The incredible inventions of intuitive AI

How many of your are creatives?

Designers, engineers,
entrepreneurs, artists,

or maybe you just have
a really big imagination.

Show of hands?

That's most of you.

I have some news for us creatives.

Over the course of the next 20 years,

more will change around the way
we do our work

than has happened in the last 2,000.

In fact, I think we're at the dawn
of a new age in human history.

Now, there have been four major historical
eras defined by the way we work.

The hunter-gatherer age lasted
several million years.

And then the Agricultural Age
lasted several thousand years.

The Industrial Age lasted
a couple of centuries,

and now the Information Age
has lasted just a few decades.

And now today,

we're on the cusp of our next
great era as a species.

Welcome to the Augemented Age.

In this new era,

your natural human capabilities are going
to be augmented by computational systems

that help you think,

robotic systems that help you make,

and a digital nervous system

that connects you to the world
fay beyond your natural senses.

Let's stated with Cognitive Augmentation.

How many of you are augmented cyborgs?

(Laughter)

I would actually argue that we're
already augmented.

Imagine you're at a party,

and somebody asks you a question
that you don't know the answer to.

If you have one of these,

in a few seconds,

you can know the answer.

But this is just a primitive beginning.

Even Siri is just a passive tool.

In fact, for the past
three-and-a-half million years,

the tools that we've had
have been completely passive.

They do exactly what we tell them
and nothing more.

Our very first tool only cut
where we struck it.

The chisel only carves where
the artist points it.

And even our most advanced tools
do nothing without out explicit direction.

In fact, to date --

this is something that frustrates me --

we've always been limited

by this need to manually
push our wills into our tools,

like manual --

like literally using our hands,

even with computers.

But I'm more like Scotty in "Star Trek."

(Laughter)

I want to have a conversation
with a computer.

I want to say, "Computer,
let's design a car,"

and the computer shows me a car.

And I say, "No, more fast-looking,
and less German,"

and bang, the computer shows me an option.

(Laughter)

That conversation might be
a little ways off,

it's actually probably less
than any of us think,

but right now,

we're working on it.

Tools are making this leap from being
passive to being generative.

Generative design tools
use a computer and algorithms

to synthesize geometry --

to come up with new designs
all by themselves.

All it needs are your goals
and your constraints.

I'll give you an example.

In the case of this Aerial
Drone [Chassy?],

all you would need to do is tell it
something like,

it has four propellers,

you want it to be
as lightweight as possible,

and you need it to be
aerodynamically efficient.

And then what the computer does

is it explores the entire solution space:

every single possibility that solves
and meets your criteria --

millions of them.

It takes big computers to do this,

but it comes back to us with designs

that we by ourselves
never could've imagined.

And the computer's coming up
with this stuff all by itself,

no one ever drew anything,

and it started completely from scratch.

And by the way,

it's no accident

that the drone body looks just like
the pelvis of a flying squirrel.

(Laughter)

It's because the algorithms are designed
to word the same way that evolution does.

What's exciting is we're starting to see
this technology out in the real world.

We've been working with [Airbus]
for a couple of years

on this concept plane for the future.

It's aways out still,

but just recently we used
a generative design AI

to come up with this.

This is a 3D printed cabin partition
that's been designed by a computer.

It's stronger than the original
yet half the weight,

and it will be flying
in the Airbus [A-320] later this year.

So computers can now generate.

They can come up with their own solutions
to our well-defined problems.

But they're not inutitive.

They still have to start from scratch
every single time,

and that's because they never learn,

unlike Maggie.

(Laughter)

Maggie's actually smarter than our
most advanced design tools.

What do I mean by that?

If her owner picks up that leash,

Maggie knows with a fair
degree of certainty

that it's time to for a walk.

And how did she learn?

Well, every time the owner
picked up the leash,

they went for a walk.

And Maggie did three things:

she had to pay attention,

she had to remember what happened

and she had to retain and create
a pattern in her mind.

Interestingly,

that's exactly computer scientists
have been trying to get AIs to do

for the last 60 or so years.

Back in 1952,

they build this computer
that could play Tic-Tac-Toe.

Big deal.

Then 45 years later,

1997,

Deep Blue beats [Casperoff] at Chess.

2011, Watson beats these two
humans at Jeopardy,

which is much harder for a computer
to play than Chess is.

In fact, rather than working
from predefined recipes,

Watson had to use reasoning
to overcome his human opponents.

And then a couple of weeks ago,

[Deep Minds' Alpha-Go] beats
the world's best human at Go,

which is the most difficult
game that we have.

In fact in Go,

there are more possible moves
than there are atoms in the universe.

So in order to win,

what Alpha-Go had to do
was develop intuition,

and in fact,

at some points,

Alpha-Go's programmers didn't understand
why Alpha-Go was doing what it was doing.

And things are moving really fast.

I mean, consider --

in the space of a human lifetime,

computers have gone from a child's game

to what's recognized as the pinnacle
of strategic thought.

What's basically happening

is computers are going
from being like Spock

to being a lot more like Kirk.

(Laughter)

Right?

From pure logic to intuition.

Would you cross this bridge?

Most of you are saying,

"Oh, hell no."

(Laughter)

And you arrived at that decision
in a split second.

You just sort of knew
that that bridge was unsafe.

And that's exactly the kind of intuition

that our deep learning systems
are starting to develop right now.

