Related papers: Building an AI-ready RSE Workforce

Building an AI-ready RSE Workforce

URL: http://arxiv.org/abs/2111.04916v1
Date: Tue, 9 Nov 2021 02:36:24 GMT
Title: Building an AI-ready RSE Workforce
Authors: Ying Zhang (1), Matthew A. Gitzendanner (1), Dan S. Maxwell (1), Justin W. Richardson (1), Kaleb E. Smith (2), Eric A. Stubbs (1), Brian J. Stucky (1), Jingchao Zhang (2), Erik Deumens (1) ((1) University of Florida, (2) NVIDIA)
Abstract summary: Machine learning and deep learning are being applied in every aspect of the research software development lifecycles. We discuss our views on today's challenges and opportunities that AI has presented on research software development and engineers.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Artificial Intelligence has been transforming industries and academic research across the globe, and research software development is no exception. Machine learning and deep learning are being applied in every aspect of the research software development lifecycles, from new algorithm design paradigms to software development processes. In this paper, we discuss our views on today's challenges and opportunities that AI has presented on research software development and engineers, and the approaches we, at the University of Florida, are taking to prepare our workforce for the new era of AI.

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