And of course the number of libraries, known algorithms, etc, is much larger than 8. There's any number of ways to make something new by combining well-understood parts.
I don't think non-expert prompting is pushing the envelope on what can be built because I think the current generation of harnesses and models pushes to using well-understood patterns in well-understood ways but it's certainly moving the line for what has been built. And with more skilled prompting you can build pretty crazy stuff + extensive validation for it.
https://www.science.org/content/article/openai-just-changed-...
Do you think playing dumb is making you look credible or something? The argument isn't "was maths in the dataset" the controversy was if someone with potentially working approaches narrowed the search space enough for the LLM not to fail
> And you think it butresses the argument that the llms can’t do _coding_ tasks they haven’t seen before?
This isn't an argument being made. At least try to respond to what's actually written rather than making yourself look foolish and trying to wordplay your way to a point.
That’s pretty hard to read differently. Can you add the nuance I’m missing?
> By definition an LLM is unable to build what has never been built before because you are going outside the realm of pretraining/RL. You might be able to combine components that already exist in a unique way
It seems you weren’t following that norm and we were talking past each other. That’s fine and I’m happy to leave it at that.
Perhaps in the future you can recognize the local norms before resorting to personal attacks even if those norms are different than the parts of the internet you normally hang out in.