JOHOR BAHRU, Apr 6 – In a world increasingly powered by artificial intelligence (AI), the demand for smarter, faster, and more energy-efficient systems is growing rapidly. Recognizing this need, International Student Society-Yemen (ISS-Yemen) at Universiti Teknologi Malaysia (UTM) hosted a cutting-edge webinar titled “From Harvard to UTM: Why the Future of Machine Learning is Tiny and Bright”, featuring two global pioneers in the field of Tiny Machine Learning (TinyML).
The event welcomed Assoc. Prof. Dr. Vijay Janapa Reddi from Harvard University and Assoc. Prof. Dr. Mohd Ridzuan Ahmad from UTM, offering participants valuable insights into the future of AI at the edge. With more than 200 attendees from academic and industry backgrounds, the session highlighted the transformative potential of TinyML, a revolutionary approach that enables AI to run on low-power, resource-constrained devices.
TinyML stands at the intersection of embedded systems and machine learning, allowing intelligent capabilities to be deployed on resource-constrained devices without the need for constant internet connectivity or cloud computing.
During the keynote, Dr. Vijay Janapa Reddi emphasized the importance of developing AI that is both sustainable and accessible. “TinyML is reshaping what’s possible with AI. It enables us to bring intelligence to the edge, where it matters most closer to people, devices, and decisions,” he shared.
Assoc. Prof. Dr. Mohd Ridzuan Ahmad provided a local perspective, discussing UTM’s contributions and initiatives in edge AI research. “This collaboration and knowledge-sharing with world leaders like Harvard are vital to putting Malaysia at the forefront of global innovation. TinyML supports our mission to deliver inclusive, impactful AI solutions that serve real-world needs.
The session covered key areas such as the evolution of TinyML, its real-world applications in healthcare, robotics, smart infrastructure, and how researchers and developers can overcome technical challenges through interdisciplinary collaboration.
An engaging Q&A segment allowed participants to explore complex questions, from deployment constraints to the ethical implications of decentralized AI systems. The lively discussion showcased the community’s enthusiasm and the growing interest in making AI both scalable and environmentally responsible.
The webinar concluded on a high note, with strong calls for continued collaboration, innovation, and investment in sustainable AI technologies. ISS-Yemen at UTM extends its sincere appreciation to both speakers, the organizing committee, and all attendees for making this event a milestone in the university’s journey toward technological excellence.
Source: UTM NewsHub