TEDGlobal 2011
Kevin Slavin: How algorithms shape our world
Kevin Slavin: Kako algoritmi oblikuju naš svet
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Kevin Slavin diskutuje o tome kako živimo u svetu dizajniranom za algoritme, koji ga sve više kontrolišu. U ovom neverovatnom govoru sa TEDGlobal-a, on pokazuje kako ovi kompleksni kompijuterski programi određuju: taktike za špijunažu, cene akcija, scenarije filmova i arhitekturu. I on upozorava da pišemo kodove koje ne možemo da razumemo, sa implikacijama koje ne možemo da kontrolišemo
Kevin Slavin - Algoworld expert
Kevin Slavin navigates in the algoworld, the expanding space in our lives that’s determined and run by algorithms. Full bio
Kevin Slavin navigates in the algoworld, the expanding space in our lives that’s determined and run by algorithms. Full bio
Double-click the English transcript below to play the video.
00:15
This is a photograph
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Ovo je fotografija
00:17
by the artist Michael Najjar,
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umetnika Mihaela Najara
00:19
and it's real,
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i ona je stvarna
00:21
in the sense that he went there to Argentina
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u smislu da je on otišao u Argentinu
00:23
to take the photo.
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da bi napravio ovu fotografiju.
00:25
But it's also a fiction. There's a lot of work that went into it after that.
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Ali je i izmišljenja. Uloženo je mnogo rada u nju nakon fotografisanja.
00:28
And what he's done
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On ju je
00:30
is he's actually reshaped, digitally,
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digitalno preoblikovao,
00:32
all of the contours of the mountains
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tako da vrhovi planina
00:34
to follow the vicissitudes of the Dow Jones index.
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prate kretanje Dau Džons (Dow Jones) indeksa.
00:37
So what you see,
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Dakle, to što vidite,
00:39
that precipice, that high precipice with the valley,
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ova provalija, duboka provalija sa dolinom,
00:41
is the 2008 financial crisis.
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je finansijska kriza iz 2008.
00:43
The photo was made
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Ova fotografija je napravljena
00:45
when we were deep in the valley over there.
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kada smo bili duboko u finansijskoj provaliji.
00:47
I don't know where we are now.
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Ne znam gde se sada nalazimo.
00:49
This is the Hang Seng index
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Ovo je Hang Seng indeks
00:51
for Hong Kong.
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berze u Hong Kongu.
00:53
And similar topography.
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I slična topografija.
00:55
I wonder why.
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Pitam se zašto?
00:57
And this is art. This is metaphor.
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Ovo je umetnost. Ovo je metafora.
01:00
But I think the point is
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Ali poenta je u tome
01:02
that this is metaphor with teeth,
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da je ovo metafora sa zubima.
01:04
and it's with those teeth that I want to propose today
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I sa tim metaforičkim zubima želim danas da predložim
01:07
that we rethink a little bit
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da malo porazmislimo
01:09
about the role of contemporary math --
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o ulozi savremene matematike,
01:12
not just financial math, but math in general.
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ne samo finansijske matematike, već generalno matematike.
01:15
That its transition
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Njena tranzicija
01:17
from being something that we extract and derive from the world
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od nečega što smo uzeli od sveta,
01:20
to something that actually starts to shape it --
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do nečega što stvarno počinje da ga oblikuje --
01:23
the world around us and the world inside us.
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svet oko nas i svet u nama.
01:26
And it's specifically algorithms,
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I njegovi specifični algoritmi
01:28
which are basically the math
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koji su u suštini matematika
01:30
that computers use to decide stuff.
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koju kompjuteri koriste da donesu odluke.
01:33
They acquire the sensibility of truth
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Oni zahtevaju osećaj za istinu
01:35
because they repeat over and over again,
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jer se stalno ponavljaju.
01:37
and they ossify and calcify,
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I oni okoštavaju i kalcifikuju se
01:40
and they become real.
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i postaju stvarni.
