An artificial intelligence model has successfully identified coronaviruses capable of infecting humans, out of the thousands of viruses that circulate in wild animals. The model, developed by a team of biologists, mathematicians and physicists at UC Davis, could be used in surveillance for new pandemic threats. The work was published in Scientific Reports.
Geared toward mathematics, statistics and computer science graduate students, MAT 280: “Fairness, Privacy and Trustworthiness in Machine Learning” aims to elevate tenets of social responsibility when it comes to developing machine learning and artificial intelligence-based systems. The special topics class focuses on the mathematical concepts underlying machine learning and how these concepts can be used for the better.
Both humans and other animals are good at learning by inference, using information we do have to figure out things we cannot observe directly. New research from the Center for Mind and Brain at the University of California, Davis, shows how our brains achieve this by constructing cognitive maps.
Three researchers from UC Davis have been awarded a total $1.2 million grant over four years from the National Institutes of Health (NIH) to generate high-quality synthetic data using artificial intelligence and machine learning that may potentially help physicians predict, diagnose and treat diseases.
