Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

“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 ...

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

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 ...

The first to attempt to calculate the speed of light was made in 1638, albeit unsuccessfully, by the “polymath from Pisa” Galileo Galilei, an Italian physicist, astronomer, natural philosopher, ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.