TED2011
Skylar Tibbits: Can we make things that make themselves?
Skylar Tibbits: Možemo li izraditi stvari koje same sebe izrađuju?
Filmed:
Readability: 4.4
1,072,366 views
Istraživač s MIT-a Skylar Tibbits radi na samo-sastavljanju -- ideja u kojoj umjesto da gradite nešto (stolac, neboder), možemo stvoriti materijale koji grade sami sebe, uvelike nalik na dvije strane DNK koje se spoje zajedno. To je veliki koncept u ranim fazama; Tibbits prikazuje tri projekta koji su još u laboratoriju koji daju uvid kako bi budućnost samo-sastavljanja mogla izgledati.
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 vam volio pokazati
00:17
the future of the way we make things.
1
2000
2000
budućnost načina na koji izrađujemo stvari.
00:19
I believe that soon our buildings and machines
2
4000
2000
Vjerujem kako će se ubrzo naše zgrade i strojevi
00:21
will be self-assembling,
3
6000
2000
sami sastavljati,
00:23
replicating and repairing themselves.
4
8000
2000
duplicirati i popravljati.
00:25
So I'm going to show you
5
10000
2000
Stoga ću vam pokazati
00:27
what I believe is the current state of manufacturing,
6
12000
2000
nešto za što ja vjerujem je trenutno stanje proizvodnje,
00:29
and then compare that to some natural systems.
7
14000
3000
i zatim ću to usporediti s nekim prirodnim sustavima.
00:32
So in the current state of manufacturing, we have skyscrapers --
8
17000
3000
Dakle, u trenutnom stanju proizvodnje, imamo nebodere --
00:35
two and a half years [of assembly time],
9
20000
2000
dvije i pol godine,
00:37
500,000 to a million parts,
10
22000
2000
od 500.000 do milijun dijelova,
00:39
fairly complex,
11
24000
2000
prilično kompleksne,
00:41
new, exciting technologies in steel, concrete, glass.
12
26000
3000
nove i uzbudljive tehnologije čelika, betona, stakla.
00:44
We have exciting machines
13
29000
2000
Imamo uzbudljive strojeve
00:46
that can take us into space --
14
31000
2000
koji nas mogu povesti u svemir --
00:48
five years [of assembly time], 2.5 million parts.
15
33000
3000
pet godina, 2,5 milijuna dijelova.
00:51
But on the other side, if you look at the natural systems,
16
36000
3000
Ali s druge strane, ako promatrate prirodne sustave,
00:54
we have proteins
17
39000
2000
imamo proteine
00:56
that have two million types,
18
41000
2000
kojih ima dva milijuna vrsta,
00:58
can fold in 10,000 nanoseconds,
19
43000
2000
mogu se skupiti u 10.000 nanosekundi,
01:00
or DNA with three billion base pairs
20
45000
2000
ili DNK s tri milijarde baznih parova
01:02
we can replicate in roughly an hour.
21
47000
3000
možemo replicirati u sat vremena.
01:05
So there's all of this complexity
22
50000
2000
Dakle, postoji sva ta kompleksnost
01:07
in our natural systems,
23
52000
2000
u našim prirodnim sustavima,
01:09
but they're extremely efficient,
24
54000
2000
ali oni su ekstremno učinkoviti,
01:11
far more efficient than anything we can build,
25
56000
2000
puno učinkovitiji od bilo čega što možemo izgraditi,
01:13
far more complex than anything we can build.
26
58000
2000
puno kompleksniji od bilo čega što možemo izgraditi.
01:15
They're far more efficient in terms of energy.
27
60000
2000
Puno su učinkovitiji u okvirima energije.
01:17
They hardly ever make mistakes.
28
62000
3000
Gotovo nikada ne rade greške.
01:20
And they can repair themselves for longevity.
29
65000
2000
I mogu popraviti sami sebe za dugovječnost.
01:22
So there's something super interesting about natural systems.
30
67000
3000
Dakle, postoji nešto super zanimljivo o prirodnim sustavima.
01:25
And if we can translate that
31
70000
2000
I ako to možemo prevesti
01:27
into our built environment,
32
72000
2000
u naš okoliš gradnje,
01:29
then there's some exciting potential for the way that we build things.
33
74000
2000
onda postoji neki uzbudljivi potencijal za način na koji gradimo stvari.
01:31
And I think the key to that is self-assembly.
