“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’re caught up in an idea that has been going around since long before any AI systems had been built
Humans rarely, if ever, produce something new. We stumble upon a concept or apply one idea to another thing
Neural networks are carefully distilled entropy. They have no subjective biases and no foundation - they’re so good at being original that they default to things useless to humans.
I like to think of training like a mold, or a filter. You only want things in the right shape to come through - the more you train, the more everything coming through looks the same.