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Green AI
Roy Schwartz
, Jesse Dodge
, Noah A. Smith
, Oren Etzioni
The Rachel and Selim Benin School of Engineering and Computer Science
Research output
:
Contribution to journal
›
Article
›
peer-review
1039
Scopus citations
Overview
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Dive into the research topics of 'Green AI'. Together they form a unique fingerprint.
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Keyphrases
Green Artificial Intelligence
100%
Artificial Intelligence
66%
Inclusivity
66%
Artificial Intelligence Research
66%
Carbon Footprint
66%
Efficiency Measurement
33%
Deep Learning
33%
Object Recognition
33%
Computationally Intensive
33%
NLP.
33%
NLP Model
33%
Learning Study
33%
Primary Evaluation
33%
Deep Pockets
33%
Floating-point Operations
33%
Machine Translation
33%
Deep Learning Model
33%
Speech Recognition
33%
Game Playing
33%
Barriers to Participation
33%
Evaluation Criteria
33%
Environmental Footprint
33%
Engineering
Artificial Intelligence
100%
Carbon Footprint
33%
Deep Learning Method
33%
Broad Range
16%
Object Recognition
16%
Environmental Footprint
16%
Floating Point
16%
Point Operation
16%
Social Sciences
Artificial Intelligence
100%
Inclusivity
33%
Natural Language Processing
33%
Automatic Translation
16%
Evaluation Method
16%
Speech Recognition
16%
Economics, Econometrics and Finance
Deep Learning Method
33%
Earth and Planetary Sciences
Carbon
33%
Agricultural and Biological Sciences
Deep Learning Model
16%