TED2003
Marvin Minsky: Health and the human mind
Marvin Minsky o zdravlju i ljudskom umu
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Poslušajte pozorno -- zaigran, eklektičan i šarmantno neobavezan govor Marvina Minskog o zdravlju, prenapučenosti i ljudskome umu pun je suptilnosti, mudrosti i tek tračka “ On se šali?” savjeta
Marvin Minsky - AI pioneer
Marvin Minsky is one of the great pioneers of artificial intelligence -- and using computing metaphors to understand the human mind. His contributions to mathematics, robotics and computational linguistics are legendary and far-reaching. Full bio
Marvin Minsky is one of the great pioneers of artificial intelligence -- and using computing metaphors to understand the human mind. His contributions to mathematics, robotics and computational linguistics are legendary and far-reaching. Full bio
Double-click the English transcript below to play the video.
00:18
If you ask people about what part of psychology do they think is hard,
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Ako ljude upitate koji dio psihologije smatraju teškim,
00:24
and you say, "Well, what about thinking and emotions?"
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ako pitate: “ A što je s mislima i emocijama?”
00:27
Most people will say, "Emotions are terribly hard.
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većina će ljudi reći: “ Osjećaji su jako teški.
00:30
They're incredibly complex. They can't -- I have no idea of how they work.
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Upravo nevjerojatno složeni. Oni se ne mogu -- nemam pojma na koji način oni djeluju.
00:36
But thinking is really very straightforward:
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Ali razmišljanje je vrlo pravocrtno:
00:38
it's just sort of some kind of logical reasoning, or something.
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to je tek jedan način logičkog razmatranja, ili slično.
00:42
But that's not the hard part."
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To nije težak dio.”
00:45
So here's a list of problems that come up.
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Dakle, evo popisa problema koji se pojavljuju.
00:47
One nice problem is, what do we do about health?
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Jedan zgodan problem jest: što učiniti po pitanju zdravlja?
00:50
The other day, I was reading something, and the person said
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Neki dan sam čitao nešto gdje je osoba rekla da je
00:54
probably the largest single cause of disease is handshaking in the West.
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vjerojatno najveći pojedinačni razlog bolesti na Zapadu rukovanje.
01:00
And there was a little study about people who don't handshake,
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Prisutno je bilo i malo istraživanje o ljudima koji se ne rukuju
01:04
and comparing them with ones who do handshake.
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naspram onih koji se rukuju.
01:07
And I haven't the foggiest idea of where you find the ones that don't handshake,
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Ne slutim ni izdaleka gdje su pronašli one koji se ne rukuju,
01:12
because they must be hiding.
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jer ti se ljudi zacijelo kriju negdje.
01:15
And the people who avoid that
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Dakle, ljudi koji izbjegavaju rukovanje
01:19
have 30 percent less infectious disease or something.
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imaju 30 posto manje zaraznih bolesti ili slično.
01:23
Or maybe it was 31 and a quarter percent.
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Ili je možda to bilo 31 i četvrtina postotka.
01:26
So if you really want to solve the problem of epidemics and so forth,
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Dakle ako doista želite riješiti problem epidemija i drugih stvari,
01:30
let's start with that. And since I got that idea,
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počnimo s time. Otkad sam došao na tu ideju
01:34
I've had to shake hundreds of hands.
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morao sam se rukovati sa stotinu ljudi.
01:38
And I think the only way to avoid it
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I mislim da je jedini način da se rukovanje izbjegne
01:43
is to have some horrible visible disease,
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imati nekakvu groznu vidljivu bolest,
01:45
and then you don't have to explain.
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tada ne morate ništa objašnjavati.
01:48
Education: how do we improve education?
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Obrazovanje: kako da unaprijedimo obrazovanje?
01:52
Well, the single best way is to get them to understand
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Pa, najbolji način bio bi učiniti da ljudi shvate
01:56
that what they're being told is a whole lot of nonsense.
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da je ono što im se priča jedna velika hrpa besmislica.
01:59
And then, of course, you have to do something
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A tada, naravno, morate učiniti nešto
02:01
about how to moderate that, so that anybody can -- so they'll listen to you.
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kako biste to ograničili kako bi vas bilo tko -- kako bi vas slušali.
02:06
Pollution, energy shortage, environmental diversity, poverty.
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Zagađenje planeta, manjak energije, različitost u okolišu, siromaštvo.
02:10
How do we make stable societies? Longevity.
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Kako da društva učinimo stabilnima? Dug život.
