If data used to train artificial intelligence models for medical applications, such as hospitals across the Greater Toronto ...

Current care in multiple sclerosis (MS) primarily relies on infrequently obtained data such as magnetic resonance imaging, clinical laboratory tests or clinical history, resulting in subtle changes ...

In a recent analysis, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and collaborator William Gilpin reported that one ...

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

In today’s digital enterprise, HR departments are rapidly evolving from people-centric administrative hubs to data-driven ...

The Allen Institute of AI updated its reward model evaluation RewardBench to better reflect real-life scenarios for enterprises.

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs ...

Models rewrite code to avoid being shut down. That’s why ‘alignment’ is a matter of such urgency.

Accurate climate prediction, particularly precipitation forecasting, remains a cornerstone for agriculture, water resource management, and disaster ...