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AI Water use is weirdly polarizing: The people who hate AI like to talk about how it's de… — @distilledscience

Diposting 29 Jul 2026 (3 bulan yang lalu)150 dtk95.280 tayangan

Statistik video

Jumlah publik dari pembaruan terakhir.

Tayangan
95.280
Suka
12.073
Komentar
261
Dibagikan
1.143
Disimpan
2.317
Interaksi
14,14%
Durasi
150 dtk
Diposting
29 Jul 2026

Wawasan video

Video TikTok @distilledscience “AI Water use is weirdly polarizing: The people who hate AI like to talk about how it's destroying the environment, often quoting the one bottle per prompt statistic, and the AI supporters tend to write the whole thing off as nothing compared to real water sucks, like beef or corn. Or golf. But, as per usual, the issue NEEDS NUANCE! A normal text prompt can have a tiny direct cooling footprint while billions of requests, expanding infrastructure and electricity generation create a much larger aggregate footprint. National totals can also look small while one facility creates serious pressure on a particular town, aquifer or water system. The numbers change depending on whether we count withdrawal or consumption; direct cooling or electricity; blue water or rain; averages or peaks; measurements or projections. It’s what lets each side with apparently contradictory claims each sound credible. Pay attention: Google's use of median vs. mean is tricky. Two precision notes for this video: The 0.04% national comparison is derived by dividing LBNL’s modeled 2023 data-center consumption by an older national blue-water-footprint estimate Microsoft’s paper says 31–52% less blue water in its abstract, while its main results table reports 31–48% under grid electricity. The table is the safer figure. Morgan Stanley’s 1.068-trillion-liter number is a 2028 base-case projection for global AI-data-center cooling and electricity—not a measurement, withdrawal estimate or all-data-center total. The point isn’t that AI is harmless or uniquely catastrophic. It’s that we need comparable, facility-level disclosure with honest boundaries. Peer-reviewed sources and DOIs: Li et al.: DOI 10.1145/3724499 Mekonnen & Hoekstra: DOI 10.5194/hess-15-1577-2011 Rushforth & Ruddell: DOI 10.5194/hess-22-3007-2018 Lei et al.: DOI 10.1016/j.resconrec.2025.108310 Alissa et al.: DOI 10.1038/s41586-025-08832-3 Additional sources: LBNL-2001637; arXiv:2607.02531; Google’s 2025 Gemini environmental analysis; DOE FEMP; USDA EIB-99; Morgan Stanley projection reported by *The Economic Times*. #AI #Water #DataCenters #Sustainability” memiliki 95.280 tayangan, 12.073 suka, 261 komentar, 1.143 kali dibagikan dalam metrik publik yang dicatat indeks ini. Itu setara tingkat interaksi sebesar 14,14% (suka, komentar, dan bagikan dibagi tayangan). Video ini diposting 3 bulan yang lalu dan berdurasi 2 menit, 30 detik. Video ini telah disimpan 2.317 kali.

Data per 26 Okt 2026 (UTC), dari pembaruan publik terakhir yang dicatat indeks ini.

Avisha |🧬Scientist Mythbuster

@distilledscience

🧬Your Skeptical Scientist: Distilling Truth from Trends🤦‍♂️ #Optimalist 💪 - NYC Business: 📧 [email protected]

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Suka
12.483.196
Video
878

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Pertanyaan umum

Berapa tayangan video TikTok ini?
Data yang diindeks di sini mencatat 95.280 tayangan, 12.073 suka, dan 261 komentar.
Siapa yang memposting video TikTok ini?
Video ini diposting oleh @distilledscience, yang ditautkan dari halaman ini.
Berapa tingkat interaksi video TikTok ini?
Dari metrik yang dicatat, tingkat interaksinya adalah 14,14% (suka + komentar + bagikan dibagi tayangan).
Kapan video TikTok ini diposting?
Video ini diposting pada 2026-07-29, 3 bulan yang lalu.
Hashtag apa saja yang dipakai di video ini?
Data yang dicatat menautkan 2 hashtag, dimulai dari #ai.
Berapa lama durasi video TikTok ini?
Klip yang dicatat berdurasi 2 menit, 30 detik.