Fernando Alonso’s terrifying F1 crash last month at the Australian Grand Prix shows how far humans will push a car for the pursuit of performance.
What if we could push racecars to the new levels of performance without endangering lives?
To find out, we’re putting our DRIVE PX 2 AI supercomputer into the cars that will compete in the Roborace Championship, the first global autonomous motorsports competition, NVIDIA CEO Jen-Hsun Huang announced Tuesday at our GPU Technology Conference, in Silicon Valley.
Superhuman Action, Powered by DRIVE PX 2
Part of the new Formula E ePrix electric racing series, Roborace combines the intrigue of robot competition with earth-friendly alternative energy racing.
Every Roborace will pit 10 teams, each with two driverless cars equipped with NVIDIA DRIVE PX 2, against each other in one-hour races. The teams will have identical cars. Their sole competitive advantage: software. It’s truly a contest to build the most advanced artificial mind.
The amount of information pouring into each of these autonomous high-speed racecars — and the need to make quick decisions — is incredibly demanding. That’s why Kinetik, the London-based investment firm behind Roborace, approached NVIDIA.
DRIVE PX 2 provides supercomputer-class performance — up to 24 trillion operations a second for AI applications — in a case the size of a lunchbox. And such a small box is exactly what these racecars need.
Since the cars don’t need human drivers, these racecars are incredibly compact, and the designs — conceived by auto designer Daniel Simon, the man behind Tron: Legacy’s light cycles — are like nothing that’s been seen on a road, or a racetrack, before. There’s no room in these racers for the trunk full of PCs that powered earlier generations of autonomous vehicles.
Thanks to DRIVE PX 2, there’s no need.
Power, Without the Pounds
DRIVE PX 2 provides the processing power of 150 MacBook Pros, enough to incorporate input from a vast array of sensors — radar, lidar, cameras, GPS and high-definition mapping, for starters.
And with DRIVE PX 2’s deep learning capabilities — which use GPUs to help machines learn from the world around them — these racecars will get better the more they race.
It’s a competition in what will lead to safer, smarter cars for everyone.
What Should We Name Our Car?
If NVIDIA were to have an autonomous racecar, what would we call it? We’ve considered “Deep Green” — a reference to deep learning and energy-efficient AI computing — but we’re looking for more suggestions.
Tell us what we should name our racecar in the comment box below.