Journal of Research and Development
Open Access
ISSN: 2311-3278
ISSN: 2311-3278
Department of Law, University of St.Thomas, Minnesota, United States of America
Review Article
How AI Models are Optimized through Web3 Governance
Author(s): Wulf Kaal*
The integration of web3 community governance, using Weighted Directed Acyclic Graphs (WDAGs) and validation pools with reputation staking in combination with a federated communications protocol, offers a transformative approach to AI model optimization. This framework supports decentralized, dynamic, evolutionary and participatory AI governance, crucial for handling the complex ethical and operational demands of various AI technologies. Specifically, deep learning models gain from decentralized data handling that mitigates bias and enhances privacy through community-validated updates. Federated learning benefits from enhanced security and privacy through block chain’s transparency and immutability, with smart contracts automating model validation and updates. Transformer AI models benefit from continuous adaptation to new data facilitated by real-time updates, ensuring relevance.. View More»
DOI:
10.35248/2311-3278.25.13.294