Gretel introduces Reinforcement Learning from Privacy Feedback (RLPF), a method that can be used to align large language models (LLMs) to improve generative quality while also making them more privacy-preserving. Language models leaking proprietary data or custom prompts is a problem that's currently plaguing many generative AI applications. We propose RLPF to mitigate some of these issues. We also suggest future directions to reduce bias, discrimination, and other harmful characteristics that might exist in today’s language models.
