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 hteo da vam pokažem budućnost našeg stvaranja predmeta. Verujem da će, uskoro, naše zgrade i mašine konstruisati, replikovati i popravljati same sebe. Pokazaću vam moje viđenje trenutnog načina proizvodnje, a zatim ću to uporediti sa nekim sistemima u prirodi.
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.
Trenutni način proizvodnje - imamo nebodere, čija izgradnja traje dve i po godine, i zahteva od 500,000 do milion, dosta složenih delova i koristi nove i uzbudljive tehnologije u domenu čelika, betona i stakla. Imamo zanimljive mašine koje nas mogu odvesti u svemir -- pet godina, dva i po miliona delova.
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, sa druge strane, ako pogledate sisteme u prirodi, imamo proteine koji imaju dva miliona tipova, i mogu se saviti za 10,000 nanosekundi, ili DNK sa tri milijardi parova baza koje možemo replicirati u roku od nekih sat vremena. Postoji sva ta kompleksnost u našim prirodnim sistemima, ali su oni ekstremno efikasni -- daleko efikasniji od bilo čega što možemo da napravimo, daleko složeniji od bilo čega što možemo da napravimo. Daleko su efikasniji u pogledu korišćenja energije. Skoro da nikada ne prave greške. I, povrh toga, mogu popravljati sami sebe da bi duže trajali.
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.
Postoji nešto vrlo interesantno u prirodnim sistemima, i, ako uspemo da to prenesemo u okvire naše proizvodnje, dobićemo uzbudljive mogućnosti za načine na koje pravimo stvari. Mislim da ključ za tako nešto leži u samokonstrukciji.
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.
Ako bismo želeli da iskoristimo samokonstrukciju u našem fizičkom okruženju, po mom mišljenju, postoje četiri ključna faktora. Prvi je to što moramo da dekodiramo svu kompleksnost onogo što želimo da napravimo -- dakle, naših zgrada i mašina -- i to trebamo dekodirati u jednostavne nizove -- u osnovi, trebamo pronaći DNK naših zgrada. Zatim su nam potrebni delovi koji se mogu programirati, koji mogu preuzeti te nizove i iskoristiti ih da bi se podigli, ili da bi promenili konfiguraciju. Potrebna nam je i energija koja će omogućiti pokretanje tih delova, koja će omogućiti delovima da se, po uputstvu iz programa, podignu. I, na kraju, potreban nam je neki oblik korekcije grešaka, da bismo osigurali uspešnu gradnju onoga 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.
Pokazaću vam nekoliko projekata na kojima moje kolege i ja radimo na Institutu za tehnologiju Masačusets u cilju dostizanja samokonstruktivne budućnosti. Prva dva su MakroBot i DeciBot. Ovi projekti su roboti velikih razmera sa mogućnošću rekonfiguracije -- proteini od 2.4 i 3.6 metara. Poseduju mehaničke električne uređaje, senzore. Dekodirate oblik u koji želite da se preklopi u niz uglova -- minus 120, minus 120, 0, 0, 120, minus 120 stepeni -- nešto poput toga; dakle, u niz uglova, ili okreta, a zatim taj niz pošaljete kroz kabl. Svaka jedinica prima svoju poruku -- dakle, minus 120. Rotira se do tog stepena, proverava da li je dotle došla, a zatim šalje poruku dalje do susedne jedinice.
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.
Na ovom projektu su radili briljantni naučnici, inženjeri i dizajneri. Mislim da zaista dovodi do pitanja: da li je sve ovo ostvarivo na većoj razmeri? Na ovog dva ipo metra visokog robota je utrošeno na hiljade dolara i mnogo radnih sati. Možemo li zaista da uvećamo sve ovo? Možemo li da uključimo robotiku u svaki deo? Sa sledećim projektom smo postavili to pitanje i razmatrali domen pasivne prirode, to jest, pasivnog posedovanja programabilnosti rekonfiguracije. Ali, ovaj projekat ide korak dalje, jer pokušava da uključi i računanje. On zapravo uključuje najosnovniji deo potreban za računanje, digitalnu logičku kapiju, direktno u vaše delove.
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.
Ovo je NAND kapija. Imate jedan tetraedar koji čini kapiju koja će obavljati računanje, i dva tetraedra za unos podataka. Jedan od njih je za unos podataka od strane korisnika, dok slažete vaše delove, a drugi je od prošlog dela koji je bio unet. Nakon toga, on vam pruža rezultat u trodimenzionalnom prostoru. To zapravo znači da korisnik može da učita ono što želi da delovi urade. Tetraedar preračuna ono što je ranije radio i ono što vi želite da uradi. A zatim se pokreće u trodimenzionalnom prostoru -- dakle, gore ili dole. Sa leve strane, unos [1,1] daje rezultat 0, što dovodi do pomeranja nadole. Sa desne strane, unos [0,0] daje rezultat 1, što dovodi do pomeranja nagore. Ovo zapravo znači da naša struktura sada poseduje plan onoga što hoćemo da sagradimo.
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.
U delove su uključene sve informacije o onome što je konstruisano. To znači da imamo određeni oblik samoreplikacije. U ovom slučaju, ja ga nazivam samonavođenom replikacijom, jer vaša struktura sadrži tačan plan. Ukoliko dođe do greške, možete zameniti deo. Uključene su sve informacije o tome kako da je ispravite. Dakle, možete imati nešto što se penje i čita informacije, i daje rezultat 1 prema 1. Sve je direktno učitano; nema instrukcija iz spoljašnje sredine.
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.
Poslednji projekat koji ću vam pokazati zove se Pristrasni Lanci, i verovatno je najuzbudljiviji primer pasivnih sistema koji se sami replikuju koji trenutno posedujemo. On poseduje sposobnost rekonfiguracije i mogućnosti programiranja u okviru kompletno pasivnog sistema. U osnovi, to je niz elemenata. Svaki element je potpuno identičan, i na neki način pristrasan. Svaki lanac, odnosno svaki element, želi da se okrene desno ili levo. Dok spajate lanac, vi ga zapravo programirate. Govorite svakoj jedinici da li da se pomeri desno ili levo. Kada protresete lanac, on se preklopi u bilo koju konfiguraciju u koji ste ga programirali -- u ovom slučaju, u spiralu, ili u ovom, u dve kocke jedna do druge. Možete programirati bilo koji trodimenzionalni oblik -- ili jedno, 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.
Šta nam ovo govori o budućnosti? Mislim da nam govori da postoje nove mogućnosti za samokonstrukciju, replikaciju, popravku, u okviru naših fizičkih struktura, naših zgrada, mašina. Postoji novi nivo programabilnosti u ovim delovima, a iz toga proizilaze i nove mogućnosti za računanje. Imaćemo prostorno računanje. Zamislite kada bi naše zgrade, mostovi, mašine, svi naši delovi bili sposobni da računaju. To predstavlja neverovatnu paralelnu i distribuiranu moć računanja, kao i nove mogućnosti za dizajn. U ovome leže zanimljive mogućnosti. Mislim da su ovi projekti koje sam vam predstavio samo mali korak napred ka ovoj budućnosti, ukoliko uspemo da ih primenimo u svrhu stvaranja novog, samokonstruktivnog sveta.
Thank you.
Hvala vam.
(Applause)
(Aplauz)