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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:

Chris Adami talks about how to find life... that is not like ours.

Christoph Adami 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. 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 wrote the textbook "Introduction to Artificial Life" (Springer, 1998) and is the recipient of NASA's Exceptional Achievement Medal.
http://www.kgi.edu/Faculty-and-Research/Christoph-Adami.html

This talk was recorded at TEDxUIUC 2011 (02/19/11), which was organized at the University of Illinois at Urbana-Champaign by a group of students led by Cristian Mitreanu.
http://www.tedxuiuc.com

About TEDx, x = independently organized event

In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
http://www.ted.com

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

English subtitles

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