“Nobody is going to beat the gigantic companies with their gigantic song generators, but who wants to?”” says Zachary Novack, a graduating Ph.D. student who will join Spotify.
“The idea of ‘press a button and we’ll generate the song’ is boring to me,” he said. “It’s a toy, but it’s not actually fun. Nobody is going to beat the gigantic companies with their gigantic song generators, but who wants to?”
Novack, advised by Berg-Kirkpatrick and UC San Diego Jacobs School of Engineering Professor Julian McAuley, has been active in helping grow the AI music community at UC San Diego. His research asks how generative music systems can move beyond one-shot song generation and become more like instruments — tools artists can play with, shape, challenge and even creatively misuse.
At the 2025 UC San Diego GenAI Summit, Novack argued that researchers should include musicians and artists throughout the development of AI systems. That philosophy runs through Novack’s work. As co-creator of Presto, a model for accelerating music generation, he has explored how to make AI music systems faster and more interactive.
In one recent project, Novack worked on making open-source generative music models responsive enough for real-time interaction. The goal was to shrink and speed up models so they could run locally, respond to controls such as pitch and volume, and become part of a performance setup.
One experimental result was unusual but revealing: a model trained on whale sounds and used in a performance with cello. The system functioned almost like a generative delay effect, responding to the performer in ways that were strange, imperfect and creatively suggestive.
Those collaborations reinforced Novack’s conviction that creative AI tools work best when artists are involved from the beginning — not as end users brought in at the finish, but as collaborators who shape what the system should do.
After graduation, Novack will join Spotify, where he expects to continue working on artist-first AI music research.
Recognition in Generative Music Competition
Another UC San Diego student, Anthony Wang, also recently earned recognition for AI music research with Dubnov. Wang, a first-year master’s student in computer science, won second place in the efficiency track of the IEEE International Conference on Multimedia Expo’s Academic Text-to-Music Generation Grand Challenge.