  Optical artificial neural networks (ONNs) have significant potential for
ultra-high computing speed and energy efficiency. We report a novel approach to
ONNs that uses integrated Kerr optical microcombs. This approach is
programmable and scalable and is capable of reaching ultrahigh speeds. We
demonstrate the basic building block ONNs, a single neuron perceptron, by
mapping synapses onto 49 wavelengths to achieve an operating speed of 11.9 x
109 operations per second, or GigaOPS, at 8 bits per operation, which equates
to 95.2 gigabits/s (Gbps). We test the perceptron on handwritten digit
recognition and cancer cell detection, achieving over 90% and 85% accuracy,
respectively. By scaling the perceptron to a deep learning network using off
the shelf telecom technology we can achieve high throughput operation for
matrix multiplication for real-time massive data processing.
