What is zkML? More than the combination of buzz words.
This talk explores how Zero-Knowledge Proofs (ZKPs) and Machine Learning (ML) can be combined to prove a model inference occurred correctly—without revealing the input, output, or the model itself.
Laurence Kirk introduces the core concepts and motivations behind zkML, and explains why privacy-preserving, verifiable machine learning is a meaningful and emerging field.

Private Machine Learning with zkML notes

• Developers interested in privacy and cryptography
• Researchers exploring the intersection of ZKPs and ML
• Anyone curious about the future of private computation