Oftentimes, innovations
solve practical problems, but the advancement of A.I. might bring new tools to chip away at the larger,
even existential questions. Are we alone in the universe? Can we create lifelike,
intelligent machines? Maybe they're all moonshots,
but imagine, one day, having a second,
synthetic version of you. -How's it going, brother?
-Oh, not bad. Just spent the last hour
mapping half the cosmos. I'm looking for
a constellation
to name after us. You mean "me," yeah? Whatever. Semantics. I'm doing all the work. Touchy. The starry night sky has been
a source of fascination and curiosity for centuries. Is there something out there? We've got all these suspect
places to look for life in our own solar system. And we're just
one little solar system in a large galaxy, which is one of many,
many galaxies in the universe. And so you realize
pretty quickly the chances of life elsewhere
are pretty high. [tuning radio] [man]<i> ...we hope we have a
number of listeners out there.</i> <i> Most of you are probably
soft and squishy humanoids.</i> <i> In case any artificial
intelligence is listening,
welcome as well.</i> [Bill Diamond]
You'll appreciate this, being a data scientist, you know we're generating
about 54 terabytes of data every day, so... See, that's music to my ears,
right there. [Diamond]
That's music to your ears. That's a nice playground
for your algorithms. [Downey]<i>
In remote northern California,</i> <i>two scientists are on their way
to collect data</i> <i> in hopes to answer
a cosmic question...</i> <i> one that's as old
as humankind itself,</i> <i> or at least, Galileo.</i> [Graham Mackintosh]
When it comes to the search for extraterrestrial
intelligence... [Diamond] Right. ...there is decades
of scientific discovery and progress which is relentlessly telling us life is more likely
than we thought. Yeah, the body of evidence
is becoming-- That's right. ...overwhelming,
but can we find it? [Mackintosh]
When I was ten years old, I was determined
to have my own computer, and I found out there was
a kit that you could buy and put together for yourself, so I earned enough money
to do that, and that got me hooked. I've been obsessed
with computers ever since. And I hope, I believe, that
A.I. can help us dig deeper, and hopefully come to the answer
we're looking for. Is there life beyond the Earth? [Diamond] Ever since
humans have been able
to gaze up at the sky and look at the stars, we've wondered, "Are we alone? Is this the only place
where life has occurred?" The SETI institute is trying
to answer this question. SETI institute was founded by Frank Drake, and Jill Tarter, and Carl Sagan. I co-founded this institute
back in 1984 as a way to save NASA money. <i> ...see if we can backtrack</i> <i> to see if we can figure out
what's venting...</i> Since then, it has grown far beyond
any of my expectations. We have nearly
80 PhD scientists here. Our research really starts
with, "How does life happen?" What are the conditions
under which life takes hold? We're trying to understand
that transition of how the universe and how our own galaxy
and solar system went from chemistry to biology. <i> The number of civilizations</i> <i> that there might be
in the galaxy</i> <i>is of the order of a million.</i> [Downey]<i> Carl Sagan
helped bring the cosmos</i> <i> down to Earth,</i> <i> but he wasn't the first
to popularize it.</i> <i> Ever since Orson Welles
scared our pants off</i> <i> with</i> War Of The Worlds, <i> pop culture has had its eyes
on the skies.</i> <i> Little green men,
extraterrestrials,</i> <i> contact with aliens continues
to capture our imagination.</i> [Diamond] We're interested
in all kinds of life, but of course we have
a special interest in intelligent or technological
life beyond Earth, hence, SETI. Hello, this is Seth Shostak
speaking to you from Big Picture Science. Today we're going to talk
about artificial intelligence. The machines of today
are a lot smarter, if you will, at least more capable, than the machines
of 50 years ago, incredibly... There's vast amounts of data
coming from space, and A.I. can, um... allows us to understand
that data better than we have been able to
in the past. It's this new capacity we have
to see patterns in data... [Tarter] We are trying
to find evidence of somebody else's
technology out there. We can't define intelligence, but we're using technology
as a proxy, so if we find some technology, something that's engineered, something that nature didn't do, then we're going to infer that at least
at some point in time, there were
some intelligent technologists who were responsible. [Diamond] So, Graham,
we call it Area 52. [chuckling] [Mackintosh] We are headed
to the Allen Telescope Array, and tonight we are going
to be doing an observation which really
is looking for signs
of extraterrestrial life, and we're gonna be
using A.I. models in a way that's
never been done before. [Diamond] All right,
we are good to go. So I gotta turn
my cell phone off,
no Bluetooth, nothing? Nope, we need to be
in a place that is radio quiet, so you don't have interference, or at least,
you minimize interference. We're gonna come around
another bend a little up ahead, and you'll see the dishes. [Mackintosh exclaiming] Oh! [Diamond] There we are. Welcome
to the Allen Telescope Array. [Downey]<i> The sole mission
of the Allen Telescope Array,</i> <i> or A.T.A.,</i> <i> is to search
