Category:
Category:
Mixture-of-Experts (MoE)
Category:
Core AI & LLM Concepts
Definition
Model architecture where only specialized subsets of parameters activate per task.
Explanation
MoE models scale efficiently by activating only certain 'experts' depending on the input. This allows models to be larger and more capable without increasing inference cost proportionally. MoE is used in cutting-edge AI systems to balance performance and efficiency. Experts can specialize in coding, math, reasoning, writing, or other capabilities.
Technical Architecture
Input → Gating Network → Selected Experts → Aggregation → Output
Core Component
Expert networks, gating network, sparse activation, aggregation layers
Use Cases
General-purpose LLMs, coding models, enterprise assistants, multilingual systems
Pitfalls
Gating instability; expert collapse; training complexity
LLM Keywords
Mixture Of Experts, Moe LLM, Sparse Experts
Related Concepts
Related Frameworks
• Routing
• Model Selection
• Transformers
• MoE Architecture Map