This is a photograph by the artist Michael Najjar, and it's real, in the sense that he went there to Argentina to take the photo. But it's also a fiction. There's a lot of work that went into it after that. And what he's done is he's actually reshaped, digitally, all of the contours of the mountains to follow the vicissitudes of the Dow Jones index. So what you see, that precipice, that high precipice with the valley, is the 2008 financial crisis. The photo was made when we were deep in the valley over there. I don't know where we are now. This is the Hang Seng index for Hong Kong. And similar topography. I wonder why.
Ovo je fotografija od umjetnika Michaela Najjara, i ona je stvarna, u smislu da je otišao u Argentinu kako bi uslikao ovu fotografiju. No ona je i fikcija. Mnogo posla je još uloženo nakon toga. A ono što je učinio je da je zapravo preoblikovao, digitalno, sve konture planina kako bi pratio promjene Dow Jones indeksa. Stoga ono što vidite, da litica, da je visoka litica u dolini, financijska kriza 2008. Fotografija je uslikana kada smo bili duboko u dolini ondje. Neznam gdje smo sada. Ovo je Hang Seng index za Hong Kong. I slična topografija. Pitam se zašto.
And this is art. This is metaphor. But I think the point is that this is metaphor with teeth, and it's with those teeth that I want to propose today that we rethink a little bit about the role of contemporary math -- not just financial math, but math in general. That its transition from being something that we extract and derive from the world to something that actually starts to shape it -- the world around us and the world inside us. And it's specifically algorithms, which are basically the math that computers use to decide stuff. They acquire the sensibility of truth because they repeat over and over again, and they ossify and calcify, and they become real.
Ovo je umjetnost. Ovo je metafora. No mislim da je poanta u tome da su ovo metafore sa zubima. I s ovim zubima želim danas predložiti da promislimo malo o ulozi suvremene matematike -- ne samo financijske matematike, već matematike općenito. Da je ona tranzicija od nečega što smo istisnuli i izvukli iz svijeta do nečega što zapravo počinje oblikovati svijet oko nas i svijet unutar nas. To se posebno odnosi na algoritme, koji su zapravo matematika koju računala koriste kako bi odlučili o nečemu. Oni stječu senzibilitet istine, jer se iznova ponavljaju. Oni se okoštavaju i kalcificiraju, te postaju stvarni.
And I was thinking about this, of all places, on a transatlantic flight a couple of years ago, because I happened to be seated next to a Hungarian physicist about my age and we were talking about what life was like during the Cold War for physicists in Hungary. And I said, "So what were you doing?"
O ovome sam razmišljao, od svih mjesta, na prekoatlantskom letu prije nekoliko godina, zato jer sam slučajno dobio mjesto kraj mađarskog fizičara mojih godina i pričali smo o tome kakav je bio život tokom hladnog rata za fizičare u Mađarskoj. Pitao sam, "I što ste radili?"
And he said, "Well we were mostly breaking stealth."
On odgovara, "Više manje smo razbijali nevidljivost."
And I said, "That's a good job. That's interesting. How does that work?" And to understand that, you have to understand a little bit about how stealth works. And so -- this is an over-simplification -- but basically, it's not like you can just pass a radar signal right through 156 tons of steel in the sky. It's not just going to disappear. But if you can take this big, massive thing, and you could turn it into a million little things -- something like a flock of birds -- well then the radar that's looking for that has to be able to see every flock of birds in the sky. And if you're a radar, that's a really bad job.
Odgovaram, "To je dobar posao. To je zanimljivo. Kako to funkcionira?" Da biste to razumjeli, morate malo razumjeti kako nevidljivost funkcionira. I tako -- ovo je pojednostavljenje -- no u osnovi, nije samo da može proći radarski signal kroz 156 tona čelika u zraku. Neće samo odjedanput nestati. No ukoliko možete uzeti ovu veliku, masivnu stvar, i možete ju pretvoriti u milijun malih stvari -- nešto kao jato ptica -- onda zapravo radar koji to traži mora biti u mogućnosti da vidi sva jata ptica u zraku. A ukoliko ste radar, to je stvarno težak posao.
