
2
4000
2000
Verujem da će, uskoro, naše zgrade i mašine
00:21
will be self-assembling,
3
6000
2000
konstruisati, replikovati
00:23
replicating and repairing themselves.
4
8000
2000
i popravljati same sebe.
00:25
So I'm going to show you
5
10000
2000
Pokazaću vam
00:27
what I believe is the current state of manufacturing,
6
12000
2000
moje viđenje trenutnog načina proizvodnje,
00:29
and then compare that to some natural systems.
7
14000
3000
a zatim ću to uporediti sa nekim sistemima u prirodi.
00:32
So in the current state of manufacturing, we have skyscrapers --
8
17000
3000
Trenutni način proizvodnje - imamo nebodere,
00:35
two and a half years [of assembly time],
9
20000
2000
čija izgradnja traje dve i po godine,
00:37
500,000 to a million parts,
10
22000
2000
i zahteva od 500,000 do milion,
00:39
fairly complex,
11
24000
2000
dosta složenih delova i
00:41
new, exciting technologies in steel, concrete, glass.
12
26000
3000
koristi nove i uzbudljive tehnologije u domenu čelika, betona i stakla.
00:44
We have exciting machines
13
29000
2000
Imamo zanimljive mašine
00:46
that can take us into space --
14
31000
2000
koje nas mogu odvesti u svemir --
00:48
five years [of assembly time], 2.5 million parts.
15
33000
3000
pet godina, dva i po miliona delova.
00:51
But on the other side, if you look at the natural systems,
16
36000
3000
Ali, sa druge strane, ako pogledate sisteme u prirodi,
00:54
we have proteins
17
39000
2000
imamo proteine
00:56
that have two million types,
18
41000
2000
koji imaju dva miliona tipova,
00:58
can fold in 10,000 nanoseconds,
19
43000
2000
i mogu se saviti za 10,000 nanosekundi,
01:00
or DNA with three billion base pairs
20
45000
2000
ili DNK sa tri milijardi parova baza
01:02
we can replicate in roughly an hour.
21
47000
3000
koje možemo replicirati u roku od nekih sat vremena.
01:05
So there's all of this complexity
22
50000
2000
Postoji sva ta kompleksnost
01:07
in our natural systems,
23
52000
2000
u našim prirodnim sistemima,
01:09
but they're extremely efficient,
24
54000
2000
ali su oni ekstremno efikasni --
01:11
far more efficient than anything we can build,
25
56000
2000
daleko efikasniji od bilo čega što možemo da napravimo,
01:13
far more complex than anything we can build.
26
58000
2000
daleko složeniji od bilo čega što možemo da napravimo.
01:15
They're far more efficient in terms of energy.
27
60000
2000
Daleko su efikasniji u pogledu korišćenja energije.
01:17
They hardly ever make mistakes.
28
62000
3000
Skoro da nikada ne prave greške.
01:20
And they can repair themselves for longevity.
29
65000
2000
I, povrh toga, mogu popravljati sami sebe da bi duže trajali.
01:22
So there's something super interesting about natural systems.
30
67000
3000
Postoji nešto vrlo interesantno u prirodnim sistemima,
01:25
And if we can translate that
31
70000
2000
i, ako uspemo da to prenesemo
01:27
into our built environment,
32
72000
2000
u okvire naše proizvodnje,
01:29
then there's some exciting potential for the way that we build things.
33
74000
2000
dobićemo uzbudljive mogućnosti za načine na koje pravimo stvari.
01:31
And I think the key to that is self-assembly.
34
76000
3000
Mislim da ključ za tako nešto leži u samokonstrukciji.
01:34
So if we want to utilize self-assembly in our physical environment,
35
79000
3000
Ako bismo želeli da iskoristimo samokonstrukciju u našem fizičkom okruženju,
01:37
I think there's four key factors.
36
82000
2000
po mom mišljenju, postoje četiri ključna faktora.
01:39
The first is that we need to decode
37
84000
2000
Prvi je to što moramo da dekodiramo
01:41
all of the complexity of what we want to build --
38
86000
2000
svu kompleksnost onogo što želimo da napravimo --
01:43
so our buildings and machines.
