TED2014
Deborah Gordon: What ants teach us about the brain, cancer and the Internet
Debra Gordon (Deborah Gordon): Čemu nas mravi uče o mozgu, raku i internetu
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Ekolog Debra Gordon proučava mrave gde god da ih nađe - u pustinji, u tropskim krajevima, u svojoj kuhinji... U ovom fascinantnom govoru, ona objašnjava svoju opsesiju insektima koje bi većina nas rado zgnječila bez imalo razmišljanja. Ona tvrdi da mravlji život pruža koristan model za učenje o mnogim drugim temama, uključujući bolest, tehnologiju i ljudski mozak.
Deborah Gordon - Ecologist
By studying how ant colonies work without any one leader, Deborah Gordon has identified striking similarities in how ant colonies, brains, cells and computer networks regulate themselves. Full bio
By studying how ant colonies work without any one leader, Deborah Gordon has identified striking similarities in how ant colonies, brains, cells and computer networks regulate themselves. Full bio
Double-click the English transcript below to play the video.
00:13
I study ants
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Ja proučavam mrave
00:14
in the desert, in the tropical forest
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u pustinji, u tropskoj šumi
00:18
and in my kitchen,
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i u svojoj kuhinji
00:19
and in the hills around Silicon Valley where I live.
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kao i u brdima
oko Silikonske doline, gde živim.
oko Silikonske doline, gde živim.
00:23
I've recently realized that ants
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Nedavno sam shvatila da mravi
00:25
are using interactions differently
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različito koriste interakcije
u različitim okruženjima,
u različitim okruženjima,
00:27
in different environments,
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i to me je navelo na razmišljanje
00:29
and that got me thinking
that we could learn from this
that we could learn from this
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da bismo mogli da iz ovoga učimo
o drugim sistemima,
o drugim sistemima,
00:31
about other systems,
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00:32
like brains and data networks that we engineer,
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kao što su mozgovi
i mreže podataka kojima upravljamo,
i mreže podataka kojima upravljamo,
00:38
and even cancer.
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pa čak i rak.
Ono što svi ovi sistemi imaju zajedničko
00:41
So what all these systems have in common
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00:43
is that there's no central control.
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jeste to da ne postoji centralna kontrola.
00:45
An ant colony consists of sterile female workers --
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Kolonija mrava se sastoji
od sterilnih radilica -
od sterilnih radilica -
00:49
those are the ants you see walking around —
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to su mravi koje viđate
kako šetaju okolo -
kako šetaju okolo -
00:52
and then one or more reproductive females
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i od jedne ili više reproduktivnih ženki
00:54
who just lay the eggs.
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koje samo polažu jaja.
00:56
They don't give any instructions.
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One ne daju nikakve instrukcije.
00:58
Even though they're called queens,
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Iako se nazivaju kraljicama,
01:00
they don't tell anybody what to do.
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one ne govore nikome šta da radi.
01:02
So in an ant colony, there's no one in charge,
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U koloniji mrava, niko nije nadležan,
01:05
and all systems like this without central control
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i svi sistemi bez centralne kontrole
kao što je ovaj
kao što je ovaj
01:08
are regulated using very simple interactions.
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se regulišu koristeći
vrlo jednostavne interakcije.
vrlo jednostavne interakcije.
01:12
Ants interact using smell.
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Mravi komuniciraju koristeći miris.
01:15
They smell with their antennae,
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Oni mirišu svojim antenama,
01:17
and they interact with their antennae,
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i komuniciraju svojim antenama,
01:20
so when one ant touches another with its antennae,
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tako da kada jedan mrav
dodirne drugog svojim antenama,
dodirne drugog svojim antenama,
01:23
it can tell, for example, if the other ant
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može zaključiti, na primer,
01:24
is a nestmate
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da li je drugi mrav iz iste kolonije
01:26
and what task that other ant has been doing.
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i kakav zadatak taj drugi mrav obavlja.
01:30
So here you see a lot of ants moving around
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Ovde vidite mnogo mrava
koji se kreću okolo
koji se kreću okolo
01:33
and interacting in a lab arena
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i komuniciraju u laboratorijskoj areni
01:35
that's connected by tubes to two other arenas.
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koja je povezana cevima
sa druge dve arene.
sa druge dve arene.
01:39
So when one ant meets another,
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Dakle, kada jedan mrav sretne drugog,
01:41
it doesn't matter which ant it meets,
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nije bitno kog mrava sretne,
01:43
and they're actually not transmitting
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i oni zapravo ne šalju
01:45
any kind of complicated signal or message.
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nikakav komplikovani signal ili poruku.
01:49
All that matters to the ant is the rate
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Sve što je bitno za mrava jeste tempo
01:51
at which it meets other ants.
