Don't have any numbers for silicon retinas, but the long-term goal IBM's cognitive computers is to simulate corelets on a supercomputer that consumes mega-Watts, then execute them on a cognitive computer that consumes kilo-Watts--1000-to-1 less power.
Regarding power dissipation it should be drastically less, because artificial neurons dissipate very little power except when firing voltage spikes, which typically only occurs every few hundred milliseconds.
Regarding using smart silicon retinas in humans, that would probably be a decade or more away, but in the shorter term the fact that cognitive functions can be built-in should make human-like perception possible for robots.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.