Uncertainty
As a software engineer working on graphics I’ve drifted a pretty long way from my original specialty, aerospace controls. I’m glad I got my PhD in controls though, because it taught me a unique way to approach problem solving, one which I tend to apply well beyond the traditional realm of controls. Controls is a very math-heavy discipline, focused on proofs and guarantees of safety because in many situations lives depend on the reliability of the system: autopilots come to mind, but there are countless examples in many fields. At its core is uncertainty and the management thereof. The first thing we’re taught when modeling systems is that our models are inevitably wrong, and not by a little: nothing is linear, nothing is rigid, nothing is independent of the world around it. These assumptions make our math tractable, but they are not realistic. And yet, all is not lost: we take our terrible models and our unreliable sensors and we bound their uncertainty. No matter how poor the input is...