TEDxUIUC
Christoph Adami: Finding life we can't imagine
Kristof Adami: Pronalaženje oblika života koje ne možemo da zamislimo
Filmed:
Readability: 3.7
652,149 views
Kako da tragamo za vanzemaljskim životom ako ne liči ni na šta nama poznato? Kristof Adami objašnjava kako koristi svoja istraživanja o veštačkom životu -- kompjuterskim programima koji se sami umnožavaju -- da nađe obeležje, "biomarker", koje će biti oslobođeno svih naših predrasuda o tome šta predstavlja život.
Christoph Adami - Artificial life researcher
Christoph Adami works on the nature of life and evolution, trying to define life in a way that is as free as possible from our preconceptions. Full bio
Christoph Adami works on the nature of life and evolution, trying to define life in a way that is as free as possible from our preconceptions. Full bio
Double-click the English transcript below to play the video.
00:15
So I have a strange career.
0
0
2000
Dakle, ja se bavim čudnim poslom.
00:17
I know it because people come up to me, like colleagues,
1
2000
3000
Znam to zato što mi ljudi, kolege na primer, prilaze
00:20
and say, "Chris, you have a strange career."
2
5000
2000
i kažu: "Krise, baviš se čudnim poslom."
00:22
(Laughter)
3
7000
2000
(Smeh)
00:24
And I can see their point,
4
9000
2000
Razumem šta hoće da kažu,
00:26
because I started my career
5
11000
2000
jer sam počeo karijeru
00:28
as a theoretical nuclear physicist.
6
13000
2000
kao teoretičar nuklearne fizike.
00:30
And I was thinking about quarks and gluons
7
15000
2000
Razmišljao sam o kvarkovima i gluonima
00:32
and heavy ion collisions,
8
17000
2000
i sudarima teških jona,
00:34
and I was only 14 years old.
9
19000
2000
a imao sam samo 14 godina.
00:36
No, no, I wasn't 14 years old.
10
21000
3000
Ne, nisam imao 14 godina.
00:40
But after that,
11
25000
2000
Ali posle toga
00:42
I actually had my own lab
12
27000
2000
sam zapravo imao svoju laboratoriju
00:44
in the computational neuroscience department,
13
29000
2000
na departmanu za računarske neuronauke
00:46
and I wasn't doing any neuroscience.
14
31000
2000
a uopšte se nisam bavio neuronaukama.
00:48
Later, I would work on evolutionary genetics,
15
33000
3000
Kasnije sam se bavio evolucionom genetikom,
00:51
and I would work on systems biology.
16
36000
2000
a potom biologijom sistema.
00:53
But I'm going to tell you about something else today.
17
38000
3000
Ali danas ću vam govoriti o nečemu drugom.
00:56
I'm going to tell you
18
41000
2000
Govoriću vam
00:58
about how I learned something about life.
19
43000
2000
o tome kako sam naučio nešto o životu.
01:00
And I was actually a rocket scientist.
20
45000
4000
A bio sam raketni naučnik.
01:04
I wasn't really a rocket scientist,
21
49000
2000
Nisam baš bio raketni naučnik,
01:06
but I was working
22
51000
2000
ali sam radio
01:08
at the Jet Propulsion Laboratory
23
53000
2000
u Laboratoriji za razvijanje mlaznog pogona
01:10
in sunny California where it's warm;
24
55000
3000
u sunčanoj Kaliforniji, gde je toplo;
01:13
whereas now I'm in the mid-West,
25
58000
2000
dok sada radim na srednjem Zapadu,
01:15
and it's cold.
26
60000
2000
i hladno mi je.
01:17
But it was an exciting experience.
27
62000
3000
Ali bilo je to jedno uzbudljivo iskustvo.
01:20
One day a NASA manager comes into my office,
28
65000
3000
Jednog dana službenik NASA-e je ušao u moju kancelariju,
01:23
sits down and says,
29
68000
3000
seo i rekao:
01:26
"Can you please tell us,
30
71000
2000
"Možete li, molim vas, da nam kažete
01:28
how do we look for life outside Earth?"
31
73000
2000
kako da tražimo život van Zemlje?"
01:30
And that came as a surprise to me,
32
75000
2000
To me je iznenadilo
01:32
because I was actually hired
33
77000
2000
jer sam bio zaposlen tamo
01:34
to work on quantum computation.
34
79000
2000
kako bih radio na kvantnom računarstvu.
01:36
Yet, I had a very good answer.
35
81000
2000
Ipak, imao sam veoma dobar odgovor na njegovo pitanje.
01:38
I said, "I have no idea."
36
83000
3000
Rekao sam: "Nemam pojma."
01:41
And he told me, "Biosignatures,
37
86000
3000
On mi je rekao: "Znakovi života,
01:44
we need to look for a biosignature."
38
89000
2000
treba da tragamo za znakovima života."
01:46
And I said, "What is that?"
39
91000
2000
Ja sam pitao: "Šta je to?"
01:48
And he said, "It's any measurable phenomenon
40
93000
2000
A on je rekao: "To su merljive pojave
01:50
that allows us to indicate
41
95000
2000
koje nam ukazuju na
01:52
the presence of life."
42
97000
2000
prisustvo života."
01:54
And I said, "Really?
43
99000
2000
Zapitao sam: "Stvarno?
01:56
Because isn't that easy?
44
101000
2000
Jer, znate, nije li to lako?
01:58
I mean, we have life.
45
103000
2000
Mislim, mi imamo život.
02:00
Can't you apply a definition,
46
105000
2000
Zar ne možete da primenite definiciju,
02:02
like for example, a Supreme Court-like definition of life?"
47
107000
4000
definiciju kakvu bi dao Vrhovni Sud, na primer?" (PREPOZNAJEM ŽIVOT KAD GA VIDIM)
02:06
And then I thought about it a little bit, and I said,
48
111000
2000
Razmišljao sam malo o tome i rekao:
02:08
"Well, is it really that easy?
49
113000
2000
"Da li je zaista toliko lako?
02:10
Because, yes, if you see something like this,
50
115000
3000
Jer, da, kada vidite ovako nešto,
02:13
then all right, fine, I'm going to call it life --
51
118000
2000
onda je u redu, to jeste život,
02:15
no doubt about it.
