PXG v3.0 – Searchable Compression via 2D Spatial Decomposition

Show HN: PXG v3.0 – Searchable Compression via 2D Spatial Decomposition

PXG v3.0 – Searchable Compression via 2D Spatial Decomposition is a company in show hn launch.

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I’ve spent the last year developing a decomposition kernel that addresses the "Linear Bottleneck" in standard compression (Zstd, LZMA, Brotli).The Problem: Traditional algorithms operate on 1D streams. They are blind to the spatial, temporal, or hierarchical architecture of modern data (3D models, nested JSON, multi-modal blobs). When you force these structures into a 1D window, you leave significant entropy on the table.The Solution: PXG v3.0 maps binary data to a 13505x13505 grayscale grid. By treating data as a coordinate system rather than a line, our engine utilizes adaptive tiling to isolate redundant blocks across the entire file, not just a sliding window.Key Benchmarks:Efficiency: C

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Website: limitpixel.com/compression