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The pipeline for th...
The pipeline for the continuous development of artificial intelligence models-Current state of research and practice
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- Steidl, Monika (författare)
- University Innsbruck, Austria.
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- Felderer, Michael, 1978- (författare)
- Blekinge Tekniska Högskola,Institutionen för programvaruteknik
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- Ramler, Rudolf (författare)
- Software Competence Center Hagenberg GmbH SCCH, Austria.
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University Innsbruck, Austria Institutionen för programvaruteknik (creator_code:org_t)
- Elsevier, 2023
- 2023
- Engelska.
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Ingår i: Journal of Systems and Software. - : Elsevier. - 0164-1212 .- 1873-1228. ; 199
- Relaterad länk:
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https://doi.org/10.1...
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https://bth.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Companies struggle to continuously develop and deploy Artificial Intelligence (AI) models to complex production systems due to AI characteristics while assuring quality. To ease the development process, continuous pipelines for AI have become an active research area where consolidated and in-depth analysis regarding the terminology, triggers, tasks, and challenges is required.This paper includes a Multivocal Literature Review (MLR) where we consolidated 151 relevant formal and informal sources. In addition, nine-semi structured interviews with participants from academia and industry verified and extended the obtained information. Based on these sources, this paper provides and compares terminologies for Development and Operations (DevOps) and Continuous Integration (CI)/Continuous Delivery (CD) for AI, Machine Learning Operations (MLOps), (end-to-end) lifecycle management, and Continuous Delivery for Machine Learning (CD4ML). Furthermore, the paper provides an aggregated list of potential triggers for reiterating the pipeline, such as alert systems or schedules. In addition, this work uses a taxonomy creation strategy to present a consolidated pipeline comprising tasks regarding the continuous development of AI. This pipeline consists of four stages: Data Handling, Model Learning, Software Development and System Operations. Moreover, we map challenges regarding pipeline implementation, adaption, and usage for the continuous development of AI to these four stages.(c) 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Software Engineering (hsv//eng)
Nyckelord
- Continuous development of AI
- Continuous (end-to-end) lifecycle pipeline for AI
- MLOps
- CI
- CD for AI
- DevOps for AI
- Multivocal literature review
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- for (ämneskategori)
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