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1 min read RAG Definition

RAG is hard. Let's learn it together.

RAG is hard. Let's learn it together.

Having spent a year immersed in generative tech news, it's obvious what sort of role post-training will play as businesses adopt new interfaces and data management systems.

I wanted to build a resource to collate the huge wave of information in the emerging space in a simple way. To that end, I hope a weekday email with a single definition of a different component of the Retrieval-augmented-generation (RAG) pipeline would be a valuable resource for those looking to stay informed about this rapidly evolving field.

RAG's importance in the growth of generative tools is straightforward. It's one of the emerging methods to reduce hallucinations and increase the accuracy of generative interfaces by grounding the responses of large language models (LLMs) in external data. 

Each day, subscribers will receive a concise, four-minute read focusing on a specific RAG concept. By breaking down these complex ideas into digestible chunks, we aim to make the world of RAG more accessible to beginners while also providing a useful refresher for experienced practitioners.

My goal is to foster a deeper understanding of RAG technologies and their potential applications in various industries. Whether you're a developer, business leader, or simply curious about the future of AI, this daily digest will help you build a comprehensive knowledge base, one concept at a time.

By subscribing to this email series, you'll gain insights into:

  1. The core components of RAG systems
  2. Advanced techniques for improving retrieval accuracy
  3. Methods for optimizing query processing and response generation
  4. Evaluation metrics and optimization strategies for RAG pipelines
  5. Emerging trends and innovations in the field

We believe that staying informed about these technologies is crucial as they continue to reshape how businesses interact with data and serve their customers. Join us on this journey of discovery and stay ahead of the curve in the exciting world of RAG.

Subscribe now to start receiving your daily dose of RAG wisdom, and let's navigate the future of AI-powered information retrieval together!

Published by:

Bryson Masse

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