People are involved in everything from training and testing algorithms to labeling data, conducting quality control, and monitoring automation.
Humans play a critical role throughout the AI lifecycle, from data cleaning and labeling to quality control and automation monitoring.
Developing ML models requires a lot of data and skilled people to work with it. Here’s our HITL approach for machine learning model development.
We are excited to announce a new offering that bundles our professionally managed workforce with a market-leading annotation platform for one price.
Autonomous vehicles and AI driver safety tools aren’t available or affordable for all. Driver Technologies created a free app and model training database to boost safety and ...
Autonomous vehicles require continuous training to ensure they operate safely. Here’s how active learning can improve that process.
Autonomous vehicles are among the most data-hungry machines the world’s ever seen. Here’s a look at data collection techniques and challenges.
From localized bias to difficulties annotating video and radar data, here are some of the biggest challenges facing the future of autonomous vehicles.
Building and maintaining relationships while working remotely calls for creativity. We use pod socials to connect globally at CloudFactory.
Image annotation is one of the most important tasks when training a computer vision model. Here are common misconceptions to overcome first.
We are delighted to welcome tech veteran John Cotterell to the CloudFactory Board of Directors. CEO Mark Sears talked with John about his new leadership role.