Lets start with the initial idea,
We have theorised something called, An Entangled Autonomous Neurons.
It’s a micro-agent architecture combining rapid statistical inference, structured symbolic reasoning, and bounded generative episodic memory.Each EAN encapsulates a statistical core for fast hypothesis scoring, a reasoning core implemented as a relational graph, and a local episodic memory for context retrieval and reconstruction. EANs operate in clusters above perception systems such as LLMs, vision encoders, and audio recognizers, enabling active learning, contradiction detection, and explainable reasoning. Inspired by entanglement in quantum mechanics, each EAN couples a learning state and reasoning state such that neither updates in isolation. We formalize the mathematical primitives for EAN operation, provide full pseudocode for the processing cycle, extend the design to a multimodal visual neuron with hierarchical feature memory, and discuss scaling strategies and theoretical foundations.