well I think the public is fascinated
with self-driving cars and it's because
there's such a visceral human response
to the automobile you know many of us
had our first date in a car for many of
us getting that you know driver's
license was our first real taste of
freedom so the idea of turning over that
authority that driving authority to a
machine it's a big deal it's a big step
you know this isn't an academic exercise
when you put a car on the road very
literally lives are at stake we care
about sending our kids to drivers train
why do we do we do it so they help you
so then questions how do you send our
cars
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each week
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so would you hear the word artificial
intelligence what's the first thing that
comes to your mind not real
both aliens thousand percent alien like
Mars Attacks alien I mean there's it's a
little scary but it's exciting I guess I
think of how computers can make
decisions can be programmed to make
decisions like Amos
yeah machinery is programmed but just a
kind of the same but I don't think if
software's artificial intelligence I
just don't I would say that it is when
computers or robot becomes self-aware
and is able to think like a person but
lesser piping's me a little I'm not
frightened like oh you know just freaks
me out a little that way like how do you
honey teach a machine to learn
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so the question is can we develop an AI
powered engine to perceive the world to
make decisions and have it reach a level
of performance and reliability that
we're confident in and confident not to
put it on the road the easiest way to
think about it is to think of AI is a
box with math and code well AI is math
enjoyed the box the data goes into the
box and decisions come out those are
decisions about the data with classical
programming you're starting with input
and rules that's what you're specifying
on you're getting outputs and reasoning
you're starting with examples of inputs
and outputs and what you're getting is
rules there's a bad food because for
many problems these rules are very much
non-obvious they're not something that
you can get a human programmer to
specify so an example that will be I
want to apply names to photographs
photographs going right JPEG files going
and names come out like that's
christenings that's Chris's mom stays
right or maybe transactions financial
transactions and the decisions are that
looks like fraud that's not from right
or or emails looks like spam or doesn't
look like me so those decisions that are
important and that affect the way we
live our lives because if my inbox is
full of spam I waste time and I'm
annoying so it's like a thermostat in
the back right
it is invisibly adjusting parameters of
your life to make it easier for you to
do something more interesting and not
struggle with something basically
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so what is going to happen is AI will
become increasingly integral to our
lives so society it can become part of
the basic infrastructure society will
become our interface to the world to a
world that will be increasingly
information rich and complex ai is going
to change what it means to be human
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the application of AI to self-driving
cars is the living edge of the eye it's
really a great test of let's say whether
a eye is really ready for the real world
if we're really going to test and figure
out whether we can trust a eye it's
going to be in allowing cars to get us
where we want to go without killing
anyone if you had to guess how does the
self-driving car work how does a
self-driving car work I would assume
that there's some kind of computers
involved definitely some cameras it's
more computerized in the dashboard and
that
there's probably human I don't even know
how many cameras would be equipped
another sensors I've seen so many
commercials about that they could park
themselves and they can do this and my
mom has one that'll break you know to
car in front of her breaks her car
starts to break you're like whoa that's
you know a surprise is shock it's an
outside force entering into the
environment that you're in she didn't
expect that you weren't prepared for to
be perfectly honest I don't have a lot
of ideas as to how all of that gets put
into a functional system driving has a
lot to do with personality so it's kind
of like telling the artificial
intelligence to get a personality so
whoever is running the software behind
that I guess is teaching it how to drive
so when we talk about autonomous
vehicles and how they work they all kind
of work the same way regardless of
whether or not we're talking about a
drone or an automated car automated
train any automated transportation
device has to develop something we call
the world model so that if you
understand what the world around you is
then you then make decisions based on
your world model
because it can convert raw sensory data
into an interpretation that allows you
to act it can be there as an important
part of that interface between the cards
where it recognizes the stop signs or
pedestrians or the lane industry so the
thinking part the decision-making part
of any driver's car really comes down to
what kind of algorithms were embedded in
it so an algorithm is a series of
instructions for going from linguistics
about good so when I talk about mapping
inputs absolutes talking about the
relationship of one thing to another
relationship of a face to a name so
self-driving cars are really just a form
of robots on wheels they use sensors to
look at the world and detect what's
relevant it uses algorithms to decide
where it's going to drive and how to
obey the rules in the road it's building
a lot of artificial intelligence
perception mapping localization
technology that's all drawn from
robotics communities and so that's where
the big leap and Technology are going to
have to come in the next few years are
the development of the perception system
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so so probably the question we get the
most is why ducks we're really trying to
rebrand robotics in a way our perception
is that robotics has a bit of a scary
image and a bit of a masculine image and
so that was really the reason to add
this sort of element of cuteness and
really the duck was the sort of perfect
example for that duckie town is a
scaled-down autonomous driving platform
that we use for research and education
the only sensor on the duckie bot is a
monocular camera one cheap camera that
sits on the front for the robot to be
able to just follow the roads it needs
