The synergistic effect of artificial intelligence technology in the evolution of visual communication of new media art.

This study aims to clarify the synergistic effect of artificial intelligence (AI) technology in the evolution of visual communication of new media art, thereby exploring an AI layout design method based on Convolutional Neural Network (CNN) in the practice of visual communication design. Firstly, this study designs an AI layout design model based on CNN, and trains and optimizes it with training data. Secondly, the automatic generation of layout design is realized by constantly adjusting the model parameters and network structure. Finally, various AI layout design algorithms are compared, and their effects and performances in layout design generation are analyzed. To verify the layout and composition matching model's performance, traditional layout design methods are selected for comparison (layout, comparison, harmonic composition, etc.). This study involved 20 design students as participants, evaluating them across three dimensions: overall comprehensive assessment, readability of text information, and rationality of visual path using a Likert 7-point scale. The results reveal that the proposed method's evaluation outcomes in these three aspects are 5.95, 5.68, and 5.74, respectively, higher than the traditional layout design methods. To sum up, the generative AI discussed here can automatically generate design elements and schemes through deep learning and big data analysis, thus providing a reference for the innovation of visual communication design.