How many of you are creatives, designers, engineers, entrepreneurs, artists, or maybe you just have a really big imagination? Show of hands? (Cheers)
Koliko vas su kreativci, dizajneri, inženjeri, preduzetnici, umetnici ili možda prosto imate veoma bujnu maštu? Pokažite ruke? (Klicanje)
That's most of you. I have some news for us creatives. Over the course of the next 20 years, more will change around the way we do our work than has happened in the last 2,000. In fact, I think we're at the dawn of a new age in human history.
To je većina vas. Imam novosti za nas kreativce. U narednih 20 godina, više će se promeniti način na koji obavljamo naše poslove nego u poslednjih 2000 godina. Zapravo, mislim da smo u praskozorju novog doba u ljudskoj istoriji.
Now, there have been four major historical eras defined by the way we work. The Hunter-Gatherer Age lasted several million years. And then the Agricultural Age lasted several thousand years. The Industrial Age lasted a couple of centuries. And now the Information Age has lasted just a few decades. And now today, we're on the cusp of our next great era as a species.
Sad, imali smo četiri značajne istorijske ere, definisane načinom našeg rada. Doba lovaca i sakupljača koje je trajalo nekoliko miliona godina. A potom zemljoradničko doba koje je trajalo nekoliko hiljada godina. Industrijsko doba je trajalo nekoliko vekova. A sadašnje informaciono doba je trajalo svega nekoliko decenija. Trenutno smo kao vrsta na samom početku naše nove značajne ere.
Welcome to the Augmented Age. In this new era, your natural human capabilities are going to be augmented by computational systems that help you think, robotic systems that help you make, and a digital nervous system that connects you to the world far beyond your natural senses. Let's start with cognitive augmentation. How many of you are augmented cyborgs?
Dobro došli u prošireno doba. U ovoj novoj eri, vaše prirodne ljudske sposobnosti će da budu proširene uz pomoć računarskih sistema koji vam pomažu da razmišljate, robotskih sistema koji vam pomažu da stvarate i digitalnih nervnih sistema koji vas povezuju sa svetom daleko izvan vaših prirodnih čula. Započnimo kognitivnim proširenjem. Koliko vas su prošireni kiborzi?
(Laughter)
(Smeh)
I would actually argue that we're already augmented. Imagine you're at a party, and somebody asks you a question that you don't know the answer to. If you have one of these, in a few seconds, you can know the answer. But this is just a primitive beginning. Even Siri is just a passive tool. In fact, for the last three-and-a-half million years, the tools that we've had have been completely passive. They do exactly what we tell them and nothing more. Our very first tool only cut where we struck it. The chisel only carves where the artist points it. And even our most advanced tools do nothing without our explicit direction. In fact, to date, and this is something that frustrates me, we've always been limited by this need to manually push our wills into our tools -- like, manual, literally using our hands, even with computers. But I'm more like Scotty in "Star Trek."
Ja bih zapravo rekao da smo svi mi prošireni. Zamislite da ste na zabavi i neko vam postavi pitanje na koje ne znate odgovor. Ako imate nešto slično ovome, za nekoliko sekundi možete znati odgovor. Ali ovo je tek primitivni početak. Čak je i Siri tek pasivno oruđe. Zapravo, u poslednjih tri i po miliona godina, oruđa koja smo imali su bila potpuno pasivna. Ona rade tačno ono što im kažemo i ništa više. Naše prvo oruđe je jedino seklo onde gde bismo udarili njime. Dleto rezbari samo onde gde ga umetnik usmeri. Čak i naša najnaprednija oruđa ne rade bilo šta bez naših eksplicitnih naredbi. Zapravo, do danas, a to je nešto što me nervira, oduvek smo bili ograničeni potrebom da ručno uteramo našu volju u naše alate - ručno, bukvalno koristeći naše ruke, čak i sa kompjuterima. No ja sam više nalik Skotiju iz "Zvezdanih staza".
(Laughter)
(Smeh)
I want to have a conversation with a computer. I want to say, "Computer, let's design a car," and the computer shows me a car. And I say, "No, more fast-looking, and less German," and bang, the computer shows me an option.
Želim da razgovaram s kompjuterom. Želim da kažem: "Kompjuteru, hajde da dizajniramo automobil", i kompjuter mi pokaže automobil. A ja kažem: "Ne, da izgleda brže i manje nemački", i, bum, kompjuter mi pokaže opciju.
