Mixture of Experts (MoE)

Mixture of Experts (MoE) is a machine learning architecture that dynamically selects a subset of models to make predictions based on the input data. This approach allows for efficient computation and can improve performance by leveraging specialized models for different tasks. In MoE, multiple 'expert' models are trained, but only a few are activated during inference, which helps manage resources and enhance scalability. Common use cases include natural language processing, computer vision, and other areas where diverse expertise can lead to better predictions and insights.