39
88000
2000
dakle, naših zgrada i mašina --
01:45
And we need to decode that into simple sequences --
40
90000
2000
i to trebamo dekodirati u jednostavne nizove --
01:47
basically the DNA of how our buildings work.
41
92000
2000
u osnovi, trebamo pronaći DNK naših zgrada.
01:49
Then we need programmable parts
42
94000
2000
Zatim su nam potrebni delovi koji se mogu programirati,
01:51
that can take that sequence
43
96000
2000
koji mogu preuzeti te nizove
01:53
and use that to fold up, or reconfigure.
44
98000
3000
i iskoristiti ih da bi se podigli, ili da bi promenili konfiguraciju.
01:56
We need some energy that's going to allow that to activate,
45
101000
3000
Potrebna nam je i energija koja će omogućiti pokretanje tih delova,
01:59
allow our parts to be able to fold up from the program.
46
104000
3000
koja će omogućiti delovima da se, po uputstvu iz programa, podignu.
02:02
And we need some type of error correction redundancy
47
107000
2000
I, na kraju, potreban nam je neki oblik korekcije grešaka,
02:04
to guarantee that we have successfully built what we want.
48
109000
3000
da bismo osigurali uspešnu gradnju onoga što želimo.
02:07
So I'm going to show you a number of projects
49
112000
2000
Pokazaću vam nekoliko projekata
02:09
that my colleagues and I at MIT are working on
50
114000
2000
na kojima moje kolege i ja radimo na Institutu za tehnologiju Masačusets
02:11
to achieve this self-assembling future.
51
116000
2000
u cilju dostizanja samokonstruktivne budućnosti.
02:13
The first two are the MacroBot and DeciBot.
52
118000
3000
Prva dva su MakroBot i DeciBot.
02:16
So these projects are large-scale reconfigurable robots --
53
121000
4000
Ovi projekti su roboti velikih razmera sa mogućnošću rekonfiguracije --
02:20
8 ft., 12 ft. long proteins.
54
125000
3000
proteini od 2.4 i 3.6 metara.
02:23
They're embedded with mechanical electrical devices, sensors.
55
128000
3000
Poseduju mehaničke električne uređaje, senzore.
02:26
You decode what you want to fold up into,
56
131000
2000
Dekodirate oblik u koji želite da se preklopi
02:28
into a sequence of angles --
57
133000
2000
u niz uglova --
02:30
so negative 120, negative 120, 0, 0,
58
135000
2000
minus 120, minus 120, 0, 0,
02:32
120, negative 120 -- something like that;
59
137000
3000
120, minus 120 stepeni -- nešto poput toga;
02:35
so a sequence of angles, or turns,
60
140000
2000
dakle, u niz uglova, ili okreta,
02:37
and you send that sequence through the string.
61
142000
3000
a zatim taj niz pošaljete kroz kabl.
02:40
Each unit takes its message -- so negative 120 --
62
145000
3000
Svaka jedinica prima svoju poruku -- dakle, minus 120.
02:43
it rotates to that, checks if it got there
63
148000
2000
Rotira se do tog stepena, proverava da li je dotle došla,
02:45
and then passes it to its neighbor.
64
150000
3000
a zatim šalje poruku dalje do susedne jedinice.
02:48
So these are the brilliant scientists,
65
153000
2000
Na ovom projektu su radili briljantni naučnici,
02:50
engineers, designers that worked on this project.
66
155000
2000
inženjeri i dizajneri.
02:52
And I think it really brings to light:
67
157000
2000
Mislim da zaista dovodi do pitanja:
02:54
Is this really scalable?
68
159000
2000
da li je sve ovo ostvarivo na većoj razmeri?
02:56
I mean, thousands of dollars, lots of man hours
69
161000
2000
Na ovog dva ipo metra visokog robota je utrošeno
02:58
made to make this eight-foot robot.
70
163000
3000
na hiljade dolara i mnogo radnih sati.
03:01
Can we really scale this up? Can we really embed robotics into every part?
71
166000
3000
Možemo li zaista da uvećamo sve ovo? Možemo li da uključimo robotiku u svaki deo?
