Nvidia wants carmakers to adopt its single unified architecture for everything from software to datacenter tech to chips for autonomous vehicles. And the company is making its pretrained libraries of deep neural network data for self-driving cars available to its partners.
Santa Clara, California-based Nvidia hopes autonomy will spread across today’s $10 trillion transportation industry. But that transformation will require dramatically more computing power to handle exponential growth in the AI models currently being developed and ensure autonomous vehicles are both functional and safe. At CES 2020, the big tech trade show in Las Vegas this week, we’ll probably see self-driving vehicles that are good but not quite there.
Nvidia’s Drive AV is an end-to-end, software-defined platform for autonomous vehicles. It includes a development flow, datacenter infrastructure, an in-vehicle computer, and pretrained AI models that can be adapted by carmakers.
In December, Nvidia unveiled Drive AGX Orin, a massive AI chip with 7 times the performance of its predecessor, Xavier.
In a press briefing, Danny Shapiro, Nvidia’s senior director of automotive, said the company’s graphics chips gave birth to this kind of self-learning design that is now becoming the heart of artificial intelligence chips for autonomous vehicles.
“Everything in the $10 trillion industry will have some degree of autonomy, and that’s what we’re really working to develop,” Shapiro said. “What’s key to recognize is that it’s a single, unified architecture, enabling us to create these software-defined vehicles, and they get better and better and better over time.”
Samples of Orin will be provided in 2020 for testing, but the chip isn’t expected to ship in vehicles until 2022. It will be capable of 200 trillion operations per second and is designed to handle the large number of applications and deep neural networks (DNNs) that run simultaneously in autonomous vehicles, while…