Comment by jstummbillig
1 day ago
I remain confused but still somewhat interested as to a definition of "novel", given how often this idea is wielded in the AI context. How is everyone so good at identifying "novel"?
For example, I can't wrap my head around how a) a human could come up with a piece of writing that inarguably reads "novel" writing, while b) an AI could be guaranteed to not be able to do the same, under the same standard.
If a LLM had written Linux, people would be saying that it isn't novel because it's just based on previous OS's. There is no standard here, only bias.
Cept its not made Linux (in the absence of it).
At any point prior to the final output it can garner huge starting point bias from ingested reference material. This can be up to and including whole solutions to the original prompt minus some derivations. This is effectively akin to cheating for humans as we cant bring notes to the exam. Since we do not have a complete picture of where every part of the output comes from we are at a loss to explain if it indeed invented it or not. The onus is and should be on the applicant to ensure that the output wasn't copied (show your work), not on the graders to prove that it wasn't copied. No less than what would be required if it was a human. Ultimately it boils down to what it means to 'know' something, whether a photographic memory is, in fact, knowing something, or rather derivations based on other messy forms of symbolism. It is nevertheless a huge argument as both sides have a mountain of bias in either directions.
> Cept its not made Linux (in the absence of it).
Neither did you (or I). Did you create anything that you are certain your peers would recognize as more "novel" than anything a LLM could produce?
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Generally novel either refers to something that is new, or a certain type of literature. If the AI is generating something functionally equivalent to a program in its training set (in this case, dozens or even hundreds of such programs) then it by definition cannot be novel.
This is quite a narrow view of how the generation works. AI can extrapolate from the training set and explore new directions. It's not just cutting pieces and gluing together.
Calling it “exploring” is anthropomorphising. The machine has weights that yield meaningful programs given specification-like language. It’s a useful phenomenon but it may be nothing like what we do.
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In practice, I find the ability for this new wave of AI to extrapolate very limited.
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Positively not. It is pure interpolation and not extrapolation. The training set is vast and supports an even vaster set of possible traversal paths; but they are all interpolative.
Same with diffusion and everything else. It is not extrapolation that you can transfer the style of Van Gogh onto a photographl it is interpolation.
Extrapolation might be something like inventing a style: how did Van Gogh do that?
And, sure, the thing can invent a new style---as a mashup of existing styles. Give me a Picasso-like take on Van Gogh and apply it to this image ...
Maybe the original thing there is the idea of doing that; but that came from me! The execution of it is just interpolation.
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uhhh can it? I've certainly not seen any evidence of an AI generating something not based on its training set. It's certainly smart enough to shuffle code around and make superficial changes, and that's pretty impressive in its own way but not particularly useful unless your only goal is to just launder somebody else's code to get around a licensing problem (and even then it's questionable if that's a derived work or not).
Honest question: if AI is actually capable of exploring new directions why does it have to train on what is effectively the sum total of all human knowledge? Shouldn't it be able to take in some basic concepts (language parsing, logic, etc) and bootstrap its way into new discoveries (not necessarily completely new but independently derived) from there? Nobody learns the way an LLM does.
ChatGPT, to the extent that it is comparable to human cognition, is undoubtedly the most well-read person in all of history. When I want to learn something I look it up online or in the public library but I don't have to read the entire library to understand a concept.
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OK, but by that definition, how many human software developers ever develop something "novel"? Of course, the "functionally equivalent" term is doing a lot of heavy lifting here: How equivalent? How many differences are required to qualify as different? How many similarities are required to qualify as similar? Which one overrules the other? If I write an app that's identical to Excel in every single aspect except that instead of a Microsoft Flight Simulator easter egg, there's a different, unique, fully playable game that can't be summed up with any combination of genre lables, is that 'novel'?
I think the importance is the ability. Not every human have produced (or even can) something novel in their life, but there are humans who have time after time.
Meanwhile, depending on how you rate LLM's capabilities, no matter how many trials you give it, it may not be considered capable of that.
That's a very important distinction.
If the model can map an unseen problem to something in its latent space, solve it there, map back and deliver an ultimately correct solution, is it novel? Genuine question, ‘novel’ doesn’t seem to have a universally accepted definition here
Good question, though I would say that there may be different grades of novelty.
One grade might be your example, while something like Gödel's incompleteness theorems or Einstein's relativity could go into a different grade.
> For example, I can't wrap my head around how a) a human could come up with a piece of writing that inarguably reads "novel" writing, while b) an AI could be guaranteed to not be able to do the same, under the same standard.
The secret ingredient is the world outside, and past experiences from the world, which are unique for each human. We stumble onto novelty in the environment. But AI can do that too - move 37 AlphaGo is an example, much stumbling around leads to discoveries even for AI. The environment is the key.
A system of humans creates bona fide novel writing. We don’t know which human is responsible for the novelty in homoerotic fanfiction of the Odyssey, but it wasn’t a lizard. LLMs don’t have this system-of-thinkers bootstrapping effect yet, or if they do it requires an absolutely enormous boost to get going
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why would you admit on the internet that you fail the reverse turing test?
Didn't some fake AI country song just get on the top 100? How novel is novel? A lot of human artists aren't producing anything _novel_.
> Didn't some fake AI country song just get on the top 100?
No
Edit: to be less snarky, it topped the Billboard Country Digital Song Sales Chart, which is a measure of sales of the individual song, not streaming listens. It's estimated it takes a few thousand sales to top that particular chart and it's widely believed to be commonly manipulated by coordinated purchases.
It was a real AI country song, not a fake one, but yes.
You have no idea if you're talking to an LLM or a human, yourself, so ... uh, wait, neither do I.
Because not everyone here has a raging ego and no humility?
Because I'm an LLM and you are too
Because we know that the human only read, say, fifty books since they were born, and watched a few thousand videos, and there is nothing in them which resembles what they wrote.