Tech Xplore on MSN

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
Phys.org

Enhancing machine-learning interatomic potentials for advanced materials modeling

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

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 ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
National Academies of Sciences%2c Engineering%2c and Medicine

Using Machine Learning in Safety-Critical Applications: Setting a Research Agenda

A committee-supported project or activity that has been completed and for which output dissemination has begun. Its committee has been disbanded and closeout procedures are underway. Machine learning ...
Frontiers

Modeling, Machine Learning, Bioinformatics and Multi-omics Data in Soil Science

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to unravel the complexity of ...
Linux Journal

Linux Meets AI: Top Machine Learning Frameworks You Need to Know

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...