> Why surely? Have you never seen an LLM try something new?
I'm afraid I can't make it any simpler than this.
And I still don't know the answer to how you're so sure. To me there's several explanations, and it seems to you there's only one.
I'm pretty happy with my communication style.
Given that this is a common technique and not a novel invention, it’s probably present in the training set.
The “surely” reads like it’s referring to the presence of that information in the training set. But your response casts it as saying “surely the AI has not invented something on its own”.
The original question stands IMO, the burden of proof is on whoever is asserting that the AI has invented something on its own, with or without training data that surely already mentions this approach
The problem with the reasoning of the person I was responding to is that it's assuming "if X is in the training set and LLM outputs X, then it did so because X is in the training set". That does not follow. Conceivably it's possible that X is in the training set and LLM outputs X, but if X hadn't been in the training set the LLM also would've output X.
Lets look at that phrase again:
> Why do we think this emerged “on its own”? Surely this technique has been discussed in research papers that are in the training set.
This phrase implies "if X was in the training set, then LLM couldn't have come up with X on its own". This is false. In fact, my claim that the implication is false is testable, in the following manner: Have two training sets, T and T'. In T, X is present. In T' you've removed X but left X-adjacent things. Train LLM A on T and A' on T'. Find a prompt that requires that A outputs X. If on the same prompt A' also outputs X, that's an example of my claim. To repeat, my claim is "it's possible that X is in the training set and LLM outputs X, but if X hadn't been in the training set the LLM also would've output X."
In fact, I've just realized I even have a method for constructing (T, T') that guarantees what I've described. Not sure if it's worth a paper on its own though.
But you’re missing the context and implication: “doing new stuff” is the major achievement we’re looking for next from LLMs. Seeing something that is “new” and is not in the training set is interesting in a way that something contained in the training set is not.
We cannot introspect LLMs meaningfully yet, so the difference between “came up with myself and it’s in the training set incidentally” and “applied a concept in the training set” is not meaningful.
A few examples: Axiom's proof of Fel’s open conjecture on syzygies of numerical semigroups: https://x.com/axiommathai/status/2019449659807219884
Erdos 457: https://www.erdosproblems.com/457
The stronger form of Erdos 650: https://www.erdosproblems.com/650
In this case, using a cheap(er) signal or heuristic as an initial filter before spending more resources on cases that pass the filter is a pattern that shows up all over the place, and LLMs are good at picking up on patterns like that and generalizing them. AFAICT.
Say what, exactly?