It's kinda more and less data at the same time. While llms have definitely been trained on more text than any of us ever will read, to get to our teenage ears, we have 10 years of basically non-stop real time stereoscopic video streaming with associated 5 senses plus six or seven years of iterative memory consolidation. (Though our brain is much slower at processing, it is way more flexible and changes on the fly unlike most of our current models).

Maybe what LLMs need right now is multimodalism for graphical and sound inputs as it can infer much more relevant information regarding positioning, world structure and different intuitions.

Also noteworthy, we "train" and "infer" with a fraction of the energy cost of running an LLM, and that's with the necessary life support and locomotive systems. With transformer models, we're obviously brute forcing something that evolutionary biology has developed more economical solutions for.

There will come a day when GPT 5.0 or 6.0 can run on a banana peel.

LLMs are trained exclusively on text, so they excel at language, basically they have an amazing model of human languages and know how to use them, what they lack for example is a model of the earth, so they fail at using latitude etc. same for math, the only reason they would know 2 + 2 = 4 is because they read enough times that 2 + 2 = 4, but they have no concept of it. If they would be trained on something like 3d objects they would understand that 2 things + 2 things make 4 things.

I'd argue that humans are trained on more data and the majority of it comes from our senses and the body itself. The texts that we read during our lifetime are probably just a small fraction of all input.