right so the topic of tonight is how to shape the future and because I’m a
shape the future and because I’m a
shape the future and because I’m a computer scientist so something that we
computer scientist so something that we
computer scientist so something that we are working on on our research team
are working on on our research team
are working on on our research team right now in Strasbourg University is to
right now in Strasbourg University is to
right now in Strasbourg University is to think on how it is possible to make
think on how it is possible to make
think on how it is possible to make computers to make them autonomous to
computers to make them autonomous to
computers to make them autonomous to have some creative autonomous computers
have some creative autonomous computers
have some creative autonomous computers so in order to understand how this can
so in order to understand how this can
so in order to understand how this can happen it can happen through the mix of
happen it can happen through the mix of
happen it can happen through the mix of two things which is ai ai is artificial
two things which is ai ai is artificial
two things which is ai ai is artificial intelligence but also artificial
intelligence but also artificial
intelligence but also artificial evolution most people don’t know that in
evolution most people don’t know that in
evolution most people don’t know that in parallel with the development of AI
parallel with the development of AI
parallel with the development of AI artificial evolution has also developed
artificial evolution has also developed
artificial evolution has also developed so if you look at a timeline on how
so if you look at a timeline on how
so if you look at a timeline on how computers have and research on these
computers have and research on these
computers have and research on these domains have been now going on
domains have been now going on
domains have been now going on well 1953 is more or less the first
well 1953 is more or less the first
well 1953 is more or less the first business computer the IBM 650 okay and
business computer the IBM 650 okay and
business computer the IBM 650 okay and you see that artificial intelligence
you see that artificial intelligence
you see that artificial intelligence developed in 1955 1960 56 and so on so
developed in 1955 1960 56 and so on so
developed in 1955 1960 56 and so on so it was what some of the very very first
it was what some of the very very first
it was what some of the very very first algorithms that have been developed on
algorithms that have been developed on
algorithms that have been developed on computers were of artificial
computers were of artificial
computers were of artificial intelligence but of course the very same
intelligence but of course the very same
intelligence but of course the very same thing that has been puzzling people is
thing that has been puzzling people is
thing that has been puzzling people is about evolution so if in 1953 you’ve got
about evolution so if in 1953 you’ve got
about evolution so if in 1953 you’ve got first trials in Australia USA in Europe
first trials in Australia USA in Europe
first trials in Australia USA in Europe in 1957 chains of bits have been evolved
in 1957 chains of bits have been evolved
in 1957 chains of bits have been evolved by Frazer and you go on like this
by Frazer and you go on like this
by Frazer and you go on like this and those two technologies have come up
and those two technologies have come up
and those two technologies have come up come of age and interestingly enough it
come of age and interestingly enough it
come of age and interestingly enough it has been sooner in artificial revolution
has been sooner in artificial revolution
has been sooner in artificial revolution than in artificial intelligence
than in artificial intelligence
than in artificial intelligence ever since the year 2000 now we have
ever since the year 2000 now we have
ever since the year 2000 now we have human competitive computers algorithms
human competitive computers algorithms
human competitive computers algorithms that are capable of creating of
that are capable of creating of
that are capable of creating of innovating creating get imagining new
innovating creating get imagining new
innovating creating get imagining new solutions that had never been thought
solutions that had never been thought
solutions that had never been thought about before by human beings
about before by human beings
about before by human beings and since 2009 there’s a there has been
and since 2009 there’s a there has been
and since 2009 there’s a there has been another revolution which is the advent
another revolution which is the advent
another revolution which is the advent of graphic processing units these are
of graphic processing units these are
of graphic processing units these are massively parallel chips on which you
massively parallel chips on which you
massively parallel chips on which you have several thousands of course that
have several thousands of course that
have several thousands of course that can work in parallel all right but the
can work in parallel all right but the
can work in parallel all right but the only problem is that you need to have
only problem is that you need to have
only problem is that you need to have the right algorithms in order to be able
the right algorithms in order to be able
the right algorithms in order to be able to exploit them and artificial
to exploit them and artificial
to exploit them and artificial revolution is one of them and in
revolution is one of them and in
revolution is one of them and in parallel artificial intelligence is also
parallel artificial intelligence is also
