Mira Sparks a New Era in AI Verification with Distributed Validation System

The onset of Mira: the revolution in AI verification. A lawyer in the United States used AI to find case law, only to reveal that it was a 'non-existent case,' which highlights a structural flaw in LLMs—namely, hallucination issues. This is not merely a trivial incident but points to fundamental challenges in expanding AI in high-stakes sectors such as healthcare, finance, and legal fields, where manual verification remains essential, thereby limiting AI's growth. Mira Network aims to address this through distributed verification, where multiple AIs cross-verify each other's outputs. Incentive designs prevent random guesses, and accuracy improvements from 73.1% to 95.6% are achieved without human intervention. Verification occurs at the token claim level and could incorporate ZK protocols to ensure privacy. The core objectives are straightforward and clear: create AI that doesn't require human verification, unlock markets worth billions in healthcare and legal sectors, and eventually develop 'verification-embedded AI models.' Mira maintains the premise that 'AI lies,' but instead focuses on constructing mechanisms to catch these lies. This approach aims to expand AI into vast, verifiable territories beyond narrow applications. The overall aim is to evolve from a narrow pipe of AI verification to a vast, verifiable AI ocean.