Pentti Haikonen's architecture for conscious machines
By Trung Doan (doanviettrung a_t gmail dot com).
Haikonen's contribution to the machine-consciousness endeavor is an architecture based on cognitive principles. He also developed some electronic microchips as a first step to building a machine based on that architecture.
Below, we look at how a Haikonen machine might achieve consciousness once built, by examining some of its cognitive capabilities, and in the process will briefly discuss the Haikonen architecture.
The Haikonen machine perceives
 Robot Brains by Pentti Haikonen Say the Haikonen machine's cameras are focusing on a yellow ball. The cameras' pixel pattern is fed into a preprocessor circuit which produces an array of, say, 10,000 signals, each signal carried by, for example, a wire. One wire is the output from the preprocessor's "roundness" circuitry and, in this case, the signal is On. Another wire, from the "squareness" circuitry, would be Off, i.e. carrying no voltage. A group of wires is the output from the spectrum-analysis circuitry, the wire corresponding to frequencies which we humans recognise as "yellow" is On while "red", "blue", etc., wires are Off. There would be many other groups of wires depicting size, brightness, edges, etc.
The machine does not internally represent the ball as a round graphic, nor a set of numbers representing diameter, color, etc., but by this signal array. Haikonen calls this a "distributed signal representation".
Suppose the machine is shown several balls of different sizes, colors, etc., one at a time, and each time its microphone hears the sound pattern we humans understand as the word "ball". Because they appear at the same time repeatedly, the machine associates the sound pattern and the visual pattern together. The making of associations is how the machine's perception is done.
After several different balls are associated with that sound pattern, the machine finally learns to associate the "ball" sound pattern with anything that is round.
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