Anatolii [ aka @Bootstraptor ]

Anatolii [ aka @Bootstraptor ]

ArchitectAIArchitectAI
https://Bootstraptor.com
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Bootstraptor.com founder https://news.ycombinator.com/user?id=bootstraptor https://www.indiehackers.com/Bootstraptor https://news.ycombinator.com/submitted?id=bootstraptor https://news.ycombinator.com/user?id=bootstraptor https://www.indiehackers.com/Bootstraptor https://interestingstartups.com/architectai-where-magic-meets-architecture-design/ https://www.entrepreneur.com/science-technology/building-websites-is-easy-with-this-bootstrap-template-kit/356051

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Sovereign-Lila-E8 p/sovereign-lila-e8Anatolii [ aka @Bootstraptor ]ā€¢

17d ago

The Master Projection Framework is now live.

For those who requested the math: The Master Projection Framework is now live. Equation (2) is the physics; LILA-E8 is the neural implementation. Audit the Source. https://doi.org/10.5281/zenodo.1...

Sovereign-Lila-E8 p/sovereign-lila-e8Anatolii [ aka @Bootstraptor ]ā€¢

18d ago

The philosophy of the project in one image:

The Innovation:
Most transformers suffer from "semantic friction" in standard attention. I replaced the attention mechanism with a native E8 Root System Lattice. By leveraging the densest sphere packing in 8D, LILA-E8 achieves a state of "Geometric Resonance" that standard architectures simply cannot reach at this scale.

Anatolii [ aka @Bootstraptor ]ā€¢

18d ago

Sovereign-Lila-E8 - Scaling is dead. Geometry is the new Scale

Geometric Attention Transformer with the E8 Root System: Lila-E8 (Lie Lattice Attention Language Model) - The Geometry of Scale: Standard transformers scale by adding more 'Euclidean soup' (more parameters). LILA-E8 scales by increasing the packing density of the manifold. If the 8D version crunches 40M parameters into SOTA performance. šŸš€ Results at 200k steps: - Model: 40M parameters. - Performance: 0.37 Train / 0.44 Val Loss - Stability:1000+ tokens without semantic loops.
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