As intelligent driving systems evolve, real-time decision-making depends on how efficiently AI processes current observations and historical context.
In this video, Dr. Xianming Liu, Head of General Intelligence Center at XPENG, explains how streaming inference combines past information with current frames to support continuous prediction and decision-making. By avoiding the repeated processing of the entire history, this approach can help reduce additional computational overhead and latency.
Watch the video to learn more about the inference mechanisms behind intelligent driving.