01:42
And I was thinking about this, of all places,
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Od svih mesta, ja sam o ovome razmišljao
01:45
on a transatlantic flight a couple of years ago,
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na preko-okeanskom letu pre par godina
01:48
because I happened to be seated
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jer su me smestili
01:50
next to a Hungarian physicist about my age
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pored mađarskog fizičara koji je bio mojih godina
01:52
and we were talking
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i razgovarali smo
01:54
about what life was like during the Cold War
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o tome kakav je bio život fizičara
01:56
for physicists in Hungary.
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u Mađarskoj za vreme Hladnog rata.
01:58
And I said, "So what were you doing?"
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Upitao sam ga: "Šta ste Vi radili?"
02:00
And he said, "Well we were mostly breaking stealth."
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A on je rekao: "Pa, uglavnom smo pokušavali da prokljuvimo nevidljivost lovačkih aviona."
02:02
And I said, "That's a good job. That's interesting.
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Rekao sam: "To zvuči kao dobar posao. To je interesantno"
02:04
How does that work?"
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Kako to funkcioniše?"
02:06
And to understand that,
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Da bi razumeli to,
02:08
you have to understand a little bit about how stealth works.
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morate da razumete kako funkcioniše nevidljivost aviona.
02:11
And so -- this is an over-simplification --
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Ovo je jako prosto objašnjenje
02:14
but basically, it's not like
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ali u suštini, ne možete tako jednostavno
02:16
you can just pass a radar signal
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da prođete radarskim signalom
02:18
right through 156 tons of steel in the sky.
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kroz 156 tona čelika na nebu.
02:21
It's not just going to disappear.
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Objekat neće tek tako nestati.
02:24
But if you can take this big, massive thing,
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Ali možete uzeti tu veliku, masivnu stvar,
02:27
and you could turn it into
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i pretvoriti je u
02:30
a million little things --
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milion malih stvari --
02:32
something like a flock of birds --
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nesto poput jata ptica --
02:34
well then the radar that's looking for that
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tada radar koji ga traži
02:36
has to be able to see
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mora biti u mogućnosti i da vidi
02:38
every flock of birds in the sky.
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svako jato ptica na nebu.
02:40
And if you're a radar, that's a really bad job.
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Ako ste radar, to je jako naporan posao.
02:44
And he said, "Yeah." He said, "But that's if you're a radar.
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"Da", reče on, "samo ako si radar".
02:47
So we didn't use a radar;
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Tako da nismo koristili radar;
02:49
we built a black box that was looking for electrical signals,
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napravili smo crnu kutiju koja je tražila električne signale,
02:52
electronic communication.
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elektronsku komunikaciju.
02:55
And whenever we saw a flock of birds that had electronic communication,
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I kad god smo videli jato ptica koje komunicira elektronski
02:58
we thought, 'Probably has something to do with the Americans.'"
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pomislili smo da to sigurno ima veze sa Amerikancima."
03:01
And I said, "Yeah.
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Rekao sam: "Da.
03:03
That's good.
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To je dobro
03:05
So you've effectively negated
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"Vi ste dakle efektivno negirali
03:07
60 years of aeronautic research.
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60 godina aeronautičkih istraživanja."
03:09
What's your act two?
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Šta je vaš drugi čin?
03:11
What do you do when you grow up?"
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Šta ćete raditi kada odrastete?"
03:13
And he said,
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I on reče,
03:15
"Well, financial services."
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Pa... finansijske usluge.
03:17
And I said, "Oh."
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"Oh", rekoh ja na to.
03:19
Because those had been in the news lately.
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O tome se nedavno govorilo u vestima.
03:22
And I said, "How does that work?"
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"Kako to funkcioniše?", pitao sam.
03:24
And he said, "Well there's 2,000 physicists on Wall Street now,
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A on je odgovorio, "Na Vol Stritu imaš trenutno 2000 fizičara
03:26
and I'm one of them."
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i ja sam jedan od njih."
03:28
And I said, "What's the black box for Wall Street?"
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"Šta je crna kutija Vol Strita?", upitah ga.
03:31
And he said, "It's funny you ask that,
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A on reče: "Zanimljivo je što to pitate,
03:33
because it's actually called black box trading.
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jer se to zapravo zove trgovanje iz crne kutije".
