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SK hynix, TetraMem, and University of Southern California researchers developed a memristor-based in-memory computing SoC for AI edge devices. The chip accelerates neural network inference at a fraction of GPU power. Peak theoretical performance reaches 2.54 TOPS, 16X below Microsoft's Copilot+ requirements.
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