About this Event
Join us for part two of Vector search and Graph use cases in SurrealDB! Learn how you can leverage this functionality in your own projects through informative talks with practical examples.
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The meetup will highlight:
The power of knowledge graphs in providing structured and semantically rich context to LLMs, leading to more informed and coherent responses.
How vector embeddings, numerical representations of text that capture semantic meaning, enable semantic search within the knowledge graph, allowing the system to retrieve the most relevant information for a given query.
A comparative demonstrating the difference in LLM responses when using:
- A standard prompt referencing source material alone.
- A prompt augmented by the knowledge graph and vector embeddings.
Attendees will gain practical insights into:
- The process of querying a graph-based RAG system for question answering.
- How to leverage the combined capabilities of SurrealDB, a multi-model database.
- Graph Capabilities: Representing relationships between entities within the knowledge graph.
- Vector Capabilities: Enabling semantic search to pinpoint relevant information within the knowledge graph.
- How this approach, utilizing SurrealDB's graph and vector features, enhances LLM responses by providing contextually relevant information retrieved through the knowledge graph.
This meetup is ideal for individuals who attended Part 1 or possess a basic understanding of knowledge graph extraction and are eager to learn advanced techniques for improving LLM outputs using graph-based RAG systems.
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🗣️ Speaker opportunity - submit your talk!
Working on an interesting project that you would like to share with the community? Submit your talk here.
⏰ Date/time: December 10, 6:30 - 9:00PM
📍 Location: The Yard: Columbus Circle Coworking Office Space NYC
👉 New to SurrealDB? Learn more here.
Event Venue & Nearby Stays
The Yard: Columbus Circle Coworking Office Space NYC, 33 West 60th Street, New York, United States
USD 0.00
