START BUILDING YOUR GENERATIVE AI SOLUTION
Constructing a compelling AI demo application that functions intermittently can be straightforward. However, to transition to a production stage, continuous iterations and enhancements to your LLM application’s performance are inevitable.
The three most common techniques for improving your GenAI application are
- prompt engineering: Creating specialized prompt to guide LLM behavior,
- retrieval augmented generation (RAG): Combining an LLM with external data,
- fine-tuning: Adapting a pre-trained LLM to specific datasets or domains
Retrieval-Augmented Generation (RAG) is an approach that enhances the capabilities of LLMs for specific domains or an organization’s internal knowledge base, without requiring model retraining.