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| Auteur principal: | |
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| Format: | Recurso digital |
| Langue: | anglais |
| Publié: |
Zenodo
2026
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| Sujets: | |
| Accès en ligne: | https://doi.org/10.5281/zenodo.19947776 |
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Table des matières:
- <p>Recent developments in machine learning, information theory, and large-scale data processing have intensified the role of information as a central concept across scientific and technological systems.</p> <p> </p> <p>Information is commonly understood as content, message, or semantic structure that can be transmitted, encoded, and interpreted. This paper revisits these assumptions from a non-modal perspective.</p> <p> </p> <p>Within this framework, information is not treated as meaning or content. Instead, it is fixed as configuration fixation.</p> <p> </p> <p>Without introducing causality, temporality, or subject-dependent interpretation, information is considered without transmission, encoding, or semantic content. This reframing calls into question the conventional understanding of information in data-driven systems.</p> <p> </p> <p>This work forms part of a broader non-modal structural framework in which core scientific concepts are examined without reliance on relation, representation, or explanatory structure.</p>