Scientists are using artificial intelligence to determine which genes collectively govern nitrogen use efficiency in plants such as corn, with the goal of helping farmers improve their crop yields and minimize the cost of nitrogen fertilizers.
Scientists inspired by the octopus's nervous system have developed a robot that can decide how to move or grip objects by sensing its environment.
A multidisciplinary team of researchers has developed an artificial intelligence (AI) model that can predict acute child malnutrition in Kenya up to six months in advance. The tool offers governments and humanitarian organizations critical lead time to deliver life-saving food, health care, and supplies to at-risk areas. The machine learning model outperforms traditional approaches by integrating clinical data from more than 17,000 Kenyan health facilities with satellite data on crop health and productivity. It achieves 89% accuracy when forecasting one month out and maintains 86% accuracy over six months -- a significant improvement over simpler baseline models that rely only on recent historical child malnutrition prevalence trends.
Researchers have developed a digital laboratory (dLab) system that fully automates the material synthesis and structural, physical property evaluation of thin-film samples. With dLab, the team can autonomously synthesize thin-film samples and measure their material properties. The team's dLab system demonstrates advanced automatic and autonomous material synthesis for data- and robot-driven materials science.
Engineers built E-BAR, a mobile robot designed to physically support the elderly and prevent them from falling as they move around their homes. E-BAR acts as a set of robotic handlebars that follows a person from behind, allowing them to walk independently or lean on the robot's arms for support.
A robotic hand can pick up 24 different objects with human-like movements that emerge spontaneously, thanks to compliant materials and structures rather than programming.
Engineers have taught a simple submarine robot to take advantage of turbulent forces to propel itself through water.
Researchers developed FaceAge, an AI tool that calculate's a patient biological age from a photo of their face. In a new study, the researchers tied FaceAge results to health outcomes in people with cancer: When FaceAge estimated a younger age than a cancer patient's chronological age, the patient did significantly better after cancer treatment, whereas patients with older FaceAge estimates had worse survival outcomes.
Researchers have developed a more efficient chip as an antidote to the vast amounts of electricity consumed by large-language-model artificial intelligence applications like Gemini and GPT-4.
A team of researchers has unveiled a cutting-edge Amphibious Robotic Dog capable of roving across both land and water with remarkable efficiency.
What makes people think an AI system is creative? New research shows that it depends on how much they see of the creative act. The findings have implications for how we research and design creative AI systems, and they also raise fundamental questions about how we perceive creativity in other people.
The growing use of smart home devices is undermining the privacy and safety of domestic workers. New research reveals how surveillance technologies reinforce a sense of constant monitoring and control by domestic workers' employers, increasing their vulnerability and impacting their mental wellbeing.
A research team develops disinfection robot combining physical wiping and UV-C sterilization.
Our brain is a complex organ. Billions of nerve cells are wired in an intricate network, constantly processing signals, enabling us to recall memories or to move our bodies. Making sense of this complicated network requires a precise look into how these nerve cells are arranged and connected. A new method makes use of off-the-shelf light microscopes, hydrogel and deep learning.
An artificial intelligence (AI) model improved outcomes in hospitalized patients by quadrupling the rate of detection and treatment of delirium. The model identifies patients at high risk for delirium and alerts a specially-trained team to assess the patient and create a treatment plan, if needed.