Before revision:  Such systems have typically been evaluated in artificial settings: for example, classifying randomly permuted images. A key limitation of these settings is the unnatural construct of discrete, sharply demarcated tasks that are solved in sequence .
After revision:  An important open problem for continual learning is a large-scale benchmark that enables realistic evaluation of algorithms .