ViTFOX—Vision Transformer architecture with mag cores

Ferroelectric oxide allows for significant reductions in energy consumption and latency.

May 27, 2025

Jon Peddie

The ViTFOX project, uniting European and South Korean partners, aims to revolutionize AI hardware by developing energy-efficient Vision Transformer (ViT) systems using ferroelectric oxide materials. Unlike traditional architectures, ViTFOX integrates memory and processing into one unit, greatly reducing energy use and latency—achieving over 50 TOPS/W. This neuromorphic approach mimics brain-like processing, supporting real-time AI tasks like image recognition and autonomous navigation. The project advances hardware-software co-design and novel material integration to enhance performance and sustainability. Funded by the EU with €1.5 million (US $1.7 million), ViTFOX promises scalable, eco-friendly solutions for future AI in edge computing and smart technologies.As artificial

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ViTFOX—Vision Transformer architecture with mag cores

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