Advanced AI and Quantum Computing Research: The Indian Institute of Technology Bombay (IIT Bombay) and the Indian Institute of Science (IISc) have partnered with International Business Machines (IBM) today. The initiative aims to foster innovation in agentic AI, sovereign AI, quantum computing, and next-generation computing systems while expanding research collaboration in India.
Building upon a collaboration with IIT Bombay that began in 2018, IBM researchers will work alongside faculty and students on sovereign and Indian language model adaptation, multimodal AI, as well as AI infrastructure and knowledge retrieval.
Both parties will work to advance sovereign AI and Indian language models, enhancing multimodal AI capabilities for Indian languages through efficient model adaptation and optimisation tools. The collaboration will also focus on developing multimodal AI systems that strengthen software programming education, human-AI collaboration, and intelligent operations within hybrid cloud environments.
The collaboration between IISc and IBM researchers, which began in 2021, is set to enter a new phase as they plan to work on agentic systems, AI for applications, and the development of quantum computing algorithms.
IIT Bombay, IISc, and the corporation have collaborated to advance research in fields such as artificial intelligence, hybrid cloud, distributed systems, and quantum computing.
IIT Bombay, IISc, and the corporation have collaborated to advance research in fields such as artificial intelligence, hybrid cloud, distributed systems, and quantum computing. Additionally, according to the institute, they have created opportunities for students and researchers to tackle industry-relevant challenges.
With the new plans emerging from this collaboration, the institutions aim to pursue interdisciplinary research, nurture the next generation of scientific talent, and foster innovations that will shape the future of computing. The partnership aims to develop agentic AI workflows that enhance orchestration within hybrid cloud environments. Furthermore, they plan to create lightweight time-series foundation models based on the IBM Granite model family for energy analytics, facilitating tasks such as forecasting, anomaly detection, load disaggregation, and energy optimisation.
