In the era of generative AI, where machines are not just learning from data but generating human-like text, images, video, and more, retrieval-augmented…
In the era of generative AI, where machines are not just learning from data but generating human-like text, images, video, and more, retrieval-augmented generation (RAG) stands out as a groundbreaking approach. A RAG workflow builds on large language models (LLMs), which can understand queries and generate responses. However, LLMs have limitations, including training complexity and a lack of…
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Source:: NVIDIA