TEDGlobal 2011
Kevin Slavin: How algorithms shape our world
Kevin Slavin: Com els algoritmes donen forma al nostre món
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Segons Kevin Slavin, vivim en un món disenyat per ―i cada vegada més, controlat per― algoritmes. En aquesta apassionant xerrada de TEDGlobal, explica com aquests complicats programes d'ordinador determinen tàctiques d'espionatge, preus de mercat, guions de cinema, i arquitectura. I avisa: estem escrivint codi que no podem entendre, amb implicacions que no podem controlar.
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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Aquesta fotografia és
00:17
by the artist Michael Najjar,
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de l'artista Michael Najjar,
00:19
and it's real,
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i en cert sentit és real,
00:21
in the sense that he went there to Argentina
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doncs l'artista va anar a Argentina
00:23
to take the photo.
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a fer la foto.
00:25
But it's also a fiction. There's a lot of work that went into it after that.
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Però també és ficció. Hi ha un munt de feina al darrere.
00:28
And what he's done
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El que l'artista ha fet,
00:30
is he's actually reshaped, digitally,
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en realitat, és modificar, digitalment,
00:32
all of the contours of the mountains
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tots els contorns de les muntanyes
00:34
to follow the vicissitudes of the Dow Jones index.
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per a fer-les encaixar amb les fluctuacions de l'índex Dow Jones
00:37
So what you see,
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Així que, això que veieu,
00:39
that precipice, that high precipice with the valley,
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aquest gran precipici al costat de la vall,
00:41
is the 2008 financial crisis.
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és la crisi financera del 2008.
00:43
The photo was made
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La foto es va fer
00:45
when we were deep in the valley over there.
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quan érem a les profunditats de la vall, allà.
00:47
I don't know where we are now.
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No sé on som ara.
00:49
This is the Hang Seng index
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Això és l'índex Hang Seng
00:51
for Hong Kong.
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de Hong Kong.
00:53
And similar topography.
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Té una topografia similar,
00:55
I wonder why.
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i em pregunto perquè.
00:57
And this is art. This is metaphor.
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I això és art, és metàfora.
01:00
But I think the point is
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Però el més important, penso jo,
01:02
that this is metaphor with teeth,
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és que és una metàfora amb força.
01:04
and it's with those teeth that I want to propose today
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I és amb aquesta força que vull proposar, avui,
01:07
that we rethink a little bit
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que pensem una mica
01:09
about the role of contemporary math --
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en el paper de les matemàtiques modernes --
01:12
not just financial math, but math in general.
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no només matemàtiques financeres, sinó matemàtiques en general
01:15
That its transition
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En la seva transició
01:17
from being something that we extract and derive from the world
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de quelcom que extraiem i derivem del món
01:20
to something that actually starts to shape it --
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cap a quelcom que, en realitat, comença a donar-li forma --
01:23
the world around us and the world inside us.
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tant al món que ens envolta com al nostre món interior.
01:26
And it's specifically algorithms,
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En particular, els algoritmes
01:28
which are basically the math
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són les matemàtiques
01:30
that computers use to decide stuff.
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que els ordinadors usen per prendre decisions.
01:33
They acquire the sensibility of truth
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Adquireixen sensibilitat a la veritat
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because they repeat over and over again,
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a base de repetir una vegada rere una altra.
01:37
and they ossify and calcify,
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I es van ossificant i calcificant
01:40
and they become real.
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i es transformen en realitat.
01:42
And I was thinking about this, of all places,
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Estava pensant en això, ara fa dos anys
01:45
on a transatlantic flight a couple of years ago,
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en un vol transatlàntic
01:48
because I happened to be seated
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perquè resulta que seia
01:50
next to a Hungarian physicist about my age
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al costat d'un físic hongarès de la meva edat
01:52
and we were talking
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i estàvem xerrant
01:54
about what life was like during the Cold War
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de com era la vida durant la guerra freda
01:56
for physicists in Hungary.
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pels físics hongaresos
01:58
And I said, "So what were you doing?"
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I li vaig dir, "I doncs, què fèieu?"
02:00
And he said, "Well we were mostly breaking stealth."
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i ell va dir, "Bé, bàsicament, trencàvem l'Stealth."
02:02
And I said, "That's a good job. That's interesting.
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I jo, "És una bona tasca. Interessant.
