DeepProve: a cryptographic receipt for every AI inference. now open source.
Halo: autonomous coordination engine for the toughest conditions.
@LagrangeFndn$LA
The Frontier Red Team at @AnthropicAI just made the case that you should be able to check which AI model answered you, without ever seeing its weights. Their research names DeepProve “the current peer-reviewed state of the art.”
A player jammed our swarm 389 times over Los Angeles, for more than ten minutes. It lost no drones and finished all eight sites 30 seconds after the jamming stopped. How long can you hold it?
holdtheswarm.lagrange.dev
For most of computing, checking someone's work meant doing it again.
You cannot do that with an AI inference. You do not have the weights. You do not have the input data. You do not have their hardware. Re-running is not expensive, it is unavailable.
That is why a proof is not
Prove you're over 18 without showing your birthday. Prove the answer is right without showing the work. DeepProve does that for AI inference, and @AnthropicAI's research team just named it the current peer-reviewed state of the art in the field. @chbpap explains the idea.
A model gets retrained on a Tuesday and every proof about it has to start over. @chbpap, our chief scientist, walks through the Eurocrypt 2026 paper on proofs that update instead.
Proud that @AnthropicAI’s research recognizes @lagrangedev's DeepProve as the current peer-reviewed state of the art.
Every AI answer should come with a proof of which model gave it. Trust is moving from “take our word for it” to “check it yourself,” and today a frontier lab
New Anthropic research: progress on provable inference for large language models.
Here, we introduce FlashProve. Building on established cryptographic techniques, FlashProve allows developers to verify whether a given response came from a given AI model. It’s substantially more