IIT Madras, Ericsson Partners For Research In Responsible AI
The symposium featured key projects, including one on Large Language Models in healthcare, Participatory AI addressing AI's black-box nature and Generative AI models based on attention mechanisms
Indian Institute of Technology (IIT) Madras’ Centre for Responsible AI (CeRAI) has forged a significant partnership with Ericsson to conduct joint research in the field of Responsible AI. The collaboration was announced during a Symposium on Responsible AI for Networks of the Future, where leaders from Ericsson Research and IIT Madras discussed advancements in Responsible AI.
At the event, Ericsson committed to a five-year partnership with CeRAI as a 'Platinum Consortium Member.' Under the Memorandum of Understanding (MoU), Ericsson Research will actively support and participate in all research activities at CeRAI.
The Centre for Responsible AI is an interdisciplinary research centre aiming to become a premier hub for both fundamental and applied research in Responsible AI, with immediate implications for deploying AI systems in the Indian ecosystem.
Chief Guest Prof Manu Santhanam, Dean (Industrial Consultancy and Sponsored Research), IIT Madras, emphasised the importance of impactful translational work in collaboration with the industry. Dr Magnus Frodigh, Global Head of Ericsson Research, highlighted the significance of responsible AI practices in 6G and future networks, which aim to seamlessly blend the physical and digital worlds.
A panel discussion on 'Responsible AI for Networks of the Future' commemorated the partnership during the symposium, showcasing ongoing research activities at the Centre for Responsible AI.
Prof B Ravindran, Faculty Head, CeRAI, IIT Madras, emphasised the importance of embedding responsible AI principles from the beginning in future networks. He noted that with 5G and 6G networks, critical applications would require explainable AI models to ensure performance guarantees.
The symposium featured key projects, including one on Large Language Models in healthcare, Participatory AI addressing AI's black-box nature and Generative AI models based on attention mechanisms. Another project explored Multi-agent Reinforcement Learning for trade-off and conflict resolution in intent-based networks.
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