History of Computing

What is the impact of computer artificial intelligence (AI) on society? A computer might be described with deceptive simplicity as “an apparatus that performs routine calculations automatically.” Such a definition would owe its deceptiveness to a naive and narrow view of calculation as a strictly mathematical process. In fact, calculation underlies many activities that are not normally thought of as mathematical. Walking across a room, for instance, requires many complex, albeit subconscious, calculations. Computers, too, have proved capable of solving a vast array of problems, from balancing a checkbook to even-in the form of guidance systems for robots-walking across a room. Before the true power of computing could be realized, therefore, the naive view of calculation had to be overcome. The inventors who laboured to bring the computer into the world had to learn that the thing they were inventing was not just a number cruncher, not merely a calculator.  This has be en g​ener at ed  wi᠎th GSA C​ontent Gen​erat or  DE MO!

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Darker colors tend to intimidate visitors. Black and other dark colors may contribute to a more drab and depressing office environment, which may be detrimental to employee morale and hinder office productivity. Studies have shown that office workers who are surrounded by lighter colors are usually more productive than those who are surrounded by dark colors. So, if you are striving for more productivity in the office, then you may want to consider a lighter office color scheme. Do You Really Need A Desk That Big? One of the biggest reasons why people buy the l shaped computer desk is the large amount of available desk space. But, what if you don’t need all of that extra space? After all, when compared to desks with less available desk space, this desk is significantly more expensive. Why pay for the extra space if you don’t need it? If you don’t have a computer and the peripherals that often go along with it, then you might just be throwing money out the window.

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Whereas incomplete or incoherent theories may be advanced at some stage of scientific inquiry, this is not the case for programs. On the other hand, Moore (1978) considers the programs-as-theories thesis another myth of computer science. As programs can only simulate some set of empirical phenomena, at most they play the role of computational models of those phenomena. Moore notices that for programs to be acknowledged as models, semantic functions are nevertheless needed to interpret the empirical system being simulated. However, the view that programs are models should not be mistaken for the definition of programs as theories: theories explain and predict the empirical phenomena simulated by models, while simulation by programs does not offer that. According to computer scientist Paul Thagard (1984), understanding programs as theories would require a syntactic or a semantic view of theories (see the entry on the structure of scientific theories). But programs do not comply with either of the two views.

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