Ethereum co-creator Vitalik Buterin conducted a personal experiment using his health and travel data to get personalized diet and exercise recommendations while preserving privacy. The approach relies on a local model (Qwen 3.8 Flash Next) that orchestrates remote models via tool calls, with three layers of protection: the local model writes queries to avoid leaking personal information or identity through writing style, zkAPI masks identity during payment, and Tor ensures network and IP-level privacy. The experiment worked and returned improved recommendations thanks to knowledge from frontier models. However, Buterin highlighted a fundamental trade-off: the stricter the privacy precautions, the less the remote model can help.
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