Explore the Retrieval-Augmented Generation (RAG) framework and its impact on Large Language Model (LLM) applications in this informative webinar. Delve into common design patterns for LLM applications, strategies for embedding knowledge into models, and the use of vector databases and knowledge graphs for domain-specific data retrieval. Gain insights into the challenges of foundation models, business implications, and prioritization strategies. Learn how to harness the potential of generative AI and LLMs to reshape industries and reimagine data strategies. Discover practical insights and methodologies for technical architects and engineers, covering topics such as vector databases, emerging technologies, and the challenges of implementing foundation models.
Supercharge Your LLM Applications with RAG
Overview
Syllabus
– Introduction
– What is RAG
– Vector databases & emerging technology
– Challenges of foundation models
– Prioritising and business implications
– QnA
Taught by
Data Science Dojo
