Speaker 1: Now now you know, we made it a point not
to not to rehearse anything, and so as I just
want to just as a as a as a just reminder,
you're you're my last thing. Okay, okay, could you not
ruin the whole thing?
Speaker 2: All right?
Speaker 1: All right? So now speaking of that, speaking of that,
I think everybody would like to before we get into
all of the good stuff, okay, and they want to
go directly to the juicy stuff.
Speaker 2: Okay, okay.
Speaker 1: And the juicy stuff is this. Look, you know, you
were quote as a saying that that artificial intelligence is
more dangerous than nuclear weapons, and I said potentially, and
and well it goes on, it goes on, and you say,
you say that it's like summoning the demon could be.
How do you consolidate, rationalize the the the conflict between
artificial intelligence of course deep learning that that obviously is
going to be very important to self driving cars. How
do you think through that?
Speaker 2: Well, I don't think.
Speaker 3: We're to worry about autonomous cars because that's sort of
like a narrow form of AI, and it's not something
that I think is very difficult. Actually, I think the
to do autonomous driving to agree that's much safer than
a person.
Speaker 2: Is much easier than people think.
Speaker 3: Yeah, right, and yeah, I think it's going to just
become normal, Like it be like an elevator, Like nobod
they used to have elevator operators and then we you know,
we've developed some simple circuitry to have elevators just automatically
come to the floor that you're at and you can
just press the button. Nobody needs to operate the elevator.
The car is just going to be like that.
Speaker 1: And the elevators these days are even smart. I mean
it knows it knows where to position an elevator, so
that if you were to need an elevator, it's pretty
close to you. Cars in the future will be pretty
smart about that too.
Speaker 3: Yeah, you'll be able to tell your car like take home,
go here, go there, anything, and it'll just do it
at an order of mag to safer than a person.
Speaker 2: In fact, in the in the distant future, I.
Speaker 3: Think it's probably going to be if people may outlaw
driving cars because it's too dangerous, Like you can't have
a person driving a two time death machine.
Speaker 1: Now, if we if we have the right type of
intelligence in a car, we we also don't have to
make the cars that heavy. I would think, you know,
cars are getting heavier and heavier, and it's got more
and more stuff in it because it needs to survive
all these incredible collisions and things like that. If I
wonder if if we were to design cars that just
simply don't collide as much. I wonder if we could,
we could relax on some of those laws and and yeah,
make cars more fuel efficient and lighter and better to.
Speaker 2: Right, you could definitely do that.
Speaker 3: If you could count on not having an accident, then
you can get rid of a huge amount of the
crash structure and the airbags. And it'll be We're a
long way from that, because there's always gonna be some
for a very long time, there'll be some amount of
legacy cars on the road. And I think it is
important to just appreciate the size of the automotive industrial base.
Like it's not as though like when somebody makes an
autonomous car that suddenly all the cars will be autonomous.
Speaker 2: It's like there's two billion of them.
Speaker 3: Okay, So the total total number of cars and trucks
on the road is two billion. In climbing, the capacity
of car and truck production is about one hundred million
a year. So if tomorrow all cars were autonomous, it
would take twenty years to replace the fleet, assuming the
fleet stayed the same size. Arguably it could get smaller
if things are autonomous, but still it's it's still you know,
maybe fifteen years or something, and it's not all going
to transition immediately. It'll take quite a while. So and
it's the same for electrification of carsing that industrial base
to be electric. I mean, if if all cars were
suddenly fall cars produced were electric tomorrow, it would still
take twenty years to replace the fleet.
Speaker 2: And right now it's less than one percent.
Speaker 1: So now you you you're you mentioned just now about
about self driving cars being easier than people think. Now
you have your vision of how to go from where
we are today. Now, my model, my P eighty five
D has lane detection and so it gets a little
you know, when I get close to a lane, yep,
it detects the uh uh the speed signs and then
uses uses computer vision technology to do that. And but
and that's today's adas. What is your what is your roadmap?
You know, how is that different than other people's roadmap?
