I’ve written a lot of Lean for economic modeling (so take this with the caveat that it’s not frontier-level mathematics research) but I think this problem is overstated. If you follow good engineering standards—keep primitives composable and design abstraction well—it’s not so hard to understand enough Lean to ensure the formalized statement is correct.
In part this is possible because mathlib is very well-designed and has a very good API (in no small part because they’re willing to make breaking changes all the time), so building on top of it makes life much easier.
Or, more accurately: it's not possible to apply copyright to generated code; if you don't release it, it's a trade secret, but if you do, people can use it how they please.
A terminal AI coding assistant with a built-in math formalization engine — describe a problem in plain language and it converts it into a Lean 4 theorem and attempts a formal proof.
I am not sure of the premise. You can have a filter which takes garbage in and outputs the clean data from the garbage, a denoiser. Also your definition of slop is not specific to slop. Any input can be garbage, including this human sourced and thought comment.
In part this is possible because mathlib is very well-designed and has a very good API (in no small part because they’re willing to make breaking changes all the time), so building on top of it makes life much easier.
[1] http://www.cs.utexas.edu/users/EWD/ewd04xx/EWD427.PDF
Value is in how maths is communicated: The process, frustrations, triumphs, etc.
We have to able to take generated formalizations from “it compiles” to “it is correct” before crystallizing them.
Do you have a formal proof of that?
By the standard methods of modal logic, it follows that it is possible that the output is garbage and therefore slop by definition. QED.
wish these project always start with an example. i dont care about quickstart or featurelist if i dont know what this is.
Lets me ignore the LICENSE.md file, and use how I want.