Boards and C-suites are adopting new governance practices to address energy constraints and operating and cyber risks to ...

Data is often called the lifeblood of modern healthcare. As the industry evolves, its ability to harness and act on data effectively will distinguish the innovators from the status quo. Today, ...

Uptime Institute predicts the data center industry in 2025 will face pressure over resource consumption, grid integration challenges, and AI infrastructure requirements. Data centers this year will ...

As artificial intelligence revolutionizes manufacturing, adoption of the technology is still hindered by challenges like data quality, legacy infrastructure and workforce adaptation. Advances in ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Suebsiri Taweepon of Tilleke & Gibbins highlights a critical issue in Thailand’s copyright regime while examining the legal uncertainties, licensing burdens, and data-scraping risks in AI development ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Yusuf Roohani, PhD, machine learning group lead at the Arc Institute, is among a team of researchers training artificial intelligence (AI) models with transcriptome data to predict how cell gene ...