Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

Artificial intelligence systems are only as powerful as the data they are trained on. High-quality labeled datasets determine whether a model performs with precision or fails in production.

Data science and machine learning teams face a hidden productivity killer: annotation errors. Recent research from Apple analyzing production machine learning (ML ...

Labeling and annotation are the foundation of context setting and the invisible backbone of AI, which are quietly shaping the ...

Tending crops by day and then logging on for a night shift of data labelling, 27-year-old Chandmani Kerketta is part of a rising rural Indian workforce helping power an artificial intelligence ...