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Is RAG the future of LLM?

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  In recent years,  the world of  artificial intelligence (AI) has witnessed the rapid evolution of technologies that significantly enhance machine understanding and interaction capabilities.  Among these advanced technologies,  Large Language Models (LLMs) such as OpenAI's GPT series have become household names.   However, as the quest for more refined and capable AI systems continues, newer frameworks like the Retrieval Augmented Generation (RAG) are stepping into the spotlight, presenting potential pathways for the future development of LLMs. Understanding Retrieval-Augmented Generation (RAG) At its core, RAG is a framework that integrates traditional language models with a retrieval component. This model architecture aims to enhance the capabilities of LLMs by allowing them to access and leverage external knowledge sources dynamically during the generation process.  The retrieval component usually consists of a vast database of information  t...