Our paper, “Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision”, has been accepted for publication at the 2023 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies conference (BDCAT). Focusing on the transformative impact of deep learning, especially with Trillion Parameter Models such as Huawei’s PanGu-Σ, our paper presents a visionary ecosystem tailored to meet the evolving needs of the scientific community. Delving into the technical challenges associated with serving Trillion Parameter Models for groundbreaking discoveries, the paper outlines essential requirements for a robust software stack and flexible interfaces.