for extraterrestrial life.</i> <i> Past telescopes
were basically toy binoculars</i> <i> compared to the A.T.A.,</i> <i> which was built in 2007</i> <i> with support from
Microsoft's Paul Allen.</i> <i> Part of what makes it
light-years ahead</i> <i> is its wider field of view,</i> <i> and ability to capture
a greater range of frequencies.</i> <i> It's also an array,</i> <i> which basically means</i> <i> it's a group
of many small dishes</i> <i> working together
to cover more ground,</i> <i> or sky.</i> Welcome to the A.T.A. Fantastic. Okay. Looks like
Jon is out there. I think he's manually
turning those dishes
to get 'em lined up. [laughing] -Hey, Jon.
-Jon! -Good to see you, man!
-Good to see you, yeah! My name is Jon Richards, and I'm the Senior
Software Engineer at the Allen Telescope Array. Radio astronomy is similar
to optical astronomy, except the radio wave
frequencies are much lower than visual, so to receive radio waves,
you need an antenna. Take a look, Graham.
Under the bell jar, you see the actual antenna that's picking up the signals
coming from space. This is spectacular. [Diamond] It's kept below the temperature
of liquid nitrogen. That brings
the noise level down, exactly what we want
for deep space observation. Just amazing. [Richards] The radio signals
from each one of these dishes are brought
into our control room, digitized, made into
binary ones and zeroes, and combined together to create the effect
of having one large dish, so we can actually
map out the sky much like you would with a regular
optical telescope. All right, let's head back. Let's go. The observation
we're gonna do tonight is with the Trappist-1 system. This is a star
that has planets circling, and at 8:00 tonight, two of those planets are gonna
align perfectly with Earth, which makes it exactly
the right moment to do an observation. We're gonna be listening in for signs of any kind
of communication between these two planets, even if that's not communication
directed at us. [Diamond] We're counting down
to 8:01 p.m., which is when
the orientation of these planets are going to be lined up
in our line of sight, the so-called conjunction. [Downey]<i> It's a little like
an intergalactic stake-out.</i> <i> The guys are waiting</i> <i> till the two planets
are closest together,</i> <i> and then plan to eavesdrop
on their conversation.</i> <i> They have no idea
what they're listening for,</i> <i> or if there's even gonna be
a conversation.</i> [Richards] So we can
take out this board here. We're gonna repurpose it. -So that's ready to go?
-Yeah, let's go put it in. All right, let's get it in. [Richards] Since the site's
getting close
to 20 years old now, my job is to get all this data
coming in cleanly and recorded cleanly, and that is a challenge. Here's the computer
which is sending all the data that we receive
from all of our dishes to our 48 terabytes
of data storage, so we need to replace a card. This card will control
our data storage. [Mackintosh] You know, often when people think of the search
for extraterrestrial life, they're thinking of someone
with headphones listening in on something
that is sent to us, something that's obvious. It's really not like that. It's a lot more subtle, and that's why we're
going to be collecting enormous amounts of data. All of the different parameters
we might have to explore set that volume,
that exploration volume, set it equal to the volume
of all the oceans on the Earth. So how much have we done,
in 50 years? Well, we've searched
one glass of water from the Earth's oceans. The technologies
that we've had to use until now were not big enough,
not adequate to the job. Okay. [Mackintosh] That's why
we need computer systems and artificial
intelligence systems to really turn that search
on its head. [Parr] When we think
about traditional software, we think about human beings
writing lines of code. What's extraordinary about A.I. is that we're teaching machines
how to learn. This is why
it's a quantum leap, because for the first time, instead of human beings
writing the software, the computer's actually building
an understanding itself. [Richards]
We have to keep in mind that the Trappist-1 system
is 39.4 light-years... 39.6. 39.6 light-years away, so this actual positioning
was 39.6 years ago. So not only are we, uh, are we doing
SETI research tonight, we're time-traveling. [Downey]<i> That's right.</i> <i> Because of how far away
these planets are,</i> <i> and how long it takes
radio waves</i> <i> to travel through space,</i> <i> the guys are listening
to a conversation</i> <i> from about 40 years ago.</i> <i> Here's some perspective.</i> <i> It takes about eight minutes</i> <i> for radio waves to get
from here to the sun.</i> <i> So, these planets?</i> <i> Yeah, a little farther away.</i> [Diamond]
Over your shoulder, Graham, there's a NASA illustration
of the Trappist system, and there's at least three
rocky, Earth-like planets where liquid water
can potentially be maintained-- Right. ...and that gives rise
to the possibility that biology could have formed
in this system. What's really interesting about this particular
planetary system, these planets
are very close together, much closer than, for example,
Earth to Mars. That means there could be
communication happening between these planets, and what we can
potentially do is listen in. Not that we can have
a conversation or understand
what they're, uh... -[Mackintosh] We don't need to.
