Science

Researchers have developed a novel system that focuses on the subtle frequency characteristics of audio to reliably identify artificially generated speech.

A new approach leveraging advanced artificial intelligence models is improving the accuracy of herd life predictions for dairy cows.

A new deep learning model uses the power of temporal imaging to forecast long-term Alzheimer’s disease progression, even with irregularly spaced scan data.

A novel framework dynamically filters out bad data to improve the accuracy of anomaly detection systems, even when training datasets are heavily contaminated.

Researchers have developed a highly accurate method for distinguishing text written by humans from that produced by artificial intelligence.

New research explores how reinforcement learning can optimize the reasoning process in large language models, leading to more efficient and effective problem-solving.

Researchers are adapting techniques originally developed for large language models to shed light on the internal workings of Transformer networks used for time series classification.

A new deep learning approach uses the brain’s own structural changes over time to forecast the progression of Alzheimer’s disease, potentially enabling earlier diagnosis and intervention.

A new method using neural networks and radio observations offers a robust way to determine supermassive black hole masses in galaxies obscured by dust.

Researchers have bridged the gap between auction theory and convex optimization, leading to a faster, more efficient way to determine fair market pricing.