02:14
Okay, there're lots of problems to worry about.
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U redu, postoji mnoštvo problema oko kojih bi trebali brinuti.
02:17
Anyway, the question I think people should talk about --
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U svakom slučaju, pitanje o kojemu mislim da bi ljudi trebali govoriti --
02:19
and it's absolutely taboo -- is, how many people should there be?
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a potpuni je tabu -- jest, koliko bi ljudi uopće trebalo postojati?
02:24
And I think it should be about 100 million or maybe 500 million.
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Ja smatram da bi nas trebalo biti oko 100 ili 500 milijuna.
02:31
And then notice that a great many of these problems disappear.
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I tada bismo primjetili kako većina ovih problema nestaje.
02:36
If you had 100 million people
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Ako imate 100 milijuna ljudi
02:38
properly spread out, then if there's some garbage,
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koji su dobro raspoređeni, ako postoji nekakvo smeće,
02:44
you throw it away, preferably where you can't see it, and it will rot.
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bacite ga, po mogućnosti gdje ga ne možete vidjeti, i ono će istrunuti.
02:51
Or you throw it into the ocean and some fish will benefit from it.
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Ili ga bacite u ocean i dobro će doći nekoj ribi.
02:56
The problem is, how many people should there be?
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Problem je u tome, koliko bi ljudi trebalo biti na svijetu?
02:58
And it's a sort of choice we have to make.
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A to je neka vrsta izbora kojeg moramo napraviti.
03:01
Most people are about 60 inches high or more,
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Većina ljudi visoka je oko 60 inča ( 152.4 cm) ili više,
03:04
and there's these cube laws. So if you make them this big,
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a postoje takozvani kubični zakoni. Tako da ako ih napravite ovako velikima
03:08
by using nanotechnology, I suppose --
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koristeći nanotehnologiju, pretpostavljam --
03:11
(Laughter)
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(Smijeh)
03:12
-- then you could have a thousand times as many.
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-- tada ih možete imati tisuću puta više.
03:14
That would solve the problem, but I don't see anybody
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To bi riješilo problem, ali nisam primjetio da se itko
03:16
doing any research on making people smaller.
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bavi pitanjem smanjivanja ljudi.
03:19
Now, it's nice to reduce the population, but a lot of people want to have children.
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Zgodno bi bilo smanjiti stanovništvo, međutim mnogi ljudi žele imati djecu.
03:24
And there's one solution that's probably only a few years off.
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Postoji jedno rješenje koje bi moglo naići za nekoliko godina.
03:27
You know you have 46 chromosomes. If you're lucky, you've got 23
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Znate da posjedujete 46 kromosoma. Ako ste imali sreće, imate po 23
03:32
from each parent. Sometimes you get an extra one or drop one out,
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od svakog roditelja. Ponekad dobijete jedan viška ili ispustite jedan,
03:38
but -- so you can skip the grandparent and great-grandparent stage
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ali -- tako da možete preskočiti faze praroditelja i šukunbaka i šukundjedova
03:42
and go right to the great-great-grandparent. And you have 46 people
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te prijeći na još stariju generaciju. I zatim imate 46 ljudi
03:47
and you give them a scanner, or whatever you need,
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i date ima skener, ili što god vam je potrebno,
03:50
and they look at their chromosomes and each of them says
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oni potom mogu gledati svoje kromosome te svaki od njih može odlučiti
03:54
which one he likes best, or she -- no reason to have just two sexes
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koji im se sviđa najviše, on ili ona -- nema više čak ni razloga za postojanjem
03:59
any more, even. So each child has 46 parents,
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samo dva spola. Tako da svako dijete ima 46 roditelja,
04:04
and I suppose you could let each group of 46 parents have 15 children.
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i pretpostavljam da možete dopustiti da svaka grupa od 46 roditelja ima po 15 djece.
04:10
Wouldn't that be enough? And then the children
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Ne bi li to bilo dovoljno? I tada bi djeca
04:12
would get plenty of support, and nurturing, and mentoring,
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dobivala dovoljno potpore, njegovanja i mentorstva,
04:16
and the world population would decline very rapidly
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dok bi stanovništvo svijeta vrlo brzo opalo
04:18
and everybody would be totally happy.
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te bi svi bili potpuno sretni.
04:21
Timesharing is a little further off in the future.
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Dijeljenje vremena međutim nalazi se malo dalje u budućnosti.
