While artificial intelligence (AI) models have proved useful in some areas of science, like predicting 3D protein structures, ...

To modernize data and infrastructure, HLC recommends expanding transparency standards and mitigating bias. It points to the transparency and disclosure requirements set out in HTI-1 and suggests ...

We present a knowledge‐guided machine learning framework for operational hydrologic forecasting at the catchment scale. Our approach, a Factorized Hierarchical Neural Network (FHNN), has two main ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Machine learning researchers using MLX will benefit from speed improvements in macOS Tahoe 26.2, including support for the M5 GPU-based neural accelerators and Thunderbolt 5 clustering. People working ...

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of these diseases ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Student dropout in primary education is a critical global challenge with significant long-term societal and individual consequences. Early identification of at-risk students is a crucial first step ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

Background: Major depressive disorder (MDD) and uremia are two chronic wasting diseases that have interactive effects and significantly aggravate patients’ distress. However, the molecular basis ...