e set of data. CBR has been proposed as a more psychologically plausible model of the reasoning used by an expert while expert systems use more fashionable rule-based reasoning systems (Riesbeck 9). This type of system uses a different computational element that decides the outcome of a given input. Instead of rules in an expert system, CBR uses cases to evaluate each input uniquely. Each case would be matched to what a human expert would do in a specific case. Additionally this system knows no right answers, just those that were used in former cases to match. A case library is set up and each decision is stored. The input question is characterized to appropriate features that are recognizable and is matched to a similar past problem and its solution is then applied. Now that each type of implementation of AI has been discussed, how do we use all this technology? Foremost, neural networks are used mainly for internal corporate applications in various types of problems. For example, Troy Nolen was hired by a major defense contractor to design programs for guiding flight and battle patterns of the YF-22 fighter. His software runs on five on-board computers and makes split-second decisions based on data from ground stations, radar, and other sources. Additionally it predicts what the enemy planes would do, guiding the jet's actions consequently (Schwartz 136). Now he and many others design financial software based on their experience with neural networks. Nolen works for Merrill Lynch & Co. to develop software that will predict the prices of many stocks and bonds. Murry Ruggiero also designs software, but his forecasts the future of the Standard & Poors index. Ruggiero's program, called BrainCel, is capable of giving an annual return ! of 292%. Another major application of neural networks is detecting credit card fraud. Mellon Bank, First Bank, and Colonial National Bank all use neural networks that can determine the diff...
