[d_watt]

Regarding the meta experiment of using LLMs to transpile to a different language, how did you feel about the outcome / process, and would you do the same process again in the future?

I've had some moments recently for my own projects as I worked through some bottle necks where I took a whole section of a project and said "rewrite in rust" to Claude and had massive speedups with a 0 shot rewrite, most recently some video recovery programs, but I then had an output product I wouldn't feel comfortable vouching for outside of my homelab setup.

[antirez]

It depends on the situation. In this case the agent worked only using the reference code provided by Flux's Black Forest Labs which is basically just the pipeline implemented as a showcase. The fundamental way for this process to work is that the agent can have a feedback to understand if it is really making progresses, and to debug failures against a reference implementation. But then all the code was implemented with many implementation hints about what I wanted to obtain, and without any reference of other minimal inference libraries or kernels. So I believe this just is the effect of putting together known facts about how Transformers inference works plus an higher level idea of how software should appear to the final user. Btw today somebody took my HNSW implementation for vector sets and translated it to Swift (https://github.com/jkrukowski/swift-hnsw). I'm ok with that, nor I care of this result was obtained with AI or not. However it is nice that the target license is the same, given the implementation is so similar to the C one.

[jhatemyjob]

When I first saw the OP, panic started to set in that I am fucked and Chat-Completions/LLMs/AI/whatever-you wanna-call-it will soon be able to create anything and eat away at my earning potential. And I will spend my elder years living with roommates, with no wife or children because I will not be able to provide for them. But upon reading that you used a reference implementation, I've realized that you simply managed to leverage it as the universal translator apenwarr believes is the endgame for this new technology [1]. So, now I feel better. I can sleep soundly tonight knowing my livelihood is safe, because the details still matter.

[1] https://apenwarr.ca/log/20251120

[rcarmo]

This is pretty great. I’ve gone and hacked your GTE C inference project to Go purely for kicks, but this one I will look at for possible compiler optimizations and building a Mac CLI for scripting…

[kubb]

This repo has Swift wrappers, not a rewrite of hnsw.c, which apparently you weren't the only author of.

[rcarmo]

I have a set of prompts that are essentially “audit the current code changes for logic errors” (plus linting and testing, including double checking test conditions) and I run them using GPT-5.x-Codex on Claude generated code.

It’s surprising how much even Opus 4.5 still trips itself up with things like off-by-one or logic boundaries, so another model (preferably with a fresh session) can be a very effective peer reviewer.

So my checks are typically lint->test->other model->me, and relatively few things get to me in simple code. Contrived logic or maths, though, it needs to be all me.