ASH Model
A new neural-network architecture built on the ASH Model.
Ennea AI
AI Architecture · Coming Soon
Ennea AI
Ennea AI is a new kind of neural-network architecture built on the ASH Model: a recursive 9-dimensional hypercube where every vertex can unfold into another 9D Enneract. Instead of relying on massive floating-point weight matrices, Ennea uses Galdr bitwise compression to encode, repair, and route intelligence through compact binary structures. The result is an AI foundation designed to be highly scalable, fast, energy-efficient, and radically smaller than conventional neural networks.
Architecture
What Ennea is built to do
Recursive Enneract
A recursive 9-dimensional Enneract hypercube structure. Every vertex can unfold into another 9D Enneract.
Galdr
Galdr bitwise compression encodes, repairs, and routes intelligence through compact binary structures.
No weight matrices
Ennea does not rely on massive floating-point weight matrices.
Scale and efficiency
Designed to be highly scalable, fast, energy-efficient, and radically smaller than conventional neural networks.
Coming soon
Ennea AI is still in development. The public project home is this page.
Coming soon
Not released yet.
Questions, and requests to hear when Ennea AI launches, can go through the Raven Forge contact page.