[ Applause ]
>>Chris Anderson: Thank you, John. So I have
five kids. None of them are anything like
Taylor Wilson.
[ Laughter ]
>>Chris Anderson: My wife and I were trained
as scientists, and we dreamed that someday
we'd have -- we'd have little Taylors and
--
[ Laughter ]
>>Chris Anderson: -- we've been doing everything
in our power to get there and it's just not
working.
[ Laughter ]
>>Chris Anderson: I want to talk a little
bit about what happens when you try to inspire
your children in science and technology and
it kind of goes horribly wrong but in an interesting
way.
Let me bring up the first slide, please.
So, you know, my adventure into what ultimately
led to a -- creating a Tijuana drone factory,
about which more you'll hear soon, started
with this.
This is my daughter Erin. She was 9 and I
was really trying to get them interested in
science and technology and Lego sent us their
brand-new Lego Mindstorm Robotics kit, and
they -- somebody else also sent us this like
radio-controlled airplane, and we thought
this would be a fantastic GeekDad weekend.
I'd started a website called GeekDad entirely
about finding cool science and technology
projects to do with your kids, and we thought
this would be a perfect example.
So here's Erin opening the box, and the first
instructions are to build a three-wheeled
robot called a tribot and we spent all morning
doing this, and at the end of the morning,
when it's programmed and assembled, it moves
forward until it hits the wall and then backs
away.
And the kids are like, "You've got to be kidding,
right? We have seen Transformers. Where are
the lasers? This is" -- they could not believe
how disappointing robotics were. And it is
super hard to compete with Hollywood when
it comes to robotics. You know, CG has ruined
robotics for most kids, and certainly mine.
Then we took an airplane to the -- to the
field, to the park, and I promptly crashed
into a -- into a tree, and -- proving, once
again to my children, that every GeekDad project
dad initiates ends up in disaster and disappointment
and I have to bribe them with ice cream.
And now -- and not only did the whole site,
GeekDad, not work, but now everything -- every
time I do a project with them, they suspect
that I'm actually doing it for the Web site,
and so they won't even let me take pictures
anymore.
So this was a -- so this was kind of bad,
and then I thought, "Well, how could that
have gone better? What could have been a more
interesting robot than a tribot? What could
have flown a plane better than me?"
And I thought, "Well, you know, these -- this
Lego, this toy, comes with these sensors,
this gyroscope sensor and accelerometer sensor
and a compass sensor and it this arm core
processor and it's kind of like the guts of
a cell phone, a smartphone, in plastic.
And I thought, "Well, gosh, I think you could
almost like fly a plane with that. That could
be like an autopilot."
So I Google "autopilot" and, you know, quickly
find out that it's incredibly complicated
stuff involving common filters and sensor
fusion and I don't know anything about that.
But I do know that I seem to have, in these
bits of plastic, the necessary elements.
And so I get the kids together and we built,
all around the dining room table, the world's
first Lego autopilot, which is, there and
we put it in a plane, which is there, and
it kind of almost worked.
And this plane is now the world's -- this
is the world's first Lego drone. It's an autonomous
Lego-powered vehicle which is now hanging
in the Lego museum in Billund, Denmark, I'm
proud to say. Turns out, by the way, that
autopilots in drones are regulated as munitions
by cruise missile controllers and that technically
we weaponized Lego.
I was really looking forward to that Congressional
hearing where they like bring my 9-year-old
up and explain how exactly they -- how they
managed to put this on the Internet and distribute
it so that bad guys might get access to Lego
munitions.
But so that -- that was kind of fascinating.
I got chills. I mean, when you -- when you
sit around with your children on a dining
table, Google "autopilot," and end up with
something that's classified as a cruise missile
controller and regulated by ITAR in an evening,
something in the world has changed.
And my kids were interested for about 10 minutes
and then lost interest, but I -- but, you
know, those moments don't happen very often
in life. It happened to me once with the Internet,
maybe once with the personal computer, and
it happened again with this notion of flying
robots.
