Massive-scale online collaboration | Luis von Ahn

311,384 views ・ 2011-12-06

TED


Please double-click on the English subtitles below to play the video.

Prevodilac: Natasa Golosin Lektor: Ivana Korom
00:15
How many of you had to fill out a web form
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Koliko vas je nekada moralo da na internetu popuni neku vrstu obrasca
00:17
where you've been asked to read
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gde ste morali da prekucate iskrivljeni niz znakova poput ovog?
00:18
a distorted sequence of characters like this?
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Koliko vas je pomislilo "Ovo je zaista iritirajuće"?
00:20
How many of you found it really annoying?
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Dobro. Odlično. Ja sam to izmislio.
00:22
(Laughter)
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00:24
OK, outstanding. So I invented that.
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(Smeh)
00:25
(Laughter)
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Ili bio sam jedan od ljudi koji su to izmislili.
00:27
Or I was one of the people who did it.
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To se zove CAPTCHA.
00:29
That thing is called a CAPTCHA.
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I tu je kako bismo bili sigurni da je stvorenje koje je popunilo formular
00:31
And it is there to make sure you, the entity filling out the form,
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zapravo čovek, a ne kompjuterski program
00:34
are a human and not a computer program
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koji je napisan kako bi popunio milione ovakvih obrazaca.
00:36
that was written to submit the form millions of times.
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To funkcioniše jer ljudi,
00:38
The reason it works is because humans, at least non-visually-impaired humans,
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ili barem ljudi koji vide,
nemaju problema da pročitaju ove izobličene znake,
00:42
have no trouble reading these distorted characters,
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dok kompjuterski programi jednostavno još uvek to ne mogu da urade.
00:44
whereas programs can't do it as well yet.
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00:46
In the case of Ticketmaster,
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Na primer, u slučaju Tiketmastera,
00:48
the reason you have to type these characters
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razlog što morate da ukucate ove simbole
00:50
is to prevent scalpers from writing a program
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je da biste sprečili tapkaroše da naprave program
00:52
that can buy millions of tickets, two at a time.
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koji će im omogućiti da kupe milione ulaznica.
00:54
CAPTCHAs are used all over the Internet.
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CAPTCHA se koristi širom interneta
00:56
And since they're used so often,
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I budući da je to veoma često,
00:58
a lot of times the sequence of random characters shown to the user
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mnogo puta konkretni niz slučajno odabranih simbola koji su pokazani korisniku
nije naročito "srećan".
01:01
is not so fortunate.
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01:02
So this is an example from the Yahoo registration page.
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Ovo je primer sa stranice za registraciju na Jahu (Yahoo).
01:05
The random characters that happened to be shown to the user
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Slučajno odabrani karakteri prikazani korisniku
su bili Č,E,K,A,J,T.E, što naravno daje reč.
01:08
were W, A, I, T, which, of course, spell a word.
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Ali najbolje od svega je što je dvadesetak minuta kasnije
01:11
But the best part is the message
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01:13
that the Yahoo help desk got about 20 minutes later.
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Jahu dobio poruku sledećeg sadržaja.
01:15
[Help! I've been waiting for over 20 minutes and nothing happens.]
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"Pomozite! Čekam već 20 minuta i ništa se ne dešava."
01:18
(Laughter)
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(Smeh)
01:23
This person thought they needed to wait.
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Ova osoba je mislila da je trebalo da čeka.
01:25
This, of course, is not as bad as this poor person.
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Ovo naravno i nije tako loše u poređenju sa ovom jadnom osobom.
01:28
(Laughter)
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(Smeh)
01:30
CAPTCHA Project is something that we did at Carnegie Melllon over 10 years ago,
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CAPTCHA projekat smo uradili ovde na Karnegi Melon univerzitetu pre više od deset godina,
i koristi se svuda.
01:34
and it's been used everywhere.
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01:35
Let me now tell you about a project that we did a few years later,
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Sada ću vam ispričati nešto o projektu koji smo uradili nekoliko godina kasnije
i što je u neku ruku evolucija CAPTCHA-e.
01:38
which is sort of the next evolution of CAPTCHA.
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Ovaj projekat smo nazvali reCAPTCHA,
01:41
This is a project that we call reCAPTCHA,
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započet je ovde u Karnegi Melonu
01:43
which is something that we started here at Carnegie Mellon,
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ali se onda pretvorio u startap kompaniju.
01:46
then we turned it into a start-up company.
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Zatim, pre oko godinu i po,
01:48
And then about a year and a half ago, Google actually acquired this company.
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Gugl je kupio ovu kompaniju,
Reći ću vam kako je projekat počeo.
01:51
Let me tell you what this project started.
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Počelo je tako što smo shvatili sledeće:
01:53
This project started from the following realization:
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ispostavi se da ljudi širom sveta svakog dana
01:56
It turns out that approximately 200 million CAPTCHAs
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ukucaju oko 200 miliona CAPTCHA kodova.
01:58
are typed everyday by people around the world.
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02:00
When I first heard this, I was quite proud of myself.
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Kad sam to čuo prvi put, bio sam prilično ponosan,
misleći kako moje istraživanje ima ogroman uticaj.
