Daniel: I think that this entire pipeline of going from a tested inputs from various sensors to feeding into inputs to machine learning models and algorithms is actually going to be really powerful in the future. So if you imagine your face ID on say an iPhone, it uses a DEP's camera to do the identification. And if you can combine that with say an image and also a clip of your voice, maybe that'll be much more secure and much more difficult to fool than it would be of just a plain image.
This week, Anna Rose and Tarun Chitra dive back into the topic of ZK ML with guests Yi Sun, co-founder of Axiom, and Daniel Kang, Assistant Professor of computer science at UIUC. They discuss Yi and Daniel’s previous academic work and what led them to get interested in ZK topics and specifically ZK ML. They then dive into a discussion about 2 recent papers which examine the use of ZK within Machine Learning architectures.
Here are some additional links for this episode:
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