On August 15, 2022, an Industry Q&A session hosted by Comet brought together Abubakar Abid of Gradio and Jakub Jurovych of Deepnote to discuss the evolving landscape of collaboration in machine learning (ML). As ML teams become more interdisciplinary, the need for sustainable collaborative tools is increasingly important. The discussion highlighted how collaboration in ML parallels stages in writing, requiring both individual and group efforts to capture the full value of collaborative work. A central theme was the importance of domain expertise in building effective models, with Abubakar advocating for validation through real-world application by experts rather than just traditional metrics. Both speakers envisioned a future where data scientists are integrated across different business areas, and advanced collaborative tools enable a single data scientist to achieve what once required a full team. The session underscored the significance of cross-functional collaboration in advancing ML and invited further engagement through Comet’s YouTube playlist and newsletter.