awesome-zkml
github.com/worldcoin/awesome-zkml ↗awesome-zkml repository
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me articles and podcasts resources from awesome-zkml"
Installation instructions →What's inside
Projects interested in ZKML
- 0xPARC
The 0xPARC Foundation promotes application-level innovation on Ethereum and other decentralized platforms
- Aleo
Platform for building fully private and programmable Web applications.
- Axiom
Axiom provides smart contracts trustless access to all on-chain data and arbitrary expressive compute over it. Like GPUs do for CPUs, Axiom augments blockchain consensus with zero-knowledge proofs
- Gizatech
Fully on-chain artificial intelligence on Starknet
- Ingonyama
Zero Knowledge ASICs (ZPU)
- Ion Protocol
Lending protocol for staked & restaked assets. They partnered with Modulus to build a risk engine that analyzes validator credit risk. Read more
Content
- An introduction to zero-knowledge machine learning - WorldcoinArticles and podcasts
Worldcoin
- Balancing the Power of AI/ML: The Role of ZK and Blockchain - SevenX VenturesArticles and podcasts
SevenX Ventures
- Chapter 1: How to Put Your AI On-ChainArticles and podcasts
- Chapter 2: Why Put Your AI On-Chain?Articles and podcasts
- Chapter 3: The World’s First On-Chain AI Trading BotArticles and podcasts
- Chapter 4: Blockchains that Self-ImproveArticles and podcasts
Use cases
- Astraly
- Aztec Protocol
- exploitability
- link
- Lyra finance
- Modulus LabsArticles and podcasts
Learn ZK
- Awesome - Matter labs - ZK proofs
Matter labs - ZK proofs
- Awesome - Mikerah - Privacy on Blockchains
Mikerah - Privacy on Blockchains
- Curated list of ZKP implementations
- Ingopedia
- Proofs, Args and ZK - Justin Thaler
Justin Thaler
- Resource: Awesome_Plonk
Papers
- Boyuan Feng, Lianke Qin, Zhenfei Zhang, Yufei Ding, and Shumo Chu (2021). "ZEN: An Optimizing Compiler for Verifiable, Zero-Knowledge Neural Network Inferences"
- Chenkai Weng, Kang Yang, Xiang Xie, Jonathan Katz, and Xiao Wang (2021). "Mystique: Efficient Conversions for Zero-Knowledge Proofs with Applications to Machine Learning"
- Daniel Kang
- Haodi Wang, Thang Hoang (2022). ezDPS: An Efficient and Zero-Knowledge Machine Learning Inference Pipeline
- Jian Liu, Mika Juuti, Yao Lu, and N. Asokan (2017). "Oblivious Neural Network Predictions via MiniONN transformations"
- Jiasi Weng, Jian Weng, Member, IEEE, Gui Tang, Anjia Yang, Ming Li, Jia-Nan Liu (2022). pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing
Codebases
- circomlib-ml
- ddkang/zkml
zkml is a framework for constructing proofs of ML model execution in ZK-SNARKs.
- ezkl
- keras2circom
- Linear A - tachikoma
tachikoma
- Linear A - uchikoma
uchikoma
Showing a sample of 100 resources. View the full list on GitHub →