03:04
The next one questions that
72
169000
2000
Sa sledećim projektom smo postavili to pitanje
03:06
and looks at passive nature,
73
171000
2000
i razmatrali domen pasivne prirode,
03:08
or passively trying to have reconfiguration programmability.
74
173000
3000
to jest, pasivnog posedovanja programabilnosti rekonfiguracije.
03:11
But it goes a step further,
75
176000
2000
Ali, ovaj projekat ide korak dalje,
03:13
and it tries to have actual computation.
76
178000
2000
jer pokušava da uključi i računanje.
03:15
It basically embeds the most fundamental building block of computing,
77
180000
2000
On zapravo uključuje najosnovniji deo potreban za računanje,
03:17
the digital logic gate,
78
182000
2000
digitalnu logičku kapiju,
03:19
directly into your parts.
79
184000
2000
direktno u vaše delove.
03:21
So this is a NAND gate.
80
186000
2000
Ovo je NAND kapija.
03:23
You have one tetrahedron which is the gate
81
188000
2000
Imate jedan tetraedar koji čini kapiju
03:25
that's going to do your computing,
82
190000
2000
koja će obavljati računanje,
03:27
and you have two input tetrahedrons.
83
192000
2000
i dva tetraedra za unos podataka.
03:29
One of them is the input from the user, as you're building your bricks.
84
194000
3000
Jedan od njih je za unos podataka od strane korisnika, dok slažete vaše delove,
03:32
The other one is from the previous brick that was placed.
85
197000
3000
a drugi je od prošlog dela koji je bio unet.
03:35
And then it gives you an output in 3D space.
86
200000
3000
Nakon toga, on vam pruža rezultat u trodimenzionalnom prostoru.
03:38
So what this means
87
203000
2000
To zapravo znači
03:40
is that the user can start plugging in what they want the bricks to do.
88
205000
3000
da korisnik može da učita ono što želi da delovi urade.
03:43
It computes on what it was doing before
89
208000
2000
Tetraedar preračuna ono što je ranije radio
03:45
and what you said you wanted it to do.
90
210000
2000
i ono što vi želite da uradi.
03:47
And now it starts moving in three-dimensional space --
91
212000
2000
A zatim se pokreće u trodimenzionalnom prostoru --
03:49
so up or down.
92
214000
2000
dakle, gore ili dole.
03:51
So on the left-hand side, [1,1] input equals 0 output, which goes down.
93
216000
3000
Sa leve strane, unos [1,1] daje rezultat 0, što dovodi do pomeranja nadole.
03:54
On the right-hand side,
94
219000
2000
Sa desne strane,
03:56
[0,0] input is a 1 output, which goes up.
95
221000
3000
unos [0,0] daje rezultat 1, što dovodi do pomeranja nagore.
03:59
And so what that really means
96
224000
2000
Ovo zapravo znači
04:01
is that our structures now contain the blueprints
97
226000
2000
da naša struktura sada poseduje plan
04:03
of what we want to build.
98
228000
2000
onoga što hoćemo da sagradimo.
04:05
So they have all of the information embedded in them of what was constructed.
99
230000
3000
U delove su uključene sve informacije o onome što je konstruisano.
04:08
So that means that we can have some form of self-replication.
100
233000
3000
To znači da imamo određeni oblik samoreplikacije.
04:11
In this case I call it self-guided replication,
101
236000
3000
U ovom slučaju, ja ga nazivam samonavođenom replikacijom,
04:14
because your structure contains the exact blueprints.
102
239000
2000
jer vaša struktura sadrži tačan plan.
04:16
If you have errors, you can replace a part.
103
241000
2000
Ukoliko dođe do greške, možete zameniti deo.
04:18
All the local information is embedded to tell you how to fix it.
104
243000
3000
Uključene su sve informacije o tome kako da je ispravite.
04:21
So you could have something that climbs along and reads it
105
246000
2000
Dakle, možete imati nešto što se penje i čita informacije,
04:23
and can output at one to one.
106
248000
2000
i daje rezultat 1 prema 1.
04:25
It's directly embedded; there's no external instructions.
107
250000
2000
Sve je direktno učitano; nema instrukcija iz spoljašnje sredine.
