Machine learning models for chemical applications such as predicting molecular and reaction properties are becoming not only increasingly popular, but also increasingly accurate, for example for quantummechanical properties, 1-3 biological effects, physicochemical properties, , reaction yields, or reaction rates and barriers. Also, promising developments in the field of retrosynthesis and forward reaction prediction, have been made.