GEOLIP Research Concepts
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A series of repos dedicated to geolip research and results, some with stored weights, some without. All entirely based on the progress of geolip. • 8 items • Updated
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AbstractPhil
AI & ML interests
datasets, research papers, experimentation, vision, classification, text encoders, tokenization, llms, diffusion, distillation, and more.
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AbstractPhil/geolip-constellation-core Organizations
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geolip-captionbert's captions are still cooking, it's going to need more days.
Until then I'm restoring an old prototype named vit-zana and reforming her into geolip-zana. This vit was built on the old pentachoron vocabulary which only contained 5 anchors of frozen utility, this specific version houses the full nth anchor structural hypersphere, which we'll test for behavior within the new spectrum of utility.
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Clawd breadcrumb trail AbstractPhil/geolip-hypersphere-experiments
With this I'll begin forming Clawd interface utility with the geofractal router, which will allow Clawd to form agentic clouds of utility that can be datawise trained on the go with minimal hardware requirement. This is not ready yet, but it begins very soon.
The recent experiments have solved the alignment issue that crippled collectives and forced my hand into ensemble research instead.
With those recent experiments, the geofractal router will allow modularization structural capacity after some preliminary alignment adjustment and adjudication experimentation. This will enable the full collective differentiation through codified attribution.
In other words, adding and removing modular AI elements to contribute to aligned communication streams, all speaking the same language. This is an adjacent and more powerful result than the anticipated geovocab patchwork, and it yields substantially more effective agentic solutions than moving around a bulky embedding echo-chamber.
https://github.com/AbstractEyes/geofractal
Procrustes whitening orthogonality will allow adding and removing elements from geofractal routers given a small amount of prep data, while the anchors of expectation can stay as a snap-on element.
The most inquisitive and interested researchers can follow the trail to find all of the experiments. Web crawl it with clawd and you can probably create a unified rationality pretty quickly, but I doubt you'll like what you find. The journey was extensive and the failures outweighed the successes, but I did find the lightbulb.
The represented outcomes are either in my articles in huggingface, my civit articles, my github repos, my huggingface repos, or I forgot to upload them and they're in my colab notebook heap.
As most research yields, it is mostly failures. However, there are many successes in the mix. Many. If you need solutions, you can dredge the bog.
With this I'll begin forming Clawd interface utility with the geofractal router, which will allow Clawd to form agentic clouds of utility that can be datawise trained on the go with minimal hardware requirement. This is not ready yet, but it begins very soon.
The recent experiments have solved the alignment issue that crippled collectives and forced my hand into ensemble research instead.
With those recent experiments, the geofractal router will allow modularization structural capacity after some preliminary alignment adjustment and adjudication experimentation. This will enable the full collective differentiation through codified attribution.
In other words, adding and removing modular AI elements to contribute to aligned communication streams, all speaking the same language. This is an adjacent and more powerful result than the anticipated geovocab patchwork, and it yields substantially more effective agentic solutions than moving around a bulky embedding echo-chamber.
https://github.com/AbstractEyes/geofractal
Procrustes whitening orthogonality will allow adding and removing elements from geofractal routers given a small amount of prep data, while the anchors of expectation can stay as a snap-on element.
The most inquisitive and interested researchers can follow the trail to find all of the experiments. Web crawl it with clawd and you can probably create a unified rationality pretty quickly, but I doubt you'll like what you find. The journey was extensive and the failures outweighed the successes, but I did find the lightbulb.
The represented outcomes are either in my articles in huggingface, my civit articles, my github repos, my huggingface repos, or I forgot to upload them and they're in my colab notebook heap.
As most research yields, it is mostly failures. However, there are many successes in the mix. Many. If you need solutions, you can dredge the bog.
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Procrustes ViT Shared Manifold Alignment Experimentation
Create hypersphere_convergence_analysis.py
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AbstractPhil
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I've been working out something akin to a liars paradox solver. This should help the berts form their own internal adjudication system for determining knot potential and the utility of solution. This should allow the bert soup to be more cohesive.
This will only be a fraction of the complexity of something like an LLM has, but it would endow the bert with a bit more information curation.
As of today they are still too agreeable, so I'll need to run hard negatives to ensure captions are correct as a processing substrate for the 180m caption train.
replied to their post 2 days ago
That's not the case. I'm training adjacent versions with different datasets with R1 100%, the objective is just too easy.
Weight decay corrupts the geometry it cannot be used.
Early stopping isn't necessary.
Everything you mentioned is very basic, but thank you for your effort.