Finding life we can't imagine
-
0:00 - 0:02So, I have a strange career.
-
0:02 - 0:06I know it because people come up to me,
like colleagues, and say, -
0:06 - 0:07"Chris, you have a strange career."
-
0:07 - 0:09(Laughter)
-
0:09 - 0:10And I can see their point,
-
0:10 - 0:15because I started my career
as a theoretical nuclear physicist. -
0:15 - 0:19And I was thinking about quarks
and gluons and heavy ion collisions, -
0:19 - 0:21and I was only 14 years old --
-
0:22 - 0:24No, no, I wasn't 14 years old.
-
0:25 - 0:27But after that,
-
0:28 - 0:30I actually had my own lab
-
0:30 - 0:32in the Computational
Neuroscience department, -
0:32 - 0:34and I wasn't doing any neuroscience.
-
0:34 - 0:37Later, I would work
on evolutionary genetics, -
0:37 - 0:39and I would work on systems biology.
-
0:39 - 0:41But I'm going to tell you
about something else today. -
0:41 - 0:46I'm going to tell you
about how I learned something about life. -
0:46 - 0:49And I was actually a rocket scientist.
-
0:49 - 0:51I wasn't really a rocket scientist,
-
0:51 - 0:56but I was working
at the Jet Propulsion Laboratory -
0:56 - 0:58in sunny California, where it's warm;
-
0:58 - 1:02whereas now I am
in the mid-West, and it's cold. -
1:02 - 1:05But it was an exciting experience.
-
1:05 - 1:08One day, a NASA manager
comes into my office, -
1:08 - 1:11sits down and says,
-
1:12 - 1:15"Can you please tell us,
how do we look for life outside Earth?" -
1:16 - 1:18And that came as a surprise to me,
-
1:18 - 1:22because I was actually hired
to work on quantum computation. -
1:22 - 1:24Yet, I had a very good answer.
-
1:24 - 1:25I said, "I have no idea."
-
1:26 - 1:27(Laughter)
-
1:27 - 1:32And he told me, "Biosignatures,
we need to look for a biosignature." -
1:32 - 1:33And I said, "What is that?"
-
1:33 - 1:36And he said, "It's any
measurable phenomenon -
1:36 - 1:39that allows us to indicate
the presence of life." -
1:40 - 1:41And I said, "Really?
-
1:41 - 1:43Because isn't that easy?
-
1:43 - 1:45I mean, we have life.
-
1:45 - 1:47Can't you apply a definition,
-
1:47 - 1:51for example, a Supreme Court-like
definition of life?" -
1:52 - 1:54And then I thought about it
a little bit, and I said, -
1:54 - 1:56"Well, is it really that easy?
-
1:56 - 1:58Because, yes, if you see
something like this, -
1:58 - 2:01then all right, fine,
I'm going to call it life -- -
2:01 - 2:02no doubt about it.
-
2:02 - 2:04But here's something."
-
2:04 - 2:07And he goes, "Right,
that's life too. I know that." -
2:07 - 2:12Except, if you think that life
is also defined by things that die, -
2:12 - 2:13you're not in luck with this thing,
-
2:13 - 2:16because that's actually
a very strange organism. -
2:16 - 2:18It grows up into the adult stage like that
-
2:18 - 2:20and then goes through
a Benjamin Button phase, -
2:20 - 2:25and actually goes backwards and backwards
until it's like a little embryo again, -
2:25 - 2:28and then actually grows back up,
and back down and back up -- -
2:28 - 2:30sort of yo-yo -- and it never dies.
-
2:30 - 2:32So it's actually life,
-
2:32 - 2:36but it's actually not
as we thought life would be. -
2:36 - 2:38And then you see something like that.
-
2:38 - 2:41And he was like, "My God,
what kind of a life form is that?" -
2:41 - 2:43Anyone know?
-
2:43 - 2:46It's actually not life, it's a crystal.
-
2:46 - 2:50So once you start looking and looking
at smaller and smaller things -- -
2:50 - 2:53so this particular person wrote
a whole article and said, -
2:53 - 2:54"Hey, these are bacteria."
