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e8-lattice

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Kaleidoscope is an experimental cognitive architecture for emergent intelligence. It uses an E8 lattice physics engine and an RL-steered LLM to autonomously generate novel theories about complex systems. Features a visualization hub of its internal thought-space.

  • Updated Dec 7, 2025
  • Python

Discrete Kakeya cover for LLM KV cache: D4/E8 nested-lattice quantisation realising a Kakeya-style tube-cover over the direction sphere. 2.4x-2.8x compression at <1% perplexity loss on Qwen3, Llama-3, DeepSeek, GLM-4, Gemma. Drop-in transformers.DynamicCache. pip install kakeyalattice.

  • Updated Apr 30, 2026
  • Python

BIHE Protocol - Next-generation vector quantization combining E8 lattice geometry with Lloyd algorithm optimization. Achieves 16× compression ratio while maintaining 88.5% recall on real-world datasets. Validated on Stanford SQuAD v2.0 (5,000 texts) and Microsoft MS MARCO (6,000 texts). Features NSM below Shannon theoretical limits.

  • Updated Oct 27, 2025
  • Python

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