It's like, what -- something -- something's
possible here that should not be possible,
when an idiot, you know, with 10 minutes of
Googling and his kids can do something that
used to require tens of millions of dollars
and defense contractors.
So what I always do in times of -- when I
don't -- have no idea of what's going on is
I do what I call being ignorant in public.
So I create a Web site and I start asking
dumb questions.
And we called it DIY Drones. And one of the
wonderful things that happens when you are
ignorant in public is that -- well, two wonderful
things happen. The first is that people answer
your questions, and the second is that it
liberates them to ask their own questions.
And this moment, this was in -- this was 2007.
That actually turned out to be a key moment.
And when you look at a lot of enabling technologies,
a lot of the kind of things like wearables
and smartphones, et cetera, they're all coming
out around then, which kind of started with
sensors, these kind of tiny mem sensors. They
were starting to get cheap. The Wii controller
was a perfect example of one of those liberating
moments.
And it turns out that much like in the Homebrew
Computing Club in 1977 which was enabled by
one chip -- I think it was the Intel 88 -- and
suddenly regular people got to do extraordinary
things, this proliferation of these cheap
sensors and basically the guts of smartphones
that made things that used to cost tens of
thousands of dollars cost -- you know, just
turn into a chip and cost a few dollars. You
can buy them at Radio Shack.
This spurred the imagination, and suddenly
regular people started doing extraordinary
things, and our Web site and our community
was one of them.
So people from around the world start combining
their various ideas into ultimately what emerged
as sort of amateur drones, and they started
trading designs and it was all open source
and it was very exciting, very make-a-movementish.
And then the next generation of people came
and said, "Look, that's fantastic you're sharing
your designs and that you can like have your
PCB fabbed and then, you know, surface-mount
these things with like a microscope, but I'd
rather not. Can I just buy it? Could you start
a company, please, and sell it to me?"
And I thought, "Okay. Well, sure, we'll start
a company."
And so one of these guys on the Internet who
I met, a guy named Jordi Munoz, we started
the company together and it kind of went like
this:
You know, it started with me and my children
packaging up bits of Lego around the dining
room table and Jordi then soldering things.
Then he got a little office space and he sent
me a picture of that and he said, "Look, we
have shelves, and I got this like pick-and-place
machine, which is like this little robot that
makes chips -- makes -- puts printed circuit
boards in the back, and over on the right,
that's Rebecca. We have a bookkeeper."
And I was like, "We have a bookkeeper?"
And then he sent me a next picture and then
he's like, "We've got new pick-and-place machines
and they're better. And then we've got to
open up a -- a -- an electronics assembly
area in Tijuana, and now we've got a new electronics"
-- and it was like holy cow.
I don't know what just happened, but basically,
a 21-year-old who I met on the Internet from
Tijuana just built an aerospace company in
three years.
So I quit my job, and -- to join him and we,
like, raised venture capital, and we realized
that this was a moment to do the home brew
computing thing for drones.
Now, again, we are like -- this is, like,
three years after I am playing with LEGO with
my kids around the dining room table and we
now have, like, tens of thousands of drones
out there, a multi-million dollar company,
we're competing with Boeing, and I'm still
trying to figure out what these things are
for.
I know that they're possible, but you know
in the beginnings of the personal computing
industry, no one knew what they were for.
If you asked Jobs and Wozniak on day one what's
a computer for, they said so you can program
it. And only later, when they put them in
the hands of regular people did we come up
with those answers like email and video games
and spreadsheets and word processors and the
rest.
And we realized there is this moment where,
by making these things super cheap and easy,
we could put them in the hands of regular
people, take them out of the military context,
into the civilian context and figure out what
aerial robotics was for.
So these are sort of -- when I say "drones,"
this is what I'm talking about. These things
are called multicopters of various sorts,
and they are a vehicle that was not possible
until about five or six years ago.