52
120000
2000
nema sumnje u to.
02:17
But here's something."
53
122000
2000
Ali evo nečega."
02:19
And he goes, "Right, that's life too. I know that."
54
124000
3000
On će na to: "Da, u redu, i to je život, znam to."
02:22
Except, if you think life is also defined
55
127000
2000
Ali, ako mislite da se život definiše
02:24
by things that die,
56
129000
2000
kao nešto što na kraju umire
02:26
you're not in luck with this thing,
57
131000
2000
onda s ovim nećete imati sreće,
02:28
because that's actually a very strange organism.
58
133000
2000
jer je ovo jedan vrlo čudan organizam.
02:30
It grows up into the adult stage like that
59
135000
2000
On postaje odrasla jedinka,
02:32
and then goes through a Benjamin Button phase,
60
137000
3000
a onda prolazi kroz fazu "Bendžamin Baton"
02:35
and actually goes backwards and backwards
61
140000
2000
zapravo, vraća se unazad
02:37
until it's like a little embryo again,
62
142000
2000
dok ponovo ne postane mali embrion,
02:39
and then actually grows back up, and back down and back up -- sort of yo-yo --
63
144000
3000
a onda poraste ponovo, pa se vrati unazad, pa ponovo raste -- kao jo-jo,
02:42
and it never dies.
64
147000
2000
i nikad ne umire.
02:44
So it's actually life,
65
149000
2000
Tako da, to jeste život,
02:46
but it's actually not
66
151000
2000
ali nije baš
02:48
as we thought life would be.
67
153000
3000
onakav kakvim ga zamišljamo.
02:51
And then you see something like that.
68
156000
2000
A onda vidite nešto kao što je ovo.
02:53
And he was like, "My God, what kind of a life form is that?"
69
158000
2000
On je upitao: "Bože, kakav je pa ovo oblik života?"
02:55
Anyone know?
70
160000
2000
Zna li neko?
02:57
It's actually not life, it's a crystal.
71
162000
3000
Ovo zapravo nije živo, to je kristal.
03:00
So once you start looking and looking
72
165000
2000
Dakle, jednom kada počnete da gledate i gledate
03:02
at smaller and smaller things --
73
167000
2000
u sve manje i manje stvari...
03:04
so this particular person
74
169000
2000
Tako je ova osoba
03:06
wrote a whole article and said, "Hey, these are bacteria."
75
171000
3000
napisala čitav članak, rekavši: "Hej, ovo su bakterije."
03:09
Except, if you look a little bit closer,
76
174000
2000
Ali, kada pogledate malo bolje,
03:11
you see, in fact, that this thing is way too small to be anything like that.
77
176000
3000
videćete, u stvari, da je ovo suviše malo da bi bilo tako nešto.
03:14
So he was convinced,
78
179000
2000
Dakle, on je bio uveren,
03:16
but, in fact, most people aren't.
79
181000
2000
ali, zapravo, većina ljudi nije bila.
03:18
And then, of course,
80
183000
2000
A onda, naravno
03:20
NASA also had a big announcement,
81
185000
2000
NASA je objavila,
03:22
and President Clinton gave a press conference,
82
187000
2000
i predsednik Klinton je imao konferenciju za štampu
03:24
about this amazing discovery
83
189000
2000
vezanu za ovo neverovatno otkriće
03:26
of life in a Martian meteorite.
84
191000
3000
života na marsovskom meteoritu.
03:29
Except that nowadays, it's heavily disputed.
85
194000
4000
Ipak, danas, ovo otkriće je predmet rasprave.
03:33
If you take the lesson of all these pictures,
86
198000
3000
Ako izvučete pouku iz svih ovih slika,
03:36
then you realize, well actually maybe it's not that easy.
87
201000
2000
shvatićete da ovo zapravo možda i nije tako lako.
03:38
Maybe I do need
88
203000
2000
Možda nam i treba
03:40
a definition of life
89
205000
2000
neka definicija života
03:42
in order to make that kind of distinction.
90
207000
2000
kako bismo napravili razliku.
03:44
So can life be defined?
91
209000
2000
Pa može li život da se definiše?
03:46
Well how would you go about it?
92
211000
2000
Kako biste vi to uradili?
03:48
Well of course,
93
213000
2000
Naravno,
03:50
you'd go to Encyclopedia Britannica and open at L.
94
215000
2000
uzeli biste Enciklopediju Britaniku i otvorili na slovo L.
03:52
No, of course you don't do that; you put it somewhere in Google.
95
217000
3000
Ne, naravno, ne biste uradili to, već biste "izguglali".
03:55
And then you might get something.
96
220000
3000
Tada biste možda dobili nešto.
03:58
And what you might get --
97
223000
2000
A ako od toga što dobijete,
04:00
and anything that actually refers to things that we are used to,
98
225000
2000
sve što govori o stvarima na koje smo navikli
04:02
you throw away.
99
227000
2000
odbacite,
04:04
And then you might come up with something like this.
100
229000
2000
dobićete nešto ovako.
04:06
And it says something complicated
101
231000
2000
Ovo vam govori nešto komplikovano
04:08
with lots and lots of concepts.
102
233000
2000
i sadrži puno različitih koncepata.
04:10
Who on Earth would write something
103
235000
2000
Ko bi na ovom svetu napisao nešto
04:12
as convoluted and complex
104
237000
2000
ovako nategnuto i kompleksno
04:14
and inane?
105
239000
3000
i blesavo?
04:17
Oh, it's actually a really, really, important set of concepts.
106
242000
4000
No, to je zapravo veoma, veoma važan skup koncepata.
04:21
So I'm highlighting just a few words
107
246000
3000
Istaći ću samo nekoliko reči,
04:24
and saying definitions like that
108
249000
2000
a davanje takvih definicija
04:26
rely on things that are not based
109
251000
2000
oslanja se na stvari koje nisu zasnovane
04:28
on amino acids or leaves
110
253000
3000
na aminokiselinama ili listovima
04:31
or anything that we are used to,
111
256000
2000
ili na bilo šta na šta smo navikli,
04:33
but in fact on processes only.
112
258000
2000
nego isključivo na procese.
04:35
And if you take a look at that,
113
260000
2000
Ako bacite pogled na to
04:37
this was actually in a book that I wrote that deals with artificial life.