02:03
I thought, look at the impact my research has had.
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Ali onda sam počeo da se loše osećam.
02:05
But then I started feeling bad.
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Jer... svaki put kad ukucate CAPTCHA
02:07
Here's the thing: each time you type a CAPTCHA,
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vi izgubite deset sekundi svog života.
02:09
essentially, you waste 10 seconds of your time.
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02:11
And if you multiply that by 200 million,
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I ako to pomnožite sa 200 miliona
02:13
you get that humanity is wasting about 500,000 hours every day
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ispada da čovečanstvo troši oko 500.000 sati svakog dana
02:16
typing these annoying CAPTCHAs.
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ukucavajući te iritantne CAPTCHA kodove.
02:18
(Laughter)
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I tako sam počeo da se osećam loše -
02:19
So then I started feeling bad.
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02:20
(Laughter)
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(Smeh)
02:22
And then I started thinking, of course, we can't just get rid of CAPTCHAs,
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A onda sam počeo da razmišljam, naravno da se ne možemo otarasiti CAPTCHA-e,
budući da bezbednost čitavog interneta zavisi od njih.
02:26
because the security of the web depends on them.
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Ali onda sam se zapitao postoji li način na koji možemo iskoristiti ovaj trud
02:28
But then I started thinking, can we use this effort
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02:30
for something that is good for humanity?
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za nešto što je dobro za čovečanstvo?
02:32
So see, here's the thing.
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Zaključak je sledeći.
02:34
While you're typing a CAPTCHA, during those 10 seconds,
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Tokom tih desetak sekundi dok ukucavate CAPTCHA kod,
vaš mozak radi nešto zaista zadivljujuće.
02:37
your brain is doing something amazing.
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02:38
Your brain is doing something that computers cannot yet do.
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On radi nešto što kompjuteri još uvek ne mogu da urade.
Dakle, možemo li izvesti da za tih deset sekundi vi uradite nešto korisno?
02:41
So can we get you to do useful work for those 10 seconds?
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Drugim rečima, postoji li
02:44
Is there some humongous problem that we cannot yet get computers to solve,
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neki ogromni problem koji kompjuteri još uvek ne mogu da reše,
a koji možemo izdeliti na malecke deonice od 10 sekundi
02:48
yet we can split into tiny 10-second chunks
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02:50
such that each time somebody solves a CAPTCHA,
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tako da svaki put kad neko reši CAPTCHA kod
reši mali deo tog problema?
02:53
they solve a little bit of this problem?
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Odgovor na ovo je "da", i upravo to sada vi radite.
02:55
And the answer to that is "yes," and this is what we're doing now.
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Ono što možda ne znate je da kada ukucate CAPTCHA,
02:58
Nowadays, while you're typing a CAPTCHA,
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ne samo da ste dokazali da ste ljudsko biće
03:00
not only are you authenticating yourself as a human,
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već nam zapravo i pomažete da digitalizujemo knjige.
03:02
but in addition you're helping us to digitize books.
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Dozvolite mi da objasnim.
03:05
Let me explain how this works.
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Postoji mnogo projekata kojima je cilj da digitalizuju knjige.
03:06
There's a lot of projects trying to digitize books.
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Gugl ima jedan. Internet arhiv ima jedan.
03:08
Google has one. The Internet Archive has one.
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Amazon, sada sa Kindlom takođe pokušava da digitalizuje knjige.
03:11
Amazon, with the Kindle, is trying to digitize books.
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To funkcioniše tako što
03:13
Basically, the way this works is you start with an old book.
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počnete sa nekom starom knjigom.
03:16
You've seen those things, right?
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Znate te stvari, zar ne? Knjige?
03:18
Like a book?
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(Smeh)
03:19
(Laughter)
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03:20
So you start with a book and then you scan it.
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Uzmete knjigu i skenirate je.
Skeniranje knjige je kao
03:23
Now, scanning a book
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03:24
is like taking a digital photograph of every page.
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digitalno fotografisanje svake stranice knjige.
Dobijete fotografiju svake stranice.
03:27
It gives you an image for every page.
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I ovo je fotografija sa tekstom za svaku stranicu knjige.
03:29
This is an image with text for every page of the book.
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Sledeći korak u procesu
03:31
The next step in the process is that the computer needs to be able
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je da kompjuter uspe da odgonetne sve reči na ovoj slici.
03:34
to decipher the words in this image.
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Tu se koristi tehnologija pod imenom OCR (OPK).
03:36
That's using a technology called OCR, for optical character recognition,
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za optičko prepoznavanje karaktera,
03:39
which takes a picture of text
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koja fotografiše tekst
03:41
and tries to figure out what text is in there.
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i pokušava da odgonetne šta tu piše.
03:43
Now, the problem is that OCR is not perfect.
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Problem je što ova tehnologija nije savršena.
Naročito kada se radi o starijim knjigama
03:46
Especially for older books
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03:47
where the ink has faded and the pages have turned yellow,
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gde je tinta izbledela i stranice požutele,
03:50
OCR cannot recognize a lot of the words.
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pa OPK ne može da prepozna mnoge reči.
