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.
Gaur gustatuko litzaidake erakustea objektuak eraikitako geroko era. Nik uste dut laster gure eraikuntzak eta makineriak autoeraikituta izango direla. haiek beraiek erreplikatzen eta konpontzen. Beraz erakutsiko dizuet zein den, nire ustez, manufaktura-prozesuaren gaurko egoera. eta gero sistema natural batzuekin konparatuko ditugu.
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.
Beraz gaurko manufaktura-prozesuan, zeru-harraskariak dauzkagu -- bi urte eta erdia [eraikitzeko], 500.000-tik milioiera zatietako nahiko konplexua, teknologia berriak eta sustagarriak altzairuan, hormigoian, beiran. Makineria sustagarriak dauzkagu haiek espaziora eramaten gaituzten -- bost urte [muntatzeko denbora], 2,5 milioi zati.
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.
Baina, beste aldetik, sistema naturalak ikusten badituzue, Proteinak dauzkagu bi milioi motakoak, muntatutako 10.000 nanosegundutan, edo DNA 3.000 milioi base-pare haiek erreplika daitezke ordu batean soilik. Beraz hor dago konplexotasuna gure sistema naturalena, hain zuzen ere, baina haiek benetan eraginkorrak. guk eraikitako baino askoz eraginkorragoak, guk eraikitako baino askoz konplexuagoak. Energia esparruan askoz erakingorragoak. Ia inoiz akatsak suertatzen dira. Eta euren buruari konpontzen diote luzaroan bizitzeko.
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.
Beraz badago oso gauza interesgarria sistema naturaletan. Eta hori eramaten badugu gure eraikuntza esparrura, orduan badago izugarrizko potentzialitasuna eraikitzeko eran. Eta nik uste dut autoeraikuntza dela gakoa.
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.
Gure ingurugiroan autoeraikuntza erabili nahi badugu, Nik uste dut lau faktore gakok daudela. Lehenengoa da guk argitu behar dugula eraiki nahi dugun konplexutasuna -- hots, gure eraikuntzak eta makineriak. Eta sekuentzia sinple batzuekin argitu behar ditugu -- gure eraikuntzen funtzionamenduren DNA. Gero zati programagarriak behar ditugu horiek sekuentziak har ditzakete eta muntatzeko edo konfiguratzeko erabiltzea. Energia pixka bat behar dugu prozesua martxan jartzeko, eta horrek baimentzen ditu zatiak muntatzeko programatik hasita. Eta akats-zuzentzaile erredundanteren bat behar dugu ziurtatzeko ea guk nahi dugun eraikuntza ondo egiten dugun.
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.
Beraz proiektu batzuk erakutsiko dizkizuet nire kideak eta biok MIT-en martxan jarri ditugunak autoeraikuntzaren geroa lortzeko. Lehenengo biak MacroBot eta DeciBot dira. Proeiktu horiek handiko robot berritxuragarriak dira -- 2,5 mt, 3,7 mt, proteina handiak. gailu mekanikoz, elektrikoz eta sentsorez beteta daude. Batak, muntatu nahi duenak dekodifikatzen du, perspektiba batzuen sekuentzian -- hemen ezeko 120, ezezko 120, 0, 0, 120, ezezko 120 -- horrelako zerbait; badaude perspektiben sekuentzia bat, edo ikuspegiak, eta arduradunak bidaltzen du sekuentzia hori kablearen zehar. Unitate bakoitzak bere mezua hartzen du -- hemen ezezko 120 -- berak biratzen du lerrokatzeko, eta helburura heltzen zen ala ez frogatzen du eta orduan bere auzokideari informazioa pasatzen du.
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.
