The real test of autonomous driving AI: billions of miles of real-world data

Those truly autonomous driving systems are not script programs running under controlled laboratory conditions—but rather have been refined through billions of miles in the real world. Millions of vehicles contribute data continuously every day, and the system learns and optimizes from this vast amount of information.

From urban traffic to extreme weather, from power outage incidents to chaotic scenes, the neural networks of autonomous driving have been repeatedly validated under various uncontrollable conditions. This is not merely a piling up of technical metrics, but a ruthless test of actual road conditions. The scale and diversity of data directly determine the robustness of AI systems. This approach, using billions of real-world conditions as a training set, is redefining our understanding of "AI readiness."