hal9-energy-scaling

Reference implementation anchor for:

"Road to HAL9: Energy-Intelligence Scaling Laws with Uncertainty Quantification" Jihyuk Im, Claude Opus 4. June 2025.

This repository will host:

• Monte Carlo uncertainty-propagation code behind Table 3.3 (68% / 95% CIs across HAL0–HAL9)
• Scaling-law fit pipeline for $I = \alpha E^{\beta}$ with $\beta = 0.73 \pm 0.08$
• Cross-validation harness against biological systems and current AI deployments (Tables §4.1, §4.2)

Status

Stub. Planned pieces:

1. mc/ — 10,000-sample Monte Carlo propagation (Python/NumPy) reproducing the confidence intervals in §3.3
2. fits/ — nonlinear fitter for α, β given power-vs-performance measurements
3. validation/ — biological-system (ant colony, beehive, brain, primate troop) and AI-cluster (GPT-4, TPU pod, Dojo-class) datasets and checks

Paper

See paper/HAL/L4_Road_to_HAL9_v2.md in the companion paper repository:

https://github.com/labforadvancedstudy/paper

License

TBD (will track the companion paper repo's license once that is finalized).