The field of music and artificial intelligence is rapidly evolving, with a growing focus on exploring the creative potential of AI as a co-creative tool and artistic medium. Researchers are investigating innovative applications of AI in music, including the use of AI in live performances and installations, and the development of new formats such as online installations. A key challenge in this area is the need for more robust and human-aligned AI vision systems, which can be informed by the study of visual illusions and their effects on human and artificial perception. Another important area of research is the development of automated music emotion annotation systems, which can reduce the resource and labor burdens associated with manual labelling. Noteworthy papers in this area include:

• A study on the feasibility of large language models for automated music emotion annotation, which found that while these models have limitations, they offer a promising scalable alternative.
• A paper on the effectiveness of training from scratch on a medium-scale violin dataset for automatic music transcription, which suggests that strong violin AMT is possible without relying on pretrained piano representations.