HN – Show HN: Zero-power photonic language model

The model uses a 1024-dimensional complex Hilbert space with 32 layers of programmable Mach–Zehnder meshes (Reck architecture) and derives token probabilities directly via the Born rule.

Despite using only unitary operations and no attention mechanism, a 1024×32 model achieves coherent TinyStories generation after < 1.8 hours of training on a single consumer GPU.

This is Part 1 - the next step is physical implementation with $50 of optics from AliExpress.

Show HN: Zero-power photonic language model–code

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