Machine learning makes big move to UT Austin
An institute to advance artificial intelligence and machine learning, which could help identify COVID treatments, among other advancements, will be housed at The University of Texas at Austin.
The National Science Foundation will locate its $2o million AI Institute for Foundations of Machine Learning at the flagship university, which will lead a team that includes researchers from the University of Washington, Wichita State University and Microsoft Research.
“Many of the world’s greatest problems and challenges can be solved with the assistance of artificial intelligence,” UT Austin interim President Jay Hartzell said in a statement.
Machine learning, the force behind artificial intelligence, analyzes data to make predictions, but the emerging technology is currently limited by computational constraints. For example, algorithms that recognize, categorize and label images can’t keep pace with the massive amount of video data that people upload to the internet every day, UT Austin experts say.
For example, Facebook, one of the AI institute’s partners, wants to use video algorithms to make its social network more accessible to people with visual impairments.
And in a partnership with UT Austin’s Dell Medical School, the institute’s researchers will work to speed up X-rays and other medical imaging diagnostics to reduce the time it takes for patients to get critical treatment.
“Machine learning can be used to predict which of thousands of recently formulated drugs might be most effective as a COVID-19 therapeutic, bypassing exhaustive laboratory trial and error,” says Adam Klivans, the UT Austin computer science professor who led the effort to bring the institute to the university. “Modern datasets, however, are often diffuse or noisy and tend to confound current techniques.”
The institute’s directors also plan to create an online master’s degree in AI, undergraduate research programming and online AI courses for high school students.
At the same time, UT Austin is establishing a Machine Learning Laboratory as a base for campus AI research by computer and data scientists, mathematicians, roboticists, engineers and ethicists.
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