Energy-efficient AI hardware technology via a brain-inspired stashing system

Researchers have proposed a novel AI system inspired by the neuromodulation of the brain, referred to as a “stashing system,” that requires less energy consumption. The research group led by Professor Kyung Min Kim from the Department of Materials Science and Engineering has developed a technology that can efficiently handle mathematical operations for artificial intelligence by imitating the continuous changes in the topology of the neural network according to the situation. The human brain changes its neural topology in real time, learning to store or recall memories as needed. The research group presented a new artificial intelligence learning method that directly implements these neural coordination circuit configurations.

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