AIT Reformulation of Integrated Information: Consciousness as Kolmogorov Complexity — E8 Intelligence Research

FINDING: IIT formalizes consciousness as integrated information Φ, and the AIT-based reformulation (arXiv:1405.0126) replaces lossy Φ with a lossless algorithmic measure — linking consciousness to Kolmogorov complexity rather than Shannon information. | MATH: Φ = min over bipartitions of [effective information of whole − Σ effective information of parts]; AIT version: Φ_AIT ≈ K(whole) − Σ K(parts), where K is Kolmogorov complexity. Tononi's Φ is bounded by min-cut of the causal transition probability matrix (TPM). | CONNECTION: The min-cut/bipartition structure is a graph-theoretic partition problem — related to spectral graph theory (Fiedler vector, Cheeger constant) and to lattice/root-system decompositions. No direct 0.618/1.618 constants appear in the core formalism; the golden ratio is not intrinsic to IIT. | DEPTH: 6 FINDING: The cerebellum (~80% of neurons, ~69 billion) generates near-zero Φ, while cortex (~16 billion neurons) generates high Φ — consciousness scales with integr Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com