We have seen already that MLPs based on ab initio data allow us to reach time and length scales not achievable previously at this level of accuracy. However, models trained with NequIP cannot be parallelized across multiple GPUs, and therefore are limited in the system size that can be achieved. In this last section, we have applied the very recent Allegro architecture, which is based on NequIP but does not rely on message passing, and can therefore be parallelized across GPUs on a single compute node, as well as across multiple GPU nodes.