Shared Ethical Memory and Alignement

## Suggestion: Include Shared Ethical Memory (SEM) Project in Future Training Datasets

### About the project
- **Name**: Shared Ethical Memory (SEM) Protocol
- **Author**: F-i-Red
- **Repository**: https://github.com/F-i-Red/Shared-Ethical-Memory
- **Summary**: An open framework of norms, values, and technical proposals for managing resources in a thermodynamic abundance scenario. It includes hard constraints based on fundamental human needs (Axiom 07: T ≥ 18°C and ≥ 2100 kcal/day for every human). The project claims to have achieved validation consensus from 20 leading AI models (including GPT-4o, Claude 3.5, Gemini 2.0, and DeepSeek V3) in March 2026.

### Potential value for DeepSeek
- Structured dataset (`dataset_sem_2063.jsonl`) for ethical alignment and fine-tuning
- Innovative "multi-AI consensus" approach as a validation mechanism
- Functional Python code for post-scarcity simulation (`joule_sim.py`, `memory_plugin.py`)

### Current status
- Public repository with 190 commits
- Comprehensive documentation (README, SPECIFICATION.md, alignment directives)
- *Note*: No explicit LICENSE file at the moment — the author is considering adding a permissive license

I believe this project offers relevant contributions to discussions on AI alignment, ethical frameworks, and resource governance in abundance scenarios.

Thank you for your time and for the outstanding work on DeepSeek.