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Alex Wissner-Gross: A new equation for intelligence
Aleks Visner-Gros (Alex Wissner-Gross): Nova jednačina za inteligenciju
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Da li postoji jednačina za inteligenciju? Da. To je F = T ∇ Sτ. U fascinantnom i informativnom govoru, fizičar i kompjuterski naučnik Aleks Visner-Gros objašnjava šta to, dođavola, znači. (Snimljeno na TEDxBeaconStreet.)
Alex Wissner-Gross - Scientist, entrepreneur, inventor
Alex Wissner-Gross applies science and engineering principles to big (and diverse) questions, like: "What is the equation for intelligence?" and "What's the best way to raise awareness about climate change?" Full bio
Alex Wissner-Gross applies science and engineering principles to big (and diverse) questions, like: "What is the equation for intelligence?" and "What's the best way to raise awareness about climate change?" Full bio
Double-click the English transcript below to play the video.
00:12
Intelligence -- what is it?
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Inteligencija - šta je to?
00:16
If we take a look back at the history
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Ako pogledamo unazad kroz istoriju
00:18
of how intelligence has been viewed,
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kako su videli inteligenciju,
00:21
one seminal example has been
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jedan važan primer je bio
00:25
Edsger Dijkstra's famous quote that
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poznati citat Edsgara Dajkstre:
00:28
"the question of whether a machine can think
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"Pitanje da li mašina može da misli
00:31
is about as interesting
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je isto tako zanimljivo
00:32
as the question of whether a submarine
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kao i pitanje da li podmornica
00:35
can swim."
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može da pliva."
00:37
Now, Edsger Dijkstra, when he wrote this,
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Kad je Edsgar Dajkstra napisao ovo,
00:41
intended it as a criticism
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nameravao je da to bude kritika
00:43
of the early pioneers of computer science,
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pionira u kompjuterskoj nauci
00:46
like Alan Turing.
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kao što je Alan Tjuring.
00:48
However, if you take a look back
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Međutim, ako pogledate u prošlost
00:50
and think about what have been
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i razmislite koje su bile
00:52
the most empowering innovations
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najvažnije inovacije
00:54
that enabled us to build
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koje su nam omogućile da pravimo
00:56
artificial machines that swim
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veštačke mašine koje plivaju
00:58
and artificial machines that [fly],
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i veštačke mašine koje lete,
01:01
you find that it was only through understanding
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otkrićete da smo samo
pomoću razumevanja
pomoću razumevanja
01:05
the underlying physical mechanisms
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fizičkih mehanizama koji čine osnovu
01:07
of swimming and flight
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plivanja i letenja
01:10
that we were able to build these machines.
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mogli da napravimo ove mašine.
01:13
And so, several years ago,
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I tako, pre nekoliko godina,
01:15
I undertook a program to try to understand
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sproveo sam program
da bih pokušao da razumem
da bih pokušao da razumem
01:19
the fundamental physical mechanisms
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fizičke mehanizme
01:21
underlying intelligence.
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koji čine osnovu inteligencije.
01:24
Let's take a step back.
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Hajde da se vratimo korak unazad.
01:26
Let's first begin with a thought experiment.
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Da počnemo prvo sa
misaonim eksperimentom.
misaonim eksperimentom.
01:29
Pretend that you're an alien race
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Zamislite da ste vanzemaljska rasa
01:32
that doesn't know anything about Earth biology
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koja ne zna ništa o biologiji Zemlje
01:35
or Earth neuroscience or Earth intelligence,
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ili o neuronauci Zemlje
ili o Zemljinoj inteligenciji,
ili o Zemljinoj inteligenciji,
01:38
but you have amazing telescopes
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ali imate neverovatne teleskope
01:40
and you're able to watch the Earth,
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i možete da posmatrate Zemlju
01:43
and you have amazingly long lives,
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i imate neverovatno duge živote,
01:45
so you're able to watch the Earth
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tako da možete da posmatrate Zemlju
01:46
over millions, even billions of years.
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milonima ili čak milijardama godina.
