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SymbolicAI: A neuro-symbolic perspective on LLMs

(github.com)
222 points futurisold | 1 comments | 27 Jun 25 18:49 UTC | HN request time: 0.207s | source
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b0a04gl ◴[27 Jun 25 22:00 UTC] No.44400641[source]▶
this works like functional programming where every symbol is a pure value and operations compose into clean, traceable flows. when you hit an ambiguous step, the model steps in. just like IO in FP, the generative call is treated as a scoped side effect. this can engage your reasoning graph stays deterministic by default and only defers to the model when needed. crazy demo though, love it
replies(1): >>44400679 #
1. futurisold ◴[27 Jun 25 22:04 UTC] No.44400679[source]▶
Yes, pretty much. We wanted it be functional from the start. Even low level, everything's functional (it's even called functional.py/core.py). We're using decorators everywhere. This helped a lot with refactoring, extending the framework, containing bugs, etc.