New AI camera could revolutionize autonomous vehicles

Stanford engineers combine two types of computers to create a faster and less energy-intensive image processor for use in autonomous vehicles, security cameras and medical devices. The image recognition technology that underlies today's autonomous cars and aerial drones depends on artificial intelligence: the computers essentially teach themselves to recognize objects like a dog, a pedestrian crossing the street or a stopped car. The problem is that the computers running the artificial intelligence algorithms are currently too large and slow for future applications like handheld medical devices. A Stanford-designed hybrid optical-electrical computer designed specifically for image analysis could be ideal for autonomous vehicles. (Image credit: Andrey Suslov / Getty Images) Now, researchers at Stanford University have devised a new type of artificially intelligent camera system that can classify images faster and more energy efficiently, and that could one day be built small enough to be embedded in the devices themselves, something that is not possible today. The work was published in the August 17 Nature Scientific Reports. "That autonomous car you just passed has a relatively huge, relatively slow, energy intensive computer in its trunk," said Gordon Wetzstein , an assistant professor of electrical engineering at Stanford, who led the research.