02:04
How does that work?"
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Com funciona?"
02:06
And to understand that,
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Per entendre això,
02:08
you have to understand a little bit about how stealth works.
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cal que entengueu una mica com funciona l'Stealth.
02:11
And so -- this is an over-simplification --
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Això és una simplificació,
02:14
but basically, it's not like
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però bé, bàsicament,
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you can just pass a radar signal
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no pots simplement travessar una senyal de radar
02:18
right through 156 tons of steel in the sky.
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amb 156 tones de metall al cel.
02:21
It's not just going to disappear.
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No pot simplement desaparèixer.
02:24
But if you can take this big, massive thing,
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Però si poguessis agafar aquesta gran cosa,
02:27
and you could turn it into
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i la poguessis transformar en
02:30
a million little things --
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un milió de petites coses --
02:32
something like a flock of birds --
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com un esbart d'ocells --
02:34
well then the radar that's looking for that
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aleshores el radar que està buscant
02:36
has to be able to see
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hauria de ser capaç de veure
02:38
every flock of birds in the sky.
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tots els esbarts d'ocells del cel.
02:40
And if you're a radar, that's a really bad job.
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I, si ets un radar, no és massa bona idea.
02:44
And he said, "Yeah." He said, "But that's if you're a radar.
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I va dir: "Si". Va dir: "Això si ets un radar.
02:47
So we didn't use a radar;
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De manera que no vam fer servir un radar;
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we built a black box that was looking for electrical signals,
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vam construir una caixa negra que buscava senyals elèctriques,
02:52
electronic communication.
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comunicacions electròniques.
02:55
And whenever we saw a flock of birds that had electronic communication,
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I quan veiem un esbart d'ocells que tenia comunicacions electròniques,
02:58
we thought, 'Probably has something to do with the Americans.'"
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sabíem que segurament tenia a veure amb els americans."
03:01
And I said, "Yeah.
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I jo vaig dir, "Sí,
03:03
That's good.
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molt bé.
03:05
So you've effectively negated
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Per tant, acabes de destrossar
03:07
60 years of aeronautic research.
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60 anys de recerca aeronàutica
03:09
What's your act two?
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i després, què?
03:11
What do you do when you grow up?"
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Què vas fer quan vas créixer?
03:13
And he said,
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I va dir,
03:15
"Well, financial services."
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"Serveis financers"
03:17
And I said, "Oh."
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I jo vaig dir, "Oh."
03:19
Because those had been in the news lately.
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Perquè feia poc havia sortit a les notícies.
03:22
And I said, "How does that work?"
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I li vaig dir: "Com funciona?"
03:24
And he said, "Well there's 2,000 physicists on Wall Street now,
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I ell em va dir, "Bé, ara mateix hi ha uns 2000 físics a Wall Street,
03:26
and I'm one of them."
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i jo sóc un d'ells."
03:28
And I said, "What's the black box for Wall Street?"
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I jo vaig dir: "I com és la caixa negra a Wall Street?"
03:31
And he said, "It's funny you ask that,
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I va dir: "És graciós que em preguntis això,
03:33
because it's actually called black box trading.
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perquè, en realitat, es parla de comerç de caixa negra,
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And it's also sometimes called algo trading,
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o també comerç algo,
03:38
algorithmic trading."
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comerç algorítmic."
03:41
And algorithmic trading evolved in part
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I el comerç algorítmic ha evolucionat, en part,
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because institutional traders have the same problems
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perquè els comerciants institucionals tenen els mateixos problemes
03:47
that the United States Air Force had,
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que les Forces Armades dels Estats Units tenien,
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which is that they're moving these positions --
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és a dir, que estan movent aquestes accions --
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whether it's Proctor & Gamble or Accenture, whatever --
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ja sigui "Proctor & Gamble" o "Accenture", és igual --
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they're moving a million shares of something
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estan movent un milió d'accions d'alguna cosa
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through the market.
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a través dels mercats.
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And if they do that all at once,
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I si les mouen totes de cop,
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it's like playing poker and going all in right away.
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passa com al pòquer: apostar-ho tot d'entrada.
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You just tip your hand.
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És com ensenyar les teves cartes.
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And so they have to find a way --
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Per tant necessiten una manera --
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and they use algorithms to do this --
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és a dir, algoritmes --
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to break up that big thing
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per dividir aquell gran moviment
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into a million little transactions.
