Moors law states that the number of transistors in an integrated circuit doubles about every two years. It has nothing to say about the capabilities of statistical models.

In fact in statistics we have another law which states that as you increase parameters the more you risk overfitting. And overfitting seems to already be a major problem with state of the art LLM models. When you start overfitting you are pretty much just re-creating stuff which is already in the dataset.