Understanding Mixture of Experts (MoE) Through Academic Administration: A Conceptual Analogy

This technical paper presents a novel conceptual framework for understanding the Mixture of Experts (MoE) architecture in Large Language Models (LLMs) through a comprehensive academic administration analogy. By mapping routers, experts, and gating networks to university offices and specialist faculty, this bilingual (English/Turkish) manuscript bridges the gap between complex deep learning mechanisms and accessible educational concepts. It aims to serve as a foundational resource for independent AI researchers and educators globally.