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Adam Klivans

On AI for the Rest of Us: How AI is Accelerating Discovery

A woman in a white lab coat and gloves holds up a molecule that has been magnified to the size of her head

12/03/2024 - From data analysis, code writing, summarizing scientific literature and even designing experiments, researchers across disciplines are using AI tools to aid in their research.Adam Klivans, a professor of computer science and Alex Dimakis, a computer and electrical engineering professor, co-direct the Machine Learning Lab and the Institute for Foundations of Machine Learning. Together with Marc Airhart and Casey Boyle discuss how artificial intelligence plays an increasingly important role in the latest scientific discoveries.

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.

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.