Ovo je fotografija koju je načinio umjetnik Michael Najjar, i ona je stvarna u smislu da je on otišao u Argentinu da je uslika Ali je također i fikcija. Uloženo je mnogo truda u nju nakon samog fotografisanja. Ono što je on ustvari uradio je preoblikovao, digitalno, sve vrhove planina kako bi odgovarali promjenama Dow Jones indeksa. Tako da je ovo što vidite ova padina, ova strma padina sa dolinom u produžetku ustvari finansijska kriza iz 2008. godine. Fotografija je napravljena kada smo zagazili duboko u dolinu. Ne znam gdje se sada nalazimo. Ovo je Hang Seng indeks berze u Hong Kongu. I slična topografija. Pitam se zašto.
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 umjetnost, zar ne? Ovo je metafora. Ali čini se da je ključno da je ovo metafora sa zubima, i sa tom mišlju vam želim predložiti danas da ponovo promislimo ulogu savremene matematike -- ne samo finansijske matematike, nego matematike uopšte. Njena trazicija iz nečega što izvodimo i deriviramo iz stvarnog svijeta u nešto što zapravo počinje oblikovati svijet -- svijet oko nas, svijet unutar nas. I posebno algoritme, koji su u osnovi matematika koju kompjuteri koriste kako bi donosili odluke. Oni stiču osjećaj istine jer se iznova ponavljaju. I oni se okoštaju i kalcificiraju, i zapravo postaju stvarni.
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.
Ja sam razmišljao o ovome, od svih mjesta, na preko-atlantskom letu prije par godina jer sam se slučajno našao na sjedištu pored mađarskog fizičara, otprilike mojih godina, i mi razgovaramo o tome kakav je bio život fizičara u Mađarskoj tijekom hladnog rata. I upitao sam ga, "Šta ste Vi radili?",
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?"
I rekao je, "Pa, uglavnom smo pokušavali da razbijemo nevidljivost lovačkih aviona.“
And he said, "Well we were mostly breaking stealth."
A ja sam rekao, "Zvuči kao odličan posao. To je interesantno." "Kako to funkcioniše?" Da biste to razumjeli, morate imate osnovno razumijevanje kako funkcioniše nevidljivost aviona. I -- ovo je potpuno pojednostavljeno -- ali u osnovi ne možete jednostavno da provučete radarski signal kroz 156 tona čelika na nebu. Objekat neće jednostavno nestati. Ali ako možete uzeti ovu veliku, masivnu stvar, i pretvoriti je u milion malih stvari -- nešto kao jato ptica -- u tom slučaju, radar koji to traži mora biti u stanju uočiti svako jato ptica na nebu. Ako ste radar, to je zaista težak posao.
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.
"Da", rekao je, "ali samo ako si radar. Tako da nismo koristili radar; napravili smo crnu kutiju koja je pretraživala električne signale, elektronsku komunikaciju. I kad god bismo vidjeli jato ptica koje ima elektronsku komunikaciju, mogli smo biti prilično sigurni Amerikanci imaju nešto s tim."
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.'"
A ja sam rekao "Da. To je dobro. "Znači, Vi ste efektivno poništili "60 godina aeronautičkog istraživanja. Šta se dešava u drugom činu? Šta radite sad kad ste porasli?" I on reče, "Pa... finansijske usluge." "Oh.", rekao sam. Obzirom da su vijesti o finansijama nešto češće u posljednje vrijeme. "Kako to funkcioniše?", pitao sam. Rekao je, "Pa trenutno ima 2.000 fizičara na Wall Streetu, i ja sam jedan od njih." "I šta je crna kutija na Wall Streetu?", pitao sam.
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?"
