@aps ugh, so that's even more allegations of plagiarism and bad scientific conduct.
It really starts to look like LLMs are great at math when you give them the opportunity to look up the answer.
Oh and I learned today that apparently they also have duplicate numbers in the dump.
Maybe the LLM should study Peano a bit more deeply
I am not a maths theory kinda person, please forgive what may be an illogical question.
LLMs are engines built by extracting human data and incorporating it into a data set. (simple version). They are predictive. They *guess* what the next token should be. (I realize decision models operate differently but those are new and untested and not the models used in any of these use cases.)
If I am entering data into, say a spreadsheet or accounting software, and I sum a list, it is not guessing, it is doing predefined calculations on the data provided. Excel is unlikely to come up with a new theory of cost analysis just because of my creative data entries.
How could any output from a predictive engine be trusted to be true? It is not calculating anything. It is guessing. Yes? Or have I failed to understand something fundamental? That happens. :)
@MissConstrue @aps I mean yeah, that's definitely part of the problem. The newer results overcome this by using formal verification to check whether a given statement is true, which is definitely a much better approach.
As I understand decision models (I don't), they are significantly better at verifying within given parameters, so I could see value in providing a hypothesis, and verifying veracity...and perhaps I have an overly romantic view of how mathematicians think, but inspiration is a uniquely human trait, I would argue, and that all breakthroughs are a result of an "Ah Ha!" moment when a human brain brings together a seemingly disparate set of information to create a unified concept.
So, I guess I tend to view any "breakthrough" announcements by frontier labs that their LLM has done something no human could do, to be unlikely at best, made up from whole cloth at worst. (AGI claims, I'm looking at you.)
In any case, pay PhD students more, and give them a career path. I have more faith that an exhausted kid will see the brownian motion in her coffee cup and discover new theory than I do that a resource furnace will do it.