Show HN: Zero-power photonic language model–code (zenodo.org)
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.
7 comments
[ 4.4 ms ] story [ 31.6 ms ] threadIf it does work, I think one of the biggest challenges will be adding enough complexity to it for it to do real, useful computation. Running the equivalent of GPT-2 is a cool tech demo, but if there's not an obvious path to scaling it up, it's a bit of a dead end.
I expect to have an answer this week...
I apologize for not being clearer.
The goal isn't actually "zero power" - the goal is "so little heat dissipation in orbit is easy".