A Neuro-Symbolic Hyperdimensional Architecture for Recursive Knowledge Intelligence

Large Language Models (LLMs) dominate contemporary Artificial Intelligence but sufferfrom hallucination, high computational cost, opacity, and poor suitability for low-resourceor offline environments. This paper introduces a novel AI architecture, internally referredto as God Node, which replaces generative modeling with a deterministic, neuro-symbolic,hyperdimensional memory system governed by recursive logic. The proposed system inte-grates a tiny neural encoder, a deterministic quantized projection layer (MPxC), hyperdi-mensional computing (HDC) based knowledge storage, and a recursive logic controller. Thisarchitecture enables semantic retrieval, controlled concept synthesis, and reliable reasoningwithout text generation. The work demonstrates that meaningful intelligence can emergefrom structured memory, vector algebra, and symbolic constraints, offering a safer and moreefficient alternative to large generative models for education, scientific knowledge systems,and low-resource AI.