Mixture of Experts: The Architecture Behind Efficient AI Scaling

Mixture of Experts (MoE) divides a model into specialized subnetworks, activating only a fraction of parameters per input to reduce compute costs. This sparse activation enables models like Mixtral and GPT-4o to scale to trillions of parameters while keeping inference efficient. Key challenges include load balancing and infrastructure complexity, but MoE is now a production standard for large language models.