Dmitri Dolgov: commitment

Transcript context

…There are all these debates that go on on Twitter around self-driving. I can think of end-to the end versus the more modular approach. There's cameras only versus array of sensors. I can't tell, are these debates actually interesting to an expert in the field, or do you think these are just settled matters, and they're just grist for the algorithm? I understand where the questions are coming from. I do find that often the way they're posed and the way the debate happens is losing a lot of the nuance and a lot of detail that really matters. To me, the most interesting technical questions are in that level. Because the way we think about building the Waymo Driver, it starts with a large off-board foundation model. I can imagine building a big model that understands how the physical world works and understands the important properties of what it means to drive, the social aspects of driving, and what it means to be a good driver as opposed to a bad one. That's the foundation. Then we specialize it into, let me call it, three main off-board teachers. There are still large, high-capacity off-board models. There's the Waymo Driver, there is the simulator, and then there's the critic. Those then get distilled into smaller models that you can run inference on faster. The Waymo Driver becomes the backbone, the backbone of what's in the car. The simulator, of course, is what powers our synthetic generative environment that can run on the cloud for training and for evaluation enclosed the system. The critic is the value. Does the simulator ever run locally?…

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