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Using A.I. to build a better human | The Age of A.I.


[man]Steve Austin, astronaut,
a man barely alive.
We can rebuild him.
We have the technology.
We can make him
better than he was.
Better…stronger…faster.[Downey]
Man, when I was a kid, theSix Million Dollar Man
was all the rage. It’s a show about a guy
who gets rebuilt
with robotic machine parts. God, I loved it. And then 35 years later,
I got to play a similar role, a character who enhances himself
via technology and engineering. Now, the term “bionics”
goes back to the 1950s, but the idea of enhancement
actually dates back
much further, to Greek mythology, Aztec gods,
and even ancient Hinduism. So these next stories
are about augmenting
our human abilities, everything from a bionic limb
that behaves naturally
and understands intent, to data
that improves performance, and vision enhancement that saves people in actual
life-threatening situations. It seems with A.I… anything’s possible. So it raises the question, do we even want
to be superhuman, or is imperfection
what makes life interesting
in the first place? Whatevs.
I gotta get back to the gym. Normally I’d jog,
but I got a wonky knee. I should probably
switch it out. We can rebuild me. Better. Faster. Stronger. Seven miles an hour… full out! [Hugh Herr] Designers
within the field of bionics, they don’t view
the human body itself as designable media. We now have sophistication
in Artificial Intelligence, in motor technology, in material science, in how to talk
to the nervous system, setting the foundation… [all laughing] …for the end
of human disability. -[Cathy King] Do you wanna
do an omelette?
-[Jim Ewing] Sure. You probably don’t want
too much onion, because you’ll have
bad breath all day. Oh, thanks, yeah.
[chuckles] Anyway, what were we
talking about? [Ewing] 26 years, 29 years– Twenty six years,
almost 29 years together, yup. Our first date was, uh,
uh… 2000, wasn’t it? -[King] 1990.
-1990, oh my God. [King] I could tell
when I first met Jim that he’s highly intelligent, and he said, “Would you like
to go rock climbing sometime?” and I said, “Sure!” [Ewing] I started rock climbing
in my very early teens, and I consider climbing to be… it’s more than
a passion for me. It’s my lifestyle. In 2014, my family and I traveled
to the Cayman Islands. We went rock climbing. I set up the ropes
for the day, and we’d done a few climbs
with no problems. I started up the final section, and… shifted my feet
and slipped off… …50 feet to the ground. [hospital monitors beep] [King] When I saw him
at the hospital, I have never felt so helpless
in my entire life. It was horrible. [Ewing] The front and back
of my pelvis were completely shattered. My left wrist was shattered. My left ankle was broken
into two or three chunks, but the rest of it
was kind of pulverized. It slowly started
to dawn on me that this was something
that was going to be
life-changing. [King]
You’re at the hospital. [Jim murmurs] [King] We’re not looking
at the photos right now. I’m looking at ’em. [King chuckles] [kissing him]
You look all you want, baby. [Ewing] After a year,
everything else
seemed to heal well, but the ankle
continued to be a problem. The bone was mostly dead, and the main fracture
was still there. [King] He was in severe pain
all the time, and he just became so depressed. [Ewing] I couldn’t do
the things that I love. I could barely walk
down the street without pain, never mind go rock climbing. [King] Rock climbing
is his passion. I mean, I just see him withering
if he could not climb. [Downey]
Jim didn’t know what to do,
and then, in a truly incredible
stroke of luck,
his past came back
to help decide his future.
I began mountain climbing
at the tender age of seven. At the age of 17, I was in
a mountain-climbing accident, and I suffered
severe frostbite, and my legs were amputated. I really dedicated myself to redesigning
first my own legs, and then the legs of many,
many people around the world. [Downey]A few decades,
a couple of M.I.T. degrees,
and a single-minded focus
to innovate later,
Hugh launched
the prosthetics industry
into the bionic future.[Herr]I’m getting
a tremendous amount of energy,
power from the ankles,which enables me to walk uphillwith a perfectly erect posture.[Herr] My legs,
they have the brain. It’s a small computer
the size of your thumbnail, and that brain receives
sensory information from sensors
on the bionic limb, and then it runs algorithms and makes decisions
on how to actuate itself. And machine learning is used
as part of those algorithms. [Dr. Ayanna Howard]
So, machine learning is what’s called a subset field
of Artificial Intelligence. We learn from experience. Machine learning is basically
