Sub-picojoule-per-bit volitional neuromorphic devices for precise targeting and tracking.

ABSTRACT: The technological revolution driven by artificial intelligence has significantly improved the hardware performance, but energy consumption remains a critical bottleneck. The state-of-the-art retinomorphic devices, as core components of artificial intelligence hardware, excel in feature extraction but are constrained by passive attention mechanisms that lack flexibility of actively extracting additional features. Inspired by the human visual system, this work introduces a volitional neuromorphic device with active volitional attention regulation. By leveraging gate-voltage-tunable photoconductance to generate adjustable differential spectral response and employing neural networks to evaluate spectral reconstruction accuracy, the device achieves selective task perception. Experimental result

SUBMITTER: Huang Y 

PROVIDER: S-EPMC12789456 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature