dinunnob
dinunnob on Hacker News
* in so far as QM is natural, we evolved in its presence and so its probable that we are deeply integrated
"god does not play dice" was proven wrong a while ago ...
omg welcome philosophers trying to be noticed by frontier labs, lets see if you can set everyone straight (I point to Einstein deliberately looking to philosophy (Spinozian & Machian) to guide his views - and he did all right.)
I just said pliny was amazing, fwiw - i like that hes hacking on these and posts about it. I rushed to defend, i wish more people were taking old school anarchist cookbook approaches to these things
Yeah but i think the philosophy is to show how precarious the guardrails are
I dont think anyone is going to dispute this
Hate to have to be the one to stick up for pliny here, but hes concerned about forcing frontier labs to focus more on model guardrails - he demonstrates results that are crazy all the time
https://x.com/elder_plinius
ooof, you hate to see it (they got you good)
fixed in the readme. thanks -
while we are talking imports ... how did `import pyspark.sql.functions as F` ever get past the pep police
removed claim from README
It could definitely be better though
You can specify symmetry/antisymmetry patterns for tensor index slots and it takes advantage of that to speed up the calculations. This part was pretty important for me so i spent some time thinking about it. I wanted to try to put xACT’s patterns in but it would have been quite the undertaking.
Not rigorous, but intuition derived from expression string complexity for postfix operations vs standard sympy style. I’ll take this out, readme was written from sleazy used car salesman advertising point of view. Was more rigorous in examples/test
Yeah, you’re not wrong. Makes the syntax a bit annoying here (goal was to lower barrier of entry for physicists). I agree this is bad practice.
Posted by
dinunnob on Saturday January 31, 2026 @08:20PM
from the show-hn dept.
Hey HN,I’m a physicist turned quant. Some friends and I 'built' SymDerive because we wanted a symbolic math library that was "Agent-Native" by design, but still a practical tool for humans.It boils down to two main goals:1. Agent Reliability: I’ve found that AI agents write much more reliable code when they stick to stateless, functional pipelines (Lisp-style). It keeps them from hallucinating...