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 ...

Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control.

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

While self-healing agentic test suites can help eliminate the manual intervention consuming engineering cycles, there are key strategies to make this approach successful.

Researchers have developed a powerful new software toolbox that allows realistic brain models to be trained directly on data.

For rare diseases, AI-driven repurposing fills a critical gap. With more than 7000 rare diseases and only a small percentage ...

Artificially generated data is helping machines perform better while challenging our ideas of truth and transparency.

Private equity investment decisions carry substantial economic and social influence; thus, responsible AI serves as the ...

The TRM takes a different approach. Jolicoeur-Martineau was inspired by a technique known as the hierarchical reasoning model ...

Once a buzzword, the "digital middle platform" is now mired in what Gartner calls the "trough of disillusionment" —data keeps ...