Covering everything you need to know in order to build AI products faster.
Teams can easily train an open-source model on their own data and use Labelbox's suite of tools across Annotate, Catalog, and Model to quickly tailor their language model to meet their specific business needs.
Labelbox•September 30, 2022
Efficiently improve models in development and production by using a third-party model, such as HuggingFace, to guide and identify targeted improvements in your training data to boost model performance.
Labelbox•September 23, 2022
Aligning with your team on key terms used in Labelbox will serve to greatly enhance collaboration and cohesiveness throughout your work in the platform. In this brief video, we introduce the fundamental elements of the Labelbox Editor.
Labelbox•September 22, 2022
Ontologies are an essential part of Labelbox's platform. You'll need to select an ontology when you create a new project or model. Learn how to create, reuse, and manage your ontologies and features.
Labelbox•September 2, 2022
Get a primer on data labeling, defined as the task of detecting and tagging data with labels, most commonly in the form of images, videos, audio and text assets.
Labelbox•August 19, 2022
Image segmentation is used to label images for applications that require high accuracy and is manually intensive.
Labelbox•August 17, 2022
Image annotation is defined as the task of annotating an image with labels. Discover how an AI data engine supports image annotation at scale.
Lisa Dimyadi•August 1, 2022