-We don't need to. [Mackintosh] I love
this kind of observation because it has
as its basic principle something
that's really important. It's not all about us. No one's sending us a signal, no one's trying
to get our attention. The whole point about the search for
extraterrestrial intelligence is you don't even-- We don't know
what we're looking for. Right, right. Instead of looking
for something specific, you have to look
for the exceptions from what is normal. That is where I think A.I. is gonna just completely
change the game for SETI. [Mackintosh]
Maybe it's communication, maybe it's just a byproduct of some technologically
advanced civilization going about its business. All we care about is it doesn't look like
the rest of nature. If it's a needle
in a haystack, it doesn't look like hay. It's like this, each one
of these little blips is like a point in time
of radio power, and we take different
points in time, different windows into the data, and we analyze them together to see if there's
any kind of repetition, anything at all that might indicate
that something isn't random, like this,
right in the middle here, where the random dots
aren't random. In a computer, think of it like
a thousand of these sheets, and it's moving them
a million times a second. [Downey]<i> To find order
in the randomness,</i> <i> the A.I. picks a small area</i> <i> and studies
its radio frequency data</i> <i> to learn what normal
sounds like.</i> <i> Then, it uses this info to
filter out background signals</i> <i> from all the data
that's been collected.</i> <i> What's left is any signal,
pattern, or repetition</i> <i> that is unnatural.</i> They're coming up
to perfect alignment. Conjunction now! [Richards] We're recording. [Diamond]
Wanna check the audio? This is good. This is good,
nice clean data. Crispy clean. [Richards] Silence. Yeah, that's what we want.
I just, well-- I mean, we've been working up to
this for the last month. It looks like,
it looks like nothing to us, but that's the point. [Diamond] That's the point. That random sound
is music to my ears. This picture here
is just immediate, real-time results, something that your normal
Allen Telescope Array would discard as nothing. Our point is, not so fast. There could well be
more in there than we realize. We do see
some little blip right here... That's true,
in and around it. Yeah.
So here, let's press... So, now,
this all looks similar. It's the sort of normal signal, but that's interesting. It just seems, I don't know-- It's like it spreads here
for some reason. Well, I don't know
what that means. It also is
a higher average power. It is. So, yeah, it's...
