Zero Knowledge Proofs (ZKPs) have become a fundamental building block for creating scalable and privacy-preserving decentralized applications. ZKPs enable verifiable computing, but the powerful math behind ZKPs is both compute and memory intensive. Furthermore, no single proof system excels at efficiently proving the diverse set of operations involved in a ML-based data processing pipeline.
In this project, you will explore producing efficient ZK proofs for the entire data processing pipeline. The project will involve exploring the latest ZK proof systems & lookup techniques and applying them to common pre-processing tasks and ML inferencing tasks used in text, image, and audio processing pipelines. The focus will be on identifying which proofs systems are best suited for the data processing operations involved. Furthermore, you will also explore ways of composing proofs from different proving systems in a universal and extensible manner.
Duration: flexible, to be agreed (typically 3-4 months), starting time is flexible
Location: Stuttgart (Germany)
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