  The ever-increasing demand for Artificial Intelligence (AI) systems is
underlining a significant requirement for new, AI-optimised hardware.
Neuromorphic (brain-like) processors are one highly-promising solution, with
photonic-enabled realizations receiving increasing attention. Among these,
approaches based upon Vertical Cavity Surface Emitting Lasers (VCSELs) are
attracting interest given their favourable attributes and mature technology.
Here, we demonstrate a hardware-friendly neuromorphic photonic spike processor,
using a single VCSEL, for all-optical image edge-feature detection. This
exploits the ability of a VCSEL-based photonic neuron to integrate
temporally-encoded pixel data at high speed; and fire fast (100ps-long) optical
spikes upon detecting desired image features. Furthermore, the photonic system
is combined with a software-implemented spiking neural network yielding a full
platform for complex image classification tasks. This work therefore highlights
the potentials of VCSEL-based platforms for novel, ultrafast, all-optical
neuromorphic processors interfacing with current computation and communication
systems for use in future light-enabled AI and computer vision functionalities.
