Training from scratch and retraining is expensive. Also, they want to avoid training on ML outputs as samples, they want primarily human made works as samples, and after the initial public release of LLMs it has become harder to create large datasets without ML stuff in them
There was a good paper that came out recently saying that training on ml data will result in a collapse of cohesion. It’s going to be real interesting, I don’t know if they’ll be able to train as easily ever again
I recall spotting a few things about Image Generators having their training data contaminated using generated images, and the output becoming significantly worse. So yeah, I guess LLMs and IGA’s need natural sources, or it gets more inbred than the Habsburgs.
Training from scratch and retraining is expensive. Also, they want to avoid training on ML outputs as samples, they want primarily human made works as samples, and after the initial public release of LLMs it has become harder to create large datasets without ML stuff in them
There was a good paper that came out recently saying that training on ml data will result in a collapse of cohesion. It’s going to be real interesting, I don’t know if they’ll be able to train as easily ever again
I recall spotting a few things about Image Generators having their training data contaminated using generated images, and the output becoming significantly worse. So yeah, I guess LLMs and IGA’s need natural sources, or it gets more inbred than the Habsburgs.
I think it’s telling that they acknowledge that the stuff their bots churn out is often such garbage that training their bots on it would ruin them.