parallel artificial intelligence is also one of the type of algorithms that can
one of the type of algorithms that can
one of the type of algorithms that can exploit these GPUs with in 2012 the the
exploit these GPUs with in 2012 the the
exploit these GPUs with in 2012 the the the advent of deep learning so for those
the advent of deep learning so for those
the advent of deep learning so for those of you who not who don’t know about deep
of you who not who don’t know about deep
of you who not who don’t know about deep learning yet and who don’t know what
learning yet and who don’t know what
learning yet and who don’t know what deep learning is capable of doing here
deep learning is capable of doing here
deep learning is capable of doing here are a couple of examples so the
are a couple of examples so the
are a couple of examples so the state-of-the-art here is deep learning
state-of-the-art here is deep learning
state-of-the-art here is deep learning has been developed by young account and
has been developed by young account and
has been developed by young account and here is typically what comes up if the
here is typically what comes up if the
here is typically what comes up if the video is coming yeah so this is what a
video is coming yeah so this is what a
video is coming yeah so this is what a computer is capable of doing right now
computer is capable of doing right now
computer is capable of doing right now yes what is the man doing typing is the
yes what is the man doing typing is the
yes what is the man doing typing is the baby sitting on his lap yes are they
baby sitting on his lap yes are they
baby sitting on his lap yes are they smiling yes is there a baby in the photo
smiling yes is there a baby in the photo
smiling yes is there a baby in the photo yes where is the baby standing bathroom
yes where is the baby standing bathroom
yes where is the baby standing bathroom what is the baby doing brushing teeth
what game is being played
what game is being played soccer is someone kicking the ball yes
soccer is someone kicking the ball yes
soccer is someone kicking the ball yes what color is the ball yellow what game
what color is the ball yellow what game
what color is the ball yellow what game is the dog playing frisbee what color is
is the dog playing frisbee what color is
is the dog playing frisbee what color is the dog black is the dog wearing the
the dog black is the dog wearing the
the dog black is the dog wearing the color yes
color yes
color yes what is the cat sniffing banana where is
what is the cat sniffing banana where is
what is the cat sniffing banana where is the cat
the cat
the cat I’m bed what color is the cat black and
I’m bed what color is the cat black and
I’m bed what color is the cat black and white what color are the bananas green
white what color are the bananas green
white what color are the bananas green okay all this is being done in real-time
okay all this is being done in real-time
okay all this is being done in real-time it is that’s the current state of the
it is that’s the current state of the
it is that’s the current state of the art of deep learning as it is called
art of deep learning as it is called
art of deep learning as it is called which is what has been developed by
which is what has been developed by
which is what has been developed by Facebook through Yemen account this is
Facebook through Yemen account this is
Facebook through Yemen account this is one of his achievements but also the
one of his achievements but also the
one of his achievements but also the problem is that you can have some big
problem is that you can have some big
problem is that you can have some big problems too because now you have Google
problems too because now you have Google
problems too because now you have Google photos that is using same technology
photos that is using same technology
photos that is using same technology with sometimes some bad labeling on some
with sometimes some bad labeling on some
with sometimes some bad labeling on some photos but then so not only is it is
photos but then so not only is it is
photos but then so not only is it is this working on photos but it’s also
this working on photos but it’s also
this working on photos but it’s also working on videos here you’re just
working on videos here you’re just
working on videos here you’re just looking for people all right the
looking for people all right the
looking for people all right the computer is automatically detecting the
computer is automatically detecting the
computer is automatically detecting the people but not only it is is it capable
people but not only it is is it capable
people but not only it is is it capable of detecting people it’s also capable of
of detecting people it’s also capable of
of detecting people it’s also capable of detecting any kind of other things so
detecting any kind of other things so
detecting any kind of other things so you can take a computer for a walk you
you can take a computer for a walk you
you can take a computer for a walk you know in town and so this is the analysis
know in town and so this is the analysis
know in town and so this is the analysis of the computer a man in a suit and a
of the computer a man in a suit and a
of the computer a man in a suit and a tie
tie
tie hold standing in front of the building
hold standing in front of the building
hold standing in front of the building of course it’s not a tie so computer
of course it’s not a tie so computer
of course it’s not a tie so computer makes some mistakes but you can see that
makes some mistakes but you can see that
makes some mistakes but you can see that the zip could really be mistaken for a
the zip could really be mistaken for a
