Artificial intelligence systems are only as powerful as the data they are trained on. High-quality labeled datasets determine whether a model performs with precision or fails in production.

Robust, deployable and collaborative machine learning (ML) methods are needed for AI to become truly useful. This ERC-funded research aims to solve a major ML bottleneck and will form a cornerstone of ...

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

Join us to learn about how to use cutting edge GPU infrastructure to solve real world material discovery problems with AI and unsupervised machine learning. Our lab in the Department of Materials ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Matt Whittle has experience writing and editing accessible education-related content in health, technology, nursing and business subjects. His work has been featured on Sleep.org, Psychology.org and ...

Just over a decade ago, Sandia National Laboratories founded the PV Performance Modeling Collaborative (PVPMC). PVPMC is increasing transparency and accuracy in PV system performance modeling, ...