02/01/2024 - Picture two rigid metal pieces tangled together. What steps would you take to untangle them? The most straightforward approach involves twisting each wire to line up the gaps and then pulling one through the other. The design of wire puzzles becomes more complex, like the ones below. Read more
01/25/2024 - The University of Texas at Austin is creating one of the most powerful artificial intelligence hubs in the academic world to lead in research and offer world-class AI infrastructure to a wide range of partners. Read more
11/08/2023 - In mathematical optimization, a new approach is emerging, promising to transform how we tackle intricate challenges across various domains. Consider the complexity of bilevel optimization, a problem that has confounded experts in machine learning, engineering, and other fields. Recent advances are providing new insights into this intricate landscape, presenting a streamlined technique that has the potential to significantly enhance our ability to navigate these complex problems.  Read more
11/02/2023 - Smriti Singh spends a lot of time on social media. But, not in the way most students do.  Read more
09/27/2023 - The work of researchers from The University of Texas at Austin’s Department of Computer Science in crash consistency has yielded a breakthrough innovation—the Chipmunk system. At its core, Chipmunk zeroes in on a crucial mission—meticulously testing file systems to identify and tackle crash consistency bugs that can significantly impact data integrity and system reliability. The UT Austin team has produced a promising solution that could pave the way for a new era in data storage and stability. Read more
05/01/2023 - The work relies in part on a transformer model, similar to the ones that power ChatGPT A new artificial intelligence system called a semantic decoder can translate a person’s brain activity — while listening to a story or silently imagining telling a story — into a continuous stream of text. The system developed by researchers at The University of Texas at Austin might help people who are mentally conscious yet unable to physically speak, such as those debilitated by strokes, to communicate intelligibly again. Read more
04/21/2023 - UT Computer Science Ph.D. Garrett Bingham’s research under Professor Risto Miikkulainen in smart automated machine learning has made significant steps toward more efficient neural network systems. Read more
04/11/2023 - AUSTIN, Texas — The University of Texas at Austin and Amazon are launching a science and engineering research partnership to enhance understanding in a variety of areas, including video streaming, search and information retrieval and robotics. Read more
03/03/2023 - A methodology developed by UT professors will allow the cost of verifying computations to be reduced by batching many separate arguments together. Brent Waters, a computer science professor and a co-author of the paper, was inspired to find a more efficient way to verify computations by refining techniques that had already come out over a decade ago. Read more
12/14/2022 - For decades, natural language processing (NLP) has provided methods for computers to understand language in a way that mimics humans. Since they are built on transformers, complex neural network layers, these large language models' decision making processes are usually incomprehensible to humans and require large amounts of data to be trained properly. In the past, researchers have tried to remedy this by having models explain their decisions by providing rationales, short excerpts of data that contributed most to the label. Read more

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