The Popular Way to Build Trusted Generative AI? RAG - SPONSOR CONTENT FROM AWS

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The Popular Way to Build Trusted Generative AI? RAG - SPONSOR CONTENT FROM AWS
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Sponsor content from AWS.

, from boosting operational efficiencies to reinventing their businesses. But as they begin to adopt this transformative technology, they’re encountering a common challenge—delivering accurate results.

On their own, LLMs may provide results that are inaccurate or too general to be helpful. To truly build trust among customers and other users of generative AI applications, businesses need to ensure accurate, up-to-date, personalized responses. And that means customizing their LLMs. Generative AI’s output is only as good as its data, so choosing credible sources is vital to improving responses. RAG augments LLMs by retrieving and applying data and insights from the organization’s data stores as well as trustworthy external sources of truth to deliver more accurate results. Even with a model trained on old data, RAG can update it with access to current, near-real-time information.

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