Summary distilled from a mediated design conversation between Jesse (monkeyboy), Aria (Gemini), and Ariadne (ChatGPT).
Working Summary: The VexaFracta Model VexaFracta is a proposed neural-computational substrate built around sparse, locally stateful, phase-sensitive units rather than dense, always-on layers. The central complaint is not that modern neural networks fail. Plainly, they do not. The complaint is that they succeed at enormous computational and financial cost, often by engaging far more machinery […]