World's largest collection of Olympiad-level math problems now available to everyone

Every year, the countries competing in the International Mathematical Olympiad arrive with a booklet of their best, most ...

AACR: New platform uses machine learning to predict responses in patients with lung cancer

An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center ...

A machine learning model that uses DNA methylation patterns may help identify the origin of cancers of unknown primary

A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types ...
AOL

The startup looking to solve health care’s fax machine problem

I sincerely don’t remember the last time I saw a fax machine. But that’s, perhaps, because I don’t work in health care. “Yes, in 2026, fax is still probably the most common way of sending documents ...
Frontiers

Fairer non-negative matrix factorization

There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods should be developed ...
Forbes

Machine Learning Trends For 2026

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...
PNAS

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Dinosaur footprints are iconic fossils, but it is challenging to identify their makers. This is illustrated by a long-standing debate about whether some footprints from the Late Triassic-Early ...
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 ...
marktechpost

Nested Learning: A New Machine Learning Approach for Continual Learning that Views Models as Nested Optimization Problems to Enhance Long Context Processing

How can we build AI systems that keep learning new information over time without forgetting what they learned before or retraining from scratch? Google Researchers has introduced Nested Learning, a ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...