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en un milió de petites transaccions.
04:13
And the magic and the horror of that
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I la màgia, o l'horror, de la qüestió
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is that the same math
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es que es poden fer servir
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that you use to break up the big thing
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les mateixes matemàtiques tant per trencar
04:19
into a million little things
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la gran cosa en un milió de petites coses
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can be used to find a million little things
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com per buscar un milió de petites coses
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and sew them back together
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i recomposar una gran cosa i,
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and figure out what's actually happening in the market.
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d'aquesta manera, saber que està passant realment als mercats.
04:27
So if you need to have some image
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Així que si us voleu fer una idea
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of what's happening in the stock market right now,
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del que passa a la borsa ara mateix,
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what you can picture is a bunch of algorithms
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podeu pensar en una colla d'algoritmes
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that are basically programmed to hide,
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pensats bàsicament per amagar,
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and a bunch of algorithms that are programmed to go find them and act.
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i una altra colla d'algoritmes pensats per trobar i actuar.
04:40
And all of that's great, and it's fine.
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I tot això està molt bé
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And that's 70 percent
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i representa el 70 %
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of the United States stock market,
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de la borsa dels Estats Units
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70 percent of the operating system
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el 70 % del sistema operatiu
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formerly known as your pension,
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altrament dit la teva pensió,
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your mortgage.
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la teva hipoteca,
04:55
And what could go wrong?
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Què podria fallar?
04:57
What could go wrong
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Podria passar tal com
04:59
is that a year ago,
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fa un any, quan
05:01
nine percent of the entire market just disappears in five minutes,
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el 9% del total del mercat simplement va desaparèixer durant 5 minuts,
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and they called it the Flash Crash of 2:45.
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i n'hi van dir el flash crash de les 2:45.
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All of a sudden, nine percent just goes away,
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Tot de cop, el 9% simplement desapareix,
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and nobody to this day
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i fins ara, ningú
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can even agree on what happened
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ha pogut aclarir que va passar,
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because nobody ordered it, nobody asked for it.
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perquè ningú ho va manar, ningú ho va demanar.
05:17
Nobody had any control over what was actually happening.
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De fet, ningú tenia cap control sobre el que realment succeía.
05:20
All they had
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Tot el que tenien era, simplement
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was just a monitor in front of them
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una pantalla davant d'ells
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that had the numbers on it
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amb un munt de números,
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and just a red button
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i un botó vermell
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that said, "Stop."
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que posava "Stop."
05:30
And that's the thing,
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El que està passant,
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is that we're writing things,
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es que escrivim coses,
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we're writing these things that we can no longer read.
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coses que ja no podem llegir
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And we've rendered something
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Hem generat quelcom
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illegible,
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il·legible
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and we've lost the sense
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I ja no sabem
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of what's actually happening
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realment què està passant
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in this world that we've made.
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en aquest món que hem construït.
05:48
And we're starting to make our way.
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I això és el començament.
05:50
There's a company in Boston called Nanex,
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Hi ha una companyia a Boston, Nanex,
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and they use math and magic
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utilitza matemàtiques i màgia
05:55
and I don't know what,
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no sé exactament com,
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and they reach into all the market data
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però agafen dades dels mercats
05:59
and they find, actually sometimes, some of these algorithms.
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i troben, de vegades, alguns d'aquests algoritmes.
06:02
And when they find them they pull them out
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Quan els troben, els extreuen
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and they pin them to the wall like butterflies.
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i els claven a la paret com papallones.
06:08
And they do what we've always done
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I aleshores fan allò que tots hem fet
06:10
when confronted with huge amounts of data that we don't understand --
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quan ens hem trobat davant de grans quantitats de dades que no enteniem--
06:13
which is that they give them a name
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simplement, els hi posen un nom
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and a story.
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i una història.
06:17
So this is one that they found,
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A aquest que van trobar,
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they called the Knife,
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li van posar "Knife",
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the Carnival,
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el "Carnival".
06:25
the Boston Shuffler,
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el "Boston Shuffler"
06:29
Twilight.
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"Twilight".
06:31
And the gag is
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El més graciós de tot és
06:33
that, of course, these aren't just running through the market.
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que, òbviament, aquests algoritmes no funcionen només als mercats.
