> I prefer an "exact" guarantee that the result is as close-as-possible rather than merely "within some relative epsilon". This is the core requirement of any

> I prefer an "exact" guarantee that the result is as close-as-possible rather than merely "within some relative epsilon". This is the core requirement of any system that quantizes the real numbers in order to perform arithmetic. The thing that distinguishes fixed-point from floating-point systems is the quantization error that gets introduced in this process: For floating point, the error is proportional to the magnitude of the number being reprsented. The article is primarily exploring the implications of this property. For fixed point, the quantization error has an absolute magnitude that doesn’t depend on the size of the input numbers. This has a completely different set of benefits and drawbacks, but still maintains your “preferred” property.