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Draft:Fractal Morphological Machine (FMM)

From Wikipedia, the free encyclopedia


A Fractal Morphological Machine (FMM) is a experimental neural network that uses a hyperdimensional shape's in much the same way black box data is used in a LLMs.

Its a modular mathematical architecture that is considered language-independent where manifolds are compartmentalized to be optimization independent. Meaning a part of the FMM can be optimized without effecting the over all action of the FMM unless a optimized-compartment is used. This flexible optimization is what largely distinguishes its self form other fractal manifold data schema which often have propagating optimization. This is because propagating optimization is considered a major effeminacy boost, however in the case of the FMM, propagating optimization is sacrificed in exchange for data integrity.

Early tests show it can be used as a deterministic genitive AI that could one day compete with the non-deterministic LLM frameworks.

However, the only known working application as of today, of an FMM is as a Codebase scanning tool.[1]

References

[edit]
  1. ↑ Scanner, Bad Character. "Why FMMs Are The Future". Bad Character Scanner™. Retrieved 2026-04-09.