this post was submitted on 19 Nov 2024
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so, basically, even a broken clock is right twice a day?
Yes, but for some tasks mistakes don't really matter, like "come up with names for my project that does X". No wrong answers here really, so an LLM is useful.
great value for all that energy it expends, indeed!
The energy expenditure for GPT models is basically a per-token calculation. Having it generate a list of 3-4 token responses would barely be a blip compared to having it read and respond entire articles.
There might even be a case for certain tasks with a GPT model being more energy efficient than making multiple google searches for the same. Especially considering all the backend activity google tacks on for tracking users and serving ads, complaining about someone using a GPT model for something like generating a list of words is a little like a climate activist yelling at someone for taking their car to the grocery store while standing across the street from a coal-burning power plant.
no, it's like a billion people taking their respective cars to the grocery store multiple times a day each while standing across the street from one coal-burning power plant.
each person can say they are the only one and their individual contribution is negligible. but get all those drips together and you actually have a deluge of unnecessary wastage.
Except each of those drips are subject to the same system that preferences individualized transport
This is still a perfect example, because while you're nit-picking the personal habits of individuals who are a fraction of a fraction of the total contributors to GPT model usage, huge multi-billion dollar entities are implementing it into things that have no business using it and are representative for 90% of llm queries.
Similar for castigating people for owning ICE vehicles, who are not only uniquely pressued into their use but are also less than 10% of GHG emissions in the first place.
Stop wasting your time attacking individuals using the tech for help in their daily tasks, they aren't the problem.
How is that faster than just picking a random name? Noone picks software based on name.
And yet virtually all of software has names that took some thought, creativity, and/or have some interesting history. Like the domain name of your Lemmy instance. Or Lemmy.
And people working on something generally want to be proud of their project and not name it the first thing that comes to mind, but take some time to decide on a name.
Wouldnt they also not want to take a random name off an AI generated list? How is that something to be proud of? The thought, creativity, and history behind it is just that you put a query into chatgpt and picked one out of 500 names?
Maybe its just a difference of perspective but thats not only not a special origin story for a name, its taking from others in a way you won't be able to properly credit them, which is essential to me.
I would rather avoid the trouble and spend the time with a coworker or friend throwing ideas back and forth and building an identity intentionally.
I suppose AI could be nice if I was alone nearly all the time.
The process of throwing ideas back and forth usually doesn't include just choosing one, but generating ideas as jumping off points, usually with some existing concept in mind. Talking with friends, looking at other projects, searching for inspiration online and in the real world, and now also generating some more ideas with an LLM to add to the mix. Using one source and just picking a suggestion probably won't get you a good result.
No, maybe more like, even a functional clock is wrong every 0.8 days.
https://superuser.com/questions/759730/how-much-clock-drift-is-considered-normal-for-a-non-networked-windows-7-pc
The frequency is probably way higher for most LLMs though lol