Like high-frequency traders on Wall Street, a growing army of bots exploit inefficiencies in decentralized exchanges, which are places where users buy, sell or trade cryptocurrency independent of a central authority, a Cornell Tech study has found.
Cornell researchers have released a free, open-source software to help make potentially subjective and time-consuming plant breeding decisions more consistent and efficient.
A predictive model combining information about plant physiology, real-time soil conditions and weather forecasts can save 40% of the water consumed by traditional irrigation strategies, according to new Cornell research.
A Cornell Tech-led team has pioneered the use of “ghostdrivers” – cars with drivers disguised under a car seat-like hood – to assess how pedestrians across cultures might react to autonomous vehicles.
Working to address a knowledge gap, the College of Human Ecology launched the Data Science and Programming Curriculum Initiative to teach students how to use data and technology in their respective disciplines.
A Cornell-led team has developed a way to use machine learning to analyze data generated by scanning tunneling microscopy, yielding new insights into how electrons interact and showing how machine learning can be used to further discovery in experimental quantum physics.