MBEs share characteristics with local descriptors but provide several key advantages. First, n-body interactions are more efficiently treated on a molecular basis instead of an atomic basis. Second, errors associated with MBE truncation can be corrected using a variety of schemes. For example, using long-range physical models to capture induction and dispersion effects. Alternatively, one could use ONIOM-style approaches such as molecule-in-molecules (MIM) and molecular tailoring approach (MTA) where low-cost calculations on the whole structure (i.e., supersystem) are used to capture all long-range interactions. Third, these n-body contributions can be observed in relatively small clusters. Local descriptors require data on large clusters to achieve similar levels of size transferability. This opens the door for many-body GDML (mbGDML) force fields trained on high levels of theory that scale poorly with system size, such as CCSD(T). In addition, mbGDML naturally incorporates intramolecular/monomer flexibility, which is extremely challenging for analytical potentials.