to be able to take the camera and figure
out where the road markings are and then
have a feedback control loop that's
keeping it in the lane in a sense it's
doing exactly the same thing that what a
current state-of-the-art vehicle does to
follow the highway self-driving cars is
very much like a problem of scale so in
ducking down we all worked on different
parts of that problem and then we should
all share our code with each other so
you knew that while you were working on
a particular issue there was going to be
updates coming from other people and by
sharing that was the only way that
anyone would have it talked about that
work we can break up the big problem
into a sequence of much smaller problems
that can all be worked on in parallel
and then merge these things all back
together again so this is part of us all
working out what the right development
cycle and how to most efficiently
allocate our resources to do this kind
of research and to make the most
progress
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the big challenge of doing autonomous
vehicle research is actually logistic
getting a car putting sensors on it and
then driving it around and developing
algorithms without running anybody over
or putting people in harm's way is a
real problem and so while this makes it
seem a little bit unrealistic as
compared to a real-life system it's
powerful in the sense that you can
demonstrate algorithms by being very
confident that you've captured all of
the possible input that you're likely to
see in ducky town and then see what how
your algorithms actually work what was
here talking about that on a normal
Street like just having the trust that
it would be able to see a green light
you know and be able to know lights are
green and or there's a yield sign or if
a cat ran into a street and it just
being able to anticipate all this really
for me cetera I do enjoy driving sir the
self-driving vehicle would be great to
break the monotony of driving like on a
long distance on a long trip that idea
of how much people want to invest in
self-driving cars or have it I think
there are a lot of social goods can be
had out of it do you think that
self-driving cars will be better at
driving than humans I think I believe
you because the human reaction time is
infinitely slower than a computer's
reaction time if you have a self-driving
car they're not going to be texting and
driving they're not going to be flipping
through the radio and out of a whole
community I really do believe there's
going to be less car racks that we use
self-driving cars
now we think reactive and in that moment
no do you remember to steer into your
fishtail remember to see her out of it
you know well the computer wouldn't know
what to do and a computer would think
for you and in that instance that could
help save your life
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well the self-driving car industry is
really at an interesting moment we're
kind of sewing the parachute on the way
down if you will there's immense promise
in this technology because you could
argue that it's a moral imperative that
we should move quickly we have within
our grasp a technology that once we get
it right we can put on the road and
reduce or eliminate the tens of
thousands of lives that are lost in the
US alone from motor vehicle accidents so
we have to move fast but the technology
to be honest is still in and R&D things
it's not yet ready for product ization
one of the really interesting things
about the AI is that it gets smarter the
more experiences of the way right so you
want as much as possible to get it out
and exposed to as many things as
possible
then the rational thing to the rational
strategy is to get it to compete against
as many people as possible and so the
question is how do we want to do that
is there a commons right that serves the
general welfare right that we should all
contribute to and that by contributing
to we can ensure everyone's life is
better and open-source is a way to
enable at the sharing this collaboration
and it's looking more and more like this
is really a problem that is going to be
solved with data that this is a data
driven problem the better the data is
that's going into the algorithm the
better the decisions are that they're
going to produce and the better
decisions you can produce more lives you
can say in a life-and-death situation
like a self-driving car so self-driving
cars collect an immense amount of data
there's data coming from vision sensors
at a high frame rate from these lidar
sensors from radar sensors from the
internal motion of the car it tells us
not only about what the world looks like
to a very very high degree of precision
it tells us about what other road users
are doing how they're behaving tells us
about the conditions of roads it can
tell us about the conditions of trees on
the side of the road
most of the big players in this industry
have held everything pretty close to
their chest well the data today is
really a prized commodity you know
everybody is putting a fleet of cars on
the road with a primary goal of
collecting as much data as they can and
so I think that it's really important
that these resources become available to
the community at large you're one of the
halves with the big fleet of cars on the
road and a huge treasure trove of data
you're less incentivized to share but if
we think about pushing the industry
forward and getting to a point where we
have safe technology on the road that's
saving lives every day a way to speed up
that process is to share the data it's
an integral choice we have to make
between the status quo where we have
millions of people are dying on the
roads and a better future you know
that's why it's so important that people
talk about this to make sure that they
understand what the ramifications are of
being so secretive where there's still
so much to be learned that that can be
detrimental and may not be survivable by
any individual company
autonomous vehicles is an incredibly
ambitious project who no single company
can just force to develop everything on
its own if we want to get there we need
to be standing on the shoulders of child
the question is you know will we as an
automotive and a technology community
get to the point where we can look at
each other in the eye and say it's
everybody's benefit to share this data
and as a society because we share these
rims right and because we're all exposed
to the risk of other cars that we need
to be making decisions about how to
share the best image of the cars and
open-sourcing
can do that get it out of the lab
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on my own even
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