In this talk, we will discuss the process of creating powerful Retrieval-Augmented Generation (RAG) solutions using Google's Gemini AI model and your own proprietary data. RAG combines the strengths of large language models with the ability to retrieve and incorporate specific information, resulting in more accurate and contextually relevant AI outputs.

You'll learn:

• The fundamentals of RAG and its advantages over traditional AI approaches

• How to prepare and format your custom data for optimal use with Gemini

• Techniques for fine-tuning Gemini on your dataset to create a specialized AI

• Best practices for integrating RAG solutions into your existing applications

• Strategies for improving response quality and maintaining data privacy