03:52
For things that were written more than 50 years ago,
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Na primer, kod stvari koje su napisane pre više od 50 godina,
kompjuter ne može da prepozna oko 30 odsto reči.
03:55
the computer cannot recognize about 30 percent of the words.
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I ono što tada radimo
03:58
So now we're taking all of the words that the computer cannot recognize
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je da uzmemo sve reči koje kompjuter ne može da prepozna
04:01
and we're getting people to read them for us
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i pitamo ljude da ih pročitaju umesto nas
04:03
while they're typing a CAPTCHA on the Internet.
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dok ukucavaju CAPTCHA na internetu.
Tako da, sledeći put kad budete kucali CAPTCHA, te reči
04:06
So the next time you type a CAPTCHA, these words that you're typing
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su zapravo reči koje dolaze iz knjiga koje se digitalizuju
04:09
are actually words from books that are being digitized
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04:11
that the computer could not recognize.
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i koje kompjuter ne može da prepozna.
04:13
The reason we have two words nowadays instead of one
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A razlog što danas imamo dve, umesto jedne reči
je zato što je jednu od reči
04:16
is because one of the words
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04:17
is a word that the system just got out of a book,
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sistem dobio iz knjige,
nije je prepoznao i pokazaće vam je.
04:20
it didn't know what it was and it's going to present it to you.
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Ali budući da ne zna odgovor, ne može ni vas da oceni.
04:23
But since it doesn't know the answer, it cannot grade it.
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Zato vam dajemo još jednu reč,
04:26
So we give you another word,
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04:27
for which the system does know the answer.
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koju sistem prepoznaje.
04:29
We don't tell you which one's which and we say, please type both.
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Ne kažemo vam koja je koja, već vas pitamo da upišete obe.
I ako upišete tačno reč
04:32
And if you type the correct word
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koju sistem već zna,
04:34
for the one for which the system knows the answer,
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on zaključuje da ste ljudsko biće
04:36
it assumes you are human
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04:37
and it also gets some confidence that you typed the other word correctly.
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i da ćete i drugu reč ukucati tačno.
Ako ponovimo ovaj proces sa 10 različitih ljudi
04:41
And if we repeat this process to 10 different people
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i svi oni se slože oko nove reči,
04:43
and they agree on what the new word is,
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dobijemo još jednu tačno digitalizovanu reč.
04:45
then we get one more word digitized accurately.
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Tako funkcioniše sistem.
04:48
So this is how the system works.
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Počeo je da radi pre oko tri ili četiri godine,
04:49
And since we released it about three or four years ago,
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i mnogi sajtovi su već prešli sa stare CAPTCHA kodove
04:52
a lot of websites have started switching from the old CAPTCHA,
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gde su ljudi gubili vreme
04:55
where people wasted their time,
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na novi CAPTCHA gde ljudi pomažu da se knjige digitalizuju.
04:56
to the new CAPTCHA where people are helping to digitize books.
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Dakle, na primer, Tiketmaster.
04:59
So every time you buy tickets on Ticketmaster,
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Svaku put kada kupite karte na Tiketmasteru pomažete digitalizaciju knjiga.
05:01
you help to digitize a book.
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Fejsbuk: Svaku put kad dodate prijatelja ili nekog "pokujete",
05:03
Facebook: Every time you add a friend or poke somebody,
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učestvujete u digitalizaciji knjiga.
05:05
you help to digitize a book.
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Tviter i oko 350.000 drugih sajtova koriste reCAPTCHA.
05:07
Twitter and about 350,000 other sites are all using reCAPTCHA.
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I zapravo, broj tih sajtova je toliko veliki
05:10
And the number of sites that are using reCAPTCHA is so high
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da je i broj reči digitalizovanih tokom jednog dana veoma veliki.
05:13
that the number of words we're digitizing per day is really large.
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Oko sto miliona dnevno,
05:16
It's about 100 million a day,
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što je ekvivalent za oko dva i po miliona knjiga godišnje.
05:17
which is the equivalent of about two and a half million books a year.
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I to sve reč po reč,
05:21
And this is all being done one word at a time
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samo uz pomoć ljudi koji ukucavaju CAPTCHA kodove na internetu.
05:23
by just people typing CAPTCHAs on the Internet.
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(Aplauz)
05:25
(Applause)
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05:32
Now, of course,
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Naravno, budući da
05:34
since we're doing so many words per day,
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uradimo toliko reči u toku jednog dana,
dešavaju se razne smešne stvari.
05:37
funny things can happen.
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05:38
This is especially true because now we're giving people
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I ovo je tako jer dajemo ljudima
dve slučajno odabrane engleske reči jednu do druge.
05:41
two randomly chosen English words next to each other.
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Pa se dese smešne stvari.
05:43
So funny things can happen.
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Na primer, pojavila se ova reč -
05:45
For example, we presented this word.
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To je reč "Hrišćani" i nema tu ništa loše.
05:47
It's the word "Christians"; there's nothing wrong with it.
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Ali ako je uparite sa drugom slučajno odabranom reči,
05:49
But if you present it along with another randomly chosen word,
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mogu se desiti loše kombinacije.
