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‘Thirsty’ ChatGPT uses four times more water than previously thought
(www.thetimes.com)
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this post was submitted on 23 Nov 2024
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You are conveniently ignoring model size here...
Which is a primary impact on power consumption.
And any other processing and augmentation being performed. System prompts and other things that are bloating the token size ...etc never mind the fact that you're getting a response almost immediately for something that an at home GPU cluster (not casual PC) would struggle with for many minutes, this isn't always a linear scale for power consumption.
You are also ignoring the realities of a data center. Where the device power usage isn't the only power consumption of the location, cooling must be taken into consideration as well. Redundant power switching also comes with a percentage loss in transmission efficiency which adds to power consumption and heat dispersion requirements.
It's true, I don't know how large the models are that are being accessed in data centers. Although if the article's estimate is correct, it's sad that such excessively-demanding models are always being used for use-cases that could often be handled with much lower power usage.
This seems a big waste of energy if that 140Wh (504,000 joules) number is correct. That amount of energy is about 2,000 times what it would take to do a very similar thing on a home PC.
Writing a 100 word email with a 7B model would take my PC about 5 seconds, times an increased power use of 50 watts, so 250 joules.
I get that they might be using a much larger model, but the e-mail is not going to be 2,000 times better.