# ChatGPT ChatGPT-4 incorporates a training method called “Reinforcement Learning from Human Feedback (RLHF)”. This method includes human demonstration of how the model should respond and ranking the responses from best to worst. In practice, human trainers play as both sides of the conversation, i.e., the user and the AI, and provides a sample conversation. When the human trainer plays the role of the chatbot, the model is asked to generate some suggestions to assist the trainer in providing the responses; then the trainer scores and ranks the responses and gives the better ones back to the model, fine-tuning and continuously iterating the model through the reward model mentioned above. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://yuriai.gitbook.io/yuriai-guidebook/background/chatgpt.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.