Just before Christmas, I witnessed
something
something extraordinary. I stood in
a
a room
a room with two robots that were
starting
starting to do something distinctly
human.
human. They were learning like
young
young children do, when they
discover
discover the world for the first
time.
time. They were developing a
language,
language, one that I didn't
understand. It's quite scary. Oh,
gosh,
gosh, it's asked me to do something.
More
More and
More and more of the things we once
thought
thought made us human are now being
taken
taken on
taken on by machines. I want to
find
find out
find out how close we are to
creating
creating artificial intelligence.
And
And what
And what that might mean for us as
human.
human. As
human. As a mathtition, should I be
worried
worried that they may put me out of
a
a job,
a job, or
a job, or could they extend human
intelligence in unimaginable new
ways?
ways? What are these machines? Or,
who
who are
who are they?
In
In February 2011, New York was a
seen
seen for
seen for a very public test of how
clever
clever machines have become. A
showdown
showdown watched by millions, took
place
place between two men and a
supercomputer. The arena for this
battle
battle was a quiz show called
Jeopardy.
Jeopardy. It's one of the most
popular
popular and long-running quiz shows
in
in America. It's famous for its
fiendishly difficult questions.
Fortunately, those in mankind's
corner
corner had no problem with these
questions. One of the two human
contestants was Brad Rutter, the
show's
show's biggest-ever money winner.
He
He became
He became a five-time champion,
earning
earning a
earning a record $3.2 million. As
long
long as
long as I
long as I can remember, I grew up
with
with Jeopardy and by the time I was
in
in high
in high school I started realising
I
I knew
I knew the answers to most
questions
questions and if I ever get a
chance
chance to
chance to try out, I think I can do
pretty
pretty well. If wow have told me
how
how well
how well I would actually do I
would
would have said you were crazy, but
$3.2
$3.2 million later here I am. Now,
the
the newcomer. This is Watson.
Watson
Watson was one of the most
sophisticated AI computers ever
built.
built. Sitting in the audience was
his
his creator. We wanted to do this
kind
kind of
kind of experiment, this
illustration of what would it take
for
for a
for a computer to play Jeopardy
against
against a
against a human. A brain that fits
in
in a
in a shoebox powered on a glass of
water
water and
water and sandwich then you have a
computer
computer 80 kilowatts of
electricity and 20 tonnes of air
conditioning. This is what it took.
In
In the
In the lead-up to the match, Watson
had
had to
had to learn how to play the game.
In
In effect, it had to be coached.
One
One of
One of the most difficult tasks it
faced
faced was
faced was to get to grips with the
cryptic
cryptic format of the game, where
the
the contestants are first given the
answer
answer and have to come up with the
question.
question. This queen fled to London.
It
It had
It had to
It had to go through the 200
million
million pages of information it had
been
been programmed with and find the
answer
answer in
answer in just three seconds. A
famous
famous clown or any incompetent
fool?
fool? Who
fool? Who is Bozzo. After four
years
years of
years of development, Watson was
considered ready for the challenge.
Let's
Let's play Jeopardy. Here we go. It
was
was a
was a really, really tense moment.
If
If I
If I was
If I was going to fail we were
going
going to
going to fail in front of - This
was
was real
was real jeopardy? This is real.
You
You were
You were putting yourself on the
line.
line. This was real and live.
People
People are going to route for the
people
people rather than the machine, so
we
we felt
we felt a
we felt a little bit of pressure,
but
but also
but also a great opportunity to
kind
kind of
kind of represent humanity against
encroaching technology, shall we
say?
say? Four-letter word for a vantage
point
point or
point or belief? What is a view.
You
You have
You have adrenaline going. It was
an
an open
an open playing field. Anything
could
could happen. Who can Grendell What
is
is the
is the 1930s? After the first round
of
of the
of the first game, Watson was tied
with
with Brad
with Brad at about $5,000. Into a
tie
tie for
tie for the lead. I think everyone
sat
sat there
sat there and thought at least we
didn't
didn't lose. In other words, at
least
least at
least at this point, the awedients
is
is understanding -- audience is
understanding that the system is
good
good to
good to tie a grand champion. Too
close
close for
close for comfort. I remember that
moment
moment when I first heard about
Watson.
Watson. I
Watson. I thought what a key moment
for
for AI.
for AI. We have already programmed
a
a computer to beat humans at chess,
but
but chess
but chess is a vertical thought
process,
process, where you are making deep,
logical
logical connections. Watson is
doing
doing something completely
different
different and thinking horizontally,
accessing
accessing a huge database. This is
machine
machine intelligence taken in a new
direction. The computer is starting
to
to think
to think in a multi-dimensional way.
How
How the
How the game would unfold was to
change
change the way many people think
about
about artificial intelligence,
including
including me. But in order to
understand the real significance of
Watson,
Watson, I
Watson, I need to know where this
dream
dream to
dream to replicate our intelligence
came
came from.
For
For thousands of years, we have
invented
invented machines to do things for
us.
us. But
us. But there was one moment in
history
history where we realised they
weren't
weren't just slaves, but had the
potential
potential to be our rivals. Or even
our
our masters.
I've
I've come
I've come to the place where this
realisation first came to life. It
was
was in
was in this building, that the
search
search for artificial intelligence
began.
began. What happened here still
resonates
resonates today. The idea that
machines
machines could be intelligent like
us
us was
us was sparked by one man. He was
the
the brilliant man, Alan Turing and
he's
he's a
he's a real hero of mine. When he
was
was a
was a young man in his 20s he came
to
to work
to work here at Bletchley Park, as
a
a code
a code breaker. This was the home
of
of British intelligence at the time.
