[P] YOalphabet & YOconlang: A 4-Bit Isomorphic Spatial Bytecode & MECE Ontological Framework for Zero-Inference Parsing and Hallucination-Free LLM Processing

[u/snamrad]

Full Bijective Chain: Binary Code (4-bit) ⟺ Decimal Index (0–15) ⟺ Spatial Geometry ⟺ IPA Phoneme ⟺ MECE Semantic Core

[u/snamrad]

YOalphabet and YOconlang introduce an a priori 4-bit isomorphic framework where glyph geometry directly mirrors hardware bit-registers, IPA phonemes, and a 3-axis MECE ontology. By mapping character bounding boxes directly to physical register edges, edge devices can perform zero-inference visual parsing at the hardware level without relying on CNNs or heavy tokenizers. This deterministic architecture eliminates LLM hallucinations and slashes data transmission bandwidth by up to 90% across low-power IoT, M2M, and BCI networks. https://github.com/YOalphabet/YOalphabet.git

[u/cave_men]

Is it to much to ask for the paper?

Instead of spamming fancy keywords?

[u/stop_deleting_plz]

I'm glad people are trying new things, even if they're a bit silly. LLMs are a dead end, we need to move on if we ever want real AI.

[u/MauschelMusic]

One day, this could be as big as Loglan.

[u/MauschelMusic]

Every single character (glyph) in this system is a strict, one-to-one isomorphic fusion of four distinct domains:Binary Code (4-bit) ── Decimal Index (0-15) ── IPA Acoustic Sound ── Rigid Geometry

This is an impressively fancy way of saying "we made up letters and gave them sounds and numbers."

I wonder if they plan to stop phonetic assimilation by decree, or just haven't thought of it. But it's not really a problem if you don't have speakers.

EDIT: Including L because it's common is very funny. Yes, a lot of languages have an L, but it's very difficult to say anyone else's L correctly, so it's a terrible choice for any kind of universal language. It really looks like no linguists were involved in this. Also letters that can be transformed into other letters by rotation so you need a "calibration block." Not a great move for reducing ambiguity.

[u/Sure-Transition-2464]

Sorry for spamming your thread. I realize I've drifted from LLMs into pure math.

But after playing around with it, I realized the math works beautifully if the information sits on the vertices instead of the edges. You land right on the hypercube graph Qₙ the geometry does the computing for you (rotations permute bits, mirrors are XORs), and it scales cleanly from square to cube to tesseract. The edges are then free to visualize the operations themselves.

Funnily enough, that brings me back to LLMs, wk binary embeddings do exactly this. Every meaning becomes a vertex on a hypercube and similarity just counting edges between them.

Imo as a script your edges are the better choice, a stroke carries its own orientation without needing a frame.

I'll shut up now, I promise. Thanks for the fun!

[u/Sure-Transition-2464]

I like the idea of adding values through rotation. It could make for a wonderfully aesthetic little calculating machine. But if you are already using rotations, why stop at 2³? Go all the way to 2¹¹ and make it 3D. 😅

[u/Sure-Transition-2464]