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.
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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.
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10/20/2022 -
Autonomous robots will soon rove the buildings and streets of The University of Texas at Austin campus. But unlike other commercial delivery services, this fleet of robots will help researchers understand and improve the experience of pedestrians who encounter them.
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09/23/2022 -
As the technological world advances, it has become increasingly difficult for the speed of computers to improve. UT Computer Science Professor Dr. Chris Rossbach's research in field-programmable gate array (FPGA) virtualization has made significant strides in the development of a more efficient computing infrastructure.
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08/05/2022 -
The University of Texas at Austin and the MITRE Corporation, a nonprofit dedicated to solving problems for a safer world, have formed a partnership that includes accelerating innovative ethical artificial intelligence (AI) research currently underway by interdisciplinary teams of researchers who are part of UT Austin's Good Systems research grand challenge.
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08/04/2022 -
It's hard to make changes to the software running on a computer network while it's in use—and that can make it harder to respond quickly to a cyberattack. The National Science Foundation has awarded a grant to computer scientists from Rice University, The University of Texas at Austin and the University of Washington to develop runtime programmable networks that can respond to real-time changes rapidly and without interruption of service.
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06/29/2022 -
The ACM Internet Measurement Conference 2010 research paper “Network Traffic Characteristics of Data Centers in the Wild”, written by UT Computer Science Professor Aditya Akella, along with collaborators Theophilus Benson and David A.
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05/24/2022 -
As chips become larger and more complex, their routing algorithms must also be improved and optimized to face the challenge. Recent UT Computer Science PhD graduate Michael Jiayuan He’s research in computer chip design has made a notable step forward towards more efficient and successful chip design in the academic arena.
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