"Interesantno da to pitate," rekao je "obzirom da se zaista zove trgovanje iz crne kutije ("black box trading"). A nekada se naziva i algo trgovanje, algoritamsko trgovanje." I algoritamsko trgovanje je nastalo dijelom jer su institucionalni investitori imali iste probleme kao američka ratna avijacija. Mijenjali su svoje vlasničke pozicije -- bilo da je to bio Proctor & Gamble, Accenture, ili neka druga firma -- mijenjali su vlasništvo nad milionima dionica nečega kroz tržište. I ako to urade odjednom to je kao da uložite sve u prvom dijeljenju u igri pokera. Jednostavno odate karte. Tako da su morali pronaći način -- a za ovo koriste algoritme -- da podijele tu jednu veliku stvar, veliku transakciju u milion malih transakcija. Čarolija i užas toga je da istu matematiku koju koristite da podijelite veliku stvar u milion malih djelića možete koristiti da pronađete milion malih djelića i ponovo ih sastavite i shvatite šta se zapravo dešava na tržištu.
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.
Tako da ako želite imati neku sliku berzovnog tržišta u ovom trenutku, možete ga zamisliti kao veliki broj algoritama koji su programirani da prikriju transakcije, i veliki broj algoritama koji su programirani da ih pronađu i djeluju. I sve je to u redu. Dok ne saznate da oni čine 70 procenata berzovnog prometa Sjedinjenih Država, 70 procenata operativnog sistema prethodno poznatog kao vaše penzije, vaši zajmovi za kuće.
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.
A šta može poći po zlu? Pa, šta može poći po zlu je da je prije godinu dana, 9 posto vrijednosti cjelokupnog tržišta nestalo za samo pet minuta. i to nazivaju "fleš krahom u 2:45". Potpuno neočekivano, 9 posto jednostavno nestane, i nitko do današnjeg dana, se čak ne može ni složiti oko toga šta se dogodilo, jer nitko nije izdao nalog, nitko to nije tražio. Niko nije imao kontrolu nad ovim. Sve što su imali bio je monitor ispred njih sa brojevima na njemu i crveno dugme na kojem je pisalo "Stop".
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."
Stvar je zapravo u tome da mi trenutno pišemo stvari, pišemo ove stvari koje više ne znamo pročitati. Načinili smo nešto nečitljivim. I izgubili smo osjećaj šta se zapravo zbiva u ovom svijetu koji smo napravili. I počinjemo tražiti put. U Bostonu postoji kompanija koja se zove Nanex, koja koristi matematiku i čarolije i ne znam šta sve ne, i oni posegnu za svim podacima o trgovini na berzi i ponekada zaista pronađu neke od ovih algoritama. I kada ih pronađu, oni ih iščupaju iz mase podataka i zakače ih na zid, kao preparirane leptirove. I rade ono što smo uvijek radili kad se suočimo sa velikom količinom podataka koje ne razumijemo -- damo im ime i priču. I tako, ovo je jedan od algoritama koji su pronašli koji zovu "Nož", "Karneval", "Bostonski mješač", "Sumrak".
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.
Stvar je da, naravno, oni nisu ograničeni samo na tržišta. Ovakve algoritme možete naći gdje god da pogledate, ukoliko naučite šta da tražite. Možete ih naći ovdje: ova knjiga o muhama koju ste možda uočili na Amazonu. Možda vam je zapala za oko kada je njena cijena dostigla 1,7 miliona dolara. Knjiga se više na štampa, ali ipak... (Smijeh) Da ste je kupili po cijeni od 1.7 miliona, to bi bila bagatela. Nekoliko sati kasnije, cijena se popela na 23.6 miliona dolara, uz troškove pošiljke i obrade. I pitanje je sljedeće: Niko nije ništa kupovao ili prodavao; šta se događalo? Možete uočiti ove pojave na Amazonu isto kao što ih možete vidjeti na Wall Streetu. I kada vidite ovu vrstu pojave, ono što vidite je manifestacija algoritama u konfliktu, algoritama zaključanih u beskonačnim krugovima jednih sa drugima, bez ikakvog ljudskog nadzora, bez roditeljske pažnje nekoga ko bi rekao, "Zapravo, 1.7 miliona je više nego dovoljno."
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."
