TEDxPortland
Maurice Conti: The incredible inventions of intuitive AI
Moris Konti (Maurice Conti): Neverovatni izumi intuitivne veštačke inteligencije
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Šta dobijete kada podarite dizajnerskom oruđu digitalni nervni sistem? Kompjuteri koji unapređuju našu sposobnost razmišljanja i zamišljanja, i robotski sistemi koji osmišljavaju (i grade) radikalno nove dizajne za mostove, automobile, dronove i još mnogo toga - sve potpuno sami. Pođite u obilazak proširenog doba sa futuristom Morisom Kontijem, i zavirite u vreme u kom roboti i ljudi rade rame uz rame, kako bi postigli stvari koje ni jedni ni drugi ne bi mogli postići samostalno.
Maurice Conti - Designer, futurist
Maurice Conti explores new partnerships between technology, nature and humanity. Full bio
Maurice Conti explores new partnerships between technology, nature and humanity. Full bio
Double-click the English transcript below to play the video.
00:12
How many of you are creatives,
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Koliko vas su kreativci,
00:15
designers, engineers,
entrepreneurs, artists,
entrepreneurs, artists,
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dizajneri, inženjeri,
preduzetnici, umetnici
preduzetnici, umetnici
00:18
or maybe you just have
a really big imagination?
a really big imagination?
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ili možda prosto imate
veoma bujnu maštu?
veoma bujnu maštu?
00:21
Show of hands? (Cheers)
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Pokažite ruke? (Klicanje)
00:22
That's most of you.
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To je većina vas.
00:25
I have some news for us creatives.
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Imam novosti za nas kreativce.
00:28
Over the course of the next 20 years,
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U narednih 20 godina,
00:33
more will change around
the way we do our work
the way we do our work
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više će se promeniti
način na koji obavljamo naše poslove
način na koji obavljamo naše poslove
00:37
than has happened in the last 2,000.
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nego u poslednjih 2000 godina.
00:40
In fact, I think we're at the dawn
of a new age in human history.
of a new age in human history.
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Zapravo, mislim da smo u praskozorju
novog doba u ljudskoj istoriji.
novog doba u ljudskoj istoriji.
00:45
Now, there have been four major historical
eras defined by the way we work.
eras defined by the way we work.
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Sad, imali smo četiri značajne istorijske
ere, definisane načinom našeg rada.
ere, definisane načinom našeg rada.
00:51
The Hunter-Gatherer Age
lasted several million years.
lasted several million years.
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Doba lovaca i sakupljača
koje je trajalo nekoliko miliona godina.
koje je trajalo nekoliko miliona godina.
00:55
And then the Agricultural Age
lasted several thousand years.
lasted several thousand years.
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A potom zemljoradničko doba
koje je trajalo nekoliko hiljada godina.
koje je trajalo nekoliko hiljada godina.
00:59
The Industrial Age lasted
a couple of centuries.
a couple of centuries.
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Industrijsko doba
je trajalo nekoliko vekova.
je trajalo nekoliko vekova.
01:02
And now the Information Age
has lasted just a few decades.
has lasted just a few decades.
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A sadašnje informaciono doba
je trajalo svega nekoliko decenija.
je trajalo svega nekoliko decenija.
01:07
And now today, we're on the cusp
of our next great era as a species.
of our next great era as a species.
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Trenutno smo kao vrsta na samom početku
naše nove značajne ere.
naše nove značajne ere.
01:13
Welcome to the Augmented Age.
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Dobro došli u prošireno doba.
01:16
In this new era, your natural human
capabilities are going to be augmented
capabilities are going to be augmented
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U ovoj novoj eri, vaše prirodne ljudske
sposobnosti će da budu proširene
sposobnosti će da budu proširene
01:19
by computational systems
that help you think,
that help you think,
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uz pomoć računarskih sistema
koji vam pomažu da razmišljate,
koji vam pomažu da razmišljate,
01:22
robotic systems that help you make,
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robotskih sistema
koji vam pomažu da stvarate
koji vam pomažu da stvarate
01:25
and a digital nervous system
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i digitalnih nervnih sistema
01:26
that connects you to the world
far beyond your natural senses.
far beyond your natural senses.
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koji vas povezuju sa svetom
daleko izvan vaših prirodnih čula.
daleko izvan vaših prirodnih čula.
01:31
Let's start with cognitive augmentation.
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Započnimo kognitivnim proširenjem.
01:33
How many of you are augmented cyborgs?
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Koliko vas su prošireni kiborzi?
01:36
(Laughter)
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(Smeh)
01:38
I would actually argue
that we're already augmented.
that we're already augmented.
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Ja bih zapravo rekao
da smo svi mi prošireni.
da smo svi mi prošireni.
01:42
Imagine you're at a party,
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Zamislite da ste na zabavi
01:43
and somebody asks you a question
that you don't know the answer to.
that you don't know the answer to.
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i neko vam postavi pitanje
na koje ne znate odgovor.
na koje ne znate odgovor.
01:47
If you have one of these,
in a few seconds, you can know the answer.
in a few seconds, you can know the answer.
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Ako imate nešto slično ovome,
za nekoliko sekundi možete znati odgovor.
za nekoliko sekundi možete znati odgovor.
01:51
But this is just a primitive beginning.
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Ali ovo je tek primitivni početak.
01:54
Even Siri is just a passive tool.
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Čak je i Siri tek pasivno oruđe.
