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  "path": "/t/continuation-drm-transformer-from-open-geometry-to-negotiated-geometry-in-ai-alignment/176106#post_7",
  "publishedAt": "2026-05-28T02:09:03.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "Your approach employs “truth-seeking, ground-seeking, intelligence concept (paradigm).” Alternative is the Entropy Attractor Intelligence Paradigm. Truth correspondence brings with it gamut of philosophical issues. Try defining intelligence in terms of entropy management, chaos navigation. For one, you get to use entropy as your measurement spine. For another, you avoid philosophical issues such as those involving Turing’s Halting Problem, Gǒdel’s Incompleteness Theorem, more. You get a “linguistic space (that) does not contain “true,” “false,” and “truth,” with “reality” as either trivial or meaningless, to use Alfred Tarski’s disquotation theory cues, where the boundary between space and cyberspace, to use Norbert Wiener’s parlance, is also treated as trivial or meaningless thanks to Claude Shannon’s formulation of entropy in the way the boundary between physics and chemistry is treated also as meaningless thanks to the formulation by Ludwig Boltzmann of entropy. In the spirit of Kurt Gödel’s Incompleteness Theorem, Alan Turing’s Halting Problem, and Alonso Church’s Undecidability of First Order Logic Thesis plus never ending demands of entropy, … (there are no) metaphysical or ontological claims nor claims to completeness … Physical, informational, and social systems live in one entropy geometry; any boundaries we draw (physics vs chemistry, offline vs online) are memetic/governance conveniences, not ontological walls.”",
  "title": "[Continuation] DRM Transformer: From Open Geometry to Negotiated Geometry in AI Alignment"
}