In the current state of automotive radar, machine learning engineers can’t work with camera-equivalent raw RGB images. Instead, they work with the output of radar constant false alarm rate (CFAR), which is similar to computer vision (CV) edge detections. The communications and compute architectures haven’t kept pace with trends in AI and the needs of Level 4 autonomy, despite radar being a staple of vehicle‑level sensing for years.  The real 3D/4D “image” signal is instead processed inside the edge device. The radar outputs objects, or in some cases point clouds, which is similar to a camera outputting a classical CV Canny edge‑detection image. Figure 1. High-level architecture of standard radar with edge processing compared with centralized processing Centralized radar processing on NVIDIA DRIVE changes this model: Raw analog‑to‑digital converter (ADC) data moves into a centralized compute platform.…