05:52
bad things can happen.
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Dakle dobili smo ovo. (Tekst: loši hrišćani)
05:54
So we get this.
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05:55
[bad Christians]
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Ali, najgore od svega je što se sve ovo desilo na sajtu
05:56
But it's even worse, because the website where we showed this
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koji se zove "Ambasada kraljevstva božijeg".
05:59
actually happened to be called The Embassy of the Kingdom of God.
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(Smeh)
06:02
(Laughter)
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Ups.
06:04
Oops.
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06:05
(Laughter)
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(Smeh)
Evo još jednog lošeg primera.
06:09
Here's another really bad one.
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DžonEdvards.com
06:11
JohnEdwards.com
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06:12
[Damn liberal]
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(Tekst: Prokleti liberal)
06:13
(Laughter)
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(Smeh)
Tako da svakodnevno vređamo ljude i desne i leve orijentacije.
06:18
So we keep on insulting people left and right everyday.
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Naravno, nije samo da ih vređamo.
06:21
Of course, we're not just insulting people.
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Budući da su reči slučajno uparene,
06:23
Here's the thing. Since we're presenting two randomly chosen words,
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mogu se desiti i interesantne stvari.
06:26
interesting things can happen.
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06:27
So this actually has given rise to a really big Internet meme
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Ovo je dovelo do
velikog internet fenomena
06:32
that tens of thousands of people have participated in,
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u kom su učestvovale na hiljade ljudi,
a koji se zove CAPTCHA umetnost.
06:35
which is called CAPTCHA art.
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06:36
I'm sure some of you have heard about it.
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Siguran sam da su neki od vas čuli za to.
06:38
Here's how it works.
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Evo kako radi.
06:40
Imagine you're using the Internet and you see a CAPTCHA
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Zamislite da surfujete internetom i vidite CAPTCHA
06:42
that you think is somewhat peculiar,
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za koj mislite da je jedinstven,
06:44
like this CAPTCHA.
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kao na primer ovaj CAPTCHA (Tekst: nevidljivi toster)
06:45
[invisible toaster]
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06:46
What you're supposed to do is you take a screenshot of it.
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Ono što bi trebalo da uradite je da sačuvate sliku sa ekrana.
A onda naravno popunite CAPTCHA
06:49
Then of course, you fill out the CAPTCHA because you help us digitize a book.
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jer nam tako pomažete da digitalizujemo knjige.
Ali prvo sačuvate tu sliku,
06:53
But first you take a screenshot
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06:54
and then you draw something that is related to it.
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i onda docrtate nešto što je u vezi sa tim.
(Smeh)
06:57
(Laughter)
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06:58
That's how it works.
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Tako to funkcioniše.
07:00
(Laughter)
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07:01
There are tens of thousands of these.
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Postoje na desetine hiljada ovoga.
07:04
Some of them are very cute.
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Neke od njih su veoma simpatične. (Tekst: stegnuo sam ga)
07:06
[clenched it]
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(Smeh)
07:07
(Laughter)
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Neke su smešnije.
07:09
Some of them are funnier.
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(Tekst: drogirani osnivači)
07:11
[stoned Founders]
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07:12
(Laughter)
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(Smeh)
07:16
And some of them, like paleontological shvisle ...
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A neke od njih,
kao "paleontološki švizl",
07:20
(Laughter)
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imaju Snup Doga.
07:22
they contain Snoop Dogg.
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07:23
(Laughter)
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(Smeh)
07:26
OK, so this is my favorite number of reCAPTCHA.
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Ok, ovo je moj omiljeni broj reCAPTCHA-e.
Ovo je nešto što mi se najviše sviđa u vezi sa celim projektom.
07:29
So this is the favorite thing that I like about this whole project.
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Ovo je broj različitih ljudi
07:32
This is the number of distinct people
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koji su nam pomogli da digitalizujemo makar jednu reč neke knjige kroz reCAPTCHA:
07:34
that have helped us digitize at least one word out of a book through reCAPTCHA:
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750 miliona
07:37
750 million, a little over 10 percent of the world's population,
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što znači da nam je oko 10 odsto celokupne svetske populacije
07:40
has helped us digitize human knowledge.
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pomoglo da digitalizujemo ljudsko znanje.
07:42
And it is numbers like these that motivate my research agenda.
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Ovo je jedan od brojeva koji me motivišu da istražujem dalje.
07:45
So the question that motivates my research is the following:
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Dakle pitanje koje me motiviše da nastavim je sledeće:
ako posmatrate grupna dostignuća čovečanstva,
07:49
If you look at humanity's large-scale achievements,
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one zaista velike stvari
07:51
these really big things
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07:52
that humanity has gotten together and done historically --
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oko kojih se čovečanstvo okupilo i uradilo nešto
07:55
like, for example, building the pyramids of Egypt
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kao, na primer, gradnju piramida u Egiptu
07:57
or the Panama Canal
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ili Panamskog kanala
07:59
or putting a man on the Moon --
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ili slanje čoveka na Mesec --
08:01
there is a curious fact about them,
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zanimljiva činjenica u vezi sa njima je
08:03
and it is that they were all done with about the same number of people.
