Files
neuron-tai/docs/adr/0003-optimistic-fraud-detection.md
Dobromir Popov 2f1f9717be tasks
2026-06-29 00:10:21 +03:00

1.4 KiB
Raw Blame History

Optimistic trust with stake slashing and strike-based bans

All inference responses are trusted by default. Validators re-run a random sample (~5%) of requests on reference nodes and compare outputs. Nodes that fail are slashed (stake reduced). Enough strikes result in a permanent on-chain ban.

New wallets must complete N jobs without earning (probationary period) to raise the economic cost of re-entering after a ban — a banned node can't just create a new wallet and immediately cheat again; it must fund a new stake and contribute N free jobs first.

zkML (zero-knowledge proofs of inference) would give cryptographic guarantees but is 100010000× slower than inference for large models and is not production-ready. Redundant execution consensus (Gensyn's approach) gives stronger guarantees but costs 23× compute per request. TEE (trusted hardware attestation) is cryptographically strong but excludes most consumer GPUs, defeating the viral GPU-sharing goal. Optimistic + slash is the pragmatic choice that ships and can be calibrated economically.

Considered Options

  • zkML: cryptographically perfect, not production-ready for large models in 2025
  • Redundant consensus: strong guarantees, 2-3× compute cost per request
  • TEE attestation: strong guarantees, excludes consumer GPUs
  • Optimistic + slash + strike ban: chosen — ships, works, economically tunable