34
76000
3000
I mislim kako je ključ toga samo-sastavljanje.
01:34
So if we want to utilize self-assembly in our physical environment,
35
79000
3000
Dakle, ukoliko želimo iskoristiti samo-sastavljanje u našoj fizičkoj okolini,
01:37
I think there's four key factors.
36
82000
2000
mislim kako postoji četiri ključna čimbenika.
01:39
The first is that we need to decode
37
84000
2000
Prvi je da moramo dekodirati
01:41
all of the complexity of what we want to build --
38
86000
2000
cijelu kompleksnost onoga što želimo graditi --
01:43
so our buildings and machines.
39
88000
2000
dakle, naše zgrade i strojeve.
01:45
And we need to decode that into simple sequences --
40
90000
2000
I moramo to dekodirati u jednostavne nizove --
01:47
basically the DNA of how our buildings work.
41
92000
2000
u osnovi DNK kako naše zgrade funkcioniraju.
01:49
Then we need programmable parts
42
94000
2000
Tada su nam potrebni dijelovi koje je moguće programirati
01:51
that can take that sequence
43
96000
2000
koji mogu uzeti te nizove
01:53
and use that to fold up, or reconfigure.
44
98000
3000
i iskoristiti ih da ih presavinu ili rekonfiguriraju.
01:56
We need some energy that's going to allow that to activate,
45
101000
3000
Potrebna nam je neka energija koja će nam omogućiti aktivaciju toga,
01:59
allow our parts to be able to fold up from the program.
46
104000
3000
dozvoliti našim dijelovima da se savijajući maknu iz programa.
02:02
And we need some type of error correction redundancy
47
107000
2000
I potrebna nam je neka vrsta redundancije koja će ispravljati greške
02:04
to guarantee that we have successfully built what we want.
48
109000
3000
i koja bi garantirala kako smo uspješno izgradili ono što želimo.
02:07
So I'm going to show you a number of projects
49
112000
2000
Stoga ću vam pokazati nekoliko projekata
02:09
that my colleagues and I at MIT are working on
50
114000
2000
na kojima moje kolege u MIT-u i ja radimo
02:11
to achieve this self-assembling future.
51
116000
2000
kako bi postigli tu budućnost samo-sastavljanja.
02:13
The first two are the MacroBot and DeciBot.
52
118000
3000
Prva dva su MacroBot i DeciBot.
02:16
So these projects are large-scale reconfigurable robots --
53
121000
4000
Dakle, ti projekti su rekonfigurabilni roboti velikog opsega --
02:20
8 ft., 12 ft. long proteins.
54
125000
3000
2,4 m, 3,6 m dugački proteini.
02:23
They're embedded with mechanical electrical devices, sensors.
55
128000
3000
U njih su ugrađeni mehanički električni uređaji, senzori.
02:26
You decode what you want to fold up into,
56
131000
2000
Dekodirate ono što želite da se presavine,
02:28
into a sequence of angles --
57
133000
2000
u niz kuteva --
02:30
so negative 120, negative 120, 0, 0,
58
135000
2000
dakle, negativno 120, negatino 120, 0, 0,
02:32
120, negative 120 -- something like that;
59
137000
3000
120, negativno 120 -- nešto poput toga;
02:35
so a sequence of angles, or turns,
60
140000
2000
dakle, niz kuteva, ili zavoja,
02:37
and you send that sequence through the string.
61
142000
3000
i pošaljete taj niz kroz žicu.
02:40
Each unit takes its message -- so negative 120 --
62
145000
3000
Dakle, svaka jedinica uzima svoju poruku -- dakle, negativno 120.
02:43
it rotates to that, checks if it got there
63
148000
2000
Rotira do toga, provjerava je li došlo do tamo
02:45
and then passes it to its neighbor.
64
150000
3000
i zatim je prepušta svom susjedu.
02:48
So these are the brilliant scientists,
65
153000
2000
Dakle, ovo su briljantni znanstvenici,
02:50
engineers, designers that worked on this project.
66
155000
2000
inžinjeri, dizajneri koji su radili na ovom projektu.
02:52
And I think it really brings to light:
67
157000
2000
I mislim kako stvarno dovodi do pitanja:
02:54
Is this really scalable?
68
159000
2000
Je li doista skalabilno?
