From Imitation to Creation: When Music AI Truly Understands
By Ziyu Wang (online)

Ziyu Wang will give a talk on “From Imitation to Creation: When Music AI Truly Understands”

Abstract

Recent advances in generative AI have led to impressive achievements in music generation. Yet, a fundamental challenge remains: how can these black-box models move beyond imitating music data to truly understand human creative intent and collaborate meaningfully with humans? We argue that the missing piece is a deeper alignment between humans and AI—one that involves shared musical concepts, structured knowledge, and even the principles behind how we learn music. In this talk, I will explore various approaches to establish such alignment in generative modeling, which naturally enhances model interpretability and controllability in music generation. Ultimately, we may find that the heart of this alignment challenge lies in understanding content and style, a timeless question that resonates across art and life.

Biography

Ziyu Wang is a PhD candidate in Computer Science at the Courant Institute of Mathematical Sciences, New York University, and holds an affiliation with NYU Shanghai. Currently, he is also a visiting scholar in the Machine Learning Department at MBZUAI. His research is conducted under the supervision of Prof. Gus Xia in Music X Lab, where he explores the intersection of music and machine learning. In 2019, he earned his undergraduate degree in Mathematics from Fudan University. Beyond his academic pursuits, he is a passionate conductor, pianist, and Erhu (a traditional Chinese string instrument) player. He has previously served as the conductor of the NYU Shanghai Jazz Ensemble and as the director of the Fudan Musical Club.