Alignment Tuning And RAG: What You Should Know
Red Hat News, Wednesday, March 26th, 2025
Incorporating artificial intelligence (AI) into an organization isn't a matter of flipping a switch; it requires careful customization to suit specific business needs.
When adapting large language models (LLMs) for the enterprise, alignment tuning and retrieval-augmented generation (RAG) are two strategies that can be used separately or together to tune an AI model. While alignment tuning, a variation of fine tuning, focuses on shaping the model's responses and behavior, RAG relies on integrating external data into the model's workflow. Both approaches customize LLM behavior and output suited for a variety of different use cases and types of data. So, let's explore each method to help you determine the best fit for your needs.