the zip could really be mistaken for a time here a sign on the wall that says
time here a sign on the wall that says
time here a sign on the wall that says it’s trying to read the sign a man is
it’s trying to read the sign a man is
it’s trying to read the sign a man is walking down the street with a cell
walking down the street with a cell
walking down the street with a cell phone in front of a building of course
phone in front of a building of course
phone in front of a building of course the thing makes mistakes but roughly you
the thing makes mistakes but roughly you
the thing makes mistakes but roughly you know it
know it
know it it gets an idea on what is happening and
it gets an idea on what is happening and
it gets an idea on what is happening and this is again current technology so this
this is again current technology so this
this is again current technology so this is what AI is currently capable of doing
is what AI is currently capable of doing
is what AI is currently capable of doing and not only does it happen to don’t
and not only does it happen to don’t
and not only does it happen to don’t does it apply to images does it apply to
does it apply to images does it apply to
does it apply to images does it apply to videos but also it applies to
videos but also it applies to
videos but also it applies to text-to-speech and roughly everything
text-to-speech and roughly everything
text-to-speech and roughly everything that is around here so for those of you
that is around here so for those of you
that is around here so for those of you who have been looking old movies here is
who have been looking old movies here is
who have been looking old movies here is a movie that was considered as being
a movie that was considered as being
a movie that was considered as being science fiction complete science fiction
science fiction complete science fiction
science fiction complete science fiction back in the 90s
back in the 90s
back in the 90s some of you will recognize it that’s the
some of you will recognize it that’s the
some of you will recognize it that’s the time Terminator
time Terminator
time Terminator okay just arrived on earth and he’s
okay just arrived on earth and he’s
okay just arrived on earth and he’s looking for some things to some clothing
looking for some things to some clothing
looking for some things to some clothing so he’s trying he’s analyzing all the
so he’s trying he’s analyzing all the
so he’s trying he’s analyzing all the people that he sees because he you know
people that he sees because he you know
people that he sees because he you know needs to find someone who that matches
needs to find someone who that matches
needs to find someone who that matches his gait and apparently this guy is
his gait and apparently this guy is
his gait and apparently this guy is matching it you know so probably this
matching it you know so probably this
matching it you know so probably this this guy has clothes that he could put
this guy has clothes that he could put
this guy has clothes that he could put on I need your clothes your boots and
on I need your clothes your boots and
on I need your clothes your boots and your motorcycle so that’s the
your motorcycle so that’s the
your motorcycle so that’s the conversation
you forgot to say please you forgot to
you forgot to say please you forgot to say please that was a wrong answer from
say please that was a wrong answer from
say please that was a wrong answer from a human because if you look at what
a human because if you look at what
a human because if you look at what happens to him next this is exactly is
happens to him next this is exactly is
happens to him next this is exactly is not what he should vegetative sunset so
not what he should vegetative sunset so
not what he should vegetative sunset so here
here
here the Terminator was a autonomous computer
the Terminator was a autonomous computer
the Terminator was a autonomous computer and what made it autonomous first of all
and what made it autonomous first of all
and what made it autonomous first of all it was capable of analyzing what was
it was capable of analyzing what was
it was capable of analyzing what was around it understanding what was
around it understanding what was
around it understanding what was happening and what you see is that what
happening and what you see is that what
happening and what you see is that what was total science fiction at this time
was total science fiction at this time
was total science fiction at this time in the domain of recognizing what is
in the domain of recognizing what is
in the domain of recognizing what is happening around it this is exactly what
happening around it this is exactly what
happening around it this is exactly what we have right now all right now what is
we have right now all right now what is
we have right now all right now what is missing in order to get an autonomous
missing in order to get an autonomous
missing in order to get an autonomous computer it is the ability for a
computer it is the ability for a
computer it is the ability for a computer to be able to find solutions on
computer to be able to find solutions on
computer to be able to find solutions on its own to problems that have appeared
so what is autonomy one of the
so what is autonomy one of the definitions autonomy is could be the
definitions autonomy is could be the
definitions autonomy is could be the ability to solve a problem on your own
ability to solve a problem on your own
ability to solve a problem on your own and it’s here that artificial evolution
and it’s here that artificial evolution
and it’s here that artificial evolution comes in before speaking of artificial
