Overfitting is a common problem in machine learning, where a model learns too much from the training data and fails to generalize well to new or unseen data. This can lead to poor ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

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

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

Jefferson Lab scientists have wrapped up three research projects that demonstrate ways in which artificial intelligence (AI) and machine learning (ML) could be used to make SRF particle ...

Lenders who utilize machine learning-based automations through LPA save money, have shorter cycle times and have greater customer satisfaction, according to a recent analysis. A fully digitized ...

More information: Yunyu Xiao et al, Machine learning to investigate policy-relevant social determinants of health and suicide rates in the United States, Nature Mental Health (2025). DOI: 10.1038 ...