71–80 of 117 posts
The difference between (A) software engineers reacting to AI models and systems for programming and (B) artists (whether it's painters, musicians or otherwise) reacting to AI models for generating images, music, etc. is very interesting. I wonder what's the reason.
Look at who the tools are marketed towards. Writing software involves a lot of tedium, eye strain, and frustration, even for experts who have put in a lot of hours practicing, so LLMs are marketed to help developers make their jobs easier. This is not the case for art or music generators: they are marketed towards (and created by) laypeople with who want generic content and don't care about human artists. These syste…
But many people use diffusion models in a much more interactive way, doing much more of the editing by hand. The simplest case is to erase part of a generated image, and prompt to infill. But there are people who spend hours to get a single image where they want it.
What is the recommended hardware to run a model like that locally on a desktop PC?
The difference between (A) software engineers reacting to AI models and systems for programming and (B) artists (whether it's painters, musicians or otherwise) reacting to AI models for generating images, music, etc. is very interesting. I wonder what's the reason.
Artists put a ton of time into education and refining their vision inside the craft. Amateur efforts to produce compelling work always look amateur. With augmentation, suddenly the "real" artists aren't as differentiated.
The whole conversation is obviously extremely skewed toward digital art, and the ones talking about it most visibly are the digital artists. No abstract painter thinks AI is coming for their occupation or cares wether it is easier to create anime dreamscapes this year or the next.
Is there an LLM that's useful for Terraform? Something that understands HCL and has been trained on the providers, I imagine.
For practical reasons, I often like to know how much GPU RAM is required to run these models locally. The actual number of weights seems to only express some kind of relative power, which I doubt is relevant to most users.
Edit: reformulated to sound like a genuine question instead of a complaint.
Does anyone know why the sizes of these models are typically expressed in number of weights (i.e 1.5B and 9B in this case), without mentioning the weight size in bytes? For practical reasons, I often like to know how much GPU RAM is required to run these models locally. The actual number of weights seems to only express some kind of relative power, which I doubt is relevant to most users. Edit: reformulated to sound…