It
It was
It was the 1930s and Britain was
gearing
gearing up to war with Germany. As
well
well as
well as needing the brute force of
the
the military, the Government were
gathering
gathering a crack team hear. And
his
his genius was precisely what was
needed
needed at
needed at this time of national
crisis.
The
The main
The main problem that he had to
wrestle
wrestle with whilst here, was this.
It's
It's an
It's an enigma machine and it's an
incredibly clever piece of kit. It
was
was used
was used by the German military to
scramble
scramble secret messages into code
that
that nobody could understand.
Cracking
Cracking this code was incredibly
difficult
difficult for humans. The Germans
believed
believed that the code was
uncrackable. It was up to human
minds
minds to
minds to decipher the cryptic
communication that was picked up on
the
the airwaves. This was an
impossibly long task. We were on
the
the brink
the brink of war and didn't have
time
time to
time to waist. -- waste. The
machine
machine consists of a key board
that
that I
that I will type my message on to
try
try to
try to encode it. If I press an R,
then
then the
then the wires in the machine go
through
through and light up a letter at
the
the top
the top here, so the R was encoded
by
by theler
by theler N, but the incredible
thing
thing is,
thing is, about the machine, if I
press
press R
press R again it doesn't get
encoded
encoded by N the next time, because
these
these rotas have kicked on one step
and
and so
and so the wires are connecting up
the
the letters in a completely
different
different way now. So when I now
press
press R
press R it is F. The operators had
different
different ways that they could set
up
up the
up the machine, so they can make a
choice,
choice, for example, of which rotas
they
they were
they were using, so there were five
different
different rotas and they would
choose
choose three and they could put
them
them inside in different orders.
Then
Then they
Then they would set each of the
rotas
rotas on
rotas on one of 26 different
settings
settings and then not only that,
they
they had
they had some plugs at the front
here,
here, which would also scramble up
all
all of
all of the letters, so the combined
effect
effect is
effect is that there are over 150
Slobodan
Slobodan Milosevic different ways
that
that the
that the machine can be -- million,
million,
million, million, different ways
that
that the
that the machine can be set up. It
really
really was human against machine.
Alan
Alan Turing and his team realised
the
the human
the human mind wasn't fast enough
to
to do
to do this and the only hope they
had
had of
had of cracking the code was to
create
create another machine to do it.
This
This is
This is the incredible machine that
he
he and
he and his colleagues created. It's
called
called the Bomb. It was from this
mesh
mesh of
mesh of cogs and switches held
together
together by over ten miles of wire
that
that finally came the ability to
crack
crack the
crack the code on a daily basis.
Something
Something that no human had come
close
close to
close to being able to do. What
this
this machine did changed the course
of
of the
of the war and many regard as
crucial
crucial to the allied victory over
the
the Germans.
In
In one
In one sense, this machine was just
a
a collection of cogs and wheels.
But
But it
But it could do something that some
of
of the
of the finest finds in Britain
couldn't.
couldn't. It was an unsettling
moment.
moment. Was this machine cleverer
than
than a
than a human? That is an incredibly
satisfying sound. It must have been
an
an amazing moment when they
switched
switched it on for the first time,
seeing
seeing the cogs clicking through
all
all the
all the different possibilities,
getting
getting a
getting a possible setting in ten
minutes
minutes what would have taken
humans
humans weeks to try to find. To see
this
this machine solve a problem that
many
many regarded as impossible, it
must
must have
must have really fired Alan
Turing's
Turing's imagination. This was
built
built to
built to crack the enigma code, but
he
he must
he must have begun to think about
what
what was
what was the limit of what machines
could
could do?
could do? Once the war was over,
his
his ideas
his ideas about machines that could
mimic
mimic the
mimic the human mind really started
to
to take
to take shape. But it was when he
asked
asked the
asked the question, can a machine
think
think in
think in a paper in 1950, that the
idea
idea finally sparked people's
imaginations. For many, it conjured
up
up terrifying visions of the future
and
and sparked furious debate. But it
was
was this
was this idea, above any other,
than
than inspired scientists in labs
across
across the world to try to re-
create
create what is essentially us. The
hunt
hunt for
hunt for artificial intelligence
has
has become tied up with one
technology, the computer. At the
heart
heart of
heart of it is the simple idea that
humans
humans and computers aren't so very
different. The central thesis of AI
is
is that
is that actually all human thought
is
is just
is just computation, that the mind
and
and the
and the brain are just a
sophisticated sort of machine. So,
if
if you
if you could make a big enough
computer,
computer, with the best software,
you
you can
you can make a copy of the human
mind.
So
So riveted by the man versus
machine
machine Jeopardy game. Because at
estheart,
estheart, it was so much more than
just
just a
just a TV
just a TV showdown. Hoare was a
machine
machine that could grapple with
natural
natural language, as well as any
human.
human. --
human. -- here. Including pun,
riddles
riddles and complex questions
across
across a
across a broad range of knowledge.
Please
Please welcome Watson. At the end
of
of the
of the first round, the
supercomputer Watson was neck and
neck
neck with
neck with human Brad. But as the
second
second round began, the computer
started
started to show what it was really
capable
capable of. Watson who is... Frans
list.
list. Who
list. Who is the church lady. It
all
all fell
all fell apart from Ken and me the
second
second day. Watson went on a tear.
