Fake videos of real people -- and how to spot them | Supasorn Suwajanakorn

1,288,447 views ・ 2018-07-25

TED


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

Prevodilac: Stevan Stanišić Lektor: Tijana Mihajlović
00:12
Look at these images.
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Pogledajte ove slike.
00:14
Now, tell me which Obama here is real.
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A sad, recite mi koji Obama je pravi.
00:16
(Video) Barack Obama: To help families refinance their homes,
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(Video) Barak Obama: Da pomognemo porodicama s refinansiranjem domova,
00:19
to invest in things like high-tech manufacturing,
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da uložimo u stvari kao što su visoko-tehnološka proizvodnja,
00:22
clean energy
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čista energija i infrastruktura koja stvara dobre nove poslove.
00:23
and the infrastructure that creates good new jobs.
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00:26
Supasorn Suwajanakorn: Anyone?
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Supasorn Suvanjakorn: Bilo ko?
00:28
The answer is none of them.
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Odgovor je: nijedan od njih.
00:30
(Laughter)
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(Smeh)
00:31
None of these is actually real.
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Nijedan od ovih zapravo nije pravi.
Dozvolite da objasnim kako smo dospeli ovde.
00:33
So let me tell you how we got here.
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00:35
My inspiration for this work
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Moja inspiracija za ovaj posao bio je projekat
00:37
was a project meant to preserve our last chance for learning about the Holocaust
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namenjen očuvanju naše poslednje šanse za saznanje o holokaustu od preživelih.
00:42
from the survivors.
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00:44
It's called New Dimensions in Testimony,
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Zove se „Nove dimenzije u svedočenju“
00:47
and it allows you to have interactive conversations
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i dozvoljava vam da vodite interaktivne razgovore
00:50
with a hologram of a real Holocaust survivor.
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sa hologramom pravog preživelog iz holokausta.
00:53
(Video) Man: How did you survive the Holocaust?
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(Video) Čovek: Kako ste preživeli holokaust?
00:55
(Video) Hologram: How did I survive?
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(Video) Hologram: Kako sam preživeo?
00:57
I survived,
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Preživeo sam,
01:00
I believe,
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verujem,
01:01
because providence watched over me.
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zato što je proviđenje bdelo nada mnom.
01:05
SS: Turns out these answers were prerecorded in a studio.
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SS: Ispostavlja se da su ovi odgovori unapred snimljeni u studiju.
01:09
Yet the effect is astounding.
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Pa ipak, efekat je zapanjujuć.
01:11
You feel so connected to his story and to him as a person.
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Osećate se privrženo njegovoj priči i njemu kao osobi.
01:16
I think there's something special about human interaction
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Mislim da postoji nešto posebno u vezi sa ljudskom interakcijom
01:19
that makes it much more profound
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što je čini mnogo dubljom
01:22
and personal
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i ličnijom
01:24
than what books or lectures or movies could ever teach us.
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nego što bi knjige, predavanja ili filmovi ikada mogli da nas nauče.
01:28
So I saw this and began to wonder,
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Dakle, video sam ovo i počeo da se pitam:
01:30
can we create a model like this for anyone?
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da li možemo da napravimo ovakav model za bilo koga?
01:33
A model that looks, talks and acts just like them?
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Model koji izgleda, priča i ponaša se baš kao oni?
01:37
So I set out to see if this could be done
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Pokrenuo sam se da vidim da li je izvodljivo
01:39
and eventually came up with a new solution
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i naposletku došao do novog rešenja
01:41
that can build a model of a person using nothing but these:
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koje može da napravi model osobe koristeći ništa drugo osim ovoga:
01:45
existing photos and videos of a person.
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postojećih fotografija i snimaka osobe.
01:48
If you can leverage this kind of passive information,
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Ako možete da iskoristite ovu vrstu pasivnih informacija,
01:51
just photos and video that are out there,
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samo dostupne fotografije i snimke,
01:53
that's the key to scaling to anyone.
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to je ključno za primenu na svakoga.
01:56
By the way, here's Richard Feynman,
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Uzgred, evo Ričarda Fajnmana,
01:57
who in addition to being a Nobel Prize winner in physics
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ko je uz to što je osvojio Nobelovu nagradu za fiziku,
02:01
was also known as a legendary teacher.
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takođe bio poznat kao legendaran predavač.
02:05
Wouldn't it be great if we could bring him back
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Zar ne bi bilo sjajno kada bismo mogli da ga vratimo
02:07
to give his lectures and inspire millions of kids,
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da drži svoja predavanja i inspiriše milione klinaca,
02:10
perhaps not just in English but in any language?
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možda čak ne samo na engleskom, već na bilo kom jeziku?
02:14
Or if you could ask our grandparents for advice and hear those comforting words
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Ili ako biste mogli da pitate naše bake i deke za savet i čujete utešne reči
02:19
even if they're no longer with us?
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čak i ako više nisu s nama?
02:21
Or maybe using this tool, book authors, alive or not,
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Ili bi možda korišćenjem ovog alata pisci knjiga, živi ili ne,
02:25
could read aloud all of their books for anyone interested.
