The 18th Century: Powered Machines and the Industrial Revolution The invention of the steam engine by James Watt in 1776 represented a major advance in the development of powered machines. It was first applied to an industrial operation - the spinning of cotton - in 1785. A new kind of work-slave it not only marked the beginning of the Industrial Revolution, but also the coming age of mass production. In the England of the 18th century five important inventions in the textile industry advanced the automation of work processes. 1) John Kay's flying shuttle in 1733 , which permitted the weaving of larger widths of cloth and significantly increased weaving speed, 2) Edmund Cartwright's power loom in 1785, which increased weaving speed still further, 3) James Hargreaves' spinning jenny in 1764, 4) Richard Arkwright's water frame and 5) Samuel Crompton's spinning mule in 1779, whereby the last three inventions improved the speed and quality of thread-spinning operations. Those developments, combined with the invention of the steam engine, in short time led to the creation of new machine-slaves and the mechanization of the production of most major goods, such as iron, paper, leather, glass and bricks. Large-scale machine production was soon applied in many manufacturing sectors and resulted in a reduction of production costs. Yet the widespread use of the novel work-slaves also led to new demands concerning the work force's qualifications. The utilization of machines enabled a differentiated kind of division of labor and eventuated in a (further) specialization of skills. While before many goods were produced by skilled craftsmen the use of modern machinery increased the demand for semiskilled and unskilled workers. Also, the nature of the work process altered from one mainly dependent on physical power to one primarily dominated by technology and an increasing proportion of the labor force employed to operate machines.

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Expert system Expert systems are advanced computer programs that mimic the knowledge and reasoning capabilities of an expert in a particular discipline. Their creators strive to clone the expertise of one or several human specialists to develop a tool that can be used by the layman to solve difficult or ambiguous problems. Expert systems differ from conventional computer programs as they combine facts with rules that state relations between the facts to achieve a crude form of reasoning analogous to artificial intelligence. The three main elements of expert systems are: (1) an interface which allows interaction between the system and the user, (2) a database (also called the knowledge base) which consists of axioms and rules, and (3) the inference engine, a computer program that executes the inference-making process. The disadvantage of rule-based expert systems is that they cannot handle unanticipated events, as every condition that may be encountered must be described by a rule. They also remain limited to narrow problem domains such as troubleshooting malfunctioning equipment or medical image interpretation, but still have the advantage of being much lower in costs compared with paying an expert or a team of specialists.

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