What
What is
What is violin. It ex exceeded
expectations Watson dominated the
entire
entire thing. The final blow for
human
human kind was when Watson went on
to
to win
to win a
to win a bonus question. Answer...
Which
Which doubleded his score. When
Watson
Watson hit the daily double that
was
was pretty much the end of the road
ch
ch you
ch you could see the look on Ken's
face,
face, we
face, we knew, the guys in the team,
that
that "It
that "It was over, we've won."
Watson's
Watson's landslide victory made
headlines
headlines across America. I would
have
have thought technology like this
was
was years
was years away but it is here now.
I
I have
I have the bruised eco-to prove it.
For
For days
For days after the interhet was
alive
alive with chatter about the demise
of
of humanity. Here was a computer
that
that was
that was displaying uniquely human
qualities. This machine could
understand all the complexities,
puns
puns and
puns and riddles much faster than
any
any human. But was this true
artificial intelligence? Was Watson
really
really thinking like us? The 1980s
the
the American philosopher John
Searle
Searle challenged the idea whether
a
a machine
a machine could ever really think.
He
He came
He came up with an interesting
thought
thought experiment to try and prove
his
his idea.
his idea. It is called the Chinese
Room.
Room. I
Room. I am going to try and put
that
that into
that into practise to explore his
idea.
He
He imagined a non-Chinese speaking
person
person like me, in a bare room,
with
with an
with an instruction manual, and a
selection
selection of Chinese characters. He
then
then imagined someone who could
speak
speak Chinese, to be outside the
room,
room, communicating with me, by a
series
series of
series of messages written using
Chinese
Chinese characters. Can you speak
Chinese?
Chinese? The messages are posted to
me
me through a door. And I have to
come
come up
come up with a response, even
though
though I
though I don't understand a word of
Chinese.
Chinese. OK I haven't got a clue
what
what this
what this says. But if I follow the
instructions in this book, I should
be
be able
be able to give some sort of
response
response to this question, which
will
will make
will make some sort of sense, so
let's
let's have a look. What do I have
to
to find?
to find? There is a little one over
X
X symbol.
X symbol. The book tells me to find
an
an exact
an exact match of the message on
the
the top
the top half of the page. And then
to
to reply
to reply by copying the Chinese
characters from the bottom half of
the
the page.
the page. That is interesting. Some
of
of the
of the characters appear in the
answer,
answer, which makes some sense.
Gosh,
Gosh, I
Gosh, I don't know whether these
are
are the
are the right way round. That looks
like
like a
like a little house with a roof on
the
the top.
the top. I need this character here.
Oh
Oh yes.
Oh yes. Bingo! Who knows what I
have
have just
have just said! Can you speak
Chinese?
Chinese? He compared the person in
the
the room
the room making up the Chinese
message,
message, to a computer reading a
bit
bit of
bit of code. Have you been to
China?
No
No I
No I haven't been to China but
would
would one
would one day like to. I am just
faking
faking I
faking I can speak Chinese. So just
how
how convincing was I? You your
Chinese
Chinese was perfect. If we were on
line
line having a chat like that, you
would
would have been convinced you were
talking
talking to... I really really would.
I
I would
I would have thought you were
someone
someone who spoke Chinese. The
Chinese
Chinese Room I think is an
important
important thought experiment. Not
for
for the
for the answers it offers but more
for
for the
for the questions it raise, because
I
I certainly didn't understand a
word
word of
word of what I was writing down
there,
there, yet I seem to be able to
fake
fake the
fake the fact I was speaking
Mandarin,
Mandarin, so if a computer is
following
following instructions, isn't
really
really thinking, is it? But then
again,
again, what is my mind doing when I
am
am actually articulating words now?
It
It is
It is following a set of
instructions, so it raises the
question,
question, where is the threshold?
What
What point can you they a machine
is
is really
is really understanding and
thinking?
thinking? So, our bigger and faster
machines
machines going to bring us closer
to
to this
to this threshold? Since John
Searle
Searle came one the Chinese Room
experiment computer power has been
doubling
doubling every two years. I am off
to
to see
to see one of the most powerful
computers
computers that exists in the world
today.
today. We
today. We enter the lab I need to
warn
warn you
warn you it will be very noisy. You
will
will need
will need some ear protection. Oh!
What
What is
What is the noise? So that is all
cold
cold air
cold air blowing through the racks,
to
to cool
to cool off the computer chip.
Because
Because they are working so hard.
Because
Because they are working so hard.
This
This is
This is the first time I have done
an
an interview with ear plugs in.
This
This beast of a machine called Blue
Gene
Gene is
Gene is a
Gene is a phenomenal piece of
engineering. It is used to perform
the
the kind
the kind of calculations that my
brain
brain could never do, and it never
has
has to
has to sleep. Fred Mintzer is the
naers
naers inventor and Cray to have
Blue
Blue Gene. -- master. So this is
first
first generation Blue Gene rack.
Its
Its commutational performance is
5.6
5.6 Terra
5.6 Terra nops a second. A teraflop
is
is a
is a million million operations per
second.
second. Faster than I can go.