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da su svi bili urađeni sa otprilike istim brojem ljudi.
Čudno; svi oni su sprovedeni sa oko 100.000 ljudi.
08:06
It's weird; they were all done with about 100,000 people.
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A razlog za to je što je pre postojanja interneta
08:09
And the reason for that is because, before the Internet,
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koordinisanje više od 100.000 ljudi,
08:12
coordinating more than 100,000 people,
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a kamoli plaćanje, bilo prosto nemoguće.
08:14
let alone paying them, was essentially impossible.
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Ali sada, uz pomoć interneta, upravo sam vam pokazao projekat
08:17
But now with the Internet, I've just shown you a project
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gde smo okupili 750 miliona ljudi
08:19
where we've gotten 750 million people to help us digitize human knowledge.
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koji su nam pomogli da digitalizujemo ljudsko znanje.
Dakle, ono što me motiviše prilikom istraživanja je,
08:23
So the question that motivates my research is,
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što ako sa 100.000 možemo da pošaljemo čoveka na Mesec
08:25
if we can put a man on the Moon with 100,000,
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08:27
what can we do with 100 million?
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šta tek možemo da uradimo sa 100 miliona?
08:29
So based on this question,
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I tako bazirano na ovom pitanju
08:31
we've had a lot of different projects that we've been working on.
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počeli smo da radimo na mnogo različitih projekata.
Pričaću vam o jednom oko kog sam najviše uzbuđen.
08:34
Let me tell you about one that I'm most excited about.
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08:36
This is something that we've been semiquietly working on
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To je nešto na čemu radimo polutajno
u poslednjih godinu i po dana.
08:39
for the last year and a half or so.
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Još ga nismo lansirali. Zove se Duolingo.
08:41
It hasn't yet been launched. It's called Duolingo.
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Budući da nije lansiram, psssst!
08:43
Since it hasn't been launched, shhh!
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(Smeh)
08:45
(Laughter)
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08:46
Yeah, I can trust you'll do that.
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Da, verujem da ćete ćutati.
Dakle ovo je projekat. Evo kako je počeo.
08:49
So this is the project. Here's how it started.
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Počeo je tako što sam postavio pitanje mom studentu,
08:51
It started with me posing a question to my graduate student, Severin Hacker.
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Severinu Hakeru.
Ok, ovo je Severin Haker.
08:55
OK, that's Severin Hacker.
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Dakle, postavio sam mu pitanje.
08:57
So I posed the question to my graduate student.
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Usput, dobro ste čuli,
08:59
By the way, you did hear me correctly; his last name is Hacker.
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njegovo prezime je Haker.
09:02
(Laughter)
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Pitao sam ga: kako možemo
09:03
So I posed this question to him: How can we get 100 million people
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da postignemo da nam 100 miliona ljudi
09:06
translating the web into every major language for free?
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prevede internet na svaki važniji svetski jezik, besplatno?
Ok, prvo moram nešto da kažem o ovom problemu.
09:10
There's a lot of things to say about this question.
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Prvo, prevod interneta.
09:12
First of all, translating the web.
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Trenutno je internet podeljen na mnogo jezika.
09:14
Right now, the web is partitioned into multiple languages.
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Veliki deo je na engleskom.
09:17
A large fraction of it is in English.
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Ako ne znate engleski, ne možete pristupiti podacima.
09:19
If you don't know English, you can't access it.
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Ali postoje i veliki delovi na drugim jezicima,
09:21
But there's large fractions in other different languages,
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i ako ne znate te druge jezike, ne možete pristupiti.
09:24
and if you don't know them, you can't access it.
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Dakle, voleo bih da prevedem ceo internet, ili makar njegov veliki deo,
09:26
So I would like to translate all of the web,
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09:28
or at least most of it, into every major language.
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na svaki važan jezik.
To bih voleo da uradim.
09:31
That's what I would like to do.
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09:32
Now, some of you may say, why can't we use computers to translate?
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Sada neki od vas mogu reći, ali zašto ne kortistite kompjutere za prevod?
Zašto ne koristimo mašine za prevod?
09:37
Machine translation is starting to translate
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Kompjutersko prevođenje prevede tu i tamo poneku rečenicu.
09:39
some sentences here and there.
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Zašto ih ne koristimo da prevedu ceo internet?
09:40
Why can't we use it to translate the web?
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Problem je što i dalje nisu dovoljno dobri,
09:42
The problem with that is it's not yet good enough
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i verovatno neće biti u narednih 15 ili 20 godina.
09:45
and it probably won't be for the next 15 to 20 years.
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Prave mnogo grešaka.
09:47
It makes a lot of mistakes. Even when it doesn't,
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Čak i kada ne naprave grešku,
09:49
since it makes so many mistakes, you don't know whether to trust it or not.
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budući da ih često prave, kako da znamo kada je prevod tačan a kada ne.
Daću vam primer
09:53
So let me show you an example
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09:54
of something that was translated with a machine.
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nečega što je preveo kompjuter.
Zapravo to je bio post na forumu.
09:57
Actually, it was a forum post.
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09:58
It was somebody who was trying to ask a question about JavaScript.
