Important points
- Zero-knowledge proofs increase transparency while maintaining confidentiality of the decision-making process.
- Lagrange is a pioneer in integrating zero-knowledge proofs into AI to ensure privacy.
- Current privacy methods in AI fall short compared to innovative cryptographic approaches.
- Privacy-preserving models require the integration of encryption from the development stage.
- Open source models often perform poorly in commercial applications.
- When deploying AI models, it is important to protect both intellectual property and consumer data.
- Many private AI solutions fail to enhance the privacy of commercially relevant models.
- The technology industry’s focus on trivial applications is hampering national security efforts.
- ZK Machine Learning relies on mathematics, not hardware, for privacy.
- Aerospace and defense venture financing is inadequate for national security needs.
- Lagrange’s Deep Proof library is a significant innovation in protecting AI data.
- Zero-knowledge technology is reshaping the cryptographic security landscape.
Guest introduction
Ismael Hishon-Rezaizadeh is CEO and co-founder of Lagrange Labs, where he leads the development of DeepProve, the world’s fastest zkML library for verifiable AI inference. He spearheaded the first zero-knowledge proof of Google’s Gemma3 large-scale language model, demonstrating production-ready validation with 158 times the performance of competing solutions. His research is advancing ZK technology from cryptographic applications to defense-critical applications such as protecting autonomous drone swarms.
