at first it seems improbable how could
it be that Tesla who has never designed
a chip before were designed the best
chip in the world but that is
objectively what has occurred not not
best by a small margin best by a huge
watching it's in the cars right now old
Tesla's being produced right now have
this computer back in October 2016 Tesla
announced that its vehicles will start
shipping with cameras and sensors to
support fully autonomous driving through
a software update and computer upgrade
to come
according to Elon Musk that day has
arrived all cars being produced have the
have all the hardware necessary compute
and otherwise for full self-driving
Tesla held an event for their investors
called autonomy investor day at their
office in Palo Alto the event showcased
software upgrades to Tesla self-driving
technology to be rolled out in a series
of over-the-air updates as of now
Tesla's autopilot feature enables
self-driving on highways on ramps and
off ramps with periodic input from the
driver Tesla CEO Elon Musk also debuted
a new computer called the Tesla FSD or
full self-driving computer previously
known as the autopilot Hardware 3.0
upgrade the FSD is said to be currently
in production and will enable Tesla's
software updates to work here's what it
looks like
I'd like to point out that this is
actually a pretty small computer it fits
behind the glove box between the glove
box and the firewall in the car it does
not take up half your trunk as they said
earlier there's two fully independent
computers on the board and that your
principle here is that if any part of
this could fail and the call will keep
driving so you have cameras bail you
could have power circuits fail you could
have one of the Tesla pulse rifle
self-driving computer chips fail car
keeps driving the probability of this
computer failing is substantially lower
than somebody losing consciousness there
in the top left you can see the cameras
Euler interface we can ingest 2.5
billion pixels per second which is more
than enough to
all the sensors that we know about in
case you use let's say lidar would it be
able to process the lidar is is a fool's
errand and anyone luck relying on
replied are is doomed doomed expensive
expensive sensors that are unnecessary
it's like having a whole bunch of a
expensive pen just appendices that
compare one appendix is bad well now I
put a whole bunch of them that's
ridiculous
you'll see every autonomy because you
want level four level five systems that
can handle all the possible situations
in in 99.99% of the cases and chasing
some of the last few nice is going to be
very tricky and very difficult and is
going to require a very powerful visual
system so I'm showing you some images of
what you might encounter in any one
slice of that line so in the beginning
you just have very simple cars going
forward then those cars start to look a
little bit funny then maybe you have
black stone cars then maybe of cars and
cars then maybe you start to get into
really rare events like cars turned over
or even cars airborne we see a lot of
things coming from the fleet and we see
them at some rate like really good rate
compared to all of our comparators and
so the rate of progress at which you can
actually address these problems iterate
on the software and really feed the
neural hours with the right data that
rate of progress is really just
proportional to how often you encounter
these situations in the wild and we
encountered them significantly more
frequently than anywhere else which is
why we're going to do extremely well we
have eight cameras but then we also have
additionally twelve ultrasonic sensors
or radar an inertial measurement unit
GPS and then one thing we forget about
we also the pedal and steering actions
so not only can we look at what's
happening around the vehicle we can look
at how humans chose to interact with
that environment and so I'll talk to
this clip right now this basically is
showing what's happening today in the
car and we'll continuing to push this
forward so we start with a single neural
network we see the detections around it
we then build all that together multiple
neural networks in multiple directions
we bring in the other sensors and we
convert that into an Elan calls of
vector space an understanding of the
world around us and this is something
where as we continue to get better and
better at this we're moving more and
more of this logic into the neural
networks
selves and the obvious endgame here is
that the neural network looks across all
the cars brings in all the information
together and just ultimately outputs a
source of truth for the world around us
does full self-driving capability make
you want to purchase a test some more
you