Climate Impact Of AI: Difference between revisions
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===Models and training=== |
===Models and training=== |
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Many recent projects in deep learning have used increasingly large computational resources to create models |
Many recent projects in deep learning have used increasingly large computational resources to create models. |
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The compute resources used for the largest model training runs was shown to have doubled in size every 3.4 months from 2012-2018<ref>{{Cite web|url=https://openai.com/blog/ai-and-compute/|title=AI and Compute|date=2018-05-16|website=OpenAI|language=en|access-date=2021-03-27}}</ref>. |
The compute resources used for the largest model training runs was shown to have doubled in size every 3.4 months from 2012-2018<ref>{{Cite web|url=https://openai.com/blog/ai-and-compute/|title=AI and Compute|date=2018-05-16|website=OpenAI|language=en|access-date=2021-03-27}}</ref>. |
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== Data Centres == |
== Data Centres == |
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Data centres accounted for almost 1% of global energy demand in 2019<ref>{{Cite web|url=https://www.iea.org/reports/data-centres-and-data-transmission-networks|title=Data Centres and Data Transmission Networks – Analysis|website=IEA|language=en-GB|access-date=2021-03-27}}</ref>, at around 200TWh, and while demand increases, efficiency gains mean this may stay flat for now<ref>{{Cite journal|last=Masanet|first=Eric|last2=Shehabi|first2=Arman|last3=Lei|first3=Nuoa|last4=Smith|first4=Sarah|last5=Koomey|first5=Jonathan|date=2020-02-28|title=Recalibrating global data center energy-use estimates|url=https://science.sciencemag.org/content/367/6481/984|journal=Science|language=en|volume=367|issue=6481|pages=984–986|doi=10.1126/science.aba3758|issn=0036-8075|pmid=32108103}}</ref>. AI's total impact then can be estimated as a fraction of this. AI may itself offer efficiency gains for data centres by optimising control systems<ref>{{Cite web|url=https://blog.google/outreach-initiatives/environment/deepmind-ai-reduces-energy-used-for/|title=DeepMind AI reduces energy used for cooling Google data centers by 40%|date=2016-07-20|website=Google|language=en|access-date=2021-03-27}}</ref>. |
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Estimates of electricity use of AI |
Estimates of electricity use of AI |
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Cloud comparison |
=== Cloud comparison === |
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The major cloud computing providers, Amazon, Google and Microsoft, have varying targets and carbon intensities for their services. |
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Google now publishes hourly estimates of the proportion of carbon-free energy (CFE) and the carbon intensity for all its cloud regions<ref>{{Cite web|url=https://cloud.google.com/sustainability/region-carbon|title=Carbon free energy for Google Cloud regions|website=Google Cloud|language=en|access-date=2021-03-27}}</ref>. |
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==== Targets ==== |
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== Processing Units == |
== Processing Units == |
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