TEDGlobal 2009
Henry Markram: A brain in a supercomputer
Henry Markram Super Bilgisayarda Beyin Olusturuyor
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Henry Markram beynin esrarlarının yakinda çözülebilecegini soyluyor. Akıl hastalığı, hafıza, algı: Bunlar noronlardan ve elektrik sinyallerinden meydana gelmistir ve O, beynin butun 100,000,000,000,000 sinapsını modelleyen super bir bilgisayarla onları bulmayı tasarliyor.
Henry Markram - Neuroscientist
Henry Markram is director of Blue Brain, a supercomputing project that can model components of the mammalian brain to precise cellular detail -- and simulate their activity in 3D. Soon he'll simulate a whole rat brain in real time. Full bio
Henry Markram is director of Blue Brain, a supercomputing project that can model components of the mammalian brain to precise cellular detail -- and simulate their activity in 3D. Soon he'll simulate a whole rat brain in real time. Full bio
Double-click the English transcript below to play the video.
00:18
Our mission is to build
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Bizim amacimiz, insan beyninin
00:21
a detailed, realistic
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ayrintili ve gercekci bir
00:23
computer model of the human brain.
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bilgisayar modelini yapmaktir.
00:25
And we've done, in the past four years,
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Ve gecen son dort yil icinde
00:28
a proof of concept
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bu fikrin ispatini
00:30
on a small part of the rodent brain,
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bir kemirgen beyninin kucuk bir bolumunde gerceklestirdik,
00:33
and with this proof of concept we are now scaling the project up
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ve bu gorusun ispati ile birlikte simdi projemizin olcegini
00:36
to reach the human brain.
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insan beynini olusturmaya kadar buyutuyoruz.
00:39
Why are we doing this?
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Neden bunu yapiyoruz?
00:41
There are three important reasons.
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Bunun uc sebebi var:
00:43
The first is, it's essential for us to understand the human brain
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Birincisi; eger topluma uyum saglamak istiyorsak
00:47
if we do want to get along in society,
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insan beynini anlamak bizim icin temel bir zorunluluktur,
00:49
and I think that it is a key step in evolution.
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ve bunun gelisim icin bir cozum yolu olduguna inaniyorum.
00:53
The second reason is,
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Ikinci sebep;
00:55
we cannot keep doing animal experimentation forever,
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deneylerimizi sonsuza kadar hayvanlar uzerinde yapamayiz,
01:01
and we have to embody all our data and all our knowledge
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tum verileri ve bilgimizi
01:05
into a working model.
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isleyen bir modelde toplamaliyiz.
01:08
It's like a Noah's Ark. It's like an archive.
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Nuh Peygamberin gemisi gibi. Ayni bir arsiv gibi.
01:12
And the third reason is that there are two billion people on the planet
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Ve ucuncu sebeb de; bu gezegende
01:15
that are affected by mental disorder,
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zihinsel bozukluklar yasayan iki milyar insan var,
01:19
and the drugs that are used today
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kullanilan ilaclar da
01:21
are largely empirical.
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cogunlukla deneysel.
01:23
I think that we can come up with very concrete solutions on
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Inaniyorum ki bu hastaliklari tedavi etmek icin
01:26
how to treat disorders.
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kesin cozumler uretebiliriz.
01:29
Now, even at this stage,
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Hatta su asama da dahi
01:32
we can use the brain model
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beynin nasil calistigina dair
01:34
to explore some fundamental questions
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belli basli sorulari arastirmak icin
01:37
about how the brain works.
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bu beyin modelini kullanabiliriz.
01:39
And here, at TED, for the first time,
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Ve burada, TED'de,
01:41
I'd like to share with you how we're addressing
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ilk kez
01:43
one theory -- there are many theories --
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bir teoriyi; ki bir cok teori var,
01:46
one theory of how the brain works.
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beynin nasil calistigina dair bir teoriyi nasil ele aldigimizi sizlerle paylasmak istiyorum.
01:50
So, this theory is that the brain
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Soyle ki; bu teoriye gore, beyin
01:54
creates, builds, a version of the universe,
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evrenin bir versiyonunu yaratir ve kurar.
02:00
and projects this version of the universe,
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Ve evrenin bu uyarlamasini
02:03
like a bubble, all around us.
