This week, we spoke with Morten Dahl, VP of Blockchain Engineering at Zama, about his work with fully homomorphic encryption (FHE) and its applications across blockchain and machine learning. Key takeaways include:

A detailed exploration of FHE, highlighting its ability to perform computations on encrypted data without decrypting it, with applications in privacy-preserving machine learning and blockchain.

Insights into Zama’s products, including TFHE-rs for core encryption, Concrete and Concrete ML for encrypted computations, and the FHEVM co-processor for scaling encrypted transactions on blockchains like Ethereum.

Discussion on challenges and advancements in FHE, such as performance bottlenecks, scalability through custom hardware, and the integration of cryptographic techniques like ZK proofs and MPC.

Vision for the future, including decentralized KMS solutions, enhancing the usability of encrypted smart contracts, and leveraging FHE for distributed identity, auctions, and gaming.

A forward-looking perspective on cryptographic innovation, focusing on combining solutions like FHE, ZK proofs, and TEs to achieve secure, scalable, and user-friendly applications.