I like using logic to do things it was never meant to do
You can refer to me as J. or as Jason
CS PhD student at UChicago
(all opinions my own)
Posts
@totbwf
Tbh NixOS is great because any service you can imagine has a configuration option
services.foo.enable = true; which sets it up with perfect reasonable defaults. Every configuration you could want has a flag and you never have to know how to work with whatever random bespoke config format that your one specific service has (but you can if you want).
They always have an easy uninstall.
The difficult thing is running random binaries off the internet, but that's usually a thing that deserves a moment of thought anyway
@androcat@toot.cat Thanks for the response! I think there's still two counterarguments:
-
For informal proofs, RL prioritizes reasoning that appears valid, and I'm not sure how much they use things like known results
-
Tools like Lean both give feedback on valid proofs enabling systems to learn to produce them, and drastically reduce the checking surface (down to just the definitions).
I believe I already said what you said, as well as addressing why the reasoning is flawed, in my first message.
GenAI is indeed just a stochastic search tool over the space of relevant text, that is biased towards producing text which is a valid proof (via RL).
One should not mistake the methods for the outcomes.
Otherwise, I believe you're attacking an imaginary adversary here; nobody made any claim of understanding as far as I can tell. You then proceeded to jump into ad hominims, which I certainly don't appreciate.
I genuinely believe it is worth understanding the depth of theoretical math that goes into machine learning and AI, along with the extensive history of empirical science.
@ncf I assume by relation you mean prop-valued. In that case decidability is effectively a prop (even without extensionality we can factor through its truncation)
strong total => decidable: so eliminate the truncation and we have inputs x y, and a function d: ∀ x y. (x ≤ y) + (y ≤ x). We play this function against itself:
consider d x y, and d y x. If the first returns the left branch or the latter returns the right, we're done by picking x ≤ y. But otherwise we have y ≤ x, in which case given x ≤ y we have x = x, and hence the two functions must have agreed, and hence we have a contradiction
strong total <= decidable: Given a decision d, and any inputs x y, let's prove x ≤ y + y ≤ x, Consider d x y, d y x. If Either returns their first input, we are done. But if both return the negation, we have a contradiction using totality, hence we have handled all cases.