The hyperspecialized expert models proposed by DeepSeek differ from existing MoE approaches in their focus on creating experts that are highly specialized in specific tasks. While traditional MoE architectures break the model into smaller experts, DeepSeek's approach involves creating swarms of experts that excel in particular areas. This specialization allows each expert to focus on a specific aspect of the prediction task, leading to potentially higher accuracy and efficiency. By leveraging hyperspecialized experts, DeepSeek aims to overcome the limitations of traditional MoE architectures and improve the overall performance of the model.