News

NSF AI Institute for Foundations of Machine Learning (IFML) secures renewed funding to support breakthrough research in generative AI.

"Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions"

UT Austin's Texas Advanced Computing Center (TACC) announced today that the much-anticipated VISTA supercomputer is now in production for the open science community. 

Join us for a two-day workshop, April 18-19, celebrating the launch of the new Center for Generative AI and featuring research experts from academia and industry. Click here to register.

The director of Texas Robotics warms up for South by Southwest

UT partnership integrates emerging disciplines of computational oncology and machine learning to transform the future of cancer care.

Adam Klivans and Alex Dimakis discuss the real-world impact of bias in AI imaging with Daniel Marin from KXAN News.

IFML authors have a strong presence at this year's conference.

Alumni seek better world through artificial intelligence research at UT.

NASA JPL team uses TACC's Maverick2 system to develop software, trains models

Buildings are far from static, changing and evolving over time the same way cities do.

Artificial agents must learn to work with people with no prior knowledge of the collaborative environment

UT Austin will be undertaking research on how robots can build competency models of their perception algorithms.

Artificial intelligence has the potential to have extremely beneficial but also detrimental effects on society as we know it.

University of Texas at Austin computer science researcher Kristen Grauman was selected as a finalist for the 2020 Blavatnik National Awards for Young Scientists.

TACC, computer science experts to create new R&D for academia and the commercial sector

The promise of artificial intelligence to solve problems in drug design, discover how babies learn language, and make progress in many other areas has been stymied by the inability of humans to understand what's going on inside AI systems.

UT researchers explore whether artificial intelligence can help identify teens and young adults at risk for mental health problems by ethically following their online footprint.