#81 Dr. Majid Fekri on Building AI RAG Systems, Vector Databases and Information Theory

Featured Guest: Dr. Majid Fekri, Co-Founder & CTO, Edge AI Innovations

📍Toronto, Canada

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In this episode, Dr. Majid explores the intersection of edge AI and information theory. He shares his vision of running AI efficiently on small devices while preserving privacy and reducing energy consumption.

Dr. Majid explains how his company developed a unique approach to retrieval augmented generation (RAG) for edge devices by redefining what "relevance" means through information theory. Their solution uses Shannon's theory of information as the foundation to compress vector signals into binary format, making operations extremely fast and efficient while maintaining accuracy.

Dr. Majid also discusses the challenges of deploying AI systems we don't fully understand, the mystery of vector spaces in neural networks, and how their approach provides more mathematical control over AI behavior.

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Links:

https://www.edgeaiinnovations.com/

Dr. Majid’s Research Papers: https://scholar.google.ca/citations?user=iCsHW4EAAAAJ&hl=en

Moorche Serverless RAG Demo: https://www.youtube.com/watch?v=Ehq8wkxIUZM

Further Reading about the Episode: https://suite.sundaypyjamas.com/share/23b32843-86dd-42cf-8367-18308bfd5666

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Credits:

Designed by the Research Labs Platform

Produced by SundayPyjamas®

Created & Hosted by Prathamesh Patel

Podcast Strategy & Production by Nishi Panchal

Music: Ukiyo - Calling (EP)

Copyright of SundayPyjamas Inc. 2025