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Generative AI: Retrieval Augmented Generation (RAG): Introduction to the Ecosystem
Retrieval Augmented Generation (RAG) allows a researcher to constrain a large language model to use specific source files, essentially providing it with a curated knowledge base to use when answering questions. This allows the service to answer questions based on the knowledge contained in the source files, and to cite its source for its answer.
Objectives: You will get an overview of the affordances of RAG and the processes necessary to build a RAG service based on your own text sources. You will also see demonstartions of RAG services based on some small-scale text collections, with introductions to the tools used to build and run them.
- Date:
- Thursday, November 7, 2024
- Time:
- 2:00 PM - 3:30 PM
- Audience:
- External Library Users Faculty Graduate Students
- Categories:
- Digital Ecosystems
Registration has closed.