How do you think about how to get to self
driving cars.
Speaker 2: Yeah, well.
Speaker 3: You kind of need the hardware foundation, the sort of
sensor and computing foundation, and then you can keep uploading
new software. At least you can with the TAILS because
it's it's always connected. So the car that you have,
you'll notice that it's the features are steadily improving. We
now you know, have active cruise control, so it'll it'll
use radar and camera fusion to track the car in
front of you. It's also looking at with some of
the things that are coming out. It's got it looks
at the brake lights, so it anticipates that the car's
got the brake lights are active. It's going to get
basically smarter and smarter even with the current hardware suite.
So the current hardware suite is three hundred and sixty
degree ultrasonic sensors that go off to about just over
five meters. It's a forward camera to Ford radar. So
we'll make even with just that sensor suite, we can
actually make a huge progress in autonomy. We can certainly
make the car steer itself on on a freeway, do
lane changes. It's really autonomy is about what level of
reliability and safety do you want?
Speaker 2: Even with the current sensorus.
Speaker 3: We could make the cargo fully autonomous, but only to
but not to a level of reliabily that would be
safe in say a complex urban environment at thirty miles
an hour, where the lanemarking's not there and children could
be playing and things could be coming at.
Speaker 2: You from the side.
Speaker 3: So in order to solve that, you need a bigger
sensor suite, and you need more computing power. And I
think what you're doing actually with the tigers in the
futures is super interesting and will really be a big
enabler for autonomous driving. So I think, you know, we're
in video is doing really great stuff on that front.
Speaker 1: I appreciate that. Yeah, And so some of the challenges
that you see, what are the what are some of
the technological hurdles that And there's all kinds of researchers
in the room, they're all kinds of engineers in room.
What are some what are some of the technological hurdles
that you think are really important for us to go tackle. Surely,
surely we're going to get to some better cruise controls
on highways, but beyond that, what are some of the
things that you would like is to go focus on
the tackle for the car.
Speaker 3: Industry, Well, it's it. You know, where it gets tricky
is is just the is that sort of urban environment
around thirty or forty miles an hour. So like right
right now, it's fairly easy to deal with, say, things
that are sub five to ten miles an hour, because
we can do that with the ultrasonics. We just make
sure it doesn't hit anything right, you know, because you.
Speaker 1: Can always just the right thing to do. Largely, that's
why would.
Speaker 3: You want to hit anything with your exactly, So at
five ten miles an hour, you can stop within the
range of the ultrasonics, and that then from let's say
ten miles an hour to.
Speaker 2: You know, call it sort of fifty miles an hour.
Speaker 3: That that that that area in complex suburban environments, that's
that's where you can get a lot of unexpected things happening,
like let's say this of like a road closure or
a manhole cover open. Children playing is a big issue bicycles.
Once you get about fifty miles an hour and you're
in kind of a freeway environment, then it also gets
easier again, like the set of possibilities is much reduced,
so highway crews is easy. Low speed is easy, intermediate
is hard. And so being able to recognize what you're
seeing and make the right decision in the suburban environment
in that ten miles an hour to fifty mile an
hour zone is the challenging portion. But I really think
it's I mean, I almost this may sound a little complacent,
but I almost viewed it as like a solve problem,
Like we know exactly what.
Speaker 2: To do, and we'll be there in a few years.
Speaker 1: Right, It's just like Mars. That's quite side. That's kind
of the spirit of a I mean, in a lot
of ways in your mind, you kind of you kind
of see things solvable or arguably arguably solved, and and
a lot of it is really about getting there.
Speaker 3: Yeah, we'll take autonomous costs for granted, in quite a
short period of time. It's amazing how comfortable you get
at how quickly you get comfortable with it.
Speaker 2: So, now, what.
Speaker 1: About government government policies? Like one of the things that
I would like to do is I would I would
just like to keep working on my email as I'm
driving to work. Sure, you know, there's there's a thirty
people do that already. Like I said, I would like
to do it without without without breaking the law. So
where where where do you where do you think government
intervention falls in some of this stuff? Because you know, obviously,
if you car drivee by itself and it does it
even better than people, you would like it to drive
by itself, but largely the laws don't allow you to
do that today, right, absolutely, So how do we cross
that bridge? And how do you think about government invention regulations?