(Smijeh)
(Laughter)
Sličan primjer Amazonu vidimo i na Netflixu. Netflix je prošao kroz nekoliko različitih algoritama tokom godina. Počeli su sa Cinematch, a onda su okušali i niz drugih. Imate Planetu dionosaura ("Dinosaur Planet"), Gravitaciju ("Gravity"). Trenutno koriste Pragmatični haos ("Pragmatic Chaos"). Pragmatični haos pokušava učiniti istu stvar kao i svi drugi Netflix algoritmi. Pokušava shvatiti vas, operativni sistem u vašim glavama, kako bi preporučio naredni film koji biste mogle pogledati -- što je veoma, veoma težak problem. Ali složenost problema kao i činjenica da ga i ne razumijemo u potpunosti, ne umanjuje učinak koji Pragmatični haos ima. Pragmatični haos, kao svi Netflix algoritmi, određuje, na kraju, 60 procenata svih filmova koji se rentaju. Dakle, jedan program sa nekom idejom o vama je odgovoran za 60 posto filmova koje pogledate.
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.
Ali šta kada biste mogli ocijeniti filmove i prije no što ih snime? Zar to ne bi bilo korisno? E, pa nekoliko informacijskih naučnika iz Velike Britanije je u Holivudu, i oni imaju algoritme za scenarije i filmske priče -- kompanije koja se zove Epagogix. I možete provući vaš scenarij kroz njihov program, i oni vam mogu reći, kvantificirati, da je to film koji će zaraditi 30 miliona dolara ili 200 miliona dolara. Stvar je u tome da ovo nije Google. Ovo nisu informacije. Ovo nisu finansijski podaci; ovo je kultura. I ono što vidimo ovdje, ili bolje rečeno, što obično ne vidimo jer ostane skriveno, jest da je ovo fizika kulture. I ako ovi algoritmi, kao algoritmi na Wall Streetu krahiraju jednog dana i pođu po zlu, kako ćemo znati, kako će to izgledati?
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?
A oni su u vašoj kući. Oni su u vašoj kući. Ovo su dva algoritma koja se bore za vašu dnevnu sobu. Ovo su dva robotizirana usisivača koja imaju vrlo različita shvatanja čistoće. I vi to možete i vidjeti ako ih usporite i dodate im svjetlo. A oni su kao neki tajni arhitekti u vašoj spavaćoj sobi. Čak i ideja da je i sama arhitektura na neki način podređena algoritamskoj optimizaciji nije nerealna. Ona je vrlo stvarna i to se već dešava oko vas.
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.
Najviše ćete je osjetiti kad se budete nalazili u zatvorenoj metalnoj kutiji, liftu nove generacije, kojeg zovu lift sa kontrolom odredišta. To su oni liftovi kod kojih morate odabrati sprat na koji idete prije negoli uđete u lift. I on koristi ono što se naziva algoritmom za pakovanje kanti. Znači ništa od ove ludosti da puštamo ljude da ulaze u lift koji žele. Svi koji žele na 10-ti sprat ulaze u lift dva, a svi koji žele na treći sprat ulaze u lift pet. Problem s ovim je da se ljudi prestrave. Ljudi se uspaniče. A možete i razumjeti zašto. Vidite zašto. Liftu nedostaje nekoliko važnih instrumenata, kao na primjer dugmad. (Smijeh) Stvari koje ljudi koriste. Sve što lift ima je broj koji se pomjera gore ili dole i crveno dugme na kojem piše "Stop". Tako dizajniramo stvari. Dizajniramo za ovaj mašinski dijalekt. I, dokle možemo ići tako? Dokle ovo možemo dovesti? Možemo ga dovesti stvarno, stvarno daleko.
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.