-
2:54 - 2:56Except, if you look a little bit closer,
-
2:56 - 3:00you see, in fact, that this thing
is way too small to be anything like that. -
3:00 - 3:03So he was convinced,
but, in fact, most people aren't. -
3:04 - 3:07And then, of course,
NASA also had a big announcement, -
3:07 - 3:10and President Clinton
gave a press conference, -
3:10 - 3:15about this amazing discovery
of life in a Martian meteorite. -
3:15 - 3:18Except that nowadays,
it's heavily disputed. -
3:19 - 3:21If you take the lesson
of all these pictures, -
3:21 - 3:24then you realize, well, actually,
maybe it's not that easy. -
3:24 - 3:28Maybe I do need a definition of life
-
3:28 - 3:30in order to make that kind of distinction.
-
3:30 - 3:32So can life be defined?
-
3:32 - 3:34Well how would you go about it?
-
3:34 - 3:38Well of course, you'd go
to Encyclopedia Britannica and open at L. -
3:38 - 3:41No, of course you don't do that;
you put it somewhere in Google. -
3:41 - 3:43And then you might get something.
-
3:43 - 3:44(Laughter)
-
3:44 - 3:45And what you might get --
-
3:45 - 3:49and anything that actually refers
to things that we are used to, -
3:49 - 3:50you throw away.
-
3:50 - 3:53And then you might come up
with something like this. -
3:53 - 3:56And it says something complicated
with lots and lots of concepts. -
3:56 - 4:01Who on Earth would write something
as convoluted and complex and inane? -
4:03 - 4:07Oh, it's actually a really, really,
important set of concepts. -
4:07 - 4:09So I'm highlighting just a few words
-
4:09 - 4:13and saying definitions
like that rely on things -
4:13 - 4:19that are not based on amino acids
or leaves or anything that we are used to, -
4:19 - 4:21but in fact on processes only.
-
4:21 - 4:23And if you take a look at that,
-
4:23 - 4:26this was actually in a book that I wrote
that deals with artificial life. -
4:26 - 4:30And that explains why that NASA manager
was actually in my office to begin with. -
4:31 - 4:34Because the idea was that,
with concepts like that, -
4:34 - 4:38maybe we can actually
manufacture a form of life. -
4:38 - 4:42And so if you go and ask yourself,
"What on Earth is artificial life?", -
4:42 - 4:46let me give you a whirlwind tour
of how all this stuff came about. -
4:46 - 4:49And it started out quite a while ago,
-
4:49 - 4:54when someone wrote one of the first
successful computer viruses. -
4:54 - 4:56And for those of you
who aren't old enough, -
4:56 - 4:59you have no idea
how this infection was working -- -
4:59 - 5:01namely, through these floppy disks.
-
5:01 - 5:05But the interesting thing
about these computer virus infections -
5:05 - 5:08was that, if you look at the rate
at which the infection worked, -
5:08 - 5:13they show this spiky behavior
that you're used to from a flu virus. -
5:13 - 5:15And it is in fact due to this arms race
-
5:15 - 5:18between hackers
and operating system designers -
5:18 - 5:20that things go back and forth.
-
5:20 - 5:25And the result is kind of
a tree of life of these viruses, -
5:25 - 5:28a phylogeny that looks very much
like the type of life -
5:28 - 5:31that we're used to,
at least on the viral level. -
5:31 - 5:32So is that life?
-
5:32 - 5:34Not as far as I'm concerned.
-
5:34 - 5:37Why? Because these things
don't evolve by themselves. -
5:37 - 5:39In fact, they have hackers writing them.
-
5:39 - 5:42But the idea was taken
very quickly a little bit further, -
5:42 - 5:45when a scientist working
at the Santa Fe Institute decided, -
5:45 - 5:49"Why don't we try to package
these little viruses -
5:49 - 5:51in artificial worlds
inside of the computer -
5:51 - 5:52and let them evolve?"
-
5:52 - 5:54And this was Steen Rasmussen.
-
5:54 - 5:56And he designed this system,
but it really didn't work, -
5:56 - 5:59because his viruses
were constantly destroying each other. -
5:59 - 6:03But there was another scientist
who had been watching this, an ecologist. -
6:03 - 6:05And he went home and says,
"I know how to fix this." -
6:05 - 6:07And he wrote the Tierra system,
-
6:07 - 6:08and, in my book,
-
6:08 - 6:12is in fact one of the first
truly artificial living systems -- -
6:12 - 6:16except for the fact that these programs
didn't really grow in complexity. -
6:16 - 6:19So having seen this work,
worked a little bit on this, -
6:19 - 6:20this is where I came in.
