Waymo tests AI driving system that learns from labeled data

Alphabet's self-driving spinoff Waymo achieved some noteworthy milestones this year, in August surpassing 10 million real-world miles with its driverless cars and last week launching Waymo One, a commercial driverless taxi service. But its researchers have their eyes fixed on the future. In a blog post published today on Medium, researchers Mayank Bansal and Abhijit Ogale detailed an approach to AI driver training that taps labeled data -- that is to say, Waymo's millions of annotated miles from expert driving demonstrations -- in a supervised manner. "In recent years, the supervised training of deep neural networks using large amounts of labeled data has rapidly improved the state-of-the-art in many fields, particularly in the area of object perception and prediction, and these technologies are used extensively at Waymo," the researchers wrote. "Following the success of neural networks for perception, we naturally asked ourselves the question: … can we train a skilled driver using a purely supervised deep learning approach?"