114
262000
3000
videćete da je to iz moje knjige koja se bavi veštačkim životom.
04:40
And that explains why
115
265000
2000
To objašnjava šta
04:42
that NASA manager was actually in my office to begin with.
116
267000
3000
je taj službenik NASA-e uopšte radio u mojoj kancelariji.
04:45
Because the idea was that, with concepts like that,
117
270000
3000
Zamisao je bila da sa takvim konceptima
04:48
maybe we can actually manufacture
118
273000
2000
možda i možemo da napravimo
04:50
a form of life.
119
275000
2000
oblik života.
04:52
And so if you go and ask yourself,
120
277000
3000
A ako se pitate:
04:55
"What on Earth is artificial life?",
121
280000
2000
"Šta je veštački život na Zemlji?"
04:57
let me give you a whirlwind tour
122
282000
2000
pustite me da vam na brzinu pokažem
04:59
of how all this stuff came about.
123
284000
2000
kako je do svega ovoga došlo.
05:01
And it started out quite a while ago
124
286000
3000
Počelo je prilično davno
05:04
when someone wrote
125
289000
2000
kada je neko napisao
05:06
one of the first successful computer viruses.
126
291000
2000
jedan od prvih uspešnih komjuterskih virusa.
05:08
And for those of you who aren't old enough,
127
293000
3000
Za one koji nisu dovoljno stari,
05:11
you have no idea how this infection was working --
128
296000
3000
nemate pojma kako je ova infekcija funkcionisala,
05:14
namely, through these floppy disks.
129
299000
2000
naime, preko disketa.
05:16
But the interesting thing about these computer virus infections
130
301000
3000
Ono što je zanimljivo kod ovih kompjuterskih virusnih infekcija
05:19
was that, if you look at the rate
131
304000
2000
je to da, ako pogledate nivoe aktivnosti
05:21
at which the infection worked,
132
306000
2000
ove infekcije,
05:23
they show this spiky behavior
133
308000
2000
dobićete ovaj talasasti prikaz
05:25
that you're used to from a flu virus.
134
310000
3000
kakav smo navikli da vidimo kod virusa gripa.
05:28
And it is in fact due to this arms race
135
313000
2000
Ovo je rezultat "nadmetanja u naoružanju"
05:30
between hackers and operating system designers
136
315000
3000
između hakera i dizajnera operativnih sistema,
05:33
that things go back and forth.
137
318000
2000
zato sve ide ovako napred-nazad.
05:35
And the result is kind of a tree of life
138
320000
2000
Rezultat je neka vrsta porodičnog stabla
05:37
of these viruses,
139
322000
2000
ovih virusa
05:39
a phylogeny that looks very much
140
324000
3000
prikaz razvoja koji prilično podseća na prikaze
05:42
like the type of life that we're used to, at least on the viral level.
141
327000
3000
razvoja živog sveta na koje smo navikli, barem na nivou virusa.
05:45
So is that life? Not as far as I'm concerned.
142
330000
3000
Je li to, dakle, život? Ne, ako mene pitate.
05:48
Why? Because these things don't evolve by themselves.
143
333000
3000
Zašto? Zato što ove stvari ne evoluiraju same od sebe.
05:51
In fact, they have hackers writing them.
144
336000
2000
Postoje hakeri koji ih pišu.
05:53
But the idea was taken very quickly a little bit further
145
338000
4000
Ipak, ideja je vrlo brzo uznapredovala
05:57
when a scientist working at the Scientific Institute decided,
146
342000
3000
kada je jedan naučnik koji je radio u Naučnom institutu rekao:
06:00
"Why don't we try to package these little viruses
147
345000
3000
"Zašto ne probamo da spakujemo ove male viruse
06:03
in artificial worlds inside of the computer
148
348000
2000
u veštačke svetove unutar kompjutera
06:05
and let them evolve?"
149
350000
2000
i pustimo ih da evoluiraju?"
06:07
And this was Steen Rasmussen.
150
352000
2000
Taj čovek je bio Stin Rasmusen.
06:09
And he designed this system, but it really didn't work,
151
354000
2000
On je dizajnirao ovaj sistem, ali on zapravo nije radio,
06:11
because his viruses were constantly destroying each other.
152
356000
3000
jer su njegovi virusi stalno uništavali jedni druge.
06:14
But there was another scientist who had been watching this, an ecologist.
153
359000
3000
Sve ovo je posmatrao drugi naučnik, ekolog.
06:17
And he went home and says, "I know how to fix this."
154
362000
3000
Otišavši kući jednog dana, rekao je: "Znam kako da rešim ovo."
06:20
And he wrote the Tierra system,
155
365000
2000
Rezultat je bio "Tierra" sistem,
06:22
and, in my book, is in fact one of the first
156
367000
3000
i u svojoj knjizi sam rekao da je to jedan od prvih
06:25
truly artificial living systems --
157
370000
2000
zaista veštačkih "živih" sistema --
06:27
except for the fact that these programs didn't really grow in complexity.
158
372000
3000
samo što ti programi nisu zaista postajali složeniji.
06:30
So having seen this work, worked a little bit on this,
159
375000
3000
Videvši ovaj rad, i poradivši malo na tome,
06:33
this is where I came in.
160
378000
2000
uključio sam se u celu stvar.
06:35
And I decided to create a system
161
380000
2000
Rešio sam da napravim sistem
06:37
that has all the properties that are necessary
162
382000
2000
koji sadrži sve potrebne osobine
06:39
to see the evolution of complexity,
163
384000
3000
koje dovode do evolucije i složenosti,
06:42
more and more complex problems constantly evolving.
164
387000
3000
sve složenije i složenije probleme koji konstantno evoluiraju.
06:45
And of course, since I really don't know how to write code, I had help in this.
165
390000
3000
Naravno, pošto ja zaista ne umem da sastavim kod, imao sam pomoć.
06:48
I had two undergraduate students
166
393000
2000
Imao sam dvojicu studenata
06:50
at California Institute of Technology that worked with me.
167
395000
3000
sa Kalifornijskog Instituta za Tehnologiju koji su radili za mene.
06:53
That's Charles Offria on the left, Titus Brown on the right.
168
398000
3000
Sa leve strane je Čarls Ofria, sa desne Tajtus Braun.
