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Finding life we can't imagine | Christoph Adami | TEDxUIUC

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

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Video Language:
English
Team:
TED
Project:
TEDxTalks
Duration:
19:51

English subtitles

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