Music poses unique and complex challenges for artificial intelligence, even as 21st-century AI grows ever more adept at generating media. The AI Music Problem: Why Machine Learning Conflicts With Musical Creativity asks why producing and constructing music is difficult for AI, with an investigation that straddles the technical, the musical, and the aesthetic. Bringing together the perspectives of the humanities and computer science, the author shows how the difficulties that music poses for AI connect to larger questions about music, artistic expression, and the increasing ubiquity of artificial intelligence.
Taking a wide view of the current landscape of machine learning and Large Language Models, The AI Music Problem offers a resource for students, researchers, and the public to understand the broader issues surrounding musical AI on both technical and artistic levels. The author breaks down music theory and computer science concepts with clear and accessible explanations, synthesizing the technical with more holistic and human-centric analyses. Enabling readers of all backgrounds to understand how contemporary AI models work, and why music is often a mismatch for those processes, this insightful book is relevant to all those engaging with the intersection between AI and musical creativity today.
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