#mira $MIRA Mira Network: The Trust Layer for AI
Mira Network is a decentralized verification protocol designed to serve as a "trust layer" between AI models and end users. It specifically targets the AI reliability gap—the inherent tendency for Large Language Models (LLMs) to produce hallucinations (fabricated info) or biased outputs.
Instead of building a new AI model from scratch, Mira builds a system to verify the outputs of existing models (like GPT-4, Llama, or Claude), bringing factual accuracy from roughly 70% up to 96% in certain use cases.
How Mira Solves AI Reliability
The protocol operates on the principle of "Collective Intelligence" rather than relying on a single source of truth.
Claim Decomposition (Binarization): When an AI generates a complex response, Mira breaks it down into discrete, "atomic" claims.
Example: "The Eiffel Tower was built in 1889 and is in Madrid" becomes:
Claim A: "The Eiffel Tower was built in 1889."
Claim B: "The Eiffel Tower is in Madrid."
Distributed Verification: These individual claims are sent to a decentralized network of Verifier Nodes. Each node runs a different AI model or verification logic to check the claim's validity.
Consensus Mechanism: Nodes vote on whether a claim is "True" or "False." By aggregating votes from diverse models, the network filters out hallucinations that might slip through a single model.
Economic Incentives: The network is secured by the $MIRA token. Node operators must stake tokens to participate; they are rewarded for honest verification and "slashed" (lose their stake) for providing incorrect or lazy data.