06:36
You can find these kinds of things wherever you look,
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Aquest tipus de coses es poden trobar arreu,
06:39
once you learn how to look for them.
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un cop se sap com buscar-les.
06:41
You can find it here: this book about flies
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Per exemple, aquí: aquest llibre sobre mosques
06:44
that you may have been looking at on Amazon.
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que potser us heu estat mirant per Amazon.
06:46
You may have noticed it
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Potser el vàreu veure
06:48
when its price started at 1.7 million dollars.
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quan costava 1.700.000 dòlars
06:50
It's out of print -- still ...
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No s'imprimeix -- encara...
06:52
(Laughter)
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(Rialles)
06:54
If you had bought it at 1.7, it would have been a bargain.
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Si l'haguéssiu comprat a 1.700.000 hauria sigut una ganga,
06:57
A few hours later, it had gone up
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doncs al cap d'unes hores havia pujat
06:59
to 23.6 million dollars,
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fins als 23.600.000 dòlars.
07:01
plus shipping and handling.
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costs d'enviament apart.
07:03
And the question is:
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La pregunta és:
07:05
Nobody was buying or selling anything; what was happening?
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Si ningú estava comprant ni venent res; què estava passant?
07:07
And you see this behavior on Amazon
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Aquests tipus de comportament s'observen tant a Amazon
07:09
as surely as you see it on Wall Street.
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com a Wall Street.
07:11
And when you see this kind of behavior,
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I el que aquests comportaments són
07:13
what you see is the evidence
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una conseqüència
07:15
of algorithms in conflict,
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d'algoritmes en conflicte,
07:17
algorithms locked in loops with each other,
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algoritmes bloquejats en bucles,
07:19
without any human oversight,
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sense cap supervisió humana,
07:21
without any adult supervision
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sense la supervisió d'un adult
07:24
to say, "Actually, 1.7 million is plenty."
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que pugui dir: "Home, 1.700.000 dòlars ja és bastant."
07:27
(Laughter)
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(Rialles)
07:30
And as with Amazon, so it is with Netflix.
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Passa el mateix amb Netflix.
07:33
And so Netflix has gone through
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Netflix ha fet servir
07:35
several different algorithms over the years.
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diferents algoritmes al llarg dels anys:
07:37
They started with Cinematch, and they've tried a bunch of others --
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van començar amb Cinematch, i després n'han anat provant d'altres.
07:40
there's Dinosaur Planet; there's Gravity.
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com "Dinosaur Planet". "Gravity".
07:42
They're using Pragmatic Chaos now.
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i, actualment, "Pragmatic Chaos".
07:44
Pragmatic Chaos is, like all of Netflix algorithms,
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El que aquest algoritme intenta, igual tots els altres,
07:46
trying to do the same thing.
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es el següent:
07:48
It's trying to get a grasp on you,
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Tracta d'entendre't a tu,
07:50
on the firmware inside the human skull,
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el que hi ha a dins teu,
07:52
so that it can recommend what movie
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per a ser capaç de recomanar-te
07:54
you might want to watch next --
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quina pel·lícula t'agradaria veure --
07:56
which is a very, very difficult problem.
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i això és una tasca molt, molt difícil.
07:59
But the difficulty of the problem
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Però que la tasca sigui difícil,
08:01
and the fact that we don't really quite have it down,
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i el fet que encara no sabem realment com resoldre-la
08:04
it doesn't take away
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no elimina
08:06
from the effects Pragmatic Chaos has.
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les conseqüències d'usar "Pragmatic Chaos".
08:08
Pragmatic Chaos, like all Netflix algorithms,
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Al cap i a la fi, aquest algoritme, i tots els altres
08:11
determines, in the end,
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que Netflix ha usat, determina
08:13
60 percent
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el 60%
08:15
of what movies end up being rented.
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de les pel·lícules que els clients acaben llogant.
08:17
So one piece of code
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És a dir, que un tros de codi,
08:19
with one idea about you
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que conté una sola idea sobre tu,
08:22
is responsible for 60 percent of those movies.
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és el responsable del 60% de les vendes.
08:25
But what if you could rate those movies
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Ara bé, què passaria si poguéssim puntuar aquestes pel·lícules
08:27
before they get made?
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abans de que existissin?
08:29
Wouldn't that be handy?
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Oi que seria molt pràctic?
