Applied to the cryptocurrency trading field, AI can help you become a genius trader, directly outperforming the competition!

People say the environment is unfavorable; it's just that we haven't found the right direction. The FHE+AI revolution has begun and will affect every aspect of our lives. If the lever is extended towards us, we must climb upwards!

In the current wave of AI sweeping the globe, data privacy has become a core issue restricting its development. Fully Homomorphic Encryption (FHE), as a black technology that allows 'calculations on encrypted data', is quietly igniting a revolution in privacy computing. It not only addresses compliance and privacy challenges when AI uses sensitive data, but also opens the door for multiple high-sensitivity scenarios.

1. The Disruptive Value of FHE+AI

Traditional AI model training and inference require access to plaintext data. Once data leaks, it poses significant risks. FHE allows data to be used directly by AI models while encrypted, without exposing any original information.

This means: Data never 'leaves the warehouse', privacy is no longer compromised, greatly enhancing the credibility and security of AI systems in finance, healthcare, and other fields.

2. Medical Field: A breakthrough for sensitive data AI.

Data in the medical industry is extremely sensitive, such as gene sequences, medical records, imaging data, etc. Once leaked, the consequences are unimaginable. Traditional solutions often struggle to find a balance between protecting privacy and extracting data value.

FHE can achieve the following breakthroughs:

AI-Assisted Diagnosis: Hospitals can share encrypted imaging data and use AI models to collaboratively diagnose diseases without needing to decrypt.

Personalized Medical Model Training: Training AI based on patients' encrypted case data to generate personalized treatment recommendations, with no risk of data leakage.

Multi-Center Research: Different medical institutions can jointly use FHE for AI research, breaking down data silos.

3. DeFi and Finance: A key puzzle piece for privacy smart contracts.

In DeFi, users' trading, asset portfolios, and strategy information are highly sensitive. The addition of FHE can change the game rules:

Privacy Oracle Data Processing: Through FHE, oracles can read and process off-chain encrypted data, then submit results without exposing the original data.

Private Credit Scoring System: FHE combined with AI models to achieve a privacy credit scoring system for on-chain users without revealing their true assets or behaviors.

High-Frequency Encrypted Trading Model Hosting: Users can encrypt their strategies and entrust them to the platform; the platform runs the model without being able to glimpse the strategy logic.

4. Games and the Metaverse: A shield for protecting player privacy.

With the development of blockchain games and the metaverse, player data (assets, behaviors, interactions) is becoming increasingly important, but it also faces the risk of being analyzed, mined, and even fed advertisements.

FHE+AI has great potential here:

Behavior Prediction and Matching Mechanism: AI can complete matching and recommendations without identifying the true behaviors of players.

Anti-cheat AI Model: Processing encrypted player behavior to ensure the fairness and privacy of the model.

Privacy NPC Interaction: Allowing AI to read players' partially encrypted preferences and attributes to achieve a more authentic interactive experience.

5. Summary of Key Usable Scenarios

Conclusion: FHE will become the 'fuel' for the next stop of AI.

Although FHE currently faces challenges in efficiency and engineering implementation, with technological breakthroughs from projects like Zama and Inpher, as well as the ongoing efforts of OpenAI and Google in privacy AI, FHE is rapidly moving towards practicality. For a new world that balances Web3, AI, and privacy, FHE is not just a shield but also an accelerator. The future data era will belong to players who can tame AI with FHE!