TL;DR
A machine learning architecture that boosts model capacity by routing processing tasks to smaller, specialized subnetworks rather than activating the entire network.
A Mixture of Experts architecture utilizes sparse conditional computation to improve both training and inference efficiency. During a pass, a learned gating network acts as a router, forwarding each input token to only a select few specialized subnetworks, or experts, instead of running a monolithic dense model. This specialized routing allows deep learning networks to scale to trillions of parameters while keeping computational costs and latency relatively stable.
Why this matters for your business
Its implementation allows AI developers to build incredibly capable, highly scaled systems without a linear explosion in required computing hardware. This makes the delivery of state-of-the-art reasoning capabilities much more accessible and cost-effective for enterprise deployment.
