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 .

Data annotation, or the process of adding labels to images, text, audio and other forms of sample data, is typically a key step in developing AI systems. The vast majority of systems learn to make ...

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 ...

Different projects require different workflows. In data annotation platforms, flexible workflows help manage quality, speed, and complexity. Rigid workflows can lead to delays and errors, especially ...

Autonomous vehicles rely on high-quality data annotation to train AI/ML models for safe and intelligent driving. This blog explores how sensor data from cameras, LiDAR, and radar is annotated using ...