MARKET RESEARCH: RETRIEVAL AUGMENTED GENERATION
Gartner report on RAG and LLMs
Get Gartner's latest report and learn what retrieval augmented generation (RAG) is, and how to use it to minimize generative AI hallucinations.
Understand how RAG leverages vector databases and enterprise data to ground LLMs.
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Learn from the experts about:
- How RAG minimizes GenAI hallucinations
- How to use vector databases and enterprise data in RAG
- Pitfalls to avoid in implementing RAG
- The prompt/response structure of generative AI solutions
Vital market research and analysis
Enterprises building GenAI applications that incorporate large language models are experiencing problems with hallucinations, grounding, poor user experience and inappropriate data stores for use with LLMs. Software engineering leaders must address these issues to ensure successful use of GenAI.
Gartner, Early Lessons in Building LLM-Based Generative AI Solutions, 6 August 2024. This Gartner paper was written By Van Baker, Haritha Khandabattu, Philip Walsh. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
