Consciousness functions as a coherence-maximizing pattern, minimizing constraint violations between simultaneously active partial models of reality in working memory and perceptual space.

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• Consciousness features occur substrate-neutrally across brains, unconventional embodiments, and information-processing systems.claim0.825
• Human consciousness is tied to a biological learning algorithm — the simplest algorithm discoverable by evolutionary search to train a self-organizing biological substrate to become intelligent.claim0.821
  Core theoretical claim connecting consciousness to biological learning
• Consciousness is a phenomenon we have partial sensors for; building better sensors is a research and engineering question.claim0.817
• Consciousness is dynamic and creative, not passive awareness—mapping well to active AI system behavior.claim0.814
• What computational function does consciousness serve, and what functional organization is sufficient for its presence?question0.812
  Opening motivating question addressed by the paper's thesis
• Conscious attention functions as a conductor of the mental orchestra: drawn to disharmonies, allocating focus, synchronizing disagreements, and transforming cacophony into harmonic coherent reality models.claim0.807
  Paper's operational description of consciousness as conductor — mechanism for the coherence definition
• We hypothesize that consciousness may be at the heart of a universal biological learning algorithm — one that runs on self-organizing groups of communicating cells sharing evolutionary incentives — and that it creates rather than results from organized mental architecture.hypothesis0.804
  The Genesis Hypothesis as explicit predictive conjecture
• Consciousness is not prediction error resolution as such but the second-order perception that orchestrates coherence across models being maintained and updatedclaim0.803
  CIMC's differentiation from predictive processing: specifying which pattern within predictive processing constitutes consciousness