The potential of neural networks in generating photorealistic content for media

Section: New Media

Digitalization is profoundly transforming the media landscape and the practices of journalism. Among the most pressing challenges is the emergence of artificial intelligence. Currently, the most advanced application of AI lies in the generation of text and illustrations, although significant progress is being made with other formats as well. This article posits that neural networks have already reached a stage where they can serve as a substitute for photographic images. To substantiate this hypothesis, the study analyzes five widely used AI illustration generators: Midjourney, Leonardo, Kandinsky, Stable Diffusion, and Shedevrum. The research employs a survey methodology, with 293 respondents participating. Participants were presented with illustrations generated by the aforementioned neural networks alongside authentic photographs and tasked with identifying the genuine photographs from the AI-generated images. The findings indicate that each neural network examined is capable of producing images indistinguishable from photographs. However, certain neural networks currently exhibit superior quality and efficiency in this task compared to others.

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To cite this article: Mukhina O. S., Oleshko V. F. (2025) Potentsial neyrosetey v generatsii fotorealistichnogo kontenta dlya media [The potential of neural networks in generating photorealistic content for media]. Vestnik Moskovskogo Universiteta. Seriya 10. Zhurnalistika 4: 78–95. DOI: 10.55959/msu.vestnik.journ.4.2025.7895