And he said, "Yeah." He said, "But that's if you're a radar. So we didn't use a radar; we built a black box that was looking for electrical signals, electronic communication. And whenever we saw a flock of birds that had electronic communication, we thought, 'Probably has something to do with the Americans.'"
On odgovara, "Da." Kaže on, "No to ako si radar." Stoga nismo koristili radar; izradili smo crnu kutiju koja traži električne signale, elektroničku komunikaciju. I svaki put kada smo vidjeli jato ptica koje ima elektroničku komunikaciju, mislili smo kako vjerovatno ima nekakve veze s amerikancima."
And I said, "Yeah. That's good. So you've effectively negated 60 years of aeronautic research. What's your act two? What do you do when you grow up?" And he said, "Well, financial services." And I said, "Oh." Because those had been in the news lately. And I said, "How does that work?" And he said, "Well there's 2,000 physicists on Wall Street now, and I'm one of them." And I said, "What's the black box for Wall Street?"
"Da" kažem ja. To je dobro. Znači vi ste efikasno negirali 60 godina aeronautičkog istraživanja. Koji vam je drugi čin? Što radite nakon što odrastete?" Odgovara on, "Pa, financijske usluge." "Oh," kažem ja. Zato jer toga vidimo po vijestima u zadnje vrijeme. Kažem ja, "I kako to funkcionira?" Odgovara on, "Trenutno je 2.000 fizičara na Wall Street-u, a ja sam jedan od njih." Kažem ja, "I što je crna kutija za Wall Street?"
And he said, "It's funny you ask that, because it's actually called black box trading. And it's also sometimes called algo trading, algorithmic trading." And algorithmic trading evolved in part because institutional traders have the same problems that the United States Air Force had, which is that they're moving these positions -- whether it's Proctor & Gamble or Accenture, whatever -- they're moving a million shares of something through the market. And if they do that all at once, it's like playing poker and going all in right away. You just tip your hand. And so they have to find a way -- and they use algorithms to do this -- to break up that big thing into a million little transactions. And the magic and the horror of that is that the same math that you use to break up the big thing into a million little things can be used to find a million little things and sew them back together and figure out what's actually happening in the market.
Odgovara on, "Smiješno što me tako pitaš, jer se zapravo zove trgovanje crnom kutijom. Nekada se još naziva algo trgovanje, algoritamsko trgovanje." I algoritamsko trgovanje je djelomično evoluiralo iz razloga što su institucionalni 'trejderi' imali iste probleme koje je imalo Američko zrakoplovstvo, gdje oni zapravo premještaju ove pozicije -- nebitno radi li se o Proctor & Gamble-u ili Accenturu -- oni premještaju milijun udjela nečega kroz tržište. Te ukoliko sve to naprave odjednom, to je kao da igrate poker i odmah sve ulažete. Zapravo ste pokazali svoje karte. Stoga moraju pronaći način -- i koriste algoritme kako bi to učinili -- da razbijete tu veliku stvar na milijun malih transakcija. Magija i horor iza toga je da ista ta matematika koju koristite da razbijete tu veliku stvar na milijun malih stvari može se koristiti za pronalaženje milijuna malih stvari koje spajate natrag zajedno i odgonetnete što se zapravo događa na tržištu.
So if you need to have some image of what's happening in the stock market right now, what you can picture is a bunch of algorithms that are basically programmed to hide, and a bunch of algorithms that are programmed to go find them and act. And all of that's great, and it's fine. And that's 70 percent of the United States stock market, 70 percent of the operating system formerly known as your pension, your mortgage.
Stoga ako trebate imati neku sliku o tome što se trenutno događa na tržištu vrijednosnica, ono što možete zamisliti je hrpa algoritama koji su u biti programirani da se sakriju, i hrpa algoritama koja je programirana da ih pronađe i djeluje. I to je sve super, u redu je. I to se odnosi na 70 posto tržišta vrijednosnica u Sjedinjenim Državama. 70 posto od operativnog sustava poznatog kao vaša mirovina, vaša hipoteka.
And what could go wrong? What could go wrong is that a year ago, nine percent of the entire market just disappears in five minutes, and they called it the Flash Crash of 2:45. All of a sudden, nine percent just goes away, and nobody to this day can even agree on what happened because nobody ordered it, nobody asked for it. Nobody had any control over what was actually happening. All they had was just a monitor in front of them that had the numbers on it and just a red button that said, "Stop."
