Types of usecases:

1. Run model on-chain:

   • Encode the whole trained model in script.
   • Results can be used arbitrarily in smart contracts.

2. Prove knowledge of input data:

   • Model encoded in circuit for zk-SNARK.
   • Prove the knowledge of a certain input that for which the trained model produces a specific output.
   • Only proof verifier is on-chain.

3. Prove possesion of trained model / pay someone for model training:

   • Structure of model is defined in circuit.
   • Weights and biases of the trained model are passed into the circuit as a private input.
   • Only proof verifier is on-chain.