Streamlined data management and key editor improvements
We've focused recent product development on streamlining essential data management workflows and are introducing new collaboration tools for labeling operations and labeling teams. We’ve also made some key updates to our Editors that enable more complex ML use cases and improve usability.
How to use embeddings to create high-quality training data
Functions and embeddings are a powerful way to quickly search and explore your unlabeled and labeled data. Using them can help you break down silos across datasets so you can focus on curating and labeling the data that will most significantly improve model performance.
We’ve made improvements to Model Diagnostics that give users access to more insightful comparison metrics and support for additional data types. We’ve also expanded model-assisted labeling (MAL) to support video bounding boxes, and are excited to offer MAL for all paid customers.