We’ve been hacking on a different approach we call the WFGY Engine — it treats embedding space not as flat or uniform, but more like a semantic energy field. So instead of forcing everything into clean cosine ops, we track these “semantic residue structures” — kind of like how meaning resists compression when you flatten it too early.
We measure stuff like ΔS (semantic tension), λ_observe (viewpoint drift), and E_resonance (contextual energy), which lets us reason across curved or even broken spaces where normal LLMs kinda lose track. It’s a mix between geodesic logic and language field dynamics — weird but surprisingly stable.
A couple of early apps built on this — TXT OS, BlahBlahBlah, etc — ended up scoring 100/100 from 6 major AI models, which was a cool surprise. We’re still in early dev, but even Tesseract gave it a formal endorsement recently, which was huge for us.
Anyway, core engine is all open source if anyone’s curious: https://github.com/onestardao/WFGY
Would love to hear if others are exploring non-flat logic or weird manifold behavior in language space too.
can link the Tesseract thing if folks want