{
  "abstract": "Thermodynamic accounts of intelligence have advanced rapidly, but they do not yet resolve a prior definitional problem: what makes internal structure intelligent rather than merely ordered? This paper argues that any thermodynamic intelligence metric should include a usefulness filter. The numerator must track internal structure that is relevant to viability, prediction, and control, not merely raw information or benchmark score. Intelligence is therefore defined as the resource-bounded capacity of an adaptive system to acquire, compress, and deploy useful internal structure so as to improve prediction, control, and robustness across a range of environments. Capability and efficiency are separated. Capability is adaptive reach, A, defined over a reference distribution of environments or task families. Efficiency is acquisition efficiency, I_eff = Delta C_u / W_diss, where C_u denotes useful internal structure and W_diss physically dissipated work. Concretely, C_u is the predictive and control-relevant information that a system's internal state carries about viability-relevant environmental structure, making it a semantic rather than purely syntactic information term. I_eff is a learning or adaptation metric, not a complete scalar measure of deployed intelligence: trained systems at steady state may have Delta C_u = 0 while still exhibiting high adaptive reach. A toy numerical example with exact Landauer-referenced dissipation costs, explicit boundary conditions, temperature-normalised reporting conventions, and falsifiable comparisons against size-based and energy-only baselines are provided.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.14197",
  "author_total": 1,
  "authors": [
    {
      "name": "Boris Djordjevic"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/eh6wwy8ghezxe.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.14197",
  "fulltext_url": null,
  "id": "eh6wwy8ghezxe",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.14197",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "physics.gen-ph"
    ],
    [
      "openalex",
      "3109|Complex Systems and Dynamics"
    ]
  ],
  "openalex": "W7221801052",
  "pdf_url": "https://arxiv.org/pdf/2610.14197",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/eh6wwy8ghezxe.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:06Z",
      "native_id": "2610.14197",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.14197"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "openalex:3109|Complex Systems and Dynamics",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "Intelligence as Useful Structure: A Thermodynamic Perspective",
  "title_text": "Intelligence as Useful Structure: A Thermodynamic Perspective",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:06Z",
  "url": "https://research.draconitic.com/paper/eh6wwy8ghezxe",
  "venue": "arXiv",
  "versions": []
}