Data Scaling Insights

Kate and Daniel discuss the importance of data scaling in ML systems, emphasizing the need for continuous improvement while considering resource constraints. They delve into prioritizing efforts based on performance gains and recognizing when to pivot towards architectural changes for further enhancements.