- cross-posted to:
- technology
- cross-posted to:
- technology
Our AI-generated future is going to be fantastic.
Archive link, so you don’t have to visit Substack: https://archive.is/hJIWk
Our AI-generated future is going to be fantastic.
Archive link, so you don’t have to visit Substack: https://archive.is/hJIWk
If you already have the computer for other reasons, such as gaming, are you paying for it to use it for a LLM? The limiting factor isn’t raw power either, it’s VRAM size. A GTX 1080 with 8Gb is capable of running some models. But an RTX 3060 12Gb can be bought new for really cheap and is more than enough for most people’s use at home. Raw GPU power only helps with the time it takes, but even if it took 12-24 hours, well, do you want it fast or do you want it cheap?
There’s more details in this reddit thread, sorry for linking the hell site: https://old.reddit.com/r/LocalLLaMA/comments/12kclx2/what_are_the_most_important_factors_in_building_a/
Yeah, if you already have it then it’s not really an extra cost. But the smaller models perform less well and less reliably.
In order to write a book that’s convincing enough to fool at least some buyers, I wouldn’t expect a Llama2 7B to do the trick, based on what I see in my work (ML engineer). But even at work, I run Llama2 70B quantized at most, not the full size one. Full size unquantized requires 320 GPU vram, and that’s just quite expensive (even more so when you have to rent it from cloud providers).
Although if you already have a GPU that size at home, then of course you can run any LLM you like :)
Okay, now ask yourself, are these books convincing enough to fool anyone? Because it’s just as likely that company has lofty promises and uses a toaster to generate the content.
Fair enough. They only have to convince the self help books crowd 🙃