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CodeReclaimers

Agreed. The wrinkle I thought was worth writing up is: there's no learned reward model here and no training at all. The "reward" is wall-clock executiion time and the model is frozen; the search is happening at inference time, not in an RL loop. So the usual "the proxy is a fuzzy approximation that degrades under optimization pressure" story doesn't apply.

This was on a ~200-line surface I thought I'd locked down, and it still got gamed in a way I might not have caught right away if it wasn't a nearly impossible run time (~45usec). So anyways...you apparently don't need a soft proxy or a lot of steps for this kind of thing to show up.

Show HN: Symbolic regression as an MCP tool (SINDy and PySR, free, no install)

https://occam.fit/

I maintain neat-python and have been building a genetic programming framework in Julia. While doing research on that project, I kept finding the same complaint in PySR's GitHub discussions: people give up not because symbolic regression doesn't work, but because getting Julia talking to Python is a repeated source of failure, especially on Windows and in notebooks.So I stood up Occam...

( Read More... | 1 comment | 3 points | on HN )
Looking forward to the day when "Yesify is down, resulting in half the internet not working" is a real headline. :)