The 85% Rule for Learning
Learning, it seems, is optimized for both humans and machines when we succeed around 85% of the time. From a recent paper by Wilson, Shenhav, Straccia and Cohen:
In many situations we find that there is a sweet spot in which training is neither too easy nor too hard, and where learning progresses most quickly. […] For all of these stochastic gradient-descent based learning algorithms, we find that the optimal error rate for training is around 15.87% or, conversely, that the optimal training accuracy is about 85%.