In current models? None that I know of. The problem with Transformers and LLMs are they're stochastic... rather like glorified Markov chains that don't understand what they're talking about. Rather, the "understanding" is baked into the syntax of the language.
In the old days there was a project called Cyc (later OpenCyc) that tried to build a collection of rules about the real world. If you could somehow marry the "inference about the real world" from Cyc with the plausible text output of transformers, you would probably have something like an AI that had some base level of common sense. I leave it to people smarter than me to figure out how to do this, 'cause I would need a research budget and a couple years just to get to the point where I felt I was asking the right questions.
In the old days there was a project called Cyc (later OpenCyc) that tried to build a collection of rules about the real world. If you could somehow marry the "inference about the real world" from Cyc with the plausible text output of transformers, you would probably have something like an AI that had some base level of common sense. I leave it to people smarter than me to figure out how to do this, 'cause I would need a research budget and a couple years just to get to the point where I felt I was asking the right questions.