MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to artificial intelligence ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...

Industry experts, competitors and even your customers are talking about machine learning and artificial intelligence. As they continue to grow in popularity, more companies than ever before are ...

Model predicts effect of mutations on sequences up to 1 million base pairs in length and is adept at tackling complex ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...