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So, it's been really exciting
to be an astrobiologist nowadays
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because astrobiology is starting to
intersect a lot of other fields
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that care very deeply about
understanding life -
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from the perspective of thinking about
more general principles.
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And, one of those fields is
the artificial life field,
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which has been exploring
fundamental properties of life
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and evolving systems
for a number of decades,
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and has made a lot of progress
in computational models
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of living processes that are starting to
be able to be used for thinking
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about problems relevant to astrobiology.
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So, I'm going to just talk about
a little bit of...
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where artificial life comes
into providing some new insights
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into what biology might be,
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and how we might think about life
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as a broader class of phenomena
from this astrobiological perspective -
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that we want to understand life,
not just on Earth,
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but life as it might exist anywhere.
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And, one of the things
that I always find really intriguing -
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being trained in physics -
is that biology seems to necessitate
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a different kind of perspective
on how we should think about
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the laws of nature,
how we should think about...
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dynamical systems.
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And, one of the things that's really
a pretty interesting contrast
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between physics and biology is that -
in physics, when we model systems,
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we always talk about like
the initial state.
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Like, you could talk of the initial state
of the universe
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or initial state of the solar system.
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And then, you have some fixed
law of motion,
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like Newton's law of gravitation,
or we could take Einstein's theory.
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And then, we can evolve our system
forward in time
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and we can predict the final state.
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In principle, we should be able
to do that with...
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perfect prediction power if we had,
you know,
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big enough supercomputers
and things.
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But, there's nothing about the laws
of motion that changes in time.
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So, Newton's law doesn't change -
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it's just the states that evolve
forward in time.
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But, in biology,
we have this really interesting case
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where we have an initial state,
like that last universal common ancestor
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of life on Earth.
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And then, as that system evolves,
it changes,
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and there's many possible final states.
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So, even though we started
from sort of a...
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shared cellular architecture
and early history of life,
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because of the interaction of life
and its environment
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and the change of information
in those systems,
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we've ended up with many, many
different final states for biology and...
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So, I'm an organism that descended
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from that last universal
common ancestor.
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And, so is the bacteria - you know -
on the screen...
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the computer screen
that I'm looking at right now.
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There's many final states
possible in biology.
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And, one of the ways
that we can talk about this
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is to even talk about the fact
that in biology
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this - the states themselves -
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are not the only thing that's evolving,
but the laws are too.
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We talk about state dependent rules
or state dependent laws in biology,
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and this is the idea -
that, as an organism evolves,
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its genetic information is changing.
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And, even as it...
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expresses that genetic information,
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it can actually dictate its own state.
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So, biology has its property
of homeostasis
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and regulating its own state -
that sort of a state control.
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And, this kind of like the rules
are actually controlling this state,
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or the constraints
are controlling the state.
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So, that seems really fundamentally
different than the situation
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that we see in physics
and how we model physical systems
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that aren't living.
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And the real story there is that -
in biology -
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part of the dynamics is the information
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and how the information
is changing in time.
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And so, in the artificial life field,
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people like to try to model
these emergent properties,
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or what's going on in biology,
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using really simple systems
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that allow us to understand
really basic things about life.
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One example that is used commonly
in the artificial life field
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is cellular automata.
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And, one of the reasons
that people really like those
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is because they have
really simple local rules,
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just like the laws of physics do,
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but we see really interesting
global patterns emerging.
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And so, for example,
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this is an elementary
cellular automata "Rule 150,"
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and you can see here
what the pattern is for the rules.
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So, if you have three white cells
it maps to one white cell.
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If you have three black cells,
it maps to a black cell.
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And then, different patterns
of whites and black cells
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will either map to a black
or a white cell.
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So, it's a very simple rule,
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but you'll see that there's this
really regular pattern that emerges
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when you run the dynamics
that's not encoded in the rule at all.
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So, we talk about that
as an emergent property.
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And, life has many emergent properties.
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So, one question is -
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would those emergent properties of life
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be explained by the structure
of the laws of physics alone,
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or do we need additional principles,
and do we really need something
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like state planet dynamics
or information
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or any new principles
that are uniquely biological
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to explain how biology has
this sort of many paths
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that we observe
through the evolutionary process?
