Definition ∞ Model privacy pertains to the protection of sensitive information embedded within or used by artificial intelligence models. This involves techniques that prevent the inference of training data from model outputs or parameters, ensuring that proprietary or personal data remains confidential. It is crucial for deploying AI in regulated environments or when dealing with confidential datasets.
Context ∞ The discussion around model privacy is increasingly relevant as AI systems are integrated into financial services and blockchain applications, where data confidentiality is a significant concern. Current debates focus on the efficacy of various privacy-preserving AI techniques, their computational costs, and the regulatory compliance requirements for AI models that handle sensitive information, especially in decentralized contexts.
Blockchain Knowledge
Cryptocurrency Foundation
Cryptospace Newsfeed
