this post was submitted on 02 May 2024
2 points (100.0% liked)
Games
16738 readers
695 users here now
Video game news oriented community. No NanoUFO is not a bot :)
Posts.
- News oriented content (general reviews, previews or retrospectives allowed).
- Broad discussion posts (preferably not only about a specific game).
- No humor/memes etc..
- No affiliate links
- No advertising.
- No clickbait, editorialized, sensational titles. State the game in question in the title. No all caps.
- No self promotion.
- No duplicate posts, newer post will be deleted unless there is more discussion in one of the posts.
- No politics.
Comments.
- No personal attacks.
- Obey instance rules.
- No low effort comments(one or two words, emoji etc..)
- Please use spoiler tags for spoilers.
My goal is just to have a community where people can go and see what new game news is out for the day and comment on it.
Other communities:
founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
What's NVidia seeing in the gaming space? Or do they conflate gaming and ML sales?
Who would buy consumer grade hardware for machine learning?
Almost everyone?
There are many different niches of ML. 99% of hobbyist would use consumer grade hardware. It's quite frankly more than good enough.
Even in commercial usage, consumer GPUs provide better value unless you need to do something that very specifically require a huge vram pool. Like connecting multiple A100 GPUs to have hundreds or tens of thousands of gigabyte vram. Those use cases only come up if you're making base models for general purpose.
If you're using it for single person use case, something like 4090 is actually the best hardware. Enough ram to run almost anything and it's higher clock speed than enterprise GPU means your results come back faster.
Even training doesn't require that much vram. Chat models are generally more vram heavy but if you're doing specific image training like stable diffusion for how to render your face, or some specific fetish porn, you only really need like 12GB of vram to do it. There are ways to even do it at lower like 8GB but 12 is sweet value spot where even 3060 or 4060ti can do. Consumer GPUs will get that trained in like 30min to 24hrs depending on settings and model.