08:31
Well, a few data scientists from the U.K. are in Hollywood,
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Bé, alguns científics del Regne Unit, experts en dades, estan a Hollywood,
08:34
and they have "story algorithms" --
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desenvolupant algoritmes per guions --
08:36
a company called Epagogix.
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Hi ha una empresa anomenada Epagogix
08:38
And you can run your script through there,
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que, a partir del teu guió
08:41
and they can tell you, quantifiably,
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et poden dir, quantitativament,
08:43
that that's a 30 million dollar movie
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si serà una pel·lícula de 30 milions de dòlars
08:45
or a 200 million dollar movie.
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o una de 200 milions.
08:47
And the thing is, is that this isn't Google.
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I això no és Google,
08:49
This isn't information.
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no és informació,
08:51
These aren't financial stats; this is culture.
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ni estadística financera: això és cultura.
08:53
And what you see here,
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I el que heu vist avui aquí,
08:55
or what you don't really see normally,
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o el que normalment no veieu
08:57
is that these are the physics of culture.
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és la física de la cultura.
09:01
And if these algorithms,
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I si aquests algoritmes,
09:03
like the algorithms on Wall Street,
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igual que els de Wall Street,
09:05
just crashed one day and went awry,
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produissin un crash,
09:08
how would we know?
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com ho sabríem?
09:10
What would it look like?
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quina pinta faria?
09:12
And they're in your house. They're in your house.
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També són a casa teva.
09:15
These are two algorithms competing for your living room.
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Això són dos algoritmes competint pel teu saló
09:17
These are two different cleaning robots
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Són dos robots netejadors diferents
09:19
that have very different ideas about what clean means.
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i tenen idees força diferents sobre que vol dir netejar
09:22
And you can see it
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Això es pot veure
09:24
if you slow it down and attach lights to them,
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posant càmera lenta i engantxant-los unes llums.
09:27
and they're sort of like secret architects in your bedroom.
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Són com una mena d'arquitectes secrets a la teva habitació.
09:30
And the idea that architecture itself
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I la idea que la pròpia arquitectura
09:33
is somehow subject to algorithmic optimization
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està subjecte a l'optimització algorítmica
09:35
is not far-fetched.
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no és gens descabellada.
09:37
It's super-real and it's happening around you.
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És ben real, i està passant al teu voltant.
09:40
You feel it most
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Ho notareu, per exemple,
09:42
when you're in a sealed metal box,
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si esteu en una d'aquestes caixes metàl·liques hermètiques
09:44
a new-style elevator;
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un d'aquests ascensors d'última generació
09:46
they're called destination-control elevators.
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ascensor amb control de destinació, se'n diuen.
09:48
These are the ones where you have to press what floor you're going to go to
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Són aquests on has de prémer el botó del pis on vas
09:51
before you get in the elevator.
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abans d'entrar a l'ascensor.
09:53
And it uses what's called a bin-packing algorithm.
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Utilitzen un algoritme d'empaquetament per grups.
09:55
So none of this mishegas
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És a dir, que res de la bogeria
09:57
of letting everybody go into whatever car they want.
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de deixar que cadascú es fiqui a l'ascensor que vol:
09:59
Everybody who wants to go to the 10th floor goes into car two,
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Tothom qui va al desè pis, ha d'agafar el segon ascensor,
10:01
and everybody who wants to go to the third floor goes into car five.
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i tothom qui va al tercer pis ha d'agafar el cinquè ascensor.
10:04
And the problem with that
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El problema, però,
10:06
is that people freak out.
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és que la gent s'espanta.
10:08
People panic.
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S'esgarrifa.
10:10
And you see why. You see why.
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I no és difícil veure perquè passa això.
10:12
It's because the elevator
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Passa perquè a l'ascensor
10:14
is missing some important instrumentation, like the buttons.
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li falten certs elements bàsics, com els botons.
10:17
(Laughter)
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(rialles)
10:19
Like the things that people use.
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Coses que la gent fa servir.
10:21
All it has
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Tot el que té
10:23
is just the number that moves up or down
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és l'indicador del pis
10:26
and that red button that says, "Stop."
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i el boto vermell que diu: "STOP".
10:29
And this is what we're designing for.
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I això és el que estem creant.
10:32
We're designing
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Estem creant
10:34
for this machine dialect.