03:36
And it's also sometimes called algo trading,
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A ponekad se zove i algo trgovanje,
03:38
algorithmic trading."
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algoritamsko trgovanje."
03:41
And algorithmic trading evolved in part
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Algoritamsko trgovanje se razvilo
03:44
because institutional traders have the same problems
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jer su institucionalni trgovci imali isti problem
03:47
that the United States Air Force had,
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kao i Američka vazdušna avijacija.
03:50
which is that they're moving these positions --
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Oni su menjali svoje vlasničke pozicije --
03:53
whether it's Proctor & Gamble or Accenture, whatever --
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bilo da su Proctor & Gamble ili Accenture ili neko drugi --
03:55
they're moving a million shares of something
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menjali vlasništvo nad milionima
03:57
through the market.
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deonica nečega na tržištu.
03:59
And if they do that all at once,
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I ako oni to urade odjednom,
04:01
it's like playing poker and going all in right away.
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to je kao da svi sve ulože u prvom delenju u pokeru
04:03
You just tip your hand.
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Samo odate karte.
04:05
And so they have to find a way --
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Tako da su morali da nađu način --
04:07
and they use algorithms to do this --
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i za to koriste algoritme --
04:09
to break up that big thing
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da podele tu jednu veliku transakciju
04:11
into a million little transactions.
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u milion malih transakcija.
04:13
And the magic and the horror of that
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Magija i horor toga
04:15
is that the same math
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je što ta ista matematika
04:17
that you use to break up the big thing
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koju koristite da biste razbili tu veliku stvar
04:19
into a million little things
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na milion manjih delova
04:21
can be used to find a million little things
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može da koristi da nađete milion malih delova
04:23
and sew them back together
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i spojite ih nazad u jednu celinu
04:25
and figure out what's actually happening in the market.
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i tako otkrijete šta se dešava na tržištu.
04:27
So if you need to have some image
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Ako vam treba slika o tome
04:29
of what's happening in the stock market right now,
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šta se dešava na berzi deonica trenutno,
04:32
what you can picture is a bunch of algorithms
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možete da zamislite kao veliki broj algoritama
04:34
that are basically programmed to hide,
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koji su u suštini programirani da prikriju transakcije,
04:37
and a bunch of algorithms that are programmed to go find them and act.
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i mnogo algoritama koji su programirani da ih nađu i deluju.
04:40
And all of that's great, and it's fine.
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I sve je to u redu.
04:43
And that's 70 percent
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Dok ne saznate da oni čine 70 posto
04:45
of the United States stock market,
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prometa na berzama u Sjedinjenim Državama,
04:47
70 percent of the operating system
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70% operativnog sistema,
04:49
formerly known as your pension,
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formalno poznatog kao vaša penzija,
04:52
your mortgage.
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vaša hipoteka.
04:55
And what could go wrong?
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A šta je moglo da krene po zlu?
04:57
What could go wrong
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Ono što je krenulo po zlu
04:59
is that a year ago,
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je da je pre godinu dana
05:01
nine percent of the entire market just disappears in five minutes,
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devet posto ukupnog tržišta nestalo za pet minuta,
05:04
and they called it the Flash Crash of 2:45.
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i to nazivaju "Blic lom u 2:45"
05:07
All of a sudden, nine percent just goes away,
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Iz čista mira, devet procenata je nestalo,
05:10
and nobody to this day
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i do današnjeg dana se niko
05:12
can even agree on what happened
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ne može složiti oko toga šta se desilo,
05:14
because nobody ordered it, nobody asked for it.
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jer niko to nije naredio, niti tražio.
05:17
Nobody had any control over what was actually happening.
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Niko nije imao kontrolu nad tim.
05:20
All they had
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Sve što su imali je bio monitor
05:22
was just a monitor in front of them
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ispred sebe
05:24
that had the numbers on it
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sa brojevima
05:26
and just a red button
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i crveno dugme
05:28
that said, "Stop."
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na kojem je pisalo, "Stop."
05:30
And that's the thing,
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Stvar je u tome
05:32
is that we're writing things,
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da mi pišemo stvari,
05:34
we're writing these things that we can no longer read.
