December saw the introduction of new features and improvements in Labelbox aimed at enhancing the search and organization of visual and natural language data. Key updates include the ability to preview HTML data rows for efficient data selection, conduct search queries on plain text, and utilize AI-powered natural language search on both text and images to quickly locate relevant data. These enhancements facilitate the identification and prioritization of data for labeling, thereby improving model performance. The updates are being gradually rolled out across Labelbox's Catalog, Annotate, and Model products, with an option for early access via user ID submission. Additionally, the HTML editor now supports detailed previews, while display settings have been improved to allow viewing of data row IDs like global key or external ID for precise data selection. The latest Python SDK version introduces a method to clear global keys and support for creating large data batches, complemented by new guides and tutorials on data curation and active learning.