AI Tech Symposium - Panel Discussion: Designing Graph RAG Architecture

Join us for an insightful panel discussion on "Designing Graph RAG Architecture," where we will explore the innovative intersection of retrieval augmented generation (RAG) and graph data structures, delving into their significance, components, and applications in AI.
Discussion Highlights:
Understanding RAG and AI:
What is retrieval augmented generation (RAG)?
What are statistical AI, symbolic AI, and neurosymbolic AI systems?
What are the key components of a RAG system, and how does it work?
Why is RAG important, and what is the role of generative AI within it?
Pros, Cons, and Infrastructure:
What are the pros, cons, and limitations of RAG?
What kind of data and information technology infrastructure is required to enable RAG?
Which organizations are currently utilizing RAG?
Role of Graph Data Structures:
What is the role of graph data structures in RAG?
What benefits do graph structures provide overall?
How can we leverage the best of both graph data structures and RAG architecture to develop a Graph RAG system?
Semantic Technology and Explainable AI:
What is the function of semantic technology in developing Graph RAG architecture for production systems?
How does Graph RAG play a role in enabling explainable AI?