Update README.md

README.md

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-license: mit
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+---
+license: mit
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+
+# What is this?
+This is to be the home for potential extensions to the geofractal router concept.
+
+Multiple global fractal router weights will be saved here.
+
+These are meant to be pretrained for specific numeric use-cases and finetuned for extension.
+
+These include message moving, prime valuation, geometric accuracy assessment, structural awareness, global wormhole fingerprints, and structural analysis utility.
+
+Each router is highly experimental and the structure may change. Consider this the natural extension of the wormhole router structure from geovit-david-beans.
+
+# What is a geofractal router?
+A router in standard-sense has a network topology that allows multiple devices to rapidly communicate through a unified structure.
+
+A GEOFRACTAL router directly leverages pytorch utilities in an attempt to provide a fully request-oriented structure for collectives to interface with.
+
+# What is the target goal?
+A collective fingerprint-centric collective coordination that can be rapidly learned, enhanced, predicted, and expanded upon.
+
+# Why?
+The larger a network becomes, the slower the network becomes at transferring information from A to B. This is a natural extension to mitigate this and provide 
+reusable learning based on cantor fingerprinting.
+
+Experiments show; when collectives begin with geofractal designs, they orient along those constraints with independent losses, objectives, and applied offsets.
+
+# Hypothesis
+A centralized routing hub for all collective representations will allow a more cohesive delegation vote between all collectives.
+This will enable a more organized and coordinated fusion between many divergent structures with easily extensible progressions from the fusion route.
+
+This router process is currently unproven. The fusion is touchy as-is, but the most recent experiments show that a converged fusion is rock solid. 
+They have trouble unlearning crystalline structures, which means as earlier david experiments show they rapidly converge to MAYBE the incorrect relational behavior.
+
+My hypothesis is, a more centralized weighting with more potential routing options will allow for rapid expansion in a more organized fashion.
+
+# Potential upsides
+Faster collectives, more rapid experiments, easier to use extensions, global anchor registry aka cantor fingerprint address, and a few other benefits.
+
+Attaching additional models that are entirely external to the structure with much easier measures than setting up entire hook/extraction systems.
+
+# Potential downsides
+Added overhead from the learning mechanisms. 
+
+# Citation
+
+Author: AbstractPhil + Claude Opus 4.5
+License: MIT
+
+A cite isn't required but it would be nice.