Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
As global warming accelerates, the increasing number of supraglacial lakes and the need to accurately measure their depths have become critical for understanding ice sheet mass balance and sea-level ...
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, ...
The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...
High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.
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 ...
A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...
Can you use the new M4 Mac Mini for machine learning? The field of machine learning is constantly evolving, with researchers and practitioners seeking new ways to optimize performance, efficiency, and ...
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