Hod Lipson: Robots that are "self-aware"

117,286 views ・ 2007-10-13

TED


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Traducător: Tita Mihai Corector: Mirzac Iulian
00:25
So, where are the robots?
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Deci, unde sunt robotii?
00:27
We've been told for 40 years already that they're coming soon.
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De 40 de ani ni se spune ca vor veni in curand.
00:30
Very soon they'll be doing everything for us.
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In curand o sa faca totul in locul nostru:
00:33
They'll be cooking, cleaning, buying things, shopping, building. But they aren't here.
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o sa gateasca,o sa faca curat,o sa faca cumparaturi, o sa construiasca.Dar nu sunt aici.
00:38
Meanwhile, we have illegal immigrants doing all the work,
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Intre timp ,avem imigranti ilegali care fac toata treaba,
00:42
but we don't have any robots.
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dar nu avem nici un robot.
00:44
So what can we do about that? What can we say?
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Asa ca ce putem sa facem? Ce putem sa spunem?
00:48
So I want to give a little bit of a different perspective
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As vrea sa va arat o modalitate alternativa
00:52
of how we can perhaps look at these things in a little bit of a different way.
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despre cum ne putem uita la lucruri intr-un mod putin diferit.
00:58
And this is an x-ray picture
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Aceasta este o radiografie
01:00
of a real beetle, and a Swiss watch, back from '88. You look at that --
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a unui gandac adevarat, si a unui ceas elvetian, din '88.Te uiti la --
01:05
what was true then is certainly true today.
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ce era adevarat atunci cu siguranta este adevarat si astazi.
01:07
We can still make the pieces. We can make the right pieces.
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Inca mai putem sa fabricam piesele, putem face piesele corecte.
01:10
We can make the circuitry of the right computational power,
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putem sa facem o placuta cu circuite de calcul,
01:13
but we can't actually put them together to make something
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dar nu putem sa le punem la un loc sa facem ceva anume
01:16
that will actually work and be as adaptive as these systems.
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care sa functioneze cu adevarat si sa fie capabil sa se adapteze la fel ca aceste sisteme.
01:21
So let's try to look at it from a different perspective.
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Asa ca sa incercam sa privim lucrurile dintr-o alta perspectiva.
01:23
Let's summon the best designer, the mother of all designers.
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Sa-l luam pe cel mai bun designer, cel mai bun designer dintre toti:
01:27
Let's see what evolution can do for us.
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sa vedem ce poate face evolutia pentru noi.
01:30
So we threw in -- we created a primordial soup
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Asa ca am amestecat-- am creat supa primordiala
01:34
with lots of pieces of robots -- with bars, with motors, with neurons.
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cu multe bucati de roboti : cu fiare, cu motoare , cu neuroni.
01:38
Put them all together, and put all this under kind of natural selection,
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Le adunam pe toate la un loc, si le supunem unui fel de proces natural de selectie,
01:42
under mutation, and rewarded things for how well they can move forward.
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unui proces de transformare, si vedem cat de bine au sa evolueze.
01:46
A very simple task, and it's interesting to see what kind of things came out of that.
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O sarcina foarte simpla, si e interesant de vazut ce fel de chestii rezulta.
01:52
So if you look, you can see a lot of different machines
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Asa ca daca va uitati, o sa vedeti o gramada de masinarii diferite
01:55
come out of this. They all move around.
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care au iesit din asta.Toate se misca,
01:57
They all crawl in different ways, and you can see on the right,
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intr-un fel sau altul,puteti vedea in dreapta,
02:01
that we actually made a couple of these things,
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chiar am creat niste chestii de astea,
02:03
and they work in reality. These are not very fantastic robots,
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si chiar functioneaza. Nu sunt cine stie ce roboti,
02:06
but they evolved to do exactly what we reward them for:
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dar au evoluat si au ajuns sa facea ce le-am cerut:
02:10
for moving forward. So that was all done in simulation,
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se mearga inainte.Toate aceastea au fost facute intr-o simulare,
02:13
but we can also do that on a real machine.
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dar putem face asta si cu o masinarie reala.
02:15
Here's a physical robot that we actually
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Acesta este un robot pe care avem
02:20
have a population of brains,
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o populatie de creiere,
02:23
competing, or evolving on the machine.
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care concureaza unele cu celelalte, sau evoluaza, pe robot.
