Time delay reservoir computing with VCSEL

Neural networks in which the interconnections between the nodes are randomly assigned are promising for the realization of neuromorphic devices in which the resource requirements for training are lower than for a fully deterministic system. Reservoir computing is a class of recurrent network for which the input and internal weights are random and fixed over time, and only the output weights are trained via a linear regression. In this work, we review the recent work on photonic reservoirs and describe our recent results on the implementation of a single node system based on multi-mode optical interconnect technology developed for high channel density and low power data transfer applications. We discuss the potential advantages of this approach for the realization of a photonic cluster of reservoirs.