Data is essential for the success of any artificial intelligence (AI) project, but understanding what makes data beneficial—or harmful—for AI is crucial. At a high level, machine learning (ML) and AI ...

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, ...