Interview and Special Report

A Story of a Qom Scientist’s Journey to Create Indigenous Artificial Intelligence

Exploring the achievements of the University of Qom’s Smart Software Lab, from the Judicial AI Assistant to the Iranian Rhino Language Model.

Introduction and Academic Background

Amir Jalali Bidgoli, an Associate Professor at the University of Qom, has made significant strides in creating and applying indigenous AI by establishing and leading the Smart Software Laboratory. He holds an M.Sc. from Iran University of Science and Technology and a Ph.D. from the University of Isfahan.

His expertise lies in Artificial Intelligence and Cybersecurity. He has published over 50 scientific articles in reputable international journals, with each work garnering over a thousand citations.

Smart Software Laboratory

Since the beginning of his tenure as a faculty member, Dr. Jalali has been passionate about moving beyond theoretical research toward practical implementation. Consequently, he founded the “University of Qom Smart Software Laboratory,” focusing on Large Language Models (LLMs) and the development of intelligent assistants.

Primary Goals of the Lab

The lab was founded with two goals: producing administrative/industrial software and researching the needs of the software engineering industry in Qom. Its mission is to apply knowledge to meet societal needs in IT.

The lab delivers secure and efficient software solutions to public and private organizations, with a special emphasis on automation and intelligence.

Key and National Projects

The research team under Dr. Jalali’s supervision has developed numerous projects directly aligned with societal and organizational needs:

01

Judicial AI Assistant

The team’s most significant project, supporting the Judiciary’s smart transformation in partnership with the Center for Statistics and Information Technology. It helps judges make more accurate decisions and reduces case processing time.

02

Faradeed Product

An intelligent assistant based on LLMs that provides organizational managers with rapid, precise access to statistical data and organizational information.

03

Rhino Language Model

Developing the Iranian “Rhino” language model and smart decision support systems in collaboration with knowledge-based companies to cover cultural needs.

Interdisciplinary Collaborations

All lab projects are designed with an operational perspective, where students acquire market-specialized skills, ensuring they enter the industry as experts upon graduation.

Diverse Collaborations
Extensive collaboration with fields like law, religion, architecture, psychology, and data analysis has been established.
Developing Multi-Purpose Models
The goal of these collaborations is to develop models capable of addressing legal and religious needs while facilitating creative design processes.

Infrastructure Challenges in AI Development

As a national reference point for AI, the University of Qom now holds the authority to assess the technical competence of AI-based products. However, the head of the lab emphasizes that this path faces serious hurdles.

The Main Challenge: Computing Hardware

Dr. Jalali divides AI challenges into three factors: specialized manpower, data, and hardware. While expertise and data are progressing, hardware access is a major obstacle. Unlike foreign researchers with access to large computing clusters, acquiring even basic powerful hardware for domestic researchers is extremely difficult.

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