Introduction to Retrieval Augmented Generation (RAG) and Implementation with Databricks

Dive into the world of Retrieval Augmented Generation (RAG) and its implementation using Databricks in this 28-minute video presentation. Gain a comprehensive understanding of why RAG is revolutionizing AI applications by incorporating external knowledge sources for enhanced context and accuracy. Explore the fundamental components, benefits, and practical steps for integrating RAG into AI projects. Through a combination of theoretical explanations and demonstrations, acquire actionable insights to elevate AI solutions with Databricks, making them more intelligent and responsive. Learn how to enhance AI capabilities through vector search, implement RAG effectively using Databricks, and develop strategies for leveraging external knowledge sources. Presented by Ina Koleva, Staff Product Manager at Databricks, this talk offers valuable resources for further exploration, including the LLM Compact Guide and the Big Book of MLOps. Connect with Databricks through various social media platforms to stay updated on the latest developments in AI and data science.

Introduction to Retrieval Augmented Generation (RAG) and Implementing with Databricks