Faster
Faster than you can go. How many
have
have you
have you got. We have 16 Rab rack,
they
they all
they all work in parallel. That is
60,000
60,000 processors and a performance
of
of 91
of 91 teraflops a second. Blue Gene
is
is solving complex calculations
about
about biological processes. It
would
would take me the rest of my life
to
to do
to do what this computer can do in
an
an hour.
an hour. But is it really being
intelligent? Or is it just doing
what
what it
what it is told? The real
intelligence comes from the
programmer. It is totally
programmed intelligence. Would you
say
say it's
say it's a big number cruncher.. It
is
is an
is an enormous number cruncher. But
it
it the
it the doing the things our brains
could
could never get anywhere near. It S
computers
computers are good at computation,
brains
brains do
brains do much more. It is
impressive to see just how powerful
they
they have
they have become. This firepower
you
you have
you have with Blue Gene is
something
something my brain could get
nowhere
nowhere near, but then again, with
when
when I
when I am
when I am doing maths it is not
just
just doing number crunching. I am
doing
doing more than that. The brain is
working,
working, making leap, a lot of
imagination, there is a lot of
choices
choices involved, which often
involve
involve a
involve a kind of aesthetic
sensibility. I am not saying a ma
sheen
sheen like that might not be able
do
do that
do that but at the moment it is a
sheer
sheer brute force crunching. It
hasn't
hasn't captured what my brain can
do.
do. These
do. These other qualities that
inare
inare inhe want hernt in how man
intelligence, like creativity and
imagine
imagine nation, are what make us so
unique.
unique. And they are the reason
that
that the
that the quest for artificial
intelligence is such an interesting
and
and difficult challenge. There is
no
no reason
no reason to think that a computer
couldn't
couldn't one day develop these
qualities
qualities too. But to do this,
scientists have got to get o grips
with
with exactly how well develop them
in
in the
in the first place.
At
At the
At the heart of human intelligence
lies
lies ourable to learn to do things
we
we have
we have never done before. Which is
what
what has
what has borough me here. And that
is
is not
is not me
is not me by the way. I have joined
the
the circus an my challenge is to
walk
walk the
walk the tightrope. Not something
mathematicians normally do. My
instructor for the day is Lila. You
are
are nervous. It is not that. There
we
we go.
we go. This is a training wire.
So...
So... This isn't the real thing. It
is.
is. It
is. It is
is. It is the same you will feel on
the
the high
the high wire. You don't have the
fear
fear fabg
fear fabg - factor because you can
stand
stand over it safely. The other one
there
there is
there is a bit of jeopardy. No, it
is
is just... You could get a body
bubble
bubble edouble. He is wearing a red
shirt!
shirt! See, no movement. So once
upon
upon a
upon a time he couldn't do that. He
wasn't
wasn't born being able do that.
That
That is
That is something he learned. Yes.
I
I should
I should have the confidence that I
can
can learn
can learn this new skill.. You know
the
the younger you learn something...
What
What are
What are you saying? I am saying it
is
is easier. You saying I am too old.
No,
No, not
No, not at all. I am going to do
this.
this. Lila can't programme me with
a
a set
a set of
a set of rules. Unlike a computer,
my
my brain
my brain and my body have to master
this
this by
this by themselves. As a
mathematician I know there is a
formula
formula to describe what is going
on
on here.
on here. But I can't calculate my
way
way out
way out of this. I just have to do
it.
Let
Let your
Let your muscles do the thinking.
Turn
Turn your
Turn your brain off a bit. I have o
do
do things
do things with my body and I have
to
to think
to think and counter act certain
things
things which I shouldn't do. There
is
is a
is a guy
is a guy over there, who can just
sort
sort of
sort of skip and dance across.
Hands
Hands up.
Hands up. Hands up. Hands up! I am
trying
trying to
trying to concentrate on the wall
over
over there and keep my hand up, I
am
am trying
am trying to keep this leg straight,
and
and maybe
and maybe I am thinking too much. I
think,
think, we
think, we have to get some of it
into
into muscle memory so you don't
think
think about that, that it comes
naturally. As I flail round on the
tightrope, I can see the
complicates physics I am asking my
brain
brain and
brain and body do to master this
new
new skill. It is this idea that the
brain
brain and
brain and body work together. That
is
is taking
is taking the hunt for AI in a
whole
whole new
whole new direction.
I
I have
I have come to meet a scientist who
has
has built
has built the world's first
anthropomimetic robot. Which means
it
it mimics
it mimics the hue -- human body.
Because
Because he believes that our fiscal
form
form actually helps shape the way
we
we think.
we think. Without a body,
artificial intelligence cannot
exist.
exist. 6.
exist. 6. What we are interested in
is
is how
is how the brain controls body and
having
having built the body we have
realised
realised what a serious problem
that.
that. Can
that. Can I interact with it? Would
you
you like
you like to shake hands with it?
Yes,
Yes, provided it doesn't clonking
me
me anywhere sensitive. Give its
hand
hand a
hand a good squeeze and a shake.
Ooh.
