Human computers a reality
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DARPA is funding IBM to work on a cognitive computing project.
‘Human’ computers remind of movies like ‘Bladerunner’, ‘Terminator’, ‘Matrix’, ‘i, Robot’ and ‘Short Circuit’, where robots have (been given) the ability to think, act and feel like humans. This is dismissed as science fiction; an impossibility; creations of overactive imaginations with access to really cool special effects labs. However, it would seem that at least one organisation is determined to try its best at making this type of robot a reality, or at the very least, explore the avenue to its full extent.
For this very reason, DARPA has awarded IBM and five universities a contract worth $4.9 million for the first phase of a programme known as the ‘Systems of Neuromorphic Adaptive Plastic Scalable Electronics’ programme (SyNAPSE), wherein a team of material and computer scientists, as well as neurobiologists and psychologists explore the possibilities of creating a computer system that is able to simulate the action, interaction, cognition, perception and sensation of a human brain.
It all sounds like machine language, doesn’t it? Or, if you’re more comfortable with it, Greek. The important thing is, these guys are trying to make a computer robot human thing, not unlike the Terminator movie characters (all fictional, of course… or is it?). Their mission is to reverse engineer the working of a brain, in order to manufacture a fake one, so to speak.
And for those who think this is just a grand new name for the older field of artificial intelligence, it needs to be said it’s not. There’s a difference between cognitive computing and artificial intelligence (this is a tricky part). Artificial intelligence research focuses on smaller, individual aspects of engineering an intelligent machine. The problem is presented first, and followed by an algorithm. Research in cognitive computing takes a more holistic approach to engineering an intelligent machine. In other words, cognitive computing takes into account all of the aspects of the workings of a brain; both micro and macro circuits. This means that the approach is completely turned around; the algorithm comes first, then the problem.
According to Dr. Dharmendra S. Modha, who leads the team of experts involved in the SyNAPSE programme, there are three reasons that prove that the time is ripe to start drawing inspiration from the brain’s dynamics, structure, behaviour and function.
Firstly, he says that neuroscience (the scientific study of the nervous system) seems to have matured enough to be able to produce enough quantitative data for formulating hypotheses of the brain’s function and dynamics.
The second point he states is that super-computing is at a point where it is ready to undertake exceedingly large-scale simulations.
The third point the doctor makes is that nanotechnology evolved to the point that essential computational functions of synapses and neurons can be represented in hardware, to rival brain power and space.
What would the success of Dr. Dharmendra and his team mean?
If the team of experts was to succeed in its project, a whole new world of novel cognitive systems, programming paradigms and computing architectures could unfold. This could lead to very practical applications, and even open up entire new industries.
In other words, you won’t just have a robot that makes you coffee in the morning; you’ll have a robot that makes you coffee, joins a union and complains about the wage you’re paying it.