01:50
And you observe a really strange effect.
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I primećujete veoma čudan efekat.
01:53
You observe that, over the course of the millennia,
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Primećujete da je tokom milenijuma
01:57
Earth is continually bombarded with asteroids
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Zemlja konstantno
bombardovana asteroidima
bombardovana asteroidima
02:02
up until a point,
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sve do jednog momenta
02:04
and that at some point,
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i da u jednom momentu
02:05
corresponding roughly to our year, 2000 AD,
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koji odgovara, po gruboj proceni,
našoj 2000. godini,
našoj 2000. godini,
02:09
asteroids that are on
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asteroidi koji su na putu
02:11
a collision course with the Earth
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da se sudare sa Zemljom,
02:13
that otherwise would have collided
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koji bi inače udarili,
02:15
mysteriously get deflected
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misteriozno bivaju skrenuti
02:17
or they detonate before they can hit the Earth.
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ili eksplodiraju pre
nego što udare u Zemlju.
nego što udare u Zemlju.
02:20
Now of course, as earthlings,
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Naravno, kao Zemljani
02:23
we know the reason would be
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znamo da je razlog to
02:24
that we're trying to save ourselves.
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što pokušavamo da se spasemo.
02:26
We're trying to prevent an impact.
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Pokušavamo da sprečimo udarac.
02:29
But if you're an alien race
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Ali ako ste vanzemaljska rasa
02:31
who doesn't know any of this,
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koja ne zna ništa od ovoga,
02:32
doesn't have any concept of Earth intelligence,
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nema nikakvu ideju
o inteligenciji na Zemlji,
o inteligenciji na Zemlji,
02:34
you'd be forced to put together
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bili biste prisiljeni da smislite
02:36
a physical theory that explains how,
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fizičku teoriju koja objašnjava kako
02:39
up until a certain point in time,
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do određenog trenutka u vremenu
02:41
asteroids that would demolish the surface of a planet
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asteroidi koji bi
uništili površinu planete
uništili površinu planete
02:46
mysteriously stop doing that.
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misteriozno ne učine to.
02:49
And so I claim that this is the same question
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Tvrdim da je ovo isto pitanje
02:53
as understanding the physical nature of intelligence.
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kao i razumevanje
fizičke prirode inteligencije.
fizičke prirode inteligencije.
02:57
So in this program that I
undertook several years ago,
undertook several years ago,
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U ovom programu koji sam
sproveo pre nekoliko godina
sproveo pre nekoliko godina
03:01
I looked at a variety of different threads
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video sam raznovrsne tragove
03:04
across science, across a variety of disciplines,
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u nauci, u raznovrsnim disciplinama
03:07
that were pointing, I think,
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koji su ukazivali, ja mislim,
03:09
towards a single, underlying mechanism
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na jedan mehanizam
koji je u osnovi
koji je u osnovi
03:12
for intelligence.
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inteligencije.
03:13
In cosmology, for example,
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U kosmologiji, na primer,
03:16
there have been a variety of
different threads of evidence
different threads of evidence
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bilo je mnoštvo različitih
tragova dokaza
tragova dokaza
03:18
that our universe appears to be finely tuned
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da je naš svemir, izgleda,
lepo naštimovan
lepo naštimovan
03:22
for the development of intelligence,
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za razvoj inteligencije
03:24
and, in particular, for the development
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i posebno, za razvoj
03:26
of universal states
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univerzalnih stanja
03:28
that maximize the diversity of possible futures.
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koja maksimiziraju raznolikost
mogućih budućnosti.
mogućih budućnosti.
03:32
In game play, for example, in Go --
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U igrama na primer, u igri Go -
03:35
everyone remembers in 1997
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svi se sećaju kada je 1997.