(Laughter)
(Smeh)
That conversation might be a little ways off, probably less than many of us think, but right now, we're working on it. Tools are making this leap from being passive to being generative. Generative design tools use a computer and algorithms to synthesize geometry to come up with new designs all by themselves. All it needs are your goals and your constraints.
Taj razgovor je možda malčice daleko, verovatno manje nego što većina nas misli, ali trenutno radimo na tome. Oruđa prave ovaj skok od pasivnih do stvaralačkih. Stvaralačka dizajnerska oruđa koriste kompjutere i algoritme, da bi tim spojem stvorila geometriju i potpuno sama došla do novih dizajna. Sve što im je potrebno su vaši ciljevi i vaša ograničenja.
I'll give you an example. In the case of this aerial drone chassis, all you would need to do is tell it something like, it has four propellers, you want it to be as lightweight as possible, and you need it to be aerodynamically efficient. Then what the computer does is it explores the entire solution space: every single possibility that solves and meets your criteria -- millions of them. It takes big computers to do this. But it comes back to us with designs that we, by ourselves, never could've imagined. And the computer's coming up with this stuff all by itself -- no one ever drew anything, and it started completely from scratch. And by the way, it's no accident that the drone body looks just like the pelvis of a flying squirrel.
Daću vam jedan primer. U slučaju ove vazdušne šasije drona, sve što bi trebalo da uradite je da tražite sledeće: da ima četiri propelera, želite da bude što lakša i želite da ima aerodinamičnu efikasnost. Potom kompjuter istražuje celokupan prostor rešenja: baš svaku mogućnost koja rešava i ispunjava vaše kriterijume - milione njih. Potrebni su veliki kompjuteri da to obave. Ali su nam uzvratili dizajnima koje mi sami ne bismo nikad mogli da zamislimo. A kompjuter je sam došao do ovoga - niko nikad nije nacrtao bilo šta - i započeo je potpuno od nule. I, usput, nije slučajno da telo drona izgleda baš kao karlica leteće veverice.
(Laughter)
(Smeh)
It's because the algorithms are designed to work the same way evolution does.
To je tako jer su algoritmi dizajnirani da deluju na isti način kao evolucija.
What's exciting is we're starting to see this technology out in the real world. We've been working with Airbus for a couple of years on this concept plane for the future. It's a ways out still. But just recently we used a generative-design AI to come up with this. This is a 3D-printed cabin partition that's been designed by a computer. It's stronger than the original yet half the weight, and it will be flying in the Airbus A320 later this year. So computers can now generate; they can come up with their own solutions to our well-defined problems. But they're not intuitive. They still have to start from scratch every single time, and that's because they never learn. Unlike Maggie.
Uzbudljivo je što počinjemo da gledamo ovu tehnologiju u stvarnom svetu. Nekoliko godina smo radili sa Erbasom na konceptu aviona iz budućnosti. I dalje je ispred svog vremena. Ali baš nedavno smo koristili generativni dizajn veštačke inteligencije da bismo smislili ovo. Ovo je pregrada odštampana 3D štampačem, koju je dizajnirao kompjuter. Jača je od prvobitne, a ipak je upola lakša i leteće u erbasu A320 kasnije ove godine. Kompjuteri sad mogu da stvaraju; mogu da osmisle sopstvena rešenja za naše dobro definisane probleme. Ali nisu intuitivni. I dalje moraju da počnu od nule, baš svaki put, a to je zato što nikad ne nauče. Za razliku od Megi.
(Laughter)
(Smeh)
Maggie's actually smarter than our most advanced design tools. What do I mean by that? If her owner picks up that leash, Maggie knows with a fair degree of certainty it's time to go for a walk. And how did she learn? Well, every time the owner picked up the leash, they went for a walk. And Maggie did three things: she had to pay attention, she had to remember what happened and she had to retain and create a pattern in her mind.
Megi je zapravo pametnija od naših najnaprednijih dizajnerskih oruđa. Šta podrazumevam time? Ako njen vlasnik uzme povodac, Megi zna s porpiličnim stepenom izvesnosti da je vreme za šetnju. A kako je naučila? Pa, svaki put kad je vlasnik uzeo povodac, išli su u šetnju. I Megi je obavila tri stvari: morala je da obrati pažnju, morala je da se priseti šta se desilo i morala je da zadrži i stvori obrazac u svom umu.
