FLock Awarded Ethereum Foundation Research Grant
Quick Take FLock awarded grant to fund research into incentive mechanisms for blockchain-based machine learning solutions
FLock.io , an industry leader in the decentralised AI (dAI) movement, is the sole AI recipient of Ethereum Foundation (EF) Academic Grants Round 2024 . This grant will fund research into incentive mechanisms for smart contract-enabled blockchain solutions for ML.
The Ethereum Foundation is a non-profit that supports the Ethereum ecosystem by funding protocol development, growing the ecosystem, and advocating for Ethereum. The Academic Grants Round 2024 is a $1M wave of grants to support Ethereum-related academic work.
FLock is at the forefront of federated machine learning on the blockchain. Having recently closed a $6 million seed round , it is building a world-first collaborative dAI training platform with on-chain governance, AI model training and hosting. The London-based Web3 startup, founded by a group of Oxford graduates, is on a mission to redirect power from centralised corporations into the hands of the community.
FLock is researching incentive mechanisms for blockchain-based AI training
This grant will accelerate FLock’s pioneering research in optimising incentive tokenomics mechanisms to deter malicious behaviour in the decentralised AI development lifecycle. This project will benefit the greater ecosystem by harnessing smart contracts for secure dAI systems, upholding principles of security, trust, and computational integrity while maintaining data privacy.
The research will expand on FLock’s published paper “Defending Against Poisoning Attacks in Federated Learning With Blockchain” in IEEE Transactions on Artificial Intelligence. This proposes a peer-to-peer voting and reward-and-slash system that protects against malicious activities by FL participants.
It will be led by Dr. Zhipeng Wang, lead blockchain researcher at FLock and Research Associate at Imperial College London, and Jiahao Sun, FLock Founder and CEO and Research Fellow at Imperial College London.
“We are immensely grateful for the EF grants that support our research. Our aim is to investigate and establish a practical blueprint for leveraging the potential of smart-contract-enabled blockchains, particularly Ethereum, to support secure and decentralised AI systems,” said Wang.
“Our research seeks to extend the boundaries at the intersection of blockchain and AI ecosystems. We look forward to collaborating with diverse communities to revolutionise the landscape,” added Sun.
FLock is dedicated to supporting the decentralisation movement
FLock is the first project to bring an end-to-end AI fine-tuning lifecycle to Web3, akin to a Web3 Hugging Face. Its permissionless, performant ML system comprises AI Arena, FL Alliance, and Model Marketplace. The AI Arena closed beta is underway, where developers compete on the best AI models on one validation dataset in a Kaggle-style leaderboard, using their own or decentralised compute.
Checkout FLock’s latest White Paper ;
Other existing academic papers co-authored by FLock include:
- “Defending Against Poisoning Attacks in Federated Learning With Blockchain” in IEEE Transactions on Artificial Intelligence, 2024
- “zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning” in IEEE Transactions on Big Data, 2024
- “GARNN: An Interpretable Graph Attentive Recurrent Neural Network for Predicting Blood Glucose Levels via Multivariate Time Series” in arXiv, 2024
For future updates, follow FLock on Twitter, and see its blog and docs .
This post is commissioned by FLock and does not serve as a testimonial or endorsement by The Block. This post is for informational purposes only and should not be relied upon as a basis for investment, tax, legal or other advice. You should conduct your own research and consult independent counsel and advisors on the matters discussed within this post. Past performance of any asset is not indicative of future results.
Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.
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