According to Sawyer Merritt, Tesla utilizes footage from its extensive vehicle fleet to synthetically generate new driving scenarios, enhancing the safety and robustness of its self-driving software. By stitching data from all eight vehicle cameras into a fully navigable 3D environment, Tesla engineers can simulate real-world conditions and interact with virtual roads powered by neural network–generated video streams. This system enables simultaneous simulation of all camera feeds, supports adversarial event injection such as adding unexpected pedestrians or vehicles, and allows engineers to replay and analyze past failures to validate improvements in AI models. These capabilities are used for testing, training, and reinforcement learning, providing Tesla with a scalable and realistic platform to accelerate development and deployment of autonomous driving technologies (Source: Sawyer Merritt, x.com/SawyerMerritt/status/1981461127046258981).