Tag
PGD-NO is a neural operator that precomputes geometry decomposition to achieve linear memory scalability, enabling high-fidelity physics simulations on meshes exceeding 10 million nodes and overcoming the single-node memory bottleneck.
This article discusses advancements in large-scale simulations of AI agents, potentially introducing new methods or frameworks for multi-agent environments.