(2) Developing novel training algorithms, which leverage multilevel and domain-decomposition-based approaches and utilize data and model parallelism.
(3) Hybridizing SciML surrogates with state-of-the-art numerical solution methods, which will be achieved by developing AI-equipped nonlinear field-split and domain-decomposition-based preconditioning strategies.