Ethereum co-founder Vitalik Buterin has detailed a personal experiment blending artificial intelligence with privacy-preserving technology, while reaffirming his long-term vision for Ethereum
Ethereum co-founder Vitalik Buterin has detailed a personal experiment blending artificial intelligence with privacy-preserving technology, while reaffirming his long-term vision for Ethereum’s evolution.
Buterin explained that he recently conducted a self-experiment using his own health and travel data to generate personalized diet and exercise suggestions. The objective was to receive meaningful recommendations from advanced AI models without compromising privacy or exposing personal details to external systems.
To implement this, Buterin combined a local AI model (Qwen 3.8 Flash Next) for orchestration with selective access to more powerful remote models. The local model handled sensitive data and delegated broader problem-solving to remote models via controlled requests, reducing the risk of confidential information being shared externally.
He utilized a skill file that guided the local model in constructing queries that revealed minimal data, while benefiting from the expertise of frontier models. According to Buterin, zkAPI wrapped with Tor was employed as a command-line tool to further safeguard his interactions.
Buterin reported that the process was effective, stating that recommendations generated with the input of advanced models showed tangible improvement over locally generated results.
Buterin shared that his system, combining zkAPI with Tor, worked as intended, offering feedback: “I got the recommendations back, info from frontier models helped to improve them.”
Despite the successful outcome, Buterin noted three main limitations. He emphasized that increased caution when communicating with remote models typically results in less helpful responses, illustrating the privacy-utility tradeoff present in current AI deployments.
Mini dictionary: zkAPI, short for Zero-Knowledge API, enables privacy-preserving interaction with AI models or external services by allowing computations or queries without revealing underlying sensitive data. The use of Tor further anonymizes internet traffic between the user and external servers.
While discussing the AI experiment, Buterin reiterated his broader ambition for Ethereum. He described Ethereum as evolving into a “cryptographic world computer,” a concept which outlines the platform’s future as a publicly verifiable network capable of private, secure, and scalable computation for global users.
In a recent post, Buterin reflected on Ethereum’s development over the past fifteen years, emphasizing that upcoming technical milestones will represent a significant shift in the platform’s core architecture.
He identified the upcoming Pectra hard fork, scheduled for next year, as the last traditional upgrade for the network. Buterin anticipates that subsequent enhancements will incorporate advanced cryptographic components, including recursive STARKs, automated formal verification, optimized consensus mechanisms, and quantum resistance. These improvements, paired with initiatives like PeerDAS, mark Ethereum’s transition to a system that is fundamentally more powerful and secure than its original blockchain design.
Buterin believes that post-Pectra, Ethereum’s transformation will accelerate, prioritizing privacy, efficiency, and high-security computation on a global scale. He characterizes this as the beginning of a new phase in Ethereum’s narrative.
The network aims to deliver computation that is much cheaper, more scalable, and more private than was possible in previous technology cycles, realizing the vision of a global cryptographic world computer.
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