Što može poći po zlu? Ono što može poći po zlu je da prije godinu dana, devet posto cijelog tržišta samo je nestalo u pet minuta, i nazivaju ga 'flash crash' od 2:45 Odjednom, devet posto samo nestane, i nitko do danas se ne može složiti što se zapravo dogodilo, jer nitko nije to naručio, nitko nije zatražio. Nitko nije imaju bilo kakvu kontrolu nad onime što se zapravo događalo. Sve što su imali je monitor ispred njih koji je prikazivao brojeve i crveno dugme na kojemu piše, "Stop."
And that's the thing, is that we're writing things, we're writing these things that we can no longer read. And we've rendered something illegible, and we've lost the sense of what's actually happening in this world that we've made. And we're starting to make our way. There's a company in Boston called Nanex, and they use math and magic and I don't know what, and they reach into all the market data and they find, actually sometimes, some of these algorithms. And when they find them they pull them out and they pin them to the wall like butterflies. And they do what we've always done when confronted with huge amounts of data that we don't understand -- which is that they give them a name and a story. So this is one that they found, they called the Knife, the Carnival, the Boston Shuffler, Twilight.
O tome se radi, da pišemo stvari, pišemo te stvari koje više ne možemo pročitati. Napravili smo nešto nečitko. I izgubili smo osjećaj što se zapravo događa u ovome svijetu koji smo stvorili. Počinjemo stvarati svoj put. Postoji kompanija u Bostonu pod imenom Nanex, koja koristi matematiku i magiju i tko zna što drugo, posežu za svim podacima s tržišta i pronađu, nekada, neke od ovih algoritama. I kada ih nađu izvuku ih van i zakvače ih za zid kao leptire. I učine, ono što uvijek činimo kad se suočavamo s velikom količinom podataka koju ne razumijemo -- a to je da im daju ime i priču. Ovo je jedan kojeg su našli, zovu ga Nož, Karneval, Bostonski prevrtljivac, Sumrak.
And the gag is that, of course, these aren't just running through the market. You can find these kinds of things wherever you look, once you learn how to look for them. You can find it here: this book about flies that you may have been looking at on Amazon. You may have noticed it when its price started at 1.7 million dollars. It's out of print -- still ... (Laughter) If you had bought it at 1.7, it would have been a bargain. A few hours later, it had gone up to 23.6 million dollars, plus shipping and handling. And the question is: Nobody was buying or selling anything; what was happening? And you see this behavior on Amazon as surely as you see it on Wall Street. And when you see this kind of behavior, what you see is the evidence of algorithms in conflict, algorithms locked in loops with each other, without any human oversight, without any adult supervision to say, "Actually, 1.7 million is plenty."
I problem je taj, naravno, da ovi ne prolaze samo kroz tržište. Možete naći ovakve stvari gdjegod pogledate, jednom kad naučite kako ih pronaći. Možete ih naći ovdje: na ovoj knjizi o muhama koju ste možda tražili na Amazonu. Možda ste primjetili kada joj je početna cijena bila 1,7 milijuna dolara. Još uvijek je izvan tiska -- (Smijeh) Da ste ju kupili za 1,7, to bi bilo jeftino. Nekoliko sati poslije, porasla je na 23,6 milijuna dolara, plus troškovi transporta i rukovanja. I pitanje je: Nitko nije kupovao ni prodavao ništa; što se događalo? Vidite ovo ponašanje na Amazonu jednako kao što vidite na Wall Streetu. I kada vidite ovakvo ponašanje, vidite dokaz algoritama u konfliktu, algoritama zatvorenih u petlje jedne s drugima, bez ljudskog nadzora, bez nadzora odrasle osobe koja kaže, "Zapravo, 1,7 milijuna je puno."
