555
‘Thirsty’ ChatGPT uses four times more water than previously thought
(www.thetimes.com)
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 23 Nov 2024
555 points (95.9% liked)
Technology
59983 readers
2154 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 2 years ago
MODERATORS
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.
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.
What? How does that relate to anything I just said?
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).
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.