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by goodwillhunting
25 days ago
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This is fairly impressive, at least at first glance and hits a niche that is interesting. I think a big challenge in finding adoption for a new lang is in the application, or more specifically, when/why/where it's used. This is something I'd love to hear from folks involved in this (if reading) what they think those are and if/how that helped them shape the lang. Good luck! |
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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.