I don't think this general complaint about AI workflows is that useful. Most people are not a competent <insert job here>. Most people don't know a competent <insert job here> or can't afford to hire one. Even something that takes longer than a professional do at worse quality for many things is better than _nothing_ which is the realistic alternative for most people who would use something like this.
Maybe not to you, but it's useful if you're in these fields professionally, though. The difference between a neat hobbyist toolkit and a professional toolkit has gigantic financial implications, even if the difference is minimal to "most people."
2. those "hobbyists" in all examples are in fact professionals now. That's why they could scale up.
Secondly, the number of hobbyists only matters if you're talking about hobbyists that develop the technology-- not hobbyists that use the technology. Until those tools are good enough, you could have every hobbyist on the planet collectively attempting to make a Disney-quality character model with tools that aren't capable of doing so and it wouldn't get much closer to the requisite result than a single hobbyist doing the same.
May be relevant in the long run, but it'll probably be 5+ years before this is commercially available. And it won't be cheap either, so out of the range of said people who can't hire a competent <insert job here>
That's why a lot of this stuff is pitched to companies with competent people instead of offered as a general product to download.
I think you should look at the progress of image, text, and video generation over the past 12 months and re-asses your timeline prediction.
But this stuff trickles down to the public very slowly. Because indies aren't a good audience to sell what is likely an expensive tech that is focused on mid-large scale production.
>Most people are not a competent <insert job here>. Most people don't know a competent <insert job here> or can't afford to hire one.
emphasis mine. Affordability doesn't have much to do with capabilities, but it is a strong factor to consider for an indie dev. Devs in fields (games, VFX) that don't traditionally pay well to begin with.
>the relevance of your argument to the reality of the scene is not clear.
I feel it's clear if you're following the conversation chain. Is there something you'd like me to clarify?
Practical applications for a medium-large studio is very different from the practical applications of a solo/small dev team. That's all I'm really getting at. There is all kinds of cool tech from 2010 that still isn't viable for indies but is probably used at every AAA studio, so there's precedent I'm basing this on.
I honestly think we'll get there within 18 months.
My skepticism is whether the technique described here will be the basis of what people will be using in ~2 years to replace their low level static 3d asset generation.
There are several techniques out there, leveraging different sources of data right now. This looks like a step in the right direction, but who knows.
At the moment, making 3d models is a lot of skilled, monotonous work, especially for stuff like scene furniture. I guess I'd be pretty happy if some of that work could be automated away, and I'm pretty confident that there's no point automating away the remainder, for the same reason you don't want ChatGPT writing your screenplay.
I just checked the timestamps on my Dall-E Mini generated images. They're dated June 2022
This is what people were doing on commodity hardware back then:
https://cdn-uploads.huggingface.co/production/uploads/165537...
This is what people are doing on commodity hardware now:
https://civitai.com/images/3853761
I'm not even going to try to predict what we'll be able to do in 2 years time; even when accounting for the current GenAI hype/bubble!