What is the difference between neuron computing and traditional artificial intelligence computing?

First, refer to different

1, artificial intelligence: It is a new technical science to study and develop theories, methods, technologies and application systems that simulate, extend and expand human intelligence.

2. Neural network: it is an algorithmic mathematical model that imitates the behavioral characteristics of animal neural network and carries out distributed parallel information processing.

Second, the methods are different.

1, artificial intelligence: trying to understand the essence of intelligence and produce a new intelligent machine that can respond in a way similar to human intelligence. The research in this field includes robot, language recognition, image recognition, natural language processing and expert system.

2. Neural network: according to the complexity of the system, the purpose of processing information is achieved by adjusting the relationship between a large number of internal nodes.

Third, the purpose is different.

1, artificial intelligence: The main goal is to make machines perform complex tasks that usually require human intelligence.

2. Neural network: initial adaptive and self-organizing ability. The value of synaptic white changes in the process of learning or training to meet the requirements of the surrounding environment. The same network may have different functions due to different learning methods and learning contents.