Mixture of Experts
Published:
As Large Language Models (LLMs) continue to grow in size and complexity, a fundamental challenge emerges: how can we scale model capacity while maintaining computational efficiency? The traditional approach of simply adding more parameters to dense networks quickly becomes prohibitively expensive, both in terms of computational cost and memory requirements. This is where Mixture of Experts (MoE) architectures shine, offering an elegant solution that dramatically increases model capacity while keeping computational costs manageable.
