Research/Hype/Summary Links

• Executive Summary
• GE Answer to QAT/Quantization
• Ultra-Sparse Architecture

Zero-Table Spatial Routing: Topological Coordinate Mapping via Implicit Neural RepresentationsAs the Augmented Reality (AR) industry accelerates toward a persistent Spatial Web, a catastrophic infrastructure bottleneck has emerged: the latency of physical coordinate retrieval. Dividing the globe into actionable 10-meter spatial domains yields roughly 5.1 trillion distinct volumetric cubes. Traditional spatial databases—relying on branch-heavy logic like Spatial Trees or SQL—function as an infinite card catalog, introducing massive cloud-side I/O latency when processing simultaneous global queries. At Grounded Entropy, we have entirely bypassed this bottleneck by abandoning the database paradigm altogether. We are utilizing Implicit Neural Representations (INRs) to transform physical geography into continuous, orthogonal topological spaces, essentially turning the geometry of the map into the latent geometry of a hyper-sparse neural network.Rather than searching a table, our architecture executes a direct mathematical translation. By feeding raw coordinate data (Latitude, Longitude, Altitude) into a continuous spatial manifold, the network instantly calculates and outputs a localized Domain State Vector—a persistent spatial hash that acts as an immediate server routing address. This "zero-table" retrieval mechanism completely severs the reliance on database indexing. Because the mathematical calculation is the search, our network resolves queries with identical sub-millisecond speeds regardless of whether it is mapping ten localized zones or trillions of global coordinates.The performance metrics of this geometric routing engine represent a radical leap in footprint compression and deployment efficiency. During our spatial simulations, we successfully compressed multi-gigabyte spatial indexing infrastructures into a standalone, sub-300,000 parameter topological network. A primary challenge in this development was overcoming spectral bias and linear dependence within continuous multidimensional output spaces. We solved this by architecting the output manifold to support truly independent topological dimensions, preventing tensor collapse and ensuring high-fidelity spatial boundary resolution without artificial gating constraints.This breakthrough in Zero-Table Spatial Routing proves that the future of AR infrastructure does not require building exponentially larger database servers. By utilizing highly compressed, zero-latency lookups, we are laying the groundwork for a hyper-sparse backbone capable of powering global mixed reality, visual positioning, and autonomous edge navigation. Grounded Entropy is currently building out the final physical models to bring this instantly scalable, sub-millisecond architecture to the enterprise spatial computing market.