Driverless startup Cruise today detailed a homegrown tool — the Continuous Learning Machine — that tackles on-the-road prediction tasks. Cruise claims the Continuous Learning Machine, which automatically labels and mines training data, allows some of the AI models guiding Cruise’s self-driving cars to predict things like whether bicycles will swerve into traffic or kids will run into streets.
One of the challenges of autonomous vehicles is predicting intent. People don’t always follow the rules of the road, and even when they do, they’re liable to bend those rules. According to the U.S. National Highway Traffic Safety Administration, 94% of serious crashes are due to drivers’ errors or dangerous choices.
That’s why Cruise built Continuous Learning Machine. Leveraging a technique called active learning, it automatically identifies errors made by perception models running on Cruise’s cars, and only scenarios with a significant difference between prediction and reality are added to the training data sets.