[hunterpayne]

Its a Horn clause resolver...that's exactly the kind of reasoning that LLMs are bad at. I have no idea how to graft Prolog to an LLM but if you can graft any programming language to it, you can graft Prolog more easily.

Also, that you push Python and JavaScript makes me think you don't know many languages. Those are terrible languages to try to graft to anything. Just because you only know those 2 languages doesn't make them good choices for something like this. Learn a real language Physicist.

[jodrellblank]

> Also, that you push Python and JavaScript

I didn't push them.

> Those are terrible languages to try to graft to anything.

Web browsers, Blender, LibreOffice and Excel all use those languages for embedded scripting. They're fine.

> Just because you only know those 2 languages doesn't make them good choices for something like this.

You misunderstood my claim and are refuting something different. I said there is more training data for LLMs to use to generate Python and JavaScript, than Prolog.

[hunterpayne]

I'm not. Python and JS are scripting languages. And in this case, we want something that models formal logic. We are hammering in a nail, you picked up a screwdriver and I am telling you to use a claw hammer.

[Karrot_Kream]

What does this comment even mean? A claw hammer? By formal definitions, all 3 languages are Turing complete and can express programs of the same computational complexity.

[dragonwriter]

> By formal definitions, all 3 languages are Turing complete and can express programs of the same computational complexity.

So is Brainfuck.

Turing equivalence does not imply that languages are equally useful choices for any particular application.

[lionturtle]

But we kinda don't use python for a database query over sql do we?

[AlecSchueler]

I use an ORM every day.

[cpfohl]

No call for talking down at people. No one has ever been convinced by being belittled.

[dragonwriter]

> I have no idea how to graft Prolog to an LLM

Wrapping either the SWI prolog MQI, or even simpler an existing Python interface like like janus_swi, in a simple MCP is probably an easy weekend project. Tuning the prompting to get an LLM to reliably and effectively choose to use it when it would benefit from symbolic reasoning may be harder, though.

[numpy-thagoras]

We would begin by having a Prolog server of some kind (I have no idea if Prolog is parallelized but it should very well be if we're dealing with Horn Clauses).

There would be MCP bindings to said server, which would be accessible upon request. The LLM would provide a message, it could even formulate Prolog statements per a structured prompt, and then await the result, and then continue.

[Woodi]

> Its a Horn clause resolver...that's exactly the kind of reasoning that LLMs are bad at. I have no idea how to graft Prolog to an LLM but if you can graft any programming language to it, you can graft Prolog more easily.

By grafting LLM into Prolog and not other way around ?