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etrafimizi saran bir balon gibi tasarlar.
02:07
Now, this is of course a topic of philosophical debate for centuries.
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Elbette, bu konu yuzyillardir tartisilan felsefi bir konudur.
02:11
But, for the first time, we can actually address this,
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Fakat, ilk kez
02:14
with brain simulation,
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bu konuyu beyin simulasyonu ile ele alabiliriz.
02:16
and ask very systematic and rigorous questions,
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ve bu teorinin dogru olup olmadigina dair
02:20
whether this theory could possibly be true.
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sistematik ve ozenle hazirlanmis sorular sorabiliriz.
02:24
The reason why the moon is huge on the horizon
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Ufuktaki Ay'in kocaman olmasinin sebebi
02:27
is simply because our perceptual bubble
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sadece bizim algi sinirimizin
02:30
does not stretch out 380,000 kilometers.
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380.000 kilometreye kadar yayilamamasindandir.
02:34
It runs out of space.
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O bizim algi sinirimizi asar.
02:36
And so what we do is we compare the buildings
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Ve biz de bu yuzden
02:40
within our perceptual bubble,
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algi sinirimiz icinde kalan binalarla kiyaslariz,
02:42
and we make a decision.
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ve bir yargida bulunuruz.
02:44
We make a decision it's that big,
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o kadar buyuk olmamasina ragmen,
02:46
even though it's not that big.
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Ay'in kocaman olduguna karar veririz
02:48
And what that illustrates
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Bu da bize gosterir ki;
02:50
is that decisions are the key things
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yapilan tespitler
02:52
that support our perceptual bubble. It keeps it alive.
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algi sinirimizi destekleyen temel taslardir. Iste bu tespitler onu canli kilar.
02:57
Without decisions you cannot see, you cannot think,
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Kararlar olmaksizin, goremezsiniz, dusunemezsiniz,
02:59
you cannot feel.
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hissedemezsiniz.
03:01
And you may think that anesthetics work
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Anestetik ilaclarin calisma sisteminin
03:03
by sending you into some deep sleep,
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sizin derin uykuya dalmaniza vesile olarak,
03:06
or by blocking your receptors so that you don't feel pain,
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ya da sinirsel uyarı iletimini keserek ise yaradigini, boylelikle aciyi hissetmediginizi sagladigini dusunuyor olabilirsiniz,
03:09
but in fact most anesthetics don't work that way.
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oysa, aslinda anestetik ilaclar bu sekilde islemez.
03:12
What they do is they introduce a noise
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Aslinda yaptiklari islem, beyne ses sinyalleri gondermektir;
03:15
into the brain so that the neurons cannot understand each other.
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ki boylelikle beyindeki noronlar birbirleriyle iletisim kuramazlar.
03:18
They are confused,
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Onlar darmadaginik olmuslardir,
03:20
and you cannot make a decision.
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ve bu yuzden siz bir karar veremezsiniz.
03:23
So, while you're trying to make up your mind
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Yani siz, doktor ya da cerrah ne yapiyor acaba diye anlamaya calisirken,
03:26
what the doctor, the surgeon, is doing
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o vucudunuzu kesmis, desmistir,
03:28
while he's hacking away at your body, he's long gone.
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coktan yanınızdan ayrilmistir bile.
03:30
He's at home having tea.
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evine varmis ve cayini yudumluyordur.
03:32
(Laughter)
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(Kahkahalar)
03:34
So, when you walk up to a door and you open it,
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Yani, bir kapiya varip, onu actiginiz zaman
03:37
what you compulsively have to do to perceive
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algilamak icin yapmak zorunda oldugunuz sey
03:40
is to make decisions,
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tespitler yapmaktir.
03:42
thousands of decisions about the size of the room,
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odanin buyuklugune dair,
03:45
the walls, the height, the objects in this room.
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duvarlarina, yuksekligine ve odadaki nesnelere dair binlerce tespit.
03:48
99 percent of what you see
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Gordugunuzun yuzde doksan dokuzu
03:51
is not what comes in through the eyes.
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goze yansiyan degildir.
03:55
It is what you infer about that room.
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Sizin o oda hakkindaki cikarimlarinizdir.
