Microsoft AI’s latest innovation, LazyGraphRAG, aims to change the narrative. By eliminating the need for costly and time-intensive prior summarization of source data, LazyGraphRAG sets a new benchmark for efficiency in graph-enabled RAG systems.
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In ensuring safety and quality of training language models, Reinforcement Learning from Human Feedback (RLHF) plays a crucial role. Recently,
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Introduction Artificial Intelligence (AI) has been growing exponentially during the recent years, giving the rise to the large language models
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Retrieval-augmented generation (RAG) is a cutting-edge technique in artificial intelligence that combines the strengths of retrieval-based approaches with generative models.
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Retrieval-Augmented Generation (RAG) is an innovative technology that integrates externally retrieved information with pre-existing model knowledge to enhance the accuracy
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