Thinking in Wetware, Thinking in Code: Where Brains and Machines Miss Each Other
People keep pairing neuroscience with artificial intelligence as if the two are already close cousins. Sometimes they are. Often they talk past each other. Brains move through time under scarcity—of energy, of certainty, of second chances. Most modern AI moves through datasets outside of time—unbounded replay, synthetic resets, a thermostat world. The difference is not a quirk. It shapes what these systems can know, what they can care about, what kinds of error they can survive. If reality at base is informational—pattern and constraint more than stuff—then the bridge between biology and code should be built where information lives: in prediction, memory, and social transmission. We can stop asking whether neural nets “are like” brains. Better question: which mismatches matter, and which m...