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naglas mogli da čitaju sve svoje knjige za sve zainteresovane.
02:29
The creative possibilities here are endless,
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Kreativne mogućnosti za ovo su beskrajne,
02:31
and to me, that's very exciting.
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i za mene, to je vrlo uzbudljivo.
02:34
And here's how it's working so far.
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A evo kako to radi za sad.
02:36
First, we introduce a new technique
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Prvo, uvodimo novu tehniku
02:38
that can reconstruct a high-detailed 3D face model from any image
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koja može da rekonstruiše veoma detaljan 3D model lica
sa bilo koje slike,
02:42
without ever 3D-scanning the person.
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bez ikakvog 3D skeniranja osobe.
02:45
And here's the same output model from different views.
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Evo istog izlaznog modela iz različitih uglova.
02:49
This also works on videos,
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Ovo funkcioniše i na snimcima,
02:51
by running the same algorithm on each video frame
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korišćenjem istog algoritma na svakoj slici snimka
02:54
and generating a moving 3D model.
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i generisanjem pokretnog 3D modela.
02:57
And here's the same output model from different angles.
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Evo istog izlaznog modela iz različitih uglova.
03:01
It turns out this problem is very challenging,
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Ispostavlja se da je ovo veoma problematično,
03:04
but the key trick is that we are going to analyze
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ali ključni trik leži u tome
da ćemo unapred analizirati veliku zbirku fotografija osobe.
03:07
a large photo collection of the person beforehand.
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03:10
For George W. Bush, we can just search on Google,
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Za Džordža V. Buša možemo prosto da potražimo na Guglu
03:14
and from that, we are able to build an average model,
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i iz toga, u stanju smo da napravimo prosečan model,
03:16
an iterative, refined model to recover the expression
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iterativan, prerađen model
da povratimo izraz u finim detaljima, kao što su brazde i bore.
03:19
in fine details, like creases and wrinkles.
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03:23
What's fascinating about this
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Ono što je fascinantno kod ovoga je
03:24
is that the photo collection can come from your typical photos.
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da zbirka fotografija može nastati od vaših tipičnih fotografija.
03:28
It doesn't really matter what expression you're making
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Nije stvarno bitno kakav izraz imate
03:30
or where you took those photos.
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ili gde ste snimili fotografije.
03:32
What matters is that there are a lot of them.
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Ono što je bitno je da ih ima mnogo.
03:35
And we are still missing color here,
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A ovde nam još uvek fali boja,
03:36
so next, we develop a new blending technique
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pa dalje razvijamo novu tehniku mešanja
03:39
that improves upon a single averaging method
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koja koristi samo jednu metodu uprosečavanja
03:42
and produces sharp facial textures and colors.
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i proizvodi jasne teksture lica i boje.
03:45
And this can be done for any expression.
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A ovo može da se uradi za bilo koji izraz.
03:49
Now we have a control of a model of a person,
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Sada imamo kontrolu nad modelom osobe,
03:52
and the way it's controlled now is by a sequence of static photos.
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a način na koji se sada kontroliše je preko niza nepokretnih fotografija.
03:55
Notice how the wrinkles come and go, depending on the expression.
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Obratite pažnju na to kako se bore pojavljuju i nestaju
u zavisnosti od izraza.
04:00
We can also use a video to drive the model.
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Možemo da koristimo i snimak da upravljamo modelom.
04:02
(Video) Daniel Craig: Right, but somehow,
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(Video) Danijel Krejg: Da, ali nekako smo uspeli
04:05
we've managed to attract some more amazing people.
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da privučemo neke još neverovatnije ljude.
04:10
SS: And here's another fun demo.
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SS: A evo još jednog zabavnog demo snimka.
04:11
So what you see here are controllable models
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Ovde vidite upravljive modele ljudi,
04:13
of people I built from their internet photos.
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koje sam napravio iz njihovih internet fotografija.
04:16
Now, if you transfer the motion from the input video,
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Sada, ako se prebaci pokret sa ulaznog snimka
04:19
we can actually drive the entire party.
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zapravo možemo da upravljamo celom družinom.
04:21
George W. Bush: It's a difficult bill to pass,
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Džordž V. Buš: „Ovaj nacrt zakona će teško proći
04:23
because there's a lot of moving parts,
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zato što ima mnogo pokretnih delova,
04:26
and the legislative processes can be ugly.
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a proces zakonodavstva ume da bude gadan.“
04:31
(Applause)
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(Aplauz)
04:32
SS: So coming back a little bit,
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SS: Dakle, da se vratim malo unazad,
04:34
our ultimate goal, rather, is to capture their mannerisms
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naš konačni cilj je radije da uhvatimo njihovu mimiku
04:38
or the unique way each of these people talks and smiles.
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ili jedinstven način na koji svako od ovih ljudi priča ili se smeši.
04:41
So to do that, can we actually teach the computer
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Da bismo to uradili, možemo li zaista naučiti računar
04:43
to imitate the way someone talks
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da podražava način na koji neko govori
04:45
by only showing it video footage of the person?
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pokazujući mu samo video snimke osobe?
