What question did this study set out to answer?

This research aims to develop and propose large-scale Hopfield neural networks utilizing vertical NAND flash memory for efficient in-memory associative computing.

April 25, 2026Open Access

Front Cover: Large‐Scale and Highly Reliable Hopfield Neural Networks Using Vertical NAND Flash Memory for the In‐Memory Associative Computing (Adv. Intell. Syst. 4/2026)

Key Points

This research aims to develop and propose large-scale Hopfield neural networks utilizing vertical NAND flash memory for efficient in-memory associative computing.
Utilized vertical NAND flash memory for the construction of Hopfield neural networks
Performed image association through sequential page-by-page operations within a single memory block
Demonstrated high reliability and efficiency in image association using the proposed architecture.

Abstract

In-Memory Associative Computing Large-scale and highly reliable Hopfield neural networks using vertical NAND flash memory is proposed for the in-memory associative computing. Owing to vertically stacked structure and sequential page-by-page operations, image association is performed within a single memory block. More details can be found in the Research Article by Woo Young Choi and co-workers (DOI: 10.1002/aisy.202500655).

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