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And, that's a great question
for artificial life.
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People have thought about that
from many different perspectives
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in addition to cellular automata.
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But, we'll talk about cellular automata
just a little bit more
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because they're a really
nice simple example.
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And so, as I said,
this is an example of this idea in physics
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of starting with an initial state
of fixed law of motion
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and evolving to some final state.
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The Game of Life is perhaps
one of the most famous examples
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of using this kind of construction
to understand
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what emergent properties are
and how complexity can emerge
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from simple rules.
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So, in The Game of Life,
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it's actually a two-dimensional
cellular automata
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as opposed to the one-dimensional one
I showed on the previous slide.
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And, what you see is,
with The Game of Life,
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all kinds of emergent patterns
appearing -
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from things that glide
across your screen
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that look like little guns
shooting things,
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to blinkers,
to all kinds of different structures,
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and they can interact
and make more complex structures.
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And so, people have actually...
there's sort of a cottage industry
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of people studying different emergent
patterns in The Game of Life,
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and under what conditions they emerge,
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what their computational capacity is.
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So, it's been a really great
toy model system to explore this idea
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that emergence might...
we might be able to talk about
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emergent properties from simple rules.
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One of my favorite cellular automata
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was actually constructed
by John von Neumann,
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and he was really interested in this idea
of self-reproducing machines.
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And so, a self-reproducing machine
or automata
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would be a system that could make
a complete reproduction of itself.
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And, he was actually really inspired
by Alan Turing
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and Turing's work
on universal computation.
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So, Turing had been interested in
whether you could build a machine
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that can compute
any computable function.
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And, von Neumann asked the question,
inspired by trying to understand life -
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so, this is very early work
in the artificial life field -
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could you build a machine
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that could build any possible machine
including itself?
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And, if it could do that,
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then it would be
a self-reproducing machine.
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But, it would also be a machine
that could - in principle -
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be capable of open-ended evolution,
which is a really important question -
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in the artificial life field
related to astrobiology -
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about the idea of whether or not evolving
systems can keep evolving forever.
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So, if you had a self-reproducing
machine that could build itself,
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but not build any arbitrary machine,
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it might stall out and not actually be
an evolving system.
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And so, von Neumann had this condition
that it should be able to build anything -
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so that the space of all possible things
would be completely open,
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that it could potentially evolve into,
as long as it could maintain the fact
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that it could reproduce itself.
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And so, he came up with
a particular architecture
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that's necessary for such a machine.
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What he basically came up with is that
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you need to have some kind
of information content -
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the instructions for specifying
the design of the machine.
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The machine has to be able to read out
those instructions to build itself,
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and then it has to be able to have
something called a "supervisory unit"
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that tells it when to copy
the instructions
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just as instructions,
rather than reading them out.
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So, the instructions have to
have a dual role.
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They have to be able to be copied
to be able to reproduce the organism,
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but they also have to be read out
to be able to be executed
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to construct the organism.
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And, the machine doing the construction
is the part that can...
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is the machine that can build
any possible machine.
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And, he called that
a "universal constructor."
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And, there is a direct analogy
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with modern cellular architecture
as we understand it,
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in that the translation machinery -
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ribosomes and all the associated
tRNAs and translation machinery -
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could be thought of
as a universal constructor
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that can construct any possible proteins.
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So, it's not a universal constructor
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in the sense that it can make
any possible object,
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but it is a universal constructor
in the sense
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that it can produce any possible protein.
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And, the instruction tape is DNA,
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which gets read out by the cell,
but also gets blindly copied
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by the cell at other stages
in cellular function.
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So, it does seem to be the case
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that this abstract idea
from artificial life -
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von Neumann's idea of
the self-reproducing automata -
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actually maps to some of the function
that we see in biology.
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And so, this was a case where
a cellular automata theory
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actually predicted some of the logical
architecture of modern organisms.
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And so, one of the things that's really
interesting about von Neumann's idea
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was that he had envisioned
the possibility of a machine
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that could build any possible machine,
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which means it could do any possible
transformation on physical matter.
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And, most cellular automata
actually can't do that.
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So, if you look at cellular automata
and you evolve them forward in time -
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in the way that we do,
where we have an initial condition
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and the cellular automata rule
is fixed for all time -
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not every state transformation
is possible.
