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Reservoir computing (RC) has reinvigorated neuromorphic computing activities in photonics. RC radically reduces the required complexity for a hardware implementation in photonics as compared to earlier efforts in the nineties. Currently, multiple photonic RC systems show great promise for providing a practical yet powerful hardware substrate for neuromorphic computing. Among those, delay-based systems offer through a time-multiplexing technique a simple technological route to implement photonic neuromorphic computation. We will review the state of the art on delay-based RC and discuss our advances in substrates implemented as passive coherent fibre-ring cavities and semiconductor lasers with delayed optical feedback. Passive coherent reservoirs built using fiber loops have achieved record performances, but are still aided by nonlinear electro-optical transformations at the input and output. Nevertheless, when targeting all-optical reservoirs, these nonlinearities will be absent. We have found that optical nonlinearities in the fibre itself can be sufficient to enhance the task solving capabilities of a passive reservoir. Also, delay-based optical substrates for RC tend to be quite bulky employing long fiber loops or free-space optics. As a result, the processing speeds are limited in the range of kSa/s to tens of MSa/s. We have studied and developed substrates using external cavities which are far shorter than what has been realized before in experiment. Specifically, by integrating a semiconductor laser together with a 10.8 cm delay line on an active/passive InP photonic chip using the Jeppix platform, we can increase the processing speed to GSa/s.
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