特斯拉为什么现在不选择VLA?

Core Insights - The article discusses Tesla's latest Full Self-Driving (FSD) technology, questioning whether its architecture is outdated compared to the emerging VLA (Vision-Language-Action) framework used in robotics [3][4]. Comparison of Robotics and Autonomous Driving - Task Objectives: Robotics can execute any human command, while autonomous driving focuses on navigation from point A to B, relying on map data for precision [4]. - Operating Environment: Autonomous driving operates on defined roads with fewer complex tasks, making it less reliant on language processing compared to robotics [4]. - Hardware Limitations: Current hardware lacks sufficient processing power (under 1000 TOPS), making it challenging to implement large language models for driving tasks, which could compromise safety [5]. Tesla's Approach - Tesla employs a hybrid logic of fast and slow thinking, primarily using an end-to-end approach for most scenarios, while only utilizing VLM in specific situations like traffic regulations or unstructured road conditions [5].