RAG Has a Dirty Little Secret: Here's How to Clean It Up and Get GenAI Right

Enterprises have worked for decades to solve the problem of providing users with the right information at the right time. Standardizing on a few APIs to access information irrespective of their physical location (on-prem or cloud object store, NAS, etc.) and their file format (e.g., Parquet files, C...

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Bibliographic Details
Published inDatabase Trends and Applications Vol. 40; no. 2; pp. 25 - 26
Main Author Doerpmund, Jens
Format Trade Publication Article
LanguageEnglish
Published Chatham Information Today, Inc 01.02.2025
Subjects
Access control
Documents
End users
Generative artificial intelligence
Large language models
Semantics
Online AccessGet full text
ISSN1547-9897

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Summary:Enterprises have worked for decades to solve the problem of providing users with the right information at the right time. Standardizing on a few APIs to access information irrespective of their physical location (on-prem or cloud object store, NAS, etc.) and their file format (e.g., Parquet files, CSV files, or database tables) significantly simplifies data access for RAG solutions. Taking these steps simplifies RAG, protects against leaking sensitive data into the LLM and to GenAl end users, drives operational efficiency and environmental and business sustainability, and helps ensure that the information users ultimately derive from GenAI is very high quality.
ISSN:1547-9897