News Category
A new program at Cornell will tackle critical environmental challenges by integrating advanced artificial intelligence (AI) tools with sustainability research across the campus, thanks to a grant from the National Science Foundation’s Research Traineeship Program.
“Cultural prompting” – asking an AI model to perform a task like someone from another part of the world – resulted in reduced bias in responses for the vast majority of the more than 100 countries tested by a Cornell-led research group.
The Communal eXtended-Reality (CXR) system is a cutting-edge blend of the physical and digital worlds in which virtual scenes are overlaid onto the real world, designed to engage communities in new ways.
A new computational system called Schemonic, developed by Cornell researchers, cuts the costs of using large language models such as ChatGPT and Google Bard by combing large datasets and generating what amounts to “CliffsNotes” versions of data
A Cornell-led collaboration developed machine-learning models that use these cell-free molecular RNA dregs to diagnose pediatric inflammatory conditions that are difficult to differentiate. The diagnostic tool can accurately determine if a patient has Kawasaki disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), a viral infection or a bacterial infection, while simultaneously monitoring the patient’s organ health.
Integrating artificial intelligence into today’s environmental control systems could reduce energy consumption for indoor agriculture by 25% – potentially helping to feed the world as its population rises, Cornell engineers have found.
Cornell researchers discovered a new way of controlling biohybrid robots that can react to their environment better than their purely synthetic counterparts: harnessing fungal mycelia’s innate electrical signals.
Researchers found that cooperative partnerships seeking to spread the cost burden of water infrastructure projects often end up forcing local partners to bear the brunt of supply and financial risks.
