Labelbox

What is Labelbox?

Labelbox is a platform that acts as a data factory for generative AI, offering high-quality data to prominent model builders and enterprise AI teams. It provides a comprehensive platform that combines expert labeling services on demand with a leading data labeling platform. Labelbox's approach prioritizes software to deliver exceptional quality, control, and efficiency. Additionally, Labelbox collaborates with Google Cloud to provide a fully managed Large Language Model (LLM) evaluation solution integrated into the Vertex AI platform. This partnership enables Google Cloud customers to easily conduct human evaluation jobs with specific criteria and receive high-quality results quickly.

Who created Labelbox?

Labelbox was created by Manu Sharma, Brian Rieger, and Matthew Baas. The company was launched on February 17, 2021. Labelbox operates as a global data labeling infrastructure and operations provider for the biggest AI workloads worldwide, offering a platform for data curation, AI-assisted labeling, model training & diagnostics, and labeling services. They work with a global expert human network for high-quality data labeling across various domains of science, technology, and language. Labelbox's software-first approach focuses on delivering unmatched quality, control, and efficiency in data labeling services, with customers including Fortune 500 enterprises and leading AI labs.

What is Labelbox used for?

• AI assisted alignment
• Optimized for quality and control
• Technology and software
• Building AI applications
• Training and fine-tuning models
• Automating tasks with Labelbox Machine Learning Models
• Data curation
• Labeling services
• Model training and diagnostics
• Global network of expert humans

Who is Labelbox for?

• AI teams
• Data labeling managers
• Model trainers

How to use Labelbox?

Labelbox is a powerful data labeling platform used for various AI workloads. Here is a step-by-step guide on how to use Labelbox effectively:

1. Accessing the Platform: Sign in to Labelbox and access the user-friendly interface.

2. Data Upload: Upload your data, which could include text, images, chat conversations, JSON, and audio files, depending on the Labelbox product you are using (Catalog, Annotate, Model).

3. Labeling Process:

   • For basic data rows, the number of LBUs consumed varies based on the product used.
   • In Annotate, each basic data row labeled equals one LBU, regardless of the number of labels.
   • In Model, five basic data rows equal one LBU, irrespective of the number of model runs.
   • In Catalog, sixty basic data rows equal one LBU per month.

4. Understanding LBU Consumption:

   • LBUs are consumed when data is uploaded to the Catalog.
   • LBUs are consumed in Annotate when labels are approved or data rows are marked as 'done.'
   • LBUs in Model are consumed when data is used in model runs or model predictions.

5. Managing LBUs:

   • Monitor LBU consumption to avoid exceeding limits.
   • Exceeding the free tier limit of 500 LBUs per month may restrict new data additions until an upgrade.

6. Labelbox Billing:

   • Billing is based on LBU consumption, with additional platform fees for enterprise plans.
   • Discounts based on annual LBU commitments are available for Enterprise users.

7. Labeling Services:

   • Labelbox Boost provides on-demand labeling services and complete AI solutions tailored to specific needs.

8. Automation and Cost Efficiency:

   • Labelbox offers automation features like pre-labeling to reduce labeling time and costs.
   • Model-assisted labeling can reduce labeling time and cost by 50-70%.

9. Data Security:

   • Labelbox ensures data security, offering a secure environment for data labeling and management.

By following these steps, you can efficiently use Labelbox for your data labeling needs and leverage its features for AI model development and evaluation.