Mixture of Experts (MoE) is a concept in artificial intelligence that can best be understood as a team of specialists.
In this approach, a complex task is divided among multiple smaller, specialized models – the so-called “experts” – instead of using a single large model for everything. A central “gatekeeper” or “router” decides which expert is best suited for a particular subtask.
This allows the system to work more efficiently and precisely, as each expert can focus on their area of specialization.
In practice, this means that an MoE model could, for example, have an expert for grammar, one for vocabulary, and one for context in text processing. The gatekeeper would then select the appropriate expert depending on the requirement.
This approach has the advantage of using computational resources more efficiently and often produces better results than a single, all-encompassing model. MoE is increasingly being used in large language models and other AI applications to enhance their performance and efficiency.