Interestingly, that's exactly what computer scientists have been trying to get AIs to do for the last 60 or so years. Back in 1952, they built this computer that could play Tic-Tac-Toe. Big deal. Then 45 years later, in 1997, Deep Blue beats Kasparov at chess. 2011, Watson beats these two humans at Jeopardy, which is much harder for a computer to play than chess is. In fact, rather than working from predefined recipes, Watson had to use reasoning to overcome his human opponents. And then a couple of weeks ago, DeepMind's AlphaGo beats the world's best human at Go, which is the most difficult game that we have. In fact, in Go, there are more possible moves than there are atoms in the universe. So in order to win, what AlphaGo had to do was develop intuition. And in fact, at some points, AlphaGo's programmers didn't understand why AlphaGo was doing what it was doing.
Zanimljivo je da je upravo to ono što naučnici za kompjutere pokušavaju da navedu VI da uradi u poslednjih oko 60 godina. Te 1952. su sagradili ovaj kompjuter koji je mogao da igra iks-oks. Velika stvar. Potom, 45 godina kasnije, 1997. Deep Blue je pobedio Kasparova u šahu. Godine 2011, Watson je pobedio ova dva čoveka u kvizu, što je daleko teže za kompjuter da iga od šaha. Zapravo, umesto da radi na osnovu već definisanih recepata, Votson je morao da koristi rasuđivanje da bi prevazišao ljudske protivnike. A onda, pre nekoliko nedelja, AlphaGo iz DeepMind-a je pobedio ljudsko biće koje je najbolje u gou, a to je najkomplikovanija igra koju imamo. Zapravo, ima više mogućih poteza u gou nego što ima atoma u univerzumu. Pa, kako bi pobedio, AlphaGo je morao da razvije intuiciju. I zapravo, u nekim momentima programeri AlphaGo-a nisu razumeli zašto je AlphaGo radio to što radi.
And things are moving really fast. I mean, consider -- in the space of a human lifetime, computers have gone from a child's game to what's recognized as the pinnacle of strategic thought. What's basically happening is computers are going from being like Spock to being a lot more like Kirk.
A stvari se odvijaju zaista brzo. Mislim, razmotrite - u okviru ljudskog životnog veka, kompjuteri su prešli od dečje igre do onoga što se smatra vrhuncem strateškog mišljenja. U suštini se dešava to da kompjuteri prestaju da budu poput Spoka i postaju mnogo više nalik Kirku.
(Laughter)
(Smeh)
Right? From pure logic to intuition. Would you cross this bridge? Most of you are saying, "Oh, hell no!"
Je li tako? Od čiste logike do intuicije. Da li biste prešli ovaj most? Većina vas govori: "Uh, nema šanse!"
(Laughter)
(Smeh)
And you arrived at that decision in a split second. You just sort of knew that bridge was unsafe. And that's exactly the kind of intuition that our deep-learning systems are starting to develop right now. Very soon, you'll literally be able to show something you've made, you've designed, to a computer, and it will look at it and say, "Sorry, homie, that'll never work. You have to try again." Or you could ask it if people are going to like your next song, or your next flavor of ice cream. Or, much more importantly, you could work with a computer to solve a problem that we've never faced before. For instance, climate change. We're not doing a very good job on our own, we could certainly use all the help we can get. That's what I'm talking about, technology amplifying our cognitive abilities so we can imagine and design things that were simply out of our reach as plain old un-augmented humans.
A stigli ste do te odluke u deliću sekunde. Prosto ste nekako znali da taj most nije bezbedan. A upravo je to tip intuicije koju naši sistemi dubinskog učenja trenutno počinju da razvijaju. Veoma brzo ćete bukvalno moći da pokažete kompjuteru nešto što ste napravili, što ste dizajnirali i on će to da pogleda i kaže: "Izvini, druže, to neće proći. Moraš opet da pokušaš." Ili ćete moći da ga pitate da li će se ljudima sviđati vaša nova pesma ili vaš novi ukus sladoleda. Ili, što je još važnije, moći ćete raditi sa kompjuterom da biste rešili problem s kojim se pre nismo suočili. Na primer, klimatske promene. Sami ne obavljamo posao naročito dobro, svakako da bi nam koristila sva moguća pomoć. O tome govorim, o tehnologiji koja naglašava naše kognitivne sposobnosti kako bismo mogli da zamislimo i dizajniramo stvari koje nisu dostupne nama, prostim starim neproširenim ljudima.
