March 13, 2024, 4:43 a.m. | Mohammad Hossein Jarrahi, Ali Memariani, Shion Guha

cs.LG updates on

arXiv:2211.14611v2 Announce Type: replace
Abstract: Data is a crucial infrastructure to how artificial intelligence (AI) systems learn. However, these systems to date have been largely model-centric, putting a premium on the model at the expense of the data quality. Data quality issues beset the performance of AI systems, particularly in downstream deployments and in real-world applications. Data-centric AI (DCAI) as an emerging concept brings data, its quality and its dynamism to the forefront in considerations of AI systems through an …

abstract ai systems artificial artificial intelligence arxiv cs.hc cs.lg data data-centric data quality data quality issues deployments however infrastructure intelligence learn performance quality systems type

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