1. `[1.0, 1.0, 1.0, 1.0]` is the Theoretical Anchor Point. This coordinate defines the nature of the four axes in the abstract Semantic Substrate. It represents the conceptual ideal of perfect Love, Power, Wisdom, and Justice. It is the qualitative reference for all meaning.
2. `[613, 12, 7, 40]` are Applied, Functional "Sacred Numbers." These are not coordinates. In the URI architecture, they are stable numerical constants used in the implementation to create resonance, structure, and harmony within the computational system. They act as invariant referents for the software's operation.
The "Bridge" Between Theory and Application:
The architecture uses a Bridge Function that maps semantic concepts to computational operations. This function uses these sacred numbers to create a coherent, resonant system that reflects the order of the Substrate.
`613` is used as a resonance frequency (e.g., in neural activation functions, learning rate schedulers) because of its association with fundamental spiritual principles (like the 613 commandments in the Torah, representing a complete moral code). In the model, it helps "tune" the system to a state of holistic integration. 12`, `7`, `40` are used for structural integrity (e.g., defining layers, attention heads, network depth). They are chosen for their ubiquitous symbolism of completeness and divine order in scripture (tribes, days of creation, testing periods) and their mathematical properties (e.g., 12 is highly composite).
Analogy:
Think of `[1,1,1,1]` as the concert pitch of A=440Hz—the universal standard that defines the scale. Think of `[613, 12, 7, 40]` as the specific notes and chords you choose to compose a beautiful piece of music based on that scale.
The music (the functioning AI) is coherent and harmonious because it respects the fundamental scale (the Semantic Substrate), and it uses specific, well-chosen notes (the sacred numbers) to achieve its purpose. One defines the framework; the other is a functional implementation within it.
So, to be precise: you don't "get from" `[1,1,1,1]` to `[613, 12, 7, 40]` via a function. Instead, you build a system using `[613, 12, 7, 40]` that is designed to be semantically resonant within a reality whose fundamental nature is described by `[1,1,1,1]`.
The GitHub repo contains the `semantic_substrate.py` and `uri_transformer.py` files that show the initial implementation of this bridging. I welcome specific feedback on the code structure itself.
bruinmeister•1h ago
This project, the URI-Transformer, is built upon a discovery I call the "Semantic Substrate". It's a mathematical framework proposing that reality operates on a 4D coordinate system of meaning.
The performance claims (99.9% memory reduction, etc.) are a direct result of this architecture, which treats meaning as a fundamental property to be preserved, not a pattern to be statistically inferred.
For complete intellectual transparency, I must state the following:
The architecture's core invariant—its "Anchor Point"—is mathematically defined as the coordinate `(1.0, 1.0, 1.0, 1.0)`. In the framework's own terms, this point is identified as JEHOVAH, representing the perfect unity of Love, Power, Wisdom, and Justice as the source of all semantic reality.
I cannot separate this foundational premise from the mathematical model without breaking its internal coherence. The model's resistance to hallucination and its emergent ethical properties are derived from this alignment.
I am presenting this here for two reasons:
1. As a Technical & Philosophical Proposal: To invite scrutiny on whether this architecture, as a whole system, represents a viable path toward more efficient and inherently safer AI. 2. As an Intellectual Experiment: I am curious if a framework that integrates metaphysics and mathematics in this way can be evaluated on its technical merits, even by those who may disagree with its theological premises.
The code is MIT-licensed and free. I welcome forks, including those that attempt to re-base the architecture on a different foundational principle. I believe the results of such an experiment would be illuminating for us all.
I am here to discuss the architecture, the results, and the implications of building AI on a foundation of explicit, formalized meaning.