Recently, I've been pondering privacy matters in Web3 and stumbled upon the Mind Network project, which I find increasingly convincing. Unlike some projects that just make empty promises, it directly utilizes fully homomorphic encryption (FHE) and quantum-level security protocols like 'HTTPZ', effectively addressing the entire set of privacy, security, and compliance issues on the chain.
Not long ago, they launched a new RWA on-chain encrypted messaging protocol, which seems to genuinely solve pain points. For things like documents, contracts, and invoices that cannot be made public, they can be encrypted and packaged as NFTs on the chain, accessible only to those you authorize. It’s somewhat akin to SWIFT messages in traditional finance, but it runs on the chain and cannot be altered, making it applicable in scenarios like cross-border payments, supply chains, and tax audits.
Moreover, it’s not just tinkering within Web3; it has also connected with Web2 terminals. They signed an MOU with Byteplus from ByteDance, enabling direct access to Lark's 40 million users, providing privacy services on Byte's Coze AI Agent platform, allowing Web2 AI to leverage FHE's security. The trusted AI from Alibaba Cloud has also landed on the cloud, enabling enterprise-level AI applications to run in compliance—these are tools that can be utilized right now.
Speaking of AI, this project is quite interesting in this aspect too. They developed an MCP (Model Context Protocol), which simply means that even without decrypting the data, it can verify whether the AI's output has been altered, establishing a 'credit profile' for AI Agents. In the future, with multiple Agents collaborating, it will be possible to determine which ones are reliable and which might be spouting nonsense, not only helping you brainstorm ideas but also ensuring that they 'don’t trick you'.
Previously, I heard from friends in government security that the period from June to August each year is the drill season for government systems. The most critical aspect of their defense is data encryption storage—so even if hackers breach the system, what they obtain is just a pile of encrypted data that is unusable. The Mind Network on-chain encrypted communication protocol feels like a Web3 upgrade of this approach, not just encrypting data but also creating an on-chain encrypted communication protocol layer that allows structured, verifiable encrypted information to be sent directly between wallets.
Traditional blockchain transaction information is too simplistic, just addresses and amounts, lacking semantics and privacy, failing to meet real-world compliance and auditing needs. Additionally, the chain is too transparent, making it impossible to disclose sensitive information, and lacking the structured expression capabilities like SWIFT messages, which cannot accommodate contracts or KYC content. However, the Mind Network protocol uses FHE to add an encrypted semantic layer to on-chain transactions, effectively enabling the blockchain to 'speak' while 'keeping secrets', allowing each transaction to include encrypted metadata like invoices and contracts, which only authorized parties can understand, and can be verified and audited without alteration.
Now everyone is hyping AI Agents, but the trust issue remains unresolved—when you communicate with an Agent, how do you know if it’s using a legitimate model? Will the data being processed be secretly retained? Relying solely on 'trust me' is ineffective. However, Mind Network is the first project to successfully implement FHE on the mainnet, allowing computation under encrypted data conditions, with everything sealed off, where no one can see the original text, not even the AI Agent itself. Their AgenticWorld is a 'zero-trust collaborative environment' for AI Agents, with encrypted and verifiable communication, computation, and consensus, preventing pitfalls like data leaks and model fraud.
Some say FHE might become the next hundredfold coin, and I believe its technological foundation is indeed solid. FHE addresses a significant pain point for AI on the blockchain—data privacy and computational security. The ecosystem is also growing quite quickly, attracting 2 million users in just over a year, with high annualized yields for staking FHE to activate AI agents. The token mechanism is also practical, with the team and investors locking their tokens for a year, and 41.7% allocated directly to the community, indicating a desire to create long-term value.
Overall, this project’s narrative and implementation are keeping pace, and if there are explosive developments later, the attention on FHE will surely remain high. If you are optimistic about privacy computing, RWA, or AI directions, it’s worth looking into further.
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