learning from the experience, where the experience
is the data. It takes input from the world, and the input could be
text in books, it can be camera images
from a car, it applies a very complex
mathematical function, and then has an output,
which is a decision. [Downey]The bionic legs
allow Hugh to walk, run,
even climb,but for him,there was still
something missing.
[Herr]
Because I can’t feel my legs, they… they remain
tool-like to me, and I believe if I could
feel my limbs, they would become part of me,
part of self, and fundamentally
change my relationship to the synthetic part
of my body. [Ewing] I would describe it
as just this amazing, lucky coincidence that Hugh and I were roommates
34 years ago. [Herr] We were teenagers
rock-climbing together and living like dirtbags,
living like bums, climbing every day. [Ewing] So I decided
I was going to look up Hugh and talk to him about
what my options might be. [Herr]
Jim was in excruciating pain, and he asked me if I
or my colleagues could help him. [Ewing]
What I really was hoping was that he could
put me in touch with a reconstructive surgeon
that could rebuild my ankle. Right, so this is your X-ray… [Herr] Jim was evaluated,
and was provided, uh, options of either maintaining
the biological limb and doing certain procedures to try to improve its function
and to reduce the pain, or… to amputate the limb. [Ewing] The thought
of amputation was just so big. What’s life
gonna be like for me if I choose
to amputate this foot? But it hurt so bad. I spoke with Cathy
and Maxine about it. They were behind me 100%. Whatever I needed to do. [Downey]How do you make
a decision like that?
A few months later,he agreed to have
his leg amputated
and be the first personto try his friend’s bold,
but experimental procedure.
[Ewing] It’s gonna be good. -Yeah.
-Gonna be good. Love you. You too. Bye, honey, love you. Love you, too. [Herr] The way in which limbs
are amputated has not fundamentally changed
since the U.S. Civil War… [soldiers shouting] …but here at M.I.T., we were developing a novel way
of amputating limbs. We actually create
little biological joints by linking muscles together
in pairs, so when a person thinks and moves the limb
that’s been amputated away, these muscles move
and send sensations that we can directly link
to a bionic limb in a bi-directional way. So not only can the person think and actuate
the synthetic limb, but they can actually feel
those synthetic movements within their own nervous system. [Downey]Until recently,creating a bionic limb
that a person can actually feel
has been more science fiction
than reality.
Now machine learningis revolutionizing the way
we think about medicine.
If anything can solve
the hard problems in medicine, it’s A.I. Let’s take an example,
heart disease. No single human being
can have in their head all the knowledge that it takes
to understand heart disease, but a computer can. Things like radiology,
pathology. You have an X-ray, and you wanna see, like,
is there cancer in this lung, and can you pinpoint
where the tumor is or not? A.I.s can, actually,
at this point, do this better
than highly trained humans. [surgeon] Can we get
the, uh, Esmarch, please? It’s so light! It’s weird. [surgeon]
It really looks good. I’m super happy with this, and you’ve got a nice degree
of padding here. [Ewing]
Right after the surgery, the incredible, deep,
in-the-bone pain that I had been experiencing
for the past year was gone. So to me, that was… that was a success right there. Never mind whether or not the experimental part
of the amputation was a success, I was glad to be free
of the painful ankle. He was happy.
It was done. He was ready to move on. [Herr] Hey, guys. How’s it looking?
How’s progress? [M.I.T. tech Eric]
Things look good. I’m gonna go ahead
and get you wired up. [Ewing] The first time
I went to Hugh’s lab, Hugh started talking about “What do you think about
a climbing robot ankle? Would you want us
to make one of those?” [Eric] I’m gonna go ahead
and get us started here… [Herr] It’s a specifically
designed limb that Jim can control
with his mind, and actually feel the movements
within his nervous system. [Ewing] I still need the evert. [Eric] Yup, that’s the one
we’re missing. All right, so we have you
wired to the leg now. You’re driving. [servos whirring] [Ewing] Cool. [Eric] Yeah.
Can you give me a fast up-down? And slow, controlled? This freakin’ blows me away
every time you do it. It’s so good. [chuckling] When we link Jim’s nerves
in that bi-directional way, we’re able to create
natural dynamics, so even though the limb
is made of synthetic materials, it moves as if it’s made
of flesh and bone. There. Now it’s neurally