01:58
In fact, for the last
three-and-a-half million years,
three-and-a-half million years,
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Zapravo, u poslednjih
tri i po miliona godina,
tri i po miliona godina,
02:02
the tools that we've had
have been completely passive.
have been completely passive.
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oruđa koja smo imali
su bila potpuno pasivna.
su bila potpuno pasivna.
02:06
They do exactly what we tell them
and nothing more.
and nothing more.
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Ona rade tačno ono što im kažemo
i ništa više.
i ništa više.
02:09
Our very first tool only cut
where we struck it.
where we struck it.
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Naše prvo oruđe je jedino seklo
onde gde bismo udarili njime.
onde gde bismo udarili njime.
02:13
The chisel only carves
where the artist points it.
where the artist points it.
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Dleto rezbari samo onde
gde ga umetnik usmeri.
gde ga umetnik usmeri.
02:17
And even our most advanced tools
do nothing without our explicit direction.
do nothing without our explicit direction.
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Čak i naša najnaprednija oruđa ne rade
bilo šta bez naših eksplicitnih naredbi.
bilo šta bez naših eksplicitnih naredbi.
02:23
In fact, to date, and this
is something that frustrates me,
is something that frustrates me,
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Zapravo, do danas,
a to je nešto što me nervira,
a to je nešto što me nervira,
02:26
we've always been limited
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oduvek smo bili ograničeni
02:27
by this need to manually
push our wills into our tools --
push our wills into our tools --
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potrebom da ručno
uteramo našu volju u naše alate -
uteramo našu volju u naše alate -
02:31
like, manual,
literally using our hands,
literally using our hands,
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ručno, bukvalno koristeći naše ruke,
02:33
even with computers.
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čak i sa kompjuterima.
02:36
But I'm more like Scotty in "Star Trek."
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No ja sam više nalik Skotiju
iz "Zvezdanih staza".
iz "Zvezdanih staza".
02:38
(Laughter)
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(Smeh)
02:40
I want to have a conversation
with a computer.
with a computer.
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Želim da razgovaram s kompjuterom.
02:42
I want to say, "Computer,
let's design a car,"
let's design a car,"
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Želim da kažem: "Kompjuteru,
hajde da dizajniramo automobil",
hajde da dizajniramo automobil",
02:45
and the computer shows me a car.
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i kompjuter mi pokaže automobil.
02:47
And I say, "No, more fast-looking,
and less German,"
and less German,"
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A ja kažem: "Ne, da izgleda brže
i manje nemački",
i manje nemački",
02:49
and bang, the computer shows me an option.
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i, bum, kompjuter mi pokaže opciju.
02:51
(Laughter)
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(Smeh)
02:54
That conversation might be
a little ways off,
a little ways off,
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Taj razgovor je možda malčice daleko,
02:56
probably less than many of us think,
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verovatno manje nego što većina nas misli,
02:59
but right now,
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ali trenutno
03:01
we're working on it.
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radimo na tome.
03:02
Tools are making this leap
from being passive to being generative.
from being passive to being generative.
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Oruđa prave ovaj skok
od pasivnih do stvaralačkih.
od pasivnih do stvaralačkih.
03:06
Generative design tools
use a computer and algorithms
use a computer and algorithms
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Stvaralačka dizajnerska oruđa
koriste kompjutere i algoritme,
koriste kompjutere i algoritme,
03:10
to synthesize geometry
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da bi tim spojem stvorila geometriju
03:12
to come up with new designs
all by themselves.
all by themselves.
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i potpuno sama došla do novih dizajna.
03:15
All it needs are your goals
and your constraints.
and your constraints.
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Sve što im je potrebno
su vaši ciljevi i vaša ograničenja.
su vaši ciljevi i vaša ograničenja.
03:18
I'll give you an example.
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Daću vam jedan primer.
03:20
In the case of this aerial drone chassis,
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U slučaju ove vazdušne šasije drona,
03:23
all you would need to do
is tell it something like,
is tell it something like,
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sve što bi trebalo da uradite
je da tražite sledeće:
je da tražite sledeće:
03:25
it has four propellers,
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da ima četiri propelera,
03:26
you want it to be
as lightweight as possible,
as lightweight as possible,
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želite da bude što lakša
03:29
and you need it to be
aerodynamically efficient.
aerodynamically efficient.
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i želite da ima aerodinamičnu efikasnost.
03:31
Then what the computer does
is it explores the entire solution space:
is it explores the entire solution space:
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Potom kompjuter istražuje
celokupan prostor rešenja:
celokupan prostor rešenja:
03:36
every single possibility that solves
and meets your criteria --
and meets your criteria --
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baš svaku mogućnost
koja rešava i ispunjava vaše kriterijume -
koja rešava i ispunjava vaše kriterijume -
03:40
millions of them.
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milione njih.
Potrebni su veliki kompjuteri da to obave.
03:41
It takes big computers to do this.
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03:43
But it comes back to us with designs
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Ali su nam uzvratili dizajnima
03:45
that we, by ourselves,
never could've imagined.
never could've imagined.
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koje mi sami ne bismo
nikad mogli da zamislimo.
nikad mogli da zamislimo.
03:49
And the computer's coming up
with this stuff all by itself --
with this stuff all by itself --
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A kompjuter je sam došao do ovoga -
03:52
no one ever drew anything,
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niko nikad nije nacrtao bilo šta -
03:53
and it started completely from scratch.