03:38
when IBM's Deep Blue beat
Garry Kasparov at chess --
Garry Kasparov at chess --
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IBM-ov "Dip blu" pobedio
Garija Kasparova u šahu -
Garija Kasparova u šahu -
03:42
fewer people are aware
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manje ljudi je svesno činjenice
03:43
that in the past 10 years or so,
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da je u poslednjih 10 godina,
03:45
the game of Go,
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igra Go,
03:46
arguably a much more challenging game
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možda mnogo izazovnija igra od šaha
03:48
because it has a much higher branching factor,
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jer ima mnogo veći faktor grananja,
03:51
has also started to succumb
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takođe počela da se predaje
03:53
to computer game players
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pred igračima kompjuterskih igara
03:54
for the same reason:
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iz istog razloga:
03:56
the best techniques right now
for computers playing Go
for computers playing Go
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trenutno, najbolje tehnike
za kompjutere koji igraju Go
za kompjutere koji igraju Go
03:59
are techniques that try to maximize future options
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su tehnike koje pokušavaju
da maksimiziraju buduće opcije
da maksimiziraju buduće opcije
04:02
during game play.
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tokom igre.
04:04
Finally, in robotic motion planning,
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Na kraju, u planiranju
robotskih pokreta
robotskih pokreta
04:08
there have been a variety of recent techniques
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postoji mnoštvo novih tehnika
04:10
that have tried to take advantage
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koje pokušavaju da iskoriste
04:12
of abilities of robots to maximize
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mogućnosti robota da maksimiziraju
04:15
future freedom of action
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buduću slobodu delovanja
04:17
in order to accomplish complex tasks.
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da bi obavili složene zadatke.
04:20
And so, taking all of these different threads
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I tako, ako uzmemo sve
ove različite tragove
ove različite tragove
04:22
and putting them together,
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i sastavimo ih,
04:24
I asked, starting several years ago,
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počeo sam da pitam
pre nekoliko godina,
pre nekoliko godina,
04:27
is there an underlying mechanism for intelligence
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da li postoji mehanizam
u osnovi inteligencije
u osnovi inteligencije
04:29
that we can factor out
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koji možemo da izdvojimo
04:31
of all of these different threads?
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od svih ovih različitih tragova?
04:33
Is there a single equation for intelligence?
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Da li postoji jedna jednačina
za inteligenciju?
za inteligenciju?
04:37
And the answer, I believe, is yes.
["F = T ∇ Sτ"]
["F = T ∇ Sτ"]
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I odgovor je, ja mislim, da.
["F = T ∇ Sτ"]
["F = T ∇ Sτ"]
04:41
What you're seeing is probably
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Ono što vidite je verovatno
04:43
the closest equivalent to an E = mc²
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najbliži ekvivalent E = mc²
04:46
for intelligence that I've seen.
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za inteligenciju koji sam video.
04:49
So what you're seeing here
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Ono što vidite ovde
04:51
is a statement of correspondence
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je iskaz odnosa
04:53
that intelligence is a force, F,
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gde je inteligencija sila, F,
04:58
that acts so as to maximize future freedom of action.
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koja se ponaša tako da maksimizira
buduću slobodu delovanja.
buduću slobodu delovanja.
05:02
It acts to maximize future freedom of action,
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Ponaša se tako da maksimizira
buduću slobodu delovanja
buduću slobodu delovanja
05:05
or keep options open,
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ili drži opcije otvorene,
05:06
with some strength T,
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sa nekom snagom T,
05:08
with the diversity of possible accessible futures, S,
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sa raznolikošću mogućih
dostupnih budućnosti, S,
dostupnih budućnosti, S,
05:13
up to some future time horizon, tau.
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do nekog budućeg
vremenskog horizonta, tau.
vremenskog horizonta, tau.
05:16
In short, intelligence doesn't like to get trapped.
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Ukratko, inteligencija ne voli
da bude zarobljena.
da bude zarobljena.
05:19
Intelligence tries to maximize
future freedom of action
future freedom of action
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Ona pokušava da maksimizira
buduću slobodu delovanja
buduću slobodu delovanja
05:22
and keep options open.
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i da drži opcije otvorene.
05:25
And so, given this one equation,
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I tako, kad imate ovu jednačinu,
05:27
it's natural to ask, so what can you do with this?
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prirodno je pitati
šta možete da uradite s njom?
