I would also like someone to clarify this for me. I (think) I understand what people mean by a neurosymbolic model however common definitions are a bit funky.

If it's neuro (llm/transformer similar) symbolic (symbolic with hand crafted rules) then, imo, that's no different from current tool calling harness implementations and I'd love for someone to explain it further to me if I've misunderstood.

If it's neuro (llm/transformer similar) symbolic (symbolic rules that have also been learned via training) then yeah I can understand how it's a distinct concept.

But every definition I've seen tells me that a standard harness of:

query->llm->[tool call symbol + tool name + tool params] aka symbols governed by logic, including param/arg validation->llm->etc

Already meets the requirements for being "neurosymbolic"...

Can totally see your point (and there are probably cases) where people are applying a harness on top of an LLM and calling it neurosymbolic.

In our case with Ontology, it's the latter! Symbolic rules learned via training + constantly updating autonomously.

IMB YouTube video explainer:

https://www.youtube.com/watch?v=ZfWDVO3rzeA