RAG Model Evaluation with Azure AI and Gretel Navigator

The text discusses how Retrieval-Augmented Generation (RAG) models, which combine retrieval-based and generative AI approaches, can be evaluated using Gretel Navigator to generate diverse and high-quality evaluation datasets of question-truth pairs. This is important because the effectiveness of RAG models depends on the quality and diversity of their training data. Azure Copilot offers a solution for evaluating these models, but creating the right evaluation datasets can be challenging. Gretel Navigator streamlines this process by generating relevant question-answer pairs from larger knowledge datasets, tailored to specific needs such as user expertise level or topics of interest. This approach ensures that synthetic datasets are broad in scope and deeply aligned with real-world use cases.

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