'We support the work of those who are trying to limit the harm generative AI is doing to videogames and our world, and apologise that Big Walk’s LLM usage may not meet their standards'
Well id argue local llms + don’t support the people making them is probably fine, so long as you’re not letting it do web searches constantly so you aren’t ddosing the internet.
They absolutely do. Just because you took the plagiarism machine offline after it stole everything and then destroyed ecosystems and neighborhoods to produce the resulting dataset doesn’t mean it’s any better than the fascist empowering online ones. It’s exactly the same. Being ever so slightly better because you’re using your own power from the power company instead of someone else isn’t worth the destruction caused to get to a point where your offline sycophant machine can sometimes confidently not lie to you.
How? I’m not paying any of the companies or supporting the people who made it in any way. This is the equivalent of a vegan eating some meat that was about to be thrown in the trash. I’m also only using it for coding some personal use slop anyway, and most of the stolen code was GPL / MIT license which means for personal use there isn’t even a license issue. Me using it offline and telling everyone not to pay for it and that the data scraping is terrible is nowhere near the same as someone paying and supporting these companies.
What constitutes an ethically acquired data set? I’m just not sure how you could definitively say that any particular data set did not include some stolen content. You would have to gather it yourself which is utterly impractical for anything other than very niche AI.
Just off the dome an ethically acquired data set would be one where the data providers have knowledge that their data will be used for training a model and consent. When I did a deepfake project for a class back in 2019 that looked like me asking my buddies “hey can you sit and read this article on deepfakes in front of a camera so I can try swapping your faces?”
In a commercial setting there are a couple ideas:
Train on your own past work. This has the added benefit of ensuring the model will be better at approximating your own style.
Stock image sources but for data. Gettysburg has a ton of images, and while they weren’t originally gathered for image generating model training they could start a new collection where they expressly get that consent. If it comes out that there are stolen images in that dataset, Gettysburg is the one liable and should likely need to provide compensation for any training already performed then remove that data from the set they sell.
Frankly niche models is probably where the technology should have gone in the first place. Why invest trillions of dollars into making general purpose models that are kinda mediocre at everything when you could build a smaller, more focused model that only does what you actually care about maybe pretty well.
Well id argue local llms + don’t support the people making them is probably fine, so long as you’re not letting it do web searches constantly so you aren’t ddosing the internet.
They absolutely do. Just because you took the plagiarism machine offline after it stole everything and then destroyed ecosystems and neighborhoods to produce the resulting dataset doesn’t mean it’s any better than the fascist empowering online ones. It’s exactly the same. Being ever so slightly better because you’re using your own power from the power company instead of someone else isn’t worth the destruction caused to get to a point where your offline sycophant machine can sometimes confidently not lie to you.
How? I’m not paying any of the companies or supporting the people who made it in any way. This is the equivalent of a vegan eating some meat that was about to be thrown in the trash. I’m also only using it for coding some personal use slop anyway, and most of the stolen code was GPL / MIT license which means for personal use there isn’t even a license issue. Me using it offline and telling everyone not to pay for it and that the data scraping is terrible is nowhere near the same as someone paying and supporting these companies.
I’d say that would depend on the dataset used to create them.
What constitutes an ethically acquired data set? I’m just not sure how you could definitively say that any particular data set did not include some stolen content. You would have to gather it yourself which is utterly impractical for anything other than very niche AI.
Just off the dome an ethically acquired data set would be one where the data providers have knowledge that their data will be used for training a model and consent. When I did a deepfake project for a class back in 2019 that looked like me asking my buddies “hey can you sit and read this article on deepfakes in front of a camera so I can try swapping your faces?”
In a commercial setting there are a couple ideas:
Frankly niche models is probably where the technology should have gone in the first place. Why invest trillions of dollars into making general purpose models that are kinda mediocre at everything when you could build a smaller, more focused model that only does what you actually care about maybe pretty well.
Seems like you get it just fine.