The future of computing beyond the Von Neumann era is expected to rely on emerging devices that utilize material and device physics for novel functionalities. These devices, crucial for power-efficient and real-time computing for AI tasks, will likely move beyond the traditional model of a stored-program digital computer. The development of neuromorphic computing hardware, which implements neural network operations, is key to this future. Nanotechnology will support hardware development, creating smaller, faster, and more energy-efficient devices. Nanoelectronic devices using ferroic ordering are a promising alternative, with research focusing on the basic architectures of spintronic and ferroelectric devices and their integration into neuromorphic and analog memory applications.
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