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kojim sreće drugog mrava.
01:54
And all of these interactions, taken together,
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I sve ove interakcije, uzete zajedno,
01:56
produce a network.
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stvaraju mrežu.
01:59
So this is the network of the ants
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Ovo je mreža mrava
02:01
that you just saw moving around in the arena,
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koje ste malopre videli
kako se kreću po areni,
kako se kreću po areni,
02:04
and it's this constantly shifting network
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i ova stalno promenljiva mreža je ta
02:07
that produces the behavior of the colony,
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koja proizvodi ponašanje kolonije,
02:10
like whether all the ants are hiding inside the nest,
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kao što je to
da li su svi mravi skriveni u gnezdu,
da li su svi mravi skriveni u gnezdu,
02:12
or how many are going out to forage.
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ili koliko njih izlazi u nabavku hrane.
Mozak zapravo radi na isti način,
02:15
A brain actually works in the same way,
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02:17
but what's great about ants is
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ali ono što je sjajno kod mrava
je to što možete videti
je to što možete videti
02:18
that you can see the whole network as it happens.
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čitavu mrežu dok se to dešava.
02:23
There are more than 12,000 species of ants,
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Postoji više od 12 000 vrsta mrava,
02:26
in every conceivable environment,
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u svakoj sredini koju možete zamisliti,
02:29
and they're using interactions differently
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i različito koriste interakcije
02:31
to meet different environmental challenges.
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kako bi se suočile
sa različitim izazovima sredine.
sa različitim izazovima sredine.
02:34
So one important environmental challenge
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Jedan značajan sredinski izazov
02:36
that every system has to deal with
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sa kojim svaki sistem
mora da se suoči
mora da se suoči
02:38
is operating costs, just what it takes
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jesu operativni troškovi,
ono što je potrebno
za pokretanje sistema.
za pokretanje sistema.
02:40
to run the system.
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02:42
And another environmental challenge is resources,
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A drugi sredinski izazov su resursi,
02:45
finding them and collecting them.
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njihovo pronalaženje i prikupljanje.
02:47
In the desert, operating costs are high
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U pustinji, operativni troškovi su veliki
02:50
because water is scarce,
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jer nema dovoljno vode,
02:52
and the seed-eating ants that I study in the desert
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i mravi koje izučavam u pustinji
koji jedu semenje
koji jedu semenje
02:54
have to spend water to get water.
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moraju da troše vodu da bi došli do vode.
02:57
So an ant outside foraging,
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Dakle, mrav u potrazi za hranom,
02:59
searching for seeds in the hot sun,
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tragajući sa semenjem po vrućini,
03:01
just loses water into the air.
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samo gubi vodu u vazduh.
03:03
But the colony gets its water
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Ali kolonija dobija svoju vodu
03:05
by metabolizing the fats out of the seeds
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metabolišući masnoće iz semenki
03:07
that they eat.
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koje jedu.
03:09
So in this environment, interactions are used
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Dakle, u ovoj sredini,
interakcije se koriste
interakcije se koriste
za aktiviranje potrage za hranom.
03:12
to activate foraging.
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03:14
An outgoing forager doesn't go out unless
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Tragač ne kreće u potragu ako ne dobije
03:16
it gets enough interactions with returning foragers,
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dovoljno interakcije
sa tragačima koji se vraćaju,
sa tragačima koji se vraćaju,
03:18
and what you see are the returning foragers
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i ono što vidite su tragači u povratku
03:20
going into the tunnel, into the nest,
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koji idu u tunel, u gnezdo,
03:22
and meeting outgoing foragers on their way out.
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i sreću tragače pri polasku napolje.
03:25
This makes sense for the ant colony,
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Ovo ima smisla za koloniju mrava,
03:26
because the more food there is out there,
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jer što više hrane ima napolju,
03:29
the more quickly the foragers find it,
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tragači će je brže naći,
03:31
the faster they come back,
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brže će se vratiti,
03:32
and the more foragers they send out.
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i više će tragača poslati napolje.
03:35
The system works to stay stopped,
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Sistem radi tako da ostaje zaustavljen,
03:37
unless something positive happens.
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dok se nešto pozitivno ne dogodi.
03:39
So interactions function to activate foragers.
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Tako interakcije funkcionišu
da bi aktivirale tragače za hranom.
da bi aktivirale tragače za hranom.
03:43
And we've been studying
the evolution of this system.
the evolution of this system.
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Izučavali smo evoluciju ovog sistema.
Najpre, postoje varijacije.
03:46
First of all, there's variation.
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03:47
It turns out that colonies are different.
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Ispostavilo se da su kolonije različite.
