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This research examines the implications of computing power on the process of model selection.

March 15, 2026Open Access

Computing power and model selection

Key Points

This research examines the implications of computing power on the process of model selection.
Investigated the relationship between computing power and model selection.
Discussed historical perspectives on motivations for model selection.
Analyzed modern computing methods for their influence on model selection.
Conclusion suggests that error reduction is not the sole goal of model selection.
Findings indicate a largely negative stance on the appeal of using computing power for model tuning.

Abstract

Abstract The relationship between computing power and model selection, following a scenario suggested by Humphreys (and others), is investigated. Against the worrisome conclusions of this scenario it is argued that using computing power to tune models has not been the only goal of science so far. Other reasons for model selection were always in play. It is discussed if modern computing methods, supplied with contemporary compute, make pursuing model selection on the grounds of error reduction alone more appealing. The conclusion is largely negative.

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Cite This Study

Nico Formánek (Fri,) studied this question.

synapsesocial.com/papers/69b606ea83145bc643d1d51e https://doi.org/https://doi.org/10.1007/s11229-026-05494-0

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