Andrew Starkey
Advancing AI with green practices and adaptable solutions for the future. [Article summary]
Starkey, Andrew; Ezenkwu, Chinedu Pascal
Abstract
Despite AI's achievements, how can its limitations be addressed to reduce computational costs, enhance transparency and pioneer eco-friendly practices?
Citation
STARKEY, A. and EZENKWU, C.P. 2024. Advancing AI with green practices and adaptable solutions for the future. [Article summary]. Posted on The Academic [online], 28 March 2024. Available from: https://theacademic.com/ai-green-practices-adaptable-solutions/
Digital Artefact Type | Website Content |
---|---|
Online Publication Date | Mar 28, 2024 |
Publication Date | Mar 28, 2024 |
Deposit Date | Apr 2, 2024 |
Publicly Available Date | Apr 4, 2024 |
Keywords | Artificial intelligence (AI); Machine learning; Computing and the environment |
Public URL | https://rgu-repository.worktribe.com/output/2293505 |
Related Public URLs | https://rgu-repository.worktribe.com/output/1982490 (Original paper) |
Additional Information | This is a summary of the following paper: STARKEY, A. and EZENKWU, C.P. 2023. Towards autonomous developmental artificial intelligence: case study for explainable AI. In Maglogiannis, I., Iliadis, L., MacIntyre, J. and Dominguez, M. (eds.) Artificial intelligence applications and innovations: proceedings of the 19th IFIP (International Federation for Information Processing) WG 12.5 Artificial intelligence applications and innovations international conference (AIAI 2023), 14-17 June 2023, León, Spain. IFIP advances in information and communication technology, 676. Cham: Springer [online], pages 94-105. Available from: https://doi.org/10.1007/978-3-031-34107-6_8 |
External URL | https://theacademic.com/ai-green-practices-adaptable-solutions/ |
Files
STARKEY 2024 Advancing AI with green
(319 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
A class-specific metaheuristic technique for explainable relevant feature selection.
(2021)
Journal Article
Downloadable Citations
About OpenAIR@RGU
Administrator e-mail: publications@rgu.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search