> What are the applications where someone would require floating point math AND both extreme speed and extreme accuracy? Scientific computation. I'm not even

> What are the applications where someone would require floating point math AND both extreme speed and extreme accuracy? Scientific computation. I'm not even sure, it is a trade-off between (computational) speed and accuracy. In my experience, error-analysis was a mandatory course for physics, but not in robotics. The error analysis was manual and time-consuming. In robotics, no one cared why it occasionally produced NaNs, etc.. people just added a small number here and there. That's faster to program. To put it more positively, I think, the view here is more having an application, which is robust in the face of errors / edge cases. What counts is the output (action). While in science the correct model is part of the output. Edge cases are an important part of it.