A new study from the Massachusetts Institute of Technology found label errors in ten of the most cited artificial intelligence data test sets. Researchers estimated an average of 3.4% errors across ...

It’s no secret that machine learning success is derived from the availability of labeled data in the form of a training set and test set that are used by the learning algorithm. The separation of the ...

Before you can even think about building an algorithm to read an X-ray or interpret a blood smear, the machine has to know what’s what in an image. All of the promise of AI in healthcare — an area ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Supervised machine learning, in which machine learning models learn from ...

With the aggressive scaling of semiconductor devices, the increasing complexity of device structure coupled with tighter metrology error budget has driven up Optical ...

The Common Data Set (CDS) initiative is a collaborative effort among higher education data providers to improve the quality and accuracy of information provided across institutions through the ...

Machine learning (ML) is a subset of artificial intelligence (AI) that involves using algorithms and statistical models to enable computer systems to learn from data and improve performance on a ...

The AI research community has tried to scrub away its past. But the internet is forever. In 2016, hoping to spur advancements in facial recognition, Microsoft released the largest face database in the ...

In dusty factories, cramped internet cafes and makeshift home offices around the world, millions of people sit at computers tediously labeling data. These workers are the lifeblood of the burgeoning ...