Whatever you are paying for labeling is too much
As the first company globally, we are making all labeling features completely free to use, including our best-in-class automation features. Our goal …
How we cleaned up PASCAL and improved mAP by 13%
We cleaned up all 17.120 images of the PASCAL VOC 2012 dataset in a week using Hasty’s AI-powered QC feature. We found that 6.5% of the images in …
Bringing active learning, model explainability, and Bayesian networks to Hasty with the help of ProFit
How we plan to use active learning further to improve the automation and effectiveness of machine learning tasks.
Buy or build ML solutions
This article will look at one of the most complex decisions for most organizations starting new AI projects. Should they buy or build the software …
Exploration of different Deep Learning model formats
There are many different ML frameworks and, as a consequence, ML formats today. In this article, we summarize popular formats in existence today and …
How to analyze the performance of vision AI models and connect it to business metrics
Many companies want to use AI to improve specific business metrics. But how do you understand the relationship between ML metrics and business …
How to organize ML teams
How do you best structure ML teams? In this article, we break down different approaches and go through the pros and cons of these approaches. …
Implementing the data flywheel
As the ML space is maturing, processes and best practices for what happens after you successfully manage a first project launch are becoming more …
Introduction to MLOps
This introduction to MLOps is intended as an introduction to the field, it's similarities and differences compared with DevOps, and how it can help …
Using the Hasty Inference Engine API
As part of our data flywheel , you can get inference results from the model you trained using the Hasty API . We provide a way to upload an image and …
Pricing a vision AI project part 1 : What projects are worth spending money on?
This article, the first of a four-part series, goes through the initial steps needed when getting started with AI. Specifically, we look at how to …
Hasty has taken our data labeling to the edge. Both semantic and bounding box labeling has gone from weeks or months on our large data sets to days. For QA, I just reviewed 19,000 labels in 5 hours. WTF!
Only 13% of vision AI projects make it to production, with Hasty we boost that number to 100%.