03:50
On dry days, some colonies forage less,
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Sušnim danima,
neke kolonije manje tragaju za hranom,
neke kolonije manje tragaju za hranom,
03:52
so colonies are different in how
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dakle, kolonije se razlikuju
po tome kako rukovode
po tome kako rukovode
03:54
they manage this trade-off
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ovom razmenom trošenja vode
03:55
between spending water to search for seeds
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da bi se tragalo za semenjem
03:58
and getting water back in the form of seeds.
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i ponovnog dobijanja vode
u obliku semenja.
u obliku semenja.
Pokušavamo da razumemo
zašto neke kolonije
zašto neke kolonije
04:02
And we're trying to understand why
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04:03
some colonies forage less than others
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tragaju za hranom manje od drugih
04:05
by thinking about ants as neurons,
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razmišljajući o mravima kao o neuronima,
04:08
using models from neuroscience.
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koristeći modele iz neurologije.
Kao što neuron
sabira stimulaciju drugih neurona
sabira stimulaciju drugih neurona
04:10
So just as a neuron adds up its stimulation
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04:13
from other neurons to decide whether to fire,
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da bi odlučio da li da se upali,
04:15
an ant adds up its stimulation from other ants
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mrav sabira stimulaciju drugih mrava
04:18
to decide whether to forage.
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da bi odlučio da li da traga za hranom.
04:20
And what we're looking for is whether there might be
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A ono što tražimo je
da li bi moglo biti
da li bi moglo biti
04:21
small differences among colonies
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malih razlika među kolonijama
04:23
in how many interactions each ant needs
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u pogledu toga koliko je interakcija
svakom mravu potrebno
svakom mravu potrebno
pre nego što postane voljan
da izađe u potragu za hranom,
da izađe u potragu za hranom,
04:27
before it's willing to go out and forage,
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04:29
because a colony like that would forage less.
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jer bi takva kolonija
manje tragala za hranom.
manje tragala za hranom.
04:32
And this raises an analogous question about brains.
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Ovo pokreće analogno pitanje o mozgovima.
04:35
We talk about the brain,
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Pričamo o mozgu,
04:37
but of course every brain is slightly different,
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ali naravno, svaki mozak
je nešto drugačiji,
je nešto drugačiji,
04:40
and maybe there are some individuals
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i možda ima nekih pojedinaca
04:41
or some conditions
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ili nekih uslova
04:42
in which the electrical properties of neurons are such
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u kojima su
elektronska svojstva neurona takva
elektronska svojstva neurona takva
04:46
that they require more stimulus to fire,
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da zahtevaju više podsticaja
da bi opalili,
da bi opalili,
04:50
and that would lead to differences in brain function.
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a to bi dovelo do razlika
u funkciji mozga.
u funkciji mozga.
04:53
So in order to ask evolutionary questions,
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Dakle, da bismo postavili
evoluciona pitanja,
evoluciona pitanja,
04:56
we need to know about reproductive success.
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potrebno je da saznamo
o reproduktivnom uspehu.
o reproduktivnom uspehu.
04:58
This is a map of the study site
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Ovo je mapa mesta istraživanja
05:01
where I have been tracking this population
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gde sam pratila ovu populaciju
05:03
of harvester ant colonies for 28 years,
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kolonija mrava žetelaca kroz 28 godina,
05:06
which is about as long as a colony lives.
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što je otprilike
onoliko koliko kolonija živi.
onoliko koliko kolonija živi.
05:09
Each symbol is a colony,
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Svaki simbol je kolonija,
05:11
and the size of the symbol is
how many offspring it had,
how many offspring it had,
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a veličina simbola označava
koliko je imala potomaka,
koliko je imala potomaka,
jer smo mogli da koristimo
genetske varijacije
genetske varijacije
05:14
because we were able to use genetic variation
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05:16
to match up parent and offspring colonies,
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da bismo spojili
kolonije roditelja i potomaka,
kolonije roditelja i potomaka,
05:19
that is, to figure out which colonies
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odnosno, da bismo otkrili koje kolonije
05:22
were founded by a daughter queen
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je osnovala ćerka kraljica
05:24
produced by which parent colony.
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i koja roditeljska kolonija
ju je stvorila.
ju je stvorila.
05:26
And this was amazing for me, after all these years,
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Ovo je bilo neverovatno za mene,
otkriti posle svih tih godina,
na primer, da kolonija 154,
na primer, da kolonija 154,
05:28
to find out, for example, that colony 154,
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05:31
whom I've known well for many years,
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koju sam dobro znala mnogo godina,
05:33
is a great-grandmother.
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je prababa.
05:35
Here's her daughter colony,
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Ovo je njena ćerka kolonija,
05:37
here's her granddaughter colony,
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ovo je njena unuka kolonija,
05:40
and these are her great-granddaughter colonies.
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a ovo su njene praunuke kolonije.
