  Optical artificial neural networks (ONNs) have significant potential for
ultra-high computing speed and energy efficiency. We report a new approach to
ONNs based on integrated Kerr micro-combs that is programmable, highly scalable
and capable of reaching ultra-high speeds, demonstrating the building block of
the ONN, a single neuron perceptron, by mapping synapses onto 49 wavelengths to
achieve a single-unit throughput of 11.9 Giga-OPS at 8 bits per OP, or 95.2
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.
