Generative artificial intelligence tools have become notorious for their tendency to fabricate information, a phenomenon known as AI hallucinations. To combat this issue, developers are turning to a novel approach called retrieval augmented generation (RAG), which aims to make AI-generated content more reliable by anchoring responses to verifiable sources. This process involves augmenting user prompts with information from a custom database, allowing the AI model to generate answers based on factual data. According to experts, RAG has the potential to significantly reduce AI hallucinations, but its effectiveness depends on the quality of the implementation and how one defines AI hallucinations in the first place. While RAG is not a silver bullet, it represents a promising step towards creating more trustworthy AI-generated content.
Taming the AI Beast
By giving the AI tool a narrow focus as well as quality information, the RAG-supplemented chatbot would be more adept than a general purpose chatbot at answering questions about WIRED and relevant topics.
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