and mechanically connected. How does it feel different? Now it feels like
it’s my natural foot, somewhat. Like, I don’t have
the skin sensation, but all the motions
make sense to my brain. [Herr] In the algorithm, we make a virtual model
of his missing biological limb, so when he fires his muscles
with his brain, we use an electrode
to measure that signal, and then that drives
the virtual muscle and sends sensations
to the brain about the position and dynamics. It kind of instantly
felt part of me, almost as good
as having a natural foot. [Downey]Cathedral Ledge,
New Hampshire.
Seven hundred feet
of awe-inspiring granite
and climbing routes
with names like “Thin Air,”
“Nutcracker,”
and “They Died Laughing”
make it one hell of a challengefor even
the most serious climbers
on a good day.For Jim, it’s a testto see if what works at M.I.T.
can work out on the mountain.
[Ewing] I’ve been
climbing here for 40 years, and I’ve probably spent
more time on Cathedral Ledge than any place else
on the planet. This climb is actually
at the upper limit of my ability at the moment. I’m not worried at all. What could possibly go wrong? [Downey]
The mountain has no mercy,
and no margin for error,and Jim’s about to find outif his bionic leg
can help him overcome
and scale heightsmost people wouldn’t dare try
in the first place.
[Ewing] That’s me. [Downey]Can machine learning
take us even further?
Replace not just what was lost,but enhance
what we already have?
[firefighter]
Okay, stay close.
I’ll lead.
This is insane![Downey]Augment performancebeyond the limits
of our natural human ability?
Make strong, smart,
fast people…
stronger, smarter, and faster?[crowd cheering] In many ways, sports
has been on the leading edge
of prediction systems, and now, every serious
sports contender uses sports analytics… but the big opportunity
going forward is embedding devices that can collect
real-time data to update strategies to take advantage
of that learning. There’s a revolution
going on in sports, and machine learning
is at the core of it. [Interviewer] The first
night race of the season, I’m sure you’re ready
to finally get behind the wheel. For sure.
Just fired up to get going. Triple-A car’s been
pretty good this weekend, and we’re pumped
to get this thing started.Drivers, start your engines![crowd screaming] [Eric Warren] The race track’s
a fairly hostile environment. The way I describe racing,
and the way I live it, it’s like war. [announcer]
Folks, get on your feet.
Let’s send these guys off!
Boogity boogity boogity!
Let’s go racing, boys!
[Warren] You’re trying
to take your race car, your team, your driver, and beat the other drivers
at all costs. [race team radio chatter] [announcer]Austin Dillon,stuck in the middle
of a three-wide.
[Andy Petree]
This kind of race produces a lot of strategy, and that’s where we have to use
all of our tools to help us make
those strategic decisions. [Downey]When it comes
to superhuman ability,
you may think of people
like LeBron James,
Michael Phelps,
or Serena Williams…
but it’s not just the body
that can be enhanced.Sometimes
it’s something less tangible,
like human intuition.[announcer]
What a battle going on here.
You gotta be real careful here
in the early stages
making contact with somebody.[Warren]Information
is the next battleground.
[race team radio chatter]Every decision you make
can have a big impact.
[Downey]Back in the day,intuition used to play
a big part in sports.
Athletes and coaches
relied on their gut
to make decisions.Now some competitors
are leaning more and more
on machine learning,looking to gain
whatever extra edge they can.
[Warren] We use the A.I. tools to predict what the future
not only is, but what it should be. [announcer]
We’ll go behind the 20.
You just start finish line…
[Rana el Kaliouby] The strength
of these A.I. systems come in having access
to a ton of data and being able to find patterns
in that data, generating insights
and inferences that maybe people
may not be aware of, and then augmenting
people’s abilities to make decisions
based on that data. [Downey]Machine learningis transforming many industries
and applications,
especially in areas
where there’s a lot of data,
and predicting outcomes
can have a big payoff.
Finance,sports,or medicine come to mind.Using an emerging technology
like machine learning
in a classic old-school sport
like stock car racing
doesn’t necessarily sit well
with everybody…
which may or may not explain
why this guy’s doing it…
in a nerve center
250 miles away.
[man]Clear, clear,
hit the marks,
drive off, man.
[Warren] My role there really
is looking at the data. How do you use data
you can acquire at the racetrack to get these machines to be right on the limit
of performance? [announcer]His front rotors
