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license: apache-2.0
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https://huggingface.co/datasets/neomonde-lab/law-e-framework/resolve/main/README.md
# Law E Framework – Thermodynamic Governance for AI Reliability

**Short description**

Law E is an operational framework that treats modern AI systems as thermodynamic information processes.  
It introduces a native governance layer that observes the “energy cost” and coherence of model outputs, and uses this signal to regulate hallucinations and unstable behaviors.

This repository hosts the **initial technical report** describing the framework, its main equations and the first proof-of-concept design.

📄 **PDF**: [`Law_E_Framework.pdf`](./Law_E_Framework.pdf)

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## Why Law E?

- Large language models are powerful but prone to **hallucinations**.
- Current guardrails are mostly **symbolic or heuristic**.
- Law E proposes a **physics-inspired governance layer**:
  - monitors useless energy dissipation ΔE
  - tracks global organization / stability
  - regulates inference when the system drifts

The goal is to move toward **self-regulated, energy-aware AI systems**.

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## Current status

- Conceptual framework and equations defined.
- First regulator–selector POC in development.
- Next steps:
  - standardized hallucination evaluation (TruthfulQA, etc.)
  - CPU/energy proxy metrics
  - public demonstrator for selected models.

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## Contact & Collaboration

Created by **Sébastien Favre-Lecca (Neomonde Lab)**  

- Website: https://neomonde.tech  
- Twitter: [@GoldOracle_E](https://twitter.com/GoldOracle_E)  

If you are working on AI safety, energy-aware AI, or robotics and want to collaborate on Law E evaluation or implementation, feel free to reach out.