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The claim establishes that live user behavior—including switching and preference signals—is fed back into ongoing model training, meaning user interactions actively shape the routing system.
Users' model-switching behavior, response preferences, and correctness signals are used as training data for the router on an ongoing basis.
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"The router is continuously trained on real signals, including when users switch models, preference rates for responses, and measured correctness, improving over time.— Excerpt from OpenAI's OpenAI GPT-5 System Card
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The claim establishes that live user behavior—including switching and preference signals—is fed back into ongoing model training, meaning user interactions actively shape the routing system.
Users' model-switching behavior, response preferences, and correctness signals are used as training data for the router on an ongoing basis.
ConductAtlas has identified this type of provision across 215 platforms. See the full comparison.
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