06:56
They are now actually respectable professors
169
401000
3000
Oni su danas ugledni profesori
06:59
at Michigan State University,
170
404000
2000
na Državnom univerzitetu u Mičigenu,
07:01
but I can assure you, back in the day,
171
406000
2000
ali, uverevam vas, u to vreme,
07:03
we were not a respectable team.
172
408000
2000
mi nismo bili ugledan tim.
07:05
And I'm really happy that no photo survives
173
410000
2000
Drago mi je što nijedna fotografija
07:07
of the three of us anywhere close together.
174
412000
3000
nas trojice zajedno nije sačuvana.
07:10
But what is this system like?
175
415000
2000
Ali kakav je ovaj sistem?
07:12
Well I can't really go into the details,
176
417000
3000
Ne mogu baš da detaljišem,
07:15
but what you see here is some of the entrails.
177
420000
2000
ali ovde možete da vidite neke od elemenata.
07:17
But what I wanted to focus on
178
422000
2000
Ono na šta sam hteo da se fokusiram
07:19
is this type of population structure.
179
424000
2000
je šema strukture populacije.
07:21
There's about 10,000 programs sitting here.
180
426000
3000
Ovde se nalazi oko 10.000 programa.
07:24
And all different strains are colored in different colors.
181
429000
3000
Različite vrste su obojene različitim bojama.
07:27
And as you see here, there are groups that are growing on top of each other,
182
432000
3000
Kao što vidite, grupe njih rastu jedna preko druge,
07:30
because they are spreading.
183
435000
2000
šire se.
07:32
Any time there is a program
184
437000
2000
Kad god se pojavi program
07:34
that's better at surviving in this world,
185
439000
2000
koji bolje preživljava u ovom svetu,
07:36
due to whatever mutation it has acquired,
186
441000
2000
koja god mutacija da se pojavila kod njega,
07:38
it is going to spread over the others and drive the others to extinction.
187
443000
3000
raširiće se preko ostalih i dovesti ih do istrebljenja.
07:41
So I'm going to show you a movie where you're going to see that kind of dynamic.
188
446000
3000
Pokazaću vam film u kome se vidi ta vrsta dinamike.
07:44
And these kinds of experiments are started
189
449000
3000
Ovakvi eksperimenti su počeli
07:47
with programs that we wrote ourselves.
190
452000
2000
sa programima koje smo mi sami napisali.
07:49
We write our own stuff, replicate it,
191
454000
2000
Pisali smo sopstvene programe, umnožavali ih,
07:51
and are very proud of ourselves.
192
456000
2000
i veoma smo ponosni na sebe.
07:53
And we put them in, and what you see immediately
193
458000
3000
Stavili smo ih unutra i, kao što se odmah vidi,
07:56
is that there are waves and waves of innovation.
194
461000
3000
javljaju se talasi i talasi inovacije.
07:59
By the way, this is highly accelerated,
195
464000
2000
Usput, ovo je vrlo ubrzano,
08:01
so it's like a thousand generations a second.
196
466000
2000
nekih hiljadu generacija u sekundi.
08:03
But immediately the system goes like,
197
468000
2000
Ali vrlo brzo, sistem kaže:
08:05
"What kind of dumb piece of code was this?
198
470000
2000
"Kakva je sad ovo glupost od koda?
08:07
This can be improved upon in so many ways
199
472000
2000
Ovo se može unaprediti na toliko načina
08:09
so quickly."
200
474000
2000
i to veoma brzo."
08:11
So you see waves of new types
201
476000
2000
Tako da vidite talase novih tipova
08:13
taking over the other types.
202
478000
2000
kako preovladavaju nad drugim tipovima.
08:15
And this type of activity goes on for quite awhile,
203
480000
3000
Ovakva aktivnost traje prilično dugo,
08:18
until the main easy things have been acquired by these programs.
204
483000
4000
sve dok svi programi ne razviju one glavne lake funkcije.
08:22
And then you see sort of like a stasis coming on
205
487000
4000
Onda vidite nešto kao stagnaciju
08:26
where the system essentially waits
206
491000
2000
u toku koje sistem čeka
08:28
for a new type of innovation, like this one,
207
493000
3000
neku novu inovaciju, kao što je ova,
08:31
which is going to spread
208
496000
2000
koja će se proširiti
08:33
over all the other innovations that were before
209
498000
2000
i nadvladati druge inovacije koje su tu bile ranije,
08:35
and is erasing the genes that it had before,
210
500000
3000
obrisati gene koji su bili tu ranije
08:38
until a new type of higher level of complexity has been achieved.
211
503000
4000
sve dok se novi, složeniji, tip ne pojavi.
08:42
And this process goes on and on and on.
212
507000
3000
Ovaj proces traje i traje i traje.
08:45
So what we see here
213
510000
2000
Dakle, ono što vidimo ovde
08:47
is a system that lives
214
512000
2000
jeste sistem koji funkcioniše
08:49
in very much the way we're used to life [going.]
215
514000
2000
na prilično sličan način na koji smo navikli da život funkcioniše.
08:51
But what the NASA people had asked me really
216
516000
4000
Ipak, ono što su me ljudi iz NASA-e zapravo pitali
08:55
was, "Do these guys
217
520000
2000
bilo je: "Da li ova "stvorenja"
08:57
have a biosignature?
218
522000
2000
daju znakove života?
08:59
Can we measure this type of life?
219
524000
2000
Možemo li da "izmerimo" ovaj oblik života?
09:01
Because if we can,
220
526000
2000
Jer, ako možemo,
09:03
maybe we have a chance of actually discovering life somewhere else
221
528000
3000
možda imamo šansu da zapravo otkrijemo život negde drugde
09:06
without being biased
222
531000
2000
i da pritom ne budemo ograničeni
09:08
by things like amino acids."
223
533000
2000
stvarima kakve su aminokiseline."
09:10
So I said, "Well, perhaps we should construct
224
535000
3000
Ja sam rekao: "Pa, možda mogu da konstruišem
09:13
a biosignature
225
538000
2000
prikaz znakova života
09:15
based on life as a universal process.
226
540000
3000
zasnovan na životu kao univerzalnom procesu.
