---
# System prepended metadata

title: 'Unraveling ZKML: Present Realities and Future Horizons in Privacy-Preserving AI - Cathie, Ethereum Foundation'
tags: [DAY1, ZK, '2023']

---

# Unraveling ZKML: Present Realities and Future Horizons in Privacy-Preserving AI - Cathie, Ethereum Foundation

###### tags: `2023`, `DAY1`, `ZK`
{%hackmd @ethtaipei/ByQLufgQ2 %}

:::success
👀 [**Presentation Slides Here**](https://www.canva.com/design/DAFgqqAboU0/4HscC5E3YkFRFk3bB64chw/view)
:::

> Share your thoughts from here

* public data, param make it possible to train the model on server (the circuit ensure the server running the right way)

* integer model is sometimes powerful in certain use cases

* folding scheme requires some fundamental change to the existing model. kind of impractical for large enteprise to change the architectureat the moment 

* FHE-ML and zkML
different entity hold the data, you do FHE
same entity hold the data, you do zk ML.
