Risk mitigation tools with RLHF and RAG

This section will take us from prompt design to advanced prompt engineering with some mitigation tools to get us started in this domain:

• RLHF

  You can organize Reinforcement Learning from Human Feedback (RLHF) beyond the process described in this section. The term may seem daunting, but you can organize this with a group of key users who can provide feedback on the responses of your system. Then, you can adapt the system accordingly and modify hyperparameters, parameters, datasets, and any aspect of the project before fine-tuning the model again or implementing RAG, for example.

• RAG

  This section implements a method of Retrieval-Augmented Generation (RAG) through a knowledge base. There are several possible approaches, such as the ones we implemented in Chapter 7, The Generative AI Revolution with ChatGPT, and Chapter 11, Leveraging LLM Embeddings as an Alternative to Fine-Tuning. A customized knowledge base...