02:56
I mean, thousands of dollars, lots of man hours
69
161000
2000
Mislim, tisuće dolara, mnogo radnih sati
02:58
made to make this eight-foot robot.
70
163000
3000
je uloženo kako bi se napravio ovaj 2,4 m visok robot.
03:01
Can we really scale this up? Can we really embed robotics into every part?
71
166000
3000
Možemo li doista to nadmašiti? Možemo li doista ugraditi robotiku u svaki dio?
03:04
The next one questions that
72
169000
2000
Idući preispituje to
03:06
and looks at passive nature,
73
171000
2000
i promatra pasivnu prirodu,
03:08
or passively trying to have reconfiguration programmability.
74
173000
3000
ili pasivno pokušava imati rekonfiguraciju programibilnosti.
03:11
But it goes a step further,
75
176000
2000
Ali ide i korak dalje,
03:13
and it tries to have actual computation.
76
178000
2000
i pokušava imati stvarnu moć izračuna.
03:15
It basically embeds the most fundamental building block of computing,
77
180000
2000
U osnovi ugrađuje najosnovnije građevne blokove računalstva,
03:17
the digital logic gate,
78
182000
2000
digitalna logička vrata,
03:19
directly into your parts.
79
184000
2000
izravno u vaše dijelove.
03:21
So this is a NAND gate.
80
186000
2000
Dakle, ovo su NAND vrata.
03:23
You have one tetrahedron which is the gate
81
188000
2000
Imate jedan tetraedar koji predstavlja vrata
03:25
that's going to do your computing,
82
190000
2000
koja će vršiti vaše izračune,
03:27
and you have two input tetrahedrons.
83
192000
2000
i imate dva ulazna tetraedrona.
03:29
One of them is the input from the user, as you're building your bricks.
84
194000
3000
Jedan od njih je ulaz s korisničke strane, kako polažete svoje cigle.
03:32
The other one is from the previous brick that was placed.
85
197000
3000
Drugi je od prethodne cigle koja je postavljena.
03:35
And then it gives you an output in 3D space.
86
200000
3000
I zatim vam daje izlaz u 3D prostoru.
03:38
So what this means
87
203000
2000
Dakle, što to znači
03:40
is that the user can start plugging in what they want the bricks to do.
88
205000
3000
je da se korisnik može uključivati u ono što cigle rade.
03:43
It computes on what it was doing before
89
208000
2000
Računa na osnovi onoga što je radio prije
03:45
and what you said you wanted it to do.
90
210000
2000
i što ste rekli da želite da radi.
03:47
And now it starts moving in three-dimensional space --
91
212000
2000
A sada se počinje kretati u trodimenzionalnom prostoru --
03:49
so up or down.
92
214000
2000
dakle, gore ili dolje.
03:51
So on the left-hand side, [1,1] input equals 0 output, which goes down.
93
216000
3000
Dakle, s lijeve strane, [1,1] ulaz je jednak 0, što znači da ide dolje.
03:54
On the right-hand side,
94
219000
2000
S desne strane,
03:56
[0,0] input is a 1 output, which goes up.
95
221000
3000
[0,0] ulaz je jednak izlaznoj 1, što znači da ide gore.
03:59
And so what that really means
96
224000
2000
I dakle, što to zapravo znači
04:01
is that our structures now contain the blueprints
97
226000
2000
je da naše strukture sada sadrže nacrte
04:03
of what we want to build.
98
228000
2000
onoga što želimo izgraditi.
04:05
So they have all of the information embedded in them of what was constructed.
99
230000
3000
Dakle, imaju sve informacije ugrađene u njima onoga što je sagrađeno.
04:08
So that means that we can have some form of self-replication.
100
233000
3000
Dakle, to znači da možemo imati neki oblik samo-dupliciranja.
04:11
In this case I call it self-guided replication,
101
236000
3000
U ovom slučaju, ja je nazivam samohodno dupliciranje,
04:14
because your structure contains the exact blueprints.
102
239000
2000
jer vaša struktura sadrži točne nacrte.
04:16
If you have errors, you can replace a part.
103
241000
2000
Ukoliko imate grešaka, možete zamijeniti dio.
04:18
All the local information is embedded to tell you how to fix it.
104
243000
3000
Sva lokalna informacija je ugrađena kako bi vam rekla kako to popraviti.
04:21
So you could have something that climbs along and reads it
105
246000
2000
Dakle, mogli biste imati nešto što se vuče po tome i čita to
04:23
and can output at one to one.
