Tag
2 reads
Waymo runs 4,000+ cars in 15 US cities on a $126 billion valuation, but about 70 remote agents on duty at any time, split between US and Philippine call centers, are the layer the marketing leaves out. The riders cannot steer, so safety depends on how fast a human answers, and the least disclosed metric is that response time. Like Amazon's logistics, the moat is operational, and here it also includes winning permission city by city.
Waymo's architecture resolves the end-to-end debate: Dolgov states pure pixels-to-trajectories drives "pretty darn well" in the nominal case but is "orders of magnitude away" from what full autonomy requires. The 500K-rides-per-week stack is one off-board foundation model fanning into three specialized teachers (Driver, Simulator, Critic), each distilled into smaller in-car students; RLFT against the critic is the physical-AI analog to RLHF. Enterprise teams shipping pure-LLM agents without the simulator and critic scaffolding are replaying Waymo's 2017, not its 2026: evaluation infrastructure is the reliability gate, not model choice.