Information can increase in computation only relative to subsystems and observers

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Information increase in computation is observer-dependent, relative to the computational direction chosen.claim0.893
  Extension of information dynamics: direction of information increase (e.g., forward multiplication vs. reverse factorization) depends on observer's goals.
• Information flow and increase must be understood relative to subsystems and their interaction with environment.claim0.870
• The direction of information increase is relative to the observer or user of the computationclaim0.863
  Example: 3×5→15 is a natural computation, but 15→3×5 (prime factorization) is also useful, showing that the 'gain' depends on the choice of normal form.
• Information increase in computation arises from data reduction and making implicit information explicit, not logical increase.claim0.848
  Author's proposed resolution to the information increase paradox: computation gains utility through extraction and filtering, not creation of logically new content.
• information increase in computationconcept0.841
  The puzzle that computation appears to gain information despite logical closure; resolved by relative to subsystems/observers.
• How can information increase in computation if output is logically implied by input?question0.834
• Agents and their interactions are intrinsic to studying information flow in computation, not peripheral to classical information theory.claim0.775
  Central thesis: traditional static information theories fail to capture dynamic interaction necessary for understanding modern computing.
• Cognitive functions, including sentience, can potentially be achieved by very different systems and their disparate substrates.claim0.759
  Central multiple-realizability claim of the paper, from abstract and §2.