02:25
It's like a rodeo show. They all get a ride on the machine,
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E ca la un rodeo show: toti apuca sa controleze masinaria,
02:28
and they get rewarded for how fast or how far
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si sunt recompensati pentru cat de repede sau cat de departe
02:31
they can make the machine move forward.
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au facut masinaria sa mearga.
02:33
And you can see these robots are not ready
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Dupa cum vedeti acesti roboti nu sunt gata inca
02:35
to take over the world yet, but
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sa preia controlul asupra lumii,dar
02:38
they gradually learn how to move forward,
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invata treptat cum sa se miste inainte,
02:40
and they do this autonomously.
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si fac aceste lucru in mod autonom.
02:43
So in these two examples, we had basically
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Deci in aceste doua exemple, am avut de fapt
02:47
machines that learned how to walk in simulation,
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masinarii care au invatat cum sa mearga intr-o simulare,
02:50
and also machines that learned how to walk in reality.
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si masinarii care au invatat sa mearga in realitate.
02:52
But I want to show you a different approach,
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Dar vreau sa va arat o abordare diferita,
02:54
and this is this robot over here, which has four legs.
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si acesta este robotul, aici, care are patru picioare,
03:00
It has eight motors, four on the knees and four on the hip.
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are opt motoare , patru la genunchi si patru la solduri.
03:02
It has also two tilt sensors that tell the machine
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Mai are si doi senzori care ii spun masinariei
03:05
which way it's tilting.
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in ce parte sa se incline.
03:08
But this machine doesn't know what it looks like.
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Dar aceasta masinarie nu stie cum arata.
03:10
You look at it and you see it has four legs,
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Tu te uiti la ea si vezi ca are patru picioare,
03:12
the machine doesn't know if it's a snake, if it's a tree,
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masinaria nu stie daca e un sarpe, daca e un copac,
03:14
it doesn't have any idea what it looks like,
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nu are nici o idee despre cum arata,
03:17
but it's going to try to find that out.
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dar o sa incerce sa afle.
03:19
Initially, it does some random motion,
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Initial, o sa incerce niste miscari aleatorii,
03:21
and then it tries to figure out what it might look like.
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si apoi incearca sa afle cum arata --
03:24
And you're seeing a lot of things passing through its minds,
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si vedeti cum o gramada de lucruri ii trec prin minte,
03:26
a lot of self-models that try to explain the relationship
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o gramada de auto-modele care incearca sa explice relatia
03:30
between actuation and sensing. It then tries to do
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dintre actiune si raspuns-- si apoi incearca
03:33
a second action that creates the most disagreement
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o a doua actiune care creaza dezacord
03:37
among predictions of these alternative models,
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printre predictiile modelelor alternative,
03:39
like a scientist in a lab. Then it does that
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ca un om de stiinta intr-un laborator. Apoi face asta
03:41
and tries to explain that, and prune out its self-models.
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si incearca sa explice, si sa isi intreaca concurentii.
03:45
This is the last cycle, and you can see it's pretty much
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Acesta e ultimul ciclu, si dupa cum puteti vedea
03:48
figured out what its self looks like. And once it has a self-model,
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si-a dat seama cum arata,odata ce a avut un model dupa care sa se ia,
03:52
it can use that to derive a pattern of locomotion.
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se poate lua dupa asta ca sa isi creeze un tipar de locomotie.
03:56
So what you're seeing here are a couple of machines --
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Deci ce vedeti aici este o adunatura de masinarii--
03:58
a pattern of locomotion.
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un tipar de locomotie.
04:00
We were hoping that it wass going to have a kind of evil, spidery walk,
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Speram ca o sa aiba un mers "smecher" ,ca al unui paianjen,
04:04
but instead it created this pretty lame way of moving forward.
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dar in schimb,si-a creat acest mod nasol de a se misca inspre inainte.
04:08
But when you look at that, you have to remember
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Dar cand te uiti la asta , trebuie sa tii cont
04:11
that this machine did not do any physical trials on how to move forward,
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ca aceasta masinarie nu stia cum sa se miste inainte,
04:17
nor did it have a model of itself.
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nici nu stia cum arata.
04:19
It kind of figured out what it looks like, and how to move forward,
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Si-a dat seama cum arata , si cum sa se miste,
04:22
and then actually tried that out.