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So, you can't move from every state
to every other state.
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But, there is this idea
that's implicit in von Neumann's theory
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for biological evolution -
from this artificial life perspective -
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of physical universality,
which is the ability to implement
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any transformation on any finite region.
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The first physical universal
cellular automata
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was actually just realized recently
by Luke Schaeffer...
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and he actually demonstrated
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that it was possible
to construct such a thing.
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And, he did so within this sort of
traditional physics paradigm,
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where he started with an initial state
and evolved the system
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according to a fixed rule,
and the physical universality
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comes about by programming
the initial state.
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Now if you're thinking about things
like biological evolution,
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then we want to think about
biological systems
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in this kind of very abstract way
inspired by artificial life.
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And, think about von Neumann's theory
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and what it's really telling us
about biology,
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one of the things we might hope for
is that biology
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would actually be capable of
performing any arbitrary transformation.
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And, a good example of that
is modern technology.
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So, I think actually modern technology
is a better approximation
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to a universal constructor
than an interior of a cell,
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in the sense that technology enables
lots of transformations to be possible.
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So, for example, we can launch
satellites into space.
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And, that's not a transformation
that would be able to be happening -
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we wouldn't be...
our planet wouldn't be anti-accreting -
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launching things into planetary orbit
without having technology.
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So, it does allow transformations
and biology seems to do this in general.
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If you think about metabolism...
allows chemical transformations
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that seem thermodynamically impossible.
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So, if you wanted to talk about
those kind of properties
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from this cellular automata perspective,
what you really would like
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is to be able to build
a cellular automata
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that can perform
any arbitrary transformation
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and has this kind of inspiration
from biology.
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So, we've been kind of playing around
with those in my group
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and this is just sort of an example of...
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an artificial life approach
to astrobiology.
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Thinking about cellular automata
with state-dependent laws...
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So, the idea here is that
we go back to that difference
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that we were observing
between physics and biology,
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and think about the fact that life
seems to have this property
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where the rules and the states
are very tightly coupled.
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So... the expression
of my genetic information
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determines the state of the cells
in my body.
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My mental state determines
something about what I do.
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So, if you want to build
systems that do that
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you can actually build cellular automata
with state-dependent laws.
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And, you see lots of different
rich structures emerging
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from these kind of systems,
and they do have this property
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of physical universality
that Schaeffer observed,
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but from this very different perspective.
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And so, these are just some examples
to raise some questions for you
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about the kinds of things
that we could be thinking about
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from more abstract models of life
in the artificial life field
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to get at more general principles
of living systems.
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So, we have this idea in mind
that information perhaps
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might be this unifying principle of life,
and that really also comes from
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the inspiration of
the artificial life field -
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because von Neumann was really interested
in this idea of the instruction,
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the information content being what's
specifying the design of the machine,
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and that the machine could actually
implement those instructions.
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And so, in some sense,
what he's talking about
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is an algorithmic process
existing in nature
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is necessary to have open-ended
evolving systems.
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And so, we really don't understand
the basic physical principles of that.
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And so, one of the things
I think is incredibly exciting
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about working across the field
of artificial life in astrobiology
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is that artificial life models have
traditionally been these very abstract,
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cellular automata type models,
or there's other things - like Avida -
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that are these digital systems
that we program into computers
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and we study their properties
and they tell us some things
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about emergent properties
or how systems can evolve.
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But, astrobiology affords the opportunity
of starting to think about
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those kind of things
as chemically embodied systems,
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and how do we think about the fact
that the origin of life transition
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actually did happen -
these properties emerged
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in the natural world from chemistry.
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And so, that's really the challenge
for astrobiology moving ahead...
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is to take the abstract ideas
from artificial life
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and turn them into quantitative science
for astrobiology to build new theories
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of what we think life is,
and how the transition
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from simple molecules to something
that has the sophisticated logical
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and informational architecture
of something
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like a von Neumann machine
actually emerged on our planet.
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And, what does that actually mean
in the broadest sense?
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And, what are the kind of classes
of phenomena
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that we might see in the world
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that could be inspired
by that understanding...
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i.e. can we find aliens?
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And so, that's really a great thing
to think about.