How AI Learns to Be Helpful and Safe: The Role of Human Feedback
This article explains how AI models go from being powerful but
💡
Why it matters
RLHF is a critical technique for making powerful AI models behave in a helpful and responsible manner, which is essential for their safe deployment and public acceptance.
Key Points
- 1Raw AI models can exhibit undesirable behaviors like toxicity and hallucination without proper training
- 2RLHF teaches the model to do more of what humans prefer by rewarding human-approved answers
- 3RLHF builds on top of a capable base model, rather than creating a model from scratch
- 4Human raters evaluate multiple model-generated answers and provide feedback to train a reward model
Details
The article explains that powerful AI models fresh out of pretraining can exhibit undesirable behaviors like producing toxic content, arguing with users, or ignoring instructions. To address this, companies realized they needed to bend the models toward being helpful, harmless, and honest (the
Like
Save
Cached
Comments
No comments yet
Be the first to comment