Trivially, humans don't emit something they don't know either. You don't spontaneously figure out Javascript from first principles, you put together your existing knowledge into new shapes.
Nontrivially, LLMs can absolutely produce code for entirely new requirements. I've seen them do it many times. Will it be put together from smaller fragments? Yes, this is called "experience" or if the fragments are small enough, "understanding".
>> Nontrivially, LLMs can absolutely produce code for entirely new requirements. I've seen them do it many times.
I think most people writing software today are reinventing a wheel, even in corporate environments for internal tools. Everyone wants their own tweak or thinks their idea is unique and nobody wants to share code publicly, so everyone pays programmers to develop buggy bespoke custom versions of the same stuff that's been done 100 times before.
I guess what I'm saying is that your requirements are probably not new, and to the extent they are yes an LLM can fill in the blanks due to its fluency in languages.
Nothing is truly and completely new. I'm not formulating my requirements in an extinct language. My point is "filling in the blanks" and "do new things" are a spectrum.
LLMs have their limits, but they really can understand and productively contribute to programs that achieve a purpose that no program on the internet has done yet. What they are doing is not interpolation at the highest level. It may be interpolation/extrapolation at a lower level, but this goes for any skill learnt by anyone ever.
What makes you categorically say that "AIs can't"?
Based on my experience with present day AIs, I personally wouldn't be surprised at all that if you showed Gemini 2.5 Pro a video of an insect colony and asked it "Take a look at the way they organize and see if that gives you inspiration for an optimization algorithm", it will spit something interesting out.
That's a good point but all it means is that we can't test the hypothesis one way or the other due to never being entirely certain that a given task isn't anywhere in the training data. Supposing that "AIs can't" is then just as invalid as supposing that "AIs can".
What makes you categorically say that "humans can"?
I couldn't do that with an ant colony. I would have to train on ant research first.
(Oh, and AIs can absolutely explore what they don't know. Watch a Claude Code instance look at a new repository. Exploration is a convergent skill in long-horizon RL.)
> Humans can observe ants and invent any colony optimization. AIs can’t.
Surely this is exactly what current AI do? Observe stuff and apply that observation? Isn't this the exact criticism, that they aren't inventing ant colonies from first principles without ever seeing one?
> Humans can explore what they don’t know. AIs can’t.
We only learned to decode Egyptian hieroglyphs because of the Rosetta Stone. There's no translation for North Sentinelese, the Voynich manuscript, or Linear A.
Trivially, humans don't emit something they don't know either. You don't spontaneously figure out Javascript from first principles, you put together your existing knowledge into new shapes.
Nontrivially, LLMs can absolutely produce code for entirely new requirements. I've seen them do it many times. Will it be put together from smaller fragments? Yes, this is called "experience" or if the fragments are small enough, "understanding".