this post was submitted on 14 Sep 2024
603 points (97.8% liked)
Technology
59174 readers
2719 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 1 year ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Just want to point out that it absolutely is possible to train an AI that will keep track of its sources for inspiration and can attribute those when it makes a response.
Meaning creators could be compensated for their parts of AI generated stuff, if anyone wanted to.
Doesn't Phind do this already? I haven't used it much but I remember it showing its sources for answers of code-related stuff
I use Phind solving computer problems. It does cite the sources it uses. At least for distro and general Linux issues. So far, it's been a very good resource when I've needed it.
Other than citing the entire training data set, how would this be possible?
The entire training set isn't used in each permutation. Your keywords are building the samples based on metadata tags tied back to the original images.
If you ask for "Iron Man in a cowboy hat", the toolset will reach for some catalog of Iron Man images and some catalog of cowboy hat images and some catalog of person-in-cowboy-hat images, when looking for a basis of comparison as it renders the image.
These would be the images attributed to the output.
Do you have a source for this? This sounds like fine-tuning a model, which doesn't prevent data from the original training set from influencing the output. The method you described would only work if the AI is trained from scratch on only images of iron man and cowboy hats. And I don't think that's how any of these models work.
I think that there are some people working on this, and a few groups that have claimed to do it, but I'm not aware of any that actually meet the description you gave. Can you cite a paper or give a link of some sort?