Affine is a an incentivized RL environment which pays miners which make incremental improvements on a set of tasks (for instance, program abduction or coding). The mechanism is sybil-proof (you cant cheat by deploying multiple miners), decoy-proof (you cant cheat by packing models into certain environments), copy-proof (you cant win by simply stealing the best model), overfitting-proof (you can't cheat by overfitting to the a single benchmark).
How does Affine work? Affine validators incentivize miners to submit models to
Subnet 64 on Bittensor (a.k.a Chutes) where they are inference load balanced
and publicly available. These models are evaluated on a set of RL-environments
with validators looking for the model which dominates the pareto frontier --
namely the model which out competes all other models on all envs (see
af validator) The network is winners-take-all where miners are
forced to copy, download and improve the pareto frontier model.
Why affine? Directed incentives for RL have never been achieved. The ability to direct intelligence and aggregate the work-effort of a large non-permissioned group of individuals on RL tasks will unlock fast advancement in intelligence, we intend to commoditize reasoning (intelligence's highest form) and break the intelligence sound barrier.