05:42
And by doing this, I was able to learn
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Radeći ovo, mogla sam da saznam
05:44
that offspring colonies resemble parent colonies
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da kolonije potomaka
podsećaju na kolonije roditelja
podsećaju na kolonije roditelja
po svojim odlukama o tome
koji dani su toliko vreli
koji dani su toliko vreli
05:47
in their decisions about which days are so hot
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05:49
that they don't forage,
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da neće ići u potragu za hranom,
05:51
and the offspring of parent colonies
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a potomci roditeljskih kolonija
05:53
live so far from each other that the ants never meet,
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žive međusobno toliko daleko
da se mravi nikada ne sreću,
da se mravi nikada ne sreću,
05:56
so the ants of the offspring colony
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tako da mravi kolonije potomka
05:58
can't be learning this from the parent colony.
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ne mogu da ovo nauče
od kolonije roditelja.
od kolonije roditelja.
Naš sledeći korak je bio da potražimo
genetsku varijaciju
genetsku varijaciju
06:00
And so our next step is to look
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06:02
for the genetic variation
underlying this resemblance.
underlying this resemblance.
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koja se nalazi u osnovi ove sličnosti.
06:07
So then I was able to ask, okay, who's doing better?
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Tada sam mogla da pitam,
okej, kome ide bolje?
okej, kome ide bolje?
06:11
Over the time of the study,
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Vremenom kroz istraživanje,
06:12
and especially in the past 10 years,
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naročito u poslednjih 10 godina,
06:14
there's been a very severe and deepening drought
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došlo je do veoma teške
i zaoštravajuće suše
i zaoštravajuće suše
06:17
in the Southwestern U.S.,
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u jugozapadu SAD-a,
06:19
and it turns out that the
colonies that conserve water,
colonies that conserve water,
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i ispostavilo se da kolonije
koje čuvaju vodu,
koje čuvaju vodu,
06:22
that stay in when it's really hot outside,
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koje ostaju unutra
kada je zaista vruće napolju,
kada je zaista vruće napolju,
06:27
and thus sacrifice getting as much food as possible,
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i tako žrtvuju pribavljanje
što više moguće hrane,
što više moguće hrane,
06:29
are the ones more likely to have offspring colonies.
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su one koje će verovatnije
imati kolonije potomaka.
imati kolonije potomaka.
06:32
So all this time, I thought that colony 154
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Sve ovo vreme sam mislila
da je kolonija 154 gubitnik,
jer bi veoma vrelih dana
jer bi veoma vrelih dana
06:35
was a loser, because on really dry days,
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06:37
there'd be just this trickle of foraging,
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bilo samo mrvica prikupljene hrane,
dok su druge kolonije bile napolju
u traganju, pribavljajući dosta hrane,
u traganju, pribavljajući dosta hrane,
06:39
while the other colonies were out
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06:41
foraging, getting lots of food,
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06:43
but in fact, colony 154 is a huge success.
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ali u stvari,
kolonija 154 je veoma uspešna.
kolonija 154 je veoma uspešna.
06:46
She's a matriarch.
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Ona je matrijarh.
06:47
She's one of the rare great-grandmothers on the site.
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Ona je jedna od retkih prababa
na lokaciji.
na lokaciji.
06:50
To my knowledge, this is the first time
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Koliko ja znam, ovo je prvi put
da smo mogli da pratimo
06:53
that we've been able to track
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06:55
the ongoing evolution of collective behavior
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evoluciju kolektivnog ponašanja
dok se ona odvija
dok se ona odvija
06:58
in a natural population of animals
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u prirodnoj populaciji životinja
07:00
and find out what's actually working best.
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i saznamo šta zaista najbolje funkcioniše.
07:04
Now, the Internet uses an algorithm
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2421
Internet koristi algoritam
07:07
to regulate the flow of data
167
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2853
da bi regulisao protok podataka
07:10
that's very similar to the one
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2227
koji je veoma sličan onome
07:12
that the harvester ants are using to regulate
169
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koji mravi žeteoci koriste za regulaciju
07:14
the flow of foragers.
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kretanja tragača za hranom.
Pogodite kako zovemo ovu analogiju?
07:16
And guess what we call this analogy?
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07:19
The anternet is coming.
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Anternet stiže.
07:21
(Applause)
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(Aplauz)
07:23
So data doesn't leave the source computer
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Podaci ne napuštaju izvorni računar
07:26
unless it gets a signal that there's enough bandwidth
175
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2861
dok ne dobiju signal
da je širina opsega dovoljna
da je širina opsega dovoljna
07:29
for it to travel on.
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da bi putovali.
