4 ms·
I wish these sort of papers would focus more on the 3 percent that it got wrong. Is it wrong by saying that a day would have a slight drizzle but it was actuall
by dagw 2y ago
I wish these sort of papers would focus more on the 3 percent that it got wrong. Is it wrong by saying that a day would have a slight drizzle but it was actually sunny all day, or was it wrong by missing a catastrophic rain storm that devastated a region?
I've worked on several projects trying to use AI to model various CFD calculations. We could trivially get 90+ percent accuracy on a bunch of metrics, the problem is that its almost always the really important and critical cases that end up being wrong in the AI model.
- gyrovagueGeist 2y agoYep, this is also the problem that self-driving cars have with the "accidents per mile" metric.
- genewitch 2y agoi was using scikit-learn or some other scaffolding/boilerplating similar software for doing predictions and i hate massaging data so i just generated primes and trained it on the prime series to like 300 or 1000, then had it go on trying to "guess" future primes or assert if a number was prime or not that it had seen before and hilariously it was completely wrong (like 12% hit rate or something). I complained online and i forget the exact scope of my lack of understanding but suffice to say i did not earn respect that day!