Today I'd like to show you the future of the way we make things. I believe that soon our buildings and machines will be self-assembling, replicating and repairing themselves. So I'm going to show you what I believe is the current state of manufacturing, and then compare that to some natural systems.
Danas bih vam volio pokazati budućnost načina na koji izrađujemo stvari. Vjerujem kako će se ubrzo naše zgrade i strojevi sami sastavljati, duplicirati i popravljati. Stoga ću vam pokazati nešto za što ja vjerujem je trenutno stanje proizvodnje, i zatim ću to usporediti s nekim prirodnim sustavima.
So in the current state of manufacturing, we have skyscrapers -- two and a half years [of assembly time], 500,000 to a million parts, fairly complex, new, exciting technologies in steel, concrete, glass. We have exciting machines that can take us into space -- five years [of assembly time], 2.5 million parts.
Dakle, u trenutnom stanju proizvodnje, imamo nebodere -- dvije i pol godine, od 500.000 do milijun dijelova, prilično kompleksne, nove i uzbudljive tehnologije čelika, betona, stakla. Imamo uzbudljive strojeve koji nas mogu povesti u svemir -- pet godina, 2,5 milijuna dijelova.
But on the other side, if you look at the natural systems, we have proteins that have two million types, can fold in 10,000 nanoseconds, or DNA with three billion base pairs we can replicate in roughly an hour. So there's all of this complexity in our natural systems, but they're extremely efficient, far more efficient than anything we can build, far more complex than anything we can build. They're far more efficient in terms of energy. They hardly ever make mistakes. And they can repair themselves for longevity.
Ali s druge strane, ako promatrate prirodne sustave, imamo proteine kojih ima dva milijuna vrsta, mogu se skupiti u 10.000 nanosekundi, ili DNK s tri milijarde baznih parova možemo replicirati u sat vremena. Dakle, postoji sva ta kompleksnost u našim prirodnim sustavima, ali oni su ekstremno učinkoviti, puno učinkovitiji od bilo čega što možemo izgraditi, puno kompleksniji od bilo čega što možemo izgraditi. Puno su učinkovitiji u okvirima energije. Gotovo nikada ne rade greške. I mogu popraviti sami sebe za dugovječnost.
So there's something super interesting about natural systems. And if we can translate that into our built environment, then there's some exciting potential for the way that we build things. And I think the key to that is self-assembly.
Dakle, postoji nešto super zanimljivo o prirodnim sustavima. I ako to možemo prevesti u naš okoliš gradnje, onda postoji neki uzbudljivi potencijal za način na koji gradimo stvari. I mislim kako je ključ toga samo-sastavljanje.
So if we want to utilize self-assembly in our physical environment, I think there's four key factors. The first is that we need to decode all of the complexity of what we want to build -- so our buildings and machines. And we need to decode that into simple sequences -- basically the DNA of how our buildings work. Then we need programmable parts that can take that sequence and use that to fold up, or reconfigure. We need some energy that's going to allow that to activate, allow our parts to be able to fold up from the program. And we need some type of error correction redundancy to guarantee that we have successfully built what we want.
Dakle, ukoliko želimo iskoristiti samo-sastavljanje u našoj fizičkoj okolini, mislim kako postoji četiri ključna čimbenika. Prvi je da moramo dekodirati cijelu kompleksnost onoga što želimo graditi -- dakle, naše zgrade i strojeve. I moramo to dekodirati u jednostavne nizove -- u osnovi DNK kako naše zgrade funkcioniraju. Tada su nam potrebni dijelovi koje je moguće programirati koji mogu uzeti te nizove i iskoristiti ih da ih presavinu ili rekonfiguriraju. Potrebna nam je neka energija koja će nam omogućiti aktivaciju toga, dozvoliti našim dijelovima da se savijajući maknu iz programa. I potrebna nam je neka vrsta redundancije koja će ispravljati greške i koja bi garantirala kako smo uspješno izgradili ono što želimo.