07:32
In the early days of the Internet,
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1441
Ranih dana interneta,
07:33
when operating costs were really high
178
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kada su operativni troškovi
bili vrlo visoki
bili vrlo visoki
07:35
and it was really important not to lose any data,
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i bilo je jako važno
ne gubiti nimalo podataka,
ne gubiti nimalo podataka,
07:38
then the system was set up for interactions
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sistem je bio podešen za interakcije
07:41
to activate the flow of data.
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da bi aktivirao protok podataka.
07:44
It's interesting that the ants are using an algorithm
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2385
Interesantno je da mravi koriste algoritam
07:46
that's so similar to the one that we recently invented,
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koji je toliko sličan onome
koji smo skoro pronašli,
koji smo skoro pronašli,
07:50
but this is only one of a handful of ant algorithms
184
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2953
ali je to samo jedan
u mnoštvu mravljih algoritama
u mnoštvu mravljih algoritama
07:53
that we know about,
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1419
za koje znamo,
07:54
and ants have had 130 million years
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3193
a mravi su imali 130 miliona godina
07:58
to evolve a lot of good ones,
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2026
da razviju dosta onih dobrih,
08:00
and I think it's very likely
188
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1506
i mislim da je veoma verovatno
08:01
that some of the other 12,000 species
189
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2557
da će neke od ostalih 12 000 vrsta
08:04
are going to have interesting algorithms
190
472140
2697
imati zanimljive algoritme
08:06
for data networks
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474837
1024
za mreže podataka
08:07
that we haven't even thought of yet.
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2697
o kojima mi još nismo ni razmišljali.
08:10
So what happens when operating costs are low?
193
478558
3085
Šta se dešava
kada su operativni troškovi niski?
kada su operativni troškovi niski?
Operativni troškovi su niski
u tropskim krajevima,
u tropskim krajevima,
08:13
Operating costs are low in the tropics,
194
481643
1787
08:15
because it's very humid, and it's easy for the ants
195
483430
2096
jer je veoma vlažno, i mravima je lako
08:17
to be outside walking around.
196
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2824
da budu napolju krećući se unaokolo.
08:20
But the ants are so abundant
197
488350
1653
Ali mravi su toliko rasprostranjeni
i raznovrsni u tropskim krajevima
i raznovrsni u tropskim krajevima
08:22
and diverse in the tropics
198
490003
1818
08:23
that there's a lot of competition.
199
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da ima mnogo konkurencije.
08:26
Whatever resource one species is using,
200
494419
1952
Koji god resurs jedna vrsta koristi,
08:28
another species is likely to be using that
201
496371
3172
druga vrsta ga verovatno
08:31
at the same time.
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2379
istovremeno koristi.
08:33
So in this environment, interactions are used
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2608
Stoga se u ovoj sredini
interakcije koriste
interakcije koriste
08:36
in the opposite way.
204
504530
1945
na suprotan način.
08:38
The system keeps going
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506475
1395
Sistem nastavlja da radi
dok se nešto negativno ne desi,
dok se nešto negativno ne desi,
08:39
unless something negative happens,
206
507870
1554
08:41
and one species that I study makes circuits
207
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2167
i jedna vrsta koju izučavam
08:43
in the trees of foraging ants
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511591
2159
pravi kružne putanje
u drveću mrava sakupljača
u drveću mrava sakupljača
08:45
going from the nest to a food source and back,
209
513750
2981
idući od gnezda do izvora hrane i nazad,
08:48
just round and round,
210
516731
1329
samo ukrug i ukrug,
dok se nešto negativno ne desi,
dok se nešto negativno ne desi,
08:50
unless something negative happens,
211
518060
1442
08:51
like an interaction
212
519502
1609
kao što je interakcija
08:53
with ants of another species.
213
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2739
sa mravima druge vrste.
08:55
So here's an example of ant security.
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523850
2937
Evo primera mravljeg obezbeđenja.
08:58
In the middle, there's an ant
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526787
1858
U sredini se nalazi mrav koji zapušava
ulaz u gnezdo svojom glavom
ulaz u gnezdo svojom glavom
09:00
plugging the nest entrance with its head
216
528645
2463
09:03
in response to interactions with another species.
217
531108
2993
kao odgovor na interakcije
sa drugim vrstama.
sa drugim vrstama.
09:06
Those are the little ones running around
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534101
1659
To su malecki koji trče okolo
09:07
with their abdomens up in the air.
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2751
sa svojim trbusima izbačenim u vazduhu.