comes in before speaking of artificial
comes in before speaking of artificial evolution what is evolution first we
evolution what is evolution first we
evolution what is evolution first we could define it in the following way in
could define it in the following way in
could define it in the following way in a dynamic environment where multiple
a dynamic environment where multiple
a dynamic environment where multiple coexisting species and individuals
coexisting species and individuals
coexisting species and individuals evolve thanks to random mutations the
evolve thanks to random mutations the
evolve thanks to random mutations the selection of the best creates some new
selection of the best creates some new
selection of the best creates some new species that are emergent and that are
species that are emergent and that are
species that are emergent and that are able to solve the problem of surviving
able to solve the problem of surviving
able to solve the problem of surviving adapting to the current conditions so if
adapting to the current conditions so if
adapting to the current conditions so if you look at what is happening in nature
you look at what is happening in nature
you look at what is happening in nature nature is extremely inventive you have
nature is extremely inventive you have
nature is extremely inventive you have some very improvable animals around here
some very improvable animals around here
some very improvable animals around here one of those that I really like is the
one of those that I really like is the
one of those that I really like is the opposite or proxy day it’s a fish that
opposite or proxy day it’s a fish that
opposite or proxy day it’s a fish that is a deep-sea fish and what you may
is a deep-sea fish and what you may
is a deep-sea fish and what you may think are its eyes are not its eyes is
think are its eyes are not its eyes is
think are its eyes are not its eyes is the gills this is where it breathes is
the gills this is where it breathes is
the gills this is where it breathes is two black spots in front and in fact its
two black spots in front and in fact its
two black spots in front and in fact its eyes this is not a drawing by the way
eyes this is not a drawing by the way
eyes this is not a drawing by the way it’s a picture
it’s a picture
it’s a picture okay so living anymore it’s taken from a
okay so living anymore it’s taken from a
okay so living anymore it’s taken from a video the eyes are the semi spheres the
video the eyes are the semi spheres the
video the eyes are the semi spheres the green semiosphere
green semiosphere
green semiosphere that are looking up okay and the fish is
that are looking up okay and the fish is
that are looking up okay and the fish is looking up through its transparent skull
looking up through its transparent skull
looking up through its transparent skull because it’s a deep-sea fish that is
because it’s a deep-sea fish that is
because it’s a deep-sea fish that is hunting for other for for other fish and
hunting for other for for other fish and
hunting for other for for other fish and typically it looks up it keeps looking
typically it looks up it keeps looking
typically it looks up it keeps looking up in order to find through to see if
up in order to find through to see if
up in order to find through to see if there’s a shadow of another fish that is
there’s a shadow of another fish that is
there’s a shadow of another fish that is swimming just over it and if there’s a
swimming just over it and if there’s a
swimming just over it and if there’s a shadow the fish would swim up the ice
shadow the fish would swim up the ice
shadow the fish would swim up the ice swivel in front in order to be able to
swivel in front in order to be able to
swivel in front in order to be able to catch its prey so you see that nature
catch its prey so you see that nature
catch its prey so you see that nature can be extremely inventive in order to
can be extremely inventive in order to
can be extremely inventive in order to find ways to adapt and and and for for
find ways to adapt and and and for for
find ways to adapt and and and for for these animals to survive so the question
these animals to survive so the question
these animals to survive so the question is can we use evolution for our own
is can we use evolution for our own
is can we use evolution for our own purposes and if can could be could we be
purposes and if can could be could we be
purposes and if can could be could we be implementing evolution into computers in
implementing evolution into computers in
implementing evolution into computers in order to create artificial evolution so
order to create artificial evolution so
order to create artificial evolution so this is what has been happening ever
this is what has been happening ever
this is what has been happening ever since the 1950s the second timeline that
since the 1950s the second timeline that
since the 1950s the second timeline that I described you start with a population
I described you start with a population
I described you start with a population that you initialize and as soon as you
that you initialize and as soon as you
that you initialize and as soon as you have a population of potential solutions
have a population of potential solutions
have a population of potential solutions to the problem you just evaluate them
to the problem you just evaluate them
to the problem you just evaluate them and this is what we call parents parents
and this is what we call parents parents
and this is what we call parents parents are solutions that have been evaluated
are solutions that have been evaluated
are solutions that have been evaluated you know whether they are good or not
