The rapid evolution of AI and machine learning technologies brings forth the necessity for systems that can enhance accuracy and relevance by leveraging the latest information. This session offers a comprehensive tour of an end-to-end Retrieval Augmented Generation (RAG) system implemented on Databricks, designed to elevate AI applications to new heights. Attendees will explore the seamless integration of RAG into data workflows, transforming the way unstructured data is ingested, processed, and utilized to augment AI responses. Through practical demonstrations, this session will unveil how to set up efficient workflows for handling unstructured data, apply embedding models for data vectorization, and leverage foundational language models to achieve unprecedented AI performance.

Why Attend?

Innovative Integration: Learn to incorporate RAG systems into your AI applications, significantly improving their accuracy and relevance with the latest information.
- Gain practical knowledge on setting up workflows to ingest unstructured data, transforming it into actionable insights.

-Discover how embedding models and foundational language models can be applied to enhance your AI's understanding and output.

-Empower your team to allocate more time on strategic initiatives by simplifying complex data interactions through efficient data management practices.

Key Learnings and Takeaways:

-Master the art of setting up and automating workflows to process unstructured data efficiently.

-Learn the process of converting text data into vectors and storing them for easy retrieval, enhancing your model's accuracy.

-Understand how to serve embedding models, utilize foundational language models, and effectively chain these components to augment AI responses.

-Walk away with the knowledge to apply these techniques in real-world scenarios, boosting the performance and relevance of your AI applications.

Who Should Attend:

This session is crafted for a broad audience interested in advancing their AI and machine learning projects:

-Those looking to enhance their applications with the latest advancements in RAG systems and data processing.
Data Engineers and Scientists: Individuals interested in efficient data ingestion, processing, and vectorization techniques.

-Professionals seeking to understand how RAG systems can be integrated into products to improve user experience and application performance.

-Anyone exploring the frontiers of AI technology and its practical applications in handling and augmenting unstructured data.

-Curious minds eager to learn about cutting-edge AI technologies and how they're applied in real-world scenarios.