So what about making all of this crazy new stuff that we're going to invent and design? I think the era of human augmentation is as much about the physical world as it is about the virtual, intellectual realm. How will technology augment us? In the physical world, robotic systems. OK, there's certainly a fear that robots are going to take jobs away from humans, and that is true in certain sectors. But I'm much more interested in this idea that humans and robots working together are going to augment each other, and start to inhabit a new space.
Pa, o čemu se radi kod stvaranja svih tih blesavih novih stvari koje ćemo izumeti i dizajnirati? Mislim da se u eri ljudskog proširivanja podjednako radi o fizičkom svetu kao i o virtuelnoj, intelektualnoj sferi. Kako će nas tehnologija proširiti? U fizičkom svetu, biće to robotski sistemi. U redu, svakako da postoji strah da će roboti da oduzmu poslove ljudima, to je tačno za određene sektore. No, mene više zanima zamisao da će ljudi i roboti radeći zajedno proširiti jedni druge, i počeće da naseljavaju nove prostore.
This is our applied research lab in San Francisco, where one of our areas of focus is advanced robotics, specifically, human-robot collaboration. And this is Bishop, one of our robots. As an experiment, we set it up to help a person working in construction doing repetitive tasks -- tasks like cutting out holes for outlets or light switches in drywall.
Ovo je primenjena istraživačka laboratorija u San Francisku, gde je napredna robotika jedna od oblasti na koje se fokusiramo, naročito saradnja između ljudi i robota. A ovo je Bišop, jedan od naših robota. Kao eksperiment, podesili smo ga da pomaže osobi koja na građevini obavlja repetitivne poslove - poslove poput bušenja rupa u gips-kartonu za utičnice ili prekidače za svetla.
(Laughter)
(Smeh)
So, Bishop's human partner can tell what to do in plain English and with simple gestures, kind of like talking to a dog, and then Bishop executes on those instructions with perfect precision. We're using the human for what the human is good at: awareness, perception and decision making. And we're using the robot for what it's good at: precision and repetitiveness.
Dakle, Bišopov ljudski partner može da mu objasni na engleskom i jednostavnom gestikulacijom, poput razgovaranja sa psom, a potom Bišop, izvodi ta uputstva savršenom preciznošću. Koristimo ljude za ono u čemu su dobri: svesnost, percepcija i donošenje odluka. A koristimo robota za ono u čemu je dobar: preciznost i ponavljanje.
Here's another cool project that Bishop worked on. The goal of this project, which we called the HIVE, was to prototype the experience of humans, computers and robots all working together to solve a highly complex design problem. The humans acted as labor. They cruised around the construction site, they manipulated the bamboo -- which, by the way, because it's a non-isomorphic material, is super hard for robots to deal with. But then the robots did this fiber winding, which was almost impossible for a human to do. And then we had an AI that was controlling everything. It was telling the humans what to do, telling the robots what to do and keeping track of thousands of individual components. What's interesting is, building this pavilion was simply not possible without human, robot and AI augmenting each other.
Još jedan sjajan projekat na kom je radio Bišop. Cilj ovog projekta, koga smo nazvali HIVE, bio je da testira iskustvo ljudi, kompjutera i robota gde svi rade zajedno kako bi rešili veoma složene dizajnerske probleme. Ljudi su služili kao radna snaga. Kružili su po gradilištu, rukovali bambusom - koji je, usput, stoga što je neizomorfan materijal, veoma težak robotima za rukovanje. No, potom su roboti namotavali ovo vlakno, a to je skoro nemoguće za ljude da urade. A potom smo imali VI koja je sve kontrolisala. Govorila je ljudima šta da rade, govorila je robotima šta da rade i nadgledala hiljade pojedinačnih komponenti. Zanimljivo je da je izgradnja ovog paviljona prosto bila nemoguća bez ljudi, robota i VI koji proširuju jedni druge.
OK, I'll share one more project. This one's a little bit crazy. We're working with Amsterdam-based artist Joris Laarman and his team at MX3D to generatively design and robotically print the world's first autonomously manufactured bridge. So, Joris and an AI are designing this thing right now, as we speak, in Amsterdam. And when they're done, we're going to hit "Go," and robots will start 3D printing in stainless steel, and then they're going to keep printing, without human intervention, until the bridge is finished.
