Application of artificial intelligence in painting and music

Mohammadreza Moradi¹ Sima Rastegar² Ali Fatehi³ Kianmehr Karimzadeh⁴ Borna Nael⁵

1) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
2) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
3) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
4) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran
5) The Researcher of Damesh Sepahan Research and New Technologies Center, Isfahan, Iran

Publication : 3rd International Conference on Recent Advances in Engineering, Innovation and Technology - Belgium(eitconf.com/3rd)
Abstract :
Artificial intelligence (AI) has brought about significant changes in the fields of art in recent years, especially in painting and music. Models based on deep learning and generative neural networks (GANs) have been able to create works that resemble human artwork in style and quality. In painting, tools such as DALL·E and DeepArt help artists experiment with new styles. In music, algorithms such as OpenAI’s MuseNet and Google’s Magenta are able to produce musical pieces in different styles. This article examines AI methods in these two fields, their impact on contemporary art, and the challenges associated with it. As one of the most important emerging technologies, AI has had a profound impact on the fields of art, especially painting and music. Deep learning algorithms, especially generative neural networks (GANs) and neural style blending (NST), have enabled the creation of digital artworks that closely resemble human works in style and quality. In painting, tools such as DALL·E and DeepArt help artists experiment with new styles and produce creative works. In music, AI systems such as MuseNet and Magenta have been able to create musical pieces in different styles and assist composers in the creative process. Despite these advances, challenges such as the lack of human creativity, intellectual property issues, and the valuation of AI-generated artworks remain. This article examines the different approaches of AI in painting and music, their impacts on contemporary art, and the challenges ahead.
Keywords : artificial intelligence digital painting smart music deep learning generative neural networks digital art