Speaker
Abstract
LLMs are often like the know-it-all at a bar - they can quickly and confidently produce realistic sounding answers to just about any question - even if the answers are complete fabrications. But an LLM can be grounded in reality by combining it with a Knowledge Graph in order to prevent hallucinations, and to prevent unauthorized access to sensitive data.
This presentation will show how knowledge graphs can be combined with LLMs to:
- eliminate hallucinations
- improve accuracy
- use current information
- enforce security and privacy
- improve reliability and explainability
- simplify access to data
- simplify ingestion of semi
-structured data
- combine vector searching with graph traversal for context-based semantic searching
We will use a Jupyter notebook in a public Github repo for a working demo.
Sponsored session
Session Sponsored By
Neo4j, the Graph Database & Analytics company, helps organizations find hidden relationships
and patterns across billions of data connections deeply, easily and quickly.
QCon San Francisco 2023 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.
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