Podeliću sa vama još jedan projekat. Ovaj je malčice blesav. Radimo sa umetnicima iz Amsterdama, Jorisom Larmanom i njegovom ekipom iz MX3D da bismo generativno dizajnirali i robotski odštampali prvi u svetu autonomno proizveden most. Dakle, Joris i VI baš dok govorimo dizajniraju taj objekat u Amsterdamu. A kad završe, pritisnućemo "Kreni" i roboti će početi 3D tehnologijom da štampaju nerđajući čelik i nastaviće da štampaju bez ljudskog uplitanja, sve dok završe most.
So, as computers are going to augment our ability to imagine and design new stuff, robotic systems are going to help us build and make things that we've never been able to make before. But what about our ability to sense and control these things? What about a nervous system for the things that we make?
Pa, kako će roboti da prošire našu sposobnost zamišljanja i dizajniranja novih stvari, robotski sistemi će da nam pomognu da gradimo i pravimo stvari koje nismo mogli da pravimo pre. No, šta je s našom sposobnošću da osetimo i kontrolišemo ove stvari? Kako bi bilo da imamo nervni sistem kod stvari koje pravimo?
Our nervous system, the human nervous system, tells us everything that's going on around us. But the nervous system of the things we make is rudimentary at best. For instance, a car doesn't tell the city's public works department that it just hit a pothole at the corner of Broadway and Morrison. A building doesn't tell its designers whether or not the people inside like being there, and the toy manufacturer doesn't know if a toy is actually being played with -- how and where and whether or not it's any fun. Look, I'm sure that the designers imagined this lifestyle for Barbie when they designed her.
Naš nervni sistem, ljudski nervni sistem, saopštava nam o svemu što se dešava oko nas. Međutim, nervni sitem stvari koje pravimo je u najboljem slučaju prost. Na primer, automobil ne saopštava gradskom odseku za javne delatnosti da je upravo udario u rupu na uglu ulice Brodvej i Morison. Građevina ne sopštava njenim dizajnerima da li ljudi unutar nje vole da budu tu, a proizvođač lutaka ne zna da li se zaista igraju njihovim igračkama - kako, gde i da li su ili nisu zabavne. Vidite, siguran sam da su dizajneri zamislili ovakav stil života za barbiku kada su je dizajnirali.
(Laughter)
(Smeh)
But what if it turns out that Barbie's actually really lonely?
Ali šta ako se ispostavi da je barbi zapravo veoma usamljena?
(Laughter)
(Smeh)
If the designers had known what was really happening in the real world with their designs -- the road, the building, Barbie -- they could've used that knowledge to create an experience that was better for the user. What's missing is a nervous system connecting us to all of the things that we design, make and use. What if all of you had that kind of information flowing to you from the things you create in the real world? With all of the stuff we make, we spend a tremendous amount of money and energy -- in fact, last year, about two trillion dollars -- convincing people to buy the things we've made. But if you had this connection to the things that you design and create after they're out in the real world, after they've been sold or launched or whatever, we could actually change that, and go from making people want our stuff, to just making stuff that people want in the first place.
Kad bi dizajneri znali šta se zaista dešava u stvarnom svetu njihovim dizajnima - putevima, građevinama, barbikama - mogli bi da koriste to znanje da stvore bolja iskustva za korisnike. Nedostaje nervni sistem koji bi nas povezao sa svim stvarima koje dizajniramo, pravimo i koristimo. Šta kad biste svi vi imali dotok takvog oblika informacija od stvari koje stvarate u stvarnom svetu? Uz sve što pravimo, trošimo ogromne količine novca i energije - zapravo, prošle godine, skoro dva biliona dolara - ubeđujući ljude da kupe stvari koje pravimo. Ali kad biste imali ovakvu vezu sa stvarima koje dizajnirate i stvarate kada se one nađu u stvarnom svetu, nakon što ih prodaju ili lansiraju ili šta god, zapravo bismo mogli to da promenimo i da se pomerimo od ubeđivanja ljudi da vole naše stvari do prosto pravljenja stvari koje su ljudima prvenstveno potrebne.
