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Old Cha says research report 🌟🌟🌟🌟🌟!! Mira Network @Mira_Network: New infrastructure for content verification, a "truth layer" on-chain worth preemptively ambushing. As Web3 has evolved, most people have come to understand one thing: Infra is always the king. No matter how the narrative changes daily, whether it's AI, RWA, DePIN, or Restaking, at the end of the day, whoever can truly provide foundational capabilities and build standards at the base layer can transcend cycles. And @Mira_Network is one of the "AI Infra" projects I've been keeping a close eye on recently. 🚀 Core positioning: A trusted verification protocol for AI content, creating an on-chain "truth layer." Do you think AI is just about generating images and writing articles? That's too shallow. The real killer application of AI is: becoming an Agent to execute tasks for us, even judging whether things are correct. The problem is that current AI often "talks a lot," presenting a whole set of claims, but in reality, it has numerous flaws and can even fabricate facts—this is what is known as AI hallucination. So what to do? How do we verify whether what AI says is true or false? This is precisely where Mira Network comes in: Decomposing AI content into structured facts → Verifying in a decentralized network → Generating trusted proof after consensus is reached. It doesn't let a single model decide, but rather allows multiple models to reach "consensus," then records this verification result on-chain, which can be reused across applications. This mechanism is a fundamental necessity for future Agent protocols. 🔧 Product matrix: Developer API, validator network, assertion credential system. Currently, Mira's products have evolved from "prototype" to "usable" stage: Mira Verify: The testnet is live, capable of verifying the authenticity of text and AI outputs, supporting content upload → Decomposition → Verification → Output credential; Multi-model verification network: Multiple model verification nodes vote in parallel, not relying on a single large model or team; Assertion Protocol: Supports citation assertions, original text comparisons, timestamps, etc., to build a citable "AI content evidence chain;" Developer API: Can be integrated into any application scenario such as Telegram Bot, browser plugins, DApps, etc.; Cooperative ecosystem: Already connected with AI infra projects like GaiaNet, Agent, KGEN, etc. 📊 Data highlights and ecosystem status: Daily average verified Tokens have exceeded 3B+; User count exceeds 4 million+, with cumulative on-chain verifications exceeding 30 million+; Supports multi-chain deployment (BSC, Base, Solana, etc.), multi-model access; Has become a verification component for leading AI Agent projects like GaiaNet, Phala, Creato, etc.; Featured by professional institutions like Messari, CoinLaunch, ChainCatcher, etc. 🎯 Token outlook & potential opportunities: Although Mira Network has not yet conducted a TGE, related signs indicate that the project has begun to fully promote the "incentive mechanism": 1. Exclusive domain entry; 2. The official has repeatedly mentioned that "contributing data and verification actions will receive incentives"; 3. Members of the MiraLabs team have participated in the construction of core modules like EigenLayer, Cosmos, Lagrange; 4. There are Retrodrop and node plan warm-ups, with intensive KOL participation. Logically speaking, as a foundational verification network, Mira's native Token may play the following roles: 1⃣️ Node staking and incentives; 2⃣️ Content verification fee settlement; 3⃣️ On-chain assertion construction and consumption; 4⃣️ Incentivizing verification participants and AI model staking. This type of dual structure of "use equals incentive" + "verification equals mining" can easily form early community dividends. 💡 Why I believe it is a "potential 100x Infra": Real demand: Untrustworthy AI outputs have become a core industry issue, and Mira was born to solve this problem; Clear positioning: Focused on the "on-chain verification layer," rather than being a jack-of-all-trades doing both LLM and Agent; Product usability, real data: Not a PPT project, on-chain data and usage have begun to scale; Wide cooperation: Already penetrated multiple AI ecosystems (GaiaNet, Phala, etc.); Token potential: No token issuance yet, clear incentives, high testnet playability, low participation cost. 🧠 Old Cha's personal advice: Immediately participate in the testnet ( Use more, verify more, provide feedback, and leave on-chain interactions in advance; Follow X (@Mira_Network), prepare for snapshots and incentive follow-ups in advance; If you are working on an AI project, it is recommended to directly integrate Mira's verification components, as on-chain trust will become increasingly important in the future; If you are an investor, it is recommended to include it in the "next batch of AI Infra" seed list, observing its TGE structure and release rhythm. Mira does not produce AI content; it simply makes content "trustworthy." Web3 lacks output tools, but what it lacks is a mechanism to judge the truth of outputs. And Mira could very well be the "Chainlink" of the AI content verification field. From an Infra perspective, it is not hype but a serious construction of foundational standards; from a value capture perspective, the Token is directly tied to behavior and traffic; from a user perspective, it is indeed useful, interactive, and has a future.

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