News: Year of AI

Researchers are using corrupted data to help generative AI models avoid the misuse of images under copyright.

Guide-dog users and trainers can provide insight into features that make robotic helpers useful in the real world.

Computer scientists Ryan Farrel and Chandrajit Bajaj will test a novel reinforcement learning approach.

UT’s Elad Liebman and Peter Stone consider robots that understand not only our commands but also our emotional states.

University of Texas at Austin AI experts and academic leaders visited the Capitol to highlight how public universities can drive artificial intelligence safety.

Jaquelin Dudley, Kristen Grauman, Arlen Johnson, Daniel Leahy, Xiaoqin “Elaine” Li and Tanya Paull receive major honor from AAAS.

The 2024-2025 rankings tout computer science at The University of Texas at Austin as among the seven best nationally.

From large language models to brain-machine interfaces, students work with faculty on cutting-edge research.

Insights from Risto Miikkulainen, a UT Austin professor of computer science and VP of AI Research at Cognizant Advanced AI Labs.

An innovative approach uses artificial intelligence and biosensors to pave the way for faster drug development.