Cell State Machine
Gene-regulation network + metabolism + signaling as a discrete-event system.
Biological computation as a stack: cells → tissues → brains → bodies → populations.
Life OS treats living systems as a multi-scale computation. Each cell is a chemical state machine; tissue is the aggregate; the nervous system is the long-distance signaling layer; the brain is a predictive model of the world; the population is a search algorithm running on the genome over evolutionary time. Life OS connects these scales into one model and exposes them to the rest of the ecosystem. Civilization OS pulls demographic projections; Decision OS pulls neural priors; Sensory OS pulls the perceptual substrate; Reality Kernel imposes thermodynamic ceilings. The honest position: most of biology is still folk physics dressed up as molecular detail; the interesting frontier is where information theory and chemistry meet.
Gene-regulation network + metabolism + signaling as a discrete-event system.
Spiking → cortical column → area → network — predictive coding hierarchy.
Population-genetic dynamics; selection, drift, recombination, novelty.
Birth, death, migration; cohort tables; projection.
Cross-checks proposals against metabolic energy ceilings (interfaces with Reality Kernel).
Provide population-level projections.
GET /life/projectionProvide neural decision priors per individual.
GET /life/{id}/neuralProvide perceptual substrate parameters.
GET /life/{id}/percept-substrateSubmit metabolic feasibility queries.
POST /metabo/feasibilityPush birth/death/marriage events.
POST /life/eventsdN/dt = r·N·(1 − N/K)Logistic — population growth bounded by carrying capacity.
ΔP(allele) = s·p(1−p) — selection differentialAllele frequency change per generation under selection coefficient s.
Brain ≈ minimum-description-length world modelEmpirical: cortex compresses sensory streams into compact predictive structure.