Building LLM Applications with Retrieval-Augmented Generation: A Fireside Chat

Building LLMs with RAG: Design Patterns and Embedding Strategies

Join us for an engaging conversation about Large Language Models (LLMs) with a panel of industry leaders: Raja Iqbal (Chief Data Scientist, Data Science Dojo), Taimur Rashid (Chief Business Officer, Redis), Sam Partee (Principal Applied AI Engineer, Redis), and Daniel Svonava (CEO, Superlinked).

In this era where generative AI and LLMs are reshaping industries, businesses must be equipped to harness their potential fully. This discussion will focus on the common design patterns for LLM applications, especially the Retrieval-Augmented Generation (RAG) framework. The speakers will discuss various strategies for embedding knowledge into these models, using vector databases and knowledge graphs in fetching domain-specific data.

This discussion aims to not only inspire organizational leaders to reimagine their data strategies in the face of LLMs and generative AI but also to empower technical architects and engineers with practical insights and methodologies.