Waymo Co-CEO Dmitri Dolgov: Data-Driven AI for Autonomous Vehicles With

Waymo’s autonomous driving technology relies on a unified, scalable "driver" system that integrates high-resolution hardware—including cameras, LiDAR, and radar—with advanced machine learning models for perception, prediction, and planning. Operating in complex urban environments like San Francisco provides critical data for refining performance in dense traffic and navigating unpredictable scenarios, such as construction zones or erratic behavior. The company’s data strategy emphasizes closing the loop between data mining, simulation, and real-world deployment to address the "long tail" of rare edge cases. By building proprietary hardware and a robust, shared infrastructure, Waymo maintains consistent performance across diverse applications, including ride-hailing and long-haul trucking. Co-CEO Dmitri Dolgov highlights that moving from an initial vision to a fully operational, driverless commercial service requires continuous iteration on both technical capabilities and operational systems to ensure safety and scalability across new geographies.