According to ChainCatcher, Messari released a research report on decentralized AI infrastructure Mira. Mira optimizes AI output reliability through distributed model consensus mechanism, and its verification layer can improve the accuracy of AI facts in scenarios such as finance and education from 70% to 96%. The protocol breaks down AI outputs into independent fact statements, which are cross-verified by heterogeneous models provided by node operators like Io.Net and Aethir, requiring consensus from over 2/3 of nodes to pass.
Mira currently processes over 3 billion text tokens daily, covering 4.5 million users across chatbots and educational platforms. The protocol adopts an economic incentive model, where verification nodes receive rewards based on their contributions, and abnormal nodes will be penalized. Partners include decentralized GPU computing providers like Hyperbolic and Exabits, achieving computing capacity expansion through node delegation mechanisms.
According to team data, the protocol reduces AI hallucination rates by 90%, with each verification taking less than 30 seconds. Users can trace the verification process through on-chain evidence, with each output accompanied by an encrypted certificate recording model voting details. Currently, integrated applications like Klok have utilized this technology to optimize educational content generation, with plans to expand into high-risk fields such as medical diagnosis in the future.
