Hallucinations in generative AI models can be a significant issue for businesses integrating the technology into their operations. Retrieval Augmented Generation (RAG) is a technical approach that promises to eliminate these hallucinations by retrieving relevant documents to provide context for the generated information. While RAG can improve model accuracy and credibility, it also has limitations and challenges that vendors may overlook.
Keyword: Hallucinations, Generative AI models, Retrieval Augmented Generation, RAG, Model accuracy, Contextual information
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Last edited on: May 7, 2024 at 09:10 pm