Saying large language models are “just predictive models” is like saying the human brain is “just neurons firing.” Both statements are technically accurate, but they explain almost nothing about the intelligence that emerges from those interactions. The comparison between AI and the human brain isn’t claiming they are identical. They clearly are not. One is biological. The other is computational. The point is that both exhibit intelligence through distributed processing, layered abstraction, associative memory, selective attention, specialized modules, and the continual integration of information. The similarities lie in their organizational architecture, not their underlying biology. Intelligence has never been defined by its substrate. Whether built from neurons or silicon, complex intelligence appears to emerge when many specialized processes cooperate across layers of memory, attention, and reasoning. The mathematics differ. The implementation differs. But the architecture is beg...