Data Labeling Insights

Identifying failure modes is crucial for effective data labeling. For computer vision, enriching data with segmentation and bounding boxes is essential, while large language models allow for more flexibility by enabling users to generate prompts and responses independently. The process of retraining models on this data remains similar, with evaluation being a key aspect to explore further.