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 world around us.

Imagine it rsquo;s a rainy Tuesday in February 2026 . An autonomous delivery robot is navigating a busy metropolitan sidewalk .

Scale AI—which helps companies like ChatGPT improve the data that feeds their systems—is pictured on a laptop in New York on Aug. 16, 2023. Scale AI—which helps companies like ChatGPT improve the data ...

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, ...

The pancreas and tumor are represented by the colors orange and green, respectively. Given the weak label, we expand it to a lesion marker (teal green) and background markers (red). We then utilize ...

In many embodiments, machine classifiers may process the set of data to identify particular features within the data. Scoring data can be generated, based on annotations provided by other adjuster ...