Retrieval Augmented Generation (RAG) in 2024: Powering the Future of LLM

In the ever-evolving landscape of natural language processing (NLP), the concept of Retrieval Augmented Generation (RAG) has emerged as a transformative force, poised to reshape the future of large language models (LLMs). As we approach the year 2024, this innovative approach has gained significant traction, capturing the attention of industry leaders, researchers, and the broader […]