you know whether they are good or not
you know whether they are good or not now once you have this population of
now once you have this population of
now once you have this population of parents well first of all you have a you
parents well first of all you have a you
parents well first of all you have a you you try to see if one of them is solving
you try to see if one of them is solving
you try to see if one of them is solving the problem if it’s the case then you
the problem if it’s the case then you
the problem if it’s the case then you stop there and you pick up the best of
stop there and you pick up the best of
stop there and you pick up the best of the population – that would be the best
the population – that would be the best
the population – that would be the best solution to your problem but if not then
solution to your problem but if not then
solution to your problem but if not then you select n parents and you have these
you select n parents and you have these
you select n parents and you have these different parents which are potential
different parents which are potential
different parents which are potential solutions to your problem you cross them
solutions to your problem you cross them
solutions to your problem you cross them over you mutate them you have variation
over you mutate them you have variation
over you mutate them you have variation operators and through those variation
operators and through those variation
operators and through those variation operators you create a population of
operators you create a population of
operators you create a population of children and once you have this
children and once you have this
children and once you have this population of children you’ll evaluate
population of children you’ll evaluate
population of children you’ll evaluate them then you get parents and children
them then you get parents and children
them then you get parents and children that you reduce through a replacement
that you reduce through a replacement
that you reduce through a replacement phase and well here you are you have a
phase and well here you are you have a
phase and well here you are you have a tip you have evolution inside a computer
tip you have evolution inside a computer
tip you have evolution inside a computer and once you get this well you get
and once you get this well you get
and once you get this well you get creative computers this is these are
creative computers this is these are
creative computers this is these are creatures that have been evolved by
creatures that have been evolved by
creatures that have been evolved by calcium’s back in 1994 and the idea was
calcium’s back in 1994 and the idea was
calcium’s back in 1994 and the idea was to find creatures that could
to find creatures that could
to find creatures that could swim so the computer has blocks you can
swim so the computer has blocks you can
swim so the computer has blocks you can assemble the blocks can move the blocks
assemble the blocks can move the blocks
assemble the blocks can move the blocks around and the idea is is to have a
around and the idea is is to have a
around and the idea is is to have a computer find a way to swim as
computer find a way to swim as
computer find a way to swim as efficiently as possible now some of them
efficiently as possible now some of them
efficiently as possible now some of them you see some some gates that that you
you see some some gates that that you
you see some some gates that that you can find in nature that the computer had
can find in nature that the computer had
can find in nature that the computer had been able to find on its own like these
been able to find on its own like these
been able to find on its own like these you know looking like sperm or and then
you know looking like sperm or and then
you know looking like sperm or and then this would be how to how you would run
this would be how to how you would run
this would be how to how you would run on a surface that would not be on the
on a surface that would not be on the
on a surface that would not be on the fluid anymore but on a solid surface but
fluid anymore but on a solid surface but
fluid anymore but on a solid surface but then of course you these are very old
then of course you these are very old
then of course you these are very old works you can see how the evolution
works you can see how the evolution
works you can see how the evolution creates for instance a marching cube so
creates for instance a marching cube so
creates for instance a marching cube so you start with a cube which has muscles
you start with a cube which has muscles
you start with a cube which has muscles which has bones which has fat cells and
which has bones which has fat cells and
which has bones which has fat cells and this is the result one of the resulting
this is the result one of the resulting
this is the result one of the resulting gates that’s another way for a cube to
gates that’s another way for a cube to
gates that’s another way for a cube to walk that has been evolved here again
walk that has been evolved here again
walk that has been evolved here again the programmer didn’t program any of
the programmer didn’t program any of
the programmer didn’t program any of these behavior it is the computer that
these behavior it is the computer that
these behavior it is the computer that came up with the behavior but through
came up with the behavior but through
came up with the behavior but through evolving steps so these are type protein
evolving steps so these are type protein
evolving steps so these are type protein problems but what could how could we be
problems but what could how could we be