04:24
And there's this great novel that Arthur Clarke wrote twice,
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Postoji jedan odličan roman koji je Arthur Clarke napisao dva puta,
04:27
called "Against the Fall of Night" and "The City and the Stars."
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zove se “ Ka spuštanju noći” te “ Grad i zvijezde.”
04:31
They're both wonderful and largely the same,
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Oba su divna i većinom ista,
04:34
except that computers happened in between.
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osim što su se u međuvremenu pojavila računala.
04:36
And Arthur was looking at this old book, and he said, "Well, that was wrong.
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I Arthur je pogledao ovu stariju knjigu i rekao: “Pa, ovo je pogrešno.
04:41
The future must have some computers."
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U budućnosti moraju postojati neka računala. “
04:43
So in the second version of it, there are 100 billion
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Tako da u drugoj verziji knjige postoji oko 100 ili
04:48
or 1,000 billion people on Earth, but they're all stored on hard disks or floppies,
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1.000 milijardi ljudi na Zemlji, međutim svi su pohranjeni na hard diskovima ili flopijima
04:56
or whatever they have in the future.
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ili štogod oni imaju u budućnosti.
04:58
And you let a few million of them out at a time.
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I pušta se samo nekoliko milijuna ljudi van.
05:02
A person comes out, they live for a thousand years
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Osoba izađe, živi tisuću godina
05:06
doing whatever they do, and then, when it's time to go back
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radeći što god inače osobe rade, i tada je vrijeme da se vrati natrag
05:12
for a billion years -- or a million, I forget, the numbers don't matter --
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na milijardu godina -- ili milijun, zaboravio sam, brojke nisu važne --
05:16
but there really aren't very many people on Earth at a time.
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ali nema previše ljudi na Zemlji istovremeno.
05:20
And you get to think about yourself and your memories,
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Ljudi počnu razmišljati o sebi i svojim uspomenama,
05:22
and before you go back into suspension, you edit your memories
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i prije nego se vrate na pohranu, mogu urediti svoje uspomene
05:27
and you change your personality and so forth.
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i promijeniti svoju osobnost i tako dalje.
05:30
The plot of the book is that there's not enough diversity,
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Radnja knjige vrti se oko toga da ne postoji dovoljno različitosti,
05:36
so that the people who designed the city
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tako da se ljudi koji su stvorili grad
05:39
make sure that every now and then an entirely new person is created.
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pobrinu da se svako toliko stvori posve nova osoba.
05:43
And in the novel, a particular one named Alvin is created. And he says,
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U romanu je stvoren pojedinac Alvin, koji pomisli da to
05:49
maybe this isn't the best way, and wrecks the whole system.
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možda i nije najbolji način te uništi cijeli taj sustav.
05:53
I don't think the solutions that I proposed
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Ne mislim da su rješenja koja sam predložio
05:55
are good enough or smart enough.
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dovoljno dobra ili pametna.
05:58
I think the big problem is that we're not smart enough
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Mislim da je velik problem u tome što nismo dovoljno pametni
06:02
to understand which of the problems we're facing are good enough.
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da shvatimo koji su od problema s kojima se suočavamo dovoljno dobri.
06:06
Therefore, we have to build super intelligent machines like HAL.
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Zbog toga moramo sagraditi super inteligentne strojeve poput HAL-a.
06:10
As you remember, at some point in the book for "2001,"
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Kao što se sjećate, u jednom trenutku u knjizi “2001”,
06:15
HAL realizes that the universe is too big, and grand, and profound
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HAL uviđa da je svemir prevelik i veličanstven i produhovljen
06:20
for those really stupid astronauts. If you contrast HAL's behavior
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za te glupe astronaute. Ako usporedite HAL-ovo ponašanje
06:24
with the triviality of the people on the spaceship,
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s trivijalnošću ljudi na svemirskom brodu,
06:28
you can see what's written between the lines.
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možete vidjeti što je napisano između redova.
06:31
Well, what are we going to do about that? We could get smarter.
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Što ćemo učiniti u vezi toga? Možemo postati pametniji.
06:34
I think that we're pretty smart, as compared to chimpanzees,
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Mislim da smo poprilično pametni u usporedbi s čimpanzama,
06:39
but we're not smart enough to deal with the colossal problems that we face,
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ali nismo dovoljno pametni kako bismo se nosili s ogromnim problemima s kojim se suočavamo,
06:45
either in abstract mathematics
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bilo to u apstraktnoj matematici
06:47
or in figuring out economies, or balancing the world around.
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ili shvaćanju ekonomije ili u održavanju svijeta u ravnoteži.
