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Soli The small computer that won't fence you in. A lot of semantic nonsense is being tossed around by some of the makers of so-called "personal" computers.
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Remember, there's no free lunch. So before you buy any personal computer, consider Soli' 11 It costs more at the start but less in the end. It can grow with your ability to use it. Sol is not cheap. But it's not a delusion either. Sol small computers are at the very top of the microcomputer spectrum. They stand up to the capabilities of mini systems costing four times as much.
No wonder we call it the serious solution to the small computer question.
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Sol is the small computer system to do the general ledger and the payroll. Solve engineering and scientific problems. Use it for word processing. Program it for computer aided instruction. Use it anywhere you want versatile computer power! Build computer power with our software. At Processor Technology we've tailored a group of high-level languages, an assembler and other packages to suit the wide capabilities of our hardware. It comes on cassette or in a disk version which has random as well as sequential files.
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One of the major problems involved in producing a robot is the design of a sophis- ticated "brain" and "nervous system" for the robot. Since World War II there has been an ever intensifying research effort to produce just such an artificial intelligence. Presently, there are two distinct groups performing this research: neural cybernetists and cognitionists. The first group, the neural cybernetists, are concerned with studying the nervous systems and brains of living organisms in hopes of emulating them with machinery.
To date, this type of research has provided much information about neurons and the entire nervous system in general. From this research, neural cyber- netists have developed noncomputer per- ceptrons artificial intelligence machines. Notable among the perceptrons already built is a system modeled after the pigeon's nervous system, used in missile navigation. The cognitionists believe, however, that highly evolved computer software is the best way to produce artificial intelligence. Although the neural cybernetists and cognitionists are essentially striving toward the same goal, they often refuse to recog- nize each other's research effort.
In the latter, Cote describes the work of neural cybernetists in artificial intelligence and robot research. Cote argues that the computer is a poor device for use in constructing an artificial intelligence. He supports his claim with the old misconception that computers are elec- tronic brains.
He feels that cognitionists have convinced themselves that a computer can become intelligent if programmed properly. Conversely, Feigenbaum and Feldman's book, a collection of published papers, has an opening chapter that, among other things, explains why the editors have ex- cluded all neural cybernetics papers. In part, they argue, cognitionists "believe that intelligent performance by a machine is an end difficult enough to achieve without starting from scratch," as a neural cyber- netist would have to.
It is unfortunate that these two groups continue to hold these views even though the books were written more than a decade ago, since, in my view, combining the two philos- ophies is the only practical way for re- searchers to understand and develop a truly sophisticated artificial intelligence.
My interests in this field prompted me to try to fill the void created by cognitionists and neural cybernetists by developing my own philosophy pertaining to the study and development of artificial intelligence and robot systems in general. Cyberani- metrics is the name I have given this field.
The eye uses a square array of light sensors that simulate the net convexity detectors found in the retina of the frog's eye, used by the frog to detect small, fast moving insects.
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The arm is similarly patterned after the frog's tongue and arm grasping and moving action. Construction of a portion of the eye mechanism is described in part 2 of this article. These animate systems are studied from the standpoint of the information movement that is necessary for the system's operation or survival. Cyber- animetrics combines neural cybernetics and computer cognition with a host of other sciences to analyze both data flow and the structure where this data flow occurs.
By studying biological and mechanical systems from this vantage, the designer becomes aware of the fact that the micro and macrostructures of both types of systems have to be specialized through either evolution or design, so that the system can operate successfully in its environment. Cyberanimetrics is, more than anything else, a study of system specialization. Specialization through good organization is important in any robot or artificial intelli- gence system. But in the past it was thought to be more important to make the system as sophisticated as possible.
Consequentially, many systems built were simply collections of unrelated but extremely advanced de- vices, making it very difficult for the early designs to operate as a system. It is not a major problem in robotics today to achieve complexity in a system; rather the problem has become how to make the complex sys- tems operationally efficient and successful for a given end. Organization is important because one method can result in a much cheaper, more reliable, and less complex system. But to organize a system, the de- signer must first see how other systems are organized.
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This is where cyberanimetrics comes in: instead of examining only the creations of engineers, the designer also examines nature's creations. Inc 13 ioral design aspects of biological systems ie: bionics. Cyberanimetrics allows the designer to appreciate the variety of methods employed by the various systems because both mechanical and biological systems are examined in terms of their similarities in structure and organization.
This means that a person designing a sys- tem must be equally familiar with biology, computer sciences, cybernetics, artificial intelligence, mechanics, and physics.