In this podcast, Dmitri Dolgov of Waymo discusses the company's journey from developing self-driving cars to having a public commercial service available to users. He talks about the fifth generation of hardware that is on the new vehicle and how it is qualitatively different from the previous generations. He also discusses how Waymo's self-driving cars are built and operated, and how Alphabet's ML infrastructure helps the process.
Dmitri Dolgov, head of Waymo's Self-Driving Car Project, discusses the company's approach to autonomous driving. He explains that Waymo is focused on safety, reliability, and comfort for passengers, and argues that the company's driverless technology has progressed from a proof-of-concept to widespread deployment. Dolgov also discusses the challenges of scaling up this technology, including improving the hardware and software architecture, developing a reliable deployment process, and developing a good product quality assurance process.
In this video, Dmitri Dolgov discusses how Waymo's self-driving cars are performing and how they are able to avoid collisions. He also discusses the trolley problem, which is a difficult philosophical construct that highlights the difficult ethical decisions that humans must make. He says that although humans are not particularly good at making these decisions, the algorithm must still make them.