the fact that llms can spit out books they've been trained on near verbatim lends some credence to this.

"However, we also find that Llama 3.1 70B memorizes some books, like Harry Potter and the Sorcerer’s Stone and 1984, almost entirely. In fact, Harry Potter is so memorized that, using a seed prompt consisting of just the first line of chapter 1, we can deterministically generate the entire book near-verbatim. "

https://reglab.stanford.edu/publications/extracting-memorize...

	▲	keeda 2 days ago \| parent [-]
		A more important quote from that link: > With our specific experiments, we find that the largest LLMs don’t memorize most books–either in whole or in part. This technique has only ever been made to work with a vanishingly small number of extremely popular works, probably because they are so overrepresented in the training data set. The risk with IP, however, is a lot more grave. You may not even need to memorize the details of the IP verbatim, just the broad idea may be enough. It may lurk encoded in the weights forever, just waiting to be activated by the right prompt to start a chain of thought that unlocks further details. Heck, it may even appear as if the model suggested the idea itself.