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Artificial intelligence (AI) has become one of the most transformative technologies of our time, with broad potential applications across nearly every sector of society. This talk will address the key challenges in advancing the functionality and performance of AI chips, with a particular focus on low-power, unmanned autonomous systems that must operate in complex, dynamic environments. We will begin with an overview of current AI technologies, particularly from the scaled CMOS point of view, followed by a discussion of emerging memory and computing paradigms — especially voltage-controlled spintronics. This includes mechanisms such as voltage-controlled magnetic anisotropy via exchange interaction and voltage-controlled Dzyaloshinskii-Moriya interaction for manipulating spin textures. The integration challenges of these novel technologies with scaled CMOS will be examined through an illustrative example. I will also present several potential applications, with an emphasis on how voltage-controlled spintronics could enable the next generation of generative AI. In addition, we will explore the role of spintronic-based convolutional neural networks and Bayesian networks, as implemented with voltage-controlled magnetic anisotropy, the latter offering promising pathways to enhance safety, reliability, and fault tolerance, which are critical for autonomous systems. Finally, I will outline several prospective research directions and conceptual frameworks aimed at stimulating discussion and fostering innovative approaches to overcoming scaling and performance bottlenecks in next-generation AI chip technologies.
Short biography:
Dr. Kang L. Wang is currently a Distinguished Professor and the Raytheon Chair Professor at the University of California, Los Angeles (UCLA). He is affiliated with the Departments of ECE, MSE, and Physics/Astronomy. He is also the Founding Director of UCLA Quantum Science and Engineering and the Director of the Joint Center of Green Nanotechnology – between UCLA and the King Abdulaziz City for Science and Technology, Saudi Arabia. He received his M.S. and Ph.D. degrees from the Massachusetts Institute of Technology and his B.S. degree from National Cheng Kung University (Taiwan). He was with HKUST as a Professor and the Dean of School of Engineering from 2000-2003. Previously, he also served as the Chair of Electrical and Computer Engineering of UCLA from 1992-1996. His research areas include semiconductors, topological matters, spintronics/magnetics, nonvolatile electronics, and quantum information and computing.