Affordable emerging computer hardware for neuromorphic computing applications.

We are pursuing an investigation of neuromorphic computational models and architectures in order to leverage present understanding of how the estimated 1011 neurons and 1015 neuron connections in the mammalian brain are able to do some of the things a human does, and as quickly as it does it, using slow base components, while consuming very little power on affordable synthetic non-biological computing hardware. Understanding and harvesting neurologically based methods is a promising approach with great potential that may help us achieve massively parallel computation far beyond the scope of traditional computing