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i započeo je potpuno od nule.
03:57
And by the way, it's no accident
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I, usput, nije slučajno
03:59
that the drone body looks just like
the pelvis of a flying squirrel.
the pelvis of a flying squirrel.
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da telo drona izgleda
baš kao karlica leteće veverice.
baš kao karlica leteće veverice.
04:03
(Laughter)
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(Smeh)
04:06
It's because the algorithms
are designed to work
are designed to work
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To je tako jer su algoritmi
dizajnirani da deluju
dizajnirani da deluju
04:08
the same way evolution does.
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na isti način kao evolucija.
04:10
What's exciting is we're starting
to see this technology
to see this technology
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Uzbudljivo je što počinjemo
da gledamo ovu tehnologiju
da gledamo ovu tehnologiju
04:13
out in the real world.
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u stvarnom svetu.
04:14
We've been working with Airbus
for a couple of years
for a couple of years
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Nekoliko godina smo radili sa Erbasom
04:17
on this concept plane for the future.
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na konceptu aviona iz budućnosti.
04:18
It's a ways out still.
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I dalje je ispred svog vremena.
04:21
But just recently we used
a generative-design AI
a generative-design AI
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Ali baš nedavno smo koristili
generativni dizajn veštačke inteligencije
generativni dizajn veštačke inteligencije
04:24
to come up with this.
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da bismo smislili ovo.
04:27
This is a 3D-printed cabin partition
that's been designed by a computer.
that's been designed by a computer.
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Ovo je pregrada odštampana 3D štampačem,
koju je dizajnirao kompjuter.
koju je dizajnirao kompjuter.
04:32
It's stronger than the original
yet half the weight,
yet half the weight,
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Jača je od prvobitne,
a ipak je upola lakša
a ipak je upola lakša
04:35
and it will be flying
in the Airbus A320 later this year.
in the Airbus A320 later this year.
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i leteće u erbasu A320 kasnije ove godine.
04:39
So computers can now generate;
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Kompjuteri sad mogu da stvaraju;
04:40
they can come up with their own solutions
to our well-defined problems.
to our well-defined problems.
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mogu da osmisle sopstvena rešenja
za naše dobro definisane probleme.
za naše dobro definisane probleme.
04:46
But they're not intuitive.
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Ali nisu intuitivni.
04:48
They still have to start from scratch
every single time,
every single time,
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I dalje moraju da počnu od nule,
baš svaki put,
baš svaki put,
04:51
and that's because they never learn.
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a to je zato što nikad ne nauče.
04:54
Unlike Maggie.
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Za razliku od Megi.
04:56
(Laughter)
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(Smeh)
04:57
Maggie's actually smarter
than our most advanced design tools.
than our most advanced design tools.
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Megi je zapravo pametnija od naših
najnaprednijih dizajnerskih oruđa.
najnaprednijih dizajnerskih oruđa.
05:01
What do I mean by that?
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Šta podrazumevam time?
05:02
If her owner picks up that leash,
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Ako njen vlasnik uzme povodac,
05:04
Maggie knows with a fair
degree of certainty
degree of certainty
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Megi zna s porpiličnim stepenom izvesnosti
05:06
it's time to go for a walk.
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da je vreme za šetnju.
05:08
And how did she learn?
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A kako je naučila?
05:09
Well, every time the owner picked up
the leash, they went for a walk.
the leash, they went for a walk.
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Pa, svaki put kad je vlasnik
uzeo povodac, išli su u šetnju.
uzeo povodac, išli su u šetnju.
05:12
And Maggie did three things:
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I Megi je obavila tri stvari:
05:14
she had to pay attention,
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morala je da obrati pažnju,
05:16
she had to remember what happened
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morala je da se priseti šta se desilo
05:18
and she had to retain and create
a pattern in her mind.
a pattern in her mind.
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i morala je da zadrži i stvori
obrazac u svom umu.
obrazac u svom umu.
Zanimljivo je da je upravo to ono što
05:23
Interestingly, that's exactly what
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05:25
computer scientists
have been trying to get AIs to do
have been trying to get AIs to do
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naučnici za kompjutere pokušavaju
da navedu VI da uradi
da navedu VI da uradi
05:28
for the last 60 or so years.
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u poslednjih oko 60 godina.
05:30
Back in 1952,
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Te 1952.
05:32
they built this computer
that could play Tic-Tac-Toe.
that could play Tic-Tac-Toe.
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su sagradili ovaj kompjuter
koji je mogao da igra iks-oks.
koji je mogao da igra iks-oks.
05:37
Big deal.
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Velika stvar.
05:39
Then 45 years later, in 1997,
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Potom, 45 godina kasnije, 1997.
05:42
Deep Blue beats Kasparov at chess.
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Deep Blue je pobedio Kasparova u šahu.
05:46
2011, Watson beats these two
humans at Jeopardy,
humans at Jeopardy,
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Godine 2011, Watson je pobedio
ova dva čoveka u kvizu,
ova dva čoveka u kvizu,
05:51
which is much harder for a computer
to play than chess is.
to play than chess is.
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što je daleko teže za kompjuter
da iga od šaha.
da iga od šaha.
05:53
In fact, rather than working
from predefined recipes,
from predefined recipes,
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Zapravo, umesto da radi
na osnovu već definisanih recepata,
na osnovu već definisanih recepata,
05:57
Watson had to use reasoning
to overcome his human opponents.
to overcome his human opponents.
