Always Retrieval Augment Your Large Language Models

Rationalizing the use of large language models (LLMs) in business applications requires a more reliable approach than relying solely on the model's black box output. Retrieval Augment Generation (RAG) offers a solution by leveraging a retrieval module to identify relevant documents from a vast database, and then passing those documents along with the user query to the LLM for generation. This setup enables the model to base its responses on vetted content that is controlled by the organization, reducing the risk of hallucinations and providing more accurate and reliable information. By combining generative AI with retrieval, LLMs can be turned into highly skilled domain experts that provide fast and trustworthy answers, making them a valuable tool in real-world products and applications.

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