04:27
So the last project I'll show is called Biased Chains,
108
252000
3000
Poslednji projekat koji ću vam pokazati zove se Pristrasni Lanci,
04:30
and it's probably the most exciting example that we have right now
109
255000
3000
i verovatno je najuzbudljiviji primer pasivnih sistema koji se sami replikuju
04:33
of passive self-assembly systems.
110
258000
2000
koji trenutno posedujemo.
04:35
So it takes the reconfigurability
111
260000
2000
On poseduje sposobnost rekonfiguracije
04:37
and programmability
112
262000
2000
i mogućnosti programiranja
04:39
and makes it a completely passive system.
113
264000
3000
u okviru kompletno pasivnog sistema.
04:43
So basically you have a chain of elements.
114
268000
2000
U osnovi, to je niz elemenata.
04:45
Each element is completely identical,
115
270000
2000
Svaki element je potpuno identičan,
04:47
and they're biased.
116
272000
2000
i na neki način pristrasan.
04:49
So each chain, or each element, wants to turn right or left.
117
274000
3000
Svaki lanac, odnosno svaki element, želi da se okrene desno ili levo.
04:52
So as you assemble the chain, you're basically programming it.
118
277000
3000
Dok spajate lanac, vi ga zapravo programirate.
04:55
You're telling each unit if it should turn right or left.
119
280000
3000
Govorite svakoj jedinici da li da se pomeri desno ili levo.
04:58
So when you shake the chain,
120
283000
3000
Kada protresete lanac,
05:01
it then folds up
121
286000
2000
on se preklopi
05:03
into any configuration that you've programmed in --
122
288000
3000
u bilo koju konfiguraciju u koji ste ga programirali --
05:06
so in this case, a spiral,
123
291000
2000
u ovom slučaju, u spiralu,
05:08
or in this case,
124
293000
3000
ili u ovom,
05:11
two cubes next to each other.
125
296000
3000
u dve kocke jedna do druge.
05:14
So you can basically program
126
299000
2000
Možete programirati
05:16
any three-dimensional shape --
127
301000
2000
bilo koji trodimenzionalni oblik --
05:18
or one-dimensional, two-dimensional -- up into this chain completely passively.
128
303000
3000
ili jedno, dvodimenzionalni -- u ovaj lanac, potpuno pasivno.
05:21
So what does this tell us about the future?
129
306000
2000
Šta nam ovo govori o budućnosti?
05:23
I think that it's telling us
130
308000
2000
Mislim da nam govori
05:25
that there's new possibilities for self-assembly, replication, repair
131
310000
3000
da postoje nove mogućnosti za samokonstrukciju, replikaciju, popravku,
05:28
in our physical structures, our buildings, machines.
132
313000
3000
u okviru naših fizičkih struktura, naših zgrada, mašina.
05:31
There's new programmability in these parts.
133
316000
2000
Postoji novi nivo programabilnosti u ovim delovima,
05:33
And from that you have new possibilities for computing.
134
318000
2000
a iz toga proizilaze i nove mogućnosti za računanje.
05:35
We'll have spatial computing.
135
320000
2000
Imaćemo prostorno računanje.
05:37
Imagine if our buildings, our bridges, machines,
136
322000
2000
Zamislite kada bi naše zgrade, mostovi, mašine,
05:39
all of our bricks could actually compute.
137
324000
2000
svi naši delovi bili sposobni da računaju.
05:41
That's amazing parallel and distributed computing power,
138
326000
2000
To predstavlja neverovatnu paralelnu i distribuiranu moć računanja,
05:43
new design possibilities.
139
328000
2000
kao i nove mogućnosti za dizajn.
05:45
So it's exciting potential for this.
140
330000
2000
U ovome leže zanimljive mogućnosti.
05:47
So I think these projects I've showed here
141
332000
2000
Mislim da su ovi projekti koje sam vam predstavio
05:49
are just a tiny step towards this future,
142
334000
2000
samo mali korak napred ka ovoj budućnosti,
05:51
if we implement these new technologies
143
336000
2000
ukoliko uspemo da ih primenimo
05:53
for a new self-assembling world.
144
338000
2000
u svrhu stvaranja novog, samokonstruktivnog sveta.
05:55
Thank you.
145
340000
2000
Hvala vam.
05:57
(Applause)
146
342000
2000
(Aplauz)
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