Ooh. It
Ooh. It is
It's
It's squeezing back. It's really
responding to contact with me,
picking
picking up something. It gives
people
people the sensation of interacting
with
with something that in a way of
really
really like themselves. This robot
called
called Ecce Robot has no blood or
skin
skin or
skin or flesh, but ha bones, joints,
muscles
muscles and tendons that move like
ours,
ours, so
ours, so it's able to have human
interactions. This is an
extraordinary piece of engineering,
but
but how
but how does it help in getting
insight
insight into intelligence? We are
interested in what is known as
embodied
embodied intelligence. This is the
idea
idea that
idea that your intelligence is not
an
an abstract free intelligence, but
tied
tied very
tied very much to having a body and
in
in particular to having a human
body.
body. In
body. In order to investigate this,
what
what we
what we have to do was build a
robot
robot that had as near to a human
body
body as
body as we can manage and
investigate the way it interacts
with
with the
with the world and enables it to
develop
develop a
develop a particular sort of
intelligence for dealing with
objects
objects and so on. Once we get on
that
that track we'll be able to see how
that
that intelligence, how that is
actually
actually determined and conditioned
by
by its
by its body. You think it will be
distinct
distinct from the sort of
intelligence that - does it know
I'm
I'm talking about it? The
intelligence that before they were
doing
doing things in robots, computers
and
and that
and that doesn't have a sense of a
body,
body, it's a box? What happened
when
when people started trying to make
robots
robots that were controlled by AI
and
and computers, is that they found
that
that the
that the things that we thought
would
would be
would be difficult like playing
drafts
drafts or
drafts or something like that were
extremely
extremely easy. What was difficult
was
was moving the pieces. The
interaction with the world is very,
very
very difficult and requires a lot
of
of computation, but we are
completely unaware of this. What
about
about the
about the ultimate goal of things
like
like imagination or consciousness,
this
this would actually become
conscious
conscious of its own body? I like
to
to think
to think it's the most interesting
question
question of all, but there are lots
of
of problems to overcome before we
get
get to
get to that stage. I happen to
believe
believe it will be possible one day
to
to build
to build a machine that will have a
kind
kind of
kind of consciousness, whether it's
the
the same
the same consciousness as ours,
whatever
whatever that means, will be an
issue.
issue. I
issue. I don't really believe we
are
are going
are going to arrive at
consciousness with a disembodied
computer.
computer. This robot suggests that
human
human intelligence simply cannot be
divorced
divorced from the human body that
created
created it. The hunt for AI has
ended
ended up
ended up on an alternative path.
It's
It's not
It's not about hardware and
software,
software, but about trying to
replicate
replicate human biology. Back at
the
the circus school, I'm still having
problems
problems with my own body as I
continue
continue to struggle to get across
the
the tightrope. Take that leg off
right
right away. Good. Up, up. Come on,
fight
fight it.
fight it. It's a battle. You think
this
this isn't going to work, but the
minute
minute you reach up you are pulling
yourself
yourself back in line. It doesn't
seem
seem logical. It really didn't. I
was
was thinking that will do that. I
feel
feel there are lots of instructions
going
going on
going on here and I've got to try
to
to put
to put them together and maybe I'm
-
- well,
- well, I
- well, I don't know, whether I'm
ever
ever going to be able to do this.
This
This is
This is something -- is this
something
something instinctive I'll be able
to
to learn,
to learn, or whatever? Move, move,
move.
move. If
move. If you are doing maths, you
are
are thinking, thinking, you need to
clear
clear that. This feels really alien.
But
But when
But when I take a step back I
realise
realise that I've done something
very
very similar to this before. That's
when
when I
when I learnt to walk as a child.
Really
Really relax your brain. Hands up.
Step.
Step. Come on. I need to get mean
now.
now. Hands up. What's truly
remarkable about our brains is that
everything we learn to do from
seeing,
seeing, thinking, walking and
talking,
talking, becomes automatic when
practice.
practice. Go, go, go. Don't rush.
Hands
Hands up.
Hands up. Hands up! We'll try a
little
little bit of military technique.
Use
Use a
Use a whip now! This ability to
learn
learn to
learn to do something instinctively,
without
without even thinking about it, is
what
what makes us human. Getting a
machine
machine to do this is one hell of a
task.
task. Getting a computer to see has
become
become one of the most difficult
challenges in AI. Our vision is key
to
to our
to our intelligence. Without it how
would
would we
would we perceive the world around
us?
us? The
us? The one scientist -- for one
scientist, the challenge has been
to
to get
to get a
to get a computer to be able to
monitor
monitor and interpret CCTV footage,
like
like a
like a human does. You would think
with
with the
with the power of computers and a
mainframe
mainframe in here scanning all the
programmes we can write, you would
be
be able
be able to pick up We haven't
written
written the programme that can do
this
this sort
this sort of thing. It's so
difficult
difficult for a computer to pick
out
out the
out the needles in the haystacks.
Our
Our brains have learnt to control
our
our eye
our eye movements effortlessly,
taking
taking in
taking in the whole seen. We
instantly
instantly combine this with our
previous
previous knowledge of what a car,
bus,
bus, person or building looks like.
In
In less
In less than seconds we can make
sense
sense of
sense of all the activity that's
going
going on
going on in busy Piccadilly Circus.
For
For a
For a computer to recognise just
one
one of
one of these elements, is almost
impossible. James wants to show me
why
why this
why this is. This is a simple
programme
programme to demonstrate how
difficult
difficult vision is. What it does
is
is remove
is remove our hardware, our vision
processing hardware from the
problem,
problem, so we have to process each
bit
bit of
bit of the image piece by piece,
rather
rather like a computer has to. My
challenge
challenge is to try to recognise a
few
few familiar faces. It's through a
tiny
tiny dot
tiny dot on the screen. Is this
somebody
somebody I should know? Yep, you
should
should know all of these. OK. I've
found
found the
found the eye. OK. I've got a bit
of
of clothing there. Check shirt.
Exactly.
