I think of an LLM as extraordinarily lossy compression. All the training data is essentially encoded in the model. You can get an approximation of the data back out again with the right input.
I don’t think it’s any less reliable that random blogs on the web, and I don’t have to wear through SEO tripe either.
The annoying thing though is that all the random blogs on the web are written with using these LLMs now. It makes it much harder to be critical of your sources, because they’re all coming from a unnamed, proprietary LLM with no information about who owns it or the training data. At least before, I could look up the user or check out their other articles, now every article is randomly generated from some unknown prompt.
I think of an LLM as extraordinarily lossy compression. All the training data is essentially encoded in the model. You can get an approximation of the data back out again with the right input.
I don’t think it’s any less reliable that random blogs on the web, and I don’t have to wear through SEO tripe either.
The annoying thing though is that all the random blogs on the web are written with using these LLMs now. It makes it much harder to be critical of your sources, because they’re all coming from a unnamed, proprietary LLM with no information about who owns it or the training data. At least before, I could look up the user or check out their other articles, now every article is randomly generated from some unknown prompt.