As AI begins to be introduced into on-chain execution and decision-making systems, a long-ignored issue gradually emerges, namely whether we can really verify the trustworthiness of AI's outputs. @inference_labs is the team working on this critical issue.

Inference Labs focuses on building verifiable AI inference infrastructure, with a core direction of introducing zero-knowledge proofs into the AI inference process, allowing on-chain systems to verify the correctness of inference results without exposing model details and input data.

The information disclosed by the official sources shows that the team has made continuous technical progress in zkML and verifiable reasoning architecture, significantly improving proof efficiency and system scalability.

This capability is particularly important for decentralized agents, automated financial strategies, and on-chain AI services, as it provides cryptographic-level trust assurance for AI outputs.

The path of Inference Labs is not to chase the hype of the application layer, but to address the core trust issues in the process of integrating AI and blockchain from the bottom up.

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