Exactly. You can put all this
together,
together, Marcus. Then I should get
it?
it? Yeah.
it? Yeah. I don't know. Give in on
that
that one.
that one. Stephen Hawking. Try
again.
again. Another face. It's weird, I
can
can pick
can pick out eyes and nose and
mouth.
mouth. Putting that all together in
bits,
bits, but
bits, but it doesn't have enough
hair
hair for
hair for Einstein. It's relevant
for
for this
for this programme. OK. Alan Turing.
We'll
We'll have one more. Beyond picking
out
out that
out that this is a face, I think
just
just the
just the little pieces kind of
piece
piece by
piece by piece - all right, it's me.
I
I don't
I don't spend ages looking at me.
It
It really
It really demonstrates how
difficult
difficult it is. A computer can
only
only interpret one small business
of
of the
of the image at a time. But we have
learnt
learnt to
learnt to piece all the pixels
together
together and see the whole thing
with
with no
with no effort at all. James has
been
been wrestling with the problems
for
for years. He has done something
really
really interesting, I think. He's
developed
developed a piece of software that
uses
uses ground-breaking technology to
recognise
recognise individuals in a crowd.
He
He wants
He wants to use me as a guinea pig.
What
What we'll do now is take you out
on
on to
on to the
on to the streets and track you out
and
and about. This means tracking you
as
as you
as you go
as you go within a camera and then
when
when you
when you move on to a different
view,
view, we'll track you into the new
camera
camera and try to find you there
and
and carry
and carry on to see how far we can
take
take you.
take you. I'll be passing under the
gaze
gaze of
gaze of the Dons of CCTV cameras in
and
and around Piccadilly Circus. --
dozens.
dozens. It's difficult for a
computer
computer to pick out, because as I
walk
walk through the different camera
shots
shots my
shots my size and position changes
all
all the
all the time. Whereas we can
separate
separate what is me and what isn't
without
without even thinking about it.
James'
James' computer system gives each
person
person a
person a sequence of numbers and
then
then attempts to recognise
individuals by matching their
number
number between all the different
camera
camera views. On the right-hand
side
side of
side of the screen we can see where
the
the computer has successfully
picked
picked me
picked me out of the crowd on my
journey
journey around central London. In
the
the end,
the end, I was tracked across five
views
views as
views as I walked a quarter of a
mile.
mile. James is making real progress
in
in getting a computer to recognise
what
what it's
what it's looking at. But there's a
deeper
deeper question at stake here. --
steak
steak here. It's not just about --
stake
stake here. It's not just about
assigning
assigning objects, but what we see.
It's
It's something that humans working
here
here don't have a problem with. I
don't
don't think we'll get rid of the
human
human intervention. On a Friday or
Saturday
Saturday night, we see lots of
people,
people, the ones who have had a
drink
drink will mess about and play
fight.
fight. I
fight. I don't think a computer
would
would be
would be able to tell the
difference between a real and play
fight,
fight, because we can look at the
expressions on faces and see if
they're
they're smiling or if they're angry,
so
so I
so I don't think we're at that
stage.
stage. The chaos of the urban
jungle.
jungle. Exactly. The human eye is
still
still better. We are programmed to
pick
pick out
pick out something unusual. That's
weird.
weird. What are you found there? A
pair
pair of
pair of shoes on a seat. I was
curious
curious as to why they are there.
It's
It's kind
It's kind of strange. I've looked
around
around to
around to see who they might belong
to
to why
to why they might be there, a
couple
couple of
couple of people have sat down next
to
to them
to them and walked away, so you
know
know they're not theirs, but I
don't
don't think a computer can be
programmed with the level of
curiosity
curiosity and that's a natural
human
human emotion. This desire to
understand meaning is absolutely at
the
the forefront of artificial
intelligence right now. Our brains
do
do it
do it by
do it by learning complue
experience and it's become a really
--
-- through experience and it's a --
it's
it's become a really complex
experience. I'm being reminded
today
today what a great human thing it
is
is to
is to be
is to be able to learn something
through
through experience. You would learn
this
this pretty quick if you thought a
crocodile
crocodile was under you. Trying to
get
get across a wire encapsulates all
the
the problems involved in getting a
machine
machine to do a new task. Through
the
the process of learning by
experience we are able to combine
all
all the
all the different abilities that
are
are needed. Like body control,
reasoning
reasoning and instinct. I've tried
everything to get across this wire.
Nothing
Nothing seems to be working. But
then
then Leila comes up with one little
thing.
thing. Try a little song. It
releases
releases any little tune. I'm
chatting
chatting to you now to try to relax
you
you a
you a bit. La, la, la, la. Keep
coming,
coming, don't stop. Keep the leg
down.
down. Keep coming. Keep it small.
Hands
Hands up.
Hands up. Hands up. Come on! That
was
was so
was so easy. You were there. So
close
close and
close and then my hand went down.
What
What you
What you just did there, right to
that
that point, looked really easy. I
thought
thought you can cracked this. I
don't
don't know, sometimes the last, the
anticipation, it's the last step or
something. This is the last bit.
You've
You've got it, so keep that
momentum
momentum going. We can't fully
explain
explain how our brains learn in
this
this way.
this way. I don't know where the
huming
huming is
huming is helping, but it is. Don't
rush.
rush. Oh,
rush. Oh, yes, I'm rushing. Mm, mm,
mm.
Hand
Hand up.
Hand up. Leg off, hand up. Hand up.
Little
Little steps. Hands up. Hand up.
Hand
Hand up.
Hand up. Yes! It wasn't elegant.
Frpbts
Frpbts it
Frpbts it was pretty elegant.
Perfect.
