The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

SANTA CLARA, CA - February 05, 2026 - - Interview Kickstart today announced the launch of its Advanced Machine Learning ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...