Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

Most contemporary artificial intelligence (AI) systems learn to complete tasks via machine learning and deep learning. Machine learning is a computational approach that allows models to uncover ...

Harvard John A. Paulson School of Engineering and Applied Sciences The Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and NTT Research, Inc., a division of NTT, announced ...

An autonomous AI system has produced a machine learning paper that passed peer review at an ICLR 2025 workshop, raising alarm over the integrity of scientific publishing. The system, developed by ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

The 2024 Nobel Prize in chemistry recognized Demis Hassabis, John Jumper and David Baker for using machine learning to tackle one of biology’s biggest challenges: predicting the 3D shape of proteins ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions via a process called cell fate determination. The fate of individual cells, ...

People have long worried about robots automating the jobs of truck drivers and restaurant servers. After all, from the invention of the cotton gin to the washing machine, we’re used to an economy ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper publishing April 22 in the Cell Press ...

SUNNYVALE, Calif. & CAMBRIDGE, Mass.--(BUSINESS WIRE)--NTT Research, Inc., a division of NTT (TYO:9432), and the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) announced the ...