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  4. Democratizing Federated Learning with Blockchain and Multi-task Peer Prediction
 
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2026
Book Article
Title

Democratizing Federated Learning with Blockchain and Multi-task Peer Prediction

Abstract
The synergy between Federated Learning and blockchain has been considered promising; however, the computationally intensive nature of contribution measurement conflicts with the strict computation and storage limits of blockchain systems. We propose a novel concept to decentralize the AI training process using blockchain technology and Multi-task Peer Prediction. By leveraging smart contracts and cryptocurrencies to incentivize contributions to the training process, we aim to harness the mutual benefits of AI and blockchain. We discuss the advantages and limitations of our design.
Author(s)
Witt, Leon
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Samek, Wojciech  
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Toyoda, Kentaroh
A-Star, Institute of High Performance Computing
Li, Dan
Tsinghua University
Mainwork
Advances in Artificial Intelligence: Efficiency, Reliability, and Innovations in Machine Learning to Healthcare, and Blockchain  
DOI
10.1007/978-3-032-12362-6_8
Language
English
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
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