Speaker 2: Right? So, I think.
Speaker 3: It'll be from the point at which a car is
definitely safer than a person, there's probably at least another
two or three years after that before regulators will allow
that to be the case, because they will want to
see a large amount of statistical proof that it's not
merely as safe as a person, but much safer. So
I think what you can do is you can run
run it in shadow mode and essentially say, okay, this
is this is what the computer would have done in
all these circumstances, and was there a crash or was
there not?
Speaker 2: Like what are the false parts of false negatives?
Speaker 3: And then you know, it's achieve a large population group
and then and then make a really clear statistical argument
with the regulators, and then they're going to digest that,
observe it for a while, see if they agree with it,
and then I think they will because the evidence will
be overwhelming.
Speaker 1: Yeah, and the evidence is actually already quite overwhelming that
if you, if you, if you would have would have
noticed a break line in front of you in the
highway and you didn't, you didn't crash into a rear
in collision. Right, A lot of laser sate, you know, ideally, ideally,
hopefully people don't don't overreact with this, with this unknown technology,
and uh and prematurely regulate no premature regulations.
Speaker 2: Well, I mean regulation that was a joke.
Speaker 3: I think it when when it comes to public safety,
I think there's there's an argument for being quite cautious
and making sure that things are okay before before there's
a change.
Speaker 2: And I mean, and I.
Speaker 3: Don't think it's the case that right now there's a
fully autonomous system and regulators are not approving it, that
that that really be a substitute for people. But they
will be in a few years now.
Speaker 1: As we get more computer rized technology into these cars
and this car becomes really a software defined car. I
mean a lot of your engineers are software engineers.
Speaker 2: I mean that's yeah, absolutely.
Speaker 1: One of the great things about Tesla. You guys right
here in Silicon Valley, you're rich with software engineers and
you have that you' have that computer sensibility about architecting
a computer properly, designing the software, properly designing the software
for many generations of cars, so where he refines and
gets better and better. And it has been getting better.
I mean the software from the first time you send
me my Tesla to the now it's just like unrecognizable software.
Speaker 2: Right, big improvement.
Speaker 3: So that's why the first thing we try to do
is establish the hardware platform, make sure that we have
the sensors and compute power. And so we do that first,
even though the software is only taking advantage of a
small percentage of the sensors and compute power. And then
we do continuous updates to make the car more and
more capable.
Speaker 2: And we're going to see a lot of that happen
later this year.
Speaker 3: If I didn't have an announcement on Thursday morning, I
would be saying a lot more of it.
Speaker 1: Yeah, the audience doesn't understand why they have to wait
until Thursday morning. You tweeted it already. You're announce that
you're going to do an Ota. What kind of announcement
is that I'm going to do an Ota on Thursday.
That's like a new product announcement.
Speaker 3: These days, it's just it's just a well, it's just
saying that there's going to be a cool on Thursday morning,
and I'll describe what's going to be in version six
point two for anyone who's interested.
Speaker 1: That's so awesome. Though I'm interested. I get excited every
time I get an Ota, and it's you know, one
of the things that was really interesting is in the beginning,
when we first built the first Tesla together, the tegra
in it, we thought was more than enough. And recently
you said, can we just squeeze more performance out of
that platform? And it just happened in literally two years,
you know, several versions of your software updates all of
a sudden, the computing platform is not powerful enough, right,
And it's because you want to add more features, and
a lot of features these days are based on software.
Speaker 2: True.
Speaker 1: Yeah, And so one last question, and it's it has
to do with I guess something that a lot of
people are very concerned about, which is your car becomes
a software platform and software platforms get hacked. How do
you think about that, How do you think about security?
And what are some of the things that we could
do to try to make make make the car more
resilient to security attacks.
