Name: Enhancing LLMs: Context Windows and RAG
Start: 2025-06-12T12:00:00-05:00
End: 2025-06-12T13:30:00-05:00
Location: WWT

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

Bill Stanley

STL AI Group

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Greg has over 25 years experience in the technology field and 20 years experience with cloud technology, particularly in the Google ecosystem. His expertise includes both cloud infrastructure and development and he has helped enterprises deploy a wide array of solutions to the cloud. For the past 5 years, Greg has been focused on designing AI solutions for the enterprise with a focus on large language models (LLMs), text classification, and computer vision.

Greg Heier

Enhancing LLMs: Context Windows and RAG 

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Enhancing LLMs: Context Windows and RAG

STL AI Group

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