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Votson je morao da koristi rasuđivanje
da bi prevazišao ljudske protivnike.
da bi prevazišao ljudske protivnike.
06:02
And then a couple of weeks ago,
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A onda, pre nekoliko nedelja,
06:04
DeepMind's AlphaGo beats
the world's best human at Go,
the world's best human at Go,
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AlphaGo iz DeepMind-a je pobedio
ljudsko biće koje je najbolje u gou,
ljudsko biće koje je najbolje u gou,
06:09
which is the most difficult
game that we have.
game that we have.
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a to je najkomplikovanija igra koju imamo.
06:11
In fact, in Go, there are more
possible moves
possible moves
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Zapravo, ima više mogućih poteza u gou
06:14
than there are atoms in the universe.
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nego što ima atoma u univerzumu.
06:18
So in order to win,
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Pa, kako bi pobedio,
06:20
what AlphaGo had to do
was develop intuition.
was develop intuition.
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AlphaGo je morao da razvije intuiciju.
06:23
And in fact, at some points,
AlphaGo's programmers didn't understand
AlphaGo's programmers didn't understand
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I zapravo, u nekim momentima
programeri AlphaGo-a nisu razumeli
programeri AlphaGo-a nisu razumeli
06:27
why AlphaGo was doing what it was doing.
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zašto je AlphaGo radio to što radi.
06:31
And things are moving really fast.
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A stvari se odvijaju zaista brzo.
06:33
I mean, consider --
in the space of a human lifetime,
in the space of a human lifetime,
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Mislim, razmotrite -
u okviru ljudskog životnog veka,
u okviru ljudskog životnog veka,
06:36
computers have gone from a child's game
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kompjuteri su prešli od dečje igre
06:39
to what's recognized as the pinnacle
of strategic thought.
of strategic thought.
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do onoga što se smatra vrhuncem
strateškog mišljenja.
strateškog mišljenja.
06:43
What's basically happening
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U suštini se dešava to
06:46
is computers are going
from being like Spock
from being like Spock
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da kompjuteri prestaju da budu poput Spoka
06:49
to being a lot more like Kirk.
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i postaju mnogo više nalik Kirku.
06:51
(Laughter)
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(Smeh)
06:55
Right? From pure logic to intuition.
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Je li tako? Od čiste logike do intuicije.
07:00
Would you cross this bridge?
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Da li biste prešli ovaj most?
07:02
Most of you are saying, "Oh, hell no!"
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Većina vas govori: "Uh, nema šanse!"
07:04
(Laughter)
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(Smeh)
07:06
And you arrived at that decision
in a split second.
in a split second.
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A stigli ste do te odluke
u deliću sekunde.
u deliću sekunde.
07:08
You just sort of knew
that bridge was unsafe.
that bridge was unsafe.
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Prosto ste nekako znali
da taj most nije bezbedan.
da taj most nije bezbedan.
07:11
And that's exactly the kind of intuition
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A upravo je to tip intuicije
07:13
that our deep-learning systems
are starting to develop right now.
are starting to develop right now.
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koju naši sistemi dubinskog učenja
trenutno počinju da razvijaju.
trenutno počinju da razvijaju.
07:17
Very soon, you'll literally be able
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Veoma brzo ćete bukvalno moći
07:19
to show something you've made,
you've designed,
you've designed,
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da pokažete kompjuteru
nešto što ste napravili,
nešto što ste napravili,
07:21
to a computer,
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što ste dizajnirali
07:22
and it will look at it and say,
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i on će to da pogleda i kaže:
07:24
"Sorry, homie, that'll never work.
You have to try again."
You have to try again."
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"Izvini, druže, to neće proći.
Moraš opet da pokušaš."
Moraš opet da pokušaš."
07:27
Or you could ask it if people
are going to like your next song,
are going to like your next song,
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Ili ćete moći da ga pitate da li će se
ljudima sviđati vaša nova pesma
ljudima sviđati vaša nova pesma
07:31
or your next flavor of ice cream.
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ili vaš novi ukus sladoleda.
07:35
Or, much more importantly,
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Ili, što je još važnije,
moći ćete raditi sa kompjuterom
da biste rešili problem
da biste rešili problem
07:38
you could work with a computer
to solve a problem
to solve a problem
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07:40
that we've never faced before.
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s kojim se pre nismo suočili.
07:42
For instance, climate change.
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Na primer, klimatske promene.
07:43
We're not doing a very
good job on our own,
good job on our own,
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Sami ne obavljamo posao naročito dobro,
07:45
we could certainly use
all the help we can get.
all the help we can get.
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svakako da bi nam koristila
sva moguća pomoć.
sva moguća pomoć.
07:47
That's what I'm talking about,
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O tome govorim,
o tehnologiji koja naglašava
naše kognitivne sposobnosti
naše kognitivne sposobnosti
07:49
technology amplifying
our cognitive abilities
our cognitive abilities
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07:52
so we can imagine and design things
that were simply out of our reach
that were simply out of our reach
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kako bismo mogli da zamislimo
i dizajniramo stvari koje nisu dostupne
i dizajniramo stvari koje nisu dostupne
07:55
as plain old un-augmented humans.
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nama, prostim starim neproširenim ljudima.
