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logseq/assets/Sundberg e Holmström - 2023 - Democratizing artificial intelligence How no-code.edn
2025-06-05 22:07:12 +02:00

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:content {:text "training AI models without any coding and we argue that they have high potential utility in operationalization of ML"},
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:content {:text "No-code AI platforms can make AI accessible and affordable for organizations that lack the size and technological competence needed for solutions that require advanced coding skills, and guide users through the process of developing and deploying AI models, with no need to learn the detailed workings of complex algorithms."},
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:content {:text "ML has been defined as “a broad subset of artificial intelligence, wherein a computer program applies algorithms and statistical models to construct complex patterns of inference within data” ("},
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:content {:text "many organizations are engaging in systematic ways of developing, deploying and monitoring ML operations"},
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:content {:text "he development of ML significantly differs from traditional software development as ML models are dynamic and constantly changing (Borg, 2022; Moreschini et al., 2022). "},
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:content {:text "end to degrade over time, unless these changes are considered, and accounted for using new datasets(Constantiou & Kallinikos, 2015), and additional cycles of training and evaluation."},
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:content {:text "generative AI models are increasingly being integrated in different kinds of systems, we expect them to be a part of many AI solutions in the near future."},
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