They are inherently unstable. They can't be
flown by a human being. They can only be flown
by a computer which operates much faster than
we can. And they don't have, like, control
surfaces. They just change the speed of the
propellers really rapidly to maintain stability.
That's called a quadcopter with four. This
is an octocopter with eight in the coaxial
configuration. That's a hexacopter with six
in another configuration.
All of them are basically applied physics.
It's like if any of you remember like matrix
math, that's what happens. You have this -- The
computer sort of says, well, I want to tilt.
We have X, Y, Z. You have three axes. You
have the yaw, the pitch and the roll, and
it sort of says this is what I want to do,
and then sends that command out to this array
and sort of converts that into motor commands.
The kind of thing that's super easy for a
computer, super hard for a human.
And what makes them drones is that they're
fully autonomous. They use GPS and smart software
to figure out where they're going and what
to do.
So you don't fly them. You just tell them
briefly, "I'd like to go there," or "Follow
this," or "Look at that," or "Survey this
area."
And what it ends up doing is abstracting the
piloting experience from one of controlling
an aircraft to completing a mission. And these
things cost somewhere between 700 and a thousand
dollars.
You may have seen some of these flying around
a little bit, so I think what I'll do is I'll
queue up the first video we have, which is
just our flight ops team who will come out
in a minute, has been sort of flying around
this area, flying around this resort. And
if we have the video, it can bring it up.
You can see a little bit of the -- No? Here
we are.
This is just outside.
[ Video playing ]
[ Video ends ]
So that's a rough view of what a basic copter
can see from the air. Put a high-quality GoPro
on the camera -- on the thing and just fly
it around. That's the basics, and that was
actually done in manual mode.
Then you start thinking about the next level
of sophistication. So this thing here on the
left is an autopilot. It's just a box. It's
the guts of a smartphone in a different package
with smart software. And because it's -- because
it abstracts the whole exercise of flying,
it can do any one of these vehicles.
So you just sort of tell it I want this to
be an autonomous car. Bingo, it drives a car.
I'd like it to fly an airplane. It flies an
airplane. Multi-copters, traditional helicopters.
You figure out what the right vehicle is for
the job. Multi-copters are good at vertical
takeoff and landing. Traditional helicopters
can be gas powered and can be in the air for
an hour. Airplanes can be in the air for three
or more hours. And cars, I'm not sure what
they're for but they're really fun, the little
ones. We swarm them to test algorithms.
But this is the sort of thing that the aerospace
industry wasn't going to invent, but a community
could invent.
The aerospace industry delivers a product
to a spec, and often a military one. Communities
just play with technology because they can.
I talked a little bit about the possibilities
of abstraction. And again, with autonomy,
where you don't have to think about flying,
you can reinvent the user experience.
So, you know, what we're doing is moving away
from the notion of sticks and sort of inheriting
cockpit like controls and moving to tablets.
And what you have here with the tablet is
in the same way that the tablets allowed us
to reinvent the desktop experience by moving
to a touch, tactile, very sort of natural
experience, so can we do with drones.
And so what we're moving to is a notion of
where you fly the camera, not the vehicle.
This tablet right here, it has -- it just
has these little sort of suction cup sticks,
and you control the vehicle through this.
You're not flying the vehicle. What you're
doing is with the left stick, you're going
to be positioning the camera in space, and
with the right stick you're deciding what
it looks like. You're basically creating a
vector with two points.
So it's a little bit like in a first person
shooter, like in a video game, where the left
stick controls your character's position in
the field and the right stick controls what
it looks like. That can be an abstracted flight
experience.
And if you want to go somewhere, you don't
even have to fly it there. You can just sort
of touch the button and say, "Go there. Look
at that." You draw a line and it follows the
line. You draw a box and it will survey that
area in the box. And it, again, turns it into
a much more kind of mission oriented, what
am I trying to get done. What's the task here?
