  Photonics integrated circuits have a huge potential to serve as a framework
for a new class of information processing machines and can enable ultrafast
artificial neural networks. They can overcome the existing speed and power
limits of the electronic processing elements and provide additional benefits of
photonics such as high-bandwidth, sub-nanosecond latencies and low-energy
interconnect credentials leading to a new paradigm called neuromorphic
photonics. The main obstacle to realize such a task is a lack of proper
material platform that imposes serious requirements on the architecture of the
network. Here we suggest and justify that transparent conductive oxides can be
an excellent candidate for such a task as they provide a nonlinearity and
bistability under both optical and electrical inputs.
