Mixture-of-experts
Mixture-of-experts (MoE) is a machine learning technique that involves the use of several expert models to solve a problem. Each expert specializes in a specific aspect of a task, and their outputs are combined by a gating mechanism that decides which expert should be used for each input. This approach helps in efficiently utilizing expert models in large networks, especially for tasks with diverse input distributions like natural language processing.