XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

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, ...

EY's Alexy Thomas says connected, trustworthy data—not AI models alone—will determine India's long-term AI innovation and ...

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.

SCWorx Leverages Leading AI Models along with its Proprietary Healthcare Data Assets to Accelerate Data Cleansing, Enrichment, Classification and Supply Chain Intelligence ...

Data operationalization, complemented by the pragmatic deployment of AI use cases with said data, is, at its core, a move ...