Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of ...

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

Machine Learning (ML) and Artificial Intelligence (AI) have become essential technologies across industries, automating tasks at a speed and scale far beyond human capabilities. However, building ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

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.

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

AI black box models lack transparency, making investment decisions unclear. White box models are slower but clarify their decision-making processes. Investors should verify AI outputs to align with ...