Robert Welborn joins us again for the second part of autonomous vehicle myths. During this discussion, Robert compares the vast and critical differences between the capabilities of today's math and the necessity of developing tomorrow's math before fully autonomous vehicles are a safe, mainstream option. He parses out the weakness in today's autonomous vehicles. For example, converting visual information into digital information and then trying to extract features from that before making a decision off of those inputs. As one could imagine, and as Robert so vividly depicts, there are issues—namely safety—in expecting a computing system to respond quickly and correctly to the infinite numbers of inputs it may receive. Robert closes the discussion with a few viable ways of progressing the technology.