Researchers in the area of AI had once hoped that a generalized intelligent system would be able to “grease a car or read Shakespeare tell a joke or play office politics”. The problem of generalized intelligence has been plaguing the field of Artificial Intelligence (AI) since its inception in the early 1960s. This approach will require a system of systems approach that uses many AI techniques: neural networks, fuzzy logic, and cognitive architectures. So the question remains: Why is generalized intelligence so difficult? If complex tasks require a significant amount of development, time and task generalization is not easily accomplished, then a significant amount of effort is going to be required to develop an intelligent system. Other examples of AI programs which learned and played games were successful at specific tasks, but generalizing the learned behavior to other domains was not attempted. However, Deep Blue only played chess it did not play checkers, or any other games. ![]() Deep Blue, the chess playing supercomputer, was developed to defeat the top rated human chess player and successfully did so by defeating Gary Kasporov in 1997. Generalized intelligence is much more difficult than originally anticipated when Artificial Intelligence (AI) was first introduced in the early 1960s.
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