Pa, o čemu se radi kod stvaranja
svih tih blesavih novih stvari
svih tih blesavih novih stvari
07:59
So what about making
all of this crazy new stuff
all of this crazy new stuff
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08:02
that we're going to invent and design?
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koje ćemo izumeti i dizajnirati?
08:05
I think the era of human augmentation
is as much about the physical world
is as much about the physical world
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Mislim da se u eri ljudskog proširivanja
podjednako radi o fizičkom svetu
podjednako radi o fizičkom svetu
08:10
as it is about the virtual,
intellectual realm.
intellectual realm.
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kao i o virtuelnoj, intelektualnoj sferi.
08:13
How will technology augment us?
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Kako će nas tehnologija proširiti?
08:16
In the physical world, robotic systems.
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U fizičkom svetu,
biće to robotski sistemi.
biće to robotski sistemi.
08:19
OK, there's certainly a fear
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U redu, svakako da postoji strah
08:21
that robots are going to take
jobs away from humans,
jobs away from humans,
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da će roboti da oduzmu poslove ljudima,
08:23
and that is true in certain sectors.
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to je tačno za određene sektore.
08:26
But I'm much more interested in this idea
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No, mene više zanima zamisao
08:29
that humans and robots working together
are going to augment each other,
are going to augment each other,
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da će ljudi i roboti radeći zajedno
proširiti jedni druge,
proširiti jedni druge,
08:34
and start to inhabit a new space.
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i počeće da naseljavaju nove prostore.
Ovo je primenjena istraživačka
laboratorija u San Francisku,
laboratorija u San Francisku,
08:36
This is our applied research lab
in San Francisco,
in San Francisco,
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08:38
where one of our areas of focus
is advanced robotics,
is advanced robotics,
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gde je napredna robotika
jedna od oblasti na koje se fokusiramo,
jedna od oblasti na koje se fokusiramo,
08:41
specifically, human-robot collaboration.
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naročito saradnja između ljudi i robota.
08:45
And this is Bishop, one of our robots.
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A ovo je Bišop, jedan od naših robota.
08:47
As an experiment, we set it up
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Kao eksperiment, podesili smo ga
08:49
to help a person working in construction
doing repetitive tasks --
doing repetitive tasks --
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da pomaže osobi koja na građevini
obavlja repetitivne poslove -
obavlja repetitivne poslove -
08:53
tasks like cutting out holes for outlets
or light switches in drywall.
or light switches in drywall.
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poslove poput bušenja rupa u gips-kartonu
za utičnice ili prekidače za svetla.
za utičnice ili prekidače za svetla.
08:58
(Laughter)
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(Smeh)
09:01
So, Bishop's human partner
can tell what to do in plain English
can tell what to do in plain English
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Dakle, Bišopov ljudski partner
može da mu objasni na engleskom
može da mu objasni na engleskom
i jednostavnom gestikulacijom,
09:05
and with simple gestures,
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09:06
kind of like talking to a dog,
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poput razgovaranja sa psom,
09:07
and then Bishop executes
on those instructions
on those instructions
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a potom Bišop, izvodi ta uputstva
09:09
with perfect precision.
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savršenom preciznošću.
09:11
We're using the human
for what the human is good at:
for what the human is good at:
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Koristimo ljude za ono u čemu su dobri:
09:14
awareness, perception and decision making.
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svesnost, percepcija i donošenje odluka.
09:17
And we're using the robot
for what it's good at:
for what it's good at:
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A koristimo robota za ono u čemu je dobar:
09:19
precision and repetitiveness.
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preciznost i ponavljanje.
09:22
Here's another cool project
that Bishop worked on.
that Bishop worked on.
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Još jedan sjajan projekat
na kom je radio Bišop.
na kom je radio Bišop.
09:24
The goal of this project,
which we called the HIVE,
which we called the HIVE,
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Cilj ovog projekta, koga smo nazvali HIVE,
09:27
was to prototype the experience
of humans, computers and robots
of humans, computers and robots
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bio je da testira iskustvo
ljudi, kompjutera i robota
ljudi, kompjutera i robota
09:31
all working together to solve
a highly complex design problem.
a highly complex design problem.
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gde svi rade zajedno kako bi rešili
veoma složene dizajnerske probleme.
veoma složene dizajnerske probleme.
Ljudi su služili kao radna snaga.
09:35
The humans acted as labor.
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09:37
They cruised around the construction site,
they manipulated the bamboo --
they manipulated the bamboo --
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Kružili su po gradilištu,
rukovali bambusom -
rukovali bambusom -
09:40
which, by the way,
because it's a non-isomorphic material,
because it's a non-isomorphic material,
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koji je, usput, stoga
što je neizomorfan materijal,
što je neizomorfan materijal,
09:43
is super hard for robots to deal with.
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veoma težak robotima za rukovanje.
09:45
But then the robots
did this fiber winding,
did this fiber winding,
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No, potom su roboti namotavali ovo vlakno,
09:47
which was almost impossible
for a human to do.
for a human to do.
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2451
a to je skoro nemoguće za ljude da urade.
09:49
And then we had an AI
that was controlling everything.
that was controlling everything.
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A potom smo imali VI
koja je sve kontrolisala.
koja je sve kontrolisala.
09:53
It was telling the humans what to do,
telling the robots what to do
telling the robots what to do
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Govorila je ljudima šta da rade,
govorila je robotima šta da rade
govorila je robotima šta da rade
09:56
and keeping track of thousands
of individual components.
of individual components.
