rlaif

**RLAIF** (Reinforcement Learning from AI Feedback) is the **technique of using AI models (instead of humans) to provide the preference feedback for RLHF** — a separate AI model evaluates and compares outputs, providing preference labels at scale without human annotators. **RLAIF Pipeline** - **AI Evaluator**: A separate (often larger) AI model rates or compares model outputs according to specified criteria. - **Criteria**: The AI evaluator is prompted with rubrics for helpfulness, harmlessness, accuracy, etc. - **Scale**: AI feedback can label millions of comparisons — far beyond human annotation capacity. - **Self-Improvement**: The same model can sometimes evaluate its own outputs (constitutional AI pattern). **Why It Matters** - **Cost**: AI feedback is orders of magnitude cheaper than human feedback. - **Scale**: Enables RLHF-style training at scale that would be infeasible with human annotators alone. - **Quality**: RLAIF can achieve comparable quality to RLHF for many tasks — AI judges correlate well with human preferences. **RLAIF** is **AI teaching AI** — using AI-generated preferences instead of human preferences for scalable, cost-effective alignment.