“Be it through reverse engineering efforts (neuromorphic computation) or artificial neural networks focused on machine and deep learning, Transformative Computing will contain components that mimic, perhaps even exceed, human brain capacity. We are already witness to the design of artificial neurons that use phase-changing, binary state (amorphous and crystalline) materials (germanium antimony telluride). Binary-state ions housed in fluid nanoelectronics/nanoionics also offer a hint as to how the proto applications will function. Development of these types of neurons is critical to brain function replication. They have the capacity to perform the necessary complex computational operations and have brain-like power consumption characteristics. This, of course, is a key feature, especially (albeit not exclusively) for wetware-based Transformative Computing. It also dovetails with Kurzweil’s prediction that within 30 years human intelligence will multiply billionfold once our neocortex wirelessly links to cloud-based “synthetic neocortex.””
Good read – read full article here: CodeX – Stanford Law School http://ow.ly/AQ4n30382IN