06:52
So one thing we can do is live longer.
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Jedna od stvari koje možemo učiniti jest da živimo duže.
06:55
And nobody knows how hard that is,
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Nitko ne zna koliko je to teško,
06:57
but we'll probably find out in a few years.
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ali vjerojatno ćemo doznati za nekoliko godina.
07:00
You see, there's two forks in the road. We know that people live
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Kao što vidite, postoje dvije prepreke na putu. Znamo da ljudi žive
07:03
twice as long as chimpanzees almost,
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gotovo dvostruko duže od čimpanzi,
07:07
and nobody lives more than 120 years,
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a nitko ne živi duže od 120 godina
07:11
for reasons that aren't very well understood.
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zbog razloga koji nisu posve shvaćeni.
07:14
But lots of people now live to 90 or 100,
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Ali mnogo ljudi danas živi 90 ili 100 godina,
07:17
unless they shake hands too much or something like that.
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osim ako se ne rukuju previše ili tako nešto.
07:21
And so maybe if we lived 200 years, we could accumulate enough skills
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Tako da ako bismo živjeli 200 godina , mogli bismo skupiti dovoljno vještina
07:26
and knowledge to solve some problems.
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i znanja kako bismo riješili neke probleme.
07:31
So that's one way of going about it.
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To je dakle jedan način kako tome pristupiti.
07:33
And as I said, we don't know how hard that is. It might be --
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I kao što sam rekao, ne znamo koliko je to teško. Moguće je --
07:36
after all, most other mammals live half as long as the chimpanzee,
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na kraju krajeva, većina drugih sisavaca živi dvostruko kraće od čimpanzi,
07:42
so we're sort of three and a half or four times, have four times
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tako da mi živimo tri i pol ili četiri puta duže, imamo četiri puta
07:45
the longevity of most mammals. And in the case of the primates,
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duži životni vijek od većine sisavaca. A u slučaju primata,
07:51
we have almost the same genes. We only differ from chimpanzees,
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imamo gotovo iste gene. Razlikujemo se od čimpanza ,
07:55
in the present state of knowledge, which is absolute hogwash,
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po trenutnom saznanju, što je potpuna HOGWASH,
08:01
maybe by just a few hundred genes.
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možda samo po nekoliko stotina gena.
08:03
What I think is that the gene counters don't know what they're doing yet.
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Ono što ja mislim jest da brojači gena još uvijek ne znaju što rade.
08:06
And whatever you do, don't read anything about genetics
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I štogod učinili, nemojte nikada čitati bilo što o genetici
08:09
that's published within your lifetime, or something.
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što je izdano tijekom vašeg života ili slično.
08:12
(Laughter)
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(Smijeh)
08:15
The stuff has a very short half-life, same with brain science.
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Sve to ima vrlo kratak poluživot, isto je sa znanošću mozga.
08:19
And so it might be that if we just fix four or five genes,
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Tako da je moguće da ako promijenimo samo četiri ili pet gena,
08:25
we can live 200 years.
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mogli bismo živjeti 200 godina.
08:27
Or it might be that it's just 30 or 40,
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Ili je moguće da je stvar u 30 ili 40 gena,
08:30
and I doubt that it's several hundred.
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a sumnjam da se radi o nekoliko stotina.
08:32
So this is something that people will be discussing
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To je nešto o čemu će raspravljati ljudi
08:36
and lots of ethicists -- you know, an ethicist is somebody
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i puno etičara -- znate, etičar je osoba
08:39
who sees something wrong with whatever you have in mind.
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koja vidi nešto pogrešno u svemu što vam padne na pamet.
08:42
(Laughter)
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(Smijeh)
08:45
And it's very hard to find an ethicist who considers any change
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Vrlo je teško pronaći etičara koji smatra da je vrijedno učiniti bilo kakvu promjenu,
08:49
worth making, because he says, what about the consequences?
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zato što će reći: “A što je s posljedicama?”
08:53
And, of course, we're not responsible for the consequences
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A naravno, nismo odgovorni za posljedice
08:56
of what we're doing now, are we? Like all this complaint about clones.
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onoga što sada činimo? Svi ovo prigovori oko kloniranja na primjer.
09:02
And yet two random people will mate and have this child,
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A ipak, dvoje nasumičnih ljudi spojit će se i imati dijete,
09:05
and both of them have some pretty rotten genes,
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i oboje imaju poprilično loše gene
09:09
and the child is likely to come out to be average.