So I'm going to show you a number of projects that my colleagues and I at MIT are working on to achieve this self-assembling future. The first two are the MacroBot and DeciBot. So these projects are large-scale reconfigurable robots -- 8 ft., 12 ft. long proteins. They're embedded with mechanical electrical devices, sensors. You decode what you want to fold up into, into a sequence of angles -- so negative 120, negative 120, 0, 0, 120, negative 120 -- something like that; so a sequence of angles, or turns, and you send that sequence through the string. Each unit takes its message -- so negative 120 -- it rotates to that, checks if it got there and then passes it to its neighbor.
Stoga ću vam pokazati nekoliko projekata na kojima moje kolege u MIT-u i ja radimo kako bi postigli tu budućnost samo-sastavljanja. Prva dva su MacroBot i DeciBot. Dakle, ti projekti su rekonfigurabilni roboti velikog opsega -- 2,4 m, 3,6 m dugački proteini. U njih su ugrađeni mehanički električni uređaji, senzori. Dekodirate ono što želite da se presavine, u niz kuteva -- dakle, negativno 120, negatino 120, 0, 0, 120, negativno 120 -- nešto poput toga; dakle, niz kuteva, ili zavoja, i pošaljete taj niz kroz žicu. Dakle, svaka jedinica uzima svoju poruku -- dakle, negativno 120. Rotira do toga, provjerava je li došlo do tamo i zatim je prepušta svom susjedu.
So these are the brilliant scientists, engineers, designers that worked on this project. And I think it really brings to light: Is this really scalable? I mean, thousands of dollars, lots of man hours made to make this eight-foot robot. Can we really scale this up? Can we really embed robotics into every part? The next one questions that and looks at passive nature, or passively trying to have reconfiguration programmability. But it goes a step further, and it tries to have actual computation. It basically embeds the most fundamental building block of computing, the digital logic gate, directly into your parts.
Dakle, ovo su briljantni znanstvenici, inžinjeri, dizajneri koji su radili na ovom projektu. I mislim kako stvarno dovodi do pitanja: Je li doista skalabilno? Mislim, tisuće dolara, mnogo radnih sati je uloženo kako bi se napravio ovaj 2,4 m visok robot. Možemo li doista to nadmašiti? Možemo li doista ugraditi robotiku u svaki dio? Idući preispituje to i promatra pasivnu prirodu, ili pasivno pokušava imati rekonfiguraciju programibilnosti. Ali ide i korak dalje, i pokušava imati stvarnu moć izračuna. U osnovi ugrađuje najosnovnije građevne blokove računalstva, digitalna logička vrata, izravno u vaše dijelove.
So this is a NAND gate. You have one tetrahedron which is the gate that's going to do your computing, and you have two input tetrahedrons. One of them is the input from the user, as you're building your bricks. The other one is from the previous brick that was placed. And then it gives you an output in 3D space. So what this means is that the user can start plugging in what they want the bricks to do. It computes on what it was doing before and what you said you wanted it to do. And now it starts moving in three-dimensional space -- so up or down. So on the left-hand side, [1,1] input equals 0 output, which goes down. On the right-hand side, [0,0] input is a 1 output, which goes up. And so what that really means is that our structures now contain the blueprints of what we want to build.
Dakle, ovo su NAND vrata. Imate jedan tetraedar koji predstavlja vrata koja će vršiti vaše izračune, i imate dva ulazna tetraedrona. Jedan od njih je ulaz s korisničke strane, kako polažete svoje cigle. Drugi je od prethodne cigle koja je postavljena. I zatim vam daje izlaz u 3D prostoru. Dakle, što to znači je da se korisnik može uključivati u ono što cigle rade. Računa na osnovi onoga što je radio prije i što ste rekli da želite da radi. A sada se počinje kretati u trodimenzionalnom prostoru -- dakle, gore ili dolje. Dakle, s lijeve strane, [1,1] ulaz je jednak 0, što znači da ide dolje. S desne strane, [0,0] ulaz je jednak izlaznoj 1, što znači da ide gore. I dakle, što to zapravo znači je da naše strukture sada sadrže nacrte onoga što želimo izgraditi.
