HPE Developer Munch & Learn: Enhancing NLP with Retrieval-Augmented Generation: A Practical Demonstration

In the evolving landscape of Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG) stands out as a powerful technique that enhances the NLP application by incorporating relevant external information. This presentation delves into the fundamentals and applications of RAG, providing a comprehensive overview of how it integrates retrieval mechanisms with generative capabilities to produce more accurate and contextually aware responses.

Following the theoretical overview, we will transition into a live demonstration showcasing the practical usage of RAG. This hands-on demo will illustrate the process of augmenting a generative model with external knowledge sources, showcasing how RAG improves the relevance and quality of generated outputs in real-time applications.