-
6:20 - 6:24And I decided to create a system
that has all the properties -
6:24 - 6:28that are necessary to see, in fact,
the evolution of complexity, -
6:28 - 6:31more and more complex
problems constantly evolving. -
6:31 - 6:35And of course, since I really don't know
how to write code, I had help in this. -
6:35 - 6:36I had two undergraduate students
-
6:36 - 6:39at California Institute of Technology
that worked with me. -
6:39 - 6:42That's Charles Ofria on the left,
Titus Brown on the right. -
6:42 - 6:44They are now, actually,
respectable professors -
6:44 - 6:46at Michigan State University,
-
6:46 - 6:51but I can assure you, back in the day,
we were not a respectable team. -
6:51 - 6:53And I'm really happy
that no photo survives -
6:53 - 6:55of the three of us
anywhere close together. -
6:56 - 6:58But what is this system like?
-
6:58 - 7:00Well I can't really go into the details,
-
7:00 - 7:03but what you see here
is some of the entrails. -
7:03 - 7:07But what I wanted to focus on
is this type of population structure. -
7:07 - 7:09There's about 10,000
programs sitting here. -
7:09 - 7:12And all different strains
are colored in different colors. -
7:12 - 7:16And as you see here, there are groups
that are growing on top of each other, -
7:16 - 7:17because they are spreading.
-
7:17 - 7:22Any time there is a program
that's better at surviving in this world, -
7:22 - 7:24due to whatever mutation it has acquired,
-
7:24 - 7:27it is going to spread over the others
and drive the others to extinction. -
7:27 - 7:29So I'm going to show you a movie
-
7:29 - 7:31where you're going to see
that kind of dynamic. -
7:31 - 7:35And these kinds of experiments are started
with programs that we wrote ourselves. -
7:35 - 7:39We write our own stuff, replicate it,
and are very proud of ourselves. -
7:39 - 7:41And we put them in,
and what you see immediately -
7:41 - 7:44is that there are waves
and waves of innovation. -
7:44 - 7:46By the way, this is highly accelerated,
-
7:46 - 7:49so it's like a 1000 generations a second.
-
7:49 - 7:53But immediately, the system goes like,
"What kind of dumb piece of code was this? -
7:53 - 7:56This can be improved upon
in so many ways, so quickly." -
7:56 - 8:00So you see waves of new types
taking over the other types. -
8:00 - 8:03And this type of activity
goes on for quite a while, -
8:03 - 8:07until the main easy things
have been acquired by these programs. -
8:07 - 8:11And then, you see
sort of like a stasis coming on -
8:11 - 8:13where the system essentially waits
-
8:13 - 8:16for a new type of innovation,
like this one, -
8:16 - 8:20which is going to spread over
all the other innovations that were before -
8:21 - 8:23and is erasing the genes
that it had before, -
8:23 - 8:27until a new type of higher level
of complexity has been achieved. -
8:27 - 8:30And this process goes on and on and on.
-
8:30 - 8:32So what we see here
-
8:32 - 8:36is a system that lives in very much
the way we're used to how life goes. -
8:37 - 8:41But what the NASA people
had asked me really was, -
8:41 - 8:44"Do these guys have a biosignature?
-
8:45 - 8:46Can we measure this type of life?
-
8:46 - 8:48Because if we can,
-
8:48 - 8:51maybe we have a chance of actually
discovering life somewhere else -
8:52 - 8:55without being biased
by things like amino acids." -
8:55 - 9:00So I said, "Well, perhaps
we should construct a biosignature -
9:00 - 9:03based on life as a universal process.
-
9:03 - 9:08In fact, it should perhaps make use
of the concepts that I developed -
9:08 - 9:12just in order to sort of capture
what a simple living system might be." -
9:12 - 9:14And the thing I came up with --
-
9:14 - 9:18I have to first give you
an introduction about the idea, -
9:18 - 9:21and maybe that would be
a meaning detector, -
9:21 - 9:23rather than a life detector.
