Could the secret to developing ML be more boring than we think? It’s time to give up the quest for the perfect model.
CloudFactory Blog
What will 2021 bring to the world of AI and machine learning? CloudFactory CEO and founder Mark Sears shares our predictions.
How can you determine if a data labeling service will deliver quality work? How they communicate and handle quality control are key indicators.
How can you determine if a data labeling service will deliver quality work? It starts with their vetting, hiring, and training processes.
People have unconscious biases that affect hiring decisions. People also can hard-code their biases into an AI system. Humans in the loop can help.
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.
Autonomous vehicles and AI driver safety tools aren’t affordable for all. Driver Technologies made a free innovative app and model training database.
Autonomous vehicles require continuous training to ensure they operate safely. Here’s how active learning can improve that process.
Discover the autonomous vehicle training conundrum. Learn about machine learning for autonomous cars and the challenges of vehicle data collection.
From localized bias to difficulties annotating video and radar data, here are some of the biggest challenges facing the future of autonomous vehicles.
In the Rise of Autonomous Vehicles the world of transportation and logistics is rapidly changing. Here are 3 AV innovators you should know about.
Can AI help us in predicting the future with computer vision? Here's how computer vision can use today’s data to model tomorrow’s outcomes.
Image annotation is an important task when training a computer vision model. Here are common misconceptions about image annotation for computer vision.
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