I don't disagree with the conclusion, I disagree with the reasoning.

There's no reason to assume that models trained to predict a plausible next sequence of tokens wouldn't eventually develop "understanding" if it was the most efficient way to predict them.

The evidence so far is a definite no. LLMs will happily produce plausible gibberish, and are often subtly or grossly wrong in ways that betray complete lack of understanding.