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i nadgledala hiljade
pojedinačnih komponenti.
pojedinačnih komponenti.
09:59
What's interesting is,
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Zanimljivo je
10:01
building this pavilion
was simply not possible
was simply not possible
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3141
da je izgradnja ovog paviljona
prosto bila nemoguća
prosto bila nemoguća
10:04
without human, robot and AI
augmenting each other.
augmenting each other.
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bez ljudi, robota i VI
koji proširuju jedni druge.
koji proširuju jedni druge.
10:09
OK, I'll share one more project.
This one's a little bit crazy.
This one's a little bit crazy.
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Podeliću sa vama još jedan projekat.
Ovaj je malčice blesav.
Ovaj je malčice blesav.
10:13
We're working with Amsterdam-based artist
Joris Laarman and his team at MX3D
Joris Laarman and his team at MX3D
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Radimo sa umetnicima iz Amsterdama,
Jorisom Larmanom i njegovom ekipom iz MX3D
Jorisom Larmanom i njegovom ekipom iz MX3D
10:17
to generatively design
and robotically print
and robotically print
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da bismo generativno dizajnirali
i robotski odštampali
i robotski odštampali
10:20
the world's first autonomously
manufactured bridge.
manufactured bridge.
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prvi u svetu autonomno proizveden most.
10:24
So, Joris and an AI are designing
this thing right now, as we speak,
this thing right now, as we speak,
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Dakle, Joris i VI baš dok govorimo
dizajniraju taj objekat
dizajniraju taj objekat
10:28
in Amsterdam.
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u Amsterdamu.
10:29
And when they're done,
we're going to hit "Go,"
we're going to hit "Go,"
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A kad završe, pritisnućemo "Kreni"
10:31
and robots will start 3D printing
in stainless steel,
in stainless steel,
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3311
i roboti će početi 3D tehnologijom
da štampaju nerđajući čelik
da štampaju nerđajući čelik
10:34
and then they're going to keep printing,
without human intervention,
without human intervention,
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i nastaviće da štampaju
bez ljudskog uplitanja,
bez ljudskog uplitanja,
10:38
until the bridge is finished.
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sve dok završe most.
10:41
So, as computers are going
to augment our ability
to augment our ability
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Pa, kako će roboti
da prošire našu sposobnost
da prošire našu sposobnost
10:44
to imagine and design new stuff,
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zamišljanja i dizajniranja novih stvari,
robotski sistemi će da nam pomognu
da gradimo i pravimo stvari
da gradimo i pravimo stvari
10:46
robotic systems are going to help us
build and make things
build and make things
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10:49
that we've never been able to make before.
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koje nismo mogli da pravimo pre.
10:52
But what about our ability
to sense and control these things?
to sense and control these things?
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No, šta je s našom sposobnošću
da osetimo i kontrolišemo ove stvari?
da osetimo i kontrolišemo ove stvari?
10:56
What about a nervous system
for the things that we make?
for the things that we make?
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Kako bi bilo da imamo nervni sistem
kod stvari koje pravimo?
kod stvari koje pravimo?
11:00
Our nervous system,
the human nervous system,
the human nervous system,
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Naš nervni sistem, ljudski nervni sistem,
11:03
tells us everything
that's going on around us.
that's going on around us.
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saopštava nam o svemu
što se dešava oko nas.
što se dešava oko nas.
11:06
But the nervous system of the things
we make is rudimentary at best.
we make is rudimentary at best.
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Međutim, nervni sitem stvari
koje pravimo je u najboljem slučaju prost.
koje pravimo je u najboljem slučaju prost.
11:09
For instance, a car doesn't tell
the city's public works department
the city's public works department
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3563
Na primer, automobil ne saopštava
gradskom odseku za javne delatnosti
gradskom odseku za javne delatnosti
11:13
that it just hit a pothole at the corner
of Broadway and Morrison.
of Broadway and Morrison.
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da je upravo udario u rupu
na uglu ulice Brodvej i Morison.
na uglu ulice Brodvej i Morison.
11:16
A building doesn't tell its designers
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2032
Građevina ne sopštava njenim dizajnerima
11:18
whether or not the people inside
like being there,
like being there,
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2684
da li ljudi unutar nje vole da budu tu,
11:21
and the toy manufacturer doesn't know
229
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3010
a proizvođač lutaka ne zna
11:24
if a toy is actually being played with --
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2007
da li se zaista igraju
njihovim igračkama -
njihovim igračkama -
11:26
how and where and whether
or not it's any fun.
or not it's any fun.
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2539
kako, gde i da li su ili nisu zabavne.
11:29
Look, I'm sure that the designers
imagined this lifestyle for Barbie
imagined this lifestyle for Barbie
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3814
Vidite, siguran sam da su dizajneri
zamislili ovakav stil života za barbiku
zamislili ovakav stil života za barbiku
11:33
when they designed her.
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kada su je dizajnirali.
11:34
(Laughter)
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1447
(Smeh)
11:36
But what if it turns out that Barbie's
actually really lonely?
actually really lonely?
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Ali šta ako se ispostavi
da je barbi zapravo veoma usamljena?
da je barbi zapravo veoma usamljena?
