[Vitalik Uses Local AI Models Combined with Remote Tool Calls to Create a Three-Layer Privacy Protection Architecture for Generating Personalized Health Recommendations] Vitalik shared a personal experiment on Twitter, utilizing his own health and travel data in combination with cutting-edge models to generate personalized diet and exercise recommendations, while avoiding the leakage of any private information to remote models. The system employs a local model (Qwen 3.8 Flash Next) for orchestration, using powerful remote models as tools to access higher-level reasoning and knowledge not available in the local model. It adopts a three-layer privacy protection architecture: - Identity Layer: The local model (Qwen 3.8B) constructs query requests on behalf of the user to prevent writing style from exposing identity. - Payment Layer: zkAPI is used to conceal payment information. - Network Layer: Tor is used to hide the IP address. The system has successfully operated and generated recommendations.