Perfect. Well done. That is an
amazing
amazing feeling to be able to get
from
from one
from one end of the tightwire to
the
the other. But that is the amazing
thing
thing about human intelligence,
just
just how
just how adaptable it is, how I can
go
go from
go from nothing to learning a new
skill
skill like doing the tightwire. If
you
you think
you think about a computer, you
would
would have to programme it
especially to be able to do such a
task
task like
task like this and throw
something different and for it to
be
be lost
be lost again. Perhaps we can try
the
the trapeze now? Yes, sure, great!
One
One other
One other human quality we like to
celebrate, and often link to
intelligence, is creativity. I have
come
come to
come to Paris, where the streets
are
are steeped in artistic culture. I
am
am here
am here to visit an unusual
artist's
artist's studio. Run by computer
scientist
scientist Simon Colton, who is
normally
normally based at Imperial College
London.
London. All these immap -- images
have
have been
have been created not by him but by
a
a computer. Because Simon wants to
find
find out
find out if it is possible to break
down
down the
down the creative process into a
set
set of
set of instructions. That is why I
started
started simulating paint strokes.
And
And this
And this is a good example of that.
As
As well
As well as programming it with
painting
painting techniques, Simon gives
the
the computer rules about different
artistic
artistic styles. We can choose a
painting
painting style according to the
emotion
emotion of the sitter. So it is
kind
kind of
kind of feeding off its suant and
trying
trying to
trying to tap in and appreciate its
mood.
mood. His
mood. His of her mood and express
that
that through the art. I can see
what
what a
what a difficult task this is. But
there
there is
there is one image that has really
caught
caught my
caught my eye. I love this one.
Lots
Lots of
Lots of comments from people. This
is
is what
is what dancers? That is right. But
these
these people don't really exist.
This
This isn't a photo that, or a video
it
it has
it has looked at. It is taking some
concept
concept of people fed into it. When
you
you watch
you watch it being painted it
paints
paints it
paints it all in one stroke. This
is
is a
is a single line. Is that is what
is
is giving
is giving it this sense of energy
and
and motion? That is right. Yes.
That
That is
That is a
That is a classic example of where
you
you put
you put in a rule, where you have
more
more out
more out of it than you put in I
had
had no
had no idea that I would get this
kind
kind of
kind of effect. I had no idea it
would
would give such a dynamism. I say
that
that real
that real creativity makes you
think
think more, so the software we are
developing, that will make us think
more
more not
more not less. Just like every
artist
artist or
artist or musician or poet wants us
to
to think
to think more. So, I see a
different
different future for AI which is
somewhere
somewhere software is out there to
challenge
challenge you. So if these
creations
creations are meant to challenge us,
what
what do
what do the city's artists make of
them?
them? There is something sexual. In
this
this artwork. Interesting. Like
bacon,
bacon, like monkey. You are seeing
bacon
bacon and
bacon and monkey? That is
interesting. Is it a man or ma heen
who
who does
who does the paintings. Why do you
think?
think? Was a it is done
automatically. How can you tell,
you
you are
you are right, but, I am interested.
You
You can
You can see it. For me I am not an
artist,
artist, so I would be hard pushed.
What
What gives it away? There is no
sensibility. Really? You can pick
that
that up.
that up. That is interesting. I
quite
quite like the image, or some of
them
them any
them any way. It is clear that
trying
trying to
trying to mimic something as
elusive
elusive as raytivety remains a huge
challenge. -- creativity. But
scientists are starting to put down
the
the first
the first important building blocks.
100 years
100 years the birth of the
visionary
visionary mathematician Alan Turing,
we
we are
we are discover hag the hunt for AI
is
is a
is a more
is a more difficult problem than he
or
or we
or we ever imagined. Machines have
surpassed
surpassed us as specific tasks, but
the
the human
the human brain sets the bar for
artificial intelligence extremely
high,
high, in
high, in its ability to constantly
learn
learn new
learn new skills. Hard wear and
software,
software, are struggling to mimic
our
our biology. But maybe there is
another
another way to create a thinking
machine.
machine. That can capture the
versatility of the human brain. I
have
have come
have come to Berlin, for the
highlight
highlight of my journey. To meet a
scientist
scientist who believes that for
something
something to be truly intelligent,
it
it needs
it needs to develop and evolve like
we
we did
we did at
we did at the very beginning of our
lives
lives and
lives and as a species. If you want
to
to understand how to create or
understand intelligence in some way,
we
we have
we have to capture this
evolutionary adaptive aspect of it.
So
So we
So we cannot programme
intelligence? We cannot hope to
give
give it
give it the purpose and do the
learning
learning and, a lot of people think
that
that today, but it, we have to
understand this continuous adaptive
nature,
nature, this flexibility, also this
motivation to continue to learn, to
be
be excited about new thing, to seek
out
out new
out new things. Luc is taking me to
a
a lab
a lab on
a lab on the outskirts of the city.
To
To show
To show me some robots that are
starting
starting to do something remarkable.
Three
Three of
Three of them. They are punch
larger
larger than I thought they were
going
going to
going to be. -- much. These robots
have
have been
have been set up to develop much
like
like a
like a young child does.
They
They are
They are beginning to understand
how
how their
how their bodies work, by looking
at
at a
at a reflection of themselves. You
have
have a
have a mirror, so what is the....
Well
Well the
Well the experiment is about that
the
the robot
the robot would learn something
about
about its
about its own body, because in
order
order to
order to move in the world, in
order
order to
order to control it, in order to
also
also recognise the movements of
another,
another, you need to have some sort
of
of model
of model of your own body. Right.