The good news is, we're working on digital nervous systems that connect us to the things we design. We're working on one project with a couple of guys down in Los Angeles called the Bandito Brothers and their team. And one of the things these guys do is build insane cars that do absolutely insane things. These guys are crazy --
Dobre vesti su da radimo na digitalnom nervnom sistemu koji bi nas povezao sa stvarima koje dizajniramo. Radimo na jednom projektu sa nekoliko momaka iz Los Anđelesa, koji sebe nazivaju Bandito Bradersima, i njihovom ekipom. A jedna od stvari koju ovi momci rade je izgradnja ludih automobila koji rade potpuno lude stvari. Ovi momci su sumanuti -
(Laughter)
(Smeh)
in the best way. And what we're doing with them is taking a traditional race-car chassis and giving it a nervous system.
na najbolji način. A mi s njima radimo tako što uzmemo tradicionalnu šasiju za trkačka auta i ugrađujemo nervni sistem u nju.
So we instrumented it with dozens of sensors, put a world-class driver behind the wheel, took it out to the desert and drove the hell out of it for a week. And the car's nervous system captured everything that was happening to the car. We captured four billion data points; all of the forces that it was subjected to. And then we did something crazy. We took all of that data, and plugged it into a generative-design AI we call "Dreamcatcher." So what do get when you give a design tool a nervous system, and you ask it to build you the ultimate car chassis? You get this. This is something that a human could never have designed. Except a human did design this, but it was a human that was augmented by a generative-design AI, a digital nervous system and robots that can actually fabricate something like this.
Dakle, opskrbili smo je desetinama senzora, stavili smo iza volana vozača svetske klase, odvezli auto u pustinju vozali ga do besvesti sedam dana. A nervni sistem automobila je zabeležio sve što se dešavalo automobilu. Zabeležili smo četiri milijarde jedinica podataka; sve sile kojima je bilo izloženo. A potom smo uradili nešto ludo. Uzeli smo sve podatke i priključili ih na VI genrativnog dizajna koju nazivamo "Dreamcatcher". Pa, šta dobijate kada dizajnerskom oruđu date nervni sistem i zatražite od njega da vam sagradi najbolju šasiju za auto? Dobijate ovo. Ovo je nešto što ljudi nikad ne bi mogli da dizajniraju. Samo što ljudi ovo jesu dizajnirali, ali to su bili ljudi prošireni VI generativnog dizajna, digitalnim nervnim sistemom i robotima koji zapravo mogu da proizvedu nešto ovakvo.
So if this is the future, the Augmented Age, and we're going to be augmented cognitively, physically and perceptually, what will that look like? What is this wonderland going to be like?
Pa, ako je ovo budućnost, prošireno doba, a mi ćemo da budemo prošireni kognitivno, fizički i čulno, kako će to da izgleda? Kako će da izgleda ova zemlja čuda?
I think we're going to see a world where we're moving from things that are fabricated to things that are farmed. Where we're moving from things that are constructed to that which is grown. We're going to move from being isolated to being connected. And we'll move away from extraction to embrace aggregation. I also think we'll shift from craving obedience from our things to valuing autonomy.
Mislim da ćemo da vidimo svet u kom se udaljavamo od stvari koje se proizvode do stvari koje se obrađuju. U kom se udaljavamo od stvari koje se konstruišu do onih koje se gaje. Udaljićemo se od izolacije ka povezanosti. I udaljićemo se od kopanja ka sakupljanju. Mislim i da ćemo se pomeriti od žudnje da nam stvari budu poslušne ka cenjenju autonomije.
Thanks to our augmented capabilities, our world is going to change dramatically. We're going to have a world with more variety, more connectedness, more dynamism, more complexity, more adaptability and, of course, more beauty. The shape of things to come will be unlike anything we've ever seen before. Why? Because what will be shaping those things is this new partnership between technology, nature and humanity. That, to me, is a future well worth looking forward to.
Zahvaljujući našim proširenim mogućnostima, naš svet će da se drastično izmeni. Imaćemo svet s više izbora, više povezanosti, dinamičniji, složeniji prilagodljiviji i, naravno, lepši. Obrisi budućnosti neće da liče na bilo šta što smo videli do sad. Zašto? Jer će sve ovo da oblikuje novo partnerstvo između tehnologije, prirode i čovečanstva. Za mene, to je budućnost koju vredi iščekivati.
Thank you all so much.
Mnogo vam hvala.
(Applause)
(Aplauz)