Version 1
: Received: 6 November 2024 / Approved: 7 November 2024 / Online: 7 November 2024 (15:33:57 CET)
How to cite:
Venkatesh, M. G.; R., D.; Prathosh. S, G.; A., N.; Sameer, I. M.; G, S. Decentralizing AI Computing: A Study with IPFS and Public Peer‐to‐Peer Networks. Preprints2024, 2024110565. https://doi.org/10.20944/preprints202411.0565.v1
Venkatesh, M. G.; R., D.; Prathosh. S, G.; A., N.; Sameer, I. M.; G, S. Decentralizing AI Computing: A Study with IPFS and Public Peer‐to‐Peer Networks. Preprints 2024, 2024110565. https://doi.org/10.20944/preprints202411.0565.v1
Venkatesh, M. G.; R., D.; Prathosh. S, G.; A., N.; Sameer, I. M.; G, S. Decentralizing AI Computing: A Study with IPFS and Public Peer‐to‐Peer Networks. Preprints2024, 2024110565. https://doi.org/10.20944/preprints202411.0565.v1
APA Style
Venkatesh, M. G., R., D., Prathosh. S, G., A., N., Sameer, I. M., & G, S. (2024). Decentralizing AI Computing: A Study with IPFS and Public Peer‐to‐Peer Networks. Preprints. https://doi.org/10.20944/preprints202411.0565.v1
Chicago/Turabian Style
Venkatesh, M. G., I. Mohamed Sameer and Srivatsan G. 2024 "Decentralizing AI Computing: A Study with IPFS and Public Peer‐to‐Peer Networks" Preprints. https://doi.org/10.20944/preprints202411.0565.v1
Abstract
Ipfs and public peer-to-peer (P2P) networks were adopted to make AI calculations more decentralized. Taking AI workloads over a decentralized network could bring better fault tolerance, guarantee data safety, and increased privacy. This research explores the challenges of centralized AI, such as data confidentiality, scalability, and accessibility, while discussing the promise of decentralized AI. Combining IPFS with decentralized systems improves scalability, data protection, and fault tolerance.
Keywords
Decentralized AI; IPFS; Peer‐to‐peer networks; Data privacy; AI computation
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
