Environmental Consequence of Deep Learning

Borowiec, Damian and Harper, R.H.R. and Garraghan, Peter (2022) Environmental Consequence of Deep Learning. ITNOW, 63 (4). pp. 10-11. ISSN 1746-5702

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Abstract

Deep learning and artificial intelligence are often viewed as panacea technologies — ones which can decarbonise many industries. But what is the carbon cost of these systems? Damian Borowiec, Richard R. Harper and Peter Garraghan discuss.

Item Type:

Journal Article

Journal or Publication Title:

ITNOW

Additional Information:

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in ITNow following peer review. The definitive publisher-authenticated versionDamian Borowiec, Richard R Harper, Peter Garraghan, The environmental consequence of deep learning, ITNOW, Volume 63, Issue 4, Winter 2021, Pages 10–11, https://doi.org/10.1093/itnow/bwab099 is available online at: https://academic.oup.com/itnow/article-abstract/63/4/10/6503628

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/1700/1702

Subjects:

?? deep learningenergymachine learningsustainabilitygreen computingartificial intelligencehardware and architecturerenewable energy, sustainability and the environmenttheoretical computer sciencesoftwarecomputer science applications ??

Departments:

Faculty of Science and Technology > School of Computing & Communications

ID Code:

161289

Deposited By:

ep_importer_pure

Deposited On:

21 Oct 2021 07:55

Refereed?:

Yes

Published?:

Published

Last Modified:

11 Nov 2024 01:26

URI:

https://eprints.lancs.ac.uk/id/eprint/161289