Different parts of automotive sub-systems have differing sensing and On-Device AI requirements, and requirements evolve over time. We will show how each sensing application has evolved into AI algorithm by citing specific examples. In addition, diverse algorithms are often employed within an application for pre-processing, inference, and post-processing.

We will also highlight key trends in DNN topologies, and make the case that, due to rapid progress in neural network research and varying processing requirements, a combination of hardwire and programmable solutions are essential.