(Laughter)
(Smijeh)
And as with Amazon, so it is with Netflix. And so Netflix has gone through several different algorithms over the years. They started with Cinematch, and they've tried a bunch of others -- there's Dinosaur Planet; there's Gravity. They're using Pragmatic Chaos now. Pragmatic Chaos is, like all of Netflix algorithms, trying to do the same thing. It's trying to get a grasp on you, on the firmware inside the human skull, so that it can recommend what movie you might want to watch next -- which is a very, very difficult problem. But the difficulty of the problem and the fact that we don't really quite have it down, it doesn't take away from the effects Pragmatic Chaos has. Pragmatic Chaos, like all Netflix algorithms, determines, in the end, 60 percent of what movies end up being rented. So one piece of code with one idea about you is responsible for 60 percent of those movies.
Kao i s Amazonom, tako je i s Netflixom. Netflix je prošao kroz nekoliko različitih algoritama tokom godina. Počeli su s 'Cinematch', a postoje i mnogi drugi. Imate Dinaosaurov planet, tu je Gravitacija. Trenutno koriste Pragmatični Kaos. Pragmatični Kaos, kao i svi Netflixovi algoritmi, pokušava činiti istu stvar. Pokušava vas dokučiti, sistem unutar ljudske lubanje, tako da bi mogao preporučiti koji film možda želite gledati -- što je vrlo, vrlo težak problem. No težina problema i činjenica da zapravo još nismo na čisto, ne osporava efekte koje ima Pragmatični Kaos. Pragmatični Kaos, kao svi Netflixovi algoritmi, određuje, u konačnici, 60 posto filmova koji se iznajme. Stoga jedan komad koda s jednom idejom o vama je odgovoran za 60 posto tih filmova.
But what if you could rate those movies before they get made? Wouldn't that be handy? Well, a few data scientists from the U.K. are in Hollywood, and they have "story algorithms" -- a company called Epagogix. And you can run your script through there, and they can tell you, quantifiably, that that's a 30 million dollar movie or a 200 million dollar movie. And the thing is, is that this isn't Google. This isn't information. These aren't financial stats; this is culture. And what you see here, or what you don't really see normally, is that these are the physics of culture. And if these algorithms, like the algorithms on Wall Street, just crashed one day and went awry, how would we know? What would it look like?
No što ukoliko biste mogli ocjeniti te filmove prije nego što se naprave? Ne bi li to bilo zgodno? Pa, nekolicina podatkovnih znanstvenika iz U.K. su u Hollywoodu, i imaju algoritme priče -- kompanija pod imenom Epagogix. I možete provući svoj scenario ovdje, i mogu vam reći, kvantificirano, da je to film od 30 milijuna dolara ili film od 200 milijuna dolara. A radi se o tome da ovo nije Google. Ovo nije informacija. Ovo nisu financijski pokazatelji; ovo je kultura. Ono što ovdje vidite, ili što normalno ne vidite, je da je ovo fizika kulture. I ukoliko se ovi algoritmi, kao algoritmi na Wall Street-u, jednoga dana sruše i odu naopako, kako bismo znali, kako bi to izgledalo?
And they're in your house. They're in your house. These are two algorithms competing for your living room. These are two different cleaning robots that have very different ideas about what clean means. And you can see it if you slow it down and attach lights to them, and they're sort of like secret architects in your bedroom. And the idea that architecture itself is somehow subject to algorithmic optimization is not far-fetched. It's super-real and it's happening around you.
I oni su u vašim kućama. Oni su u vašim kućama. Ovo su dva algoritma koji se natječu za vaš dnevni boravak. Ovo su dva različita robota spremača koji imaju vrlo različite ideje o tome što znači čisto. I možete to vidjeti ukoliko ih usporite i zakvačite svijetlo na njih. I oni su kao tajni arhitekti u vašoj spavačoj sobi. Te ideja da je arhitektura sama po sebi na neki način subjekt algoritamske optimizacije nije daleka. To je super stvarno i događa se oko vas.
You feel it most when you're in a sealed metal box, a new-style elevator; they're called destination-control elevators. These are the ones where you have to press what floor you're going to go to before you get in the elevator. And it uses what's called a bin-packing algorithm. So none of this mishegas of letting everybody go into whatever car they want. Everybody who wants to go to the 10th floor goes into car two, and everybody who wants to go to the third floor goes into car five. And the problem with that is that people freak out. People panic. And you see why. You see why. It's because the elevator is missing some important instrumentation, like the buttons. (Laughter) Like the things that people use. All it has is just the number that moves up or down and that red button that says, "Stop." And this is what we're designing for. We're designing for this machine dialect. And how far can you take that? How far can you take it? You can take it really, really far.