Very soon you'll literally be able
to show something that you've made,

you've designed,

to computer,

and it will look at it and say,

"Mm, sorry homey, that will never work,

you'll have to try again."

Or you could ask it if people
are going to like your next song,

or your next flavor of ice cream.

Or, much more importantly,

you could work with a computer to solve
a problem that we've never faced before.

For instance climate change.

We're not doing a very
good job on our own,

we could certainly use
all the help we can get.

That's what I'm talking about:

technology amplifying
our cognitive abilities

so we can imagine and design things

that were simply out of our reach
as plain old unaugmented humans.

So, what about making
all of this crazy new stuff

that we're going to invent and design?

I think the era of human augmentation
is as much about the physical world

as it is about the virtual,
intellectual realm.

So how will technology augment us?

In the physcial world,

robotic systems.

OK, there's certainly a fear that robots
are going to take jobs from humans,

and that is true in certain sectors.

But I'm much more interested in this idea

that humans and robots working together
are going to augment each other,

and start to inhabit a new space.

This is our applied
research lab in San Francisco,

where one of our areas of focus
is advanced robotics,

specifically human-robot collaboration.

And this is Bishop,

one of our robots.

As an experiment,

we set it up to help a person working
in construction doing repetitive tasks.

Tasks like cutting out holes for outlets
or light switches in dry wall.

(Laughter)

So Bishop's human partner can tell
what to do in plain English

and simple gestures,

kind of like talking to a dog.

And then Bishop executes
on those instructions

with perfect precision.

We're using the human for what
the human is good at,

right?

Awareness, perception and desicion making.

And we're using the robot
for what it's good at:

precision and repetitiveness.

Here's another cool project
that Bishop worked on.

The goal of this project,

which we called, "The Hive,"

was the prototype the experience
of humans, computers and robots

all working together to solve
a highly complex design problem.

The humans acted as labor.

They cruised around the construction site,

they manipulated the bamboo --

which by the way,

because it's a non-icomorphic material,

is super hard for robots to deal with.

But then the robots
did this fiber winding,

which was almost impossible
for a human to do.

And then we had an AI
that was controlling everything.

It was telling the humans what to do,

it was tell the robots what to do,

and keeping track of thousands
of individual components.

What's interesting is building
this pavillion was simply not possible

without human, robot and AI
augmenting each other.

OK, I'll share one more project.

This one's a little bit crazy.

We're working with Amsterdam-based artist,
[Youris Marvin and his team at MX3D]

to generatively design
and robotically print

the world's first autonomously
manufactured bridge.

So, Youris and an AI are designing
this thing right now, as we speak,

in Amsterdam.

And when we're done,

we're going to hit Go,

and robots will start 3D printing
in stainless steel,

and then they're going to keep printing
without human intervention

until the bridge is finished.

So as computers are going
to augment our ability

to imagine and design new stuff,

robotic systems are going to help us

build and make things that we've
never been able to make before.

But what about our ability
to sense and control these things?

What about a nervous system
for the things that we make?

Our nervous system --

the human nervous system --

tells everything that's
going on around us.

But the nervous system of the things
we make is rudimentary at best.

For instance,

a car doesn't tell the city's
Public Works department

that it just hit a pothole at the corner
of Broadway and Morrison;

A building doesn't tell its designers

whether or not the people
inside like being there,

and the toy manufacturer doesn't know
if a toy is actually being played with --

how and where and whether
or not it's any fun.

Look, I'm sure that the designers
imagined this lifestyle for Barbie

when they designed her --

right?

(Laughter)

But what if it turns out that Barbie's
actually really lonely?

(Laughter)

If the designers had known what was
really happening in the real world

with their designs --

the road, the building, the Barbie --

they could've used that knowledge

to create an experience
that was better for the user.

What's missing is a nervous system

connecting us to all of the things
that we design, make and use.

What if all of you had that kind
of information flowing to you

from the things you create
in the real world?

With all of the stuff we make,

we spend a tremendous amount
of money and energy --

in fact last year about
two trillion dollars --

convincing people to buy
the things that we've made.

But if you had this connection
to the things that you design and create,

after they're out in the real world,

after they've been sold,
or launched or whatever,

we could actually change that,

and go from making people want our stuff,

to just making stuff that people want
in the first place.

The good news is we're working
on digital nervous systems

that connect us to the things we design.

We're working on one project
with a couple of guys down in Los Angeles

called the Bandito Brothers,

and their team,

and one of the things these guys do
is build insane cars

that do absolutely insane things.

These guys are crazy.

(Laughter)

In the best way.

And what we're doing with them

is taking a traditions racecar [Chassy],

and giving it a nervous system.

So we instrumented it
with dozens of censors,

and then we put a world-class driver
behind the wheel,

took it out to the desert

and drove the hell out of it for a week.

And the car's nervous system captured
everything that was happening to car.

We captured four billion data points.

All of the forces
that it was subjected to.

And then we did something crazy.

We took all of that data,

and plugged it into a generative
design AI that we call, "Dreamcatcher."

So what do get when you give
a design tool a nervous system,

and you ask it to build you
the ultimate car [chassy]?

You get this.

This is something that human
could never have designed.

Except a human did design this,

but it was a human that was augmented
by a generative design AI,

a digital nervous system,

and robots that can actually
fabricate something like this.