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pišemo stvari koje nismo u stanju više da pročitamo.
05:37
And we've rendered something
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Dobili smo nešto
05:39
illegible,
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nečitko.
05:41
and we've lost the sense
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I izgubili smo ideju
05:44
of what's actually happening
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o tome šta se stvarno dešava
05:46
in this world that we've made.
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u svetu koji smo napravili.
05:48
And we're starting to make our way.
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I počeli smo da radimo po sopstvenom nahođenju.
05:50
There's a company in Boston called Nanex,
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U Bostonu postoji kompanija koja se zove Nanex,
05:53
and they use math and magic
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i oni koriste matematiku i magiju
05:55
and I don't know what,
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i ne znam šta još sve ne,
05:57
and they reach into all the market data
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i pristupaju svim podacima tržišta
05:59
and they find, actually sometimes, some of these algorithms.
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i pronalaze, ponekad, neke od tih algoritama.
06:02
And when they find them they pull them out
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Tu gde ih nađu oni ih izvuku
06:05
and they pin them to the wall like butterflies.
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i zakače na zid kao leptire u insektarijumu.
06:08
And they do what we've always done
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Oni rade ono što mi oduvek radimo
06:10
when confronted with huge amounts of data that we don't understand --
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kada smo suočeni sa velikom količinom podataka koje ne razumemo,
06:13
which is that they give them a name
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a to je da im daju imena
06:15
and a story.
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i priču.
06:17
So this is one that they found,
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Ovo je jedna koju su našli,
06:19
they called the Knife,
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i nazvali je "Nož",
06:23
the Carnival,
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"Karneval",
06:25
the Boston Shuffler,
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"Bostonski mešač",
06:29
Twilight.
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"Sumrak".
06:31
And the gag is
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Stvar je u tome da,
06:33
that, of course, these aren't just running through the market.
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naravno, oni nisu ograničeni samo na tržište.
06:36
You can find these kinds of things wherever you look,
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Možete ih naći gde god pogledate,
06:39
once you learn how to look for them.
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kada naučite da ih tražite.
06:41
You can find it here: this book about flies
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Možete ih naći ovde: u ovoj knjizi o muvama,
06:44
that you may have been looking at on Amazon.
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koju ste tražili na Amazonu.
06:46
You may have noticed it
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Možda ste primetili
06:48
when its price started at 1.7 million dollars.
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kada je njena cena bila 1,7 miliona dolara.
06:50
It's out of print -- still ...
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Knjiga nije više u štampi, ali...
06:52
(Laughter)
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(Smeh)
06:54
If you had bought it at 1.7, it would have been a bargain.
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Da ste je kupili po ceni od 1,7 miliona, to bi bilo skoro besplatno.
06:57
A few hours later, it had gone up
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Nekoliko sati kasnije, cena je porasla
06:59
to 23.6 million dollars,
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na 23,6 miliona dolara,
07:01
plus shipping and handling.
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plus troškovi slanja i obrade pošiljke.
07:03
And the question is:
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Pitanje je sledeće:
07:05
Nobody was buying or selling anything; what was happening?
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Niko nije ništa kupovao niti prodavao; šta se dešavalo?
07:07
And you see this behavior on Amazon
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Možete uočiti takve pojave na Amazonu
07:09
as surely as you see it on Wall Street.
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kao što ih možete uočiti na Volstritu.
07:11
And when you see this kind of behavior,
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Kada vidite ovakvo ponašanje,
07:13
what you see is the evidence
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to što vidite je dokaz
07:15
of algorithms in conflict,
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algoritamskog konflikta,
07:17
algorithms locked in loops with each other,
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algoritama koji su zapetljani jedan u drugi
07:19
without any human oversight,
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bez ljudskog nadzora,
07:21
without any adult supervision
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bez nadzora odrasle osobe,
07:24
to say, "Actually, 1.7 million is plenty."
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nekoga ko bi rekao, "1,7 miliona je mnogo."
07:27
(Laughter)
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(smeh)
07:30
And as with Amazon, so it is with Netflix.
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Sa Netfliksom je isto kao sa Amazonom.
07:33
And so Netflix has gone through
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Netfliks je prošao
07:35
several different algorithms over the years.
