Where the training of machine learning models is concerned, there’s always a risk of overfitting — or corresponding to closely — to a particular set of data. In point of fact, it’s not infeasible that popular machine learning benchmarks like the Arcade Learning Environment encourage overfitting, in that they have a low emphasis on generalization.