Dynamic Routing

Dynamic routing is a technique that efficiently allocates computational resources by selectively routing data or tasks to specialized processing units, thereby improving efficiency and performance in various applications. Current research focuses on developing adaptive routing algorithms, often employing Mixture-of-Experts (MoE) models and reinforcement learning, to optimize resource allocation in large language models, autonomous systems, and network traffic management. These advancements are significant because they enable the scaling of complex systems while mitigating computational costs and improving performance, with applications ranging from speech recognition and natural language processing to autonomous driving and satellite communication.