That's not quite how auto-regressive models are trained (the expression of "ideas" bit). There is no notion of "ideas." Words are not defined like we humans do, they're only related.
And on the latent space bit, it's also true for classical models, and the basic idea behind any pattern recognition or dimensionality reduction. That doesn't mean it's necessarily "getting the right idea."
Again, I don't want to "think of it as a probability." I'm saying what you're describing is a probability distribution. Do you have a citation for "probability to express correctly the sentence/idea" bit? Because just having a latent space is no implication of representing an idea.
And on the latent space bit, it's also true for classical models, and the basic idea behind any pattern recognition or dimensionality reduction. That doesn't mean it's necessarily "getting the right idea."
Again, I don't want to "think of it as a probability." I'm saying what you're describing is a probability distribution. Do you have a citation for "probability to express correctly the sentence/idea" bit? Because just having a latent space is no implication of representing an idea.