As reliable quantum chemistry data became available, these were initially used to augment the experimental data, and fitted using similar linear correlations . However in the last decade it has become practical to compute an enormous number of molecules and reactions using quantum chemistry , so much data that it can make sense to use much more complicated nonlinear correlations, a.k.a. "machine-learning (ML)", Fig. .