Speaker 3: Yeah, I think that that becomes really important when the
cars are fully autonomous. I mean, the way the cars
work right now, every system of the car, it's assumed,
could actually have a mechanical failure of some kind or
a logic failure, a fundamental logic failure. So you can
always overwhelm the breaking of the car with your foot,
and you can overwhelm the steering wheel with your hands. So,
but but when when there is a steering wheel, or
there isn't you know, a brake, pedal or something in
that like you know many is from now, then it's
really really dangerous, you know, because but even as it
is right now, what we spend most of our time
on is making sure that it's it's very difficult to
do a multi car hack. Like if you have direct
access to a car, just like if you've got direct
access to a computer or even a conventional car, you
can do a lot of things to it.
Speaker 2: But but that's less of.
Speaker 3: A concern than somebody being able to hack an arbitrary
car or multiple cars. So that's what we focus our
energy on is making sure that that in that ways
it's it's it's a lot like a like a cell
phone or a laptop, you know, you focus on making
sure that they can't or that it's very difficult for
that to be any kind of system wide hack. So
we put a lot of effort into that, and we
have third parties try to attack it. And in certain
parts of the car at the very fundamental level, like
the drive unit controller or the steering controller have an
additional level of security. So somebody may be able to uh,
you know, hack something that's cosmetic, but it's much harder
to hack something that's that's actually physically agerous.
Speaker 2: There's multiple levels of.
Speaker 1: Secure and so this way, if you if you weren't
able to penetrate maybe the entertainment system, it doesn't allow
you quickly as a result of.
Speaker 3: That, right, I may display a funny message or something,
but it would not you would not be able to
then control the steering or the motor.
Speaker 1: Yeah. Well, the future of cars is so exciting and
the work that you guys are doing are so exciting,
and it's it's it's great to see you guys pioneering
these computer rized cars. I mean a lot of people
think about think about Tesla as the electric car, but
I think it's obviously more than that. It's an electric car,
but it's a whole computer platform on top of that.
Speaker 3: Yeah, I think I think Tess is sort of the
leader in electric cars, but I think we'll also sort
of be the leader in autonomous cars, at least autonomous
cars that people can buy. And and so we're I mean,
if there's anybody interested in working on autonomous cars, would
love to have you work at Tesla, by the way.
So we're gonna put a lot of effort into automotive
autonomous driving because it's just going to be the default
thing and it could save a lot of lives.
Speaker 1: Yeah, so save a lot of lives and hopefully, hopefully
one of these days, it would be nice if Nvidia's
campus has no parking lot, yeah right, that it drops
us off and the meanders off to a place where
the land's a little cheaper and you know, and parks
a whole bunch of cars there and when it's time
to go home, were someone at to.
Speaker 3: Come, it will be extremely transformative, that's for sure. But yeah,
I mean when it comes to AI, I'm not really
worried about narrow AI like like autonomous cars or like
you know, a smart air conditioning unit at the house
or something. It's more like sort of the deep intelligent
stuff that is where we need to be cautious. I
actually think there's many potential flavors of AI. And you know,
it's odd that we're at we're so close to the
advent of AI, Like it's it seems strange that we
would be alive in this in this time.
Speaker 1: We'll come back every year, come back every year, and
you'll see the work that this group was going to do.
I mean, there's so much deep learning work being done here.
You have a lot of engineers here as well, and
there is fantastics to see the whole community focused on
advancing this field. And along the way, we're gonna spin
off a whole bunch of new capabilities. As you know,
that's gonna make cars just safer and more fun to drive.
Long before we have to get to essentially a self
driving car, there's going to be a lot of versions
along the way that's just going to bring joy to
a lot of people.
Speaker 2: Yeah. Absolutely, I just hope there's something left for used
humans to do.
Speaker 1: Well. I'm not gonna let let go of my steeringwell,
you know, I've got mine on the craziness mode and
the sports steering mode. Is that the way you have it?
You get driven to work? Now?
Speaker 3: No, well I drive half the time actually, And which
mode do you have it in? I always have it
insane mode?
Speaker 1: Yeah right, all right, thank you,