This invention describes a computing system designed to improve how AI models, particularly large language models, perform. It works by using reinforcement learning algorithms to automatically pick the best settings for an AI model, based on how well the model completes a specific task. The system measures the AI's performance and then adjusts its settings to get better results.
Why it matters: The rapid growth in the scale and deployment of large language models since 2024 has made the automated optimization of their settings, as claimed, a more pressing and complex challenge.
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