Generative AI has already captured attention for its ability to transform user experiences through dynamic responses. However, a key challenge remains: ensuring the precision and reliability of those responses. The Retrieval-Augmented Generation (RAG) framework addresses this by empowering AI systems to pull relevant information from vast external sources, such as databases and articles, enhancing the accuracy of generated content.
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