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kroz mnoge različite algoritme tokom godina.
07:37
They started with Cinematch, and they've tried a bunch of others --
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Počeli su sa Cinematch algoritmom i probali još mnoge druge.
07:40
there's Dinosaur Planet; there's Gravity.
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"Planetu dinosaurusa" i "Gravitaciju".
07:42
They're using Pragmatic Chaos now.
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Trenutno koriste "Pragmatični haos".
07:44
Pragmatic Chaos is, like all of Netflix algorithms,
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"Pragmatični haos" je sličan "Netfliks" algoritmu,
07:46
trying to do the same thing.
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pokušava da uradi istu stvar.
07:48
It's trying to get a grasp on you,
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Pokušava da vas razume,
07:50
on the firmware inside the human skull,
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kao operativni sistem u vašoj lobanji,
07:52
so that it can recommend what movie
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kako bi vam predložio koji biste
07:54
you might want to watch next --
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sledeći film mogli da pogledate
07:56
which is a very, very difficult problem.
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što je veoma, veoma težak problem.
07:59
But the difficulty of the problem
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Poteškoća kod ovog problema
08:01
and the fact that we don't really quite have it down,
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i činjenice da ga ne razumemo najbolje,
08:04
it doesn't take away
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ne umanjuje značaj
08:06
from the effects Pragmatic Chaos has.
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efekta "Pragmatičnog haosa".
08:08
Pragmatic Chaos, like all Netflix algorithms,
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"Pragmatični haos", kao i svi "Netfliks" algoritmi,
08:11
determines, in the end,
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određuje, na kraju,
08:13
60 percent
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60 procenata
08:15
of what movies end up being rented.
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svih filmova koji se iznajmljuju.
08:17
So one piece of code
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Tako da je jedan program
08:19
with one idea about you
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sa jednom idejom o Vama
08:22
is responsible for 60 percent of those movies.
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odgovoran za 60 procenata filmova koje pogledate.
08:25
But what if you could rate those movies
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Ali šta ako biste mogli oceniti te filmove
08:27
before they get made?
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pre nego li budu snimljeni?
08:29
Wouldn't that be handy?
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Da li bi to bilo korisno?
08:31
Well, a few data scientists from the U.K. are in Hollywood,
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Nekoliko informacionih naučnika iz Velike Britanije je u Holivudu,
08:34
and they have "story algorithms" --
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i imalu algoritme za scenarije --
08:36
a company called Epagogix.
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kompanija koja se zove Epagogix.
08:38
And you can run your script through there,
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Možete ubaciti svoj scenario kroz njihov program
08:41
and they can tell you, quantifiably,
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i on vam može reći, kvantitativno,
08:43
that that's a 30 million dollar movie
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da je to film koji će zaraditi 30 miliona dolara
08:45
or a 200 million dollar movie.
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ili 200 miliona dolara.
08:47
And the thing is, is that this isn't Google.
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Stvar je u tome da to nije Google.
08:49
This isn't information.
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To nije informacija.
08:51
These aren't financial stats; this is culture.
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To nisu finansijske statistike; to je kultura.
08:53
And what you see here,
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I ovo što vidite,
08:55
or what you don't really see normally,
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tj što normalno ne vidite,
08:57
is that these are the physics of culture.
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je fizika kulture.
09:01
And if these algorithms,
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I ako bi ovi algoritmi,
09:03
like the algorithms on Wall Street,
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kao oni na Volstritu,
09:05
just crashed one day and went awry,
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pali i nestali,
09:08
how would we know?
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kako ćemo znati,
09:10
What would it look like?
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kako će to izgledati?
09:12
And they're in your house. They're in your house.
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A oni su i u vašoj kući. Oni su u vašoj kući.
09:15
These are two algorithms competing for your living room.
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Ovo su dva konkurentna algoritma za vašu dnevnu sobu.
09:17
These are two different cleaning robots
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Ovo su dva različita robota za čišćenje
09:19
that have very different ideas about what clean means.
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koji imaju različite ideje šta znači čišćenje.
