Lagrange's recent collaboration with Mira Network is worth following, as both parties are building a trust infrastructure for decentralized AI. Mira has always focused on decentralized verification of AI outputs, auditing and consensus verification of model responses through a distributed network of verification nodes. However, Lagrange's DeepProve technology takes this to a new level — it can generate zk-SNARKs for each model inference, achieving a proof generation speed 158 times faster than the existing zkML libraries.

This combination is very interesting. Mira is responsible for verifying the authenticity of AI outputs, while DeepProve mathematically proves the correctness of the computational process. Specifically, it addresses three core questions: Is the model actually running? Is the computation executed correctly? Can the output be trusted on-chain? This dual verification mechanism sets a new standard for Decentralization in AI.
On the technical indicators, DeepProve shows obvious advantages. In addition to its impressive proof speed, it can also maintain privacy-preserving logical verification, which is particularly important for AI applications that need to handle sensitive data. More crucially, these proofs can be directly integrated with oracles, smart contracts, or compliance systems, providing a verifiable AI service foundation for the entire Web3 ecosystem.
From the perspective of application prospects, this architecture may reshape the way AI services are used. Developers can build models that can self-verify logic, and intelligent agents can validate each output, ultimately forming an auditable AI service network. Considering the prevalent "black box" problem in the current AI + blockchain field, this verifiability design clearly aligns more with the spirit of Decentralization. As cooperation deepens, the role of LA tokens in the verification network may become more pronounced.

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