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We just released a paper proposing a 'Topological Restructuring of AI'. Instead of training deep networks with Backpropagation (which is slow and energy-hungry), we project data onto a fixed Ramanujan Graph (optimal spectral expander) and solve the readout in closed-form. Benchmarks: Desktop (i5-4570, 4th gen): 287x speedup vs standard MLP training. Mobile (Android ARM64): <0.6ms latency per inference (1600+ fps). Accuracy: ~95.2% on MNIST (comparable to trained MLPs). The code is C++ (for edge) and Python (for research). We believe this is a path towards deterministic, Green AI that runs on commodity hardware.

Happy to answer questions about Spectral Graph Theory.