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Naver Optimizes AI Tab with Lightweight MoE Model, Doubling Speed and Reducing Hallucinations

Naver has integrated a newly optimized, lightweight Mixture-of-Experts (MoE) model into its 'AI Tab' service, significantly improving response times and reducing hallucination rates. This new model, a product-native LLM based on HyperCLOVA X, achieves double the speed and a 30 percentage point reduction in hallucination rates, partly thanks to expanded reinforcement learning and a clarity reinforcement learning technique. The division-of-labor SLM (small language model) structure also cuts operational equipment costs by up to three times.

Why it matters

This optimization enhances the efficiency and reliability of Naver's AI search services, demonstrating how specialized, lightweight models and advanced reinforcement learning can improve user experience and reduce operational costs for large-scale AI applications.

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