So they have all of the information embedded in them of what was constructed. So that means that we can have some form of self-replication. In this case I call it self-guided replication, because your structure contains the exact blueprints. If you have errors, you can replace a part. All the local information is embedded to tell you how to fix it. So you could have something that climbs along and reads it and can output at one to one. It's directly embedded; there's no external instructions.
Dakle, imaju sve informacije ugrađene u njima onoga što je sagrađeno. Dakle, to znači da možemo imati neki oblik samo-dupliciranja. U ovom slučaju, ja je nazivam samohodno dupliciranje, jer vaša struktura sadrži točne nacrte. Ukoliko imate grešaka, možete zamijeniti dio. Sva lokalna informacija je ugrađena kako bi vam rekla kako to popraviti. Dakle, mogli biste imati nešto što se vuče po tome i čita to i može dati izlazi jedan naprema jedan. Izravno je ugrađeno; nema vanjskih instrukcija.
So the last project I'll show is called Biased Chains, and it's probably the most exciting example that we have right now of passive self-assembly systems. So it takes the reconfigurability and programmability and makes it a completely passive system. So basically you have a chain of elements. Each element is completely identical, and they're biased. So each chain, or each element, wants to turn right or left. So as you assemble the chain, you're basically programming it. You're telling each unit if it should turn right or left. So when you shake the chain, it then folds up into any configuration that you've programmed in -- so in this case, a spiral, or in this case, two cubes next to each other. So you can basically program any three-dimensional shape -- or one-dimensional, two-dimensional -- up into this chain completely passively.
Dakle, posljednji projekt koji ću vam pokazati se zove Nagibni Lanci, i to je vjerojatno najuzbudljiviji primjer što sada imamo pasivnih samo-sastavljajućih sustava. Dakle, uzima rekonfigurabilnost i programabilnost i pretvara ga u potpuno pasivni sustav. Dakle, u osnovi imate lanac elemenata. Svaki element je potpuno identičan, i oni su nagibni. Dakle, svaki lanac, ili svaki element, se želi zaokrenuti lijevo ili desno. Dakle, kako sastavljate lanac, vi ga u osnovi programirate. Govorite svakoj jedinici bi li se treba okrenuti lijevo ili desno. Dakle, kada protresete lanac, zatim se skupi u bilo koju konfiguraciju za koju ste ga isprogramirali -- dakle, u ovom slučaju, u spiralu, ili u ovom slučaju, dvije kocke jedna pored druge. Dakle, u osnovi možete isprogramirati bilo koji trodimenzionalni oblik -- ili jednodimenzionalni, dvodimenzionalni -- u ovaj lanac potpuno pasivno.
So what does this tell us about the future? I think that it's telling us that there's new possibilities for self-assembly, replication, repair in our physical structures, our buildings, machines. There's new programmability in these parts. And from that you have new possibilities for computing. We'll have spatial computing. Imagine if our buildings, our bridges, machines, all of our bricks could actually compute. That's amazing parallel and distributed computing power, new design possibilities. So it's exciting potential for this. So I think these projects I've showed here are just a tiny step towards this future, if we implement these new technologies for a new self-assembling world.
Dakle, što nam to govori o budućnosti? Mislim kako nam govori kako postoje nove mogućnosti za samo-sastavljanje, repliciranje, popravak u našim fizičkim strukturama, našim zgradama, strojevima. Ovdje je nova programabilnost u ovim dijelovima. A iz toga imate nove mogućnosti za računanje. Imati ćemo prostorno računanje. Zamislite kada bi naše zgrade, naši mostovi, strojevi, sve naše cigle mogle zapravo računati. To je nevjerojatna paralela i distribuirana moć računanja, nove dizajnerske mogućnosti. Dakle, potencijal za to je uzbudljiv. Stoga mislim kako su ti projekti koje sam vam pokazao samo sićušan korak prema budućnosti, ukoliko implementiramo te nove tehnologije za novi svijet samo-sastavljanja.
Thank you.
Hvala vam.
(Applause)
(Pljesak)