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zk-SNARKs in 10 Milliseconds
Key technical topics covered in this session include:
- The 10-Millisecond Benchmark: A deep dive into the performance metrics where the system achieves a mean verification time of 10.55 ms (~94.77 ops/s), fulfilling the criteria for "instant verifiability",.
- Hybrid Proof Policies: Analyzing the runtime selection between BN254 Groth16 zk-SNARKs, STARK-backed transcripts, or a hybrid mode to balance speed and cryptographic robustness,.
- Lean 4 Theorem 5 (Instant Verifiability): Examining the formal mathematical proofs that guarantee every model update can be verified against the protocol's security claims,.
- Verifiable Aggregation at Scale: How these proofs enable the auditable coordinator model, where updates are verified inline to prevent "faked" rounds in the 10-million-node architecture,.
- Python SDK Integration: A look at how these complex cryptographic primitives are exposed through high-level helpers in the Mohawk Python SDK v2 for developer ease of use,.
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By Ryan WilliamsKey technical topics covered in this session include:
- The 10-Millisecond Benchmark: A deep dive into the performance metrics where the system achieves a mean verification time of 10.55 ms (~94.77 ops/s), fulfilling the criteria for "instant verifiability",.
- Hybrid Proof Policies: Analyzing the runtime selection between BN254 Groth16 zk-SNARKs, STARK-backed transcripts, or a hybrid mode to balance speed and cryptographic robustness,.
- Lean 4 Theorem 5 (Instant Verifiability): Examining the formal mathematical proofs that guarantee every model update can be verified against the protocol's security claims,.
- Verifiable Aggregation at Scale: How these proofs enable the auditable coordinator model, where updates are verified inline to prevent "faked" rounds in the 10-million-node architecture,.
- Python SDK Integration: A look at how these complex cryptographic primitives are exposed through high-level helpers in the Mohawk Python SDK v2 for developer ease of use,.