šta možete da uradite s njom?
05:30
How predictive is it?
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Kolika joj je mogućnost predviđanja?
05:31
Does it predict human-level intelligence?
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Da li predviđa inteligenciju
ljudskog nivoa?
ljudskog nivoa?
05:33
Does it predict artificial intelligence?
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Da li predviđa veštačku inteligenciju?
05:36
So I'm going to show you now a video
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Sada ću vam pokazati video
05:38
that will, I think, demonstrate
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koji će, ja mislim, demonstrirati
05:41
some of the amazing applications
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neke od neverovatnih primena
05:44
of just this single equation.
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samo ove jedne jednačine.
05:46
(Video) Narrator: Recent research in cosmology
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(Video) Narator: Skorija
istraživanja u kosmologiji
istraživanja u kosmologiji
05:48
has suggested that universes that produce
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su ukazala da univerzumi
koji proizvode
koji proizvode
05:50
more disorder, or "entropy," over their lifetimes
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više nereda ili "entropije"
tokom svog postojanja
tokom svog postojanja
05:54
should tend to have more favorable conditions
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bi trebalo da pokazuju tendenciju
da imaju povoljnije uslove
da imaju povoljnije uslove
05:56
for the existence of intelligent
beings such as ourselves.
beings such as ourselves.
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za postojanje inteligentnih bića
kao što smo mi.
kao što smo mi.
05:59
But what if that tentative cosmological connection
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Ali šta ako ta provizorna
kosmološka povezanost
kosmološka povezanost
06:02
between entropy and intelligence
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između entropije i inteligencije
06:04
hints at a deeper relationship?
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nagoveštava dublji odnos?
06:05
What if intelligent behavior doesn't just correlate
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Šta ako inteligentno ponašanje
nije samo u uzajamnoj vezi
nije samo u uzajamnoj vezi
06:08
with the production of long-term entropy,
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sa proizvodnjom dugoročne entropije,
06:10
but actually emerges directly from it?
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već, u stvari, direktno nastaje od nje?
06:12
To find out, we developed a software engine
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Da bismo to saznali,
razvili smo softver
razvili smo softver
06:14
called Entropica, designed to maximize
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zvani Entropika,
napravljen da maksimizira
napravljen da maksimizira
06:17
the production of long-term entropy
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proizvodnju dugoročne entropije
06:19
of any system that it finds itself in.
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bilo kog sistema u kome se nađe.
06:21
Amazingly, Entropica was able to pass
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Entropika je, neverovatno,
uspela da prođe
uspela da prođe
06:23
multiple animal intelligence
tests, play human games,
tests, play human games,
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višestruke testove životinjske
inteligencije, da igra ljudske igre
inteligencije, da igra ljudske igre
06:27
and even earn money trading stocks,
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i čak da zarađuje novac
trgujući deonicama,
trgujući deonicama,
06:29
all without being instructed to do so.
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a da joj to nije bilo naloženo.
06:31
Here are some examples of Entropica in action.
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Evo nekih primera Entropike u akciji.
06:34
Just like a human standing
upright without falling over,
upright without falling over,
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Baš kao što čovek stoji uspravno,
a da ne padne,
a da ne padne,
06:37
here we see Entropica
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ovde vidimo Entropiku
06:38
automatically balancing a pole using a cart.
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koja automatski balansira
na gredi koristeći kolica.
na gredi koristeći kolica.
06:41
This behavior is remarkable in part
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Ovo ponašanje je vredno pažnje
06:43
because we never gave Entropica a goal.
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delom zato što uopšte nismo
zadali cilj Entropici.
zadali cilj Entropici.
06:45
It simply decided on its own to balance the pole.
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Jednostavno je sama odlučila
da balansira na gredi.
da balansira na gredi.
06:48
This balancing ability will have appliactions
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Ova sposobnost balansiranja
će imati primenu
će imati primenu
06:51
for humanoid robotics
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u humanoidnoj robotici
06:52
and human assistive technologies.
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i u tehnologiji za pomoć ljudima.
