Science

New research reveals that artificial intelligence, despite vast medical knowledge, struggles to reliably interpret complex, real-world patient data.

A new analysis details the vulnerabilities and strengths of Boston’s Green Line subway system, offering critical insights for improving its operational reliability and security.

A new approach uses advanced mathematical tools to build more reliable predictions of robot movements, even with imperfect information about the environment.

A new data-driven tool helps clinicians determine the best treatment – surgical or transcatheter – for patients with aortic stenosis.

A new framework combines economic viability with sustainable agricultural practices to create resilient crop plans in the face of unpredictable conditions.

A new study reveals how neural networks lose accuracy when faced with unfamiliar data, and introduces a method to realign their internal representations for better performance.

A new approach combines the power of language models with graph networks to achieve accurate text classification, even when labeled data is limited.

A new approach combines the strengths of kernel methods and neural networks to dramatically accelerate aerodynamic simulations while maintaining high accuracy.

A new approach to building inclusive language tools prioritizes ethical data creation and community involvement for languages often left behind.

Despite impressive accuracy, new research reveals that large language models are surprisingly vulnerable to cleverly crafted phishing attacks.