Training AI models with AI-generated synthetic content causes the quality of the models' outputs to disintegrate, a new paper shows.
“Our primary conclusion across all scenarios is that without enough fresh real data in each generation of an autophagous loop, future generative models are doomed to have their quality (precision) or diversity (recall) progressively decrease,” they added. “We term this condition Model Autophagy Disorder (MAD).”
Interestingly, this might be a more challenging problem as we increase the use of generative AI models online.
You are not logged in. However you can subscribe from another Fediverse account, for example Lemmy or Mastodon. To do this, paste the following into the search field of your instance: !technology@beehaw.org
A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.
Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.
I forget where I heard this quote:
gonna file this away for five or ten years from now…
So, the most valuable Reddit archives are the ones that were already made before they set ruinous prices on their APIs. Nice.