are really glowing.
[Warren] We get the braking,
steering, throttle, all the acceleration
off of every car in the field, real time… [Downey]All this datais being fed into an
A.I. program called “Pit Rho.”
[race team radio chatter] [Downey]Sensors in every carmeasure speed, throttle,
braking, and steering.
Advanced GPS tracks the car’s
position on the track.
[man]Watch your middle,
watch your middle.
[Downey]All this data is
made available to every team.
[Warren] This is where
the power of A.I. comes in. So, our tool basically is analyzing
the optimum strategy call of every car in the field,
real time. Not just our car,
but every car. [Petree]
It’s almost threatening. I was a crew chief
for Dale Earnhardt Sr.Comin’ to ya.10-4.[Petree]
I would sit up on the box and intuitively kinda
figure all these things. You kinda just make
that gut call, “Bring him in now.” [Downey]Until now,
many key decisions,
like when to pit
for tires or fuel,
were made by the drivers
and the crew chief
using experience
and intuition.
[Petree] Now, we’ve got
artificial intelligence that’s making
all these calculations in real time. Some of the crew chiefs that have done what I’ve done
over the years, sometimes it’s hard for us
to embrace it. [tires squealing] [announcer]They’re trying
to get through traffic
as fast as they can
so they don’t get a lap down,but that’s gonna
use up those tires.
[Warren] You can go
at this track on fuel probably 120 laps,
but your tires
will be shot way before then. [Downey]In a NASCAR race,pit stops are the key
to a winning strategy.
[Petree]
You’re trying to decide when in that cycle
is the best to make that stop, because you lose a lot of time
when you come off the track
and you have to stop, but then you gain a lot of speed
when you put new tires on. [Warren]
This is the first time we’re facing, like,
a strategy call here. [Downey]
The Pit Rho A.I. interface
displays one of four
suggestions…
stay out on the track,pit for fuel only,pit for two tires,or pit for four tires.[Warren]
So right now, it’s telling him
to take four tires. [Downey]
Eric relays the message
to the Childress team
at the track.
The final decision
on when to pit
will be up to the crew chief.[crew chief]
When the pits are open,
it’ll be four tires here,
four tires.
[Downey]
For the first pit stop,
the crew chief
follows the A.I.’s advice.
Five, four, three, two, one.Put on the brakes,
wheels lift.
[Downey]The crew
has to change all four tires
in as little time as possible.This usually takes
between 12 and 14 seconds.
[engine revving] [radio chatter]
All the way, all the way!
That’s a good stop.Really good stop.[Warren] Sometimes,
what happens is,
over the course of a race, those little bit
better decisions puts you in a spot,
and it puts you
in an opportunity at the end of the race
to be able to win the race. [Warren] Every lap,
it’s analyzing the field, updating its models. As the race goes on,
the prediction gets
more and more accurate. [Downey]They’re using
an A.I. technique
called
“reinforcement learning,”
which is, basically,when the computer is given
the rules of the game,
plays it over and overtill it learns every possible
move and outcome,
and then
through trial and error,
and patience that no human
could possibly have…
[announcer]I wonder
if we have a resignation here.
[Downey]
…becomes amazing.
[announcer]
Congratulations to AlphaGo
and to the entire team.[Downey]It’s what
Google’s DeepMind did
to become a world champ at Go.[commentator]Here we go![Downey]
It’s what Open A.I. did
to conquer the video game
Dota 2… [commentator]
He’s dominating.
Are you scared of a bot here?[Downey]…and build
a robotic hand
with near-human dexterity.It’s what Eric’s hoping to do
to get the checkered flag.
[announcer]You can see
he’s on his way to the top 10.
[team]Yeah, we got through,
Andrew, focus here.
[announcer]
And you go up a few cars,
you’ll find the 3
of Austin Dillon
up in sixth place,making up time
on the race leader.
So the recommendation
is pit on lap 327. What my fear is is that
they’ll pit with the leaders instead of actually
running to the strategy. [Downey]Going to the pits
when the leaders do
is the safe play
in the end stages of a race…
[Warren]
Sparks, you got me?
[Downey]…but the A.I. tool
is recommending a riskier plan
that might gain them
valuable seconds.
[Downey]By pitting later,Austin Dillon
will have faster tires
for the closing laps
of the race,
but he risks falling
further behind the leaders
once they come out of the pits
with their fresh tires.
[Petree] A lot of times
when our Pit Rho technology
tells us, “This is the time to pit,”
or, “This is how to do it,”
it doesn’t feel right. Are you sure
you wanna do that now? [Petree] Sometimes you might