problems but what could how could we be using them for real this is an example
using them for real this is an example
using them for real this is an example with the st5 project at nasa by jason
with the st5 project at nasa by jason
with the st5 project at nasa by jason long the idea now is that you have
long the idea now is that you have
long the idea now is that you have satellites that are micro satellites
satellites that are micro satellites
satellites that are micro satellites really small but because they’re really
really small but because they’re really
really small but because they’re really small they don’t have much batteries
small they don’t have much batteries
small they don’t have much batteries they are very they’re not powerful at
they are very they’re not powerful at
they are very they’re not powerful at all and they have to transmit back their
all and they have to transmit back their
all and they have to transmit back their data to the earth so either you have an
data to the earth so either you have an
data to the earth so either you have an antenna that is a single wire in which
antenna that is a single wire in which
antenna that is a single wire in which case you have an omni omnidirectional
case you have an omni omnidirectional
case you have an omni omnidirectional antenna that emits through the whole
antenna that emits through the whole
antenna that emits through the whole universe and just you catch a very small
universe and just you catch a very small
universe and just you catch a very small part of the signal from the earth or
part of the signal from the earth or
part of the signal from the earth or you’re trying to focus the signal
you’re trying to focus the signal
you’re trying to focus the signal towards a radio telescope and if you’re
towards a radio telescope and if you’re
towards a radio telescope and if you’re trying to focus the signal to a radio
trying to focus the signal to a radio
trying to focus the signal to a radio telescope you you had rather focus it so
telescope you you had rather focus it so
telescope you you had rather focus it so that you’ve got the exact surface of the
that you’ve got the exact surface of the
that you’ve got the exact surface of the radio telescope that is listening to the
radio telescope that is listening to the
radio telescope that is listening to the satellite so that you don’t waste any
satellite so that you don’t waste any
satellite so that you don’t waste any part of the signal typically have such
part of the signal typically have such
part of the signal typically have such little energy to transmit with the
little energy to transmit with the
little energy to transmit with the problem is that if you use
problem is that if you use
problem is that if you use the antennas hoody you gay models to
the antennas hoody you gay models to
the antennas hoody you gay models to model this well you could need an
model this well you could need an
model this well you could need an antenna that would be several meters
antenna that would be several meters
antenna that would be several meters long or if you were using a parabola the
long or if you were using a parabola the
long or if you were using a parabola the parabola would be much too large for the
parabola would be much too large for the
parabola would be much too large for the very tiny satellites that you’re
very tiny satellites that you’re
very tiny satellites that you’re creating so at some point a way to do is
creating so at some point a way to do is
creating so at some point a way to do is to give artificial revolution the
to give artificial revolution the
to give artificial revolution the Maxwell equations to give a an antenna
Maxwell equations to give a an antenna
Maxwell equations to give a an antenna simulator to the computer and say okay
simulator to the computer and say okay
simulator to the computer and say okay please can you evolve an antenna that
please can you evolve an antenna that
please can you evolve an antenna that would be small enough to be compatible
would be small enough to be compatible
would be small enough to be compatible the size of satellite but in that valid
the size of satellite but in that valid
the size of satellite but in that valid nevertheless would be able to focus
nevertheless would be able to focus
nevertheless would be able to focus enough the data towards the radio
enough the data towards the radio
enough the data towards the radio telescope and after I think it was three
telescope and after I think it was three
telescope and after I think it was three weeks of massively power computing using
weeks of massively power computing using
weeks of massively power computing using artificial evolution this is the result
artificial evolution this is the result
artificial evolution this is the result that was obtained by computer scientists
that was obtained by computer scientists
that was obtained by computer scientists not antenna engineers all right
not antenna engineers all right
not antenna engineers all right because we can’t see anything that was
because we can’t see anything that was
because we can’t see anything that was what was found by the computer and
what was found by the computer and
what was found by the computer and what’s very interesting is that it is
what’s very interesting is that it is
what’s very interesting is that it is the computer that found this shape very
the computer that found this shape very
the computer that found this shape very odd very strange shape very complex
odd very strange shape very complex
odd very strange shape very complex shape and when this was shown to the
shape and when this was shown to the
shape and when this was shown to the antenna engineers they said what is this
