CanonBittensor
Bittensor: paper, then practice.
Bittensor's paper ranks machine-learning peers by each other's scores. A score among peers is not a proof that the model is right.
Yuma Rao. 2021. Status: Design paper. Last reviewed: 1 October 2026.
- The paper. Rao's paper for a market in which machine-learning models score each other. Peers rank neighbours, ranks accumulate on a ledger, and an incentive mechanism is specified to resist a naive cartel of mutual high scores. It is a design for pricing intelligence as a commodity, not a benchmark of any particular model.
- A reward for a measurable stand-in.
- If software can pay.
What this chain does not claim
It does not rank a network, quote a yield, or say the live client still matches the paper. The full study keeps the limits. Primary source: Bittensor white paper.