How will $1 million in artificial intelligence research impact Florida industry?
The University of Florida announced a $1 million investment into artificial intelligence. Twenty faculty teams will study wide-ranging uses on data analysis in a range of fields from agriculture to education.
The research will make use of a $60 million gift from NVIDIA and co-founder Chris Malachowsky, a UF alumnus. The funding has been used to increase computing capabilities at the Gainesville school.
“As part of UF’s push to become a national leader in artificial intelligence research and education, the AI Research Catalyst Fund was created to encourage multidisciplinary teams of faculty and students to rapidly pursue imaginative applications of AI across the institution,” said David Norton, vice president for research for the university. “We anticipate that this seed funding will position these teams to pursue additional funding from government agencies and industry.”
It’s work lawmakers like Sen. Ben Albritton, a Wauchula Republican, sees revolutionizing Florida. A longtime agriculture leader himself, he tweeted that the research could be invaluable in the field.
“Fantastic work by the [UF Institute of Food and Agricultural Sciences] program to promote Artificial Intelligence research in the farmlands and crop fields of Florida,” he said. “These projects will help lay the foundation for the future of Florida farmers.”
“Effective management requires accurate parasitic nematode identification,” DiGennaro said. “But human-based identification requires years of intensive training. Developing a machine learning algorithm to identify and quantify nematode species could revolutionize parasitic nematode identification services, increasing speed and accuracy of recommendations to farmers.”
The university grants will also fund research methods educational groups operate in the state. For example, Wanli Xing, an assistant professor in the UF College of Education’s School of Teaching and Learning, will study how data can predict student performance in math and identify when there should be early intervention.
“We hope to use machine learning techniques to analyze big data to automatically detect students’ emotions and engagement factors, two of the most important factors influencing online students’ learning outcomes,” Xing said.
This story originally appeared on Florida Politics.