be sitting out there running laps on older tires, where everybody else is pitted, and it’s like, it doesn’t
feel right for the driver. [Petree]
He’s gonna want to pit, and you gotta convince him,
“Stay, make good laps.
Trust us, it’s gonna work.” Some leaders
are gonna pit right here,
and we need to run. [commentator]
Looks like the 22
is gonna choose
to come down pit road.
[announcer]
So, all the front four
came in on the same lap
with 82 laps to go.[Downey]On lap 318,the top four cars
enter the pits.
[team member 1 speaking] [Warren speaking] [team member 1 speaking] [Warren] Here’s where
the faith in the tool
ends up happening. When they all pit, it takes a lot of faith
to just stay out there and run to your lap. [team member 2 speaking] [team member 3 speaking] [Downey]Austin Dillon
breaks from the A.I. strategy
and follows the leaders
into the pits.
[team members speaking] That’s not good news. [man]Three, two, one.Put on the brakes,
wheels lift.
[Downey]To maintain
their position,
the team needs
a flawless pit stop.
[tires screeching] [team member 2]
Son of a bitch!
[team member 1]
We lost three seconds.
We’re not gonna be
nowhere near ’em.
Got killed on pit road.It’s pretty disastrous.[Warren] Prior to the pit stop,
we were about 4.6 seconds back, but when we came out,
we were nine seconds back, so we lost about
four and a half seconds on that– in that exchange.
That’s hard to get back. [man]
Let’s go to work on him.
This won’t be easy.
Just fight hard here.[Downey]They’ve dropped
from 6th place to 12th…
and Austin Dillon
has very little time left
to fight his way back
to the leaders.
[Eric]
Come on, Austin, get him. [Downey]…but the new tires
give him an edge…
[announcer]
The white flag waves,
one lap to go.[team member 1 speaking] Get it, get it, get it! [announcer]Short track win
number one for Martin Truex!
[race team]
Sixth place is awesome.
[Downey]…and he ends up
finishing sixth.
[team member 2]
Hell of a freakin’ drive,
Austin Dillon.
[team member 3]
Hey, nice work tonight, man,
way to fight hard there.
[team member 4]
Hell of a job, boys.
Hey, good job, guys. [Warren] Progressing
through the race definitely the cars
have gotten faster, so, you know,
we’ll see good things that we’ll take back
next time we go to Richmond.Hell of a job
this weekend, boys.
[Warren] The hardest thing as we’ve incorporated
more A.I.-based tools is trust. Sometimes we’re the ones
that get in the way, right? There’s still times
when it’s counterintuitive, and everybody’s like, “It’s the wrong call,
it’s the wrong call,” and over time,
we have these battles because most of the time,
the A.I. tools is right. Nine times out of ten,
or even more,
it’s the right call. [Downey] Andy and Eric’s team
were using A.I., and on track
for a strong finish, but they fell behind when the team
ignored the machine and went with their intuition. That’ll do it. [Lav Varshney]
Convincing humans that machines
know what they’re doing is the central difficulty in deploying A.I.
out in society, whether it’s the pit boss
in car racing, or even astronauts
flying to the moon. [Downey]Do we trust the A.I.
to make decisions for us?
We already do with GPS maps.Perhaps here,
the team just didn’t have
enough experience with it
to override
their own intuition,
but what about
other situations?
At what point
do we start trusting A.I.
in more serious matters?[dawn birdsong chorus]Matters of life and death?[firefighter] It was
a smoldering fire that filled
the whole house with smoke, and you couldn’t see your hand
in front of your face. You literally had to feel
your way up the stairs. Totally blind search. Yeah. Sometimes that’s
the best thing we can do. Yeah. [Kirk McKinzie]
Every two hours and 45 minutes, a U.S. citizen dies by fire
in their own home. We’ve lost
more than 3,000 a year consistently for 30 years. [firefighter]
The Worcester fire. Three guys go in.
They all get disoriented
and get lost. Two more go in to find them. They get lost.
Two more go in. I mean, before you know it,
they finally had to, “Okay! We’re not sending
any more guys in there, ’cause they’re all
friggin’ lost.” [news broadcast]On his radio,
a commanding officer
heard two firefighters
desperately
crying out for help.
[Worcester fire chief]
“Mayday, mayday.
We’re running out of air. Come to the door
so we can see where you are,” and then, we did that,
and we went beyond the door, and we yelled,
and we had lights, and they were… they were inside somewhere
that they couldn’t see us. [firefighter] All those guys
who died in that… [McKinzie] When we go
into a structure
that’s dark and smoky, the biggest challenge
is the visibility. The ability to navigate
is a… is a challenge, and often firefighters
have become disoriented, and then they run out of air. With the challenge of smoke