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si apoi a facut o incercare.
04:26
(Applause)
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(Aplauze)
04:31
So, we'll move forward to a different idea.
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Asa, se ne indreptam atentia spre o idee diferita.
04:35
So that was what happened when we had a couple of --
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Deci asta sa intamplat cand am avut o gramada de --
04:40
that's what happened when you had a couple of -- OK, OK, OK --
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asta sa intamplat cand am avut o gramada de -- Ok ,Ok ,Ok--
04:44
(Laughter)
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(Rasete)
04:46
-- they don't like each other. So
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-- nu se plac.Deci
04:48
there's a different robot.
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e un robot diferit.
04:51
That's what happened when the robots actually
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Asta sa intamplat cand robotii
04:53
are rewarded for doing something.
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au fost recompensati pentru ca fac ceva.
04:55
What happens if you don't reward them for anything, you just throw them in?
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Dar ce se intampla cand nu ii recompensezi, doar ii arunci acolo?
04:58
So we have these cubes, like the diagram showed here.
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Deci avem cuburile astea,dupa cum arata diagrama asta.
05:01
The cube can swivel, or flip on its side,
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Cubul poate sa pivoteze ,sau sa sara pe o parte,
05:04
and we just throw 1,000 of these cubes into a soup --
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si aruncam 1,000 de cuburi de astea intr-o supa--
05:08
this is in simulation --and don't reward them for anything,
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asta intr-o simulare-- si nu ii recompensam pentru nimic.
05:10
we just let them flip. We pump energy into this
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ii lasam acolo sa sara. Le dam energie
05:13
and see what happens in a couple of mutations.
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si vedem ce se intampla in cateva mutatii.
05:16
So, initially nothing happens, they're just flipping around there.
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Initial, nimic nu se intampla, doar sar de colo colo.
05:19
But after a very short while, you can see these blue things
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Dar dupa o scurta perioada de timp,puteti vedea aceste chestii albastre
05:23
on the right there begin to take over.
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din dreapta incep sa preia controlul.
05:25
They begin to self-replicate. So in absence of any reward,
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Incep sa se auto-reproduca.Asa ca in absenta vreunei recompense,
05:29
the intrinsic reward is self-replication.
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propria recompensa este auto-reproducerea.
05:32
And we've actually built a couple of these,
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Si chiar am construit cativa din astia ,
05:33
and this is part of a larger robot made out of these cubes.
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si asta e o parte dintr-un robot mai mare facut din aceste cuburi,
05:37
It's an accelerated view, where you can see the robot actually
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e o filmare accelerata, in care puteti vedea cum robotul
05:40
carrying out some of its replication process.
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urmeaza pasii spre procesul de replicare.
05:42
So you're feeding it with more material -- cubes in this case --
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Deci o hranim cu mai mult material-- cuburi in cazul de fata--
05:46
and more energy, and it can make another robot.
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si mai multa energie, si poate face un alt robot.
05:49
So of course, this is a very crude machine,
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Dar desigur , aceasta este o masinarie foarte primitiva,
05:52
but we're working on a micro-scale version of these,
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dar lucram la versiuni microscopice ale acestor masinarii,
05:54
and hopefully the cubes will be like a powder that you pour in.
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si speram ca ,cuburile o sa fie ca o pudra pe care o adaugi.
05:57
OK, so what can we learn? These robots are of course
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OK, deci ce putem invatat? Acesti roboti nu sunt desigur
06:02
not very useful in themselves, but they might teach us something
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foarte folositori, dar ne pot invata cate ceva
06:05
about how we can build better robots,
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despre cum putem sa contruim roboti mai buni,
06:08
and perhaps how humans, animals, create self-models and learn.
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si poate cum oameni , animalele, pot crea auto-modele si invata.
06:13
And one of the things that I think is important
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Si unul din lucrurile pe care il consider important
06:15
is that we have to get away from this idea
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este acela ca trebuie sa ne indepartam de idea
06:17
of designing the machines manually,
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de a proiecta manual masinariile,
06:19
but actually let them evolve and learn, like children,
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si in schimb sa le lasam sa evolueze si sa invete,precum copiii,
06:22
and perhaps that's the way we'll get there. Thank you.
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si poate in felul acesta o sa reusim . Multumesc.
06:24
(Applause)
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(Aplauze)
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