Agentic Ai and Agentic RAG

## Details

Join us for an online event dedicated to exploring principles, tools and applications in the domain of Agentic AI and Agentic RAG (Retrieval Augmented Generation). Whether you're a beginner looking to dive into Agentic AI, this event will have something for everyone. We will discuss the role of Agentic AI and Agentic RAG in today's world and the importance of various applications. Generative AI uses LLMs to generate text, images, videos along with other contents based on prompts. Agentic AI takes actions making decisions, interacting with the environment, utilizing LLMs in order to reach certain objectives. Agentic AI operates with a level of autonomy and intelligence to add new dimensions. Agentic RAG (Retrieval-Augmented Generation) is a framework which augments capabilities of traditional RAG by using AI agents to control and manage retrieval and generation tasks in a dynamic way. AI agents in Agentic RAG make intelligent decisions regarding retrievals from data sources along with decisions about correct responses to generate accurate results.

Google Meet Link: **https://meet.google.com/edn-fhut-non**
(Time in Pacific Daylight Time ‎(UTC-7)‎, California (USA) time)
12:00 PM - 12:05 PM Introduction
12:05 PM - 12: 50 PM Session 1

Title: Agentic Large Language Relational Model (LLRM) architecture and flow of functions

Speaker: Dr. Shyam S Sarkar, Big Data Science Meetup Organizer

Abstract: Agentic AI systems are capable of providing agentic designs for reflection, multi-agent collaborations, planning with adaptive collaborations and complex workflows. In this talk there will be discussions about different architecture based on agent collaborations in
Large Language Relational Model (LLRM) where LLRM-SQL query coordinators or orchestrators execute by collaborations over SELECT agent, PROJECT agent, JOIN agent, FETCH agent along with many other agents in a workflow in key applications such as healthcare, finance etc.
There will be discussions about FETCH agent to activate Group Relative Policy Optimization (GRPO) for Group Policy Evaluation, Source Selection Optimization, Reinforcement Learning Update over inputs from Mail agents, Chat agents, Web agents, External data sources agents, Social agents along with other agents. This comprehensive flow process over various agents provides the complete blueprint for implementing and understanding the Agentic LLRM system's complex interconnected architecture.

12:50 PM - 12:58 PM Q/A