What is Retrieval Augmented Generation (RAG)?
What is Retrieval Augmented Generation (RAG)?
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Retrieval Augmented Generation is a pipeline framework that retrieves information via an external discovery system, enhancing the knowledge retrieval process for large language models.
Generative AI and large language models (LLMs) are emerging as some of today’s most transformative workplace technologies – however, many solutions struggle with knowledge retrieval. Retrieval Augmented Generation addresses this issue by separating the knowledge retrieval from the generation process.
Discover what it takes to make RAG work and how it unlocks the full potential of generative AI in this two-pager by Glean.
We respect your privacy, by clicking "Download Your Copy" you agree to having your details passed onto the sponsor who may promote similar products and services related to your area of interest subject to their privacy policy. You have the right to object. In addition, you will receive our e-newsletter, including information on related online learning opportunities. For further information on how we process and monitor your personal data, and information about your privacy and opt-out rights, click here. Download PDF Attachment