Forget how the aircraft flies. The community
deals with that. But this autonomy allows
us to move to the next level of performance,
meaning you don't need to be a pilot, you
don't need to be skilled.
It has these way point things. I'm going to
show you a little bit of one particular function
called Follow Me which is kind of fun.
Imagine you're a windsurfer or something and
you would like to have that perfect GoPro
shot of you out there.
So what you do is you just carry your phone
or some other device and it just follows you,
keeping the camera focused on you the entire
time.
These are the Droids you're looking for. This
is exactly what you want. You love GoPros.
You just wish they were a little higher and
they would follow you from the perfect orientation.
This has only been possible recently, because
we have these combinatorial innovations of
smartphones and tablet interfaces and improved
wireless communications and all this stuff
costs, like, less than a thousand dollars.
So I wanted to end by just talking about the
big surprise to me. As we got these things
out there, of course we were hobbyists. We
were just doing it for fun and then there
were other people using it. And then just
as Jobs and Wozniak put the personal computer
out there and then the users told them what
computers were for, the users figured it out,
the same thing happened with us.
Once we took drones away from the military
and started putting them in the hands of regular
people, regular people found applications
that never occurred to us. And the most profound
turned out to be agriculture.
I had barely stepped foot on a farm, but then
farmers started using drones and sort of saying,
"You know what? The top-down view of the crops
is something we can't easily get." Satellites
are too far away and above the clouds. Manned
aircraft costs a thousand dollars an hour.
Sometimes I just want to know what's going
on in my farm.
I'm like, "Why don't you walk the farm?" It
turns out with the consolidation of agriculture,
farms are getting bigger and bigger and there's
fewer and fewer people on them. And overall,
farming has become increasingly robotic from
milking cows to driving tractors.
So what happens is farmers started using these,
and what they discovered was that this a big
data opportunity.
If any of you have been to a vineyard recently
you often see this rose at the end of a line
of grapes, and this rose is like a 2,000-year-old
one pixel analog sensor. And the theory -- we're
not even sure whether this is true, but kind
of the theory of the rose is that roses are
affected by the same fungal infections as
grapes and they show the effect sooner. So
it's like the canary in the coal mine. And
you can see if the rose starts to wilt, you
know you've got a fungal infection and you
can treat it.
And that was like the state of the art of
monitoring for vineyards forever. And you
started thinking it's 2013. We can do a better
job than that.
So what you realize is you want to get more
sensors out there, but putting sensors in
the field is hard, especially if the ground
is being turned over regularly. Powering them,
the wireless data networks. Sometimes what
you want is you want to take the sensor to
the crops or above the crops rather than embedding
them in them.
So what we end up finding is that we have
essentially a big data opportunity. Agriculture
is a big data opportunity without the big
data. It's the biggest industry in the world,
and it's one where it's essentially what we
call an open-loop system.
You put these inputs in, these chemicals,
fertilizers and pesticides and herbicides
and water, and months later we get an output.
But what's going on throughout the process?
We don't really know.
In small farms, maybe you can walk them. In
big farms, you're guessing. And the reason
we settle for mono culture and the kind of
the big ag kind of approach is because there's
a predictability of buying one kind of seed
and applying it generically everywhere. But
there's a real cost to mono culture, which
is genetic diversity, and you have to be very
conservative in your treatment.
So, for example, you spray fungicide because
it's June. You spray according to the calendar.
Why don't you wait until you have a fungal
infection? Because you don't know, and by
the time you know, it's too late and you've
lost the season.
So we're spraying tons of chemicals on our
crops because we don't know whether we have
an infection or not.
So what we have here is an opportunity to
close the loop, to basically use data to improve
the way we manage farms, to use less inputs,
less chemicals, lower the chemical load, and
on the ground, lower the chemical load in
our food.
And we simply do this by using drones to fly
the crops regularly, like a piece of farm
equipment, and bring to the farmer's perspective,
to their view, information that will allow
them to farm differently.
