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With artificial intelligence increasingly integrated into our daily lives, one of the most pressing concerns about this emerging technology is ensuring that the new innovations being developed consider their impact on individuals from different backgrounds and communities. The work of researchers like Cornell Tech PhD student Ben Laufer is critical for understanding the social and ethical implications of algorithmic decision-making.
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.
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.
Using a combination of machine learning and powerful X-rays, Cornell researchers have solved a mystery behind the unusual behavior seen in a class of materials with potential for thermoelectric energy conversion and other applications.
Researchers have uncovered DNA markers associated with retroelements, remnants of ancient viral genetic material, in our genes that act as highly accurate epigenetic clocks predicting chronological age.
Eighteen students from across the country got a crash course in computer vision, machine learning, and how to secure a research career in tech during the 2024 SoNIC Summer Research Workshop, held June 24-28 on Cornell’s Ithaca campus.
Over 10 weeks this summer, Rev’s Prototyping Hardware Accelerator guided product teams from back-of-the-napkin ideas to fully-fledged startups. In categories from climate technology to agricultural innovations, and with projects that range from canoe racing tools to improved tea dispensers, teams gained access to experts in their industry’s field, working together to figure out if their concept might be commercially desirable, technologically feasible and economically viable.
