Reliquary's Minable Post-Training Mechanism on Bittensor Explained
const_reborn · x · 2026-09-30
The author breaks down Reliquary's "minable objective" mechanism on Bittensor, calling it one of the most compelling structures for scalable post-training: miners spin up compute fleets, download the network model, and search rollouts on a target model to partition the reward landscape, surfacing negative samples that become optimal training inputs — analogous to Bitcoin miners burning energy for hashes. He frames it as harnessing idle market compute in ways frontier labs can't, a protocol-coordinated, market-coordinated route that is "inevitable and unstoppable."
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