Machine learning predictions and system updates in real-time. ... KSQL, or Spark Streaming, to process streaming data. Many people believe that online prediction is less efficient, ...

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 ...

The process of machines learning from data unleashes the power of exploding resource. It uncovers what drives people and the actions they take. ... Machine Learning: Prediction, decision and action.

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

The project I was a part of, Tectonic, was using machine learning to advance earthquake prediction. The European Research Council was sufficiently convinced of its potential to award it a four ...

To estimate currents and find divergences, oceanographers have used a machine-learning technique known as a Gaussian process, which can make predictions even when data are sparse.

Filling gaps in data sets or identifying outliers—that's the domain of the machine learning algorithm TabPFN, developed by a team led by Prof. Dr. Frank Hutter from the University of Freiburg.

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 ...