zkML enables proving model predictions without revealing the model itself. This opens up possibilities that weren't feasible before.
Think about trading models. They're your edge. Your secret sauce. You want investors to trust your returns but you can't show them how the sausage is made. With zkML you can prove your model predicted something with specific accuracy without revealing anything about how it works.
The implementation is absolutely brutal though. Every neural network operation has to become polynomial constraints. Even a tiny model explodes into millions of gates. Proof generation takes forever.
But here's the beautiful part. Verification only takes milliseconds. So you spend minutes generating a proof but anyone can verify it instantly. That asymmetry is powerful.
The applications go way beyond trading. Medical diagnosis models that keep their methods secret. Proprietary algorithms that can be validated without being exposed. Competitive ML that stays competitive.
We're still early but the tech is improving fast. What seems impossible today will be standard tomorrow.
Keep reading
- ZK Coprocessors Are Underrated
Offload heavy computation to ZK proving, bring results back to chain. Smart contracts just got way more powerful.
- Verifiable Computation Without Trust Anchors
Verifiable computation usually leans on some anchor of trust, but proofs that work with zero assumptions about the prover would be ideal.
- Smart Contracts Think Now
Embedding AI models in smart contracts is theoretically possible. On chain intelligence at massive gas costs.