Content Moderation in LLMs

Summary: ChatGPT's content moderation happens in two phases: model training and reinforcement learning. During training, the model learns from a vast dataset. Reinforcement learning with human feedback fine-tunes the model's behavior, teaching it how to respond appropriately to various prompts, including harmful ones. Insights:

• Content moderation is integrated into LLMs like ChatGPT during the training and fine tuning process instead of filtering after.
• Two phases, initial training on large dataset and reinforcement learning with human feedback fine-tunes the model for better behavior.
• Instead of reacting to harmful prompts, the model is trained to not respond to such prompts in the first place. Proper Nouns:
• ChatGPT: A large language model developed by OpenAI.
• OpenAI: The company behind ChatGPT, focused on artificial intelligence research and deployment.

Research

• What are some of the ethical considerations surrounding the use of RLHF in training large language models?
• How can RLHF be improved to make LLMs more robust to adversarial attacks or attempts to bypass content moderation?
• What are the trade-offs between allowing more open user interaction vs tighter restrictions when building these models?