3 ms·
Even if a state of the art machine learning system is going to work 99.999% of the time - with millions of diffs run daily - that's still too many failures. So
by voqv 7y ago
Even if a state of the art machine learning system is going to work 99.999% of the time - with millions of diffs run daily - that's still too many failures.
So basically with diff we had 1 problem, with ML-diff we'll have two.
- modeless 7y agoJust because a system uses ML doesn't mean it has to be less reliable, especially when it replaces a heuristic that's already unreliable. The correctness of the patch can be easily verified, and the reasonableness of the patch can also be ensured with some heuristics that would be much easier to make than a whole diff algorithm. There seems to be a serious bias against ML in systems programming that is unwarranted. There are plenty of problems using bad heuristics today that could be improved with ML in a way that doesn't reduce reliability. Scheduling, compiler optimization, stuff like that.