Machine learning neural networks have almost nothing to do with how brains work besides a tenuous mathematical relation that was conceived in the 1950s.
You can say that if you want to nitpick, but there are recent studies showing that neural and brain representations align rather well, to the point that we can predict what someone is seeing from brain waves, or generate the image with stable diffusion.
I think brain to neural net alignment is justified by the fact that both are the result of the same language evolutionary process. We're not all that different from AIs, we just have better tools and environments, and evolutionary adaptation for some tasks.
Language is an evolutionary system, ideas are self replicators, they evolve parallel to humans. We depend on the accumulation of ideas, starting from scratch would be hard even for humans. A human alone with no language resources of any kind would be worse than a primitive.
The real source of intelligence is the language data from which both humans and AIs learn, model architecture is not very important. Two different people, with different neural wiring in the brain, or two different models, like GPT and T5 can learn the same task given the training set. What matters is the training data. It should be credited with the skills we and AIs obtain. Most of us live our whole lives at this level and never come up with an original idea, we're applying language to tasks like GPT.
