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Despite this criticism, there's a compelling argument to be made for Tesla's unique approach to training its autonomous systems. Unlike its competitors, Tesla relies heavily on machine learning and vast amounts of driver data accrued over countless miles instead of traditional maps and LIDAR.
Navigating the Critique of Safety Responsibility
Unease surrounding Tesla's public assertions about full autonomy ties back to the very definitions of "safety drivers" and "supervisors." In traditional autonomous fleet deployments, the human role typically involves immediate intervention capabilities. Tesla's deployment model, featuring a supervisor in the passenger seat rather than at the controls, raises questions about its adherence to safety standards.