this is weird, right? It is. [Diamond]
There are a couple of things that we are looking at
in the data that look interesting. Now, it's very subtle, and this is why we'll need
machine-learning to extract whether what we're seeing
is just something we're seeing, or it's real,
a real phenomenon. All right, so we are done
with the Trappist system. [Mackintosh] This is great. We've clearly grabbed good data. It's exactly what we need. [Downey]<i> It's gonna
take Graham a few days</i> <i> to analyze the data,</i> <i> nothing compared
to what it used to take</i> <i> to do manually.</i> [Pedro Domingos]
Some people think that the emergence
of artificial intelligence is the biggest event
on the planet since life, because it's going to be
a change that is as big as the emergence of life. It will lead
to different kinds of life that are very different from the entire set of,
you know, DNA, carbon-based life that we've had so far. [Downey]<i> While some
are ramping up the search</i> <i> in outer space,</i> <i> others are using A.I.</i> <i>to further explore inner life.</i> [Suzanne Gildert]
In 20 to 30 years' time, you might see a street
like this, with humans
walking up and down it, but there might also be
a new thing, which is human-like robots might be walking
up and down, too, with us. Humans and robots are really gonna be doing
the same kinds of things, and some of the things
they'll be doing will be maybe
superior to humans. [Downey]<i> Suzanne
is one of the founders</i> <i> of Sanctuary A.I.,</i> <i>a tech startup that's building
what they call "synths,"</i> <i> or synthetic humans.</i> <i> That's right.</i> <i> Artificial intelligence
wrapped in a body.</i> [Gildert] Our mission
is to create machines that are indistinguishable
from humans physically, cognitively,
and emotionally. [Downey]<i> Doing so</i> <i> involves solving problems
of engineering,</i> <i> computer science,
neuroscience,</i> <i> biology,
even art and design.</i> <i> But for her,</i> <i> the problem of artificially
replicating a person</i> <i> boils down
to a deeper question...</i> <i>What does it mean to be human?</i> [Gildert] Understanding
what it is to be human is a question that
we've been asking ourselves for many thousands of years, so I'd like to turn science
and technology to that question to try and figure out
who we are. [Downey]<i> We love stories
and films about clones</i> <i> and replicants
and humanoid robots.</i> <i> Why are we so obsessed</i> <i> with the idea
of recreating ourselves?</i> <i> Is it biological?</i> <i> Existential?</i> [Gildert] To try
and understand something fully, you have to reverse-engineer it, you have to
put it back together. [Downey]<i> The human
that Suzanne knows best</i> <i> is... Suzanne,</i> <i> so one of her projects</i> <i>is to build a synthetic replica
of herself.</i> [Gildert] There's this thing
called the Turing test, which is trying to have an A.I. that you can't tell
is not a human. So I wanna try and create
a physical Turing test, where you can't tell
whether or not the system you're actually
physically interacting with is a person,
or whether it's a robot. So here we have 132 cameras... which are all pointed at me, and they all take a photograph
simultaneously. This data is used to create a full three-dimensional
body scan of me that we can then use
to create a robot version of me. [Downey]<i> Suzanne believes</i> <i> that we experience life
through the senses,</i> <i> so she's putting as much work
into making the body lifelike</i> <i> as she is the mind.</i> [Gildert] We broke down
this very ambitious project into several
different categories. The first category is physical. Can you build a robotic system
that looks like a person? So the synth
has bones and muscles that are roughly analogous
to the human body, but not quite as complex. These hands are 3D-printed
as an entire piece on our printers. [Gildert] We can actually
print in carbon fiber and Kevlar, and we can create robot bones that are stronger
than aluminum machined parts, with these beautiful
organic biological shapes. So I'm adding in
a finger sensor. This, uh, current generation has a single sensor
on the fingertip. [Gildert] We build a machine
that perceives like a human by trying to copy the human
sensorium very accurately. The most complicated part
of the perception system is actually
the sense of touch. Are you monitoring the touch? Yes.
Touch received. [Holly Marie Peck]
We've actually embedded capacitive touch sensors
in the synth's hand, essentially pressure sensors allowing it to feel, uh,
its environment, and interact
and manipulate objects. Let's just test the pressure. -Okay.
-This should max it out. Yep, yep. Maxed out. Just stretch out her hand.
Okay, go. [Gildert] The reason
the hand and the arm is able to move so fluidly is because of
pneumatic actuators. They work using compressed air. You actuate
one of these devices, and it kind of contracts and pulls on a tendon, so the actuation mechanism is
very similar to a human muscle. It's just not yet
quite as efficient. [Shannon] I'm adding
the camera into the eyeball. Now I'm adding
the cosmetic front of the eye. [Gildert] The eyes are
super important to get right. Similar
to our own vision system, they can see
similar color spectrum, and they can also,
because there's two cameras, they can have
depth perception too. [Peck] Restarting
facial detection. [Gildert] That actually
looks pretty good. [Peck] Mm-hmm. Do you wanna
come forward a little bit? Yeah. -I'm gonna restart
her headboard.
-[Gildert] Okay. That information is fed through a series
of different A.I. algorithms. One algorithm
is a facial detection system. She's definitely seeing me. [Peck] Yes, she is. I can tell
she's looking at me, 'cause she looked
straight at me. Yeah, gaze tracking
is working. Okay, cool.
