Memristor demonstrates use in fully analog hardware-based neural network

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"As AI processing demands reach the limits of current CMOS technology, neuromorphic computing—hardware and software that mimic the human brain's structure—can help process information faster and more efficiently. A new memristor made from 2D layers of bismuth selenide combines long-term data retention and analog tuning to enhance AI energy efficiency and processing speed. The University of Michigan Engineering study is published in ACS Nano. The (bismuth selenide) memristor demonstrated three...