06:55
Just as some animals can use objects
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Baš kao što neke životinje mogu
da koriste predmete
da koriste predmete
06:57
in their environments as tools
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u svojoj okolini kao alatke
06:58
to reach into narrow spaces,
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da bi dohvatili nešto
kroz uzak prostor,
kroz uzak prostor,
07:00
here we see that Entropica,
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ovde vidimo Entropiku koja,
07:02
again on its own initiative,
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ponovo na sopstvenu inicijativu,
07:04
was able to move a large
disk representing an animal
disk representing an animal
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uspeva da pomeri veliki disk
koji predstavlja životinju
koji predstavlja životinju
07:07
around so as to cause a small disk,
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da bi mali disk
07:09
representing a tool, to reach into a confined space
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koji predstavlja alatku
stigao u zatvoreni prostor
stigao u zatvoreni prostor
07:12
holding a third disk
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u kome je treći disk
07:13
and release the third disk
from its initially fixed position.
from its initially fixed position.
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i izbacuje treći disk
sa njegove početne pozicije.
sa njegove početne pozicije.
07:16
This tool use ability will have applications
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Ova upotreba sposobnosti alatke
će imati primene
će imati primene
07:18
for smart manufacturing and agriculture.
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u "pametnoj" proizvodnji
i poljoprivredi.
i poljoprivredi.
07:21
In addition, just as some other animals
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Osim toga, baš kao što su
neke druge životinje
neke druge životinje
07:23
are able to cooperate by pulling
opposite ends of a rope
opposite ends of a rope
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sposobne da sarađuju tako što
vuku suprotne krajeve konopca
vuku suprotne krajeve konopca
07:25
at the same time to release food,
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u isto vreme, da bi oslobodile hranu,
07:27
here we see that Entropica is able to accomplish
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ovde vidimo da je Entropika
sposobna da postigne
sposobna da postigne
07:30
a model version of that task.
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verziju tog zadatka pomoću modela.
07:32
This cooperative ability has interesting implications
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Ova sposobnost kooperacije
ima zanimljive implikacije
ima zanimljive implikacije
07:34
for economic planning and a variety of other fields.
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na ekonomsko planiranje
i mnoštvo drugih oblasti.
i mnoštvo drugih oblasti.
07:38
Entropica is broadly applicable
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Entropika ima široku primenu
07:40
to a variety of domains.
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na niz domena.
07:42
For example, here we see it successfully
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Na primer, ovde vidimo
kako uspešno igra
kako uspešno igra
07:44
playing a game of pong against itself,
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igru pong, sama protiv sebe,
07:47
illustrating its potential for gaming.
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ilustrujući svoj potencijal za igre.
07:49
Here we see Entropica orchestrating
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Ovde vidimo Entropiku kako pravi
07:51
new connections on a social network
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nove veze na društvenoj mreži
07:53
where friends are constantly falling out of touch
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gde prijatelji konstantno gube kontakt
07:56
and successfully keeping
the network well connected.
the network well connected.
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i uspešno drži mrežu dobro povezanom.
07:58
This same network orchestration ability
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Ova sposobnost organizovanja mreže
08:01
also has applications in health care,
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takođe ima primenu u zdravstvu,
08:03
energy, and intelligence.
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energetici i inteligenciji.
08:06
Here we see Entropica directing the paths
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Ovde vidimo Entropiku
kako usmerava puteve
kako usmerava puteve
08:08
of a fleet of ships,
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flote brodova,
08:10
successfully discovering and
utilizing the Panama Canal
utilizing the Panama Canal
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tako što uspešno otkriva
i koristi Panamski kanal
i koristi Panamski kanal
08:13
to globally extend its reach from the Atlantic
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da bi ih sprovela od Atlantika
08:15
to the Pacific.
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do Pacifika.
08:17
By the same token, Entropica
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Pored toga, Entropika ima
08:19
is broadly applicable to problems
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široku primenu na probleme
08:20
in autonomous defense, logistics and transportation.
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autonomne odbrane, logistike i prevoza.
