The Critical Role of Annotations
Annotations play a crucial role in AI training:
- Definition: Annotations are labels or descriptions attached to raw data, providing context and meaning.
- Purpose: They serve as guideposts, teaching models to distinguish between different concepts, objects, or ideas.
- Example: In image classification, photos labeled "kitchen" help a model learn to identify kitchen characteristics (e.g., presence of appliances, countertops).
- Importance of accuracy: Mislabeled data (e.g., labeling kitchen images as "cow") can lead to severely misguided models, highlighting the need for high-quality annotations.