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Agility in Software...
Agility in Software 2.0 – Notebook Interfaces and MLOps with Buttresses and Rebars
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- Borg, Markus (author)
- Lunds universitet,RISE,Mobilitet och system,Lund University, sweden,Programvarusystem,Institutionen för datavetenskap,Institutioner vid LTH,Lunds Tekniska Högskola,Software Engineering Research Group,Department of Computer Science,Departments at LTH,Faculty of Engineering, LTH,Research Institutes of Sweden (RISE)
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Przybylek, Adam (editor)
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Jarzebowicz, Aleksander (editor)
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Lukovic, Ivan (editor)
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Ng, Yen Ying (editor)
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(creator_code:org_t)
- 2022-01-12
- 2022
- English.
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In: International Conference on Lean and Agile Software DevelopmentLASD 2022: Lean and Agile Software Development pp 3-16. - Cham : Springer Science and Business Media Deutschland GmbH. - 1865-1356 .- 1865-1348. - 9783030942373 ; , s. 3-16
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http://dx.doi.org/10...
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Abstract
Subject headings
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- Artificial intelligence through machine learning is increasingly used in the digital society. Solutions based on machine learning bring both great opportunities, thus coined “Software 2.0,” but also great challenges for the engineering community to tackle. Due to the experimental approach used by data scientists when developing machine learning models, agility is an essential characteristic. In this keynote address, we discuss two contemporary development phenomena that are fundamental in machine learning development, i.e., notebook interfaces and MLOps. First, we present a solution that can remedy some of the intrinsic weaknesses of working in notebooks by supporting easy transitions to integrated development environments. Second, we propose reinforced engineering of AI systems by introducing metaphorical buttresses and rebars in the MLOps context. Machine learning-based solutions are dynamic in nature, and we argue that reinforced continuous engineering is required to quality assure the trustworthy AI systems of tomorrow.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Software Engineering (hsv//eng)
Keyword
- Computer software
- Reinforcement
- AI systems
- Digital society
- Engineering community
- Essential characteristic
- Experimental approaches
- Integrated development environment
- Machine learning models
- Machine learning
Publication and Content Type
- ref (subject category)
- kon (subject category)
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