Getting started with Retrieval-Augmented Generation (RAG): Boosting Your LLM Experience

Sumit Jaiswal (~justjais)




Unlock the Power of Retrieval-Augmented Generation (RAG) to Revolutionize Your Language Learning Models (LLMs)

Are you ready to take your language learning models to the next level? Do you want to generate high-quality text that's tailored to specific contexts and conversations? In this presentation, I'll introduce you to Retrieval-Augmented Generation (RAG), a powerful technique for boosting your LLM capabilities.

Presentation Highlights:

  • An introduction to RAG and its applications in NLP
  • Hands-on experience with RAG for generating high-quality text
  • A live chatbot demo showcasing how RAG can be used to create intelligent conversational interfaces that understand context and generate relevant responses


  • A comprehensive understanding of RAG's capabilities and limitations
  • Hands-on experience with RAG for generating high-quality text
  • Insights on how to integrate RAG with popular AI libraries and frameworks
  • Inspiration for using RAG in your own LLM projects
  • A deeper understanding of how RAG can be used to create innovative chatbots that understand context and generate relevant responses

Who Should Attend:

  • NLP enthusiasts
  • Researchers working with language learning models
  • Anyone interested in exploring the potential of RAG for generating high-quality text and creating intelligent conversational interfaces.


Here are some suggested prerequisites for the talk:

  1. Basic knowledge of NLP: Attendees should have a basic understanding of natural language processing concepts, such as text representation, tokenization, and sentiment analysis.
  2. Familiarity with LLMs: It would be helpful if attendees are familiar with the basics of language learning models (LLMs), including their applications in chatbots, voice assistants, and other areas where language understanding is crucial.


  1. Attendees will have a basic understanding of programming concepts (e.g., Python).
  2. Attendees will have a general understanding of NLP and LLMs.

By having these prerequisites in mind, audience will be able to effectively engage and understand the crux of the discussion.

Speaker Info:

With over a decade of experience weaving my way through the intricate web of technological advancements, I, Sumit Jaiswal, have journeyed from the depths of device drivers to the thrilling heights of AI and machine learning. I am a open-source enthusiast and enjoy experimenting with different open-source technologies. Currently residing in Noida, I've previously lived in Bangalore for more than a decade and fondly miss the city's weather and its Biryani. I am a adventurous soul, who loves traveling and engaging in discussions about emerging technologies throughout the day.

Speaker Links:

  • As, I am part of RedHat Ansible organization I actively contribute towards writing blog around Ansible and its applications, ref:
  • I've delivered multiple talks at several conferences like AnsibleFest, DevConf, and Config Management Camp. All of the talks are available at their respective youtube channels.
  • LinkedIn profile:

Section: Artificial Intelligence and Machine Learning
Type: Talk
Target Audience: Intermediate
Last Updated: