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.

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Artificial intelligence (AI) has made significant strides in recent years, largely due to ...

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, ...

New data classification feature transforms how enterprises build high-quality training data, delivering up to 80% faster results and 25% improvement in consistency, without sacrificing quality SAN ...

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