09:10
But as soon as the threat is passed,
220
538511
2046
Ali čim pretnja prođe,
09:12
the entrance is open again,
221
540557
2755
ulaz je ponovo otvoren,
09:15
and maybe there are situations
222
543312
1790
i možda ima situacija
u kompjuterskoj bezbednosti
09:17
in computer security
223
545102
1089
09:18
where operating costs are low enough
224
546191
2206
gde su operativni troškovi dovoljno niski
09:20
that we could just block access temporarily
225
548397
3375
da možemo da samo
blokiramo pristup privremeno,
blokiramo pristup privremeno,
09:23
in response to an immediate threat,
226
551772
2193
kao odgovor na trenutnu pretnju,
09:25
and then open it again,
227
553965
2026
i zatim ga ponovo otvorimo,
umesto pokušaja da izgradimo
09:27
instead of trying to build
228
555991
1269
09:29
a permanent firewall or fortress.
229
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3980
trajni zaštitni zid ili tvrđavu.
09:33
So another environmental challenge
230
561240
1940
Drugi sredinski izazov
09:35
that all systems have to deal with
231
563180
1695
kojim svi sistemi moraju da se bave
09:36
is resources, finding and collecting them.
232
564875
5452
jesu resursi,
njihovo pronalaženje i prikupljanje.
njihovo pronalaženje i prikupljanje.
A da bi to činili, mravi rešavaju problem
09:42
And to do this, ants solve the problem
233
570327
1673
09:44
of collective search,
234
572000
1258
kolektivne potrage,
09:45
and this is a problem that's of great interest
235
573258
1576
i to je problem koji je sada
09:46
right now in robotics,
236
574834
1484
od velikog značaja u robotici,
09:48
because we've understood that,
237
576318
1732
jer smo shvatili da,
09:50
rather than sending a single,
238
578050
1614
umesto slanja jednog,
09:51
sophisticated, expensive robot out
239
579664
3495
sofisticiranog, skupog robota
09:55
to explore another planet
240
583159
1417
da istraži drugu planetu
09:56
or to search a burning building,
241
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2567
ili da pretraži zgradu koja gori,
09:59
that instead, it may be more effective
242
587143
2600
da umesto toga, može biti efektivnije
10:01
to get a group of cheaper robots
243
589743
4377
uzeti grupu jeftinijih robota
10:06
exchanging only minimal information,
244
594120
2545
koji će razmenjivati
samo minimum informacija,
samo minimum informacija,
10:08
and that's the way that ants do it.
245
596665
2799
a to je način na koji mravi to čine.
10:11
So the invasive Argentine ant
246
599464
1765
Tako invazivni argentinski mrav
10:13
makes expandable search networks.
247
601229
2330
pravi proširive mreže pretrage.
10:15
They're good at dealing with the main problem
248
603559
2273
Oni su dobri u bavljenju
glavnim problemom
glavnim problemom
10:17
of collective search,
249
605832
1331
kolektivne potrage,
10:19
which is the trade-off between
250
607163
2566
a to je kompromis između
10:21
searching very thoroughly
251
609729
1336
vrlo temeljnog traganja
10:23
and covering a lot of ground.
252
611065
1997
i pokrivanja mnogo zemlje.
A ono što rade jeste,
10:25
And what they do is,
253
613062
895
10:25
when there are many ants in a small space,
254
613957
2387
kada ima mnogo mrava na malom prostoru,
10:28
then each one can search very thoroughly
255
616344
2213
onda svaki od njih
može da traži vrlo temeljno
može da traži vrlo temeljno
10:30
because there will be another ant nearby
256
618557
1624
jer će biti drugi mrav u blizini
10:32
searching over there,
257
620181
1357
koji traga tamo,
10:33
but when there are a few ants
258
621538
1647
ali kada ima malo mrava
10:35
in a large space,
259
623185
2055
na velikom prostoru,
10:37
then they need to stretch out their paths
260
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2414
onda treba da rašire svoje putanje
10:39
to cover more ground.
261
627654
1803
da bi pokrili više terena.
10:41
I think they use interactions to assess density,
262
629457
2954
Mislim da koriste interakcije
da procene gustinu,
da procene gustinu,
10:44
so when they're really crowded,
263
632411
1229
pa kada je stvarno gužva,
10:45
they meet more often,
264
633640
1102
češće se sreću,
10:46
and they search more thoroughly.
265
634742
2465
i tragaju temeljnije.
10:49
Different ant species must use different algorithms,
266
637207
3400
Različite vrste mrava
moraju koristiti različite algoritme,
moraju koristiti različite algoritme,
10:52
because they've evolved to deal with
267
640607
2522
jer su evoluirali da se bave
10:55
different resources,
268
643129
1671
različitim resursima,
10:56
and it could be really useful to know about this,
269
644800
2559
i može biti korisno znati,
10:59
and so we recently asked ants
270
647359
1642
nedavno smo tražili od mrava
11:01
to solve the collective search problem
271
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2450
da reše problem kolektivne potrage
11:03
in the extreme environment
272
651451
1368
u ekstremnoj sredini
11:04
of microgravity
273
652819
1558
mikrogravitacije
11:06
in the International Space Station.
