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AI technologies are advancing rapidly, but their increasing power consumption poses challenges. New spintronic devices developed by researchers at Tohoku University, National Institute for Materials Science, and Japan Atomic Energy Agency promise to enhance energy efficiency in AI chips. These devices mimic brain-like functions, allowing for efficient information processing and storage.
The breakthrough involves electrically programmable switching between non-collinear antiferromagnets and ferromagnets, enabling multiple magnetic states. This innovation could lead to significant improvements in AI chip performance, reducing energy costs and environmental impact. The research team aims to further optimize these devices for practical applications in AI.
• New spintronic devices enhance energy efficiency in AI chip technology.
• Electrically programmable switching opens pathways for advanced AI hardware.
Spintronics involves the use of electron spin for information processing, enhancing energy efficiency in AI applications.
Neuromorphic computing mimics neural networks, allowing for more efficient AI processing and learning.
Electrical mutual switching enables the control of magnetic states, crucial for developing advanced AI chips.
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