Generative Latent Reconstruction (GLR) Protocol: A Post-Pixel Architecture for Transductive Media Transmission

For three decades, digital media transmission has relied on pixel-preserving compression algorithms (e.g., MPEG-4, AV1) that utilize block transforms, motion vectors, and discrete cosine transforms to reduce data footprints. As these legacy architectures approach their patent expiration cliffs, they are hitting the theoretical limits of Shannon’s channel capacity. The Generative Latent Reconstruction (GLR) Protocol abandons pixel transmission entirely. Instead, it transmits semantic intent. By leveraging an Asymmetric Autoencoder and a mathematically pure Finite Scalar Quantization (FSQ) bottleneck, the cloud encoder packs deterministic UI and architectural states into an 8-dimensional latent bitstream (the .glr format). At the edge, a highly optimized neural network (“The Cylinder”) transduces these discrete coordinates back into high-fidelity pixels. This architecture achieves up to a 100× reduction in bandwidth, decoupling visual complexity from file size and allowing resolution-independent rendering directly on Neural Processing Units (NPUs).