One of the coolest frontiers now reachable thanks to nanotechnology is the ability to reproduce biological systems. That's why artificial retinas, "bionic" ears and other wonders are within our reach, now that we have the ability to go small. And there's nothing more central to this effort than to figure out how to artificially reproduce even the most simple fuctions of the human brain -- like speech, facial recognition or blogging.
That's why I stopped in the middle of my regular patent search when I came across this one, recently granted to Alex Nugent and his company, KnowmTech LLC. I stopped, then read it slowly, then read the whole thing a few times. Maybe it's just me, but Patent 6,889,216 makes for some fascinating reading.
The simplest way I can explain it is this: Life is not digital. Life is analog, with continuously altering and overlapping variables that cannot be dealt with through a series of programmed 1s and 0s, and "ifs" and "thens." That's why computers might be able to beat us at chess, where all variables can be digitized, but they're incredibly stupid when it comes to handling the various challenges that our own brains face every day.
The answer is not to simply pack more crosstown traffic on a chip, but to arrange them in a "neural network" that can recognize patterns and learn from from them -- much like the way I'm witnessing my own 11-month-old child learn to speak, walk and distinguish family from strangers. Where nanotech comes in, is the ability to simply form more connections and "neurons."
I'll let the inventor tell it in his words. I've edited out the redundancies necessary in patent-speak.
- Neural networks are computational systems that permit computers to essentially function in a manner analogous to that of the human brain. Neural networks do not utilize the traditional digital model of manipulating 0's and 1's. Instead, neural networks create connections between processing elements, which are equivalent to neurons of a human brain. ... Generally, a neural network is an information-processing network, which is inspired by the manner in which a human brain performs a particular task or function of interest. ... The elementary building block of biological neural systems is of course the neuron, the modifiable connections between the neurons, and the topology of the network.
Biologically inspired artificial neural networks have opened up new possibilities to apply computation to areas that were previously thought to be the exclusive domain of human intelligence. Neural networks learn and remember in ways that resemble human processes. Areas that show the greatest promise for neural networks, such as pattern classification tasks such as speech and image recognition, are areas where conventional computers and data-processing systems have had the greatest difficulty. More here
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