Recent Progress in Synaptic Devices Paving the Way toward an Artificial Cogni-Retina for Bionic and Machine Vision

The state-of-the-art conception of a bionic/robotic eye is a somewhat bulky multipart system comprising a video camera connected to a processing unit that in turn communicates data through a wireless transmitter to either an in vivo retinal implant or a computer system. An artificial cogni-retina is a millimeter-scale, intelligent apparatus designed as a replacement for these systems, while executing simple image processing tasks. As a bionic limb, it can connect directly to the optic nerve and perform rudimentary cognitive functions such as perceiving, learning, remembering, and classifying elementary visual data. This theoretical system presents a quantum leap in terms of size, power consumption, and speed to both prosthetic human eyes and robotic vision in artificial intelligence-based platforms such as autonomous vehicles. Recently, an increasing number of publications have used interesting materials in artificial synaptic devices that drive this idea closer toward becoming a real-world application. Such devices may form a basis for hardware-based deep learning artificial neural networks that can potentially execute image processing tasks within a single clock cycle compared to software algorithms running on conventional von Neumann machines that require millions of cycles to perform image sensor interfacing, memory fetch operations, and data path propagation.