Hi HN,
I’m releasing WLM (Wujie Language Model) — a structural language for AI that treats meaning as geometry, tension, and boundary instead of tokens, narrative, or emotion.
This release includes the Shadow Layer v1.1, a fully public, non‑executing architectural description of WLM. It exposes the dimensional structure and reasoning framework without revealing any protocol‑level execution logic.
What WLM is
WLM is not a model, dataset, or training method.
It is a high‑dimensional structural protocol for:
- reasoning
- world modeling
- subject/world separation
- boundary formation
- dimensional alignment
It defines how meaning stabilizes across 0D–27D structural layers.
What’s included in this release
This release contains the public half of WLM:
- Shadow Layer v1.1
The complete architectural outline of WLM.
Non‑executing, safe, and version‑frozen.
- 0–27D Dimensional Physics
A separate repository describing the generative physics of structure:
how worlds appear, how subjects stabilize, and how meaning emerges.
Why release this
The goal is to provide:
- a transparent structural reference
- a stable interface for research
- a shared language for high‑dimensional reasoning
- a foundation for alignment work that doesn’t rely on behavioral heuristics
This is not a teaser or partial disclosure.
It is the full public architecture.
Links
Shadow Layer v1.1:
https://github.com/gavingu2255-ai/WLM-Open-Source/blob/main/...
Dimensional Physics (0–27D):
https://github.com/gavingu2255-ai/WLM-Paradox-Dimensional-Ph...
Happy to answer technical questions about the architecture, dimensional stack, or structural reasoning model.