A More Robust Memory Device for AI Systems

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A research team from Northwestern Engineering and the University of Messina in Italy have developed a new magnetic memory device that could lead to faster, more robust Artificial Intelligence (AI) systems. Composed of antiferromagnetic materials, the memory technology is immune to external magnetic fields and could one day improve a variety of computing systems, including AI hardware, cryptocurrency mining, and space exploration programs. A paper outlining the work, titled “Observation of Current-induced Switching in Non-collinear Antiferromagnetic IrMn3 by Differential Voltage Measurements,” was published June 22 in the journal Nature Communications. Pedram Khalili, associate professor of electrical and computer engineering at the McCormick School of Engineering, led the study. The team includes joint first authors Sevdenur Arpaci and Victor Lopez-Dominguez, both members of Khalili’s laboratory, and Giovanni Finocchio, an associate professor of electrical engineering at the University of Messina, who co-led the research with Khalili. Other team members at Northwestern Engineering include Matthew Grayson, professor of electrical and computer engineering, and Mark Hersam, Walter P. Murphy Professor of Materials Science and Engineering.

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