03:59
So I can say, with some certainty,
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O halde, acikca diyebilirim ki;
04:03
"I think, therefore I am."
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"Dusunuyorum, oyleyse varim."
04:06
But I cannot say, "You think, therefore you are,"
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Fakat, "Dusunuyorsunuz, oyleyse varsiniz." diyemem.
04:10
because "you" are within my perceptual bubble.
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cunku siz benim algi sinirim icindesiniz.
04:15
Now, we can speculate and philosophize this,
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Simdi, bu konuda tartisip, felsefe yapabiliriz,
04:18
but we don't actually have to for the next hundred years.
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fakat, onumuzdeki bir kac yuz yil boyunca bunu gercekten tartismak zorunda degiliz.
04:21
We can ask a very concrete question.
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Cok net bir soru sorabiliriz.
04:23
"Can the brain build such a perception?"
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Beyin boyle bir algilamayi olusturabilir mi?
04:27
Is it capable of doing it?
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Bunu yapabilme istidati var midir?
04:29
Does it have the substance to do it?
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Bunu yapabilecek toz'e sahip midir?
04:31
And that's what I'm going to describe to you today.
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Iste, size bugun anlatacagim konu budur.
04:34
So, it took the universe 11 billion years to build the brain.
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Oyle ki; evrenin beyni olusturmasi on bir milyar yil aldi.
04:38
It had to improve it a little bit.
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Bunu biraz da gelistirmesi gerekti.
04:40
It had to add to the frontal part, so that you would have instincts,
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Ic gudulerimizin olabilmesi icin, beynin on bolumunu eklemesi gerekti
04:43
because they had to cope on land.
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cunku karada hayatta kalmakla basedebilmeliydi.
04:46
But the real big step was the neocortex.
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Fakat, asil buyuk adim neokorteks oldu.
04:50
It's a new brain. You needed it.
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Yeni bir beyin. Buna ihtiyaciniz vardi.
04:52
The mammals needed it
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Memeli hayvanlarin buna ihtiyaci vardi
04:54
because they had to cope with parenthood,
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cunku ebebeyn olabilmek icin
04:58
social interactions,
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sosyal iletisimlerle
05:00
complex cognitive functions.
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bilmeye veya kavramaya iliskin karmasik fonksiyonlarla basedebilmesi icin bu gerekliydi.
05:03
So, you can think of the neocortex
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Yani, neokorteks'i bugun aslinda
05:05
actually as the ultimate solution today,
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bildigimiz evrenin nihai cozumu olarak
05:10
of the universe as we know it.
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dusunebilirsiniz.
05:13
It's the pinnacle, it's the final product
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Evrenin urettigi zirve,
05:15
that the universe has produced.
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en son olusum
05:19
It was so successful in evolution
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Evrimde oylesine basariliydi ki;
05:21
that from mouse to man it expanded
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noronlarin sayisi, neredeyse urperti veren bu organi,
05:23
about a thousandfold in terms of the numbers of neurons,
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yapiyi gelistirebilmek icin
05:26
to produce this almost frightening
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fareden insana kadar
05:29
organ, structure.
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bin misli artti.
05:32
And it has not stopped its evolutionary path.
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ve neokorteks evrimsel gelisimine son vermis degildir.
05:35
In fact, the neocortex in the human brain
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Aslinda, insan beynindeki neokorteks
05:37
is evolving at an enormous speed.
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inanilmaz bir hizla gelismektedir.
05:40
If you zoom into the surface of the neocortex,
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Eger neokorteks'in yuzeyini buyultürseniz,
05:42
you discover that it's made up of little modules,
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bilgisayardaki gibi kucuk modullerden,
05:45
G5 processors, like in a computer.
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G5 islemcilerinden, meydana geldigini farkedersiniz.
05:47
But there are about a million of them.
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fakat, bunlarin sayisi milyonlarcadir.
05:50
They were so successful in evolution
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Evrimde oylesine basariliydi ki;
05:52
that what we did was to duplicate them
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bizim yaptigimiz islem, kafatasinda hic yer kalmayacak kadar
05:54
over and over and add more and more of them to the brain
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onlari tekrar tekrar,
05:56
until we ran out of space in the skull.
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defalarca kopyalamakti.
