We are super excited to organize an evening event on LLMs, Graph Databases, and RAG on Google Cloud Platform. Come and join us for this in-person meetup in Reston, VA. Pizza will be provided.
You will learn about RAG from two veteran speakers who have been presenting about it for the past year: Brian Snyder, Google and Sydney Beckett, Neo4j.
Talk #1: Augmenting and Grounding LLMs with Information Retrieval – Brian Snyder, Google
Grounding helps LLMs access additional information beyond their training data to improve responses. Explore Retrieval Augmented Generation (RAG), a method of enriching prompts with supporting data stored in vector databases. Discover how this approach improves response quality and context, reducing the necessity for model retraining.
Talk #2: Going Beyond Vectors – Sydney Beckett
Retrieval Augmented Generation (RAG) with vector embeddings are enormously powerful. But there are also limitations to vectors and general challenges to implementing RAG systems. In this talk, we’ll discuss some of those challenges and introduce using stored knowledge graphs to address some of them. We showcase how to integrate an LLM to query the newly-created knowledge graph with plain English questions. This will leverage Neo4j’s graph database along with GCP’s VertexAI.