Dopustite mi da se vratim na Wall Street. Jer algoritmi na Wall Streetu zavise od jedne stvari više no od bilo čega drugog, a to je brzina. A oni operišu u milisekundama i mikrosekundama. Da bih vam dao osjećaj šta je mikrosekunda, potrebno vam je 500,000 mikrosekundi da biste kliknuli mišem. Ali ako ste algoritam na Wall Streetu i ako kasnite 5 mikrosekundi, vi ste gubitnik. Dakle ako ste algoritam, tražili biste arhitektu kao jednoga kojeg sam upoznao u Frankfurtu koji ispražnjuje cijeli neboder -- izbacuje sav namještaj, svu infrastrukturu koju koriste ljudi, i samo postavlja čelik na podove kako bi ih pripremio za nizove servera koji će ići unutra -- sve kako bi algoritam mogao prići bliže Internetu.
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.
Obično razmišljamo o Internetu kao o distribuiranom sistemu. I naravno, on to i jeste, ali je distribuiran iz različitih lokacija. U New Yorku, distribuiran je odavde: Carrier hotel u ulici Hudson. Odavde žice ulaze direktno u grad. I realnost je da što ste dalje od ove lokacije uvijek ste par mikrosekundi sporiji. Ovi momci s Wall Streeta, Marco Polo i Cherokee Nation oni su osam mikrosekundi sporiji od ovih algoritama koje lociraju u ispražnjene zgrade oko Carrier hotela. I to će nastaviti da se dešava. Nastavićemo da ih ispražnjujemo, jer vi, centimetar po centimetar, dolar po dolar, nitko od vas ne može iscijediti veći prihod iz tog prostora od Bostonskog mješača.
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.
Ali, ako se malo izdvojite iz slike i pogledate krupni plan, vidjećete kanal dug 1,330 kilometara između New Yorka i Čikaga koji izgrađen tijekom posljednjih par godina od kompanije koja se zove Spread Networks. Ovo je optički kabl koji je pružen između ova dva grada za saobraćaj samo jednog signala 37 puta brže no što vi možete kliknuti mišem -- izgrađen samo za ove algoritme, samo za Karneval, za Nož. I kada pomislite na to, da trčimo kroz Sjedinjene Države sa dinamitom i razbijačima stijena samo kako bi algoritam mogao zaključiti transakciju tri mikrosekunde brže, sve za komunikacijski okvir koji nijedno ljudsko biće neće upoznati to je neka vrsta manifestne sudbine koja će uvijek pomjerati nove granice.
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.
Nažalost, posao pred nama je vrlo ambiciozan. Ovo je samo teoretski. Ovo su pripremili neki matematičari sa MIT-a. I, da budem iskren, ni ja ne razumijem mnogo od ovoga o čemu su pričali. Uključujući neke svjetlosne kupole i kvantnu zamršenost, i je ne razumijem ništa od toga. Ali mogu se snaći na ovoj mapi. I ono što nam ova mapa kaže je da, ukoliko mislite zaraditi novac na tržištima gdje su ove crvene tačke, gdje se nalaze ljudi, u gradovima, moraćete postaviti servere na mjesta označena plavim tačkama kako biste bili najučinkovitiji. Možda ste primjetili da se mnoge od ovih plavih tačaka nalaze na sredini okeana. Znači to ćemo raditi, pravićemo neke balone ili nešto slično, ili platforme. bukvalno ćemo razdvajati more kako bismo uzimali novac iz zraka, jer pred vama je blistava budućnost, ukoliko ste algoritam.
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.
(Smijeh)
(Laughter)
Novac sam i nije toliko interesatan. Interesantno je kako nas novac motiviše. Tako mijenjamo oblik i izgled površine Zemlje u cilju algoritamske efikasnosti. I kada se u tom svjetlu vratite i pogledate fotografije Michaela Najjara, shvatite da to nisu metafore, već predskazanja. To su predskazanja seizmičkih, reljefno mijenjajučih efekata matematike. Pejsaž je uvijek bio proizvod čudne, nespokojne saradnje prirode i čovjeka. Ali sada imamo i treću ko-evolucijsku snagu: algoritme -- Bostonskog mješača, Karneval. I moraćemo ih početi razumijevati kao dio prirode. Na neki način, oni to i jesu.
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.
Hvala vam.
Thank you.
(Aplauz)
(Applause)