According to Sawyer Merritt, Tesla has launched a new safety page detailing how its fleet of 8.6 million vehicles generates anonymous data from real-world driving scenarios. This massive data collection enables Tesla to leverage artificial intelligence for continuous safety improvements, which are then deployed to all vehicles through free over-the-air software updates. The integration of real-time AI-driven insights not only enhances vehicle safety but also provides Tesla with a significant competitive advantage in the automotive AI market, demonstrating a scalable model for AI-powered fleet learning and rapid safety iteration (Source: Tesla, Sawyer Merritt).

According to Andrej Karpathy (@karpathy) on Twitter, the latest Tesla HW4 Model X running FSD version 13 delivers a significant leap in autonomous driving performance. Karpathy highlights that the AI-driven Full Self-Driving system is now exceptionally smooth, confident, and consistently outperforms previous HW3 versions. Notably, the vehicle handled complex city scenarios, intricate left turns, and highway navigation without requiring human intervention, reducing typical post-drive issues to zero. Karpathy attributes these improvements to Tesla's data-driven, end-to-end neural network approach, as discussed in Ashok Elluswamy’s recent ICCV25 presentation, which leverages multi-modal sensor streams and continuous fleet learning. This robust AI stack positions Tesla as a leader in scalable autonomous driving, offering substantial business opportunities in robotaxi services, fleet management, and AI robotics platforms. (Source: @karpathy, Twitter; @aelluswamy, ICCV25 talk)