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3mo ago

Cornell Researchers Demonstrate First Microwave Neural Network Chip

Achieving digital-comparable accuracy at sub-200-mW power in a 0.088 mm2 footprint, it promises low-power edge AI once integrated into conventional systems.

Cornell University researchers have come across an exciting discovery.
The chip’s extreme sensitivity to inputs makes it well-suited for hardware security applications like sensing anomalies in wireless communications across multiple bands of microwave frequencies, according to the researchers. Credit: Neuroscience News
The low-power microchip researchers call a “microwave brain” is the first processor to compute on both ultra-fast data signals and wireless communication signals by harnessing the physics of microwaves.

Overview

  • The integrated silicon chip computes directly in the microwave frequency domain to process ultrafast data streams and wireless signals without conventional digital sampling.
  • It consumes less than 200 milliwatts of power and occupies a 0.088 square millimeter footprint while achieving at least 88 percent accuracy on wireless-signal classification tasks.
  • The analog, nonlinear architecture exploits coupled microwave oscillations in tunable waveguides to perform pattern recognition without clock-driven operations.
  • Researchers highlight potential applications in low-power edge AI, radio-frequency signal processing and hardware security sensing across microwave bands.
  • Future work will focus on boosting accuracy, reducing power consumption further and integrating the microwave processor with existing digital and microwave platforms.