Revisiting accepted wisdom in SNARK design

Justin Thaler (a16z crypto) explains how Lasso and Jolt, which represent a fundamentally new approach to SNARK design, upend some conventional wisdom about SNARK design. These misconceptions include:

#1. SNARKs over large fields are wasteful. Everyone should use FRI, Ligero, Brakedown, or variants because these avoid elliptic curve techniques, which typically work over large fields.

#2: Simpler instruction sets lead to faster zkVMs.

#3. Breaking large computations into small pieces comes with no performance loss.

#4: High-degree constraints are necessary for efficient SNARKs. #5. Sparse polynomial commitment schemes are expensive and should be avoided if possible. None of these holds any longer.

About the presenter

Justin is Research Partner at a16z crypto and an Associate Professor in the Department of Computer Science at Georgetown University. His research interests include verifiable computing, complexity theory, and algorithms for massive data sets. In 2011, he produced the first implementation of a general-purpose interactive proof system. He is the author of a comprehensive survey on SNARKs titled Proofs, Arguments, and Zero-Knowledge, and a co-creator of Apache DataSketches, an open-source library of production-quality streaming algorithms.Before joining a16z crypto and Georgetown, Justin was a Research Scientist at Yahoo Labs. Before that he completed her PhD in Computer Science at Harvard University.

About a16z crypto research

a16z crypto research is a multidisciplinary lab that works closely with our portfolio companies and others toward solving the important problems in the space, and toward advancing the science and technology of the next generation of the internet. More about us: a16z.com/2022/04/21/announcing-a16z-crypto-research