Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

More information: Xinwei Su et al, Machine learning modeling assisted intelligent process analysis for high - performance virus filtration, Journal of Membrane Science (2025). DOI: 10.1016/j ...

Like everything else associated with machine learning, deep learning, and large language models, the generative AI development process is subject to change, often with little or no notice.

Machine learning can make these calculations using samples of simulated data, a process that takes closer to 24 hours and creates a database that astrophysicists can sample from in a matter of seconds ...

They used two AI models—an isolation model to detect anomalies during the batch phase of the process and a random forest model to predict required operator ... based on machine learning, ...

Biases in data can be amplified by the training process, leading to distorted — or even unjust — results. And even when a model does work, it’s not always clear why. (Deep learning algorithms are ...

The insurer will use Akur8’s Core Platform, which leverages proprietary ML technology to improve pricing processes.

Machine learning can be used to create a brutal foe. IBM’s Deep Blue and Google’s DeepMind AlphaStar have proven that. However, that isn’t always the desirable—not only because it raises ...

Their development of new varieties has broadened the gene pool for U.S. rice while also incorporating specific, ... Jamshidi’s efforts in building this model are especially novel because the final ...

The potential for machine learning algorithms to accelerate drug formulation could reduce the time and cost associated with drug development, making promising new medicines available faster. Share ...