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‘Thirsty’ ChatGPT uses four times more water than previously thought (www.thetimes.com)

submitted 4 weeks ago by [email protected] to c/[email protected]

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Writing a 100-word email using ChatGPT (GPT-4, latest model) consumes 1 x 500ml bottle of water It uses 140Wh of energy, enough for 7 full charges of an iPhone Pro Max

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[–] [email protected] 2 points 4 weeks ago (1 children)

Mainly because energy and data centers are both expensive and companies want to use as little as possible of both - especially on the energy side. OpenAI isn't exactly profitable. There is a reason companies like Microsoft release smaller models like Phi-2 that can be run on individual devices rather than data centers.

[–] [email protected] 1 points 3 weeks ago (1 children)

I didn't realize coal plants were concerned about data centers or AI. TIL.

But in the interest of being slightly less of a dick and responding to what you said even though it's kinda a non sequitur, companies are only vaguely interested in efficiency. I think it's more accurate to say that AI is hot for everyone right now so there's more eyes on it which makes the concept you laid out valid. Where it's invalid in my experience is that efficiency is just based on "where x executive is paying attention" not an honest attempt to look at return on investment in a rigorous way across the enterprise.

[–] [email protected] 0 points 3 weeks ago

I didn't realize coal plants were concerned about data centers or AI. TIL.

What? How does that relate to anything I just said?

But in the interest of being slightly less of a dick and responding to what you said even though it's kinda a non sequitur, companies are only vaguely interested in efficiency.

How is it a non sequitur? If anything the thing you just said makes no sense. Energy is probably the biggest cost these companies have. This I believe is true even for regular data centers and cloud services which is why they always try to use the latest most energy efficient hardware. It's still not as bad as most anti-AI people seem to believe, mainly because the most energy intensive part happens only once per model (training).

I think it's more accurate to say that AI is hot for everyone right now so there's more eyes on it which makes the concept you laid out valid. Where it's invalid in my experience is that efficiency is just based on "where x executive is paying attention" not an honest attempt to look at return on investment in a rigorous way across the enterprise.

Human labour is expensive. So trying to replace it with AI, even if AI is also expensive, is typically still worth it.

You talk about experience, but I honestly don't think you have any. Do you actually work in tech? What are your qualifications? Most of the people coming here to complain about this stuff don't actually have a functional understanding of the thing they are complaining about.