05:59
And the brain started to fold in on itself,
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Ve beyin kendisinde katlanmaya basladi,
06:01
and that's why the neocortex is so highly convoluted.
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iste bu yuzden neokorteks bu kadar yogun sarilmistir.
06:04
We're just packing in columns,
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Biz sadece kolonlar halinde toparliyoruz;
06:06
so that we'd have more neocortical columns
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ki boylelikle daha karmasik fonksiyonlari meydana getirebilmek icin
06:09
to perform more complex functions.
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daha fazla neokortikal kolonlarimiz olabilsin.
06:12
So you can think of the neocortex actually as
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Yani neokorteks'in aslinda
06:14
a massive grand piano,
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bir milyon tuslu,
06:16
a million-key grand piano.
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kocaman bir piyano gibi oldugunu dusunebilirsiniz.
06:19
Each of these neocortical columns
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Her bir neokortal kolon
06:21
would produce a note.
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bir nota sesi cikartir.
06:23
You stimulate it; it produces a symphony.
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Onu harekete gecirirsiniz ve bir senfoni olusur.
06:26
But it's not just a symphony of perception.
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Fakat bu sadece bir algi senfonisi olmakla kalmaz,
06:29
It's a symphony of your universe, your reality.
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bu sizin evreninizin senfonisi, sizin gerceginiz haline gelir.
06:32
Now, of course it takes years to learn how
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Elbette, bir milyon tuslu pianoyu calmayi ogrenmek
06:35
to master a grand piano with a million keys.
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uzmanlasmak, yillarinizi alir.
06:38
That's why you have to send your kids to good schools,
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Iste bu yuzden cocuklarinizi iyi okullara, mumkunse
06:40
hopefully eventually to Oxford.
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nihayetinde Oxford'a, gondermeniz gerekir.
06:42
But it's not only education.
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Ancak, bu sadece egitimle kalmaz.
06:45
It's also genetics.
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genetik ozellikler de bunda rol oynar.
06:47
You may be born lucky,
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Sansli dogmus olabilirsiniz,
06:49
where you know how to master your neocortical column,
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ya da neokortal kolonunuzu uzmanlastirma bilgisine vakif olabilirsiniz
06:53
and you can play a fantastic symphony.
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ve boylelikle de muhtesem bir senfoni ortaya koyabilirsiniz.
06:55
In fact, there is a new theory of autism
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Aslinda, otizm'in
06:58
called the "intense world" theory,
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"Yogun Dunya" ismini verdigi yeni bir teorisi vardir;
07:00
which suggests that the neocortical columns are super-columns.
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ki bu teoriye gore; neokortikal kolonlarin super kolonlar oldugu ileri surulur.
07:04
They are highly reactive, and they are super-plastic,
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Son derece tepkisel ve super esnek yapilardir,
07:08
and so the autists are probably capable of
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ki; otizm hastalari,
07:11
building and learning a symphony
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bizim inanamayacagimiz bir senfoniyi olusturma
07:13
which is unthinkable for us.
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ve ogrenebilme yetisine sahip olabilirler.
07:15
But you can also understand
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Ancak, sunu da kabul etmelisiniz ki;
07:17
that if you have a disease
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eger bu kolonlar icerisinde
07:19
within one of these columns,
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bir hastaliginiz varsa,
07:21
the note is going to be off.
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o nota kapali olacaktir.
07:23
The perception, the symphony that you create
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Algi, yani yarattiginiz senfoni
07:25
is going to be corrupted,
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bozuk olacak,
07:27
and you will have symptoms of disease.
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ve sizde hastaligin belirtileri ortaya cikacaktir.
07:30
So, the Holy Grail for neuroscience
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Yani, Nöroloji bilimi icin kutsal kase,
07:34
is really to understand the design of the neocoritical column --
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neokortical kolonun tasarimini cozebilmektir.
07:38
and it's not just for neuroscience;
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ve bu sadece Noroloji bilimi icin degil,
07:40
it's perhaps to understand perception, to understand reality,
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algiyi anlayabilmek, gercegi okuyabilmek,
07:43
and perhaps to even also understand physical reality.
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ve hatta fiziksel gercegi cozebilmek icin de cok onemlidir.
