Vitalik tests privacy protection AI health system: local model + zkAPI + Tor three-layer architecture to prevent identity leakage

Vitalik.eth posted on Farcaster revealing that he is conducting a personal experiment to generate personalized diet and exercise recommendations using personal health and travel data by combining local models with remote cutting-edge models while protecting privacy.

The system employs a three-layer privacy protection architecture:

• Identity Layer: A local model (Qwen 3.8B) replaces the user to construct query requests, avoiding the exposure of writing style that could reveal identity.
• Payment Layer: Uses zkAPI to hide payment information.
• Network Layer: Hides IP addresses through Tor.

The system is currently operational, but Vitalik pointed out three major shortcomings: Tor is inefficient and has high latency in unlinking requests; the local model runs at only 20-30 TPS, and a smooth experience requires over 100 TPS; the stricter the data protection, the more limited the assistance that the remote model can provide. The relevant code has been submitted to the Ethereum zkAPI repository.