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Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...
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Tech Xplore on MSNQuantum machine learning improves semiconductor manufacturing for first timeSemiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the ...
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Tech Xplore on MSNReinforcement learning for nuclear microreactor controlA machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...
More information: Xinwei Su et al, Machine learning modeling assisted intelligent process analysis for high - performance virus filtration, Journal of Membrane Science (2025).
A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.
Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.
Researchers at Tohoku University used machine learning potential to create large-scale models of tin (Sn) catalysts under ...
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AZoBuild on MSNAI Model Identifies Greener Cement Mixes Without Compromising StrengthInnovative AI techniques in cement formulation lead to eco-friendly mixes, significantly cutting emissions and improving ...
Brian Ongioni, chief product officer, uMotif, discusses how AI and machine learning can enhance patient-reported outcomes by ...
A new study reveals how children outlearn AI - using movement, senses, and social cues to master language faster than any ...
A Tribune reporter and data nerd went looking for a smarter way to evaluate and draft NBA players. From Cooper Flagg to a few ...
To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...
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