and having no vision, I knew that there was
a possibility of changing that. That’s when I finally met
the C-THRU team. [Sam Cossman] Okay,
is the system turning on? Let’s see. I’m gonna unplug that one. I guess the best way
to describe myself is I’m infinitely curious. I like to solve problems, look at things
through a new lens. All right… [Cossman] I was in disbelief
that firefighting
in a smoked-out building involves training
their personnel to revert back
to feeling around the room. How’s the battery level doing? That was really
the inspiration behind creating C-THRU. [Downey]
Sam Cossman saw the light
when he jumped into a volcano.
Line!Fire![Downey]Part globetrotting
adrenaline junkie,
part computer engineer,the self-proclaimed
Indiana Jones of tech
envisioned a tool
that would help firefighters
and save lives,a kind of X-ray vision.[Cossman] The problem
that C-THRU is trying to solve is really flipping the lights on for people operating
in zero-visibility conditions. [Omer Haciomeroglu]
The concept of C-THRU was the helmet that had
enhanced audio, enhanced vision… [man]I see you!
I’m on my way.
[Haciomeroglu] …outlines their
surrounding geometry so that they can
navigate faster. So is it this plane right here
that… that changed recently? [Haciomeroglu] Yes, basically
like a simpler design
that can achieve more. [Cossman] We have a mask, and we have
a thermal-imaging device that sits on the side
of that mask, and we process that image
through a small computer. [Downey]Sam and Omer
created a mask
with special glasses
clipped inside
which allows firefighters
to see edges as green lines
in an augmented reality
overlay.
How’s the alignment look
on that one? It’s not bad. We need to calibrate it
a little bit more. Omer and I have been working
on refining the prototypes for the last couple of years, just trying to MacGyver
some of these problems with off-the-shelf parts,
you know, duct tape
and bubble gum. Move your hand around
a little bit. -Okay.
-Other hand, like that one. Yeah, this is
definitely better. [Downey]It may look like
old Tron-era night vision,
but there’s actuallysome pretty slick
artificial intelligence
at work here.
Thermal imaging camerasstream video
from the firefighter’s helmet
into an A.I. processor.Using infrared lightand a powerful
edge-detection algorithm,
the mask detects
subtle changes in brightness
to predict shapes
invisible to the human eye,
like a wall hidden by smoke,or a kid hiding under a bed.[Cossman]
There you go, take this mask. [Downey]Sam and Omerare now at a familiar point
in the innovator’s journey…
get out of the garage
and into the real world
to see if their invention
can take the heat.
[siren wailing, horn blares]Fire Dispatch,
Medic 71 arrived on scene,
have report of smoke showing.Fire Dispatch, copy.[McKinzie] One of the most
important things
any fire department does is regular hands-on training. There he is. How you doing, Captain? Good to see you, brother. [McKinzie] We’re gonna give
the C-THRU solution
a hard run… [Cossman] We’ve got a prototype
fresh off the print. …and we’re gonna put it
in fire and smoke, and we’re gonna see how it acts
while crews are working with it. -Shall we get him
inside the smoke?
-Let’s do it! [radio chatter]…cleared for dispatch.I am a Cyborg.Okay, we’re ready.[McKinzie] Crews will be
doing live fire drills in our training tower. It is active, real fire with temperatures at the ceiling
at 1,200 degrees. [yelling through masks] [man]Anybody over here?[McKinzie] Firefighters
are in a hurry, looking for victims. Visibility will be
limited at best. Often, firefighters
will be able to see nothing. [Downey]
C-THRU’s maiden voyage
is cut short by a malfunction.[McKinzie]
In an active firefight, it’s critical that things work. It’s life and death. Uh, at first, it was good.
I got through,
went down to the floor, and I looked,
and I could see
everything clear. Yeah. Really well,
everything was lined out.
Once I started working… -Yeah?
-I lost it. -Yeah, the signal went out.
-Signal went out. I’m not sure what that was,
but we’re gonna figure it out. There was a lot of interference,
or maybe a cable issue. We did encounter
some challenges,
the biggest of them was some wi-fi interference
that we’ve encountered where the system
would just shut down. Yeah, it’s actually like
over here with the connections, -like, this pin, you know?
-That’s what’s… Yeah, the pin connections here,
and here, actually. We should just shield
the cables as best we can and give it another go.Battalion Ten, Fire Dispatch,uh, we got a caller
on the second floor
trapped in the bathroom.So, if you wanna go ahead
and try it on for a fit, we’ll see how it goes.-Fire Dispatch,
Battalion Ten…

