A startup called iSee thinks a new approach to AI will make self-driving cars better at dealing with unexpected situations.
by Will Knight, senior editor for AI at MIT Technology Review.
Boston’s notoriously unfriendly drivers and chaotic roads may be the perfect testing ground for a fundamentally different kind of self-driving car.
An MIT spin-off called iSee is developing and testing the autonomous driving system using a novel approach to artificial intelligence. Instead of relying on simple rules or machine-learning algorithms to train cars to drive, the startup is taking inspiration from cognitive science to give machines a kind of common sense and the ability to quickly deal with new situations. It is developing algorithms that try to match the way humans understand and learn about the physical world, including interacting with other people. The approach could lead to self-driving vehicles that are much better equipped to deal with unfamiliar scenes and complex interactions on the road.
“The human mind is super-sensitive to physics and social cues,” says Yibiao Zhao, cofounder of iSee. “Current AI is relatively limited in those domains, and we think that is actually the missing piece in driving.”
Zhao’s company doesn’t look like a world beater just yet. A small team of engineers works out of a modest lab space at the Engine, a new investment company created by MIT to fund innovative local tech companies. Located just a short walk from the MIT campus, the Engine overlooks a street on which drivers jostle for parking spots and edge aggressively into traffic.