The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
Nowadays, compute-intensive programs, like those for training artificial intelligence and machine learning models, are used extensively. Modern ...
A new AI model accurately predicts gas adsorption in metalorganic frameworks and explains its results, offering faster, ...
Traditional experimental methods for evaluating gas adsorption performance of metal–organic frameworks (MOFs) are costly and time-consuming, while ...
Evaluating the advantages and potential drawbacks of shielding as a method for safe RL. Bettina Könighofer is an assistant ...
The Chosun Ilbo on MSN
AI Emerges as Researcher's 'Second Brain' in Material Discovery
An era is opening where artificial intelligence (AI) can imagine the structures of new materials and even identify ...
“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...
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