The
The way
The way that the model is going to
be
be built
be built up is that the robot is
doing
doing actions, and watching itself.
Performing the actions. So to get a
relation
relation between the visual image,
and
and movement of the motor for. So
here
here you
here you see this looking at the
its
its hand.
its hand. You also see very much
how
how I
how I was
how I was trying to keep balance.
It
It is
It is very impressive. How all the
motor
motor commands are in an early
phase,
phase, right. Well caught! It has
just
just woken up. I know that feeling.
I
I think
I think this was a beautiful
example
example of feedback, and of finding
balance.
balance. It is extraordinary. It
really
really does look like it is
encountering itself for the first
time.
time. But
time. But what is even more
remarkable about Luc's robots, is
that
that once
that once they are able to
recognise
recognise themselves, they start to
evolve
evolve their own language and
communicate with each other. So
what
what will
what will happen now? Well, one of
them
them is
them is going to speak, then he is
going
going o
going o to ask the other one to do
an
an action. He is going to invent a
word,
word, because he doesn't have yet
the
the word
the word to maim that action. Right.
OK,
OK, so
OK, so then he says the word and
this
this one
this one isn't sure whether what it
could
could mean, this is a brand-new
word,
word, so
word, so he will make a guess, and
if
if the
if the guess is OK, totally by luck,
well
well they
well they both know this word and
they
they know
they know for the future they can
use
use this
use this word to communicate with
each
each other. What if he gets it
wrong?
wrong? If
wrong? If it gets it wrong this one
will
will say
will say this is not what I had in
mind.
mind. He
mind. He will show it. OK. I mean I
don't
don't know which one is going to
speak
speak first. OK, he is speaking
first.
first. He
first. He is doing the action. That
is
is fantastic. OK. Notice how he
looked.
looked. So he is... He is doing the
real
real action. So now there is
another
another interaction going to happen
again.
again. I
again. I don't know which one is
going
going to
going to speak. OK. Is that the
word
word it
word it just learned. Kimato? He is
doing
doing it.
doing it. He will say yes,
presumably. Yes. So would they
interact
interact with me, to learn this
language?
language? Yes, we could try it. OK.
Do
Do you
Do you remember any one of the
words.
words. We
words. We will see. In is scary.
Gosh
Gosh it
Gosh it has asked me to do
something. Kimato. What was that?
Was
Was it
Was it that, have I got it right.
OK,
OK, you
OK, you tell me what Kimato is. OK,
that
that is
that is right. All right. Tomima.
Tomima.
Tomima. I
Tomima. I think that was lifting my
right
right arm. Did it get it right. Yes.
I
I am
I am learning robot! What would you
say
say to
say to people that would suggest
that,
that, well this looks simple. They
are
are doing
are doing a few action, swapping
words
words what is the big deal? The
first
first thing I would say to people,
just
just try
just try it yourself, OK, just try
to
to build
to build a robot that stands up.
And
And then,
And then, you already will see its
extraordinary complicated. How fast
do
do you
do you think the development will
be
be in
be in of
be in of the intelligence of these
robot,
robot, such they are beginning to
create
create a
create a new language between
themselves, but how long will it be
before
before they are, I don't know,
creating
creating great works of art, the
sort
sort of
sort of things that we can do? You
know,
know, if
know, if we have these two robots
and
and we
and we let them alone. We come back
at
at the
at the end o of the day and they
will
will have
will have developed a vocabulary
for
for co-ordinating their action,
once
once they
once they start talking about
shapes
shapes and colours and we don't
know
know when
know when they say Bobita do they
mean
mean a
mean a colour or a position in
space.
space. You will be going through
the
the same
the same process that the robot did
to
to acquire that language, I mean...
Yeah.
Yeah. The
Yeah. The exciting thing about the
robots,
robots, is they have their own
evolutionary journey to go on.
Tomima.
Tomima. Which could happen much
quicker
quicker than ours. And they open up
the
the possibility for intelligences
very
very different from our own to
emerge.
emerge. That was a striking example
of
of a
of a merging intelligence,
something
something which wasn't
preprogrammed. Those robots really
started
started with a pretty blank sheet,
and
and by
and by the end of the day just
talking
talking to each other, they had
evolved
evolved their own language. A Laing
cadge
cadge I
cadge I couldn't really understand.
Turing
Turing asked can machines think? I
think
think he
think he would be excited by what I
just
just saw.
--
-- a
-- a language I couldn't understand.
I
I have
I have discovered that computers
have
have far
have far surpassed humans in many
fields
fields but are unlikely to put us
out
out of
out of business yet. Because these
super
super machines haven't come close
to
to capturing the true nature of our
intelligence. But I also learned
how
how closely our intelligence is
linked
linked to
linked to our biology. And that
perhaps
perhaps the secret to creating
thinking
thinking machines lies in letting
them
them develop like we do.
But
But the
But the one thought that has been
creeping
creeping up on me throughout all of
this,
this, is
this, is that maybe we have become
obsessed
obsessed with our own abilities.
And
And are
And are blinded by being human. It
does
does raise the question about
whether
whether we should be bothering to
try
try and
try and recreate what is us, when
machines
machines can do something so
different
different to what human beings can.
For
For me,
For me, the really exciting thing
about
about AI
about AI is the potential machines
have
have to
have to generate a new kind of
intelligence, that has its own
distinct
distinct identity.