One of the most exciting applications for AI is autonomous AI.
This is essentially a data center on wheels, and AI is processing at real time with sensors
feeding it, and it has to process so fast that it can make decisions in a split of a second.
Autonomous vehicles is one of the greatest computing challenges and will surely be one
of the most impactful.
This is one of the largest industries in the world.
10 trillion miles are driven each year.
It is because of this that we've created an architecture that is scalable.
Ladies and gentlemen, today I'm announcing that the Ampere architecture is coming to
NVIDIA DRIVE.
Because of the scalability of the Ampere architecture the efficiency and incredible computational
performance, we can now scale our driving car computer from ADAS behind the windshield
all the way up to robot taxis.
From a low power chip for ADAS driver assistance to a powerful in-car computer for full self-driving
autopilot all the way up to driverless robot taxi: one single programmable architecture.
This is basically the entire range of everything that moves, and it's our belief that everything
that moves will eventually be autonomous.
This will represent cars, passenger cars, taxis, trucks, shuttles, delivery bots.
We're going to have autonomous vehicles of all kinds.
The Ampere architecture will span this whole range.
We also developed an end-to-end system for creating the AV autopilot application: testing
and simulating it, deploying it into the car, all the way to operating it with remote control.
This entire system is built on one architecture.
NVIDIA is collecting data, labeling and augmenting the data, training the AI models.
We created a virtual reality driving simulator, testing the entire stack in the car, to an
AI agent that would assist you, all the way to a virtual reality telepresence system that
allows you to portal into the mind of the car so that you can remotely control the car.
This end-to-end system and the entire scalable architecture from ADAS to autopilot to robot
taxi is the DRIVE system.
Now, let me show you our latest update.
Before I show it to you, let me first remind you everything you're about to see is in virtual virtual.
All of our engineers are safely sheltering at home.
They could develop their application at home and virtually drive their autopilot in our data centers.
Please enjoy.
Wasn't that great?
The NVIDIA DRIVE platform is an open platform.
We're doing so, so we can understand the great challenges of this new computing form.
NVIDIA is developing the DRIVE system from beginning to end.
From the collection of data all the way to the testing of the cars.
We're developing the entire stack from top to bottom and we're creating an architecture
that spans ADAS to autopilot to robot taxis.
This entire platform is open.
You can engage the platform however you like.
You could use our libraries, use our tools, in any part of it to augment your own.
The openness of our platform is the reason why we have so many partners around the world.
Cars, trucks, tier one OEMs, mobility services, startups, software companies, mapping companies
and simulation companies.
We have partners all over the world using DRIVE, developing all kinds of different forms
of autonomous transportation.
This end-to-end pipeline, this end-to-end infrastructure is one of our greatest achievements,
and we've learned so much in doing this about the future of autonomous vehicles.