[CompanyGardener]

Thanks for taking a look.

Tungsten is terse and fairly token efficient (20-30% less than Python). I've found it works well for prototyping with LLMs - even though they haven't been trained on it.

I've been using it lately for some scientific exploration, made a flip-graph search for matrix multiplication algorithms (low-rank decompositions of the matmul tensor over GF(2)). It has independently matched the world records for 3x3, 4x4, and 5x5.

Oddly enough, even though it's fresh out the gate, I think it makes a good fit for language implementation (at least as a stage1). I have a few reference lexers, an arena-slabbed AST layout, and a NaN-boxed 64-bit layout in the repo.

The bignum math is nearly as fast as GMP, without GPL license issues. The native regex engine was matching PCRE.

There's a scrubbing feature in the REPL that is pretty fun as well - inspired by a paper and talk from Bret Victor a while back.