04:48
And what I did exactly was, I let a computer watch
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Tako sam pustio računaru da gleda
04:51
14 hours of pure Barack Obama giving addresses.
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14 sati isključivo Baraka Obame i njegovih obraćanja.
04:55
And here's what we can produce given only his audio.
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I evo šta možemo da izvedemo samo iz njegovog zvučnog snimka.
04:58
(Video) BO: The results are clear.
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(Video) BO: Rezultati su jasni.
05:00
America's businesses have created 14.5 million new jobs
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Američki biznisi su stvorili 14,5 miliona novih poslova
05:05
over 75 straight months.
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tokom 75 meseci neprekidno.
05:07
SS: So what's being synthesized here is only the mouth region,
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SS: Dakle, ono što se ovde spaja je samo oblast usta,
05:10
and here's how we do it.
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i evo kako to radimo.
05:12
Our pipeline uses a neural network
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Naš sistem koristi neuronsku mrežu
05:14
to convert and input audio into these mouth points.
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da pretvori i dovede audio snimak u ove tačke usta.
05:18
(Video) BO: We get it through our job or through Medicare or Medicaid.
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(Video) BO: Dobijamo to preko našeg posla ili preko zdravstvene zaštite.
05:22
SS: Then we synthesize the texture, enhance details and teeth,
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SS: Tada stvaramo teksturu, poboljšavamo detalje i zube
05:26
and blend it into the head and background from a source video.
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i stapamo u glavu i pozadinu iz izvornog snimka.
05:29
(Video) BO: Women can get free checkups,
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(Video) BO: Žene mogu besplatno da se pregledaju
05:31
and you can't get charged more just for being a woman.
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i ne može vam se naplatiti više samo zato što ste žena.
05:34
Young people can stay on a parent's plan until they turn 26.
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Mladi mogu da ostanu u roditeljskom programu do 26. godine.
05:39
SS: I think these results seem very realistic and intriguing,
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SS: Mislim da ovi rezultati izgledaju vrlo realistično i interesantno,
05:42
but at the same time frightening, even to me.
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ali istovremeno zastrašujuće, čak i za mene.
05:45
Our goal was to build an accurate model of a person, not to misrepresent them.
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Naš cilj je bio da napravimo precizan model osobe,
ne da je pogrešno predstavimo.
05:49
But one thing that concerns me is its potential for misuse.
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Ali, ono što me brine je potencijal za zloupotrebu.
05:53
People have been thinking about this problem for a long time,
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Ljudi su dugo razmišljali o ovom problemu,
05:56
since the days when Photoshop first hit the market.
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još otkad je „Fotošop“ izašao na tržište.
05:59
As a researcher, I'm also working on countermeasure technology,
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Kao istraživač, takođe radim na tehnologiji za protivmeru
06:03
and I'm part of an ongoing effort at AI Foundation,
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i učestvujem u tekućem poduhvatu u fondaciji za veštačku inteligenciju
06:06
which uses a combination of machine learning and human moderators
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gde se koristi kombinacija mašinskog učenja i ljudskih moderatora
06:10
to detect fake images and videos,
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da se otkriju lažne slike i video-snimci,
06:12
fighting against my own work.
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boreći se protiv sopstvenog posla.
06:14
And one of the tools we plan to release is called Reality Defender,
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Jedan od alata koji planiramo da izdamo se zove „Branilac stvarnosti“ -
06:17
which is a web-browser plug-in that can flag potentially fake content
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dodatak za internet pretraživače koji može da označi potencijalno lažne sadržaje
06:21
automatically, right in the browser.
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automatski, direktno u samom pretraživaču.
06:24
(Applause)
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(Aplauz)
06:28
Despite all this, though,
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Uprkos svemu ovome,
06:30
fake videos could do a lot of damage,
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lažni video-snimci mogu da učine dosta štete
06:32
even before anyone has a chance to verify,
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čak i pre nego što iko stigne da ih proveri,
06:35
so it's very important that we make everyone aware
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tako da je vrlo važno da svakoga osvestimo
06:38
of what's currently possible
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o tome šta je trenutno moguće,
06:40
so we can have the right assumption and be critical about what we see.
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tako da možemo pravilno da pretpostavimo i da posmatramo kritički.
06:44
There's still a long way to go before we can fully model individual people
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I dalje smo daleko od toga da možemo potpuno da modelujemo pojedince
06:49
and before we can ensure the safety of this technology.
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i pre nego što osiguramo bezbednost ove tehnologije.
06:53
But I'm excited and hopeful,
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Ali ja sam uzbuđen i pun nade,
06:54
because if we use it right and carefully,
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jer ako ga koristimo na pravi način i pažljivo,
06:58
this tool can allow any individual's positive impact on the world
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ovaj alat može da omogući da pozitivni uticaj ma kog pojedinca na svet
07:02
to be massively scaled
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bude mnogostruko uveličan
07:04
and really help shape our future the way we want it to be.
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i zaista pomogne da oblikujemo budućnost u onakvu kakvu želimo.
07:07
Thank you.
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Hvala vam.
07:08
(Applause)
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(Aplauz)
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