Part 8/12:
Almost three years ago, Andre Carpathé explained the inefficiencies of multi-sensor stacks and emphasized the importance of scaling data collection through a large fleet. His theories have been validated by Tesla’s recent progress; within months of launching their robo-taxi service, Tesla’s operational area overtook competitors like Wimo, which had been active for over five years.
This rapid scale-up illustrates that high-resolution maps and region-specific pre-mapping are bottlenecks for global deployment. Maintaining centimeter-level precision across extensive regions is impractical and costly, further justifying Tesla’s focus on vision-based perception.