this post was submitted on 24 Feb 2024
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Climate - truthful information about climate, related activism and politics.

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Discussion of climate, how it is changing, activism around that, the politics, and the energy systems change we need in order to stabilize things.

As a starting point, the burning of fossil fuels, and to a lesser extent deforestation and release of methane are responsible for the warming in recent decades: Graph of temperature as observed with significant warming, and simulated without added greenhouse gases and other anthropogentic changes, which shows no significant warming

How much each change to the atmosphere has warmed the world: IPCC AR6 Figure 2 - Thee bar charts: first chart: how much each gas has warmed the world.  About 1C of total warming.  Second chart:  about 1.5C of total warming from well-mixed greenhouse gases, offset by 0.4C of cooling from aerosols and negligible influence from changes to solar output, volcanoes, and internal variability.  Third chart: about 1.25C of warming from CO2, 0.5C from methane, and a bunch more in small quantities from other gases.  About 0.5C of cooling with large error bars from SO2.

Recommended actions to cut greenhouse gas emissions in the near future:

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[–] rowrowrowyourboat 6 points 9 months ago

one assessment suggests that ChatGPT, the chatbot created by OpenAI in San Francisco, California, is already consuming the energy of 33,000 homes. It’s estimated that a search driven by generative AI uses four to five times the energy of a conventional web search. Within years, large AI systems are likely to need as much energy as entire nations.

And it’s not just energy. Generative AI systems need enormous amounts of fresh water to cool their processors and generate electricity. In West Des Moines, Iowa, a giant data-centre cluster serves OpenAI’s most advanced model, GPT-4. A lawsuit by local residents revealed that in July 2022, the month before OpenAI finished training the model, the cluster used about 6% of the district’s water. As Google and Microsoft prepared their Bard and Bing large language models, both had major spikes in water use — increases of 20% and 34%, respectively, in one year, according to the companies’ environmental reports. One preprint suggests that, globally, the demand for water for AI could be half that of the United Kingdom by 2027.