6.3 ML-enabled MSM
As noted earlier, one of the main objectives of MSM is to couple the physics at different scales using bridging algorithms that pass information between two scales, such as in QM/MM, MM/CG, CG/CM, and field-based methods discussed in section 5. However, the implementation of this methodology on parallel supercomputing HPC architectures is complicated and cumbersome. To address this significant limitation in implementation, we advocate for an ML-enabled integration or bridging of scales as a viable approach to develop the next generation of MSM methods to achieve maximal efficiency and flexibility in integrating scales.