09:22
And you can see it
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To možete da vidite
09:24
if you slow it down and attach lights to them,
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ako ih usporite i zakačite svetlo na njih.
09:27
and they're sort of like secret architects in your bedroom.
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Oni su kao tajne arhitekte u vašoj spavaćoj sobi.
09:30
And the idea that architecture itself
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Ideja da je i sama arhitektura
09:33
is somehow subject to algorithmic optimization
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na neki način subjekt algoritamske optimizacije
09:35
is not far-fetched.
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nij nerealna.
09:37
It's super-real and it's happening around you.
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Veoma je stvarna i dešava se oko vas.
09:40
You feel it most
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Najviše je osetite
09:42
when you're in a sealed metal box,
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kada se nalazite u zatvorenoj metalnoj kutiji,
09:44
a new-style elevator;
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liftu nove generacije,
09:46
they're called destination-control elevators.
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koji se zovu lokaciono kontrolisani liftovi.
09:48
These are the ones where you have to press what floor you're going to go to
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To su oni kod kojih treba da odaberete na koji sprat idete
09:51
before you get in the elevator.
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pre nego uđete u lift.
09:53
And it uses what's called a bin-packing algorithm.
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On koristi tzv algoritam pakovanja kutije.
09:55
So none of this mishegas
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Znači ništa od ove ludosti
09:57
of letting everybody go into whatever car they want.
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da puštamo ljude da ulaze u lift koji žele.
09:59
Everybody who wants to go to the 10th floor goes into car two,
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Svako ko želi da ode na deseti sprat ulazi u lift broj dva,
10:01
and everybody who wants to go to the third floor goes into car five.
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a svako ko hoće na treći sprat ulazi u lift broj pet.
10:04
And the problem with that
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Problem sa ovim je
10:06
is that people freak out.
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što se ljudi pogube.
10:08
People panic.
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Ljudi počnu da paniče.
10:10
And you see why. You see why.
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Vidite zašto. Vidite zašto.
10:12
It's because the elevator
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Zato što liftu
10:14
is missing some important instrumentation, like the buttons.
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nedostaju neki važni instrumenti, poput dugmića.
10:17
(Laughter)
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(smeh)
10:19
Like the things that people use.
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I druge stvari koje ljudi vole da koriste.
10:21
All it has
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Sve što lift ima
10:23
is just the number that moves up or down
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je broj koji ide gore-dole
10:26
and that red button that says, "Stop."
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i crveno dugme koje kaže "Stop."
10:29
And this is what we're designing for.
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To je ono što dizajniramo.
10:32
We're designing
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Dizajniramo
10:34
for this machine dialect.
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za taj mašnski dijalekat.
10:36
And how far can you take that? How far can you take it?
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Koliko daleko može to da ode? Dokle možemo to da odvedemo?
10:39
You can take it really, really far.
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Možemo ga odvesti jako, jako daleko.
10:41
So let me take it back to Wall Street.
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Zato ću se vratiti nazad na Volstrit.
10:45
Because the algorithms of Wall Street
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Jer algoritmi na Volstritu
10:47
are dependent on one quality above all else,
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zavise od jedne stvari pre svega,
10:50
which is speed.
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a to je brzina.
10:52
And they operate on milliseconds and microseconds.
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Oni operišu brzinama u milisekundama i mikrosekundama.
10:55
And just to give you a sense of what microseconds are,
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Da biste shvatili šta je mikrosekunda --
10:57
it takes you 500,000 microseconds
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potrebno vam je 500 000 mikrosekundi
10:59
just to click a mouse.
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da biste kliknuli mišem.
11:01
But if you're a Wall Street algorithm
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Ali ako ste algoritam na Volstritu
11:03
and you're five microseconds behind,
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i kasnite pet mikrosekundi,
11:05
you're a loser.
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vi ste gubitnik.
