The floating point types and their consequences have been nothing short of a disaster for the world of computers. It's a representation model that is neither reliably deterministic across platforms and compiler settings, nor mathematically accurate, nor particularly faithful at representing ordinary decimal numbers. Values as simple as 0.1 cannot be stored exactly in binary floating point, routine operations lose associativity, accumulated rounding error creates silent numerical drift, and seemingly harmless changes in instruction ordering, optimization flags, or processor architecture can produce materially different outputs. These are not academic edge cases.. the Patriot missile timing error accumulated until the system failed to intercept an incoming missile, contributing to the deaths of 28 people, while the Ariane 5 rocket self-destructed after an unchecked numeric conversion overflow propagated through its guidance software. The standard compounds this fragility with special values such as NaN, positive and negative infinity, signed zero, denormalized numbers, and exception states that many developers barely understand, allowing invalid data to bypass comparisons, poison calculations, destabilize control loops, or create novel abuse paths. What began as an efficiency-oriented approximation has spiraled into a systemic reliability liability, forcing entire industries to layer epsilon comparisons, decimal libraries, deterministic execution modes, overflow guards, numerical analysis, and defensive validation around a primitive that routinely violates intuitive arithmetic and converts minor implementation details into catastrophic operational risk.
https://youtu.be/O6FsyQZzJJ0
it's faster
floating bar is the answer.
retard
>>109387184They’re just dyadic rationals with a finite number of terms, unless you have infinite memory this is literally the best you can do.