08:26
Finally, here we see Entropica
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Na kraju, ovde vidimo Entropiku
08:28
spontaneously discovering and executing
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kako spontano otkriva i izvršava
08:30
a buy-low, sell-high strategy
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strategiju "kupi jeftino, prodaj skupo"
08:32
on a simulated range traded stock,
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na simulaciji promena na berzi,
08:35
successfully growing assets under management
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uspešno uvećavajući dobit
pod svojim vođstvom
pod svojim vođstvom
08:37
exponentially.
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eksponencijalno.
08:38
This risk management ability
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Ova sposobnost
menadžmenta sa rizikom
menadžmenta sa rizikom
08:40
will have broad applications in finance
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imaće široke primene u finansijama
08:42
and insurance.
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i osiguranju.
08:46
Alex Wissner-Gross: So what you've just seen
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Aleks Visner-Gros: Ono
što ste upravo videli
što ste upravo videli
08:48
is that a variety of signature human intelligent
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je niz originalno ljudskih
inteligentnih
inteligentnih
08:52
cognitive behaviors
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kognitivnih ponašanja
08:54
such as tool use and walking upright
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kao što su korišćenje alata
i uspravan hod
i uspravan hod
08:57
and social cooperation
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i društvena saradnja
08:59
all follow from a single equation,
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koji proizilaze iz jedne jednačine
09:02
which drives a system
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koja pokreće sistem
09:04
to maximize its future freedom of action.
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da bi maksimizirala
buduću slobodu delovanja.
buduću slobodu delovanja.
09:07
Now, there's a profound irony here.
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U ovome ima duboke ironije.
09:10
Going back to the beginning
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Ako se vratimo na početak
09:12
of the usage of the term robot,
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korišćenja izraza "robot",
09:16
the play "RUR,"
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dramski komad "R.U.R";
09:19
there was always a concept
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uvek je postojala ideja
09:21
that if we developed machine intelligence,
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da ako bismo stvorili
mašinsku inteligenciju,
mašinsku inteligenciju,
09:24
there would be a cybernetic revolt.
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desila bi se kibernetska pobuna.
09:27
The machines would rise up against us.
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Mašine bi se pobunile protiv nas.
09:31
One major consequence of this work
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Jedna velika posledica
ovog rada je ta
ovog rada je ta
09:33
is that maybe all of these decades,
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da smo možda svih ovih decenija
09:36
we've had the whole concept of cybernetic revolt
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imali obrnut princip kibernetske
09:39
in reverse.
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pobune.
09:41
It's not that machines first become intelligent
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Nije se desilo da su mašine
prvo postale inteligentne
prvo postale inteligentne
09:44
and then megalomaniacal
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pa onda megalomanijačne
09:46
and try to take over the world.
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i pokušale da preuzmu svet.
09:48
It's quite the opposite,
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Potpuno je suprotno.
09:50
that the urge to take control
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Poriv da se preuzme kontrola
09:53
of all possible futures
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svih mogućih budućnosti
09:55
is a more fundamental principle
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je osnovniji princip
09:57
than that of intelligence,
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od inteligencije.
09:58
that general intelligence may in fact emerge
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Opšta inteligencija
može, u stvari, da nastane
može, u stvari, da nastane
10:02
directly from this sort of control-grabbing,
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direktno od ovakvog
grabljenja kontrole,
grabljenja kontrole,
10:06
rather than vice versa.
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pre nego obrnuto.
10:10
Another important consequence is goal seeking.
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Još jedna važna posledica je
traženje cilja.
traženje cilja.
10:14
I'm often asked, how does the ability to seek goals
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Često me pitaju kako
sposobnost za traženje ciljeva
sposobnost za traženje ciljeva
10:18
follow from this sort of framework?
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1620
proizilazi iz ovakve strukture?
