I can also volunteer. I mostly lurk but I do try to give good advice here (and in similar communities) when I see my PoV hasn't been offered yet. The community is reasonably active so it would be good to have a moderator that is also active here.

While I'd love to, it sounds like they're good for now and will find another moderator if/when they need more help.

Those would've also been nice improvements to the Decky store front itself. They could've done it cooperatively by contributing those changes to the main store front too.

This could've just been an alt store yet instead they decided to reinvent the wheel (the entire store front)

I'm decently active but mostly a lurker. I'd happily help out as long as I'm not taking the position away from anyone else (I'm a man).

Usually I use this account to post but I'm fine with using another account on a different instance.

EDIT: My lemmy.world account is https://lemmy.world/u/NGram

Walter Koenig (Chekov)

That's only a (USA) reporting limit. A private company can still have more than 2000 shareholders, but it must then publicly report its finances like a public company would.

That's the old format (first generation)

The Steam client uses CEF not Electron (which also uses CEF), not that the distinction is very important

They're going to skip the C series gaming GPUs, aren't they?

You've ignored all of the other impacts of LLMs while comparing different lifecycles.

If you're going to include the manufacturing of smartphones, you must also include the "manufacturing" of LLMs. That requires everything from the construction of datacentres and the manufacturing of computers which go into them to the less "real" copious scraping, training, and shutdown that is required.

Here's some other numbers that I found for a mix of ChatGPT 3.5 and 4 (since the stats for newer models are hard to find):

• Around 10K GPUs were used to train the model
• Each GPU has a manufacturing carbon usage of around 164 kg CO2e (8 GPUs per server)
• GPU usage accounts for 85-95% of CO2e emissions (5-15% manufacturing and other impacts) for a 3 year usage lifespan

That puts the total per-card emissions around 3280 kg CO2e and the total usage around 32 800 tonnes CO2e just for one model. Per your smartphone metrics, that's about equivalent to 560K people's smartphone use. If you use a smartphone that is more carefully constructed, you can get that up to 1.13M. So for the same atmospheric pollution as 0.5-1 million people buying a phone, we made one model run for 3 years. Now consider there are multiple models and they usually get replaced more often than once every 3 years.

Most people rely on a smartphone these days, very few people need an LLM. Phones are significantly less polluting than an LLM datacentre so you'd be better off using your phone.

Now for other concerns, including the rest of the environmental devastation, which smartphones and most other products do not have. Most of these are still unknown or hard to quantify because the tech industry has long since abandoned open development of new products. I'm just going to list the problems because no one wants to read anymore paragraphs from me:

• Societal impacts
  • Reduced barrier to misinformation
  • Increased concentration of power (the political kind, not electricity)
  • Reduced barrier to professional skills
    • (this might seem like a good thing, but LLMs are not competent by themself, so)
    • Increased danger in safety critical applications
    • Increased ease of embedding malicious elements
    • Reduced confidence in professionals
  • AI psychosis
  • Isolation
  • Increased bot traffic
  • Reduced access to infrastructure
  • Reduced access to critical resources
• Other environment impacts
  • Increased water usage
  • Land destruction
  • Noise pollution
  • Water pollution
  • Ground toxicity/pollution
  • Increased raw material demands (feedback loop for the other env impacts)

The only real positive of the tech industry shenanigans is that prices have gone up, which is discouraging people from buying these significantly environmentally impactful products and instead extending the lifespan of existing hardware.

My intention isn’t to be confrontational, though I am genuinely perplexed, and that’s probably what you’re reading.

Meanwhile...

Ipso facto, for all the AI “Akshually” pedants, I’ve tagged this as AIP. Politely go fuck yourselves :)

“Fork it, fix it or fuck it” - dealers choice :)

Got dunked on for AI slop despite explicitly marking which parts were AI-assisted

I get it - Lemmy hates AI in any capacity.

Anyway:

On regret: why should anyone “regret” using a tool? If we need to take moral consideration into tool use… well…should we regret using mobile phones? I would argue they are just as reprehensible.

I think you're finally getting to the realization: doing things without considering the moral or ethical implications is inherently, uhhh, immoral and unethical. Do you do more good than bad with your smartphone? Does it use thousands of watts (hours) every time you use it? Do you replace your phone every year with the new model, maximizing your environmental impact with the manufacturing? What do you think makes using a smartphone just as bad as using an LLM?

Look, I get it: considering all of the consequences of your actions all of the time is tiring. I don't like doing it either. Clearly companies don't do it at all (at least not for external consequences). Look where that has got us. Apathy is not an option.

If a dev used a local model to spelunk the codebase and write the documentation, would that sit better? Why? I’m not sure the line is where people think it is.

Local models are better in many ways, yes. The local user has control over how much power they use (for the query, not on training), other resource usage (water, electrical power sources), what model (and by extent the training data it uses), and exactly what documentation they get out (depending on the query/ies). The best option is still obviously to write the documentation yourself, as the subject-matter expert.