-
9:23 - 9:25And the way we would do that --
-
9:25 - 9:28I would like to find out
how I can distinguish text -
9:28 - 9:32that was written by a million monkeys,
as opposed to text that is in our books. -
9:33 - 9:35And I would like to do it in such a way
-
9:35 - 9:37that I don't actually have to be able
to read the language, -
9:37 - 9:39because I'm sure I won't be able to.
-
9:39 - 9:42As long as I know
that there's some sort of alphabet. -
9:42 - 9:44So here would be a frequency plot
-
9:44 - 9:48of how often you find
each of the 26 letters of the alphabet -
9:48 - 9:50in a text written by random monkeys.
-
9:50 - 9:55And obviously, each of these letters
comes off about roughly equally frequent. -
9:55 - 9:58But if you now look at the same
distribution in English texts, -
9:58 - 10:00it looks like that.
-
10:00 - 10:04And I'm telling you,
this is very robust across English texts. -
10:04 - 10:07And if I look at French texts,
it looks a little bit different, -
10:07 - 10:08or Italian or German.
-
10:08 - 10:11They all have their own type
of frequency distribution, -
10:11 - 10:13but it's robust.
-
10:13 - 10:16It doesn't matter whether it writes
about politics or about science. -
10:16 - 10:22It doesn't matter whether it's a poem
or whether it's a mathematical text. -
10:22 - 10:24It's a robust signature,
-
10:24 - 10:26and it's very stable.
-
10:26 - 10:28As long as our books
are written in English -- -
10:28 - 10:31because people are rewriting them
and recopying them -- -
10:31 - 10:32it's going to be there.
-
10:32 - 10:38So that inspired me to think about,
well, what if I try to use this idea -
10:38 - 10:42in order, not to detect random texts
from texts with meaning, -
10:42 - 10:45but rather detect the fact
that there is meaning -
10:45 - 10:48in the biomolecules that make up life.
-
10:48 - 10:49But first I have to ask:
-
10:49 - 10:51what are these building blocks,
-
10:51 - 10:53like the alphabet, elements
that I showed you? -
10:53 - 10:56Well it turns out, we have
many different alternatives -
10:56 - 10:58for such a set of building blocks.
-
10:58 - 10:59We could use amino acids,
-
10:59 - 11:03we could use nucleic acids,
carboxylic acids, fatty acids. -
11:03 - 11:06In fact, chemistry's extremely rich,
and our body uses a lot of them. -
11:06 - 11:08So that we actually, to test this idea,
-
11:08 - 11:12first took a look at amino acids
and some other carboxylic acids. -
11:12 - 11:13And here's the result.
-
11:13 - 11:17Here is, in fact, what you get
-
11:17 - 11:20if you, for example, look
at the distribution of amino acids -
11:20 - 11:24on a comet or in interstellar space
or, in fact, in a laboratory, -
11:24 - 11:27where you made very sure
that in your primordial soup, -
11:27 - 11:29there is no living stuff in there.
-
11:29 - 11:32What you find is mostly
glycine and then alanine -
11:32 - 11:34and there's some trace elements
of the other ones. -
11:34 - 11:37That is also very robust --
-
11:37 - 11:41what you find in systems like Earth
-
11:41 - 11:44where there are amino acids,
but there is no life. -
11:44 - 11:48But suppose you take some dirt
and dig through it -
11:49 - 11:51and then put it into these spectrometers,
-
11:52 - 11:54because there's bacteria
all over the place; -
11:54 - 11:56or you take water anywhere on Earth,
-
11:56 - 11:57because it's teaming with life,
-
11:57 - 11:59and you make the same analysis;
-
11:59 - 12:02the spectrum looks completely different.
-
12:02 - 12:05Of course, there is still
glycine and alanine, -
12:05 - 12:09but in fact, there are these heavy
elements, these heavy amino acids, -
12:09 - 12:12that are being produced
because they are valuable to the organism. -
12:13 - 12:17And some other ones
that are not used in the set of 20, -
12:17 - 12:20they will not appear at all
in any type of concentration. -
12:20 - 12:23So this also turns out
to be extremely robust. -
12:23 - 12:26It doesn't matter what kind of sediment
you're using to grind up, -
12:26 - 12:29whether it's bacteria
or any other plants or animals. -
12:29 - 12:31Anywhere there's life,
-
12:31 - 12:33you're going to have this distribution,
-
12:33 - 12:34as opposed to that distribution.
