This article discusses the importance of zero-knowledge proofs (ZK proofs) in verifying and securing artificial intelligence (AI) models. ZK proofs allow one party to prove that a computation was executed correctly without revealing the actual data or requiring the verifier to redo the calculations. This is valuable for off-chain computational tasks, as it enables verification without burdening blockchains. Machine learning (ML), a subset of AI, has heavy computational demands, and using blockchains for verification can be expensive. ZK cryptography can bridge the gap between ML's computational demands and blockchain's security guarantees by allowing off-chain execution of computations and on-chain verification. ZKML has various applications, including in decentralized finance (DeFi), where it can ensure the legitimacy of AI algorithms and protect users' trading data. The article emphasizes the need for trust and accountability in AI models and suggests that integrating ZK cryptography into AI can help build this trust. Overall, ZK cryptography can serve as a method to verify the integrity of AI models and ensure they are authentic, ultimately enhancing the security and reliability of AI in various industries.



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