Abstract: Data labeling, a job once outsourced by grad students to hungry undergrads paid in pizza, has grown and evolved into a +$1B industry. In my talk I will discuss the evolution of data labeling from the humble bounding box around a cat, to software platforms and global operational teams who clean, sort, label, and report on labeled data. My goal is to shed light on the data labeling challenges of today, both for ML/AI and data labeling companies. Finally, I hope to leave you all with guideposts and bread crumbs that lead you all down a better path to success in your data curation, creation, and operations endeavors.
Bio: Soo has been working with Computer Vision, Machine Learning Engineers, and Research Scientists, across industries to create training datasets for the last 4+ years. As a Solutions Architect at iMerit, she helps our clients by connecting the dots between the technical details of tooling, designing annotation workflows, and integrating a remote data labeling team for the execution. Previously, Soo served as the Data Operations Manager at a geospatial analytics startup where she built and scaled a Data Operations team from the ground up, leading a team 10 analysts.