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Machine Learning

‘To do things they hadn't even thought of’: Senior Turing Scholar publishes second computer science research paper

Turing student Alan Baade pictured in gray and white against geometic print on white background and orange soundwaves running behind Alan's head.

10/01/2024 - Computer Science and Mathematics senior Alan Baade really enjoys spending hours on problems.Especially the particularly hard ones, he said. Spending 40 hours on one equation with a small break for sleep somewhere in the middle is rewarding to him.“I think it's because you can tell at the end of this you are going to understand the material,” Baade said.  “You're going to understand computers.”

Turbocharging Protein Engineering with AI

Three people stand silhouetted in front of a wall-sized video display that shows several large colorful illustrations of molecules

09/26/2024 - Biotech advances from UT’s new Deep Proteins group are changing the game with help from artificial intelligence.Working as a chemist in Houston, Danny Diaz spent a lot of time plodding his way through crosstown traffic, pondering how to speed up his research.“I realized that my impact in the short term would be limited to the amount of chemistry experiments I could do with my hands,” he recalled.

New AI Institute Led by UT Researchers Will Accelerate Cosmic Discovery

Four quadrants of scientific-images come together, with webs showing bright spots for star formation, galaxy clustering, identifications of galaxies that are labeled and a futuristic network.

09/18/2024 - The University of Texas at Austin has been selected to lead the NSF-Simons AI Institute for Cosmic Origins, a new $20 million research initiative focused on using AI to explore the universe’s biggest mysteries, from dark matter to the origins of life. Greg Durrett, Associate Professor of Computer Science at UT, is a co-investigator on this groundbreaking project, further cementing UT’s leadership in AI research.

Artificial Intelligence Trained to Draw Inspiration From Images, Not Copy Them

Three rows of similarly themed illustrations—earnest dogs, scientist pandas and robot graffiti—differ in each of five iterations per row.

05/17/2024 - Researchers are using corrupted data to help generative AI models avoid the misuse of images under copyright. Powerful new artificial intelligence models sometimes, quite famously, get things wrong — whether hallucinating false information or memorizing others’ work and offering it up as their own. To address the latter, researchers led by a team at The University of Texas at Austin have developed a framework to train AI models on images corrupted beyond recognition.

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