The only reason why output from a generative LLM appears intelligent or sentient is that it parrots a random sampling of texts written by intelligent and sentient people.
In order to play the game of go effectively one needs to have a model or theory of how the game of go works. That's a very simple model that can be defined by a simple formula. That's why it is fairly easy for a neural network to learn how to play the game of go very effectively or even infinitely effectively.
A lot of what happens in the world can be modeled in a similar vein by a very simple mathematical model like the game of life. But there is also a lot that cannot. I do believe that eventually also human understanding is just a model of the world that we feed input from perceptions and gain output as opinions, but it is way more complex than the current large language-trained models.
For a very simple example, a LLM would answer a prompt the same way every time unless it wasn't fed some randomness. Can you imagine any sentient being that would respond the same way every time if you asked the same question three times in a row?
I cannot. I would imagine any sentient object would give a different answer every time. The first time it would give you an honest answer based on what it knows about the topic. The second time it would be a little embarrassed that you repeat the question, as if you hadn't heard the first answer. The third time it would be pissed off and think you are a troll.
A LLM does none of this. It doesn't remember you or your previous questions. It just keeps hallucinating.