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[dead] solohunter001
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sysguest
> Happy to go deep on the calibration math, the compile/cache design, or where this does and doesn't make sense.

yes plz

dpacmittal
Was this entirely vibe coded? The readme is very obviously Claude with no human edits at all.
nodja
Yes, even the comment you replied to is very noticeably claude authored.
majorchord
You could not even take the time to write your own comment here?
solohunter001
Sorry Too busy !! Meanwhile you can focus on the project and ask relevant question.. for BShittn use reddit
solohunter001
Thanks for feedback, I will try doing this going forward
jMyles
I think that "infer once, repeat resulting logic forever" is one of the most important / sustainable / humane ways to imagine how AI acclimates to the universe.

https://pickipedia.xyz/wiki/PickiPedia:Artificial_Dumb

solohunter001
I was working with a large entries on Batch inference, and yes LLMs are quite expensive to process Billions of contracts at latency, so I in my orignial paper was on the expensive thinking once, run the cheap deterministic result forever.
wonnage
> If a ghost is close (nearest_ghost_distance small, " "within 2 steps), choose flee_ghost. Otherwise choose " "chase_dot to eat the nearest dot."

Dude, this is AI psychosis. Just ask the LLM to write you a program (“compile”) and then you can run it locally forever

publlus_enigma
I love the concept, but tried reading the README on the got, but I am still unclear about precisely what it does or how it does it. Some more detail would be welcome.
luhgor
So, obvious question: What is the difference / advantage to Jev-style decision models?
solohunter001
My apologizes for pulling my Claude notes while I am busy running tests myself, I realize there are some rules of using AI content, going forward I will use my own comments and label the text whichever is AI referrer, this applies to existing comment as well ( I will update it)
solohunter001
Updated the Readme!! Some new benchmarks available, Ty