274
654377
1976
u Međunarodnoj svemirskoj stanici.
Kada sam prvi put videla ovu sliku,
11:08
When I first saw this picture, I thought,
275
656353
1545
11:09
Oh no, they've mounted the habitat vertically,
276
657898
2857
pomislila sam:
O ne, montirali su stanište vertikalno,
O ne, montirali su stanište vertikalno,
11:12
but then I realized that, of course, it doesn't matter.
277
660755
2618
ali onda sam shvatila da,
naravno, to nije bitno.
naravno, to nije bitno.
11:15
So the idea here is that the ants
278
663373
2637
Dakle, ideja je da mravi
11:18
are working so hard to hang on
279
666010
1970
rade tako vredno da vise
11:19
to the wall or the floor or whatever you call it
280
667980
3057
na zidu ili podu ili
kako god ga nazovete,
kako god ga nazovete,
11:23
that they're less likely to interact,
281
671037
3009
da je manje verovatno da će komunicirati,
i tako bi se poremetio odnos
11:26
and so the relationship between
282
674046
1244
11:27
how crowded they are and how often they meet
283
675290
2120
između toga kolika je gužva
i koliko se često sreću.
i koliko se često sreću.
11:29
would be messed up.
284
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1725
Još uvek analiziramo podatke.
11:31
We're still analyzing the data.
285
679135
1395
11:32
I don't have the results yet.
286
680530
1964
Još uvek nemam rezultate.
11:34
But it would be interesting to know
287
682494
1694
Ali bi bilo zanimljivo znati
kako druge vrste
kako druge vrste
11:36
how other species solve this problem
288
684188
2459
rešavaju ovaj problem
u različitim sredinama na Zemlji,
u različitim sredinama na Zemlji,
11:38
in different environments on Earth,
289
686647
2564
i stoga uspostavljamo program
11:41
and so we're setting up a program
290
689211
1266
11:42
to encourage kids around the world
291
690477
2160
da bismo podstakli decu širom sveta
11:44
to try this experiment with different species.
292
692637
2536
da probaju ovaj eksperiment
sa različitim vrstama.
sa različitim vrstama.
11:47
It's very simple.
293
695173
1767
Veoma je jednostavno.
11:48
It can be done with cheap materials.
294
696940
2090
Može se uraditi sa jeftinim materijalima.
11:51
And that way, we could make a global map
295
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2833
I na taj način
možemo napraviti globalnu mapu
možemo napraviti globalnu mapu
11:53
of ant collective search algorithms.
296
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3347
mravljih algoritama kolektivne potrage.
I mislim da je prilično verovatno
da će invazivne vrste,
da će invazivne vrste,
11:57
And I think it's pretty likely that the invasive species,
297
705210
2483
11:59
the ones that come into our buildings,
298
707693
2149
one koje dolaze u naše zgrade,
12:01
are going to be really good at this,
299
709842
1742
biti jako dobre u ovome,
12:03
because they're in your kitchen
300
711584
1848
zato što su u našoj kuhinji
12:05
because they're really good
at finding food and water.
at finding food and water.
301
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3907
jer su jako dobri
u pronalaženju vode i hrane.
u pronalaženju vode i hrane.
12:09
So the most familiar resource for ants
302
717339
3265
Najpoznatiji resurs za mrave
12:12
is a picnic,
303
720604
1315
je piknik,
12:13
and this is a clustered resource.
304
721919
2145
a to je resurs na jednom mestu.
Kada je tu jedan komad voća,
12:16
When there's one piece of fruit,
305
724064
999
12:17
there's likely to be another piece of fruit nearby,
306
725063
2515
verovatno će tu biti
i drugo parče voća u blizini,
i drugo parče voća u blizini,
12:19
and the ants that specialize on clustered resources
307
727578
3432
i mravi koji su specijalizovani
za grupisane resurse
za grupisane resurse
12:23
use interactions for recruitment.
308
731010
1942
koriste interakcije za regrutovanje.
Kada jedan mrav sretne drugog,
12:24
So when one ant meets another,
309
732952
1277
12:26
or when it meets a chemical deposited
310
734229
1625
ili kada naiđe na hemijske nanose
12:27
on the ground by another,
311
735854
1736
na zemlji od drugog,
12:29
then it changes direction to follow
312
737590
1833
onda menja pravac da bi išao
12:31
in the direction of the interaction,
313
739423
1573
u pravcu interakcije,
12:32
and that's how you get the trail of ants
314
740996
1977
i tako dobijate putanju mrava
12:34
sharing your picnic.
315
742973
1413
koji dele vaš piknik.
12:36
Now this is a place where I think we might be able
316
744386
1695
Ovde mislim da možemo
12:38
to learn something from ants about cancer.