106
248000
2000
i može dati izlazi jedan naprema jedan.
04:25
It's directly embedded; there's no external instructions.
107
250000
2000
Izravno je ugrađeno; nema vanjskih instrukcija.
04:27
So the last project I'll show is called Biased Chains,
108
252000
3000
Dakle, posljednji projekt koji ću vam pokazati se zove Nagibni Lanci,
04:30
and it's probably the most exciting example that we have right now
109
255000
3000
i to je vjerojatno najuzbudljiviji primjer što sada imamo
04:33
of passive self-assembly systems.
110
258000
2000
pasivnih samo-sastavljajućih sustava.
04:35
So it takes the reconfigurability
111
260000
2000
Dakle, uzima rekonfigurabilnost
04:37
and programmability
112
262000
2000
i programabilnost
04:39
and makes it a completely passive system.
113
264000
3000
i pretvara ga u potpuno pasivni sustav.
04:43
So basically you have a chain of elements.
114
268000
2000
Dakle, u osnovi imate lanac 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 oni su nagibni.
04:49
So each chain, or each element, wants to turn right or left.
117
274000
3000
Dakle, svaki lanac, ili svaki element, se želi zaokrenuti lijevo ili desno.
04:52
So as you assemble the chain, you're basically programming it.
118
277000
3000
Dakle, kako sastavljate lanac, vi ga u osnovi programirate.
04:55
You're telling each unit if it should turn right or left.
119
280000
3000
Govorite svakoj jedinici bi li se treba okrenuti lijevo ili desno.
04:58
So when you shake the chain,
120
283000
3000
Dakle, kada protresete lanac,
05:01
it then folds up
121
286000
2000
zatim se skupi
05:03
into any configuration that you've programmed in --
122
288000
3000
u bilo koju konfiguraciju za koju ste ga isprogramirali --
05:06
so in this case, a spiral,
123
291000
2000
dakle, u ovom slučaju, u spiralu,
05:08
or in this case,
124
293000
3000
ili u ovom slučaju,
05:11
two cubes next to each other.
125
296000
3000
dvije kocke jedna pored druge.
05:14
So you can basically program
126
299000
2000
Dakle, u osnovi možete isprogramirati
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 jednodimenzionalni, dvodimenzionalni -- u ovaj lanac potpuno pasivno.
05:21
So what does this tell us about the future?
129
306000
2000
Dakle, što nam to govori o budućnosti?
05:23
I think that it's telling us
130
308000
2000
Mislim kako nam govori
05:25
that there's new possibilities for self-assembly, replication, repair
131
310000
3000
kako postoje nove mogućnosti za samo-sastavljanje, repliciranje, popravak
05:28
in our physical structures, our buildings, machines.
132
313000
3000
u našim fizičkim strukturama, našim zgradama, strojevima.
05:31
There's new programmability in these parts.
133
316000
2000
Ovdje je nova programabilnost u ovim dijelovima.
05:33
And from that you have new possibilities for computing.
134
318000
2000
A iz toga imate nove mogućnosti za računanje.
05:35
We'll have spatial computing.
135
320000
2000
Imati ćemo prostorno računanje.
05:37
Imagine if our buildings, our bridges, machines,
136
322000
2000
Zamislite kada bi naše zgrade, naši mostovi, strojevi,
05:39
all of our bricks could actually compute.
137
324000
2000
sve naše cigle mogle zapravo računati.
05:41
That's amazing parallel and distributed computing power,
138
326000
2000
To je nevjerojatna paralela i distribuirana moć računanja,
05:43
new design possibilities.
139
328000
2000
nove dizajnerske mogućnosti.
05:45
So it's exciting potential for this.
140
330000
2000
Dakle, potencijal za to je uzbudljiv.
05:47
So I think these projects I've showed here
141
332000
2000
Stoga mislim kako su ti projekti koje sam vam pokazao
05:49
are just a tiny step towards this future,
142
334000
2000
samo sićušan korak prema budućnosti,
05:51
if we implement these new technologies
143
336000
2000
ukoliko implementiramo te nove tehnologije
05:53
for a new self-assembling world.
144
338000
2000
za novi svijet samo-sastavljanja.
05:55
Thank you.
145
340000
2000
Hvala vam.
05:57
(Applause)
146
342000
2000
(Pljesak)
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