Waymo's perception lead explains how deep learning, sensors, and massive simulation turn a self-driving demo into a production system.

Sacha Arnoud — Director of Engineering and head of perception at Waymo, formerly on Google's Street View team leading the Street Smart deep-learning project.
Sacha Arnoud, Waymo's director of engineering and perception lead, gives an MIT lecture tracing self-driving from Google's 2009 Chauffeur project to Waymo's driverless milestone of removing safety drivers in late 2017. He explains the rise of deep learning inside Google, from Street View house-number recognition to real-time embedded perception on the cars. He details perception techniques: sensor fusion across cameras, radar, and lidar; segmentation; single-shot detection; embeddings; and recurrent networks for behavior prediction. He emphasizes that algorithms are only part of the work, with labeling, compute, TensorFlow infrastructure, and a three-pronged testing program of real driving, simulation, and a structured test facility. He closes with future directions around expanding operating domains and deeper semantic understanding.