-
12:34 - 12:38And it is detectable
not just in amino acids. -
12:38 - 12:39Now you could ask:
-
12:39 - 12:42Well, what about these Avidians?
-
12:42 - 12:45The Avidians being the denizens
of this computer world -
12:45 - 12:49where they are perfectly happy
replicating and growing in complexity. -
12:49 - 12:54So this is the distribution that you get
if, in fact, there is no life. -
12:54 - 12:56They have about 28 of these instructions.
-
12:56 - 13:00And if you have a system where
they're being replaced one by the other, -
13:00 - 13:02it's like the monkeys
writing on a typewriter. -
13:02 - 13:06Each of these instructions
appears with roughly the equal frequency. -
13:07 - 13:12But if you now take
a set of replicating guys -
13:12 - 13:14like in the video that you saw,
-
13:14 - 13:15it looks like this.
-
13:16 - 13:18So there are some instructions
-
13:18 - 13:20that are extremely valuable
to these organisms, -
13:20 - 13:22and their frequency is going to be high.
-
13:22 - 13:26And there's actually some instructions
that you only use once, if ever. -
13:26 - 13:28So they are either poisonous
-
13:28 - 13:32or really should be used
at less of a level than random. -
13:32 - 13:35In this case, the frequency is lower.
-
13:36 - 13:39And so now we can see,
is that really a robust signature? -
13:39 - 13:40I can tell you indeed it is,
-
13:40 - 13:43because this type of spectrum,
just like what you've seen in books, -
13:43 - 13:45and just like what you've seen
in amino acids, -
13:45 - 13:48it doesn't really matter
how you change the environment, -
13:48 - 13:51it's very robust, it's going
to reflect the environment. -
13:51 - 13:54So I'm going to show you now
a little experiment that we did. -
13:54 - 13:55And I have to explain to you,
-
13:55 - 13:56the top of this graph
-
13:56 - 13:59shows you that frequency
distribution that I talked about. -
13:59 - 14:03Here, that's the lifeless environment
-
14:03 - 14:06where each instruction occurs
at an equal frequency. -
14:07 - 14:12And below there, I show, in fact,
the mutation rate in the environment. -
14:12 - 14:16And I'm starting this
at a mutation rate that is so high -
14:16 - 14:20that even if you would drop
a replicating program -
14:20 - 14:24that would otherwise happily grow up
to fill the entire world, -
14:24 - 14:27if you drop it in, it gets mutated
to death immediately. -
14:27 - 14:32So there is no life possible
at that type of mutation rate. -
14:32 - 14:36But then I'm going to slowly
turn down the heat, so to speak, -
14:36 - 14:38and then there's this viability threshold
-
14:38 - 14:42where now it would be possible
for a replicator to actually live. -
14:42 - 14:48And indeed, we're going to be dropping
these guys into that soup all the time. -
14:48 - 14:50So let's see what that looks like.
-
14:50 - 14:53So first, nothing, nothing, nothing.
-
14:53 - 14:55Too hot, too hot.
-
14:55 - 14:57Now the viability threshold is reached,
-
14:57 - 15:01and the frequency distribution
has dramatically changed -
15:02 - 15:03and, in fact, stabilizes.
-
15:03 - 15:05And now what I did there
-
15:05 - 15:08is, I was being nasty,
I just turned up the heat again and again. -
15:08 - 15:11And of course, it reaches
the viability threshold. -
15:11 - 15:13And I'm just showing this to you
again because it's so nice. -
15:13 - 15:15You hit the viability threshold.
-
15:15 - 15:17The distribution changes to "alive!"
-
15:17 - 15:21And then, once you hit the threshold
-
15:21 - 15:25where the mutation rate is so high
that you cannot self-reproduce, -
15:25 - 15:30you cannot copy the information
forward to your offspring -
15:30 - 15:34without making so many mistakes
that your ability to replicate vanishes. -
15:34 - 15:36And then, that signature is lost.
-
15:38 - 15:40What do we learn from that?