09:18
In fact, it should perhaps make use
227
543000
2000
Zapravo, taj prikaz može da koristi
09:20
of the concepts that I developed
228
545000
2000
koncepte koje sam razvio
09:22
just in order to sort of capture
229
547000
2000
samo kako bih zabeležio
09:24
what a simple living system might be."
230
549000
2000
šta bi jednostavan živi sistem mogao da predstavlja."
09:26
And the thing I came up with --
231
551000
2000
Ono što mi je palo na pamet,
09:28
I have to first give you an introduction about the idea,
232
553000
4000
da napravim uvod u ideju,
09:32
and maybe that would be a meaning detector,
233
557000
3000
bi zapravo bio neki detektor značenja,
09:35
rather than a life detector.
234
560000
3000
pre nego detektor života.
09:38
And the way we would do that --
235
563000
2000
Način na koji bismo to postigli --
09:40
I would like to find out how I can distinguish
236
565000
2000
recimo, želim da saznam kako da razlikujem
09:42
text that was written by a million monkeys,
237
567000
2000
tekst koji je napisalo milion majmuna,
09:44
as opposed to text that [is] in our books.
238
569000
3000
od teksta koji je u knjigama i koji ima smisla.
09:47
And I would like to do it in such a way
239
572000
2000
I želeo bih to da uradim na takav način
09:49
that I don't actually have to be able to read the language,
240
574000
2000
da uopšte i ne moram da znam da čitam na tom jeziku,
09:51
because I'm sure I won't be able to.
241
576000
2000
pošto sam siguran da neću znati.
09:53
As long as I know that there's some sort of alphabet.
242
578000
2000
Uvek mora da postoji neka vrsta alfabeta.
09:55
So here would be a frequency plot
243
580000
3000
Dakle ovo je nivo učestalosti,
09:58
of how often you find
244
583000
2000
tj. koliko često se javlja
10:00
each of the 26 letters of the alphabet
245
585000
2000
svako od 26 slova alfabeta
10:02
in a text written by random monkeys.
246
587000
3000
u tekstu koji su napisali neki majmuni.
10:05
And obviously each of these letters
247
590000
2000
Očigledno, svako od ovih slova
10:07
comes off about roughly equally frequent.
248
592000
2000
javlja se otprilike podjednako često.
10:09
But if you now look at the same distribution in English texts,
249
594000
4000
Ali ako pogledate distribuciju slova u tekstovima na engleskom,
10:13
it looks like that.
250
598000
2000
nivo učestalosti je ovakav.
10:15
And I'm telling you, this is very robust across English texts.
251
600000
3000
Kažem vam, ovaj nivo učestalosti u tekstovima na engleskom je vrlo stalan.
10:18
And if I look at French texts, it looks a little bit different,
252
603000
2000
Ako bi pogledali tekstove na francuskom, slika bi bila malo drugačija,
10:20
or Italian or German.
253
605000
2000
kao i u tekstovima na italijanskom ili nemačkom.
10:22
They all have their own type of frequency distribution,
254
607000
3000
U svakom su slova drugačije distribuirana,
10:25
but it's robust.
255
610000
2000
ali nivo učestalosti je stalan.
10:27
It doesn't matter whether it writes about politics or about science.
256
612000
3000
Nije bitno da li tekst govori o politici ili o nauci,
10:30
It doesn't matter whether it's a poem
257
615000
3000
da li je u pitanju poezija
10:33
or whether it's a mathematical text.
258
618000
3000
ili tekst o matematici,
10:36
It's a robust signature,
259
621000
2000
ova slika
10:38
and it's very stable.
260
623000
2000
je vrlo stabilna.
10:40
As long as our books are written in English --
261
625000
2000
Dok god pišemo knjige na engleskom,
10:42
because people are rewriting them and recopying them --
262
627000
3000
a ljudi ih stalno iznova pišu i umnožavaju,
10:45
it's going to be there.
263
630000
2000
takva slika će biti prisutna.
10:47
So that inspired me to think about,
264
632000
2000
To me je inspirisalo da razmislim o sledećem --
10:49
well, what if I try to use this idea
265
634000
3000
dakle, šta ako pokušam da primenim ovu ideju,
10:52
in order, not to detect random texts
266
637000
2000
ne da bih razlučio nasumične tekstove
10:54
from texts with meaning,
267
639000
2000
od onih koji imaju značenje,
10:56
but rather detect the fact that there is meaning
268
641000
4000
već da bih otkrio da li postoji značenje
11:00
in the biomolecules that make up life.
269
645000
2000
u biomolekulima koji sačinjavaju život.
11:02
But first I have to ask:
270
647000
2000
Prvo moram da se zapitam:
11:04
what are these building blocks, like the alphabet, elements that I showed you?
271
649000
3000
šta su uopšte ove kockice, ovaj alfabet, ovi elementi koje sam vam pokazao?
11:07
Well it turns out, we have many different alternatives
272
652000
3000
Ispostavilo se da ima više različitih zamena
11:10
for such a set of building blocks.
273
655000
2000
za ovaj set kockica.
11:12
We could use amino acids,
274
657000
2000
To mogu biti aminokiseline,
11:14
we could use nucleic acids, carboxylic acids, fatty acids.
275
659000
3000
nukleinske kiseline, karboksilne kiseline, masne kiseline.
11:17
In fact, chemistry's extremely rich, and our body uses a lot of them.
276
662000
3000
Zapravo, hemija je izuzetno bogata, i naše telo koristi mnogo hemikalija.
11:20
So that we actually, to test this idea,
277
665000
3000
Dakle, kako bismo testirali ovu ideju
11:23
first took a look at amino acids and some other carboxylic acids.
278
668000
3000
morali smo prvo da ispitamo aminokiseline i neke druge karboksilne kiseline.
11:26
And here's the result.
279
671000
2000
I evo rezultata.
11:28
Here is, in fact, what you get
280
673000
3000
Evo, ovo se dobija
11:31
if you, for example, look at the distribution of amino acids
281
676000
3000
kada, na primer, ispitate distribuciju aminokiselina
11:34
on a comet or in interstellar space
282
679000
3000
na nekoj kometi u međuzvezdanom prostoru
11:37
or, in fact, in a laboratory,
283
682000
2000
ili u laboratoriji
11:39
where you made very sure that in your primordial soup
284
684000
2000
za koju ste sigurni
11:41
that there is not living stuff in there.