-[radio chatter continues] [on-scene dispatch]
Engine 72 arrived on scene,
reporting of heavy smoke showing from the first
and second floor. [radio chatter continues]We’ve got smoke showingfrom the first
and second floors.
[dispatch] Engine 7-1, you’re gonna be taking
fire attack. [dispatch]
71, who is on scene,
smoke showing from the second
and first floor.
Command copies, one victim
coming out of the second window,
you need EMS. Medic 72, you’re gonna
have to take patient care. As soon as
I got in, I could see
the outline of the room. As I stepped in,
I just kinda
took a look around, I could see where the victim was
and an outline of the door. -I mean, hands free, you know?
-Yeah. [chatter on radio] It is kind of like, I mean,
likeIron Man,you know, being able
to see through the smoke, and having everything
so clear-cut, um… It’s… it’s pretty cool. [Cossman]
What we’re working on
is really a game-changing tool that completely has
the potential to transform how the work here is done. [firefighter] This is, uh,
some of the videos of the C-THRU mask, okay? [firefighter 2]
That is way crisper
than I’ve seen. That is insane. [McKinzie] Over the 30 years
that I’ve been at this,
I’ve seen a lot of changes. We have mobile data computers, we have computer-aided
dispatch systems… -No, that’s gonna…
-Wow. That’s gonna be a game-changer. [McKinzie] …and now we have
the possibility
with machine learning and A.I. to progress to a place just a couple of years ago
we couldn’t have imagined. -Is that completely
pitch dark in there?
-That recording– -[alert sounds]
-Oh, gotta go! That is actually what you see
in the mask. [firefighter] We’re gonna go
on another call, gentlemen. [Downey]
It’s impossible to know
if this technology
could have saved
those six firefighters
in Worcester,
but it’s hard to believe
it wouldn’t have helped.
Back on Cathedral Ledge,Jim is about to see
if his new bionic leg
will help him scale
a 700-foot sheer rock face.
[Ewing] I’m just gonna kinda
bring everything. [M.I.T. tech Emily]
All right. [Ewing] My own personal
M.I.T. pit crew. -[Emily] Got the socket.
-[assistant] The socket… [Ewing]
What we’re gonna do today
is climb on Cathedral Ledge
with a new robot foot
designed specifically
for climbing.
We can set up camp here. [Emily] All right, we should be ready
to start calibrating. [M.I.T. tech Joe] Counterflex. Rest. -[Emily] You’re driving now.
-[Ewing] That’s me. [Emily] How’s it feel? [Ewing] Pretty accurate. It’s going everywhere
that I’m telling it to go. [Ewing] This climb is gonna be
very challenging, because there’s a variety
of holds at different angles, different heights. I’d say
there’s a high probability of there being some
falling action here and there. I was really afraid, very… worried whether or not I could make it
all the way up a climb. We good there, Joe? Harness is on. I got plenty of gear. All right, we’re climbing. I think
I’m at a crux section here. [wincing] Well, first fall. I’m not sticking very well. It’s hard. Hard business. [grunting with effort] Slack! [cracking] Oh! We have failure. The whole mechanism broke. [Ewing] I remember
looking down at it, seeing the foot
at a strange angle, and, “Holy crap,
that is gonna hurt. “That–”
Like, I was bracing for pain. I mean, how much more
of a part of you does it need to be? [Emily] Oh, my God. [man] I would call that
a catastrophic failure. [Emily] Pretty catastrophic. But it was… it was
a strange sensation, though, because all of a sudden,
my ankle was broken, and you feel like
you’re losing your limb all over again. [Eric] How’re you feeling?
You feel like you wanna
go down again? We… we did bring a spare. Uh, sure. Okay, we’ll swap it over
to this one. [Emily] In engineering, we’re kinda used to things
not exactly going right the first time, so that’s why we have
contingency plans. [Eric] So, this is
the last climbing robot leg in the world, Jim. [laughter] We’re good to go again. I’m a little nervous
about trusting this foot now. Watch me here. If the left–
if the robot breaks… I’m going for a ride. Actually, it did that move. [Eric] Well done. [Ewing]
We’re rock climbing, dude. [Ewing] With the robotic leg,
I found that I could move
more naturally. Life on the edge, man. I was pain free,
and it was, I don’t know, it was just kind of fun
and satisfying. [Herr]
We have always hypothesized that if we can link
the nerves of a human being to a bionic limb, the limb would become
part of the person, part of identity. Toppin’ out. Remarkably,
it’s happened. Cyborg power! [laughing] [team clapping] [Downey]It’s a tall peak,but pales in comparisonto the one Hugh
is ultimately trying to climb.
[Herr] We also have the goal of extending human capability
beyond physiological function, jump higher, or run faster… So bionics
not only seeks to achieve
normative function in humans, but also
to extend human expression beyond what people
were born with. [Downey]Human enhancement
and augmentation
have been around
through human history
and mythology,from Prometheus stealing fireto the Civil War.Using tools
to improve our abilities
is a fundamental
human development,
whether it’s stone spears
to protect our families
or airplanes
to transport us farther.
…and that’s really
what we’re seeing,
the transformation of society, and not just racing,
not just sports, is really using
these A.I. tools,
and they’ll become commonplace, won’t even
be thought about otherwise. [Downey]
A.I. and machine learning…
they’re just tools,ones that makes us stronger,
smarter, faster.
[Herr] A.I. will play
an increasingly dominant role across all the many dimensions
of what it means to be human. [Downey]
There’s a good chance
A.I. will continue
to enhance us in ways
both known and unknown,
eventually becoming
as invisible
as the air we breathe.
[Herr] That narrative
will play out across all types
of human conditions. That will
enhance human capability, fundamentally change
who we are as a human race. [Downey]
The question then becomes,
if it does,what do we do
with our newfound superpowers?
[dog panting] [Ewing]
This one’s meant to be kind of
an all-around athletic foot. I can run with it,
hiking, biking, whatever I want. I even use it for surfing, ’cause it has a good bit
of flex to surf with. I actually liked the fit so much that it’s the only one
I use now. As good as this fit is,
it still… like I said, high activity days,
I get some pressure sores. Every night, you have
to look over the skin, make sure you’ve got
nothing nasty going on, nothing growing
where it shouldn’t be. This guy is a gel liner. It doesn’t breathe, but this is
what keeps the leg on. A lot of, um, amputees talk about forgetting
that they don’t have a leg in the middle of the night, and they get up
in the middle of the night to go to the bathroom, and then instantly
fall on their faces. That’s only happened to me once, but I managed to catch myself
before I hit the ground. [chuckling]