So as we started doing this and realizing
the opportunity, we realized this was a perfect
market. Agriculture is the biggest industry
in the world, and all the big concerns about
drones -- privacy, flying over your backyard,
danger, et cetera -- are largely resolved
when it's private land, when drones are not
seen as sort of scary military things flying
over cities but, rather, farm equipment buzzing
over fields to gather data to use less chemicals.
Then suddenly the popular sentiment about
them, the concern, the sort of stigma that
comes with drones changes.
Remember, the Internet used to be a military
technology. GPS was invented to drive -- to
steer cruise missiles. A lot of military technology
has become demilitarized once we come up with
new uses for them, and we think we have the
same opportunity to do that with drones by
using them in agriculture.
So I really wanted to bring up my team at
this point who are going to sort of put some
of these in the air so you can just see some
blades whirl. But the experience that we're
moving towards is one where five years from
now, when you think drones, you don't think
predators. You don't think global hawks. Instead,
you think of an experience where you're driving
around fields and there's clouds of these
things just monitoring the crops. Maybe even
some day spraying the crops.
That a drone experience will be one where
a farmer will simply pick up their smartphone,
draw a box around the field. The drones would
then take off, automatically map the area,
gather the data, analyze the data, and highlight
areas of interest using blob detection and
such, the actionable stuff.
One thing's -- The big secret here is that
cameras, even regular cameras have the ability
to show farmers things they can't see with
their own eyes. And this is something called
a normalized differential vegetation index,
and it's simply near infrared.
Healthy chlorophyll reflects infrared, but
unhealthy chlorophyll reflects them both.
And what you can do is by taking a regular
camera -- and we actually take 3D cameras,
which have two lenses, and we just strip out
this infrared filter that's in one and put
in a blue filter, and one takes visual, the
other takes near infrared. You combine the
two and you get a shot like this. The red
is damaged chlorophyll, damaged plants. The
green is healthy.
This is something a farmer can't see with
their own eyes. This is actionable information,
and it uses cheap, off-the-shelf cameras just
in the right position.
So what we do is we stitch them together very
quickly in realtime, and we end up with -- even
simple pictures like this turn out to be actionable
to farmers. This is a vineyard where we fly
up near Sebastopol. And just being able to
see the different color of grapes doesn't
mean some are bad or some are good, it just
means they are different. And that information,
in this case, the farmer is actually to able
create these geofences, these GPS borders,
and tell the pickers you got two buckets.
Once you cross -- they had these, like, smartphones.
When the smartphone shows green, put the grapes
in this bucket. When it shows red, put the
grapes in that bucket. That simple information
allows them to differentiate their wines and
have a more sort of -- more distinguished
taste. They are able to sort of -- they are
able to precision manage their farm by simply
using data that's available from the air.
Another example just from a farm, what you
can see here is that green strip in the middle,
that is not a good thing or bad thing. It's
the remnants of an ancient stream, the alluvial
soil. It is different grapes. They create
the geofence.
Oh, and by the way, in the top left-hand corner,
they see they have a little irrigation leak.
A simple picture, a regular camera, just your
smartphone put in the right position gave
the farmer information that allowed them to
make better choices.
So with that, I think what I would like to
do is have our team up here, Joe and Craig,
just do the very simplest thing which is to
show you what these things look like in the
air. They are going to fly radio-control mode,
which is to say totally manual. You want to
see them fly automs, then we're going to have
to go outside. Maybe they will do that later
in the day.
These things are -- you have got a hexacopter
here with six props, an octocopter there with
eight. They have cameras on board. And this
is the sort of thing that may some day be
farm equipment. This is the sort of thing
you might see flying over crops, normal basis,
monitoring them for farmers autonomously.
One of those is now filming the other one.
(Drones whirring).
>>Chris Anderson: So yesterday my children's
hobby, tomorrow the future of agriculture.
Thank you very much.
[ Applause ]