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Neko ko je pokušavao da pita nešto o jeziku Java.
10:01
It was translated from Japanese into English.
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Bilo je prevedeno sa japanskog na engleski.
10:04
So I'll just let you read.
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Daću vam da pročitate.
10:06
This person starts apologizing
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Osoba počinje izvinjenjem
10:08
for the fact that it's translated with a computer.
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zbog činjenice da se radi o kompjuterskom prevodu.
10:10
So the next sentence is going to be the preamble to the question.
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Dakle sledeća rečenica je uvod u pitanje.
On nešto objašnjava.
10:14
So he's just explaining something.
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Upamtite, pitanje je o Java programskom jeziku.
10:16
Remember, it's a question about JavaScript.
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10:18
[At often, the goat-time install a error is vomit.]
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(Tekst: Na često, koza-vreme instaliranja greška je bljuvanje)
10:20
(Laughter)
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(Smeh)
10:25
Then comes the first part of the question.
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Onda dolazi prvi deo pitanja.
10:29
[How many times like the wind, a pole, and the dragon?]
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(Tekst: Koliko puta kao vetar, motka i zmaj?)
10:32
(Laughter)
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(Smeh)
A onda dolazi moj omiljeni deo pitanja.
10:37
Then comes my favorite part of the question.
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10:39
[This insult to father's stones?]
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(Tekst: Ova uvreda očevom kamenju?)
10:41
(Laughter)
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(Smeh)
A onda dolazi kraj, koji mi je omiljeni deo cele stvari.
10:45
And then comes the ending,
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10:46
which is my favorite part of the whole thing.
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(Tekst: Molimo vas da se izvinite za svoju glupost. Postoje mnoge hvala)
10:48
[Please apologize for your stupidity. There are a many thank you.]
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10:51
(Laughter)
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(Smeh)
10:53
OK, so computer translation, not yet good enough.
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Dobro, znači kompjuterski prevod, još uvek nedovoljno dobar.
Nazad na pitanje.
10:56
So back to the question.
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Trebaju nam ljudi da prevedemo ceo internet.
10:58
So we need people to translate the whole web.
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Sledeće što biste mogli pitati je:
11:01
So now the next question you may have is,
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zašto jednostavno ne platimo ljudima da to urade?
11:03
well, why can't we just pay people to do this?
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Mogli bismo platiti profesionalnim prevodiocima da to urade.
11:05
We could pay professional translators to translate the whole web.
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Mogli bismo.
11:08
We could do that.
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11:09
Unfortunately, it would be extremely expensive.
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Nažalost, to bi bilo preskupo.
11:11
For example, translating a tiny fraction of the whole web, Wikipedia,
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Na primer, prevod samo malog dela interneta, Vikipedije,
u neki drugi jezik, na primer španski,
11:15
into one other language, Spanish.
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11:17
OK? Wikipedia exists in Spanish,
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Vikipedija postoji na španskom,
11:19
but it's very small compared to the size of English.
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ali je veoma mala u poređenju sa onom na engleskom.
Predstavlja oko 20 odsto engleske verzije.
11:22
It's about 20 percent of the size of English.
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Ako bismo hteli da prevedemo na španski tih 80 odsto,
11:24
If we wanted to translate the other 80 percent into Spanish,
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koštalo bi najmanje 50 miliona dolara --
11:27
it would cost at least 50 million dollars --
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i to za najiskorišćeniju zemlju koja postoji.
11:29
and this is even at the most exploited, outsourcing country out there.
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Dakle, bilo bi mnogo skupo.
11:33
So it would be very expensive.
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I zato želimo da u to uključimo 100 miliona ljudi
11:34
So what we want to do is, we want to get 100 million people
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koji će prevesti internet na svaki veći jezik
11:37
translating the web into every major language for free.
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besplatno.
Ako je ovo ono što hoćete da uradite
11:40
If this is what you want to do, you quickly realize
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vrlo brzo shvatate da ćete naići na dve stvari koje će to otežati,
11:42
you're going to run into two big hurdles, two big obstacles.
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dve velike prepreke.
11:45
The first one is a lack of bilinguals.
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Prva je manjak ljudi koji govore dva jezika.
11:48
So I don't even know
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Ni ne znam da li
11:50
if there exists 100 million people out there using the web
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postoje 100 miliona ljudi koji koriste internet
11:53
who are bilingual enough to help us translate.
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koji govore dva jezika dovoljno dobro da nam pomognu sa prevodima.
To je veliki problem.
11:56
That's a big problem.
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11:57
The other problem you're going to run into is a lack of motivation.
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Drugi problem je nedostatak motivacije.
Kako ćemo motivisati ljude
12:00
How are we going to motivate people to actually translate the web for free?
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da zaista prevedu internet besplatno?
Obično platite ljudima za to.
12:04
Normally, you have to pay people to do this.
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12:06
So how are we going to motivate them to do it for free?
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Kako ćemo ih onda motivisati da to urade besplatno?
Kada smo počeli da razmišljamo o svemu, ove dve stvari su nas kočile.
12:09
When we were starting to think about this, we were blocked by these two things.