11:39
(Laughter)
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(Smeh)
11:43
If the designers had known
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Kad bi dizajneri znali
šta se zaista dešava u stvarnom svetu
11:44
what was really happening
in the real world
in the real world
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2107
njihovim dizajnima - putevima,
građevinama, barbikama -
građevinama, barbikama -
11:46
with their designs -- the road,
the building, Barbie --
the building, Barbie --
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2583
mogli bi da koriste to znanje
11:49
they could've used that knowledge
to create an experience
to create an experience
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da stvore bolja iskustva za korisnike.
11:52
that was better for the user.
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Nedostaje nervni sistem
11:53
What's missing is a nervous system
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1791
11:55
connecting us to all of the things
that we design, make and use.
that we design, make and use.
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3709
koji bi nas povezao sa svim stvarima
koje dizajniramo, pravimo i koristimo.
koje dizajniramo, pravimo i koristimo.
11:59
What if all of you had that kind
of information flowing to you
of information flowing to you
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Šta kad biste svi vi imali
dotok takvog oblika informacija
dotok takvog oblika informacija
12:03
from the things you create
in the real world?
in the real world?
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od stvari koje stvarate u stvarnom svetu?
12:07
With all of the stuff we make,
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1451
Uz sve što pravimo,
12:08
we spend a tremendous amount
of money and energy --
of money and energy --
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trošimo ogromne količine
novca i energije -
novca i energije -
12:11
in fact, last year,
about two trillion dollars --
about two trillion dollars --
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zapravo, prošle godine,
skoro dva biliona dolara -
skoro dva biliona dolara -
12:13
convincing people to buy
the things we've made.
the things we've made.
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ubeđujući ljude da kupe
stvari koje pravimo.
stvari koje pravimo.
12:16
But if you had this connection
to the things that you design and create
to the things that you design and create
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3388
Ali kad biste imali ovakvu vezu
sa stvarima koje dizajnirate i stvarate
sa stvarima koje dizajnirate i stvarate
12:20
after they're out in the real world,
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kada se one nađu u stvarnom svetu,
12:21
after they've been sold
or launched or whatever,
or launched or whatever,
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3614
nakon što ih prodaju
ili lansiraju ili šta god,
ili lansiraju ili šta god,
zapravo bismo mogli to da promenimo
12:25
we could actually change that,
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12:27
and go from making people want our stuff,
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3047
i da se pomerimo
od ubeđivanja ljudi da vole naše stvari
od ubeđivanja ljudi da vole naše stvari
12:30
to just making stuff that people
want in the first place.
want in the first place.
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3434
do prosto pravljenja stvari
koje su ljudima prvenstveno potrebne.
koje su ljudima prvenstveno potrebne.
12:33
The good news is, we're working
on digital nervous systems
on digital nervous systems
256
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2787
Dobre vesti su da radimo
na digitalnom nervnom sistemu
na digitalnom nervnom sistemu
12:36
that connect us to the things we design.
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koji bi nas povezao
sa stvarima koje dizajniramo.
sa stvarima koje dizajniramo.
12:40
We're working on one project
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Radimo na jednom projektu
12:42
with a couple of guys down in Los Angeles
called the Bandito Brothers
called the Bandito Brothers
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3712
sa nekoliko momaka iz Los Anđelesa,
koji sebe nazivaju Bandito Bradersima,
koji sebe nazivaju Bandito Bradersima,
12:45
and their team.
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i njihovom ekipom.
12:47
And one of the things these guys do
is build insane cars
is build insane cars
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A jedna od stvari koju ovi momci rade
je izgradnja ludih automobila
je izgradnja ludih automobila
12:50
that do absolutely insane things.
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2873
koji rade potpuno lude stvari.
12:54
These guys are crazy --
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Ovi momci su sumanuti -
12:56
(Laughter)
264
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1036
(Smeh)
12:57
in the best way.
265
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na najbolji način.
13:00
And what we're doing with them
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A mi s njima radimo
13:02
is taking a traditional race-car chassis
267
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2440
tako što uzmemo tradicionalnu
šasiju za trkačka auta
šasiju za trkačka auta
13:05
and giving it a nervous system.
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i ugrađujemo nervni sistem u nju.
13:06
So we instrumented it
with dozens of sensors,
with dozens of sensors,
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Dakle, opskrbili smo je
desetinama senzora,
desetinama senzora,
13:09
put a world-class driver behind the wheel,
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stavili smo iza volana
vozača svetske klase,
vozača svetske klase,
13:12
took it out to the desert
and drove the hell out of it for a week.
and drove the hell out of it for a week.
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odvezli auto u pustinju
vozali ga do besvesti sedam dana.
vozali ga do besvesti sedam dana.
13:15
And the car's nervous system
captured everything
captured everything
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A nervni sistem automobila je zabeležio
13:18
that was happening to the car.
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sve što se dešavalo automobilu.
13:19
We captured four billion data points;
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Zabeležili smo četiri milijarde
jedinica podataka;
jedinica podataka;
13:22
all of the forces
that it was subjected to.
that it was subjected to.
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sve sile kojima je bilo izloženo.
13:24
And then we did something crazy.
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A potom smo uradili nešto ludo.
13:27
We took all of that data,
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Uzeli smo sve podatke
13:28
and plugged it into a generative-design AI
we call "Dreamcatcher."
we call "Dreamcatcher."
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i priključili ih na VI genrativnog dizajna
koju nazivamo "Dreamcatcher".
koju nazivamo "Dreamcatcher".
