Blog

How to get the most out of your labeling operations

Teams that monitor and refine their labeling operations realize significant savings in time and costs, and can more accurately estimate future requirements.

New study finds that non-expert labeling teams can create high quality training data for medical use cases

Imperial College London’s BioMedIA research group and the iFind Project set out to challenge the assumption that only those medical training can provide quality annotations for clinical deep learning models.

New text editor features: Annotation relationships + issues & comments

We’re excited to introduce our updated text editor, which makes it easy for teams to collaborate and use Labelbox for more complex NLP use cases.

Accelerate your computer vision journey with YOLOv5 and Labelbox

Labelbox customers can now combine any of the YOLOv5 models with our training data platform.

NASA’s Jet Propulsion Laboratory employs ML to find signs of life in our solar system

Does life exist beyond our planet? This ML team is training an algorithm to help researchers find life elsewhere in our solar system.

Productionizing unstructured data for AI & analytics: 3 key takeaways

At the Data + AI Summit last week, Labelbox launched a connector between Labelbox and Databricks.

Ontology management with Labelbox

Being able to quickly create, edit, and reuse ontologies is key to faster iteration cycles in machine learning.

How Sharper Shape built a robust ML pipeline with Labelbox and Valohai

Learn how Sharper Shape currently utilizes Labelbox and Valohai to collaborate more efficiently and take advantage of both platforms to manage a mature and large-scale machine learning operation.

Simplify collaboration with Issues and Comments

We’re excited to make collaboration and communication within and across teams in Labelbox even easier with the introduction of Issues and Comments.

How Move.ai is revolutionizing video content creation

Emerging AI company Move.ai is set to change the status quo, making processes like motion capture and key point recognition easier, faster, and less expensive.