Now, do you wanna just smile? I'll see if she's actually
capturing your emotion? [Gildert] If you're smiling, the corners of your mouth
come up, your eyes open a little bit, and the A.I. system
can actually detect how those landmarks have moved
relative to one another. [Rana el Kaliouby]
I think the moment in time we're at right now is very exciting because there's this field
that's concerned about building human-like
generalized intelligence, and sometimes even kind of
surpassing human intelligence. [Daphne Koller]
There's people out there who believe that this is
on our immediate horizon. I don't. I think we're a long ways away from machines
that are truly conscious and think on their own. She's responding.
I can see her face changing. [synth]<i> You look happy.</i> -Good.
-Mm-hmm. I'm gonna look sad. <i> You look sad.</i> Okay, good. [Peck]
We have actually configured a lot of A.I. algorithms
on the back end that give the robot the capabilities
of recognizing people, detecting emotion, recognizing gestures and poses
that people are making. It then responds
in various ways with its environment. [Gildert]
Bring up her node graph so you can see
what's running in her brain. Yeah, let's see
all the online modules. The chatbot,
emotion detection, object detection... Wonderful. Gaze tracking... [Gildert] The body,
in a way, is the easy part. Creating the mind
is a lot harder. [Downey]<i> Creating the mind
is more than hard.</i> <i> It's basically impossible,</i> <i> at least for now,</i> <i> and maybe forever,</i> <i> because a mind
is not just knowledge,</i> <i> or skill, or even language,</i> <i> all of which
a machine can learn.</i> <i> The part that makes us
really human is consciousness;</i> <i> an awareness,
a sense of being,</i> <i> of who we are</i> <i> and how we fit in time
and space around us.</i> <i> A human mind has that...</i> <i> and memory.</i> "I remember the experience
of buying a new pencil case and the supplies to go in it, getting all those
new little things that smelled nice, and were all clean
and colorful." If you think about
how people work, it's very unusual for you
to meet a person that doesn't have a backstory. I can use all the data
that I have about myself to try and craft something
that has my memories, it has my same mannerisms, and it thinks and feels
the way I do. I would like them
to become their own beings, and to me, creating the copy is a way
of pushing the A.I. further towards making it
a realistic human by having it be a copy
of a specific human. <i> I remember going
to Bolton Town Center</i> <i> quite often.</i> <i> We just called it "Town."</i> [Gildert] The basic idea is you send in
a large amount of text data, and the system learns
correlations between words, and the idea is that the synth could use
one of these models to kind of blend together
an idea of a memory that may have happened
or may not have happened, so it's a little bit
of an artistic way of recreating memories. <i> I remember going
into WH Smith.</i> <i> It had a very distinct smell
that I can still recall.</i> [Gildert] So by giving them
these backstories now, we believe that we will be able
to learn in the future how they can create
their own memories from their experiences. [Bran Ferren] I love the idea that there are
passionate people who are dedicating
their time and energy to making these things happen. Why? Because if and when
it does happen, it's going to be because of
those passionate people. We talk about
the computer revolution like it's done. It's barely begun. We don't understand where the impact
of these technologies will be over the next five, ten, 20, 30, 50, 100 years. If you think it's exciting
and confusing now, fasten your seatbelts, because it hasn't begun. <i> What is your name?</i> My name is Holly. What is your name? Hmm. [Gildert] Of course
there's that unknown, like are we gonna
run into a problem with trying to recreate a mind that no one's thought of yet? <i> My name is Nadine.</i> Interesting. <i> I am glad to see you.</i> [Downey]<i> Even if we do
one day figure out</i> <i> how to create a virtual mind,</i> <i> it's not just the science.</i> <i> There's also the ethics.</i> <i> What kind of rights
will the robots have?</i> <i> Can we imbue it
with good values,</i> <i> make sure it's unbiased?</i> <i> What if breaks the law
or commits a crime?</i> <i> Are we responsible
for our synths?</i> [el Kaliouby] There are
big ethical challenges in the field of A.I. I believe that as a community
of A.I. innovators and thought leaders, we have to really be
at the forefront of enforcing and designing these best practices
and guidelines around how we build
and deploy ethical A.I. I like to say
that artificial intelligence should not be
about the artificial, it should be about the humans. <i> You look angry.</i> Landmarks are registering. [Ferren] I think
it's perfectly reasonable to have a set of rules
that govern ethical behavior when you are dealing
with technologies that can have direct impact
into people's lives and their families
