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Core Concepts

Introduction to RAG

RAG, or Retrieval-Augmented Generation, is a methodology that enhances machine learning models by combining generative and retrieval-based aspects.

Good embeddings are vital for the successful execution of RAG applications. They serve as the basis for retrieving contextually relevant information.

Vectorboard simplifies the complex task of optimizing these embeddings by providing a structured framework for running experiments.