Improving AI models requires collecting accurate user feedback,which can be difficult. The article explores more into the importance of collecting human feedback and discusses the need for creating an organized database to effectively store and use this valuable input. We hope to continuously improve our large language models, ensuring they deliver greater performance and match user expectations more effectively.

Design feedback mechanism for LLM applications

Explore how we solved the catastrophic forgetting problem in LLMs by building an external knowledge system that mimics learning through context manipulation, without touching the model's parameters.

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