Machine Understanding


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June 11, 2012 by William P. Meyers

Aping as the Basis of Intelligence

2. Specifications for the Language Machine

Typically in systems of artificial intelligence designed for language there is a front-end feature detection system. Thus the slight fluctuations in air pressure we call sound are analyzed for features. In the case of human language these features are often quite complex, but at this point they are well-studied. Thus detectors have been devised for common syllables and voice ranges.

In a developing human there are likely some very generalized feature detectors, but they are also very flexible. This would also be true in mammals and birds that have shown they can learn some human words. Thus a human baby can learn a primitive, click-based tongue from Africa, the simple syllables of modern English, or a tone-based Asian language system. In effect feature detectors evolve based on exposure to language.
Voicing is also complex, controlled by a wide range of muscles. It too is learned, and requires considerable practice to achieve perfection. Aping the voices of other humans is the primary method of learning to speak so as to be understood.

Four major input/output streams can be defined for a human-like language machine. There is the audio input from the ears. There is output to a variety of muscles that produce sounds and speech. There are other inputs ultimately external to the body, necessary to provide positive and negative behavior reinforcement, such as touch. There are internal desire (or rejection) type inputs, notably hunger and other discomforts or wants. There is also a need for decision making: given all the other inputs, deciding what sounds to make and when. This decision making could be incorporated into the language machine or it could be external, and probably is some combination of both in humans.

In addition, the language machine must have an ape imperative. Possibly this would arise out of conditioning from experimentation and feedback, but it is likely innate in human beings. It likely the result of pre-human evolution. The ape imperative creates a goal of aping the outer world. It prompts attempts at aping and measures for successes and partial successes.

Creating a language machine capable of moving from an essentially blank slate to an ability to mimic human language while connecting choices to internal and external states is possible, but it is a complex project to start with. The number of variables involved, and neural units and connections required to handle them, indicates that we need to have a very good idea of what the general plan is, or else no amount of tweaking will reach the goal. We need a simpler aping problem to solve. But first let's look at another complex one we are familiar with from everyday reality.


Next: Physical Gesture Aping Machine