285
686000
2000
da u njoj nema ničeg živog.
11:43
What you find is mostly glycine and then alanine
286
688000
3000
Ono što ćete naći su uglavnom glicin i alanin
11:46
and there's some trace elements of the other ones.
287
691000
3000
a ostalih kiselina ima u tragovima.
11:49
That is also very robust --
288
694000
3000
Ova slika je takođe vrlo konstantna --
11:52
what you find in systems like Earth
289
697000
3000
ovo je ono što bismo našli u sistemima nalik Zemlji
11:55
where there are amino acids,
290
700000
2000
u kojima ima aminokiselina,
11:57
but there is no life.
291
702000
2000
ali nema života.
11:59
But suppose you take some dirt
292
704000
2000
Ali šta ako bismo uzeli malo zemlje
12:01
and dig through it
293
706000
2000
i kopali malo po njoj
12:03
and then put it into these spectrometers,
294
708000
3000
i onda je stavili u ovaj spektrometar?
12:06
because there's bacteria all over the place;
295
711000
2000
Pošto ima bakterija na sve strane.
12:08
or you take water anywhere on Earth,
296
713000
2000
Isti rezultat bi bio i sa vodom uzetom bilo gde na Zemlji,
12:10
because it's teaming with life,
297
715000
2000
kada bi se sprovela ista analiza,
12:12
and you make the same analysis;
298
717000
2000
jer je i ona prepuna života;
12:14
the spectrum looks completely different.
299
719000
2000
spektar bi izgledao potpuno drugačije.
12:16
Of course, there is still glycine and alanine,
300
721000
4000
Naravno, glicin i alanin bi još uvek bili tu,
12:20
but in fact, there are these heavy elements, these heavy amino acids,
301
725000
3000
ali bilo bi i teških elemenata, teških aminokiselina,
12:23
that are being produced
302
728000
2000
koje se proizvode
12:25
because these are valuable to the organism.
303
730000
2000
zato što su od značaja za život organizma.
12:27
And some other ones
304
732000
2000
Neke druge
12:29
that are not used in the set of 20,
305
734000
2000
koje ne spadaju u dvadeset esencijalnih,
12:31
they will not appear at all
306
736000
2000
se uopšte ne bi pojavile
12:33
in any type of concentration.
307
738000
2000
ni u kojoj koncentraciji.
12:35
So this also turns out to be extremely robust.
308
740000
2000
Dakle, i ova slika je konstantna.
12:37
It doesn't matter what kind of sediment you're using to grind up,
309
742000
3000
Nije bitno koji sediment je u pitanju,
12:40
whether it's bacteria or any other plants or animals.
310
745000
3000
da li su u pitanju bakterije ili neke biljke ili životinje.
12:43
Anywhere there's life,
311
748000
2000
Gde god ima života
12:45
you're going to have this distribution,
312
750000
2000
imaćete ovakvu distribuciju,
12:47
as opposed to that distribution.
313
752000
2000
a ne ovakvu.
12:49
And it is detectable not just in amino acids.
314
754000
3000
Ove razlike možemo očitati ne samo kada su aminokiseline u pitanju.
12:52
Now you could ask:
315
757000
2000
Sada se možda pitate:
12:54
well, what about these Avidians?
316
759000
2000
dakle šta sa ovim "Avidijancima"?
12:56
The Avidians being the denizens of this computer world
317
761000
4000
"Avidijanci" su stanovnici kompjuterskog sveta
13:00
where they are perfectly happy replicating and growing in complexity.
318
765000
3000
u kome su savršeno srećni umnožavajući se i postajući sve složeniji.
13:03
So this is the distribution that you get
319
768000
3000
Dakle, ovo je prikaz distribucije koji dobijamo
13:06
if, in fact, there is no life.
320
771000
2000
u slučaju da života nema.
13:08
They have about 28 of these instructions.
321
773000
3000
Oni imaju 28 ovakvih instrukcija,
13:11
And if you have a system where they're being replaced one by the other,
322
776000
3000
i ukoliko imamo sistem u kome se one javljaju jedna za drugom,
13:14
it's like the monkeys writing on a typewriter.
323
779000
2000
sistem nema značenja -- kao majmuni sa kucaćim mašinama.
13:16
Each of these instructions appears
324
781000
3000
Svaka od instrukcija se pojavljuje
13:19
with roughly the equal frequency.
325
784000
3000
otprilike podjednako često.
13:22
But if you now take a set of replicating guys
326
787000
4000
Ali ako uzmemo skup ovih stvorenja koja se množe
13:26
like in the video that you saw,
327
791000
2000
kao na snimku koji ste videli,
13:28
it looks like this.
328
793000
2000
prikaz distribucije izgleda ovako.
13:30
So there are some instructions
329
795000
2000
Dakle, postoje neke instrukcije
13:32
that are extremely valuable to these organisms,
330
797000
2000
koje su izuzetno važne za ove "organizme",
13:34
and their frequency is going to be high.
331
799000
3000
i one će se javljati učestalije.
13:37
And there's actually some instructions
332
802000
2000
A ima i onih instrukcija
13:39
that you only use once, if ever.
333
804000
2000
koje se koriste samo jednom, ili nikad.
13:41
So they are either poisonous
334
806000
2000
One su, dakle, ili otrovne, ili ih treba koristiti ređe
13:43
or really should be used at less of a level than random.
335
808000
4000
nego što bi se pojavljivale kada bi sve bilo nasumično.
13:47
In this case, the frequency is lower.
336
812000
3000
Nivo učestalosti ovih instrukcija je niži.
13:50
And so now we can see, is that really a robust signature?
337
815000
3000
Sada možemo da vidimo da li zaista postoji neka šema.
13:53
I can tell you indeed it is,
338
818000
2000
Mogu vam reći da postoji,
13:55
because this type of spectrum, just like what you've seen in books,
339
820000
3000
jer smo ovakav spektar videli na primeru sa knjigama,
13:58
and just like what you've seen in amino acids,
340
823000
2000
kao i na primeru sa aminokiselinama,
14:00
it doesn't really matter how you change the environment, it's very robust;
341
825000
3000
i ne menja se kada promenite okruženje, veoma je postojan;
14:03
it's going to reflect the environment.