07:47
So, what we did was, for the past 15 years,
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Iste, son on bes yildir bizim yaptigimiz da
07:50
was to dissect out the neocortex, systematically.
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neokorteks'i sistematik olarak parcalara ayirmak ve incelemek oldu.
07:54
It's a bit like going and cataloging a piece of the rainforest.
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Bu calisma, gidip yagmur ormanlarinin bir bolumunun kataloğunu hazırlamaya benzetilebilir.
07:58
How many trees does it have?
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Orada kac tane agac vardir?
08:00
What shapes are the trees?
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Bu agaclarin sekilleri nasildir?
08:02
How many of each type of tree do you have? Where are they positioned?
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Her turden kac tane agac var? Nerelere yerlesmisler?
08:05
But it's a bit more than cataloging because you actually have to
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Ancak bu calisma, kataloglamadan daha kapsamlidir cunku
08:07
describe and discover all the rules of communication,
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iletisim ve baglanti kurallarini
08:11
the rules of connectivity,
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tasvir etmek ve ortaya cikarmak zorundasiniz;
08:13
because the neurons don't just like to connect with any neuron.
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cunku noronlar birbiriyle gelisiguzel baglanti kurmazlar.
08:16
They choose very carefully who they connect with.
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Hangi noronla baglanti kuracaklarini dikkatle tespit ederler.
08:19
It's also more than cataloging
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Katologlamadan daha kapsamli olmasinin diger bir sebebi;
08:22
because you actually have to build three-dimensional
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onlarin uc boyutlu dijital orneklerini
08:24
digital models of them.
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bilfiil olusturmanizi gerektirmesidir.
08:26
And we did that for tens of thousands of neurons,
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Ve biz bunu binlerce noron uzerinde gerceklestirdik,
08:28
built digital models of all the different types
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buldugumuz farkli tur noronlarin
08:31
of neurons we came across.
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dijital orneklerini olusturduk.
08:33
And once you have that, you can actually
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Iste bunu bir kez gerceklestirdiginiz zaman
08:35
begin to build the neocortical column.
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neokortal kolonu olusturmaya baslayabilirsiniz.
08:39
And here we're coiling them up.
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Iste burada onlari sariyoruz.
08:42
But as you do this, what you see
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Bunu yaptikca fark ediyoruz ki;
08:45
is that the branches intersect
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dallar
08:47
actually in millions of locations,
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milyonlarca yerde kesisiyorlar
08:50
and at each of these intersections
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ve her bir kesisim noktasinda
08:53
they can form a synapse.
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iki neronun birleştiği yeri; sinaps'i olusturabilirler.
08:55
And a synapse is a chemical location
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Sinaps, noronlarin bibirleriyle iletisim kurduklari,
08:57
where they communicate with each other.
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kimyasal bir noktadir.
09:00
And these synapses together
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Bu sinapslar beraberce
09:02
form the network
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bu agi
09:04
or the circuit of the brain.
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ya da beynin devrelerini olustururlar.
09:07
Now, the circuit, you could also think of as
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Iste, bu devreyi
09:11
the fabric of the brain.
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beynin dokusu olarak dusunebilirsiniz.
09:13
And when you think of the fabric of the brain,
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Ve beynin dokusunu dusundugunuzde
09:16
the structure, how is it built? What is the pattern of the carpet?
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bu yapi nasil meydana gelmistir diye sorarsiniz? Bu halinin modeli nedir?
09:20
You realize that this poses
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Fark edersiniz ki;
09:22
a fundamental challenge to any theory of the brain,
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bu, beyin konusundaki tum teoriler icin bir engel teskil eder
09:26
and especially to a theory that says
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ozellikle de,
09:28
that there is some reality that emerges
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bu halidan, iste belli bir modeli olan bu halidan,
09:30
out of this carpet, out of this particular carpet
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bir gercek cikarabilecegini one suren
09:33
with a particular pattern.
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teoriye meydan okur.
09:35
The reason is because the most important design secret of the brain
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Bunun sebebi, beynin olusumundaki en onemli sir :
09:38
is diversity.
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cesitliliktir.
09:40
Every neuron is different.
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Her bir noron farklidir.
09:42
It's the same in the forest. Every pine tree is different.
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Tipki orman orneginde oldugu gibi. Her bir cam agaci farklidir.
