what’s the argument against locally hosted AI? lile seriously man I have issues with plagiarism, innacurate information and social dependency, but even with all that AI isn’t of the devil. Learn to have nuance
local models don’t appear out of the ether. using a local model solves one problem around privacy of your prompts, does little about consolidation of power, and nothing about the thousands of other problems genai brings.
if your organic coffee is made with slave labor, you still have a massive problem.
and they may not be of the devil, but they definitely are of the humans who most resemble the devil.
The models you are self-hosting first have to be trained at the data centers, which is a contributing factor to the environmental impact of AI.
I know how to run local models, but just because they’re more environmentally friendly than alternatives doesn’t mean they’re not still contributing to the broader environmental impact of data centers.
How does running a local LLM that’s already been trained contribute to the environmental costs of training? It’s already trained whether I run it or not, and running it locally isn’t generating any revenue for the company that did the training (therefore it doesn’t encourage them to train more). This isn’t like a physical product where every time someone obtains a copy, more environmental damage has to be done manufacturing it, training is a one time cost.
The environmental impact of running a local LLM is significantly lower than buying a half-gallon carton of almond milk.
Sure, but you could also make the argument that anything based on networked computing is contributing to the spread of data centers. AI is a large part of that today, but it’s not like data centers never existed prior to ChatGPT. Before, it was about trying to convince laypeople to avoid “the cloud”.
Non-AI datacenters aren’t massive fuckoff Complexes that spew pollution (noise and atmospheric) into the surrounding area and triple your electric bill. It’s the massive hyperscale AI datacenters that are the problem.
That’s true, loads of non-AI datacenters are also environmentally destructive noise pollution machines, which also needs to be dealt with, but hyperscale AI datacenters are much more environmentally destructive much more of the time. You’re right tho
what’s the argument against locally hosted AI? lile seriously man I have issues with plagiarism, innacurate information and social dependency, but even with all that AI isn’t of the devil. Learn to have nuance
local models don’t appear out of the ether. using a local model solves one problem around privacy of your prompts, does little about consolidation of power, and nothing about the thousands of other problems genai brings.
if your organic coffee is made with slave labor, you still have a massive problem.
and they may not be of the devil, but they definitely are of the humans who most resemble the devil.
I don’t follow, how does running a local model consolidate power? Geniune question
re-read, it says the opposite: helps a little.
although, tbh, i’m not entirely sure of that either, but the reasoning is complex and longer-term.
Oh I see
Do you live in the environment, like the rest of us? I’ve got some bad news about AI.
Someone self hosting an AI is doing less environmental damage than a good video game play session, though.
The models you are self-hosting first have to be trained at the data centers, which is a contributing factor to the environmental impact of AI.
I know how to run local models, but just because they’re more environmentally friendly than alternatives doesn’t mean they’re not still contributing to the broader environmental impact of data centers.
How does running a local LLM that’s already been trained contribute to the environmental costs of training? It’s already trained whether I run it or not, and running it locally isn’t generating any revenue for the company that did the training (therefore it doesn’t encourage them to train more). This isn’t like a physical product where every time someone obtains a copy, more environmental damage has to be done manufacturing it, training is a one time cost.
The environmental impact of running a local LLM is significantly lower than buying a half-gallon carton of almond milk.
Sure, but you could also make the argument that anything based on networked computing is contributing to the spread of data centers. AI is a large part of that today, but it’s not like data centers never existed prior to ChatGPT. Before, it was about trying to convince laypeople to avoid “the cloud”.
Non-AI datacenters aren’t massive fuckoff Complexes that spew pollution (noise and atmospheric) into the surrounding area and triple your electric bill. It’s the massive hyperscale AI datacenters that are the problem.
They still are, and it’s been known and talked about for years. All of these predate the AI boom:
https://www.vice.com/en/article/data-centres-dirty-energy-secret/
https://web.archive.org/web/20120927113253/https://www.nytimes.com/2012/09/23/technology/data-centers-waste-vast-amounts-of-energy-belying-industry-image.html
https://web.archive.org/web/20190821212342/https://www.azcentral.com/story/news/local/chandler/2018/04/15/chandler-tech-company-hums-along-and-noise-annoying-residents/504641002/
That’s true, loads of non-AI datacenters are also environmentally destructive noise pollution machines, which also needs to be dealt with, but hyperscale AI datacenters are much more environmentally destructive much more of the time. You’re right tho
Server farms before AI weren’t growimg out of control and spinning up gas yurbines everywhere. That’s the boom and bust of AI training.
Depends on a lot of factors, I would imagine.
I was trynna make a bit about it because peeps on here are so furiously against anything ML by now that I’m sure this is the stance.
i dont actually take this stance.