Labelbox Blog

Automate labeling with your own model

Model-assisted labeling from Labelbox is the fastest way to improve model performance. Reduce labeling costs by up to 50-70% with your own model.

Featured

Labelbox | a month ago | 3 min read

Using Labelbox to optimize crop production

Learn how Labelbox's training data platform plays a central role in xarvio's ML pipeline to handle the full data annotation process and help farmers innovate through digital farming.

Featured

Labelbox | 9 months ago | 2 min read

Labelbox February Updates

Winter is drawing to a close, the birds are out, and here at Labelbox, we’re working on a number of updates to our new Image Editor, including improved search and a Superpixel tool. Let’s dive in!

Featured

Labelbox | 10 months ago | 9 min read

Asking good questions isn’t the first step to building enterprise ML, it’s step 0

When email first came on the scene, it was revolutionary. People were excited to try a faster method of communicating with friends and business contacts. But of course, someone quickly found a way to ruin it. Spam (unwanted bulk emails, not the canned meat product) started popping up in huge

Video

Labelbox | 14 days ago | 3 min read

Teach your ML model to perceive time

At Labelbox, our mission is to build tools that teach machines how to perceive reality and understand and predict patterns in our surroundings.

Automation

John Thomas | 20 days ago | 3 min read

Tutorial: Use model-assisted labeling to improve speed and accuracy

Follow this tutorial to learn how model-assisted labeling can improve labeling speed and accuracy using your own model.

Automation

Brian Rieger | 25 days ago | 4 min read

Automating Computer Vision Annotation: Let Your Model Do The Work.

Discover the 3 basic ways to automate labeling depending on how aware the method is of the data to be labeled.

Labelbox in the Media

Labelbox | a month ago | 3 min read

How Labelbox tackles technical challenges in distributed systems

Last week, our team had the pleasure of appearing on the Software Engineering Daily podcast. CEO Manu Sharma shared some of the challenges that ML teams face — and how Labelbox’s technology can solve them.

Product Updates

Labelbox | a month ago | 2 min read

Labelbox October updates

This month we’ve rolled out a number of improvements to simplify and speed up your workflows. See how Labelbox is engineered for speed and usability.

Automation

Labelbox | a month ago | 2 min read

Automate labeling with your own model

Model-assisted labeling from Labelbox is the fastest way to improve model performance. Reduce labeling costs by up to 50-70% with your own model.

Case Studies

Labelbox | a month ago | 3 min read

Using Labelbox to optimize crop production

Learn how Labelbox's training data platform plays a central role in xarvio's ML pipeline to handle the full data annotation process and help farmers innovate through digital farming.

Case Studies

Labelbox | a month ago | 2 min read

How Cape Analytics uses active learning to get to production AI faster

Learn how Cape Analytics created an active learning workflow whereby low confident predictions were visible and prioritized to their data scientists and labelers for quick analysis and correction.

Case Studies

Labelbox | 2 months ago | 2 min read

Customizing an optimal training data workflow using an API-first approach

Learn how Cape Analytics, a leading provider of AI-powered geospatial property data used Labelbox's APIs to automate their training data workflows.

Case Studies

Labelbox | 2 months ago | 4 min read

How MIT researchers are using neural nets to automate manual tasks for novel serotonin research

Jungsoo Kim is a PhD graduate student at MIT’s Flavell Lab which focuses on cutting-edge neuroscience research. His team is currently exploring how computation and behavior emerge from neural circuits. Neurons, just like electronics, need to be properly wired in order to function well. Their project investigates how serotonin