# What is RLAIF? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Model Training  
> **Canonical Citation:** [https://spidits.com/ai-glossary/rlaif](https://spidits.com/ai-glossary/rlaif)

## Definition
Reinforcement Learning from AI Feedback (RLAIF) is a model alignment technique where human evaluators are replaced by an AI model (the judge) to generate preference labels for training, lowering alignment training costs.

## Architectural Mechanics & Deep Dive
RLAIF (Reinforcement Learning from AI Feedback) is an alignment methodology that replaces human annotators with advanced AI models to rank model outputs. By using a strong LLM guided by a safety constitution to score and label preference datasets, RLAIF accelerates the alignment process, reduces costs, and maintains high output alignment.

## Industry Applications & Real-World Use Cases
Rapid model alignment, safe LLM training, and synthetic preference databases

## Frequently Asked Questions

### How does RLAIF compare to RLHF?
RLAIF is much cheaper and faster to scale since AI judgments can be generated instantly in parallel, avoiding slow and expensive human labeling pipelines.

### What is constitutional alignment in RLAIF?
Using an AI model to evaluate outputs based on a constitutional set of guidelines, acting as the feedback mechanism to align the model.

## Related Terminology
- [rlhf](https://spidits.com/ai-glossary/rlhf)
- [alignment](https://spidits.com/ai-glossary/alignment)
- [constitutional-ai](https://spidits.com/ai-glossary/constitutional-ai)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*