New AI Math Technique SEMQ Cuts Hardware Demands

Researchers propose SEMQ, an abstraction layer that separates semantics from embeddings, potentially reducing AI hardware requirements. The method could lower computational costs for large models. Early tests show promise but real-world impact remains unproven.