Cited by 80Green IT and SustainabilityEnergy Efficiency in ComputingEthics and Social Impacts of AI

How much energy will AI really consume? The good, the bad and the unknown

Chen, Sophia·2025·Nature

Integrity signals

Registry

Crossref · 10.1038/d41586-025-00616-z

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • A lower bound estimate of energy consumption during image captioning by an LLM is 105 Wh per 1000 tasks.

    “a lower bound estimate of energy consumption during image captioning by an LLM is 105 Wh per 1000 tasks performed”

    From There is no such thing as conscious artificial intelligence (2025) · cites this paper as Chen (2025)

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Chen, S.
Corresponding author
Chen, Sophia
Venue
Nature
Published
2025-03-05
Volume
639
Issue
8053
Pages
22-24
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W4408160654
Cited by
78
References
2
Citations by year
2026: 45 · 2025: 33
FWCI
17.45
Type
journal article
Language
en
Open access
closed
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Green IT and Sustainability
  • Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
artificial intelligence energy consumption, electricity demand, corporate transparency, energy efficiency

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review