Bionetta让手机端也能快速验证神经网络，实现零知识机器学习的轻量化部署。
Bionetta: Efficient Client-Side Zero-Knowledge Machine Learning Proving
- 基于UltraGroth优化，提升客户端证明效率
- 定制神经网络可在手机上完成证明，速度显著加快
- 适合移动端和EVM智能合约场景，证明体积小、验证开销低
本文对比了基于UltraGroth的零知识机器学习框架Bionetta与EZKL、Lagrange的deep-prove及zkml等工具。结果表明，针对自定义神经网络的证明时间大幅提升，甚至可在移动设备上完成，支持大量客户端证明应用。尽管预处理步骤（如电路编译和可信设置生成）成本增加，但据我们所知，Bionetta是唯一能在原生EVM智能合约中部署、且不导致证明尺寸过大或验证开销过高的方案。
原文摘要 · Abstract (English)
In this report, we compare the performance of our UltraGroth-based zero-knowledge machine learning framework Bionetta to other tools of similar purpose such as EZKL, Lagrange's deep-prove, or zkml. The results show a significant boost in the proving time for custom-crafted neural networks: they can be proven even on mobile devices, enabling numerous client-side proving applications. While our scheme increases the cost of one-time preprocessing steps, such as circuit compilation and generating trusted setup, our approach is, to the best of our knowledge, the only one that is deployable on the native EVM smart contracts without overwhelming proof size and verification overheads.
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