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aquesta comunicació amb les màquines
10:36
And how far can you take that? How far can you take it?
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I fins on podem arribar, estirant aquest concepte?
10:39
You can take it really, really far.
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Doncs bastant, bastant lluny
10:41
So let me take it back to Wall Street.
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Deixeu-me que torni a Wall Street.
10:45
Because the algorithms of Wall Street
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Els algoritmes de Wall Street
10:47
are dependent on one quality above all else,
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depenent, per sobre de tot, d'una característica:
10:50
which is speed.
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la velocitat.
10:52
And they operate on milliseconds and microseconds.
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Operen en milisegons i microsegons
10:55
And just to give you a sense of what microseconds are,
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Per que us en feu una idea,
10:57
it takes you 500,000 microseconds
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es triguen uns 500.000 microsegons
10:59
just to click a mouse.
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a fer clic amb el ratolí.
11:01
But if you're a Wall Street algorithm
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Però si ets un algoritme de Wall Street
11:03
and you're five microseconds behind,
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i vas 5 microsegons enrere
11:05
you're a loser.
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estàs perdut.
11:07
So if you were an algorithm,
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Per tant, si fossis un algoritme
11:09
you'd look for an architect like the one that I met in Frankfurt
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buscaries un arquitecte com el que jo vaig conèixer a Frankfurt
11:12
who was hollowing out a skyscraper --
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que estava buidant un gratacels --
11:14
throwing out all the furniture, all the infrastructure for human use,
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llençant tots els mobles i tot allò que les persones usen,
11:17
and just running steel on the floors
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i posant acer al terra
11:20
to get ready for the stacks of servers to go in --
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per a poder posar-hi piles de servidors --
11:23
all so an algorithm
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tot per tal que un algoritme
11:25
could get close to the Internet.
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pogués estar més a prop d'Internet.
11:28
And you think of the Internet as this kind of distributed system.
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Potser penseu que Internet es un sistema distribuït.
11:31
And of course, it is, but it's distributed from places.
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És distribuït, però distribuït des de certs llocs.
11:34
In New York, this is where it's distributed from:
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A Nova York, per exemple, es distribueix des d'aquí:
11:36
the Carrier Hotel
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l'Hotel Carrier
11:38
located on Hudson Street.
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al carrer Hudson.
11:40
And this is really where the wires come right up into the city.
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Aquí és de on realment surten els cables cap a la ciutat
11:43
And the reality is that the further away you are from that,
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I el que passa és que si estàs més lluny d'aquí,
11:47
you're a few microseconds behind every time.
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estàs uns microsegons enrere.
11:49
These guys down on Wall Street,
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I aquesta gent de Wall Street,
11:51
Marco Polo and Cherokee Nation,
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Marco Polo i Cherokee Nation,
11:53
they're eight microseconds
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van 8 microsegons endarrere
11:55
behind all these guys
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respecte tota aquesta gent
11:57
going into the empty buildings being hollowed out
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que van als edificis que es buiden
12:01
up around the Carrier Hotel.
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al voltant de l'hotel Carrier.
12:03
And that's going to keep happening.
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I això seguirà passant.
12:06
We're going to keep hollowing them out,
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Seguirem buidant edificis,
12:08
because you, inch for inch
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ja que, centímetre a centímetre,
12:11
and pound for pound and dollar for dollar,
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lliura a lliura i dòlar a dòlar
12:14
none of you could squeeze revenue out of that space
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cap de nosaltres podria treure més profit d'aquest espai
12:17
like the Boston Shuffler could.
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que el Boston Shuffler.
12:20
But if you zoom out,
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Però si ens allunyem,
12:22
if you zoom out,
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si ens allunyem,
12:24
you would see an 825-mile trench
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veiem una rasa de 1300 quilòmetres de llargada
12:28
between New York City and Chicago
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entre Nova York i Chicago
12:30
that's been built over the last few years
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que ha estat construïda darrerament
12:32
by a company called Spread Networks.
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per una empresa anomenada Spread Networks.
12:35
This is a fiber optic cable
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Això és un cable de fibra òptica
12:37
that was laid between those two cities
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estès entre aquestes dues ciutats.
12:39
to just be able to traffic one signal
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només per transmetre un senyal
12:42
37 times faster than you can click a mouse --
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37 vegades més ràpid que el clic d'un ratolí,
12:45
just for these algorithms,
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només per aquests algoritmes:
12:48
just for the Carnival and the Knife.