and the future. [Gildert] The vision's
very ambitious for this. We'd like to think that that is
a 10- to 20-year mission. You might say
we're somewhere like five to 10% of the way along. Why is her arm doing that? It's almost like
it's not clearing the buffer. Yeah... interesting. Let's just restart you
so your arm goes-- Oh, wait, it's going
back down again. Okay, that's good. Okay. How do you feel today, Nadine? <i> It feels good to be a synth.</i> Nice. "It feels good to be a synth." [Gildert] The synths
are not mobile at the moment, they can't move around, they can't walk yet. That's something
we're going to be adding in within the next couple of years. The grand goal is to make these
into their own beings with their own volition
and their own rights. There are these moments
you can have where you really feel
something that's unusual. It's surprising. I was adjusting
the synth's hair, and then she suddenly,
like, smiled, and opened her mouth
a little bit, like, you know, like I'd just
tickled her or something. It was just, like, synchronous
with what I was doing. [Downey]<i> In some ways,</i> <i> Suzanne's vision
is already coming alive.</i> <i> She's making a connection,
albeit small, with a machine.</i> <i> Isn't that something?</i> [Domingos] I think A.I.
is part of evolution. The same evolution that led from bacteria
to animals, and has led people
to create technology, has led them to create A.I. In some ways, we're still
in the very early infancy of this new age. [Downey]<i> Will we ever
create intelligent life</i> <i> here on Earth...</i> <i> or maybe we'll find it
out there first?</i> So I'm on my way to the SETI Institute
headquarters in Mountain View, and, and I'm gonna show, uh,
what the A.I. system found in the data that we collected. I'm excited.
I'm a little nervous too. [Tarter] We need to be able
to follow up in real time... [Diamond] Mm-hmm. [Tarter]
...as closely as we can, so that a signal that's there is still gonna be there
when we go back to look for it, and we can then classify it. Jill Tarter is really a legend in this whole field
of SETI research. Also really a pioneer
as a woman astronomer. The character played
by Jodie Foster in<i> Contact,</i> is based, at least
in the first half of that movie, on Jill Tarter. [Tarter] People often talk about finding
a needle in a haystack as being a difficult task, but the SETI task is far harder. If I got out of bed
every morning thinking, "This is the day
we're gonna find the signal," I have pretty good odds I'm gonna go to bed
that night disappointed. I don't get up in the morning
thinking that. What I do
get up in the morning thinking is that today,
I'm going to figure out how to do this search better, do new things, do things you could not do
in the past. Early on, the technology
just wasn't there... Mm-hmm. ...and now we're doing something that we've never
been able to do. I'm excited. -Hello?
-Oh, hey! -Look who's here!
-How are ya? -Good to see you!
-Hi, Graham. -Nice to see you.
-Nice to see you. Likewise.
Good to see you too. -Hey, Bill.
-It's been a couple
of whole days? -I know! [laughs]
-Thanks for coming down. -My pleasure, I'm excited.
-Yeah. We're thinking maybe
you've got some news. Well, I wanna
step you through it. Here you can kinda see the system is
initially very active. It's all lit up, and very quickly, it starts to get a handle
on what the shape, you know, what a signal
from the Trappist-1 system
should look like. Over on the far right
is its areas of interest... What I'm showing here is a time-compressed video
of the A.I. system looking at the signal
we gathered. ...and if you focus in on that, the A.I. system did indeed
flag this one area, at that point, saying, -"Whoa, back up.
Something just happened."
-[Tarter] Ooh, wow. "That's not right," and if you zoom in
on the actual data, sure enough, there's that spike, so that is not
from the Trappist system. That was generated
by the Allen Telescope Array, but, you know, beyond that, this is an area
that the A.I. system is saying, "This isn't quite
what I would have expected." This is a little
more interesting 'cause there's
more structure to it, and we should take its hints, and have a deeper analysis done
of this part of the observation. We didn't write any code. We didn't tell it to...
to look for spikes of power or anything else. We just said, "You know what,
you figure out what's normal, and you let us know when something catches
your attention," which is exactly
what it's doing there. It's encouraging, because already
with just this one observation, we started to see
some real progress in what the A.I. system can do
compared to our own eyes, and that's just
one observation. What about the next,
and the next, and as it gets better with each new round of data
that we collect? This is after two hours. I wonder how good it's gonna get
after a hundred hours. Yeah. If we just routinely keep
feeding the data from the A.T.A. into this model, it's gonna get better
and better and better. We can just scale this out. -Right.
