  This paper briefly analyzes the advantages and problems of AI mainstream
technology and puts forward: To achieve stronger Artificial Intelligence, the
end-to-end function calculation must be changed and adopt the technology system
centered on scene fitting. It also discusses the concrete scheme named Dynamic
Cognitive Network model (DC Net). Discussions : The knowledge and data in the
comprehensive domain are uniformly represented by using the rich connection
heterogeneous Dynamic Cognitive Network constructed by conceptualized elements;
A network structure of two dimensions and multi layers is designed to achieve
unified implementation of AI core processing such as combination and
generalization; This paper analyzes the implementation differences of computer
systems in different scenes, such as open domain, closed domain, significant
probability and non-significant probability, and points out that the
implementation in open domain and significant probability scene is the key of
AI, and a cognitive probability model combining bidirectional conditional
probability, probability passing and superposition, probability col-lapse is
designed; An omnidirectional network matching-growth algorithm system driven by
target and probability is designed to realize the integration of parsing,
generating, reasoning, querying, learning and so on; The principle of cognitive
network optimization is proposed, and the basic framework of Cognitive Network
Learning algorithm (CNL) is designed that structure learning is the primary
method and parameter learning is the auxiliary. The logical similarity of
implementation between DC Net model and human intelligence is analyzed in this
paper.
