The Creation of Computers that Surpass Human Though

Typical definitions we might break dance would include concepts bid leaves and branches. However, consider that the computer also has no concept of what branches or leaves are, either; so these concepts need to be defined as well if they are to be of each use. Also, even if a computer could understand these ideas, how would you rationalize to a machine how to tell a leafless steer in the winter from a telephone pole? After all, some(prenominal) see "branches" and in the winter neither one has leaves (AbuMostata and Psaltis 92).

From the difficulties we have had trying to describe a tree in comminuted terms, it seems clear that we don't use a conventional computer's method of business solving. After all, we can identify treeswith or without leaveswith little difficulty, and advert trees from other objects like telephone poles that possess many treelike characteristics. In fact, we do use a only different method of job solving that involves what scientists consider the keystone to random caper solving: associative memory (AbuMostata and Psaltis 92). season the workings of associative memory are still a mystery for neuroscientists, its existence is undeniable; for we use it nearly every moment of our lives. Stated simply, this phenomenon is what occurs when, for instance, you see a picture of firm and immediately think of your family, your dog

However, this mildew of the human brain may have severe limitations for devil main reasons. First, the body and the brain are inseparably conjugate by a variety of bodily chemicals including common compounds like hormones. These chemicals can have a large impact on the brain's functioning; for example, scientists now trust that higher quantities of estrogen flash back the brain's ability to work spatial problems, a theory that would explain why women tend to solve these problems less effectively than men. Also, philosophers believe that if the functioning of the brain is reduced to purely mechanical processes, eject will is destroyed. In other words, if the brain follows intelligible laws, the brain's chemical reaction can be predicted from this knowledge.

This action, then, ceases to be free will and fundamentally becomes a machine following its programming (Cast) and Karlqvist 185).

Unfortunately, neural meshing technology has two types of weaknessesthose inherent to vanes and those externalresulting from the technology's youth. The first problem inherent to networks is the difficulty in narrowing the amount of study that must be dealt with. For example, when Bell Laboratories designed a network to read handwritten zip codes they reported this limitation of tuition to be the biggest developmental problem (O'Reilley 92). The fact is our brains have trillions of neurons much than a neural network; yet our brains regularly frame out huge amounts of information. When we consider all of the things we forget or never even notice in an oridinary day, the task of limiting the informatlion a network has to deal with comes into focus. For example, many of us in all probability can't remember the color of our neighbor's car or what the King of police wagon is holding in his hands despite having viewed these objects hundreds of times. The other problem is even more fundamental to the structures of neural networks; like us, they put to death algorithmic functions slowly and imprecisely (Abu
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