Najviše možete osjetiti kada ste u zatvorenoj metalnoj kutiji, dizala novog stila, nazivaju se dizala kontrole destinacije. To su ona na kojima morate prisitsnuti na koji kat želite ići prije nego uđete u dizalo. I koristi tzv. algoritam pakiranja kutije. Stoga ništa od ovih besmislica dopuštanja svima ulazak u vozilo koje žele. Svatko to želi ići na 10 kat ulazi u vozilo dva, a svatko tko želi ići na treći kat ulazi u vozilo pet. A problem s time je da ljudi polude. Ljudi paniče. I možete vidjeti zašto. Vidite zašto. To je zato jer dizalu nedostaju neki važni instrumenti, kao dugmad. (Smijeh) Nešto što ljudi koriste. Jedino što ima je broj koji se kreće gore ili dolje i crveno dugme koje kaže, "Stop." I zbog toga dizajniramo. Mi dizajniramo za ovaj dijalekt strojeva. I koliko daleko možete ići s time? Koliko daleko možete otići? Možete otići jako, jako daleko.
So let me take it back to Wall Street. Because the algorithms of Wall Street are dependent on one quality above all else, which is speed. And they operate on milliseconds and microseconds. And just to give you a sense of what microseconds are, it takes you 500,000 microseconds just to click a mouse. But if you're a Wall Street algorithm and you're five microseconds behind, you're a loser. So if you were an algorithm, you'd look for an architect like the one that I met in Frankfurt who was hollowing out a skyscraper -- throwing out all the furniture, all the infrastructure for human use, and just running steel on the floors to get ready for the stacks of servers to go in -- all so an algorithm could get close to the Internet.
Vratimo se nazad na Wall Street. Jer algoritmi s Wall Streeta ovisni su o jednoj kvaliteti iznad svega, a to je brzina. I oni rade na milisekundama i mikrosekundama. Da dobijete osjećaj što su mikrosekunde, potrebno je 500.000 mikrosekundi kako bi kliknuli miša. No ako ste algoritam s Wall Street-a i zaostajete pet mikrosekundi, vi ste gubitnik. Stoga da ste algoritam, potražili bi arhitekta kao onoga što sam sreo u Frankfurtu koji je ispražnjavao neboder -- izbacujući sav namještaj, svu infrastrukturu potrebnu čovjeku, i samo ostavljajući čelik na podovima spremajući ga za postavljanje servera -- sve kako bi algoritam bio bliže Internetu.
And you think of the Internet as this kind of distributed system. And of course, it is, but it's distributed from places. In New York, this is where it's distributed from: the Carrier Hotel located on Hudson Street. And this is really where the wires come right up into the city. And the reality is that the further away you are from that, you're a few microseconds behind every time. These guys down on Wall Street, Marco Polo and Cherokee Nation, they're eight microseconds behind all these guys going into the empty buildings being hollowed out up around the Carrier Hotel. And that's going to keep happening. We're going to keep hollowing them out, because you, inch for inch and pound for pound and dollar for dollar, none of you could squeeze revenue out of that space like the Boston Shuffler could.
A vi zamišljate Internet kao sistem distribucije. Naravno, on to je, ali se distribuira s određenog mjesta. U New Yorku, odavde se distribuira: Carrier Hotel smješten u Hudson ulici. I ovdje je zapravo mjesto gdje žice izlaze van u grad. I stvarnost je ta da što ste dalje od toga, vi ste nekoliko mikrosekundi iza svaki put. Ovi momci dolje s Wall Streeta, Marko Polo i Cherokee Nacija, oni su osam mikrosekundi iza svih ovih drugih koji se nalaze u ovim praznim ispraznjenim zgradama oko Carrier Hotela. I to će se nastaviti događati. Nastavit ćemo ih ispražnjavati zato jer, inč po inč i funtu za funtu i dolar za dolar, nitko od vas ne može iscjediti prihod iz prostora kao što to može Bostonski Prevrtljivac.
