Hello,

I hope you are doing well. Happy 4th of July.

I am thrilled to tell you that I am writing a new book "A Simple Guide to Retrieval Augmented Generation" with Manning Publications and the first three chapters are now available through the Manning Early Access Program (MEAP)

Today is the last day of the Launch Discount - As a token of appreciation for your support, I’m offering a 50% discount till 4th of July, 2024. Use code mlkimothi at checkout.

Get your copy now! Go to this link -> https://mng.bz/EZor

Why this book?

Advancements in Large Language Models (LLMs) have captured the imagination of the world. With the release of ChatGPT by OpenAI, in November, 2022, Artificial Intelligence has become a commonly known term. Business Leaders, Software Developers and Entrepreneurs are in hot pursuit of using AI to their advantage. With the enormous capability the LLMs possess, they come with their own set of challenges. As the world became aware of the magical text generation ability of these LLMs, it also became aware of their “Hallucinations” – The propensity of LLMs to generate incorrect information with confidence. The questions around reliability and trust began to emerge rapidly.

To address these issues, researchers and practitioners have come up with a novel technique of Retrieval Augmented Generation (RAG). In their seminal paper, “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks”, Lewis et al introduced the concept to enhance the memory of the LLMs. RAG is a relatively new concept. While popular in research, in the applied world, there is a learning curve required of the practitioners. In the current scenario, individuals have to rely on scattered information on the internet.

This book is a foundational guide for individuals looking to explore Retrieval Augmented Generation. It offers a gentle, yet comprehensive introduction to the concept along with practical insights helpful in leveraging RAG to their advantage. It delves into creating RAG pipelines using Python, LangChain, OpenAI and the Transformers library from HuggingFace to lay the foundations for building RAG applications. Readers will get an understanding of the intricacies of RAG and a pathway to advanced techniques for further exploration.

What you'll learn?

This book is for technology professionals who want to get introduced to the concept of Retrieval Augmented Generation and build LLM based apps. It will prove to be a handy book for beginners as well as experienced professionals. You'll also get an opportunity to code along in python but the book is intended for non-coders as well. From introducing the technique to building RAG pipelines in production, in 9 chapters the book covers the following -

Chapter 1 - Large Language Models and the Need for Retrieval Augmented Generation [First draft Released]
Chapter 2 - RAG-enabled systems and their design [First draft Released]
Chapter 3 - Indexing Pipeline : Creating a knowledge base for RAG based applications [First draft Released]
Chapter 4 - Generation Pipeline: Real time interaction for contextual responses
Chapter 5 - RAG Evaluation : Checking accuracy, relevance and faithfulness
Chapter 6 - Evolving RAGOps Stack : Technologies that make RAG possible
Chapter 7 - Progression of RAG systems : Naive to Advanced to Modular
Chapter 8 - Nuances : Comparison with fine-tuning, multimodal and agentic RAG
Chapter 9 - Cutting Edge : Best practices and further exploration

Why join MEAP?

By joining the Manning Early Access Program, you'll get:

Immediate access to the book's current draft and all future updates
A chance to provide feedback and shape the final content
Exclusive discounts and early-bird offers

Special offer for early supporters

As a token of appreciation for your support, I’m offering a 50% discount till 4th of July, 2024. Use code mlkimothi at checkout.
https://mng.bz/EZor

Thank you for your continuous support. I hope you find this book as exciting and informative as I have found writing it.

If you have any questions or comments, please feel free to reach out to me by replying to this email or on any other social channels.

Cheers,

Abhinav Kimothi

A Simple Guide to Retrieval Augmented Generation

https://linktr.ee/abhinavkimothi

https://mng.bz/EZor

PS - A first chapter summary of the book is also available on YouTube - https://youtu.be/R9E2WQhNz-0?si=Fl43m3vhg1gnSJ7M

0 comments

All Chapters Released : A Simple Guide to Retrieval Augmented Generation

New Gen AI Essential: Retrieval Augmented Generation in 80 Questions

Webinar Recording : Introduction to RAG

RAG Evaluations : Chapter 5 released

The Power of Embeddings : Keeping Context Alive

See all posts from Abhinav Kimothi