Earlier quoted context omitted.
People who use "make your own game" games aren't good at making games. They might enjoy a simplified process to feel the accomplishment of seeing quick results, but I find it unlikely they'll be competing with indie developers.
Yeah, and if there was going to be such a tool, people who invest more time in it would be better than those casually using it. In other words, professionals.
MeshGPT: Generating triangle meshes with decoder-only transformers
91–100 of 166 posts
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#92Earlier quoted context omitted.
> I don't think this general complaint about AI workflows is that useful 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."
Linux vs Unix. Wikipedia vs Britannica. GCC vs Intel compiler. Good enough free hobby toy beats expansive professional tools given enough hobbysts.
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.
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#93Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#94Earlier quoted context omitted.
>Most people don't know a competent or can't afford to hire one 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 That's why a lot of this stuff is pitched to companies with competent people instead of offered as a general product to download.
> but it'll probably be 5+ years before this is commercially available 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.
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#95Earlier quoted context omitted.
> A competent modeler can make these types of meshes in under 5 minutes. I don't think this general complaint about AI workflows is that useful. Most people are not a competent . Most people don't know a competent 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 us…
>Most people don't know a competent or can't afford to hire one 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 That's why a lot of this stuff is pitched to companies with competent people instead of offered as a general product to download.
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#96Earlier quoted context omitted.
Is the target market really "most people," though? I would say not. The general goal of all of this economic investment is to improve the productivity of labor--that means first and foremost that things need to be useful and practical for those trained to make determinations such as "useful" and "practical."
Millions of people generating millions of images (some of them even useful!) using Dall-E and Stable Diffusion would say otherwise. A skilled digital artist could create most of these images in an hour or two, I’d guess… but ‘most people’ certainly could not, and it turns out that these people really want to.
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#97Earlier quoted context omitted.
Millions of people generating millions of images (some of them even useful!) using Dall-E and Stable Diffusion would say otherwise. A skilled digital artist could create most of these images in an hour or two, I’d guess… but ‘most people’ certainly could not, and it turns out that these people really want to.
Are those millions of people actually creating something of lasting value, or just playing around with a new toy?
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#98This is what a truly revolutionary idea looks like. There are so many details in the paper. Also, we know that transformers can scale. Pretty sure this idea will be used by a lot of companies to train the general 3D asset creation pipeline. This is just too great. "We first learn a vocabulary of latent quantized embeddings, using graph convolutions, which inform these embeddings of the local mesh geometry and topolog…
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#99Earlier quoted context omitted.
>Most people don't know a competent or can't afford to hire one 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 That's why a lot of this stuff is pitched to companies with competent people instead of offered as a general product to download.
Is there a reason to expect it'd be significantly more expensive than current-gen LLM? Reading the "Implementation Details" section, this was done with GPT2-medium, and assuming running it is about as intensive as the original GPT2, it can be run (slowly) on a regular computer, without a graphics card. Seems reasonable to assume future versions will be around GPT-3/4's price.
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!
Re: MeshGPT: Generating triangle meshes with decoder-only transformers
#100Earlier quoted context omitted.
“Make your own game” games will never replace regular games. They target totally different interests. People who play games (vast majority) just want to play an experience created by someone else. People who like “make your own game” games are creative types who just use that as a jumping off point to becoming a game designer. It’s no different than saying “these home kitchen appliances are really gonna kill off the…
Hmm I think it will destroy the market in a couple ways. AI creating video games would drastically increase the volume of games available in the market. This surge in supply could make it harder for indie games to stand out, especially if AI-generated games are of high quality or novelty. It could also lead to even more indie saturation( the average indie makes less than 1000 dollars). As the market expectations shif…
The games market has been in the same place as the rest of the arts for some time now: if you want to be noticed, you have to mount a bit of a production around it, add layers of design effort, and find a marketing funnel for that particular audience. The days of just making a Pong clone passed in the 1970's.
What technology has done to the arts, historically, is add either more precision or more repeatability. The relationship to production and arts as a business maps to what kinds of capital-and-labor-intensive endeavors leverage the tech.
Photographs didn't end painting, they ended painting as the ideal of precisely representational art. In the classical era, just before the tech was good enough to switch, painting was a process of carefully staging a scene with actors and sketching it using a camera obscura to trace details, then transferring the result to your canvas. Afterwards, the exact scene could be generated precisely in a photo, and so a more candid, informal method became possible both through using photographs directly and using them as reference. As well, exact copies of photographs could be manufactured. What changed was that you had a repeatable way of getting a precise result, and so getting the precision or the product itself became uninteresting. But what happened next was that movies and comics were invented, and they brought us back to a place of needing production: staged scenes, large quantities of film or illustration, etc.
With generative AI, you are getting a clip art tool - a highly repeatable way of getting a generic result. If you want the design to be specific, you still have to stage it with a photograph, model it as a scene, or draw it yourself using illustration techniques.
And so the next step in the marketplace is simply in finding the approach to a production that will be differentiating with AI - the equivalent of movies to photography. This collapses not the indie space - because they never could afford productions to begin with - but existing modes of mobile gaming, because they were leveraging the old production framework. Nobody has need of microtransaction cosmetics if they can generate the look they want.