Abstract
This chapter focuses on three key problems encountered by AI at present, which are interpretability, learning, and common sense. Artificial intelligence applications aim to output decision-making judgments. Interpretability refers to the degree to which humans can understand the reasons for a decision. The higher the interpretability of the artificial intelligence model is, the easier it is for people to understand why certain decisions or predictions are made. And it is easier for machines to learn and transfer this homogeneous and linear similar system. However, it is challenging to realize the analogy and conversion of heterogeneous and nonlinear similar systems. At present, the understanding and definition of artificial intelligence in various fields differ because of the field distinction, but there is consensus in common technologies and basic research. Solutions of these problems have become the key to the continuous development of artificial intelligence.
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