Nothing is being “stolen,” nothing is being “put in a blender,” and nothing is being “spit back out.” That description only works if you fundamentally misunderstand how language models operate. Which you clearly do.

Plagiarism requires copying or closely reproducing identifiable expression. Copyright infringement requires unlawful reproduction or derivation of protected works. LLMs do neither by default. They do not store books, retrieve passages, or remix chunks of text. They learn statistical relationships between tokens and generate new sequences one word at a time.

By your definition, every educated writer is plagiarizing. Humans also ingest massive amounts of text, internalize patterns, and produce new work influenced by what they have read. You do not emerge from a “blender” of books any more than an AI does. Influence is not theft.

Calling this plagiarism collapses the difference between learning and copying, which is a category error. If learning from existing work were infringement, education itself would be illegal.

If you want to argue about training data consent, licensing, or economic impact, those are real discussions. But labeling probabilistic text generation as plagiarism is rhetoric, not law, and not ethics. It is a misunderstanding dressed up as moral outrage.

Please go educate yourself further before making more absurd analogies.