Its a very curious project, but don't you end up pinning repligraph usability on model weights? Since you take indeterminism out of the equation, a repligraph's notability is as significant as the producing model's weights, and since there is no dice rolls to be made, the eyeball problem:

> Our blind spots, while not perfectly correlated, have substantial overlap

is entirely replicated. Models that are diffused from one another can have the same blind spots, the same loose statistical reality that exists with humans. This is partially addressed in steering:

> A repligraph proves that a model generated some artifact. It does not prove that the model did a good job, or that the artifact is safe.

but I think the "Peer Review" solution is inadequate, and with some jailbreaking prompts' innocuous looks considered, "the attacker just needs to find one prompt" might be much easier than it appears.

Batching seems to be a huge economic turn off for proprietary model determinism, but I think its entirely viable for consumer models. Trustless evals are brilliant and should've been our reality. Nice project, good luck on your endeavor.

[0]: https://mtlynch.io/tags/sia/