Machine learning can sound pretty complicated, right? Like something only super-smart tech people get. But honestly, it’s ...

Machine learning has moved past its initial experimental phase. In earlier years, development often focused on creating the largest possible models to see what capabilities might appear. Today, the ...

Drug discovery pipelines are notorious for being costly, slow, and failure-prone, leading to AI and machine learning becoming more commonplace to accelerate progress and improve outcomes. Currently, ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines. By Daniel Fusch Neel Somani, a ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...