HB2151 threatens to speed up controversial data center construction statewide Harrisburg, PA — Today, the House Energy Committee held a hearing for HB2151, a Shapiro-backed bill that would provide a ...

Unverified and low-quality data generated by artificial intelligence (AI) models – often known as AI slop – is forcing more security leaders to look to zero-trust models for data governance, with 50% ...

MongoDB Inc. is making its play for the hearts and minds of artificial intelligence developers and entrepreneurs with today’s announcement of a series of new capabilities designed to help developers ...

AI promises a smarter, faster, more efficient future, but beneath that optimism lies a quiet problem that’s getting worse: the data itself. We talk a lot about algorithms, but not enough about the ...

AI applications rarely deal with one clean table. They mix user profiles, chat logs, JSON metadata, embeddings, and sometimes spatial data. Most teams answer this with a patchwork of an OLTP database, ...

It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

The 3D printing laboratory, operating within the Simulation Centre of the Faculty of Medicine at Masaryk University (SIMU), has contributed to the development of 3D printing in medicine by launching a ...

Editor's note: The IAPP is policy neutral. We publish contributed opinion and analysis pieces to enable our members to hear a broad spectrum of views in our domains. Artificial intelligence systems ...

Abstract: In artificial intelligence, the significance of thorough documentation of models and datasets for publication is underestimated. However, due to the rising trend in the explainability and ...

If you wandered the trade show floor at the American Baseball Coaches Association convention in Washington, D.C. this past January, it was impossible to miss the shift. Technology booths sprawled ...

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, ...