antenna engineers they said what is this
antenna engineers they said what is this computer scientists that well we don’t
computer scientists that well we don’t
computer scientists that well we don’t know the computer found this with your
know the computer found this with your
know the computer found this with your equations with your simulators right and
equations with your simulators right and
equations with your simulators right and what they did there then this of course
what they did there then this of course
what they did there then this of course tests the antenna into an anechoic
tests the antenna into an anechoic
tests the antenna into an anechoic chamber it worked perfectly and now they
chamber it worked perfectly and now they
chamber it worked perfectly and now they tested the second antenna with other
constraints and the computer came up
constraints and the computer came up with another antenna that was different
with another antenna that was different
with another antenna that was different or maybe a third antenna and the
or maybe a third antenna and the
or maybe a third antenna and the computer keeps coming up with antennas
computer keeps coming up with antennas
computer keeps coming up with antennas that are totally improbable and when you
that are totally improbable and when you
that are totally improbable and when you just plug them on they’re working
just plug them on they’re working
just plug them on they’re working perfectly well in the end so NASA had
perfectly well in the end so NASA had
perfectly well in the end so NASA had made a very small movie to deploy the
made a very small movie to deploy the
made a very small movie to deploy the est five mission and I think that they
est five mission and I think that they
est five mission and I think that they had at some point they said it was the
had at some point they said it was the
had at some point they said it was the first time a nonhuman technology was
first time a nonhuman technology was
first time a nonhuman technology was sent into space why is it non-human
sent into space why is it non-human
sent into space why is it non-human hasn’t been designed by a human has been
hasn’t been designed by a human has been
hasn’t been designed by a human has been designed by a computer and you’re not
designed by a computer and you’re not
designed by a computer and you’re not able to reproduce it it’s only computers
able to reproduce it it’s only computers
able to reproduce it it’s only computers that can do it
that can do it
that can do it so the idea now is that if you imagine
so the idea now is that if you imagine
so the idea now is that if you imagine that artificial intelligence allows
that artificial intelligence allows
that artificial intelligence allows computers to spot out problems because
computers to spot out problems because
computers to spot out problems because it knows what is happening around it
it knows what is happening around it
it knows what is happening around it then if it spots out a problem has to
then if it spots out a problem has to
then if it spots out a problem has to solve in order to complete this mission
solve in order to complete this mission
solve in order to complete this mission then computers could use artificial
then computers could use artificial
then computers could use artificial evolution to find a way to complete the
evolution to find a way to complete the
evolution to find a way to complete the mission to be inventive to find a new
mission to be inventive to find a new
mission to be inventive to find a new solution and so the the next revolution
solution and so the the next revolution
solution and so the the next revolution to come in computer science could be to
to come in computer science could be to
to come in computer science could be to a couple artificial intelligence and
a couple artificial intelligence and
a couple artificial intelligence and artificial evolution in order to have
artificial evolution in order to have
artificial evolution in order to have computers that are autonomous now of
computers that are autonomous now of
computers that are autonomous now of course there could be unexpected
course there could be unexpected
course there could be unexpected problems and that was one expected
problems and that was one expected
problems and that was one expected problem it should have been zooming on
problem it should have been zooming on
problem it should have been zooming on the on the bottom part of it and because
the on the bottom part of it and because
the on the bottom part of it and because now we need to think of a bit of
now we need to think of a bit of
now we need to think of a bit of philosophy and I have three sentences
philosophy and I have three sentences
philosophy and I have three sentences that were supposed to be printing just
that were supposed to be printing just
that were supposed to be printing just on the bottom of the screen the first
on the bottom of the screen the first
on the bottom of the screen the first sentence sentence comes from a French
sentence sentence comes from a French
sentence sentence comes from a French writer who said that scientists who
writer who said that scientists who
writer who said that scientists who should really rethink about what they’re
should really rethink about what they’re
should really rethink about what they’re doing and the real sentence I just
doing and the real sentence I just
doing and the real sentence I just forgot it because it was just written
forgot it because it was just written
forgot it because it was just written there well I’m not going to be
there well I’m not going to be
there well I’m not going to be remembering it it is possibly a French