But if you zoom out, if you zoom out, you would see an 825-mile trench between New York City and Chicago that's been built over the last few years by a company called Spread Networks. This is a fiber optic cable that was laid between those two cities to just be able to traffic one signal 37 times faster than you can click a mouse -- just for these algorithms, just for the Carnival and the Knife. And when you think about this, that we're running through the United States with dynamite and rock saws so that an algorithm can close the deal three microseconds faster, all for a communications framework that no human will ever know, that's a kind of manifest destiny; and we'll always look for a new frontier.
No ako odzumirate ako odzumirate, vidjeli bi rov od 825 milja između New Yorka i Chicaga koji se gradi zadnjih nekoliko godina od kompanije Spread Networks. Ovo je svjetlosni optički kabel koji je položen između ova dva grada kako bi bili u mogućnosti poslati samo jedan signal 37 puta brže nego što možete kliknuti mišem -- samo za ove algoritme, samo za Karneval i Nož. I kada razmislite o ovome, da prolazimo kroz Sjedinjene Države s dinamitom i pilama za kamen kako bi algoritam mogao zatvoriti poziciju tri mikrosekunde brže, sve za komunikacijski sistem za koji čovjek nikad neće znati, to je kao manifest sudbine i uvijek će tražiti nove granice.
Unfortunately, we have our work cut out for us. This is just theoretical. This is some mathematicians at MIT. And the truth is I don't really understand a lot of what they're talking about. It involves light cones and quantum entanglement, and I don't really understand any of that. But I can read this map, and what this map says is that, if you're trying to make money on the markets where the red dots are, that's where people are, where the cities are, you're going to have to put the servers where the blue dots are to do that most effectively. And the thing that you might have noticed about those blue dots is that a lot of them are in the middle of the ocean. So that's what we'll do: we'll build bubbles or something, or platforms. We'll actually part the water to pull money out of the air, because it's a bright future if you're an algorithm.
Nažalost, mi smo izostavljeni iz ovog posla. Ovo je samo teoretski. Ovo su neki matematičari sa MIT-a. Istina je da nažalost ne razumijem mnogo toga o čemu pričaju. Uključuje svjetlosni stožac i kvantnu zapreku, i ne razumijem ništa od toga. Ali mogu čitati ovu kartu. A ono o čemu ova karta govori je da ukoliko želite zaraditi novac na tržištima gdje se nalaze crvene točke, tamo gdje se nalaze ljudi, gradovi, morat ćete postaviti servere tamo gdje se nalaze plave točke kako bi bili što efikasniji. Ono što ste mogli zamjetiti na plavim točkama je da se mnogo njih nalaze usred oceana. I to je što ćemo napraviti, sagradit ćemo balone ili nešto drugo, ili platforme. Mi ćemo zapravo razdvajati vodu kako bi izvukli novac iz zraka zato jer je to sjajna budućnost ukoliko ste algoritam.
(Laughter)
(Smijeh)
And it's not the money that's so interesting actually. It's what the money motivates, that we're actually terraforming the Earth itself with this kind of algorithmic efficiency. And in that light, you go back and you look at Michael Najjar's photographs, and you realize that they're not metaphor, they're prophecy. They're prophecy for the kind of seismic, terrestrial effects of the math that we're making. And the landscape was always made by this sort of weird, uneasy collaboration between nature and man. But now there's this third co-evolutionary force: algorithms -- the Boston Shuffler, the Carnival. And we will have to understand those as nature, and in a way, they are.
I ne radi se o novcu da je toliko interesantan zapravo. Radi se o tome što novac motivira. Mi zapravo teraformiramo samu Zemlju s ovom algoritamskom efikasnošću. U tome svjetlu, vratite se nazad i pogledajte fotografije Michaela Najjara, i shvatite da one nisu metafora, one su proročanstvo. One su proročanstvo za ove seizmičke, zemaljske učinke matematike koju stvaramo. I pejzaž je uvijek bio načinjen od ove čudne, nelagodne suradnje između prirode i čovjeka. No sada imamo i treću ko-evolucijsku silu: algoritme -- Bostonskog Prevrtljivca, Karneval. I morat ćemo ih shvatiti kao prirodu. Na neki način, oni to i jesu.
Thank you.
Hvala vam.
(Applause)
(Pljesak)