Mosstone/Eidolon: Prerelease

Self improving, scalable agentic AI model focused on analytics and research automation. The architecture is specifically designed for open ended scalability. It refines training data with use to allow for more efficient paramter extraction from the abundant publicly available sources, extracting more viable data than otherwise possible. Dynamic loading of fine grained weights and software for use with a logical core model affords users a highly specialized model for their respective use cases while still receiving support from development of the core model. It aims to become an EU alternative to current frontier models, fully compliant with GDPR and European regulations. Sigil and other mechanisms facilitate sophisticated ontological and (well, sort of) cogntive affects. This significantly improve general performance relative to the size of the model, facilitates graceful handling of uncertainty, and focuses context on relevant data through abstract associations which current models struggle with. The model will focus on augmentation of human roles, replicating observed effective patterns in professional and academic settings for promoting creativity and minimizing time spent in repetition. Focused automation and human augmentation rather than general automation and human obsolescence. Passive development using visual and simulation models aims to create a native perception and robotics interface for the model without abstraction layers, allowing for fine motor function, responsiveness, and planning without relying on model interfaces. Applications particularly aligned with construction zone monitoring using drones and androids in a human assistive capacity wherein qualified skilled human workers receive alerts and safety data while remotely orchestrating the behaviour of automated labour. Developed and operated entirely in the EU.