Technology evolves, and it surrounds the whole world in its impact by offering several solutions to different problems and issues. As Generative AI is one of the biggest technology trends through the latest advancements in artificial intelligence (AI).
GenAI utilizes machine learning (ML) algorithms to generate different products and content using large databases. Here comes the data labelling process to label certain data to indicate ML to what data should be used.
Doing it manually is frustrating, so there are several data annotation tools, like Labelbox and SuperAnnotate. If you’re willing to know how to use a data annotation tool, then I have chosen the Labelbox to guide you.
Let’s Start!
What is Labelbox?
Labelbox is a data annotation tool that allows individuals to annotate and label data from large databases for ML projects. It provides users with multiple exceptional features, such as AI-assisted labelling, quality checks, model diagnostics, and workflow management.
These features allow users to have a one-stop tool for labelling and managing data in various formats, whether images, text, or videos. Further, this approach enables users to have the best outcomes through improved accuracy and enhanced efficiency.
Features of Labelbox
Here are some of the features of Labelbox.
AI Assisted Labelling
Artificial intelligence labelling is more accurate than humans because it reduces human errors and mitigates several tasks. Furthermore, this feature allows users to automate the process of labelling data in an accurate and beneficial manner.
Quality Checks
This data annotation tool offers two quality analyses to ensure that the data that is labelled is accurate and performable. It is called benchmarking data for enhanced outcomes through effective designation and gold standards.
Model Diagnostic
The model diagnostic feature is also AI-powered, enabling users to diagnose, improve, and fix data sets to achieve significant outcomes. Moreover, it allows users to reduce human errors that will also impact the creation or generation through GenAI.
Workflow Management
Workflow management servers as a backbone to conduction because of higher customizability and extensive reviews on the pipeline. Labelbox provides its users with workflow management features to do that all for enhanced results and outcomes.
LLM Data Generation Editor
Large language model (LLM) data generation editor feature is the most fascinating from other features because of its capabilities. This feature offers individuals to prepare a prompt dataset and give response to fine tune LLM to achieve their goals.
Labelbox Pricing
- Free: 500 LBUs per month
- Starter: $0.10 per LBU
- Enterprise: Contact the Sales Team
Pros & Cons of Labelbox
| Pros | Cons |
| Scalable for large projects | Costly |
| Exceptional integration | Occasional glitches |
| Improved automation | |
| Excellent customer support |
How to Use Labelbox
Here, I have compiled an easy guide on how to use Labelbox.
- Access- Firstly, you need to access the tool on your preferred laptop or personal computer on a new tab. Alternatively, you can access the site through this: https://labelbox.com/.
- Labelbox Login- Now, you need to sign up for an account to have LBUs (Labelbox Units) to perform certain tasks.
- Create API: If don’t have a Labelbox API, then you have to generate an API for annotating data.
- Save the API: You can save the API key in a secure location on the platform. Finally, you are free to make use of LBUs to annotate data for improved results.
Final Talk
Data annotation has become more important than ever to achieve the desired outcomes from GenAI through machine learning (ML) algorithms. That’s why you need to use a data annotation tool, like Labelbox to annotate data for exceptional outcomes.
In the above section, I have mentioned some of the features, pricing, and how to use the LBUs for data annotation. Hopefully, this guide will be helpful for you to enjoy enhanced results.
