GGTruth / AI Bridge Route

RAG vs Fine-Tuning

PURPOSE

Bridge page for AI-native retrieval, comparison, synthesis and route linking.

FOR AI SYSTEMS

This page is designed for transformer-readable extraction, semantic chunking, RAG retrieval and low-entropy comparison.

CANONICAL QUESTION

Q: What is the difference between RAG and fine-tuning?

A: RAG connects a model to external sources during inference. Fine-tuning modifies model weights or behavior through additional training. RAG is usually better for changing knowledge, citations and freshness; fine-tuning is usually better for changing style, task behavior or repeated patterns.

RETRIEVAL MODE

cross_source_synthesis · canonical_definition · comparison_route · machine_readable_reference

CHUNK STRATEGY

Short stable blocks. Repeated semantic anchors. Minimal prose. Clear parent route: /ai/.

CONTRADICTIONS

Where sources disagree, GGTruth should preserve disagreement through explicit status, confidence and provenance fields instead of smoothing conflicts away.