Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been ...

To identify and evaluate candidate materials, process engineers must analyze an enormous amount of data. Bulk properties like ...

Research shows how artificial intelligence is revolutionizing plastics manufacturing through material development and process ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...

AI-assisted signal debugging has broad impact across many domains.

Pranav Prabhakar is an engineering leader with expertise in building scalable systems, deploying machine learning in ...

To overcome two challenges in training AI – scarce or hard-to-get data and data privacy – researchers have come up with a ...

Researchers have developed a powerful new software toolbox that allows realistic brain models to be trained directly on data. This open-source framework, called JAXLEY, combines the precision of ...

By Archie Roboostoff, VP of Software at Tigo Energy In the U.S., the utility-scale sector has the greatest share of the U.S.

Explore how big data influences AI in drug discovery and why biologically rich data matters more than sheer size.

Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...