Zero-power photonic language model–code
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.
In plain words
Zero-power photonic language model–code is a language model that uses a 1024-dimensional complex Hilbert space with programmable Mach–Zehnder interferometer layers instead of traditional neural network components. It generates token probabilities through quantum mechanics' Born rule rather than attention mechanisms, and can produce coherent text generation after training for under 1.8 hours on a consumer GPU. The project is designed for researchers exploring quantum approaches to machine learning, with plans for eventual physical optical implementation.
written from the facts on this page · September 2026
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