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i dijete će vrlo vjerojatno ispasti prosječno.
09:13
Which, by chimpanzee standards, is very good indeed.
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Što je po standardima čimpanzi, zapravo vrlo dobro.
09:19
If we do have longevity, then we'll have to face the population growth
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Ako posjedujemo dug životni vijek svejedno ćemo se morati suočiti
09:22
problem anyway. Because if people live 200 or 1,000 years,
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s rastom stanovništva. Ako ljudi žive 200 ili 1.000 godina,
09:26
then we can't let them have a child more than about once every 200 or 1,000 years.
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ne možemo im dopustiti da imaju dijete više od jednom svakih 200 ili 1.000 godina.
09:32
And so there won't be any workforce.
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Tako da neće biti dovoljno radne snage.
09:35
And one of the things Laurie Garrett pointed out, and others have,
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Jedna od stvari koje su Laurie Garret i drugi ljudi istaknuli
09:39
is that a society that doesn't have people
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jest da je društvo bez ljudi
09:44
of working age is in real trouble. And things are going to get worse,
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u radnoj dobi u pravoj nevolji. A stvari će se pogoršavati
09:47
because there's nobody to educate the children or to feed the old.
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jer neće biti koga da obrazuje djecu ili nahrani stare.
09:53
And when I'm talking about a long lifetime, of course,
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I kada govorim o dugom životnom vijeku,
09:55
I don't want somebody who's 200 years old to be like our image
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ne želim da netko tko je 200 godina star bude poput naše vizije
10:01
of what a 200-year-old is -- which is dead, actually.
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200-godišnjaka -- što je mrtav, zapravo.
10:05
You know, there's about 400 different parts of the brain
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Znate, postoji oko 400 različitih dijelova mozga
10:07
which seem to have different functions.
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koji svi imaju drugačije funkcije.
10:09
Nobody knows how most of them work in detail,
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Nitko ne zna u pojedinost kako većina njih radi,
10:12
but we do know that there're lots of different things in there.
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ali znamo da postoji mnoštvo različitih stvari u mozgu.
10:16
And they don't always work together. I like Freud's theory
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A one ne rade uvijek zajedno. Sviđa mi se Freudova teorija
10:18
that most of them are cancelling each other out.
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da se one međusobno isključuju.
10:22
And so if you think of yourself as a sort of city
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Tako da ako razmišljate o sebi kao o gradu
10:26
with a hundred resources, then, when you're afraid, for example,
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sa stotinu izvora, tada ako ste uplašeni na primjer,
10:32
you may discard your long-range goals, but you may think deeply
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moguće je da ćete odbaciti svoje dugoročne ciljeve, ali ćete razmišljati duboko
10:36
and focus on exactly how to achieve that particular goal.
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i usredotočiti se na to kako postići jedan određeni cilj.
10:40
You throw everything else away. You become a monomaniac --
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Sve ostalo ćete odbaciti. Postajete monomanijak --
10:43
all you care about is not stepping out on that platform.
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sve o čemu se brinete jest da riješite taj određeni problem.
10:47
And when you're hungry, food becomes more attractive, and so forth.
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Također, kada ste gladni hrana postaje privlačnija, itd.
10:51
So I see emotions as highly evolved subsets of your capability.
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Tako da ja vidim osjećaje kao visoko razvijene podvrste vaših sposobnosti.
10:57
Emotion is not something added to thought. An emotional state
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Osjećaj nije nešto što je nadodano na misao. Osjećajno stanje
11:01
is what you get when you remove 100 or 200
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jest ono što dobijete kada uklonite 100 ili 200
11:05
of your normally available resources.
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vaših uobičajenih izvora.
11:08
So thinking of emotions as the opposite of -- as something
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Razmišljati o osjećajima kao o suprotnosti -- kao o nečemu
11:11
less than thinking is immensely productive. And I hope,
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manjem od razmišljanja je neizmjerno korisno. Nadam se
11:15
in the next few years, to show that this will lead to smart machines.
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da će ovo za nekoliko godina dovesti do pametnih strojeva.
11:19
And I guess I better skip all the rest of this, which are some details
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I pretpostavljam da je bolje da preskočim ostatak ovoga, što su neki detalji
11:22
on how we might make those smart machines and --
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o tome kako da sagradimo te pametne strojeve --
11:27
(Laughter)
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(Smijeh)
11:32
-- and the main idea is in fact that the core of a really smart machine
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-- i glavna ideja jest da je srž doista pametnog stroja
11:37
is one that recognizes that a certain kind of problem is facing you.