342
828000
2000
i oslikava okruženje.
14:05
So I'm going to show you now a little experiment that we did.
343
830000
2000
Sada ću vam pokazati jedan mali eksperiment koji smo napravili.
14:07
And I have to explain to you,
344
832000
2000
Moram da objasnim --
14:09
the top of this graph
345
834000
2000
na vrhu ovog grafikona
14:11
shows you that frequency distribution that I talked about.
346
836000
3000
prikazana je učestalost distribucije elemenata o kojoj sam pričao.
14:14
Here, in fact, that's the lifeless environment
347
839000
3000
Ovde imamo okolinu bez života
14:17
where each instruction occurs
348
842000
2000
gde se svaka od instrukcija ponavlja
14:19
at an equal frequency.
349
844000
2000
podjednako često.
14:21
And below there, I show, in fact,
350
846000
3000
A ispod je prikazan
14:24
the mutation rate in the environment.
351
849000
3000
nivo promene učestalosti instrukcija u okolini.
14:27
And I'm starting this at a mutation rate that is so high
352
852000
3000
Počeću eksperiment sa nivoom promene dovoljno visokim
14:30
that, even if you would drop
353
855000
2000
da, čak i ako bismo ubacili
14:32
a replicating program
354
857000
2000
program koji se umnožava
14:34
that would otherwise happily grow up
355
859000
2000
i koji bi inače rado porastao
14:36
to fill the entire world,
356
861000
2000
i ispunio čitav svet,
14:38
if you drop it in, it gets mutated to death immediately.
357
863000
4000
on bi u ovom slučaju "umro" na licu mesta.
14:42
So there is no life possible
358
867000
2000
Dakle, život je nemoguć
14:44
at that type of mutation rate.
359
869000
3000
kada je nivo mutacije ovakav.
14:47
But then I'm going to slowly turn down the heat, so to speak,
360
872000
4000
Ali ako polako smanjim temperaturu, da tako kažem,
14:51
and then there's this viability threshold
361
876000
2000
dolazim do praga održivosti u životu
14:53
where now it would be possible
362
878000
2000
na kome bi bilo moguće da
14:55
for a replicator to actually live.
363
880000
2000
program koji se umnožava preživi.
14:57
And indeed, we're going to be dropping these guys
364
882000
3000
Dakle, ubacivaćemo ova stvorenja
15:00
into that soup all the time.
365
885000
2000
u ovu čorbu sve vreme.
15:02
So let's see what that looks like.
366
887000
2000
Pogledajmo kako to sve izgleda.
15:04
So first, nothing, nothing, nothing.
367
889000
3000
U početku: ništa, ništa, ništa.
15:07
Too hot, too hot.
368
892000
2000
Vrelo, vrelo.
15:09
Now the viability threshold is reached,
369
894000
3000
Sada je prag održivosti dostignut,
15:12
and the frequency distribution
370
897000
2000
a učestalost distribucije
15:14
has dramatically changed and, in fact, stabilizes.
371
899000
3000
značajno izmenjena, tj. stabilizovana.
15:17
And now what I did there
372
902000
2000
A sada šta sam uradio?
15:19
is, I was being nasty, I just turned up the heat again and again.
373
904000
3000
Pa, bio sam nevaljao, povećao sam temperaturu ponovo.
15:22
And of course, it reaches the viability threshold.
374
907000
3000
I naravno, dostigli smo prag održivosti.
15:25
And I'm just showing this to you again because it's so nice.
375
910000
3000
Pokazujem vam ovo ponovo jer je mnogo lepo.
15:28
You hit the viability threshold.
376
913000
2000
Dostigli smo prag održivosti.
15:30
The distribution changes to "alive!"
377
915000
2000
Prikaz distribucije instrukcija se promeni u: "Živo!"
15:32
And then, once you hit the threshold
378
917000
3000
A onda, ako ponovo dođemo do tačke
15:35
where the mutation rate is so high
379
920000
2000
na kojoj je nivo mutacije toliko visok
15:37
that you cannot self-reproduce,
380
922000
2000
da se programi ne mogu samoumnožiti,
15:39
you cannot copy the information
381
924000
3000
informacije se ne mogu preneti
15:42
forward to your offspring
382
927000
2000
na potomstvo
15:44
without making so many mistakes
383
929000
2000
bez pravljenja toliko grešaka
15:46
that your ability to replicate vanishes.
384
931000
3000
da sama sposobnost umnožavanja nestaje.
15:49
And then that signature is lost.
385
934000
3000
Taj znak života je time izgubljen.
15:52
What do we learn from that?
386
937000
2000
Šta možemo zaključiti iz toga?
15:54
Well, I think we learn a number of things from that.
387
939000
4000
Pa, mnogo toga.
15:58
One of them is,
388
943000
2000
Između ostalog, zaključićemo
16:00
if we are able to think about life
389
945000
3000
da, ako smo u stanju da zamislimo život
16:03
in abstract terms --
390
948000
2000
u apstraktnom smislu,
16:05
and we're not talking about things like plants,
391
950000
2000
ne kao biljke,
16:07
and we're not talking about amino acids,
392
952000
2000
aminokiseline
16:09
and we're not talking about bacteria,
393
954000
2000
ili bakterije,
16:11
but we think in terms of processes --
394
956000
2000
već kao skup procesa,
16:13
then we could start to think about life,
395
958000
3000
možemo početi da gledamo na život
16:16
not as something that is so special to Earth,
396
961000
2000
ne kao na nešto isključivo svojstveno Zemlji,
16:18
but that, in fact, could exist anywhere.
397
963000
3000
već kao nešto što bi moglo postojati bilo gde.
16:21
Because it really only has to do
398
966000
2000
Zato što život ima veze,
16:23
with these concepts of information,
399
968000
2000
pre svega, sa konceptima vezanim za informacije,
16:25
of storing information
400
970000
2000
za skladištenje informacija
16:27
within physical substrates --
401
972000
2000
u okviru fizičkog konteksta --
16:29
anything: bits, nucleic acids,
402
974000
2000
bitova, nukleinskih kiselina
16:31
anything that's an alphabet --
403
976000
2000
bilo šta što predstavlja sistem znakova tj. alfabet --
16:33
and make sure that there's some process
404
978000
2000
obavezno je i postojanje nekog procesa
16:35
so that this information can be stored
405
980000
2000
koji omogućava da informacije budu skladištene
16:37
for much longer than you would expect
406
982000
2000
mnogo duže nego što biste očekivali
16:39
the time scales for the deterioration of information.