09:44
You may have many different types of trees,
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Degisik turler olabilir,
09:46
but every pine tree is different. And in the brain it's the same.
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fakat, her bir cam agaci farklidir ve beyin de iste aynen boyledir.
09:49
So there is no neuron in my brain that is the same as another,
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Oyle ki; beynimdeki hic bir noron bir digeri ile ayni degildir
09:52
and there is no neuron in my brain that is the same as in yours.
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ve benim beynimdeki hic bir noron sizin beynininizdeki noronun aynisi degildir.
09:55
And your neurons are not going to be oriented and positioned
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Ve sizin noronlariniz da ayni sekilde yonlendirilmis
09:58
in exactly the same way.
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veya konumlanmis olmayacaktir.
10:00
And you may have more or less neurons.
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Ve hatta; daha cok ya da daha az sayida noronlariniz olabilir.
10:02
So it's very unlikely
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Ayni dokuya ya da devre sistemine
10:04
that you got the same fabric, the same circuitry.
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sahip olmaniz mumkun degildir.
10:08
So, how could we possibly create a reality
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O halde nasil olur da
10:10
that we can even understand each other?
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birbirimizi anlayabilecegimiz bir gercekligi yaratabilmemiz mumkun olabilir?
10:13
Well, we don't have to speculate.
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Aslinda bunun uzerine mütalaa etmemize hic gerek yok.
10:15
We can look at all 10 million synapses now.
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Simdi 10 milyon sinaps'in hepsine bakabiliriz.
10:18
We can look at the fabric. And we can change neurons.
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Dokusuna bakabiliriz. Ve noronlari degistirebiliriz.
10:21
We can use different neurons with different variations.
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Degisik noronlari, farkli varyasyonlarda kullanabiliriz.
10:23
We can position them in different places,
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Onlari farkli konumlara yerlestirebilir,
10:25
orient them in different places.
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farkli yerlere yonlendirebiliriz.
10:27
We can use less or more of them.
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Onlari daha cok ya da daha az sayida kullanabiliriz.
10:29
And when we do that
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Iste bunu yaptigimiz zaman
10:31
what we discovered is that the circuitry does change.
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devre sisteminin degistini fark ettik.
10:34
But the pattern of how the circuitry is designed does not.
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Fakat devre sisteminin orulus dokusu degismez
10:41
So, the fabric of the brain,
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Yani beynin dokusu
10:43
even though your brain may be smaller, bigger,
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beyniniz daha kucuk ya da buyuk olsa da
10:45
it may have different types of neurons,
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farkli sinir hucreleri olsa da
10:48
different morphologies of neurons,
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sinir hucrelerinin
10:50
we actually do share
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farkli morfolojisi olsa da
10:53
the same fabric.
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OZde ayni dokuyu paylasiyoruz.
10:55
And we think this is species-specific,
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Ve inaniyoruz ki; bu da her canli turunde o ture ozgudur.
10:57
which means that that could explain
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ki bu da nicin baska canli turleriyle iletisim kuramadigimizin
10:59
why we can't communicate across species.
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sebebini aciklar.
11:01
So, let's switch it on. But to do it, what you have to do
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Gelin simdi bunu devreye sokalim, fakat onu yapabilmeniz icin once
11:04
is you have to make this come alive.
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bunu hayata gecirmek zorundasiniz.
11:06
We make it come alive
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Bunu formullerle, bir cok matematik denklemlerle
11:08
with equations, a lot of mathematics.
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hayata geciriyoruz.
11:10
And, in fact, the equations that make neurons into electrical generators
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Aslinda, sinir hucrelerini elektrik ureticilerine donduren denklemleri
11:14
were discovered by two Cambridge Nobel Laureates.
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Cambridge'den, Nobel odullu iki kisi tarafindan kesfedilmistir.
11:17
So, we have the mathematics to make neurons come alive.
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Yani, sinir hucrelerini hayata gecirecek matematigi biliyoruz.
11:20
We also have the mathematics to describe
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Sinir hucrelerinin bilgiyi nasil topladigini
11:22
how neurons collect information,
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ve birbirleriyle iletisim kurmak icin nasil
11:25
and how they create a little lightning bolt
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kucuk bir simsek olusturduklarini
11:28
to communicate with each other.
