To paraphrase Kahan, it's not interesting to me whether a method is accurate enough or not, but whether you can predict how accurate you can be. So, if ML methods can predict that they're right 98% of times then we can build this in our systems, even if we don't understand how they work.
Deterministic methods can predict result with a single run, ML methods will need ensemble of results to show the same confidence. It is possible at the end of day that the difference in cost might not he that high over time.
Deterministic methods can predict result with a single run, ML methods will need ensemble of results to show the same confidence. It is possible at the end of day that the difference in cost might not he that high over time.