What is surprising is that our brain, as complex as it is, can train so fast on such a meager energy budget.
So interesting question, but I'm not convinced it's only a scale issue. Like finished models don't really learn the same way as humans do - we actually change the parameters "at runtime", basically updating the model and learning is not only for the current context.
But yes, of course it's not just a scale issue. Note though that a "finished model" can still be fine-tuned, and you can in fact allow it to fine-tune itself even. It's just that this is prohibitively expensive in practice (once again, the hardware is lagging behind the wetware here).
Not necessarily so for the dynamics of magnetic fields, or nonhuman animal communications, or dark energy/matter.
We are bombarded nonstop by magnetic fields, nonhuman animal communications, and live in a universe which seems to be majority dominated by dark energy and matter, and yet understand little to none of it all.