by Nicholas West

August 8, 2013
from ActivistPost Website








The goal to create a computer brain every bit the equal to its human counterpart is nearing reality... if the researchers involved can be believed. These are the same researchers, after all, who have made disingenuous claims in the past.

On one hand it has been stated that mapping the vast structure of the human brain - particularly true cognition, not only computational power - is nearly insurmountable:

Using today’s state of the art technology, it takes an AI-assisted researcher almost 50 hours to reconstruct a SINGLE neuron! At that pace, one researcher would need to devote the next 500 million years to neural mapping; no bathroom breaks allowed.


Nevertheless, two new developments - one in hardware and one in software - seek to overcome the problem of decoding the human brain.

On the hardware side, Gizmag reported advancements with neuromorphic chips which aim to reverse engineer the brain. This goal is trying to be reached through "an interdisciplinary amalgam of neuroscience, biology, computer science and a number of other fields that attempts first to understand how the brain manipulates information, and then to replicate the same processes on a computer chip."

They are specifically sidestepping straight computational power, since that is the part that consumes the most energy.


As they note, the human brain with a consumption power of only 20W outclasses the world's fastest supercomputer when it comes to the most common human tasks seen in the real world based on sensory input.


By contrast, the world's fastest supercomputer consumes 200,000 times as much energy within a massive physical structure.


There is a long technical description to be sure, but the essence of what is trying to be achieved is summarized by highlighting that the brain, unlike the standard computer, uses both analog and digital for data processing and decision making (thought):

...that information is processed on a massively parallel scale at relatively slow speeds; that memory and instruction signals are often seamlessly combined; and that continuous adaptation and self-organization of its neural networks play a crucial part in its function.


Most attempts at replicating a human brain involve simulating a very large number of neurons on a supercomputer; the neuromorphic approach, however, is quite different because it involves developing custom electronic circuits that simulate the neuron firing mechanisms in the actual brain and are similar to the brain in terms of size, speed and energy consumption.

To complement this approach, researchers at IBM have created a new software program called Corelet which they say operates like the human brain when neuromorphic chips are used for processing.

Building blocks, or corelets, can be built using 256-neuron neuromorphic CPUs designed to do specific tasks. The “True North” library already has some 150 pre-designed corelets to do things like detect motion or image features, or even learn to play games.


To play pong, for example, a layer of input neurons would be given information about the “ball” and “paddle” motions, an output layer would send paddle motion updates, and intermediate layers would perform some indeterminate processing.

While some of the achievements seem impressive, this approach is still admitted to be at a very simplistic level, mainly because a real human brain involves many parallel, simultaneous processing features that cannot yet be fully duplicated.

Watch the following below video which shows the proposed "Cognitive Apps" to see what is hoped for. Naturally all of what is mentioned seems beneficial to humanity.


What negatives do you see on the flipside of this technology should it ever be fully realized?






For now, it would seem that trying to recreate the human brain in all of its complexity will take much longer than many in this field hope for... perhaps even an infinite length of time, as some have suggested.


Nevertheless, the reductionists see the potential for adding an artificial brain into the matrix... to what final purpose remains to be seen.


In the meantime, is this the type of research that should be receiving billions in worldwide funding, even as real-world, tangible problems like infrastructure collapse are being disregarded?