Does a bigger list of FP32 numbers amplify floating-point errors when finding the max? Avonetics experts crack the code: the comparison itself doesn’t add rounding errors—it just picks one of the existing numbers. The real culprit? How those numbers were initially represented. But here’s the twist: if your data already has stochastic errors, a larger list might sneak in a skewed max value. Dive into the nitty-gritty of FP32 precision and avoid costly mistakes. For advertising opportunities, visit Avonetics.com.