Second, it also eliminates the process of PES reweighing to uncover the original energy landscape by running unbiased MD simulations. Most importantly, deep neural architectures learn the clustering of metastable states from short MD trajectories which could be further processed to extract starting conformations for WE simulations. Both methods involved in the DeepWEST approach add no statistical bias to the system, and thereby, kinetics and thermodynamics obtained from this approach are exact. However, a longer MD simulation time may be required to discretize metastable states as the system size increases to provide statistically relevant starting conformations for WE simulations. Recent improvements in the WE method have been made to achieve faster kinetics. An even more accurate and faster kinetics and thermodynamic sampling could be achieved if DeepWEST is combined with these improvements in WE.