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u tome da može prepoznati određenu vrstu problema s kojim se suočavamo.
11:42
This is a problem of such and such a type,
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Ovo je problem te i te vrste,
11:45
and therefore there's a certain way or ways of thinking
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tako da postoji određeni način ili načini razmišljanja
11:50
that are good for that problem.
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koji su pogodni za ovakav problem.
11:52
So I think the future, main problem of psychology is to classify
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Tako da mislim da će u budućnosti glavni problem u psihologiji biti svrstati
11:56
types of predicaments, types of situations, types of obstacles
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vrste preduvjeta, vrste situacija i prepreka
12:00
and also to classify available and possible ways to think and pair them up.
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te također razvrstati dostupne i moguće načine razmišljanja te ih spariti.
12:06
So you see, it's almost like a Pavlovian --
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To je gotovo poput uvjetovanja --
12:09
we lost the first hundred years of psychology
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izgubili smo prvih stotinu godina psihologije
12:11
by really trivial theories, where you say,
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na vrlo trivijalne teorije gdje se raspravlja o tome
12:14
how do people learn how to react to a situation? What I'm saying is,
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kako ljudi reagiraju na određene situacije. Ono što govorim jest da
12:20
after we go through a lot of levels, including designing
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nakon što prođemo kroz mnoštvo razina, uključujući stvaranje
12:25
a huge, messy system with thousands of ports,
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ogromnog neurednog sustava s tisuću ulaza,
12:28
we'll end up again with the central problem of psychology.
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opet ćemo se naći pred središnjim problemom psihologije.
12:32
Saying, not what are the situations,
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Govoriti ne o tome kakve su situacije
12:35
but what are the kinds of problems
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već kakvi su problemi
12:37
and what are the kinds of strategies, how do you learn them,
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i strategije, kako ih naučiti,
12:40
how do you connect them up, how does a really creative person
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kako ih povezivati, kako doista kreativna osoba
12:43
invent a new way of thinking out of the available resources and so forth.
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može izmisliti nov način razmišljanja iz već dostupnih izvora i tako dalje.
12:48
So, I think in the next 20 years,
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Mislim da se u idućih 20 godina
12:50
if we can get rid of all of the traditional approaches to artificial intelligence,
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možemo riješiti svih tradicionalnih pristupa umjetnoj inteligenciji
12:55
like neural nets and genetic algorithms
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kao što su neuralne mreže i genetski algoritmi
12:57
and rule-based systems, and just turn our sights a little bit higher to say,
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i sustavi upravljani pravilima te samo postaviti naš pogled malo više
13:03
can we make a system that can use all those things
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kako bismo uvidjeli možemo li razviti sustav koji može koristiti sve te stvari
13:05
for the right kind of problem? Some problems are good for neural nets;
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za pravu vrstu problema. Neki problemi su dobri za neuralne mreže;
13:09
we know that others, neural nets are hopeless on them.
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znamo da su neuralne mreže beskorisne za neke druge.
13:12
Genetic algorithms are great for certain things;
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Genetski algoritmi su odlični za određene stvari;
13:15
I suspect I know what they're bad at, and I won't tell you.
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pretpostavljam da znam za što su loši, ali vam neću reći.
13:19
(Laughter)
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(Smijeh)
13:20
Thank you.
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Hvala.
13:22
(Applause)
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(Pljesak)
ABOUT THE SPEAKER
Marvin Minsky - AI pioneerMarvin Minsky is one of the great pioneers of artificial intelligence -- and using computing metaphors to understand the human mind. His contributions to mathematics, robotics and computational linguistics are legendary and far-reaching.
Why you should listen
Marvin Minsky is the superstar-elder of artificial intelligence, one of the most productive and important cognitive scientists of the century, and the leading proponent of the Society of Mind theory. Articulated in his 1985 book of the same name, Minsky's theory says intelligence is not born of any single mechanism, but from the interaction of many independent agents. The book's sequel,The Emotion Machine (2006), says similar activity also accounts for feelings, goals, emotions and conscious thoughts.
Minsky also pioneered advances in mathematics, computational linguistics, optics, robotics and telepresence. He built SNARC, the first neural network simulator, some of the first visual scanners, and the first LOGO "turtle." From his headquarters at MIT's Media Lab and the AI Lab (which he helped found), he continues to work on, as he says, "imparting to machines the human capacity for commonsense reasoning."
Marvin Minsky | Speaker | TED.com