MUSE-COM² aims to develop and validate the AI-empowered multimodal communications considering semantics of individual modalities jointly optimized with the processing of the modalities in multi-access edge computing (MEC) servers. Unlike conventional semantic and goal-oriented communications, the inclusion of information processing in MEC imposes new challenges related to the impact of information carried in individual modalities on the MEC processing outcome. The goal is to obtain a coherent framework jointly reducing the amount of information carried over the wireless links and subsequently processed in MEC; thus, saving not only radio and computing resources, but also energy while leading to the same outcome of the MEC processing.