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aciklayabilecek matematigi de biliyoruz.
11:30
And when they get to the synapse,
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Iste sinaps'a vardiklarinda
11:32
what they do is they effectively,
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sinaps'a gercekten,
11:34
literally, shock the synapse.
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tesirli bir sekilde sok etkisi yaparlar
11:37
It's like electrical shock
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Bu, sinapslardan kimyasal maddeleri
11:39
that releases the chemicals from these synapses.
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yayan elektrik bir sok gibidir.
11:42
And we've got the mathematics to describe this process.
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Bu islemi aciklayacak matematigi de biliyoruz.
11:45
So we can describe the communication between the neurons.
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Yani, sinir hucreleri arasindaki iletisimi aciklayabiliriz.
11:49
There literally are only a handful
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Neokorteks'in hareketinin benzerini yapmaniz gereken,
11:52
of equations that you need to simulate
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gercekten de cok az sayida
11:54
the activity of the neocortex.
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formul vardir.
11:56
But what you do need is a very big computer.
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Fakat, bunun icin cok buyuk bir bilgisayara ihtiyaciniz var.
11:59
And in fact you need one laptop
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Aslinda, sadece bir tek noronun tum hesaplamalarini yapabilmek icin bile
12:01
to do all the calculations just for one neuron.
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bir dizustu bilgisayara ihtiyac vardir.
12:04
So you need 10,000 laptops.
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O halde 10,000 tane dizustu bilgisayara ihtiyaciniz olacaktir.
12:06
So where do you go? You go to IBM,
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Bunun icin nereye gitmeniz gerekir? IBM'e gidersiniz
12:08
and you get a supercomputer, because they know how to take
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ve super bir bilgisayar alirsiniz,
12:10
10,000 laptops and put it into the size of a refrigerator.
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cunku onlar 10,000 adet dizustu bilgisayari alip, bir buzdolabi buyuklugune nasil getireceklerini biliyorlar.
12:14
So now we have this Blue Gene supercomputer.
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Iste simdi "Mavi Gen" (Blue Gene) super bir bilgisayarimiz oldu.
12:17
We can load up all the neurons,
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Tum sinir hucrelerini,
12:19
each one on to its processor,
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her birini bu bilgisayarin islemcilerine yukleyebiliriz,
12:21
and fire it up, and see what happens.
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calistirir ve olacaklari goruruz.
12:25
Take the magic carpet for a ride.
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Sihirli halida bir yolculuga cikariz.
12:28
Here we activate it. And this gives the first glimpse
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Burada bunu harekete geciriyoruz ve
12:31
of what is happening in your brain
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bir uyari oldugu zaman beyninizde neler oldugunun
12:33
when there is a stimulation.
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ilk goruntusunu veriyor.
12:35
It's the first view.
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Bu ilk goruntu.
12:37
Now, when you look at that the first time, you think,
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Simdi, buna ilk baktiginizda
12:39
"My god. How is reality coming out of that?"
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"Aman Allah'im. Buradan nasil bir gerceklik cikabilir ki?" diye dusunebilirsiniz.
12:44
But, in fact, you can start,
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Fakat, aslinda
12:47
even though we haven't trained this neocortical column
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bu neokortical kolonu henuz gelistirmemis olsak da
12:51
to create a specific reality.
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aslinda belirli bir gerceklik cikarmaya baslayabiliriz.
12:53
But we can ask, "Where is the rose?"
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Ancak " Gul nerede" diye sorabiliriz.
12:57
We can ask, "Where is it inside,
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"Eger onu bir resimle uyariyorsak, o iceride nerededir "
12:59
if we stimulate it with a picture?"
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diye sorabiliriz.
13:02
Where is it inside the neocortex?
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Neokorteks'in icinde, neresindedir?
13:04
Ultimately it's got to be there if we stimulated it with it.
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Eger bununla uyardiysak, sonuc itibariyle orada olmak zorundadir.
13:08
So, the way that we can look at that
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O halde, soyle bakabiliriz
13:10
is to ignore the neurons, ignore the synapses,
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sinir hucrelerini, sinapslari goz ardi ederek
13:13
and look just at the raw electrical activity.
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yanlizca saf elektrik hareketlerine bakabiliriz.
