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Episode 265: Where ZK and ML intersect with Yi Sun and Daniel Kang
Zero Knowledge
The Challenges of Quantization in Machine Learning on Edge Devices
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I actually do think that there are potentially ways to basically bridge the gap of like differentiable ML and also ZKP. I would say some of these quantization techniques are already the focus of a lot of work for people doing machine learning on edge devices, basically to save power on your cell phone. And it turns out that very roughly speaking, the difficulty of implementing inference in ZK can be proxied in some way by how much battery power a model actually takes. So people have been working on quantizing these models and reducing the compute. We can leverage a lot of that work to pick the best model to put in ZK.
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