Mixture of Experts (MoE) is a deep learning technique that combines multiple models to make predictions. It was originally proposed in the 1990s but has gained popularity recently due to advancements in computing power and model architecture. MoE models consist of two main components: an expert network and a router. The router selects which experts to use for each input, while the experts themselves are responsible for making predictions. --- Why it matters: This matters because MoE can improve the performance of neural networks by allowing them to specialize in specific tasks, leading to better accuracy on complex problems. Source: https://huggingface.co/blog/moe