10:20
And the answer is, the ability to seek goals
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I odgovor je da će
sposobnost za traženje ciljeva
sposobnost za traženje ciljeva
10:23
will follow directly from this
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proizaći direktno iz ovoga,
10:24
in the following sense:
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u sledećem smislu:
10:26
just like you would travel through a tunnel,
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baš kao što biste putovali kroz tunel,
10:29
a bottleneck in your future path space,
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uskim prolazom u prostoru
vašeg budućeg puta,
vašeg budućeg puta,
10:32
in order to achieve many other
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da biste postigli mnoge druge
10:34
diverse objectives later on,
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različite ciljeve kasnije
10:36
or just like you would invest
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ili kao kad biste uložili
10:38
in a financial security,
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u finansijsku sigurnost,
10:40
reducing your short-term liquidity
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smanjujući svoju kratkoročnu
platežnu moć
platežnu moć
10:42
in order to increase your wealth over the long term,
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da biste uvećali svoje bogatstvo
tokom dužeg perioda,
tokom dužeg perioda,
10:44
goal seeking emerges directly
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traženje ciljeva direktno nastaje
10:47
from a long-term drive
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od dugoročnog poriva
10:48
to increase future freedom of action.
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da se uveća buduća
sloboda delovanja.
sloboda delovanja.
10:52
Finally, Richard Feynman, famous physicist,
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Na kraju, Ričard Fajnmen,
čuveni fizičar,
čuveni fizičar,
10:56
once wrote that if human civilization were destroyed
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jednom je napisao da kad bi
ljudska civilizacija bila uništena
ljudska civilizacija bila uništena
11:00
and you could pass only a single concept
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i kad biste mogli da
prenesete samo jednu ideju
prenesete samo jednu ideju
11:02
on to our descendants
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našim potomcima
11:03
to help them rebuild civilization,
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da im pomognete da ponovo
izgrade civilizaciju,
izgrade civilizaciju,
11:05
that concept should be
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ta ideja bi trebala da bude
11:07
that all matter around us
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da se sva materija oko nas
11:09
is made out of tiny elements
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sastoji od sićušnih elemenata
11:11
that attract each other when they're far apart
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koji se privlače međusobno
kad su razdvojeni,
kad su razdvojeni,
11:14
but repel each other when they're close together.
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ali se međusobno odbijaju
kad su blizu.
kad su blizu.
11:17
My equivalent of that statement
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Moj ekvivalent ovoj izjavi
11:19
to pass on to descendants
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za prenošenje potomcima
11:20
to help them build artificial intelligences
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da bismo im pomogli
da prave veštačke inteligencije
da prave veštačke inteligencije
11:23
or to help them understand human intelligence,
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ili da razumeju ljudsku inteligenciju,
11:26
is the following:
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je sledeći:
11:27
Intelligence should be viewed
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inteligenciju bi trebalo posmatrati
11:29
as a physical process
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kao fizički proces
11:30
that tries to maximize future freedom of action
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koji pokušava da maksimizira
buduću slobodu delovanja
buduću slobodu delovanja
11:33
and avoid constraints in its own future.
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i izbegne ograničenja
u svojoj budućnosti.
u svojoj budućnosti.
11:37
Thank you very much.
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Hvala vam mnogo.
11:38
(Applause)
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(Aplauz)
ABOUT THE SPEAKER
Alex Wissner-Gross - Scientist, entrepreneur, inventorAlex Wissner-Gross applies science and engineering principles to big (and diverse) questions, like: "What is the equation for intelligence?" and "What's the best way to raise awareness about climate change?"
Why you should listen
Alex Wissner-Gross is a serial big-picture thinker. He applies physics and computer science principles to a wide variety of topics, like human intelligence, climate change and financial trading.
Lately Wissner-Gross started wondering: Why have we searched for so long to understand intelligence? Can it really be this elusive? His latest work posits that intelligence can indeed be defined physically, as a dynamic force, rather than a static property. He explains intelligence in terms of causal entropic forces, ultimately defining it as "a force to maximize future freedom of action."
Wissner-Gross is a fellow at the Harvard Institute for Applied Computational Science and a research affiliate at the MIT Media Lab. He has a Ph.D. in physics from Harvard and bachelor's degrees in physics, electrical science and engineering, and mathematics from MIT.
Alex Wissner-Gross | Speaker | TED.com