Data labeling is a crucial step in any machine learning project, as it provides the ground truth for training and evaluating models. However, data labeling can also be a tedious, time-consuming, and ...

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, ...