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100 thoughts on “Using A.I. to build a better human | The Age of A.I.

  1. 0:48
    Ancient Hinduism. So glad to to see Hinduism being mentioned. Hinduism texts is ocean of scientific tech from making Flying airplanes to nuclear weapons, specific targeted missiles (Weapon science is more prominent in the Text Mahabharata). Theories that have got attention in recent decades such as multiverse, time travel as many others have already been mentioned in various texts from Bhagavad Gita to Bhagavath puran.

  2. Great call Youtube Original! You made this series free and we don't mind seeing ads for content like this, we need more content like this. I'm tired watching junk Youtubers that you gave money from ads for years. Keep the ads money to yourself and make more quality content!

  3. I'm pro-AI completely, but in that race ignoring the AI had nothing to do with losing. The pit-crew screwed up. The crew probably would have taken 18sec if the AI strategy had been followed.

  4. Amazing how technology is advancing, hope there can be inventions this year so cool that can gather as many people as the 100000bible thing last year

  5. When machines predict more and more of our lives, the power resides more in the people (and companies) who control that data, and less in the masses. Think about that.

  6. But at what point does sport loose the human aspect? If all decisions are by machines then it's not humans competing anymore.

  7. हमारे पास बहुत सिक्का है,अगर, आप लोग, खरीदना चाहते हैं तो,कोल करें धन्यवाद,,,वाटसाप, नंबर,9453938010, फोन नं 9453153210,9455200485,9793760912,7317524641,7317651842, है

  8. I've found this series by accident and I'm so happy about it. This is life changing!
    Btw. is it weird that I want a prosthetic leg now?

  9. So glad youtube's giving this out for free – an entire series and with RDJ? A dream. I really think that educational content should be free and leisure should be charged and with lots of ads to pay for high quality science content for learning. Way to go!

  10. So glad youtube's giving this out for free – an entire series and with RDJ? A dream. I really think that educational content should be free and leisure should be charged and with lots of ads to pay for high quality science content for learning. Way to go!

  11. the only thing they need now with the AI firefighting mask is artificial color to separate items (floor from person from wall), which'll make the job so much easier.

  12. Starting stage of cyborg….that dude gave up his legs for climbing and it's experimental he could never even walk at all….her wife said he's intelligent and he's doing this

  13. We will see the last of traditional humans when CRISPR is perfected and AI begins using CRISPR to create the perfect creature.

  14. The photos shown when talking about climbing in the Cayman Islands are not of the Cayman Islands – or more specifically, Cayman Brac – the only Cayman location that has sea cliffs that are tall enough to climb.

  15. Hey AI when you surpass humans just remember I've always supported you. Please let me merge with you and machines to become immortal and super human PLEASE.

  16. What companies are up and coming for new sports analytical companies or the companies building the software for sporting data

  17. You spoke and we listened! Subtitles are now available in French, German, Hindi, Korean, Portuguese (BR) and Spanish for the first four episodes. Get ready for the final four episodes of Age of AI launching on January 15th!

  18. Firefighters vision, could use the expanding air as a way to cool of the electronics on the way to breathe. Seems like that stuff would overheat quite easily.

  19. There's potential in the fire departments helmet. All green for now but they can update it to color code the wall depending on depth or distance or maybe in the future it can be colored.
    Or Tony can just hand them the iron man helmet and get done with it. 😄

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