Birdwatch Archive

Birdwatch Note

2023-10-03 20:36:06 UTC - MISINFORMED_OR_POTENTIALLY_MISLEADING

Microsoft, whose data centers power OpenAI, reported 1.6 billion gallons of water for all of 2022. This represents 0.00001% of US freshwater withdrawals in 2015 (281B gal per day). Researchers have estimated that training GPT-3 consumed 185,000 gallons of water. https://www.datacenterdynamics.com/en/news/microsofts-water-consumption-jumps-34-percent-amid-ai-boom/ https://www.usgs.gov/special-topics/water-science-school/science/total-water-use-united-states#overview https://gizmodo.com/chatgpt-ai-water-185000-gallons-training-nuclear-1850324249

Written by 84BCBB342A3B2190100A676DB4D1133C4242F4599900C11767CD4270CC9598F5
Participant Details

Original Tweet

Tweet embedding is no longer reliably available, due to the platform's instability (in terms of both technology and policy). If the Tweet still exists, you can view it here: https://twitter.com/foo_bar/status/1709233810796167493

Please note, though, that you may need to have your own Twitter account to access that page. I am currently exploring options for archiving Tweet data in a post-API context.

All Information

  • ID - 1709306350902386975
  • noteId - 1709306350902386975
  • participantId -
  • noteAuthorParticipantId - 84BCBB342A3B2190100A676DB4D1133C4242F4599900C11767CD4270CC9598F5 Participant Details
  • createdAtMillis - 1696365366090
  • tweetId - 1709233810796167493
  • classification - MISINFORMED_OR_POTENTIALLY_MISLEADING
  • believable -
  • harmful -
  • validationDifficulty -
  • misleadingOther - 0
  • misleadingFactualError - 1
  • misleadingManipulatedMedia - 0
  • misleadingOutdatedInformation - 0
  • misleadingMissingImportantContext - 0
  • misleadingUnverifiedClaimAsFact - 0
  • misleadingSatire - 0
  • notMisleadingOther - 0
  • notMisleadingFactuallyCorrect - 0
  • notMisleadingOutdatedButNotWhenWritten - 0
  • notMisleadingClearlySatire - 0
  • notMisleadingPersonalOpinion - 0
  • trustworthySources - 1
  • summary
    • Microsoft, whose data centers power OpenAI, reported 1.6 billion gallons of water for all of 2022. This represents 0.00001% of US freshwater withdrawals in 2015 (281B gal per day). Researchers have estimated that training GPT-3 consumed 185,000 gallons of water. https://www.datacenterdynamics.com/en/news/microsofts-water-consumption-jumps-34-percent-amid-ai-boom/ https://www.usgs.gov/special-topics/water-science-school/science/total-water-use-united-states#overview https://gizmodo.com/chatgpt-ai-water-185000-gallons-training-nuclear-1850324249

Note Status History

createdAt timestampMillisOfFirstNonNMRStatus firstNonNMRStatus timestampMillisOfCurrentStatus currentStatus timestampMillisOfLatestNonNMRStatus mostRecentNonNMRStatus participantId
2023-10-03 20:36:06 UTC
(1696365366090)
2023-10-04 00:03:37 UTC
(1696377817596)
CURRENTLY_RATED_HELPFUL 2023-10-04 02:49:07 UTC
(1696387747507)
CURRENTLY_RATED_HELPFUL 2023-10-04 00:03:37 UTC
(1696377817596)
CURRENTLY_RATED_HELPFUL

Note Ratings

rated at rated by
2023-10-03 19:17:00 -0500 Rating Details
2023-10-03 19:11:46 -0500 Rating Details
2023-10-03 19:10:07 -0500 Rating Details
2023-10-03 18:59:05 -0500 Rating Details
2023-10-03 18:54:39 -0500 Rating Details
2023-10-03 17:59:23 -0500 Rating Details
2023-10-03 17:36:00 -0500 Rating Details
2023-10-03 17:24:30 -0500 Rating Details
2023-10-03 17:22:51 -0500 Rating Details
2023-10-03 17:20:39 -0500 Rating Details
2023-10-03 17:19:29 -0500 Rating Details
2023-10-03 17:17:42 -0500 Rating Details
2023-10-03 17:16:33 -0500 Rating Details
2023-10-03 17:11:11 -0500 Rating Details
2023-10-03 17:09:00 -0500 Rating Details
2023-10-03 16:46:07 -0500 Rating Details
2023-10-03 16:44:56 -0500 Rating Details
2023-10-03 16:44:26 -0500 Rating Details
2023-10-03 16:41:56 -0500 Rating Details
2023-10-03 16:35:39 -0500 Rating Details
2023-10-03 16:29:06 -0500 Rating Details
2023-10-03 16:24:43 -0500 Rating Details
2023-10-03 16:23:59 -0500 Rating Details
2023-10-03 16:23:39 -0500 Rating Details
2023-10-03 16:10:24 -0500 Rating Details
2023-10-03 16:08:31 -0500 Rating Details
2023-10-03 16:06:16 -0500 Rating Details
2023-10-03 16:02:16 -0500 Rating Details
2023-10-03 15:58:41 -0500 Rating Details
2023-10-03 15:54:29 -0500 Rating Details
2023-10-03 15:53:02 -0500 Rating Details
2023-10-03 15:52:49 -0500 Rating Details
2023-10-03 15:48:39 -0500 Rating Details
2023-10-04 09:46:38 -0500 Rating Details
2023-10-04 05:36:54 -0500 Rating Details
2023-10-04 05:33:44 -0500 Rating Details
2023-10-04 05:21:31 -0500 Rating Details
2023-10-04 04:18:54 -0500 Rating Details
2023-10-04 02:13:43 -0500 Rating Details
2023-10-04 00:55:08 -0500 Rating Details
2023-10-04 00:29:34 -0500 Rating Details
2023-10-03 21:53:45 -0500 Rating Details
2023-10-03 21:39:04 -0500 Rating Details
2023-10-03 20:37:43 -0500 Rating Details
2023-10-03 20:22:59 -0500 Rating Details
2023-10-03 20:22:44 -0500 Rating Details
2023-10-03 19:37:47 -0500 Rating Details
2023-10-04 22:49:56 -0500 Rating Details
2023-10-04 21:07:46 -0500 Rating Details
2023-10-03 20:19:40 -0500 Rating Details