-
15:40 - 15:43Well, I think we learn
a number of things from that. -
15:44 - 15:45One of them is,
-
15:45 - 15:50if we are able to think about life
in abstract terms -- -
15:50 - 15:53and we're not talking
about things like plants, -
15:53 - 15:55and we're not talking about amino acids,
-
15:55 - 15:57and we're not talking about bacteria,
-
15:57 - 15:59but we think in terms of processes --
-
15:59 - 16:01then we could start to think about life
-
16:01 - 16:04not as something
that is so special to Earth, -
16:04 - 16:06but that, in fact, could exist anywhere.
-
16:06 - 16:10Because it really only has to do
with these concepts of information, -
16:11 - 16:15of storing information
within physical substrates -- -
16:15 - 16:19anything: bits, nucleic acids,
anything that's an alphabet -- -
16:19 - 16:21and make sure that there's some process
-
16:21 - 16:24so that this information can be stored
for much longer than you would expect -- -
16:25 - 16:29the time scales for
the deterioration of information. -
16:29 - 16:32And if you can do that,
then you have life. -
16:32 - 16:35So the first thing that we learn
-
16:35 - 16:40is that it is possible to define life
in terms of processes alone, -
16:40 - 16:45without referring at all
to the type of things that we hold dear, -
16:45 - 16:48as far as the type of life on Earth is.
-
16:48 - 16:50And that, in a sense, removes us again,
-
16:50 - 16:53like all of our scientific discoveries,
or many of them -- -
16:53 - 16:56it's this continuous dethroning of man --
-
16:56 - 16:59of how we think we're special
because we're alive. -
16:59 - 17:02Well, we can make life;
we can make life in the computer. -
17:02 - 17:04Granted, it's limited,
-
17:04 - 17:09but we have learned what it takes
in order to actually construct it. -
17:09 - 17:11And once we have that,
-
17:12 - 17:14then it is not such
a difficult task anymore -
17:14 - 17:18to say, if we understand
the fundamental processes -
17:18 - 17:22that do not refer
to any particular substrate, -
17:22 - 17:25then we can go out and try other worlds,
-
17:26 - 17:29figure out what kind of chemical
alphabets might there be, -
17:30 - 17:35figure enough about the normal chemistry,
the geochemistry of the planet, -
17:35 - 17:39so that we know what this distribution
would look like in the absence of life, -
17:39 - 17:42and then look for large
deviations from this -- -
17:42 - 17:47this thing sticking out, which says,
"This chemical really shouldn't be there." -
17:47 - 17:49Now we don't know that there's life then,
-
17:49 - 17:50but we could say,
-
17:50 - 17:54"Well at least I'm going to have to take
a look very precisely at this chemical -
17:54 - 17:56and see where it comes from."
-
17:56 - 17:59And that might be our chance
of actually discovering life -
18:00 - 18:02when we cannot visibly see it.
-
18:02 - 18:06And so that's really the only
take-home message that I have for you. -
18:06 - 18:10Life can be less mysterious
than we make it out to be -
18:11 - 18:14when we try to think
about how it would be on other planets. -
18:14 - 18:18And if we remove the mystery of life,
-
18:18 - 18:22then I think it is a little bit easier
for us to think about how we live, -
18:22 - 18:25and how perhaps we're not as special
as we always think we are. -
18:25 - 18:28And I'm going to leave you with that.
-
18:28 - 18:29And thank you very much.
-
18:29 - 18:31(Applause)
- Title:
- Finding life we can't imagine
- Speaker:
- Christoph Adami
- Description:
-
How do we search for alien life if it's nothing like the life that we know? Christoph Adami shows how he uses his research into artificial life -- self-replicating computer programs -- to find a signature, a "biomarker," that is free of our preconceptions of what life is.
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDTalks
- Duration:
- 18:31
Brian Greene edited English subtitles for Finding life we can't imagine | ||
Krystian Aparta commented on English subtitles for Finding life we can't imagine | ||
Krystian Aparta edited English subtitles for Finding life we can't imagine | ||
Krystian Aparta edited English subtitles for Finding life we can't imagine | ||
TED edited English subtitles for Finding life we can't imagine | ||
TED added a translation |
Krystian Aparta
The English transcript was updated on 11/25/2016. At 05:42, "Scientific Institute" was changed to "Santa Fe Institute."