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A More Robust Memory Device for AI Systems


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A schematic representation of the device showing current sources and the nanovolt meter (V) connections for one of the switching experiments.

A research team from Northwestern Engineering and the University of Messina in Italy have developed a magnetic memory device that could lead to faster, more robust artificial intelligence systems.

Credit: Northwestern University McCormick School of Engineering

Artificial intelligence systems could be strengthened by a new magnetic memory device designed by researchers at the Northwestern University McCormick School of Engineering (Northwestern Engineering) and Italy's University of Messina.

The device is fabricated from antiferromagnetic (AFM) materials, which boast innately faster dynamics than ferromagnetic materials, and cause no unwanted magnetic interactions; AFM-based memory cannot be deleted with external magnetic fields.

The researchers used the manufacturing-conducive iridium manganese AFM system to build a memory device that expands on an earlier silicon-compatible device.

The new device can write data, and more reliably read out information once it has been written.

Said Northwestern Engineering's Pedram Khalili, "Our technology is general-purpose and could be applied anywhere memory is used in high-performance computing systems today."

From Northwestern University McCormick School of Engineering
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