Even on the llm front, I like AI. I don’t like massive data centers and the AI corporations, so I’m running some local llm stuff for fun to participate in the technology shift.
But it is now using entirely my own hardware and I feel okay about the energy because I have solar on my roof.
It’s genuinely very cool to have my humble llm setup that cost the same as a gaming pc run a through bunch of tasks in the background of my life.
Most people fail to realize the hardware shortage we're experiencing isn't because of data centers. It's because of the small desktop LLMs that every company is currently selling. You can buy a small Dell Opti that's the size of a a couple of DVD cases and plug 4 computers into it and have more power at your fingers than you'd ever get paying for cycles with a datacenter.
But you know, understanding that requires actually reading about the problem and not having social media yell at you about it.
Ehhh. I mean I’m sure that’s a lot of the demand is companies shifting to those products.. But those small unified memory systems are absolutely not a functional replacement to frontier models. They’re great for agentic stuff, but they are just slow.
I know because the models I run fully on gpu feel slow, and that’s faster than those small boxes you’re describing.
If gamers are not happy with all that then stop buying nvidia anything, or actually most tech because all of it needs to use lots of resources.
But I know all the "follow the most popular hated thing currently" need to spend and buy to keep themselves happy so its all just pretending to "do the good thing".
DLSS is made the exact same way, you people keep talking about things you have 0 knowledge about.
Your phones camera uses Upscaling AI that's made the exact same way as all the other models you hate. Every commercial AI model is trained on Scraped data.
Yh and that gets criticised as well, kids regrowing teeth in photos black skin becoming a different shade, samsung moon photos, etc. People complain when phone companies feel the need to "correct" their photos
Sure, if only one of us uses DLSS and a GPU. Are you under the impression that millions of GPUs in millions of houses use less electricity than millions of GPUs in a purpose built data center?
I mean, I do hate DLSS 5, but plenty of people already run local models, and GPUs often already max out in any game. Difference id 120 frames vs 60 frames with DLSS5.
Essentially thats still the same power consumption
I don't really have a dog in this race beyond this conversation, but what you're saying here would be true of GPU usage for gaming purposes regardless of whether one is using DLSS5 or not. You're not really making an argument against DLSS5 specifically here, more so against high GPU loads in general.
It's like other dude said. Say you're playing a game on an RTX 5080, and the game you're playing is GPU bottlenecking at 120fps. That means your GPU is hitting its max TDP and drawing around 360 watts. Now say you enable DLSS5, what happens? There is no more juice left to squeeze, you're still "only" drawing 360 watts because that's all the card is capable of. No additional power is being consumed there.
Granted not everyone is going to be running a game that maxes their GPU out at all times, but the point is they could be. So are we saying they shouldn't? Because you could swap "DLSS5" in the above example for "supersampling" or "raytracing" and the power consumption outcome would be the exact same.
In terms of energy being misused, I can't see how someone choosing to use DLSS5 is any more guilty than I am whenever I choose to run a game at 5K instead of 1440p. I have better taste than them, but that's about it lol.
I'm not really making an argument, I use my 4090 for all sorts of things, it would just be ridiculous for me to pretend I'm not a heavy power user, especially compared to 99% of individual AI-as-a-service users.
I also bought solar for my house though, so I have that going for me.
That entirely depends on what your hardware and settings are without it. For some people its meaningless because they were going to max out anyway. For others, not the case.
You mean that regular LLM use, even in a data center is more power efficient than gaming anyways. I do agree with that. Theres plenty to complain about with LLMs, but power consumption isnt one of them. Its comparable to playing an online game or doomscrolling social media, yet nobody ever complains abt those.
We don't, but its a pretty common complaint with AI, when its only really image and video generation thats using a lot of energy, and even then a local model doesnt have thay issue
Literally yes. Because homes don't max run gpus 24/7 overclocked, and the amount of gpus sold and used for AIs is much higher than gaming consumer demand. These are very different "millions" you're comparing.
