Prolog itself is still developed and used in various settings (mostly swi-prolog?), but other languages and logic engines solve domain specific but similar problems better (rule engines, formal proof verifiers, etc). For exploratory work it can be useful.
I have tried to use it in combination will LLMs unsuccessfully, partly because the domain was not specific enough. Otherwise you need a lot of real world knowledge and a large fact database.
Logic engines for first order logic in RDF/OWL also have interesting logical inference abilities, like graphdbs.
Any programming language can do "logic" and the work at MIT/CSAIL in probabilistic programming may turn out to be a better way to combine fuzzy logic and formal proofs.
Not sure this answers your question, but maybe this points towards some interesting directions.
I have tried to use it in combination will LLMs unsuccessfully, partly because the domain was not specific enough. Otherwise you need a lot of real world knowledge and a large fact database.
Logic engines for first order logic in RDF/OWL also have interesting logical inference abilities, like graphdbs.
Any programming language can do "logic" and the work at MIT/CSAIL in probabilistic programming may turn out to be a better way to combine fuzzy logic and formal proofs.
Not sure this answers your question, but maybe this points towards some interesting directions.