-Absolutely. We just got smarter.
Thank you, machine. Yes, exactly. [Tarter]
I'm absolutely so excited. I'm really blown away. I can see
the tools that are being built give us a new way
of looking for things that we hadn't thought of, and things that we don't have
to define up front, anomalies that
the machines will find simply because
they've looked at so much data. [Mackintosh] I do think
we're going to find ET. I do think we are gonna find
signs of civilization beyond Earth, and I do think that it's going
to be A.I. that finds it. [Downey]<i> Is there
intelligent life out there?</i> <i> Can we create
human-like machines?</i> [Domingos]
The odds are overwhelming that we will eventually be able
to build an artificial brain that is at the level
of the human brain. The big question
is how long will it take? [Downey]<i> Outer space,</i> <i> inner life...</i> <i> Age-old mysteries
now seem more solvable.</i> [Chris Botham]
If we wanna go to Mars, if we wanna populate
other planets, these types of things require
these advanced technologies. [Downey]<i> Moonshots, yeah,</i> <i> but also
other pressing problems,</i> <i> like...</i> -[gasps of shock]
-All five! Whoa! [Downey]<i>
...the mind and body.</i> [Tim Shaw]
Are you working today? [beeping] It's wonderful. [Downey]<i> Adaptation...</i> [Jim Ewing]
I'm thinking and doing and getting instant response. It makes it feel like
it's part of me. [Downey]<i> Work...</i> Action! [Downey]<i>
...and creativity...</i> These types of technologies
can help us do our tasks better. Three, two, one. [computer voice]<i>
Autonomous driving started.</i> [el Kaliouby] I believe
if we do this right, these A.I. systems can truly,
truly compliment what we do as humans. [Eric Warren]
We use the A.I. tools to predict what the future
not only is, but what it should be. <i> Yo, what's up?
This is will.i.am.</i> [laughing] [Mark Sagar] This is
the new version of you. The way it's looking so far
is mind-blowing. [firefighter]<i>
Stay close, I'll lead.</i> [Downey]<i> Survival...</i> [firefighter]<i>
Over here, I see him!
Three yards at 2:00!</i> [Martin Ford] I believe
that artificial intelligence is really going to be the most important tool
in our toolbox for solving the big problems
that we face. [firefighter]<i> I got him!</i> [crowd chanting] [Downey]<i> Conservation...</i> The fact that we can
look across the world and find where famine
might happen four months from now, it's mind-blowing. [Downey]<i> All out of the realm
of sci-fi and magic,</i> <i> and now just science.</i> <i> Still hard problems,
but now possible,</i> <i> with innovation,</i> <i> computing power,
will, and passion...</i> -[cheering] Yay!
-Yes! There it is. [Downey]<i> ...and yet,
despite all that,</i> <i> a vestige of unknown endures.</i> <i> Who are we?</i> <i> What are we becoming?</i> Every major
technological change leads to a new kind of society, with new moral principles, and the same thing will happen
with A.I. [Downey]<i> Technology's
changing us, for sure.</i> <i> The whole idea
of what it means to be human</i> <i> is getting rewired.</i> <i> A.I. might be humanity's
most valuable tool...</i> <i> ...but it's also just that.</i> <i> A tool.</i> [clattering] [Downey]<i> What we choose
to do with it...</i> <i> that's up to you and I.</i> [Seth Shostak]
If you could project yourself into the next millennium, a thousand years from now, would we look back
on this generation and say, "Well, they were the last
generation of Homo sapiens that actually ran the planet"? [James Parr]
There's a lot of paranoia. The media's done
a really good job of making people frightened, but A.I. is just
a portrait of reality, a very close portrait,
but it isn't reality. It's just a bucket
of probabilities. Where I think human beings
will always have the edge are understanding other humans. It's going to take a long time before we have an A.I. that can understand
all of the nuances and various layers
of the human experience at a societal level. [Shostak] James Parr, thanks
so very much for being with us. Great, thank you.
Looking forward to more quality documentary from YouTube.