We Didn’t Invent Attention — We Just Rediscovered It

The "attention" mechanism powering modern AI is not a new invention, but rather a rediscovery of a fundamental principle for processing information under constraints. This core pattern, defined by selective signal amplification followed by normalization, has convergently emerged across vastly different domains. For over 500 million years, animal nervous systems have used this strategy, and it has even appeared independently in self-organizing chemical reactions. This surprising convergence suggests that universal thermodynamic and information-theoretic laws push any complex system toward the same efficient mathematical solution.