317
746081
3741
naučiti nešto od mrava o raku.
12:41
I mean, first, it's obvious that we could do a lot
318
749822
1981
Mislim, prvo, očigledno je da bismo mogli
12:43
to prevent cancer
319
751803
1610
učiniti puno toga da sprečimo rak
12:45
by not allowing people to spread around
320
753413
2577
ne dozvoljavajući ljudima da šire okolo
12:47
or sell the toxins that promote
321
755990
1944
ili prodaju toksine koji podstiču
12:49
the evolution of cancer in our bodies,
322
757934
2780
razvoj raka u našim telima,
ali ne mislim da nam mravi
mogu mnogo pomoći sa ovim
mogu mnogo pomoći sa ovim
12:52
but I don't think the ants can help us much with this
323
760714
2346
12:55
because ants never poison their own colonies.
324
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3358
jer mravi nikada ne truju
sopstvene kolonije.
sopstvene kolonije.
Ali možda možemo naučiti nešto od mrava
12:58
But we might be able to learn something from ants
325
766418
1332
12:59
about treating cancer.
326
767750
1763
o lečenju raka.
13:01
There are many different kinds of cancer.
327
769513
2225
Postoji mnogo različitih vrsta raka.
13:03
Each one originates in a particular part of the body,
328
771738
2978
Svaki od njih potiče
iz određenog dela tela,
iz određenog dela tela,
13:06
and then some kinds of cancer will spread
329
774716
2966
i zatim, neke vrste raka
će se raširiti ili metastazirati
će se raširiti ili metastazirati
13:09
or metastasize to particular other tissues
330
777682
2830
do drugih određenih tkiva
13:12
where they must be getting
resources that they need.
resources that they need.
331
780512
2880
gde moraju pribaviti
sredstva koja su im potrebna.
sredstva koja su im potrebna.
13:15
So if you think from the perspective
332
783392
1808
Ako razmišljate iz perspektive
13:17
of early metastatic cancer cells
333
785200
1950
ranih metastazirajućih ćelija raka
13:19
as they're out searching around
334
787150
1623
dok tragaju unaokolo
13:20
for the resources that they need,
335
788773
2317
za resursima koji su im potrebni,
13:23
if those resources are clustered,
336
791090
1983
ako su ti resursi grupisani,
13:25
they're likely to use interactions for recruitment,
337
793073
3013
verovatno je da će koristiti interakcije
za regrutaciju,
za regrutaciju,
13:28
and if we can figure out how
cancer cells are recruiting,
cancer cells are recruiting,
338
796086
3093
a ako možemo da otkrijemo
kako se ćelije raka okupljaju,
kako se ćelije raka okupljaju,
13:31
then maybe we could set traps
339
799179
2347
onda bismo možda mogli da postavimo zamke
13:33
to catch them before they become established.
340
801526
4049
da ih uhvatimo pre nego se uspostave.
13:37
So ants are using interactions in different ways
341
805575
3235
Dakle, mravi koriste interakcije
na različite načine
na različite načine
13:40
in a huge variety of environments,
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u mnogim različitim sredinama,
13:43
and we could learn from this
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i možemo naučiti iz ovoga
13:45
about other systems that operate
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o drugim sistemima koji rade
13:47
without central control.
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bez centralne kontrole.
13:49
Using only simple interactions,
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Koristeći samo proste interakcije,
13:51
ant colonies have been performing
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kolonije mrava vrše neverovatne podvige
13:53
amazing feats for more than 130 million years.
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više od 130 miliona godina.
13:56
We have a lot to learn from them.
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Imamo mnogo da naučimo od njih.
13:58
Thank you.
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Hvala vam.
(Aplauz)
14:01
(Applause)
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ABOUT THE SPEAKER
Deborah Gordon - EcologistBy studying how ant colonies work without any one leader, Deborah Gordon has identified striking similarities in how ant colonies, brains, cells and computer networks regulate themselves.
Why you should listen
Ecologist Deborah M. Gordon has learned that ant colonies can work without central control by using simple interactions like how often the insects touch antennae. Contrary to the notion that colonies are organized by efficient ants, she has instead discovered that evolution has produced “noisy” systems that tolerate accident and respond flexibly to the environment. When conditions are tough, natural selection favors colonies that conserve resources.
Her studies of ant colonies have led her and her Stanford colleagues to the discovery of the “Anternet,” which regulates foraging in ants in the same way the internet regulates data traffic. But as she said to Wired in 2013, "Insect behavior mimicking human networks ... is actually not what’s most interesting about ant networks. What’s far more interesting are the parallels in the other direction: What have the ants worked out that we humans haven’t thought of yet?" Her latest exploration: How do ants behave in space?
Deborah Gordon | Speaker | TED.com