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Ali onda smo shvatili da postoji način
12:12
But then we realized, there's a way
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i da postoji jedno rešenje za oba problema.
12:14
to solve both these problems with the same solution.
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Jednim udarcem ćemo ubiti dve muve.
12:16
To kill two birds with one stone.
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A to je da prevođenje pretvorimo u nešto
12:18
And that is to transform language translation
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12:20
into something that millions of people want to do
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što milioni ljudi hoće da rade
12:23
and that also helps with the problem of lack of bilinguals,
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i to nam takođe pomaže sa problemom manjka bilingvista
12:26
and that is language education.
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a to je učenje jezika.
12:29
So it turns out that today,
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Ispostavilo se da danas
12:31
there are over 1.2 billion people learning a foreign language.
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imate preko 1,2 milijarde ljudi koji uče strani jezik.
Ljudi zaista žele da nauče strane jezike.
12:35
People really want to learn a foreign language.
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I to ne samo zato što ih u školama teraju da to rade.
12:37
And it's not just because they're being forced to do so in school.
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Na primer, samo u SAD
12:40
In the US alone, there are over five million people
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postoji preko pet miliona ljudi koji su platili više od 500 dolara
12:43
who have paid over $500 for software to learn a new language.
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za softvere za učenje stranih jezika.
Dakle ljudi zaista žele da nauče nove jezike.
12:46
So people really want to learn a new language.
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Tako smo u poslednjih godinu i po dana radili na novom sajtu
12:48
So what we've been working on for the last year and a half
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zove se Duolingo --
12:51
is a new website -- it's called Duolingo --
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gde je osnovna ideja da ljudi besplatno uče jezik
12:53
where the basic idea is people learn a new language for free
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12:55
while simultaneously translating the web.
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dok istovremeno prevode internet.
I zapravo oni uče dok prevode.
12:58
And so basically, they're learning by doing.
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Način na koji ovo radi
13:00
So the way this works
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13:01
is whenever you're a just a beginner, we give you very simple sentences.
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je da, dok ste tek početnik, dobijate veoma jednostavne rečenice.
Naravno, na internetu ih ima mnogo.
13:05
There's a lot of very simple sentences on the web.
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Damo vam veoma, veoma jednostavne rečenice
13:07
We give you very simple sentences along with what each word means.
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zajedno sa značenjem svake reči.
13:10
And as you translate them
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I dok ih prevodite i dok vidite kako ih drugi prevode,
13:12
and as you see how other people translate them,
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počinjete da učite jezik.
13:14
you start learning the language.
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Sa vašim napretkom
13:16
And as you get more advanced,
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13:17
we give you more complex sentences to translate.
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dajemo vam sve kompleksnije rečenice na prevod.
13:19
But at all times, you're learning by doing.
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Ali sve vreme učite dok radite.
13:21
Now, the crazy thing about this method is that it actually really works.
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Luda stvar u vezi sa ovim metodom
je da on zapravo funkcioniše.
13:25
People are really learning a language.
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Prvo, ljudi zaista uče jezik.
13:27
We're mostly done building it and now we're testing it.
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Projekat je gotovo završen i sada je u fazi testiranja.
Ljudi tako zaista mogu naučiti jezik.
13:30
People really can learn a language with it.
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I nauče ga jednako dobro kao uz pomoć vodećih programa za učenje jezika.
13:32
And they learn it about as well as the leading language learning software.
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Dakle, ljudi zaista nauče jezik.
13:35
So people really do learn a language.
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I ne samo da ga nauče,
13:37
And not only do they learn it as well, but actually it's more interesting.
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već je i mnogo interesantnije.
Jer, uz Duolingo, ljudi uče koristeći realne sadržaje.
13:41
Because with Duolingo, people are learning with real content.
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Nasuprot učenju kroz izmišljene rečenice,
13:44
As opposed to learning with made-up sentences,
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uči se na stvarnim sadržajima, što je samo po sebi zanimljivije.
13:46
people are learning with real content, which is inherently interesting.
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Dakle ljudi zaista uče jezik.
13:49
So people really do learn a language.
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Možda su još više iznenađuje da su
13:51
But perhaps more surprisingly,
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prevodi koje smo dobili od ljudi koji koriste sajt,
13:53
the translations that we get from people using the site,
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13:55
even though they're just beginners,
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iako su početnici,
13:57
the translations that we get
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bili tačni koliko i oni koje su radili profesionalni prevodioci,
13:59
are as accurate as those of professional language translators,
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što je veoma iznenađujuće.
14:01
which is very surprising.
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Daću vam još jedan primer.
14:03
So let me show you one example.
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14:04
This is a sentence that was translated from German into English.
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Ovo je rečenica prevedena sa nemačkog na engleski.
Gore je nemački.
14:07
The top is the German. The middle is an English translation
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U sredini je engleski prevod
14:10
that was done by a professional translator
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koji je uradio profesionalni prevodilac,
14:12
who we paid 20 cents a word for this translation.
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koga plaćamo 20 centi po reči.
A dole je prevod urađen od strane korisnika Duolinga,
14:15
And the bottom is a translation by users of Duolingo,
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od kojih nijedan nije znao ni malo nemačkog
14:18
none of whom knew any German before they started using the site.
