Dmitry Dolgov, co-CEO of Waymo, explains how Waymo is evolving its tech stack by combining domain-specific autonomous driving AI with modern generative vision-language models.
Insight
Dolgov: End-to-end AI models alone cannot achieve full autonomous driving
“You can take, you know, an end-to-end model, go from sensor to, you know, trajectories or actuation. You know, typically you don't build them in one stage, you build them in stages, but, you know, you can do, like, backprop through the whole thing, so, you kno…”
Prediction Held up
Dolgov: Waymo will continue using LiDAR, radar, and cameras together
“So yeah, I think the trend, you know, for us that we'll, you know, using all three modalities just, you know, makes a lot of sense.”
Insight
Dolgov: Distilling huge AI models beats training small models directly
“Where you're much better off training a huge model and then distilling it into a smaller model than just training small models.”
Assertion Supported
Dolgov: Waymo driverless cars cut injury crashes by 3.5x
“And I think 3.5 acts as the reduction in injury. And that's about two X reduction in the police reportable kind of lower severity incidents.”
Assertion Partly supported
Dolgov: Swiss Re study showed zero bodily injury claims for Waymo
“We published a joint study with a Swiss RE. Which is, I think, the largest global reinsurer in the world, and the way they look at it is, you know, who contributed to an event, and there we saw, ah, like the same theme, but the numbers were, ah, very strong, t…”
Insight
Dolgov: Building AV drivers requires iteratively modeling simulation environments and actors
“To build a good driver, you need to have a very good simulator, but to have a good simulator, you actually have to build models of, like, realistic pedestrians and cyclists and drivers, right? So it's, you know, you kind of do that iteratively.”