Not to sound condescending, but this reads like someone fimiliar with LLMs but very unfamiliar with statistics in general.
If we could understand economics, or poverty, or any number of other social structures, simply by cramming data into a statistical model with billions of parameters, we would've done that decades ago and these problems would already be understood.
In the real world, though, there is a phenomenon called overfitting. In other words you can perfectly model the training data but be unable to make useful predictions about new data (i.e. the future).
Deep neural networks can generalize well even when they're far into the overparametrized regime where classical statistical learning theory predicts overfitting. This is usually called "double descent" and there are many papers on it.
Okay, tried again and got 0.0034 which is still says is beyond the human limit! I'll have to give this to my mum because we often argue about colours and I suspect she might be a tetrachromat.
Both tests on a Pixel 10 btw