The difference between artificial intelligence language and traditional language

People may ask, what is the difference between using artificial intelligence language to solve problems and traditional methods?

Traditional methods usually express all the knowledge of the problem in a fixed program with various models, and solve the problem step by step (item by item) under the guidance of the program. The method to solve the problem is consistent with the structure of von Neumann computer. At present, large-scale database methods, mathematical model methods and statistical methods are all strictly structured methods.

For the problems to be solved by artificial intelligence technology, it is often impossible to embody all the knowledge in a fixed program. It is usually necessary to establish a knowledge base (including facts and inference rules), and the program decides its own actions according to the environment, given input information and problems to be solved, so it is an inference process under the guidance of the environment model. This method has great flexibility, dialogue ability, self-explanation ability and learning ability. This method is superior to the traditional method for some unstructured problems whose conditions and objectives are unclear or incomplete (that is, they cannot be well formalized and described). It usually adopts heuristic and heuristic strategies to solve problems.

The difference between artificial intelligence program and traditional program

When dealing with some simple problems, there is no difference between traditional methods and methods used by artificial intelligence. However, when solving complex problems, artificial intelligence methods are different from traditional methods. Artificial intelligence method: The problem to be solved by artificial intelligence cannot embody all the knowledge in a fixed program. It wants to build a knowledge base (including facts and inference rules), and the program decides its own actions according to the environment, given input information and problems to be solved, so it is an inference process under the guidance of the environment model. This method has great flexibility, dialogue ability, self-explanation ability and learning ability. This method is more suitable for solving some ill-structured problems than traditional methods. Weak structure means that "X" and "Y" are unclear or incomplete, that is, they cannot be well formalized and described. "->" through trial and error. AI has not developed to completely solve all the problems of this kind of problem. This kind of problem is the problem to be solved in AI research. I also hope that there will be a revolution in computer hardware structure and a breakthrough in von Neumann architecture.