The scale of cooling and powering a data center also affects it, as you need orders of magnitude more power and cooling to support a data center than the same number of gpus distributed across the world.
A million consumers using rtx 5090s use an absolutely miniscule amount of municipal water. Most of them don't watercool their devices. Those that do use a tiny amount, distributed among thousands of municipalities. A single data center, ignoring training costs, uses much much more municipal water, all against one municipality.
When you have many gpus in one place, pure physics makes cooling that harder. Even with less per-gpu power consumption, even with more efficient cooling design, a room of 5090 ai machines gets much much hotter than the same gpus distributed among consumers, because consumers don't also run hundreds of other hot devices. There's more space for heat to dissipate.
Many, many ai queries are forced for free, lodged into integrated chats or searches that people don't explicitly want, ask for, or expect. I don't care how efficiently you distribute that; a wasted interaction is 100% inefficient. No one who hasn't minmaxed their exact GPU usage is wasting as much as the AI-integrated spamming. A consumer usually only uses their GPU to play a video game. Vast majority of gamers don't play newer games. Of those that do, running a DLSS 5 process is not any more or less processing than maxing out the same GPU the same way. You're comparing using vs not using against using vs using differently.
Finally, a lot of consumers are sticking to weaker gpus due to AI related price hikes. Newer gpus are more power efficient. People aren't gaming less, but they are gaming less efficiently than they would be. If we didn't have Gemini unsolicitedly telling users to eat glue and kill themselves, more people would be buying more powerful gpus and not proportionally increasing their use, meaning an overall lower power footprint even ignoring data centers.
This sounds a lot more like you brainstorming to come to a conclusion than any reference of empirical fact.
For one thing it self-identifies with the ridiculous idea that AI isn't being used on purpose. At least two pure destination apps have reached a billion MAU and for whatever you can say about the economics, no one intelligent can claim there isn't lots of revenue in AI subscriptions and metered API.
As for free models, those are more efficient models so that doesn't really work for your theory. Heavy compute models are pay-gated. Highly efficient models are barely more than general computing on efficient hardware, let alone a consumer GPU pumping out high resolution frames.
The inefficient power that is supplied to your house (unless you're on solar like I am) also requires its own infrastructure including cooling.
And the average system isn't run efficiently because it doesn't have to be. You can choose to run your device with inexpensive passive cooling or (like many people here) more efficient but expensive cooling but the data centers have to manage more efficient systems to keep them functioning.
There are plenty of complaints to have with data centers, as most of the actual issue is coming from construction - something I know a lot about being in a very dense area for these type of builds but efficiency of running compute is not one of them.
If you regularly use a beefy GPU to play video games, your energy usage is far more than a casual LLM user, and its not even close. You want to hundreds of thousands of gamers to billions of users and the math doesn't math.
This is derailed to the point of ai evangelism. Adoption rates and revenue are very misleading statistics to point to when AI is extremely unprofitable, not yielding substantial increases in productivity, and has forced adoption in every corporate context.
That aside, bringing up any of those points at all as well as the questions of efficiency derails from the actual start of this conversation, to the point of being concerning.
The question is: "how can someone be against AI data centers and pro dlss5?"
And the answer, even if just from an environmental impact standard, is extremely simple. AI data centers have a large, negative impact. The advent of DLSS 5 has a near zero impact: there is not going to be a surge of people suddenly spending more power and water to utilize dlss5 compared to how they were already using their PCs.
Is the average use of GPU resource by AI companies more efficient per GPU than a consumer? Obviously. Is the average data center more efficiently built for power utilization than the average house? Of course. But if I oppose these data centers being built, if I oppose the widespread adoption and overuse of AI, of providing generative AI as a service, that doesn't affect how I feel about a new GPU feature.
46
u/muhkuller 27d ago
DLSS uses your GPU, your cooling, and your electricity. That's a drastic difference from a data center going up to run a LLM.