Graph Exchange: Rishi Puri, GNNs & LLMs in PyG

This talk will cover how Graph Neural Networks can be used to enhance LLMs using PyG to improve accuracy for RAG like tasks across any kind of data domain. This will include examples on real world data. We will also cover how LLMs can be used to enhance GNNs for graph machine learning tasks. ​Rishi Puri graduated from UC Berkeley and is a lead engineer for the Deep Learning FrameWork PyG at NVIDIA. He is also a core contributor to the open source PyG framework and community. His main focus is researching how to combine state of the art graph and language modeling techniques. He enjoys teaching about this work at Stanford, conferences, webinars, and through the PyG Slack and LinkedIn communities.