For AI training, what is considered high quality data?
High-quality data for AI training refers to data that is:
- Accurate: Free from errors, inconsistencies, and inaccuracies.
- Complete: Includes all relevant information and is not missing any critical data points.
- Relevant: Relevant to the specific task or problem being addressed.
- Diverse: Includes a wide range of examples, scenarios, and edge cases to help the model generalize well.
- Well-annotated: Has clear, consistent, and accurate annotations or labels.