Climate Impact Of AI: Difference between revisions

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Efforts to quantify the CO2 impact of ML have been undertaken<ref name=":0">{{Cite journal|last=Lacoste|first=Alexandre|last2=Luccioni|first2=Alexandra|last3=Schmidt|first3=Victor |last4=Dandres|first4=Thomas|date=2019-10-21|title=Quantifying the Carbon Emissions of Machine Learning|url=https://arxiv.org/abs/1910.09700|journal=arXiv:1910.09700 [cs, stat]}}</ref><ref>{{Cite journal|last=Henderson|first=Peter|last2=Hu|first2=Jieru|last3=Romoff|first3=Joshua|last4=Brunskill|first4=Emma|last5=Jurafsky|first5=Dan|last6=Pineau|first6=Joelle|date=2020-01-31|title=Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning|url=http://arxiv.org/abs/2002.05651|journal=arXiv:2002.05651 [cs]}}</ref>, and tools and recommendations for best practice have been created<ref name=":1">{{Cite web|last=|first=|date=|title=ML CO2 Impact|url=https://mlco2.github.io/impact/|url-status=live|archive-url=|archive-date=|access-date=2021-03-27|website=}}</ref><ref>{{Cite web|url=https://github.com/Breakend/experiment-impact-tracker|title=Experiment Impact Tracker|date=2021-03-27|website=|url-status=live|archive-url=|archive-date=|access-date=}}</ref>.
 
== DeepMachine Learning Application Areas ==
 
===Models and training===
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Development of other chip types - TPUs, IPUs etc
 
== Background Readings ==
==References==
 
== Online Courses and Course Materials ==
 
== Community ==
 
== Libraries and Tools ==
 
== Data ==
 
== References ==
<references />