MIAI develops the next generation of Artificial Intelligence models and systems, from hardware and embedded architectures to software.

28/11/2023

The field of Artificial Intelligence (AI) decision systems is expanding rapidly, impacting various aspects of our daily lives. These systems present challenges in mathematical foundations, security, privacy, fairness, and data efficiency, especially when dealing with limited annotated data. Additionally, the need for AI to move beyond the cloud, address communication overload, and respect data privacy is emphasized. Hardware architectures for AI, embedded in low-power, low-latency devices, are recognized as crucial for advancing new applications.

Despite challenges, AI offers innovative solutions with potential applications in smart health, environmental monitoring, hazard prediction, energy consumption reduction, and advancements in manufacturing processes.
The Grenoble Alpes University’s MIAI (Multidisciplinary Institute in Artificial Intelligence) is at the forefront of addressing these challenges. With a diverse team of academic members spanning computer science, mathematics, biology, medicine, sociology, and more, MIAI collaborates with over 90 private partners. Their research spans theoretical work on the mathematical foundations of AI to applied advancements in visual and language processing, hardware architectures, and environmental applications. Notably, MIAI has contributed to AI regulation, hardware architecture innovation, and the practical application of AI in fields like material science.

In the realm of health, MIAI showcases four chairs focused on integrating AI into medical practices. These chairs address challenges ranging from patient empowerment through participatory health projects to computer-assisted medical interventions. Through these initiatives, MIAI aims to create an international reference for interactive, generative AI systems that are frugal, trustworthy, and beneficial to both humans and the environment. The institute’s commitment to research and collaboration underscores its contribution to advancing AI in diverse domains beyond health, including education, quantum computing, and cultural and creative industries.