This session explores contextual Generative AI solutions by leveraging retrieval-augmented generation (RAG) methodology. Attendees will gain an understanding of RAG architecture and the pivotal role of contextual information.
The session will cover the RAG framework and the implications of contextual cues in enhancing generative AI outcomes. Through practical demonstrations in Azure Databricks, participants will dive into the nuances of data preparation for generative AI applications, seamlessly integrating this preparatory phase with implementing an RAG architecture. In addition, the session dives into advanced concepts surrounding vectors and vector databases, improving their relevance in augmenting generative AI capabilities.

In essence, this session provides attendees with the knowledge and tools necessary to navigate contextual generative AI, empowering them to leverage the transformative potential of RAG methodology in diverse applications.