Science

A new deep learning approach tackles the challenge of reliably detecting weak health signals from wearable sensors amidst the crowded 2.4 GHz radio spectrum.

A new machine learning framework draws inspiration from biological neural networks to deliver accurate medical image analysis with reduced computational demands.

Researchers are exploring how artificial intelligence, specifically large language models, can dynamically optimize traffic signals in response to unexpected events and improve urban flow.

A new framework systematically charts the common failure points of large language models, offering a crucial step towards more reliable and understandable AI.

A new study demonstrates that pairing advanced AI models with external knowledge sources dramatically improves their ability to identify misleading content related to climate change.

New research demonstrates how artificial intelligence can enhance the detection of structural defects in critical underground infrastructure like culverts and sewers.

A new study reveals significant inconsistencies in the safety and performance of large language models when tested beyond English, highlighting critical gaps in current evaluation methods.

New research using multi-agent simulations reveals that large language models may reinforce harmful stereotypes about autistic individuals and their communication styles.

A new hybrid AI framework, AgriPINN, combines the power of deep learning with established agricultural models for more accurate and interpretable crop biomass predictions under challenging conditions.

A new mobile application translates complex artificial intelligence predictions into clear, user-friendly explanations of individual diabetes risk.