Waymo closes $5.6B investment round

Waymo’s current status and user experience

• Several commenters report regularly seeing and using Waymo robotaxis in cities like Phoenix/Scottsdale and Atlanta, describing the experience as “amazing” and futuristic.
• Waymo is said to be doing >100k paid driverless rides per week and ~20M driverless miles to date.
• Some argue Waymo effectively “created and now dominates” the robotaxi market, with other players far behind in actual driverless deployment.

Waymo vs Tesla and other AV approaches

• Strong debate over Waymo’s LiDAR + cameras + radar + HD maps + remote-support stack versus Tesla’s camera-only, map-light, in-car-supervised FSD.
• Pro-Waymo side: only driverless miles and legal assumption of liability matter; Tesla has zero driverless public-road miles and remains an advanced driver-assist system requiring constant supervision.
• Pro-Tesla side: FSD is already very capable for supervised use, improving quickly, and backed by vastly more fleet data; they argue Tesla’s generalized, vision-heavy approach will scale better geographically than Waymo’s mapped, geofenced model.
• Many emphasize that both use traditional robotics pipelines with ML components; neither is a pure end‑to‑end “AI magic box.”

Remote operation, safety, and liability

• Multiple comments clarify Waymo’s remote support: humans choose from high-level options when the car is stopped or stuck; they do not joystick-drive the car in real time.
• Some criticize media and critics for conflating this with teleoperation.
• Safety comparisons: posters cite dozens of Tesla Autopilot/FSD fatalities versus no widely known Waymo passenger fatalities; others question disengagement metrics and definitions.
• Liability question raised: in a crash, Tesla still puts responsibility on the supervising driver, whereas Waymo assumes more direct liability for its driverless service.

Economics, scaling, and profitability

• Wide agreement that Waymo’s economics are currently challenging: expensive vehicles, depots, mapping, support staff, and large fixed R&D and compute costs.
• Back-of-envelope calculations suggest revenue per car might cover variable operating costs but not yet overall burn; others think scaling trends imply they may be near operating breakeven in at least some cities.
• Debate over whether HD mapping is a fatal scalability flaw or just a data cache that a company with Google’s mapping experience can scale.
• Long-term bull case: robotaxis could displace a large share of private car ownership and capture “the driver’s cut” of ride-hailing, potentially justifying very high valuations; skeptics see an expensive niche taxi company subsidized by Alphabet.