New Texas Center Will Create Generative AI Computing Cluster Among Largest of Its Kind
The University of Texas at Austin is launching the Center for Generative AI, powered by a new GPU computing cluster. This cluster will be one of the largest in academia and will offer world-class AI infrastructure to a wide range of partners.
UT Launches Center for Generative AI
The University of Texas at Austin is establishing the Center for Generative AI, which will be powered by a new GPU computing cluster. This cluster is set to be one of the largest in academia, with 600 NVIDIA H100s GPUs.
The Texas Advanced Computing Center (TACC) will host and support the cluster, known as Vista. The cluster, consisting of graphics processing units (GPUs), will enable rapid mathematical computations, making it ideal for training AI models.
Advancing AI Research and Collaboration
The Center for Generative AI will focus on biosciences, health care, computer vision, and natural language processing (NLP). It will be housed within UT's interdisciplinary Machine Learning Laboratory and led by the Cockrell School of Engineering and the College of Natural Sciences.
The center recognizes the growth of generative AI technologies and aims to collaborate with external partners in various industries. By applying generative AI solutions to challenging problems, the center seeks to drive innovation and make advancements in key sectors.
UT's Commitment to AI and Research
The University of Texas at Austin is investing in AI research and infrastructure to shape the future through teaching and research. The establishment of the Center for Generative AI is part of UT's broader efforts to leverage AI for advancements in healthcare, drug development, materials, and other industries.
UT's existing AI initiatives, such as the AI Institute for Foundations of Machine Learning (IFML) and the powerful Frontera supercomputer, provide a strong foundation for the Center for Generative AI. With this investment, UT aims to accelerate scientific discovery and solve complex engineering challenges.