remembering it it is possibly a French
remembering it it is possibly a French writer who said that science is but the
writer who said that science is but the
writer who said that science is but the rim of the soul if you’re not looking at
rim of the soul if you’re not looking at
rim of the soul if you’re not looking at what you’re doing now the second
what you’re doing now the second
what you’re doing now the second sentence was a very interesting one
sentence was a very interesting one
sentence was a very interesting one because it came from a very renowned
because it came from a very renowned
because it came from a very renowned scientist who said well if we knew what
scientist who said well if we knew what
scientist who said well if we knew what we were doing we wouldn’t be we wouldn’t
we were doing we wouldn’t be we wouldn’t
we were doing we wouldn’t be we wouldn’t be calling this research would we and so
be calling this research would we and so
be calling this research would we and so who has been saying this sentence if we
who has been saying this sentence if we
who has been saying this sentence if we knew what we were doing we wouldn’t be
knew what we were doing we wouldn’t be
knew what we were doing we wouldn’t be calling it research it’s just
calling it research it’s just
calling it research it’s just Einstein who said that and finally there
Einstein who said that and finally there
Einstein who said that and finally there is another philosopher lavished horse
is another philosopher lavished horse
is another philosopher lavished horse who said that scientist is not here to
who said that scientist is not here to
who said that scientist is not here to give answers the scientist is here to
give answers the scientist is here to
give answers the scientist is here to ask the right questions so finally we
ask the right questions so finally we
ask the right questions so finally we are now in a stage where we can create
are now in a stage where we can create
are now in a stage where we can create autonomous computers this is what we are
autonomous computers this is what we are
autonomous computers this is what we are doing in my team in Strasbourg
doing in my team in Strasbourg
doing in my team in Strasbourg University but it is we need to be very
University but it is we need to be very
University but it is we need to be very wary of what we are doing because these
wary of what we are doing because these
wary of what we are doing because these computers can make mistakes and if they
computers can make mistakes and if they
computers can make mistakes and if they do make you make mistakes then they they
do make you make mistakes then they they
do make you make mistakes then they they are autonomous they can
are autonomous they can
are autonomous they can think of new solutions in order to
think of new solutions in order to
think of new solutions in order to circumvent the problems and they will do
circumvent the problems and they will do
circumvent the problems and they will do it and the the last there was a very
it and the the last there was a very
it and the the last there was a very small video which was taken from 2001
small video which was taken from 2001
small video which was taken from 2001 Space Odyssey where you had Hal the
Space Odyssey where you had Hal the
Space Odyssey where you had Hal the computer that was flying the ship who
computer that was flying the ship who
computer that was flying the ship who computed that the in order to fulfill
computed that the in order to fulfill
computed that the in order to fulfill its mission there would be more
its mission there would be more
its mission there would be more probability for the computer to fulfill
probability for the computer to fulfill
probability for the computer to fulfill its mission without the human crew than
its mission without the human crew than
its mission without the human crew than with the human crew so at some point in
with the human crew so at some point in
with the human crew so at some point in the movie the computer decides to do
the movie the computer decides to do
the movie the computer decides to do away with the human crew because it
away with the human crew because it
away with the human crew because it computed that the probability for its to
computed that the probability for its to
computed that the probability for its to completes mission would be better
completes mission would be better
completes mission would be better without the humans so it proceeds into
without the humans so it proceeds into
without the humans so it proceeds into eliminating the humans so you see that
eliminating the humans so you see that
eliminating the humans so you see that computers can become very inventive and
computers can become very inventive and
computers can become very inventive and so now the very last sentence by a great
so now the very last sentence by a great
so now the very last sentence by a great philosopher who is sharpen our is that
philosopher who is sharpen our is that
philosopher who is sharpen our is that the task is not so much to see what not
the task is not so much to see what not
the task is not so much to see what not what no one has yet seen but to conceive
what no one has yet seen but to conceive
what no one has yet seen but to conceive what no one has yet imagined but that
what no one has yet imagined but that
what no one has yet imagined but that everyone sees so I let you ponder on
everyone sees so I let you ponder on
everyone sees so I let you ponder on this thank
this thank
this thank [Applause]
[Applause]
[Applause] [Music]
[Music]
[Music] merci beaucoup ejaculate
”
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