11:07
So if you were an algorithm,
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Tako da ako ste algoritam,
11:09
you'd look for an architect like the one that I met in Frankfurt
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tražićete arhitektu poput onoga kojega sam upoznao u Frankfurtu
11:12
who was hollowing out a skyscraper --
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koji je ispraznio ceo neboder --
11:14
throwing out all the furniture, all the infrastructure for human use,
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izbacio sav nameštaj i infrastukturu namenjenu ljudskoj upotrebi,
11:17
and just running steel on the floors
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i postavio čelik na podove
11:20
to get ready for the stacks of servers to go in --
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kako bi se gomile servera mogle useliti unutra --
11:23
all so an algorithm
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sve kako bi algoritam
11:25
could get close to the Internet.
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bio blizu Internetu.
11:28
And you think of the Internet as this kind of distributed system.
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Vi smatrate da je Internet distribuiran sistem.
11:31
And of course, it is, but it's distributed from places.
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On to i jeste, ali se distribuira sa različitih mesta.
11:34
In New York, this is where it's distributed from:
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U Njujorku se distribuira iz
11:36
the Carrier Hotel
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hotela "Carrier"
11:38
located on Hudson Street.
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koji se nalazi u ulici Hadson.
11:40
And this is really where the wires come right up into the city.
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To je mesto odakle se kablovi šire po celom gradu.
11:43
And the reality is that the further away you are from that,
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Istina je, da što ste dalje od tog mesta,
11:47
you're a few microseconds behind every time.
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kasnićete par mikrosekundi.
11:49
These guys down on Wall Street,
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Momci sa Volstrita,
11:51
Marco Polo and Cherokee Nation,
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"Marko Polo" i "Čeroki Nejšn",
11:53
they're eight microseconds
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su osam mikrosekundi u zaostatku
11:55
behind all these guys
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za ovim algoritmima
11:57
going into the empty buildings being hollowed out
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koji ulaze u prazne zgrade
12:01
up around the Carrier Hotel.
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oko hotela "Carrier".
12:03
And that's going to keep happening.
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I to će nastaviti da se dešava.
12:06
We're going to keep hollowing them out,
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Nastavićemo da ih ispražnjavamo,
12:08
because you, inch for inch
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jer vi, centimetar po centimetar,
12:11
and pound for pound and dollar for dollar,
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funtu po funtu, dolar po dolar,
12:14
none of you could squeeze revenue out of that space
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niko od vas ne bi mogao izvući prihod iz tog prostora
12:17
like the Boston Shuffler could.
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kao što može "Bostonski mešač".
12:20
But if you zoom out,
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Ali ako se udaljite od slike,
12:22
if you zoom out,
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i pogledate krupni plan,
12:24
you would see an 825-mile trench
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videćete kanal dug 1328 km
12:28
between New York City and Chicago
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između Njujorka i Čikaga,
12:30
that's been built over the last few years
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koji je u toku zadnjih nekoliko godina
12:32
by a company called Spread Networks.
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izgradila "Spread Networks" kompanija.
12:35
This is a fiber optic cable
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Ovo je optički kabel
12:37
that was laid between those two cities
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koji leži između dva grada
12:39
to just be able to traffic one signal
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i može da provodi samo jedan signal
12:42
37 times faster than you can click a mouse --
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37 puta brže no što vi možete da kliknete mišem,
12:45
just for these algorithms,
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izgrađen je samo za algoritme,
12:48
just for the Carnival and the Knife.
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samo za "Karneval" i "Nož".
12:51
And when you think about this,
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Kada razmislite o tome,
12:53
that we're running through the United States
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da trčimo kroz SAD
12:55
with dynamite and rock saws
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sa dinamitom i razbijačima za kamen
12:58
so that an algorithm can close the deal
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kako bi algoritmi zaključili transakciju
13:00
three microseconds faster,
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tri mikrosekunde brže,
13:03
all for a communications framework
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sve to radi komunikacionog okvira
13:05
that no human will ever know,
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koji nijedan čovek neće spoznati,
13:09
that's a kind of manifest destiny;
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to je neka vrsta očigledne sudbine
13:12
and we'll always look for a new frontier.
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koja će uvek pomerati nove granice.
13:15
Unfortunately, we have our work cut out for us.
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Nažalost, predstoji nam vrlo ambiciozan posao.
13:18
This is just theoretical.
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Ovo je samo teorijski.
13:20
This is some mathematicians at MIT.
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To je samo matematika sa MIT-a.
