Ruslan Magana Vsevolodovna • 6/3/2026

From Mixture of Experts to Mixture of Agents: Sparse Routing Is Escaping the Model

This article explains the Mixture of Experts (MoE) architectural trick used in many frontier AI models, which decouples total parameter count from per-token compute cost via sparse routing. It details how a gating network selects only a few expert networks per token, allowing large knowledge capacity at small inference cost. The piece then speculates on extending this sparsity principle beyond neural networks to multi-agent systems, warning of collapse if balance drops below 45%. It is a technical deep dive into AI model design and future trends, relevant to IT/technology.

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#Neural Networks #Transformers #Mixture Of Experts