Bit rot is the degradation of the performance of a ML model over time. When a model is trained it is learning a set of assumptions about the "universe" and over

Bit rot is the degradation of the performance of a ML model over time. When a model is trained it is learning a set of assumptions about the "universe" and over time the universe changes which can invalidate some of those assumptions which degrades the models performance. For example you create a model to classify tweets by sentiment and then people start referring to your company as sick and phat which your model doesn't understand. The bigger challenge is that most models attempt to predict human behavior but humans have the ability to learn and so simply deploying the model changes the universe. For example your FICO score is an attempt to predict your credit default risk but over time people learn how to trivially manipulate their scores which degrades the ability to use FICO scores to predict default risk.