407
984000
4000
da mogu odoleti vremenu.
16:43
And if you can do that,
408
988000
2000
Ako omogućimo tako nešto,
16:45
then you have life.
409
990000
2000
dobili smo život.
16:47
So the first thing that we learn
410
992000
2000
Dakle, prvo što smo zaključili
16:49
is that it is possible to define life
411
994000
3000
jeste da je život moguće definisati
16:52
in terms of processes alone,
412
997000
3000
i samo kao skup procesa,
16:55
without referring at all
413
1000000
2000
bez ikakvog oslanjanja
16:57
to the type of things that we hold dear,
414
1002000
2000
na stvari na koje smo naviknuti
16:59
as far as the type of life on Earth is.
415
1004000
3000
kada je u pitanju zemaljski život.
17:02
And that in a sense removes us again,
416
1007000
3000
To nas na neki način udaljava,
17:05
like all of our scientific discoveries, or many of them --
417
1010000
3000
kao i sva naša velika naučna otkrića, ili bar većina njih --
17:08
it's this continuous dethroning of man --
418
1013000
2000
postepeno nas skida sa trona
17:10
of how we think we're special because we're alive.
419
1015000
3000
naših ubeđenja kako smo posebni jer smo živi.
17:13
Well we can make life. We can make life in the computer.
420
1018000
3000
Dakle, možemo da napravimo život. Barem na kompjuteru.
17:16
Granted, it's limited,
421
1021000
2000
Naravno, to je ograničen život,
17:18
but we have learned what it takes
422
1023000
3000
ali smo tako naučili šta nam sve treba
17:21
in order to actually construct it.
423
1026000
2000
da bismo ga konstruisali.
17:23
And once we have that,
424
1028000
3000
Jednom kad to budemo savladali
17:26
then it is not such a difficult task anymore
425
1031000
3000
više neće biti tako teško zamisliti
17:29
to say, if we understand the fundamental processes
426
1034000
4000
da, pošto razumemo fundamentalne procese
17:33
that do not refer to any particular substrate,
427
1038000
3000
koji se ne odnose ni na jedan određeni kontekst,
17:36
then we can go out
428
1041000
2000
možemo otići odavde
17:38
and try other worlds,
429
1043000
2000
i ispitati druge svetove,
17:40
figure out what kind of chemical alphabets might there be,
430
1045000
4000
otkriti kakvi bi hemijski alfabeti tamo mogli da postoje,
17:44
figure enough about the normal chemistry,
431
1049000
2000
saznati nešto o njihovom hemijskom sastavu,
17:46
the geochemistry of the planet,
432
1051000
3000
odnosno geohemiji te planete,
17:49
so that we know what this distribution would look like
433
1054000
2000
kako bismo znali kako nivoi distribucije izgledaju
17:51
in the absence of life,
434
1056000
2000
u odsustvu života,
17:53
and then look for large deviations from this --
435
1058000
3000
tada bismo mogli tragati za odstupanjima od toga --
17:56
this thing sticking out, which says,
436
1061000
3000
ukoliko naiđemo na nešto što se izdvaja, recimo:
17:59
"This chemical really shouldn't be there."
437
1064000
2000
"Ovoj hemikaliji ovde nije mesto."
18:01
Now we don't know that there's life then,
438
1066000
2000
Nećemo tada biti sigurni da tu ima života,
18:03
but we could say,
439
1068000
2000
ali moći ćemo da kažemo:
18:05
"Well at least I'm going to have to take a look very precisely at this chemical
440
1070000
3000
"Ispitaću ovu hemikaliju vrlo pažljivo
18:08
and see where it comes from."
441
1073000
2000
da vidim odakle potiče."
18:10
And that might be our chance
442
1075000
2000
To može biti naša šansa da
18:12
of actually discovering life
443
1077000
2000
otkrijemo život
18:14
when we cannot visibly see it.
444
1079000
2000
i kada život ne bude bio očigledan.
18:16
And so that's really the only take-home message
445
1081000
3000
Dakle, to je jedina poruka koju želim
18:19
that I have for you.
446
1084000
2000
da ponesete odavde.
18:21
Life can be less mysterious
447
1086000
2000
Život postaje manje misteriozan
18:23
than we make it out to be
448
1088000
2000
nego što nam se čini
18:25
when we try to think about how it would be on other planets.
449
1090000
4000
kada pokušamo da ga zamislimo na drugim planetama.
18:29
And if we remove the mystery of life,
450
1094000
3000
Ako uklonimo veo misterije sa naše predstave o životu,
18:32
then I think it is a little bit easier
451
1097000
3000
postaće nam lakše
18:35
for us to think about how we live,
452
1100000
2000
da razmišljamo o tome kako mi živimo,
18:37
and how perhaps we're not as special as we always think we are.
453
1102000
3000
i shvatićemo da možda nismo toliko posebni kao što smo oduvek mislili.
18:40
And I'm going to leave you with that.
454
1105000
2000
Mislite o tome.
18:42
And thank you very much.
455
1107000
2000
I hvala vam puno.
18:44
(Applause)
456
1109000
2000
(Aplauz)
ABOUT THE SPEAKER
Christoph Adami - Artificial life researcherChristoph Adami works on the nature of life and evolution, trying to define life in a way that is as free as possible from our preconceptions.
Why you should listen
Christoph Adami researches the nature of living systems, using 'artificial life' -- small, self-replicating computer programs. His main research focus is Darwinian evolution, which he studies at different levels of organization (from simple molecules to brains). He has pioneered theapplication of methods from information theory to the study of evolution, and designed the "Avida" system that launched the use of digital life as a tool for investigating basic questions in evolutionary biology.
He is Professor of Applied Life Sciences at the Keck Graduate Institute in Claremont, CA, and a Visiting Professor at the BEACON Center for the Study of Evolution in Action at Michigan State University. He obtained his PhD in theoretical physics from the State University of New York at Stony Brook.
Christoph Adami | Speaker | TED.com