How Neural Networks Differ from Traditional Computing and Expert Systems Neural networks offer a different way to analyze data, and to recognize patterns within that data, than traditional computing methods. However, they are not a solution for all computing problems. Traditional computing methods work well for problems that can be well characterized. Balancing checkbooks, keeping ledgers, and keeping tabs of inventory are well defined and do not require the special characteristics of neural networks. Table 2.6.1 identifies the basic differences between the two computing approaches.
Traditional computers are ideal for many applications.
They can process data, track inventories, network results, and protect equipment. These applications do not need the special characteristics of neural networks. Expert systems are an extension of traditional computing and are sometimes called the fifth generation of computing. The second generation occurred because of the development of the transistor. The fifth generation involves artificial intelligence.