13:15
Because that is what it's creating.
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Cunku onlari olusturan budur.
13:17
It's creating electrical patterns.
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O, elektrik sekiller dizisini olusturuyor.
13:19
So when we did this,
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Yani, bunu yaptigimiz zaman,
13:21
we indeed, for the first time,
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gercekten de ilk kez
13:23
saw these ghost-like structures:
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hayalet gibi gozuken;
13:26
electrical objects appearing
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neokortal kolonun icinde
13:29
within the neocortical column.
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elektriksel cisimler gozlemledik.
13:32
And it's these electrical objects
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Iste bu elektriksel objeler de
13:35
that are holding all the information about
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uyariciya dair tum bilgileri
13:38
whatever stimulated it.
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icerirler.
13:41
And then when we zoomed into this,
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Ve bu yapiya yakindan baktigimizda
13:43
it's like a veritable universe.
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tipki evren gibi gorunur.
13:47
So the next step
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O halde bir sonraki asamada
13:49
is just to take these brain coordinates
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yapmamiz gereken sey sadece bu beyin koordinatlarini alip
13:53
and to project them into perceptual space.
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algisal alana yansitmaktir.
13:57
And if you do that,
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Iste bunu yaptiginiz zaman
13:59
you will be able to step inside
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bu makina tarafindan, bu beyin parcasi tarafindan, yaratilmis olan gercegi gorme imkaniniz olucaktir.
14:01
the reality that is created
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bu beyin parcasi tarafindan,
14:03
by this machine,
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yaratilmis olan gercegi
14:05
by this piece of the brain.
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gorme imkaniniz olucaktir.
14:08
So, in summary,
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Yani, ozetle,
14:10
I think that the universe may have --
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Sanirim evren...
14:12
it's possible --
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olasidir ki...
14:14
evolved a brain to see itself,
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kendine ayna olacak bir beyni gelistirmis olabilir
14:17
which may be a first step in becoming aware of itself.
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ki bu da kendi hakikatini tanimaya dair ilk adim olabilir.
14:22
There is a lot more to do to test these theories,
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Bu teorileri ve diger teorileri test etmek icin
14:24
and to test any other theories.
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yapilacak daha cok sey var.
14:27
But I hope that you are at least partly convinced
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Ancak, umarim kismen de olsa ikna olmussunuzdur ki;
14:30
that it is not impossible to build a brain.
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beyni olusturmak imkansiz degildir.
14:33
We can do it within 10 years,
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Bunu 10 yil icinde basarabiliriz.
14:35
and if we do succeed,
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ve sayet bunu basarabilirsek,
14:37
we will send to TED, in 10 years,
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10 yil icinde, TED'e
14:39
a hologram to talk to you. Thank you.
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sizinle konusacak bir hologram gonderecegiz. Tesekkur ederim.
14:42
(Applause)
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(Alkislar)
ABOUT THE SPEAKER
Henry Markram - NeuroscientistHenry Markram is director of Blue Brain, a supercomputing project that can model components of the mammalian brain to precise cellular detail -- and simulate their activity in 3D. Soon he'll simulate a whole rat brain in real time.
Why you should listen
In the microscopic, yet-uncharted circuitry of the cortex, Henry Markram is perhaps the most ambitious -- and our most promising -- frontiersman. Backed by the extraordinary power of the IBM Blue Gene supercomputing architecture, which can perform hundreds of trillions of calculations per second, he's using complex models to precisely simulate the neocortical column (and its tens of millions of neural connections) in 3D.
Though the aim of Blue Brain research is mainly biomedical, it has been edging up on some deep, contentious philosophical questions about the mind -- "Can a robot think?" and "Can consciousness be reduced to mechanical components?" -- the consequence of which Markram is well aware: Asked by Seed Magazine what a simulation of a full brain might do, he answered, "Everything. I mean everything" -- with a grin.
Now, with a successful proof-of-concept for simulation in hand (the project's first phase was completed in 2007), Markram is looking toward a future where brains might be modeled even down to the molecular and genetic level. Computing power marching rightward and up along the graph of Moore's Law, Markram is sure to be at the forefront as answers to the mysteries of cognition emerge.
Henry Markram | Speaker | TED.com