What is the difference between "novel" and "novel to someone who hasn't consumed the entire corpus of training data, which is several orders of magnitude greater than any human being could consume?"
The difference is that when you do not know how a problem can be solved, but you know that this kind of problem has been solved countless times earlier by various programmers, you know that it is likely that if you ask an AI coding assistant to provide a solution, you will get an acceptable solution.
On the other hand, if the problem you have to solve has never been solved before at a quality satisfactory for your purpose, then it is futile to ask an AI coding assistant to provide a solution, because it is pretty certain that the proposed solution will be unacceptable (unless the AI succeeds to duplicate the performance of a monkey that would type a Shakespearean text by typing randomly).
Joking aside, I think you have too strict of a definition of novel. Unfortunately "novel" is a pretty vague word and is definitely not a binary one.
ALL models can produce "novel" data. I don't just mean ML (AI) models, but any mathematical model. The point of models is to make predictions about results that aren't in the training data. Doing interpolation between two datapoints does produce "novel" things. Thinking about the parent's comment, is "a blue tiger" novel? Probably? Are there any blue tigers in the training data? (there definitely is now thanks to K-Pop Demon Hunters) If not, then producing that fits the definition of novel. BUT I also agree that that result is not that novel. It is entirely unimpressive.
I'm saying this not because I disagree with what I believe you intend to say but because I think a major problem with these types of conversations is that many people are going to interpret you more literally and dismiss you because "it clearly produces novel things." It isn't just things being novel to the user, though that is also incredibly common and quite telling that people make such claims without also checking Google...
Citation needed that grokked capabilities in a sufficiently advanced model cannot combinatorially lead to contextually novel output distributions, especially with a skilled guiding hand.
It's not, because I haven't ruled out the possibility. I could share anecdata about how my discussions with LLMs have led to novel insights, but it's not necessary. I'm keeping my mind open, but you're asserting an unproven claim that is currently not community consensus. Therefore, the burden of proof is on you.
I agree that after discussions with a LLM you may be led to novel insights.
However, such novel insights are not novel due to the LLM, but due to you.
The "novel" insights are either novel only to you, because they belong to something that you have not studied before, or they are novel ideas that were generated by yourself as a consequence of your attempts to explain what you want to the LLM.
It is very frequent for someone to be led to novel insights about something that he/she believed to already understand well, only after trying to explain it to another ignorant human, when one may discover that the previous supposed understanding was actually incorrect or incomplete.
The point is that the combined knowledge/process of the LLM and a user (which could be another LLM!) led to it walking the manifold in a way that produced a novel distribution for a given domain.
I talk with LLMs for hours out of the day, every single day. I'm deeply familiar with their strengths and shortcomings on both a technical and intuitive level. I push them to their limits and have definitely witnessed novel output. The question remains, just how novel can this output be? Synthesis is a valid way to produce novel data.
And beyond that, we are teaching these models general problem-solving skills through RL, and it's not absurd to consider the possibility that a good enough training regimen cannot impart deduction/induction skills into a model that are powerful enough to produce novel information even via means other than direct synthesis of existing information. Especially when given affordances such as the ability to take notes and browse the web.
> I push them to their limits and have definitely witnessed novel output.
I’m quite curious what these novel outputs are. I imagine the entire world would like to know of an LLM producing completely, never-before-created outputs which no human has ever thought before.
Here is where I get completely hung up. Take 2+2. An LLM has never had 2 groups of two items and reached the enlightenment of 2+2=4
It only knows that because it was told that. If enough people start putting 2+2=3 on the internet who knows what the LLM will spit out. There was that example a ways back where an LLM would happily suggest all humans should eat 1 rock a day. Amusingly, even _that_ wasn’t a novel idea for the LLM, it simply regurgitated what it scraped from a website about humans eating rocks. Which leads to the crux: how much patently false information have LLMs scraped that is completely incorrect?