UT is launching the Center for Generative AI, powered by a new GPU computing cluster, among the largest in academia. The cluster will comprise 600 NVIDIA H100s GPUs — short for graphics processing units, specialized devices to enable rapid mathematical computations, making them ideal for training AI models.
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The findings, published this week in the Proceedings of the National Academy of Sciences, highlight the problems that arise when data published for one task are used to train algorithms for a different one. Jonathan Tamir, assistant professor of electrical and computer engineering in the Cockrell School of Engineering and a member of the UT-led National Science Foundation AI Institute for the Foundations of Machine Learning, is one of the study’s co-authors.