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pre nego što su počeli da koriste sajt.
14:21
If you can see, it's pretty much perfect.
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Možete i sami videti, savršeno je.
14:23
Of course, we play a trick here
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Naravno, ovde koristimo trik
14:25
to make the translations as good as professional language translators.
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da bi prevodi bili dobri koliko i profesionalni.
Kombinujemo prevode više početnika
14:28
We combine the translations of multiple beginners
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kako bismo dobili kvalitet jednog profesionalca.
14:31
to get the quality of a single professional translator.
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14:33
Now, even though we're combining the translations,
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Iako kombinujemo prevode
14:38
the site actually can translate pretty fast.
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sajt se prevodi prilično brzo.
Pokazaću vam,
14:41
So let me show you,
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14:42
this is our estimates of how fast we could translate Wikipedia
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naše procene koliko brzo možemo da prevedemo Vikipediju
sa engleskog na španski.
14:45
from English into Spanish.
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14:46
Remember, this is 50 million dollars' worth of value.
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Zapamtite, to košta 50 miliona dolara.
14:49
So if we wanted to translate Wikipedia into Spanish,
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Dakle, ako bismo hteli da prevedemo Vikipediju na španski,
mogli bismo to uraditi za pet nedelja sa 100.000 aktivnih korisnika.
14:52
we could do it in five weeks with 100,000 active users.
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I mogli bismo to uraditi za 80 sati sa milion aktivnih korisnika.
14:55
And we could do it in about 80 hours with a million active users.
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Budući da su svi projekti na kojima je moja grupa radila uspeli da uključe milione korisnika
14:58
Since all the projects my group has worked on so far
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15:00
have gotten millions of users,
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nadamo se da ćemo kroz ovaj projekat uspeti da prevodimo
15:02
we're hopeful that we'll be able to translate extremely fast.
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uspeti da prevodimo prilično brzo.
Sada, stvar oko koje sam najuzbuđeniji oko Duolinga
15:05
Now, the thing that I'm most excited about with Duolingo
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je što mislim da obezbeđuje fer biznis model za učenje jezika.
15:08
is I think this provides a fair business model for language education.
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Evo o čemu se radi:
15:11
So here's the thing:
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trenutni model za učenje stranih jezika
15:13
The current business model for language education
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je takav da student plaća,
15:15
is the student pays,
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15:16
and in particular, the student pays Rosetta Stone 500 dollars.
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i na primer, učenik plaća za Rozeta Stoun 500 dolara.
(Smeh)
15:19
(Laughter)
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To je postojeći model poslovanja.
15:21
That's the current business model.
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Problem sa tim je što
15:23
The problem with this business model
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95 odsto svetske populacije nema 500 dolara.
15:25
is that 95 percent of the world's population doesn't have 500 dollars.
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Tako da je potpuno nefer prema siromašnima.
15:28
So it's extremely unfair towards the poor.
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Totalno je usmereno na bogate.
15:31
This is totally biased towards the rich.
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A u Duolingu
15:33
Now, see, in Duolingo,
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15:34
because while you learn, you're actually creating value,
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dok učite
zapravo stvarate vrednost, prevodite stvari --
15:38
you're translating stuff --
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15:39
which, for example, we could charge somebody for translations,
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za šta bismo mogli da nekog platimo.
15:42
so this is how we could monetize this.
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Ovo je način da to unovčimo.
15:44
Since people are creating value while they're learning,
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Budući da ljudi stvaraju vrednost dok uče
oni ne moraju da plate svojim novcem, već plaćaju svojim vremenom.
15:47
they don't have to pay with their money, they pay with their time.
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Ali magična stvar je da oni plaćaju svojim vremenom,
15:50
But the magical thing here
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15:52
is that is time that would have had to have been spent anyways
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a to je vreme koje bi bilo potrošeno svakako
na učenje jezika.
15:55
learning the language.
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15:56
So the nice thing about Duolingo
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Dakle, dobra stvar kod Duolinga je da obezbeđuje fer biznis model --
15:58
is, I think, it provides a fair business model --
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koji ne diskriminiše siromašne.
16:00
one that doesn't discriminate against poor people.
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Evo i sajta. Hvala.
16:03
So here's the site. Thank you.
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(Aplauz)
16:04
(Applause)
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Evo ga i sajt.
16:13
We haven't yet launched,
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Nije još pušten u rad,
16:15
but if you go there, you can sign up to be part of our private beta,
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ali ako ga posetite možete sa upisati kako biste bili deo naše "private beta"
16:18
which is probably going to start in three or four weeks.
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koja će sigurno početi za tri ili četiri nedelje.
Nismo još lansirali ovaj Duolingo.
16:21
We haven't yet launched it.
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16:22
By the way, I'm the one talking here,
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Usput, ja ovde pričam,
16:24
but Duolingo is the work of a really awesome team,
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ali zapravo Duolingo je proizvod zaista fenomenalnog tima, a neki od njih su ovde.
16:27
some of whom are here. So thank you.
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Hvala vam.
16:28
(Applause)
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(Aplauz)
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

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