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 ...

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 ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Imagine a retail firm’s AI spitting out a sales forecast for a regional manager, merging ...