Hemen daude zientzilari distiratsuak, proiektu honetan lan egiten zuten ingeniariek, diseniatzaileek. Eta nik uste dut hark argitzen duena dela: Hau egin al daiteke eskala handiko batean? Esan nahi dut, milaka dolar, ehundaka lanordu 2,5 metroko robot bat egiteko. Egin al daiteke? Zati guztietan robotika sar dezakegu? Hurrengo adibideak saiatzen du erantzuten eta aztertu ezazu bere natura pasiboa, edo pasiboki saiatzen du programazio berritxugarria eskuratzen. Baina urrutiko urratsa doa, eta denbora errealean saiztzen du kalkulatzen. Berak, funtsean, konputazio funtsezko blokeak sartzen ditu, ate logiko digitalak, zatietan modu zuzenean.
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.
Hau da NAND atea. Tetaedroa daukagu, zein atea den eta prozesamendua egingo du, eta bi sartzeko tetaedro dauzkagu. Batak, erabiltzailearen sarrera du,blokeak muntatu ahala. Bestea, aurretik jarritako bloketik dator. Eta hiru-dimentsioko espazioan ondorioa ematen digu. Eta horrek jakin nahi du erabiltzaileak berak konekta dezakeela blokeek egin nahi duten lana. Berak prozesatzen du arestian egin zuena eta guk nahi genuen egitea. Eta orduan hiru-dimentsioko espazioan mugitzen da -- gora eta behera. Ezkerraldean, [1,1] sarrera daukagu eta irteera da 0, orduan beherantz doa. Eskuinean, [0,0] sarrera 1 irteera da, orduan gora doa. Horrek esan nahi du gure egiturek planoak dauzkatela guk eraikin nahi ditugun eraikuntzetik.
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.
Haiek aurretik eraikin zenaren informazio integratua dute. Horrek esan nahi du autoerreplikazio mota bat daukagula eskura. Kasu honetan, auto-gidari erreplikazioari deritzogu egiturak instrukzio berberak egiten dituelako. Akatsak badaude, zati bat alda daiteke. Bertako informazioa integratuta dago konponbideak nola egin daitezken erakusteko. Orduan badaukagu gailu bat, zeinek leku hartara igotzen eta han irakurtzen duen eta irtenbide bat eskainiko digun banan banan. Dena integratuta; ez dago kanpoko instrukziorik.
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.
Orduan nik erakutsiko dizuedan azken proiektua, Kate Bihurriak, eta nik uste dut garai honetako adibide hunkigarriena dela autoerainkuntzako sistema pasibokoak. Berak berkonfigurazioa eta programazioa kontuan hartuta sistema guztiz pasibo bat bihurtzen du. Beraz, osagai-katea daukazu. Osagai bakoitza berdin-berdina da, eta bihurriak dira. Osagai bakoitzak ezkerretara edo eskuinera jiratu nahi du. Beraz, katea lotzean, programazio bat egiten ari zara. Osagai bakoitzari esaten diogu ezkerrera edo eskuinera jiratu nahi izateko. Eta katea astintzen dugunean, tolestu egiten da aurretiko antolatzeko konfigurazioan -- kasu honetan, kiribila, edo beste kasu horretan, bi kubo, bata bestearen ondoan. Orduan programa daiteke edozein hiru-dimentsioko gailu -- edo dimentsio-bakarrekoa, bi-dimentsikoa -- kate honetan modu pasibo batean.
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.
Beraz, zer esaten digu horrek geroari buruz? Uste dut adibide horiek erakusten dizkigutela autoeraikuntzarako, erreplikaziorako, konponketarako posibilitate berriak daudela gure egitura fisikoetan, eraikutzetan, makinerietan. Osagai horietan programazio-ahalmen berriak daude. Eta hortik, konputazio-ahalmen berriak. Espazioko konputazio izango dugu. Demagun gure eraikuntzek, gure zubiek, makineriek, gure adreiluek kalkuluak egin ditzatekeela. Harrigarria da konputazio-ahalmen paralelo eta banatu hori, diseinatzeko aukera berriak. Ahalmen hunkigarria da, benetan. Orduan, nik uste dut erakusteko proiektuak oso urrats txikiak direla gerorako bidean, teknologia berri horiek inplementatzen baditugu autoeraikuntzako mundu berri baterako.
Thank you.
Mila esker.
(Applause)
(Txaloak)