Estimating fuel savings from aircraft modifications is a laborious process for Air Force experts, but not for an SEI machine learning model.

Spin as an input parameter: Machine learning predicts magnetic properties of materials by Lauren Smith, Carnegie Mellon University Chemical Engineering edited by Gaby Clark, reviewed by Robert Egan ...

This paper develops a frequency-domain iterative machine learning (IML) approach for output tracking. Frequency-domain iterative learning control allows bounded noncausal inversion of system dynamics ...

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

Input Determines Output: Building a Protein Expression Platform Integrating best practices in AI, genomics, cell culture, and laboratory techniques together contribute to protein expression success ...

Machine-learning pioneer Yann LeCun on why “a new revolution in AI” is coming Our podcast on science and technology. Meta’s chief AI scientist and one of the “godfathers” of machine ...