Abstract
Today a very tenuous and as yet undeveloped way of dealing with the imprecise situations is provided by the attributes of the various Artificial Intelligence (AI) programming languages and techniques. To acquire this understanding the professional AI computer scientist who creates useful programs for decision support and automation needs to be tightly coupled to the manufacturing application expert. The grandfather of AI was the English philosopher Thomas Hobbles whose life and ideas are discussed by Haugeland. In the 1650s his concept of thinking in terms of symbolic representation formed the basis of todays’ AI technology. The use of symbolic representation and methodicial rules made the thinking process clear and rational. Computer science is being served by its AI prodigy through the development of support systems for programming and debugging. AI is also creating incentives for new types of computing architecture and hardware that better support AI applications.
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