liquidise 37 minutes ago
If I say every model is trained on CSAM, I too will correctly identify 100% of the models that were. Says little about my false positive rate though.
yk 29 minutes ago
I know some reasons for 100% accuracy in machine learning, first of all the test set leaking into training data. Or you just accept a silly high false positive rate.
When I was an admin I liked to joke that if you guarantee more than 5 nines, then you are an insurance company and you are planning to pay the penalty instead of actually fulfilling your promise, here the principle is probably the same.
gnabgib 18 minutes ago
[0]: https://news.mit.edu/2026/new-method-keeps-kids-safe-from-il... (https://news.ycombinator.com/item?id=48893301)
andy99 9 minutes ago
Worse, the ignorant will believe the 100% claim and equate a positive classification with truth.
I should add, it’s an interesting problem space for which there are no good solutions, unfortunately I don’t think this is very helpful and could cause a lot of problems when there are false positives.
16 minutes ago
Comment deletedcrest 39 minutes ago