zkML (Zero-Knowledge Machine Learning) Definition - Glossary

zkML (Zero-Knowledge Machine Learning) is a method enabling machine learning models to prove results without revealing data used.

zkML (Zero-Knowledge Machine Learning) is an innovative approach that combines zero-knowledge proofs with machine learning. It allows models to provide proof of their outputs without disclosing the underlying data or model details. This is particularly useful for privacy-preserving applications where sensitive data must remain confidential. By using cryptographic techniques, zkML ensures that the model's predictions or decisions can be verified for accuracy without compromising data privacy. This technology is gaining traction in areas like finance and healthcare, where data security is paramount.