An LLM takes an input string a corpus of text, and returns a series of text that best comes after the next input string.
To get a paragraph of output, you run the search over and over again
Both the search and LLM reshuffle the inputs to the outputs.
If I'm describing the purpose of the LLM, it's got a wide number of usages. "Making my resume look more professional" or "be a crud api" or "reformat my ask into a api call to X service" or "give me a timeline of events surrounding Y with source links"
If I'm describing the purpose of an 18 wheeler, it's got a wide number of usages. "Carry my chicken" or "carry my lettuce" or "carry my Cheetos". Or, simply, "carry my groceries".
And how did the training data contribute to the content in any meaningful way? Inspiration isn't substance.
You think all fantasy writers gotta pay Tolkien estate bc so much of fantasy draws from his tropes? Lmao no.
If training data is so unimportant, why not simply not use it and avoid the controversy? At the very least that would certainly fix the issue where the model demonstrates how "inspired" it is by NYT articles by reproducing them verbatim.
:)
The whole point of a search engine (as we've classically known them) is to index the web and respond to queries with a list of links that you will inspect and click through on. The whole point of an LLM chatbot tool is to eliminate those inspecting and clicking-through steps, becoming a one-stop shop for content whose substance was created by someone else. That's also the whole point of GP's hypothetical, which is why it works as an analogy.
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There are substantially better arguments for search engines being legitimate fair use. Consider, for example, transformation. AI defenders will argue that these systems are transformative because they reshuffle elements of their input in their output, but that's clearly a much weaker form of transformation than one in which the transformed work has an entirely different nature and purpose, i.e. search engines vs. the results they return. Ultimately these technicality-based "nuh uh" arguments aren't going to save the practice of training AI on unlicensed data, because they are incompatible with the spirit of copyright law even if the novel nature of these technologies means the letter of said law can't quite nail them down yet.
If these arguments do succeed, it will be because the judicial/regulatory environment in which they were applied has been corrupted by capital.