ADVANTAGES AND DISADVANTAGES OF RETRIEVAL AUGMENT-ED GENERATION (RAG) IN GENERATIVE AI

Abstract

In this study, the Retrieval-Augmented Generation (RAG) technology, which is an important devel-opment in the field of artificial intelligence, was examined and its performance was evaluated based on its models. RAG systems are a new generation technology that helps overcome the limited knowledge of traditional large language models (LLMs), allowing them to use the most up-to-date information and generate more accurate content. The study addresses the basic working mechanism, principles, benefits and technical challenges of RAG technology. Research findings show that RAG systems increase information reliability, reduce the formation of fake findings generated by artificial intelligence, and provide quality results in sectoral applications. However, significant disadvantages such as system complexity, problems arising from poor quality data and ethical concerns have also been identified.

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