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el Carnival i el Knife.
12:51
And when you think about this,
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I quan pensem això,
12:53
that we're running through the United States
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que estem foradant els Estats Units
12:55
with dynamite and rock saws
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amb dinamita i serres de roca
12:58
so that an algorithm can close the deal
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per a que un algoritme pugui tancar un contracte
13:00
three microseconds faster,
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tres microsegons més ràpid,
13:03
all for a communications framework
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tot en un marc de comunicacions
13:05
that no human will ever know,
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que cap humà arribarà a conèixer,
13:09
that's a kind of manifest destiny;
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és una mena de destí manifest
13:12
and we'll always look for a new frontier.
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que sempre cercarà una frontera nova.
13:15
Unfortunately, we have our work cut out for us.
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Però encara tenim molta feina a fer.
13:18
This is just theoretical.
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Tot això es teoria
13:20
This is some mathematicians at MIT.
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d'uns matemàtics del MIT.
13:22
And the truth is I don't really understand
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I, la veritat, és que no entenc
13:24
a lot of what they're talking about.
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gaire del que parlen.
13:26
It involves light cones and quantum entanglement,
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Es tracta de cons lluminosos y connexions quàntiques.
13:29
and I don't really understand any of that.
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i el cert és que no comprenc res d'això.
13:31
But I can read this map,
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Això sí, puc llegir aquest mapa.
13:33
and what this map says
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que diu que
13:35
is that, if you're trying to make money on the markets where the red dots are,
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si intentem guanyar diners als mercats a on es troben els punts vermells,
13:38
that's where people are, where the cities are,
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és a dir, a on es troba la gent, a on són les ciutats,
13:40
you're going to have to put the servers where the blue dots are
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haurem de posar els servidors a on estan els punts blaus
13:43
to do that most effectively.
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per tal d'obtenir la màxima eficiència.
13:45
And the thing that you might have noticed about those blue dots
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I potser heu notat que la majoria de punts blaus
13:48
is that a lot of them are in the middle of the ocean.
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es troben al mig de l'oceà.
13:51
So that's what we'll do: we'll build bubbles or something,
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Així doncs, haurem de construir bombolles
13:54
or platforms.
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o plataformes.
13:56
We'll actually part the water
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En realitat, anem a compartir l'aigua
13:58
to pull money out of the air,
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per tal d'extreure diners a l'aire
14:00
because it's a bright future
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perquè allí hi ha un futur brillant
14:02
if you're an algorithm.
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si som algoritmes.
14:04
(Laughter)
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(Rialles)
14:06
And it's not the money that's so interesting actually.
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En realitat, els diners no són el que ens interessa més,
14:09
It's what the money motivates,
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sinó més aviat la motivació que porten els diners.
14:11
that we're actually terraforming
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El fet de transformar
14:13
the Earth itself
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el mateix planeta
14:15
with this kind of algorithmic efficiency.
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amb aquesta mena d'eficiència algorítmica.
14:17
And in that light,
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Sota aquesta perspectiva
14:19
you go back
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tornem a veure
14:21
and you look at Michael Najjar's photographs,
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les fotografies de Michael Najjar
14:23
and you realize that they're not metaphor, they're prophecy.
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i ens adonem de que no són metafòriques, són profètiques.
14:26
They're prophecy
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S'anticipen
14:28
for the kind of seismic, terrestrial effects
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als efectes sísmics, terrestres
14:32
of the math that we're making.
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de les matemàtiques que fem.
14:34
And the landscape was always made
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I el paisatge sempre ha estat configurat
14:37
by this sort of weird, uneasy collaboration
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per aquesta mena de col·laboració, estranya i difícil,
14:40
between nature and man.
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entre la natura i el home.
14:43
But now there's this third co-evolutionary force: algorithms --
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Però ara existeix aquesta tercera força coevolutiva: els algoritmes;
14:46
the Boston Shuffler, the Carnival.
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el "Boston Shuffler", el "Carnival".
14:49
And we will have to understand those as nature,
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I haurem de considerar-los com una part de la natura.
14:52
and in a way, they are.
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I d'alguna, ho són.
14:54
Thank you.
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Gràcies.
14:56
(Applause)
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(Aplaudiment)
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