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.

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

Annotation involves labelling data sets to make them more valuable to human readers or machines. As a result, annotation is quickly becoming an important sub-discipline within machine learning, where ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Artificial intelligence is blamed for taking away thousands of jobs. But, it also creates a few — at least for now. That’s because some artificial intelligence systems are still pretty dumb. They need ...