13:33
So what do get when you give
a design tool a nervous system,
a design tool a nervous system,
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Pa, šta dobijate kada dizajnerskom oruđu
date nervni sistem
date nervni sistem
13:37
and you ask it to build you
the ultimate car chassis?
the ultimate car chassis?
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i zatražite od njega da vam sagradi
najbolju šasiju za auto?
najbolju šasiju za auto?
13:40
You get this.
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Dobijate ovo.
13:44
This is something that a human
could never have designed.
could never have designed.
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Ovo je nešto što ljudi
nikad ne bi mogli da dizajniraju.
nikad ne bi mogli da dizajniraju.
13:48
Except a human did design this,
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Samo što ljudi ovo jesu dizajnirali,
13:50
but it was a human that was augmented
by a generative-design AI,
by a generative-design AI,
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ali to su bili ljudi prošireni
VI generativnog dizajna,
VI generativnog dizajna,
digitalnim nervnim sistemom
13:54
a digital nervous system
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13:56
and robots that can actually
fabricate something like this.
fabricate something like this.
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i robotima koji zapravo mogu
da proizvedu nešto ovakvo.
da proizvedu nešto ovakvo.
13:59
So if this is the future,
the Augmented Age,
the Augmented Age,
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Pa, ako je ovo budućnost, prošireno doba,
14:03
and we're going to be augmented
cognitively, physically and perceptually,
cognitively, physically and perceptually,
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a mi ćemo da budemo prošireni
kognitivno, fizički i čulno,
kognitivno, fizički i čulno,
14:07
what will that look like?
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kako će to da izgleda?
14:09
What is this wonderland going to be like?
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Kako će da izgleda ova zemlja čuda?
14:12
I think we're going to see a world
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Mislim da ćemo da vidimo svet
14:14
where we're moving
from things that are fabricated
from things that are fabricated
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u kom se udaljavamo
od stvari koje se proizvode
od stvari koje se proizvode
14:17
to things that are farmed.
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do stvari koje se obrađuju.
14:20
Where we're moving from things
that are constructed
that are constructed
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U kom se udaljavamo od stvari
koje se konstruišu
koje se konstruišu
14:23
to that which is grown.
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do onih koje se gaje.
14:26
We're going to move from being isolated
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Udaljićemo se od izolacije
14:28
to being connected.
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ka povezanosti.
14:30
And we'll move away from extraction
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I udaljićemo se od kopanja
14:33
to embrace aggregation.
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ka sakupljanju.
14:35
I also think we'll shift
from craving obedience from our things
from craving obedience from our things
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Mislim i da ćemo se pomeriti
od žudnje da nam stvari budu poslušne
od žudnje da nam stvari budu poslušne
14:39
to valuing autonomy.
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ka cenjenju autonomije.
14:42
Thanks to our augmented capabilities,
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Zahvaljujući našim
proširenim mogućnostima,
proširenim mogućnostima,
14:44
our world is going to change dramatically.
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naš svet će da se drastično izmeni.
14:47
We're going to have a world
with more variety, more connectedness,
with more variety, more connectedness,
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Imaćemo svet s više izbora,
više povezanosti,
više povezanosti,
14:50
more dynamism, more complexity,
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dinamičniji, složeniji
14:53
more adaptability and, of course,
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prilagodljiviji i, naravno,
14:55
more beauty.
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lepši.
14:57
The shape of things to come
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Obrisi budućnosti
14:58
will be unlike anything
we've ever seen before.
we've ever seen before.
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neće da liče na bilo šta
što smo videli do sad.
što smo videli do sad.
15:01
Why?
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Zašto?
15:02
Because what will be shaping those things
is this new partnership
is this new partnership
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Jer će sve ovo da oblikuje
novo partnerstvo
novo partnerstvo
15:06
between technology, nature and humanity.
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između tehnologije, prirode i čovečanstva.
15:11
That, to me, is a future
well worth looking forward to.
well worth looking forward to.
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Za mene, to je budućnost
koju vredi iščekivati.
koju vredi iščekivati.
15:15
Thank you all so much.
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Mnogo vam hvala.
15:16
(Applause)
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(Aplauz)
ABOUT THE SPEAKER
Maurice Conti - Designer, futuristMaurice Conti explores new partnerships between technology, nature and humanity.
Why you should listen
Maurice Conti is a designer, futurist and innovator. He's worked with startups, government agencies, artists and corporations to explore the things that will matter to us in the future, and to design solutions to get us there.
Conti is currently Chief Innovation Officer at Alpha -- Europe's first moonshot factory, powered by Telefónica. Conti and his team are responsible for coming up with the ideas, prototypes and proofs of concepts that will go on to become full-blown moonshots at Alpha: projects that will affect 100 million people or more, be a force for good on the planet and grow into billion-euro businesses.
Previously, Conti was Director of Applied Research & Innovation at Autodesk where built and led Autodesk's Applied Research Lab. Conti's work focuses on applied machine learning, advanced robotics, augmented and virtual realities, and the future of work, cities and mobility.
Conti is also an explorer of geographies and cultures. He has circumnavigated the globe once and been half-way around twice. In 2009 he was awarded the Medal for Exceptional Bravery at Sea by the United Nations, the New Zealand Bravery Medal and a US Coast Guard Citation for Bravery for risking his own life to save three shipwrecked sailors.
Conti lives in Barcelona, Spain, and travels around the world speaking to groups about innovation, technology trends, the future, and high adventure.
Maurice Conti | Speaker | TED.com