13:22
And the truth is I don't really understand
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Istina je da ni ja, stvarno, ne razumem
13:24
a lot of what they're talking about.
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mnogo toga o čemu pričaju.
13:26
It involves light cones and quantum entanglement,
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Radi se o svetlosnoj kupoli i kvantnoj upletenosti,
13:29
and I don't really understand any of that.
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a ja to stvarno ne razumem.
13:31
But I can read this map,
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Ali mogu da pročitam ovu mapu.
13:33
and what this map says
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A ono što nam ova mapa kaže
13:35
is that, if you're trying to make money on the markets where the red dots are,
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je da ako pokušavate da zaradite novac na tržištu gde se nalaze crvene tačke,
13:38
that's where people are, where the cities are,
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tamo gde su ljudi, gde su gradovi,
13:40
you're going to have to put the servers where the blue dots are
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moraćete servere staviti tamo gde su plave tačke
13:43
to do that most effectively.
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da bi ste radili efikasno.
13:45
And the thing that you might have noticed about those blue dots
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Možda ste primetili da se mnoge plave tačke
13:48
is that a lot of them are in the middle of the ocean.
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nalaze na sredini okeana.
13:51
So that's what we'll do: we'll build bubbles or something,
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Ono što treba da uradimo je
13:54
or platforms.
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da izgradimo balone ili platforme.
13:56
We'll actually part the water
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Da bukvalno razdvojimo more
13:58
to pull money out of the air,
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i izvlačimo novac iz vazduha,
14:00
because it's a bright future
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jer je svetla budućnost pred vama
14:02
if you're an algorithm.
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ako ste algoritam.
14:04
(Laughter)
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(Smeh)
14:06
And it's not the money that's so interesting actually.
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I nije novac taj koji je zapravo toliko interesantan.
14:09
It's what the money motivates,
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Već šta novac motiviše.
14:11
that we're actually terraforming
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Mi zapravo transformišemo
14:13
the Earth itself
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samu Zemljinu površinu
14:15
with this kind of algorithmic efficiency.
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sa ovakvom vrstom algoritamske uspešnosti.
14:17
And in that light,
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I u tom svetlu
14:19
you go back
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vi se vraćate
14:21
and you look at Michael Najjar's photographs,
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i gledate fotografije Mihaela Najara
14:23
and you realize that they're not metaphor, they're prophecy.
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i uviđate da one nisu metafore, one su proročanstva.
14:26
They're prophecy
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One su proročanstvo
14:28
for the kind of seismic, terrestrial effects
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seizmičkih, zemaljskih efekata
14:32
of the math that we're making.
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koje pravi naša matematika.
14:34
And the landscape was always made
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Krajolik je uvek bio rezultat
14:37
by this sort of weird, uneasy collaboration
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čudne, teške saradnje
14:40
between nature and man.
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između prirode i čoveka.
14:43
But now there's this third co-evolutionary force: algorithms --
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Ali sada je tu ta treća koevoluciona sila - algoritam,
14:46
the Boston Shuffler, the Carnival.
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"Bostonski mešač", "Karneval".
14:49
And we will have to understand those as nature,
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I moraćemo ih razumeti kao prirodu.
14:52
and in a way, they are.
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Jer na neki način oni to i jesu.
14:54
Thank you.
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Hvala.
14:56
(Applause)
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(Aplauz)
ABOUT THE SPEAKER
Kevin Slavin - Algoworld expertKevin Slavin navigates in the algoworld, the expanding space in our lives that’s determined and run by algorithms.
Why you should listen
Are you addicted to the dead-simple numbers game Drop 7 or Facebook’s Parking Wars? Blame Kevin Slavin and the game development company he co-founded in 2005, Area/Code, which makes clever game entertainments that enter the fabric of reality.
All this fun is powered by algorithms -- as, increasingly, is our daily life. From the Google algorithms to the algos that give you “recommendations” online to those that automatically play the stock markets (and sometimes crash them): we may not realize it, but we live in the algoworld.
He says: "The quickest way to find out what the boundaries of reality are is to figure where they break."
Kevin Slavin | Speaker | TED.com