When it comes to enterprise use cases, getting actual value from an LLM usually involves feeding it custom data. There are many methods for equipping an LLM with data that don’t involve doing custom model training. In this session, we will demonstrate two of the most common methods: context windows and retrieval augmented generation (RAG). You’ll see the impact that adding custom data has to LLM results and how these methods are approachable for not just data scientists but a wide range of information workers.
Agenda:

* Introduction
* Data Augmentation vs. Custom Training
* What is a Context Window?
* Context Window demo
* What is Retrieval Augmented Generation (RAG)?
* RAG demo
* Q&A

STL AI Group

Bill Stanley

payal135133

Patricia Johnson

Angela

Gary Mastin

Kathy K

cparker5222

Purvag Patel

Chris O'Neill

Stephanie Fraser

John Fernau

praveen4936

Jessica Brock

Vince Toon

Tyler Mason

landonsmoore57

Shawn Smith

Darrick Latta

Todd T. Hunt

Fortunato Ferrer

Enhancing LLMs: Context Windows and RAG 

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