IIT-Kharagpur launches India's first school for Physical AI

A new focus on physical interaction

IIT-Kharagpur has announced the creation of the Benjamin Gupta School of Physical AI. This marks the first time in India that a dedicated academic institution will focus specifically on intelligent systems that interact with the physical world. The school is designed to move beyond the standard use of AI in digital environments.

Unlike conventional AI, which primarily relies on large datasets and digital algorithms, Physical AI incorporates scientific principles. It aims to create systems that can understand and navigate the real world through sensing and intelligent control. This distinction is vital for developing technology that functions outside of a computer screen.

The school will house the Department of Artificial Intelligence at the institute. It is intended to support a wide range of interdisciplinary research and academic activities. By creating a dedicated space for this field, the institute hopes to lead the transition toward more physically aware technology in India.

Funding and institutional backing

The establishment of the school is backed by a total investment of Rs 35 crore. This funding comes from a combination of private philanthropy and institutional support. A memorandum of understanding was signed between the institute, the IITKGP Foundation USA, and a prominent alumnus.

The Vinod Gupta family contributed Rs 12.5 crore toward the initiative. Additionally, an anonymous alumnus provided Rs 10 crore to help fund the new school. The institute will cover the remaining balance of the total investment to get the project off the ground.

The school is named in memory of Benjamin Gupta, who was the son of the philanthropist Vinod Gupta. This naming reflects a personal connection to the project's origins. The goal is to create a lasting academic legacy that combines personal contribution with national technological advancement.

Technical pillars of the curriculum

The school will concentrate on several specific technical areas to achieve its goals. These include physics-informed machine learning and scientific AI. These fields focus on ensuring that AI models adhere to the laws of physics rather than just finding patterns in data.

Other key areas of study will include intelligent robotics and autonomous systems. The curriculum will also cover advanced sensing and AI-enabled experimentation. These subjects are essential for building machines that can perform complex tasks in unpredictable real-world environments.

A major goal of the school is to develop reliable and explainable AI. Explainable AI refers to systems where the reasoning behind a decision can be understood by humans. This is particularly important for safety-critical applications where physical accuracy and accountability are non-negotiable requirements.

Who will be affected by the launch

Academic programs are expected to begin in the upcoming session, pending the necessary approvals. These programs will be designed to serve a broad audience. They will cater to students, researchers, and working professionals from various scientific backgrounds.

The school intends to reach people in engineering, the physical sciences, life sciences, and medicine. By opening these doors, the institute aims to combine domain expertise with modern AI capabilities. This allows specialists in fields like healthcare to apply AI to their specific professional needs.

The initiative also seeks to create a collaborative ecosystem for various stakeholders. It will bring together academia, industry, healthcare institutions, and research laboratories. Startups and international partners will also be involved to accelerate technology development and professional reskilling.

Moving beyond the black box

Director Suman Chakraborty noted that AI has already transformed how we process information. He believes the next leap will involve transforming how we engineer and interact with the physical world. The school aims to lead this transition by moving beyond treating AI as a black-box solution.

A black-box solution is one where the internal workings are hidden or too complex to interpret. The school wants to encourage professionals to combine algorithmic capabilities with fundamental scientific knowledge. This approach ensures that the technology is robust and grounded in reality.

By fostering this approach, the school hopes to create a more responsible framework for AI development. It aims to ensure that as machines become more autonomous, they remain predictable and safe. This research will provide the foundation for the next generation of industrial and scientific tools.