Artificial intelligence systems designed with inherent properties that allow for external, cryptographic proof of their computational correctness and integrity.
Mechanism
This involves techniques like zero-knowledge proofs (ZKPs) or verifiable delay functions (VDFs) to generate proofs demonstrating that an AI model executed as intended on specific data, without revealing the model or the sensitive input data itself.
Methodology
The system architect designs AI models and their execution environments to produce cryptographic proofs, enabling trustless verification of AI outputs and model integrity in decentralized applications or sensitive computational contexts. This addresses transparency and trust issues in AI.
This deployment establishes a robust framework for institutional capital to engage with Ethereum's Layer 2 ecosystem, optimizing yield and mitigating risk.
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