The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects

R. Dzhusupova, Jan Bosch, Helena Holmström Olsson

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

3 Citaten (Scopus)

Samenvatting

Artificial intelligence is increasingly becoming important to businesses since many companies have realized the benefits of applying Machine Learning (ML) and Deep Learning (DL) into their operations. Nevertheless, ML/DL technologies' industrial development and deployment examples are still rare and generally confined within a small cluster of large international companies who are struggling to apply ML more broadly and deploy their use cases at a large scale. Meanwhile, current AI market has started offering various solutions and services. Thus, organizations must understand how to acquire AI technology based on their business strategy and available resources. This paper discusses the industrial experience of developing and deploying ML/DL use cases to support organizations in their transformation towards AI. We identify how various factors, like cost, schedule, and intellectual property, can be affected by the choice of approach towards ML/DL project development and deployment within large international engineering corporations. As a research result, we present a framework that covers the trade-offs between those various factors and can support engineering companies to choose the best approach based on their long-term business strategies and, therefore, would help to accomplish their ML/DL project deployment successfully.
Originele taal-2Engels
TitelCAIN '22
SubtitelProceedings of the 1st International Conference on AI Engineering: Software Engineering for AI
Plaats van productieNew York
UitgeverijAssociation for Computing Machinery, Inc
Pagina's124–135
Aantal pagina's12
ISBN van elektronische versie978-1-4503-9275-4
DOI's
StatusGepubliceerd - 17 okt. 2022
Extern gepubliceerdJa
Evenement1st International Conference on AI Engineering, CAIN 2022 - Pittsburgh, Verenigde Staten van Amerika
Duur: 16 mei 202224 mei 2022

Congres

Congres1st International Conference on AI Engineering, CAIN 2022
Verkorte titelCAIN 2022
Land/RegioVerenigde Staten van Amerika
StadPittsburgh
Periode16/05/2224/05/22

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