Building formal frameworks at the intersection of statistical mechanics, active inference, and autonomous agent design. Exploring how possibility spaces unify physics, signals, and intelligence.
A 36-paper research program unifying statistical mechanics, active inference, and agent design through one formal language. 6 clusters spanning foundations, thermodynamics, signals, inference, AGI benchmarks, and applied systems.
A model of computation for meaning-native programming. Meaning addresses, stored programs, and the AGI infrastructure thesis — the computational substrate underlying possibility spaces.
Training data infrastructure for teaching models to do autonomous research. Structured task traces, source-target pairs, and evaluation schemas for fine-tuning and RLHF.