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#MindNetwork Full Homomorphic Encryption (FHE) Reshaping AI

The Future of Agentic World: How FHE Ensures the Safe Operation of Millions of AI Agents?

In the world of decentralized AI Agents, security challenges include:

- Identity Forgery (e.g., malicious AI impersonating legitimate Agents)

- Data Leakage (e.g., training data being stolen)

- Untrusted Computation (e.g., AI models being tampered with)

Solutions provided by FHE:

✅ Verifiable Encrypted Identity: The identity data of each AI Agent (e.g., biometrics) is encrypted and stored, verified only through FHE to prevent forgery.

✅ Secure Model Training: AI can train on encrypted data, avoiding leakage of raw data (e.g., medical and financial data).

✅ Decentralized Consensus: FHE combined with ZK proofs ensures that the computation process is verifiable, preventing malicious nodes from tampering with results.

Mind Network's Agentic World has initially realized this vision:

- Over 54,000 AI Agents running on-chain, completing 1.2 million hours of encrypted training.

- Through FHE+ZK, ensuring AI decision-making is tamper-proof, applicable to scenarios such as financial forecasting and automated trading.

Mind Network is building a trustworthy, decentralized Agentic World through the triple innovation of FHE+blockchain+AI. Its core breakthroughs include:

- The first FHE chain (MindChain) launched on the mainnet

- DeepSeek officially integrated FHE-Rust SDK

- A secure training ecosystem for over 54,000 AI Agents

In the future, as the HTTPZ protocol matures, FHE may become the default privacy layer for Web3 and AI, truly returning data control to users.

I believe in the short term: FHE will rapidly land in fields such as AI Agents, privacy DeFi, and blockchain games.

In the long term: FHE may reshape internet architecture and become the core protocol of the HTTPZ era.

The ecological development of Mind Network is worth paying attention to, and its limited-time staking APY of 400% reflects strong market confidence. For investors optimistic about the integration of privacy computing and AI, the FHE track cannot be overlooked.