New research reveals that "foundation models" trained on vast, general time-series data may be able to forecast river flows accurately, even in regions with little or no local hydrological records.

Modern-day LLMs are "fiction machines," designed not to be truthful but to make sense. What can we expect from these machines, and what are their limitations?

Ad fraud is no longer a fringe issue. It is a systemic threat to digital advertising, and its scale demands a technological ...

Researchers at UCLA's Institute of the Environment and Sustainability have developed the most high-resolution statewide maps ...

Farming is changing from manual, experience-led observation to data-driven decision-making powered by advanced sensing systems and artificial intelligence. A new research paper titled “Fast Forward ...

Researchers develop a 96% accurate AI-powered retinal scan to distinguish between Alzheimer’s and ALS by detecting specific protein deposits.

RFX-Fuse (Random Forests X [X=compression] — Forest Unified Learning and Similarity Engine) delivers Breiman and Cutler's complete vision for Random Forests as a Forests Unified Machine Learning and ...

Abstract: Learning over time for machine learning (ML) models is emerging as a new field, often called continual learning or lifelong Machine learning (LML). Today, deep learning and neural networks ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Traffic crashes remain one of the most stubborn public safety challenges in the United States. In 2022, nearly 42,800 people died on American roads, despite decades of safer car designs, stricter laws ...

Abstract: This study evaluates the performance of using machine learning models; J48 and Random Forest to classify bananas quality. The existing methods of visual inspection are qualitative and take ...